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Automated Sample Processing for
Pathogen Detection Systems
LORRE, Laboratory of Renewable Resources Engineering
Center for Food Safety Engineering
Laboratory of Renewable Resources Engineering
Agricultural and Biological Engineering
Food Science
Biomedical Engineering
Electrical and Computer Engineering (U. Illinois)
Purdue University
Eduardo Ximenes, Hunter Vibbert,
Amy Fleishman-Littlejohn, Linda Liu, Kirk Foster, Jim
Jones, Richard Hendrickson, Arun Bhunia, Rashid
Bashir, Michael Ladisch
1
Acknowledgments
LORRE, Laboratory of Renewable Resources Engineering
Dr. Jim Lindsay, Dr. Shu-I Tu
USDA Cooperative Agreement OSQR
Eastern Regional Research Center
Center for Food Safety Engineering
Dr. George Paoli from USDA-ARS
Dr. Jaeho Shin, Dr. Mira Sedlak, Dr. Nathan Mosier, LORRE,
ABE
Bruce Applegate, Lisa Mauer, Department of Food Science
Co-founder of Biovitesse: Rashid Bashir; Arun Bhunia, Consultant
2
Outline
LORRE, Laboratory of Renewable Resources Engineering
1. The Need and Goal
2. Distribution of Microorganisms
3. The Science Behind the Cell Concentration and Recovery
(CCR) Process
4. Hollow Fiber Membrane CCR Instrument: The Engineer
5. Applications
Automated Sample Processing for Pathogen
Detection Systems
3
The Need and Goal
LORRE, Laboratory of Renewable Resources Engineering
Rapid Detection of Food Pathogens as Well as the Source:
reduce public health risks
Microbial concentrations need to be
brought to detectable level
Enrichment
Culture
Cell Concentration
and Recovery
4
The Need and Goal
LORRE, Laboratory of Renewable Resources Engineering
Enrichment
Culture
Cell Concentration
and Recovery
Time Consuming Shorter Time Goal: t < 4 h
5
DISTRIBUTION OF MICROORGANISMS
LORRE, Laboratory of Renewable Resources Engineering
6
Bacterial Attachment to Surface
(generally a 2 steps model used for description)
1- Initial Reversible Attachment
Involves weak forces between bacterium and
the substratum:
Van de Waals forces
Electrostatic forces
Hydrophobic interactions
DISTRIBUTION OF MICROORGANISMS
LORRE, Laboratory of Renewable Resources Engineering
7
2- Irreversible attachment
When in some case electrostatic repulsion can be greater
than weak attractive forces
Cellular surface structures (flagella and fimbraie) and
substances (exopolysaccharides) overcome the
electrostatic repulsion to adhere to the substratum
Other factors involved: stronger forces (covalent and
Hydrogen bonds) and strong hydrophobic interactions
= Irreversible
Attachment
Goulter et al. 2009. Letters in Applied Microbiology 49: 1-7
DISTRIBUTION OF MICROORGANISMS
LORRE, Laboratory of Renewable Resources Engineering
8
Alternatively:
Saggers et al. 2008: bacterial colonization of prepared fruit
and vegetable tissues is the result of 3 phases:
1- an initial attachment;
2- a consolidation phase (may involve production of
extracellular polymer);
3- subsequent growth to form microcolonies
Saggers et al. (2008). Journal of Applied Microbiology 105: 1239-1245
Distribution of
Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
9
The binding affinity is measured by using the formula below:
Cs = a measure of concentration of bacteria bound on the specific
substrate;
Cs = measured in cfu/g, where the average mass of the samples was
used to determine a weight to substitute in for the mass;
Cw = a measure of concentration of the bacteria in the unbound
phase; measured in cfu/mL;
Kd = measured on a log scale to enhance larger differences.
Kd= Log (CS/CW)
Distribution of Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
10
Substrate Sample
& Bacteria in
Buffer
Bacteria
Sample in
Buffer
Buffer
Substrate
& BufferMethod:
1. Prepare ligand and calculate volume;
2. Vegetable or meat substrate sprayed with 70 % (v/v) ethanol and let drying;
3. Substrates placed in labeled microplate (low binding affinity) under hood;
4. In a hood, dilute bacteria to appropriate concentration;
5. Place 10 mL of buffer (PBS, PBS + 0.1 % Tween or Buffered Peptone Water)
in each microplate well;
6. Inoculate appropriate wells with bacteria;
7. Place in ice bath shaker at 120 RPM for 1 hour at 4oC;
8. Plate Samples (Selective Medium: LB-amp for E. coli and Chromo agar for
Salmonella).
