Senior Design 2010-2011

Point-of-care diagnostic device for monitoring CD4 levels of HIV patients in resource-poor settings

Lina M. AboulmounaPeter F. DelNeroParker A. GouldRosalynne R. KormanChristopher M. Madison Stephen R. Schumacher

Advisor: Dr. Kevin T. Seale

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Abstract

The goal of this project is to design a point-of-care device that quickly and cost-effectively

determines the CD4 count of an HIV-positive patient. This count is essential in determining a

patient’s suitability for antiretroviral treatment. The device is comprised of a microfluidic

platform for immunology and cell trap-based separation of white blood cells, coupled with a

CCD camera to capture and quantify fluorescent signals from tagged CD4 cells. This device is

designed to facilitate a simple, quick diagnosis of a patient’s stage in the HIV/AIDS progression,

which is crucial in the resource-poor medical setting found in many developing countries. The

design parameters include a per-test cost of under $2, minimal power requirements, simple

operation by minimally-trained technicians, and same-day test results. The motivation for this

project stems from the Gates Foundation CD4 Initiative for a low-cost, point-of-care device to

replace flow cytometry for accurate CD4 cell counting in under-developed regions.

Introduction

Acquired immunodeficiency syndrome (AIDS) is a disease caused by the human

immunodeficiency virus (HIV). Not everyone who is HIV-positive has AIDS; only when HIV

has depleted CD4 T helper lymphocytes beyond the given threshold of 200 cells per microliter of

whole blood is the patient considered to have AIDS. There is an inverse relationship between the

replication of HIV-1 and the destruction of lymphocytes. As HIV progresses, more and more

HIV-1 RNA circulates in the bloodstream while fewer and fewer CD4 cells are left. CD4

lymphocyte counts are predictive of progression to AIDS and, eventually, death.1

1 O’Brien, WA, Hartigan, PM, Daar, ES, Simberkoff, MS, and Hamilton, JD. Changes in plasma HIV RNA levels and CD4þ lymphocyte counts predict both response to antiretroviral therapy and therapeutic failure, VA Cooperative Study Group on AIDS. Ann Intern Med 126: 939–945 (1997).

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The World Health Organization has declared finding an affordable and effective way to obtain

CD4 lymphocyte counts in resource poor areas a high priority.2 Similarly, the Gates Foundation

has identified low-cost HIV diagnostics as one of its Grand Challenges in Global Health.3 CD4

counts provide important information to an attending physician on the current stage of the

disease, when to initiate antiretroviral treatment, how the patient is responding to treatment, and

when to consider modifying the current treatment regimen. Flow cytometry is the traditional

method for obtaining CD4 counts. However, flow cytometry is generally limited to developed

countries because of its requirements of expensive instrumentation and a trained staff.4 Lacking

the financial and technical means to obtain these CD4 counts, HIV/AIDS treatment in poor

countries is often started too soon or too late, which can result in poor clinical outcomes,

unnecessary burdens on the patient, and imprudent or inefficient use of the limited resources

available.

Along with other signs and symptoms, CD4 lymphocyte counts are used to stage the progression

of HIV infection according to standards set by the Centers for Disease Control and Prevention

(CDC). Patients with HIV who have CD4 counts above 500 cells/µL are in stage 1 infection,

CD4 counts between 500 cells/µL and 200 cells/µL are in stage 2, and CD4 counts of 200

cells/µL and below are in stage 3 and are classified as having AIDS.5

Both the World Health Organization (WHO) and the CDC recognize the importance of CD4

counts in deciding when to initiate antiretroviral treatments and when to adjust treatments. These

2 http://www.who.int/hiv/pub/guidelines/artadultguidelines.pdf3 http://www.nature.com/nm/journal/v13/n10/full/nm1007-1131.html4 Rodriguez, WR, et al. A Microchip CD4 Counting Method for HIV Monitoring in Resource-Poor Settings, PLoS Medicine, July 2005, Volume 2, Issue 7.5 http://www.aids-ed.org/aidsetc?page=cm-105_disease#S1X

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organizations have provided guidelines for making these decisions based on the CD4 count for a

particular patient.6

There are other methods of quantifying the progression of HIV and AIDS, such as CD4/CD8

ratios and nucleic acid amplification tests. Based on the CDC’s standards for the stages of HIV

and AIDS, as well the work of others in the field, we have decided to focus this project on

obtaining accurate CD4 counts.

