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USING SURFACE PLASMON RESONANCE IMAGING (SPRi)
TO STUDY BIOFILMS AND BIOFOULING
A Dissertation Presented
By
Pegah Naghshriz Abadian
to
The Department of Chemical Engineering
in partial fulfillment of the requirements
For the degree of
Doctor of Philosophy
In the field of
Chemical Engineering
Northeastern University
Boston, Massachusetts
March 2, 2016
i
In loving memory of my grandmother, Zari Najati (1943–2015).
ii
ACKNOWLEDMENT
I would like to express my special appreciation and thanks to my advisor, Professor
Edgar D. Goluch. Thank you Prof. Goluch for providing me guidance, and expertise
whenever I needed, for supporting me very patiently during the last five years. I am really
grateful that you gave me the freedom to work on the area I was more interested in and for
encouraging me in collaborative works. Most importantly for being a person who I would
first count on when I needed support. Your patience, flexibility, genuine caring and
concern made my PhD experience a great one.
I would like to extend my thanks to Professor Thomas Webster, Professor Eno
Ebong of the Chemical Engineering Department and Professor Yunrong of the Biology
Department for being on my dissertation committee. I gratefully acknowledge the members
of my Ph.D. committee for their time and valuable feedback on preliminary versions of
this thesis.
I would like to thank my labmates, with whom I shared a lot of moments, Dr.
Thaddaeus Webster, Nil Tandogan, Hunter Sismaet, and Martin Kimani. Thank you for
making this journey very memorable and enjoyable. A good support system is important
to surviving and staying sane in graduate school and I am proud to call you my friends.
This dissertation would not have been possible without the help of the numerous
undergraduate students, high school students and teachers with whom I had the pleasure
of interacting with during my time in the Goluch Group. While there are many I would like
to highlight Catherine Reiter, John Jamieson, and Chase Kelley for helping me in the
experiments with great enthusiasm.
iii
Thanks to William Fowle of the Biology Department for training me on the proper
protocols of biological sample preparation and helping me grow to be so skilled in the use
of his Scanning Electron Microscope.
I also thank Robert Eagan of the Chemical Engineering Department for helping me
make all of the complicated pieces that I used in this work, and for being very responsive
and enthusiastic in his support.
Last, but certainly not least, I must acknowledge with tremendous and deep thanks
my family, especially my Mom, Shamila. Thank you for guiding me to choose the right
priorities in life and always providing me the best support in all steps of my life. Thank
you for listening to all my stories at 2 am in the morning hundreds of miles away. For
motivating me all the time when I was doubtful about the path I chose. For making me stay
positive in the hardest time. For being an amazing Mother.
iv
ABSTRACT
Surface Plasmon Resonance imaging (SPRi) is a label-free detection method with
the capability of real-time detection of multiple interactions occurring simultaneously on a
gold surface. In this work, SPRi was used for the first time to study bacterial
adhesion/growth, biofilm formation/disassembly, and cleaning of biofouled surfaces.
These processes are important to study because biofilms are reservoirs of bacteria and a
source of endotoxins, which both can enter the circulation system of a patient and cause
systemic disorders. More than 60% of hospital-acquired infections are caused by bacterial
biofilms. Formation of biofilms is the main cause of many bacterial infections.
SPR detection is based on changes in the refractive index at the sensing surface
caused by changes in the composition of the material directly above (~200 nm) the sensor
surface. Unlike in traditional SPR where a single point on a surface is measured, SPR
imaging allows the rapid collection of information about refractive index changes and the
location of these events with high precision (~10 µm) over a large area (~1 cm2)
simultaneously.
Using a SPRi system, physiological behavior of bacterial cells and biofilm
dynamics was monitored in real-time. This information were used to help predict and
control bacteria activity in fluidic systems. Studies were conducted to determine the
effectiveness of different chemicals and antibiotics in removing biofilm from a sensor
surface. The efficacy of antibiotics and surface coatings for preventing biofilm formation
on the surface were also studied. Finally, the effects of fluid dynamics on bacterial suface
adhesion and removal was investigated.
v
Staphyloccocus aureus, a gram positive bacteria and one of the major causes of
hospital aquired infections, Pseudomonas aeruginosa, a gram negative species and model
organism for biofilm studies, Eschericia coli, a gram negative and a model prokaryotic
organism, and Bacillus cereus a gram positive and facultative anerobic bacteria, were used
in this study.
vi
TABLE OF CONTENTS
LIST OF FIGURES…………………………………………………………………….……….ix
1.0 INTRODUCTION……………………………………………………………………....1
2.0 CRITICAL LITERATURE REVIEW……………………………………....………...3
2.1. Technology ……………………………………………………………………………….3
2.1.1. Surface Plasmon Resonance (SPR) Sensors………………...…………………....3
2.1.1.1. SPR phenomena……………………..…………………………………..………..3
2.1.1.2. SPR condition…………………………………………………………………….7
2.1.1.3. SPR sensing method……………………………………………………………..10
2.1.2. Surface Plasmon Resonance imaging (SPRi)…………………………………....13
2.2. Cell Detection with SPR sensors…………………………………………………………14
2.2.1. Bacterial Cell Detection with Surface Plasmon Resonance Imaging………..…..14
2.2.2. Mammalian Cell Detection with Surface Plasmon Resonance Imaging…………36
2.3. Biology….………………………………………………………………………….........44
2.3.1. Biofilms…………………………………………………………………………44
2.3.1.1. E. coli……………………………………………………………………………46
2.3.1.2. P. aeruginosa…………………………………………………………………....47
2.3.1.3. S. aureus…………………………………………………………………...……49
2.3.1.4. Bacillus species (Bacillus cereus)…………………………………………...….50
3.0 DISSERTATION GOALS……………………………………………………………52
4.0 EXPERIMENTAL……………………………………………………………………..54
4.1. System Setup for Monitoring Bacterial Growth and Biofilm Formation (Goal 1)………..54
4.1.1. Monitoring Changes on the Surface with SPRi…………………………………54
4.1.2. Monitoring Bacterial Growth with SPRi…………………………………...…...55
4.1.3. Monitoring Bacterial Biofilm Formation……………………………………….56
4.2. Prevention of Biofilm Formation on the Surface (Goal 2)………………………………58
4.2.1. Surface Coatings………………………………………………………………...58
4.2.2. Loading Antibiotics in Solution………………………………………………...60
4.3. Biofilm Removal from the Surface (Goal 3)…………………………………………….63
vii
4.3.1. Cleaning with Different Chemical Compounds………………………………...63
4.3.2. Disinfection with Antimicrobial Components………………………………......64
4.4. Effect of flow rate on bacterial growth (Goal 4)………………………………………...66
4.4.1. SPRi Experiments…………………………………………………………..…...66
4.4.2. COMSOL Multiphysics Modeling…………………………………………...…67
5.0 RESULTS AND DISCUSSION……………………………………………...………68
5.1. System Setup for Monitoring Bacterial Growth and Biofilm Formation (Goal 1)……...69
5.1.1. Bead Imaging……………………………………………………………………69
5.1.2. Cell Growth and Biofilm Formation……………………………………………71
5.1.2.1 E. coli growth and biofilm formation…………………………………………….71
5.1.2.2 P. aeruginosa growth and biofilm formation……………………………….…….76
5.2. Prevention of Biofilm Formation on the Surface (Goal 2)………………………………81
5.2.1. Surface Coating…………………………………………………………………81
5.2.1.1. Casein and BSA……………………...………………………………………….81
5.2.1.2. Penicillin/Streptomycin and BSA……………………………………………......89
5.2.1.3. Penicillin/Streptomycin and Casein………………………………………….....94
5.2.2. Loading Antibiotics in Solution………………………………………………...95
5.2.2.1 Control Experiment…………………………………………………………......95
5.2.2.2 Penicillin/Streptomycin (S. aureus)……………………………………...……...97
5.2.2.3 Colistin (P. aeruginosa)…………………………………………………...……..99
5.2.2.4 Spectinomycin (B. cereus)………………………………………………….…..101
5.3. Biofilm Removal from the Surface (Goal 3)…………………………………………...104
5.3.1. Cleaning with Different Chemical Compounds……………………………….104
5.3.2. Disinfection with Antimicrobial Components………………………………....108
5.4. Effects of flowrate on Bacterial Adhesion (Goal 4)……………………………………..111
5.4.1. SPRi Experiments……………………………………………………………...111
5.4.2. COMSOL Multiphysics Modeling ………………………………………....…115
6.0 Conclusions and Future work………………………………………………………..117
6.1. Goal 1: System Setup for Monitoring Bacterial Growth and Biofilm Formation……...117
viii
6.2. Goal 2: Prevention of Biofilm Formation on the Surface……………………………….118
6.3. Goal 3: Biofilm Removal from the Surface…………………………………………….120
6.4. Goal 4: Effects of flow rate on Bacterial growth………………………………………...122
7.0. METHODS…………………………………………………………………….…...…124
7.1. PDMS Fabrication……………………………………………………………………...124
7.2. Bacterial Culture Preparation………………………………………………………..…127
7.3. Bacterial Culturing……………………………………………………………………..127
7.4 Sample preparation for Scanning Electron Microscopy (SEM)………………………..129
8.0 REFERENCES……………………………………………………………………….131
ix
LIST OF FIGURES
Figure 1: Refraction of light at different incident angles…………….....................5
Figure 2: (a) Otto Configuration, (b) Kretschmann Configuration….………..…2
Figure 3: Schematics of (a) TE and (b) TM polarization of light……………….…7
Figure 4: Excitation of SPs on the thin metal film…………………………………8
Figure 5: (a) SPR wavelength configuration curve, which shows the intensity of
the reflected light versus the incident wavelength. (b) The graph is
plotted the coupling wavelength versus the refractive index of the
sample above the prism……………..…………......................................11
Figure 6: a) SPR angular configuration curve, which shows the intensity of the
reflected light versus the incident angle. (b) The graph is plotted the
coupling angle versus the refractive index of the sample above the
prism…………………………………………………….………………12
Figure 7: Difference image from the chip surface generated by the SPRi device.
The bright spots represent the sections functionalized with (S) specific
antibodies and (N) non-specific antibodies. The dark section shows the
uncoated gold surface…………………………………………………..13
Figure 8: Steps of biofilm formation…………………………………………...…44
Figure 9: Scanning Electron Microscopy image of E. coli………………………47
Figure 10: Scanning Electron Microscopy image of Pseudomonas aeruginosa.....49
Figure 11: Scanning Electron Microscopy image of Staphylococcus aureus……..50
Figure 12: Scanning Electron Microscopy image of Bacillus subtilis…………….51
Figure 13: Setup for initial Surface Plasmon Resonance imaging (SPRi)
experiments. 50 m beads in DI water placed onto a prism coated with
50 nm of gold……………………………………………………….……55
Figure 14: Setup for Surface Plasmon Resonance imaging (SPRi) experiments.
PDMS with two channels. The left channel was filled with LB growth
media and the right channel will be filled with GFP labeled E.
coli……………………………………………………………………….56
x
Figure 15: Setup for monitoring biofilm formation using Surface Plasmon
Resonance imaging (SPRi). PDMS with three channels. The left
channel was filled with trypticase soy broth, middle channel was filled
with PelA mutant P. aeruginosa PA14 and the right channel was filled
with wild type PA14….............................................................................57
Figure 16: Setup for coating experiments using SPRi. The gold surface inside the
chamber is coated with two biomolecules……………………………...60
Figure 17: Setup for studying the effect of antibiotics on prevention of biofilm
formation using SPRi………………………....………………………...62
Figure 18: Setup for studying bacterial growth under different flowrates using
SPRi……………………………………………………………………...67
Figure 19: (Right column) SPRi images of 50µm beads, (left column) stereo
microscope fluorescent images of the same beads…........……………..70
Figure 20: (Top) Schematic of the setup for E. coli SPRi experiments. A PDMS
chip containing two microchambers is reversibly sealed against the
sensor surface. (Bottom) SPR images of LB, and GFP E.coli filled
channels(a-f) Fluorescence images of the same channels (g,h)………..74
Figure 21: Difference images taken with SPRi at different time points. The arrows
are pointing to the center of the GFP labeled E. coli bacterial media
droplet, where the bacteria preferred to gather. j) A fluorescent image
of the surface of the prism surface after being removed from the SPRi
system……………………………………………………………………75
Figure 22: (Top) Schematic of the biofilm formation experiments using SPRi.
PDMS, with three channels, is reversibly sealed against a high
refractive index glass prism coated with 50 nm of gold. (Bottom)
Difference images of SPRi in after 3hours…..…………………………77
Figure 23: Images of P. aeruginosa PAO1 after being grown overnight in LB
growth media. (a-h) SPRi images after overnight growth. (i) GFP-
filtered fluorescence image of the right side of the dried biofilm on the
sensor surface. (j) SEM images of the right side of the biofilm. (k) SEM
image of the center of the chamber…….......…………………………..80
Figure 24: SPRi difference images of P. aeruginosa (CFP-PA01) growth on the
gold surface coated with BSA (left) and casein (right) after (a) 6, (b) 12,
(c) 18, and (d) 24 hours……………………....………………………….83
xi
Figure 25: SPRi difference images of S. aureus growth on the gold surface coated
with BSA (left) and casein (right) after (a) 6, (b) 12, (c) 18, and (d) 24
hours….....................................................................................................86
Figure 26: Scanning electron microscope (SEM) images of the coated and
uncoated sensor surfaces after 6 hours of exposure to flowing solutions
containing to S. aureus. (a) Low-magnification and (b), (c) high-
magnification images of the boundary between BSA and bare gold. (d)
Low magnification and (e), (f) high-magnification images of the
boundary between bare gold and casein…………………………….…88
Figure 27: SPRi difference images of P. aeruginosa (CFP-PA01) growth on the
gold surface coated with BSA (left) and penicillin/streptomycin (right)
after (a) 6, (b) 12, (c) 18, and (d) 24 hours……………..……………….91
Figure 28: SPRi difference images of S. aureus growth on the gold surface coated
with BSA (left) and penicillin/streptomycin (right) after (a) 6, (b) 12, (c)
18, and (d) 24 hours……………......……………………………………92
Figure 29: SPRi difference images of P. aeruginosa growth on the gold surface
coated with casein (left) and penicillin/streptomycin (right) after (a) 6,
(b) 12, (c) 18, and (d) 24 hours…….......………………………………...94
Figure 30: SPRi difference images of S. aureus growth on the sensor surface with
continuous LB flow over the surface after a) 35’, b) 330’, c) 635’, d)
1170’…………………………………………………………………......96
Figure 31: SPRi difference images of the surface. The left column shows the
images from S. aureus growth on the chamber without having any
antibiotic in the inlet media as a control, right column is shows the
difference images at the same time points by running
penicillin/streptomycin from the beginning of the experiment……….98
Figure 32: SPRi difference images of P. aeruginosa growth with and without
antibiotics. The left column shows the images of P. aeruginosa growth
in the chamber when running Colistin from the beginning of the
experiment, right column is shows the difference images at the same
time points without having any antibiotic added to the inlet
media.......................................................................................................100
Figure 33: SPRi difference images of B. cereus growth with and without antibiotics.
The left column shows the images of B. cereus growth in the chamber
xii
when running Spectinomysin solution from the beginning of the
experiment, right column shows the difference images at the same time
points without having any antibiotic added to the inlet
media………………………………………………………..………….102
Figure 34: Quantitative analysis showing the reflectivity changes over time as B.
cereus bacteria grow on the surface in the presence (orange line) and
absence (blue line) of Spenctinomycin antibiotic…………..………...103
Figure 35: Biomass coverage on the sensor surface at different time point. The
orange columns represent B. cereus growth on the surface in the
presence on antibiotics in the solution, the blue columns represent B.
cereus growth in the normal solution sans antibiotics……………….103
Figure 36: S. aureus growth and removal with 1%SDS from the sensor surface
during the experiment period…………………………………………105
Figure 37: P. aeruginosa growth and removal with 1%SDS from the sensor
surface during the experiment period…………………………..……106
Figure 38: B. cereus growth and removal with 1%SDS from the sensor surface
during the experiment period………………………….……………...107
Figure 39: The effect of penicillin/streptomycin on treatment of S. aureus
biofilm……………………………………………………………...…..109
Figure 40: The effect of spectinomycin on treatment of B. cereus biofilm………110
Figure 41: The average reflectivity change in the difference image at each time
point as a result of B. cereus growth under different flowrates.
Blue=stagnant condition, Orange=10µl/min, and gray=40µl/min
flowrates……………………………………………………………….112
Figure 42: SPRi difference images showing S. aureus growth under 10µl/min (left
column) and 120µl/min (right column) flowrates after (a,b) 6 hours,
(c,d) 12 hours, (e,f) 18 hours, and (g,h) 24 hours……………………..114
Figure 43: COMSOL Multiphysics modeling of the shear stress distribution on the
sensor surface. The red color indicates the highest and the blue color
represents the lowest shear stress on the surface…………………….116
Figure 44: (A) Schematic of the SPRi setup for antibiotic resistance experiments.
(B) The average brightness change in the channels filled with LB
xiii
without cells (diamonds), or 5.4E+6 cells/mL S. aureus with no
antibiotic (purple), with 1000X diluted antibiotic (blue), with 200X
diluted antibiotic (sloping lines)………………….………………...…119
Figure 45: Channel design to study biofilm formation under different flowrate
and in non-uniform structures. Bends are in a) 90 degree angle and b)
30 degree angles…………………………….....……………………….123
Figure 46: Schematic of the fabrication of a PDMS chamber. a) The hexagonal
mold made of Aluminum, b) PDMS is poured on the mold and cured
in the over, c) The cured PDMS in peeled off from the mold, d) each
mold contain 6 hexagons, which in the step are cut separately, e) one
hexagon chamber f) is placed on the gold coated prism……………...125
Figure 47: Schematic of the fabrication of PDMS channel. a) The three and two
linear channels on the silicon wafer, b) PDMS is poured on the mold
and cured in the oven. c) The cured PDMS is peeled off from the mold.
d) Each mold contains several groups of channels, which are cut and
separated. e) A PDMS piece containing two separate linear channels f)
is placed on the gold coated prism…………………….………………126
Figure 48: Staphylococcus aureus bacteria cultured on a LB agar plate….…….128
1
1.0 INTRODUCTION
There is a constant need for rapid detection of pathogenic bacteria in the areas of
food, water, and public health to ensure environmental safety, prevent illness, and
economic loss due to bacterial infection and contamination.
Based on estimates from the Centers for Disease Control and Prevention (CDC), in
the United States, foodborne pathogens cause roughly 79 million illnesses, 325000
hospitalizations, and almost 5000 deaths each year [1]. Among all foodborne pathogenic
microorganisms, bacteria are responsible for 91% of all foodborne illnesses in USA [2, 3].
Outbreaks of foodborne illnesses cost billions of dollars each year. According to the United
States Department of Agriculture (USDA) Economic Research Service (ERS), medical
costs and loss of productivity caused by five major pathogens, E. coli O157:H7, non-O157
STEC (Shiga Toxin Producing Escherichia coli), Salmonella (non-typhoidal serotypes
only), Listeria monocytogenes, and Campylobacter is $6.9 billion annually [4, 5].
