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ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
1
MICROFLUIDICS LAB ON CHIP
ABSTRACT
Recent progress in reconstructing gene regulatory networks has established a framework for a quantitative
description of the dynamics of many important cellular processes Such a description will require novel
experimental techniques that enable the generation of time series data for the governing regulatory proteins in a
large number of individual living cells An ideal data acquisition system would allow for the growth of a large
population of cells in a defined environment which can be monitored by high resolution microscopy for an
extended period of time Thus this lab will consist on a brief theory about microfluidics then will follow the
practical work going from the chip fabrication to one of its applications the tracking or monitoring of particles
(beads or E coli) in this device and the subsequent analysis of the acquired data Some imaging techniques will
also be introduced Finally a few questions will be discussed in order to outline some important points
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
2
TABLE OF CONTENTS
1 Theory 3
11 Basic Principles of Microfluidics 4
12 Device Fabrication 5
13 Questions (Theory) 8
14 Integration of Microfluidics and Microscopy 9
2 Practical work 11
21 Material requirements 11
22 PDMS silicon mold 11
23 Integration of Microfluidics and Microscopy 14
24 Run the sample 16
25 Viewing Tracking Particles in Device Geometry 17
26 Epifluorescence 18
3 Data analysis 19
31 Calibration 19
32 Particle Tracking 19
33 Matlab analysis 23
34 Particle analysis 23
35 Questions 26
4 References 26
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
3
1 THEORY
Recent progress in reconstructing gene regulatory networks has established a framework for a quantitative
description of the dynamics of many important cellular processes Such a description will require novel
experimental techniques that enable the generation of time series data for the governing regulatory proteins in a
large number of individual living cells An ideal data acquisition system would allow for the growth of a large
population of cells in a defined environment which can be monitored by high resolution microscopy for an
extended period of time
In this laboratory exercise we fabricate and use such a data acquisition system With our setup the gene
expression state of each cell could be monitored for the length of the experiment giving the experimenter
accurate data about the temporal progression of each individual cell within the larger population To this end
bioengineers have increasingly used devices with fluid channels on the micron scale known as microfluidic
devices The goal of this exercise is to fabricate and use such a microfluidic device
Figure 1 Microfluidics provide a tool for the miniaturization and serial processing of fluids allowing better control of their
properties integration of different operations and parallelization Reproduced from 1
Microtechnology in general and microfluidics in particular can facilitate the accurate study of cellular behavior
in vitro because it provides the necessary tools for recreating in vivo-like cellular microenvironments
Microfluidics involve the handling and manipulation of very small fluid volumes enabling creation and control of
microliter-volume reactors while drawing advantages from low thermal mass efficient mass transport and large
surface area-to-volume ratios
Because fluid viscosity not inertia dominates fluid behavior at this scale microfluidic flow is laminar ensuring
that the system does not include turbulent flows which would be detrimental for observing cellular behavior under
high magnification
Lately microfluidic ldquolab-on-a-chiprdquo devices have become increasingly valuable as the known complexity of
gene networks grows driving the need for reduced-scale assays in probing entire parameter spaces of genetic
circuits The result has been the development of integrated microfluidic circuits analogous to their electrical
counterparts which aim to support large-scale multi-parameter analysis in parallel Recent applications of
microfluidics in biotechnology include DNA amplification purification separation 2 and sequencing
3 large-scale
proteomic analysis4 development of memory storage devices
5 cell sorting
6 and single-cell gene expression
profiling
The use of microfluidic devices to conduct biomedical research and create clinically useful technologies has a
number of significant advantages First because the volume of fluids within these channels is very small usually
several nanoliters the amount of reagents and analytes used is quite small This is especially significant for
expensive reagents The fabrication techniques used to construct microfluidic devices (discussed in more depth
later) are relatively inexpensive and very amenable both to highly elaborate multiplexed devices and mass
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
4
production In a manner similar to that for microelectronics microfluidic technologies enable the fabrication of
highly integrated devices for performing several different functions on the same substrate chip One of the long
term goals in the field of microfluidics is to create integrated portable clinical diagnostic devices for home and
bedside use thereby eliminating time consuming laboratory analysis procedures
11 Basic Principles of Microfluidics
111 Reynolds number The flow of a fluid through a microfluidic channel can be characterized by the Reynolds number defined as
equation (11)
avg
e
L VR
(11)
Where L is the most relevant length scale micro is the viscosity ρ is the fluid density and Vavg is the average
velocity of the flow For many microchannels L is equal to 4AP where A is the cross sectional area of the
channel and P is the wetted perimeter of the channel
Due to the small dimensions of microchannels the Re is usually much less than 100 often less than 1 In this
low Reynolds number regime flow is completely laminar and no turbulence occurs ndash the transition to turbulent
flow generally occurs in the range of Reynolds number 2000 Laminar flow provides a means by which molecules
can be transported in a relatively predictable manner through microchannels Note however that even at
Reynolds numbers below 100 it is possible to have momentum-based phenomena such as flow separation
112 Poiseuillersquos Law
In such a laminar flow of viscous and incompressible fluid the pressure drop and the flow rate as well as the
effective resistance might be obtained by using the Poiseuille equation (12)
and (12)
Where Δp is the pressure drop Q is the volumic flow rate R is the resistance to flow L is the length of the
channel r radius of the channel η is the dynamic fluid viscosity and x the distance in direction of flow
113 Pressure Driven Flow
There are two common methods by which fluid actuation through microchannels can be achieved In pressure
driven flow the fluid is pumped through the device via positive displacement pumps such as syringe pumps
One of the basic laws of fluid mechanics for pressure driven laminar flow the so-called no-slip boundary
condition states that the fluid velocity at the walls must be zero This produces a parabolic velocity profile within
the channel (Figure 2a)
The parabolic velocity profile has significant implications for the distribution of molecules transported within a
channel Pressure driven flow can be a relatively inexpensive and quite reproducible approach to pumping fluids
through microdevices With the increasing efforts at developing functional micropumps pressure driven flow is
also amenable to miniaturization (Figure 2a)
Δp=8μLQ
πr4
R=8ηΔx
πr4
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
5
114 Electrokinetic Flow Another common technique for pumping fluids is that of electroosmotic pumping If the walls of a microchannel
have an electric charge as most surfaces do an electric double layer of counter ions will form at the walls When
an electric field is applied across the channel the ions in the double layer move towards the electrode of opposite
polarity This creates motion of the fluid near the walls and transfers via viscous forces into convective motion of
the bulk fluid If the channel is open at the electrodes as is most often the case the velocity profile is uniform
across the entire width of the channel (Figure 2b) However if the electric field is applied across a closed channel
(or a backpressure exists that just counters that produced by the pump) a recirculation pattern forms in which
fluid along the center of the channel moves in a direction opposite to that at the walls (Figure 2c) In closed
channels the velocity along the centerline of the channel is 50 of the velocity at the walls
a b
c
Figure 2 a) Velocity profile in a microchannel with aspect ratio 25 under conditions of pressure driven flow Note that the
velocity is assumed to be zero at the walls in most treatments of transport of liquids b) The very uninteresting flow velocity
profile calculated for electroosmotic pumping in an open channel Such a channel (in the absence of backpressure) exhibits plug
flow Shown in the situation for negatively charged walls the anode is at the left and the cathode is at the right In fact the profile
is very interesting close to the walls since velocity drops to zero at the walls over a distance that is comparable to the thickness
of the electrical double layer c) The view of the electroosmotic flow velocity vectors in a closed channel Note that the
recirculation results in equal total flows to the right and left at all vertical planes through the channel The anode is on the left and
the cathode is on the right and the walls are negatively charged
12 Device Fabrication
121 Photolithography
In recent years soft lithography has become the preferred method for fabricating microfluidic devices for
biology Soft lithography includes a suite of methods for replicating a pattern using elastomeric polymers (Figure
4) Soft lithography can be represented as a three-step process comprised of concept developing rapid
prototyping and replica molding The first step concept developing involves drafting a device design in a computer-aided design (CAD) program
Here a general idea for a device that serves some purpose is fleshed out using engineering approaches Using the
laws of fluid dynamics under the condition of low Reynolds number for microvolume flow fluid channel
resistances are calculated and modified to satisfy desired driving pressures and flow rates Following fine-tuning
of the entire channel architecture the device design is broken up into multiple layers where all features of a given
height are placed on a single layer for photolithographic purposes Finally all the device layers are printed at high
