Automated Sample Processing for Pathogen Detection Systems · Automated Sample Processing for Pathogen Detection Systems 3. The Need and Goal LORRE, Laboratory of Renewable Resources

Automated Sample Processing for

Pathogen Detection Systems

LORRE, Laboratory of Renewable Resources Engineering

Center for Food Safety Engineering

Laboratory of Renewable Resources Engineering

Agricultural and Biological Engineering

Food Science

Biomedical Engineering

Electrical and Computer Engineering (U. Illinois)

Purdue University

Eduardo Ximenes, Hunter Vibbert,

Amy Fleishman-Littlejohn, Linda Liu, Kirk Foster, Jim

Jones, Richard Hendrickson, Arun Bhunia, Rashid

Bashir, Michael Ladisch

1

Acknowledgments


Dr. Jim Lindsay, Dr. Shu-I Tu

USDA Cooperative Agreement OSQR

Eastern Regional Research Center

Center for Food Safety Engineering

Dr. George Paoli from USDA-ARS

Dr. Jaeho Shin, Dr. Mira Sedlak, Dr. Nathan Mosier, LORRE,

ABE

Bruce Applegate, Lisa Mauer, Department of Food Science

Co-founder of Biovitesse: Rashid Bashir; Arun Bhunia, Consultant

2

Outline


1. The Need and Goal

2. Distribution of Microorganisms

3. The Science Behind the Cell Concentration and Recovery

(CCR) Process

4. Hollow Fiber Membrane CCR Instrument: The Engineer

5. Applications

Automated Sample Processing for Pathogen

Detection Systems

3

The Need and Goal


Rapid Detection of Food Pathogens as Well as the Source:

reduce public health risks

Microbial concentrations need to be

brought to detectable level

Enrichment

Culture

Cell Concentration

and Recovery

4

The Need and Goal


Enrichment

Culture

Cell Concentration

and Recovery

Time Consuming Shorter Time Goal: t < 4 h

5

DISTRIBUTION OF MICROORGANISMS


6

Bacterial Attachment to Surface

(generally a 2 steps model used for description)

1- Initial Reversible Attachment

Involves weak forces between bacterium and

the substratum:

Van de Waals forces

Electrostatic forces

Hydrophobic interactions



7

2- Irreversible attachment

When in some case electrostatic repulsion can be greater

than weak attractive forces

Cellular surface structures (flagella and fimbraie) and

substances (exopolysaccharides) overcome the

electrostatic repulsion to adhere to the substratum

Other factors involved: stronger forces (covalent and

Hydrogen bonds) and strong hydrophobic interactions

= Irreversible

Attachment

Goulter et al. 2009. Letters in Applied Microbiology 49: 1-7



8

Alternatively:

Saggers et al. 2008: bacterial colonization of prepared fruit

and vegetable tissues is the result of 3 phases:

1- an initial attachment;

2- a consolidation phase (may involve production of

extracellular polymer);

3- subsequent growth to form microcolonies

Saggers et al. (2008). Journal of Applied Microbiology 105: 1239-1245

Distribution of

Microorganisms


9

The binding affinity is measured by using the formula below:

Cs = a measure of concentration of bacteria bound on the specific

substrate;

Cs = measured in cfu/g, where the average mass of the samples was

used to determine a weight to substitute in for the mass;

Cw = a measure of concentration of the bacteria in the unbound

phase; measured in cfu/mL;

Kd = measured on a log scale to enhance larger differences.

Kd= Log (CS/CW)

Distribution of Microorganisms


10

Substrate Sample

& Bacteria in

Buffer

Bacteria

Sample in

Buffer

Buffer

Substrate

& BufferMethod:

1. Prepare ligand and calculate volume;

2. Vegetable or meat substrate sprayed with 70 % (v/v) ethanol and let drying;

3. Substrates placed in labeled microplate (low binding affinity) under hood;

4. In a hood, dilute bacteria to appropriate concentration;

5. Place 10 mL of buffer (PBS, PBS + 0.1 % Tween or Buffered Peptone Water)

in each microplate well;

6. Inoculate appropriate wells with bacteria;

7. Place in ice bath shaker at 120 RPM for 1 hour at 4oC;

8. Plate Samples (Selective Medium: LB-amp for E. coli and Chromo agar for

Salmonella).