Distribution of Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
11
Non-Pathogenic E. coli GFP
Binding to vegetables (4°C) : Potato (Skin, Fresh and both)
Solvents
PBS +
0.1 % TweenBuffered Peptone Water
Kd
(mL/g
)
Flesh
Both
Skin
PBS
0.0
1.0
2.0
Distribution of Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
12
Non-Pathogenic E. coli GFP
Binding to meat (4°C): Hot dog
103
104
105
102
cfu/mL
Sample
1-Buffered Peptone Water (some contamination)2-Buffered Peptone Water (no contamination)
3-Water (no contamination)
Kd
(mL/ g
)
-2
-1
0
1
1
2 3
Distribution of Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
13
Pathogenic Salmonella enteritidis
Binding to meat (4°C):Chicken breast in buffered peptone
** Sample in Buffered Peptone Water
Distribution of Microorganisms
LORRE, Laboratory of Renewable Resources Engineering
14
Work in Progress : use our method to test different
experimental conditions:
1- Microorganisms and/or Substrates;
2- Buffers, pH;
3- Temperature;
4- Incubation time, agitation etc
Literature : Significant binding at 20°C (up to 30 min
incubation time) to chicken muscle surfaces immersed
in water and surface of prepared vegetable tissues.
Thomas and McMeekin (1981). Applied EnvironmentalMicrobiology 42 (1) : 130-134;
Saggers et al. (2008). Journal of Applied Microbiology (105): 1239-1245
The Science Behind the CCR
Process
LORRE, Laboratory of Renewable Resources Engineering
MAJOR CHALLEGES TO BE ADDRESSED
Separation of Food Samples and Bacteria
Membrane Fouling
Recover Viable Cells
15
First CCR Instrument
Flat Membrane CCR Process
(1st Prototype)
LORRE, Laboratory of Renewable Resources Engineering
Effective for concentrating microbial
cells for microbiological analysis of
water, dairy, and food products*
1. Fouling of the membrane
and the need for removing
and handling it.
2. Achieving semi-continuous,
hands-off operation
Challenge
*Chen et al. 2005. Biotechnol Bioeng. 89:263-273.
16
Hollow Fiber Membrane CCR Process
LORRE, Laboratory of Renewable Resources Engineering
Advantages Over Flat Membranes:
High surface area to volume ratio;
Higher flux per unit volume of the
membrane module;
Continuous operation that avoids
manual handling of the membrane
and sample;
Easily back flushed to recover
concentrated cells of interestCross section view of
a hollow fiber
200 μM
17
First Hollow Fiber System
(2nd Prototype )
The concentration of cells utilizing hollow fibers in an
integrated system has been prototyped and run
Lessons applied to development of devices
LORRE, Laboratory of Renewable Resources Engineering
18
Dead End HF Microfiltration
– Liquid solution passes through the HF membrane. Particles
retained on the inner HF membrane surface and module surface.
– Permeate flux decreases rapidly.
– A fouling layer build-up causes the system to plug up
LORRE, Laboratory of Renewable Resources Engineering
19
Liquid solution passes through the HF membrane. Particles
retained on the inner HF membrane surface and module
surface.
Permeate flux decreases rapidly. A fouling layer build-up
causes the system to plug up.
Dead-End Filtration
Feed
Permeate
Fluid in the system is continuously circulated over
the filter surfaces;
Particle layer build up is reduced to a minimum
CROSS FLOW FILTRATION
LORRE, Laboratory of Renewable Resources Engineering
Hollow Fiber Membrane CCR Process:
(3rd Prototype)
LORRE, Laboratory of Renewable Resources Engineering
Valve
Sample
Solution
Pressure
Gauge
Pump
Hollow Fiber
Permeate
Homogenized Hot Dog Experiment:
Permeate Volume Retentate Volume0
50
100
150
200
250
0 50 100 150 200 250Time (min)
Vo
lum
e (
ml)
21
Hollow Fiber Membrane CCR Process:
(4th Prototype)
LORRE, Laboratory of Renewable Resources Engineering
Second pump passes liquid through the permeate side
of the membrane in order to achieve a constant
pressure gradient and increase transmembrane flux.