In order to decrease the health risks, deaths, and reduce economic losses due to
pathogenic bacteria there is an essential need for rapid, sensitive, and selective detection
methods to sense the disease-causing bacteria in food and beverages [6]. Various
techniques have been employed for pathogenic bacteria detection [7], such as conventional
microbiological culture methods [8], Polymerase Chain Reaction (PCR) [9-16], Enzyme-
linked immunosorbent assays (ELISA) [17, 18], amperometric biosensors [19-23],
piezoelectric biosensors [23-26], potentiometric biosensors [27, 28], bioluminescence [29,
30], fluorescent labeling [31, 32], and ultrasound [33]. All of these methods have concerns,
such as long detection times, enrichment requirements, labelling steps, high costs, and
trained personnel to run them [34, 35]. Therefore, there is a need for alternative rapid, low
2
cost, and sensitive detection techniques. These needs can be fulfilled by Surface Plasmon
Resonance (SPR), which provides label-free, real-time, and quantitative detection and can
monitor interaction between biomolecules continuously [36-38].
SPR sensors are optical sensors that employ variations in surface plasmons on
surface of gold coated sensor chips as their detection principle. Surface plasmons are
sensitive to changes (due to biomolecular interactions on the surface) of the local refractive
index within approximately 200 nm of the sensor surface. The changes on the refractive
index are measured using optical signals, which are detected by the device and the results
expressed as Resonance Units (RU) versus time [39-41].
In this work, bacterial behavior such as bacterial growth and biofilm formation will
be studied in real-time with a surface plasmon resonance imaging (SPRi) instrument. SPRi
sensors allow for multiple detection areas on the sensor surface, and we will use this feature
to study the preventative effects of various coatings on biofilm formation. In addition, the
effect of various antibiotics on prohibiting biofilm formation on the sensor surface will be
investigated in real-time. This information is of great importance to both medical and
industrial applications.
3
2.0 CRITICAL LITERATURE REVIEW
2.1. Technology
In this section, Surface Plasmon Resonance techniques will be discussed, including
the working principles and different common variations of this detection method. Also,
work done by other groups on cell detection with SPR sensors will be presented.
2.1.1. Surface Plasmon Resonance (SPR) Sensors
In the past decade the use of SPR-based biosensors has increased significantly [42].
Surface Plasmon Resonance (SPR) based sensors provide highly sensitive, label-free
detection with the capability for real-time monitoring of surface phenomena at the
molecular level [36-38]. Sensors based on SPR phenomena provide promising tools for
use in biomolecular level applications. SPR techniques are used in various applications for
measuring film thickness, binding kinetics, molar concentrations, and provide a highly
sensitive tool with the potential to be used in wide range of diagnostics devices. These
sensors are commonly used for qualitative and quantitative studies of binding kinetics and
binding affinity between two biomolecules: antigen-antibody [43-49], DNA-DNA [50-54],
DNA-protein [55-59], RNA-DNA [60, 61], and carbohydrate-protein [62-65].
2.1.1.1. SPR phenomena
The SPR phenomenon begins with the formation of Surface Plasmons (SPs). SPs
are charge density oscillations of free conductive electrons. When SPs propagate at the
interface between two media with different refractive indices, they are referred to as
Surface Plasmon Polaritons (SPPs) [39-41]. SPR sensors consist of a prism made of high
4
refractive index glass coated with 50 nm of a noble metal. In SPR experiments, gold and
silver are the most commonly used metals [66, 67]. Gold is an inert and biocompatible
metal usually used for SPR-based biological studies. Silver has better sensitivity, but it has
less stability because it oxidizes readily [68].
To describe SPR phenomena, first consider the situation without having the thin
metal film, which is known as Total Internal Reflection (TIR). When light passes from a
material with higher refractive index (prism) to a material with lower refractive index (air),
based on the incident angle value, one of two conditions occur. If the angle of the incident
light is smaller than the critical angle, some portion of the energy will reflected back and
some portion will exit from the prism surface. TIR also occurs when the incident angle is
larger than the critical angle (Figure 1). In TIR, all of the incident light is reflected back
inside the prism. The critical angle occurs when the incident angle is reflected back at an
angle where the reflected light is parallel to the surface of the material. The value of the
critical angle depends on difference in the refractive index between the two media and can
be calculated from Snell’s law (Equation 1).
5
Figure 1: Refraction of light with different incident angle. When θincident<θcritical
smaller than the critical angle the light will transmit from the medium
with higher refractive index (n1) to less denser medium (n2). TIR occur at
θincident>θcritical.
Snell’s law to calculate the critical angle:
𝑛1 Sin θ1 = 𝑛2 Sin θ2 , 𝜃𝑐 = Sin−1 (𝑛2
𝑛1) (1)
Where: θ1 is the incident angle,
θ2 is the refracted angle,
n1 is the refractive indices of the denser medium
n2 is the refractive indices of the less dense medium.
Now when a thin metal film is coated on the prism surface, the SPR phenomena is
observed when an TIR light orientation is employed. In this case, while all the incident
light is reflecting back, it also generates an evanescent field. An evanescent field is an
6
inhomogeneous electromagnetic wave in which the wavelength is identical to the incident
light. The amplitude of the field decreases exponentially at the rate proportional to 1/e in
the direction perpendicular to the thin metal surface toward the dielectric and extends 200
nm above the metal surface. This evanescent wave can couple with the SPs in the thin
metal film at the metal-dielectric interface and excite them to generate SPPs.
Kretschmann and Otto are two pioneers in demonstrating optical excitation of
Surface Plasmon Polaritons. Based on their respective designs, there are two different
configurations for SPR: Kretschmann and Otto. In the Otto configuration, the thin metal
film is located close to the prism and the sample passes between the metal film and the
prism (Figure 2a) [69, 70]. The Kretschmann set up is the more commonly used
configuration in SPR experiments. In this configuration, which is used in this study as well,
the thin metal film in coated on the prism surface while the fluid passes over the metal. In
both configurations, the incident light excites the SPs by interacting with the evanescent
field within the thin metal film, resulting in SPR (figure 2b) [71-73].
Figure 2: (a) Otto Configuration, (b) Kretschmann Configuration.
7
2.1.1.2. SPR condition
SPs can only oscillate in the direction perpendicular to the metal-dielectric
interface. Therefore, the Transverse Magnetic (TM) polarized light, in which the electric
field oscillates normal to the metal film surface, can excite the SPs. The electric field of
the Transverse Electric (TE) polarization of light, which is parallel to the thin metal plane,
and subsequently parallel to the SPs, cannot excite oscillating free electrons. The schematic
of the two different polarizations of light is illustrated in Figure 3.
Figure 3: Schematics of (a) TE and (b) TM polarization of light.
As mentioned above, at SPR conditions, energy from the incident light in the form
of an evanescent wave will excite the Surface Plasmons. In order to couple the energy with
SPs, the wave vector of the SPs (Ksp) should match the wave vector of the incident light
8
(Kx) which is parallel to the metal-dielectric interface as shown in Figure 4 (Kx=Ksp). The
wave vector of the incident light is expressed by Equation 2 [74-77].
Figure 4: Excitation of SPs on the thin metal film occurs when the wave vector of the
incident light (kx) match the wave vector of the SPs (ksp).
𝑘𝑥 = 𝑘0𝑛𝑝𝑟𝑖𝑠𝑚sin θ𝑖𝑛 (2)
Where: k0=2π/λ is the free space wave vector,
nprism is the refractive index of the prism and
θin is the incident angle.
The wave vector for the SP is expressed in Equation 3.
𝑘𝑠𝑝 = Re {𝐾0√𝜀𝑚.𝜀𝑠
𝜀𝑚+𝜀𝑠} (3)
9
Where: K0=2π/λ is the free space wave vector
εm is the complex dielectric constant of the thin metal film
εs is the complex dielectric constant of the sample.
Ksp can be written as shown in Equation 4. By neglecting the imaginary part of the
dielectric constants,
𝑘𝑠𝑝 = 𝑘0√𝑛𝑚
2 .𝑛𝑠2
𝑛𝑚2 +𝑛𝑠
2 (4)
Where: K0=2π/λ is the free space wave vector
𝑛𝑚 = √𝜀𝑚 is the refractive index of thin metal film
𝑛𝑠 = √𝜀𝑠 is the refractive index of the sample
In a standard SPR experiment, if the properties of the incident light, and
consequently Kx vector, do not change, the resonance condition will depend on the optical
properties of the sample and the metal. This means any changes to the refractive index due
to attachments at the surface will change the resonance.
At the resonance condition energy from the photons of the incident light will be
transferred to the metal free electrons to excite the surface plasmons this will reduce the
intensity of the reflected light. Therefor SPR can be measured at certain wavelength or
angle of the incident light. Therefore, the resonance angle/wavelength is the
angle/wavelength at which a drop occurs in the intensity curve of the reflected light and
the reflectivity is at a minimum.
10
2.1.1.3. SPR sensing method
In all SPR experiments based on the measured property of the reflected light, three
different modulations exist:
Wavelength modulation: In wavelength modulation a white light, which includes
different wavelengths, is used. The incident angle is fixed and light with different
wavelengths enters the prism. The reflected light is gathered with a CCD camera and the
spectral properties of it are analyzed. Reflected light exhibits changes in the intensity and
at the wavelength where SPR occurs an adsorption dip in the reflectivity curve is observed.
The wavelength at which the dip in the intensity of the reflected light occurs is known as
the coupling wavelength (λsp). The SPR coupling wavelength shifts when the refractive
index of the sample changes. Figure 5a shows the reflectivity versus wavelength curve and
represents the SPR coupling curve and Figure 5b shows the shift due to variation of the
sample refractive index [78].
11
Figure 5: (a) SPR wavelength configuration curve, which shows the intensity of the
reflected light versus the incident wavelength, in which the minimum
intensity occurs at the coupling wavelength (λspr). (b) The graph is
plottedshows the coupling wavelength versus the refractive index of the
sample above the prism.
Angular modulation: In this modulation, a monochromatic light source is used and
the intensity of the reflected light is measured at a range of incident angles. At the SPR
condition, a dip in the intensity of the reflected light will be observed. This angle is known
as resonance angle (θr). The same way as with the coupling wavelength, when the refractive
0
0.5
1
500 600 700 800 900
No
rm.
Ref
lect
ion I
nte
nsi
ty
Wavelength (nm)
655
660
665
670
675
1.333 1.334 1.335 1.336
Coupli
ng W
avel
ength
(nm
)
Reflection Index
(a)
(b)
12
index of the media on the metal thin film varies a shift in the θr will be observed. Figure 6
illustrates the angle of resonance and its shift due to changes in the refractive index of the
sample.
Figure 6: (a) SPR angular configuration curve, which shows the intensity of the
reflected light versus the incident angle. The angle at which the minimum
intensity occurs is called the coupling angle (θspr). (b) The graph shows the
relationship between the coupling angle and the refractive index of the
sample above the prism.
Intensity Modulation: In the intensity modulation, monochromatic light is used as
a light source at a fixed incident angle. The intensity of the reflected light is measured by
the device as the refractive index of the dielectric material changes the resonance condition
0
0.5
1
50 52 54 56 58 60
Norm
.Ref
lect
ion
In
ten
sity
Angle (deg)
55.4
55.5
55.6
55.7
1.333 1.334 1.335 1.336
Coupli
ng A
ngle
(D
eg)
Refractive Index
(a)
(b)
13
and consequently the amount that intensity of the reflected light varies depends on the new
refractive index [78].
2.1.2. Surface Plasmon Resonance imaging (SPRi)
In a traditional SPR system, the average intensity of the reflected light from the
entire surface is measured and the results show the average refractive index variation of
the sample on the entire surface. In SPR imaging, the intensity of the reflected light is
analyzed at each position on the sensing surface. The output of this sensor is a grey scale
image, which is called a difference image and represents the refractive index change of the
dielectric media above the metal film pixel by pixel. The pixel size determines the
resolution of the device, which is 7 µm2 in our device.
In SPRi sensors, multiple areas on the surface can be monitored simultaneously. In
this sensor, if the surface is functionalized with various ligands, the binding kinetics of
different analytes can be monitored at the same time (Figure 7).
Figure 7: Difference image from the chip surface generated by the SPRi device. The
bright spots represent the sections functionalized with (S) specific
antibodies and (N) non-specific antibodies. The dark section shows the
uncoated gold surface.
14
2.2. Cell Detection with SPR sensors
This section presents a review of investigations where SPR is used to study
bacterial cells. The information is partly adapted from “Cellular Analysis and Detection
Using Surface Plasmon Resonance Techniques” in Analytical Chemistry journal, volume
86, 2014 [79]. The results are presented with permission from Analytical Chemistry
journal. It will be useful in learning about different problems that need to be studied and
how people use SPR detection to approach the problem and get the best results. Different
techniques for modification of sensor surfaces for various cell detection and the results that
different research groups attained are discussed.
2.2.1. Bacterial Cell Detection with Surface Plasmon Resonance Imaging
While SPR can provide significant new fundamental insights about bacteria, thus
far research efforts have justifiably explored sensing applications. In order to decrease
health risks, deaths, and reduce economic losses due to pathogenic bacteria there is a
critical need for rapid, sensitive and selective detection methods to sense the disease-
causing organisms in food and beverages [80].
Among all microorganisms, bacteria cause 91% of all foodborne illnesses n USA
[81, 82]. Based on the estimates from the Centers for Disease Control and Prevention
(CDC), in the United States foodborne pathogens cause roughly 79 million illnesses,
325,000 hospitalizations, and nearly 5000 deaths each year [83]. In addition, outbreaks of
foodborne illnesses result in economic losses totaling several billions of dollars annually.
According to the United States Department of Agriculture (USDA) Economic Research
Service (ERS), medical costs and loss of productivity caused by five major pathogens,
Escherichia coli O157:H7, non-O157 STEC (Shiga Toxin Producing E. coli), Salmonella
15
(non-typhoidal serotypes only), Listeria monocytogenes, and Campylobacter is $6.9 billion
annually [84, 85]. Various detection techniques have been employed for pathogenic
bacterial detection applications [86], such as conventional microbiological culture method
[87], polymerase chain reaction (PCR) [9, 88-94], enzyme-linked immunosorbent assays
(ELISA) [95, 96], amperometric biosensors [97-101], piezoelectric biosensors [101-104],
potentiometric biosensors [105, 106], bioluminescence [107, 108], fluorescent labeling
[109, 110], and ultrasound [111]. All of these methods have concerns such as long
detection time, enrichment requirements, labeling necessity, requirements of trained
personnel, and high cost [35, 112]. Therefore, there is a need for alternative rapid, low cost,
and sensitive detection in complex samples. These needs can be fulfilled by Surface
Plasmon Resonance (SPR), which provides label-free, real-time, and quantitative detection
[36, 113, 114].
In the study done by Choi, et al. [115] SPR device was used for monitoring
environmental pollutants, such as phenol. The surface was functionalized with a self-
assembled synthetic oligopeptide. The self-assembly technique provides reliable control
over packing density of ligands on the surface. In this self-assembled synthesis,
oligopeptide sequences, including modified Arg-Gly-Asp (RGD), were immobilized on
the gold surface. The upper part of modified peptide (RGD) was utilized for
immobilization of cells on the surface. RGD is believed to influence positively target cell
immobilization on the surface. Two different designs of peptides were used for the
immobilization of cells, one is a single stranded oligopeptide (C-(RGD)4) and the other is
a poly-oligopeptide network grafted with four branches of (C-(RGD)4). The angle shift in
SPR was monitored in each step during surface functionalization. The resonance angle for
16
bare gold surface was detected with the instrument. Adsorption of single stranded
oligopeptide (C-(RGD)4) causes a shift in the resonance angle. Then the resonance angle
shifts significantly after immobilization of E. coli O157:H7 on the surface. This shift of
the resonance angle after immobilization of E. coli O157:H7 is higher for surfaces
primarily functionalized with grafted C-(RGD)4 than with C-(RGD)4.
The researchers combined Atomic Force Microscopy (AFM) with SPR to study
surface topography as well as biological interactions on the surface. The AFM results from
the surface before and after oligopeptide immobilization confirm the successful
immobilization step.
The concentration of immobilized bacteria (E. coli O157:H7) plays a significant
role in toxicity detection because a higher amount of immobilized bacteria creates more
sensing elements on the surface, which leads to a larger shift in resonance angle and
determines the limit of detection for the sensor. A greater shift in the resonance angle
occurs with higher concentrations of synthetic oligopeptide on the sensor surface,
indicating that a higher number of bacterial cells are immobilized. The results show the
highest bacterial cell immobilization for the surface functionalized with grafted C-(RGD)4.
The live cells keep their physical integrity, including their cellular membranes,
which help them bind to each other and to the surface modified with oligopeptides. As
soon as the cells die due to any toxicity, they lose physical integrity, which causes the
intracellular material to decrease and results in angular shifts in the plasmon curve. The
researchers used this phenomenon to detect the presence of toxic chemicals with SPR.
Different concentrations of phenol were injected to the modified surface and the angular
17
shift in the plasmon curve was obtained for each concentration. The smallest detectable
shift occurred for 5 ppm of phenol, which determined the limit of detection for this sensor.
Arya, et al. [116] used SPR as a transduction technique to detect a specific strain
of Escherichia coli bacteria, E. coli K12. T4 bactriophages, as specific receptors of the
bacteria, were immobilized on the gold surface using a self-assembled monolayer of
dithiobis(succinimidyl propionate) (DTSP).
All steps of surface functionalization were monitored with SPR. It was shown that
using a higher concentration of T4 bacteriophage solution increases the phage
immobilization on the surface and subsequently results in a higher SPR response for the
same concentration of bacteria. The bioassay platform was also shown to be specific to E.
coli K12 as negligible changes in SPR signal were observed for the non-specific bacteria
strains, E. coli NP10 and NP30. A reproducibility experiment, which was done by injecting
a regeneration solution after each injection (in order to set baseline), showed a stable
platform for different experiments on the same chip. This SPR-based platform was able to
detect K12 bacteria concentrations in the range of 7x102 to 7x108 CFU/mL.
Taylor, et al. [7] used SPR to detect E. coli O157:H7 that were processed in three
different ways: untreated, heat killed then soaked into ethanol, and detergent lysed. The
surface was functionalized with a mixed, self-assembled, monolayer of alkanethiols
followed by immobilization of Mouse anti-E. coli O157:H7 monoclonal antibody (MAb).
After surface modification, SPR experiments were run to determine the detection range of
each bacteria sample. In each experiment, different concentrations of bacteria were flowed
over the surface and direct detection of MAb and bacteria occurred, subsequently
additional MAb was flowed over the surface to amplify the response.
18
The resonance wavelength shift was detected with the device and results show that
for untreated bacteria, heat killed, and detergent lysed bacteria the limit of detection was
107, 106, and 105 respectively. Then a sandwich assay was added to the detection protocol
to increase the LOD for each type of bacteria. After bacteria attached to the MAb on the
sensor surface, subsequent binding of a secondary MAb to the bacteria, amplified the
detection limit by an order of magnitude for all three samples.
The reproducibility test for this antibody immobilized sensor surface was done with
SPR by using three non-specific bacteria, E. coli K12 serotype, S. choleraesuis, and L.
monocytogenes. In this set of experiments, the nonspecific bacteria was flowed over the
sensing surface and any shifts in the resonance wavelength were due to binding of non-
specific bacteria to antibodies on the surface. The results show negligible resonance shift
after running the non-specific bacteria over the surface. Addition of the sandwich assay
protocol after the non-specific bacterial also did not shift the resonance angle.
