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High Throughput Microfluidic Platform Capable of Mimicking Key Vascular Microenvironments
by
Oleg Chebotarev
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Mechanical and Industrial Engineering University of Toronto
© Copyright by Oleg Chebotarev 2013
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High throughput microfluidic platform capable of mimicking key
vascular microenvironments
Oleg Chebotarev
Master of Applied Science
Department of Mechanical and Industrial Engineering
University of Toronto
2013
Abstract
The process of finding a new drug against a chosen target for a vascular disease usually involves high-
throughput screening in static multi-well plates. However, due to the disconnect between cell behavior
in static culture and the physiological environment, only a small fraction of move on to clinical trials. To
address this, I designed and fabricated a multi-channel microfluidic platform capable of mimicking key
vascular environments to be used for drug screening. An experiment studying the effects of TNFα on
moncyte-EC adhesion were performed under flow conditions using the platform and in a static multi-
well plate. Results showed a similar response in monocyte adhesion with the increase in TNFα dose in
both conditions. However, wells with non-treated ECs in static plates produced 40x more florescence
than wells with no monocytes. The microfludic platform however circumvents this issue by washing
away these weakly adhered ECs allowing small dose variations to be noticeable.
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Acknowledgments
First and foremost I would like to deeply thank my primary supervisor, Dr. Craig Simmons, for my
completion of this thesis; without him I wouldn’t actually have had to write this thesis and do all that
hard work. I am, in fact, sincerely grateful for all his guidance, his encouragement, humor (I’ll miss that
the most), for all the free food he bought us over the years (no wait, I’ll miss this one the most), and
above all his infinite, infinite patience with me. At times, when any sane man would completely
disregard my incomprehensible nonsense, Craig would make an effort to tolerate my behavior. Seriously
Craig, you are without a doubt the sickest (means superlative in slang talk) supervisor I have ever had.
Thank you.
I would also like to thank my co-supervisor Dr. Aaron Wheeler and his lab members for all the
inspiration and help I received over these two years. Without their ideas, I would still be trying to figure
out how to do science. Also, the sushi dinners were fun.
Further, I would like to acknowledge all my lab members who were more like friends than just co-
workers. I also thank you all for tolerating and embracing my random nonsense. Jenna, Wing, Agnes,
Justin, Luke, Zahra, Bogdan (oh Bogdan…), Mark; Thank you all for making my experience in the lab a
blast! Without you none of this would be possible (or enjoyable).
Last but not least, I would like to thank my committee members, Dr. Jonathan Rocheleau and Dr. Lidan
You, for agreeing to listen to my ramblings as to why I should be allowed to graduate.
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Table of Contents
1 : Introduction ............................................................................................... 1
1.1 Objectives ............................................................................................................................................2
2 : Literature review ........................................................................................ 3
2.1 The drug screening process .................................................................................................................3
2.1.1 High throughput screening of drug candidates: fast, yet inefficient ...........................................4
2.2 Essential vascular micro-environments ...............................................................................................4
2.2.1 Extracellular matrix regulates endothelial cell behavior and is necessary for cell survival .........5
2.2.2 Cell-cell signaling: sticking together .............................................................................................6
2.2.3 Blood flow and resultant mechanical forces: the shear stress of it all ........................................7
2.3 Cell culture systems to mimic vasculature ..........................................................................................8
2.3.1 Shear flow systems versus static culture: quality over quantity? ................................................9
2.3.2 The many benefits of culturing vascular cells in platforms capable of inducing physiological
shear stresses ..................................................................................................................................... 10
2.4 Can microfluidics be utilized in drug screening sector? ................................................................... 15
2.4.1 Commercial drugs screened in microfluidic platforms: putting the drugs to the test .............. 16
2.5 Utilizing microfluidic platforms for HTS ........................................................................................... 17
2.5.1 Critical issues in HTS .................................................................................................................. 18
2.6 Conclusions ....................................................................................................................................... 20
3 : Device concept and design ......................................................................... 22
3.1 Requirements ................................................................................................................................... 22
3.2 Alpha HTS Platform Concept ............................................................................................................ 24
3.2.1 Pumping mechanism ................................................................................................................. 25
3.2.2 Cell seeding and imaging functionality ...................................................................................... 27
3.3 Initial conceptual design and operation ........................................................................................... 29
3.4 Overview of basic operation ............................................................................................................ 31
3.4.1 Pre-experimental cell culture .................................................................................................... 31
3.4.2 Generating shear stress ............................................................................................................. 32
3.4.3 Post experimental data collection ............................................................................................. 32
3.5 Microchannel design ........................................................................................................................ 33
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3.5.1 Channel design simulations ....................................................................................................... 34
4 : Device fabrication, characterization and optimization ..................................... 38
4.1 Initial prototype fabrication ............................................................................................................. 38
4.1.1 Channel module fabrication - PDMS ......................................................................................... 39
4.1.2 Channel layer fabrication – Polystyrene .................................................................................... 41
4.2 Device operation (software, pressure regulation) ........................................................................... 44
4.3 Shear stress and flow-rate measurement ........................................................................................ 47
4.3.1 Channel dimension verification ................................................................................................. 47
4.3.2 Flow rate sensor ........................................................................................................................ 48
4.4 Flow-rate characterization ............................................................................................................... 51
4.4.1 Undesirable hydrostatic pressure ............................................................................................. 52
4.4.2 PID Control................................................................................................................................. 56
4.4.3 Resistance Increase – filter paper or channel design ................................................................ 58
4.4.4 Flow-rate variability across wells .............................................................................................. 61
4.5 96-well upscale ................................................................................................................................. 62
4.5.1 Channel module: 2.0 ................................................................................................................. 63
4.5.2 Cell seeding subsystem .............................................................................................................. 66
4.5.3 Flow subsystem ......................................................................................................................... 67
4.5.4 Conditioning subsystem ............................................................................................................ 69
5 : Device validation and pilot studies ............................................................... 71
5.1 Well plate reader sensitivity ............................................................................................................. 71
5.1.1 Methods .................................................................................................................................... 71
5.1.2 Results ....................................................................................................................................... 72
5.2 Monocyte adhesion assay ................................................................................................................ 74
5.2.1 Methods: assay in microfluidic platform ................................................................................... 74
5.2.2 Methods: assay in static well plates .......................................................................................... 75
5.2.3 Statistical analysis ...................................................................................................................... 75
5.2.4 Results and discussion ............................................................................................................... 76
5.3 Cell conditioning with long-term shear stress .................................................................................. 80
5.3.1 Methods .................................................................................................................................... 80
5.3.2 Results ....................................................................................................................................... 81
6 : Conclusions ............................................................................................. 82
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6.1 Future recommendations ................................................................................................................. 82
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List of Tables
Table 1 – Pumping mechanism options. Each option is ranked on accuracy (higher is better), complexity
(lower is better), and spatial and temporal flowrate variability (lower is better) ..................................... 25
Table 2 – Device design concepts: modular vs. non-modular. Each option is ranked on ease of use
(higher is better), fabrication complexity (lower is better) ........................................................................ 28
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Table of Figures
Figure 1 – Schematic overview of a blood vessel and the endothelial cell microenvironment. The ECs
reside on the inner layer of the vascular wall receiving external cues from: the underlying ECM which
also serves as an anchor to stabilize the ECs, local cells (monocytes and SMCs) and shear stress. Due to
the complexity of the system, mimicking all the necessary components of this environment in vitro
platform can prove to be challenging [15]. ...................................................................................................5
Figure 2 – Cell culture systems mimicking specific components of the vasculature. A) By injecting a
compound in the middle channel, it is possible to create a stable concentration gradient across the
channe cross section allowing studies such as cell migration to be performed [46]. B) A schematic of a
platform capable of co-culture of ECs and SMCs. The two cell types have direct contact allowing cell-cell
communication. This device also produces regions of disturbed and continues shear stresses which are
essential environments of the vasculature [50]. ........................................................................................ 12
Figure 3 – High throughput microfluidic platforms. A) a microfluidic device used for studying
concentration gradients in a network of branching serpentines, an on chip function which allows high
throughput with very little complexity [88]. B and C) The BioFlux 200 System for live-cell assays under
controlled shear flow. The system utilizes a well plate format, which is not yet compatable with existing
automated well plate handling equipment, however it is a step in the right direction [38]. .................... 19
Figure 4 – NucleoVac 96 Manifold system. An existing vacuum manifold typically used for rapid manual
parallel purification of nucleic acids. The system provides a chamber that can withstand negative
pressure, which drives the flow through a filter well plate [93]. ............................................................... 27
Figure 5 – Final conceptual desing of the HTS platform. A) an exploded view of all modules in the system.
The platforms is comprised of several layers which are stacked on each other and clamped together
using 4 bolts. B) Fully assembled device. The platform resembles a deep 96 well plate making it
compatable with automated well plate handling equipment such as well plate readers and liquid
handlers. C) Cross section view of a single well (channel). The inlets and the outlets are positioned in a
way to be invisible to well plate readers when looking down a well. ........................................................ 30
Figure 6 – A concept of a single microfludic channel. A) AutoCAD rendering of a channel’s outline. The
inlets, outlets and the curved regions of the channels are positioned in a way to be invisible when
looking down a well. B) Channel mesh (generated in COMSOL) to be studied in detail using
computational fluid dynamics software. .................................................................................................... 35
Figure 7 – Simulated channel pressure and shear stress distributions. Simulation parameters were
chosen to mimic: fluid properties of water, maximum allowable flowrates of 0.67 mL/hr and channel
dimensions of 500 x 50 μm. A) Majority of the pressure is distributed across the serpentine channel. A
pressure difference of 700 Pa is needed to generate maxium allowable flowrate. B) Shear stress
distibution was shown to be equal across the length of the channel ........................................................ 36
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Figure 8 – Flow streamlines and shear stress distribution of curved and straight regions of the channel.
A) Shear stress was shown to be symmetrical in the straight region of the channel 250 microns before
and after each bend. B) Channel clogging was simulated as immovable obstacles across the channel. As
the blockage increases, the shear stress around that region exponentially increases which hopefully may
aid in dislodging the blockade and stabilizing flow. A block of this severity reduces flow rates and shear
stress across the whole channel by 11% .................................................................................................... 36
Figure 9 – Velocity profile in a straight region of a channel. A) 2D velocity profile in a channel’s cross
section. B) Velocity profile distribution at the center of the channel. The profile shows an equal flow
distribution for the majority of the channel (60%) suggesting a uniform wall shear stress distribution at
the bottom of the channels. ....................................................................................................................... 37
Figure 10 – Dissasembled view of the initial prototype. A 12 well minature prototype was fabricated
based on the 96 well concept. Every well and channel were made to the same scale as a 96 well plate
(same well profile pattern). ........................................................................................................................ 38
Figure 11 – Assembled view of the initial prototype. The PDMS channels were bonded to the omniwell
plate which in turn became the base for microfludic channels. ................................................................ 39
Figure 12 – PDMS channel layer fabrication process. 1) A master and a glass wafer are thoroughly
washed using acetone and isopropanol to remove any debris on both surfaces. 2) PDMS + cross linker
were poured on both surfaces and then degassed to remove any trapped bubbles between the PDMS
and the master. 3) Rubber spacers (of identical height) were placed in the master which was then
covered by the glass wafer in order to produce an equal thickness PDMS substrate with flat surfaces. 4)
The PDMS was baked for 4 hours and the master along with the glass wafer were carefully delaminated
from the cured PDMS. ................................................................................................................................ 41
Figure 13 – Rapid prototyping technique for hot embossed substrates developed by Young, EWK et al.
[98]. The method involves fabricating a hardened epoxy mould identical to the SU-8 master. The epoxy
mold can then be used for hot embossing polymer substrates. ................................................................ 43
Figure 14 – Channel moulds used for hot embossing polystyrene. A) Hardened aluminum epoxy mould
used to fabricate 12 well channel prorotypes. B) Machined aluminum master used for hot embossing 96
well pattern of microfludic channels. ......................................................................................................... 44
Figure 15 – Photo of pressure contol system used to generate a vacuum in the manifold. The Arduinio
board, which was laid out on a breadboard, sent commands to the pressure regulator which was hooked
up to a small solenoid pump. The volume sensor circuit (section 4.3.2) was connected directly to the
National Instruments data acquisition board (image not shown) which related flowrate information
directly to the PC. ....................................................................................................................................... 45
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Figure 16 – Labview control software interface. The program displayed pressure control waveforms as
well as volume information in a single well. The software had the capability to record sensor inputs and
program pressure functions into the system. ............................................................................................ 46
Figure 17 – PDMS channel cross section cutouts used for dimension measurements. The images were
analayzed in ImageJ software. ................................................................................................................... 48
Figure 18 – Well volume sensor design. A) Two conductive wires are placed inside the well at opposite
ends. B) A circuit that generates an alternating current (2 kHz, 10 Vp-p) through the fluid in the well. The
voltage drop across the well can be measured and related to the liquid level inside the well in real-time.