11

Non-Pathogenic E. coli GFP

Binding to vegetables (4°C) : Potato (Skin, Fresh and both)

Solvents

PBS +

0.1 % TweenBuffered Peptone Water

Kd

(mL/g

)

Flesh

Both

Skin

PBS

0.0

1.0

2.0



12

Non-Pathogenic E. coli GFP

Binding to meat (4°C): Hot dog

103

104

105

102

cfu/mL

Sample

1-Buffered Peptone Water (some contamination)2-Buffered Peptone Water (no contamination)

3-Water (no contamination)

Kd

(mL/ g

)

-2

-1

0

1

1

2 3



13

Pathogenic Salmonella enteritidis

Binding to meat (4°C):Chicken breast in buffered peptone

** Sample in Buffered Peptone Water



14

Work in Progress : use our method to test different

experimental conditions:

1- Microorganisms and/or Substrates;

2- Buffers, pH;

3- Temperature;

4- Incubation time, agitation etc

Literature : Significant binding at 20°C (up to 30 min

incubation time) to chicken muscle surfaces immersed

in water and surface of prepared vegetable tissues.

Thomas and McMeekin (1981). Applied EnvironmentalMicrobiology 42 (1) : 130-134;

Saggers et al. (2008). Journal of Applied Microbiology (105): 1239-1245

The Science Behind the CCR

Process


MAJOR CHALLEGES TO BE ADDRESSED

Separation of Food Samples and Bacteria

Membrane Fouling

Recover Viable Cells

15

First CCR Instrument

Flat Membrane CCR Process

(1st Prototype)


Effective for concentrating microbial

cells for microbiological analysis of

water, dairy, and food products*

1. Fouling of the membrane

and the need for removing

and handling it.

2. Achieving semi-continuous,

hands-off operation

Challenge

*Chen et al. 2005. Biotechnol Bioeng. 89:263-273.

16

Hollow Fiber Membrane CCR Process


Advantages Over Flat Membranes:

High surface area to volume ratio;

Higher flux per unit volume of the

membrane module;

Continuous operation that avoids

manual handling of the membrane

and sample;

Easily back flushed to recover

concentrated cells of interestCross section view of

a hollow fiber

200 μM

17

First Hollow Fiber System

(2nd Prototype )

The concentration of cells utilizing hollow fibers in an

integrated system has been prototyped and run

Lessons applied to development of devices


18

Dead End HF Microfiltration

– Liquid solution passes through the HF membrane. Particles

retained on the inner HF membrane surface and module surface.

– Permeate flux decreases rapidly.

– A fouling layer build-up causes the system to plug up


19

Liquid solution passes through the HF membrane. Particles

retained on the inner HF membrane surface and module

surface.

Permeate flux decreases rapidly. A fouling layer build-up

causes the system to plug up.

Dead-End Filtration

Feed

Permeate

Fluid in the system is continuously circulated over

the filter surfaces;

Particle layer build up is reduced to a minimum

CROSS FLOW FILTRATION


Hollow Fiber Membrane CCR Process:

(3rd Prototype)


Valve

Sample

Solution

Pressure

Gauge

Pump

Hollow Fiber

Permeate

Homogenized Hot Dog Experiment:

Permeate Volume Retentate Volume0

50

100

150

200

250

0 50 100 150 200 250Time (min)

Vo

lum

e (

ml)

21

Hollow Fiber Membrane CCR Process:

(4th Prototype)


Second pump passes liquid through the permeate side

of the membrane in order to achieve a constant

pressure gradient and increase transmembrane flux.

Key Components

Fiber module 0.2 µm hollow fiber

11 inch,

Polysulfone

Pressure

Transmitter

60 PSI max

2 Peristaltic Pumps Rainin Rabbit Plus

Flow Meter 0-50 mL/min

Software Labview 2009f3

22

CCR Box Front Panel Display


23

Monoflow


STEP Membranes Time for

Filtration

Volume

Applied

Volume

Recovered

Chicken*

Extract +

3 X 104

cfu/mL

S. enteritidis

1

Glass

Microfiber

Filters

(2.7m)

1 min 200 mL ~ 200 mL

Chicken

Extract

3 X104 cfu/mL

S. enteritidis

2 Hollow fiber

(CCR)

(0.2 m)

60 min ~200 mL ~ 2.5 mL

2 X106

cfu/mL

S. Enteritidis

24

*100 g of chicken legs was mixed with 500 mL water in a stomach bag. The chicken

legs in water were finger massaged for 2 min, few times, and then incubated at room

for 2.5 h. The liquid was collected for further work.