For the first time, Wang, et al. [117] used a SPR biosensor with lectin modified on
the sensor surface as a receptor to detect E. coli O157:H7. To choose the best lectin
regarding binding to the bacteria, five different lectins from Triticum vulgaris (WGA),
Canavailia ensiformis (Con A), Ulex europaeus (UEA), Arachis hypogaea (PNA),
Maackia amurensis (MAL) were immobilized on separate chips, and bacterial attachment
to different surfaces determined the best lectin option for use as a receptor. When E. coli
O157:H7 binds to the immobilized lectin on the surface, an increase in the refractive index
occurs, which is detected with SPR. SPR also determines kinetic binding parameters (ka=K
association , kd=K dissociation), which allows the determination of KA (affinity parameter
ka/kd), which determines how tightly bacteria bound to lectin. SPR results show highest KA
19
values and greatest changes in the refractive index due to bacterial attachment to the WGA
lection with a detection limit of 3 x 103 CFU/mL. It was proposed that WGA is better
because of its biological structure, which provides more binding sites for bacteria to attach
to than the other lectins. They were also able to detect E. coli O157:H7 in cucumber and
ground meat with a LOD of 3.0 x 104 and 3.0 x 105 CFU/mL, respectively.
The effect of two different surfaces on E. coli detection have studied with SPR by
Bacca, et al. [118]. The first surface was primarily functionalized with an acid-thiol self-
assembled monolayer (SAM) and subsequently modified with anti-E. coli antibody for
detection of E. coli. The second substrate was functionalized by immobilizing modified
gold nanoparticles on the surface, which consequently create a larger surface area.
SPR expriments were performed by flowing E. coli bacteria on modified surfaces
and monitoring changes in the refractive index versus incident angle over time. The
resonance angle shift was monitored with the device for all surface functionalization steps
as well as subsequent bacterial attachment to the ligands. The results showed more
bacterial attachment to surfaces functionalized with gold nanoparticles, which makes this
sensor a better option to use for E. coli detection.
The limit of detection for functionalized gold surfaces and surfaces functionalized
with gold nanoparticles was 103 CFU/mL and 104 CFU/mL, respectively.
Subramanian, et al. [119] studied the effect of different surface chemistry for
Staphylococcus aureus detection with SPR. Surfaces with monothiol and dithiol self-
assembled monolayers were examined in different ways to evaluate the best surface
chemistry to choose for a SPR-based biosensor.
20
In the first step, primary anti-S. aureus antibodies were immobilized on the sensor
surface and different concentrations of S. aureus bacteria were passed over the sensor
surface. Binding of S. aereus against anti-S. aureus antibody was measured by a peak in
the SPR output. Increasing the amount of immobilized bacteria on the surface resulted in
a higher peak in the corresponding SPR signal. The results show greater response for
surfaces functionalized with a monothiol SAM. The sensitivity of the sensor was increased
by doing a sandwich assay detection, where binding of secondary anti-S. aureus antibodies
to the already immobilized S. aureus bacteria on the surface decreased the sensor detection
limit to 105 CFU/mL, which was 100 times better than direct detection alone.
In the study done by Lee, et al. [120], E. coli with auto-displayed Z-domains were
immobilized on modified SPR sensor surfaces for molecular recognition. The outer
membrane of E. coli is negatively charged because of phosphate groups in the
lipopolysaccharide layers, which allowed immobilization on the surface coated with a
positively charged layer by charge interaction.
In this work, the efficacy of cell immobilization on different surfaces, the stability
of the immobilized cells and the sensitivity of the sensor for detection of C-reactive Protein
(CRP) was studied.
The efficacy of immobilizing fluorescently labeled E. coli was determined by
counting the immobilized cells on three different surfaces: bare gold, only poly L-lysin
coated, and parylene-H film with a poly-L-lysine coating. The results showed a greater
number of cells immobilized on the surface coated with parylene-H film with poly-L-lysin
compared to the other two surfaces.
21
The stability of different coatings has been studied by treating the surfaces with salt
at different concentrations, and the SPR response change was been monitored for each
surface. The results indicate much less change in the SPR response after sequential
treatments for the gold surface coated with parylene-H film with poly-L-lysine, which
means that this surface had greater stability than the others.
To measure the sensitivity of the sensor for detecting CRP, first anti-CRP antibody
was injected to the surface to react with auto displayed Z-domains on the sensor surface,
then the SPR response to different concentrations of CRP was monitored. The results show
a higher sensitivity and lower detection limit (1 ng/mL with an SPR response of 25.9±37.9
RU) for the surface coated with parylene-H film with poly-L-lysin compare to the other
two surfaces.
Tawil, et al. [121] created a homemade SPR biosensor to specifically detect E. coli
and methicillin-resistant Staphylococcus aureus (MRSA) without further enrichment
requirements in less than 20 minutes. They functionalized the sensor surfaces by
immobilizing T4 bacteriophages for detection of E. coli and BP14 bacteriophages for
detection of MRSA. The sensor was used to detect different concentrations of bacteria with
a detection limit of 103 CFU/mL. The specificity of the sensor for BP14 MRSA versus
EC12 E. coli was studied with SPR. No SPR response was observed upon E. coli injection,
confirming the specificity of the sensor surface.
Subramanian, et al. [6] fabricated an SPR chip for direct detection of E. coli
O157:H7 by using a mixed alkanethiol self-assembled monolayer. They investigate the
effect of different concentrations of primary polyclonal antibodies for bacteria capture by
using three different concentrations of antibodies on the surface. To enhance the detection
22
signal, they used a sandwich assay approach by passing secondary antibody (anti-E. coli
O157:H7) over the sensor surface after bacterial immobilization. The results indicate that
adding the secondary antibody binding improved the sensitivity by 1000 times. The limit
of detection of the sensor was investigated by varying the concentrations of primary and
secondary antibodies, and was found to be 103 CFU/mL of E. coli O157:H7 with the
sandwich assay format.
The specificity of the sensor against different concentrations of S. enteritidis also
in the cocktail including E. coli O157:H7 (106 CFU/mL), S. enteritidis (106 CFU/mL),and
E. coli O55 (109 CFU/mL) was also studied. They also showed that using a Protein G assay
with anti-E. coli O157:H7 Mabs enhanced the sensitivity of the sensor.
Koubová, et al. [122] created a method based on SPR for rapid, sensitive, and
specific detection of the bacterial pathogens: Salmonella enteritidis and Listeria
monocytogenes, responsible for many common foodborne illnesses in humans. The
specific bacteria were identified through the attachment of antibodies to the sensor surface.
The antibodies used in this study were a monoclonal antibody specific to the somatic
antigen (O) serotype 9 surface lipopolysaccharide of Salmonella and the IgG fraction of
rabbit anti-Listeria.
The surface was functionalized in two distinct ways. In the first method, an
antibody layer was adsorbed on the gold surface from citrate buffer (CB) at a pH of 4.
Dextran sulfate sodium salt (DS) polyanions were electrostatically attached to the
positively charged antibodies. A second layer was then electrostatically adsorbed on the
DS layer. 0.5% glutaraldehyde in CB was used to crosslink the multilayer, connecting the
two layers of antibodies through covalent bonding. Phosphate buffered physiological
23
saline (PBS) was used to wash out the DS and any antibody molecules that were not cross-
linked (which were both negatively charged at a pH of 7.4). In the second functionalization
method, a bovine serum albumin (BSA) layer was adsorbed on the gold surface from CB
at a pH of 4. A 2% glutaraldehyde solution in CB was used to crosslink the amino groups
of the BSA, and the antibody was bound to the aldehyde groups on the BSA layer from
PCB (a mixture of PBS and CB). Throughout both of these processes, the SPR system was
used to monitor the presence and attachment of the various solutions and antibodies. The
first method, which utilized a double layer of antibodies, elicited a larger response from
the optical sensor in the SPR mechanism than did the BSA method, as the probability of
antigen binding increased due to the second layer of antibodies on the surface.
The attachment of the bacterial antigens to the antibodies fixed on the sensor
surface altered the wavelength of the reflected light, and this change in wavelength was
used in the SPR process to detect the presence of these specific bacteria. The resulting data
from the SPR wavelength detection process showed that this method of bacterial detection
and identification was able to detect up to a limit of 106 cells per milliliter of solution for
both Salmonella and Listeria, which is on par with the results of the ELISA identification
technique but is not sensitive enough for practical health applications. In addition, the flow
rate seemed to have a large influence on bacterial attachment and overall reflectivity, and
this problem was not addressed.
Waswa, et al. [123] used a SPR based biosensor to directly detect E. coli O157:H7
spiked into food samples: milk, apple juice, and ground beef. The gold surface of the
sensor was modified with biotinylated Rabbit antisera containing polyclonal antibodies
against the pathogen and food samples spiked with E. coli O157:H7 in different
24
concentrations were flowed over the sensor-modified surface. The sensitivity of above
sensor for bacterial detection was established to be 102–103 CFU/mL. The detection limit
of the sensor calculated from the lowest bacterial concentration that generated a response
signal and was at least three standard deviations larger than the signal from a negative
control in the spiked food samples, which the results show it is comparable with other
detection techniques such as fiber-optics. Specificity of the sensor to E. coli O157:H7 was
tested against genetically similar species, shigella sp. and E. coli K12. The response of the
sensor to non-target pathogens was similar to the negative control in which there were no
bacteria present.
Waswa, et al.[124] also used SPR to detect Salmonella enteritidis and Escherichia
coli. Salmonella enteritidis and Escherichia coli are common bacterial foodborne
pathogens in the United States and abroad, causing approximately 1.7 million cases of
illness annually in the United States. Therefore, a method of rapid detection of these
pathogens is in the best interest of public health; the goal of this study was to accomplish
this objective through the use of surface plasmon resonance (SPR).
In this setup, the gold sensor surface was coated with carboxymethyl dextran,
which provided a binding site for the antibodies used in this experiment. For Salmonella,
mouse polyclonal affinity-purified antiserum was used, and polyclonal rabbit antibodies
for E. coli O26 were purchased. The surface was functionalized by covalently linking
protein A (acquired from S. aureus) to the carboxymethyl dextran layer through an amine
coupling method and binding one of the antibodies to the protein A.
Experiments were performed using bacterial solution in buffer as well as skim milk
spiked with varying concentrations of bacterial cells (from 10 to 106 CFU/mL, with a
25
negative control of 0 CFU/mL). For the bacterial solution tests, each species in various
concentrations (from 102 to 107 CFU/mL) was injected into the SPR system with the sensor
surface functionalized with each species’ respective antibody. The change in the refractive
index was recorded and plotted, and the results were normalized by expressing the
refractive index change for each concentration as a ratio with respect to that of the same
species at the maximum concentration (107 CFU/mL). The results of the tests were
averaged by species and concentration, and the R2 results indicate that the process was very
sensitive for both Salmonella and E. coli. The bacteria could be easily washed off the
surface with sodium hydroxide solution, allowing for the same functionalized surface to
be reused several times. Specificity was tested by cross-testing antibodies against
increasing concentrations of nonbinding bacterial species, and the results showed that each
antibody was very specific to its bacterial species and did not show a significant response
to other species or to the negative control.
Subsequently, tests were conducted with spiked skim milk with bacterial
concentrations of 10 to 106 CFU/mL. The limit of detection was chosen to be three standard
deviations higher than the results of the negative control. Based on the results of the SPR
experiments, the limit of detection was calculated to be 25 CFU/mL for E. coli and 23
CFU/mL for Salmonella enteritidis, which is remarkable in comparison to the detection
limits of other rapid response biosensing techniques for Salmonella (105 CFU/mL). The
sensitivity, reproducibility, and specificity of this assay shows incredible promise for the
field of public health and pathogen detection.
Dudak, et al. [125] developed a SPR-based immunosensor for enumeration of E.
coli in water samples from rivers and E. coli inoculated tap water. The surface was
26
modified by immobilization of streptavidin followed by biotin conjugated polyclonal
antibodies against E. coli. SPR response signal to each step of surface functionalization
was monitored with the device. To show the sensitivity, different concentrations of E. coli
in water samples was passed over the surface and the changes in the RU were determined
by measuring the difference between the sensing signal and the baseline. The sensitivity
was established to be comparable with conventional methods such as plate counting but
requires only 30 minutes, which is much less than the 24-48 hour required for conventional
methods. The specificity of the above sensor was tested against E. aerogenes and E.
dissolvens, which are also found in water, as a result of fecal contamination. The results
show much less response to these species than to the target bacteria.
Oh, et al. [126] developed a SPR based immunosensor for rapid detection of
Salmonella paratyphi. To increase the sensitivity Protein G was coated on the gold surface
by using a self-assembly technique. It was shown previously that coating the sensor surface
with protein G increased antibody immobilization on the surface, which consequently
increased the sensor sensitivity (Oh, et al., 2004). The SPR resonance angle shift was
monitored while coating the surface with Protein G, immobilizing Mab against S.
paratyphi on the layer, and subsequently capturing the target S. paratyphi on the
antibodies. The SPR angle shift increased significantly upon adsorption of antibody and
subsequent capture of bacteria. The relationship between SPR response signal and S.
paratyphi concentration showed that increasing the concentration of bacteria produced a
corresponding linear SPR angle shift. The lower detection limit of 102 CFU/ml is four
orders of magnitude more sensitive than other common detection methods, such as ELISA.
27
The specificity of the sensor was studied by monitoring the cross reaction between
Mab against S.paratyphi and other pathogens that also exist in contaminated water
samples. The results indicated that the SPR angle shift for binding between Mab against S.
paratyphi and non-specific pathogens was much less that the shift due to specific binding
between S. paratyphi and Mab against S. paratyphi.
Jyoung, et al. [127] developed a sensor for detection of Vibrio cholerae O1 with
SPR. To control the orientation of capture antibodies on the sensor surface, the surface was
coated with G protein layer. A self-assembled monolayer (SAM) of 11-
mercaptoundecanoic acid (MUA) was added prior to the G protein layer to help with
protein adhesion. The formation of SAM of 11-MUA, protein G layer, and immobilization
of Monoclonal antibodies (Mab) against Vibrio cholerae O1 were monitored with SPR
spectroscopy and the shift in SPR resonance angle increased in each step, as expected.
After surface modification with Mab, different concentrations of Vibrio cholerae
O1 were injected over the surface, and changes in the minimum SPR angle were monitored
by the device. The results show that increasing the concentration of Vibrio cholerae O1
increased the minimum angle in SPR linearly with a detection range of 3.7x105 to 3.7x109
cells/mL, which are of value for detecting Vibrio cholerae O1 in fecal samples.
The specificity of the sensor to Vibrio cholerae O1 was investigated by using E.
coli O157:H7 and L. pneumophila as non- target samples. Very small shifts in SPR angle
indicated that the above immunosensor was selective and can be used for detection of
Vibrio cholerae O1.
Linman, et al. [128] developed a SPR based biosensor for detection of Escherichia
coli bacteria in fresh spinach. First a SAM of MUA was formed on the surface, then the
28
surface was activated by NHS-EDC solution followed by immobilization of goat anti-E.
coli fused with horseradish peroxidase (HRP) antibody on the surface. Different
concentrations of E. coli in PBS and in extracted samples from spinach were passed over
the sensor surface.
To enhance the sensitivity, a sandwich assay was performed, and HRP labeled anti-
E. coli antibodies were crossed over the surface to bind to already immobilized bacteria on
the surface, followed by injection of undiluted tetramethylbenzidine (TMB) over the
surface. It is worth mentioning that the surface was rinsed with PBS between each step.
SPR response signal was monitored during surface functionalization steps and upon
binding between bacteria and antibodies. This group used TMB to enhance the sensitivity
in bacterial detection for the first time.
For E. coli samples in PBS, SPR results showed very little response upon binding
of bacteria on the modified surface and the signal increased only a small amount after
binding of the anti-E. coli HRP conjugated antibody on the bacteria surface. The author’s
claim that this is because bacteria are large (1-5 µm in diameter) compared to the
evanescent field in SPR (200-300 nm) [129]. The SPR signal increase upon injection of
the TMB was 263% compared to samples without using HRP/TMB. The limit of detection
of E. coli in PBS was calculated to be 6x103 CFU/mL.
For E. coli samples in spinach, the results showed the same behavior, but with a
150% increase upon injection of TMB for signal enhancement, with a detection range of
104 to 106 CFU/mL. The calibration curves indicated a linear relationship with TMB
enhancement in which the SPR response was directly proportional to the concentration of
E. coli.
29
Salmonella (specifically serovars typhimurium and enteritidis) is the most common
bacterial pathogen to cause foodborne gastroenteritis. Detection of this bacteria is crucial
for the prevention of this devastating illness; however, current methods of detection are
time consuming and often require molecular labeling. Barlen, et al. [35] innovated a new
technique to both detect and identify different serovars of Salmonella simultaneously using
SPR. The SPR system measured the change in refractive index of the light reflected caused
by bacterial cell attachment to antibodies on the functionalized hydrophobic gold surface.
The system used was cuvette-based, allowing the researchers to bypass the difficulties
associated with fluid flow and use only 10 µL of sample.
The antibodies used in this experiment were comprised of two categories.
Polyclonal antibodies were used to first attach the bacterial cells to the surface, and O-
specific antibodies were used for specific serovar identification. Polyclonal rabbit
antibodies (IgG) were purchased, as well as O:4 and O:9 specific antibodies. Killed
Salmonella typhimurium and enteritidis cells were also purchased, and E. coli was cultured
on-site and used for cross-reactivity studies. Lipopolysaccharide (LPS) for both serovars
of Salmonella was purchased for further studies on sequential identification in single-
channel SPR.
The first test was to determine the lower detection limit of each bacterium in
separate buffer solutions (PBS). The surface was functionalized by binding polyclonal
antibody to a hydrophobic C18 functionalized gold surface. The bacteria were then
captured. In order to determine the specific bacterium, O-specific antibodies for a certain
serovar (O:4 for typhimurium and O:9 for enteritidis) were then allowed to attach to the
bacteria, increasing the change in refractive index. The detection limits in buffer were 1.25
30
x 105 cells/mL for typhimurium and 2.50 x 108 cells/mL for enteritidis. The same test was
performed with bacteria in spiked milk. The detection limit was unchanged for enteritidis
and increased slightly to 2.50 x 105 cells/mL for typhimurium. O-specific antibodies were
cross-reacted with the opposite strain of Salmonella and with E. coli, and these tests
determined that the polyclonal antibody was specific to Salmonella and the O-specific
antibodies were specific to their respective serovars.
Subsequently, experiments were performed to test the detection of each serovar in
a mixture of both serovars in spiked milk. The O-specific detection signals were additive
when both antibodies were added at the same time, indicating that simultaneous detection
is possible. Multi-channel analysis was used to detect the different serovars (one channel
per serovar). Sequential detection in a single channel was also performed successfully;
however, it was determined that, due to the small field size in the SPR system, the signal
of the second O-specific interaction was reduced. Therefore, the serovar with the lowest
detection signal must be tested for first if the assay is to be performed sequentially in a
single channel. This team of researchers pioneered the use of the surface plasmon
resonance system to both detect and identify different serovars of Salmonella, as well as
developed a new protocol for single-channel sequential serovar detection with SPR.
Acidovorax avenae subsp. citrulli (Aac) is a bacterium responsible for bacterial
fruit blotch in watermelons and cantaloupes, a devastating crop disease that is transmitted
through seed infection. In a series of experiments, Puttharugsa, et al. [130] tried to
determine if surface plasmon resonance imaging (SPRi) is a viable option for the detection
of Aac in naturally infected plants. Antibodies fixed to the gold sensor surface selectively
bound the Aac bacteria, and the SPRi machine interpreted the changes in light reflectivity
31
to determine the presence of the specific bacteria at various concentrations. The antibodies
used were monoclonal antibody MAb 11E5 (produced in mice and found to be very
specific to Aac) and polyclonal antibody rPAb-MPC (purchased from the Department of
Plant Pathology, Kasetsart University, Thailand).
