Automated Sample Processing for Pathogen Detection Systems

Automated Sample Processing for Pathogen Detection Systems Eduardo Ximenes, Hunter Vibbert, Amy Fleishman-Littlejohn, Linda Liu, Kirk Foster, Jim Jones, Richard Hendrickson, Arun Bhunia, Rashid Bashir, Michael Ladisch 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 1 LORRE, Laboratory of Renewable Resources Engineering

Acknowledgments Dr. Jim Lindsay, Dr. Shu-I Tu USDA Cooperative Agreement OSQR Eastern Regional Research Center Center for Food Safety Engineering Dr. George Paoli from USDA-ARS

Dr. Jaeho Shin, Dr. Mira Sedlak, Dr. Nathan Mosier, LORRE, ABE Bruce Applegate, Lisa Mauer, Department of Food Science

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

2 LORRE, Laboratory of Renewable Resources Engineering

Outline Automated Sample Processing for Pathogen Detection Systems 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

3 LORRE, Laboratory of Renewable Resources Engineering

The Need and Goal Rapid Detection of Food Pathogens as Well as the Source: reduce public health risks

Microbial concentrations need to be brought to detectable level

Enrichment Culture

Cell Concentration and Recovery 4

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The Need and Goal Cell Concentration and Recovery

Enrichment Culture

Time Consuming

Shorter Time

Goal: t < 4 h 5

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DISTRIBUTION OF MICROORGANISMS 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

6 LORRE, Laboratory of Renewable Resources Engineering

DISTRIBUTION OF MICROORGANISMS 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

= Irreversible Attachment Other factors involved: stronger forces (covalent and Hydrogen bonds) and strong hydrophobic interactions Goulter et al. 2009. Letters in Applied Microbiology 49: 1-7 LORRE, Laboratory of Renewable Resources Engineering

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DISTRIBUTION OF MICROORGANISMS 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 8 LORRE, Laboratory of Renewable Resources Engineering

Distribution of Microorganisms The binding affinity is measured by using the formula below: Kd= Log (CS/CW)

Cs = Cs = Cw = Kd =

a measure of concentration of bacteria bound on the specific substrate; measured in cfu/g, where the average mass of the samples was used to determine a weight to substitute in for the mass; a measure of concentration of the bacteria in the unbound phase; measured in cfu/mL; measured on a log scale to enhance larger differences.

9 LORRE, Laboratory of Renewable Resources Engineering

Distribution of Microorganisms Buffer

Substrate Sample & Bacteria in Buffer Bacteria Sample in Buffer Substrate Method: & Buffer 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). 10

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Distribution of Microorganisms Non-Pathogenic E. coli GFP Binding to vegetables (4°C) : Potato (Skin, Fresh and both) 2.0

Kd (mL/g)

1.0

Flesh Both 0.0

Skin PBS

PBS + 0.1 % Tween Solvents

Buffered Peptone Water

11 LORRE, Laboratory of Renewable Resources Engineering

Distribution of Microorganisms Non-Pathogenic E. coli GFP Binding to meat (4°C): Hot dog

Kd (mL/g)

1 0 -1

1

cfu/mL 2

3

-2

102 103 104 105

1-Buffered Peptone Water (some contamination) 2-Buffered Peptone Water (no contamination) 3-Water (no contamination) Sample 12 LORRE, Laboratory of Renewable Resources Engineering

Distribution of Microorganisms Pathogenic Salmonella enteritidis Binding to meat (4°C):Chicken breast in buffered peptone

** Sample in Buffered Peptone Water 13 LORRE, Laboratory of Renewable Resources Engineering

Distribution of Microorganisms 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 14 LORRE, Laboratory of Renewable Resources Engineering

The Science Behind the CCR Process

MAJOR CHALLEGES TO BE ADDRESSED Separation of Food Samples and Bacteria

Membrane Fouling Recover Viable Cells

15 LORRE, Laboratory of Renewable Resources Engineering

First CCR Instrument Flat Membrane CCR Process (1st Prototype) Effective for concentrating microbial cells for microbiological analysis of water, dairy, and food products*