History and Context

Previous work

Rodriguez et al. previously fabricated a microchip similar to our proposed device for HIV

diagnostics.4 However, our device differs significantly in the manner by which a whole blood

sample is tagged and filtered. Also, due to the pumping mechanism we have utilized, our device

is significantly less expensive to fabricate and use.

Methodology

Microfabrication of device components

Two microfluidic platforms connected by PEEK tubing (150µm inner diameter, 360µm outer

diameter) comprise the HIV test platform. These components are fabricated by PDMS soft

lithography using an SU-8 mold according to protocols developed at the Vanderbilt Institute for

Integrative Biosystems Research and Education (VIIBRE). The protocol is briefly outlined

below, and in Figure 1. The microfluidic device patterns were designed using Autodesk’s

AutoCAD software package. These patterns were reproduced to scale by selectively etching a 6 http://www.who.int/hiv/pub/guidelines/artadultguidelines.pdf

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chrome-plated glass mask. Master molds were then fabricated on three-inch silicon wafers using

MicroChem SU-8 photoresist and the chrome masks, in accordance with the standard

photolithographic protocol practiced in the VIIBRE cleanrooms. Sylgard 184 PDMS (Dow-

Corning) prepolymer was mixed with the corresponding curing agent at a 10:1 mass ratio, cast

onto the mold, degassed in a vacuum chamber for 20 minutes, and then cured at 70°C for four

hours. The PDMS was then carefully peeled from the mold and inlet/outlet holes were punched

using sharpened Luer-Lock syringe tips.

Figure 1: Step-by-step procedures for photolithography and replica molding.

The patterned PDMS and a glass coverslip were then exposed to an oxygen plasma for 30

seconds, and then placed in contact with one another, causing a hydrolysis reaction and a

permanent bond between the PDMS and glass. The microfluidic peristaltic pump was fabricated

using a similar replica molding-based protocol. An SU-8 patterned silicon wafer was spun with

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a thin layer of uncured PDMS, and then cured cubes of PDMS were placed above the inlet/outlet

hole patterns. These cubes serve to provide structural stability for the inlet/outlet tubing

connections. This two-layer PDMS device was then allowed to cure at 70°C for 4 hours, along

with a flat, unpatterned, 1 mm thick layer of PDMS in a separate petri dish. After curing, the

two-layer patterned PDMS device (both layers now sealed together) was removed from the

silicon master, and inlet/outlet holes were punched. The device was then bonded to the

concurrently prepared 1 mm thick layer of PDMS using an oxygen plasma.

Blood Sample Preparation

Whole blood samples were acquired via finger stick from volunteers using the procedure

established by the Vanderbilt University Institutional Review Board. Samples were obtained

using a standard CVS brand finger-stick device. A 75 mm Fischer microhematocrit tube was

used to collect approximately 35L of whole blood. Whole blood was aspirated directly from the

hematocrit tube into the device through PEEK tubing.

Pumping

The peristaltic pump operates by compressing a microfluidic track with ring of ball bearings. The

motor is automatically controlled through a microchip using Arduino software. The pump is also

capable of manual control by rotating the shaft. The flow rate is determined by the diameter of

the microfluidic track, which can be tailored to optimize sample loading.

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Figure 2: Hand-crankable peristaltic pump. A novel microfluidic pump was designed which allows manual pumping of inputs through the device. The pump’s rotation forces fluid through the device, and

the hand-crank mechanism allows for the pump to be operated with no electrical power input. The device is composed of inlet ports for the various inputs, mixer elements to insure proper mixing, and the circular

array of channels to allow pump action.

White blood cell trapping

White blood cells were captured using a trap device developed in SyBBURE/VIIBRE. Cells are

captured in the array of U-shaped traps as demonstrated in Figure 3. While red blood cells are

small and flexible enough to squeeze through the gaps in each trap, white blood cells remain

confined. The downstream flow prevents cells from escaping. In order to extract the maximum

number of cells from a volume of blood, the outlet tube was connected to the inlet port and the

sample was recirculated through the device.

