The Pennsylvania State University

The Graduate School

Department of Chemistry

MICROFLUIDIC SYSTEMS FOR HIGH-THROUGHPUT SINGLE-

CELL ASSAYS

A Dissertation in

Chemistry

by

Michael F. Santillo

© 2009 Michael F. Santillo

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

December 2009

The dissertation of Michael F. Santillo was reviewed and approved* by the following: Andrew G. Ewing Professor of Chemistry Professor of Neural and Behavioral Sciences J. Lloyd Huck Chair in Natural Sciences Dissertation Adviser Chair of Committee Philip C. Bevilacqua Professor of Chemistry Thomas E. Mallouk DuPont Professor of Materials Chemistry and Physics Andrew L. Zydney Walter L. Robb Chair and Professor of Chemical Engineering Barbara J. Garrison Shapiro Professor of Chemistry Head of the Department of Chemistry

* Signatures are on file in the Graduate School

ii

Abstract

Microfluidic devices have recently emerged as useful tools for performing biological and

cellular assays. Compared to conventional assays, microfluidic technology has several

advantages including the consumption of small sample volumes and ability to integrate multiple

steps of an analysis into a single system. Furthermore, microfluidic systems can be automated

and perform assays in a high-throughput fashion, resulting in faster analysis times and collection

of data on the single cell level. In this dissertation applications of microfluidic systems for

performing cell-based assays are demonstrated. In the second chapter, a device for monitoring

changes in intercellular connectivity in an in vitro neuronal network was fabricated and the fluid

flow characterized via confocal microscopy, simulations, and amperometry. This system

exploits laminar flow and hydrodynamic focusing, allowing individual cells in specific locations

to be addressed with pharmacological agents while imaging is performed on the cells in the

network. Lysis of a non-pathogenic amoeba, Arcella vulgaris, was monitored on a microfluidic

platform and described in the third chapter. This device allows multiple cells to be observed

simultaneously after exposure to constant, controlled flow of chemical biocides. The data

obtained shows that single cell lysis events are much different from an average value obtained

from a cell population, and the efficacy of several detergents and biocides was compared. In the

fourth chapter, computational fluid dynamics simulations were used to develop amperometric

detection schemes for microchip electrophoresis. A novel technique for fabricating microfluidic

devices was explored in the fifth chapter in which tape was used as a master mold to fabricate

two PDMS micromixers. The fabrication scheme is easy to perform and allows microfluidic

technology to be adapted without the use of cleanrooms and photolithography. In the sixth

chapter, a microfluidic system for high-throughput exposure of PC12 cells was used to quantify

reactive oxygen species in response to neurotoxins. The device contains a passive mixer and an

array of cell traps that isolate cells and simplify multiplexed fluorescence imaging.

iii

Table of contents

List of figures ................................................................................................................................. vi Preface .......................................................................................................................................... viii Acknowledgements ........................................................................................................................ ix Chapter 1. Introduction to microfluidic technology for cell assays .........................................1 Miniaturization in analytical chemistry ...........................................................................................1 Physics of fluid flow on the microscale ...........................................................................................2 Microfluidic device fabrication ........................................................................................................5 Conventional techniques for exposing and analyzing cells .............................................................8 Applications demonstrating advantages of microfluidics ..............................................................12 Dissertation goals and overview ....................................................................................................23 Conclusions ....................................................................................................................................24 References ......................................................................................................................................25 Chapter 2. Flow characterization of a microfluidic device to selectively and reliably apply reagents to a cellular network .....................................................................................................34 Introduction ....................................................................................................................................34 Procedure .......................................................................................................................................35 Results and discussion ...................................................................................................................38 Conclusions ....................................................................................................................................44 References ......................................................................................................................................45 Chapter 3. Temporal analysis of protozoan lysis in a microfluidic device ............................47 Introduction ....................................................................................................................................47 Procedure .......................................................................................................................................49 Results and discussion ...................................................................................................................52 Conclusions ....................................................................................................................................61 References ......................................................................................................................................62 Chapter 4. Computational modeling of electrochemical detection on microfluidic chips ...65 Introduction ....................................................................................................................................65 Procedure .......................................................................................................................................67 Results and discussion ...................................................................................................................69 Conclusions ....................................................................................................................................77 References ......................................................................................................................................78 Chapter 5. Fabrication of PDMS microfluidic mixers with tape-based molds .....................80 Introduction ....................................................................................................................................80 Procedure .......................................................................................................................................81 Results and discussion ...................................................................................................................84

iv

Conclusions ....................................................................................................................................91 References ......................................................................................................................................93 Chapter 6. High-throughput analysis of reactive oxide species in PC12 cells .......................98 Introduction ....................................................................................................................................98 Procedure .......................................................................................................................................99 Results and discussion .................................................................................................................101 Conclusions ..................................................................................................................................107 References ....................................................................................................................................108 Chapter 7. Future directions for using microfluidic systems to investigate communication between cells within an in vitro neural network .....................................................................109 Cells and patterning .....................................................................................................................109 Analytical techniques ...................................................................................................................111 Pharmacological investigations related to Parkinson’s disease ...................................................113 References ....................................................................................................................................116

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List of figures

Figure 1.1. Simulations illustrating the effects of convection and diffusion on lateral mixing across two channels..........................................................................................................................4 Figure 1.2. Fabrication of a microfluidic device via photolithography and soft lithography ........7 Figure 1.3. Pseudocolored fluorescence image time series of FITC puffed from micropipette ..10 Figure 1.4. Partial treatment of cells and embryos with laminar flow .........................................14 Figure 1.5. High-throughput cell assays with microfluidic systems ............................................17 Figure 1.6. Microfluidic cell culture systems ..............................................................................20 Figure 1.7. Microfluidic gradient systems ...................................................................................22 Figure 2.1. Fabrication scheme for making the complete microfluidic device ............................36 Figure 2.2. Fluorescence microscopy images of a stream of FITC exiting a pharmacological channel outlet hole and being directed by bulk flow of water .......................................................39 Figure 2.3. CFD simulations and confocal microscopy of fluid flow profiles ............................41 Figure 2.4. CFD simulations and amperometry of fluid flow profiles ........................................43 Figure 3.1. Microfluidic device assembly and image of cells in the device ................................51 Figure 3.2. CFD simulation of linear flow velocity in the device ...............................................54 Figure 3.3. Fluorescence images and plot of Arcella exposed to benzalkonium chloride over time ................................................................................................................................................56 Figure 3.4. Plots of decay and lysis onset times of Arcella exposed to benzalkonium chloride at various flow rates and concentrations ............................................................................................58 Figure 3.5. Comparison of decay and lysis onset times for a variety of biocidal agents .............60 Figure 4.1. Steps in computational modeling ..............................................................................68 Figure 4.2. Hybrid capillary-microfluidic device for separation, lysis, and quantification of vesicles and concentration profiles ................................................................................................71 Figure 4.3. Illustration of the microfluidic device for coulometrically efficient detection .........73

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Figure 4.4. Coulometric efficiency calculations from simulations ..............................................75 Figure 5.1. Fabrication schemes ..................................................................................................82 Figure 5.2. SEM images of tape molds ........................................................................................86 Figure 5.3. Optical images of micromixers and straight channels ...............................................88 Figure 5.4. Performance characteristics of the semicircular barrier micromixer .........................89 Figure 5.5. Performance characteristics of the sawtooth micromixer ..........................................92 Figure 6.1. Diagram of the device and image of trapped cells ..................................................102 Figure 6.2. Mixing characterization images and plot of concentration in each channel ............104 Figure 6.3. Comparison of 6-hydroxydopamine and isotonic saline on PC12 cells ...................106 Figure 7.1. Selective lysis of PC12 cells ....................................................................................110 Figure 7.2. Top view of the microfluidic device for proposed studies of neural network communication .............................................................................................................................112

vii

Preface

The contents of Chapter 2 were adapted with permission from MF Santillo, IG Arcibal, AG Ewing, Lab Chip 2007, 7, 1212-1215. [doi:10.1039/b708928g] © 2007 Royal Society of Chemistry.

The contents of Chapter 3 were reproduced with permission from MF Santillo, ML Heien, AG Ewing, Lab Chip 2009, 9, 2796-2802. [doi:10.1039/b907942d] © 2009 Royal Society of Chemistry.

Part of Chapter 4 was adapted with permission from DM Omiatek, MF Santillo, ML Heien, AG Ewing, Anal. Chem. 2009, 81, 2294-2302. [doi:10.1021/ac802466g] © 2009 American Chemical Society. Part of this chapter was also submitted (Oct 2009) as a trends article authored by MF Santillo, ML Heien, and AG Ewing to Anal. Bioanal. Chem. (Springer-Verlag).

The contents of Chapter 5 were submitted (Sep 2009) to the Analyst authored by MF Santillo, ML Heien, and AG Ewing. Proposed [doi:10.1039/b919003a] Royal Society of Chemistry.

viii

Acknowledgements

Graduate school was a challenging six-year experience which would not have been

possible without the aid of several people. First I would like to thank my adviser Andy Ewing

along with Michael Heien for their support throughout my studies at Penn State. I am greatful to

Andy for keeping the lab operational at Penn State while he began his new position in Sweden.

I also thank my dissertation committee and faculty members Anne Andrews, Philip

Bevilacqua, Christine Keating, Thomas Mallouk, and Andrew Zydney for their feedback, advice,

and writing recommendations for me. I appreciate Penn State Nanofab engineers going out of

their way to assist me and taking an interest in my research. I am indebted to Imee Arcibal for

helping me on several projects in the past five years and for motivating me throughout graduate

school. I appreciate all other members of the Ewing group who have assisted me along the way.

I also thank my family for their support.

ix

x

What I want to talk about is the problem of manipulating and controlling things on a small scale.

As soon as I mention this, people tell me about miniaturization, and how far it has progressed

today. They tell me about electric motors that are the size of the nail on your small finger. And

there is a device on the market, they tell me, by which you can write the LORD’s Prayer on the

head of a pin. But that’s nothing; that’s the most primitive, halting step in the direction I intend

to discuss. It is a staggeringly small world that is below. In the year 2000, when they look back

at this age, they will wonder why it was not until the year 1960 that anybody began seriously to

move in this direction.

—Richard P. Feynman*

* RP Feynman, There’s Plenty of Room at the Bottom, American Physical Society Meeting, Pasadena, CA, 29 Dec 1959. The speech has been reproduced in J. Microelectromech. Sys. 1992, 1, 60-66. [doi:10.1109/84.128057]

Chapter 1: Overview of microfluidic technology for performing cellular assays

MINIATURIZATION IN ANALYTICAL CHEMISTRY

In the 1950s the first silicon semiconductor transistors were fabricated using

photolithography and associated microengineering techniques [1]. These small transistors could

be mass produced and are major components of integrated circuits, leading to high-performance

computing in which a large number of transistors can be fit into a small chip. Shortly thereafter,

microelectromechanical systems (MEMS) [2-4], small sensors such as accelerometers in air bags

and piezoelectric ink jet print heads were introduced, taking advantage of the same

microfabrication techniques [5, 6] used for making integrated circuits. The field of analytical

chemistry soon began to use micromachining as well. In 1979, Terry et al. [7] reported a gas

chromatograph constructed in silicon, which was one of the first microanalytical devices made.

It was not until the 1990s, however, that miniaturization for analytical chemistry emerged as

popular a field with the introduction of electrophoretic separations on silicon and glass chips [8].

The introduction of microchip separations led A Manz and HM Widmer to introduce the concept

of a micro total analysis system [9-11], in which an entire chemical analysis requiring several

steps could be integrated into a single portable chip. Since these pioneering reports in the early

1990s, there have been numerous applications of microfluidics for microbiology [12],

neuroscience [13, 14], drug discovery [15], combinatorial chemical synthesis [16-20], and high-

throughput cell screening [21, 22]. Although microfluidic systems are primarily used in

academic research, microfluidic device development has recently been on the rise in the

commercial sector as well [23-29], led by companies such as Caliper Life Sciences, Inc. and

Agilent Technologies, Inc.

Microfluidic or lab-on-a-chip devices [30, 31], along with micro total analysis systems,

have many advantages compared to traditional macroscale methods [32-36]. Microfluidic

devices consume small volumes of reagents and consequently generate less waste. With the

introduction of soft lithographic methods, these devices can be rapidly prototyped from molds,

making the devices inexpensive, disposable, and mass produced in large numbers [37].

1

Furthermore, devices can be customized to fit the analysis being performed. Microsystems are

small making them portable and useful, for example, for clinical point-of-care diagnostics [38-

42]. Their small size further allows many steps of an analysis to be integrated into a single

system [43], avoiding sample loss during transfer from one step to another. Microfluidic systems

can be automated and allow many analyses to be performed in a multiplexed, high-throughput

fashion, resulting in faster analysis times. Finally, microchannels are commonly on the same

size scale as biological cells, leading to unique applications for cell assays, which may not be

possible with traditional macroscale methods [44-59].

PHYSICS OF FLUID FLOW ON THE MICROSCALE

In order to realize the benefits and motivations of microfluidic systems, it is important to

understand the behavior of fluids on the microscale [60]. It is known that many physical

descriptions applied to matter on the macroscale differ from that observed on the microscale.

For example, on the atomic level matter is described with quantum mechanics, whereas on the

macroscopic level matter can be described by classical mechanics. The same paradigm can also

be observed with fluids. On the microscale fluid flow is dominated by forces such as viscosity

but on the macroscale inertial forces dominate, and the influence of diffusion is evident.

Reynolds number

One way to describe fluid flow is with the dimensionless Reynolds number [61-63],

defined as Re = ρℓv/η, where ρ is density, ℓ is the diameter of the channel, v is average linear

velocity, and η is viscosity. Fluids where Re < 2300 are defined as laminar, whereas when Re >

2300 the fluid is turbulent. For laminar flow, pressure and velocity are dependent on position

and independent of time. This causes streams of fluid to run parallel, meaning for two adjacent

fluids, mixing only occurs at the interface due to diffusion. Conversely, with turbulent flow,

pressure and velocity vary in space and time. Fluids can form vortices and eddies, mixing in a

chaotic, unpredictable manner (e.g., rapidly flowing water in a river). Since laminar flow is

predictable, it can be used to direct fluids to specific regions via hydrodynamic focusing [64-70].

This can be used to apply fluids, for instance to a specific area on a cultured cell for a biological

assay on a chip. However, laminar flow is sometimes not desirable, especially in chemical

2

synthesis, where rapid mixing of reagents may be needed to form a product in a short amount of

time. In situations where rapid mixing is required, microchannels with unique geometries are

often employed [71-77]. In most microfluidic devices, flow is laminar (typically Re < 1) since

the flow rates are low and channel sizes are small [78].

Diffusion

Another important influence on fluid behavior is diffusion. Diffusion is a statistical

description of the random movement of molecules, and is a major form of molecular transport on

the microscale [79]. In biological systems, especially, diffusion plays a major role as small

molecules such as oxygen and carbon dioxide enter and exit cells through membranes via

diffusion, which is vital for cellular respiration. According to Einstein and Smoluchowski, the

average distance a group of molecules diffuses in one dimension can be approximated by the

equation x = (2Dt)1/2, where x is distance, D is the diffusion coefficient, and t is time [80]. It is

important to note that diffusion depends on the molecular size, temperature, and viscosity. In

microchannels, diffusion plays a major role for fluid transport due to the small length scales

involved [81, 82].

Peclet number

It is often important to describe the contributions of both convection and diffusion in

microfluidic systems. The Peclet number is another dimensionless quantity defined by Pe =

ℓv/D, where ℓ is the characteristic length (in microchannels this is most commonly channel

width), v is average linear fluid velocity, and D is the diffusion coefficient. The Peclet number

compares the contributions of convection, represented in the numerator, and diffusion

represented in the denominator. Large fluid flow velocities (i.e., high rates of convection)

correspond to high Peclet numbers. A simulation illustrating the effects of diffusion and

convection in a flowing stream in a microchannel is illustrated in Figure 1.1. This contains two

parallel flowing solutions, one containing a species at a given concentration, and the other with a

concentration of zero. In Figure 1.1a, the flow rate of the two streams is 167 µm s-1 whereas the

rate in Figure 1.1b is 100 times larger (16.7 mm s-1). Since the flow rate (and Peclet number) in

Figure 1.1a is lower, the two fluids have more contact time with each other and therefore,

3

Figure 1.1. Simulations illustrating the effects of convection and diffusion on lateral mixing across two channels. Plots of concentration (normalized to the maximum) in which two fluids flow adjacent to each other at a velocity of (a) 167 µm s-1 and (b) 16.7 mm s-1. Scale bar is 200 µm.

4

according to the Einstein diffusion equation x = (2Dt)1/2, there is more diffusive mixing at the

interface since t is large. Since the flow rate in Figure 1.1b is 100 times faster, the fluid

molecules are moving faster in the direction of the flow and do not have as much contact time

with the adjacent fluid; therefore, t is lower and there is less diffusive mixing. As one can see,

controlling the fluid flow rate dictates the amount of time solutions are in contact with each other

resulting in different degrees of mixing.

Hydrodynamic flow

There are several ways to transport fluids in microfluidic devices. The most common

methods are hydrodynamic (pressure driven) and electrophoretic flow [83]. Fluid flow is

described by the Navier-Stokes equations, a series of partial differential equations that yield

pressure and velocity of a fluid continuum [84]. Hydrodynamic flow is the simplest transport

scheme; fluid is typically driven with a syringe pump that allows accurate control of delivered

fluid volumes over time. When fluids are driven through rectangular microchannels via

pressure, the resulting velocity profile is parabolic, described by the equation

⎟⎟⎠

⎞⎜⎜⎝

⎛−= 2

2

max6)(wx

wxvxv

where v(x) is the velocity at width x from the wall, vmax is the maximum velocity, and w is

channel width. According to the equation, the maximum velocity is located at the center of the

channel, and the velocity at the channel walls is zero. Furthermore, the average velocity in a

rectangular channel is given by vavg = 2vmax/3.

MICROFLUIDIC DEVICE FABRICATION

The earliest microsystems were engineered in silicon or glass with traditional

photolithographic and wet chemical etching [8, 85, 86]. Unfortunately, these systems have

several disadvantages. Silicon is expensive and imaging is not possible since it is opaque to

visible and ultraviolet light. Furthermore, fabrication of silicon-based microsystems is expensive

and time-intensive since fabrication is serial in nature; the same fabrication steps must be

performed on each device. Although glass microfluidics are transparent to visible wavelengths

5

of light, they are similarly fabricated in a serial manner, making construction a time-consuming

process.

The introduction of soft lithography by Whitesides and coworkers [87] revolutionized the

microfluidics field, allowing microdevices to be fabricated with polymers such as

poly(dimethylsiloxane) (PDMS) [88]. With soft lithography, a single master mold is produced

via photolithography followed by casting and curing PDMS onto the mold (see Figure 1.2).

