T U   D E L F T  

Abstract  The   goal   of   this   project   is   to   model,   fabricate   and   characterize   a   multi   microchamber  biochip,   which   allows   for   crosstalk   between   two   types   of   living   cells.   This   biochip   uses  laminar  flow  to  separate  two  microchambers  for  cell  co-­‐culture.  A  study  of  fluid  dynamics  through   finite   element   analysis   was   implemented   to   optimize   two  methods   for   crosstalk  between   the   microchambers.   The   fabrication   process   that   consists   of   multilayer   soft  lithography  was   also   optimized   for   this   particular   biochip.     The   knowledge   acquired   from  the  theoretical  modeling  and  preliminary  experiments  with  a  single  microchamber  biochip  led   to   the   production   of   a   working   prototype   ready   to   be   tested   for   cell   culture  experiments.    

December  12  2011    

Optimization   of   a   Multi   Microchamber  Biochip  for  Cell  Co-­‐culture  

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Table  of  Contents  

Introduction ...................................................................................................................... 3  Microfluidics  for  cellomics ....................................................................................................3  Gradient  control ....................................................................................................................4  Cell  Co-­‐culturing ....................................................................................................................4  Purpose  of  Research ..............................................................................................................5  Approach................................................................................................................................5  Summary  of  purpose  of  research  and  requirements  for  experiments ...............................6  

Methods  and  materials ...................................................................................................... 7  Optimization  of  Model  on  COMSOL .....................................................................................7  

Laminar  Flow ......................................................................................................................7  Transport  of  Diluted  Fluids ................................................................................................8  Single  microchamber  biochip ............................................................................................9  Multi  microchamber  biochip ...........................................................................................10  

Microfabrication ..................................................................................................................12  Design  of  mask .................................................................................................................13  Fabrication  of  Master  Molds  through  UV-­‐Photolithography ..........................................13  Multilayer  Soft  Lithography .............................................................................................14  

Experimental  Setup .............................................................................................................16  Fluid  control  system.........................................................................................................16  Calculation  of  Fluid  Flow  Rate .........................................................................................18  Cell  Culture.......................................................................................................................18  

Results............................................................................................................................. 19  Microfabrication ..................................................................................................................19  Optimization  of  flow  within  single  microchamber  biochip ...............................................20  

Gradient  control...............................................................................................................20  Optimization  of  dimensions  and  flow  within  mutli  microchamber  biochip .....................22  

Optimization  of  crosstalk  control  channel.......................................................................23  Crosstalk  by  diffusion .......................................................................................................24  Crosstalk  by  an  impulse ...................................................................................................26  Cell  culture .......................................................................................................................28  

Discussion  and  Conclusions.............................................................................................. 29  Microfabrication ..................................................................................................................29  Optimization  of  Gradient  control .......................................................................................29  Optimization  of  Crosstalk....................................................................................................30  Optimized  geometry  of  a  multi  microchamber  biochip.....................................................31  Recommendations  for  future  research ..............................................................................32  Summary  of  discussion  and  conclusions ............................................................................32  

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Introduction  Microfluidics is a branch of fluid dynamics that involves dimensions at the microscale. Microfluidics is a multidisciplinary study that can be applied to fields of engineering, physics, chemistry, microtechnology, and biotechnology. The use of microfluidics in molecular biology and other applications has attracted interest from both industry and academia, because of its potentials and advantages.

A microfluidic device is an engineered component designed to perform a specific function related to the analysis and manipulation of small volumes of fluid [1]. Microfluidic devices allow for the use of fewer reagents, shorter reaction times, and the possibility of parallel operation. They also allow for the shrinking of an entire laboratory onto a single chip. This type of system, known as a Lab-on-a-chip (LOC), has evolved dramatically ever since polymeric materials were introduced to the field.

In microfluidics, the most common material used is polydimethylsiloxane (PDMS). This polymer is inexpensive, nontoxic and optically transparent. Also, PDMS is described as hyperelastic, meaning that it can undergo large strains and still have full recovery [2].

PDMS is popular because it can be fabricated by soft lithography, a fabrication technique described in detail in the Methods and Materials section. Soft lithography allows pattern transfer from molds created by optical lithography to polymeric replicas. PDMS is suited for this process because its preparation is very simple and the replica process is fast and cost effective. PDMS is also suited for more complex devices, since a PDMS layer can be bonded covalently to other PDMS layers or other materials such as glass [3], or thermoplastic polymers [4]. This bond is very strong and can prevent leakage of fluids within a microfluidic device [5], [6].

The volume of fluid typically flowing within a microfluidic device is measured in nanoliters (nL), and flow rates are generally no greater than a few microliters (µL) per minute. 1 nL describes a cube that has dimensions of 100 µm on each side, which falls below the limit of resolution by the human eye [7]. At the microscale, fluids behave differently and there are certain parameters, such as flow rate and sensitivity, which are more controllable.

Microfluidics  for  cellomics  

Ever since advances in polymeric fabrication methodologies have allowed for biological studies, there has been an enormous increased interest in research on Micro total Analysis Systems (µTAS) or Lab-on-Chips (LOC) [8]. This fact can be illustrated by MicroTAS, the international conference for µTAS, a new journal called Lab-on-Chip and many articles on this topic appearing in other highly regarded journals. In the beginning, research on Lab-on-chip was focused on either combining microsensors with fluidic components (mixers, valves) or miniaturizing of methods for analytical chemistry. The latter had a large impact on genetic analysis, which can now be considered more or less of a routine method thanks to µTAS. In the past ten years, research on LOC has shifted focus onto more complex biological systems such as living cells and recently even whole organisms [9], [10]. New, simpler, cheep microfabrication techniques have allowed for the life science field to apply microfluidics in cell biology, neurobiology, pharmacology and tissue engineering. This type of research is often denoted cellomics [1].

Microfluidic devices are particularly interesting for cellomics research because they are capable of manipulating single objects with cellular dimensions. Cells fit very comfortably in these LOC, or biochips, given that the microchannels generally have widths ranging from 10-100µm [9]. Microfluidic devices allow for the manipulation of large number of cells simultaneously. Manipulating cells becomes easy given that these devices are designed to have complete environmental control [11].

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Gradient  control  

One of the first major applications of microfluidics in cellomics was to control the cell medium within the device. There is a strong interest in producing chemical gradients to mimic natural stimuli, which occur in biological processes such as cell migration, differentiation, or development [12]. The study of cellular response to chemical gradients requires fine spatial control of local concentration because cells can respond to concentration gradients localized to a region as small as 2% of their diameter [13].

There has been little success in generating gradients at a macroscopic scale. Macroscopic gradient generators (MGGs) are not reproducible and cannot generate complex stable gradients. This realization led to an interest in fabricating microscale gradient generators at a macroscopic scale (µGGs). Microfluidic devices can create multiple biochemical gradients with a controlled distribution. µGGs have been successfully used to study neural stem cell growth and differentiation [14], [15] migration [16], cancer cell chemotaxis [17], [18], and cellular response to a virus [19].

Stem cells have shown a promise for cell based therapies and tissue engineering. Manipulating the chemical environment of the culture in time and space allows the behavior of stem cells, such as proliferation and differentiation, to be controlled. For example, a microfluidic stem-cell culture platform with a concentration gradient can help study the effect of a growth-factor concentration on stem-cell behavior [14], [15].

Another application for generating gradients at the microscale is to develop a controllable drug delivery system [20]. By applying specific drugs to cells by means of a localized microfluidic channel, the physiological changes can be monitored in real time. The effects observed can be used to determine the optimal treatment of these drugs.

The same concept can be applied to study the response of a healthy cell to a virus or an infected cell. Viruses are mixed with a cell culture at a predetermined concentration and the infection cycle is allowed to occur [19]. Generating a concentration gradient of this infected cell culture shows how the healthy cells react to the virus at various concentrations.