Testing 4TH Prototype



25

Membrane Fouling:

Minimized, but still an issue

Monoflow

Maximum

Sustainable

Pressure



26

1st to 3rd Quartile Process Control

Monoflow



27

Dual Flow



28

Dual Flow



29

Flow rate

WORK IN PROGRESS


1- Optimization of Pre- and Pos- Filtration Steps:

Membrane fouling : fats, oil, proteins

major obstacle hindering wide membrane applications

30

Reduces Permeate flux;

Shortens the membrane life;

Increases the maintenance cost;

Eventually add capital cost for replacement

Extension of membrane life time

(Troppocolaggen

triple helix)

Unsaturated

fat triglyceride.

http://upload.wikimedia.org/wikipedia/commons/b/be/Fat_triglyceride_shorthand_formula.PNG

WORK IN PROGRESS


31

Procedures to control membrane fouling

1- Pretreatment of feed;

2- Membrane modification;

3- Changes in operating parameters;

4- Using different cleaning techniques

Kimura et al. (2004). Water Research 38: 3431-3441

Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158

Work

in

progress

PS: 2 and 3 are challenging once the membrane is installed

Work in Progress


1- Optimization of Pre- and Post-Filtration Steps;

1.1 Pre-Filtration (1 min) : Glass microfiber (2.7 m)

No loss of cells

Addition of one step using glass microfiber filter (1.6 m)

32

Work in Progress


1.2 Post-Filtration Steps

Macro cleaners (Ex: NaOH)

Efficiency may be dependent on the transmembrane

pressure;

Micro cleaners

Enzymes (Lipases, Proteases) + Surfactants (Ex:Tweens)

Literature: Enzyme used in combination with NaOH and

citric acid = 90% removal of foulant in cross flow humic

acid-fed ultrafiltration (Hollow fiber module –polysulfone

membrane)Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158

33

Work in Progress


2- Additional tests to confirm cleaning and sanitization

of membranes for re-using;

Exhaustive tests under progress to test efficiency of

70% (v/v) ethanol;

Alternatively 10% bleach may also to be tested for

comparison.

34

Work in Progress


Testing 5th Prototype:

New feature: smaller pumps were added to the instrument

35

Reduction of Dead Volume by 5 TIMES observed in

initial tests with cells in buffer: from 2.5 mL

(Prototype #4) to 0.5 mL

Translates to 5 Increase in Cell Concentration (500

times total cell concentration: from ~ 1x104 cells to ~

5x106 cells

Work in Progress


Further Optimization Work in Progress:

Addition and test of small diaphragm pumps;

Addition and test of level and turbidity sensors;

Modeling studies (for instance pressure and flow rate);

Optimization of pre-filtration and cleaning steps

36

Applications


Identification by Different

Methods

Concentrate Cells (Salmonella

sp, Listeria sp, E.coli sp)

Against a Background of

Microorganisms

Multifluidic

DetectionAntibody PCR

Bacteriophage

Reporter

Ramon

Spectroscopy

Light

Scattering

37

Microfliudic Biochip


Dielectrophoresis (DEP) = concentration

of bacteria

Immobilization of Antibody = specificity

to capture target

pathogen

Results in

selective capture

of target pathogen

from background flora

38

Schematic of the

micro-fluidic biochip

used for capture of

bacteria using DEP

(Yang, et al. 2006)

Flat silicon substrate

16μm tall micro channel

PDMS cover

Interdigitated electrodes

•.

0

0.5

1

1.5

2

2.5

3S

. K

entu

cky

S. H

avana

S. A

natu

m

S. M

bandaka

S. S

eftenberg

S. Litchfield

S. T

hom

asville

S. B

randenburg

S. P

oona

S. A

gona

S. G

allinaru

m

S. R

ubis

law

S. P

ullo

rum

S. M

aars

een

S. A

rizonae

S. E

nte

ritidis

PT

46

S. C

hole

rasuis

S. In

dia

na

S. E

nte

ritidis

PT

21

E. coli

K12

S. S

chottm

uelle

ri

S. S

eftenburg

E. coli

0157:H

7 S

CA

13753

S. T

yphim

urium

var.