AC current was used instead of DC to avoid electrolysis. .......................................................................... 49
Figure 19 – Volume sensor was calibrated by consequtevely adding 50 μL of water to the well. Due to
the non-linear relationship between liquid level and voltage, the sensor’s resolution (sensitivity)
increases as the well volume decreases. .................................................................................................... 51
Figure 20 – Nonlinear well volume decrease in early prototype characterization. The vacuum manifold
was left open to produce a constant 0 (atmospheric) pressure in the manifold. The resulting non-
linearity was caused by the hydrostatic pressure change in the well reservoir during the course of the
experiment. ................................................................................................................................................ 52
Figure 21 – Volume and pressure parameters used in flowrate charachterization model. ...................... 54
Figure 22 – System model simulated in Simulink (MATLAB). Simulation was necessary due to non-linear
functions such as derivatives and integrals. Blue boxes represent controllable parameters (such as
channel dimensions or initial volumes), white boxes are functions or constants necessary for the model,
and yellow box represents variable functions (such as pressure or flowrate regulations in the vacuum
manifold). ................................................................................................................................................... 55
Figure 23 – Simulink output of well volume functions. A) Volume change when applying a constant
pressure in vacuum manifold (500 Pa). Flowrate remains non-linear throughout the assay, and the
majority of the well depletes within 15 minutes. B) Constant air outflow from the vacuum manifold
(emulating a syringe pump or a peristatltic pump) produces a linear volume depletion (constant
flowrate) only after 10 minutes into the experiment at which point the majority of the well is depleted
leaving little reagents for the rest of the experiment. ............................................................................... 56
Figure 24 – Active PID control is able to successfully stabalize the flow using volumetric flowrate data
from the volume sensor as feedback. The PID controller however is only able to regulate a single well,
and requires a complex setup (such as a PC and a sensor) to properly function. .................................... 57
Figure 25 – Revised channel profile. The new channel incorporates 2 resistive branches which produce
enough resistance to slowdown the flow and enforce a higher pressure gradient which theoretically
should diminish flowrate variability caused by the hydrostatic pressure decay. A) AutoCAD model of the
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revised channel. Blue ring indicates which channel areas are visible my well plate reader. B) Aluminum
cast mold of the revised channel profile used for hot-embossing polystyrene channels. ........................ 59
Figure 26 – COMSOL simulations of the new channel profile. A) The negative pressure needed to
produce desirable flowrates increased from 700 Pa to 10 kPa, well over the range of hydrostatic
pressure. B) Shear stress distribution in the new channel profile remained the same as in the initial
channel profile. ........................................................................................................................................... 59
Figure 27 – Well volume is finally able to decrease linearly over the duration of 3 hours. The filter paper
provides enough resistance to require pressure ranges of 10-30 kPa, negating any undesired effects
caused by the hydrostatic pressure. .......................................................................................................... 60
Figure 28 – Shear stress variability across 94 simultaneous conditions. The data was collected using the
upscaled 96 well version (section 4.5) by measuring the remaining volume after a 3 hour experiment. A)
Shear stress/flowrate variation in each channel. Some cases show flowrate deviation as high as 105.8%.
B) Shear stress histogram across all 94 conditions. ................................................................................... 62
Figure 29 – System block diagram, along with all the sub-systems and their modules. Each sub-system
employs a unique well block and a base plate. The channel module is shared across all sub-systems .... 63
Figure 30 – Channel module fabricated from polystyrene by hot-embossing fabrication methods using an
aluminum mold (section 4.1.2) .................................................................................................................. 63
Figure 31 – Cell seeding mask characterization. ECs were grown on the channel substrate with or
without the mask. The cells were stained with Calcein AM (2 μM, Invitrogen) and Hoechst 33342 (2
µg/mL, Invitrogen). A) Cells grown on polystyrene channels without the mask adhere to areas outside
the channel. B) Cells grown on polystyrene channels with the presence of the mask. After cells reach
confluency, the mask is peeled away, and the channel was imaged. The cells only reside inside the
channels. C) Leftover adhesive after mask removal. The adhesive is invisible under brightfield
microscopy, but auto-flouresces in the red spectrum. This induces artifacts when imaging cells which
have been stained with fluorophores that emit in the red wavelength. ................................................... 64
Figure 32 – Surface of hot embossed polystyrene channels. A) The milling action (during mold
fabrication) produces a circular pattern in the surface finish, while B) grinding/polishing the channel
surfaces on the mold with sand paper to produces a scarred surface. ..................................................... 65
Figure 33 - PDMS gasket fabrication process. 1) PS channels (coated with cell seeding mask) and a glass
wafer are thoroughly washed using isopropanol to remove any debris on both surfaces. The PS channels
were then plasma treated in Harrick Plasma expanded plasma cleaner for 3 minutes. 2) PDMS + cross
linker were poured on both surfaces and then degassed to remove any trapped bubbles between the
PDMS and the PS substrate. 3) Rubber spacers (of identical height) were placed in the master which was
then covered by the glass wafer in order to produce an equal thickness PDMS substrate with flat
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surfaces. 4) The PDMS was baked for 4 hours and only the glass wafer was carefully delaminated from
the cured PDMS. 5) Holes were punched over every channel to expose their surfaces. .......................... 66
Figure 34 – Cell seeding subsystem. A) Assembled view of the final device. B) Exploded view showing all
the modules in the sub-system (gaskets are not shown) ........................................................................... 67
Figure 35 - Flow subsystem. A) Assembled view of the final device on a vacuum manifold. B) Exploded
view showing all the modules in the sub-system (gaskets and vacuum manidold are not shown) .......... 68
Figure 36 – Filter membrane layer. A) 94 separate filter disks are held together by 2 PVC membranes. B)
Cross section view of a single filter section. A hole is cut above and below each filter disk to allow flow
through the filter. ....................................................................................................................................... 68
Figure 37 - Conditioning subsystem. A) Assembled view of the final device. B) Exploded view showing all
the modules in the sub-system (gaskets are not shown) ........................................................................... 69
Figure 38 – Results from pilot well plate reader sensitivity assay. A) Flourescently labeled monocytes
(calcein AM, 2 μM) were added to 36 wells at a varying concentration (60 – 20,000 cells/mL). The well
plate was incubated for an hour and scanned using a tabletop plate reader. B) A well that had at least 10
cells/mm2 was distiguishable from a well with no flourescently labelled cells in a plate reader. C and D)
Wells were then imaged under a florescent microscope in order to accurately determine the number of
cells in each well. ........................................................................................................................................ 73
Figure 39 – Flourescence intensity and distribution across the device recorded by the well plate reader
after monocyte adhesion assay. Each row had an equal TNFα activation concentration (n = 7 or 8) with
12 different conditions (12 columns). A and B) Assay perfomed in a static well plate. C and D) Assay
performed in flow sub-system. Data are shown as mean ± standard error. ............................................. 77
Figure 40 – A) Relationship between TNFα activation concentration and resulting florescence intensity
reading per channel. Dashed line shows results obtained from static well plate and solid line shows
results obtained from shear flow; * p = 0.046, ** p < 0.001. B and C) fluorescent microscopy images of
channels after flow assay. The monocytes outside of the channels were seen to be introduced during
post assay device disassembly. This can be avoided by aspirating the remaining media (with monocytes)
from the wells after the experiment and replacing it with a washing buffer then again inducing shear
flow for a short duration to rise the channels of any unbound monocytes. ............................................. 78
Figure 41 – Re-circulatory flow loop used for long-term cell shear stress conditioning experiment. The
media is pumped out of the subsystem, into the flow dampener which converts pulsatile flow to
continuous uninterrupted flow. The media leaves the dampener and enters the peristaltic pump. The
pump then guides the media back into the conditioning subsystem. ....................................................... 80
Figure 42 – Live dead stain of endothelial cells after flow condotion assay. The cells were sheared for 48
hours at 5 dynes/cm2, then stained with 2 μM calcein AM (Invitrogen) and 8 μM ethidium homodimer
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(Invitrogen) for 20 minutes. A) majority of ECs remained viable and confluent after 2 day conditioning
assay. B) Some channel regions did not have confluency after cell conditioning assay. ........................... 81
Figure 43 – A) CFD analysis of pressure drop across a (50 µm high) channel with new membrane. B) The
membrane hole was modeled as a 10 µm diameter, 250 µm long tube. 11.4 kPa of pressure is needed to
drive the flow at the maximum desired shear stress (5 dynes/cm2). ........................................................ 83
Figure 44 – Channel surface roughness. PDMS channels were cast using methods described in section
4.1.1 and imaged using AFM techniques. .................................................................................................. 84
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1: Introduction
Cardiovascular diseases remain the biggest cause of deaths worldwide [1], so a great deal of effort has
been invested in trying to unravel mechanisms that determine vascular function and dysfunction.
Vascular dysfunction is manifested in several major diseases, including atherosclerosis [2], diabetes [3],
and cancer [4]. The root causes of these diseases involve regulation of the functions of vascular cells by
their dynamic microenvironment, including biochemical and biophysical factors and interactions with
other cells. Conventional tissue culture technologies (i.e., static multiwell plates) poorly recapitulate the
dynamic vascular microenvironment, and it is now clear that cells cultured in conventional static
systems respond differently than those in vivo [5].
To circumvent experimental artifacts resulting from growing cells in static culture, flow chambers and
bioreactors that are capable of mimicking key vascular microenvironmental conditions, such as fluid
flow-induced shear stress, have been developed. Over the last few years, the importance of
miniaturization and parallelization coupled with advances in micro-fabrication techniques has driven this
research field to utilize microfludic technologies. While early concepts of microfluidic technology were
applied in sensory devices where small amounts of analytes needed to be transferred through a straight
channel to a sensor [6], recent efforts are motivated by providing in vitro models that faithfully mimic
dynamic microenvironments, so-called organ-on-a-chip systems [7].
Despite these significant technological advances, the drug screening sector maintains multi-well plates
as the standard platform because of their simplicity. Static culture plates have been continuously
developed and optimized for high throughput screening since the birth of multi-well plates in 1950’s.
However, because these platforms poorly represent the in vivo environment, they likely hinder
discovery of lead compounds, reduce the rate of drugs developed, and consequently increase
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development costs. Microfluidic platforms have the potential to better mimic the in vivo environment,
but at least in terms of platforms for dynamic cell culture, have not yet achieved the throughput
required by the drug screening sector.
1.1 Objectives
The overall objective of this thesis was to develop a microfluidic system that addresses the limited
capability of static well plates to mimic in vivo-like vascular microenvironments while maintaining high
throughput capability and compatibility with screening infrastructure. My specific goals were to:
1. Design and prototype a cell culture system capable of mimicking essential vascular micro-
environments (biochemical, mechanical, and extracellular matrix (ECM) cues, and cell-cell
interactions) while allowing high throughput (parallel) experimentation
Determine the driving requirements for the new platform and produce an initial conceptual
design for the system
Fabricate and characterize an initial prototype that meets the design requirements
Develop and optimize the system to be comparable in terms of throughput to a standard 96-
well cell culture well plate
2. Demonstrate the effect of mimicking the vascular microenvironment on the outcomes of a standard
cellular assay
Compare monocyte adhesion to endothelium treated with tumour necrosis factor (TNF)-α using
the new platform with that obtained using a standard protocol in static well-plates.
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2: Literature review
In order to design a new product, I must first identify the drawbacks of the existing competing systems,
the most recent advances in drug screening technology, and how microfluidic platforms can be utilized
in order to enhance the efficiency of drug discovery. In this chapter, I discuss the capabilities of existing
microfluidic devices used in vascular studies, their throughput and the critical considerations that are
necessary for appropriating lab-on-a-chip technology in the drug screening sector.
2.1 The drug screening process
Drug discovery is a very costly and time consuming process. The estimated cost for a new drug to be
developed, tested and released to the market ranges from about $800 million to $1 billion [8]. However,
the true bottle neck is the average time spent for this process, which is approximately 10-15 years. In
fact, in a pool of 1000-2000 experimental drugs, only a single candidate moves on to clinical trials [8, 9].