Cell  Co-­‐culturing  

Co-culturing cells is an effective method to studying the communication between different cellular populations. The simpliest co-culture system consists in seeding two or more cell types in a single Petri dish, allowing them to grow in the same environment. This approach is relatively simple, but the information that can be extracted from it is rather small. A way to improve co-culturing systems consists in confining the different cell types in different compartments, selecting the degrees of freedom left for communication. Examples of this devices can be found in Campenot chambers [21], where walls of gel are used to create macroscopic areas on a Petri dish confining the somas of dorsal root ganglia (DRG) cells and letting only the process pass the barrier reaching different chambers. Co-culturing cells has proven to be a promising area for microfluidics to make a contribution to the field of biological research [22][23]. Being able to control cellular microenvironments precisely and dynamically allows these devices unique functions and advantages over traditional in vitro systems.

Several attempts have been made to create a microfluidic cell co-culture device for different biological applications. However, to date, only two reported platforms have been able to integrate all of the desirable features of a co-culture system into a microfluidic device [24], [25]. The first group, Hsu et al., designed a co-culture system to study the paracrine loop between cancer cells and fibroblasts. Using pneumatic valves to control the interaction between the two types of cells, they were able to control the culture medium within the chambers. The second group, Gao et al., developed a microfluidic cell co-culture device that uses a pneumatic/hydraulic valve to separate two cell populations in two chambers that 100

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µm apart. Gao et al. were able to completely seal off both chambers to culture cells. Once cells were stable, the valve barrier would be released and cell- cell interaction was studied. There are, however, several downfalls to the designs of both of these biochips. The dimensions of the cell culture chambers are in the millimeter scale, which provides less accuracy and control of the microenvironment. Also, these devices have no way of feeding the cells with chemical cues or implementing a concentration gradient within the cell culture chambers.

Purpose  of  Research  

The purpose of this research is to develop a multi microchamber biochip (MMB) that can be used to study interaction between two cell populations that can be manipulated by a concentration gradient. This MMB is modeled using finite-element modeling software called COMSOL Multiphysics 4.2. It is then fabricated in PDMS using multi-layer soft lithography in a clean room environment. Finally, several experiments help to determine whether or not the MMB works as it was modeled.

Figure 1: Schematic setup of multi microchamber biochip. The midchamber channel (MC) connects both

microchamber chambers while the crosstalk control channel (CC) separates the two chambers by laminar flow.

This device must be able to load distinct cell types into their separate areas. It must also allow for optimal control of the microenvironment of each cell type independently. When studying cell-cell interaction, this device should allow for a controllable crosstalk between the two microchambers. In biology, crosstalk refers to the instances in which one components pathway affects a different pathway. This process should be completely controllable within the MMB. Finally, this device must be able to create independent concentration gradients in each chamber.

The potential of this device is to simulate normal physiological conditions. One possible application is to study the differentiation of cardiac resident stem cells when in presence of cardiomyocytes. In the heart, there are stem cells that differentiate into cardiomyocytes, or heart muscle cells. The MMC can be used to study this process given that tests of this kind cannot be done in a Petri dish. Applying a concentration gradient in pulses puts a strain on these cells, which mimics the natural conditions of the heart.

Approach  

Before optimizing this MMB, a single microchamber biochip (SMB) is designed and fabricated. Running experiments on the SMB can help identify the possible limitations of the MMB. The specific dimensions and shape of the chambers, microchannels and vales of the MMB will be a reflection of the optimization process of the SMB.

MC  

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Figure 2: Schematic setup of single microchamber biochip. Access 1 is used for the loading of cells and medium.

Access 2 is used as an input to load drugs or chemical ques that generate a concentration gradient within the chamber. Access 3 is the output of the fluid that enters system. Valves 1, 2 and 3 control the fluid flow of the

system independently of each other.

The SMB consists of a microchamber for cell culture and three microchannels that work as inputs and outputs of the microchamber (Figure 2). With this setup, cells and their medium can be introduced through one channel, chemical cues and/or drug can be delivered through a different channel, and the fluid can leave the system through the third channel. Having two input channels creates a concentration gradient between the two fluids coming into the chamber. The gradient must be characterized as a function of the input flows.

Once the SMB is optimized and characterized, the MMB is modeled, designed and fabricated. COMSOL is used to model and optimize the crosstalk between the chambers by diffusion and by applying an impulse to increase the diffusion time of the two liquids. The optimized fabrication process for the SMB is used to fabricate the MMB.

Summary  of  purpose  of  research  and  requirements  for  experiments    

The purpose of this research is to optimize a multi microchamber biochip (MMB) that can be used to study interaction between two cell populations. This device must be able to

• load distinct cell types into their separate areas. • control of the microenvironment of each cell type independently. • allow for a controllable crosstalk between the two microchambers. • apply independent concentration gradients to each chamber.

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Methods  and  materials  This section describes the simulation process that is used through COMSOL Multyphysics to model and analyze both the single and multi microchamber biochips. The optimized microfabrication process to create these biochips is later described. Finally, the experimental setup of the fluid flow system and cell culturing is specified.

Optimization  of  Model  on  COMSOL  

A finite-element model is implemented in COMSOL Multiphysics 4.2 (COMSOL, Inc., Burlington, MA) and used to analyze and predict the microfluidic behavior of both the single and multi chamber biochips.

Laminar  Flow  To begin the modeling, the type of fluid flow within the system must first be known. What determines the type of fluid flow in a system is called the Reynolds number (Re), a dimensionless number representing the balance between inertial and viscous forces involved in the flow. Re is calculated as a function of density ρ, velocity U, characteristic length L, and dynamic viscosity µ:

(1)

For microfluidics, when Re small, the viscosity completely dominates over the inertial effects of the system and the flow will be laminar . Fluid flow is assumed to be laminar, meaning it will flow in parallel layers without mixing, as long as Re is below 1. Once Re surpasses this threshold, a fluid will begin to show signs of turbulence, or irregular, unpredictable fluid motion [26], [27]. At the microscale, flows are largely dependent on the small size of the microchannels.

In this particular case, water, which is the dominant fluid flowing within the system, is the liquid used to determine the Reynolds number. Water has ρ ≈ 1,000 kg/m3, µ ≈ 0.001 N·s/m2 and, using values from literature, it flows within a microfluidic channel at 0.1 nL/min through a microchannel of diameter 100µm. The resulting Reynolds number of this system is 0.017. Since the Reynolds number of the system is much lower than the threshold of 1, the devices were modeled in two-dimensions with a laminar fluid flow.

Incompressible  flow  The Laminar Flow Interface on COMSOL is used primarily to model slow-moving flow in environments without sudden changes in geometry, material distribution, or temperature. When selecting laminar flow in COMSOL, the default setting is for the flow to be compressible. However, since the flow of the system is much slower than the speed of light and the temperature remains constant, the flow is considered incompressible. This changes the overruling equation in microfluidics, the Navier-Stokes equation for steady state flow, to

(2)

where u is the velocity vector, p is the pressure , µ is the dynamic viscosity , and f are the body forces (per unit volume).

Shallow  channel  approximation    Another option in the Laminar Flow Interface is to use a shallow channel approximation. Shallow channels refer to a Hele-Shaw regime where the depth of a channel, z, is much smaller than the length, x, and width, y [28]. The flow within these types of systems are described as z-averaged, which means that it is a quasi-2D flow. By choosing this model approximation, a drag term is introduced to the fluid flow equation (equation 3). Specifically,

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it represents the resistance that the parallel boundaries place on the flow. Fluidic resistance depends on the shape of the channel where the fluid is flowing [29]. COMSOL by default considers the channels to be rectangular shaped and thus the added term is

(3)

where µ is fluid viscosity, L is the channel length, w is the channel width and h is the channel height. Fluidic resistance is directly proportional to the flow rate within a microfluidic device. The flow rate within a microchannel is given by

(4)

where Q is the flow rate, ΔP is the pressure drop across the channel, and R is the channel resistance. The flow rate is a fundamental aspect of design for a microfluidic device. The consistency of a system depends highly on the controllability of the flow rate within the microchannels.