S. T

ennessee

S. T

yphi

S. H

eild

eburg

GF

P E

. coli

A4

50

nm

3238 Average AntiSE Average

0

0.5

1

1.5

2

2.5

3

3.5

4

B. ce

reu

s

C. p

erf

rin

ge

ns

S. T

yp

him

uri

um

PT

NO

S-1

S. T

yp

him

uri

um

PT

NO

S-3

S. S

tan

ley

S. S

ch

wa

rze

ng

run

d

S. B

ert

a

S. T

ho

mp

so

n

S. S

efte

nb

urg

L.r

ha

mn

osu

s

A490 n

m

3238 AntiSE

(a) (b)

ELISA Testing of Anti-Salmonella Antibodies


ELISA with AntiSE and 3238 (in house polyclonal) antibodies with various

microorganisms. Values are the average of three replicates of live cells

and presented with standard deviations 39

* AntiSE shows less cross

reactivity with other related

Enterobacteriaceae via ELISA* 33 Salmonella serovars screened

Antibody Coated Biochips with and

without DEP


A) Biochip coated in Anti-SE

antibody without DEP.

B) Biochip coated in antibody

3238 without DEP.

C) Biochip with immobilized

3238 antibody, no DEP.

D) Enhanced capture

with application of

DEP on 3238 antibody

coated chip.

40

A B

S. Enteriditis on chips are stained with acridine orange

Specific capture of

Acridine orange

stained Sal. Enteritidis

PT-21

Current and Future Work


• Utilization of antibodies and/or ligands to

preferentially capture specific serovars of

Salmonella serovars.

• On chip and off-chip PCR confirmation of target

pathogen

• Immobilization of ligands that will facilitate the

specific capture and detection of Shiga toxin

producing Escherichia coli.

• Results obtained from biochip will be validated using

standard USDA culture based assay procedure and

multiplex PCR assay for three pathogens.

• The long term goal of this project will be to develop an

automated device for capture and detection of

multiple pathogens (Kim and Bhunia, 2008) on one

chip device and on-chip PCR

• Confirmation/identification in eight hours or less.41

42

Rashid Bashir, Yi-Shao Liu, Eric Salm

University of Illinois at Urbana-Champaign, IL.

http://libna.mntl.uiuc.edu/

Arun Bhunia, Michael Ladisch, Richard Linton

Purdue University, West Lafayette, IN.

Electronic Micro-fluidic Biochips for

Detection of Bacteria

http://www.publicaffairs.uiuc.edu/idstandards/iis.html

http://www.publicaffairs.uiuc.edu/idstandards/iis.html

Starting

Sample

Sample Prep

Concentration

Detection/

ID

Data Analysis/

Results

Overall Approach

~ 30 min ~ 1- 3 hr

Electrical Detection

of cell GrowthOn-Chip

Concentration

1000X

~ 15 - 30 min

Automated Off-Chip

Cell Concentration And

Recovery - 1000X

Sample

100 – 1000 ml

~ 1- 3 hr

Electronic

Biomolecular

identification

1 cfu/100 ml use 1000 ml 10 cfu 0.1 - 1 ml

Integrated Chips for Detection of

Microorganisms and Cells

“Lab on a Chip” with microfluidics and micro/nanosensors

Glass cover

In/Out ports Cavities/

Wells

Epoxy adhesive

Pin 70

0µ

m

Lab-on-a-chip for Detection of Live

Bacteria

Nanopore Sensors for DNA

Detection

Dielectrophoresis

Filters an Traps for

Biological Entities

Micro-Mechanical Cantilevers for

Detection of Spores

Trapping/Lysing of Bacteria/Viruses In Microfluidic Devices

Nano-Mechanical Cantilever Sensors for Detection of Viruses

Silicon Nanowires and Nanoplates for DNA

and Protein Detection

Genomic

Detection

On-Chip PCR

(optical/

electrical)

Cell Lysing

Temp/

Chem.-mediated

Micro-scaleImpedance

Meas.

Culture/Growth

Detection

Conc.Sorting

On-chipDielectro-

phoresis

SelectiveCapture

Ab-based

Capture

MEMS

Filters

Filters

h

Bacterial Growth & Impedance Microbiology !

Invented in late 1800s (Petri and Koch)

Still the most widespread means to grow

and detect the presence of bacteria !