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Figure 3: Microfluidic trap device. An array of U-shaped structures captures cells as they flow through the device. (Inset) Magnified diagram is of a cell trap containing two cells (green). Inset by K. Seale.

Fluorescent CD4 labeling with FITC

FITC-conjugated CD4 antibodies were used to label both CD4 Jurkat T lymphocytes and CD4

cells from whole blood. Cells were captured in the trap device, after which fluorescent antibodies

were pumped through. Finally, the traps were rinsed with PBS solution to remove excess

antibodies. Fluorescent images were captured using a Zeiss microscope equipped with a FITC

filter. Off-chip labeling was accomplished by mixing antibody solution in a 1:5 ratio with cells

and incubating for 30 minutes prior to loading the trap chambers.

Time-resolved fluorescent imaging

Latex beads containing europium were conjugated to anti-CD4 antibodies according to the

protocol developed with the aid of Dr. Robert Buck of Gauge Scientific:

1. Suspend antibodies and CMEUs (carboxylate-modified europium nanoparticles) at 30 g

IgG/mg CMEU in the coating buffer: 10mM NaPO4 pH 8.0 .

2. Allow the antibodies to coat the CMEUs for 1-2 hours, with gentle shaking.

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3. After the coating, spin down the CMEUs, remove supernatant, and resuspend in blocking

buffer: either 10 mg/ml BSA in buffer, or 5% PEG in buffer.

4. Wash 2 or 3 times:  Spin down the CMEUs at 10,000-12000g, remove supernatant,

resuspend in blocking buffer.

5. Spin down CMEUs, remove supernatant, resuspend in Conjugate Dilution Buffer

(obtained from Gauge Scientific).

The Vanderbilt Reader, purchased from Gauge Scientific and shown in Figure 4, enables

microsecond resolution of digital image acquisition, allowing autofluorescent noise to diminish

before collecting images of the europium signal, as shown in Figure 5.

Figure 4: The Vanderbilt Reader. A portable, point-of-care time resolved fluorescence (TRF) platform. This imaging device connects to a laptop via a USB connection.

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Figure 5: TRF imaging generates a fluorescent excitation but does not capture an image until after a short time delay. This time delay allows cellular auto-fluorescence and background fluorescence (blue line) to decay to minimal levels, while the fluorescence from europium nanoparticles (red line) remains strong.

Results and Discussion

The microfluidic peristaltic pump was able to induce precise and reliable flow rates in the cell

trap device. Manual operation was capable of controlling nanoliter volumes. Each revolution of

the bearing yields approximately 200 nL of flow. In addition, the feasibility of direct trap loading

and cell labeling on chip via aspiration of whole blood directly from a microhematocrit tube was

confirmed experimentally: this result is summarized in Figure 6. This ability to perform all of

the required mixing on chip represents a significant reduction in the difficulty of operation,

thereby eliminating the need for pipets and trained technicians. By rinsing the pump device with

buffer solution (and replacing the cell trap device), a second test can be performed immediately

using the same blood sample. A second test provides significant confirmation to the outcome of

the first test, which allows for more confident diagnosis. Flushing the pump with ethanol

immediately prepares the device for the next patient.

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Figure 6: FITC-CD4 antibodies identify CD4 cells in whole blood. Although the CD4 cells are initially indistinguishable in a sea of red blood cells (A), they become discrete when illuminated with fluorescence

(B). As whole blood is flowed through the device, red blood cells pass through while some white blood cells are trapped. DIC (C) and FITC (D) images were taken at t = 0 sec, 6 sec, and 6 min. FITC images were thresholded (E) and overlayed on top of the corresponding DIC images (F). The number of trapped

CD4 cells increases over time from 1 to 2 to 4, suggesting that the number of trapped CD4 cells will continue to increase as the whole blood is recirculated through the device.

The multitrap nanophysiometer captured white blood cells (WBC) from whole blood.