To understand why so few novel drugs prove to be effective we need to explore the drug discovery field
in greater detail.
The first step in drug discovery is to identify a target for the disease in question. Drug targets can be
proteins, receptors, lipid channels, DNA, cytokines, hormones or one of many other biochemical entities
[10]. Once an effective target is identified, it needs to be experimentally validated both in living cell
cultures (in vitro) and in animal models (in vivo). After validation, the drug target is then exposed to a
library of thousands of compounds (drug candidates) in a high throughput screening (HTS) mode in
hopes of identifying a few compounds that act on the selected target and elicit the desired response.
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2.1.1 High throughput screening of drug candidates: fast, yet inefficient
HTS is an essential aspect in the drug discovery cascade. Since the 1980s, improvements in screening
technologies have resulted in throughputs that have increased from 10,000 assays per year to current
levels of as high as 100,000 assays per day [11]. Over this time, the substantial increase in assay
throughput was made possible by better screening technologies that were able to perform drug
screening using lower compound sample volumes , which lead to the evolution of multi-well plates of
384 and 1,536 wells that require nanoliters of sample for an entire assay. The whole HTS process is
facilitated by automated infrastructure such as liquid handling systems and well plate readers, saving
time and manpower [12].
Although HTS technology advancement has been driven by the need to screen more compounds in a
shorter time, the need for overall efficiency improvement has been left unsatisfied. A large scale
screening of up to 1 million compounds, which may take up to several months to complete, would on
average generate 1,000 hits (positive results). However, due to the disconnect between cell behaviour in
traditional static well plates vs. in vivo, only about five of these 1,000 hits become lead compound series
that move on to clinical trials [13]. This is not surprising because conventional well plates are not able to
accurately model complex micro-environments, which may influence how a compound interacts with a
drug target. Not only do these inaccuracies reduce the number of drug hits that become lead
compounds, but they may also miss compounds that could have proven to be effective “hits” in clinical
studies, but were missed during the HTS step. To eliminate these inaccuracies and increase drug
screening efficiency, current HTS systems must incorporate the complex vascular micro-environments.
2.2 Essential vascular micro-environments
The transport and effects of drugs from the blood into the underlying tissue are largely mediated by the
endothelium, a confluent monolayer of endothelial cells (ECs) that coats the luminal surface of blood
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vessels [14]. Because of their critical role, they are often the focus of cardiovascular drug screens, and
as such, are the focus of this review and thesis.
ECs reside in a complex vascular microenvironment, involving multiple cell types and their regulation by
biochemical and biophysical stimuli, including binding to the ECM, cell-cell contacts, and shear stress
(Figure 1). Moreover, it is important to keep in mind that pH, temperature, and oxygen tension rarely
vary in vivo, but can be potent stimuli if not controlled in vitro, and therefore must be considered as part
of the cellular microenvironment.
Figure 1 – Schematic overview of a blood vessel and the endothelial cell microenvironment. The ECs reside on the inner layer of the vascular wall receiving external cues from: the underlying ECM which also serves as an anchor to stabilize the ECs, local cells (monocytes and SMCs) and shear stress. Due to the complexity of the system, mimicking all the necessary components of this environment in vitro platform can prove to be challenging [15].
2.2.1 Extracellular matrix regulates endothelial cell behavior and is necessary for cell survival
Endothelial cells are supported by a underlying ECM that provides structural and organizational stability.
The ECM provides essential assistance in local cellular signaling events that regulate EC migration,
proliferation, and above all survival [16]. Furthermore, the ECM serves as a physical substrate for ECs
and therefore plays key roles in mechanotransduction. The majority of the ECM supporting the ECs is
produced by ECs during angiogenesis [16]. The cells mainly lay down laminin, type IV collagen and
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heparin sulfate (HS) proteoglycans which, together, make up the basic structure of the EC basement
membrane. The ECs adhere to the matrix via integrins, which provide the cells with a ‘vision’ of the
external world through mechano-transduction signaling pathways. The composition of the ECM is very
important as it contributes to the effective stiffness of the local environment to which the ECs can
respond by restructuring their cytoskeleton and modulating their own stiffness [17]. The substrate
stiffness can also regulate EC spread area [18] producing isotropic spreading on stiffer surfaces or even
elongated cell shape on softer substrates [19]. The ECM composition is even capable of dictating the ECs
response to shear stress through the integrin mechanotransduction mechanisms [20].
2.2.2 Cell-cell signaling: sticking together
The ECM is not the only player in regulating EC behavior through mechanical stimuli. Neighboring ECs
can interact with one another though cell-cell junctions. This is either performed “directly, by engaging
signaling proteins or growth-factor receptors, or indirectly, by tethering and retaining transcription
factors at the cell membrane, thereby limiting their nuclear translocation” [21] ([22, 23]). In addition,
the cells can also produce cytokines that stimulate themselves or nearby cells through autocrine or
paracrine signaling, respectively. EC to EC signaling also differs depending on the endothelium maturity.
For example, sub-confluent ECs cultured in vitro behave similarly to sparse/sub-confluent monolayers
found in vivo during angiogenesis or even other cell types such as fibroblasts or other mesenchymal cells
[21]. They are very mobile and sensitive to growth-factor activation. After reaching confluence, the ECs
mature and are much less sensitive to various angiogenic growth factors, their junctions become
organized and the cells switch to a resting stable condition [24]. Once the junctions are established,
junctional proteins continuously transfer factors that stabilize the endothelium monolayer [25].
Smooth muscle cells (SMCs) and pericyte cells lie beneath the endothelial layer. Much like the
neighboring ECs, these cells are able to signal the endothelium and can receive external cues from the
7
ECs. For example, SMCs modulate the constriction/dilation of the blood vessels, which is regulated by
the amount of nitric oxide (NO) that is supplied to the inner SMC layer by the endothelial cells, thus
controlling the blood flow rate and resulting shear stress. In the heart valves, valve interstitial cells (VICs)
reside in the ECM beneath the endothelial monolayer. These cells, like SMCs, are sensitive to external
cues from the surrounding environment and can, in turn, send signals to the ECs residing on the surface
of the valves.
The ECs also interact with circulating cells carried by the blood plasma. Cells, such as those in the
leukocyte family, are involved in immune response cascades, including the response after clinical drug
stimulation. Monocytes (a type of leukocyte) are involved in acute innate immune responses, and are
seen to firmly adhere to ECs during early stages of inflammation. This process is potentiated by
circulating growth factors and cytokines or injected drug compounds that illicit an inflammatory
response, causing the ECs to express series of surface adhesion molecules (vascular and intracellular cell
adhesion molecules) to allow the passing monocytes to adhere to the ECs and enter the sub-endothelial
tissue.
2.2.3 Blood flow and resultant mechanical forces: the shear stress of it all
Blood plasma carries most of the nutrients and cells along with many hormones, growth factors, and any
drugs injected into the system. Although every passing hormone or signaling factor has an impact on the
endothelium’s behavior, most of them have been studied in great detail using static well culture
systems. However, the vasculature system is far from static, an ECs are subjected to a range of
mechanical forces generated by blood flow. Mechanical forces that are present in the vascular
microenvironment can be categorized as follows: (1) shear due to viscous forces in laminar flow; (2)
compression from blood pressure; (3) tension resulting from pressure forces; and (4) tension due to
shear forces applied to neighboring cells (thereby resulting in tension forces in cell-cell junctions). ECs
8
are not only able to recognize and withstand these forces, but they require these dynamic fluid stresses
in order to maximize their survival. [26].
Of the forces experienced by ECs, shear stresses are thought to be the most potent in regulating EC
function and best correlate with EC dysfunction in disease [27]. Shear stresses experienced by the
endothelium show high degrees of variability. Not does shear stress vary spatially (direction and
location), but it also oscillates due to systolic pulses. Typically, the average shear stress on an individual
cell can vary from 5 to 15 dyne/cm2 depending on the cell's location (capillary, artery), with flow reversal
(local oscillatory flow) in branched regions [28, 29]. Shear stress is essential to the development of the
vasculature and can be protective against atherosclerosis. Physiological shear stress has been repeatedly
shown to mature novel endothelial cells ensuring a stable (non-leaky) endothelium by inhibiting EC
sensitivity to angiogenic growth factors and inducing endothelial alignment in the direction of the blood
flow [30]. More significantly, shear stress can induce ECs to generate atheroprotective factors that
inhibit coagulation and leukocyte adhesion and migration [31]. Certain regions of the vascular network
such as flow branches, bifurcations or arterial narrowing have lower mean induced shear due to the
geometry. Therefore it is not surprising that these regions are more susceptible to atherosclerotic lesion
formation. Vascular cell adhesion molecule 1 (VCAM-1), an important binding molecule involved in
monocyte adhesion and recruitment, has been shown to be over-expressed in ECs residing in
atherosclerotic lesions (very low to no shear) [32].
2.3 Cell culture systems to mimic vasculature
Traditional static culture plates have found widespread use due to their simplicity and low cost, and
pharmaceutical companies have incorporated static multi-well plates into the drug screening process to
increase compound screening rates. In response to increased awareness of the roles played by the cell’s
microenvironment in determining cell fate and disease progression, present efforts aim to develop
9
culture protocols that recapitulate key aspects of the in vivo environment while maintaining high
experimental throughput. The lab-on-a-chip era has brought devices which not only allow bio-chemical
cell stimulation, but also mechanical stimulation. The ‘lung-on-a-chip’ platform [33] is an elegant
example of a recently developed system that delivers multiple stimuli to organ constructs in appropriate
micro-environments. Microfluidics has been well integrated into lab-on-a-chip devices due to its many
advantages (low reagent volumes, high versatility). Microfluidic technologies have also become popular
for use in bio-chemical assays and vascular screening devices due to its capability of generating
controllable shear stress and cell compatible environments. By appropriating current microfluidic
technologies to the drug screening process in order to mimic vascular micro-environments, problems
such as low hit rates and lead compound identification may be reduced and hopefully eventually
eliminated.
2.3.1 Shear flow systems versus static culture: quality over quantity?
Since the first use of flow chambers to study the effects of shear on ECs in 1987 [34], long after multi-
well plates became the standard in drug screening and cell culture, there has been a flood of
improvements to the systems used for vascular cell culture. These flow chamber systems introduced
shear flow to in vitro experimentation, which was previously not possible. Since then, numerous studies
have shown that shear stress is an essential component in the vasculature capable of that affecting key
cellular functions (proliferation, apoptosis, migration, permeability, remodeling and etc., reviewed in
[27]). In order to use precious primary cells and fewer reagents, microfluidic devices became the next
iteration of shear flow technology. Microfluidic approaches are popular due to ease and low cost of
fabrication (which typically involves casting with PDMS, which is optically transparent and therefore
compatible with microscopy). Most microfluidic chips allow for staining and imaging cells in an
assembled and fully functional device. This is critical in devices which are designed to track cells under
constant flow in real time [35]. Moreover, constant perfusion in these devices allows the cells to be
10
supplied with a constant stream of fresh media and removal of generated cell waste. The size of
microfluidic channels makes them suitable for high throughput studies, thereby allowing multiple
parameters to be tested in a single assay much like standard static multi-well plates. Efforts to integrate
microfluidic channels into microarrays [36, 37] and multi-well plates [38, 39] have already made an
appearance. To go a step further, some microfluidic devices integrate multiple steps, such as cell
culturing, lysis, and analysis in one device [40]. Although the throughput of this technology is typically
lower than multi-well plates used in ultra high throughput drug screening, numerous microfluidic
devices are now able to perform these biochemical assays in parallel, increasing their popularity in cell
culture [40].
2.3.2 The many benefits of culturing vascular cells in platforms capable of inducing
physiological shear stresses
Due to the inherent and obvious similarities between microfluidic devices (or flow chambers) and blood
vessels, many systems are created to simulate shear stress across a monolayer of endothelial cells (and
in some cases smooth muscle cells [41]). As shear stress is directly proportional to the flow rate and
inversely proportional to channel dimensions, low and steady flowrates are sufficient to stimulate ECs
for a visible response (such as cell alignment and factor secretion). In fact, flowrates as low as 200 μL per
hour are sufficient to generate physiological shear stress in order to elongate and align the endothelium
in the direction of the flow [42], and higher flow rates are used to study the effects of abnormally high
shear stress on ECs [43]. Although simulating continuous shear stress is an improvement to static cell
culture, the shear stress observed in the vasculature is dynamic, oscillatory and varies spatially. To study
this phenomenon in greater detail, some groups have developed systems that incorporate cardiac
waveforms into their shear induced assays (something that would be impossible to test under static only
conditions). Estrada et al. [44] found that disturbed flow, similar to bifurcation and atherosclerosis
susceptible regions, is unable to effectively align the ECs in the direction of the flow. Moreover, it was
11
shown that ECs under disturbed flow express higher level of β-Catenin (a molecule shown to play a
significant role in Wnt signaling pathway and enhancement of monocyte adhesion to ECs) than the ECs
cultured under normal physiological flow [45].