Challenge 1. Fouling of the membrane and the need for removing and handling it. 2. Achieving semi-continuous, hands-off operation

*Chen et al. 2005. Biotechnol Bioeng. 89:263-273. 16 LORRE, Laboratory of Renewable Resources Engineering

Hollow Fiber Membrane CCR Process Advantages Over Flat Membranes: High surface area to volume ratio; Higher flux per unit volume of the membrane module; Continuous operation that avoids manual handling of the membrane 200 μM and sample; Cross section view of Easily back flushed to recover concentrated cells of interest a hollow fiber

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First Hollow Fiber System (2nd Prototype ) The concentration of cells utilizing hollow fibers in an integrated system has been prototyped and run Lessons applied to development of devices

18 LORRE, Laboratory of Renewable Resources Engineering

Dead End HF Microfiltration Dead-End Filtration Feed

Permeate

Liquid solution passes through the HF membrane. Particles retained on the inner HF membrane surface and module – Liquid solution passes through the HF membrane. Particles surface. retained on the inner HF membrane surface and module surface. Permeate flux flux decreases rapidly. A fouling layer build-up – Permeate decreases rapidly. causes the system to plug causes up. – A fouling layer build-up the system to plug up

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CROSS FLOW FILTRATION  Fluid in the system is continuously circulated over the filter surfaces;  Particle layer build up is reduced to a minimum

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Hollow Fiber Membrane CCR Process: (3rd Prototype) Pump

Pressure Gauge

Valve Sample Solution Hollow Fiber

Volume (ml)

250 200

Permeate

150 100 50 0 0

50

100 150 Time (min)

200

250

Homogenized Hot Dog Experiment: Permeate Volume Retentate Volume 21

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Hollow Fiber Membrane CCR Process: (4th Prototype) 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

Second pump passes liquid through the permeate side of the membrane in order to achieve a constant pressure gradient and increase transmembrane flux. 22 LORRE, Laboratory of Renewable Resources Engineering

CCR Box Front Panel Display

23 LORRE, Laboratory of Renewable Resources Engineering

Testing 4TH Prototype Monoflow STEP Chicken* Extract + 3 X 104 cfu/mL S. enteritidis Chicken Extract 3 X104 cfu/mL S. enteritidis

1

2

Membranes Glass Microfiber Filters (2.7m)

Hollow fiber (CCR) (0.2 m)

Time for Filtration

Volume Applied

Volume Recovered

1 min

200 mL

~ 200 mL

60 min

~200 mL

~ 2.5 mL 2 X106 cfu/mL S. Enteritidis

*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. 24 LORRE, Laboratory of Renewable Resources Engineering

Testing 4TH Prototype Monoflow Maximum Sustainable Pressure

Membrane Fouling: Minimized, but still an issue

25 LORRE, Laboratory of Renewable Resources Engineering

Testing 4TH Prototype Monoflow 1st to 3rd Quartile Process Control

26 LORRE, Laboratory of Renewable Resources Engineering

Testing 4TH Prototype Dual Flow

27 LORRE, Laboratory of Renewable Resources Engineering

Testing 4TH Prototype Dual Flow

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Testing 4TH Prototype Flow rate

29 LORRE, Laboratory of Renewable Resources Engineering

WORK IN PROGRESS 1- Optimization of Pre- and Pos- Filtration Steps: Extension of membrane life time Membrane fouling : fats, oil, proteins Unsaturated fat triglyceride. (Troppocolaggen triple helix)

major obstacle hindering wide membrane applications Reduces Permeate flux; Shortens the membrane life; Increases the maintenance cost; Eventually add capital cost for replacement 30 LORRE, Laboratory of Renewable Resources Engineering