The surface was functionalized by utilizing mixed self-assembled monolayers
(SAMs) which consist of two thiols of different chain lengths. In the direct detection assay,
a mixture of 11-MUA, which contains a carboxyl group that binds to the monoclonal
antibody, and 3-MPOH, containing a hydroxyl group as a spacer, in a concentration ratio
of 1:40 was used as an attachment point for the monoclonal antibody MAb 11E5, produced
in hybridoma mouse cells. Casein was used to prevent non-specific binding, increasing the
specificity of the process for detecting Aac. In addition, a sandwich assay was created by
adding polyclonal antibody rPAb-MPC to the bound MAb/Aac layers, which was found
through SPRi experiments to reduce the amount of cells required for detection.
The SPRi system was first used to identify the optimal antibody concentration for
the highest specific Aac binding. Through a multi-channel experiment, both whole and
broken cells were added to channels with varying amounts of bound antibody, and it was
found that 10 µg/mL was the optimal concentration of antibodies for specific cell binding.
Subsequent SPRi experiments determined that the limit of detection with the direct
detection assay (only monoclonal antibody) was 106 cells/mL; with the polyclonal
antibody added in the sandwich assay, the limit of detection dropped to 5 x 105 cells/mL.
Although these processes do not match up to the level of detection of the ELISA process
(5 x 104 cells/mL), the precision of the SPRi processes is good enough for applications of
infection detection for Aac. In addition, many attributes of the SPRi identification
32
processes described in this paper set SPRi apart from its competition, including the ability
to perform multiple cycles with the same mixed SAM (a wash with 10 mM glycine pH 2.0
washed off the Aac cells but left the SAM intact) and the performance of simultaneous
multichannel analysis. Most importantly, the SPRi process was able to adequately and
selectively detect Aac in a naturally infected plant, which was the main goal of this study.
Ostuni, et al. [131] examined the hypothesis that self-assembled monolayers
(SAMs) that resist protein adsorption also resist the attachment of bacterial and mammalian
cells to the surface. Using SPR, the researchers were able to determine the qualities of
inert SAMs (i.e. SAMs that adequately resist protein adsorption). Inert SAMs generally
contain only hydrogen bond acceptors, have an overall neutral charge, and are polar. Using
these characteristics, the experimenters developed six homologous single-component
SAMs with structurally different terminal groups in order to test their effects on protein
adsorption and cell adhesion on the surface. In the first set of experiments, adsorption of
proteins, specifically fibrinogen and lysozyme, onto the SAMs was tested using surface
plasmon resonance. Hexadecanethiolate (HDT) was used as a reference for this
experiment, and the changes in reflectivity of the chosen SAMs were normalized into a
ratio (%ML) of refractive index change of the SAM vs. refractive index change of HDT.
None of the chosen SAMs resisted adsorption better than the most inert SAM known (tri-
ethylene glycol), %ML = 0.2); however, the protein adsorption for both fibrinogen and
lysozyme was sufficiently low for practical applications.
Subsequently, using the principle that the number of bacterial colonies grown on
an agar plate is proportional to the number of colony forming units (CFU) recovered from
the SAMs, bacterial adhesion to each of the single-component SAMs was tested. The
33
species used in this test were S. aureus and S. epidermidis, as these species are responsible
for 30 – 50% of infections on indwelling medical devices. After adhesion of these species
to the SAM surfaces, agar plate cultures were made of each SAM for each bacterial strain.
The results of the colony formation showed that bacterial adhesion had little to no
correlation with protein adsorption, and that bacterial adhesion must be related to other
factors; this goes against the previously stated hypothesis. In addition, bovine capillary
endothelial (BCE) mammalian cells were used to test mammalian cell adhesion to each
SAM. After the cells in modified Eagle’s medium were allowed to adhere to the SAM
surfaces, the cells were fixed and counted. The results showed that mammalian cell
adhesion also had little to no correlation to protein adsorption, and bacterial adhesion and
mammalian cell adhesion also did not correlate. The results of these experiments did not
agree with the hypothesis; however, the SPR investigations illustrated the use of SPR for
SAM testing and testing protein adsorption, allowing the researchers to quickly screen for
the best possible SAMs for their experiment.
In order to physically defend a wound, the body will often coat the area with
proteins, such as fibronectin. When S. aureus binds to the fibronectin, this can lead to
infection. Holmes, et al. [132] develoed a method using SPR to demonstrate the role of
fibronectin binding protein A (FbpA) in the attachment of S. aureus to fibronectin as well
as the identity of the domain of fibronectin used as a binding site location for S. aureus and
S. epidermidis. SPR was used to experimentally determine the optimal concentrations and
flow rates and the rate of binding for FbpA, S. aureus, and S. epidermidis to fibronectin
and its domain fragments. Fibronectin was purchased and purified, and fibronectin
fragments were isolated. FbpA was purified from S. aureus.
34
The gold-plated surface was functionalized with fibronectin or fragments (30-100
µg/mL) in sodium acetate flowed over the surface for 2 to 7 minutes at 5 µL/min; the
remaining surface was blocked with ethanolamine. During the experiments, the bacteria
were again suspended and flowed over the surface at varying concentrations and flow rates.
Controls were run using gelatin and polyclonal fibronectin antibodies. The experiments
found that the binding of S. aureus to fibronectin required long contact times and the
bonding kinetics were largely unaffected by the flow rate. The flow rate that elicited the
highest response was 2 µL/min. Binding of the S. aureus to immobilized fibronectin had a
limit of detection of 1 x 108 CFU/mL. They also found that FbpA and S. aureus bind with
high affinity to both whole fibronectin and the 27 kDa fragment (containing the N-terminal
of fibronectin), which indicates that FbpA is the protein in S. aureus responsible for
binding and that S. aureus binds to the N-terminal of the fibronectin protein. Their high
affinity is further illustrated by their unwillingness to dissociate. Attachment of S.
epidermidis could not be detected using the standard BIAcore SPR system; instead, the
BIAcore 2000 multichannel system was used, which allowed the researchers to show that
S. epidermidis bound to the C-terminal of fibronectin with a low affinity, requiring a
concentration of 5 x 109 CFU/mL.
This study successfully pioneered the use of surface plasmon resonance in the
detection of binding of whole bacterial cells. The use of intact bacteria and the lack of
molecular labeling and protein modification highlights the value of SPR in the field of cell
detection.
Salmonella bacteria are a major cause of infections and foodborne illnesses in the
United States, and traditional methods of detecting the bacterium are costly, time-
35
consuming, and require large samples of cultured bacteria. Lan, et al. [133] used SPR to
detect the Salmonella typhimurium bacterium in a chicken carcass, a common source of
the foodborne pathogen. The analyte (in this case, the bacteria) was passed over a surface
functionalized with a ligand during SPR measurements. The S. typhimurium was
purchased, cultured, and diluted in buffered peptone water (BPW), and the chickens were
purchased and washed with PBS; that PBS wash was then diluted in BPW for use in the
experiment. The antibody used was a lyophilized affinity-purified antibody to S.
syphimurium common structural antigens (CSA-1), rehydrated in carbonate buffer and
diluted to 500 µg/mL.
A sugar experiment was run in order to find the critical concentration of sugar
required for statistically significant detection. In this experiment, it was determined that a
2.5% analyte solution was required to change the refractive index by an amount that was
statistically significant, identifying a large limitation in their process. For the bacterial
detection, the gold sensor surface for SPR was first immersed in neutravidin dissolved in
PBS solution. In order to functionalize the surface for the experiment, the avidinated
surface was immersed in a biotinylated antibody solution to bind the antibody via an
avidin-biotin interaction. From the subsequent SPR experiment, it was determined that the
limit of detection of this process was 1 x 106 CFU/mL. Although the detection limit is not
groundbreaking, the SPR technique shows promise in the field of rapid, real-time detection
of pathogenic bacteria, saving time and money for the food industry as a whole.
36
2.2.2. Mammalian Cell Detection with Surface Plasmon Resonance Imaging
Hiragun, et al. [134] used a SPR system to examine how antigen stimulation and
epidermal growth factor receptors (EGFR) affected changes in the angle of resonance
(AR). In addition to initially studying how Chinese Hamster Ovary (CHO) cells reacted to
EGFR, some human carcinoma cell lines were examined to determine their SPR signal
patterns. Antibodies were used to immobilize the cells.
The results fell into five distinct categories. The first discovery was as follows:
“CHO cells expressing the wild type EGFR and HaCaT cells show triphasic changes of
AR in response to AGF.” The SPR signals reflected three distinct phases of cell activity
induced by the EGFR. Next, “CHO cells expressing the EGFR mutated on the ATP-
binding domain show the minimal change of AR in response to EGF.” The mutation the
cells experienced on the ATP-binding domain on their membrane does not significantly
affect a change in AR. Thirdly, they reviewed the effect of wortmannin, a PI3K inhibitor,
on the cell phases with SPR. They discovered that PI3K weakened the third phase of AR
shift. Therefore, it can be inferred that PI3K was “involved in the last phase of SPR signal
evoked by EGF simulation.” The next result was that “the pattern of AR change was not
dependent on the concentration of EGF.” The SPR patterns are more likely a function the
cell type and chemical stimulation. Lastly, “carcinoma cell lines exhibited diversities in
changes of AR induced by EGF.” This particular result is significant for the greater purpose
of implementing SPR in functional cancer diagnosis as cancerous cells showed different
SPR patterns than regular cells.
In the other research done by Chabot, et al. [135] the SPR effect was investigated
when living, mammalian cells were stimulated by three specific types of chemical agents:
37
lipopolysaccharides (an endotoxin), sodium azide (a chemical toxin), and thrombin (a
physiological agonist). These specific chemicals were chosen to examine different cell
activities. Lipopolysaccharides “cause an important cellular response often leading to cell
death.” Sodium azide inhibits cellular respiration and can therefore provide insight into
how sensitive the cell was to activation by chemical agents. Thrombin affects cell layer
integrity, which will test how SPR reacts to a change in the cell membrane traits. The
different chemicals each affect SPR by altering cellular morphology, which in turn changes
the cell’s effective refractive index at the interface between the cell membrane and the
metal layer. Poly-d-lysine was used to create adhesion for the kidney cells to the gold
surface.
Increasing lipopolysaccharide concentration resulted in a higher measured SPR
response. The SPR measurements were cross referenced with phase contrast microscopy
to affirm morphological changes in the cells. Sodium azide caused a decrease in SPR
reflectance as the cells shrunk. Thrombin was also observed to show cell contraction as the
intercellular gaps increased upon application. Ultimately, SPR can be used as a real time
detection scheme to collect a dose-response relation in mammalian cells.
Lee, et al. [136] used SPR to characterize molecular interactions. HEK-293 cells
expressing the protein ODR-10 were examined to view intracellular events when these
cells were exposed to diacetyl, an odorant molecule specific to ODR-10. Exposure to
diacetyl causes an opening of the Ca2+ channels within the cell. SPR was used to detect
these intracellular events that were caused by the binding of odorant molecules in diacetyl
on the membrane/surface of the kidney cells. These ODR-10 affected cells were compared
38
to a control experiment in which HEK-293 cells were not genetically altered to express the
ODR-10 protein.
Poly-d-lysine was used to induce cell adhesion to the gold surface. Poly-d-lysine
is an effective adhesive as it contains multiple positive charges. The rho-tag gene within
the HEK cells was used to express ODR-10. Gel electrophoresis was then performed to
affirm the production of ODR-10.
They measured the change in resonance angle with respect to time as the diacetyl
was injected on to the surface. The ODR-10 protein affected cells reached a resonance
angle maximum at 150s. This is when the team ceased diacetyl injection. The control HEK
cell group showed no reaction on the SPR image to diacetyl. This change is was propsed
to be the caused in response to the intracellular change in Ca2+ ions. It was also postulated
that an increase in diacetyl concentration causes an increase in the intensity of the SPR
signal. This experiment successfully used SPR to “identify odorant molecules specific to
each olfactory receptor in a real-time manner and without any labeling.”
Iribe, et al. [137] examined the effect of B and T lymphocyte binding with
antibodies as surface antigens. The effects were detected using SPR signal changes. It has
been proposed that SPR changes can measure not only morphological changes, but also
intracellular events. Lymphocytes were chosen for this study as they cause an intracellular
reaction with a minimal morphological change. The cells utilized in this study were
collected from mouse spleens.
Specifically, anti-IgM and anti-CD19 were used for B lymphocytes and anti-CD3
were used for T lymphocytes. B type cells responded to anti-IgM and anti-CD19, but not
andti-CD3. The spleen cells (which are a mixture of B and T cells) responded to both types
39
of lymphocytes by showing increased SPR signal response. The study concluded that
“specific surface antigens of ‘single’ B and T lymphocyte could be observed without any
labeling by using the high resolution 2D-SPR.”
The reaction of living cells has been studied by Yanase, et al. [138]. This study had
two main purposes: 1) To fix living cells on a gold surface and 2) to recover adherent cells
from the culture dish while preserving their functions for analysis with SPR. They tested
three different ways to adhere living cells to a gold surface. First, they inserted a
biocompatible anchor into the cell membranes. Second, they used a positively charged
amino group that bound to the negatively charged cell membrane. Third, they exploited
covalent, peptide bonds formed between the cell and dithiobis[succinimydylpropionate]
(DSP). To test how to keep adhered cells intact they tested four methods. First, they used
a type of dish where the cells are cultured while floating. Second, they cultured the cells
on a temperature responsive polymers that melted at 32 °C or at lower temperatures. Third,
they used trypsin, an enzyme that breaks down proteins, to dissociate the cells from the
culture plates. Finally, they vigorously pipetted at 4 °C the standard cell-culture dishes.
For this study, the type of cells used were human blood cells, specifically B-
lymphocytes. Amino-alkanethiol, DSP, and the biocompatible anchor for cell membranes
(BAM) were used successfully to fix the basophils to the gold plated chips. In addition this
study “demonstrated that SPR sensors can detect not only reactions of adherent cells, but
also those of non-adherent cells, by locating them on the surface of a SPR sensor chip.”
The most efficient adherent was cysteamine, a type of aminoalkanethiol.
Horii, et al. [139] tested the allergenic response of rat basophilic leukemia cells
(RBL-2H3) with 2D-SPR imager which can obtain 2D-images of local refractive index
40
change on the surface of a gold thin film. The cells were pre-sensitized with anti-DNP IgE.
The response was measured by the change in reflection intensity in the SPR signal. The
SPR angle of the cell region was 52.2° and was 50.8° for the bare gold region. The cell
region angle shifted to 52.4° when antigen stimulation was introduced.
They also tested the degranulation of the rat cells. They concluded that the SPR
measurement was more sensitive for antigen stimulation than for degranulation. They
observed an intensity change near the rat cells and an expansion of adhered area on the 2D-
SPR upon antigen stimulation. This study reaffirmed the use of 2D-SPR as a label-free and
real-time monitoring tool for cellular studies.
Hide, et al. [140] studied RBL cells similarly to the study described above and used
DNP as antigen stimulation. The response of the cells showed a long SPR signal change
that was directly dependent on the dose of DNP applied. The signal may have remained
higher for a long period of time, even after the ligand stimulation was removed, because
of resulting biochemical reactions triggered by the binding. To test this theory, they also
applied other chemicals that affected the cell while the cells where still stimulated by the
DNP. Genistein eliminated the SPR signal. The SPR signal was partially inhibited by
phorbol 12-myristate 13-acetate and wortmannin. This study also tested degranulation by
b-hexosaminidase measurements, reaching the same conclusion as the previous paper.
The control cells, not pre-sensitized by IgE, did not alter SPR signals. This study
established that SPR has to capability to detect biologically significant interactions
between cells and reactive molecules. Their results demonstrated detection of not only
simple binding kinetics between surface receptors on the cells and molecules, but also
reflected intracellular reactions such as the movement of Ca2+ ions.
41
An important finding of this study was that the SPR signal remained high even
after the stimulator was removed from the cell sample. They hypothesized that effect was
caused by other chemical reactions in the cell that were induced by the stimulator. When
analyzing the control, they found that IgE pre-sensitization was required for a cellular
reaction to DNP. Also, the intensity of the signal was dependent on the antigen
concentration. Finally, they proposed that SPR could be used as a way to study the
interaction of molecules with the plasma membrane along with the typical ligand-receptor
sites.
Liu, et al. [141] examined the real time secretion of Vascular Endothelial Growth
Factor (VEGF) using SPR. They cultured living cells on the ceiling of a customized
polydimethylsiloxane (PDMS) SPR flow cell chamber. They used the SKOV-3 (human
ovarian carcinoma) cell line. They coated the SPR chip with a G protein solution containing
antibodies. SPR angle shift indicated the presence of VEGF.
After proving cells could survive in the PDMS flow chamber, the special gasket
was detached from the SPR flow chamber. The control experiments were repeated on an
uncoated PDMS gasket and a tissue culture plate. They concluded that SPR is an effective
tool to measure VEGF biomarker secretion by living SKOV-3 carcinoma cells. Also, their
SPR flow cell chamber set up “mimics the in vivo microenvironment of the VEGF
signaling pathway.” This is important as it could lead to further studies that examine the
cell signaling pathways in regards to drug development.
Baumgarten, et al. [142] studied the effectiveness of SPR for measuring volume
changes in cells. They used two lines of renal epithelial cells: MDCK II and NRK. To fix
cells to the SPR chip, the used glutaraldehyde and non-isotonic media to induce volume
42
changes in cells. They determined, by comparing their results to typical kinetic models,
that SPR can measure the integral, or volume, parameter as a sum of several cellular
reactions.
Upon hypertonic stimulation, the cells showed an increase of reflectivity that
correlated directly with the change in osmolarity. When the signal stabilized, they deduced
that the cells had adapted to the new conditions in their environment. Upon hypotonic
stimulation, they found that the signal decreased as a result of a decrease in osmolarity.
The cells in both tests returned to normal levels after an isotonic solution was added.
Their results concluded that cellular reactions caused by osmotic stress cause a shift
in the cell layer’s refractive index that can be measured with SPR. They found that the
LOD was below 5mOsm/kg (milliosmols per kilogram) and that this is sufficiently
sensitive for bioanalysis.
Yanase, et al. [143] tested how the area of cell adhesion adjusted to the sensor chip
and how the area of the cell reacted to different stimulants by measuring differences in AR
using SPR. They used RBL-2H3 and PAM212 cells and studied the structural changes in
cell membranes when treated with a cell motility inhibitor and antigens. They did observe
a change in the area of cell adhesion, but concluded that “The experimental results
demonstrated that the change in the area of cell adhesion to a sensor chip and that of
membrane structure is insufficient to explain the entire AR change in response to the
activation of living cells.”
Most of their results were expected. They found that antigen and EGF induce large
AR signal changes in both types of cells and that the AR increased proportionally with the
number of cells cultured on a sensor chip. The unexpected result was that there was a higher
43
AR change as a result of an increase in the cell adhesion area in RBL-2H3’s response to
antigen. They concluded that SPR also detects intracellular events and other cellular
changes beyond simply the adhesion area.