resolution onto transparency film These are then fastened to ultra-transmissive borosilicate glass for use as a
photomask set in the following contact lithography step Or alternatively as we did in the CMI (Center of
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
2
TABLE OF CONTENTS
1 Theory 3
11 Basic Principles of Microfluidics 4
12 Device Fabrication 5
13 Questions (Theory) 8
14 Integration of Microfluidics and Microscopy 9
2 Practical work 11
21 Material requirements 11
22 PDMS silicon mold 11
23 Integration of Microfluidics and Microscopy 14
24 Run the sample 16
25 Viewing Tracking Particles in Device Geometry 17
26 Epifluorescence 18
3 Data analysis 19
31 Calibration 19
32 Particle Tracking 19
33 Matlab analysis 23
34 Particle analysis 23
35 Questions 26
4 References 26
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
3
1 THEORY
Recent progress in reconstructing gene regulatory networks has established a framework for a quantitative
description of the dynamics of many important cellular processes Such a description will require novel
experimental techniques that enable the generation of time series data for the governing regulatory proteins in a
large number of individual living cells An ideal data acquisition system would allow for the growth of a large
population of cells in a defined environment which can be monitored by high resolution microscopy for an
extended period of time
In this laboratory exercise we fabricate and use such a data acquisition system With our setup the gene
expression state of each cell could be monitored for the length of the experiment giving the experimenter
accurate data about the temporal progression of each individual cell within the larger population To this end
bioengineers have increasingly used devices with fluid channels on the micron scale known as microfluidic
devices The goal of this exercise is to fabricate and use such a microfluidic device
Figure 1 Microfluidics provide a tool for the miniaturization and serial processing of fluids allowing better control of their
properties integration of different operations and parallelization Reproduced from 1
Microtechnology in general and microfluidics in particular can facilitate the accurate study of cellular behavior
in vitro because it provides the necessary tools for recreating in vivo-like cellular microenvironments
Microfluidics involve the handling and manipulation of very small fluid volumes enabling creation and control of
microliter-volume reactors while drawing advantages from low thermal mass efficient mass transport and large
surface area-to-volume ratios
Because fluid viscosity not inertia dominates fluid behavior at this scale microfluidic flow is laminar ensuring
that the system does not include turbulent flows which would be detrimental for observing cellular behavior under
high magnification
Lately microfluidic ldquolab-on-a-chiprdquo devices have become increasingly valuable as the known complexity of
gene networks grows driving the need for reduced-scale assays in probing entire parameter spaces of genetic
circuits The result has been the development of integrated microfluidic circuits analogous to their electrical
counterparts which aim to support large-scale multi-parameter analysis in parallel Recent applications of
microfluidics in biotechnology include DNA amplification purification separation 2 and sequencing
3 large-scale
proteomic analysis4 development of memory storage devices
5 cell sorting
6 and single-cell gene expression
profiling
The use of microfluidic devices to conduct biomedical research and create clinically useful technologies has a
number of significant advantages First because the volume of fluids within these channels is very small usually
several nanoliters the amount of reagents and analytes used is quite small This is especially significant for
expensive reagents The fabrication techniques used to construct microfluidic devices (discussed in more depth
later) are relatively inexpensive and very amenable both to highly elaborate multiplexed devices and mass
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
4
production In a manner similar to that for microelectronics microfluidic technologies enable the fabrication of
highly integrated devices for performing several different functions on the same substrate chip One of the long
term goals in the field of microfluidics is to create integrated portable clinical diagnostic devices for home and
bedside use thereby eliminating time consuming laboratory analysis procedures
11 Basic Principles of Microfluidics
111 Reynolds number The flow of a fluid through a microfluidic channel can be characterized by the Reynolds number defined as
equation (11)
avg
e
L VR
(11)
Where L is the most relevant length scale micro is the viscosity ρ is the fluid density and Vavg is the average
velocity of the flow For many microchannels L is equal to 4AP where A is the cross sectional area of the
channel and P is the wetted perimeter of the channel
Due to the small dimensions of microchannels the Re is usually much less than 100 often less than 1 In this
low Reynolds number regime flow is completely laminar and no turbulence occurs ndash the transition to turbulent
flow generally occurs in the range of Reynolds number 2000 Laminar flow provides a means by which molecules
can be transported in a relatively predictable manner through microchannels Note however that even at
Reynolds numbers below 100 it is possible to have momentum-based phenomena such as flow separation
112 Poiseuillersquos Law
In such a laminar flow of viscous and incompressible fluid the pressure drop and the flow rate as well as the
effective resistance might be obtained by using the Poiseuille equation (12)
and (12)
Where Δp is the pressure drop Q is the volumic flow rate R is the resistance to flow L is the length of the
channel r radius of the channel η is the dynamic fluid viscosity and x the distance in direction of flow
113 Pressure Driven Flow
There are two common methods by which fluid actuation through microchannels can be achieved In pressure
driven flow the fluid is pumped through the device via positive displacement pumps such as syringe pumps
One of the basic laws of fluid mechanics for pressure driven laminar flow the so-called no-slip boundary
condition states that the fluid velocity at the walls must be zero This produces a parabolic velocity profile within
the channel (Figure 2a)
The parabolic velocity profile has significant implications for the distribution of molecules transported within a
channel Pressure driven flow can be a relatively inexpensive and quite reproducible approach to pumping fluids
through microdevices With the increasing efforts at developing functional micropumps pressure driven flow is
also amenable to miniaturization (Figure 2a)
Δp=8μLQ
πr4
R=8ηΔx
πr4
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
5
114 Electrokinetic Flow Another common technique for pumping fluids is that of electroosmotic pumping If the walls of a microchannel
have an electric charge as most surfaces do an electric double layer of counter ions will form at the walls When
an electric field is applied across the channel the ions in the double layer move towards the electrode of opposite
polarity This creates motion of the fluid near the walls and transfers via viscous forces into convective motion of
the bulk fluid If the channel is open at the electrodes as is most often the case the velocity profile is uniform
across the entire width of the channel (Figure 2b) However if the electric field is applied across a closed channel
(or a backpressure exists that just counters that produced by the pump) a recirculation pattern forms in which
fluid along the center of the channel moves in a direction opposite to that at the walls (Figure 2c) In closed
channels the velocity along the centerline of the channel is 50 of the velocity at the walls
a b
c
Figure 2 a) Velocity profile in a microchannel with aspect ratio 25 under conditions of pressure driven flow Note that the
velocity is assumed to be zero at the walls in most treatments of transport of liquids b) The very uninteresting flow velocity
profile calculated for electroosmotic pumping in an open channel Such a channel (in the absence of backpressure) exhibits plug
flow Shown in the situation for negatively charged walls the anode is at the left and the cathode is at the right In fact the profile
is very interesting close to the walls since velocity drops to zero at the walls over a distance that is comparable to the thickness
of the electrical double layer c) The view of the electroosmotic flow velocity vectors in a closed channel Note that the
recirculation results in equal total flows to the right and left at all vertical planes through the channel The anode is on the left and
the cathode is on the right and the walls are negatively charged
12 Device Fabrication
121 Photolithography
In recent years soft lithography has become the preferred method for fabricating microfluidic devices for
biology Soft lithography includes a suite of methods for replicating a pattern using elastomeric polymers (Figure
4) Soft lithography can be represented as a three-step process comprised of concept developing rapid
prototyping and replica molding The first step concept developing involves drafting a device design in a computer-aided design (CAD) program
Here a general idea for a device that serves some purpose is fleshed out using engineering approaches Using the
laws of fluid dynamics under the condition of low Reynolds number for microvolume flow fluid channel
resistances are calculated and modified to satisfy desired driving pressures and flow rates Following fine-tuning
of the entire channel architecture the device design is broken up into multiple layers where all features of a given
height are placed on a single layer for photolithographic purposes Finally all the device layers are printed at high
resolution onto transparency film These are then fastened to ultra-transmissive borosilicate glass for use as a
photomask set in the following contact lithography step Or alternatively as we did in the CMI (Center of
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
3
1 THEORY
Recent progress in reconstructing gene regulatory networks has established a framework for a quantitative
description of the dynamics of many important cellular processes Such a description will require novel
experimental techniques that enable the generation of time series data for the governing regulatory proteins in a
large number of individual living cells An ideal data acquisition system would allow for the growth of a large
population of cells in a defined environment which can be monitored by high resolution microscopy for an
extended period of time
In this laboratory exercise we fabricate and use such a data acquisition system With our setup the gene
