microfluidics and biosensors for point-of- care...

Microfluidics and Biosensors for Point-of-Care Diagnostics

Xuanhong Cheng

Materials Science and Engineering

Bioengineering Lehigh University

November 24, 2014

Basic Water Supply Microfluidics for Medicine

Micronit.com

Advantage of Microfluidic Systems

•  Small sample volume •  Small reagent volume •  Low production cost •  Portable, potential for integration and

automation •  High surface to volume ratio •  Laminar flow, predictable transport

property

POC Diagnostics

Master

Micro-scale Fabrication

CD4 Count

Time (years)

6 4 2

1000

200

WHO Stage 4 AIDS CD4 < 200 TB, infections Death ~18 months

WHO Stage 2 and 3: Symptomatic HIV infection CD4 200 - 500 Mild infections Weight loss, fatigue TB, Thrush

WHO Stage 1: Asymptomatic HIV infection CD4 >500

350

HIV Diagnostics

CD4

Viral load (HIV RNA level)

time Years Weeks

Begin ART

Impact of Treatment

Basic Water Supply Clinical Indicators

Years

Weeks

‘Viral load’

HIV RNA level

(copies/

mL plasma)

1 2 3 4 5 6 7 8

CD4 cell count

(cells/µL blood)

900

800

700

600

500

400

300

200

100

0

108

107

106

105

104

103

102

101

100

Basic Water Supply State of the Art Technologies

BD FACSCalibur

RT PCR

CD4-count start treatment < 200 cells/ul

Viral load count measure resistance to treatment

Basic Water Supply Lab Diagnostics in Resource Poor Settings

•  Low cost

•  Easy to use

•  Rapid and Robust

•  Portable

•  Sensitive and specific

What is Needed

Basic Water Supply Microchip Technology for Medicine

Portable CD4 Counter

K+ Cl-

Na+K+ K+

Cl-

Cl-

Cl-

Cheng, X. et. al, Lab on a Chip, 2007

Microfluidic Cell Counting Chip

Daktari Diagnostics Inc.

CD4 counting microchip

•  Controllable pore size •  High porosity •  Bio-functionality •  Tight pore size distribution •  Thin membranes

Nanoporous Membrane for Viral Processing and Sensing

PDMS  membrane  

Embedded Nanoporous Membranes for Virus Capture

Embedded Nanoporous Membranes for Virus Staining

Optically Forced Cytometry for Nanoparticle Counting

•  Significant in clinical diagnosis, biohazard surveillance, food safety monitoring, etc.

•  Contemporary approaches require laboratory access •  Electrical test can be fast, compact, sensitive and label free

Flow Cytometer Cell Staining Molecular Markers

Detection of Bacteria Viability

HP  Schwan  (1985):  Hypothesis  based  on  :ssue  measurement  

Frequency  (Hz)  

Dielectric  Con

stan

t  

Cond

uc:v

ity  (m

S/cm

)  

Cellular  Proper:es  

Subcellular  Proper:es  

Molecular  Proper:es  

Broadband Electrical Sensing

22  

Broad Band Electrical Sensing

Syringe  Pump   Inverted    

Microscope  

Signal  Generator  

Network    Analyzer  

High-­‐Speed  Oscilloscope  

Micro-­‐  Chamber  

Cells In

RF In

Experimental Setup

Cells  In  

RF  In  

RF  Connector  

Cells  in  μ-­‐Chamber  

RF  Connector  

Transmission  

Input  

Reflec2on  

Sample  Volume  =  20  cubes  of  10μm×10  μm×10  μm  

Modeling to Extract Cell Information

Cell Immobilized by Dielectrophoresis

0  

0.5  

1  

1.5  

2  

0   5   10   15   20  

S 11  D

isp.  (1

0−10   dB/Hz

)  

No.  of  Cells  Trapped  

S11    Live  

S11  Dead  

Differentiating Live vs Dead HEK Cells

0  

0.25  

0.5  

0.75  

1  

0   5   10   15   20  

S 11  D

isp.  (1

0−10   dB/Hz

)  

No.  of  Cells  Trapped  

S11  Dead  Jurkat    

S11  Dead  HEK    

HEK   Jurkat  

Differentiating Dead HEK and Jurkat Cells

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0 0 500 1000 1500 2000

aver

age

delta

S11

(dB

) Number of bacteria

Live

Dead

Differentiating Live and Dead E. coli

0  0.2  0.4  0.6  0.8  1  

1.2  1.4  1.6  

0.01   1   100  Ab

sorban

ce    

Log  scale  Conduc:vity  (mS)  

CM1  19  h  

LB  19h  

Culture    

Biofilm Monitoring on a Chip

Next Steps •  Monitor biofilm growth on

chip •  Screen anti-biofilm reagents

Acknowledgments

Collaborators  Fil  Bartoli  Arthur  Chiou  (Yangming  U,  Taiwan)  Tim  Friel  (LVHN)  MarJn  Hirsch  (MGH)  Jim  Hwang  Jim  Gilchrist  Sabrina  Jedlicka  Yaling  Liu  Alp  Oztakin  Daniel  Ouyang  William  Rodriguez  (MGH)  Olga  LaJnovic  (IHV)  Peikuen  Wei  (Academia  Sinica,  Taiwan)  Frank  Zhang  

Students  Caroline  Multari  Krissada  Surawathanawises  Bu  Wang  Chao  Zhao  

•  Controllable pore size •  High porosity •  Bio-functionality •  Tight pore size distribution •  Thin membranes

Nanoporous Membrane for Viral Processing and Sensing

Embedded Nanoporous Membranes for Viral Processing

Perc

enta

ge o

f Viri

ons

(%)

0

20

40

60

80

100

120

200nm Pores 20nm Pores

Filtrate

Absorbed on membrane

Suspended above membrane

Vira

l Con

cent

ratio

n (/m

L)

0

2e+7

4e+7

6e+7

8e+7

Original Sample 1mL filtration + 10µL Wash

% o

f Viri

ons

Cap

ture

d on

Mem

bran

es

0

10

20

30

40

50

60

70

Bare PEG

AntiCD44

Community-based Care

Care takes place in the community. Reinforced in the

clinic.