# o

f b

acte

ria

Time

Lag phase

Stationary phase

Gro

wth

ph

ase

Energy Metabolism

SugarsOxygen

Na+ATP

OtherProcesses

CO2

Carbonic Acid

H2O

Ion

Channels Lactic Acid

Acetic Acid

Cell

K+

Na+Z

Owicki et al., Biosens.

Bioelectron. (1992)

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

1.E+07

0 1 2 3 4 5 6 7 8 9

Detection time in hours

Init

ial c

ell p

op

ula

tio

n (

C0) [

CF

U/m

l]

Low number of bacteria

in large volume takes

long time to detect

Low number of bacteria in

very small volume (in

biochip!) can be detected

much faster

-

Detection Time (arbit. units)

46

Gomez, et al., Sensors and Actuators B, 2002; Gomez, et al., IEEE/ASME JMEMS, 2005

Impedance Microbiology on a Chip

• A large cell concentration by confining a few bacteria in a small volume 107

cfu/ml = 10 cfu/nl

• On-chip miniaturization Short detection time

• Electrical detection (Impedance Microbiology) Automation

PC board

w. heater

Micro -

fluidic

Tubes

Edge Connector BioChip

A Petri Dish-on-a-Chip

100µm

Measurement

electrodes

DEP capture

electrodes

Outlet Inlet

330µm

100µm

Measurement

electrodes

DEP capture

electrodes

Outlet Inlet

330µm

• Dielectrophoresis-based concentration system collects particles from a large flow stream and diverts them to a smaller stream

Gomez, et al. IEEE/ASME JMEMS, 2005

Yang, et al. Lab Chip, 2007

Koo, et al, Analytical Chemistry, 2009

Bacterial Cell Concentration on-Chip

Lee, et al.

Analytical

Chemistry, 2009

Park, et al. Lab

Chip, 2009

102

103

104

105

106

103

104

105

106

Ma

gnitu

de [

]

Fits to incubation of L. innocua (~3x107 ml-1) in TA4-B6

Ch. 2. Well WB2. 39C.

102

103

104

105

106

-60

-50

-40

-30

-20

-10

Frequency [Hz]

An

gle

[D

egre

es]

Meas. (2) 10/16/02. Fit (8) 10/24/02

Time

On-Chip Incubation of L. innocua in LB BrothInitial concentration: ~3x107 cfu/ml

Measured Impedance

Fitted circuit model

Time

On-Chip Incubation of L. monocytogenes

95%

100%

105%

110%

115%

120%

125%

130%

0 2 4 6 8 10 12 14 16 18 20

Time [hours]

Rela

tive C

onducta

nce

1 cfu

9 cfu

34 cfu

Approximate number of

colony-forming-units (cfu)

in a 5.27nl volume:Growth

Growth

Growth

ZwZw ZwZw

Cdi

Rs

Dielectric capacitance

Electrolyte

resistance

Electrode-electrolyte interfaces

Electrode-

Electrolyte

Interface Model:

Constant-angle

impedance

BjZ

nw)(

1

49

In-process Rapid Detection & Identification of Live CellsBioVitesse, Inc.

• „Petri dish on a chip‟ to miniaturize impedance microbiology

• To quickly and reliably detect and identify live bacteria in 2 to 4 hours, instead of 2 to 10 days

• Provides in-process quality control monitoring systems

• To the industrial microbiological market (Bio/Pharma and Food Safety)

Goal – Become the leader in rapid detection and identification of live cells

BioVitesse, Inc. Company Confidential

Silicon

BiochipChip Cartridge

CCRTM

Cartridge

Automated System

Sample, Media,

Sanitizing Fluid

Towards Label Free Electrical Detection of

PCR Products

• Polymerase Chain Reaction

– Target molecule doubles every cycle

Cycle # # of Molecules Conc. (#/n)

1 2

2 4

3 8

4 16

5 32

10 1024 (103) 103 #/nl

20 1048576 (106) 106 #/nl

30 1073741824 (109) 109 #/nl

40 1099511627776 (1012) 1012 #/nl

• What is the minimum concentration of dsDNA molecules (e.g. 500bp) that can be directly detected in solution using impedance measurements ???