expression state of each cell could be monitored for the length of the experiment giving the experimenter
accurate data about the temporal progression of each individual cell within the larger population To this end
bioengineers have increasingly used devices with fluid channels on the micron scale known as microfluidic
devices The goal of this exercise is to fabricate and use such a microfluidic device
Figure 1 Microfluidics provide a tool for the miniaturization and serial processing of fluids allowing better control of their
properties integration of different operations and parallelization Reproduced from 1
Microtechnology in general and microfluidics in particular can facilitate the accurate study of cellular behavior
in vitro because it provides the necessary tools for recreating in vivo-like cellular microenvironments
Microfluidics involve the handling and manipulation of very small fluid volumes enabling creation and control of
microliter-volume reactors while drawing advantages from low thermal mass efficient mass transport and large
surface area-to-volume ratios
Because fluid viscosity not inertia dominates fluid behavior at this scale microfluidic flow is laminar ensuring
that the system does not include turbulent flows which would be detrimental for observing cellular behavior under
high magnification
Lately microfluidic ldquolab-on-a-chiprdquo devices have become increasingly valuable as the known complexity of
gene networks grows driving the need for reduced-scale assays in probing entire parameter spaces of genetic
circuits The result has been the development of integrated microfluidic circuits analogous to their electrical
counterparts which aim to support large-scale multi-parameter analysis in parallel Recent applications of
microfluidics in biotechnology include DNA amplification purification separation 2 and sequencing
3 large-scale
proteomic analysis4 development of memory storage devices
5 cell sorting
6 and single-cell gene expression
profiling
The use of microfluidic devices to conduct biomedical research and create clinically useful technologies has a
number of significant advantages First because the volume of fluids within these channels is very small usually
several nanoliters the amount of reagents and analytes used is quite small This is especially significant for
expensive reagents The fabrication techniques used to construct microfluidic devices (discussed in more depth
later) are relatively inexpensive and very amenable both to highly elaborate multiplexed devices and mass
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
4
production In a manner similar to that for microelectronics microfluidic technologies enable the fabrication of
highly integrated devices for performing several different functions on the same substrate chip One of the long
term goals in the field of microfluidics is to create integrated portable clinical diagnostic devices for home and
bedside use thereby eliminating time consuming laboratory analysis procedures
11 Basic Principles of Microfluidics
111 Reynolds number The flow of a fluid through a microfluidic channel can be characterized by the Reynolds number defined as
equation (11)
avg
e
L VR
(11)
Where L is the most relevant length scale micro is the viscosity ρ is the fluid density and Vavg is the average
velocity of the flow For many microchannels L is equal to 4AP where A is the cross sectional area of the
channel and P is the wetted perimeter of the channel
Due to the small dimensions of microchannels the Re is usually much less than 100 often less than 1 In this
low Reynolds number regime flow is completely laminar and no turbulence occurs ndash the transition to turbulent
flow generally occurs in the range of Reynolds number 2000 Laminar flow provides a means by which molecules
can be transported in a relatively predictable manner through microchannels Note however that even at
Reynolds numbers below 100 it is possible to have momentum-based phenomena such as flow separation
112 Poiseuillersquos Law
In such a laminar flow of viscous and incompressible fluid the pressure drop and the flow rate as well as the
effective resistance might be obtained by using the Poiseuille equation (12)
and (12)
Where Δp is the pressure drop Q is the volumic flow rate R is the resistance to flow L is the length of the
channel r radius of the channel η is the dynamic fluid viscosity and x the distance in direction of flow
113 Pressure Driven Flow
There are two common methods by which fluid actuation through microchannels can be achieved In pressure
driven flow the fluid is pumped through the device via positive displacement pumps such as syringe pumps
One of the basic laws of fluid mechanics for pressure driven laminar flow the so-called no-slip boundary
condition states that the fluid velocity at the walls must be zero This produces a parabolic velocity profile within
the channel (Figure 2a)
The parabolic velocity profile has significant implications for the distribution of molecules transported within a
channel Pressure driven flow can be a relatively inexpensive and quite reproducible approach to pumping fluids
through microdevices With the increasing efforts at developing functional micropumps pressure driven flow is
also amenable to miniaturization (Figure 2a)
Δp=8μLQ
πr4
R=8ηΔx
πr4
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
5
114 Electrokinetic Flow Another common technique for pumping fluids is that of electroosmotic pumping If the walls of a microchannel
have an electric charge as most surfaces do an electric double layer of counter ions will form at the walls When
an electric field is applied across the channel the ions in the double layer move towards the electrode of opposite
polarity This creates motion of the fluid near the walls and transfers via viscous forces into convective motion of
the bulk fluid If the channel is open at the electrodes as is most often the case the velocity profile is uniform
across the entire width of the channel (Figure 2b) However if the electric field is applied across a closed channel
(or a backpressure exists that just counters that produced by the pump) a recirculation pattern forms in which
fluid along the center of the channel moves in a direction opposite to that at the walls (Figure 2c) In closed
channels the velocity along the centerline of the channel is 50 of the velocity at the walls
a b
c
Figure 2 a) Velocity profile in a microchannel with aspect ratio 25 under conditions of pressure driven flow Note that the
velocity is assumed to be zero at the walls in most treatments of transport of liquids b) The very uninteresting flow velocity
profile calculated for electroosmotic pumping in an open channel Such a channel (in the absence of backpressure) exhibits plug
flow Shown in the situation for negatively charged walls the anode is at the left and the cathode is at the right In fact the profile
is very interesting close to the walls since velocity drops to zero at the walls over a distance that is comparable to the thickness
of the electrical double layer c) The view of the electroosmotic flow velocity vectors in a closed channel Note that the
recirculation results in equal total flows to the right and left at all vertical planes through the channel The anode is on the left and
the cathode is on the right and the walls are negatively charged
12 Device Fabrication
121 Photolithography
In recent years soft lithography has become the preferred method for fabricating microfluidic devices for
biology Soft lithography includes a suite of methods for replicating a pattern using elastomeric polymers (Figure
4) Soft lithography can be represented as a three-step process comprised of concept developing rapid
prototyping and replica molding The first step concept developing involves drafting a device design in a computer-aided design (CAD) program
Here a general idea for a device that serves some purpose is fleshed out using engineering approaches Using the
laws of fluid dynamics under the condition of low Reynolds number for microvolume flow fluid channel
resistances are calculated and modified to satisfy desired driving pressures and flow rates Following fine-tuning
of the entire channel architecture the device design is broken up into multiple layers where all features of a given
height are placed on a single layer for photolithographic purposes Finally all the device layers are printed at high
resolution onto transparency film These are then fastened to ultra-transmissive borosilicate glass for use as a
photomask set in the following contact lithography step Or alternatively as we did in the CMI (Center of
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
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Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
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9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
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10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
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Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
4
production In a manner similar to that for microelectronics microfluidic technologies enable the fabrication of
highly integrated devices for performing several different functions on the same substrate chip One of the long
term goals in the field of microfluidics is to create integrated portable clinical diagnostic devices for home and
bedside use thereby eliminating time consuming laboratory analysis procedures
11 Basic Principles of Microfluidics
111 Reynolds number The flow of a fluid through a microfluidic channel can be characterized by the Reynolds number defined as
equation (11)
avg
e
L VR
(11)
Where L is the most relevant length scale micro is the viscosity ρ is the fluid density and Vavg is the average
velocity of the flow For many microchannels L is equal to 4AP where A is the cross sectional area of the
channel and P is the wetted perimeter of the channel
Due to the small dimensions of microchannels the Re is usually much less than 100 often less than 1 In this
low Reynolds number regime flow is completely laminar and no turbulence occurs ndash the transition to turbulent
flow generally occurs in the range of Reynolds number 2000 Laminar flow provides a means by which molecules
can be transported in a relatively predictable manner through microchannels Note however that even at
Reynolds numbers below 100 it is possible to have momentum-based phenomena such as flow separation
112 Poiseuillersquos Law
In such a laminar flow of viscous and incompressible fluid the pressure drop and the flow rate as well as the
effective resistance might be obtained by using the Poiseuille equation (12)
and (12)
Where Δp is the pressure drop Q is the volumic flow rate R is the resistance to flow L is the length of the
channel r radius of the channel η is the dynamic fluid viscosity and x the distance in direction of flow