For the simulations, the modeled channel thickness dz is of 25µm.

Material    Since the main component in cell culture medium is water, the material selected to complete the simulations is water. Also, during the experiments, water is used along with fluoresein dissolved in water to test the biochips without cells.

Mesh  The mesh of the system is selected. A mesh is a subdivision of the domains of the geometric model into small geometries. In this case, the geometry is divided into small triangles denoted as a Fine Triangular Mesh. COMSOL assigns a set of characteristic equations to each of these small geometries that describe physical properties, boundary conditions and imposed forces. These are then solved as a set of simultaneous equations to predict the entire geometry’s behavior. The accuracy of the model depends on how fine the mesh is.

Transport  of  Diluted  Fluids  COMSOL offers the option to couple different phenomena within the same model. Since the only mixing that occurs during laminar flow is diffusion, it is important to couple our model with a study of diffusion. Diffusion describes the process by which molecules redistribute themselves in response to concentration gradients (Figure 3)[30].

Figure 3: Mixing by diffusion of two streams flowing in contact [4].

In the Microfluidics Module in COMSOL, the Transport of Diluted Species Interface models the transport of chemical species and ions. This interface is suggested for solutions where the transported species have concentrations at least one order of magnitude less than their solvent. This is applicable for the biochip at hand given that medium, or water, is the predominant component being flowed through the system.

By default the Transport of Diluted Species Interface accounts for the diffusion of species by Fick’s Law and convection due to bulk fluid flow. Fick’s First Law describes diffusion where

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the flux of molecules J can be determined by the concentration C of molecules and a diffusion coefficient D,

(5)

D has dimensions of length squared per unit time, which in microfluidics is described as µm2/s. Although diffusion occurs regardless of the size of a particle, smaller particles redistribute faster by diffusion than larger ones [31]. The change in concentration with respect to time is expressed in Fick’s Second Law:

(6)

Convection  and  Diffusion  By selecting the Transport of Diluted Species Interface, certain values must be input to the program. It must be determined if the model will be solved using convection as well as diffusion. Since convection is defined as the movement of molecules within a net motion of fluid, it is safe to say that this model must also be solved using convection.

The diffusion coefficient between the two fluids in question must then be determined. Since the experiments will be done between water and fluorescein, the diffusion coefficient was set at 1.7e-10 m2/s [32],[33].

Single  microchamber  biochip  

Geometry  Once the units of the model were set to micrometers, the geometry of the single chamber biochip was drawn (Figure 4). The Chamber, where cells will be cultured, has an area of 200x200µm2. In2 has a width of 40µm, while In1 and Out have a width of 100µm. All walls except for the inputs and outputs are defined as No Slip. This is due to the general assumption that a solid boundary, the fluid will have zero velocity relative to the boundary. The inputs are defined as Inlets with laminar inflow. This means that the input to the system is a flow rate (m3/s). From literature, it is known that flow rate within a microfluidic device is at the scale of nL/min [7]. In these simulations, an input flow of 1nL/min ± two orders of magnitude is used. The output, Out, is set to Pressure, no viscous stress. This boundary condition is physically equivalent to a boundary that is exiting into a large container. It is numerically stable and admits total control of the pressure level along the entire boundary.

Figure 4: Geometry of single microchamber biochip. The Chamber has an area of 200x200µm. In1 and Out have a

width of 100µm. In2 has a width of 40µm.

Gradient  control  In order to understand the limitations and capabilities of the chip, different flow rates are applied to In1 and In2. When both flows come into the microchamber, a gradient forms between the two solutions. The area of the Chamber can be filled from 0% up to 100% with

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one solution or the other depending on the input flow rates. The percentage was calculated manually by tracing the area using ImageJ. This percentage of the Chamber filled can be characterized by calculating a ratio of input values between In1 and In2.

Thanks to the Transport of Diluted Species Interface, the inlets that can also have a molar concentration value along with a flow rate. The concentration specifies the amount of a constituent within the liquid. By defining a boundary as an inflow, the value of the concentration is asked. In this case, 0.1mg of fluorescein was diluted in 10mL of deionized water, which translates to 1E-7 M. This value was as solution A flowing through In2, while a value of 0 M was used for the inflow of In1. The outlets were then defined as outflows.

Going back to the possible future application of this MMB, the most important growth factor in the differentiation of stem cells to cardiomyocytes is called angiotensein II (AngII). This growth factor has been used previously within culture medium to enhance the differentiation of stem cells into cardiomyocytes [31]. Interestingly enough, the molar concentration that is given to these cells is 1E-7 ± one order of magnitude. This means that the simulations for this model not only represent the flows between water and fluorescein, but also represent the flows between AngII and culture medium.

Shear  Stress  Shear stress can be defined as the force applied by the flowing fluid to its boundary. In fluid mechanics, shear forces are always present and a fluid will always react to these forces by displaying strain [7]. Without a boundary, and therefore without any shear stress, it would be impossible for a fluid to move. By surrounding a fluid with a minimal boundary, it now has all the elements it needs to move [28]. Shear stress is the velocity gradient multiplied with the dynamic viscosity. For this case, a thin geometry implies a parabolic velocity profile in the z-direction. The value at the wall can be estimated as

(7)

where DH is the hydraulic diameter of the channel or chamber in question.

In biochips, shear stress cannot increase arbitrarily because cells grow on the floor of the chamber; the shear stress they experience is very important for their behavior. It is well known that shear stresses lead to cell polarization [16]. Higher levels of shear stress can even lead to cell detachment. For this reason, the shear stress on the surface of the biochip is measured to ensure that it does not exceed 0.3 Pa [34].

Multi  microchamber  biochip  

Geometry  MMB is obtained using two SMB symmetrically disposed and connected by a midchamber channel (MC) (Figure 5). The dimensions of the MC must be optimized to allow the fastest diffusion possible within the system. A crosstalk control channel (CC) is also added to separate the two chambers. When the flow of this channel is on, the two microchambers are separated. When the flow is off, there is crosstalk.

The optimal geometry was determined by modeling the system on COMSOL and varying geometrical and fluidic parameters.

Therefore, MMB is constituted as can be seen in Figure 5: two chambers with a surface area of 200x200µm2; four 100µm wide channels, two used as input (In1 and In2) and two as ouput (Out1 and Out2); two 40µm wide channels (In3 and In4); one midchamber channel (MC); one crosstalk channel (CC).

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Figure 5: Geometry of multi chamber biochip. There are two single microchamber biochips connected by a

midchamber channel (MC), and a crosstalk control channel (CC) that separates the two chambers from each other by laminar flow.

Gradient  control  It is important to ensure that the concentration gradients that were characterized by the SMB apply to the MMB model as well. Simulations are performed using the optimized flow rates obtained from the SMB model. Each microchamber with its respective input microchannels is tested independently. Then, In1-In4 are turned on to see if there is any crosstalk between the two chambers when generating gradients. Finally, the CC is turned on and the crosstalk between the two chambers is calculated once again.

Crosstalk  by  diffusion  This simulation can be better understood by continuing with the example of co-culturing cardiomyocytes with resident stem cells. The cells would be loaded independently into their microchambers and left to adhere for some time while medium is flowing through CC. During this time, AngII is produced by the cardiomyocytes that, in Figure 6, have been inserted into Chamber1. Once the cells have attached, the flow through CC is stopped and the medium of both cell cultures are allowed to crosstalk.