Recirculation of the blood helps to increase the cell trapping efficiency, which is crucial to

producing a reliable diagnosis of CD4 cells per microliter. Fluorescent microscopy images show

accumulation of CD4 cells over time in a localized field of view due to trapping, as seen in

Figure 6. Alternative trap layouts with increased density and offset patterning were fabricated on

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chrome masks to optimize WBC capture. The trap device is disposable and affordable, costing

approximately $0.15 per chip.

On-chip fluorescent labeling of WBCs from whole blood samples was performed with FITC-

conjugated anti-CD4 antibodies. Images were acquired from the Zeiss optical microscope and

the ImageJ software suite was used for image analysis: several representative images are

displayed in Figure 7. The labeling demonstrated selective binding to CD4 cells in whole blood

with significant signal output after rinsing with buffer. This demonstrated that the only manual

sample preparation required will be the original finger prick and loading a new trap device.

Figure 7: CD4 cells can be labeled on chip. FITC-CD4 antibodies were flowed into a device containing Jurkat T cells. The excess antibodies were rinsed from the device, revealing the presence of newly-labeled

CD4 Jurkat cells. A series of fluorescent pictures (A) is given, as well as the overlay of the fluorescent and DIC images (B). This is proof of concept that CD4 cells can be labeled on chip.

Attempted conjugation of anti-CD4 antibodies to carboxylate-modified europium chelate

nanoparticles did not yield detectable binding to CD4 cells. A reliable conjugation and labeling

protocol has been investigated in collaboration with Dr. Buck of Gauge Scientific and Dr. Jay

Dickerson of the Vanderbilt Physics Department. The detection threshold using the Vanderbilt

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1:1001:501:251:101:1

Reader portable TRF device was approximately 1:25 dilution from the original nanoparticle

concentration (1% solids). These detection threshold test images are displayed in Figure 8.

Figure 8: TRF images of cell traps. Europium nanoparticles were pumped into a trap array, and a TRF images were taken. This figure demonstrates that europium phosphorescence can be detected at dilutions

as low as 1:25. Also, the resolution of the TRF image was high enough to illustrate the microscale structure of the trap array, which promises to aid diagnosis by allowing trap-by-trap image analysis

instead of less precise macroscale analysis.

Healthy and immuno-suppressed data were simulated by combining measurements from the

FITC-labeled whole blood with accepted concentrations of CD4 lymphocytes. Cell size and

signal intensity data were used to calculate the relative signal ratio in healthy versus diseased

patients. The absolute quantification of CD4 cells per microliter of blood is a function of the total

signal intensity in the Vanderbilt Reader and the fraction of CD4 cells captured during

recirculation. The signal intensity of the europium-chelate nanoparticles was used to estimate a

minimum threshold of trapped cells needed to obtain a detectable signal in the Vanderbilt

Reader, and from this threshold the minimum number of recirculation passes was calculated.

Assuming the europium fluorescence of a particular labeled cell is equivalent to the fluorescent

intensity observed in the device from the conjugated europium solution, calculations suggest that

6.8% of the device area must be illuminated to reach the detection threshold. However, this

assumption depends on the concentration of CD4 receptors on the lymphocytes, which must be

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determined experimentally with europium conjugated particles. According to these results,

approximately 22700 cells must be captured; a finger-stick equivalent of 40% of CD4 WBCs in

healthy patients and 150-250% in an AIDS patients. Therefore, unless the actual signal strength

of europium-labeled cells is higher than the original diluted signal, a magnifying lens of at least

10x power should be added to the TRF detection system.

Detection Threshold Calculations

We performed a theoretical analysis of the fluorescent behavior of cells the trap device. The

variables defined below are used in Equation 1.

s = number of pixels in the field of view (FOV) of the image of the trap device n = number of white blood cells in FOV n+ = number of CD4 cells in FOV f+ = fraction of white blood cells that are CD4 p = number of pixels that are lit due to fluorescence of a single tagged CD4 cell l = fraction of FOV that is illuminated

The total number of pixels in FOV that are lit is given by (n+)(p), which is equal to (f+)(n)(p).

Therefore, the luminance l is given by Equation 1

l=f +¿np

s¿ (1)

This value is exact if the cells in the trap device can be resolved by the imaging device (i.e. a

single cell’s size is multiple pixels, or, more precisely, the fluorescence of a tagged cell is

multiple pixels). However, this resolution constraint requires a powerful microscope and is

therefore unsuitable for a point-of-care product. Another analysis, based on the illumination of

the device as a whole, is needed. For this analysis, we define the following variables.