113 Pressure Driven Flow
There are two common methods by which fluid actuation through microchannels can be achieved In pressure
driven flow the fluid is pumped through the device via positive displacement pumps such as syringe pumps
One of the basic laws of fluid mechanics for pressure driven laminar flow the so-called no-slip boundary
condition states that the fluid velocity at the walls must be zero This produces a parabolic velocity profile within
the channel (Figure 2a)
The parabolic velocity profile has significant implications for the distribution of molecules transported within a
channel Pressure driven flow can be a relatively inexpensive and quite reproducible approach to pumping fluids
through microdevices With the increasing efforts at developing functional micropumps pressure driven flow is
also amenable to miniaturization (Figure 2a)
Δp=8μLQ
πr4
R=8ηΔx
πr4
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
5
114 Electrokinetic Flow Another common technique for pumping fluids is that of electroosmotic pumping If the walls of a microchannel
have an electric charge as most surfaces do an electric double layer of counter ions will form at the walls When
an electric field is applied across the channel the ions in the double layer move towards the electrode of opposite
polarity This creates motion of the fluid near the walls and transfers via viscous forces into convective motion of
the bulk fluid If the channel is open at the electrodes as is most often the case the velocity profile is uniform
across the entire width of the channel (Figure 2b) However if the electric field is applied across a closed channel
(or a backpressure exists that just counters that produced by the pump) a recirculation pattern forms in which
fluid along the center of the channel moves in a direction opposite to that at the walls (Figure 2c) In closed
channels the velocity along the centerline of the channel is 50 of the velocity at the walls
a b
c
Figure 2 a) Velocity profile in a microchannel with aspect ratio 25 under conditions of pressure driven flow Note that the
velocity is assumed to be zero at the walls in most treatments of transport of liquids b) The very uninteresting flow velocity
profile calculated for electroosmotic pumping in an open channel Such a channel (in the absence of backpressure) exhibits plug
flow Shown in the situation for negatively charged walls the anode is at the left and the cathode is at the right In fact the profile
is very interesting close to the walls since velocity drops to zero at the walls over a distance that is comparable to the thickness
of the electrical double layer c) The view of the electroosmotic flow velocity vectors in a closed channel Note that the
recirculation results in equal total flows to the right and left at all vertical planes through the channel The anode is on the left and
the cathode is on the right and the walls are negatively charged
12 Device Fabrication
121 Photolithography
In recent years soft lithography has become the preferred method for fabricating microfluidic devices for
biology Soft lithography includes a suite of methods for replicating a pattern using elastomeric polymers (Figure
4) Soft lithography can be represented as a three-step process comprised of concept developing rapid
prototyping and replica molding The first step concept developing involves drafting a device design in a computer-aided design (CAD) program
Here a general idea for a device that serves some purpose is fleshed out using engineering approaches Using the
laws of fluid dynamics under the condition of low Reynolds number for microvolume flow fluid channel
resistances are calculated and modified to satisfy desired driving pressures and flow rates Following fine-tuning
of the entire channel architecture the device design is broken up into multiple layers where all features of a given
height are placed on a single layer for photolithographic purposes Finally all the device layers are printed at high
resolution onto transparency film These are then fastened to ultra-transmissive borosilicate glass for use as a
photomask set in the following contact lithography step Or alternatively as we did in the CMI (Center of
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
5
114 Electrokinetic Flow Another common technique for pumping fluids is that of electroosmotic pumping If the walls of a microchannel
have an electric charge as most surfaces do an electric double layer of counter ions will form at the walls When
an electric field is applied across the channel the ions in the double layer move towards the electrode of opposite
polarity This creates motion of the fluid near the walls and transfers via viscous forces into convective motion of
the bulk fluid If the channel is open at the electrodes as is most often the case the velocity profile is uniform
across the entire width of the channel (Figure 2b) However if the electric field is applied across a closed channel
(or a backpressure exists that just counters that produced by the pump) a recirculation pattern forms in which
fluid along the center of the channel moves in a direction opposite to that at the walls (Figure 2c) In closed
channels the velocity along the centerline of the channel is 50 of the velocity at the walls
a b
c
Figure 2 a) Velocity profile in a microchannel with aspect ratio 25 under conditions of pressure driven flow Note that the
velocity is assumed to be zero at the walls in most treatments of transport of liquids b) The very uninteresting flow velocity
profile calculated for electroosmotic pumping in an open channel Such a channel (in the absence of backpressure) exhibits plug
flow Shown in the situation for negatively charged walls the anode is at the left and the cathode is at the right In fact the profile
is very interesting close to the walls since velocity drops to zero at the walls over a distance that is comparable to the thickness
of the electrical double layer c) The view of the electroosmotic flow velocity vectors in a closed channel Note that the
recirculation results in equal total flows to the right and left at all vertical planes through the channel The anode is on the left and
the cathode is on the right and the walls are negatively charged
12 Device Fabrication
121 Photolithography
In recent years soft lithography has become the preferred method for fabricating microfluidic devices for
biology Soft lithography includes a suite of methods for replicating a pattern using elastomeric polymers (Figure
4) Soft lithography can be represented as a three-step process comprised of concept developing rapid
prototyping and replica molding The first step concept developing involves drafting a device design in a computer-aided design (CAD) program
Here a general idea for a device that serves some purpose is fleshed out using engineering approaches Using the
laws of fluid dynamics under the condition of low Reynolds number for microvolume flow fluid channel
resistances are calculated and modified to satisfy desired driving pressures and flow rates Following fine-tuning
of the entire channel architecture the device design is broken up into multiple layers where all features of a given
height are placed on a single layer for photolithographic purposes Finally all the device layers are printed at high
resolution onto transparency film These are then fastened to ultra-transmissive borosilicate glass for use as a
photomask set in the following contact lithography step Or alternatively as we did in the CMI (Center of
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
6
MicroNanoTechnology EPFL) for this laboratory a photomask may be created by patterning chrome on a glass
plate
For the design we have chosen the recently proposed microfluidics chip that has been used for monitoring the
collective synchronization properties in an engineered gene network with global intercellular coupling in a
growing population of cells that exhibit spatiotemporal waves occurring at millimeter scales 7 The chip design is
shown in Figure 3
Figure 3 Microfluidic device used for maintaining E coli or beads at a constant density The main channel (blue) supplies media
to cells in the trapping chamber and the flow rate can be externally controlled to change the effective rates of an engineered
gene network7
There is presented the lithography concept to understand the how have been made the wafer that you will use to
fabricate your device Due to the time constraints of this exercise this part of fabrication is already made by TA
In rapid prototyping a positive or negative photoresist is spin coated onto a clean silicon wafer at a specified
thickness and then exposed to UV light through the photomask to selectively crosslink the features represented by
the mask Since each exposure iteration creates all device features of a given height (being the depth of the
photoresist layer) this process can be repeated to pattern the wafer for multi-layer device features The final result
is a positive relief of photoresist on the silicon wafer known as a ldquomaster moldrdquo whose topology precisely
reflects the desired device channel and feature structures and can be used repeatedly to form successive batches of
devices Fabrication of this master mold completes the rapid prototyping step of soft lithography The final step
called replica molding involves the casting of a transparent silicone-based liquid prepolymer (usually PDMS)
against the master mold to generate a negative replica of the master
The prepolymer is first poured onto the wafer and heat-cured in place to form a rubbery silicone solid This
silicone monolith is then peeled from the mold to reveal the inverted feature topology represented by the mold
For example ridges on the master mold appear as valleys in the replica This monolith is then diced into
individual devices bored with a cylindrical punch to form holes for connection to fluid reservoirs and cleaned
using Scotch tape and methanol In the final step the feature sides of the devices along with opposing coverslip
surfaces are briefly treated with low power oxygen plasma This process ldquoactivatesrdquo the surfaces of the PDMS
devices and glass coverslips so that they form a permanent bond when placed in contact In bonding the two
objects fluid channels in the PDMS are sealed against the flat coverslip surface to form microchannels internally
connecting the device fluidic ports These finished devices mark completion of the replica molding step of soft
lithography
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
7
or create chrome mask
Your TArsquos prepared wafers beforehand
Concept copied form
Danino et al Nature 463 326-330 (2010)
Your will fabricate microfluidic device
from this point
Figure 4 Schematic of microfluidic device fabrication using soft lithography (adapted from Ref 8)
122 Multilayer soft lithography