Key Components
Fiber module 0.2 µm hollow fiber
11 inch,
Polysulfone
Pressure
Transmitter
60 PSI max
2 Peristaltic Pumps Rainin Rabbit Plus
Flow Meter 0-50 mL/min
Software Labview 2009f3
22
CCR Box Front Panel Display
LORRE, Laboratory of Renewable Resources Engineering
23
Monoflow
LORRE, Laboratory of Renewable Resources Engineering
STEP Membranes Time for
Filtration
Volume
Applied
Volume
Recovered
Chicken*
Extract +
3 X 104
cfu/mL
S. enteritidis
1
Glass
Microfiber
Filters
(2.7m)
1 min 200 mL ~ 200 mL
Chicken
Extract
3 X104 cfu/mL
S. enteritidis
2 Hollow fiber
(CCR)
(0.2 m)
60 min ~200 mL ~ 2.5 mL
2 X106
cfu/mL
S. Enteritidis
24
*100 g of chicken legs was mixed with 500 mL water in a stomach bag. The chicken
legs in water were finger massaged for 2 min, few times, and then incubated at room
for 2.5 h. The liquid was collected for further work.
Testing 4TH Prototype
Testing 4TH Prototype
LORRE, Laboratory of Renewable Resources Engineering
25
Membrane Fouling:
Minimized, but still an issue
Monoflow
Maximum
Sustainable
Pressure
Testing 4TH Prototype
LORRE, Laboratory of Renewable Resources Engineering
26
1st to 3rd Quartile Process Control
Monoflow
Testing 4TH Prototype
LORRE, Laboratory of Renewable Resources Engineering
27
Dual Flow
Testing 4TH Prototype
LORRE, Laboratory of Renewable Resources Engineering
28
Dual Flow
Testing 4TH Prototype
LORRE, Laboratory of Renewable Resources Engineering
29
Flow rate
WORK IN PROGRESS
LORRE, Laboratory of Renewable Resources Engineering
1- Optimization of Pre- and Pos- Filtration Steps:
Membrane fouling : fats, oil, proteins
major obstacle hindering wide membrane applications
30
Reduces Permeate flux;
Shortens the membrane life;
Increases the maintenance cost;
Eventually add capital cost for replacement
Extension of membrane life time
(Troppocolaggen
triple helix)
Unsaturated
fat triglyceride.
WORK IN PROGRESS
LORRE, Laboratory of Renewable Resources Engineering
31
Procedures to control membrane fouling
1- Pretreatment of feed;
2- Membrane modification;
3- Changes in operating parameters;
4- Using different cleaning techniques
Kimura et al. (2004). Water Research 38: 3431-3441
Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158
Work
in
progress
PS: 2 and 3 are challenging once the membrane is installed
Work in Progress
LORRE, Laboratory of Renewable Resources Engineering
1- Optimization of Pre- and Post-Filtration Steps;
1.1 Pre-Filtration (1 min) : Glass microfiber (2.7 m)
No loss of cells
Addition of one step using glass microfiber filter (1.6 m)
32
Work in Progress
LORRE, Laboratory of Renewable Resources Engineering
1.2 Post-Filtration Steps
Macro cleaners (Ex: NaOH)
Efficiency may be dependent on the transmembrane
pressure;
Micro cleaners
Enzymes (Lipases, Proteases) + Surfactants (Ex:Tweens)
Literature: Enzyme used in combination with NaOH and
citric acid = 90% removal of foulant in cross flow humic
acid-fed ultrafiltration (Hollow fiber module –polysulfone
membrane)Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158
33
Work in Progress
LORRE, Laboratory of Renewable Resources Engineering
2- Additional tests to confirm cleaning and sanitization
of membranes for re-using;
Exhaustive tests under progress to test efficiency of
70% (v/v) ethanol;
Alternatively 10% bleach may also to be tested for
comparison.
34
Work in Progress
LORRE, Laboratory of Renewable Resources Engineering
Testing 5th Prototype:
New feature: smaller pumps were added to the instrument
35
Reduction of Dead Volume by 5 TIMES observed in
initial tests with cells in buffer: from 2.5 mL
(Prototype #4) to 0.5 mL
Translates to 5 Increase in Cell Concentration (500
times total cell concentration: from ~ 1x104 cells to ~
5x106 cells
Work in Progress
LORRE, Laboratory of Renewable Resources Engineering
Further Optimization Work in Progress:
Addition and test of small diaphragm pumps;
Addition and test of level and turbidity sensors;
Modeling studies (for instance pressure and flow rate);
Optimization of pre-filtration and cleaning steps
36
Applications
LORRE, Laboratory of Renewable Resources Engineering
Identification by Different
Methods
Concentrate Cells (Salmonella
sp, Listeria sp, E.coli sp)
Against a Background of
Microorganisms
Multifluidic
DetectionAntibody PCR
Bacteriophage
Reporter
Ramon
Spectroscopy
Light
Scattering
37
Microfliudic Biochip
LORRE, Laboratory of Renewable Resources Engineering
Dielectrophoresis (DEP) = concentration
of bacteria
Immobilization of Antibody = specificity
to capture target
pathogen
Results in
selective capture
of target pathogen
from background flora
38
Schematic of the
micro-fluidic biochip
used for capture of
bacteria using DEP
(Yang, et al. 2006)
Flat silicon substrate
16μm tall micro channel
PDMS cover
Interdigitated electrodes
•.