First, photoresist (a light sensitive organic compound) is spin-coated onto a substrate such silicon

or glass. The angular velocity of the substrate during the spin-coating process determines the

thickness of the photoresist layer on the substrate. For manufacturing PDMS-based microfluidic

devices, the negative photoresist SU-8 [89-95] is most often employed. After spin coating, the

substrate is heated, evaporating organic solvents that let the photoresist spread evenly on the

substrate. Photoresist is then exposed to ultraviolet light through a mask, which contains the

features to be defined on the mold. The most common masks used for photolithography are

made of chrome on glass and are expensive. Many microfluidic systems contain features on the

order of tens of micrometers, therefore chrome masks are not necessary. Instead, masks can be

printed onto transparencies [96, 97] or high-resolution photoplots [98]. These masks are less

expensive compared to chrome masks and allow more researchers to take advantage of the

technology. Since SU-8 is a negative photoresist, all areas of photoresist exposed to ultraviolet

light are polymerized. After exposure, a heating step is performed which further strengthens the

polymerization of exposed resist. Lastly, the photoresist-coated substrate is immersed in a

developer solution that dissolves the soluble, unexposed photoresist. Features with high aspect

ratios [99] can be fabricated in SU-8, which is an important factor in many microfluidic systems.

After defining a master mold with SU-8 photoresist, the polymer poly(dimethylsilxane)

(PDMS) is cured onto it. PDMS is an inexpensive, biocompatible silicone polymer and is

transparent in the ultraviolet and visible light range [100]. This makes microscopy [101] and

other forms of imaging possible when using PDMS-based microfluidic systems. Since the

polymer is biocompatible, cells can be cultured in these platforms making them useful for

biological assays [102, 103]. Because PDMS is gas permeable, adequate oxygen and carbon

dioxide exchange occurs with cells cultured in PDMS microdevices. PDMS is also compatible

with aqueous solutions along with other solvents [104]. Lastly, because PDMS is deformable,

many unique components [105] can be fabricated such as valves and pneumatic pumps, which

6

Figure 1.2. Fabrication of a microfluidic device via photolithography and soft lithography. (a) A silicon wafer, glass, or other substrate is cleaned and (b) spin-coated with photoresist. (c) A mask is placed on top of the photoresist-coated substrate, causing areas corresponding to the mask to be exposed to ultraviolet light. (d) The substrate is placed into developer solution that dissolves away photoresist that was not exposed to ultraviolet light, resulting in a master mold. (e) Soft lithography is performed in which the master mold is cured with poly(dimethylsiloxane). (f) The PDMS is peeled away from the mold, inlet/outlet holes are punched out, and the PDMS is bonded to glass or other substrate.

7

are not possible with rigid materials such as glass and silicon. Although PDMS is not suitable

for all microfluidic applications [106], it has remained as the most popular material for easy and

effective microfluidic device fabrication (it is important to note that there are a variety of other

polymers that are used for microfluidics [107, 108], although PDMS is most popular). The final

steps of fabrication involve exposing the PDMS to oxygen plasma, which renders the surface

negatively charged and hydrophilic [109-113], allowing irreversible bonding of PDMS against

glass or another piece of PDMS.

CONVENTIONAL TECHNIQUES FOR EXPOSING AND ANALYZING CELLS

Bathing a cell population

Cell assays, in general, are experiments in which amounts of intracellular chemical

compounds are detected and quantified. In drug discovery, for example, cell assays serve a vital

role in which the effects of many drug candidates on changes in intracellular metabolites are

studied. The simplest way to perform cell assays is to incubate a population with a chemical

compound of interest, followed by analysis via optical spectroscopic methods (i.e., fluorescence,

UV/visible absorbance, or luminescence). This can be done with adhered cells in petri dishes,

microtiter plates, or cell suspensions. For instance, cells cultured in petri dishes can be incubated

with a suspected toxin along with a fluorescent viability dye. The dye, while in solution, is non

fluorescent; however, once inside the cell, endogenous enzymes cleave parts of the dye molecule

yielding a fluorescent product. This reaction only occurs inside cells that are viable and have

membranes intact. Other assays exist in which various metabolites, secondary messengers, and

other compounds can be quantified, depending on the fluorophore employed [114].

Although bathing a cell population is easy and useful data is obtained from these

experiments, there are several drawbacks. Bathing cells in petri dishes is a low-throughput

approach; several dishes must be used for different treatments. Many experiments involve

exposure to several concentrations, which is more cumbersome when using multiple dishes.

Furthermore, automation cannot be done with this conventional scheme. Dishes frequently

require volumes in the milliliter range, which can be problematic for volume-limited samples or

small cell populations. Microtiter plates are an improvement over conventional dishes, as they

integrate many wells into a single plate and require smaller volumes. The optical signal from

8

each well can be recorded with a spectrometer (plate reader). While microtiter plates improve

the throughput compared to single dishes, microtiter plates typically require volumes over 100

µL. There are many examples of cell assays which cannot be done in this manner, which are

explained later in which the benefits of microfluidic technology is discussed.

Micropipettes

Glass micropipettes are used to briefly "puff" solution onto cultured cells. Micropipettes

are manufactured by subjecting a glass capillary (< 1 mm i.d.) to intense heat via a CO2 laser or

filament. While heating, the capillary is pulled such that a finely sealed tip is created. The tip is

cut under a microscope, creating an opening where fluid may exit. The resulting micropipette is

then interfaced with a pressure-based pump and mounted onto a micromanipulator, allowing the

position of the micropipette tip to be accurately controlled in a dish containing cells.

Micropipettes are commonly used to create gradients for studying cell growth and chemotaxis

[115, 116], and volumes as low as 100 pL can be reproducibly delivered [117].

When using pressure-based ejection, the volume of fluid delivered is proportional to the

ejection pressure and duration. A series of fluorescence images over time of FITC dye ejected

from a micropipette (5 lb in-2 for 5 s) is presented in Figure 1.3a-d. The data in Figure 1.3a were

obtained after a pressure was applied for 5 s, the time at which the ejection ceased. The data in

Figure 1.3b-e show that after ejection the dye has diffused considerably. Although pressure

ejection via micropipettes is useful for exposing cells for a brief period of time, micropipettes are

not well suited for conditions where spatial addressing or continuous perfusion are required.

Because each pipette is controlled with a micromanipulator, exposing several cells

simultaneously would require a micromanipulator for each pipette. It is important to note that

flux (velocity and concentration) of ejected solution varies over space; therefore, cells experience

varying flux depending on position relative to the pipette. This situation is disadvantageous

when cells require exposure to an equal amount of chemical compounds. Sterility is another

issue when employing micropipettes. Cells in the petri dish are exposed to air because the

pipette tip must be positioned in solution near cultured cells. Exposure to air may compromise

the sterility of cultured cells if they are exposed multiple times over a long time period. Finally,

as evidenced in Figure 1.3a-d, the movement of fluid was shifted upward due to convective

currents. Nevertheless, the use of micropipettes is a straightforward way of exposing groups of

9

Figure 1.3. Pseudocolored fluorescence image time series of FITC puffed from micropipette (5 lb in-2 for 5 s) after (a) 5 s, (b) 15 s, (c) 35 s, and (d) 60 s. Each image is 1.8 × 1.8 mm in size. (e) Plot of normalized concentration (c/c0) over time corresponding to a-d.

10

cells to a chemical compound where the exact concentration or exposure time is not a major

concern.

Flow cytometry

Flow cytometry is an instrumental technique used to measure both physical and chemical

properties of single cells [118]. A cell suspension is introduced into a chamber in which there

are two fluid streams (sheath flow streams) that flow parallel to the cell suspension stream

(coaxial flow stream). The fluid flow in the chamber is laminar; therefore, the sheath streams

cause the coaxial stream to narrow such that the cells travel single file. Individual cells pass

through a laser beam; scattered light or emitted fluorescence signal is recorded which is

indicative of specific cell properties such as size, enzyme activity, or presence of an antibody-

antigen interaction. In addition to analysis, fluorescence-activated cell sorting can also be

performed on many flow cytometry systems. In this specific mode of cytometry, after

fluorescence signal is measured from a cell, individual cells are isolated in droplets that are given

positive or negative charge. A deflection plate then diverts the cell droplets into one of two

containers, depending on the charge. Flow cytometry is a powerful bioanalytical tool, but cannot

be used to analyze single cells adhered to a surface. Flow cytometry also does not allow the

same individual cell to be interrogated multiple times, and subcellular localization of

fluorophores cannot be determined. Unlike microfluidic devices, flow cytometers are bulky and

not amenable to portability. Finally, flow cytometry systems cannot integrate several steps of a

cell assay and are unable to be specifically customized to the assay being performed.

Chemotaxis assays

There exist many examples where chemical gradients play an important role in biological

systems [119]. During development in vivo, a fertilized egg releases biomolecules that diffuse,

thus forming gradients, in an effort to initiate additional biological events that occur at a distance

from the secretagogue source. Neural development also requires gradients. Axonal and

dendritic projections from the cell body grow in response to gradients of growth factor proteins

that guide neurons such that they may form a complex network of connections with one another.

11

Many traditional techniques have been extensively used for studying cell migration in

response to chemical gradients [120]. Biological hydrogels are a simple way to create gradients.

Cells are cultured with hydrogel; the secreted biomolecules diffuse throughout the porous

hydrogel, thereby creating a spatiotemporal gradient. Although it is an easy technique in which

multiple, independent gradients can be investigated, it is difficult to quantify the gradients via

microscopy as the biomolecules are present at low concentrations. Furthermore, gradient

profiles cannot be modified and are always time-evolving. Boyden chambers and transwell

assays are common investigatory tools for biochemical gradients. Two glass chambers are

separated by a membrane on which cells adhere. Diffusion through the membrane induces a

gradient that causes cells to move through the membrane pores from one chamber to another.

With this technique, it is possible to measure cell migration distances for a population of many

individual cells; however, imaging may be difficult and the gradient profiles cannot be modified.

Zigmond and Dunn chambers consist of two reservoirs separated by a gap. Cells are cultured on

a coverslip that is placed above the gap channel between the chambers; a diffusive gradient then

forms at the interface of the solutions within the gap. With Zigmond and Dunn chambers, it is

easy to perform direct imaging, and established gradients remain for up to an hour.

Unfortunately, the gradient profiles cannot be modified and the reservoirs containing solutions

are prone to evaporation, which may disrupt the gradients over time.

APPLICATIONS DEMONSTRATING ADVANTAGES OF MICROFLUIDICS

Perturbation of microenvironments in embryos and single cells

The high degree of spatial heterogeneity both within the cell cytoplasm and on the

membrane surface is known to be vital for biological function. Vesicular neurotransmitter

release [121], membrane lipid domains [122], and cytosolic compartmentalization [123] are all

examples of how the cell surface and interior are highly heterogeneous. Obtaining spatial

information on the subcellular scale is routine with a variety of analytical techniques such as

fluorescence microscopy and scanning electron microscopy. However, techniques for selectively

perturbing cellular microenvironments reamain challenging, due to diffusion. As discussed

previously, the effects of diffusion on the microscale is apparent; the distances traveled by

molecules due to diffusion on short time scales (seconds) often exceed the length of the cell,

12

making subcellular exposure difficult. On the other hand with microfluidics, and the

consequences of laminar flow, subcellular exposure to different chemical compounds can more

easily be done on the microscale.

Embryos from the fruit fly, Drosophila melanogaster, are a good model for studying

genetic and developmental processes. Using microfluidics, a single embryo (approximately 500

µm diameter) was positioned in a microchannel and exposed at two temperature extremes from

two fluids [124, 125] with laminar flow. Mixing of the fluids only occurs at the interface due to

diffusion with laminar flow; therefore a temperature gradient was established across the embryo.

The embryo, after fluorescence staining, had a higher density of nuclei in the warmer area than in

the cooler area (Figure 1.4a). It is well known that the Paired protein develops in known regions

of the embryo in a specific sequence. After exposure to an extreme temperature gradient, the

embryo was histochemically stained; it was found that Paired protein stripes formed out of order,

but in the correct positions. This result suggests that there is a compensatory mechanism in

embryonic development, and its exact nature remains yet to be elucidated. This experiment

demonstrates the unique advantage exhibited with microfluidics; simultaneous exposure of the

embryo to two different fluids would be difficult with any traditional technique.

In addition to embryos, single cells have also been probed on the subcellular level using

microfluidics and laminar flow [126-128]. Single bovine capillary endothelial cells were treated

with parallel laminar flows [126, 127] of mitochondrial fluorophores, and initially the two

labeled populations remained on either side of the cell; however, within 2.5 h, the two

populations were mixed within the entire cell interior. The cell was also partially treated with

latrunculin, a compound that breaks apart actin filaments. Over time, the nucleus and

mitochondria shifted away from the laminar stream of latrunculin, but the overall shape of the

cell remained unchanged.

Orwar and coworkers have applied the partial treatment of cells with laminar flows in a

unique microchannel-micropipette hybrid device (Figure 1.4b) [129]. A total of 16 parallel

channels flow into a large reservoir where a cell is immobilized onto a micropipette. The

computer-controlled micropipette is shifted through each laminar flow stream, exposing the cell

to various solutions while maintaining an accurate rate of movement across solution streams. It

was shown that with this device, a cell could be placed at the interface of two laminar flow

streams, thus creating an intracellular gradient. In this experiment, a single cell was first exposed

13

Figure 1.4. Partial treatment of cells and embryos with laminar flow. (a) Drosophila embryo exposed to two parallel flows of warm and cool fluid. Fluorescence image shows the number of nuclei on each side of the embryo. Reproduced from reference [125]. (b) Dynaflow 16 microfluidic chip for treatment of a single cell adhered to a micropipette. Reproduced from reference [129]. (c) PDMS device for isolation of soma and axons of neurons. Reproduced from reference [133].

14

to digitonin, which permeabilizes the cell membrane, followed by exposure at the interface of

parallel flows of media and fluorescein diphosphate. Fluorescein diphosphate, once inside the

cell, is converted to fluorescein by alkaline phosphatase. Using fluorescence microscopy,

varying gradients of fluorescein were observed within a single cell due to the different

concentrations of fluorescein diphosphate being delivered at the laminar flow stream interface.

A similar microfluidic-micropipette hybrid system using laminar flow was also used by Cooper

and coworkers for subcellular addressing single myocytes [130, 131].

Neurons exhibit a high degree of spatial functionality. A neuron is defined by its soma

(cell body), dendrites, synapses, and axons, and each of these parts carries out different

biological functions. There exist several examples using microfluidics to spatially address

different areas of cultured neurons. Several reports by Jeon and coworkers feature a PDMS

device containing a series of microgrooves connecting two chambers [132-134]. Neuronal

somata are placed into one chamber, and over time only axons grow into the microgrooves

(Figure 1.4c). Since the series of microgrooves between reservoirs were small, there was a high

fluidic resistance between the two chambers, thus isolating fluids in each chamber and

preventing them from mixing appreciably. In Figure 1.4c, Texas red dextran is clearly isolated

in the axonal reservoir. This isolation allows the neurites to be exposed to different compounds

while leaving the somata untreated. In Figure 1.4c, the axonal chamber was filled with

CellTracker Green, which was taken up by axons, eventually migrating to the somata. Using this

device, mRNA was collected from axons; it was discovered that mRNA coding for the

presynaptic vesicle protein, synaptophysin, is present within axons, which was not known

previously. The device has great potential for studying axonal injury and regeneration since

compounds can be selectively applied to axons. Axons were lesioned by aspiration, without

affecting the soma located in the other chamber. Neurotrophin was then added to the chamber

and it was found that axonal growth was much higher compared to control cells, thereby

illustrating the capability of this system for screening drugs related to neurodegeneration.

One disadvantage of this system and many other microfluidic systems is inflexibility;

channel dimensions and device design are considered static. Often, an ad hoc method of spatial

exposure is desired. Shear and coworkers [135] developed a technique for subcellular exposure

to neurons using laser ablation. A membrane of cultured cells was located between two flow

channels. A femtosecond titanium/sapphire laser was used to create a hole in the membrane near

15

a cell of interest. After ablation, fluid from the upper channel traveled through the hole, and due

to laminar flow, was used to selectively address the cell. In order to seal a pore, a solution of

bovine serum albumin and flavin adenine dinucleotide was flowed through the channel, followed

by exposure to a titanium/sapphire laser, which ultimately caused photopolymerization of the

protein in the hole. With this laser ablation method, cultured NG108-15 cells could be

selectively damaged with ethanol and subcellular regions labeled with fluorophores. Although

useful, this technique requires sophisticated equipment and cannot be easily adopted by

researchers.

High-throughput single cell analysis

It is important to note that obtaining data from single cells can be much different than that

of a bulk average from a cellular population. Such differences might occur if several

subpopulations exist and, when averaged, these lead to a single value located between the

individual populations. Another situation in which single cell responses differ from an average

is when many short cellular processes occur over a long time period; although each event is

short, the average value is broad and not indicative of the true event length [46, 136].

One common method for analyzing single cells is in an array format [137]. The array

enables single cells to be isolated in known locations such that data analysis and imaging can be

automated and easier to perform. LP Lee and coworkers have successfully fabricated a

microchannel containing an array of hydrodynamic traps capable of capturing single cells [138,

139] (Figure 1.5a). As cell suspension travels through the channel, cells are captured in the array

while small gaps in the traps allow solution to escape. The trapping efficiency is high, and the

trap size and density can be modified depending on size of the cell being trapped. Using

hydrodynamic trapping, cells have been perfused with nordihydroguaiaretic acid, an esterase

inhibitor, and calcein AM, an esterase substrate and the kinetics of esterase activity has been

determined [138]. Understanding carboxylesterase activity is important as it activates many

prodrugs in vivo and may contribute to the inactivation of other pharmaceuticals.

One of the advantages of fabricating microfluidic devices from elastic PDMS is that

pumps and valves can be integrated into a device for the precise control of fluid handling. A

device containing a series of valves and pumps in conjunction with a hydrodynamic trap has

been used for fluorescence monitoring of single cells [140]. The hydrodynamic trap allows a

16

Figure 1.5. High-throughput cell assays with microfluidic systems. (a) Hydrodynamic trapping array. Reproduced from reference [139]. (b) Trapped single cell exposed to trypan blue dye, methanol, and trypan blue dye. Reproduced from reference [140]. (c) Microchannel electrophoresis chip for cell selection, lysis, separation, and detection. Reproduced from reference [143].

17

single cell to be isolated from a laminar flow stream, even under high flow rates (1 mm s-1).

Using a series of valves and pumps, a cell viability assay has been performed on a single Jurkat

T-cell (Figure 1.5b). In these experiments, the cell is first exposed to a laminar flow of trypan

blue, a cell viability dye; the absence of staining inside the cell indicates that the cell is viable. A

valve is then used to expose the cell to methanol. Shortly thereafter, trypan blue is introduced

again, and the cell absorbs the dye due to prior exposure to methanol that kills the cell. With this

system, a single cell assay has been carried out in only 2 min consuming 105 less reagent

compared to a conventional assay. Furthermore, the short switching time (< 100 ms) between

reagents leads to the ability of monitoring dynamic cell processes that occur on a fast time scale.

In a similar device [141], a hydrodynamic trap was used to capture single cardiac myocyte cells.

The system allowed single myocytes to be loaded with fluorescent dye on chip, which is often

advantageous because centrifugation that is performed during the dye loading process can

damage cells.

In many experiments, the quantification of intracellular contents is desired, which can be

accomplished via electrophoretic separations [142]. Microchannel electrophoresis is a powerful

tool, especially when applied to single cell analysis, due to its efficiency, fast separation times,

and ease of integration into other steps of an assay. Figure 1.5c shows a microchip

electrophoresis system for selection, lysis, separation, and detection of the component in a single

cell in a high-throughput fashion [143]. Jurkat cells were transported via hydrodynamic flow

along with emulsification agent. Once cells encountered a perpendicular channel with a high

potential applied, the cells rapidly lysed and the contents separated via electrophoresis. The

components were then detected via laser-induced fluorescence. Before analysis, cells were

loaded with fluorescent dyes, and it was determined that all of the dye present was detected, thus

the entire contents of the cell were injected into the separation channel after lysis occurred. This

high-throughput method allowed up to 12 cells per minute to be analyzed, which is over 100

times greater throughput versus conventional capillary electrophoresis.