Figure 6: Initial conditions of MMB. Chamber1 and the channels leading to the pressure valves contain solution A.

The rest of the biochip contains water.

It is important to know how long it will take for the system to reach equilibrium by diffusion. This way, the reaction time of the cells will be controlled. The purpose of this is for the stem cells to be exposed to as much AngII as possible to enhance the differentiation of the cells.

Crosstalk  by  impulse  If equilibrium within the system takes too long by diffusion or not enough Solution A, or AngII, from Chamber1 has been delivered to Chamber2, a way to speed up the process has

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been designed. The initial setup of the system is changed by adding an output where In4 once was (Figure 7).

Figure 7: Setup of multi microchamber biochip for diffusion by impulse. In4 is now Out3 for the purposes of this

experiment.

By applying a pulse of medium through In2, the concentration within Chamber1 is pushed through the MC and delivered to Chamber2 (Figure 8a). Once a maximum concentration of AngII has been pushed into Chamber2, the CC is turned on to separate both chambers once again (Figure 8b). This allows for the cardiomyocytes to produce more AngII before giving another impulse. The time of the impulse, along with the input flow rates of In2 and CC must be optimized for this type of mixing.

a.

b.

Figure 8: a. Directionality of flow during impulse. b. Directionality of flow during separation of both chambers.

Microfabrication  

Although there are several different methods for fabricating microfluidic chips in PDMS, the most common approach was used for these experiments. Multilayer PDMS microfluidic devices are generally fabricated using molding methods. A photoresist pattern is printed onto a silicon wafer through UV-photolithography to generate a master mold. This master mold can then be used tens of times to mold PDMS replicas of the printed pattern. Since this method of fabricating microfluidic chips is less expensive and requires less time for design, fabrication and testing than conventional fabrication techniques, it is very advantageous in the prototype stage of designing these devices. All processes outlined here were conducted in a clean room to avoid surface contamination.

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Design  of  mask    The patterns that need to be printed onto the master mold can be designed using commercial computer drawing packages. AutoCAD was used to design the patterns for both the channel layer and the valve layer. The graphic designs were then printed onto transparencies using a high-resolution printer operating at 2400dpi (~ 10 micrometer res.). These transparencies were used in contact UV-photolithography (described in detail shortly) to generate features of photoresist with dimensions as small as 40µm on a silicon wafer.

Fabrication  of  Master  Molds  through  UV-­‐Photolithography  Once the masks were printed, they were used in UV-photolithography to generate the master molds. In this procedure, a thin layer of photoresist is spin-coated onto a silicon wafer. Using different types of photoresist of various viscosities, thicknesses of 1–300µm can be reliably spin-coated [5]. The photoresist is exposed to UV light through the mask, and a developing reagent is used to dissolve the unexposed regions. The resulting structure serves as a master for fabricating PDMS molds.

One master mold was needed for the channel layer and another was needed for the valve layer. The purpose of having two layers is to be able to block the fluid that is traveling through the channel layer by applying pressure from the upper valve layer. Two molds were necessary for each chip, one for each layer composing it. Both SMB and MMB are provided with valves (Figure 9) used to close the channels when flow or diffusion from the channels to the chambers must be avoided.

In order for the channel layer to close completely, it is imperative for the channels to be round in shape [35]. Positive photoresist AZ9260 (MicroChem, Berlin) allows for a pattern thickness of 40µm and was therefore chosen for the master mold of the channel layer. When this photoresist is baked after development, it reflows and the inverse channels become rounded. The valve layer master mold, on the other hand, is patterned with commonly used negative photoresist SU-8 2025 (MicroChem, Berlin). The protocols to produce master molds for each layer are described as follows.

Figure 9: An active valve (vertical) stopping flow of fluorescein coming into the microchamber.

For each master mold, a silicon wafer (Silicon Materials, Kaufering) is cleaned in a 5min bath of acetone following a 5min bath of isopropyl alcohol. The wafer is then placed on a hot plate at 200°C for 5min to remove all of the organic residues from the surface. Once the silicon wafer is cleaned and cooled down, it can be spin-coated.

Fabricating  the  channel  layer  master  mold  For the channel layer, AZ9260 is poured from the bottle until an even layer of the photoresist covers the surface. The desired film thickness is reached with two sequential spin-coats, each one depositing a resist layer of 15µm. The wafer is first spun for 30s at 1500rpm and immediately placed on the hotplate for 80s at 110°C, then spun a second time for 30s at

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1500rpm and placed on the hotplate for 180s at 115°C. The result is homogeneous film of resist 30±1µm thick.  

It is important to state that the photoresist reaches a much thicker height on the edges than in the center of the silicon wafer. This causes complications when placed under the UV-photolithography since the mask cannot come into direct contact with the desired exposed area causing the exposure to lose precision. To overcome this problem, an edge removal procedure is performed: a first exposure (113s at 15mW/cm2) is performed using mask with a central opaque area is used in order to expose the edges of the wafer. Since AZ9260 is a positive resist, the wafer can be developed without compromising the unexposed area of the sample. The mask used for this process was custom made, placing aluminum foil on a UV-transparent glass. After the exposure, the coated silicon wafer is then developed for 4min in AZ 400 K (MicroChem) diluted in deionized water at 1:3. The developing process is stopped by placing the wafer into deionized water for 1min.

The channel mask is then placed in contact with the coated silicon wafer. The wafer is exposed and developed as previously mentioned leaving only the pattern of the channels on the surface. As long as proper contact was achieved during the UV-photolithography, the dimensions of the patterns on the masks are transferred to the resist with maximum error of 2µm [36]. At this point, the photoresist on the master mold has square shaped profile. By placing it on a hotplate for 2 min at 110°C, the photoresist reflows and the channels became rounded.

Fabricating  the  valve  layer  master  mold  The protocol for the valve layer uses the same processes. When a cleaned and cooled silicon wafer is available, SU-8 2025 is poured from the bottle onto the wafer until the silicon is completely covered by the photoresist. The silicon must then be spun for 30s at 500rpm, to assure a homogeneous layer, and then for 1min at 3000rpm to reach the desired thickness of 20µm. The wafer is immediately placed on a hotplate to pre-bake the photoresist for 3min at 65°C, 5min at 95°C and finally cooled down to a temperature of 65°C.

The valve mask is placed in contact with the silicon wafer and the photoresist is exposed to a UV light for 27s at 9mW/cm2. The wafer is placed on a hotplate to post-bake the photoresist for 1min at 65°C, 5min at 95°C and finally cooled down to a temperature of 65°C. The photoresist is developed for 5min in SU-8 developer (MicroChem) and the process is then stopped in an isopropyl alcohol bath for 1min. The master mold is then hard-bake on a hotplate for 10min at 200°C.

Both master molds are placed in a closed container with a small well of a few drops of trimethychlorosilane (Sigma Aldrich) placed on the side for 3min. This process will protect the molds and facilitate the mold release when producing the PDMS replicas.

Multilayer  Soft  Lithography    Although various elastomers can be used for soft lithography, the most common one is a two-part polymer called polydimethylsiloxane (PDMS). The two parts consist of an elastomer and a curing agent, that when mixed together, create PDMS. When the PDMS is pealed off, it contains the patterns from the master. PDMS stamps are capable of reproducing features with dimensions as small as ~25 nm [26]. Therefore, designing and fabricating a detailed master is the only limitation for creating a PDMS device. PDMS has many favorable properties that allow for both microfabrication and biological research [35]. It has high optical transparency, which allows for microscopic analysis. Also, it is stable against humidity and temperature and it is mechanically durable [6].