H = height of the trap chamber A = area of the trap chamber (as viewed from above) V = volume of the trap chamber Ac = area of the trap chamber occupied by CD4 cells (as viewed from above)

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ac = cross-sectional area of a CD4 cell N+ = total number of CD4+cells trapped in the trap chamber

Using these variables, we can define the macroscopic luminance as

lm=Ac

A=ac

N +¿

A¿ (2)

Finally, assuming that during a test, we flow in enough blood to exactly fill the trap chamber,

then the CD4 count is exactly N+/V, i.e. the number of CD4 cells per volume of blood. But N+ is

equal to Ac/ac, and V is equal to the area of the trap chamber times its height. Therefore, the CD4

count is given by

N +¿

V=

A c

ac HA=

lm

ac H¿ (3)

Then, since the average cross-sectional area of a CD4 cell is about 40 µm2,7 and the height of the

trap chamber is set by the production process (typically between 11 and 15 m) all that is

required to determine the CD4 count is a measurement of the luminance.

However, this macroscopic luminance is no longer an exact, pixel-by-pixel value. A correlation

between the microscopic luminance l and the macroscopic luminance lm is necessary. In order to

accomplish this, experiments are needed which measure the two luminances from a single trap

device to calibrate the macroscopic luminance to its microscopic counterpart.

A final consideration concerning the detection of CD4 cells in this device is how to achieve the

requisite concentration of cells in the trap chamber for the imaging device to make a reliable

measurement of the CD4 count in a sample. Our initial experiments suggest that it is necessary to

recirculate the blood sample through the trap device in order to reach a high enough

concentration of cells. Once again, we define variables for analysis of recirculation:

7 Abbas AK and Lichtman AH (2003). Cellular and Molecular Immunology (5th ed.). Saunders, Philadelphia. ISBN 0-7216-0008-5.

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Vs = volume of whole blood sample Nt,i = number of CD4 cells remaining in the whole blood sample at the

beginning of the sample’s ith pass through the trap Nr,i = number of CD4 cells captured in the trap after the sample’s ith pass

through the trap fi = fraction of entering CD4 cells which were captured on pass i

Using the definitions of fi, Nt,i, and Nr,i, we can write a recursive equation for fi:

f i=N r , i

N t ,i−1−N r ,i−1=

N r ,i

N t , i−1−N t , i−1 f i−1=

N r ,i

N t , i−1(1−f i−1)

(4)

Next, assuming that the trap fraction fi is approximately constant—i.e. that trapping cells does

not significantly affect the trap’s performance—then fi = fi-1 = f. Performing the recursion of

Equation 4 yields

f (1−f )i−1=N r , i

N t ,1(5)

The total number of CD4 cells trapped after n passes of the sample through the device is the sum

of the cells trapped by each pass.

N trapped=∑i=1

n

N r , i=¿∑i=1

n

N t ,1 f (1−f )i−1=N t ,1(1−(1−f )n)¿ (6)

Modifying Equation 2 so that that N+ is replaced by the total number of cells trapped, we can

relate the macroscopic luminance to the right-side of Equation 6:

N t ,1 (1−(1−f )n )= A lm

ac(7)

Rearranging yields

N t , 1

V s=

A lm

ac V s (1− (1−f )n )

(8)

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Therefore, the CD4 cell count of a sample of blood is given in terms of the area of the trap

chamber (A), the cross-sectional area of a CD4+ cell (ac), the trapping efficiency of the device

(f), the number of recirculation passes (n), and the macroscopic luminance (lm). A and ac are

known quantities, n is determined by the duration of recirculation, lm is measured by the

experiment, leaving only f to be determined experimentally. It seems plausible that f is

approximately constant, but only for small values of n.

Cost Considerations

The cost of the CD4 counter per test is given by the detailed breakdown presented in Table 2.