The techniques described here can be extended to perform multilayer soft lithography which provides the
capability to bond multiple patterned layers of elastomer to create active microfluidic systems containing on-off
valves switching valves and pumps There will not be any such sophisticated components in our device but it is
always good to know for your future research since it is more and more used in laboratories In multilayer soft
lithography in addition to a layer of microchannels cast in PDMS as described before a second deformable thin
membrane of PDMS is cast by spin coating PDMS onto a master mold This allows for a layer with a thickness of
only about 50 to 100 microns The thin PDMS layer is then partially cured and bonded to the thick PDMS layer
Both layers are then bonded to a flat substrate
Figure 5 a) Multilayer soft lithography fabrication process A microchannel layer is molded in a thin deformable PDMS membrane
through a spin-coating process A second layer of microchannels is molded from a thick layer of PDMS The two PDMS layers are bonded
together and the structure is then bonded to a flat substrate b) Example of a peristaltic pump fabricated from multilayer soft lithography
By successive pressurization of the upper control layer channels fluid is pumped through the lower fluidic layer (Adapted from Ref 1)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
8
The end result is a set of microchannel layers separated vertically by a thin membrane of PDMS The advantage
of this architecture is that air or fluid pressure in one of the microchannels can be used to deform the membrane
blocking or constricting fluid flow in the second microchannel This allows for simple integration of valves and
pumps into these multilayered fluidic structures An overview of the fabrication process and an example of a
peristaltic pump are illustrated in Fig 5
Recent research in the microfluidics field has produced several examples of complex devices with hugely parallel
active channel structures for high-throughput cell analysis In approaching years the fundamental benefits of soft
lithography for biology which include ease of fabrication inexpensive production and rapid device turnover
will continue to aid the researcher seeking increasingly functional cell assays
13 Questions (Theory)
Q1 How does the laminar flow help microfluidic design Why
Q2 Which network has equal flow through branches
Why How is it designed in your chip
Q3 Which path will have higher flow Why
Q4 For what are the hooks between media input and waste outputs useful
Q5 Why do we have 2 inlets and 2 outlets
Q6 Define low Reynolds number Typical Ecoli (20μm long and 05μm in diameter) is characterized
by low or high Reynolds number
Q7 How are fluidic resistance and channel width related
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
9
14 Integration of Microfluidics and Microscopy
Microfluidics has recently found wide applications in research aimed at observing cellular development within
dynamic microenvironments Devices designed for these purposes frequently possess the ability to generate
thermal andor chemical gradients across the cell development volume Another recently demonstrated strength of
microfluidics is the ability to generate large-scale and highly parallel integrated circuits of fluidic channels for
high-throughput cellular analysis11-13
However for researchers interested in studying the behavior of synthetic
gene circuits the most challenging goal of microfluidics has been in supporting long-term single-cell analysis
for large sample populations Therefore much recent research has focused on this goal using various design
strategies
One group approached the difficulties in single-cell analysis by developing a microfluidic network enabling the
passive and gentle separation of a single cell from bulk suspension14
This individual cell is focused by
hydrostatic pressure and laminar flow streams to a trapping region where integrated valves and pumps enable the
precise delivery of nanoliter volumes of reagents to that cell Whereas this research focused on individual cells
over a relatively short time span another group developed a microfluidic platform for long-term cell culture
studies spanning the entire differentiation process of mammalian cells15
They demonstrated operation of this
device by observing a culture of muscle cells differentiating from myoblasts to myotubes over the course of two
weeks
To researchers interested in long-term gene expression variability within single-celled prokaryotic and
eukaryotic populations a chemostat likely represents the ideal cell assay In recent years the many challenges
involved in operating continuous macroscale bioreactors (such as the need for large quantities of reagents) have
driven the miniaturization of these devices into microfluidic chip-based formats In continually providing fresh
nutrients and removing cellular waste to support exponential growth the microfluidic chemostat (small cell
trapping region) presents a nearly constant environment that is ideal for long-term cell culture monitoring with
single-cell resolution Recently one group presented a microfluidic chemostat for culturing bacterial and yeast
cells in an array of shallow microscopic chambers with support for dynamically-defined media16
Similarly a
recent implementation of a microfluidic bioreactor has enabled long-term culturing and monitoring of small
populations of bacteria with single-cell resolution17
This microchemostat contained an integrated peristaltic pump
and a series of micromechanical valves to add medium remove waste and recover cells The device was used to
observe the dynamics of an E coli strain carrying a synthetic ldquopopulation controlrdquo circuit that regulates cell
density through a feedback mechanism based on quorum sensing
A final implementation of the chemostat design was utilized to precisely control and constrain exponential
growth of the yeast Scerevisiae and E coli to a monolayer18
Here dimensions of the chemostat device were
precisely controlled to constrain exponential growth of yeast and E coli cells to a monolayer The device has
been modified for imaging a culture of cells growing in exponential phase for many generations The construction
was such that a shallow trapping region will constrain a population of cells to the same focal plane
The significant advantage of monolayer growth in a height-constrained chamber was demonstrated by
visualization of a group of cells residing at the trapping region boundary Through directed planar growth the
researchers were able to resolve the temporal evolution of single-cell gene expression levels with the aid of
segmentation and tracking software Advantages of this device design and software package included simple
operation and automated single-cell fluorescence trajectory extraction Such novel data should prove useful in
investigating the timing and variability of gene expression within various synthetic gene regulatory network
architectures on the time scale of many cellular generations
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
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MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
10
141 Fluorescence imaging
Fluorescence microscopy is the most popular method for studying the dynamic behavior exhibited in live cell
imaging This stems from its ability to isolate individual proteins with a high degree of specificity from non-
fluorescing material The sensitivity is high enough to detect as few as 50 molecules per cubic micrometer
Different molecules can now be stained with different colors allowing multiple types of molecule to be tracked
simultaneously These factors combine give fluorescence microscopy a clear advantage over other optical
imaging techniques for both in vitro and in vivo imaging
Fluorescence microscope is a light microscope used to study properties of organic or inorganic substances using
the phenomena of fluorescence instead of or in addition to reflection and absorption In most cases a
component of interest in the specimen is specifically labeled with a fluorescent molecule called a fluorophore
(such as GFP Green Fluorescent Protein) GFP is a fluorescent protein that was first found in the jellyfish
Aequorea Victoria It has the useful property that its formation is not species specific This means that it can be
fused to virtually any target protein by genetically encoding its cDNA as a fusion with the cDNA of the target
protein This can be done in a live cell and hence the movement of individual cellular components can now be
analyzed across time
a) b)
Wavelenght (nm)
Spectrum
Figure 6 a) Fluorescence imaging principle (Wikipedia Fluorescence_microscopy) b) Excitation and emission spectra of the dyes
used in this practical FITC very close the GFP excitation and emission spectra
There is no requirement to fix and permeablize the cells first The discovery of GFP has made the imaging of
real-time dynamic processes commonplace and caused a revolution in optical imaging The GFP revolution goes
even further with the development of different colored GFP isoforms such as yellow GFP and cyan GFP This
allows multiple proteins to be viewed simultaneously in a cell
In this practical we use 25 microm PeakFlowtrade green flow cytometry reference beads that stained with fluorescent
dye (FITC) that have been carefully selected to produce emission peaks coincident with labeled cells used in
typical flow cytometry applications (GFP labeled cells) Because PeakFlowtrade beads are highly uniform with
respect to both size and fluorescence intensity and because they approximate the size emission wavelength and
intensity of many biological samples they can be used to calibrate a flow cytometer‟s laser source optics stream
flow and cell sorting system without wasting valuable and sensitive experimental material
The specimen is illuminated with light of a specific wavelength which is absorbed by the fluorophores causing
them to emit longer wavelengths of light (of a different color than the absorbed light) The illumination light is
separated from the much weaker emitted fluorescence through the use of a dichroic mirror Typical components
of a fluorescence microscope are the light source (Xenon or Mercury arc-discharge lamp) the excitation filter the
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
11
dichroic mirror (or dichromatic beamsplitter) and the emission filter The filters and the dichroic are chosen to
match the spectral excitation and emission characteristics of the fluorophore used to label the specimen
142Filters Filters used in this work are called FITC (Figure 7) according to the traditional fluorochromes that were earlier
commonly used for green and red fluorescence In the figure the blue (1) curve shows the excitation ie the
wavelengths that illuminate the sample The red (2) curve shows the emission ie the wavelengths that are shown