Cell culture on a chip

The ability to maintain cell cultures for prolonged periods of time, coupled with

biochemical analysis, is possible with microfabricated platforms [144]. Microfluidic cell culture

systems are beneficial because they are self-contained and cells may be continuously perfused

18

with media, while waste is continuously transported away. A cell culture array platform

integrating a concentration gradient generator is shown in Figure 1.6a. The chip-based cell

culture system features a 10 × 10 array of culture microchambers, each perfused with a different

concentration of chemical compound [145, 146]. After HeLa cells were loaded into the

chambers and reached confluency, trypsin was used to subculture the cells. It was found that

after subculturing, cells reached confluency again, revealing that the platform possesses a

controllable microenvironment suitable for culturing cells for multiple generations over time.

Likewise, Quake and co-workers [147] developed a complex automated microchemostat

for monitoring bacterial growth (Figure 1.6b). The system contained 16-nL bacterial growth

chambers, along with inlets for lysis buffer and bacteria introduction and pumps for fluid

transport. The system allowed small populations (< 100) of bacteria to be non-invasively imaged

with single-cell resolution. Maintaining small populations of bacteria is important because small

populations help preserve genetic homogeneity. With this automated system, bacterial growth

was monitored for hundreds of hours in a controlled environment, and the synergistic effects of

quorum sensing were studied.

It is known that bacteria in the environment live in symbiotic relationships and help

maintain healthy ecosystems. Ismagilov and coworkers employed a microfluidic device for

investigating the spatial symbiotic relationships among three soil bacteria [148]. The device

features three chambers, one for each bacterial species, which are separated by nanopore

membranes. The membranes confine the bacteria, while allowing chemical communication

among the different species. When the bacteria were cultured in total isolation, each of the three

species decreased in population. However, when bacteria were grown in the device allowing

chemical communication, all bacteria increased in population. Surprisingly, when all three

species were cultured in the same chamber without spatial isolation, the population did not

increase. These results showed that the spatial organization is important between bacteria in an

artificial system, and that there is a fine balance between consumption of nutrients and

production of metabolites, which are essential for bacterial survival.

Solution gradients for inducing cell growth

As mentioned previously, traditional techniques for establishing gradients for studying

cell migration are simple to perform but are not flexible or reproducible, in addition to the fact

19

Figure 1.6. (a) Cell culture system with gradient generator, where each chamber is exposed to a different concentration. Reproduced from reference [146]. (b) Automated microchemostat for monitoring bacterial growth. Reproduced from reference [147].

20

that imaging is often difficult. However, the use of controlled laminar fluid flow in

microchannels and flexibility in geometric design offers a way to produce both time-evolving

and steady-state gradients for studying chemotaxis. One hurdle when forming gradients on the

microscale is that convective flow causes disruptions in the gradient. Abhyankar et al., [149]

developed a simple microchannel with a nanopore membrane capable of producing gradients for

24 h, while keeping convection to a minimum (Figure 1.7a). The system was composed of two

reservoirs, a source containing bacterial peptide formyl-methionine-leucine-phenylalanine

(fMLF), and a sink where neutrophils were added. A polyester track etched nanopore membrane

which allowed small amounts of fMLF to escape was located at the bottom of the source

reservoir; the high fluidic resistance of the membrane eliminated convective flow so that the

gradient could remain more stable. Over time, neutrophils were observed migrating towards the

source reservoir. Although simple and easy to use, this nanopore gradient generator is unable to

maintain gradients for long-term studies. Furthermore, the spatiotemporal profile cannot be

modified as the gradient is defined by the diffusion coefficient and temperature of solution.

Another time-evolving gradient generator developed by Folch and coworkers [150]

incorporates pneumatically actuated PDMS valves. The device, shown in Figure 1.7b, features

two channels, one loaded with interleukin-8 (source channel), and the other with leukocyte cells

(sink channel). These two channels are separated by a valve, and each chamber contains valves

at the inlet and outlet. After loading the chambers with cells and chemoattractant, valves near

the inlet are closed, isolating the cells and chemoattractant and preventing unwanted convection.

The valve linking the two channels is then opened, allowing interleukin-8 to diffuse from the

source into the sink chamber. The diffusion profile was found to be radial, and leukocytes could

be imaged over time as the gradient evolved.

Although time-evolving gradients are found in vivo, steady-state gradients are also of

interest, especially since many steady-state gradients continuously perfuse cells with fresh media

while removing waste products. Jeon and colleagues [151] developed a premixer for forming

steady-state gradients and applied it to studying neurophil migration. In the device, two inlet

channels split into a series of serpentine channels, which cause the two inlet solutions to mix

(Figure 1.7c). Each serpentine channel contains a different concentration, and the mixed fluids

converge into a larger channel where a gradient results along the width of the channel. The

device is capable of producing well-defined gradients including ones with sigmoid, parabolic,

21

Figure 1.7. (a) Microchannel with nanopores for time-evolving gradients. Reproduced from [149]. (b) Microfluidic device incorporating valves for time-evolving gradients. Reproduced from [150]. (c) Premixer steady-state gradient generator. Reproduced from [151]. (d) Cross-channel gradient generator. Reproduced from [153].

22

and sawtooth shapes. A modified version of the device in Figure 1.7c has been used to produce

non-linear gradients of epidermal growth factor, a biomolecule associated with the spread of

breast cancer [152]. Breast cancer cells were loaded into the device and it was found that linear

gradients, regardless of the slope, did not induce chemotaxis; however, non-linear gradients

induced chemotaxis of the breast cancer cells.

A cross-channel gradient generator has been reported (Figure 1.7d), capable of producing

either linear or non-linear gradient profiles [153], depending on the channel geometry. The

device consists of two parallel channels, one as a source and the other as a sink, separated by a

series of smaller, parallel channels. An array of cavities is also located on the wall of the sink

channel. By varying the length of the channels connecting the source and sink channels, linear,

concave and convex gradient shapes result, as shown in Figure 1.7d. Although no cell studies

have yet been performed in this system, it holds promise for investigating cell chemotaxis and

migratory behavior.

DISSERTATION GOALS AND OVERVIEW

The goals of this dissertation are to develop microfluidic platforms for performing

cellular assays and to obtain data that would be difficult, if not impossible, to obtain with

conventional methods. In the second chapter, a device for monitoring communication patterns in

an in vitro neural network is discussed. This unique system exploits laminar flow and

hydrodynamic focusing, allowing neurons in specific locations of a network to be addressed with

different pharmacological compounds. The flow profiles were characterized with confocal

fluorescence microscopy, computational fluid dynamics simulations, and carbon-fiber

amperometry. In the future, this system will be patterned with primary neuronal cultures. The

changes in neural network activity will be monitored via fluorescence microscopy after specific

cells in the network are exposed to pharmacological agents such as toxins and neuroprotectants.

In the third chapter, lysis of a non-pathogenic amoeba, Arcella vulgaris, is presented.

Lysis was monitored in a microfluidic platform and this was used as a model for pathogenic

amoebic species. This device allows multiple cells to be observed simultaneously with single-

cell resolution after exposure to constant, controlled flow of chemical biocides. The data

obtained shows that single cell lysis events are much different from a bulk average, and the

efficacy of several detergents and biocides was compared.

23

In the fourth chapter, the use of computational fluid dynamics simulations is discussed.

These simulations have been performed in order to validate and develop amperometric detection

schemes for two specific experiments. Simulations were performed to validate flow profiles in a

hybrid capillary-microfluidic device for the separation, lysis, and detection of neurotransmitter

vesicles. Simulations were also used in the development of efficient amperometric detection in a

microchip electrophoresis device. The electrode detection was modeled in order to maximize the

coulometric efficiency, which is problematic in many electrophoretic separations. The results

will be used in the future fabrication of this device.

The fifth chapter presents a non-photolithographic technique for fabricating PDMS

microfluidic mixers with tape-based master molds. Mixers with two geometries were

constructed and the mixing efficiency was characterized via simulations and fluorescence

microscopy.

A microfluidic device for performing high-throughput assays on PC12 cells is presented

in the sixth chapter. The device contains a channel where diffusive mixing occurs; a total of

eight different concentrations are applied to chambers containing cultured PC12 cells. With this

device, an assay for free radical generation was performed investigating the effects of 6-

hydroxydopamine. Lastly, in the seventh chapter, future directions for microfluidic applications

in studying neural network communication are discussed.

CONCLUSIONS

Microfluidic devices have emerged as a popular technology for performing cellular

assays. Microfluidics offer an alternative to many time-consuming conventional techniques and

possess many advantages including automation and low reagent consumption. There are many

applications of this technology in biology, including those in neuroscience, studies of cell

growth, and monitoring membrane disruption. This thesis demonstrates the advantages of

microfluidics for cellular assays, and shows that the data gathered from these systems is difficult

to obtain with conventional techniques.

24

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Chapter 2: Flow characterization of a microfluidic device to selectively and reliably apply reagents to a cellular network*

INTRODUCTION

The use of microfluidics as analytical tools to investigate cellular systems has become

widespread in recent years [1-5]. The field of neuroscience, however, has yet to take full

advantage of the technique’s utility for studying brain function, particularly communication and

behavior in neural networks. Currently, most analytical techniques for studying changes in

network communication in the presence of a treatment involve bathing the entire culture in the

chemicals being investigated [6-8] or use glass micropipettes to expose single neurons in an in

vitro network to different solutions [9-11]. Unfortunately, neither of these methods allow

individual or small patches of cells to be exposed selectively since all cells are exposed to the

treatment in the case of a bath or the majority exposed via the rapid diffusion of solutions after

being “puffed” out of pipettes. While several researchers have begun to integrate fluidic systems

for perfusion and treatment with network cultures [12-19], these systems feature complex

designs that require advanced, multiple-step microfabrication techniques or expensive equipment

such as lasers and to date do not allow multiple cells to be addressed in culture with different

solutions at different locations.

Here a two-layer microfluidic device capable of selective exposure of specific cells and

subsequent monitoring of the network response has been created using soft lithography and its

flow patterns have been characterized. The microfluidic platform consists of a bottom layer of

channels used for the delivery of pharmacological solutions to specific cells in the network

(pharmacological channels) and a top layer of channels for gently directing the flow stream of

the pharmacological solutions with low linear flow rates (bulk flow channels). By varying the

bulk flow rates, the direction and height of the pharmacological fluid streams can be altered by

hydrodynamic focusing [20-22], allowing application of reagents to specific locations. * Adapted with permission from MF Santillo, IG Arcibal, AG Ewing, Lab Chip 2007, 7, 1212-1215. [doi:10.1039/b708928g] © 2007 Royal Society of Chemistry.

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Uniquely, this device is able to deliver different solutions to multiple sites in a network of cells

with controllable and well-defined laminar flow for both transient and long-term stimulations.

Computational fluid dynamics (CFD) simulations, as well as confocal fluorescence microscopy

and carbon-fiber amperometry experiments have been used to determine the direction and height

of the flow streams at various bulk flow rates. In the future, this platform will be used to

selectively and precisely expose nerve cells to different drugs, toxins, and other pharmacological

solutions while monitoring neural network activity via fluorescence microscopy.

PROCEDURE

Device fabrication

The fabrication details are illustrated in Figure 2.1a. Masks were designed in Adobe

Illustrator CS2 and printed onto transparency films by a laser photoplotter (The Photoplot

Store/International Phototool Co., Colorado Springs, CO). The pharmacological channel layer

was made by depositing two 100-µm thick layers of SU-8 50 photoresist (MicroChem Corp.,

Newton, MA) onto a silicon wafer (Silicon Quest International, Inc., Santa Clara, CA) and

exposing them sequentially with a mask aligner (Karl Suss MA6, Suss Microtec, Waterbury

Center, VT) according to the resist manufacturer protocol. The mold for the bulk channels was

also photolithographically fabricated with a single 200-µm layer of SU-8 100 resist. Photoresist

was developed with 1-methoxy-2-propyl acetate (SU-8 developer, MicroChem Corp., Newton,

MA). The master molds were stored under vacuum overnight in a desiccator with a few drops of

1H,1H,2H,2H-perfluorooctyldimethylchlorosilane (Alfa Aesar, Ward Hill, MA, USA) in a vial.

A 10:1 (base:curing agent by weight) mixture of PDMS prepolymer (Sylgard 184, Dow Corning,

Midland, MI) was poured onto the master molds and cured in an oven at 70 °C for 2 h. For the

pharmacological master, a weight was placed above the mold allowing the PDMS to form a thin,

even layer with the posts so outlet holes would form [23]. The PDMS was peeled away from the

master molds and 1.5-mm inlet holes removed with a leather punch. The pharmacological

channel layer of PDMS and a glass slide were exposed to oxygen plasma for 30 s at 75 W (M4L,

Metroline Industries, Corona, CA) and bonded together, followed by subsequent bonding of the

bulk channel layer on top of the pharmacological channel layer. For the purposes of this study,

only two bulk channels, arranged perpendicular to each other, were attached to the

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Figure 2.1. (a) Fabrication scheme for making the complete microfluidic device. The master for the lower pharmacological layer is produced from two layers of photoresist, which are exposed sequentially through masks (steps 1 and 2). PDMS and a weight are placed onto the master (step 3) and it is cured. The bulk channel layer involves a single photoresist layer and exposure (steps 1' and 2') to create the larger channel. Following PDMS curing on both masters, the polymer is removed and adhered to a glass slide via exposure to oxygen plasma (steps 3' and 4). Inlet holes and NanoPorts are not shown and only one pharmacological channel is shown for sake of simplicity. (b) Area of interest of the device showing nine pharmacological channel outlet holes and two bulk flow channels. In future studies, cells will be cultured on the surface in between the nine outlet holes. Inlet holes and NanoPorts are not shown.

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pharmacological layer for ease in flow characterization (Figure 2.1b). The distance between the

exits of these bulk channels and the pharmacological channel outlet holes was varied to

investigate the effects of distance on flow exiting the pharmacological channels. NanoPorts (N-

333, Upchurch Scientific, Oak Harbor, WA) were assembled according to the manufacturer's

instructions and attached to the pharmacological channel inlet holes.

CFD simulations

CFD simulations were performed with Comsol Multiphysics 3.3 (Comsol, Inc.,

Burlington, MA), a finite element analysis solver. A two-dimensional geometry was used to

model the microfluidic system in order to yield a cross-sectional view of the fluid flow. The

following constants were used: diffusion coefficient, D = 4.0 × 10-6 cm2 s-1 [24]; density, ρ = 1.0

× 103 kg m-3; dynamic viscosity, µ = 1.0 × 10-3 Pa s; initial concentration, c0 = 36 µM.

Incompressible Navier-Stokes equations were initally solved, given by:

uuuu 2∇+−∇=∇⋅+∂∂ μρ p

t

0=⋅∇ u

where u is velocity, t is time, ρ is density, p is pressure, and µ is dynamic (absolute) viscosity.

Subsequently, the convection/diffusion equation,

cDctc 2∇=∇⋅+∂∂ u

was solved, where c is concentration, t is time, u is velocity, and D is the diffusion coefficient.

Confocal fluorescence microscopy

Syringe pumps (Harvard Apparatus and KD Scientific, Holliston, MA) were used to

control the volumetric flow rates of 36 µM fluorescein isothiocyanate (FITC, Sigma, St. Louis,

MO) and water in the microfluidic system. The pumps interfaced with the NanoPorts and inlet

holes of the PDMS microchannels via plastic syringes connected to polyethylene tubing (0.86

mm i.d., 1.52 mm o.d.). Fluorescence images were acquired with a laser scanning confocal

microscope (Carl Zeiss LSM 5 Pascal, Thornwood, NY). FITC was excited with an argon-ion

laser at 488 nm and fluorescence emission was collected at 515 nm.

37

Amperometry

Syringe pumps were likewise utilized in conjunction with plastic syringes and

polyethylene tubing to control the volumetric flow rates of 100 µM catechol (Sigma, St. Louis,

MO), 1 M potassium chloride (Sigma, St. Louis, MO), and water in the microfluidic system. A

carbon-fiber microelectrode (5 µm diameter) was fabricated as described previously [25]. The

electrode was held at a potential of +700 mV versus a Ag/AgCl reference electrode for all

experiments. The position of the electrode in the fluid was controlled with a micromanipulator

under a microscope. The current generated by the oxidation of the catechol was measured and

recorded at different locations within the fluid stream, as the electrode was moved incrementally

in a vertical direction.

RESULTS AND DISCUSSION

The microfluidic platform

The microfluidic platform is comprised of two layers: a bottom layer consisting of nine

pharmacological channels, each terminating as 100 µm × 100 µm outlet holes on the surface, and

a top layer with channels 200 µm in height and 1.7-2.0 mm wide at the outlet (Figure 2.1b). The

lower channels are capable of delivering pharmacological agents to cells that will be adhered in

between the channel outlet holes on the surface of the device. The top layer consists of bulk

flow channels for the flow of water/KCl, or in the future, cell media across the surface. More

importantly, the bulk channels flow solutions perpendicular to those exiting the pharmacological

channels, thereby controlling the direction and height of the streams of fluid exiting from the

pharmacological channels.

Characterization of controlled flow in the device

Microscope images were acquired showing the top view of the pharmacological channel

outlet holes (Figure 2.2). A solution of FITC dye was flowed from the center pharmacological

channel, while water was flowed out of the bulk channel located at the left (Figure 2.2a), bottom

(Figure 2.2b), or the left and bottom bulk channels simultaneously (Figure 2.2c). As the dye

exited the hole, it flowed upward, out of the plane of the paper. However, the bulk flow of water

38

Figure 2.2. Fluorescence microscopy images of a stream of FITC (20 µL min-1) exiting a pharmacological channel outlet hole and being directed by bulk flow of water (2000 µL min-1;

black arrows) from the (a) left, (b) bottom, and (c) left and bottom simultaneously. Bulk flow channels are not shown in the images. Scale bar is 400 µm.

39

forced the FITC to flow parallel to the surface and not straight up. It is easy to see that this

direction of flow can be used to apply a specific reagent to a group of cells on a surface.

Furthermore, the flow is laminar since the fluids to flow in constant, predictable, discrete

streams.

In addition to controlling the direction of fluid flow, controlling the height of the flow

streams is also important as this allows application of reagents to one set of cells and away from

subsequent cells. Initially, two-dimensional CFD simulations were carried out to investigate the

interaction between the bulk flow of water and two adjacent pharmacological channels delivering

FITC and water. The results of these calculations are shown in Figure 2.3a. For these

simulations, the flow rates of the solutions exiting the pharmacological channels were held

constant at 20 µL min-1, while the flow of water from the bulk channel was varied from 1000 to

2000 µL min-1 in 250-µL min-1 increments (linear velocity at the channel outlet ranged from

4167 to 9804 µm s-1). At each flow rate, the height of FITC was measured 100 µm to the right

of the water outlet hole. The dye solution flowed upward but quickly turned to the right due to

the influence of the bulk flow of water. The FITC stream continued to flow to the right, staying

in contact with the surface, until reaching the water stream from the adjacent pharmacological

channel. At this point, the flow of water from the adjacent channel then forced the FITC stream

upward, driving the FITC away from the surface. This process can clearly be used to apply a

reagent to a cell located to the right of the first channel outlet, and, while avoiding application to

cells located beyond the second outlet hole.