44
2.3. Biology
In this section the different bacteria types and strains, which were used in the study,
are described. The literature review highlights the significance of proposed bacteria in this
study.
2.3.1. Biofilms
When bacterial cells stick to the surface, and to each other, and the cellular
concentration reaches a certain threshold, they form colonies. These colonies are
surrounded in a self-produced matrix of exopolysaccharide (EPS) [144-146]. The bacterial
EPS is a complex mixture of polysaccharides, proteins, nucleic acids, lipids, phospholipids
and humic substances, with proteins and polysaccharides contributing up to 89% of the
EPS composition [147-151]. The polysaccharide acts as a shield for microorganisms and
protects them from host immune defense systems; making bacteria inside biofilm up to
1000 times more resistant to any antibacterial chemicals compared to those in suspension
[152-154]. Figure 8 depicts the steps of biofilm formation [77, 155].
Figure 8: Steps of biofilm formation [155].
45
Several factors influence bacterial attachment onto a surface. Some of these factors
are: the condition of substrate surface, the bacterial cell surface properties, the flow rate of
the media passing over the substrate, and the available fresh food for bacterial growth. It
is shown that rougher and more hydrophobic surfaces have higher potential for bacteria to
attach and form biofilm [156-160]. The presence of extracellular appendages and cell
surface hydrophilicity are the key cell surface properties, which play a crucial role in cell-
cell signaling and biofilm formation [157, 161].
Biofilms are reservoirs of bacteria and a source of endotoxins, which both can enter
the circulatory system of a patient and cause systemic disorders. More than 60% of
hospital-acquired infections are caused by bacterial biofilms [162, 163]. Formation of
biofilms is the main cause of many bacterial infections [164].
In medical applications, bacterial biofilms can contaminate implants and
indwelling medical devices such as tracheotomy tubes (TTs) [165], urinary catheters,
venous catheters [144], and can cause many diseases from lung and kidney infections to
tooth decay [166]. Biofilm formation increases the resistance of infections to treatment
procedures and can lead to implant failure and the need for replacement as a result. In the
United States, 80% of nosocomial infections are related to medical implants and indwelling
devices; within this number the fatality rate is 60% [155].
In the food industry, biofilm is a major concern in different sections such as
brewing, meat, poultry, and dairy processing [151, 167-169]. Among all foodborne
pathogenic microorganisms, bacteria cause 91% of total foodborne illnesses in USA [2, 3].
Based on the estimation of the Centers for Disease Control and Prevention (CDC), in the
United States, foodborne pathogens cause roughly 79 million illnesses, 325000
46
hospitalizations and almost 5000 deaths each year [1]. Also, outbreaks of foodborne
illnesses cost billions of dollars each year.
In industry, biofouling and microbial corrosion in marine vessels and oil, water,
and gas pipelines cost significant amounts in both money and time [170-173]. In order to
decrease the health risks, deaths, and reduce economic losses due to pathogenic bacteria,
there is an essential need for rapid, sensitive, and selective detection methods to sense
disease-causing bacteria [6].
2.3.1.1. E. coli
A model prokaryote organism, Escherichia coli is gram-negative, rod-shaped, and
can usually be found in the lower intestine of warm-blooded organisms [174]. A scanning
electron microscope image of several E. coli cells attached to a surface is shown in Figure
9. E. coli can cause serious food poisoning in humans [174]. E. coli in one of the main
food-borne pathogenic microorganisms, inadequate sanitizing of fresh cut food help the
survival of this bacteria. E. coli infections are mainly related to ingesting of ready-to-eat
foods [175-177].
Some strains of E. coli such as E. Coli O157:H7 are responsible for serious
gastrointestinal diseases like diarrhea, hemorrhagic colitis, and hemolytic uremic
syndrome, with a mortality rate of 50% in children and seniors [121, 178]. In the United
States, annually about 270000 cases of illnesses are caused by E. coli [124].
The ability to grow in both aerobic and anaerobic environments, fully identified
gene sequence and the high rate of growth make it the best option in the field of
biotechnology. Having peritrichous flagellation, motility mechanism of E. coli has been
47
studied as a model for microrobotics, which consequently will be used in drug delivery
systems [179, 180].
In addition to avoiding economic damage to food companies, studying E. coli
growth is providing information for future biological problems. Most experiments in this
proposal will use genetically modified Green Fluorescent Protein (GFP) E. coli K12,
obtained from the laboratory of Prof. Veronica Godoy-Carter in the Department of Biology
at Northeastern University. The Goluch Group also has m-cherry labeled E. coli K12, and
access to other strains via on-campus collaborations.
Figure 9: Scanning Electron Microscope image of E. coli [174].
2.3.1.2. P. aeruginosa
Pseudomonas aeruginosa is a model organism for investigating biofilm formation
and pathogenesis [181]. P. aeruginosa is a gram-negative, rod-shaped bacterium (Figure
10) [182] that has incredible nutritional flexibility, capable of consuming more than
seventy-five different organic compounds, which it is why it is one of the most abundant
48
organisms on earth [183]. P. aeruginosa has been found in environments such as soil,
water, humans, animals, plants, sewage, and hospitals.
P. aeruginosa is an opportunistic human pathogen, meaning it rarely infects healthy
individuals. It is considered a serious problem for patients whose immune system has been
compromised, like those hospitalized with severe burns, cancer, AIDS and cystic fibrosis
[184]. P. aeruginosa is the most commonly found gram-negative bacterium in hospital
acquired infections, carrying a 40-60% mortality rate and listed as one of most frequent
gram-negative pathogens [185-188]. Early detection of P. aeruginosa growth will
potentially decrease the high rate of deadly infections in immunocompromised patients.
P. aeruginosa has many strains: P. aeruginosa PA01 and P. aeruginosa PA14 are
two common strains, which have had their complete genomes sequenced. A comparison
between the two shows that although the genome of PA14 (6.5 Mbp) is slightly larger than
that of PA01 (6.3 Mbp), both genomes are very similar. There are 58 gene clusters from
PA14 that are missing in PA01 and it is proposed that some of these genes are what make
PA14 more infectious than PA01 [189, 190].
49
Figure 10: Scanning Electron Microscope image of Pseudomonas aeruginosa [182].
2.3.1.3. S. aureus
Staphylococcus aureus is a gram positive and facultative anaerobic bacteria, which
has spherical shape (Figure 11) [191]. S. aureus causes hospital-acquired diseases such as
endocarditis, osteomyelitis and abscesses. Staphylococcus bacteria is able to adhere to the
surface of the indwelling medical devices and form biofilm on different surfaces, such as
plastics and metals [192, 193]. This capability makes it one on the most serious blood
stream pathogens responsible for about 38% of this type of infection [194].
Early stage detection of bacterial attachment on the surfaces plays crucial role in
prohibiting further growth and biofilm formation. SPRi provides kinetic information of
biofilm formation on the surface and is able to monitor the surface in real-time, as bacteria
grow, attach the gold surface and form biofilms on it.
50
Figure 11. Scanning Electron Microscope image of Staphylococcus aureus [191].
2.3.1.4. Bacillus species (Bacillus cereus)
B. cereus is a gram positive, spore forming, and rod shape bacteria (Figure 12)
[195]. B. cereus is facultative anaerobic food bacterium [196]. The ability of this species
to form spores make them resistance to chemicals, a wide range of pH and temperatures;
the spores can also survive for decades. B. cereus causes two forms of food poisoning: the
diarrhoeal form and emetic form [196-201]. The emetic form is caused by cells growing
and depositing toxins in food, the diarrhoeal syndrome is the result of different toxins that
can be formed in the food and in the small intestine [196, 201, 202]. B. cereus bacteria are
the main contamination source of milk and dairy products and are also known as school
related pathogens because many schools provide dairy products on a daily basis for
51
children [201, 203]. B. cereus is one of the most damaging pathogens in ocular infections
which progress in 24-48 hours and in many cases lead to vision loss [202, 204-206].
n biological studies and development of biosensors, B. cereus spores are used as
simulants for the dangerous spores of B. anthracis [207]. B.anthracis exists in the form of
rod shape bacteria and spores. B.anthracis is a dangerous pathogen, which causes anthrax
in humans through injection and inhalation [208-211].
Figure 12: Scanning Electron Microscope image of Bacillus cereus bacteria[212].
52
3.0 DISSERTATION GOALS
Goal 1. System Setup for Monitoring Bacterial Growth and Biofilm Formation (Goal 1)
The Changes due to particle attachments were monitored with SPRi
Growth of GFP E.coli bacteria was monitored and compared with a control
channel
Mutant P. aeruginosa (PA14) and Wild type P. aeruginosa (PA14) was
monitored with SPRi to compare and differentiate bacterial growth with
bacterial biofilm formation
Goal 2. Prevention of Biofilm Formation on the Surface (Goal 2)
The preventative effect of different surface coatings were evaluated with
SPRi system
The effect of different antibiotics at various concentrations were monitored
in prevention of bacterial growth
Goal 3. Biofilm Removal from the Surface (Goal 3)
SDS was used to clean the biofilm from the substrate and the process was
monitored with SPRi
The effect of different antibiotics were studied in disinfecting bacterial
biofilms using SPRi
Goal 4. Effects of flow rates on Bacterial Growth (Goal 4)
The effect of flow rate and consequently shear stress on bacterial growth
was studies in real-time with SPRi
53
The shear stress distribution profile was simulated with COMSOL
multiphysics modeling software
54
4.0 EXPERIMENTAL
The overall goal of this research was to develop a label-free methodology to study
bacterial behavior and biofilm formation under different conditions. In the first level, the
effect of different surface coatings, different antibiotics in solution and various flowrates
on initial bacterial attachment and further biofilm formation on the substrate are studied
with SPRi. Next, biofilm removal with different chemicals and biofilm disruption with
antibiotics are also investigated. In this section, experimental setups were developed to
combine microfluidic devices with a SPRi instrument so that it can be used to study general
bacterial behavior such as bacterial growth and biofilm formation. The following
experiments were designed to provide an analytical approach for studying biofilm related
problems including growth kinetics, biofilm formation prevention, and biofilm removal.
4.1. System Setup for Monitoring Bacterial Growth and Biofilm Formation
(Goal 1)
The overall goal of this research was to study bacterial behavior and biofilm
formation under different conditions. In the first goal, the capability of SPRi to real-time
monitor changes on the surface as biological interactions took place were investigated.
4.1.1. Monitoring Changes on the Surface with SPRi
When something attaches to the sensor surface in SPRi, it will change the resonance
condition in the binding spot, this change will prevent the incident light from reacting with
the surface free electron and as a result it will prevent conversion of light to SPs.
Consequently, a portion of the incident light will be reflected back, which causes a bright
spot to appear in the SPRi difference image. In the first step, the ability of the device to
monitor the changes on the surface as relatively large objects (much greater than 200 nm)
55
attach to it was studied. For this purpose, microscale beads was used on the chip surface.
It was expected that the attached beads would change the reflectivity and would appear as
bright points in the difference image.
Figure 13: Setup for initial Surface Plasmon Resonance imaging (SPRi) experiments.
50 m beads in DI water was placed onto a prism coated with 50 nm of
gold. The setup was placed inside of a SPR imaging system (Horiba).
4.1.2. Monitoring Bacterial Growth with SPRi
Once detection of beads was accomplished with SPRi, bacterial growth was
examined. This was carried out by loading bacteria in solution in micro channels on the
sensor surface. This would allow the growth and movement of bacteria, and the formation
of biofilm was monitored for the first time with a SPRi device. To study bacterial growth,
E. coli labeled with Green Fluorescent Protein (GFP) was injected in a linear microchannel
placed on the sensor surface and the changes on the surface as bacteria attach were
monitored continuously with the SPRi device. At the same time, a parallel microchannel
was filled with only growth media as a control. There was no growth in this channel and
nothing would attach the surface during the experiment. To study bacterial movement and
to identify the preferred areas for initial aggregation of bacteria prior to forming biofilm, a
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droplet of GFP-labeled E. coli (of an order of magnitude in the microliter range) was placed
on the prism and covered by a PDMS chamber. While bacteria swam around, some of them
touched the surface, moved and touched another location. This entire process was
monitored with the instrument.
Figure 14: Setup for Surface Plasmon Resonance imaging (SPRi) experiments.
PDMS with two channels was reversibly sealed against a high refractive
index glass prism coated with 50 nm of gold. The left channel was filled
with LB growth media and the right channel was filled with GFP labeled
E. coli. The setup was placed inside of a SPR imaging system (Horiba).
4.1.3. Monitoring Bacterial Biofilm Formation
Bacterial biofilm formation was monitored with the SPRi device. In biofilms,
bacterial cells surround themselves with a complex matrix of exopolysaccharides (EPS)
and other biomolecules, which result in the appearance of much larger spots on the SPR
image than individual cell attachment events. For these experiments, different strains of P.
aeruginosa bacteria were injected in separate linear microchannels placed on the prism
57
surface, as shown in Figure 15. To all direct comparison across experiments, one of the
channels was filled with only growth media. The images of this channel was used as a
control in the experiment. To compare the biofilm formation and bacterial growth, two
different strains of P. aeruginosa were used: PelA mutant PA14 and Wild Type (WT)
PA14. The PelA gene in P. aeruginosa is responsible for producing biofilm, and when
knocked-out this strain performs its natural bacterial functions with the exception of
producing biofilm. The wild type PA14 forms biofilm as it grows during the experiment.
The results of this experiment provided useful information to compare bacterial growth
and biofilm formation.
Figure 15: Setup for monitoring biofilm formation using Surface Plasmon Resonance
imaging (SPRi). PDMS with three channels was reversibly sealed against
a high refractive index glass prism coated with 50 nm of gold. The left
channel was filled with trypticase soy broth, middle channel was filled
with PelA mutant P. aeruginosa PA14 and the right channel was filled
with wild type PA14. The setup was placed inside of a SPR imaging system
(Horiba).
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4.2. Prevention of Biofilm Formation on the Surface (Goal 2)
Considering the fact that prevention of biofilm formation is more ideal than treating
it, the goal of this aim was to study the effects of different surface coatings on bacterial
growth and biofilm formation as well as the effect of antibiotics on growth kinetics of
bacterial cells. In all the following experiments bacteria were cultures in 6 mL of fresh LB
at 37⁰C for 18 hours. Then they were diluted in fresh LB by 1:100 ratio. Different amounts
of this diluted media were used for each experiment.
4.2.1. Surface Coatings
In this experiment, three different biomolecules were chosen as surface coatings to
study their effect on biofilm formation on the surface. Penicillin/Streptomycin, Casein and
Bovine Serum Albumin (BSA) were chosen for this aim because of their specific properties
mentioned below.
The prism surface was coated with two different biomolecules at the same time to
allow a direct comparison between coatings. Growth media containing bacteria was loaded
in the PDMS chamber placed on top of the prism, and the effect of the coating on
preventing bacterial adhesion to the surface was studied.
Penicillin is a well-known antibiotic for treatment of Gram positive bacteria such
as Staphylococcus aureus. Penicillin belongs to the class of β-lactam antibiotics and, as
other antibiotics in this class, it works by inhibiting cell wall synthesis in bacterial cells.
Casein is the main protein found in milk and is known to decompose slowly. It has
the ability to release amino acids for up to 7 hours. The effect of casein as a coating on
implants to prevent biofilm formation and further infections is important, as it is
inexpensive and known to be compatible with human body.
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Bovine Serum Albumin (BSA) is a common blocking agent, which is used in many
biochemical experiments to prevent non-specific bindings [213]. Casein and BSA are both
commonly used proteins in microfluidics to avoid non-specific bindings on the surface.
During the biofilm formation process, bacteria first attach to the surface to form
colonies. In this stage, the refractive index of the attachment spot changes and this variation
is detected by the SPRi sensor. The changes in the refractive index appear as bright spots
on the initially dark difference image. SPRi provides difference images of the surface every
3 seconds and offers real-time monitoring of bacterial growth on the gold surface.
The SPRi difference images at different time intervals provide useful information
about biofilm formation on the surface. As bacteria grow and attach to the surface, bright
spots start to appear on the surface. The more bacteria attach to the surface, the larger the
change in the refractive index above the sensor surface, and as a result, the bright area
expands and gets brighter.
The mean value of the contrast change for the three different surface sections will
be calculated for each experiment. A graph displaying the contrast change during the
experimental period will present the bacterial growth on the sections of the surface coated
with different biomolecules. When bacteria attach to the surface, the contrast of the
grayscale SPRi difference image will increase; this rise in contrast represents a
proportional increase in the amount of biofilm on the surface.
Having both SPRi difference image and graphs showing contrast variation during
for a set of experiments will provide useful information about bacterial growth kinetics and
biofilm formation on different surfaces.
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Figure 16: Setup for coating experiments using SPRi. The PDMS chamber is placed
on the gold-coated prism surface, and the gold surface inside the
chamber was coated with two biomolecules. The setup was placed inside
of a SPR imaging system (Horiba).
4.2.2. Loading Antibiotics in Solution
Penicillin with streptomycin, a well-known antibiotic combination for treatment of
gram positive bacteria such as Staphylococcus aureus, Colistin, an antibiotic for treatment
of P. aeruginosa, and Spectinomycin, an alternative antibiotic for patients who are allergic
to penicillin, for treatment of Bacillus cereus were used in this study. Antibiotic effects
were being tested in this fashion to simulate conditions for indwelling devices that may
remain in the body for a few hours or days and cannot be coated or modified in different
ways.
The effect of penicillin/streptomycin on growth and biofilm formation of S. aureus
was studied by placing the bacteria solution on the surface and inside the PDMS chamber.
Penicillin/streptomycin solution was added to the growth media at the inlet, which would
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flow continuously during the experiment period to provide fresh food for the bacteria in
the chamber. SPRi provided difference images every three seconds and let us monitor
bacterial adhesion and biofilm formation on the surface in real-time.
The effect of Colistin on the adhesion and biofilm formation of P. aeruginosa was
studied by placing the bacterial solution on the surface and inside the PDMS chamber.
Colistin was added to the inlet media, which would then pass over the surface continuously
during the entire experiment to provide fresh media for bacteria inside the chamber. SPRi
difference images was let us monitor biofilm formation on the surface in real-time and
study the adhesion of bacteria under antibiotic treatment.
The effect of Spectinomycin on B. cereus growth on the surface was studied
following the same procedure. PDMS made chamber was placed on the gold surface and
200 µL of solution of B. cereus in LB (1:100 v:v) was loaded inside the chamber. The
entire setup was then loaded into the SPR system and the spectinomycin solution in fresh
LB was passed over the surface continuously with peristaltic pump. SPR imaging provided
real-time images from the surface, which represented B. cereus growth under the effect of
spectinomycin antibiotic. Figure 17 shows the system setup for this part of the research.
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Figure 17: Setup for studying the effect of antibiotics on prevention of biofilm
formation using SPRi. The PDMS chamber was placed on the gold-
coated prism surface, bacteria media in loaded inside the chamber and
antibiotic solution was flowed over the surface. The setup was placed
inside of a SPR imaging system (Horiba).
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4.3. Biofilm Removal from the Surface (Goal 3)
Currently, there is no established method for permanently and completely
preventing biofilm formation. In this section, biofilm removal from a contaminated surface
was studied with SPRi. After early stage detection of biofilm formation, which was
discussed in Goal 1, the efficacy of different chemicals to remove biofilm and the rate of
removal from the surface were studied in real-time with SPRi. It was the first time SPRi
has been used for biofilm removal studies and would provide kinetics and real-time
information for cleaning procedures. In this aim, the effects of cleaning with chemicals,
and disinfection using antimicrobial agents was studied with the SPRi device.