to the viewer
Figure 7 FITC filter spectrum 1 = excitation band 2 = emission band
2 PRACTICAL WORK
21 Material requirements
Handling Safety glasses gloves tweezers Petri dishes pipettes spoons cups razor blades scalpels
aluminum foil
Machines Ventilated fume hood high precision scale nitrogen gun mechanical mixer vacuum
desiccators manual hole-punching machine binocular ovenhot plate oxygen plasma
Products Sylgard 184 silicone base Sylgard curing agent silanizing agent (TMCS
Chlorotrimethylsilane 33014 from sigma)
22 PDMS silicon molds
The first step in PDMS molding is designing molds and creating them SU-8 processing and silicon etching are
the two protocols commonly used to realize molds for PDMS micro-molding Procedures for creating these molds
are not presented in this present document Our TA‟s prepared molds and they are in the AMBL marked wafer
holder
221 Surface conditioning
The surface conditioning of the mold is important to prevent PDMS sticking A silanization allows passivation
of the surfaces to aid release from PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
12
TMCS is corrosive - causes skin burns harmful in contact with skin also it is armful if swallowed and it
is respiratory irritant Therefore its handling should be done under the fume hood and you are suggested to
wear extra pair of gloves
1) Put on single use additional gloves and operate
only under the fume hood
2) Place a few drops of TMCS in the small glass
receptacle located in the desiccator (single use
pipettes are available for that purpose)
Note If TMCS bottle is not in the glass desiccator
fetch it in the ldquosolventrdquo cabinet located on the right
side of the wet bench
TMCS
Wafer with
PDMS mold
Glass
receptacle
Desiccator
single use
pipettes
3) Remove any dust on the surface of the mold using a
nitrogen gun
4) Place the siliconSU8 mold in this very same desiccator
5) Close the desiccator and place it under vacuum (this
causes the TMCS to evaporate and to form a passivation
layer on the mold surface)
6) Close well the TMCS bottle (use tape also) Fill-in the
ldquochemicals follow-uprdquo document 7) When desired time is reached (~15min) vent the
desiccator DO NOT breath directly above the open
desiccator
8) Take your mold back put the TMCS bottle in the
desiccator and put it back under vacuum
15 min
222 Mixing ndash Degassing
Silicone prepolymer material is very viscous and sticky Use additional gloves before handling the liquid
PDMS Aluminum foil is used as a liner for protecting equipment in contact with the (Petri dishes scale etc) A
single use plastic cup is to be used for preparing the PDMS mixture The plastic cups are compatible with the
mechanical mixer and their maximum capacity is 50g This means the total mixture must weigh 50 g maximum
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
13
5) Use the mechanical mixer to correctly
homogenize the mixture (Program 1)
o Mixing 1min 2000rpm
o Defoaming 2min 2200rpm
6) Clean the scale well before switching it off and
clean the product bottles
223 Pouring ndash Spin coating
Pour the PDMS mixture over the passivated mold placed in a
Petri dish or plastic disposable dish The interior of that dish
should be protected with aluminum foil
1) Be careful not to create bubbles while pouring the
mixture (proceed slowly)
2) The mixture is then degassed in the desiccator to remove
any remaining entrapped bubbles If large bubbles form
at the surface vent vacuum slowly so the mixture does not foam out Put it back under vacuum until no
bubbles are visible This also improves the filling of small structures
224 Baking ndash Curing
PDMS can cure without heating in ~24 hours To decrease cure time
put the Petri dish in an oven for 1 hour at ~80degC Curing time
depends on temperature and on the thickness of PDMS After curing
the wafer is stable and can be stored for months if necessary To save
time we provide you an already cured PDMS
80 degC
1) Put an empty and clean single use plastic cup on
the precision scale- Tare the scale so it displays 0
2) Add the base PDMS (max 40g) and write down the
value
3) Tare the scale so it displays 0- Using a pipette add
the catalyst (max 4g) to reach the ratio value 101
4) Place the cup in the mixing machine and adjust the
revolution balance dial according to the total
weight of the cup
Caution adapter weight of 115g to be added to the
weight of your cup
bubbles no bubbles
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
14
binocular
hole punching
machine
225 Alignment - Demolding ndash Creating access ports by punching
After cooling the PDMS is easily peeled off and cut Use adequate
tools to perform it (tweezers razor bladeshellip)
1) Cut the PDMS into the desired shape DO NOT damage the device
network
2) Create access ports using the manual hole punching machine fitted
with a light source and a video camera Alignment of PDMS
samples with other glassPDMSsilicon pieces can be done using the
binocular
226 Surface activation for bonding
PDMS can be bonded to glass silicon and itself using
oxygen plasma surface activation PDMS is hydrophobic
with a low energy and non-reactive surface It is therefore
difficult to bond it with other surfaces By exposing
PDMS to oxygen plasma its surface becomes hydrophilic
and more reactive This results in irreversible bonding
when it contacts glass silicon or even another PDMS
piece that was exposed to the same oxygen plasma
Contact should be made quickly after plasma exposition
because the PDMS surface will undergo reconstitution to
its hydrophobic and non-reactive state within hours A fine tuning of the oxygen plasma is necessary a too long
exposure will create too many Si-OH sites resulting in a non-sticking silica layer A too short exposure will not
create enough Si-OH sites for good bonding 100 W 03 torr and 6 sec are suggested as parameters The bonding
is accelerated if a post-bake is then performed
23 Integration of Microfluidics and Microscopy
231 Set up the pressure controller
The fluid flow through the device is controlled with a pressure controller rather than a direct control of the flow
rate This means that the actual flow rates will be a function of the tubing length and diameter the relative height
of the different components and the pressures The needed pressures will therefore be slightly different for each
time the experiment is set up
The MFCS controller needs a 10 minute warm up period It should be turned on and warming up while the rest of
the components are prepared
1) Turn on the controller (power switch on the back)
2) Open the MFCS_4C software
3) Press the green button on the front of the controller ndash the warm up timer should begin counting down
Plasma
glass coverslip
PDMS
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
15
Pressure channels
Figure 8MFCS controller and software interface
232 Set up the tubing
While the controller is warming up prepare the inlet and outlet tubing pieces Minimizing the overall length of
the tubing used will allow for the use of lower pressures and will also help with the flow stability of the system
1) Use equal length tubing for both inlets and equal length tubing for both outlets
2) Small pieces of steel adaptor tubing are used to couple the inlet and outlet tubing into the device The
adaptors will press-fit into the 002rdquo ID Tygon tubing and also into the cored holes in the PDMS
3) Use the shortest length Tygon tubing that will reach from the device inlets to the sample tubes (fluiwells)
leaving some room to move the device around on the microscope stage
4) The sample end of the inlet tubing will fit through the ferrule on the top of the sample tube in the pressure
controller The ferrule should be screwed down tightly to get the best pressure control The end of the
tubing should sit near the bottom of the sample tube
5) Use very short pieces of Tygon tubing for the outlets (~10 cm)
6) Arrange the end of the outlet tubing so that the flow can spill into a suitable dish eg a petri dish as
shown in Figure 9
7) Make sure that the sample tubes are kept at the same height as the device
Inlet 1 Media
Inlet 2 Cellsbeads
Outlet 1 Outlet 2
Outlet 1 Outlet 2
Inlet 2 Cellsbeads
Inlet 1 Media
WASTE container
Figure 9 Tubing connection
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
16
233 Sample preparation
1) Prepare a bead solution by adding some of the bead stock solution into buffer A good bead concentration
is at least 10L of 1 bead stock solution per mL of buffer Shake vigorously beforehand the bead
solution anytime you handle it
2) Add about 2 mL of bead solution to a sample tube and attach the sample tube to the appropriate channel
in the sample holder
3) Fill another sample tube with buffer Attach the sample tube to the appropriate channel in the sample
holder
4) Make sure all components are sealed tightly
234 Microscopy
You will use the Olympus IX 81 inverted compound microscope Please refer to the MicroscopyKoehlerdark
field illumination section of the master handout to perform this step
Aside from initial calibration and occasional high-power measurements you will find the 20x objective and dark-
field illumination most useful
1) Set up the Kogler illumination
2) Then set the dark field illumination
24 Run the sample
In general the waste outlets should always be at a lower pressure relative to the media and cell inlets Since the
outlets are not connected to the pressure controller a positive pressure on the inlets will satisfy this
1) To control pressures the bdquodirect control‟ button needs to be clicked
2) The pressures in each channel can be controlled with the appropriate slider or by entering the
value in the bdquorequested pressure‟ box You don‟t need to change any of the other control
parameters
3) The flow rate through the device to observe particle motion will be much lower than the flow
rate needed to fill the inlet tubing in a reasonable time The pressure controller has two channels
with a range from 0-25 mBar and two channels with a range from 0-1000 mBar Therefore the
inlet tubing should first be connected to the high pressure channels to fill the inlet tubing quickly
and then switched to the low pressure channels 4) Use channels 3 and 4 to fill the device with buffer Make sure the tubing from the controller to the sample
holder is connected from the correct channel to the correct sample
5) At pressures of around 50 ndash 100 mBar filling the device will only take a minute or so
6) While fluid is flowing inspect the device under the microscope to see if there are a significant amount of
bubbles still in the device If so let the buffer run for a while longer at high pressure
7) Once the device is filled with fluid turn the requested pressures to 0 You should be able to see beads in
the channel when the fluid motion is stopped
8) Switch to controlling the pressure through channels 1 and 2 by changing the tubing connections at the