Multilayer soft lithography defines the bonding of two or more elastomer stamps made from a photolithography-produced master mold [35]. In this particular case, one layer consists of the fluid channel network stamp and the other layer contains a control channel network stamp. The control channels are designed to perpendicularly cross the fluid channels wherever valves

15  

 

are desired. The bottom layer is spun with the elastomer material so that only a thin layer covers the network of channels (Figure 10). When the other layer is bonded on top, a thin membrane is created where the channels cross. When a control channel is pressurized, this layer deflects and thus occludes the fluid channel. If the fluid layer is the bottom layer, this configuration results in push-down valves. On the other hand, if the control layer is the bottom layer, the configuration results in push-up valves.

Figure 10: Fabrication procedure for a multilayer microfluidic device [36].

For the purpose of these experiments, a push-down configuration has been chosen. This means that the channel stamp is a thin, spin coated layer of PDMS while the valve stamp is a thick layer of PDMS. Each layer is first produced separately, and then bonded together. Finally, the chip is bonded onto Cyclic Olefin Copolymer (COC), which is a biocompatible thermoplastic material with excellent transparency in the visible range, suitable for high resolution microscopy.

Fabrication  of  layers  PDMS (Sylgard 184, Dow Corning) is prepared with different prepolymer to catalyst ratio formulations for each layer. The bottom channel layer a 20:1 ratio is used, while a 5:1 ratio is used for the top layer. These ratios of base to catalyst are important for the bonding between layers. It ensures that the top layer has an excess of the catalyst and the bottom layer has a deficiency. Both preparations are mixed thoroughly causing many air bubbles to appear in the mixture. They are then put into a vacuum bell jar until all of the air bubbles are removed. When the 5:1 mixture is degassed, it is removed from vacuum, poured on top of the valve master mold and put back into the vacuum to degas completely.

When the 20:1 PDMS mixture completely degassed, it is spun on to the channel master mold for 4min at 1100rpm to achieve a height of 30µm. The optimization of the spin curve was performed and can be found in Appendix. This spin-coated silicon wafer must rest for 30min at room temperature to obtain a more homogeneous layer of PDMS. After this resting period, both wafers are partially cured into an oven for 15min at 80°C. After this step, the PDMS is solid enough to be handled without losing its shape but the curing is not finished, so the two layers can still bond to each other.

Cutting  individual  stamps  and  bonding  PDMS  to  PDMS  The thicker valve stamps can now be cut out into individual chips and peeled off of the mold. To quicken the fabrication process, each master mold contains the same pattern repeated 4 times. On each valve stamp, there are inputs and outputs indicated by a circular star that now must be punched out with a needle under a microscope.

Each valve stamp can now be aligned on top of the channel PDMS layer. The valves must be facing down and specific features can help align the two patterns before placing them in contact with each other. The two layers are aligned by hand and so errors may occur. As long

16  

 

as all of the valves cross on top of the channels, the biochip will work. The wafer containing the two combined layers is put back in the oven at 80°C for 3h.

After 3 hours, the wafer is taken out of the oven and all 4 multilayer chips can be peeled away from the master mold. The inputs and outputs of the channel layer must now be punched out with a needle under a microscope. The bottom layer of this chip must remain clean until bonded with COC since this is where the fluids and cells will run through.

Bonding  PDMS  to  COC  By exposing PDMS to air plasma, silanol groups (Si-OH) are introduced onto the surface [35]. The biochips are exposed to oxygen plasma for 25s at a power of 10W with 1.5e-1 mbar of O2.

They are then placed in a beaker with 1% solution of (3-Aminopropyl)triethoxysilane (APTES) (Sigma Aldrich) in deionized water for 20min at room temperature. APTES acts as a bridge between PDMS and COC functionalizing PDMS to allow for a bond between the two materials [4].

COC (IBIDI, Germany) is cut up into pieces to cover surface of the chips and placed into oxygen plasma for 15s at a power of 10W with 1.5e-1 mbar of O2. This plasma exposition creates free oxygen radicals on the thermoplastic surface, increasing its wettability and reactivity. After 20min, the chips are dried with nitrogen gas to remove the excess fluid and placed on the COC. The bond between these layers is very stable and able to withstand pressures higher than 30psi [4]. These chips are left to dry for at least 12h.

Experimental  Setup  

Fluid  control  system  The experiments are set up on a system, which can be seen in Figure 11, that consists of a flow control through a pneumatic pressure pump and LabView software (National Instruments, Austin, TX). The use of LabView allows for digital control, which enables observing and recording the experiments.

The pressure pump has two sets of outputs. The first set consists of 5 outputs used as the valve inputs. Since PDMS is permeable to gas [37], valves cannot be pneumatically actuated, so they are filled with water before the experiments. The input pressure for the valves is fixed can be read directly off of the gage of the system, which indicates the total air pressure being delivered to the system. In the experiments, the fixed value being applied to the valves is 20psi. The LabView program controls the valves, acting as a switch for each valve input. Also, the valves can be set to pulse on and off periodically.

The second set of outputs of the pressure pump consists of 2 outputs that are controllable to a precision of 1psi. These are used as channel inputs in experiments for both the single and multi chamber biochips.

Another input control used is the syringe pump (Harvard Apparatus 11 Plus). This pump can be programmed to a precision of 1µL/min. A syringe of 10mL is used to enable the precision of this pump. Because of its precision, this pump is used in the experiments run on the multi chamber biochip as the input for the crosstalk control.

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Figure 11: Experimental setup. 1) Nikon TI optical microscope, 2) pressure system, 3) two controllable outputs, 4)

give outputs for valves, 5) pressure gage, 6) LabView control

The valve outputs are connected directly from the pressure pump system to the valve inputs in the biochip. Water is filled in transparent plastic tubes (Cole Parmer Tygon Tubong, Switzerland) and is then connected to the biochip through stainless steel (AISI 304) tubes (Unimed, Switzerland).

To connect the channel inputs of the pressure system to the biochip, one vial (National Scientific Target, Switzerland) was filled with water and another was filled with Fluorescein solution with a concentration of 0.5mg/mL. This allows for a clear visualization of the concentration gradient within the chamber of the biochip. These vials are connected to the controllable outputs of the pressure pump. Another tube connects the vial to the biochip, as seen in Figure 12. This configuration makes air pressure come into the vial and push the liquid up into the biochip.

The outputs of the channels in the biochip were attached to an empty vial for the waste to freely leave the system.

Once all of the tubes are attached, the biochip is then observed through an optical microscope (Nikon Eclipse Ti) at a magnification of 40x for the SMB and 20x for the MMB.

Figure 12: Connection of vials to biochip.

3

1

2

4

55

6

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Calculation  of  Fluid  Flow  Rate  An experiment is repeated 5 times, each time with a different biochip, to get an estimation of the flow rate of fluid going through the microchannels at any specific time. This simple experiment is set up with the knowledge that

�=��, (8)

where Q is the flow rate, V is the velocity of the fluid that is passing through a channel and A is the cross section area of the channel. Pressure is applied through both microchannels 1 and 2 and the distance achieved of the fluid through the tubing system is recorded, along with the time it took. By dividing the distance over the time, th/e velocity is obtained.

Knowing from equation (4) that resistance influences the flow rate, it is necessary to try all possible combinations of pressure inputs to compute the flow rates in specific instances.