4.3.1. Cleaning with Different Chemical Compounds
Effective cleaning of biofilm is the first step in eliminating bacterial infection.
Ineffective cleaning will cause subsequent steps to be unsuccessful, because antimicrobial
products cannot easily reach the cells living inside a biofilm to kill them [151]. Commonly
used chemicals for removing the biofilm from a contaminated surface are surfactants and
alkali products. These compounds act as cleaning agents by denaturing proteins and
reducing surface tension, which leads to dissolution of biofilm [129, 214, 215]. However,
these processes have never been observed in real-time. The effects of well-known cleaning
chemical, Sodium dodecyl sulfate (SDS) on biofilm removal from contaminated surfaces
was studied. SDS is and anionic surfactant which is used in many cleaning detergents. SDS
has been chosen because of its common use in industry and the laboratory. The goal is to
study the effectiveness of tis chemical on biofilm removal.
For this study, bacteria media was first placed on a gold-coated prism surface and
inside the PDMS chamber. Lysogeny Broth (LB) growth media was run over the surface
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for 24 hours to provide fresh food for the bacteria and allow the biofilm to form on the
surface. After biofilm formation on the surface for 24 hours the inlet solution was switched
from fresh LB to SDS. SDS was then flowed over the surface for few hours to remove the
biofilm. In this process when the solution reaches the surface, it chemically affects the
biofilm on the surface and, if the chosen chemical performs as expected, it removes the
biofilm. To eliminate the effect of running solution in reflectivity variation, at the end of
SDS run, fresh LB was run over the surface for few more hours. This step allowed having
accurate comparison on the reflectivity levels before and after SDS effect. The procedure
was repeated several times.
In these experiments, the position where biofilm is formed appeared as large bright
areas in the SPRi difference image due to its different refractive index and its effects on
the resonance condition on that area. When bacteria were removed from the surface by the
loading chemicals, the running media replaced them and the refractive index changed back
to its first value. This resulted in the disappearance of the bright spots in the difference
image as a result of biofilm removal. The whole procedure was monitored with SPRi. The
results provided useful information about effectiveness of SDS on biofilm removal and the
kinetics of cleaning.
4.3.2. Disinfection with Antimicrobial Components
A cleaning procedure can remove 95% or more of a biofilm; however, as for killing
the microorganisms, disinfection of bacteria are required. This is a crucial step in both
science and industry; if the bacterial cells are not all killed after removal of the bulk
biofilm, they can move and deposit in a new location and form another biofilm, which will
increase the time and cost required [151, 216]. Disinfection products should be safe,
effective, and easy to use, and they should leave no toxic residues behind. Disinfecting is
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defined here as the use of antimicrobial products to kill the microorganisms within the
biofilm. When bacteria inside the biofilm are killed they will detach from the surface,
biofilm structure will be disrupted. This would make biofilm removal with other techniques
(mechanical and chemical ways) more effective. At the same time disinfection step will
reduce the number of viable cells on the surface and decrease the chance of biofilm
reformation and subsequent infections.
In this part of the research, the effects of different antibiotics on killing
microorganisms and eliminating biofilm attachment on the surface was studied.
Penicillin/streptomycin solution for S. aureus bacteria, Colistin for P. aeruginosa, and
Spectinomycin for B. cereus was used. It is believed that a large, rapidly administered dose
of antibiotics will inactivate the susceptible living microorganisms and will prevent
regrowth of biofilm even though bacterial cells can increase resistance toward antibiotics
by mutation or genetic exchange [151, 217-220].
To test the effectiveness of disinfection, after biofilm is formed on the surface for
24 hours, solution of different concentrations of antibiotics in fresh LB was run over the
surface for another 24 hours to provide enough time for antibiotics to diffuse through the
new biofilm on the surface and effect bacteria inside the biofilm. The changes in the
reflectivity as antibiotics effect biofilm was continuously monitored with SPRi.
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4.4. Effect of flow rate on bacterial growth (Goal 4)
In this part of the research the effect of various flowrates on biofilm formation was
studied. The first step toward biofilm formation is bacterial irreversible attachment on the
surface. Theoretically different flowrates over the surface will result in various shear
stresses and will interfere with bacterial initial attachment on the surface. Also mechanical
force is considered the most effective method for biofilm removal and is used whenever
possible. In this investigation, the effect of shear stress as a physical method for prevention
of initial bacterial attachment and further biofilm formation was studied by modeling the
system with COMSOL Multiphysics and also experimentally with SPRi system.
4.4.1. SPRi Experiments
The SPRi device includes a fluidic flow system, which allows the operator to set
the flow rate of the inlet solution. In this part, hexagon shape PDMS made chamber was
placed on the gold surface. Then bacterial media was loaded inside the chamber with
pipette. The entire setup was then placed inside the SPRi system. Fresh LB at various flow
rates was flowed over the surface for 24 hours. Figure 18 shows the system setup for SPRi
experiments. Flow rate affect the fluidic shear stress on the surface where bacteria grew
and formed biofilm. The SPRi technique was used to study these effects in real-time and
monitor the surface as bacteria attach and form biofilm under different flow rates. The
section where biofilm was formed on the surface had a different refractive index and
appeared as a bright area on the difference image. SPRi difference images, which were
taken every three seconds, let us monitor the effect of flow rate, and therefore shear stress,
on bacterial attachment and biofilm formation over the period of 24 hours.
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Figure 18: Setup for studying bacterial growth under different flowrates using
SPRi. The PDMS chamber was placed on the gold-coated prism surface,
and bacterial media was loaded inside the chamber. The setup was
placed inside of a SPR imaging system (Horiba).
4.4.2. COMSOL Multiphysics Modeling
In this part the system setup was modeled using COMSOL Multiphysics modeling.
COMSOL Multiphysics software was used to simulate and model shear stress profile in
the conduits. Simulation will be used to study the effect of flowrate on the consequent
shear stress of the flow on the surface. Shear stress itself will influence the biofilm
formation mechanism on the sensor surface. In this model, the non-slip wall boundary
condition was chosen for the hexagon shape PDMS chamber. The fluid was following
under the laminar flow condition. The results of this model provided useful information
about the shear stress distribution over the entire surface of our system.
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5.0 RESULTS AND DISCUSSION
This section will outline the preliminary results obtained thus far. The results
include monitoring of bacterial growth and biofilm formation with SPRi, using surface
coatings and antibiotics to prevent biofilm formation, and using chemicals for biofilm
removal.
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5.1. System Setup for Monitoring Bacterial Growth and Biofilm Formation (Goal
1)
The results presented in this section are partly from “Using surface plasmon
resonance imaging to study bacterial biofilms” in Biomicrofluidics, volume 8, 2014. The
results are presented with permission from Biomicrofluidics journal.
5.1.1. Bead Imaging
To first demonstrate the ability of SPRi to detect microscale objects, a control
experiment was performed using 50-µm-diameter beads. A drop of deionized (DI) water
containing a very dilute amount of 50-µm-diameter beads was placed directly onto the gold
coated prism surface (Figure 19) and a single image was obtained using SPRi. Knowing
that the majority of the surface would not have beads on it and should therefore remain
dark when imaged, it was possible to find the critical angle for imaging the surface. The
prism was then removed from the instrument and a series of images of the surface were
acquired using a CCD camera mounted on a stereo microscope with illumination from an
oblique angle. Since it is not possible to obtain high magnification images of a square
centimeter using a microscope, the SPRi image was cropped for comparison against
micrographs with similar surface areas (Figure 19: b, d, f, h). A comparison of the SPRi
images with the micrographs of corresponding areas of the surface (Figure 19: (a, b) (c, d)
(e, f) (g, h)) reveals that it is possible to detect individual 50-µm-diameter beads using
SPRi. Bead aggregates appear as larger bright areas in both sets of images. It is interesting
to note that a halo is observed around the beads in the SPRi image; it is believed that this
is caused by SPPs reflecting from the spherical beads. This effect is also observed at
chamber walls.
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Figure 19: (Right column) SPRi images of 50µm beads, (left column) Stereo
microscope fluorescent images of the same beads (a, e), (b, f), (c, g), (d, h)
microscope and SPRi images of same spots.
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5.1.2. Cell Growth and Biofilm Formation
Images of the surface were acquired every three seconds, making it possible to
observe movement at the bottom surface of a chamber. A large chamber was filled with E.
coli in LB and allowed to grow over night. The chamber was several millimeters tall,
allowing cells to move far away from the surface.
5.1.2.1 E. coli growth and biofilm formation
We first used SPRi to detect the growth and movement of GFP-labeled E. coli along
the sensor surface inside a closed microchamber. To perform experiments simultaneously,
two separate rectangular chambers were made in one piece of PDMS. One of the chambers
was filled with 5 µl of LB growth media as a control while the second chamber was filled
with GFP-labeled E. coli in LB as shown in Figure 20, top. Prior to filling, the bacteria
were grown at 37⁰C for 7 h to reach exponential growth phase. Difference images of the
two chambers were obtained simultaneously using SPRi for 6 h (Figures 20(a)–20(f)) at
room temperature, and were compared with fluorescence images obtained with a stereo
microscope of the same areas on the sensor chip (Figures 20(g) and 20(h)).
As shown in Figure 20(b), after 6 min, bright spots begin to appear in the bacteria
containing chamber as cells begin to attach to the surface, while the control chamber
(Figure 20(a)) remains completely dark. Bright spots indicate a change in the refractive
index of the surface over time, which, in the context of this experiment, translates to
biomass accumulation and bacterial growth on the surface of the prism. After 1 h, Figure
20(d) shows an increase in the number of bright spots, as new cells divide and attach to the
surface. The spot size also increases as an extracellular matrix is created around the
adherent cells. A few bright lines appeared in the control chamber (Figure 20(c)). The lines
correspond to features, such as scratches, on the gold. This phenomenon is observed in
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SPR images after a few minutes when the bulk fluid is stagnant. In this experiment, the
chamber access holes were not sealed and after 6 h, the fluid in the chambers evaporated.
Since air has a different index of refraction than water, images of the chamber surface
became bright. The resulting surface morphology that is observed in the chambers after
they were dried is quite interesting. The control chamber in Figure 20(e) is much smoother
than the chamber containing cells (Figure 20(f)) where a biofilm formed on the surface.
Finally, the chip was removed from the instrument, the PDMS chambers removed
from the prism, and fluorescence images of the surface were taken. The surface inside the
control chamber remained dark (Figure 20(g)) while the chamber containing cells had
many fluorescent cells on the surface (Figure 20(h)).
Figure 20(f) shows that the entire surface is covered with biomass, while only a
few fluorescent areas are visible in Figure 20(h). There are multiple reasons why the
fluorescent image in Figure 20(h) does not match what is observed in Figure 20(f). Most
notably, the extracellular matrix and dead cells do not fluoresce and hence are not visible
in Figure 20(h). In addition, a relatively low camera exposure time was used to obtain the
images to highlight the location of live cells and minimize photo-bleaching as multiple
images across the surface had to be acquired to confirm our findings. Unfortunately, the
opaque gold substrate prevents transmission bright field imaging.
Next, we inoculated GFP-labeled E. coli in LB. We placed 200µL of bacterial
culture on the gold-coated prism and put a large PDMS chamber on top of it to isolate the
media from the surrounding environment. The solution did not touch the PDMS chamber
in these experiments.
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The chamber was several millimeters tall, allowing cells to move far away from the
surface. The bacteria in this experiment were not incubated at 37⁰C prior to loading; instead
they were grown the entire time at room temperature which increased the amount of time
needed to form a biofilm. Difference images taken every 3 s with SPRi let us monitor
bacterial growth and biofilm formation in real time. Figures 21(a)–21(i) show the initial
biofilm formation around 7 h after the start of the experiment. We took fluorescence images
(Figure 21(e)) of the same location on the sensor surface to confirm the SPRi results.
Similar to the images shown in Figure 19, many cells died when the solution in the chamber
was dried prior to fluorescence microscopy and therefore Figure 21(j) does not match the
features shown in Figure 21(i). The drying effects can be seen on the lower right portion
of Figure 21(e), where salt crystal dendrites have formed. The general size and shape of
the fluorescent region in Figure 21(e) do match what was observed with SPRi.
To confirm that the location of biofilm formation was not affected by external
factors, such as impurities on the sensor surface or exposure to non-uniform light intensity,
we repeated the experiment several times by placing the large PDMS chamber on different
ends of the prism. We also performed the experiment with multiple gold sensor surfaces.
In all experiments, the bacteria consistently gathered in the middle of the chamber. We
hypothesize that the center of the hemispherical shaped droplet provides a higher
concentration of available nutrients and signaling molecules for the bacteria. Control
experiments without bacteria added to the chamber did not show significant contrast
change after 24 h.
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Figure 20: (Top) Schematic of the setup for E. coli SPRi experiments. A PDMS chip
containing two microchambers was reversibly sealed against the sensor
surface. (Bottom) SPR images of LB filled channels at (a) 6 min, (c) 1 hr,
(e) 6 hr, GFP E.coli filled channels at (b) 6 min, (d) 1 hr, (f) 6 hr.
Fluorescence images of (g) channel filled only with LB, and (h) GFP E-
coli filled channel. Each image is at the same magnification. White lines
have been added to the images to highlight the location of channel
sidewalls.
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Figure 21: Difference images taken with SPRi at a) 6,45’; b) 6,47’; c) 6, 49’; d) 6,51’;
e) 6,53’; f) 6,55’; g) 7 hours; h) 7,6’; i) 7,10’ are shown. The arrows are
pointing to the center of the GFP labeled E. coli bacterial media droplet,
where the bacteria preferred to gather. j) A fluorescent image of the
surface of the prism surface after being removed from the SPRi system.
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5.1.2.2 P. aeruginosa growth and biofilm formation
The robust biofilms that P. aeruginosa forms aid significantly in its pathogenesis
and a better understanding of the initial cell adhesion and biofilm formation processes will
provide significant insight into strategies for preventing infections. We monitored biofilm
formation of two P. aeruginosa PA14 strains, wild type and mutant pelA. A PDMS chip
containing three linear chambers was placed on the sensor surface. One chamber contained
no bacteria, the second chamber was filled with pelA mutant, which cannot produce a
robust biofilm, and the third chamber was filled with wild type, which produces biofilm.
Trypticase soy broth was used as growth media in all three chambers. The pelA gene is
responsible for biosynthesis of cellulase-susceptible polysaccharide that is essential for
formation of robust biofilms, but has no influence on the cellular adhesion [221].
Prior to being loaded into the microchambers, the two bacterial strains were incubated at
37⁰C for 5 h to initiate exponential growth. Difference images of the loaded chambers were
collected for 3 h using SPRi (Figure 22), and afterwards, the sensor surface was imaged
with a stereo microscope to confirm the formation of biofilm. We repeated this experiment
three times and obtained consistent results. The chamber without cells remained dark
(Figure 22(a)). Some growth was observed in the chamber containing the pelA strain
(Figure 22(b)). The small bright spots in the image are cells that attached to the surface and
began growing. Biofilm growth in the chamber with wild type cells was extensive after 3
h in this small (approximately 3 µL) fluid volume (Figure 22(c)).
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Figure 22: (Top) Schematic of the biofilm formation experiments using SPRi. PDMS
with three channels was reversibly sealed against a high refractive index
glass prism coated with 50 nm of gold. The left channel was filled with
trypticase, middle channel was filled with PelA mutant PA14and the right
channel is filled with wild type PA14. The setup was placed inside of a
SPR imaging system (Horiba). (Bottom) Difference images of SPRi in
after 3hours. The left column is the difference images taken with SPRi of
channel filled with just trypticase soy broth, the middle column is the
difference images of channel filled with PelA mutant PA14 and the right
channel is difference images of Wild type PA14.
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Next, we inoculated CFP-PA01 in LB. We placed 200µL of bacterial culture on the
gold-coated prism and put a large PDMS chamber on top of it to isolate the media from
the surrounding environment, similar to the procedure in the last experiment with GFP-
E.coli. The solution did not touch the PDMS chamber in these experiments.
The chamber was several millimeters tall, allowing cells to move far away from the
surface. The bacteria in this experiment were not incubated at 37⁰C prior to loading;
instead, they were grown the entire time at room temperature, which increased the amount
of time needed to form a biofilm. Difference images taken every 3 s with SPRi let us
monitor bacterial growth and biofilm formation in real time. Shown in Figure 23(a)-23(h)
are SPRi images of P. aeruginosa PAO1 grown in a large chamber overnight at the same
conditions as GFP-labeled E. coli shown in the last experiment. The PAO1 cells behave
differently than E. coli cells. PAO1 cells initially formed a biofilm at the edges of the
droplet, and only later began forming a biofilm in the center. This knowledge of biofilm
assembly may potentially be exploited to identify bacterial species in unknown samples.
The spots outside of the fluid region are caused by contact of the PDMS chamber with the
sensor surface. They were present throughout the experiment and did not change in size or
shape. After SPRi, the prism was removed from the system, the biofilm was dried, and the
PDMS chamber was removed. Figure 23(i) is a GFP-filtered fluorescence image of the
right side of the biofilm, which crystallized during the drying process. A camera exposure
time of 50 ms was used, which makes the image very overexposed. A clear boundary is
visible where the biofilm ends and the PDMS chamber begins. The image is the brightest
directly next to the PDMS where a large amount of cells are located and the fluorescence
intensity decreases when moving away from chamber wall. Figure 23(j) is a SEM image
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of a portion of the biofilm on the right side of the chamber. The gold surface on the right
side of the image, which was not exposed to bacteria, is very clean. The drying process
potentially adds more cells to the surface than there were adhered in the SPRi, however,
this can be distinguished partly as cells originally immobilized on the surface have
extracellular matrix formed around them. The fixing process can also remove cells that are
not tightly bound to the surface, thus preventing an exact comparison. The SEM image
shows a biofilm geometry that is consistent with the SPRi and fluorescence microscopy
images. On the left side of Figure 23(j), after the cellular biofilm ends, there is biomaterial
on the surface that is measured with SPRi with lower contrast than the cells at the chamber
perimeter. This biomaterial is distinguishable in the SEM from the clean gold surface on
the right side of Figure 23(j). Figure 23(k) is a SEM image from the center of the chamber
area where a biofilm was forming and contrast was increasing in the SPRi at the end of the
experiment.
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Figure 23: Images of P. aeruginosa PAO1 after being grown overnight in LB growth
media. (a-h) SPRi images after overnight growth. The red arrow on the
right side of (h) points to the area that is shown in (i,j). The green arrow
in the center of (h) points to the area shown in (k). (i) GFP-filtered
fluorescence image of the right side of the dried biofilm on the sensor
surface. (j) SEM images of the right side of the biofilm. (k) SEM image of
the center of the chamber.
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5.2. Prevention of Biofilm Formation on the Surface (Goal 2)
The results presented in this section are from “Surface plasmon resonance imaging
(SPRi) for multiplexed evaluation of bacterial adhesion onto surface coatings” in
Analytical Methods, volume 7, 2015. The results are presented with permission from
Analytical Methods journal.
The goal of this study was evaluating the effectiveness of different parameters on
prevention of bacterial growth and biofilm formation. In this regard, the preventative effect
of various surface coatings were simultaneously studies and compared. Also the effect of
certain concentrations of antibiotics in decreasing biofilm formation on the surface was
monitored in real time.