0
0.5
1
1.5
2
2.5
3S
. K
entu
cky
S. H
avana
S. A
natu
m
S. M
bandaka
S. S
eftenberg
S. Litchfield
S. T
hom
asville
S. B
randenburg
S. P
oona
S. A
gona
S. G
allinaru
m
S. R
ubis
law
S. P
ullo
rum
S. M
aars
een
S. A
rizonae
S. E
nte
ritidis
PT
46
S. C
hole
rasuis
S. In
dia
na
S. E
nte
ritidis
PT
21
E. coli
K12
S. S
chottm
uelle
ri
S. S
eftenburg
E. coli
0157:H
7 S
CA
13753
S. T
yphim
urium
var.
S. T
ennessee
S. T
yphi
S. H
eild
eburg
GF
P E
. coli
A4
50
nm
3238 Average AntiSE Average
0
0.5
1
1.5
2
2.5
3
3.5
4
B. ce
reu
s
C. p
erf
rin
ge
ns
S. T
yp
him
uri
um
PT
NO
S-1
S. T
yp
him
uri
um
PT
NO
S-3
S. S
tan
ley
S. S
ch
wa
rze
ng
run
d
S. B
ert
a
S. T
ho
mp
so
n
S. S
efte
nb
urg
L.r
ha
mn
osu
s
A490 n
m
3238 AntiSE
(a) (b)
ELISA Testing of Anti-Salmonella Antibodies
LORRE, Laboratory of Renewable Resources Engineering
ELISA with AntiSE and 3238 (in house polyclonal) antibodies with various
microorganisms. Values are the average of three replicates of live cells
and presented with standard deviations 39
* AntiSE shows less cross
reactivity with other related
Enterobacteriaceae via ELISA* 33 Salmonella serovars screened
Antibody Coated Biochips with and
without DEP
LORRE, Laboratory of Renewable Resources Engineering
A) Biochip coated in Anti-SE
antibody without DEP.
B) Biochip coated in antibody
3238 without DEP.
C) Biochip with immobilized
3238 antibody, no DEP.
D) Enhanced capture
with application of
DEP on 3238 antibody
coated chip.
40
A B
S. Enteriditis on chips are stained with acridine orange
Specific capture of
Acridine orange
stained Sal. Enteritidis
PT-21
Current and Future Work
LORRE, Laboratory of Renewable Resources Engineering
• Utilization of antibodies and/or ligands to
preferentially capture specific serovars of
Salmonella serovars.
• On chip and off-chip PCR confirmation of target
pathogen
• Immobilization of ligands that will facilitate the
specific capture and detection of Shiga toxin
producing Escherichia coli.
• Results obtained from biochip will be validated using
standard USDA culture based assay procedure and
multiplex PCR assay for three pathogens.
• The long term goal of this project will be to develop an
automated device for capture and detection of
multiple pathogens (Kim and Bhunia, 2008) on one
chip device and on-chip PCR
• Confirmation/identification in eight hours or less.41
42
Rashid Bashir, Yi-Shao Liu, Eric Salm
University of Illinois at Urbana-Champaign, IL.
http://libna.mntl.uiuc.edu/
Arun Bhunia, Michael Ladisch, Richard Linton
Purdue University, West Lafayette, IN.
Electronic Micro-fluidic Biochips for
Detection of Bacteria
Starting
Sample
Sample Prep
Concentration
Detection/
ID
Data Analysis/
Results
Overall Approach
~ 30 min ~ 1- 3 hr
Electrical Detection
of cell GrowthOn-Chip
Concentration
1000X
~ 15 - 30 min
Automated Off-Chip
Cell Concentration And
Recovery - 1000X
Sample
100 – 1000 ml
~ 1- 3 hr
Electronic
Biomolecular
identification
1 cfu/100 ml use 1000 ml 10 cfu 0.1 - 1 ml
Integrated Chips for Detection of
Microorganisms and Cells
“Lab on a Chip” with microfluidics and micro/nanosensors
Glass cover
In/Out ports Cavities/
Wells
Epoxy adhesive
Pin 70
0µ
m
Lab-on-a-chip for Detection of Live
Bacteria
Nanopore Sensors for DNA
Detection
Dielectrophoresis
Filters an Traps for
Biological Entities
Micro-Mechanical Cantilevers for
Detection of Spores
Trapping/Lysing of Bacteria/Viruses In Microfluidic Devices
Nano-Mechanical Cantilever Sensors for Detection of Viruses
Silicon Nanowires and Nanoplates for DNA
and Protein Detection
Genomic
Detection
On-Chip PCR
(optical/
electrical)
Cell Lysing
Temp/
Chem.-mediated
Micro-scaleImpedance
Meas.