Z

Electrical Nature of DNA Molecules

Baker-Javis et al., 1998Baker-Javis et al., 1998

Cap.=d

Ak eCap.=

d

DNA polarization (dipole effect)

Dielectric relaxation (Debye relaxation) :

eee

j+

D+

1

with L(or #)

Cap. Z

Counter Ion movement: ZRsol

DNA polarization (dipole effect)

Dielectric relaxation (Debye relaxation) :

eee

j+

D+

1

with L(or #)

Cap. Z

Counter Ion movement: ZRsol

Thymine

DNA prepared by QIAquick Gel Extraction Kit, QIAGEN,

Valencia, CA

Bulk-EIS for Label free DNA detection

e increases with # or L, C increases, Z decreases

Detection limit in DI Water for 500bp DNA = 1e9 #/l (1.33 nM)

Liu, et al. Applied Physics Letters, 2008.

Frequency (Hz)

Z (

oh

m)

102 103 104 105

103

104

105

1011#/µl

1010#/µl

109#/µl

108#/µl; + DI Control

500 bp dsDNA

Z (

oh

m)

102

103

104

105

Frequency (Hz)103 104 105

1000 bp

500 bp

100 bp

DI Control

109 #/µl dsDNA

1.00E+01

1.00E+02

1.00E+03

DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE

1e8 molecules/ul

1e9 molecuels/ul

1e10 molecules/ul

% C

han

ge o

f C

di

Background solutions

DNA con

centration

1.00E+01

1.00E+02

1.00E+03

DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE

1e8 molecules/ul

1e9 molecuels/ul

1e10 molecules/ul

% C

han

ge o

f C

di

1.00E+01

1.00E+02

1.00E+03

DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE

1e8 molecules/ul

1e9 molecuels/ul

1e10 molecules/ul

% C

han

ge o

f C

di

Background solutions

DNA con

centration

Label free detection of DNA molecules suspended in diluted TE buffers and de-ionized

water. The detection limit (defined as 20% change in Cdi) for a 508bp long dsDNA

molecule, was found to be about 109 molecule/µl in 0.1TE buffer and 1010 molecule/µl in

0.5 TE buffer and above.

-3.00E+01

-2.00E+01

-1.00E+01

0.00E+00

1.00E+01

2.00E+01

3.00E+01

4.00E+01

5.00E+01

6.00E+01

0 5 10 15 20 25 30

1 µg

0.1 µg

0.01 µg

PCR cycles

% C

han

ge

of

Cd

i

control

-3.00E+01

-2.00E+01

-1.00E+01

0.00E+00

1.00E+01

2.00E+01

3.00E+01

4.00E+01

5.00E+01

6.00E+01

0 5 10 15 20 25 30

1 µg

0.1 µg

0.01 µg

PCR cycles

% C

han

ge

of

Cd

i

control

Label free DNA detection in PCR Reagents

sample (PCR mix plus DNA template)

control (PCR mix only)

prfA 508 bp segment target for specific detection of Listeria monocytogenes

5‟CGGGATAAAACCAAAACAATTT3‟ and R-5‟TGAGCTATGTGCGATGCCACTT3‟

Liu, et al. IEEE Sensors Conference,

2008

Liu, et al. Submitted, 2010

Label free DNA detection in PCR Solution

1 g starting concentration (3e8 cells / 25ul)

55Silicon substrate

Glass cover

Metal 1 (impedance)

Metal 1

(wire bonds)

BioVitesse Silicon Chip Cartridge and

DNA Measurements

Volume ~

60nl

100 bp dsDNA BioVitesse 60nl Chip Sensitivity

1E+05

1E+06

1E+07

1E+08

0.1 1 10 100 1000 10000

Frequency (Hz)

Ma

gn

itu

de

(o

hm

s)

-180

-160

-140

-120

-100

-80

-60

-40

-20

0

Ph

as

e (

de

gre

es

)

3.2e8

1.0e9

3.2e9

1.0e10

3.2e10

1.0e11

Increasing

Concentration

Increasing

Concentration

1.5e11

DI Reference

100bp dsDNA BioVitesse 60nl Chip Sensitivity

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1.4E+06

1.6E+06

1E+08 1E+09 1E+10 1E+11 1E+12

DNA Concentration (molecules/ul)

Ma

gn

itu

de

(o

hm

s)