5.2.1. Surface Coating
In this section, the effects of different surface coatings, such as Casein, BSA, and
Penicillin/streptomycin on preventing bacterial biofilm formation on the sensor surface are
presented. As it is possible to monitor a 1 cm square are of the sensor surface with the SPRi
device, the surface was coated with two different biomolecules at the same time, and the
results are compared with the non-coated gold surface.
5.2.1.1. Casein and BSA
In the next set of experiments, the effects of casein, a well-known family of proteins
for preventing biomolecular attachment in microfluidic applications [222], and BSA, a
hydrophilic protein frequently used to prevent non-specific biofouling [223, 224], were
investigated. First, P. aeruginosa adhesion was evaluated on a sensor surface with BSA
coated on the left side, casein coated on the right, and bare gold in the middle. The graph
in Figure 24 shows the normalized mean reflectivity for each coating, with error bars
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representing the standard deviations. After 24 hours of exposure to flow containing P.
aeruginosa, the BSA coating had about 15% less biomass and the casein coating had over
80% less biomass than bare gold.
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Figure 24: SPRi difference images of P. aeruginosa (CFP-PA01) growth on the gold
surface coated with BSA (left) and casein (right) after (a) 6, (b) 12, (c) 18,
and (d) 24 hours. Differences in brightness are clearly distinguishable
between surface coatings. The regions selected for analysis in each of the
images are outlined in panel (a) using yellow dashed lines. (e) Changes in
the mean value of the reflectivity caused by binding of P. aeruginosa to
portions of the surface coated with BSA, casein and non-coated (red brick
= BSA, solid brown = bare gold, horizontal green lines = casein). Error
bars show the standard deviations of three separate experiments. *
indicates a change from the control bare gold at each time (p < 0.05, 2-
tailed t-test with unequal variance).
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Next, BSA and casein were exposed to flow containing planktonic S. aureus cells.
Images in Fig. 25a–d show the difference images from one experiment at six-hour intervals
and reveal the formation of biofilm on the surface. Fig. 25e shows the results of the data
analysis, which was performed the same way as for the P. aeruginosa experiments. After
24 hours, the BSA coating had 20% less biomass and the casein coating had 60% less
biomass than bare gold. The increased standard deviation for the results using S. aureus,
shown in Fig. 25, is attributed to the greater variability in attachment behavior for this
species. S. aureus cells tend to cluster together and attach to surfaces in clumps at the tested
flow conditions. The greater contrast increase for bare gold, shown in Fig. 24 and 25,
indicates more biofilm formation in comparison to the two coatings. Fig. 24 and 25
indicate, both qualitatively and quantitatively, that casein prevented biofilm attachment
onto the surface. BSA provided a statistically significant decrease in biofouling for P.
aeruginosa, but was not effective at preventing S. aureus attachment. Given that bacteria
with hydrophobic cellular membranes are generally attracted to hydrophobic surfaces and
repelled by hydrophilic surfaces, the results support a conclusion that the casein coating
remains hydrophilic throughout the experiment. The BSA was perhaps partially denatured
by the gold surface, exposing some of its hydrophobic amino acids to the solution [225,
226]. We ran a contact angle test and the casein-coated surface wetted significantly more
than the BSA-coated side. A drop of water on the casein surface exhibited a contact angle
of less than 20⁰ while the contact angle on BSA was ~45⁰, indicating that the BSA coating
creates a less hydrophilic surface. A control SPRi experiment without the addition of
bacteria showed negligible change in brightness for both coatings, indicating that the
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material was not removed or degraded by the flow, and thus we do not expect cross
contamination of the surfaces.
86
Figure 25: SPRi difference images of S. aureus growth on the gold surface coated
with BSA (left) and casein (right) after (a) 6, (b) 12, (c) 18, and (d) 24
hours. Differences in brightness are clearly distinguishable between
surface coatings. The regions selected for analysis in each of the images
are outlined in panel (a) using yellow dashed lines. (e) Changes in the
mean value of the reflectivity caused by binding of S. aureus to portions
of the surface coated with BSA, casein and non-coated (blue checker =
BSA, solid orange = bare gold, upward sloped grey lines = casein). Error
bars show the standard deviations of three separate experiments. *
indicates a change from the control bare gold at each time (p < 0.05, 2-
tailed t-test with unequal variance).
87
To validate the SPRi results, one of the S. aureus experiments was stopped after
six hours and imaged using an SEM. Figure 26a and d show the borders between the
BSA/bare gold and bare gold/casein, respectively, at a low magnification. There is
significantly more biomass on the bare gold than on either of the coatings. Figure 26b and
c show two sections of the surface at the border between the BSA and bare gold at a higher
magnification. Figure 26e and f show the border between bare gold and casein. S. aureus
cells are attached to the bare gold surface and beginning to form biofilms while the BSA
and casein surfaces are still relatively uncontaminated. There were no visible edge effects
in the coating materials on the surface, and the cell distribution is uniform across each
individual coating. The boundaries between coatings are sharply defined and match the
shape of the initial droplets that were placed on the sensor surface prior to drying.
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Figure 26: Scanning electron microscope (SEM) images of the coated and uncoated
sensor surfaces after 6 hours of exposure to flowing solutions containing
to S. aureus. (a) Low-magnification and (b), (c) high-magnification images
of the boundary between BSA and bare gold. (d) Low magnification and
(e), (f) high-magnification images of the boundary between bare gold and
casein.
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5.2.1.2. Penicillin/Streptomycin and BSA
In this set of experiments, we studied the effects of a penicillin/ streptomycin
antibiotic cocktail as a surface coating for inhibition of P. aeruginosa and S. aureus biofilm
formation. The experiments were repeated three times and the data was analyzed the same
way as in the BSA/casein experiments. Figure 27 shows the results of experiments with P.
aeruginosa. The antibiotic cocktail was consistently less effective than BSA at preventing
bacterial adhesion over the course of 24 hours for species. Figure 28a–d shows the SPRi
difference images at six hour intervals for the antibiotic and BSA coatings when they are
exposed to S. aureus. For the right side of the chamber, which was coated with
penicillin/streptomycin, bacterial adhesion is initially suppressed; however, the coating
ceases to be effective after a few hours. After 24 hours, the area with the antibiotic coating
is nearly indistinguishable from the bare gold surface.
Figure 28e shows the normalized contrast changes due to bacterial growth on
different parts of the surface. The quantitative analysis shows that the difference between
the antibiotic coating and the bare gold surface is not statistically different after 24 hours.
It is suspected that the bacteria rapidly degraded the antibiotics as only a small dose was
present on the surface versus dissolving it in the growth medium continuously [227]. The
antibiotics on their own did not appear to degrade, as a control SPRi experiment without
bacteria showed minimal changes in brightness on the coated surface over 24 hours. At the
conclusion of the experiments, the BSA coating had 25% less biomass than the bare gold
region when exposed to P. aeruginosa and 50% less biomass when exposed to S. aureus.
The perceived improvement in BSA effectiveness versus the BSA/ casein experiments is
attributed to a slightly lower initial concentration of bacterial cells. The absolute values for
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the reflectivity changes on the bare gold surface, for the BSA/casein and BSA/antibiotic
experiments after 24 hours, were within 10% of each other. The larger standard deviation
for the S. aureus results at the 6 hour time point is the result of minor changes in initial
concentration and growth rates between experiments that resulted in changes in the rate at
which cells initially attached to the coatings. These variables cannot be controlled with
very high precision, and the results highlight the additional issues faced when testing
individual coatings in separate experiments.
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Figure 27: SPRi difference images of P. aeruginosa (CFP-PA01) growth on the gold
surface coated with BSA (left) and penicillin/streptomycin (right) after (a)
6, (b) 12, (c) 18, and (d) 24 hours. The region of the chip coated with BSA
is darker than the antibiotic-coated region, which is nearly
indistinguishable from the bare gold region. (e) Changes in the mean
value of the reflectivity caused by binding of P. aeruginosa to portions of
the surface coated with BSA, antibiotics, and non-coated gold (red brick
= BSA, solid brown = bare gold, vertical pink lines = antibiotics).
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Figure 28: SPRi difference images of S. aureus growth on the gold surface coated
with BSA (left) and penicillin/streptomycin (right) after (a) 6, (b) 12, (c)
18, and (d) 24 hours. The region of the chip coated with BSA is darker
than the antibiotic-coated region, which is nearly indistinguishable from
the bare gold region. (e) Changes in the mean value of the reflectivity
caused by binding of S. aureus to portions of the surface coated with BSA,
antibiotics, and non-coated gold (blue checker = BSA, solid orange = bare
gold, downward sloped purple lines = antibiotics).
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5.2.1.3. Penicillin/Streptomycin and Casein
This set of experiments was conducted to directly compare the preventative effect
of penicillin/streptomycin antibiotic cocktail and casein coatings on P. aeruginosa biofilm
formation. The left side of the surface was coated with casein and the right side was coated
with antibiotics while the center of the gold surface was not coated. Bacterial solution was
placed in the chamber and the SPRi experiment was run for 24 hours. Figure 29 show
difference images generated at the surface by the SPRi sensor show much lower attachment
for the section coated with casein, while the region coated with antibiotic showed almost
no effect on preventing the bacterial growth (Figure 29).
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Figure 29: SPRi difference images of P. aeruginosa growth on the gold surface coated
with casein (left) and penicillin/streptomycin (right) after (a) 6, (b) 12, (c)
18, and (d) 24 hours. Differences in brightness are clearly distinguishable
between surface coatings.
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5.2.2. Loading Antibiotics in Solution
In this section, the efficacy of penicillin/Streptomycin to prevent S. aureus
infection, Colistin to prevent P. aeruginosa growth and Spectinomycin to prevent B. cereus
growth were investigated. A control experiment was first completed to determine the
normal bacterial growth on the gold surface without antibiotics. Then the growth rate and
biofilm formation kinetics were monitored in the presence of antibiotics in the inlet growth
media. The results of both experiments provided useful information about the kinetics of
biofilm formation under the effect of antibiotics.
5.2.2.1 Control Experiment
In this experiment, a PDMS chamber was first placed on the sensor surface. LB
growth media was run for 3 minutes at a high flow rate in the SPRi system to make sure
all of the tubing system was filled with LB. 200 µL of LB growth media containing S.
aureus was placed in the PDMS chamber on the sensor surface and the prism was placed
in the SPR device. The SPRi experiment was run for 24 hours. Fresh LB was provided for
the bacteria during the entire experiment by flowing LB over the sensor surface at a flow
rate of 10 µL/min.
Figure 30 shows the SPRi difference images at different time intervals. As bacteria
grew and attached to the surface, bright spots started to appear on the surface. The more
bacteria attached to the surface, the larger the change in the refractive index above the
sensor surface; as a result, the chamber area increased in brightness over time.
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Figure 30: SPRi difference images of S. aureus growth on the sensor surface with
continuous LB flow over the surface after a) 35, b) 330, c) 635, and d) 1170
min.
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5.2.2.2 Penicillin/Streptomycin (S. aureus)
In this section, 200 µL of the diluted media was placed in the PDMS chamber on
the sensor surface and the prism was placed in the SPR device. To study the preventive
effect of penicillin/streptomycin on the growth of S. aureus, penicillin/streptomycin
solution was added to the inlet LB growth media (1:100). The flow system ran during the
entire 24-hour experimental period in order to provide fresh food for the S. aureus cells
initially present in the chamber. The SPRi device provided difference images of the sensor
surface every 3 seconds. Figure 31 shows the comparison between the results of this
experiment and the control experiment. The results indicate that the
penicillin/streptomycin reduced bacterial growth.
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Figure 31: SPRi difference images of the surface. The left column shows the images
from S. aureus growth on the chamber without having any antibiotic in
the inlet media as a control, right column shows the difference images at
the same time points by running penicillin/streptomycin from the
beginning of the experiment. Growth in the two chambers is shown at
(a,b) 35, (c,d) 330, (e,f) 635, and (g,h) 1414 min from the start of the
experiment. This image compares the bacterial growth in the two
experiments to study the effect of penicillin/streptomycin on prevention
of bacterial growth.
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5.2.2.3 Colistin (P. aeruginosa)
In this section, 200 µL of diluted (1:100) P. aeruginosa bacteria in LB, which was
initially inoculated in 6 mL of LB growth media and incubated overnigh for 18 hours, was
placed in the PDMS chamber on the gold surface of the sensor. 50 mg of Colistin was
added to 50 mL of the inlet LB growth media to make a final concentration of 1g/L. The
experiment was run for one day, and the SPRi system monitored the bacterial growth. The
results showed that Colistin prevented bacterial growth completely, as shown in Figure 32.
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Figure 32: SPRi difference images of P. aeruginosa growth with and without
antibiotics. The left column shows the images of P. aeruginosa growth in
the chamber when running Colistin from the beginning of the experiment.
The right column shows the difference images at the same time points
without having any antibiotic added to the inlet media. Images are shown
after (a,b) 3 hrs , (c,d) 9 hrs, (e,f) 17 hrs.
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5.2.2.4 Spectinomycin (B. cereus)
In this section, 200 µL of diluted (1:100) B. cereus bacteria in LB, which was
initially inoculated in 6 mL of LB growth media and incubated over night for 18 hours,
was placed in the PDMS hexagon shape chamber on the gold surface of the sensor. 10 mg
of Spectinomycin was added to 50 mL of the inlet LB growth media to make a final
concentration of 100 µg/mL. The experiment was run for 24 hours, and the SPRi system
monitored the bacterial growth. Images at 6 hour intervals are presented infigure 33.
Comparing B. cereus growth with and without antibiotics shows that Spectinomycin
decreased overall bacterial growth and stopped bacterial growth on the surface after 6
hours. Figure 34 shows the reflectivity changes over time as B. cereus bacteria grow on
the surface in the presence and absence of Spenctinomycin antibiotic and provides more
quantitative analysis. Reflectivity change in directly proportional to the biomass
accumulation on the surface and it was calculated to show the biomass accumulation on
the surface each 6 hours. Figure 35 shows the amount of biomass coverage on the surface
every 6 hours. As presented in this graph in the presence of antibiotics stopped bacterial
further growth after around 6 hours and the total mass coverage in the absence of antibiotics
(~3000 pg/mm2) was almost five times more that when antibiotics was present (600
pg/mm2).
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Figure 33: SPRi difference images of B. cereus growth with and without antibiotics.
The left column shows the images of B. cereus growth in the chamber
when running Spectinomysin solution from the beginning of the
experiment, right column shows the difference images at the same time
points without having any antibiotic added to the inlet media. Images
shown at (a,b) 1 hr, (c,d) 6 hrs, (e,f) 12 hrs, (g,h) 18 hrs, and (i,j) 24 hrs.
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Figure 34: Quantitative analysis showing the reflectivity changes over time as B.
cereus bacteria grow on the surface in the presence (orange line) and
absence (blue line) of Spenctinomycin antibiotic.
Figure 35: Biomass coverage on the sensor surface at different time point. The
orange columns represent B. cereus growth on the surface in the presence
on antibiotics in the solution, the blue columns represent B. cereus growth
in the normal solution sans antibiotics.
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5.3. Biofilm Removal from the Surface (Goal 3)
Currently, there is no established method for permanently and completely
preventing biofilm formation. In this section, biofilm removal from a contaminated surface
was studied with SPRi. After early stage detection of biofilm formation, the efficacy of
different chemicals to remove biofilm and the rate of removal from the surface were
studied in real-time with SPRi. It was the first time SPRi has been used for biofilm removal
studies and would provide kinetics and real-time information for cleaning procedures. In
this aim, the effects of cleaning with chemicals, and disinfection using antimicrobial agents
was studied with the SPRi device.
5.3.1. Cleaning with Different Chemical Compounds
In this part of the research the effect of SDS a well-known surfactant used in
detergents was studied on biofilm removal of different bacterial species. The chosen
bacteria were S. aureus, P. aeruginosa, and B. cereus. The bacteria was cultured in 6 mL
fresh LB for 18 hours at 37 °C. Then this media was diluted in fresh LB (1:100 v:v). All
experiments were run using the diluted cultures. SPRi experiments began by running fresh
LB first to let the signal stabilize, then bacteria media was flowed over the surface for 24
hours, this allows bacteria attach on the surface, growth, and form biofilm. After this period
of time, 1%SDS was flowed over the surface for 3 hours to remove the biofilm, as biofilm
removes from the surface the reflectivity returns to the original state, because the biomass
in replaced by liquid. In these experiments it is important to remember, the reflectivity
change is partly due to biofilm removal and partly due to the variation in the refractive
index of the running solution, from LB to SDS. To eliminate the effect of refractive index
of the solution and to compare the exact amount of biomass removal, after SDS was run
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for few hours, the experiment was ended by running fresh LB as a reference solution. The
signal level of the LB before and after SDS run represented the biomass removal, and as a
result the efficacy of SDS.
Figure 36 shows S. aureus growth for 24 hours on the surface, bacteria covered
4000pg/mm2 on the surface after 24 hours. Then 1%SDS was run over the surface for 3
more hours, the sharp decrease in biomass coverage is partly due to the solution variation
from bacterial media (LB) to SDS. After SDS run, fresh LB was run again on the surface,
this allowed the accurate comparison of biomass removal. The results showed ~80%
biomass removal for S. aureus bacteria.
Figure 36: S. aureus growth and removal on the sensor surface during the
experiment period. Arrows indicate the time when the mentioned solution
was loaded through the system. The dashed lines compare the level of
mass coverage value at each step of the experiment. The double-sided red
arrow represents the amount of biomass removal after SDS run.
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In the next experiment the effect of SDS was studied in biofilm removal of P.
aeruginosa. The experiment was run following the exact same procedure as for S. aureus.
The results for this bacteria showed almost 100% biofilm removal (Figure 37).
Figure 37: P. aeruginosa growth and removal on the sensor surface during the
experiment period. Arrows indicate the time when the mentioned solution
was loaded through the system. The dashed lines compare the level of
mass coverage value at each step of the experiment. The double-sided red
arrow represents the amount of biomass removal after SDS run.
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Finally 1% SDS was used to remove B. cereus biofilm, bacteria was growth of the
surface following the same protocol for 24 hours, then 1% SDS was run over the surface
for 3 hours to remove the biomass. The level of LB before and after SDS run was compared
and showed 87.5% biofilm removal for B. cereus bacteria. (Figure 38)
Figure 38: B. cereus growth and removal on the sensor surface during the
experiment period. Arrows pointing at the time when the mentioned
solution was loaded through the system. The dashed lines compare the
level of mass coverage value at each step of the experiment. The double
head red arrow represents the amount of biomass removal after SDS run.
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5.3.2. Disinfection with Antimicrobial Components
In this section, the effect of antibiotics on biofilm was investigated. Antibiotic
treatment is one of the main options to treat infections related to medical devices and
implants. It is known that bacteria inside biofilm are up to 1000 times more resistant to
different antimicrobial components. Biofilm matrix acts as a barrier for any antibacterial
molecule to diffuse through and kill the organism inside it. This is the first time a SPRi
instrument was used to real-time study the effect of various antibiotics on killing bacteria
inside the biofilm and disrupting biofilm.
First, the selected bacteria were grown on the sensor surface for 24 hours following
the procedure mentioned in the last section. After 24 hours of biofilm formation antibiotics
specific to the chosen bacteria at the minimum inhibitory concentration (MIC) were flowed
over the surface for another 24 hours. This would allow enough time for the antibiotic
molecules to diffuse through the biofilm and potentially kill bacteria inside the biofilm. If
the antibiotic at the MIC concentration is effective, the biofilm will start to detach from the
surface as a result of degradation and any changes in the attachment of biofilm on the
surface will be observed with SPRi.