Simulations of the FITC flow stream have been compared to flows measured

experimentally with confocal fluorescence microscopy under similar conditions. The confocal

microscope was used to acquire multiple images, each on a separate focal plane, which were

merged together to yield a three-dimensional image viewable from different angles. The flow

profile obtained with confocal microscopy (Figure 2.3b) shows FITC flowing up after exiting the

channel, and then traveling to the right in contact with the surface of the device. As shown with

the CFD simulation, once the FITC reached the adjacent water pharmacological channel outlet,

the FITC stream flows further upward and the two methods show similar profiles.

Carbon-fiber amperometry was also performed to support data collected with CFD

simulations and confocal microscopy. The characterization of flow by amperometry was

performed under the same conditions as the confocal experiments, with electroactive catechol

40

Figure 2.3. (a) CFD simulation showing the side-view concentration profile of FITC flow. The height of the FITC stream was measured 100 µm away from the water outlet hole. Scale bar is 100 µm. (b) Confocal fluorescence image of FITC flow viewed from the side, at a 20° angle above the surface. The displaced height of the FITC stream was measured 100 µm away from the water outlet hole. The bulk channel is not shown in the image. Scale bar is 100 µm. (c) Plot of displaced height of FITC flow stream compared to the bulk flow rate of water and distance, d, from the bulk channel to the outlet hole of FITC. Points show theoretical height calculated from simulations where d = 300 µm (Δ), d = 500 µm () and average height measured by confocal microscopy (n = 4) where d = 300 µm () and d = 500 µm (). The standard error of the mean ranges from 3 to 16 for each bulk flow rate for the confocal measurements.

41

replacing FITC and the use of KCl solution in lieu of water for bulk flow to allow current

conduction through the solution. A microelectrode was positioned 100 µm to the right of the

water outlet hole (Figure 2.4a) and the current was measured at various heights. Near the

surface, no current was detected, indicating that only water, which is not electroactive at the

potential applied to the electrode (+700 mV), was present. However, as the height of the

electrode was increased, measurable current was detected, indicating the presence of catechol

due to its oxidation to o-benzoquinone. Profiles generated from these data correlate well with

the confocal images and simulations of the FITC/water interaction.

Two parameters in this experiment affected both the heights of the FITC and catechol

streams exiting the pharmacological layer, the bulk flow rate and the distance, d, from the bulk

flow channel to the FITC/catechol outlet hole (Figures 2.3c and 2.4b). While keeping the

pharmacological channel flow rates constant at 20 µL min-1, the FITC/catechol streams

decreased in height as the bulk flow rate increased. As its rate was increased, bulk flow had

more of an influence on the FITC/catechol height, forcing the solutions to be more parallel with

the surface of the device. At low bulk flow rates, the FITC/catechol flow rate was more

dominant, causing it to travel in a more upward direction.

The distance, d, of the bulk flow channel to the FITC/catechol outlet hole also played a

role in the height of the FITC/catechol stream. When the bulk flow channel was closer to the

FITC/catechol outlet hole, the linear flow rate of water was higher versus a lower linear flow rate

when it is farther away and influences the height of FITC/catechol to a greater degree. Since a

typical cell is 10-20 µm in height, the fastest flow rate used in these experiments (2000 µL min-1)

would cause the FITC or catechol to be approximately 130 µm in height (Figures 2.3c and 2.4b),

thereby capable of avoiding application to cells in the region near the water outlet hole in future

experiments.

Though the displacement height calculated by CFD simulations follows a similar trend

when compared to those measured by confocal microscopy and amperometry (Figures 2.3c and

2.4b), some discrepancies exist between the simulations and experimental results. At higher bulk

flow rates, the simulations and experimental data are not significantly different at 95%

confidence, while they are significantly different at lower bulk flow rates. These differences

occur because the simulations were performed in only two dimensions, the simulations did not

take into account the parabolic flow profile in the missing dimension (across the surface of the

42

Figure 2.4. (a) Top-view microscope image of the amperometry setup showing two adjacent pharmacological channel outlet holes and carbon fiber electrode. The reference electrode and bulk flow channel are not shown. Scale bar is 100 µm. (b) Plot of the displaced height of catechol flow stream compared to the bulk flow rate of aqueous KCl solution and distance, d, from the bulk fluid channel to the catechol channel outlet. Points show theoretical height calculated from simulations where d = 200 µm (Δ), d = 600 µm () and average height measured by amperometry (n = 4) where d = 200 µm () and d = 600 µm (). The standard error of the mean ranges from 15 to 20 for each bulk flow rate for the amperometric measurements. Amperometry data was collected by IG Arcibal.

43

device). With this flow profile, the highest velocity occurs over the center set of outlet holes

while the velocity decreases as the flow spreads outward. Since the confocal and amperometry

experiments were completed using the outlets not directly in the center of the flow, the CFD

simulations, although similar, do not completely agree with the experimental data.

CONCLUSIONS

A PDMS microfluidic device for investigating neural communication has been

successfully fabricated by photolithography and oxygen plasma bonding. Computational fluid

dynamics simulations, confocal fluorescence microscopy, and carbon-fiber amperometry have

been used to characterize the flow profiles by measuring the height and direction of the flow

streams. This information will be subsequently used to stimulate and expose cells in different

areas of a patterned neural network.

44

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46

Chapter 3: Temporal analysis of protozoan lysis in a microfluidic device*

INTRODUCTION

Microfluidic and lab-on-a-chip devices for analyzing a variety of single cells, [1-6]

embryos, [7, 8] and whole animals [9, 10] have been recently developed. Microfluidic systems

are excellent tools for biological assays; they require small volumes of reagents and sample

sizes, and allow for multiple steps of an analysis to be integrated into a single system. In

addition, measurements on microfluidic chips can be multiplexed and/or automated allowing

simultaneous analyses to be performed. Commonly, microfluidic devices are rapidly prototyped

via soft lithography with poly(dimethylsiloxane) (PDMS), [11] an inexpensive, biocompatible

polymer. This soft lithographic fabrication technique allows for flexibility in device design

which can be tailored to meet the needs of the assay, making these systems ideally suited for

investigating biological phenomena. [12] One such phenomenon is the reaction of biological

cells following exposure to chemical biocides.

Biocidal agents (i.e., disinfectants and antiseptics) are an important class of chemical

compounds that encompass a variety of molecular sizes, structures, elemental compositions, and

modes of action. [13-20] Biocides exhibit a large degree of diversity since their targets—fungi,

protozoa, bacteria, viruses, and other parasites—all have unique cellular structure and

composition. Aldehydes, for example, are biocidal as they induce cross-linking of proteins and

DNA, whereas silver salts interact with thiol groups on membrane-bound enzymes, effectively

killing the cell. Many detergents and related compounds (e.g., quaternary ammonium

compounds and chlorhexidine digluconate) are employed as disinfectants and antiseptics whose

mode of action is disruption and permeabilization of the cellular membrane. [21-26] These

common compounds are often found in commercially available products; hence, determining

their efficacy and mode of action is important in evaluating their toxicity.

* Reproduced with permission from MF Santillo, ML Heien, AG Ewing, Lab Chip 2009, 9, 2796-2802. [doi:10.1039/b907942d] © 2009 Royal Society of Chemistry.

47

Current methods for evaluating biocidal efficacy and toxicity are carried out with either

liposomes or cells. Liposomes are useful models as they are easy to prepare and the membrane

composition can be controlled. [27] Typical studies of membrane lysis in liposomes use

spectrofluorimetry to monitor leakage of an encapsulated fluorophore. [28-33] These assays are

easy to perform and can provide valuable information; however, they involve a large population

and do not allow individual liposomes to be observed microscopically. Liposomes used in these

studies are often much smaller than cells (< 1 µm diameter), making direct microscopic imaging

difficult or impossible. Furthermore, liposomes are only simple membrane models and do not

contain all of the necessary components of biological membranes such as proteins. Toxicity

studies can also carried out by fluorescence or absorbance measurements in petri dishes or

microtiter plates of cell populations incubated with detergents and disinfectants. [34] However,

these studies are limited as it is difficult to collect data if membrane disruption occurs in a short

time frame. These assays do not allow cells to be imaged with single-cell resolution, preventing

the observation of morphological changes. When viability dye is released from lysed cells, there

is no means of removing it from solution. Similarly, populations of luminescent bacteria or

dinoflagellates have been employed as whole-cell biosensors to quantify toxicity in

environmental water samples. [35, 36] With these tests, cells are exposed to toxins, and

decreases in luminescence are monitored over time with a photometer. Unfortunately, these

assays suffer from many of the same challenges as assays performed using liposome and cell

populations (vide supra). In order to observe responses of individual cells upon chemical

exposure, compounds can be applied to cells with micropipettes and lysis observed via optical

microscopy. However, the solution applied using micropipettes is rapidly diluted due to

diffusion, thus forming irreproducible temporal and spatial concentration gradients [37-39]

leading to variation in the flux across cells. Additionally, micropipettes often expose a single

cell or liposome at a time, limiting throughput. Lastly, each of the aforementioned techniques

requires large volumes along with large cell populations that are not always available, which is

another benefit of the microliter volumes utilized in microfluidics.

There are several techniques [2, 40, 41] for lysing single cells in microfluidic devices,

including the use of lasers and electrical pulses, application of heat, mechanical lysis with

nanobarbs, and chemical lysis with detergents. However, these lysis applications do not focus on

the use of detergents as biocidal agents with the goal of screening disinfectant efficacy on a

48

microbial species. Here, a microfluidic device has been fabricated to quantify changes in

membrane integrity after chemical biocide and detergent exposure on the amoeba Arcella

vulgaris, a common, non-pathogenic unicellular protozoan species. Arcella serves as a model for

several pathogenic amoebae responsible for diseases such as amoebiasis (dysentery), [42]

acanthamoeba keratitis, [43, 44] granulomatous amoebic encephalitis, [44, 45] and primary

amoebic meningoencephalitis. [44, 46-48] The device presented here allows the real-time

monitoring of multiple cells via fluorescence microscopy. In contrast to the application of

biocides with micropipettes, the fluid flow is laminar, simultaneously exposing many cells to a

uniform concentration of detergent over an extended period of time. The unique structure of the

system contains chambers that capture cells and prevent them from moving while under

continuous flow. The device was characterized by determining the effects of flow rate and

concentration of biocides on trapped cells. Cell lysis rates among detergents and biocides were

compared, yielding information on membrane integrity and efficacy of these compounds as

biocidal agents on amoeboid species.

PROCEDURE

Chemicals

Poly(dimethylsiloxane) (PDMS/Sylgard 184) was obtained from Dow Corning Corp.

(Midland, MI, USA). SU-8 photoresist and developer solution (1-methoxy-2-propyl acetate)

were purchased from MicroChem Corp. (Newton, MA, USA), and 3-in silicon wafers were

purchased from Silicon Quest International, Inc. (Santa Clara, CA, USA). Benzalkonium

chloride, chlorhexidine digluconate (20% v/v in water), phenol, sodium dodecyl sulfate (SDS),

and Triton X-100 were obtained from Sigma-Aldrich Co. (St. Louis, MO, USA).

Chlorotrimethylsilane was obtained from Fluka/Sigma-Aldrich Co. (Seelze, Germany) and

acetone was from EMD Chemicals, Inc. (Gibbstown, NJ, USA). Fluorescein diacetate and Alexa

Fluor 647 were obtained from Invitrogen Corp. (Eugene, OR, USA). Water (18 MΩ) was

purified through a Millipore Milli-Q system (Billerica, MA, USA).

49

Microfluidic device fabrication

Masks were designed in Illustrator CS3 (Adobe Systems, Inc., San Jose, CA, USA) and

printed onto transparency films by a laser photoplotter (CAD/Art Services, Inc., Bandon, OR,

USA). A layer of SU-8 25 photoresist (50 µm) was spun onto a silicon wafer, exposed through a

mask with a mask aligner (Karl Suss MA6, Suss Microtec, Waterbury Center, VT, USA), and

developed according to the photoresist manufacturer protocol. This master mold contains the

capture channels and serves as the lower layer in the final device. A second mold was prepared

with a 10-µm layer of SU-8 5 which does not contain any capture wells (upper layer channel).

Both master molds were stored under vacuum in a desiccator with 1 mL of chlorotrimethylsilane

for at least 1 h. A 10:1 (base:curing agent by weight) mixture of PDMS prepolymer was poured

onto the master molds and cured in an oven at 70 °C for 2 h. PDMS was peeled away from the

master molds and a 1-mm inlet hole was removed with a tissue punch (Harris Uni-Core) on the

upper layer. The two PDMS layers were exposed to air plasma for 90 s at 18 W (PDC-32G

plasma cleaner, Harrick Plasma, Ithaca, NY, USA). The lower layer channels were placed face

up, and the upper layer channel was placed face down and conformally sealed (Figure 3.1a). The

device was treated with air plasma prior to loading with fluids to increase hydophilicity and

wetting of the channels.

Fluorescence microscopy and flow experiments

A syringe pump (KD Scientific Inc., Holliston, MA, USA) was used to control the

volumetric flow rates of solutions in the microfluidic device. The pump interfaced with the inlet

holes of the PDMS microchannels via syringes connected to polyethylene tubing (0.58 mm i.d.,

0.965 mm o.d.). Stock solutions of lysis agents (10 mM in water) were diluted in filtered Arcella

media. Alexa Fluor 647 (1.33 mg mL-1 water) was diluted to 6.67 µg mL-1 in working lysis

solutions to facilitate the time at which the protozoa were exposed to detergents. Fluorescein

diacetate (14.4 mM in acetone) was diluted to 72 µM in suspensions of Arcella vulgaris

(Carolina Biological Supply Co., Burlington, NC, USA) for at least 3 min before introducing

them into the device. Fluorescence images were acquired with a laser-scanning confocal

microscope (TCS SP5, Leica Microsystems, Inc., Bannockburn, IL, USA). Fluorescein was

excited with an argon-ion laser at 488 nm and fluorescence collected at 500-580 nm; Alexa Fluor

50

Figure 3.1. (a) Microfluidic device assembly in which two PDMS channels facing each other are sealed together. The bottom channels are 50 µm high and the top channel is 10 µm high. Drawing is not to scale, and only three of eight total chambers are shown. (b) Diagram of the chambers along with channel dimensions. (c) Image of Arcella incubated with fluorescein diacetate in capture chambers. Scale bar is 100 µm.

51

647 was excited with a HeNe laser at 633 nm and fluorescence collected at 640-700 nm.

Fluorescence intensities were normalized according to the equation,

Inorm =I − Ib

Imax − Ib

where Inorm is normalized intensity, I is raw intensity, Imax is maximum intensity before lysis, and

Ib is background intensity. Lysis was quantified by measuring the decay time and lysis onset

time. The decay time is defined as the time in which fluorescence intensity decreases from 95%

to 5% (t0.95-t0.05). Lysis onset time represents the time at which there is a 50% decrease in

fluorescence intensity due to lysis (t0.50) and is indicative of the time required for lysis to occur

after initial exposure to detergent. All errors are expressed as standard error of the mean (SEM).

Computational fluid dynamics (CFD) simulations

CFD simulations were performed with Comsol Multiphysics 3.4 (Comsol, Inc.,

Burlington, MA, USA), a finite element method solver in order to determine the velocity flow

profile in three dimensions. The density and dynamic viscosity of water were used (ρ = 1.0 g

cm-3 and µ = 1.0 × 10-3 Pa s). Incompressible Navier-Stokes equations were solved, given by:

∂u∂t

+ ρu ⋅ ∇u = −∇p + μ∇ 2u

∇ ⋅u = 0

where u is velocity, t is time, ρ is density, p is pressure, and µ is dynamic (absolute) viscosity.

RESULTS AND DISCUSSION

Device design and characterization

A microfluidic system for quantifying the toxicity of several compounds was

characterized by studying the effects of biocide flow rate and concentration on single cells. The

microfluidic device for monitoring cell lysis is depicted in Figure 3.1. Figure 3.1a shows two

layers of channels, each cast from an SU-8 master mold, which are sealed together resulting in a

complete system. The bottom channel (50 µm high) has a 1-mm wide inlet which eventually

diverges to a width of 2 mm (Figure 3.1b). At this point, the wide channel splits into eight

separate capture chambers. The entrance to each chamber is 250 µm wide and narrows to 100

52

µm. On top of the capture chambers is a 10-µm high channel that extends beyond the end of the

chambers. As fluid flows through the system, cells are captured in the chambers (Figure 3.1c)

and fluid continues through the top channel so it can exit the device. The width and height of the

capture chambers confines single cells or small groups of cells to the chambers during lysis. The

number of cells trapped in each chamber was related to the cell density of the suspension and the

amount of time spent flowing the cell suspension through the device. An average of 1.75 ± 0.13

cells (n = 23 runs) were captured in each chamber. The use of multiple chambers, each

accommodating between one and eight cells, demonstrates high-throughput screening capability

with single-cell resolution. Although not quantified, cells occasionally escaped capture

chambers during the loading process. No cells escaped during biocide perfusion in all

experiments in which linear fluid velocities were 360, 1080, and 3600 µm s-1.

Hydrodynamic flow through microchannels results in a parabolic velocity profile,

meaning the shear stress and the flux of molecules will vary across the width of a channel. The

system presented here has a single, large channel that splits into eight separate ones, each 100

µm wide and able to accommodate protozoan cells. A computational fluid dynamics (CFD)

simulation (Figure 3.2) shows the linear fluid velocity profile in the microfluidic system. Fluid

velocity at the entrance of the channels is low and increases further downstream as the chamber

width decreases, as illustrated in the cross-sectional velocity profiles (colored boxes) taken in

Figure 3.2a. The velocity profile taken across the width of all eight channels possesses minimal

channel-to-channel variation (Figure 3.2b, trace taken at a distance of 30 µm from the channel

floor and channel ceiling). Areas of zero velocity in between parabolae correspond to the walls

located between channels. The results of the simulation show that velocity profiles in all

chambers are nearly identical, and therefore cells located in them would experience equal shear

stress and fluid flux. The small deviations in maximum velocity (< 5%) for each channel are

attributed to voxel size in the simulation which limits computational accuracy. Volumetric flow

rates used in lysis studies were 5, 15, and 50 µL min-1, corresponding to average linear flow

velocities of 360, 1080, and 3600 µm s-1, and Reynolds numbers (Re) of 0.036, 0.108, and 0.36,

respectively. Therefore, the flow in this system is laminar (Re << 2300).

53

Figure 3.2. (a) Three-dimensional CFD simulation displaying cross-sectional linear fluid velocity profiles in the microfluidic chambers corresponding to a volumetric flow rate of 5 µL min-1. Only five of eight total chambers are shown. (b) Normalized velocity line profile taken across the width of all eight chambers, 30 µm from the channel floor.