WORK IN PROGRESS Procedures to control membrane fouling 1- Pretreatment of feed; 2- Membrane modification; 3- Changes in operating parameters; 4- Using different cleaning techniques

Work in progress

PS: 2 and 3 are challenging once the membrane is installed Kimura et al. (2004). Water Research 38: 3431-3441 Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158 31 LORRE, Laboratory of Renewable Resources Engineering

Work in Progress 1- Optimization of Pre- and Post-Filtration Steps; 1.1 Pre-Filtration (1 min) : Glass microfiber (2.7 m) No loss of cells

Addition of one step using glass microfiber filter (1.6 m) 32 LORRE, Laboratory of Renewable Resources Engineering

Work in Progress 1.2 Post-Filtration Steps Macro cleaners (Ex: NaOH) Efficiency may be dependent on the transmembrane pressure;  Micro cleaners Enzymes (Lipases, Proteases) + Surfactants (Ex:Tweens) Literature: Enzyme used in combination with NaOH and citric acid = 90% removal of foulant in cross flow humic acid-fed ultrafiltration (Hollow fiber module –polysulfone membrane) Yu et al. (2010). Journal of Hazardous Materials 177: 1153-1158 33 LORRE, Laboratory of Renewable Resources Engineering

Work in Progress 2- Additional tests to confirm cleaning and sanitization of membranes for re-using;

 Exhaustive tests under progress to test efficiency of 70% (v/v) ethanol;  Alternatively 10% bleach may also to be tested for comparison.

34 LORRE, Laboratory of Renewable Resources Engineering

Work in Progress Testing 5th Prototype: New feature: smaller pumps were added to the instrument 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

35 LORRE, Laboratory of Renewable Resources Engineering

Work in Progress Further Optimization Work in Progress:  Addition and test of small diaphragm pumps;  Addition and test of level and turbidity sensors;  Modeling studies (for instance pressure and flow rate);  Optimization of pre-filtration and cleaning steps

36 LORRE, Laboratory of Renewable Resources Engineering

Applications Concentrate Cells (Salmonella sp, Listeria sp, E.coli sp) Against a Background of Microorganisms Identification by Different Methods Multifluidic Detection

Antibody PCR

Ramon Light Bacteriophage Spectroscopy Scattering Reporter

37 LORRE, Laboratory of Renewable Resources Engineering

Microfliudic Biochip Dielectrophoresis (DEP) = concentration of bacteria Immobilization of Antibody = specificity to capture target pathogen

Results in selective capture of target pathogen from background flora Flat silicon substrate 16μm tall micro channel PDMS cover Interdigitated electrodes LORRE, Laboratory of Renewable Resources •. Engineering

Schematic of the micro-fluidic biochip used for capture of bacteria using DEP (Yang, et al. 2006)

38

0

(a)

LORRE, Laboratory of Renewable Resources Engineering L.rhamnosus

3238

S. Seftenburg

S. Thompson

2

S. Berta

S. Schwarzengrund

0.5

S. Stanley

* 33 Salmonella serovars screened

S. Typhimurium PT NOS-3

2.5

S. Typhimurium PT NOS-1

AntiSE Average

C. perfringens

1 A490 nm

3238 Average

B. cereus

S. Kentucky S. Havana S. Anatum S. Mbandaka S. Seftenberg S. Litchfield S. Thomasville S. Brandenburg S. Poona S. Agona S. Gallinarum S. Rubislaw S. Pullorum S. Maarseen S. Arizonae S. Enteritidis PT 46 S. Cholerasuis S. Indiana S. Enteritidis PT 21 E. coli K12 S. Schottmuelleri S. Seftenburg E. coli 0157:H7 SCA 13753 S. Typhimurium var. S. Tennessee S. Typhi S. Heildeburg GFP E. coli

A450 nm 3

ELISA Testing of Anti-Salmonella Antibodies * AntiSE shows less cross reactivity with other related Enterobacteriaceae via ELISA 4

3.5 AntiSE

1.5 3

2.5 2

1.5 1

0.5 0

(b)

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

Antibody Coated Biochips with and without DEP A

B

Specific capture of Acridine orange stained Sal. Enteritidis PT-21 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.