2.3.2.1 Gradient generation and migration assays
Biochemical gradients serve a vital role in many cellular functions such as migration, angiogenesis, and
tumorgenesis, making them worthwhile to include in assays. Multiple parallel fluid flows that are
introduced in a single microfluidic channel permit the study of diffusion-based reagent exchange and
biochemical gradients. If one stream contains active compounds or a drug, a stable gradient can be
achieved across the two (or more) streams. Numerous studies (described below) have shown how this
phenomenon can be used in experiments involving vascular cells, most of which focus on cell migration
in response to biochemical gradients.
A simple study involving the generation of vascular endothelial growth factor (VEGF) concentration
gradients across the endothelium showed a preferential migration of ECs towards a higher
concentration of the growth factor [46]. The device had three parallel streams, with the middle stream
containing VEGF, which resulted in an increasing concentration gradient from either side towards the
middle (Figure 2-A). Furthermore, the steepness of this gradient was modulated by adjusting the flow
rates of the two side streams with respect to the middle stream (low flow rate allowed compounds to
diffuse more slowly, producing a shallow gradient). By varying the shape of the gradient, EC migration
rate was shown to depend on the gradient’s magnitude; these results would be impossible to obtain
using static cell culture protocols.
Cells also respond to mechanical cues such as tension and stiffness gradients in their environments.
Zhang et al [47] fabricated a device that allowed them to seed a density gradient of fibronectin on a
single channel floor using a microfluidic gradient generator (described in greater detail in section 2.5.1) .
12
Seeding human umbilical vascular endothelial cells (HUVECs) on a gradient did not allow for an even
distribution; the number of adherent cells increased with the density of cell adhesion ligands. Although
a migration study was not performed, there is evidence that endothelial cells respond to and migrate in
the presence of surface bound proteins such as fibronectin [48]. Similarly, Zaari et al. [49] designed a
microfluidic device that generated a gradient of crosslinker molecules across a solution of acrylamide.
The device (with the solution gradient) was then exposed to UV light in order to create a polyacrylamide
gel with a stiffness gradient. By seeding SMCs onto the gels, they observed cell migration towards the
stiffer surface.
Figure 2 – Cell culture systems mimicking specific components of the vasculature. A) By injecting a compound in the middle channel, it is possible to create a stable concentration gradient across the channe cross section allowing studies such as cell migration to be performed [46]. B) A schematic of a platform capable of co-culture of ECs and SMCs. The two cell types have direct contact allowing cell-cell communication. This device also produces regions of disturbed and continues shear stresses which are essential environments of the vasculature [50].
A
B
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2.3.2.2 Cell-cell interactions
Co-culture systems such as those involving ECs, medial cells such as SMCs or valve interstitial cells (VIC),
and circulating cells such as leukocytes or platelets, are becoming popular, and in some cases, essential
in understanding cell communication and how it affects pathogenesis or drug response in the
cardiovascular system. Unlike prior systems that focused on achieving stability/homeostasis of both cell
types in a single static chamber, many devices today are not only able to sustain multiple cell types for
co-culture studies, but are also equipped with a shear flow feature to help study vascular cell-cell
communication in a dynamic environment (Figure 2-B). Most systems designed for non-circulating cell-
cell interaction achieve this by using a membrane to separate two (or more) cell types in a single
chamber or channel, growing cells together side by side, or in some cases growing a cell type directly on
top of the other. Co-culture systems, along with mechanical stimulation, permit further enhancements
to simulated in vivo environments to better understand how the presence of a new factor or compound
(such as a drug) can affect cellular responses. For example, by allowing SMCs to signal ECs under shear
flow, it was shown that ECs have an increased rate of proliferation and migration [51, 52], while shear
alone inhibits this function. In addition, co-cultured SMCs are able to inhibit intracellular cell adhesion
molecule (ICAM) expression in sheared ECs [53], which may imply a lower affinity for monocyte
recruitment. Even more recently, Hergenreider et al. [50, 54] showed that sheared ECs can secrete
extracellular vesicles containing microRNAs, which then control target gene expression in co-cultured
SMCs inhibiting atherosclerotic lesion formation; a phenomenon which would have gone unseen in the
absence of shear flow or either cell type.
A common method for creating a co-culture with shear flow system involves the use of semi-permeable
membranes inside parallel plate flow chambers. ECs and SMCs can be grown on opposite sides of a
membrane that is inserted into a flow chamber creating two compartments, one of which is exposed to
continuous perfusion to create shear stress on ECs [55-58]. This model permits direct contact between
14
the two cell types which then can be used to understand how SMCs affect EC behavior. Alternatively,
SMCs are grown directly on the bottom of the flow chamber and SMC-EC communication is limited to
soluble factor signaling; the space between SMCs and the membrane is then replaced by a collagen gel
in order to study the effects of sheared ECs on SMC migration through the gel [59]. Membrane-based
co-cultures are readily integrated with microfluidic platforms. Srigunapalan et al. [60] fabricated a
microfluidic platform with two channel layers separated by semi-permeable membrane to study
monocyte adhesion and transmigration though the endothelial layer. ECs were injected into the top
channel and were cultured on the membrane. Monocyte chemoattractant protein (MCP)-1 was injected
into the lower channel, and the ECs were sheared with media containing monocytes. This setup permits
the study of complex cell-cell interactions such as monocyte diapedisis (from top channel to lower
channel) using standard optical microscopy and fluorescence-based imaging.
Other co-culture strategies include the use of patterned adhesive proteins to direct cell-type-specific
adhesion [61] or by spatial confinement of cells in temporary wells until they adhere to the substrate,
after which the substrate is removed from the device and placed in a shear flow system [52, 62]. A more
elegant technique to pattern cells in a microfluidic device utilizes parallel streams (discussed above)
which can be employed to selectively pattern cells on a single side of a microfluidic channel. By
combining cell types together (in two separate streams), they can be cultured in direct contact with each
other without having to disassemble the device for further experimentation [63]. This method can be
used to grow ECs and SMCs in one device.
To further simulate cell behavior and interactions in ex vivo systems, several groups designed complex
setups to study cell-cell signaling phenomena. Kladakis et al. [64] and Ziegler et al. [65] fabricated a co-
culture shear flow system by embedding human aortic SMCs in collagen gel, then seeded human
coronary artery ECs on the gel’s surface creating a simulated blood vessel wall structure in vitro. The
15
engineered vessel wall was then embedded into a parallel flow chamber to induce shear stimulation on
ECs. The same system can be applied to mimic endothelial cell interactions with interstitial cells (instead
of SMCs) within the aortic valvular micro-environment [66]. A completely new class of ex-vivo systems,
which delivers a tubular ‘lumen’ like micro-environment in addition to co-culture and perfusion
functionality has been made available commercially (Cellmax Quad Artificial Capillary Cell Culture
System). The system is equipped with several Pronectin-F (a synthetic protein polymer that incorporates
multiple copies of the RGD cell attachment ligand of human fibronectin) coated polypropylene tubular
membranes that permits ECs and SMCs to be grown on either side [67, 68]. There are clear advantages
to this system, such as a continuous endothelial wall with consistent shear stress throughout the lumen
which is not available in standard flow chambers or microfluidic systems. One shortcoming of this
system involves challenges during post-experimental analyses of cells grown on curved tubes. To go one
step further, a lab-on-a-chip device, termed artery-on-a-chip, was developed by Gunther et al. [69] to
allow on-chip fixation of live artery segments. The authors successfully fixated intact mouse mesenteric
artery segments in a microfluidic channel and tuned the surrounding environment (shear, biochemical
signaling) to achieve virtually identical physiological responses. Although these systems closely mimic
physiological microenvironments, they are often costly and require sophisticated fabrication techniques
and experimental setups . Nevertheless, the inherent nature of microfluidic devices would help provide
great opportunities to further understand communication between cell types and eventually provide a
reliable environment for screening drug compounds for clinical research.
2.4 Can microfluidics be utilized in drug screening sector?
The capability of the microfluidic technology to mimic the in vivo environment allows for a convenient
platform that should be utilized in the drug screening context. Microfluidic devices have demonstrated
utility for drug screening steps such as target validation [70, 71], lead compound identification [72, 73],
16
and examination of drug delivery mechanisms [74, 75] and compound toxicity [5, 76]. Based on these
early successes, the outcome of drug screening assays that are performed using static cell culture
conditions clearly need to be compared with those performed in microfluidic platforms where fluid flow
and associated mechanical stresses are present. It is worth examining how microfluidic cell-culture
platforms are able to sway the outcome of drug screening assays (compared to static cell culture) and
what is needed to increase the experimental throughput in order to utilize microfluidic technology for
high content drug compound screening.
2.4.1 Commercial drugs screened in microfluidic platforms: putting the drugs to the test
Common static well plates used in today’s high throughput drug screening labs may cause false positives
when testing the effectiveness of a compound in question. At times, when a compound results in a
positive effect in a static well plate, the effectiveness of this drug is hindered (sometimes negated) in
vivo. As discussed before, this may be due to the lack of necessary microenvironments in a common
static well plate. A large number of studies (described below) have demonstrated the differences in the
behavior of numerous compounds when tested in a shear flow condition versus a static environment;
some have highlighted the effectiveness of commercial lead compounds in common drug libraries in
microfluidic systems. An elegant example of such a system is a microfluidic platform, fabricated by Sung
and ShulerIn, which was designed as a 3D hydrogel cell culture platform to study the cytotoxicity of an
anticancer drug [77]. On a single device, colon cancer cells, a hepatomatic cell line (mimicking the liver)
and a myeloblast cell line (mimicking marrow) were cultured in separated chambers, and connected via
microchannels. Comparison of experimental results using either a static 96 well plate or a microfluidic
platform demonstrated that the microfluidic platform reproduced the metabolism of Tegafur, a prodrug
(i.e., a substance that is administered in an inactive form requiring typically activation though a
metabolic processes), in the liver and consequently resulted in the death of colon cancer cells, while the
cultures in a 96-well microtiter plate did not.
17
The effects of statins, a class of drugs mainly used to lower cholesterol levels, have also been extensively
tested in microfluidic devices that mimic in vivo microenvironments and compared to static culture. The
behavior of these drugs is beneficial when tested in static vitro environments, but when combined with
in vivo like shear flow environments the drug effects can become impaired. Rossi et al. [78] investigated
the response of human abdominal aortic endothelial cells to simvastatin when conditioned with steady,
pulsatile, or oscillating shear stress in 2 mm tubular channels. Simvastatin, steady flow, and non-
reversing pulsatile flow each separately upregulated several factors expressed by the endothelium
(Kruppel-like factor 2 (KLF2), endothelial nitric oxide synthase (eNOS), and thrombomodulin (TM)).
Although the combination of statin and unidirectional steady or pulsatile flow produced an overall
additive increase in mRNA levels of KLF2, eNOS and TM, oscillating flow impaired KLF2 and TM, but not
eNOS expression by simvastatin. Because oscillating shear stress renders the endothelial cells less
responsive to simvastatin, the results suggest that the pleiotropic effects of statins in vivo may be less
effective in endothelial cells exposed to atheroprone hemodynamics. Furthermore, a similar study
concluded that laminar shear stress prevents simvastatin-induced adhesion molecule expression (ICAM-
1 and VCAM-1) in cytokine activated endothelial cells [79]. By activating ECs with tumor necrosis factor
alpha (TNFα) and simvastatin the authors were able to upregulate ICAM-1 and VCAM-1 expression in
ECs under static conditions. After applying shear stress to the activated cells, the previous upregulation
of adhesion molecules was eliminated. The results therefore conclude that an induction of cell adhesion
molecules by statins may not occur in endothelial cells exposed to shear stress from blood flow.