Table 2: Cost analysis of the point-of-care diagnostic device

Item Amount Capital Cost Cost per testPDMS base and curing agent Sylgard 184

3g $0.31 $0.31

Anti-CD4 antibodies .3ug $ 0.14 $0.14Europium nanoparticles 10uL $1.07 $1.07Glass Slides 1 $0.12 $0.12

PEEK tubing 20cm $0.40 $0.04Photolithography (500k tests) 1 $10 $0.01Pump (500k tests) 1 $60 $0.01TRF Reader (500k tests) 1 $1020 $0.01Total -- $1,092 $1.71

Note that the PDMS base and curing agent are used in the making of the trap device as well as

the pump. The costs of photolithography, the pump (motor and controls), and the TRF reader

become negligible when their capital costs are divided by the number of tests they are expected

to last: we estimate this to be about 500,000 tests. The price of the TRF reader estimated here is

for a production model, rather than the prototype model used in this project.

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Conclusions, Recommendations, and Future Directions

Significant progress toward a functional prototype for a point-of-care HIV diagnostic system has

been accomplished. All of the components of the device were designed, fabricated, and tested for

application in CD4 counting from whole blood samples. Thus far, protocols for microfluidic

pumping and recirculation, white blood cell trapping, on-chip fluorescent labeling of whole

blood, and time-resolved fluorescent imaging with europium nanoparticles have been developed.

With the exception of the TRF reader, current results indicate that each component of the point-

of-care system is capable of meeting the design criteria proposed for a point-of-care diagnostic

instrument as an affordable alternative to clinical blood testing in low-resource settings.

Conjugation of europium nanoparticles to anti-CD4 antibodies and subsequent TRF analysis of

whole blood remain the final steps for direct point-of-care application. Based on calibration

images of nanoparticle solutions, this step may prove challenging with the current detection

system. Assuming the europium fluorescence of a particular labeled cell is equivalent to the

fluorescent intensity observed in the device from the conjugated europium solution, calculations

suggest that 6.8% of the device area should be illuminated to reach the detection threshold.

However, this assumption depends on the concentration of CD4 receptors on the lymphocytes,

which must be determined experimentally with europium conjugated particles. According to

these results, approximately 22700 cells must be captured; a finger-stick equivalent of 40% of

CD4 WBCs in healthy patients and 150-250% in an AIDS patients. Therefore, unless the actual

signal strength of europium-labeled cells is higher than the original diluted signal, a magnifying

lens of at least 10x power should be added to the TRF detection system. Alternative methods for

higher density WBC trapping have been proposed for future investigation but may still be

insufficient for TRF detection.

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With an expected price of $1.71 per test, this platform is anticipated to match the target of $2 per

test stipulated by global health initiatives like the Gates Foundation Challenge. Non-recurring

engineering costs of the prototype system were distributed across their expected lifetime as

shown in Table 2. Reagents and disposable trap cartridges comprised the majority of the cost per

test.

The only sample preparation step is the initial loading of the blood into the PEEK tubing.

Ultimately, operation with Lab-View and ImageJ will enable automated on-chip labeling and

image processing capabilities. The disposable trap cartridge with a re-useable pump and imaging

system is ideal for facile, affordable, point-of-care application. By containing hazardous

biological samples on-chip, disposal of used chips becomes the only device-specific safety

concern. Peripheral considerations for implementation of this diagnostic tool must be addressed.

These include transportation and storage of antibodies, disposal of finger-pricks and used

cartridges, and availability of reagents and finger-sticks.

Once a complete working TRF prototype has been fabricated, the device’s ability to measure

CD4 counts must be tested against conventional techniques like flow cytometry (R = 0.9).

Because the test affords immediate, facile test replication, the precision can be reduced to

R = 0.7 with a double positive as a clear diagnosis.

Acknowledgements

Our special thanks go to our project mentors Professor Kevin Seale and Professor John Wikswo,

of the Vanderbilt Institute for Integrative Biosystems Research and Education, for their efforts to

guide our work. In addition, we extend our sincere gratitude to Dan Morrow and Dr. Bob Buck

of Gauge Scientific for providing their technical expertise in time-resolved fluorescent imaging.

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We also thank Loi Hoang for his help with pump operation and troubleshooting. Finally, we

thank Professor Paul King for his feedback and guidance in completing our project.