S. Enteriditis on chips are stained with acridine orange

40 LORRE, Laboratory of Renewable Resources Engineering

Current and Future Work • Utilization of antibodies and/or ligands to preferentially capture specific serovars of Salmonella serovars. • On chip and off-chip PCR confirmation of target pathogen • Immobilization of ligands that will facilitate the specific capture and detection of Shiga toxin producing Escherichia coli. • Results obtained from biochip will be validated using standard USDA culture based assay procedure and multiplex PCR assay for three pathogens. • The long term goal of this project will be to develop an automated device for capture and detection of multiple pathogens (Kim and Bhunia, 2008) on one chip device and on-chip PCR • Confirmation/identification in eight hours or less. LORRE, Laboratory of Renewable Resources Engineering

41

Electronic Micro-fluidic Biochips for Detection of Bacteria 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.

42

Overall Approach Sample Prep Concentration

Detection/ ID

Data Analysis/ Results

Starting Sample

Sample 100 – 1000 ml

Automated Off-Chip Cell Concentration And Recovery - 1000X

~ 15 - 30 min

On-Chip Concentration 1000X

Electrical Detection of cell Growth

~ 30 min

~ 1- 3 hr

Electronic Biomolecular identification

~ 1- 3 hr

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

Integrated Chips for Detection of Microorganisms and Cells MEMS Filters

Lab-on-a-chip for Detection of Live Bacteria

70 0µ m

On-chip AbDielectro- based phoresis Capture

Micro-scale Temp/ On-Chip PCR Impedance Chem. (optical/ -mediated Meas. electrical)

Nanopore Sensors for DNA Detection

h

Glass cover Pin

In/Out ports

Cavities/ Wells

Epoxy adhesive

Filters Dielectrophoresis Filters an Traps for Biological Entities

Conc. Sorting

Trapping/Lysing of Bacteria/Viruses In Microfluidic Devices

Selective Capture

Culture/ Growth Detection

Nano-Mechanical Cantilever Sensors for Detection of Viruses

Cell Lysing

Genomic Detection

Silicon Nanowires and Nanoplates for DNA and Protein Detection

Micro-Mechanical Cantilevers for Detection of Spores

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

Bacterial Growth & Impedance Microbiology ! Owicki et al., Biosens. Bioelectron. (1992)

Oxygen Sugars

Other Processes

Cell Na+

Energy Metabolism

ATP

K+

Invented in late 1800s (Petri and Koch) Still the most widespread means to grow and detect the presence of bacteria !

CO2

Ion Channels

Lactic Acid Acetic Acid

phase Grow th

Time

Initial cell population (C0) [CFU/ml]

# of bacteria Lag phase

Carbonic Acid

Low number of bacteria in very small volume (in biochip!) can be detected much faster

1.E+07

Stationary phase

Z

H2 O

Na+

1.E+06 1.E+05

Low number of bacteria in large volume takes long time to detect

1.E+04 1.E+03 1.E+02 1.E+01 1.E+00

0

1

2

3

4

5

6

7

Detection hours Detectiontime Timein (arbit. units)

8

9

-

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

A Petri Dish-on-a-Chip Measurement electrodes

Micro fluidic Tubes PC board w. heater Edge Connector

Inlet 100µ

Outlet

BioChip

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

DEP capture electrodes 330µm

Bacterial Cell Concentration on-Chip • 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

Park, et al. Lab Chip, 2009

Lee, et al. Analytical Chemistry, 2009

On-Chip Incubation of L. monocytogenes On-Chip Incubation of L. innocua in LB Broth 7 -1 concentration: Fits Initial to incubation of L. innocua ~3x10 (~3x107 mlcfu/ml ) in TA4-B6