In the first experiment, S. aureus bacteria was grown on the surface for 24 hours
then, penicillin/Streptomycin solution in LB (0.06 µg/mL) was flowed over the surface for
another 24 hours. The results are presented in figure 38 and show that mass coverage did
not change after treating S. aureus biofilm with penicillin/streptomycin (0.06 µg/ml)
solution for 2 hours. Penicillin/streptomycin at MIC was not sufficient for treatment of the
biofilm; the concentration of antibiotics or the treatment time was not enough for
antibacterial molecules to diffuse through the biofilm matrix, kill the bacteria, and remove
the biomass attachment from the surface.
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Figure 39: The effect of penicillin/streptomycin on treatment of S. aureus biofilm.
The black arrow points at the time point when the bacterial media was
flowed over the sensor surface (t=0). The red arrow points at the time
point when antibiotic solution was flowed over the surface to treat the
biofilm (t=24h).
In the next experiment, the effect of spectinomycin antibiotic on B. cereus biofilm
was investigated. The concentration of antibiotic was 200 µg/mL. Initially, B. cereus
bacterial was cultured in 6 mL of fresh LB at 37⁰C for 18 hours. Then the bacterial media
was diluted 100 times in fresh LB (v:v). This diluted culture was flowed over the gold
surface of the prism for 24 hours and B. cereus growth was monitored in real time.
After 24 hours, the bacterial media was switched with the solution of 200 µg/mL
specitinomycin in fresh LB. The antibiotic solution was then run over the B. cereus biofilm
for another 24 hours at the same flow rate of 10 µL/min. The graph in figure 40 represents
the B. cereus growth profile over the period of 24 hours. The red arrow indicates the time
at which the antibiotic solution was loaded through the system. The results show almost an
800 pg/mm2 reduction in the attached biomass density on the surface ~21 hours after the
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antibiotic started being introduced. At 45 hours, which means 21 hours after starting the
antibiotic, bacteria start to regrow on the surface which resulted in an increase in the
biomass accumulation. This is believed to show bacterial natural behavior of developing
resistance toward antibiotics. B. cereus biofilm was treated with the consistent MIC of
spectinomycin, the results indicated this antibiotic is effective at reducing bacterial
attachment for around 21 hours only, and after that bacteria will form a resistance and will
grow again, to avoid that the concentration of antibiotic need to be increased or another
type of effective antibiotics need to be used.
Figure 40: The effect of spectinomycin on treatment of B. cereus biofilm. The black
arrow points at the time point when the bacterial media was flowed over
the sensor surface (t=0). The red arrow points at the time point when
antibiotic solution was flown over the surface to treat the biofilm (t=25h).
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5.4. Effects of flowrate on Bacterial Adhesion (Goal 4)
Changes in the flowrate directly in a channel affect the flow velocity at the channel
surface. Shear stress is proportional to the change in velocity (u) with height above the
surface (z) multiplied by the fluid's dynamic viscosity (v), which is expressed as:
𝜏 = 𝜈𝜕𝑢
𝜕𝑧
In our system, the channel height and the fluid’s dynamic viscosity was constant, so the
shear stress on the surface is only related to the fluid’s velocity and flowrate.
Changes in flowrate affect bacterial attachment and growth on the surface. The
SPRi system was used to study the effect of flowrate on bacterial growth and biofilm
formation on the surface in real time. COMSOL Multiphysics was used to simulate the
fluidic flow system and investigate the shear stress distribution on the surface in our
system.
5.4.1. SPRi Experiments
B. cereus growth was first monitored on the entire surface over a period of 24 hours
in stagnant fluid, which represented the 0 flowrate. The average reflectivity change over
the entire surface was calculated and results are presented at 6 hour intervals.
Next, B. cereus growth was monitored under 10 µL/min and 40 µL/min flowrates,
respectively, with the same procedure mentioned above. The average reflectivity changes
were obtained following the same procedure and the results are presented for each flowrate
at 6 hours time intervals. Figure 41 shows the changes in bacterial growth on the surface
as flowrate increases at each time point.
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Figure 41: The average reflectivity change in the difference image at each time point
as a result of B. cereus growth under different flowrates. Blue=stagnant
condition, Orange=10µL/min, and gray=40µL/min flowrates.
0
5
10
15
20
25
30
1 6 12 18 24
Ref
lect
ivit
y (
A.U
.)
Time (hour)
Stagnant condition 10 ul/min 40 ul/min
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Next, the effect of fluidic flowrate on S. aureus growth was investigated. Bacteria
were cultured in fresh LB for 18 hours at 37 °C prior to the experiment. This media was
then diluted in fresh LB (1:100 v:v) to provide bacteria enough food to perform normal
activities. This media was flowed over the sensor surface at different flowrates. SPRi
provided images of the surface every 3 seconds. S. aureus bacterial growth was studied at
the slow flowrate of 10 µL/min for 24 hours. The results presented in figure 42-left column
shows S. aureus growth over the period of 24 hours, with images at every 6 hours presented
here. S. aureus at a 10 µL/min flowrate formed a uniform biofilm on the entire surface.
Bacterial growth increased gradually over time, and after 24 hours, biofilm covered the
entire surface.
Next, the S. aureus experiment was repeated using a higher flowrate of 120 µL/min.
The results in figure 42-right column show non-uniform bacterial growth over this period
of time. The results show that bacteria tend to grow more on the sides on the channel rather
than the middle. Also higher bacterial growth was detected toward the bottom part of the
channel where the fluid exits through the outlet tube. The reason for higher biofilm
formation toward the bottom of the channel is because of the flow direction, which is from
top toward the bottom of the image. The flow direction pushes bacteria toward the bottom
of the channel and then media leaves upward from that site, this gives bacteria more
residence time on the bottom part of the channel rather than top part. In order to understand
the physical properties of the solution over the surface, the fluidic system was simulated
with COMSOL Multiphysics modeling software, which is discussed later in this section.
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Figure 42: SPRi difference images showing S. aureus growth under 10µl/min (left
column) and 120µl/min (right column) flowrates after (a,b) 6 hours, (c,d)
12 hours, (e,f) 18 hours, and (g,h) 24 hours.
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5.4.2. COMSOL Multiphysics Modeling
COMSOL Multiphysics modeling was carried out to simulate the shear stress
distribution on the entire sensor surface. Shear stress is directly related to flowrate of the
fluid passing over the surface and it affects bacterial attachment and further biofilm
formation.
In this model, the non-slip wall boundary condition was assumed for the hexagon-
shaped PDMS chamber. The Reynold’s number for this simulation indicates a laminar
flow. The results of this simulation are shown in figure 43, where the color code represents
the shear stress distribution over the surface. Red represents the highest and blue the lowest
shear stress on the surface. The results clearly show higher shear stress at the boundaries,
where there was no slip condition applied. The higher shear stress at the boundaries means
lower flow velocity. The lower flow velocity results in a higher residence time for bacteria
in those regions. Residence time determines the time bacteria can sit on a spot and
potentially form attachments. The higher residence time consequently increases the chance
of bacterial attachment on those regions. When bacteria form irreversible attachments they
will then start to produce exopolysaccharide matrix around themselves and form biofilm.
That explains the higher biofilm formation on the sides of the PDMS hexagon chamber.
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Figure 43: COMSOL Multiphysics modeling of the shear stress distribution on the
sensor surface. The red color indicates the highest and the blue color
represents the lowest shear stress on the surface. The Color shows highest
shear stress at the boundaries where the chamber walls are, and the lowest
shear stress was detected toward the middle of the channel.
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6.0 Conclusions and Future work
6.1. Goal 1: System Setup for Monitoring Bacterial Growth and Biofilm
Formation
These experiments show for the first time that SPRi is a viable technique for real-
time, label-free imaging of biofilm formation and removal on a surface. The technique
provides spatial information about where cells are adhering within a chamber or channel
that is not available with standard SPR. We used SPRi to image biofilms produced by two
common bacterial species, E. coli and P. aeruginosa. This straightforward methodology
allows researchers to begin using SPRi for high resolution large-area studies of bacteria on
surfaces. This type of population level analysis of bacterial response may provide new
insights for medicine, biotechnology, and ecology. Further, the gold sensing surface used
in these experiments lends itself to chemical functionalization, which makes this an ideal
approach for adhesion experiments. Finally, this approach complements other methods,
such as confocal microscopy for studying biofilms, and is the first to offer real-time, high-
resolution analysis of biofilm removal.
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6.2. Goal 2: Prevention of Biofilm Formation on the Surface
This set of experiments demonstrates as a proof-of-concept that SPRi can be used
to investigate the effects of different surface coatings on the inhibition of biofilm formation
by imaging multiple coatings in a single experiment in real-time. This side–by-side
comparison minimized variability between runs and increased throughput. This is
important because slight variations in the starting concentration of bacteria and
experimental conditions can significantly change the results, making comparisons between
experiments difficult. SPRi difference images indicate that bacteria adhere the least to
casein-coated gold surfaces, suggesting that casein is a better candidate than BSA as a
surface coating for the prevention of P. aeruginosa and S. aureus biofilm formation. The
results also show that penicillin/streptomycin solution does not have much long-term effect
in the prevention of biofilm formation on a surface, as the surface was nearly
indistinguishable from bare gold after 24 hours. The results of one experiment were further
investigated using SEM to show that the biomass surface coverage is indeed proportional
to the intensity change observed with SPRi. While only three surfaces were tested per run
in these experiments, the multiplexing capabilities for coatings can be extended further by
using a template to selectively pattern smaller regions on the 1 cm2 sensor area. However,
care must be exercised when adjusting the size of the coated region so that there are
sufficient interactions with the bacterial cells during the course of the experiment to test
the antifouling properties.
Further, interactions between coatings can be minimized, if needed, by using a
fluidic setup consisting of multiple smaller flow channels that are fed by a single inlet.
Given that the evanescent field of the surface plasmons extends a few hundred nanometers
119
from the surface, it is possible to coat the gold with multiple layers of coatings, creating,
for example, functionalized polymer and oxide coatings for analysis. As the next step, we
plan to develop standardized testing protocols that will evaluate the effectiveness of
antimicrobial surface coatings exposed to varying fluid shear stress and other common
pathogens.
Further studies can be done by integrating other microfluidic geometries with the
SPRi system. The preliminary studies on this area were presented at the Micro Total
Analysis Systems Conference, 2014. In this system, microfluidic channels (Figure 44) can
be placed on top of the gold surface and bacteria can be exposed to multiple concentrations
and antibiotics in a single run.
Figure 44: (A) Schematic of the SPRi setup for antibiotic resistance experiments. (B)
The average brightness change in the channels filled with LB without cells
(diamonds), or 5.4E+6 cells/mL S. aureus with no antibiotic (purple), with
1000X diluted antibiotic (blue), with 200X diluted antibiotic (sloping
lines). The experiment was run four times. The error bars show the
standard deviation of 3 data sets.
120
6.3. Goal 3: Biofilm Removal from the Surface
As completely preventing bacterial growth and biofilm formation is not possible
for long periods of time, we did several studies to evaluate the effectiveness of various
methods on removing bacterial biofilm from the substrates.
In the first, part we looked at the effect of SDS which is a well-known chemical
compound used in detergents in removing biofilm from the surface. The effectiveness of
1% SDS was studied on biofilm removal of P. aeruginosa, S. aureus, and B. cereus. The
results showed that a few hours of running 1% SDS at the slow flowrate of 10 µL/min
effectively removes 80-100% of the biomass from the surface. SPRi provided real-time
analysis of the biofilm formation and removal over the entire 1cm2 surface for the entire
experimental period of 24 hours. The SPRi difference images allowed for visual study of
biomass accumulation and removal on the surface. The reflectivity graph also provided
thorough quantitative analysis of the exact biomass coverage on the surface.
In the next part, antibiotic treatment was evaluated using SPRi. Antibiotic treatment
is still the main treatment for infections related to medical devices and implants. These
processes usually consist of treatment of the infected part with high doses of antibiotics.
We investigated the capability of SPRi to measure the efficacy of biofilm treatment with
antibiotics. For this purpose the effect of Colistin, Penicillin/streptomycin, and
Spectinomycin was investigated in treatment of biofilms of P. aeruginosa, S. aureus, and
B. cereus. The results, as expected, showed no effect when biofilms were treated for 24
hours at MIC. The MIC for treatment of biofilms was not sufficient, while being effective
for killing planktonic bacteria. One explanation of this observation is that the biofilm
matrix acts as a shield and impedes antibiotic diffusion.
121
This methodology provided a sensitive approach for studying, in real time, the
effectiveness of different kinds of antibacterial and chemical components in treating
biofilms.
122
6.4. Goal 4: Effects of flow rate on Bacterial growth
In the final part of the study, bacterial growth was investigated under different flow
rates. Flow rate is directly related to shear stress on the surface. Shear stress interfered with
initial bacterial attachment on the surface and further biofilm formation. The results
indicated that higher flowrate decrease bacterial growth over the same period of time on
the surface.
To analyze the relationship between shear stress and flowrate on the entire surface,
COMSOL Multiphysics modeling was used to simulate the setup. The results showed
higher shear stress at the boundaries, which caused lower flow rates in those locations. The
effect of flow rate, and as a result shear stress, was more pronounced at higher flow rates
and the bacterial growth profile for the bacterial species tested. At slow flow rates uniform
biofilm formation on the entire surface was detected, however uneven growth was
observed at faster flows, indicating a bias for bacterial attachment.
In future, the same setup and simulation can be used to study the effect of different
channel geometries and binding angles in bacterial growth and streamer formation.
Streamers are a special morphology of biofilms which are formed under certain flow
conditions. Streamers bridge between corners in non-uniform environments, such as filters,
porous materials, and medical devices. Bacterial growth and streamer formation has been
studied under different laminar flow condition [228-230] using fluorescence and other
microscopy techniques.
It is possible to study bacterial growth in channel geometries and bending angles
and investigate the kinetics of steamer formation using SPRi. The suggested channel design
123
and the related geometries are shown in figure 45, where Figure 45-a shows a channel
design with 90 degree angle bends and figure 45-b shows 150 degree bends to study
streamer formation.
Figure 45: Channel design to study biofilm formation under different flowrate and
in non-uniform structures. Bends are in a) 90 degree angle and b) 150
degree angles.
124
7.0. METHODS
7.1. PDMS Fabrication
Polydimethylsiloxane (PDMS) is a commonly used polymer in biofilm research
[231]. PDMS channels and chambers with different shapes were made. The channels and
chambers were placed on a gold-coated prism surface and bacterial cells were loaded in
them.
The two major components of PDMS are silicone elastomer base, which is a
monomer, and a silicone elastomer curing agent. The mixing ratio of these two components
plays a crucial role in the final properties of the PDMS polymer, such as stiffness, which
increases by decreasing the base to curing agent ratio [232]. The ratio which was used in
this study was 10:1, which is the most common ratio used for microfluidics experiments.
To fabricate the channels, first the two components, at the mentioned ratio, was mixed
together thoroughly and the solution was poured on a mold containing the designs for a
desired experiment. Then the mold was placed in oven at 70 °C for approximately two
hours to cure the polymer. The cured polymer was then be peeled off from the mold and it
was cut into pieces that have the same size as the prism. Before each experiment, the
channel was placed on the prism surface. In these experiments, two different channels was
used. The fabrication process for each is represented in Figure 46 and 47.
125
Figure 46: Schematic of the fabrication of a PDMS chamber. a) The hexagonal mold
is made of aluminum. b) PDMS was poured on the mold and cured in an
oven. c) The cured PDMS was peeled off from the mold. d) each mold
contains 6 hexagons, which were cut into separate pieces. e) One hexagon
chamber f) was placed on the gold coated prism at a time.
126
Figure 47: Schematic of the fabrication of PDMS channel. a) The silicon mold has
three and two linear raised feature groups on it. b) PDMS was poured on
the mold and cured in the oven. c) The cured PDMS was peeled off from
the mold. d) Each mold contains several groups of channels, which were
cut and separated. e) A PDMS piece containing two separate linear
channels f) was placed on the gold coated prism.
127
7.2. Bacterial Culture Preparation
Different bacteria species was used in this research, which have been provided
kindly by our collaborators. The two growth media used for culturing the bacteria were
Lysogeny Broth (LB) growth media and trypticase soy broth (TSB) growth media. To
prepare 500 mL of LB growth agar media, first 12.5g of LB broth and 7.5g of Agar
(solidifying agent) were mixed with distilled water completely. To prepare 500 mL of
trypticase agar media, 7.5 g of solidifying agent and 15 g of trypticase soy broth were
mixed thoroughly with distilled water. The solutions were then autoclaved at high pressure
and temperature. The agar solution solidifies as it cools down, so when the temperature
was around 50 °C the agar solution was poured in petri dishes and was left to solidify. The
petri dishes containing the agar media were stored in the fridge at -20 °C.
7.3. Bacterial Culturing
Bacteria was cultured on agar plates by streak culturing. In this method, a sterile
inoculation loop was used. The loop was dipped in the bacterial stock solution and then the
sample on the loop was spread on the agar plate. The plate was then incubated at 37 °C for
24 hours. Figure 48 shows the agar plate after 24 hours of incubation when the bacteria
grew and formed colonies. After the bacteria grew on the plates, a colony of the bacteria
was selected with the inoculation loop and cultured in 6 mL of liquid growth media. The
liquid culture was incubated at 37 °C for 18 hours to make sure the bacteria reach
exponential growth phase. These bacterial cultures were diluted at a 1:100 ratio in fresh
LB growth media before being used in the experiments.
128
Figure 48: Staphylococcus aureus bacteria cultured on a LB agar plate.
129
7.4 Sample preparation for Scanning Electron Microscopy (SEM)
1. Fixation of the specimen:
Initially, bacteria was grown on the surface under different conditions. For primary
fixation, the biological samples on the surface were soaked into 2.5% glutaraldehyde, 2.5%
formaldehyde in 0.1 M Na cacodylate buffer solution at pH 7.2 for 2 hours at 4⁰C.
Formaldehyde penetrates into the sample quickly and glutaraldehyde reacts rapidly. Cold
temperature is important to avoid lysis of cells by autolytic enzymes.
2. Washing step:
The sample was washed three times with 0.1M Na cacodylate buffer at pH 7.2 for 45
minutes at 4 °C at 15 minutes intervals.
3. Post fixation of the sample:
The sample was treated with 1.0% osmium tetroxide in 0.1 M Na canodylate buffer at pH
7.2 at 4 °C for 2 hours. After this step, temperature changes and osmolarity are not
important.
4. Washing step:
The sample was again washed three times with 0.1 M Na cacodylate buffer at pH 7.2 for
45 minutes at 15 min intervals.
5. Dehydration step:
Samples were placed into ethanol solutions with various concentrations at room
temperature to replace water molecules with ethanol in the specimen.
130
30% ethanol solution for 10-15 minutes
50% ethanol solution for 10-15 minutes
70% ethanol solution for 10-15 minutes
85% ethanol solution for 10-15 minutes
95% ethanol solution for 10-15 minutes
100% ethanol solution for 1 hour (the sample was washed with fresh 100% ethanol
three times)
6. Drying step:
The sample was placed in vacuum chamber for 2-3 hours
7. Sputter coating step:
In order to make the surface conductive for SEM procedure, the sample was sputter coated
with 5nm of Cr.
131
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