controller
9) When running at low pressures to observe particle motion the pressure difference between the media and
cellwaste ports will be rather small to get flow from both into the waste outlets ndash if one is too high it will
cause backflow into the other The difference between the two is likely to be less than 1 mBar Final
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
17
working pressures will be in the range of 2 - 10 mBar At the lower pressures the fluid motion will be
slow enough to track the particle motion through the main channel Only a few beads will enter the traps -
most will flow in main section A good way to observe beads flowing through the traps is to use the 40X
objective focused on a trap with a higher pressure setting so that more beads are passing per time period
25 Viewing Tracking Particles in Device Geometry
Now that the device has been contacted and flow regulated and the microscope has been fully configured we
are now ready to take data
1) Use 25m beads sample to establish the pixel size of your camera
2) Turn on the Andor camera
3) Open Andor camera software called Solis
4) Turn the switch on the microscope to send an image to CCD camera
5) Click on the movie camera icon to get a live image from your sample
6) Set up the exposure time to 005s by pressing exposure button (Figure 12)
7) To take pixel calibration image open in the main menu acquisition under setup CCD select c Single
enter following values exposure time 001-0075s next under Setup acquisition open binning to 512-512
pixels you can move binning box to the region around your 25m bead press Ok and close Acquisition
menu
8) Press Record and save image as sif file
9) Now we are ready to collect movies for your analysis session
10) To setup your movies exposure time t kinetic series length (number of frames in your movies ) open
in the main menu acquisition under setup CCD select Kinetic series enter following values exposure
time 001-0075s kinetic series length 500 next under Setup acquisition if necessary open binning to 512-
512 pixels you can move binning box to the region containing the most beads Mark in your notebook
the values you entered Otherwise note in the notebook that you have take full images (13921040)
11) Press record
12) Save files as sif Collect all necessary data and save them in your folder
13) Repeat this for several bead speeds
14) Once you have finished data collection you will need to convert all sif files in raw files You can do it
file by file or using a batch conversion option in File menu (Main Menu) Make sure that you convert it in
16 bit unsigned integer (with range 0-65322) This is format required for the analysis session
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
18
RecordLive Exposure
Figure 10 Andor Solis program for data acquisition Bright field image of device and 1m beads
26 Epifluorescence
Before starting turn on the Mercury LAMP
controller
We have only one filter cube set suitable or imaging
of FITC labeled beads and GFP labeled bacteria
Locate its position (out of 6 possible) and open the
filter cube shutter If you observe bright blue light
as shown on Figure 11 you have located it
Figure 11 Epifluorescence
1) Now you can close the shutter and put light protection on the microscope body
2) Use brightfield first to locate your specimen
3) Switch to the Mercury lamp as the light source
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
19
4) Open the filter cube shutter
5) Make sure that sample is uniformly illuminated (if not open the diaphragm located close to the Mercury
lamp)
6) Repeat the same measurements as in bright filed (for imageJ analysis fluorescence movies are easier to
analyze) Steps 6-14 are same maybe you will need to adjust exposure time
Note When not viewing the specimen close the fluorescence shutter (push the shutter slider in) to minimize
photobleaching of the specimen
Depending on the objective size you should observe something similar to images shown below
a) b)
Figure 12 Fluorescence images of the device and beads using in a) 5 X in b) 40 x objective
7) Now stop running beads and try to flush only medium (water through the channel) this should remove
most of the beads from channels and leave the one in the traps
8) Take fluorescence images of 5 traps
3 DATA ANALYSIS
31 Calibration (done by TA beforehand)
1) Open in ImageJ your dark filed image of 25m beads taken for bin size of
512512 pixels or 13921040 pixels
2) Use a line tool in ImageJ toolbox to draw a line across the selected bead Below
the Image J toolbox you will notice xy coordinates of your line together with
the angle and the length of the drawn line Make sure to draw the line straight
across the bead diameter
3) Next open AnalyzeSet Scale from File menu where you enter the length of
25m bead as known distance It will calculate the pixel aspect ratio of either 1
(512512) or 133 (13921040) Use these parameters to set a scale on all
movies that you will be processing
Make sure you have used same objective and same binning
32 Particle Tracking
To obtain single particle trajectories from recorded movies you will need to use Particle Detector and Tracker
which is an ImageJ Plugin for particles detection and tracking from digital videos
The plugin implements the feature point detection and tracking algorithm as described in recent publication by
Sbalzarini et al6 This plugin presents an easy-to-use computationally efficient two-dimensional feature point-
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
20
tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell
biology The tracking process requires no apriori mathematical modeling of the motion it is self-initializing it
discriminates spurious detections and it can handle temporary occlusion as well as particle appearance and
disappearance from the image region The plugin is well suited for video imaging in cell biology relying on low-
intensity fluorescence microscopy It allows the user to visualize and analyze the detected particles and found
trajectories in various ways i) Preview and save detected particles for separate analysis ii) Global non
progressive view on all trajectories iii) Focused progressive view on individually selected trajectory and iv)
Focused progressive view on trajectories in an area of interest
It also allows the user to find trajectories from uploaded particles position and information text files and then to
plot particles parameters vs time - along a trajectory
321 File opening
1) Before the plugin can be started you must open an image sequence or a movie in ImageJ For opening
your saved movie use the Import Raw from the File menu You should input following parameters as
indicated in Figure 13 (Check your lab notes for number of frames and binning size) Upon file import
you should obtain video sequence of your moving beads
Figure 13 Import parameters
2) Next you need to improve contrast and adapt your movie so that it can be treated with ParticleTracker
plugin To do so use the ImageType 8 bit option from File menu
3) Next you need to increase contrast you will do it by using ProcessEnhance Contrast option from File
menu It is safe to select 01saturated pixels under Use Stack Histogram
4) To filter out noise use ProcessFilterGaussian blur option from File menu Again safe sigma value to
use is 12 Before applying this filtering you can preview your movie
Q8 What is going on when your sigma is larger than 3
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
21
322 Plugin start
5) Now that the movie is open and compatible with the plugging you can start the plugin by selecting
ParticleTracker from the Plugins - Particle Detector amp Tracker menu After starting the plugin a dialog
screen is displayed The dialog has two parts ldquoParticle Detectionrdquo and ldquoParticle Linkingrdquo
Figure 14 Parameters for better movie quality
Particle Detection This part of the dialog allows you to adjust parameters relevant to the particle
detection (feature point detection) part of the algorithm
Preview the detected particles in each frame according to the parameters This options offers
assistance in choosing good values for the parameters Save the detected particles according to the
parameters for all frames The parameters relevant for detection are
Radius Approximate radius of the particles in the images in units of pixels The value should be
slightly larger than the visible particle radius but smaller than the smallest inter-particle separation
Cutoff The score cut-off for the non-particle discrimination
Percentile The percentile (r) that determines which bright pixels are accepted as Particles All local
maxima in the upper rth percentile of the image intensity distribution are considered candidate Particles
Unit percent ()
6) Clicking on the Preview Detected button will circle the detected particles in the current frame according
to the parameters currently set To view the detected particles in other frames use the slider placed under
the Preview Detected button You can adjust the parameters and check how it affects the detection by
clicking again on Preview Detected Depending on the size of your particles and movie quality you will
need to play with parameters
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
22
Note that very rarely you detect all particles in the field of view mostly due to the fact that they quickly go out of
focus
7) To start on 25m beads enter these parameters radius = 6 cutoff = 0 percentile = 04 and click on
preview detected Check the detected particles at the next frames by using the slider in the dialog menu
With radius of 5 they are rightly detected as 2 separate particles If you have any doubt they are 2 separate
particles you can look at the 3rd frame Change the radius to 10 and click the preview button With this
parameter the algorithm wrongfully detects them as one particle since they are both within the radius of
10 pixels
8) Try other values for the radius parameter Go back to these parameters radius = 5 cutoff = 0 percentile =
04 and click on preview detected It is obvious that there are more real particles in the image that were
not detected Notice that the detected particles are much brighter then the ones not detected Since the
score cut-off is set to zero we can rightfully assume that increasing the percentile of particle intensity
taken will make the algorithm detect more particles (with lower intensity) The higher the number in the
percentile field - the more particles will be detected Try setting the percentile value to 2 After clicking
the preview button you will see that much more particles are detected in fact too many particles - you
will need to find the right balance (for our dark filed movies between 03-07 )
There is no right and wrong here - it is possible that the original percentile = 01 will be more suitable