6

Magnitude []

10

Meas. (2) 10/16/02. Fit (8) 10/24/02 5

10

Dielectric capacitance

Measured Impedance

Cdi

Fitted circuit model 4

10

Electrolyte resistance

3

Angle [Degrees]

10 2 10 -10

3

5

10

-20

6

10

10

Zw

Time

-50 3

4

10

5

10 Frequency [Hz]

6

10

10 Ch. 2. Well WB2. 39C.

Growth

115% Growth

110%

Growth

105% 100% 95% 0

Rs Zw

Electrode-electrolyte interfaces

-40

1 cfu 9 cfu 34 cfu

120%

Zw 

-30

Approximate number of colony-forming-units (cfu) in a 5.27nl volume:

125%

Relative Conductance

4

10

-60 2 10

130%

ElectrodeElectrolyte Interface Model:

Time

2

4

6

8

10

12

Time [hours]

14

16

18

20

1 ( j ) n B

Constant-angle impedance

BioVitesse, Inc.

In-process Rapid Detection & Identification of Live Cells

• „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 Automated System Silicon Biochip

Chip Cartridge

CCRTM Cartridge 49 BioVitesse, Inc. Company Confidential

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

Z

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

Electrical Nature of DNA Molecules Thymine

Cap.=

k eA d

DNA polarization (dipole effect) Dielectric relaxation (Debye relaxation) : De e  e + with L(or #) 1 + j Cap.

Z

Counter Ion movement:

Rsol

Z

Baker-Javis et al., 1998

Bulk-EIS for Label free DNA detection 105

Z (ohm)

108#/µl; + DI Control 104

109#/µl 1010#/µl

103 500 bp dsDNA

102

1011#/µl

103

104

105

Frequency (Hz)

Z (ohm)

105

DI Control 100 bp

104

500 bp 1000 bp

103

109 #/µl dsDNA 102

103

104

105

Frequency (Hz)

DNA prepared by QIAquick Gel Extraction Kit, QIAGEN, Valencia, CA

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.

Label free DNA detection in PCR Reagents

6.00E+01 5.00E+01

1 µg

4.00E+01

1.00E+02

1e10 molecules/ul ion 1e9 molecuels/ul

1.00E+01

n

1e8 molecules/ul DI

0.05 TE 0.1 TE

0.5 TE 0.84 TE

A

D

N

co

tr ec n

at

% Change of Cdi

% Change of Cdi

1.00E+03

0.1 µg

3.00E+01 2.00E+01

control

1.00E+01 0.00E+00 -1.00E+01 0 -2.00E+01

5

10

15

20

25

30

0.01 µg

-3.00E+01

PCR cycles

Background solutions

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.

Label free DNA detection in PCR Solution 1 g starting concentration (3e8 cells / 25ul) prfA 508 bp segment target for specific detection of Listeria monocytogenes 5‟CGGGATAAAACCAAAACAATTT3‟ and R5‟TGAGCTATGTGCGATGCCACTT3‟ sample (PCR mix plus DNA template) control (PCR mix only)

Liu, et al. IEEE Sensors Conference, 2008 Liu, et al. Submitted, 2010

BioVitesse Silicon Chip Cartridge and DNA Measurements

Volume ~ 60nl

Metal 1 (wire bonds) Glass cover

55

Metal 1 (impedance)

Silicon substrate

100 bp dsDNA BioVitesse 60nl Chip Sensitivity 1E+08

0 -20

-60 Increasing Concentration

-80 -100

1E+06

-120

DI Reference 3.2e8 1.0e9 3.2e9 1.0e10 3.2e10 1.0e11

-140 -160

Increasing Concentration

1.5e11

1E+05 1

10

100

-180 10000

1000

Frequency (Hz)

|Z| @ 1kHz

100bp dsDNA BioVitesse 60nl Chip Sensitivity

θ @ 100Hz

Detection Limit ~ 1e10 molecules/ul

1.6E+06

0

1.4E+06

-10

1.2E+06

-20 DI Water Reference

1.0E+06

-30

8.0E+05

-40

6.0E+05

-50

4.0E+05

-60

2.0E+05

-70

0.0E+00 1E+08

1E+09

1E+10

DNA Concentration (molecules/ul)