Cell  Culture  Preliminary experiments to culture cells within the single chamber biochip are attempted. As a cell model, rat embryo fibroblasts (REF) stably transfected with Paxillin-EGFP were used. Paxillin is a protein that concentrates in early and mature focal adhesions, linking the cell cytoskeleton to the cell substrate adhesion points. The construct inserted with the transfection is a fluorescent label that allows for real time observation of the cell attachment to the substrate. The single chamber biochip was first cleaned with ethanol for 10min and then washed with deionized water for 5min. Phosphate buffered saline (PBS), a water-based salt solution that helps maintain a constant pH, is then flushed through the system for 10min. Dulbecco/Vogt modified Eagle's minimal essential medium (DMEM) is then flowed through the chip. Before inserting the cells into the system, a solution of 100µg/mL of poly–L-lysine (PLL) in deionized water is flowed through the system for 1h at 37°C to enhance attachment [38]. A concentration of 7 million cells per mL of DMEM is determined to optimize the observation possibilities within the microchamber. They are injected at high pressure through a syringe and after only a few seconds, the valves are closed to ensure that cells remain within the chamber.

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Results  This section first describes the results obtained from the microfabrication process. Next, the SMB was simulated to understand the limitation of the biochip before taking on the MMB. The concentration gradient formed in the chamber was characterized. Some experiments were also performed with the SMB. The crosstalk between the two chambers of the MMB was then optimized through COMSOL and the results are described in detail. Finally, some preliminary cell tests were performed in a SMB.

Microfabrication  

Microfabricating the biochips involved optimizing several processes. The masks first produced on AutoCAD and were then printed using the highest resolution available (2400 dpi. For the SMB, a mask was designed with a chamber area of 200x200µm. The design for the multi chamber biochip took into consideration the flaws from the single chamber biochip. One flaw that was observed was that a washing system was needed in order to flush out the excess of cells in the channels. Also, there were some difficulties closing the channels with a width of 40µm. The new design increased the width of the channel where the valves apply pressure to ensure the flow of fluid to be stopped. The designs for these masks can be found in the Appendix.

Optimizing the master mold fabrication process was imperative to producing the biochips. The valve master mold was squared, very resistant and had a thickness of 18µm. The channel layer master mold was rounded and had a thickness of 30µm. Both layers needed to have different properties for the biochip to work as intended. The recipes to fabricate these molds can be found in the Methods and Materials section.

Multilayer soft lithography was used to fabricate the biochips made of PDMS. The valve layer, as shown in Figure 13, was placed on top of the channel layer to form a push-down configuration. The thickness of the membrane in between the two layers was critical for proper closing of the channels. If the membrane was too thin, the valve could close the central part of the channel but not around the edges. On the other hand, if the membrane were too thick, the channel would not close at all. The optimization of this parameter led to a thickness of 15µm for channels with a height of 30µm.

Figure 13: Cross section cut of biochip. The push-down configuration has the valve layer fully bonded on top of

the channel layer.

The first SMB fabricated showed difficulties in proper closing of the 40µm channel. A proper understanding of the problem requires an explanation of another parameter that has to be considered in the design of a chip: the aspect ratio of the channel. In particular, for a fixed

20  

 

thickness, the larger a channel is, the better it closes because the curvature decreases (Figure 13). On the other hand, channel thickness has a lower limit under which the sidewalls cannot withstand the weight of the roof, and the channel collapses. Unger et al. fixed this limit at a 1:10 aspect ratio. If a layer contains channel of the same size, dimensioning the thickness is quite simple. Chips like SMB and MMB, however, have varied channel and chamber sizes. In particular, SMB has three different elements in a single layer: 40µm channel, 100µm channel and 200µm chamber. All elements lay on the same layer, so they have the same thickness. To prevent a collapse, the thickness must be dimensioned to the greatest element: the diagonal of the chamber, which measures approximately 280µm. In order to respect the 1:10 ratio, the thickness of the channel layer was fixed to 30µm. This trade-off is that the valves no longer close the 40µm channel properly.

Knowing this, the channel layer mask for the MMB was designed with a larger area where the valves intersected the channels. This was done to ensure that the valves would completely close the channels and no fluid would leak.

a.

b.

Figure 14: a. Cross section of 100µm channel. b. Cross section of 40µm channel.

Optimization  of  flow  within  single  microchamber  biochip  

Before optimizing the MMB, a SMB was optimized. Running experiments on the SMB helped identify some of the limitations the MMB would have. The specific dimensions and shape of the chambers, microchannels and valves of the MMB were determined based on the results obtained from the SMB. The most important feature of the SMB is the gradient generation, which was characterized fully as can be seen in the following section.

Gradient  control  The configuration of the SMB allows for two different solutions to be introduced into the chamber through separate channels. Having two input channels creates a concentration gradient between the two solutions flowing into the chamber.

To characterize this gradient, the SMB was first simulated using flow rates found in literature that were at the nL/min scale. Water was input through In1 and solution A was input through In2. What was found was that by increasing the order of magnitude of the flow rate inputs from 1 and 2nL/min to 10 and 20nL/min, the gradient, or the interface between the two solutions, would change from blurry to sharp (Figure 15). However, the percentage of chamber filled with solution A remained constant. In the case of Figure, 20% of the microchamber is filled with solution A.

Using this information, it was clear that a fixed ratio between the flow rates could help calculate the percentage of the chamber that would be filled by solution A. This ratio can be found in Table 1. This relationship between the two inputs proved true above the scale of 0.01nL/min and below the scale of 10µL/min.

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a.

b.

c.

Figure 15: All chambers are filled at a 20% with solution A. a. A very weak gradient is produced. b. A slow gradient between both solutions is produced. c. A very sharp gradient is produced.

Table 1: Percentage of microchamber filled with solution A with respect to input flow rates obtained from simulations

Ratio of Flow Rates In1:In2 Percentage of Microchamber filled

with Solution A

4:1 10

1:2 20

1:3 30

1:5 40

1:7 50

1:20 60

1:40 70

While simulating the model, the shear stress of the surface was calculated to ensure that the value did not go over 0.3Pa. When the flow rate was above 20nL/min, the shear stress would surpass this threshold in the 100µm wide channel. The shear stress within the chamber would surpass the threshold above a flow rate of 70nL/min.

When the biochip was fabricated and connected to the pressure system, the flow rate of the experimental process was found to be in the order of magnitude of 100µL/min. Running these values through the COMSOL model caused several errors. This is due to the fact that the Reynolds number at this speed exceeds the threshold for laminar flow within a microchannel. Nevertheless, experiments were performed and the filling ratios were obtained. A fluorescein solution was used through In2 and water was used through In1 to test the gradient generation capabilities of the SMB.

By varying the input pressures from 1-7psi, the chamber would be filled with different percentages of fluorescein and can be seen in Figure 16. From all 5 experiments performed, the ratio between the two input flows did not correspond to the ratios found in the simulations, as can be seen in Table 2. The experimental concentration gradients do in fact qualitatively represent the simulated gradients. Therefore, the experimental system must be optimized to adapt to the flow rates that were simulated.

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a.

b.

c.

d.

Figure 16: a. 10% of chamber filled with fluorescein b. 20% of chamber filled with fluorescein c. 50% of chamber filled with fluorescein d. 70% of chamber filled with fluorescein.

Table 2: Percentage of microchamber filled with solution A with respect to input flow rates obtained from experiments

Optimization  of  dimensions  and  flow  within  mutli  microchamber  biochip  

Before optimizing the MMB, it was important to guarantee that it had the same characteristics of the SMB. A study was performed to ensure that the concentration gradients that were characterized in the SMB apply to the MMB model as well. This was found to be true. Each chamber with its inputs and output performs as an independent SMB, even without applying a flow through the crosstalk control channel.

Figure 17: Multi microchamber biochip with independent gradient concentrations in the microchamber. MMB acts

as two independent SMB.

Flow Rate In1 (µL/min)

Flow Rate In2 (µL/min)

Ratio of Flow rates In1:In2

Percentage of Microchamber filled with Solution A

300 10 30:1 10

280 20 14:1 20

240 30 8:1 30

175 35 5:1 40

160 40 4:1 50

100 50 2:1 60

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Optimization  of  crosstalk  control  channel  

Figure 18: Directionality of flow when only crosstalk control chamber is on.