54

Single cell vs. average lysis

A motivating factor in using microfluidics for cellular assays is the ability to probe events

at the single cell level. This is in contrast to data collected from a population of cells, which

would yield an average value for the entire collection of cells. Here we explored the responses

of single cells during cell lysis with benzalkonium chloride, a quaternary ammonium compound

and cationic detergent. Arcella vulgaris cells were first incubated with fluorescein diacetate, a

cell viability dye, which is nonfluorescent and can penetrate cell membranes. Once inside the

cell, endogenous esterases cleave acetyl groups on the dye molecule, yielding fluorescein which

has strong fluorescence emission at a wavelength of 520 nm. After incubation with the dye, the

cells were loaded into the device and then exposed to benzalkonium chloride. Fluorescence

images over time for a single Arcella exposed to 250-µM benzalkonium chloride at a flow rate of

5 µL min-1 are shown in Figure 3.3a-d. A marked decrease in fluorescence intensity over time,

corresponding to the lysis event, is evident in these images. It is important to note that there is

debris present around the cell pictured in Figure 3.3a-d, which was present in the suspension.

Some of this debris consists of proteinous shells from dead Arcella in the original sample prior to

loading into the device. Quantitative data regarding lysis is expressed as a plot of normalized

fluorescence intensity over time in Figure 3.3e. In order to determine if shear stress caused cells

to leak fluorescein, which would lead to decreased fluorescence over time, control flow

experiments were carried out using only media (black trace in Figure 3.3e). The results confirm

that the cells do not leak dye or lose integrity due to shear stress. Furthermore, the laser

excitation did not cause photobleaching over the period of time corresponding to lysis.

Arcella cells in the channels were then exposed to benzalkonium chloride, and the

fluorescence intensity monitored over time. The fluorescence intensities of three individual

Arcella cells along with an average of 15 cells exposed to benzalkonium chloride are displayed

in Figure 3.3e. The average trace was determined by averaging the fluorescence intensities of 15

individual cells at each time point. The average fluorescence reveals a broad decrease in

intensity over time (decay time, t0.95-t0.05) and larger variation when compared to a single cell.

The results for each individual cell lysis event illustrate that the decay time for single cells (41 ±

2 s, n = 19) is much faster than the decay time measured from the average trace of 15 cells (220

s). The decay time of the average trace appears to be a reflection of the variation in the lysis

onset times (t0.50) for individual Arcella. There are several reasons why the single cell lysis onset

55

Figure 3.3. Fluorescence images of Arcella exposed to a 5 µL min-1 flow of 250 µM benzalkonium chloride after (a) 195 s, (b) 215 s, (c) 235 s, and (d) 255 s. Scale bar is 50 µm. (e) Normalized fluorescence of three representative individual Arcella cells () and average response (, n = 15 cells) during exposure to 250 µM benzalkonium chloride at 5.0 µL min-1. Control cells (, n = 4) were exposed to media only. Error bars represent SEM.

56

times may vary. Arcella are a type of amoebae; their shape and membranes deform as

pseudopods grow from the cell, meaning their sizes may vary. These differences in size can

account for different lysis onset times; cells with larger intracellular volumes will take a longer

time for the fluorophore, and thus the intracellular contents, to be released. Furthermore, Arcella

are testate, meaning that they are protected by a porous, hemispherical shell. The orientation of

the cell can account for the differences in lysis onset times since one side of the shell might be

completely exposed while the other areas contain a porous coat. Although the cells have varying

lysis onset times (176 ± 13 s, n = 19), the decay time for each cell is shorter and has less

variation (41 ± 2 s, n = 19). This demonstrates that each lysis event, once begun, is relatively

rapid.

Effect of flow velocity and concentration on lysis rates

When employing conventional assays (vide supra) without hydrodynamic flow, lysis

depends on concentration and diffusive flux. Convection, although present, is uncontrollable and

thus highly variable in conventional assays. Conversely, in the microfluidic device, cells are

exposed to a constant flow of detergent, meaning the mass transfer of detergent to the cell is

faster than in a stagnant solution. The microfluidic system presented here allows accurate

control of concentration and convection, thus lysis is dependent on the convective flux.

Furthermore, flow enables detergent molecules that solubilize lipids in the membrane to be

removed, exposing more membrane which can be solubilized further. To investigate the

influence of flow rate and concentration on cell lysis, solutions of benzalkonium chloride (100-

1000 µM) were pumped through the device at different volumetric flow rates (5.0, 15.0, and 50.0

µL min-1) followed by monitoring the fluorescence intensity of individual cells over time. The

results of these experiments are plotted in Figure 3.4a and b showing the effects of concentration

and flow rate of benzalkonium chloride on lysis decay time and onset time. At low

concentration, Arcella is exposed to less detergent, which yields significantly longer lysis onset

and decay times (Figure 3.4a, two-way ANOVA, F = 9.8, p < 0.0001; Figure 3.4b, F = 8.4, p <

0.0001). Alternatively, higher detergent concentrations induce lysis in a shorter amount of time.

The traces in Figure 3.4a and b decrease with increasing concentration and flow rate although at

low concentrations the decrease in decay and lysis onset times is sharper than at higher

concentrations where the decrease is less apparent. In addition to concentration, there are also

57

Figure 3.4. Plots of (a) decay and (b) lysis onset times of Arcella cells exposed to benzalkonium chloride (100-1000 µM) at flow rates of 5.0 (), 15.0 (), and 50.0 µL min-1 (). (c) Amount of benzalkonium chloride delivered to cells calculated from lysis onset time at the same flow rates in parts (a) and (b). Values are expressed as mean ± SEM (the number of cells, n, ranges from 17 to 75 for each point).

58

significant differences in the rates of lysis versus flow rate. At higher flow rates, more detergent

is delivered to cells in the device, whereas at lower flow rates, less detergent is delivered and

there are longer lysis onset/decay times.

The total amount of biocide required to cause cell lysis can be determined by calculating

convective flux, J:

cvAtNJ ==

where N is the amount of biocide in moles, A is cross-sectional area of the microfluidic channel, t

is the lysis onset time (defined as the time at which fluorescence intensity of intracellular

viability dye reached 50%), c is bulk concentration, and v is average linear velocity determined

by CFD simulation. This allows the amount of biocide delivered to a cell at each lysis onset time

to be determined. The results in Figure 3.4c illustrate the differences in amount of benzalkonium

chloride required to cause cell lysis at concentrations ranging from 100-1000 µM and flow rates

5.0, 15.0, and 50.0 µL min-1. In general, for each flow rate, the amount of benzalkonium

chloride required to lyse the cell remained constant as the concentration is varied; straight lines

fit to the data at each flow rate have slopes that are not significantly non-zero (p > 0.22 for each

line). There was a difference in the amount of detergent required to induce lysis across the three

flow rates, but within each flow rate the concentration did not matter. It is important to note that

at 50.0 µL min-1, there was more variation in the amount of benzalkonium delivered to induce

lysis (Figure 3.4c); however, the slope is not significantly non-zero. We hypothesize that at

higher flow rates, there is less interaction time between the detergent and cell membrane;

therefore, a higher amount of detergent was required for solubilization and lysis. At a flow rate

of 50.0 µL min-1 and concentration of 250 µM, a much larger amount of detergent was required,

compared to the other concentrations at the same flow rate.

Comparison of various equimolar detergent lysis profiles

In addition to benzalkonium chloride, the lysis of Arcella during exposure to several

biocides including chlorhexidine digluconate, phenol, sodium dodecyl sulfate, and Triton X-100

were also studied to compare their efficacy. With the microfluidic system, Arcella was exposed

to equimolar concentrations (1 mM) of biocides and detergents at a constant flow rate of 5.0 µL

min-1. The decay and lysis onset times of these biocides and detergents are shown in Figure 3.5.

59

Figure 3.5. (a) Decay and (b) lysis onset times of Arcella exposed to 1000 µM benzalkonium chloride (BAC, n = 26 cells), chlorhexidine digluconate (CDG, n = 16), phenol (Ph, n > 20), sodium dodecyl sulfate (SDS, n > 20), and Triton X-100 (TX-100, n = 15). Flow rate for all biocides was 5.0 µL min-1. ∞ indicates that lysis did not occur within 40 min. Values are expressed as mean ± SEM.

60

Neither SDS nor phenol induced lysis after 40 min of exposure. It has been reported that

Amoeba proteus contains a mucopolysaccharide coating on the membrane which is negatively

charged. [49] Since Arcella is also an amoeboid species, it may similarly contain a negatively-

charged membrane which hinders lysis by SDS. For the same reason, benzalkonium chloride is

an effective lysis agent of Arcella as it is a cationic, quaternary ammonium detergent, enabling it

to effectively penetrate and solubilize components of the membrane. This is characterized by the

short decay and lysis onset times in Figure 3.5. Conversely, chlorhexidine digluconate had

relatively long decay times. Chlorhexidine is known to cause congealment and coagulation in

cell cytoplasm [15] making it an effective biocide. Unlike benzalkonium chloride, which is

characterized by short, sudden decay times, the loss of fluorescence began quickly after Arcella

were exposed to chlorhexidine. Triton X-100, a nonionic detergent, was similarly effective in

causing lysis, characterized by short decay and lysis onset times, when compared to

benzalkonium chloride.

CONCLUSIONS

A microfluidic chip has been fabricated to carry out temporal analysis of individual cells

exposed to various biocides at a constant, controlled concentration. These characteristics are

difficult to achieve with conventional methods. Arcella vulgaris cells, a model for pathogenic

amoebae, were lysed with different biocidal agents and the concentration and flow rate

dependence was investigated. With this microfluidic system, lysis events from single cells were

quantified, yielding information not easily obtained with population study using conventional

techniques. Results show that lysis rates are dependent on both concentration and flow rate, and

that there was a wide range of lysis rates among the biocides and detergents employed in these

studies.

61

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Chapter 4: Computational modeling of electrochemical detection on microfluidic chips*

INTRODUCTION

Miniaturization of laboratory analyses offers many improvements when compared to

traditional laboratory methods. Indeed, microfluidic platforms, lab-on-a-chip devices, and micro

total analysis systems (µ-TAS) [1, 2] consume small amounts of reagents, generate less waste,

and offer portable, integrated systems capable of automated, high-throughput assays. Many

detection schemes can be coupled to these devices, making microfluidic systems applicable to a

wide range of analyses. The most popular detection mode, laser-induced fluorescence, offers

high sensitivity. Unfortunately, not all chemical species are fluorescent; nonfluorescent species

must be derivatized, thus adding an additional degree of complexity to the analysis. Other

optical methods [3] such as UV/visible absorbance are seldom used in microfluidic systems

because small path lengths present in microchannels lead to low sensitivity and, consequently,

higher limits of detection. Mass spectrometry is unique because it yields the chemical identity of

a substance; however, mass spectrometers are often large and expensive, negating the advantages

of portability and integration. Nevertheless, portable mass spectrometers are under development

[4-6] that may eventually become common in portable microfluidic systems.

Electrochemical detection offers many advantages for measuring molecules on

microfluidic chips [7-10]. Electrochemical detectors consume small amounts of power, making

them an excellent choice for portable microsystems that perform clinical point-of-care testing

(e.g., glucose sensors [11, 12] and the commercially-available i-STAT portable clinical analyzer

[13-15]). Additionally, electrochemical detection does not require large equipment, which is

another advantage for incorporation in portable devices. Many chemical species are

electroactive, thus labeling and derivatization are not required. If an analyte is not electroactive,

a detection scheme using an enzyme-modified electrode is often used. The enzyme produces an * Part of this chapter was adapted with permission from DM Omiatek, MF Santillo, ML Heien, AG Ewing, Anal. Chem. 2009, 81, 2294-2302. [doi:10.1021/ac802466g] © 2009 American Chemical Society. Part of this chapter was also submitted (Oct 2009) as a trends article authored by MF Santillo, ML Heien, and AG Ewing to Anal. Bioanal. Chem. (© Springer-Verlag).

65

electroactive molecule based on the analyte concentration, yielding an electrochemical signal.

Both high sensitivity and selectivity are achieved with electrochemical detection. The most

popular electrochemical detection mode for microfluidics is amperometry. A working electrode

is held at a constant potential versus a reference electrode. When chemical species in solution

reaches the electrode surface, it is oxidized or reduced; the measured current is proportional to

the amount of species present. Amperometry is useful for detecting neurotransmitters,

metabolites, and other small molecules, which have been electrophoretically separated.

Mathematical modeling is a useful tool for the design and validation of experimental data

from microfluidic systems [16-18]. Microfluidic system design is labor-intensive since

parameters such as channel dimensions and flow rates must be optimized for a given device.

There is less labor involved performing a computational analysis versus the development,

fabrication, and subsequent testing of several microdevices with varied geometry and

parameters, which saves time. Validation is another benefit of computational modeling;

experimental results can be explained by known mathematical expressions. Once a solution is

obtained from a model, other system parameters may be extrapolated. Perhaps the greatest

advantage of computational modeling is that different physical domains can be coupled and

solved. Often in microfluidic devices there are several modes of transport involved and several

processes occurring simultaneously (e.g., convection, diffusion, chemical reactions, and surface

binding); equations describing these domains can be coupled and solved, yielding a solution to a

complex set of phenomena.

Computational fluid dynamics simulations can be performed with manually written code

or commercial software packages. Commercial packages have become popular in the

microfluidics community in the past decade because commercial packages are designed to be

user-friendly; the goal of these programs is to allow researchers in an interdisciplinary field such

as microfluidics, who may not have backgrounds in fluid dynamics, to successfully model

microfluidic phenomena. Some examples of commercially available software packages [19]

include Comsol Multiphysics (formally Femlab; Comsol, Inc.), Fluent (Ansys, Inc.), CFD-ACE+

(CFD Research Corp.), and Coventor (Coventor, Inc.).

Here computational fluid dynamics (CFD) simulations were used to design and validate

electrochemical detection in two unique microfluidic systems: a hybrid capillary-microfluidic

device for the separation, lysis, and quantification of neurotransmitter in vesicles and a

66

microchip electrophoresis chip for the coulometrically efficient amperometric detection of

neurotransmitters. In both systems, modeling was successfully applied to determine the

concentration flow profiles resulting from different flow rates. The results both validate

experimental data and serve as a framework for future development.

PROCEDURE

CFD simulations were performed with Comsol Multiphysics 3.5 (Comsol, Inc.,

Burlington, MA), a finite element analysis program. The finite element method is a

mathematical technique commonly used to solve partial differential equations in systems

possessing a complex geometry. Figure 4.1 outlines the steps involved of a typical model of an

electrode under hydrodynamic flow in a microchannel with the goal of obtaining information on

the amount of generated current. A simple diagram describing the system (Figure 4.1a) shows a

side view of a microchannel with an electrode located on the channel floor. In this system, as

fluid flows over the electrode, molecules in the fluid undergo a redox reaction at the electrode,

and the chemical species flow out of the system. Here a two-dimensional geometry was used to

model the electrode because a three-dimensional model would be computationally intensive.

Nevertheless, the use of a two-dimensional geometry is sufficient if the channel width is much

larger than the height because the velocity profile will remain constant across the majority of the

channel width.

After defining the geometry of the system, the domain is discretized (divided) into a

number of smaller parts (i.e., finite elements), which is referred to as the mesh. The discretized

domain is illustrated in Figure 4.1b in which the individual triangular spatial elements can be

seen. Smaller spatial elements imply a more accurate solution; however, the higher number of

elements increases computational time. Next, equations describing the physical processes

occurring in the system are applied (Figure 4.1c). Navier-Stokes equations, which describe the

velocity and pressure distribution in the microchannel, are solved. Additionally,

convection/diffusion equations are solved, yielding information on concentration within the

microchannel domain. Boundary conditions for both equations are then applied so that a unique

solution can be obtained. For the Navier-Stokes equations, an initial velocity is defined where

fluid is introduced into the system (u = u0), the velocity at the walls is equal to zero (u = 0;

referred to as the no-slip condition), and pressure is defined to be zero at the outlet (p = 0).

67

Figure 4.1 Example outlining the steps of the finite element method applied to a microchannel electrode. (a) The initial geometry shows the side view of a channel with an electrode and fluid flowing from left to right. (b) The system is discretized into a finite number of elements. (c) Navier-Stokes and convection/diffusion transport equations are applied along with boundary conditions. (d) Concentration and velocity are plotted over the spatial domain.

68

Similarly, for convective/diffusive transport, an initial bulk concentration of species A is defined

at the inlet (c = c0), convective flux is set at the outlet [n · (–D∇c) = 0], and the walls are defined

to be insulative [n · (–D∇c + cu) = 0]. At the electrode surface, the concentration of species A is

equal to zero (c = 0), reflecting its consumption at the electrode from the electrochemical

reaction and conversion to B. This assumption is made if the redox processes are mass-transfer

limited. Alternatively, equations for electron transfer kinetics (e.g., Butler-Volmer) or

adsorption (e.g., Langmuir isotherm) can be applied at the electrode surface in situations where

the process is not mass-transfer limited. It is important to note that simulation results can be

steady-state or time-dependent; in the case of time-dependent processes, initial conditions at time

zero must also be defined. After solving, physical descriptions of the system are plotted

throughout the geometric domain (Figure 4.1d). In the example shown in Figure 4.1,

concentration and velocity profiles are plotted over the geometrical domain of the microfluidic

channel after solving the Navier-Stokes and convective/diffusive transport equations at steady-

state. These results are displayed graphically and the values between elemental nodes are

interpolated such that the values are continuous over the entire geometric domain.

RESULTS AND DISCUSSION

Modeling a device for quantification of vesicles loaded with neurotransmitters

Neurons communicate by propagating electrical and chemical signals from cell to cell

within a complex network. An action potential (electrical impulse) is propagated along the axon,

and eventually terminates at the synapse, where it initiates exocytosis. During exocytosis,

vesicles containing neurotransmitters fuse with the membrane. The neurotransmitters are

released into the synaptic cleft and once there, the neurotransmitters diffuse out of the cleft, may

be reuptaken by the presynaptic cell, or the molecules bind to receptors on the postsynaptic

neuron. Upon binding to a receptor, the postsynaptic cell may either begin another action

potential or inhibit one from forming. Vesicles play a central role in neural communication as

they store neurotransmitter molecules prior to exocytosis and binding to postsynaptic receptors.

Knowledge of the size, chemical identity, and amount of neurotransmitter in synaptic vesicles is

important, and a direct method of analyzing small synaptic vesicles can be achieved with

capillary electrophoresis coupled with amperometric detection.

69

The system presented here (Figure 4.2a) features a fused silica capillary (15 µm diameter

and etched to 30 µm at the exit) interfaced with a microfluidic chip containing channels 125 µm

high. Large unilamellar vesicles encapsulated with catechol were used as synthetic models of

synaptic vesicles containing biogenic amine neurotransmitter molecules. Suspensions of vesicles

were injected into the capillary where they were separated. Upon exiting the capillary, separated

vesicles were exposed to a parallel (sheath) flow of sodium dodecyl sulfate, a chemical lysis

solution. The exposure of liposomes exiting the capillary to the parallel flow of chemical lysis

solution caused the release of the electroactive catechol. The released catechol was oxidized at a

cylindrical carbon fiber electrode (5 µm diameter and 500 µm long), positioned approximately

10 µm from the capillary exit. The current generated at the electrode due to the oxidation of

catechol was proportional to the amount of catechol present in the vesicle.