1E+11

-80 1E+12

Phase (degrees)

0.1

Electrical Measurements of 100bp dsDNA in solution

Phase (degrees)

1E+07

Magnitude (ohms)

Magnitude (ohms)

-40

500 bp dsDNA BioVitesse 60nl Chip Sensitivity 1E+08

0 -20

-60 Increasing Concentration

-80 -100

1E+06

-120 DI Reference 3.2e8 1.0e9

-140

3.2e9 1.0e10 3.2e10 1.0e11

-160

Increasing Concentration

1E+05 1

10

100

-180 10000

1000

Frequency (Hz)

|Z| @ 1kHz

500bp dsDNA BioVitesse 60nl Chip Sensitivity

θ @ 100Hz

1.2E+06

0

-10 1.0E+06 -20

Detection Limit ~ 5e9 molecules/ul

8.0E+05

DI Water Reference

-30

6.0E+05

-40

-50 4.0E+05 -60 2.0E+05 -70

0.0E+00 1E+08

1E+09

1E+10

DNA Concentration (molecules/ul)

-80 1E+11

Phase (degrees)

0.1

Electrical Measurements of 500bp dsDNA in solution

Phase (degrees)

1E+07

Magnitude (ohms)

Magnitude (ohms)

-40

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)

• • • •

Electrodes on chip – droplets in Ionic Liquid Cell concentration: 106 ~ 107 cells/ml Droplet size100um diameter  ~ 5-10 cells Bulk impedance measurements

A cluster of bacteria Inside the droplet

100 µm

Before PCR cycling

After 30 cycles, 15 sec per thermal cycling step, total 1 hr.

200

% Change Cdi

• • • • •

With primer

150

ch1 and template

100

Without primer ch2 with template

50 0 0 cycle -50 -100 -150

10 cycle

20 cycle

25 cycle

30 cycle

30

Generation of Droplets in Viscous Fluids Weber Number (We)

We 

  density of the fluid   velocity

Parameterize droplet breakup processes when inertia and capillary pressure are more important than viscous stresses.

Capillary Number (Ca)

l  droplet diameter   surface tension

Ca 

More important than Weber Number for characterizing droplet formation in microfluidic device.

 2l 

 

  viscosity of the oil phase   velocity of the total flow rate   interfacia l tension between the oil and water

PBS (0.2 - 0.025 ul/min) vs [BMIM][PF6] (0.2 ul/min) 70

100 m

20 m

diameter

20 m

Metal electrodes

60

Ionic Liquid

gap 50

50 m

30 m

100 m

Size and gap (micron)

Droplets

40 PBS buffer or liquid with cells

30 20 10 0

0

2

4

6

8

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

10

Simulation of droplet formation using Lattice Boltzmann Method (LBM) Single droplet: experiment - simulation

Effect of Capillary number on droplet formation in a microchannel

Comparison between numerical and experimental results (Ca= 0.15)

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

Experimental result (Dr. Bashir's group, UIUC ) Ca=1.1e-2, Q1/Q2=5:1

Figure4:

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

Numerical result from LBM simulation Fan (OSU), Soorykumar (OSU), Bashir (UIUC)

Droplet encapsulation of cells via lattice Boltzmann simulation of two-phase flow Ca=6.5e-3, Q1/Q2=5:1

0s

0.1s

0.2s

0.3s

0.4s Fan (OSU), Soorykumar (OSU), Bashir (UIUC)

Ionic Liquids (ILs) Composed entirely of ions, but liquid at low temperature (