Culture/Growth
Detection
Conc.Sorting
On-chipDielectro-
phoresis
SelectiveCapture
Ab-based
Capture
MEMS
Filters
Filters
h
Bacterial Growth & Impedance Microbiology !
Invented in late 1800s (Petri and Koch)
Still the most widespread means to grow
and detect the presence of bacteria !
# o
f b
acte
ria
Time
Lag phase
Stationary phase
Gro
wth
ph
ase
Energy Metabolism
SugarsOxygen
Na+ATP
OtherProcesses
CO2
Carbonic Acid
H2O
Ion
Channels Lactic Acid
Acetic Acid
Cell
K+
Na+Z
Owicki et al., Biosens.
Bioelectron. (1992)
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E+07
0 1 2 3 4 5 6 7 8 9
Detection time in hours
Init
ial c
ell p
op
ula
tio
n (
C0) [
CF
U/m
l]
Low number of bacteria
in large volume takes
long time to detect
Low number of bacteria in
very small volume (in
biochip!) can be detected
much faster
-
Detection Time (arbit. units)
46
Gomez, et al., Sensors and Actuators B, 2002; Gomez, et al., IEEE/ASME JMEMS, 2005
Impedance Microbiology on a Chip
• A large cell concentration by confining a few bacteria in a small volume 107
cfu/ml = 10 cfu/nl
• On-chip miniaturization Short detection time
• Electrical detection (Impedance Microbiology) Automation
PC board
w. heater
Micro -
fluidic
Tubes
Edge Connector BioChip
A Petri Dish-on-a-Chip
100µm
Measurement
electrodes
DEP capture
electrodes
Outlet Inlet
330µm
100µm
Measurement
electrodes
DEP capture
electrodes
Outlet Inlet
330µm
• Dielectrophoresis-based concentration system collects particles from a large flow stream and diverts them to a smaller stream
Gomez, et al. IEEE/ASME JMEMS, 2005
Yang, et al. Lab Chip, 2007
Koo, et al, Analytical Chemistry, 2009
Bacterial Cell Concentration on-Chip
Lee, et al.
Analytical
Chemistry, 2009
Park, et al. Lab
Chip, 2009
102
103
104
105
106
103
104
105
106
Ma
gnitu
de [
]
Fits to incubation of L. innocua (~3x107 ml-1) in TA4-B6
Ch. 2. Well WB2. 39C.
102
103
104
105
106
-60
-50
-40
-30
-20
-10
Frequency [Hz]
An
gle
[D
egre
es]
Meas. (2) 10/16/02. Fit (8) 10/24/02
Time
On-Chip Incubation of L. innocua in LB BrothInitial concentration: ~3x107 cfu/ml
Measured Impedance
Fitted circuit model
Time
On-Chip Incubation of L. monocytogenes
95%
100%
105%
110%
115%
120%
125%
130%
0 2 4 6 8 10 12 14 16 18 20
Time [hours]
Rela
tive C
onducta
nce
1 cfu
9 cfu
34 cfu
Approximate number of
colony-forming-units (cfu)
in a 5.27nl volume:Growth
Growth
Growth
ZwZw ZwZw
Cdi
Rs
Dielectric capacitance
Electrolyte
resistance
Electrode-electrolyte interfaces
Electrode-
Electrolyte
Interface Model:
Constant-angle
impedance
BjZ
nw)(
1
49
In-process Rapid Detection & Identification of Live CellsBioVitesse, Inc.
• „Petri dish on a chip‟ to miniaturize impedance microbiology
• To quickly and reliably detect and identify live bacteria in 2 to 4 hours, instead of 2 to 10 days
• Provides in-process quality control monitoring systems
• To the industrial microbiological market (Bio/Pharma and Food Safety)
Goal – Become the leader in rapid detection and identification of live cells
BioVitesse, Inc. Company Confidential
Silicon
BiochipChip Cartridge
CCRTM
Cartridge
Automated System
Sample, Media,
Sanitizing Fluid
Towards Label Free Electrical Detection of
PCR Products
• Polymerase Chain Reaction
– Target molecule doubles every cycle
Cycle # # of Molecules Conc. (#/n)
1 2
2 4
3 8
4 16
5 32
10 1024 (103) 103 #/nl
20 1048576 (106) 106 #/nl
30 1073741824 (109) 109 #/nl
40 1099511627776 (1012) 1012 #/nl
• What is the minimum concentration of dsDNA molecules (e.g. 500bp) that can be directly detected in solution using impedance measurements ???