2.5 Utilizing microfluidic platforms for HTS
Although the studies discussed above provided valuable information on the efficacy and toxicity of drugs
in increasingly realistic environments and at an early stage of drug testing, there is still a major gap
between the experimental throughputs of current microfluidic platforms and ultra-high throughput
18
assays used in pharmaceutical drug screening. Successful realization of microfluidic cell culture
platforms for drug screening depends heavily on the throughput capability of these systems.
2.5.1 Critical issues in HTS
To increase the use of microfluidic platforms for HTS applications, on-chip assay parallelization must be
achieved without sacrificing biomimicry. Furthermore, low cost scalable fabrication methods are
required.
Numerous challenges must be addressed when designing HTS microfluidic platforms capable of
reproducing key components of the vasculature, some of which are summarized below.
The first and essential component of any microfluidic platform is the pumping mechanism. Commercially
available pumps, which require complex networks of tubing, have limitations for high throughput drug
screening tasks. Alternatively, microfluidic platforms achieve fluid flow using a variety of pumping
methods that are more readily integrated into high-throughput parallelization platforms. These include
membrane-based valve pneumatics [80-82], gravity [83], or surface tension [84] driven micropumps.
HTS experimental setups that test multiple compounds in an array of shear stress chambers can either
use a simultaneously driven array of micro-pumps [82] to produce pulsatile flow for every separate
condition, which may introduce flowrate variations across the chambers), or a multiplexer to serially
address each channel individually [85, 86], thereby increasing screening time. To circumvent these
problems, liquid division mechanisms (Figure 3) test discrete steps in compound concentrations in
parallel while utilizing a single pumping mechanism; however, this method is limited to testing
concentration-dependent effects of a single compound and is inefficient for testing vast drug libraries.
Other naturally driven pumping mechanisms such as the use of gravity can be easily miniaturized and
integrated in high throughput platforms. By utilizing a standard 96 well plate, each well can be filled to
generate hydrostatic pressure to drive flow through a nearby microfluidic channel [87]. The drawbacks
19
to gravity-driven flow are the lack of accurate or dynamic flow rate control and the inability to achieve
re-circulatory flow required for long-term shear studies.
Figure 3 – High throughput microfluidic platforms. A) a microfluidic device used for studying concentration gradients in a network of branching serpentines, an on chip function which allows high throughput with very little complexity [88]. B and C) The BioFlux 200 System for live-cell assays under controlled shear flow. The system utilizes a well plate format, which is not yet compatable with existing automated well plate handling equipment, however it is a step in the right direction [38].
Due to the high cost of drug libraries used in traditional screening assays, it is crucial to minimize
volumes used in high content screening assays. This is achieved by platform miniaturization. Typically, a
microchannel used in vasculature studies contains several micro-liters of fluid whereas reagent volumes
used in high content drug screening can be as low as nanoliters (especially in 1536 well plates).
A B
C
20
Furthermore, simulating blood flow shear stress requires a continuous supply of reagents and media
which may accrue to as much as microliters of fluids per channel. It is possible to miniaturize microfludic
channels in order achieve physiological shear stress at very low flowrates but reduction of channel
dimensions is strictly limited by the size of cells that are contained within the device and/or in the
perfused media. Moreover, long term shear induced studies consume large volumes of reagents,
rendering microfludic devices impractical. Flow loops that permit continuous re-circulatory flow have
not yet been implemented in microfludic high throughput technology.
Automation is a key component in any HTS technology. Today’s drug screening infrastructure consists of
large laboratories with robotic liquid handling systems to continuously test numerous reagents in
standard well plates. Microfluidic platforms that are designed for high content screening must also be
automated. Several ‘high throughput’ microfluidic platforms have been designed with automation in
mind [89, 90]. However these autonomous platforms require proprietary control systems for successful
operation which in turn means expensive acquisition of novel automation infrastructure. HTS devices
that are compatible with existing robotic handlers (e.g., tubeless, surface tension driven high density
microfluidic platform developed by Meyvantsson et al. [91]) may become more popular in the drug
screening research centers. Similarly, automated post experimental imaging is conventionally performed
by well plate readers or high content imaging systems; well plate format microfluidic platforms can take
advantage of this infrastructure to fully automate drug screening and potentially replace static well
plates.
2.6 Conclusions
Much of the work completed so far clearly illustrates the potential for microfludic platforms to facilitate
and even improve current vascular research. More importantly, this technology has the potential to
increase the efficiency of drug research by screening compounds in environments that closely resemble
21
the living vasculature. It is important to understand that these lab-on-a-chip platforms open up novel
areas of research that are currently not possible with conventional setups.
Standardized fabrication methods and scale-up of proven on-chip assays are expected to reduce costs
and ease the integration of these devices within existing HTS platforms and infrastructure.
Furthermore, this technology is no longer in its infancy and is becoming more developed in terms of
throughput and commercial availability. Continuing forward, automation, standardization and increasing
scale will only further and mature these microfludic systems to compliment (and maybe eventually
replace) the current standard static cell culture platforms which in turn may allow pharmaceutical
companies to produce therapeutic products at a higher rate for a lower cost.
22
3: Device concept and design
3.1 Requirements
As described before, the vascular network provides multiple biochemical and mechanical cues to the
residing cells. Mimicking these cues in in vitro has become much easier and efficient with the
introduction of flow chambers and microfludic platforms in which cells can be cultured in channels and
then sheared to mimic vascular micro-environments. However, unlike flow chamber setups, microfludic
systems have become popular in high throughput experimentation due to their smaller profiles which
allows several channels to be placed on a single chip to be operated in parallel. , The drawback is the
operation of microfludic devices, especially ones made for parallel experimentation, require complex
off-chip setups including vast networks of tubing and pumping accessories. The biggest challenge in
successfully integrating the proposed device in high throughput drug screening is the same challenge
any high throughput platforms faces: repeatability. Current ultra-high throughput static well plates,
although unable to mimic vascular environments, are simple and therefore possess very high tolerances
for repeatability. With the addition of several conditions, such as: shear flow and shear stress, we have
to worry about providing near identical flowrates, channel dimensions and cell culture conditions across
all conditions.
Aside from the fundamental mechanics, the new platform must have a relatively simple setup to be
easily integrated and used in high throughput facilities. Being compatible with existing robotic systems,
the HTS platform would need to follow the existing dimension formats for static well plates. Liquid
handling systems usually work with multiple plates in parallel and require easy access to each stationed
device, therefore this limits the complexity of the setup for HTS platform operation (i.e. no complex
tubing networks connected to off device setups). Due to the size limitations imposed by liquid handlers
23
and well plate readers, the platform would have a limited reservoir for reagents or media, thereby
limiting the duration of experiments and magnitude of shear stress that can be achieved under flow
conditions. Post experimental processing or imaging will preferably be automated using a well plate
reader. This poses further size limitations on the device, or at least that the platform will require to be
easily modified after an experiment to be compatible with conventional plate readers.
A summary of the primary requirements:
Mimic key vascular micro-environments The device should be more efficient in vascular drug screening by offering a more in vivo like environment
Induce and control flow rates in a range of 0 to 5 dynes/cm2 Physiological vasculature shear stress varies from 0 to ~20 dynes/cm2.but lower shear stress are relevant for many vascular pathologies, as they occur in low shear stress regions, as does adhesion and transmigration of circulating cells and pathogens [92]. Therefore, designing a platform capable of inducing high shear stresses (20 dynes/cm2) is unnecessary and the specified range (0 to 5 dynes/cm2) is more relevant for drug screening
Produce uninterrupted shear stress conditions for a minimum of 3 hours 3 hours of uninterrupted flow is sufficient to encompass the majority of short-term continuous shear stress assays (such as monocyte adhesion experiments)
Maintain equal flow-rates and shear stress across all conditions The microfluidic channels must have accurate and precise shear stresses across all conditions to produce reliable results.
Allow high throughput screening (~5000 samples to be tested in 3 weeks) To achieve high throughput screening, the device should perform multiple experiments in parallel, similar to a multi-well plate. Although, traditional HTS facilities achieve experimental throughputs more than 10x the screening capability stated in this requirement,testing 5000 samples in 3 weeks is comparable to the throughput of early HTS technology.
Compatible with liquid handling and micro plate reader systems (autonomous) Must use robotic equipment in order to achieve high throughput ability in the previous requirement
Maintain cell viability during the experimental procedure An average experiment would shear or stimulate cells for 2-3hrs, during which the cells must be kept viable, which requires sufficient heat, gas exchange, etc.
Easy to use (assemble/disassemble) To increase throughput, the device should be easy to use/implement. The pre-experimental setup should be simple and quick (growing cells, device assembly)
24
An additional set of requirements that help increase the ease of use and further the impact are listed
below. These requirements are not necessary for fundamental operation (or early prototypes), but
should be considered in future development:
Fully automated operation, including cell seeding and pre-experimental treatment/conditioning Pre-experimental preparation (cell seeding/treatment) can be automated to further increase throughput capabilities
Allow for long term cell culture and shear conditioning (~48 h) ECs are often conditioned in continuous shear flow to achieve a physiological equilibrium state prior to testing the effects of drugs or reagents
Automated device temperature and media pH level control while mounted on robotic liquid handling system Although the device can be moved off the liquid handling system after reagent delivery, leaving the platform on robot would provide additional benefits such as further ease of use and capability of adding various reagents at different time points.
3.2 Alpha HTS Platform Concept
The above mentioned requirements dictate the general concept of the initial design. To achieve high
throughput ability while maintaining compatibility with robotic equipment designed for multi-well plate
use, the HTS platform should indeed resemble a well plate. Microfludic channels, used to mimic vascular
shear stresses, typically vary from a few microns to a millimeter. A 96 well plate format provides
sufficient area (9 mm x 9 mm per well region) to house a multiple few micron wide channels in a single
well. Higher density well plate formats (384 or 1536 well) can be considered in future development and
optimization stages.
Aside from restricting the general shape and dimensions, the primary requirements do not severely
narrow various options for several key mechanics, includingthe pumping mechanism, cell seeding
procedures and imaging functionality.
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3.2.1 Pumping mechanism
Microfludic platforms employ numerous mechanisms for pumping fluid through the microchannels. The
following table summarizes all available pumping methods and ranks them according various categories:
Accuracy and precision– flow rate control and consistency over time. Complexity – the requirement of off-device hardware and setup. Simplicity is always better. Variability across wells - The less variation in flow-rate across wells, the better. Table 1 – Pumping mechanism options. Each option is ranked on accuracy (higher is better), complexity
(lower is better), and spatial and temporal flowrate variability (lower is better)
Pumping method Accuracy/Precision Complexity Variability Other
considerations
Constant flow pumping of each channel
High – depending on control method
High – vast network of tubing and controllers required for each channel
Low – each channel can be individually controlled
Needs a very complex setup that may not be compatible with automated systems
Pressure driven flow
High – depending on channel dimensions
Low – a single vaccum pressure is needed to generate flow
Depending on channel tolerances and fabrication techniques
The simplest active flowrate control solution, platforms already exist for purchase
Gravity driven flow
Low – flowrate cannot be easily controlled
Low – only requires a media reservoir
High – as reservoir empties, flowrate diminishes
Simple to implement, but low accuracy
Capillary effect Low – flowrate cannot be easily controlled
Low – small media reservoir and waste collectors
High – depends on channel tolerances
Requires very small reagent volumes
Conventional active pumping techniques involve either the use of a constant current generator
(peristaltic pump) or pressure regulation. The platform’s micro-channels maintain their dimensions
throughout the experiment, and therefore flow resistance remains constant. Because of this (flowrate =
pressure drop / channel resistance), deciding between flow or pressure control becomes irrelevant.
However, the options of choosing to either pool the outlets of all 96 channels into a single outlet
simplifying the setup, or running each individual tube to the pump for precise control of each channel
26
still needs to be explored. Microfluidic setups are notorious for their vast and complex tubing networks,
so having a single outlet from the device to a pumping mechanism would greatly decrease the
platform’s complexity. For this solution to be viable, the resistance of every channel (condition) must be
well controlled in order to avoid flow rate variability. Conversely, having 96 separate tubes would hinder
the liquid handler dexterity and accessibility to the device, but allow accurate flow rate control of each
channel.
Other options such as gravity driven flow or capillary force induced flow require no active pumping
mechanisms, and therefore no complicated off device setups. The cost of this, however, is the lack of
active control. Gravity driven flow rates will depend on the pressure head/reservoir volume, which can
be regulated via a liquid handling system if the platform is designed to remain on the handler during an
experiment, but this would essentially turn the handler into a ‘pumping mechanism’ for a single device
making it unavailable to tend to other platforms. Even then, achieving constant flowrate would be a
challenge due to the lag time in liquid dispensing. Similarly, capillary induced flow will require the
robotic equipment to constantly refill each reservoir during the duration of the experiment.