Both CFD simulations and confocal fluorescence microscopy were used to visualize flow

profiles of rhodamine B dye exiting the capillary along with sheath flow of buffer, and the data is

presented in Figure 4.2b. The simulations model the channel in two dimensions as viewed from

the top. In the model, the velocity of rhodamine dye solution in the capillary was fixed at 0.055

cm s-1, and the sheath flow rates were varied (0.1, 0.5, and 2.0 μL min-1) to explore the effects of

hydrodynamic focusing. An optimal sheath flow rate would confine the eluent to the diffusion

layer of the detection electrode and allow ample time for interaction of the eluent with the

electrode. To determine the optimal flow rate, concentration line profiles presented in Figure

4.2b were taken across the width of the channel 50 µm downstream from the capillary outlet. As

the sheath flow rate increased, the eluent was hydrodynamically focused, minimizing diffusional

broadening around the detection electrode (the electrode was not included in these simulations

for sake of simplicity). The CFD simulation concentration flow profiles match those obtained by

fluorescence microscopy; correlation coefficients (r2) between the simulation and fluorescence

data were 0.99, 0.98, and 0.96 for the 0.1, 0.5, and 2.0 μL min-1 sheath flow rates, respectively.

This illustrates the importance of electrode position and flow rate selection for optimal detection

in this platform. An electrode with a radius of 3 μm has a diffusion layer thickness of

approximately 20 μm. According to the data in Figure 4.2b, at 0.1 μL min-1 the electrode

diffusion layer does not encompass the eluent concentration profile, meaning that much of the

eluent flows past the electrode without being detected. Conversely, at 2.0 μL min-1 the diffusion

layer encompasses the entire eluent concentration profile. However, at this flow rate there is less

70

Figure 4.2. (a) Top-view, two-dimensional geometry of the device used in simulations for separation, lysis, and detection of neurotransmitter in vesicles. The electrode was not included in simulations. (b) Concentration profiles taken across channel width of at sheath flow rates 0.1, 0.5, and 2.0 µL min-1 obtained from fluorescence microscopy (red traces) and CFD simulations (black traces) along with fluorescence images and concentration profiles determined from simulations. Fluorescence data was smoothed using a moving average of five points. Scale bars are 50 µm.

71

interaction time of the eluent with the electrode; the linear flow velocity in the channel is 0.082

cm s-1, allowing only 0.6 s for the solution to interact with a 500 μm long electrode located at the

capillary outlet. The intermediate sheath flow rate (0.5 μL min-1) allows approximately 2.4 s of

interaction time with the electrode and encompasses approximately 70 % of the eluent

concentration profile. Therefore, the intermediate sheath flow rate of 0.5 μL min-1 allows a

compromise between the effects of convection and diffusion, i.e., the interaction time of eluent

with the electrode is maximized and the effects of diffusion are minimized.

Modeling coulometrically efficient amperometric detection for microchip separations

When quantifying current generated by bulk electrolysis, Faraday’s law can be applied,

given by:

nNFidtQ == ∫

where Q is charge, i is current, t is time, n is the number of electrons per equivalent, N is amount

in moles, and F is Faraday’s constant (96485 C mol-1). Unfortunately, most amperometric

sensors do not operate in this regime, which is problematic when quantifying low amounts of

analyte. With most amperometric sensors, the charge is proportional to current, but cannot be

calculated directly as with bulk electrolysis. Microchip electrophoresis coupled with

electrochemical detection has excellent mass sensitivity; therefore, it is important to maximize

detection sensitivity when quantifying such low amounts. With an efficient electrophoretic

separation chip quantification is also simplified because all electroactive analyte is being

oxidized, making it trivial to determine the amount via Faraday’s law for bulk electrolysis. It is

for these reasons that efficient amperometric detection is desired when performing microchip

separations.

A device for coulometrically efficient amperometric detection is illustrated in Figure 4.3.

The device contains two 300-µm wide channels molded in PDMS, located perpendicular to each

other, which are bonded to a quartz wafer substrate that contains a patterned carbon electrode

(500 nm high, 100 µm long, and 300 µm wide). Sample introduction is accomplished via a

cross-T injection scheme [20]. To inject sample, voltage is applied to a reservoir containing

sample and a waste reservoir, which are located directly across from each other in the shorter

72

Figure 4.3. (a) Top-view illustration of the complete microfluidic device for coulometrically efficient detection. (b) Three-dimensional illustration of the modeled detection region.

73

channel (Figure 4.3a). After a sufficient amount of sample has electrophoretically migrated into

the channel, voltage is switched to the buffer and waste reservoirs, located at the beginning and

end, respectively, of the longer channel allowing the compounds in the sample to be separated

and then detected at the carbon electrode.

Simulations were performed to investigate the relationship between flow rate, channel

height, and the amount of current generated at the electrode. The channel was modeled in two

dimensions, yielding a side-view profile perpendicular to fluid flow in the microchannel.

Simulations were first performed on a device with a channel height h = 5 µm, and it was

assumed a molecule such as dopamine was used (the diffusion coefficient was fixed at D = 5.0 ×

10-6 cm2 s-1). The linear velocity was varied from 0.06 to 1.00 cm s-1, which exceeded the typical

velocities present in microchip electrophoresis (1 × 10-2 cm s-1). Side-view concentration profile

images at the electrode for v = 0.06, 0.28, and 0.83 cm s-1 are presented in Figure 4.4a, b, and c,

respectively. At low flow rate (0.06 cm s-1, Figure 4.4a), most of the material in solution was

oxidized at the electrode since the concentration approached zero toward the top of the channel

and further distance downstream. As the flow rate was increased (Figure 4.4b and c), convection

dominated over diffusion and more material was able to flow through the channel past the

electrode without being oxidized. Therefore, it is concluded that under conditions of lower flow

rates, more analyte is oxidized and there is higher detection efficiency.

The flux at the electrode surface, J, calculated by simulations was converted to current, i,

according to the equation

JnFAi e=

where n is the number of electrons transferred to the electrode, F is Faraday’s constant, and Ae is

the surface area of the electrode (ℓ × w). For these simulations, an electroactive species such as

dopamine was used for the model, meaning two electrons were transferred to the electrode

during oxidation (n = 2). The amount of current assuming 100% coulometric efficiency has

been calculated by

0c%100 nFcvAi =

where v is average linear flow velocity, c0 is bulk concentration (20 µM), F is Faraday’s

constant, n is the number of electrons transferred to the electrode (two), and Ac is the channel

cross-sectional area (h × w). The coulometric detection efficiency is therefore defined as i/i100%.

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Figure 4.4. Side-view concentration profiles taken at (a) v = 0.06 cm s-1, (b) v = 0.28 cm s-1, and (c) v = 0.83 cm s-1. The channel height was 5 µm. (d) Relationship between current and flow rate for simulations () and theoretical response assuming 100 % coulometric efficiency () for the device depicted in parts (a-c). (e) Summary of coulometric efficiency for devices with channel heights of 5 (), 10 (), and 20 µm (). (f) Dimensionless parameter incorporating velocity, channel height, electrode length, and diffusion coefficient compared to coulometric efficiency.

75

Current generated as a function of average linear flow velocity in the microchannel is presented

in Figure 4.4d. If it is assumed that coulometric efficiency at the electrode is 100 %, as flow rate

increases, there is a linear increase in current, as seen in Figure 4.4d. At low linear flow

velocity, the actual current generated is near 100 % efficiency. However, as flow rate increases,

amount of current no longer increases as quickly because the effects of convection begin to

dominate and the diffusion layer thickness decreases. In a typical microchip electrophoretic

separation, the linear flow velocity is on the order of 1 × 10-2 cm s-1, which is in the same regime

as the first two data points in the graph displayed in Figure 4.4d.

A summary of coulometric detection efficiency at varied velocity (0.06 to 1.00 cm s-1) for

devices with different channel heights (h = 5, 10, and 20 µm) is presented in Figure 4.4e. The

coulometric efficiency decreases as the linear flow velocity increases. This trend holds for each

of the device heights simulated. A trend is also observed when varying channel height. At a

given flow velocity, the coulometric efficiency decreases as the height of the microchannel

increases. A higher channel allows more analyte to flow beyond the diffusion layer of the

electrode, thereby resulting in lower detection efficiency. Conversely, at lower channel heights,

there is much higher coulometric efficiency since the diffusion layer thickness is near the

channel height, thus more analyte is able to reach the electrode diffusion layer.

Since there are several variables to consider — electrode surface area, linear flow

velocity, channel height, and diffusion coefficient — a universal dimensionless parameter (v h2 ℓ-

1 D-1) has been developed incorporating these quantities and plotted against coulometric

efficiency (Figure 4.4f). With this dimensionless quantity, different combinations of the

aforementioned parameters can be varied to see the consequences on coulometric efficiency.

According to the plot in Figure 4.4f, large values of the dimensionless parameter correspond to

low efficiency, and small values correspond to high efficiency. Therefore, to maximize detection

efficiency, the channel height must be minimized, while the length of the electrode must be

maximized (it is important to note that larger electrode surface area will also lead to higher noise

which must be considered experimentally). Since the height increases to the second power

compared to the other values in the expression, microchannel height is one of the most important

parameters when maximizing amperometric detection efficiency in microchip separations.

76

CONCLUSIONS

Computational fluid dynamics simulations are a useful approach in the development,

design, and validation of microfluidic devices. CFD simulations employing the finite element

method were successfully applied to model the behavior of amperometric detection in two

unique microchip separation devices. CFD simulations were used to successfully validate the

flow profiles in a microfluidic device for quantifying the contents of individual vesicles.

Simulations were also used to develop a microchip electrophoresis device for highly efficient

amperometric detection. Use of simulations allows prediction of the efficiency of amperometric

detection, thereby saving time and effort fabricating and characterizing a large number of

systems.

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Chapter 5: Fabrication of PDMS microfluidic mixers with tape-based molds*

INTRODUCTION

Microfluidic devices [1] and micro total analysis systems [2, 3] have emerged as

important analytical tools for point-of-care clinical diagnostics [4-7], drug discovery [8],

chemical synthesis [9, 10], and cell assays [11, 12]. These microsystems are useful since they

consume low volumes of reagents, generate little waste, and are disposable [13]. Furthermore,

micro total analysis systems integrate many separate steps into a single device, resulting in fast

analysis times while avoiding sample transfer between steps.

The introduction of soft lithography with poly(dimethylsiloxane) (PDMS) [14], has

resulted in the proliferation of microfluidic technology since the polymer is inexpensive,

transparent, and biocompatible [15]. The majority of PDMS-based microfluidic devices are

rapidly prototyped by casting the polymer onto master molds of SU-8 negative photoresist [16-

23], which are photolithographically defined via transparency film masks [24-26]. Fabrication of

SU-8 master molds typically involves a clean room environment and photolithography. Creating

features of different heights on a single mold requires multiple masks that must be aligned prior

to exposure to ultraviolet light.

There are several reports of alternative methods for fabricating microfluidic devices,

many of which circumvent photolithography, with the goal of producing simple, inexpensive and

disposable microfluidic systems in a short time frame. Transparencies printed on laser printers

and photocopiers, for example, have been used directly as master molds to construct PDMS-

based microfluidic devices [27-29]. Unfortunately, these masters contain features that are less

than 30 µm high (corresponding to the thickness of toner), which is problematic if taller channels

are desired. Furthermore, because toner contains small, spherical particles, features are not

always smooth and well-defined. In contrast, with solid object printers, it is possible to produce

masters with tall features over 250 µm, but solid object printers cost over 50,000 USD [30].

* Submitted (September 2009) to the Analyst authored by MF Santillo, ML Heien, and AG Ewing. Proposed [doi:10.1039/b919003a] Royal Society of Chemistry.

80

Microfluidic systems have also been made using Shrinky Dinks [31, 32], wax printers [33], hot

embossing [34], nylon thread [35, 36], printed circuit boards [37-39], tubing [40, 41], cutting

plotters [42, 43], and paper [44-56]. These materials and methods all provide simple and

inexpensive avenues for constructing microfluidic platforms. Inexpensive microfluidic

components are vital for portable point-of-care clinical diagnostic platforms employed in the

developing world [5]. In addition, researchers who are unfamiliar with microfabrication and

wish to perform submicroliter chemical synthesis [9, 10] can benefit from uncomplicated

fabrication of these devices, along with those performing microscale enzymatic bioassays that

require mixing [57].

In this paper, tape is used to define channels in PDMS microfluidic systems. A mold

consisting of 250-µm high tape takes minutes to fabricate, compared to three hours for a SU-8

master mold of the same thickness defined via photolithography. With tape molds, PDMS

channel height can be controlled by stacking multiple layers of tape, which also permit

multilayer features to be defined without repeated alignment and exposure of multiple layers of

photoresist. Two micromixers were fabricated from tape-defined molds, demonstrating the

capabilities of these molds for making common components found in a variety of microsystems.

PROCEDURE

Device fabrication and imaging

A summary of the two fabrication schemes is depicted in Figure 5.1. For the semicircular

barrier micromixer, Scotch Super 88 vinyl electrical tape (3M, St. Paul, MN) with a thickness of

141.4 ± 1.7 µm (mean ± SEM, n = 10) was placed onto a glass slide. A tissue corer (Harris Uni-

Core, Ted Pella, Inc., Redding, CA) was used to remove semicircular portions of electrical tape

on a glass slide, and a scalpel was used to remove other areas of tape. Cutting was aided by use

of a binocular headband magnifier (OptiVisor, Donegan Optical Co., Lenexa, KS) and SZ60

stereo microscope (Olympus Corp., Center Valley, PA). A 10:1 base:curing agent mixture of

poly(dimethylsiloxane) (PDMS/Sylgard 184, Dow Corning, Midland, MI) was heated on the

master mold at 85 °C for 1 h. The PDMS was peeled away from the positive-relief master mold

and inlet/outlet holes were removed with a tissue corer. PDMS was exposed to air plasma for 90

s at 18 W (PDC-32G plasma cleaner, Harrick Plasma, Ithaca, NY) and bonded to a glass slide

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Figure 5.1. Tape mold fabrication schemes. (a) Semicircular barrier micromixer fabricated from a positive-relief master mold in which (i) a piece of tape (orange) is placed onto a glass slide. The unwanted tape is cut away (ii) leaving the desired pattern suitable for (iii) PDMS curing and subsequent bonding, (iv) resulting in a complete microfluidic device. (b) Fabrication of sawtooth mixer in which (i) tape (orange) is arranged on a glass slide producing a primary, negative-relief mold. PDMS (yellow) is (ii) cured onto the tape and peeled away, resulting in a (iii) secondary, positive-relief mold (yellow). PDMS (blue) is (iv) cured onto the secondary PDMS mold (yellow), peeled away, and (v) bonded to a glass slide yielding a complete microfluidic device.

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yielding a complete microfluidic device. A total of three semicircular barrier micromixers were

made from three independent master molds.

For the sawtooth mixer [58], two pieces of Storage Tape 3650 (3M, St. Paul, MN), with

thickness of 72.0 ± 0.5 µm (mean ± SEM, n = 10) were cut on a metal sawtooth dispenser blade

and placed opposite to each other on a glass slide resulting in a 1-mm gap, along with a square

piece for forming inlet channels. This arrangement of tape serves as a negative mold, and is

illustrated in Figure 1b. PDMS was cured on the tape mold and then peeled away, yielding a

positive-relief secondary mold. Chlorotrimethylsilane (Fluka/Sigma-Aldrich Co., Seelze,

Germany) was swabbed onto the secondary mold, followed by curing another layer of PDMS

which was subsequently peeled away, exposed to plasma, and bonded to a glass slide. A total of

three sawtooth micromixers were made from three independent master molds.

Straight channels were fabricated with positive relief tape molds, in the same manner as

the semicircular barrier micromixer. The channels were designed in Illustrator CS3 (Adobe

Systems, Inc., San Jose, CA) and printed onto clear adhesive (General polyester laser media,

Hemmi Papilio Supplies LLC, Rhome, TX). The printed adhesive was placed onto the tape and

cut with a scalpel. A total of three straight channel devices were made from three independent

master molds.

All scanning electron micrographs were obtained with a JSM 5400 scanning electron

microscope (Jeol USA, Inc., Peabody, MA) and optical images were acquired with a MZ 16

stereomicroscope (Leica Microsystems, Inc., Bannockburn, IL). Tape height and roughness

were measured with a surface profilometer (Alpha-Step 500, Tencor, San Jose, CA).

Fluorescence microscopy

A syringe pump (Harvard Apparatus, Holliston, MA) was used to control the volumetric

flow rates of aqueous 18 µM fluorescein isothiocyanate (FITC, Sigma-Aldrich Co., St. Louis,

MO) and deionized water (18 MΩ) in the microfluidic system. The pump interfaced with the

inlet holes of the PDMS microchannels via 1 mL glass syringes connected to polyethylene tubing

(0.58 mm i.d., 0.965 mm o.d.; Becton Dickinson and Co., Sparks, MD). Fluorescence images

were acquired with a laser scanning confocal microscope (TCS SP5, Leica Microsystems, Inc.,

Bannockburn, IL). FITC was excited with an argon-ion laser at 488 nm and fluorescence

emission collected from 515-600 nm. Fluorescence intensity line profiles were taken in different

83

sections of the microfluidic channels. The mixing efficiency was calculated according to the

expression 1 – σ/σmax, where σ is the standard deviation of the pixels (n > 200) in a line profile

taken across the channel width and σmax is the standard deviation of a pixel line profile associated

with an unmixed state, measured at the highest flow rate where two inlet channels merge. All

mixing efficiencies are expressed as mean ± standard error of the mean (SEM) for three devices

of each type.

Computational fluid dynamics simulations

Computational fluid dynamics (CFD) simulations were performed with Comsol

Multiphysics 3.5 (Comsol, Inc., Burlington, MA), a finite element method solver. A two-

dimensional geometry was used to model a top view of the fluid flow in a straight channel. The

following constants were used: FITC diffusion coefficient [59], D = 4.0 × 10-6 cm2 s-1; density, ρ

= 1.0 g cm-3; dynamic viscosity, µ = 1.0 × 10-3 Pa s; initial bulk concentration, c0 = 18 µM.

Incompressible Navier-Stokes equations were initally solved, given by:

∂u∂t

+ ρu ⋅ ∇u = −∇p+ μ∇2u

∇ ⋅ u = 0 where u is velocity, t is time, ρ is density, p is pressure, and µ is dynamic (absolute) viscosity.

Subsequently, the convection/diffusion equation,

∂c∂t

+ u ⋅ ∇c = D∇2c

was solved, where c is concentration, t is time, u is velocity, and D is the diffusion coefficient.

The standard deviation and mixing index of the simulated fluids in the straight channel were

calculated in the same manner as fluorescence microscopy except normalized concentration

values were used in lieu of fluorescence intensities.

RESULTS AND DISCUSSION

Characteristics of tape for molding microfluidic devices

Two different soft lithographic approaches were used for making PDMS micromixers

with tape molds. The first approach involved a single positive-relief mold illustrated in four

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steps in Figure 5.1a. First, tape was placed onto a glass slide (Figure 5.1a, step i) and areas were

cut away, yielding a positive-relief mold (step ii) onto which PDMS is cured (step iii). After

removal of PDMS from the mold, the inlet/outlet holes were removed, and the PDMS was

bonded to a glass slide resulting in a complete microfluidic system (step iv).

The second approach for making microchannels, illustrated in Figure 5.1b, involved the

use of negative and positive molds. Two pieces of tape with serrated edges were arranged on a

glass slide such that the serrated edges faced each other and were separated by an approximately

1 mm gap, shown in Figure 5.1b, step i. Additionally, a third piece of tape was placed

perpendicular to the serrated edges that defined the inlet channels for the micromixer. PDMS

was cured on this negative-relief mold (step ii) and removed, yielding a positive-relief mold of

PDMS (step iii). Another layer of PDMS was cured on the positive PDMS mold (step iv), and

after curing, the PDMS was bonded onto a glass slide resulting in a microfluidic device (step v).