Z
Electrical Nature of DNA Molecules
Baker-Javis et al., 1998Baker-Javis et al., 1998
Cap.=d
Ak eCap.=
d
DNA polarization (dipole effect)
Dielectric relaxation (Debye relaxation) :
eee
j+
D+
1
with L(or #)
Cap. Z
Counter Ion movement: ZRsol
DNA polarization (dipole effect)
Dielectric relaxation (Debye relaxation) :
eee
j+
D+
1
with L(or #)
Cap. Z
Counter Ion movement: ZRsol
Thymine
DNA prepared by QIAquick Gel Extraction Kit, QIAGEN,
Valencia, CA
Bulk-EIS for Label free DNA detection
e increases with # or L, C increases, Z decreases
Detection limit in DI Water for 500bp DNA = 1e9 #/l (1.33 nM)
Liu, et al. Applied Physics Letters, 2008.
Frequency (Hz)
Z (
oh
m)
102 103 104 105
103
104
105
1011#/µl
1010#/µl
109#/µl
108#/µl; + DI Control
500 bp dsDNA
Z (
oh
m)
102
103
104
105
Frequency (Hz)103 104 105
1000 bp
500 bp
100 bp
DI Control
109 #/µl dsDNA
1.00E+01
1.00E+02
1.00E+03
DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE
1e8 molecules/ul
1e9 molecuels/ul
1e10 molecules/ul
% C
han
ge o
f C
di
Background solutions
DNA con
centration
1.00E+01
1.00E+02
1.00E+03
DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE
1e8 molecules/ul
1e9 molecuels/ul
1e10 molecules/ul
% C
han
ge o
f C
di
1.00E+01
1.00E+02
1.00E+03
DI 0.05 TE 0.1 TE 0.5 TE 0.84 TE
1e8 molecules/ul
1e9 molecuels/ul
1e10 molecules/ul
% C
han
ge o
f C
di
Background solutions
DNA con
centration
Label free detection of DNA molecules suspended in diluted TE buffers and de-ionized
water. The detection limit (defined as 20% change in Cdi) for a 508bp long dsDNA
molecule, was found to be about 109 molecule/µl in 0.1TE buffer and 1010 molecule/µl in
0.5 TE buffer and above.
-3.00E+01
-2.00E+01
-1.00E+01
0.00E+00
1.00E+01
2.00E+01
3.00E+01
4.00E+01
5.00E+01
6.00E+01
0 5 10 15 20 25 30
1 µg
0.1 µg
0.01 µg
PCR cycles
% C
han
ge
of
Cd
i
control
-3.00E+01
-2.00E+01
-1.00E+01
0.00E+00
1.00E+01
2.00E+01
3.00E+01
4.00E+01
5.00E+01
6.00E+01
0 5 10 15 20 25 30
1 µg
0.1 µg
0.01 µg
PCR cycles
% C
han
ge
of
Cd
i
control
Label free DNA detection in PCR Reagents
sample (PCR mix plus DNA template)
control (PCR mix only)
prfA 508 bp segment target for specific detection of Listeria monocytogenes
5‟CGGGATAAAACCAAAACAATTT3‟ and R-5‟TGAGCTATGTGCGATGCCACTT3‟
Liu, et al. IEEE Sensors Conference,
2008
Liu, et al. Submitted, 2010
Label free DNA detection in PCR Solution
1 g starting concentration (3e8 cells / 25ul)
55Silicon substrate
Glass cover
Metal 1 (impedance)
Metal 1
(wire bonds)
BioVitesse Silicon Chip Cartridge and
DNA Measurements
Volume ~
60nl
100 bp dsDNA BioVitesse 60nl Chip Sensitivity
1E+05
1E+06
1E+07
1E+08
0.1 1 10 100 1000 10000
Frequency (Hz)
Ma
gn
itu
de
(o
hm
s)
-180
-160
-140
-120
-100
-80
-60
-40
-20
0
Ph
as
e (
de
gre
es
)
3.2e8
1.0e9
3.2e9
1.0e10
3.2e10
1.0e11
Increasing
Concentration
Increasing
Concentration
1.5e11
DI Reference
100bp dsDNA BioVitesse 60nl Chip Sensitivity
0.0E+00
2.0E+05
4.0E+05
6.0E+05
8.0E+05
1.0E+06
1.2E+06
1.4E+06
1.6E+06
1E+08 1E+09 1E+10 1E+11 1E+12
DNA Concentration (molecules/ul)
Ma