Although passive flow mechanisms are inherently simplistic, they do not allow for accurate or active
flow rate control even with aid from the robotic equipment, making them inadequate for this project..
A peristaltic pump can be used as a re-circulatory flow mechanism, but without the advantage of having
separate 96 conditions (all channels would have to be pooled into a single inlet/outlet) to avoid complex
tubing networks. This approach was used in this thesis to drive re-circulatory flow necessary for long
term shear flow cell conditioning assays (Section 4.5.4).Constant pressure driven flow, on the other
hand, appears to be the most practical choice for short term (separate conditions) flow assays.
Furthermore, pressure assisted flow equipment (such as vacuum manifolds, Figure 4) have been widely
27
appropriated to be compatible with liquid handling systems and existing well plates making it easier to
integrate this pumping mechanism into the new HTS system..
Figure 4 – NucleoVac 96 Manifold system. An existing vacuum manifold typically used for rapid manual parallel purification of nucleic acids. The system provides a chamber that can withstand negative pressure, which drives the flow through a filter well plate [93].
3.2.2 Cell seeding and imaging functionality
In order to emulate the key components of the vascular structure, we must include biochemical and
cellular organisms into the shear flow system. Typically, extracellular matrix (ECM) proteins and ECs are
injected directly into microfludic channels. The ECs arel eft to proliferate and grow to confluence to form
a confluent monolayer. A similar method can be designed to grow cells in 96 separate channels.
However manually injecting cells into each well can be troublesome and slow, and designing/optimizing
a novel method or device for automated cell injection to all wells in parallel would require expensive
and bulky machinery driving up the complexity and the cost of the device. Another method for cell
delivery is to culture cells on a separate module (a substrate with direct access to channel surface) and
then have the module integrated into the device prior to experimentation (similar to glass/membrane
insert in flow chambers, section 2.3.2.2). This would mean the device would require being modular and
28
force the end user to assemble the platform. The following table summarizes and evaluates the two
concepts (modular vs. non modular) according to two categories:
Ease of use (cell accessibility) - How easily and quickly the user would prepare the device for experimental procedure (grow cells) and post experimentation imaging Fabrication complexity – Aside from end user operation, the device should be relatively easy to prototype especially in the early stages of the design Table 2 – Device design concepts: modular vs. non-modular. Each option is ranked on ease of use (higher
is better), fabrication complexity (lower is better)
Design Ease of use Fabrication complexity Other considerations
Modular Medium – would require user assembly and disassembly
Low – each components would be cheap and easy to produce
Components can be interchanged with each other or replaced
Non modular
High – if all components are preassembled prior to use
High – the device would need enclosed channels, very hard to make a single piece
A non-modular design would imply a single piece of hardware, which would make the end use of the
product extremely simple. In this scenario the user would only need to load the device with drugs or
reagents (provided the right cell types are already present in the microchannels) and start the
experiment. Growing cells, on the other hand, in already enclosed channels may be unfavorable. Cells
require constant gas exchange and fresh media to survive; an enclosed channel (located at the center of
the device) would not allow sufficient gas perfusion and constantly feeding cells is a difficult and time
consuming task for the end user (the goal of the device is to make a user friendly and simple to use
platform). The platform would also need clear sections/openings to image cells using a well plate reader.
Fabricating a device with already enclosed channels would be difficult compared to a modular
counterpart.
29
A modular design has clear benefits such as interchangeable parts and easy access to the microchannels.
This device would need to be assembled before running an experiment and possibly disassembled
before imaging. However, part interchangeability would mean the possibility of reusing or replacing
modules, which can reduce fabrication costs as well as increase device functionality range (e.g.,
replacing the microchannel module with different designs to test various shear stress conditions).
Having a modular design would make it easier to achieve compatibility with robotic systems which may
require different platform profiles or dimensions. Removable channel module would also ease the
process of seeding and imaging cells. Despite the slight increase in labor required to assemble the device
(however still less intensive than growing cells in an enclosed system), a modular design would be a
superior concept and would make prototype fabrication much less complicated.
3.3 Initial conceptual design and operation
The initial HTS platform design (Figure 5) consisted of multiple layers (or modules) that can be easily
interchanged for future design changes. The modules stack together and are tightly held together by 4
bolts. Starting from the topmost layer, the device is formulated out of:
30
Figure 5 – Final conceptual desing of the HTS platform. A) an exploded view of all modules in the system. The platforms is comprised of several layers which are stacked on each other and clamped together using 4 bolts. B) Fully assembled device. The platform resembles a deep 96 well plate making it compatable with automated well plate handling equipment such as well plate readers and liquid handlers. C) Cross section view of a single well (channel). The inlets and the outlets are positioned in a way to be invisible to well plate readers when looking down a well.
Deep well block
Gasket
Well block
Gasket
Inlet layer
Channel layer
Base block
Well
Outlet
Channel
Inlet
A
B C
31
Deep well block – A block resembling a deep 96 well plate. This layer acts as the reagent/media
reservoir; holding 2mL of liquid per well, it can supply the microchannels with enough volume to ensure
uninterrupted flow (0.185 µL/s) to produce 5 dynes/cm2 of shear stress on the ECs for the duration of a
3 h experiment (Section 3.5.1)
Shallow well block – Similar shape as the deep well block, however the purpose of this layer is to keep
each well separate (by allowing the layers to remain clamped together) when the deep well block is
removed during post experimental imaging. Many microscopes or well plates have a size restriction
which prevents the device with the deep well block to be placed inside
Inlet layer – The inlet layer functions as both an inlet source to transport the media from the reservoirs
to the channels and as the top wall of the micro channel layer below it
Channel layer – 96 separate microchannels sit under the well blocks. The layer (by itself) contains
cavities which together with the above inlet layer compose complete channels. This layer can be easily
removed from the device to allow adherent cells (e.g., ECs) to be grown and imaged in the open cavities
with relative ease.
Base plate – The bottommost module that acts together with the two well blocks in order to firmly
clamp the device together. The base plate also functions as the outlet source for media waste. The
added posts provide guidance for the user to assist in the device assembly.
3.4 Overview of basic operation
3.4.1 Pre-experimental cell culture
Mimicking the vascular microenvironment in a microfluidic channel requires a confluent layer of ECs on
the channel’s surface. Growing ECs long-term in closed channels is challenging, so an open-face channel
32
layer was used instead. The channel layer was sterilized under ultraviolet (UV) light for 20 minutes, and
then washed in 100% ethanol, then in 70% ethanol followed by a rinse in PBS. The ethanol, aside from
further sterilizing the substrate, also helps wet the channel surface preventing future bubble formation.
Small droplets containing fibronectin were placed on top of each channel cavity to allow the ECM
proteins to adsorb to the channel surfaces. The channel layer was then washed in PBS once again to
remove any unbound proteins. Droplets filled with suspended adherent cells were then placed over
each channel cavity and incubated until the majority of cells were bound to channel surfaces. The
substrate was then rinsed in PBS and placed in a bath of media. The cells were incubated until each
channel had a confluent monolayer.
3.4.2 Generating shear stress
After the cells have achieved confluence, the substrate was placed onto the base plate and covered with
the inlet layer. The well block was placed on top and the device was bolted together. Media/reagents
were deposited in each well and the assembled platform was then placed onto a vacuum manifold.
Vacuum was generated below the device to create a pressure difference across the system. The media
was driven down out of the well block through the inlets and the channels generating shear stress on
the adherent cells. The media then flowed out of the channel layer, through the base plate and pooled
in the vacuum manifold. Drug candidates were either mixed in with media which was used to treat cells
during flow, or were used to treat cells prior to shear flow experiment.
3.4.3 Post experimental data collection
Immediately after the experiment was complete, the device was removed from the manifold and
disassembled. The channel layer was then removed for post processing. Depending on the type of
experiment or drug candidate, there are many ways to collect and analyze experimental data, but
typical drug screening post processing involves (immuno)fluorescent staining of cells in all wells (e.g.,
33
with an antibody to a specific target or calcein AM to determine cell viability), and then placing the well
plate into a plate reader for rapid data collection.
3.5 Microchannel design
In addition to global (system wide) requirements (section 3.1), the microchannel has several sub-
requirements generated from the high level requirements (summarized below). Because the system has
to be compatible with a plate reader, the channel layout must follow standard well plate formats.
Furthermore, conventional plate readers can only read simple outputs such as fluorescent intensity from
each well, therefore each microchannel must produce enough signal to be seen by the reader. The
fundamental obligations, such as low flow rate and low shear stress variability, must be applied across
all channels and within a single channel.
The following is a summary of channel module requirements derived from primary system
requirements:
Channel cross section coefficient (width∙height2) must be below 2.37 x 10-3 mm3 (see appendix A for calculations) Due to the limited media reservoir, most experiments will require low flow rates. Therefore, in order to produce the maximum required continuous shear stress (5 dynes/cm2) over the duration of the experiment (3 hrs, 0.185 µL/s), the channel cross section coefficient should be low.
Channel heights must be above 28.2 μm Endothelial cells that will be grown in each channel (in order to mimic a vascular wall) have a maximum height of 4.1 μm [94]. Furthermore, some drug screening assays require other cell types (e.g., monocytes) to be suspended in the media during flow experiments with average diameter of 10 μm [95]. Therefore to make sure we safely (safety factor of 2x) avoid channel blocking, the channels must be large enough to let the cells pass through.
Channel height:width aspect ratio must be below 1/3 (see appendix A for calculations) High channel height:width aspect ratio generates a large shear stress gradient across the channel’s cross section. To prevent artifacts caused by shear stress variability, the aspect ratio should be kept to a minimum.
Channel base area should be above 8 mm2 (value chosen based on simulation results, section 3.5.1) A small, short channel may not have enough surface area for the fluorescently labeled cells to produce enough output signal for a well plate to detect. More surface area would yield a more intense signal per well resulting in a lower noise to signal ratio.
34
Channels must be in the same spatial pattern as a standard well plate and directly visible by plate readers. Most well plate readers read from the top, forcing the channel layer to be visibly seen from the top. In addition, plate readers read a small area directly below the sensor meaning that each well (part that needs to be read) must be present in the viable area (directly under each well).
Channel height variability must not exceed +/- 1 µm (see appendix A for calculations) To avoid flowrate and shear stress variability across the channels, the dimension tolerances need to be tight
The channel cross section coefficient restriction, along with the height requirement, prevents a short,
wide design to achieve a large base area. Therefore, the channel must have a small cross section, but be
long enough to generate an output signal to still be visible by the plate reader. The only option
remaining is to design a long serpentine channel that would fit into a single visible well area of a 96 well
plate (~38 mm2). In order to decide on a channel’s dimensions that fit the requirements, various designs
were simulated using computational fluid dynamics (CFD) software (COMSOL).
3.5.1 Channel design simulations
To decide which channel dimensions were appropriate, a range of values was tested using 3-
dimensional CFD simulations. Because shear stress is exponentially dependent on channel height,
deciding on this dimension would first would dictate the other dimensions. A range of 50 – 100 µm
channel height provides enough depth to avoid channel obstruction during flow while allowing sufficient
shear stress in low flow rate conditions. To satisfy the channel cross section requirement (maximum
width of 948 µm with channel height of 50 µm), a value of 500 µm was chosen for channel width
(although the 100 μm high channels only permit a maximum of 2.57 dynes/cm2, they can be used to
perform low shear stress assays). Next, designing a channel with a width of 500 µm and height range of
50 – 100 µm would require a minimum length of 16 mm to satisfy the minimum visible area
requirement.
Using the above chosen parameters, a channel outline was created in AutoCAD (Figure 6) and imported
into COMSOL. A CFD analysis was performed using laminar fluid flow module, fluid properties were
35
chosen based on water (room temperature) and the finest mesh setting available (>9 M elements).
Initially, the simulations were to determine the wall shear stress distribution and pressure gradient
across the channel designs. Two channel height parameters (50 and 100 µm) were tested to obtain
shear stress ranges for a given flow rate range (0 to 0.185 µL/s). Further simulations were performed (on
a smaller section of a channel, Figure 7) to determine streamlines, velocity profiles around the channel
bends, and the effects of channel blocking by clumps of cells, should this occur.