The CC was optimized to control the cell-cell interaction by means of laminar flow. When the CC is active, substances from one of the two chambers diffusing through MC are trapped in the flow of CC, and do not reach the other chamber. As a result, no crosstalk happens between the two chambers. Figure 18 shows the directional flow of the solution passing through CC when it is on. The initial conditions of the model were set as Figure 6, with solution A filled through Chamber1 and water filled through Chamber2. Water was flowed at 0.025, 0.25, 2.5 and 25nL/min through a CC with widths of 40, 60 and 80µm. The results relative to a CC 40µm wide can be found in Figure 19. Additional details can be found in the Appendix.

The presence of a laminar flow that intersects the volume of the chambers provides a virtual isolation for free diffusion. Figure 19 shows that after 3h each of the curves corresponding to different flows in CC is decreased under the 10% of the initial value of 1E-7M. A minimum value acceptable for the flow in CC can be estimated from Figure 20, which shows how a flow higher than 0.025nL/min is required to prevent substance transfer from Chamber1 to Chamber2.

Figure19: Normalized graph with initial concentration of Chamber1at 1E-7. Concentration is lost in Chamber1 due

to the flow through the CC.

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Figure 20: Concentration of solution A gained in Chamber2 due to the flow through the CC.

The concept of crosstalk controlled by laminar flow was then proved experimentally. A rhodamine solution was flowing at a constant rate through Chamber1 of the MMB and a fluorescein solution was flowing at a constant rate through Chamber2. The CC was filled with water and can be seen separating both chambers in Figure 21.

Figure 21: Rhodamine and fluorescein simultaneously flowing through the MMB while water was flowing through the CC to separate both solutions.

Crosstalk  by  diffusion  This experiment was set up to optimize the width of the MC and to determine the time needed for the system to diffuse completely in a closed environment. The initial conditions of Chamber1 were set at 1E-7M. This value represents both the concentration of fluorescein that was used for the experimental processes as well as (continuing the example) the amount of AngII that is produced by cardiomyocytes (Figure 20a). The rest of the system had a concentration of 0M given that there would be no presence of AngII. The model simulated the diffusion between these two concentrations for 4hr to ensure complete mixing (Figure 22c).

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a.

b.

c.

Figure 22: a. Initial conditions of the model. Chamber 1 has a concentration of 10E-7 M, while the rest of the system has a concentration of 0 M. b. Crosstalk that has occurred half an hour after the system begun diffusing. c.

The system is completely mixed after one and a half hours.

In order to reduce the mixing time, different geometries of the MC were taken into account. Both channel width and length were separately varied and mixing time was simulated for each configuration. Figure 23 shows how the concentration changes in the two chambers as a function of time at increasing MC widths. The concentrations in the two chambers are inversely proportional, reflecting the fact that the system is closed and headed toward equilibrium.

Figure 23: Complete diffusion time in both chambers of the MMB. The concentration of solution A lost in

Chamber1 is shown in the top half of the graph and the concentration gained in Chamber2 is shown in the bottom half of the graph.

Figure 24 a, b, c are details of Figure 23 for different MC lengths, showing the concentration changes of Chamber2. The three curves have different asymptotes, reflecting the change in the volume in which AngII is diluted, consequent to the increase of MC’s size. This change is quite small compared to the total volume of the chambers, and for this reason the asymptotes are very near each other. Indeed, the parameter mainly influenced by MC width, is not the equilibrium concentration, but the time constant of the diffusion: a system with a 120µm wide MC reaches its complete diffusion time (or saturation point) in half of the time it takes a system with a MD 40µm (Figure 24 d,e,f).

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a.

d.

b.

e.

c.

f.

Figure 24: a,b,c. Complete diffusion time in Chamber2. d.e.f. A comparison of the time it takes for Chamber2 of each system to reach total diffusion (red). Another comparison of how much time it takes for each system to

achieve the half point of diffusion (black).

Crosstalk  by  an  impulse  In an attempt to speed up the crosstalk process between the two chambers, input In4 was turned into an output, Out3 (Figure 7). With this configuration, all accesses were closed except for In2 and Out3 and an impulse of fluid with a concentration of 0M pushed the contents of Chamber1 into Chamber2 (Figure 25a). Since this fluid is incompressible and all the other outputs closed, the fluid in Chamber1 is subject to a semi-rigid motion in the

27  

 

direction of Chamber2. Once the maximum possible concentration was reached, In2 and Out3 were switched off. The CC was then switched on and a fluid with a concentration of 0M separated both microchambers, stopping the crosstalk.

a.

b.

Figure 25: a. Concentration profile during impulse at 20 s. b. Concentration profile during separation of both chambers at 50s.

The duration of the impulse, along with the input flow rates of In2 and CC were optimized for MMBs with different widths and lengths of the MC. Figure 26 shows a comparison between two possible, configurations with the same MC length (300µm) and different widths (40µm and 120µm). The two curves show the concentration of substance A in Chamber2 during the impulse experiment. In both cases, the flow rates delivered from In2 and CC are 5nL/min and 2.5nL/min, respectively. The timing of impulse delivery from In2 and crosstalk isolation form CC were optimized to maximize the concentration of substance A in Chamber2. Optimal times found were 40s for the 40µm MC and 25s for the 120µm configuration. The two curves show that wider channels are characterized by shorter rising times but as a drawback, the maximum concentration that we can transfer is less.

Figure 26: Optimal solutions for crosstalk sped up by an impulse. Both of these MMBs have a MC length of 300

µm.

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Cell  culture  Preliminary cellular experiments were performed using SCBs. Rat Embryo Fibroblasts (REF, see Materials an Methods) were chosen for these tests because of their excellent adhesion properties.

REFs were injected into In1 of previously sterilized chip with a syringe. When cells began to flow into the chamber, the flow was stopped and valves were closed. Trapped cells were left in the chamber for over 2h. REF used in this experiment were transfected with Paxillin-EGFP, a construct that added a fluorescent tag to Paxillin, a protein involved in the adhesion process. Thanks to this, it is possible to monitor cell adhesion analyzing the emission of fluorescently labeled Paxillin. After only 30 min in the chamber, it is possible to observe fluorescence emission from REF. Figure 27 shows an experiment performed with a 500x500µm SMB.

Figure 27: REF cells loaded into a SMB. Thanks to the transfection of a fluorescently labeled paxillin, it is

possible to monitor the adhesion process looking at the emission of EGFP.

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Discussion  and  Conclusions  This paper discusses the design, optimization and fabrication of a microfluidic cell co-culture biochip that uses laminar flow to separate two cell populations in two microchambers. Each microchamber can be both cultured and treated individually. The final discussion of how this microfluidic device was optimized can be found in this section.

Microfabrication  

In order to create MMB and SMB, clean room facilities were widely used. Different techniques had to be learned and optimized, and solution to specific fabrication problems had to be found. The first constraint imposed by the experimental need of embedding valves into the chip led to multilayer soft lithography architecture. Even though this technique was already performed by the researchers at NEST laboratory [39], this device required a sensitive adaptation of the already acquired knowledge to the process discussed above in Results session.