gn
itu
de
(o
hm
s)
-80
-70
-60
-50
-40
-30
-20
-10
0
Ph
as
e (
de
gre
es
)
|Z| @ 1kHz
θ @ 100Hz
DI Water Reference
Electrical Measurements
of 100bp dsDNA in solution
Detection Limit
~ 1e10 molecules/ul
500 bp dsDNA BioVitesse 60nl Chip Sensitivity
1E+05
1E+06
1E+07
1E+08
0.1 1 10 100 1000 10000
Frequency (Hz)
Ma
gn
itu
de
(o
hm
s)
-180
-160
-140
-120
-100
-80
-60
-40
-20
0
Ph
as
e (
de
gre
es
)
3.2e8
1.0e9
3.2e9
1.0e10
3.2e10
1.0e11
Increasing
Concentration
Increasing
Concentration
DI Reference
500bp dsDNA BioVitesse 60nl Chip Sensitivity
0.0E+00
2.0E+05
4.0E+05
6.0E+05
8.0E+05
1.0E+06
1.2E+06
1E+08 1E+09 1E+10 1E+11
DNA Concentration (molecules/ul)
Ma
gn
itu
de
(o
hm
s)
-80
-70
-60
-50
-40
-30
-20
-10
0
Ph
as
e (
de
gre
es
)
|Z| @ 1kHz
θ @ 100Hz
DI Water Reference
Electrical Measurements
of 500bp dsDNA in solution
Detection Limit
~ 5e9 molecules/ul
PCR Amplification in Static Droplets
• Static droplets of PBS in oil
• Cell concentration: 106 ~ 107 cells/ml
• Droplet size100um diameter ~ 5-10 cells
• Primer conc.: 1 µM each of forward and reverse primer
• Target gene: Listeria monocytogenes prfA gene (508 bp)
Before PCR
cycling
A cluster of bacteria
Inside the droplet
100 µm
After 30 cycles, 15 sec
per thermal cycling step, total 1 hr.
-150
-100
-50
0
50
100
150
200
0 cycle 10 cycle 20 cycle 25 cycle 30 cycle 30 cycle 2
% C
ha
ng
e C
di
ch1
ch2
With primer
and template
Without primer
with template
• Electrodes on chip – droplets in Ionic Liquid
• Cell concentration: 106 ~ 107 cells/ml
• Droplet size100um diameter ~ 5-10 cells
• Bulk impedance measurements
Generation of Droplets in Viscous Fluids
Weber Number (We)
Parameterize droplet breakup processes when inertia and
capillary pressure are more important than viscous stresses. tensionsurface
diameterdroplet
velocity
fluid theofdensity
2
l
lWe
Capillary Number (Ca)
More important than Weber Number for characterizing
droplet formation in microfluidic device.
waterand oil ebetween th tension linterfacia
rate flow total theofvelocity
phase oil theofviscosity
Ca
100 m30 m 20 m
Metal electrodes0
10
20
30
40
50
60
70
0 2 4 6 8 10
Size
an
d g
ap
(m
icro
n)
Flow rate ratio (PBS:[BMIM][PF6])
PBS (0.2 - 0.025 ul/min) vs [BMIM][PF6] (0.2 ul/min)
diameter
gap
PBS bufferor liquid with cells
Ionic Liquid
100 m
50 m
20 m
Droplets
Simulation of droplet formation using Lattice
Boltzmann Method (LBM)
Figure4:
Ca=1.3e-2, Q1/Q2=5:1
Ca=1.1e-2, Q1/Q2=5:1
Ca=8.0e-3, Q1/Q2=6.25:1
Effect of Capillary number on droplet
formation in a microchannelComparison between numerical and
experimental results (Ca= 0.15)
Experimental result (Dr. Bashir's group, UIUC )
Numerical result from LBM simulation
Single droplet:
experiment - simulation
Fan (OSU), Soorykumar (OSU), Bashir (UIUC)
Ca=6.5e-3, Q1/Q2=5:1Ca=6.5e-3, Q1/Q2=5:1
0s
0.1s
0.2s
0.3s
0.4s
Droplet encapsulation of cells via lattice
Boltzmann simulation of two-phase flow
Fan (OSU), Soorykumar (OSU), Bashir (UIUC)
Ionic Liquids (ILs)
Composed entirely of ions, but liquid at low temperature (<100℃).