-80

-70

-60

-50

-40

-30

-20

-10

0

Ph

as

e (

de

gre

es

)

|Z| @ 1kHz

θ @ 100Hz

DI Water Reference

Electrical Measurements

of 100bp dsDNA in solution

Detection Limit

~ 1e10 molecules/ul

500 bp dsDNA BioVitesse 60nl Chip Sensitivity

1E+05

1E+06

1E+07

1E+08

0.1 1 10 100 1000 10000

Frequency (Hz)

Ma

gn

itu

de

(o

hm

s)

-180

-160

-140

-120

-100

-80

-60

-40

-20

0

Ph

as

e (

de

gre

es

)

3.2e8

1.0e9

3.2e9

1.0e10

3.2e10

1.0e11

Increasing

Concentration

Increasing

Concentration

DI Reference

500bp dsDNA BioVitesse 60nl Chip Sensitivity

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

1.0E+06

1.2E+06

1E+08 1E+09 1E+10 1E+11

DNA Concentration (molecules/ul)

Ma

gn

itu

de

(o

hm

s)

-80

-70

-60

-50

-40

-30

-20

-10

0

Ph

as

e (

de

gre

es

)

|Z| @ 1kHz

θ @ 100Hz

DI Water Reference

Electrical Measurements

of 500bp dsDNA in solution

Detection Limit

~ 5e9 molecules/ul

PCR Amplification in Static Droplets

• Static droplets of PBS in oil

• Cell concentration: 106 ~ 107 cells/ml

• Droplet size100um diameter ~ 5-10 cells

• Primer conc.: 1 µM each of forward and reverse primer

• Target gene: Listeria monocytogenes prfA gene (508 bp)

Before PCR

cycling

A cluster of bacteria

Inside the droplet

100 µm

After 30 cycles, 15 sec

per thermal cycling step, total 1 hr.

-150

-100

-50

0

50

100

150

200

0 cycle 10 cycle 20 cycle 25 cycle 30 cycle 30 cycle 2

% C

ha

ng

e C

di

ch1

ch2

With primer

and template

Without primer

with template

• Electrodes on chip – droplets in Ionic Liquid

• Cell concentration: 106 ~ 107 cells/ml

• Droplet size100um diameter ~ 5-10 cells

• Bulk impedance measurements

Generation of Droplets in Viscous Fluids

Weber Number (We)

Parameterize droplet breakup processes when inertia and

capillary pressure are more important than viscous stresses. tensionsurface

diameterdroplet

velocity

fluid theofdensity

2

l

lWe

Capillary Number (Ca)

More important than Weber Number for characterizing

droplet formation in microfluidic device.

waterand oil ebetween th tension linterfacia

rate flow total theofvelocity

phase oil theofviscosity

Ca

100 m30 m 20 m

Metal electrodes0

10

20

30

40

50

60

70

0 2 4 6 8 10

Size

an

d g

ap

(m

icro

n)

Flow rate ratio (PBS:[BMIM][PF6])

PBS (0.2 - 0.025 ul/min) vs [BMIM][PF6] (0.2 ul/min)

diameter

gap

PBS bufferor liquid with cells

Ionic Liquid

100 m

50 m

20 m

Droplets

Simulation of droplet formation using Lattice

Boltzmann Method (LBM)

Figure4:

Ca=1.3e-2, Q1/Q2=5:1

Ca=1.1e-2, Q1/Q2=5:1

Ca=8.0e-3, Q1/Q2=6.25:1

Effect of Capillary number on droplet

formation in a microchannelComparison between numerical and

experimental results (Ca= 0.15)

Experimental result (Dr. Bashir's group, UIUC )

Numerical result from LBM simulation

Single droplet:

experiment - simulation

Fan (OSU), Soorykumar (OSU), Bashir (UIUC)

Ca=6.5e-3, Q1/Q2=5:1Ca=6.5e-3, Q1/Q2=5:1

0s

0.1s

0.2s

0.3s

0.4s

Droplet encapsulation of cells via lattice

Boltzmann simulation of two-phase flow

Fan (OSU), Soorykumar (OSU), Bashir (UIUC)

Ionic Liquids (ILs)

Composed entirely of ions, but liquid at low temperature (<100℃).