Figure 6 – A concept of a single microfludic channel. A) AutoCAD rendering of a channel’s outline. The inlets, outlets and the curved regions of the channels are positioned in a way to be invisible when looking down a well. B) Channel mesh (generated in COMSOL) to be studied in detail using computational fluid dynamics software.
The resulting simulations (Figure 9) showed an even shear stress distribution across 60 % of the
channel’s middle region in 100 um high channels (500 um wide). This region of constant shear stress at
the center of the channel increased in the 50 µm deep channels (to about 75 %) due to the decrease in
the aspect ratio. In addition, shallower channels require half the flowrate in order to produce the same
amount of wall shear stress. However, 50 µm channels require a drastic increase in dimensional
tolerance due to the shear stress exponential dependency on channel height. The pressure drops
required to achieve desirable flowrates (0 – 0.185 μL/s) were in the range of 0 to 193 Pa for 100 µm
deep channels and 0 to 720 Pa for 50 µm deep channels.
A B
36
Figure 7 – Simulated channel pressure and shear stress distributions. Simulation parameters were chosen to mimic: fluid properties of water, maximum allowable flowrates of 0.67 mL/hr and channel dimensions of 500 x 50 μm. A) Majority of the pressure is distributed across the serpentine channel. A pressure difference of 700 Pa is needed to generate maxium allowable flowrate. B) Shear stress distibution was shown to be equal across the length of the channel
Figure 8 – Flow streamlines and shear stress distribution of curved and straight regions of the channel. A) Shear stress was shown to be symmetrical in the straight region of the channel 250 microns before and after each bend. B) Channel clogging was simulated as immovable obstacles across the channel. As the blockage increases, the shear stress around that region exponentially increases which hopefully may aid in dislodging the blockade and stabilizing flow. A block of this severity reduces flow rates and shear stress across the whole channel by 11%
A B
A B
37
Figure 9 – Velocity profile in a straight region of a channel. A) 2D velocity profile in a channel’s cross section. B) Velocity profile distribution at the center of the channel. The profile shows an equal flow distribution for the majority of the channel (60%) suggesting a uniform wall shear stress distribution at the bottom of the channels.
A
B
38
4: Device fabrication, characterization
and optimization
4.1 Initial prototype fabrication
A downscaled 12-well miniature prototype was initially built (Figure 10) in order to characterize the
device mechanics on a small scale. Most components required simple machining steps to fabricate. The
well blocks were fabricated from large poly(methyl methacrylate) (PMMA) blocks by machining an array
of wells according to a standard well plate format. Similarly, the inlet layer only required a repetitive
drilling process. The base plate was machined from aluminum to provide the device with rigidity and
considerable clamping force which is generated by 4 bolts on each corner of the device. The
microchannel layer however required multiple micro-fabrication steps.
Figure 10 – Dissasembled view of the initial prototype. A 12 well minature prototype was fabricated based on the 96 well concept. Every well and channel were made to the same scale as a 96 well plate (same well profile pattern).
Vacuum manifold
Base plate
Well block
Channel module
39
Figure 11 – Assembled view of the initial prototype. The PDMS channels were bonded to the omniwell plate which in turn became the base for microfludic channels.
4.1.1 Channel module fabrication - PDMS
Early stages of the HTS platform employed soft polydimethylsiloxane (PDMS) substrates due to relatively
easy fabrication techniques with PDMS. PDMS substrates are created using soft lithography methods;
first a SU-8 master is made to serve as a mold for the microchannel pattern, which can be then used for
replica molding PDMS substrates.
SU-8 masters are typically fabricated in a clean room environment by several spin-coating and baking
steps (see Appendix B for step by step protocol). First, a seed layer, which acts as an adhesive for
bonding features to glass, was fabricated by spin-coating a positive photoresist SU-8 5 (Microchem;
Newton, MA, USA) at 3000 RPM on 3” x 2” glass wafers. The glass slides (along with the SU-8 seed layer)
were then baked, exposed to UV light, and post-baked to obtain a 7 μm layer. To fabricate the channel
40
features, SU-8-25 or SU-8-50 (Microchem; Newton, MA, USA) was spin-coated at 1000 RPM on top of
the seed layer, baked, exposed to UV light through a photomask (printed at CAD/Art Services, Inc.;
Bandon, OR, USA), and post-baked in a similar fashion to the seed layer fabrication to obtain a thickness
of 50 or 100 μm respectively. The slides were then developed and hard-baked for 3 days in order to
strengthen SU-8 adhesion to the glass wafers. Before using the SU-8 masters for replica molding, a
silanization treatment was performed in order to facilitate the delaminating process when removing
cured PDMS from the SU-8 molds. The masters were treated overnight with the silanization agent
(Tridecafluoro-1,1,2,2-tetra-hydrooctyl)-1-trichlorosilane (United Chemical Technologies; Bristol, PA,
USA), under vacuum conditions.
Using the SU-8 masters, I was able to fabricate multiple negative replicas by a simple casting process.
The masters were initially cleaned using isopropanol and dried using compressed nitrogen gas. Uncured
Sylgard 184 PDMS was well mixed with a heat activated cross-linking agent in a 10:1 ratio and poured
onto the SU-8 mold. The mold was then placed in a desiccator to remove trapped air bubbles and to
force the liquid PDMS to assume the contour of the mold. It was essential to keep both surfaces (top
and bottom) of the channel layer flat and parallel, a second glass slide was placed on top of the liquid
PDMS along with identical spacers (Figure 12) to achieve a flat parallel surface on the other side of the
substrate. The uncured PDMS (along with the mold) was then baked at 80˚C for at least 4 hours to allow
the polymer to fully crosslink.
41
Figure 12 – PDMS channel layer fabrication process. 1) A master and a glass wafer are thoroughly washed using acetone and isopropanol to remove any debris on both surfaces. 2) PDMS + cross linker were poured on both surfaces and then degassed to remove any trapped bubbles between the PDMS and the master. 3) Rubber spacers (of identical height) were placed in the master which was then covered by the glass wafer in order to produce an equal thickness PDMS substrate with flat surfaces. 4) The PDMS was baked for 4 hours and the master along with the glass wafer were carefully delaminated from the cured PDMS.
4.1.2 Channel layer fabrication – Polystyrene
Although the PDMS channels served their purpose, later stage system prototypes demanded that the
channels be fabricated out of a stiffer and easier to handle material. Unlike PDMS, polystyrene (PS)
substrates were able to withstand higher clamping forces (without noticeable deformation) necessary
for device assembly and were easier to handle when moving the channel layer from one platform to
another. Furthermore, polystyrene circumvents a common problem in PDMS microfluidic devices which
is protein absorption [96]; by inhibiting small particles from diffusing into the substrate, polystyrene
prevents any loss in signaling factors/reagents in the micro-channels. Adherent cells also adhere better
to polystyrene than to PDMS [97] which is why most static well plates are fabricated from polystyrene.
For these reasons, the substrate of the channel module was upgraded to polystyrene.
1)
2)
3)
4)
Master Glass wafer
PDMS
Spacers
Cured PDMS
42
The fabrication process for a PS substrate is a three step process (rapid hot embossing technique
developed by Young et al.[98], Figure 13):
1. Fabricating the desired channel pattern using SU-8 soft lithography 2. Casting and hardening a metallic epoxy replica of the channel design 3. Hot embossing polystyrene wafers using metallic epoxy mold
The first step, creating the initial master, involves either using soft lithography technique or CNC
machining. The 12 channel prototype was created using SU-8 micro fabrication technique described in
section 4.1.1. Later, the 96 channel design masters were created in a machine shop using a CNC router.
Similar to the second step in the soft lithography process, uncured Sylgard 184 PDMS was well mixed
with the cross-linking agent in a 10:1 ratio and poured onto the master mold. The mold was then placed
in a desiccator to remove trapped air bubbles and to force the liquid PDMS to assume the contour of the
mold. A glass sheet was placed on top of the PDMS to force the negative mold to remain rigid and flat
during the following steps. The PDMS was placed into 80˚C oven and allowed to crosslink for at least 4
hours. Afterwards, the PDMS, along with the glass wafer, was carefully delaminated from the master
mold. Because both substrates (Master and PDMS + glass) are rigid, ethanol was used to lubricate both
surfaces to ease the delaminating process. The negative PDMS mold was then used for the following
epoxy casting process. Aluminum filled epoxy resin (EC-415 ultra high-temp aluminum filled casting
system, ADTECH plastic systems) was mixed was mixed with epoxy hardener (provided in the epoxy kit)
in a 10:1 weight ratio. The negative PDMS mold was first degassed in a desiccator for 15 minutes to
remove any gasses that permeated into the mold, to prevent bubble formation in the epoxy casting
step. The epoxy/hardener mix was poured into the PDMS mould and desiccated once more. Due to the
viscosity of the epoxy mix, bubbles trapped on the surface of the mold (after desiccating) were manually
removed using a pair of blunt tweezers. After the successful removal of all the trapped bubbles, the
epoxy was left at room temperature for 24 hours and then baked at 60 degrees for 8 hours. The
43
hardened epoxy was then removed out of the PDMS mold (again, due to both surfaces being rigid,
ethanol was used to help the delaminating process). The epoxy mold required intense baking in order to
fully harden. The mold was baked in four iterations: 93 ˚C for 2 hours, 121 ˚C for 2 hours, 149 ˚C for 2
hours and finally at 176 ˚C for 2 hours. The mold was left in the oven to slowly cool down to room
temperature. The hardened epoxy mold has a compressive strength of 110 MPa, making it well suited
for hot embossing.
Figure 13 – Rapid prototyping technique for hot embossed substrates developed by Young, EWK et al. [98]. The method involves fabricating a hardened epoxy mould identical to the SU-8 master. The epoxy mold can then be used for hot embossing polymer substrates.
The final step was to use the hardened aluminum filled epoxy to hot emboss polystyrene channel
substrates. The hot embossing process involved heating a plastic wafer (PS or PMMA initially used as a
substitute for PS) slightly above the glass transition temperature and firmly pressing the mold into the
wafer, embossing the pattern into the plastic substrate. A Jenoptik HEX-02 hot embossing system at the
UHN facility (University of Toronto) was used to emboss microfludic channel designs into polystyrene
and PMMA wafers. The mold and a plastic sheet were initially heated to 120˚C or 150˚C for PS or PMMA
44
respectively, and then clamped together for 5 minutes at a force of 70,000 Newtons. The mold and the
polymer substrate were then cooled to 60˚C while maintaining the clamping force. The mold, along with
the plastic wafer were removed from the machine and then carefully delaminated from each other using
ethanol to lubricate both surfaces. The excess plastic was then trimmed off, leaving only holes to be
drilled or cut in each channel outlet. In the case of PS, the holes were manually drilled using a drill press;
however, PMMA substrates were compatible with the VLS3.50 laser cutting system (Universal Laser
Systems) which was able to automatically cut an array of holes in the substrate using a pattern created
in AutoCAD software.
Figure 14 – Channel moulds used for hot embossing polystyrene. A) Hardened aluminum epoxy mould used to fabricate 12 well channel prorotypes. B) Machined aluminum master used for hot embossing 96 well pattern of microfludic channels.
4.2 Device operation (software, pressure regulation)
The assembled device was placed on the vacuum manifold (GenElute™ 96 Vacuum Manifold) which was
connected to Bellofram type 3110 analog vacuum pressure regulator (Figure 15). The whole system was
controlled by two components: a PC running custom written Labview program, and an Arduino (ATMEL)
board.
A B
45
Figure 15 – Photo of pressure contol system used to generate a vacuum in the manifold. The Arduinio board, which was laid out on a breadboard, sent commands to the pressure regulator which was hooked up to a small solenoid pump. The volume sensor circuit (section 4.3.2) was connected directly to the National Instruments data acquisition board (image not shown) which related flowrate information directly to the PC.
The Arduino microcontroller acted as an interface between the PC and pressure regulator. The PC sent
the desired pressure values to the microcontroller via a serial port; the pressure value was then passed
to a digital to analog converter which provided the pressure regulator with the appropriate voltages (0-
10 V) needed to maintain the desired pressure. A pressure sensor connected to the vacuum manifold
sent a feedback signal to the Arduino, which in turn was passed to the PC in order to allow precise
measurement of the negative pressure in the vacuum manifold.