No effective vapor pressure, Non-flammable, High
ionic conductivity
Wide liquid range up to 300℃, Thermally stable up to
200 ℃
Ability to dissolve a wide range of inorganic,
organometallic compounds, Ability to capture small
molecules (H2, CO, CO2, and O2)
Immiscibility with some organic solvents, e.g. alkanes
Highly polar yet non-coordinating
Polarity and hydrophilicity/lipophilicity can be easily
tailored
Physical & Chemical Properties
N
N
R1
R2
X
NNR1 R3
R2
R5 R4
N
R4
R5R3
R2
R1
R6
R4
NR3
R1R2
R4
PR3
R1R2
Common cations Common anions
Cl-/AlCl3
Cl-, Br-, I-
[NO3]-, [SO4]2
-
[BF4]-
[PF6]-
[(CF3SO2)2N]-
Immidazolium-based ILs
Miscibility
with H2OM.P. (℃)
Density
(gcm-3)
Viscosity
(cP) (25℃)
Conductivty
(S/m)
[emim][PF6] ○ 60 -
[bmim][PF6] × -61 1.37 272.1 0.146
[hmim][PF6] × -73.5 1.30 497 0.110
Selected Properties of ILs
R1 = butyl, R2 = methyl, X = PF6
: [bmim]PF6
50 m
20 m
20 m
Ionic
Liquid,
0.6 l/min
PBS buffer, 0.04 l/min
100 m
10 m wide
electrodes with 10 m space
Height = 27.5 m
Ionic Liquid, 0.01 l/min
Ionic Liquid, 0.01 l/min
• Ionic liquid: [BMIM][PF6]
• PBS buffer solution: 0 (DI), 0.3x,
0.6x, 1.0x, 1.5x, pH 7.4
• Measurement and data acquisition:
dual lock-in amplifier equipped with
pre-signal amplifier, 100 kHz, 1 V,
sampling 57.2 kHz
• Post acquisition treatment: software
filtering and peak analysis by
Clampfit
Electrical Measurements of Droplets in Flow
2826Time (ms)
Sig
na
l 0
0
(mV
)
-3e-4
-2e-4
-1e-4
0
43
DI Droplets in Ionic Liquid
High Impedance
807570Time (ms)
Sig
na
l 0
0
(mV
)
0
0.01
43PBS Droplets in Ionic Liquid
High Impedance
R1
Oil or Ionic Liquid
PDMS
PBS
Electrodes
Si
R1 R1R1
R2
PBS Droplets in Mineral Oil
No Signal
Conclusions
• Electrical detection of bacterial growth
– 1 cfu/ml in 100ml
• Electrical detection of DNA molecules and
PCR
– Detection concentration of about 1e7cells/nl
– 10-100 cells in nanoliter droplets – after 30
cycles 1e9 molecules
Electrical Petri Dish
PCR a an Electrical Point of Care Test
64
5-10ul volumes
10-100nl volumes
10-100pl volumes
65
Acknowledgements
Researchers:
• Dr. Woo-Jin Chang
• Dr. Larry Millet
• Dr. Kidong Park
• Dr. Pinar Zorlutuna
• Piyush Bajaj
• Vincent Chan
• Greg Damhorst
• Brian Dorvel
• Bobby Reddy
• Murali Venkatesan
• Nick Watkins
Faculty Collaborators
– Prof. A. Alam (ECE, Purdue)
– Prof. D. Bergstrom (Med Chem, Purdue)
– Prof. A. Bhunia (Food Science, Purdue)
– Prof. S. Claire (IU-SOM)
– Prof. M. Ladisch (Ag& Bio Engr, Purdue)
– Prof. W. P. King (MechSE, UIUC)
– Prof. M. Toner (Harvard Med School)
– Prof. L. P. Lee (UC Berkeley)
– Prof. J. Lee (Ohio State University)
– Prof. W. Rodriguez (Harvard Med School)
– Prof. T. Saif (MechSE, UIUC)
– Prof. L. Schook (Animal Sciences, UIUC)
– Prof. S. Solin, (Physics, WashU)
– Dr. G. Vasmatzis (Mayo Clinic)
– Prof. S. Wickline (Wash U)
Funding Agencies
• Army TATRC
• Intel
• NIH NCI, NIBIB
• National Science Foundation
• NIH SCCNE, Wash U (Wickline, PI)
• NSF NSEC @ OSU (J. Lee, PI)
• USDA ARS, Center for Food Safety Engineering at
Purdue (Linton, PI)