In order to obtain channel layers thick enough to prevent chamber collapse and to leave enough space for cells to flow, adhere and efficiently exchange nutrients with the medium, a thick positive resist (AZ9260) had to be used. Considering that the diameter of a non adherent cell is in average 10µm and that (as previously stated in the Results) the minimum thickness that prevented a chamber collapse was 28µm, both the requirements were fulfilled choosing a thickness of 30µm for the channel layer. This constraints imposed a quite hard drawback, because the thicker a channel is, the harder it is closing it using a valve. In particular, the thickness of the PDMS membrane was a key parameter for the correct functioning of the valve. Membranes thinner than 10µm could only close in the center of the channel and had hysteresis problems, while membranes thicker than 20µm were too hard to completely bend. The optimal thickness was set to 15µm. In order to obtain such a result, a pressure of 25psi had to be reached into the control lines. This underlined the need of a tight bond between the two PDMS layers. Several attempts failed when the pressure was above 20psi. A significant improvement was obtained cleaning the surface of the PDMS with 3M Magic Scotch Tape before placing the two PDMS layers in contact. This removed all the particles that may lie between the layers, introducing discontinuities in the material.

Another critical passage that had to be optimized was the rounding of the channels in the master mold of the fluidic layer. This rounding was achieved by a thermal process known as reflow. Indeed, all resists that do not crosslink can be heated in order to make them more fluid. When this happen, they tend to acquire a shape which is more convenient from an energetic point of view, and this has as a first consequence the rounding of the edges and the smoothing of the surfaces. AZ9260 is a positive resist, so it fits the requirements to undergo this process.

Optimization  of  Gradient  control  

Being able to generate a concentration gradient within a microfluidic device for co-culturing cells is one of the reasons that make this biochip a novelty. Biological processes that occur naturally due to a chemical gradient can be mimicked and studied with this biochip. Cells can first be loaded through In1 and given time to attach to the surface. They can then be manipulated by chemical cues or drugs through In2. The gradient, or interaction between the two fluids, depends entirely on the relationship between the flow rates of the inputs.

What makes this biochip so versatile is that under different input conditions, the gradient reacts differently. When the input values are in the order of 0.1nL/min, a very blurry and distributed gradient forms within the microchamber (Figure 15a). This type of gradient is needed to determine how much of a treatment is needed to promote cells to change. On the other hand, when the input values are in the order of 10nL/min, the gradient is very sharp and

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thin (Figure 15c). A sharp gradient is needed when delivering a treatment to a fixed amount of the cells within the microchamber.

The relationship between the inputs also affects the area of the microchamber that being treated. Table 1 shows the relationship between the two flows that is needed to treat a required area. This relationship can be applied to both chambers simultaneously, as can be seen in Figure 30.

Figure 30: Chamber1 is filled with 20% of Solution A, while Chamber2 is filled with 60%.

Optimization  of  Crosstalk  

A microfluidic device for co-culturing cells is used to study the communication between the different cellular populations. This communication can be referred to as crosstalk. This device used laminar flow to control the crosstalk between two different cell cultures. Choosing to control crosstalk by flow rate rather than by a valve allowed for proper modeling of the system. It is know that each time a valve opens and closes, it moves a volume of liquid that can change the concentrations of the fluids surrounding it [35]. To avoid this problem and to place the chambers geometrically closer to each other, the CC was designed.

If all accesses are closed, the solutions in the chambers are allowed to communicate. Activating only the CC separates the biochip into two SMBs. The laminar flow coming in through the CC intersects the MC, where a gradient begins to form between the solutions. The time it takes for the input solution to take over the entire chip depends on the width of the CC and the flow rate. The wider the CC and the faster the flow, the faster the system will be filled by the input solution (Figure 19). To reduce this, the CC must measure 40µm wide and can have a minimum flow rate of 0.1nL/min. When fluid is flowing through In1 and In3, however, the three solutions have a laminar flow and do not mix.

Crosstalk between the solutions in each microchamber can be performed in two methods. One method is to close all of the accesses of the chip and allow the two solutions to diffuse completely into a homogeneous mixture. When using a Solution A with a concentration of 1E-7M and a solution B with a concentration of 0M, the resulting mixture contains a concentration of approximately 40% of the initial Solution A. Taking a closer look at Figures 24a.b.c, there is a crossover in concentration between the three MC widths. This is due to the fact that the volume containing Solution A remains the same, but the volume containing solution B varies depending on the MC. Therefore, the concentration of Solution A in the homogeneous mixture depends on how wide the MC is.

The time needed to complete crosstalk by diffusion depends on the diffusion coefficient between the two solutions and the dimensions of the chamber connecting the two

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microchambers. Increasing the width of the MC and reducing its length results in a faster diffusion time (Figure 24). A MMB with MC measureing 120x300µm takes 2h to diffuse completely.

The second method to promote crosstalk between the two chambers is by applying an impulse to push the contents of Chamber1 into Chamber2 (Figure 25a), following a flow through the CC separating the two chambers once again. Diffusion still happens at the interface between the two solutions causing a loss in concentration during the motion. This means that Chamber2 will be exposed to a very concentrated Solution A for under a minute. As long as the biomolecule needed for the biological process at hand is being produced continuously by the cells in Chamber1, the cells in Chamber2 can be exposed to continuous pulses of high concentration of Solution A.

Reducing the width size of the MC increases the concentration of Solution A pushed into Chamber2. However, the fall time of the exposure is faster with a narrower MC.

Figure 31: Concentration in Chamber2 when an impulse is applied. The line represents the 40% of concentration

that is achieved when the MMB undergoes crosstalk by diffusion.

The versatility of this microfluidic chip allows for the crosstalk to be controlled either by diffusion or by impulse. It is important to note that a higher concentration of Solution A in Chamber2 is achieved by impulse crosstalk than by diffusion. The homogeneous mixture after diffusion reaches a concentration of 40% of Solution A. With an impulse, an MMB with MC of 120µm reaches at least 20% more concentration of Solution A in Chamber2 (Figure 31).

Optimized  geometry  of  a  multi  microchamber  biochip  

Taking all of the results into consideration, the optimal geometry for the MMB is as follows:

• Two microchamber of 200x200µm, • Two channels for cell loading of 100µm in width, • Two channels for drug delivery or chemical cues of 40µm in width, • Midchannel of 120x300µm, • Crosstalk control channel of 40µm in width.

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Recommendations  for  future  research  

The knowledge acquired from the theoretical modeling and preliminary experiments led to the production of a working prototype ready to be tested for cell culture experiments. The biocompatibility of the MMB must be tested, although it should prove to have the same properties of the SMB. Once biocompatibility is proven, different cell types must be cultured within the biochip to ensure the crosstalk method works as modeled.

The future applications for this device are unlimited. It can be used to study differentiation of cells and drug delivery. Furthermore, it can be used to understand the affects diseased cells have on healthy cells.

Summary  of  discussion  and  conclusions  

In summary, the following points can be concluded from this research:

• The geometry of the microchip was adjusted to fulfill the limitations caused by the fabrication process.

• Flow rates in the order of 0.1nL/min produce a blurry and distributed concentration gradient within the microchamber Flow rates in the order of 10nL/min produced very sharp and thin concentration gradient within the microchamber.

• Unless the device is needed for a specific process that undergoes shear stress, it is recommended to stay below a flow rate of 70nL/min.

• The solutions reach a homogeneous mixture after 2h of crosstalk by diffusion with 40% of Solution A.

• Through crosstalk by impulse, continuous pulses of high concentration of Solution A can be pushed into Chamber2.

 

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Acknowledgments    I’d like to use this space to thank the people who have helped me accomplish the goal I set for myself in March of 2011. Thank you to my supervisor at TU Delft, Dick Plettenburg, who overviewed my progress. You gave me the possibility to branch out and learn something new and inspiring. This work could have never been realized without my supervisor at NEST, Marco Cecchini. You guided me through this entire process with a friendly smile and an open door. I am very grateful to Sandro Meucci who was always willing and able to give great advice. I would also like to thank Christian Poelma for accepting me as a student and discussing my work with me. Finally, I’d like to thank my family. Your never-ending support gives me the confidence to keep setting goals for myself.

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