After curing PDMS on the molds (85 °C for 1 h), neither storage tape nor vinyl electrical tape

exhibited any observable deformation due to melting or loss of adhesive ability.

One important consideration for molding microfluidic channels is surface roughness of

the mold. The surface roughness of vinyl electrical tape, storage tape, and SU-8 photoresist was

measured by profilometry. Electrical tape exhibited the largest average roughness (Ra) of 623 ±

63 nm (mean ± SEM, n = 15 line profiles), whereas the roughness of storage tape (Ra = 45 ± 5

nm, n = 15) and SU-8 photoresist (Ra = 28 ± 4 nm, n = 15) was one-tenth as much. The

nanometer scale roughness for both types of tape and SU-8 photoresist suggests that the flow

profiles will not be perturbed appreciably, except near the channel walls. Nevertheless, the

microfluidic systems fabricated here consist of channels that are several hundred micrometers in

height and width; therefore, the effects of surface roughness on flow disturbance are negligible

for these devices. To qualitatively visualize the PDMS surfaces after curing on tape molds,

scanning electron micrographs were obtained of channels molded from electrical and storage

tape (Figures 5.2a and 5.2b, respectively). These images show that the sidewall profiles of tape-

molded channels are sharp and well defined. In both SEM images there is a slight protrusion of

PDMS from the channel walls. This overhang is due to small amounts of PDMS curing between

the glass surface and edge of the tape. One benefit of tape molds over photolithographic ones is

the ability to fabricate multilayer features, examples of which are presented in Figures 5.2c and

5.2d. Multilayer features are important for constructing three dimensional microfluidic systems

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Figure 5.2. Scanning electron micrographs of PDMS microchannels molded from (a) vinyl electrical tape and (b) storage tape. (c-d) Multilayer PDMS channels cast from molds of vinyl electrical tape. Scale bars are 500 µm.

86

[47, 60, 61] and are more difficult to make with photolithography due to repeated alignment,

exposure, and baking steps. Although alignment with photolithography will fabricate features

with higher precision regarding their placement, the large (> 300 µm) sizes of features in Figures

5.2c and 5.2d can be easily attained with manually defined tape molds.

Performance of micromixers fabricated from tape molds

Fluid flow in microfluidic devices is characterized by low Reynolds numbers; therefore,

fluid flow is laminar and mixing is difficult to achieve in a short amount of time. Mixing can be

more rapidly achieved in microfluidic devices by incorporating active or passive mixing

principles [62-67]. Active mixing involves application of external energy that causes fluids to

mix in a shorter period of time; common modes of active mixing involve electrokinetic forces,

acoustics, and magnetic forces. Passive mixers, on the other hand, increase fluid mixing without

the input of external energy; passive mixers involve the design of microchannel geometries to

increase fluid-to-fluid contact time and decrease diffusion distances. Passive mixers do not

require external energy and are easier to implement, which are two important considerations

when fabricating simple, inexpensive microsystems. There are many applications in

microfluidic devices where rapid fluid mixing is desired. For example, in microscale

combinatorial chemical synthesis, multiple chemical compounds must be mixed on a chip in a

high-throughput fashion, which requires short reaction times and short microchannel lengths.

Many biochemical assays on microfluidic chips also require efficient mixing, in which the

products of a chemical reaction yield quantitative information on the amount of analyte present

[57].

In order to induce diffusive mixing on a faster time scale, two passive mixers with

different channel geometries were fabricated from tape molds. The semicircular barrier mixer

(Figure 5.3a) contains two inlet channels, each 637 ± 34 µm in width, converging into a larger

channel 1825 ± 39 µm wide containing alternating semicircular protrusions from the channel

walls. FITC solution and water were introduced from the inlet channels into the mixing channel

at flow rates of 0.625-5.000 µL min-1, corresponding to average inlet linear velocities of 124-992

µm s-1 and Reynolds numbers 0.07-0.60. A series of fluorescence images of the initial, 5th, 10th,

15th, and 20th mixing sections for water and FITC (each 1.25 µL min-1) are presented in Figure

5.4a. It is evident from the series of images that there is a progression of mixing between FITC

87

Figure 5.3. Optical images of microchannels and micromixers. (a) Semicircular barrier micromixer with dimensions w = 637 ± 34 µm, α = 867 ± 23 µm, and β = 1500 ± 35 µm. An individual mixing section is denoted by s. The channel height is 141.4 ± 1.7 µm and the distance of the 20th mixing section from the inlet channels is 23.4 ± 0.8 mm. (b) Straight channel molded from vinyl electrical tape with dimensions w = 704 ± 37 µm and β = 1212 ± 61 µm. (c) Sawtooth micromixer with dimensions w = 1190 ± 6 µm, α = 1007 ± 43 µm, and β = 1825 ± 39 µm. An individual mixing section is denoted by s. The channel height is 72.0 ± 0.5 µm and the distance of the 40th mixing section from the inlet channels is 23.5 ± 0.1 mm. (d) Straight channel molded from storage tape with dimensions w = 1264 ± 48 µm and β = 1690 ± 56 µm. All dimensions are expressed as mean ± SEM (n = 3 devices for each geometry).

88

Figure 5.4. Performance characteristics of the semicircular barrier micromixer. (a) Fluorescence images of FITC and water (each flow rate of 1.250 µL min-1) at different sections of the mixing channel. Scale bar is 1 mm. (b) Graph of mixing efficiency determined by fluorescence microscopy in each section at flow rates of 0.625 (), 1.250 ( ), 2.500 (), and 5.000 µL min-1 (). Each point represents the mean ± SEM (n = 3 devices). (c) Comparison of mixing efficiency at the 20th section of the semicircular barrier micromixer (Δ) with mixing in a straight channel containing no geometric modifications determined via fluorescence microscopy () and CFD simulations (). Mixing in the straight channel was measured at a distance of 23.4 mm from the inlet channels, which corresponds to the distance of the 20th section from the inlet channels in the micromixer. Each point represents the mean ± SEM (n = 3 devices).

89

dye and water from the initial to the 20th section. The mixing efficiency was quantified by

measuring the standard deviation of the pixel intensity in the fluorescence images, which yields

information on the heterogeneity of fluorescence intensity across the width of the microchannels.

The data in Figure 5.4b show that the mixing efficiency increases at each flow rate along the

length of the channel, reaching a maximum at the end of the mixing channel (20th section). At

the lowest flow rate employed in this study (0.625 µL min-1), a mixing efficiency of 0.942 ±

0.011 achieved at the 20th section, whereas a mixing efficiency of 0.371 ± 0.026 was achieved at

the highest flow rate investigated (5.000 µL min-1) at the 20th section. The data in Figure 5.4b

further show that in a given section of the mixer, the mixing efficiency increases as the flow rate

decreases. At lower flow rates there is less convection, allowing diffusive transport to dominate.

This causes increased contact time between the fluid streams, thus leading to higher mixing

efficiency. The points on the graph in Figure 5.4b represent the average mixing efficiency

values calculated from devices fabricated from three separate tape molds. The standard error of

the mean ranged from 0.030 to 0.068 for all measured mixing efficiencies presented in Figure

5.4b.

To demonstrate the efficacy of the semicircular barrier mixer geometry, the mixing

efficiency in the micromixer at the 20th section was compared to mixing efficiency in a straight

channel, which served as a control. Mixing efficiency was measured in a straight channel

(Figure 5.3b) containing two inlet channels, each 704 ± 37 µm wide and 141.4 ± 1.7 µm high,

merging into a single 1212 ± 61 µm wide channel. Both fluorescence microscopy and CFD

simulations were used to measure mixing efficiency in the straight channel. Figure 5.4c shows

the mixing efficiency in the 20th section of the semicircular barrier micromixer (located 23.4

mm away from the inlet channels) along with mixing in a straight channel at a distance of 23.4

mm from the inlet channels. The data in Figure 5.4c indicate that at each flow rate investigated,

mixing efficiency is always higher in the micromixer versus the straight channel. At the lowest

flow rate employed in this study (0.625 µL min-1), a mixing efficiency of 0.942 ± 0.011 was

obtained in the semicircular barrier mixer compared to mixing efficiencies of 0.593 ± 0.038 and

0.494 for a straight channel determined via fluorescence and CFD simulations, respectively. The

fluorescence and CFD data agree well (Figure 5.4c); the fluorescence data is 10 % higher at

0.625 µL min-1 and 2 % higher at 5.000 µL min-1. It is believed that these discrepancies are due

to the different channel widths for fabricated devices and CFD simulations.

90

The sawtooth micromixer [58] (Figure 5.3c) was characterized in the same manner as that

of the semicircular barrier mixer. The sawtooth mixer consists of two inlet channels each 1190 ±

6 µm wide leading into channel 1825 ± 39 wide containing series of sawtooth-shaped structures

(Figure 5.3c). Characterization of the mixer was performed at flow rates of 0.313, 0.625, and

1.250 µL min-1, corresponding to average inlet linear velocities of 60, 121, and 241 µm s-1 and

Reynolds numbers 0.07, 0.15, and 0.29, respectively. Figure 5.5a shows a series of fluorescence

images of FITC and water flowing at 0.313 µL min-1 at the initial, 10th, 20th, 30th, and 40th

sections; the fluorescence images show a clear progression of mixing between FITC and water

from the initial to the 40th section. At a given section of the mixer, there was more mixing at

lower flow rates, and less mixing at higher flow rates (Figure 5.5b), for the same reasons

explained for the semicircular barrier mixer. Again, the lower flow rate allows a longer contact

time between FITC and water, leading to higher mixing efficiency. At the lowest flow rate

(0.313 µL min-1), a mixing efficiency of 0.861 ± 0.039 was achieved at the 40th section of the

sawtooth micromixer, compared to mixing efficiencies of 0.328 ± 0.027 and 0.435 in a straight

channel, determined via fluorescence microscopy and CFD simulations, respectively (Figure

5.5c).

CONCLUSIONS

Tape has been shown to be an inexpensive, fast, and easy way to fabricate microfluidic

channels on the order of several hundred microns and into the millimeter range. Tape-based

devices can be made quickly, easily, and inexpensively. Two fabrication schemes were

presented for making micromixers, and the mixing efficiency was quantified by fluorescence

microscopy. Both micromixers had mixing efficiencies that were 1.6 to 2.6 times higher versus

mixing efficiency measured and simulated in a straight channel. The presented micromixer

performance exhibits the utility of tape molds for inexpensive fabrication of simple microfluidic

platforms.

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Figure 5.5. Performance characteristics of the sawtooth micromixer. (a) Fluorescence images of FITC and water (each flow rate of 0.313 µL min-1) at different sections of the mixing channel. Scale bar is 1 mm. (b) Graph of mixing efficiency determined by fluorescence microscopy in each section at flow rates of 0.313 (), 0.625 (), and 1.250 µL min-1 (). (c) Comparison of mixing efficiency at the 40th section of the sawtooth micromixer (Δ) with mixing in a straight channel containing no geometric modifications determined via fluorescence microscopy () and CFD simulations (). Mixing in the straight channel was measured at a distance of 23.5 mm from the inlet channels, which corresponds to the distance of the 40th section from the inlet channels in the micromixer. Each point represents the mean ± SEM (n = 3 devices).

92

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Chapter 6: High-throughput single cell assay for reactive oxide species in PC12 cells

INTRODUCTION

The ability to interrogate single cells is of great interest in biological research because

obtaining data from single cells may differ greatly compared to a bulk average from a cellular

population [1, 2]. Such differences might occur if several subpopulations exist and, when

averaged, these lead to a single value located between the individual populations. Another

situation in which single cell responses differ from an average is when many short cellular

processes occur over a long time period; although each event is short, the average value is broad

and not indicative of the true event length.

There are several techniques for analyzing single cells. Micropipettes are commonly

used to flow chemical compounds onto cultured cells, followed by fluorescence imaging of the

exposed cells. Although useful for brief chemical exposure, the fluid ejected from micropipettes

rapidly diffuses, such that accurate chemical concentrations cannot be applied for an extended

period of time. Furthermore, cells treated in this manner are often randomly adhered to the

surface, such that the locations of cells vary from experiment to experiment, making imaging

more difficult. Flow cytometry is a popular instrument for performing high-throughput analyses

of single cells [3]. Flow cytometers are capable of recording fluorescence emission from

individual cells in suspension and can sort cells based upon their fluorescence labels. Flow

cytometers, however, cannot analyze adhered cells and do not allow cells to remain in their

native environment. Furthermore, flow cytometry cannot be used for the temporal analysis of a

given cell in which multiple measurements are required over a given time period.

Microfluidic devices have surfaced as important tools for high-throughput single cell

assays [4, 5]. Compared to conventional methods, microfluidic platforms consume small

amounts of reagents, generate less waste, and can integrate many separate steps of an analysis

into a single system. An array format in a microfluidic device enables fast fluorescence imaging

to be performed due to the fixed, accurate locations of individual cells [6]. Additionally, arrays

allow the same cell to be imaged over time, which is important if data is required on the same

98

cell’s response both before and after treatment. A microchannel also allows continuous

perfusion, such that fresh growth medium is constantly supplied and waste is removed,

maintaining a high level of cell viability.

Here a microfluidic system was used to perform high-throughput assays to measure the

amount of reactive oxygen species generated in PC12 cells in response to the neurotoxin 6-

hydroxydopamine. The system contains two features of interest: a passive mixer [7] and

hydrodynamic traps [8, 9]. The passive mixer allows two inlet fluids to mix to varying degrees,

and each serially diluted mixture flows past a series of hydrodynamic traps which isolate

individual cells, leading to high-throughput single cell imaging.

PROCEDURE

Chemicals

Poly(dimethylsiloxane) (PDMS/Sylgard 184) was obtained from Dow Corning Corp.

(Midland, MI). SU-8 photoresist and developer solution (1-methoxy-2-propyl acetate) were

purchased from MicroChem Corp. (Newton, MA), and 3-in silicon wafers were purchased from

Silicon Quest International, Inc. (Santa Clara, CA). RPMI 1640 was obtained from Mediatech,

Inc. (Manassas, VA). Fetal bovine and donor equine sera were obtained from HyClone

Laboratories (Logan, UT). Sodium chloride, magnesium chloride hexahydrate, calcium chloride

dihydrate, potassium chloride, glucose, HEPES, chlorotrimethylsilane, 6-hydroxydopamine, and

dimethyl sulfoxide were purchased from Sigma-Aldrich Co. (St. Louis, MO). Fluorescein

diacetate, 5-(and-6)-chloromethyl-2',7'-dichlorodihydrofluorescein diacetate, acetyl ester (CM-

H2DCFDA) and Alexa Fluor 647 carboxylic acid, succinimidyl ester were obtained from

Invitrogen, Inc. (Eugene, OR). Penicillin/streptomycin was obtained from EMD Biosciences

(Gibbstown, NJ). Water (18 MΩ) was purified through a Millipore Milli-Q system (Billerica,

MA).

Microfluidic device fabrication

Masks were designed in Illustrator CS3 (Adobe Systems, Inc., San Jose, CA) and printed

onto transparency films by a laser photoplotter (CAD/Art Services, Inc., Bandon, OR). All

photolithographic steps were performed according to the photoresist manufacturer protocol. The

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channel was made by first depositing a 5-µm thick layer of SU-8 5 photoresist and exposure with

a mask not containing any cell traps with a mask aligner (Karl Suss MA6, Suss Microtec,

Waterbury Center, VT). Subsequently, a 45-µm thick layer of SU-8 25 was deposited onto the

first layer, and the photoresist was exposed through a mask containing hydrodynamic traps; this

was followed by immersion in SU-8 developer solution. The master mold was stored under

vacuum in a desiccator with approximately 1 mL of chlorotrimethylsilane for at least 1 h. A 10:1

(base:curing agent by weight) mixture of PDMS prepolymer was poured onto the master mold

and cured in an oven at 80 °C for 1 h. Holes for fluid inlets/outlets (1 mm diameter) were

removed with a tissue punch (Harris Uni-Core). PDMS and a glass bottom petri dish (In Vitro

Scientific, Sunnyvale, CA) were exposed to oxygen plasma at 75 W for 30 s (M4L, Metroline

Industries, Corona, CA) and conformally sealed. The device was treated with air plasma (18 W

for 90 s, PDC-32G plasma cleaner, Harrick Plasma, Ithaca, NY) prior to loading with fluids to

sterilize the device and increase hydophilicity of the channels.

Cell culture

Rat pheochromocytoma (PC12) cells were obtained from American Type Culture

Collection (Manassas, VA). Cells were cultured in RPMI 1640 supplemented with 10% (v/v)

fetal bovine serum, 5% (v/v) equine serum and 0.2% (v/v) penicillin-streptomycin. Cells were

grown in 25 cm2 collagen IV-coated flasks (BD Biosciences, Franklin Lakes, NJ) at 37 ºC in a

7% CO2 atmosphere and were passaged after reaching confluency every 5-10 days. Isotonic

physiological saline (150 mM NaCl, 5 mM KCl, 1.2 mM MgCl2, 5 mM glucose, 10 mM HEPES,

and 2 mM CaCl2) was used as diluent for all solutions.

Fluorescence microscopy and flow experiments

The reactive oxide species indicator CM-H2DCFDA (1.73 mM in DMSO) was diluted to

a concentration of 9 µM in PC12 cell suspension, and cells were subsequently loaded into the

device manually with a syringe. A syringe pump (Harvard Apparatus or KD Scientific Inc.,

Holliston, MA) was used to control the volumetric flow rates of solutions in the microfluidic

device. The pump interfaced with the inlet holes of the PDMS microchannels via syringes

connected to polyethylene tubing (0.58 mm i.d., 0.965 mm o.d.). Flow characterization studies

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were performed with water and Alexa Fluor 647 (2.67 µg mL-1 in water). Fluorescence images

were acquired with a laser-scanning confocal microscope (TCS SP5, Leica Microsystems, Inc.,

Bannockburn, IL). The reactive oxygen species indicator CM-H2DCFDA was excited with an

argon-ion laser at 488 nm and fluorescence collected from 500-580 nm. Alexa Fluor 647 was

excited with a HeNe laser at 633 nm and fluorescence collected from 645-720 nm. A culture

dish heater (Warner Instruments, LLC, Hamden, CT) was used to maintain the temperature of

the microfluidic device at 37 ºC.

Computational fluid dynamics (CFD) simulations

CFD simulations were performed with Comsol Multiphysics 3.5 (Comsol, Inc.,

Burlington, MA), a finite element method solver. A two-dimensional geometry was used to

model the microfluidic system in order to yield a top view of the fluid flow. The following

constants were used: Alexa Fluor 647 diffusion coefficient, D = 4.0 × 10-6 cm2 s-1; density, ρ =

1.0 × 103 kg m-3; dynamic viscosity, µ = 1.0 × 10-3 Pa s; initial bulk concentration, c0 = 36 µM.

Incompressible Navier-Stokes equations were initially solved, given by:

∂u∂t

+ ρu ⋅ ∇u = −∇p + μ∇2u

∇ ⋅ u = 0

where u is velocity, t is time, ρ is density, p is pressure, and µ is dynamic (absolute) viscosity.

Subsequently, the convection/diffusion equation,

∂c∂t

+ u ⋅ ∇c = D∇2c

was solved, where c is concentration, t is time, u is velocity, and D is the diffusion coefficient.