No effective vapor pressure, Non-flammable, High

ionic conductivity

Wide liquid range up to 300℃, Thermally stable up to

200 ℃

Ability to dissolve a wide range of inorganic,

organometallic compounds, Ability to capture small

molecules (H2, CO, CO2, and O2)

Immiscibility with some organic solvents, e.g. alkanes

Highly polar yet non-coordinating

Polarity and hydrophilicity/lipophilicity can be easily

tailored

Physical & Chemical Properties

N

N

R1

R2

X

NNR1 R3

R2

R5 R4

N

R4

R5R3

R2

R1

R6

R4

NR3

R1R2

R4

PR3

R1R2

Common cations Common anions

Cl-/AlCl3

Cl-, Br-, I-

[NO3]-, [SO4]2

-

[BF4]-

[PF6]-

[(CF3SO2)2N]-

Immidazolium-based ILs

Miscibility

with H2OM.P. (℃)

Density

(gcm-3)

Viscosity

(cP) (25℃)

Conductivty

(S/m)

[emim][PF6] ○ 60 -

[bmim][PF6] × -61 1.37 272.1 0.146

[hmim][PF6] × -73.5 1.30 497 0.110

Selected Properties of ILs

R1 = butyl, R2 = methyl, X = PF6

: [bmim]PF6

50 m

20 m

20 m

Ionic

Liquid,

0.6 l/min

PBS buffer, 0.04 l/min

100 m

10 m wide

electrodes with 10 m space

Height = 27.5 m

Ionic Liquid, 0.01 l/min

Ionic Liquid, 0.01 l/min

• Ionic liquid: [BMIM][PF6]

• PBS buffer solution: 0 (DI), 0.3x,

0.6x, 1.0x, 1.5x, pH 7.4

• Measurement and data acquisition:

dual lock-in amplifier equipped with

pre-signal amplifier, 100 kHz, 1 V,

sampling 57.2 kHz

• Post acquisition treatment: software

filtering and peak analysis by

Clampfit

Electrical Measurements of Droplets in Flow

2826Time (ms)

Sig

na

l 0

0

(mV

)

-3e-4

-2e-4

-1e-4

0

43

DI Droplets in Ionic Liquid

High Impedance

807570Time (ms)

Sig

na

l 0

0

(mV

)

0

0.01

43PBS Droplets in Ionic Liquid

High Impedance

R1

Oil or Ionic Liquid

PDMS

PBS

Electrodes

Si

R1 R1R1

R2

PBS Droplets in Mineral Oil

No Signal

Conclusions

• Electrical detection of bacterial growth

– 1 cfu/ml in 100ml

• Electrical detection of DNA molecules and

PCR

– Detection concentration of about 1e7cells/nl

– 10-100 cells in nanoliter droplets – after 30

cycles 1e9 molecules

Electrical Petri Dish

PCR a an Electrical Point of Care Test

64

5-10ul volumes

10-100nl volumes

10-100pl volumes

65

Acknowledgements

Researchers:

• Dr. Woo-Jin Chang

• Dr. Larry Millet

• Dr. Kidong Park

• Dr. Pinar Zorlutuna

• Piyush Bajaj

• Vincent Chan

• Greg Damhorst

• Brian Dorvel

• Bobby Reddy

• Murali Venkatesan

• Nick Watkins

Faculty Collaborators

– Prof. A. Alam (ECE, Purdue)

– Prof. D. Bergstrom (Med Chem, Purdue)

– Prof. A. Bhunia (Food Science, Purdue)

– Prof. S. Claire (IU-SOM)

– Prof. M. Ladisch (Ag& Bio Engr, Purdue)

– Prof. W. P. King (MechSE, UIUC)

– Prof. M. Toner (Harvard Med School)

– Prof. L. P. Lee (UC Berkeley)

– Prof. J. Lee (Ohio State University)

– Prof. W. Rodriguez (Harvard Med School)

– Prof. T. Saif (MechSE, UIUC)

– Prof. L. Schook (Animal Sciences, UIUC)

– Prof. S. Solin, (Physics, WashU)

– Dr. G. Vasmatzis (Mayo Clinic)

– Prof. S. Wickline (Wash U)

Funding Agencies

• Army TATRC

• Intel

• NIH NCI, NIBIB

• National Science Foundation

• NIH SCCNE, Wash U (Wickline, PI)

• NSF NSEC @ OSU (J. Lee, PI)

• USDA ARS, Center for Food Safety Engineering at

Purdue (Linton, PI)

http://www.nsf.gov/index.jsp

http://www.intel.com/index.htm?iid=homepage+hdr_logo

http://www.tatrc.org/index.html

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