even with this film if for example only very high intensity particles are of interest
Figure 15 Parameters for particle detection On the left panel with default values In the right movie with particles
identified using following parameters radius = 5 cutoff = 0 percentile = 04
323 Viewing the results
9) After setting the parameters for the detection (we will go with radius = 5 cutoff = 0 percentile = 06) you
should set the particle linking parameters The parameters relevant for linking are
Displacement The maximum number of pixels a particle is allowed to move between two succeeding
frames
Link Range The number of subsequent frames that is taken into account to determine the optimal
correspondence matching
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
23
10) These parameters can also be very different from one movie to the other and can also be modified after
viewing the initial results Put following initial guess for the displacement=5 and link range =3You can
now go ahead with the linking by clicking OK
11) After completing the particle tracking the result window will be displayed Click the Visualize all
Trajectories button to view all the found trajectories
12) Window displays an overview of all trajectories found It cannot be saved It is usually hard to make
sense of so much information One way to reduce the displayed trajectories is to filter short trajectories
Click on the Filter Options button to filter out trajectories under a given length Enter 75 and click OK
(Be careful if you select to long length you might end up with very few trajectories and lose
information)
13) Select a trajectory by clicking it once with the mouse left button A rectangle surrounding the selected
trajectory appears and the number of this trajectory will be displayed on the trajectory column of the
results window
14) Now that a specific trajectory is selected you focus on it to get its information Click on Selected
Trajectory Info button The information about this trajectory will be displayed in the results window
15) Click on the Focus on Selected Trajectory button - a new window with a focused view of this trajectory is
displayed This view can be saved with the trajectory animation through the File menu of ImageJ Look at
the focused view and compare it to the overview window - in the focused view only the selected
trajectory is displayed
16) Finally you can save the data by pressing Save Full report Repeat particle tracking for all 3 experimental
conditions measured in the first part of the practical work (2 different speeds)
33 Matlab analysis
Now when you have obtained single particle tracks for two different speeds by using provided matlab
code you can
1) Plot trajectories of certain length (not shorter than 50 frames)
2) Calculate speed (mark the exposure time)
3) Find and plot MSD
34 Particle analysis (If you have enough time)
The goal of this part is to count and determine the size distribution of trapped fluorescent beads
Particle counting can be done automatically if the specimen lends itself to it ie the individual particles can touch
ndash but not too much If automatic particle counting cannot be done ImageJ can facilitate manual counting with the
ldquoPoint Pickerrdquo or ldquoCell counterrdquo plugin
341 Automatic Particle counting
The biggest issue is one referred to as ldquosegmentationrdquo which is to distinguish the object from the background
Once the objects have been successfully segmented they can then be analysed
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
24
342 Loading an image into the ImageJ program
1) Open the ImageJ program
2) Go to FileOpen Select the picture that you would like to analyze
Note It may be the case that you need to convert the image to a JPEG or analogous format To do this
simply open the picture with Preview and save the picture as a JPEG using Save As then use the toggle to
select the format to JPEG
3) You should now be able to see the image that you want to analyze
Optional If you would like to know the actual areas of objects on the screen say the areas of a collection of cells
and then knowing units is a must ImageJ does this with ease
4) On the ImageJ Tool Bar select the straight-line icon (This is on the same tool bar as a square an oval
etc It‟s the same tool bar that opens up with ImageJ)
5) Using the straight-line tool use the cursor to mark the length of any object on the picture that you know
the length of
6) On the top tool bar select Analyze
7) Scroll down to Set Scale
8) Fill in Known Distance to the length of the object that you are measuring This allows ImageJ to set up a
pixel to distance ratio that allows area to be expressed in the appropriate units
9) Fill in the units of measurement Any units of distance should work cm mm microns etc
10) Click Global
11) Click Okay
12) To check that you have indeed set the scale use the line tool again and measure another object Select
Analyze and then select Measure A window should pop up that displays the length of the object you just
measured
343 Particle analysis
1) Click on the image in the ImageJ window
2) On the top tool bar select Image Select Type
3) Select 8-bit This converts the image into a
format that makes analysis possible You
should now see that your image is no longer in
color
4) If necessary crop only image part that contains trapped particles
5) You can do that by drawing the rectangle and by cropping the image Ctrl +Shift+X
6) On the top tool bar select Image
7) Duplicate Image
8) On the top tool bar select Image
9) Select Adjust the select Threshold
10) This step should have turned all of the objects of interest Red (adjust scrollbar ) and then clicking on
Apply once you are satisfied with the selection
11) This will turn your image in binary image (if you need you can fill holes by pressing Process-Binary-Fill
Holes)
12) If two particles are joined together you can use processing filters such as Process Binary ndash Watershed to
separate them
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
25
13) On the top tool bar select Analyze
14) Select Analyze Particles
15) A window will pop up Under Size (in the units you specified) give
the area that you want to analyze a lower bound So if you wanted a
minimum of say 10m2 you would write 10-Infinity in the box Click
Display Results and don‟t click any of the other boxes All other
boxes should be clear of check marks
16) In the Toggle Menu select Outlines
17) Click Okay
18) Two windows should have popped up One with the areas of the
objects listed in the units you specified and another window with the
objects outlined with numbers inside their outlines Each number
with an area corresponds to the area of the object with that number in
it
19) Results will be saved as excel file
344 Statistics
1) If you would like a distribution of the areas click on your image again The objects of interest should still
be in red
2) On the top tool bar select Analyze
3) Select Distribution
4) Unselect Automatic Binning
5) Write in the number of bins that you want and what area range to consider
6) Click Okay
7) A window should come up that gives you all necessary statistics for the areas of the objects in your
picture and their distribution in a bar format
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
26
35 Questions
Q9 What is the average velocity of the moving beads In which section of the channel does the interface move the
fastest for a given applied pressure Compute according to the Error Propagation Handout the standard deviation of
the average velocity
Q10 For a given applied pressure how will the fluid speed vary in the differently sized channels (as observable) by
looking at the motion of the beads Why
Q11 What is an average number of trapped beads Can you suggest how to increase the number of trapped beads
Q12 Propose one biological application for a Lab on the chip device
4 REFERENCE
1 Unger M A Chou H P Thorsen T Scherer A amp Quake S R Monolithic microfabricated valves
and pumps by multilayer soft lithography Science 288 113-116 (2000) 2 Ashton R Padala C amp Kane R S Microfluidic separation of DNA Current Opinion in Biotechnology
14 497-504 doiDoi 101016S0958-1669(03)00113-7 (2003) 3 Paegel B M Blazej R G amp Mathies R A Microfluidic devices for DNA sequencing sample
preparation and electrophoretic analysis Current Opinion in Biotechnology 14 42-50 doiDoi 101016S0958-1669(02)00004-6 (2003)
4 Lion N et al Microfluidic systems in proteomics Electrophoresis 24 3533-3562 doiDOI 101002elps200305629 (2003)
5 Groisman A Enzelberger M amp Quake S R Microfluidic memory and control devices Science 300 955-958 (2003)
6 Huh D Gu W Kamotani Y Grotberg J B amp Takayama S Microfluidics for flow cytometric analysis of cells and particles Physiol Meas 26 R73-R98 doiDoi 1010880967-3334263R02 (2005)
7 Danino T Mondragon-Palomino O Tsimring L amp Hasty J A synchronized quorum of genetic clocks Nature 463 326-330 doiDoi 101038Nature08753 (2010)
8 Lin F et al Generation of dynamic temporal and spatial concentration gradients using microfluidic devices Lab on a Chip 4 164-167 doiDoi 101039B313600k (2004)
9 Dertinger S K W Chiu D T Jeon N L amp Whitesides G M Generation of gradients having complex shapes using microfluidic networks Anal Chem 73 1240-1246 (2001)
10 Mao H Yang T amp Cremer P S A microfluidic device with a linear temperature gradient for parallel and combinatorial measurements J Am Chem Soc 124 4432-4435 doija017625x [pii] (2002)
11 Hong J W Studer V Hang G Anderson W F amp Quake S R A nanoliter-scale nucleic acid processor with parallel architecture Nature Biotechnology 22 435-439 doiDoi 101038Nbt951 (2004)
12 Fu A Y Chou H P Spence C Arnold F H amp Quake S R An integrated microfabricated cell sorter Anal Chem 74 2451-2457 doiDoi 101021Ac0255330 (2002)
13 Balaban N Q Merrin J Chait R Kowalik L amp Leibler S Bacterial persistence as a phenotypic switch Science 305 1622-1625 doiDOI 101126science1099390 (2004)
14 Wheeler A R et al Microfluidic device for single-cell analysis Anal Chem 75 3581-3586 doiDoi 101021Ac0340758 (2003)
15 Tourovskaia A Figueroa-Masot X amp Folch A Differentiation-on-a-chip A microfluidic platform for long-term cell culture studies Lab on a Chip 5 14-19 doiDoi 101039B405719h (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)
ADVANCED BIOENGINEERING METHODS LABORATORY
MICROFLUIDICS LAB ON CHIP
Aleksandra Radenovic
27
16 Groisman A et al A microfluidic chemostat for experiments with bacterial and yeast cells Nature Methods 2 685-689 doiDoi 101038Nmeth784 (2005)
17 Balagadde F K You L C Hansen C L Arnold F H amp Quake S R Long-term monitoring of bacteria undergoing programmed population control in a microchemostat Science 309 137-140 doiDOI 101126science1109173 (2005)
18 Cookson S Ostroff N Pang W L Volfson D amp Hasty J Monitoring dynamics of single-cell gene expression over multiple cell cycles Mol Syst Biol - doiArtn 20050024 Doi 101038Msb4100032 (2005)