RESULTS AND DISCUSSION

Device design and characterization of diffusive mixing

A microfluidic system for the high-throughput analysis of single PC12 cells is illustrated

in Figure 6.1. The device features two inlet channels, a central diffusive mixing distributor, and

eight channels containing hydrodynamic cell traps. Two inlet channels, each 1 mm in width,

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Figure 6.1. (a) Diagram of the device (scale bar is 2 mm). (b) Representative bright-field image of PC12 cells residing in hydrodynamic traps and (c) corresponding fluorescence image of cells incubated with fluorescein diacetate viability dye. Scale bars in (b) and (c) are 150 µm.

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merge into a single channel 1 mm wide (the height of all channels in the system is 55 µm). One

inlet channel is used to introduce a pharmacological compound (e.g., 6-hydroxydopamine), while

the other inlet is used to introduce physiological isotonic saline. The two inlet fluids are

ultimately mixed, resulting in a series of concentrations that are perfused over individually

trapped cells contained in a series of eight channels.

When laminar fluid flow streams of Alexa Fluor 647 dye and water from the inlet

channels (each 0.50 µL min-1) initially come into contact, they do not mix appreciably (Figure

6.2a). Further downstream, the channel widens from 1 to 2 mm as the dye and water enter the

diffusive mixing distributor. As the channel widens, the linear fluid flow velocity (convective

transport) decreases, and the fluids are allowed to mix considerably due to the rate of diffusion

dominating over the decreased rate of convection. The fluorescence image in Figure 6.2b shows

Alexa Fluor 647 dye and water (each 0.50 µL min-1) flowing through the mixing distributor. The

channel splits into eight 100-µm wide channels, each receiving a different range of fluorescent

dye concentrations. In the initial entrance of the eight channels mixing is not complete, as

evidenced by the heterogeneous concentration distribution in several of the eight channels

(Figure 6.2b). However, once the dye reaches the hydrodynamic cell traps, the concentration of

fluid is homogeneous throughout the entire channel (Figure 6.2c-f), meaning that cells located

within each channel will be exposed to equal concentrations of a pharmacological compound.

The graphs in Figure 6.2g-h show the effects of flow rate on Alexa Fluor dye

concentration determined by CFD simulations (Figure 6.2g) and fluorescence microscopy

(Figure 6.2h) in each of the eight cell channels. Both methods were used to measure the average

normalized concentration within each channel at flow rates of 0.25, 0.50, and 2.00 µL min-1. At

higher flow rates, the dye and water mixed to a lesser degree, and there was a narrow

concentration distribution among the eight cell channels. Conversely, at lower flow rates, there

was more mixing of the dye and water, and there was a broad concentration distribution in the

eight cell channels. Both CFD simulations (Figure 6.2g) and fluorescence microscopy (Figure

6.2h) were in close agreement and followed the same trend.

The hydrodynamic traps in each channel were designed to accommodate one or a few

cells. The traps consist of a shallow U-shaped obstacle which extends 50 µm from the channel

ceiling, and there exists a 5-µm gap between the bottom of the trap and the channel floor. This

gap allows fluid to flow past the obstacle while capturing the cell, since the cell is approximately

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Figure 6.2. Fluorescence images of Alexa Fluor 647 (0.50 µL min-1) and water (0.50 µL min-1) at the (a) merge point of both inlet channels, (b) diffusive mixing distributor, and within cell channel numbers (c) 2, (d) 4, (e) 6, and (f) 8. Distribution of average normalized concentration of dye within each cell channel determined via (g) CFD simulations and (h) fluorescence microscopy at flow rates of 0.25 µL min-1 (), 0.50 µL min-1 (), and 2.00 µL min-1 ().

104

15 µm in diameter and unable to flow through the gap. The cells were loaded manually via a

syringe and the trapping efficiency was dependent on the amount of time spent flowing cell

suspension through the device and the cell density. Although not all cells introduced into the

channel were successfully trapped, cells that were trapped did not subsequently escape. Ideally,

each trap would contain a single cell; however, due to the size of the traps, between one and four

cells were trapped as seen in Figure 6.1c.

Quantification of reactive oxygen species

Free radical oxidation has been implicated in a variety of neurodegenerative diseases,

such as Parkinson’s, along with the aging process. Parkinson’s disease is characterized by the

loss of dopaminergic neurons, and it is believed that free radical oxidation plays an important

role in the etiology of the disease [10]. The compound 6-hydroxydopamine, in particular, has

been shown to cause cell death in dopaminergic neurons due to generation of reactive oxygen

species. Using the microfluidic system presented here, PC12 cells, a model for dopaminergic

neurons, were incubated with CM-H2DCFDA [11], a fluorescent dye used to detect reactive

oxygen species. Initially, the dye is nonfluorescent and capable of entering cells via diffusion

through the membrane. The dye, once inside the cell, is transformed by elimination of acetyl

groups by endogenous intracellular esterases, effectively retaining the molecule inside the cell.

Subsequently, reactive oxygen species react with the dye, yielding a fluorescent species.

Figure 6.3 shows the changes in fluorescence of PC12 cells over time under continuous

perfusion (0.50 µL min-1) of 1 mM 6-hydroxydopamine and isotonic saline. Points on the graph

represent average values of four cells measured at each time point. The graph in Figure 6.3

shows that when cells are exposed to isotonic saline, the fluorescence intensity remains constant

over a 10-minute period. The constant intensity of the control cells means that the fluid flow did

not cause leakage of fluorophore, and a large increase in reactive oxygen species was not

present. However, when cells were perfused with 1 mM 6-hydroxydopamine, a large increase in

fluorophore was observed, indicating the generation of reactive oxygen species. These results

illustrate the utility in using this device for performing fluorescence assays on free radical

oxidation, and together with characterization of the diffusive mixing distributor, will allow that

several concentrations of a chemical compound to be continuously perfused over isolated cells.

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Figure 6.3. Plot of normalized fluorescence intensity of PC12 cells exposed to 1 mM 6-hydroxydopamine () and isotonic saline as a control (). Flow rate of each solution was 0.50 µL min-1. Values are expressed at mean ± SEM (n = 4 cells).

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In the future, the effects of antioxidants and additional neurotoxins that induce free radical

oxidation will be explored with this microfluidic platform.

CONCLUSIONS

A microfluidic device for high-throughput single cell assays has been fabricated. The

device allows fluorescence imaging of individual cells in an array of hydrodynamic traps which

isolate the cells from suspension in solution. Two key components, a diffusive mixer and

hydrodynamic cell traps, allow several concentrations of a chemical compound to be exposed to

cells simultaneously in isolated channels. The potential of this system for investigating free

radical oxidation on PC12 cells was demonstrated using the neurotoxin 6-hydroxydopamine.

107

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Chapter 7: Future directions for using microfluidic systems to investigate communication between cells within an in vitro neural network

CELLS AND PATTERNING

In the second chapter of this thesis, laminar flow profiles in microfluidic device for

studying neural network communication were characterized. The results presented in the second

chapter illustrated that fluid flow can be directed to different areas, allowing cultured cells to be

spatially addressed with different pharmacological agents. The next step for this project is to

culture cells on the device. Rat pheochromocytoma (PC12) cells [1-3] are a good choice for

investigating patterning and viability in the device because they are a well-characterized and

robust cell line. Preliminary data of spatially addressing groups of cells is presented in Figure

7.1. The device was coated with laminin, a cellular adhesion protein, followed by incubation

with a suspension of PC12 cells (Figure 7.1a). After allowing cells to adhere to the laminin-

coated PDMS surface, cell media was introduced via bulk flow channels, and a solution of Triton

X-100 was flowed through a pharmacological agent channel. Figure 7.1b shows a specific

region of PC12 cells that were lysed after a 60-s exposure Triton X-100, demonstrating how a

directed laminar flow of fluid can be used to selectively address cells in this system.

Although PC12 cells are robust, neuron-like dopaminergic models, they do not form

functional synapses, making them unsuitable for studying communication between neuron cells

in an in vivo network. Other cell lines (e.g., embryonic carcinoma or P19 [4, 5]) are better

candidates for studying neural network communication because, unlike the PC12 cell line, P19

cells form functional synapses and respond to both GABA and glutamate. Primary cultures of

hippocampal and nigrostriatal neurons from neonatal rats are the most biologically relevant

system; however, they are difficult to culture, especially on a PDMS surface, and are sensitive to

their surrounding environment. Frequently, primary cultures must be grown with glial cells and

are susceptible to contamination. However, there are other primary cultures that can be used in

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Figure 7.1. PC12 cells adhered to the device (a) before and (b) after 60 s of directed, regional exposure to Triton X-100. Scale bar is 150 µm.

110

lieu of mammalian ones. Neurons from the sea slug Aplysia californica, for example, are an

excellent choice. Aplysia has a simple nervous system with large neurons that are easy to dissect

and grow in culture. Primary neurons from Aplysia are relatively robust and do not require the

same strict sterile conditions as primary mammalian cultures. Aplysia cells are known to form

simple networks, and have been used by Kandel as a model for studying habituation along with

learning and memory [6, 7].

Techniques for patterning cells onto the microfluidic platform are another area of

investigation. Large neurons from Aplysia are individually dissected from the organism and can

be positioned onto desired areas of the device which is coated with polylysine. The other

aforementioned cell types are much smaller and individually positioning them is not feasible, so

the surface must be patterned followed by incubation with a cell suspension. For these cells,

patterning techniques [8] such as microcontact printing [9] or stencils [10, 11] can be employed.

Microcontact printing involves coating a photolithographically-molded PDMS stamp with cell

adhesion proteins such as polylysine or laminin. The stamp is brought into contact with a

surface, which transfers the adhesion protein in a well-defined pattern. Additionally, stencil

patterning can also be used. A thin, photolithographically-defined PDMS membrane containing

holes can be placed onto the device, followed by surface modification corresponding to the

pattern, resulting in a geometry which can be used to adhere cells to form a network.

ANALYTICAL TECHNIQUES

There are several analytical techniques that will be used to monitor in vitro neural

network activity. Fluorescence microscopy is the simplest technique for monitoring

communication. Cells incubated with voltage-sensitive fluorescent dyes indicate when cells are

being excited and undergoing exocytotic release of neurotransmitters. Fluorescence microscopy

is an excellent technique for monitoring communication since it is easy to record from many

cells simultaneously in a single field of view.

Figure 7.2 shows the overall scheme for performing experiments with the device using

fluorescence microscopy. First, a single cell in the network is stimulated with a solution

containing a high concentration of potassium (Figure 7.2a). This high exposure to potassium

causes an action potential to travel from cell to cell within the network. After stimulation, the

network can be monitored as the action potential propogates to the other cells with voltage-

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Figure 7.2. Top view of the microfluidic device for proposed studies of neural network communication. Pharmacological agent outlet channels are represented by four squares, and cells are represented by green circles. (a) A high potassium solution is flowed through one of the pharmacological agent channels and is directed upward by bulk flow of media, thereby stimulating the cell (blue circle). In order to avoid exposing multiple cells, media is also flowed through an adjacent pharmacological channel. After stimulation, the network activity is monitored with fluorescence microscopy. (b) A cell in the network is exposed to a toxin, ultimately causing cell death (grey circle). (c) The network is monitored for changes in connectivity (shown as red lines) or other compensatory mechanisms.

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sensitive fluorescent dyes. After establishing a pattern of intercellular communication, a toxin

can then be used to expose a cell in the network, thus causing cell death (Figure 7.2b). After the

neuron is no longer viable, it is proposed that the cells located nearby will form new connections

and possibly compensate for the loss of the dead neuron (Figure 7.2c).

Although fluorescence microscopy yields information on the excitability of neurons in a

network, it does not yield any information on the chemical identity or amount of released

neurotransmitters. Electrode arrays, on the other hand, can be used to monitor network activity

by detecting release of redox-active neurotransmitters. The array format allows spatial

resolution over the entire network so that each individual electrode in the array functions

independently on a specific cell or area of cells. The array is a significant improvement from

using single carbon fiber electrodes to detect exocytotic release which must be controlled with

micromanipulators, making simultaneous monitoring of release from many networked cells

unfeasible.

Quartz crystal microbalance (QCM) arrays are another technique that can detect release

from cells. QCM, first developed by Sauerbrey [12], consists of a quartz crystal driven at a

specific resonance frequency. When the mass changes, a shift in resonance frequency occurs

which is proportional to the change in mass [13-15]. Upon stimulation, exocytosis occurs,

neurotransmitters are released by the cell, and there is a change in mass that can be observed by a

change in frequency on the QCM. One advantage of QCM is that it is less invasive compared to

fluorescence microscopy in which dyes must be incubated with cells or electrophysiology

measurements involving direct electrical contact with cells. QCM has already been used to

measure release from a PC12 cell population in which sensitivity of 14 ng/Hz was attained [16].

It is believed that this instrumentation can be modified to an array format and that femtogram

sensitivity is possible, which means that release of single vesicles (1.4 fg per vesicle) can be

detected.

PHARMACOLOGICAL INVESTIGATIONS RELATED TO PARKINSON’S DISEASE

A long-term goal is to study Parkinson's disease, a neurodegenerative disorder

characterized by the loss of dopaminergic neurons (> 80%) in the substantia nigra of the brain

[17-19]. People suffering from Parkinson's exhibit loss of motor control, stupor, dementia, and

bradykinesia. There is no cure for Parkinson's; however, the dopamine precursor 3,4-

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dihydroxyphenylalanine (L-DOPA) is often administered to patients to alleviate the symptoms.

L-DOPA, once inside the neuron, can be converted to dopamine, thereby restoring some

dopaminergic activity. Unfortunately, L-DOPA may cause side effects e.g. hallucinations, and

more importantly, it might lead to oxidative stress [20] as the fewer nerve cells present will be

less able to metabolize the increased amount of dopamine formed. Additionally, the therapeutic

effects of L-DOPA usually wear off over time.

Experiments will be planned to investigate the effects of physical and chemical damage

on cell networks as a model of neurodegeneration exhibited in Parkinson’s disease. Cells will be

exposed to potassium solution in the network using microfluidic channels, and the overall pattern

of neuronal communication will be observed. Some of the neurons will be physically destroyed,

which will be followed by monitoring changes in communication patterns. In addition to

physical damage, the effects of chemical damage by neurotoxins like 6-hydroxydopamine (6-OH

DA) will also be studied to mimic Parkinson's. The neurotoxin 6-OH DA enters dopaminergic

neurons via the dopamine transporter and once inside the cell, 6-OH DA causes cell damage and

ultimately cell death by free radical oxidation [21]. Selected cells in the network will be exposed

to 6-OH DA, and changes in communication patterns will be observed.

It is possible that glutamatergic neuronal activity has an effect on deterioration of

dopaminergic neurons after being exposed to 6-OH DA [22]. To investigate this idea, primary

neuronal cultures containing both dopaminergic and glutamatergic neurons will be exposed to

high levels of potassium and NMDA, which selectively stimulates glutamate cells. The cell

communication patterns with and without NMDA exposure will be compared to determine if

gluatamatergic neurons magnify the deteriorative effects of 6-OH DA.

Recent studies have indicated that nicotine [23, 24], caffeine [23, 24], and estradiol [25]

all reduce neurodegeneration and therefore act as neuroprotective agents against Parkinson's

disease. To investigate this hypothesis, neural primary cultures will be patterned, followed by

exposure to each of the aforementioned neuroprotective compounds. The toxic compound 6-OH

DA will be introduced to the cells and the changes in cell communication patterns will be

observed by fluorescence microscopy with a goal of determining if these agents affect the change

in pattern of neuronal communication following exposure to the toxin.

Investigating neuronal communication will further our fundamental knowledge on how

the mechanisms of neuronal adaptation, recovery, and compensation play a role in

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neurodegenerative diseases like Parkinson's. By using microfluidics, individual cells in a

patterned neuronal network can be selectively exposed to a variety of protective and toxic

compounds, and the changes in communication patterns among the cells can be monitored. This

relatively simple in vitro cell network will function as a model for the brain, a more complex

network of neurons. It is expected that neuronal communication patterns will change after cells

are physically damaged. Additionally, cells exposed to L-DOPA will die, and the remaining

cells will adapt and change connectivity. After exposure to neuroprotective agents like caffeine,

nicotine, and estrogen, it is expected that cells exposed to the toxin 6-OH DA will either form

new connections or possibly make existing connections stronger.

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Vita – Michael F. Santillo

EDUCATION Ph.D. Chemistry, The Pennsylvania State University, University Park, PA (10/2009) B.S. Chemistry (ACS Approved), Elizabethtown College, Elizabethtown, PA (5/2003)

AWARDS Braucher Fellowship, Department of Chemistry, The Pennsylvania State University (7/2007) Roberts Graduate Fellowship, Department of Chemistry, The Pennsylvania State University (8/2003) Award for Academic Excellence, Elizabethtown College (12/2002) Dean’s Merit Scholarship, Elizabethtown College (8/1999)

PUBLICATIONS [Google Scholar] [PubMed] [Thomson ResearcherID] MF Santillo, ML Heien, AG Ewing, Temporal analysis of protozoan lysis in a microfluidic device, Lab Chip 2009, 9, 2796-2802. [doi:10.1039/b907942d] DM Omiatek, MF Santillo, ML Heien, AG Ewing, Hybrid capillary-microfluidic device for the separation, lysis, and electrochemical detection of vesicles, Anal. Chem. 2009, 81, 2294-2302. [doi:10.1021/ac802466g] IG Arcibal, MF Santillo, AG Ewing, Capillary electrophoresis for the analysis of single cells: Sampling, detection, and applications, in Handbook of Capillary and Microchip Electrophoresis and Associated Microtechniques, 3rd Edition, JP Landers, ed., CRC Press, Boca Raton, FL, 2008. [OCLC 137294983] MF Santillo, IG Arcibal, AG Ewing, Flow characterization of a microfluidic device to selectively and reliably apply reagents to a cellular network, Lab Chip 2007, 7, 1212-1215. [doi:10.1039/b708928g] IG Arcibal, MF Santillo, AG Ewing, Recent advances in capillary electrophoretic analysis of individual cells, Anal. Bioanal. Chem. 2007, 387, 51-57. [doi:10.1007/s00216-006-0690-0]

SELECTED PRESENTATIONS MF Santillo, ML Heien, AG Ewing, A microfluidic device for quantification of lipid membrane lysis, oral presentation given at Pittcon 2009, Chicago, IL, Mar 8-13, 2009. MF Santillo, Microfluidics for cellular assays, oral presentation given at the Elizabethtown College Department of Chemistry & Biochemistry Seminar, Elizabethtown, PA, Feb 27, 2009. MF Santillo, ML Heien, AG Ewing, Exploitation of laminar flow for cell assays on a chip, oral presentation given at Pittcon 2008, New Orleans, LA, Mar 1-7, 2008. MF Santillo, AG Ewing, Exploitation of laminar flow for cell-based assays, oral presentation given at Comsol Conference Boston 2007, Newton, MA, Oct 4-6, 2007. MF Santillo, IG Arcibal, AG Ewing, Chemical analysis in a microfluidic device to study neural communication between single cells in a network, oral presentation given at Pittcon 2007, Chicago, IL, Feb 25-Mar 2, 2007. MF Santillo, IG Arcibal, AG Ewing, Characterization of a microfluidic system for investigating neural network communication, poster presented at Lab Automation 2007, Palm Springs, CA, Jan 27-31, 2007.