The PC, running Labview software (Figure 16), was responsible for generating a pressure signal
necessary to drive the flow. The software acted as a control system which received data from the user
Pressure regulator
Arduino controller
Well volume censor circuit
Solenoid Pump
46
and sendt to the Arduino microcontroller. It allowed real-time control of the pressure in the vacuum
manifold and was able to be programmed to regulate the pressure as a function of time (allowed the
user to program custom pressure functions). The software also received data from the pressure sensor
and the well volume sensor (section 4.3.2) and displayed it for the user. Furthermore, the software had
the capability to calibrate the well volume sensor in real-time. Although the PC was used to generate
and send the signal to regulate the pressure, later prototypes (after rigorous characterization) were
controlled via simple controllers with pre-set pressure settings or waveforms in order to avoid the use of
a complicated control system such as a PC.
Figure 16 – Labview control software interface. The program displayed pressure control waveforms as well as volume information in a single well. The software had the capability to record sensor inputs and program pressure functions into the system.
47
4.3 Shear stress and flow-rate measurement
The system’s basic requirements state that the device must produce shear stresses of 0 to 5 dynes/cm2.
Furthermore, the generated shear stresses must be equal across all channels. There are several
techniques available for measuring fluid velocity (and in turn shear stress) directly (such as particle
image velocimetry), however these methods require intricate micro-fabrication protocols and complex
instrumentation setups. Instead, using a simple (yet reliable) mathematical model (equation (5)), I was
able to calculate shear stress as a function of channel dimensions and flowrate.
4.3.1 Channel dimension verification
The SU-8 micro fabrication protocols require precise temperature settings and baking periods in order to
produce accurate, repeatable feature dimensions. Due to the fabrication imperfections (temperature
gradients across hot plates, or timing periods), not every master was made identically; even the smallest
change in channel height can cause a substantial difference in shear stress. Moreover, spin coating (an
essential step in SU-8 fabrication protocol) in conjunction with uneven temperature gradients can
produce spatial height variations of up to 10 %. This variability can mean the difference between 5 and
6.12 dynes/cm2 (22 %) in 50 μm deep channels. Therefore I needed to measure the dimension of every
channel to accurately assess the variability in the shear stresses across the device.
Sacrificial channel layer substrates were fabricated out of PDMS (section 4.1.1) and dissected across
every channel. A thin section was removed from each row and imaged (Figure 17) at high magnification.
Using Image-J software, an image for every channel (well) was imported and measured in order to
quantify the dimensions of every channel.
48
Figure 17 – PDMS channel cross section cutouts used for dimension measurements. The images were analayzed in ImageJ software.
The variability of the channel widths proved to be very repeatable with only 4.6 % variability
(maximum). The height dimensions, however, varied by 6 %. This discrepancy results in 12.6 % deviation
in the generated shear stress. This error was deemed acceptable in early prototypes of the platform,
and was further reduced when the SU-8 channel molds were replaced by their aluminum counterparts
that were milled using automated machinery. The machined masters had channel heights of 35 and 250
µm which were not the same as the SU-8 masters (50 and 100 µm). However, the resulting heights still
satisfied all the necessary requirements, so the final channel substrates (Section 4.5.1) were fabricated
using these dimensions.
4.3.2 Flow rate sensor
Measuring flowrate in microfludic deviceswas not a trivial task. A variety of existing sensors were
available for measuring fluid velocity in small channels. However, much like shear stress sensors, these
flowrate sensors required delicate fabrication techniques. To circumvent this problem, flowrate was
measured using the well reservoir instead of directly measuring fluid velocity in each microchannel.
Quantifying volume was a much simpler task which was implemented using simpler technology.
Flowrate was then calculated from the volumetric change in the well.
472 um
249 um
506 um
35 um
49
To accurately quantify the change in volume, there must be a method to measure the liquid level in real-
time. For this, I was able to track the volumetric change of a single well by designing a sensor which
measured the electrical impedance of the remaining liquid in a well. The sensor comprised of two
conductive poles (wires) placed on opposite ends of a well and a circuit designed to induce alternating
current across the well. By measuring the voltage drop across the well, I was able to relate the data to
well volume and flowrate.
The circuit (Figure 18) which produced a 2 kHz, 10 Vp-p signal across the two poles also measured and
converted the impedance reading to a -5 to +5 volt signal.
Figure 18 – Well volume sensor design. A) Two conductive wires are placed inside the well at opposite ends. B) A circuit that generates an alternating current (2 kHz, 10 Vp-p) through the fluid in the well. The voltage drop across the well can be measured and related to the liquid level inside the well in real-time. AC current was used instead of DC to avoid electrolysis.
A B
C
50
This was done by monitoring the well’s resistance and capacitance (total impedance). The following
equations show the relationship between the well’s impedance coefficients and their relationship to the
water level (L), wire radius (a), well diameter (d), and water electrical properties: resistivity (ρ) and
permittivity (ε)
(1)
Using equation (1), I was able to relate the capacitive and resistive coefficients to impedance values to
produce total electrical impedance for the system:
(2)
(3)
The total system impedance (ZT) given in equation (3) is a function of the well’s capacitance (C),
resistance (R) and the applied angular frequency (ω). However, in order to quantify the impedance, one
must use an additional circuit to relate the measurement to a readable voltage level. To do this, a
resistor (RL) was added to the circuit to produce a voltage divider. The resistor value (15 kΩ) was chosen
to be closest value to the sensor’s impedance (15 kΩ to inf) which was calculated using the following
parameters:
Water resistivity (ρ) = 200 Ω·m Water permittivity (ε) = 7.089 x 10-10 F/m Wire radius (a) = 1 mm Well diameter (d) = 6 mm Water level (L) = 0 – 40 mm Applied angular frequency (ω) = 12566 1/s (2 kHz) By measuring the voltage drop across the well (equation (4)) I was able to record and monitor the total
water/reagent volume in real-time.
51
(4)
The output voltage was then fed to a data acquisition board (National Instruments NI PCI-6251 DAQ
board) and logged using Labview software. The sensor was first calibrated using 50 μL volume
increments (Figure 19) to produce a relationship between the voltage reading and well volume.
Figure 19 – Volume sensor was calibrated by consequtevely adding 50 μL of water to the well. Due to the non-linear relationship between liquid level and voltage, the sensor’s resolution (sensitivity) increases as the well volume decreases.
4.4 Flow-rate characterization
Initial experiments showed a non-linear flow-rate profile when using negative pressure to drive the flow
through the micro-channels (Figure 20). The flow-rate decay was undesirable for many reasons, and
Voltage readout (V)
50 μL step
Time (s)
0 μL
900 μL
52
violated a key design requirement which demanded that the system to produce controllable shear
stresses. Fixing this problem required determining the source of the issue by modeling the dynamic
pressure effects on the system during the experiment.
Figure 20 – Nonlinear well volume decrease in early prototype characterization. The vacuum manifold was left open to produce a constant 0 (atmospheric) pressure in the manifold. The resulting non-linearity was caused by the hydrostatic pressure change in the well reservoir during the course of the experiment.
4.4.1 Undesirable hydrostatic pressure
Liquid reservoirs have an inherent pressure gradients generated by their own weight. Typically, the
pressure buildup at the bottom of a well is directly proportional to the height of a well (equation (7)).
This generates unwanted pressures in systems which possess large liquid reservoirs, and the HTS
platform was no exception. Furthermore, this pressure head (in each well) varied over the course of the
experiment, affecting the pressure gradient across the microfludic channels under each well. This is not
a problem in many microfludic platforms because most systems use peristaltic pumps or other constant
current sources. The two pumping mechanisms chosen for the new HTS platform generated a constant
Volume (μL)
Time (min)
53
air pressure or constant air flow-rate (peristaltic pump) below the platform, thereby pulling the liquid
through the channels. Therefore, the variation in the pressure head above the channels will inevitably
vary the flow rate, and in turn shear stress generated in the channels during the experiment.
To fully understand the effects of the generated pressure head on the dynamics of the flowrate and
shear stress, I modeled the system using the following relations for wall shear stress (τw) and flowrate
(Q):
(5)
The shear stresswas a function of channel width (w), height (h), flowrate (Q), and fluid viscosity (μ). The
pressure gradient (dp/dx) was simply derived using a discrete linear model:
(6)
where Δp is the pressure drop across the channel and L is the channel length. So the flowrate equation
reduced to a function of channel dimensions, fluid properties (μ and ρw), pressure head (Pi) and pressure
in vacuum manifold (Po):
(7)
The pressure headwas a simple function of liquid density (ρw), gravity constant (g) and the remaining
volume height in the well (hw). This equation was now easily solvable if Po was actively controlled using a
pressure regulator. However, a peristaltic pump produced a constant air outflow (in the initial stage of
the experiment) which resulted in the variation of the air density (ρa) inside the manifold. This deviation
had to be further modeled (equation (8)) using the following parameters (shown in Figure 21): reservoir
54
volume (Vw), channel dimensions (w and h), initial air density (ρai), volume in vacuum manifold (Vo),
pump outflow rate (Qa) and time (t).
Figure 21 – Volume and pressure parameters used in flowrate charachterization model.
(8)
Therefore constantly pumping air out of the manifold reduced air density/pressure, this was however
balanced (at different rate) by the liquid inflow (into the manifold) which increased and stabilized the
pressure in the manifold.
A final relationship between reservoir height (hw) and flowrate was required in order to fully define this
system:
(9)
The model had 7 unknowns and 7 equations, and was therefore solvable. Due to the complexity of the
solution, the system was modeled in Simulink (MATLAB, Figure 22) and simulated to generate a solution
Vo Q
a
Vw
Po
55
for the channel flowrate as a function of time and the negative outflow rate generated by the peristaltic
pump.
Figure 22 – System model simulated in Simulink (MATLAB). Simulation was necessary due to non-linear functions such as derivatives and integrals. Blue boxes represent controllable parameters (such as channel dimensions or initial volumes), white boxes are functions or constants necessary for the model, and yellow box represents variable functions (such as pressure or flowrate regulations in the vacuum manifold).
The pressure generated by the reservoir was approximately 500 Pa and reduced to 0 Pa over the course
of the experiment. The maximum pressure needed to overcome channel resistance (to produce desired
flowrate) was estimated to be 193 Pa for 100 μm deep channels and 720 Pa for shallow (50 μm)
channels. The resultant pressure head was at the least 69 % of the value needed to drive the flow at
maximum flowrate. The simulation showed an exponential decay in the flowrate (without ever achieving
stable linear flowrate) during the course of the experiment for constant pressure scenario. The constant
flowrate case still showed an exponential decay in flowrate (represented as temporal change in well
volume, Figure 23), however it was able to stabilize after 10 minutes into the experiment. Furthermore,
56
due to high flowrates (and the resulting shear stresses) that occur at the start of the experiment, most
of the reservoir is depleted in the first 5 minutes therebylimiting the duration of the flow study.
Figure 23 – Simulink output of well volume functions. A) Volume change when applying a constant pressure in vacuum manifold (500 Pa). Flowrate remains non-linear throughout the assay, and the majority of the well depletes within 15 minutes. B) Constant air outflow from the vacuum manifold (emulating a syringe pump or a peristatltic pump) produces a linear volume depletion (constant flowrate) only after 10 minutes into the experiment at which point the majority of the well is depleted leaving little reagents for the rest of the experiment.
These findings were proved to be accurate during early prototype characterization. Therefore in order to
solve this issue, I explored two unique methods: active vacuum control and channel resistance
modification.
4.4.2 PID Control
The pressure gradient across a channel is reduced over time as the reagent reservoir depletes. Therefore
adjusting the vacuum underneath the device may compensate for the loss of the static pressure head.
By actively monitoring the well volume and adjusting the driving pressure (feedback control) one can re-
stabilize the flow and achieve constant flow rates.
Active feedback control required a sensor capable of monitoring flowrate in real-time in order to
constantly adjust the vacuum pressure. Conveniently, the information from the flowrate sensor
>10 min
Desired flow-rate
Time (min)
Well volume (μL) Well volume (μL)
Time (min)
A B
57
(described in section 4.3.2), which was implemented in the original platform prototype, was used for the
feedback data needed to actively control the system. A PID controller was added to the control software
(section 4.2) which was able to interpret the data from the sensor and actively regulate the pressure in
the vacuum manifold.
Active PID control was able to stabilize the flow and produce linear volume depletion (Figure 24) and in
turn constant flowrates in a single well (with the volume sensor). Although the data gathered from the
sensor was from a single well, a system fabricated with tight tolerances would result in identical
flowrates across the device. Although the active control solution solved the problem caused by the
depleting reservoirs, the addition of a sensor and a control setup for every platform is a major drawback
to the original requirements (easy to use and operate). The setup times for every experiment drastically
increased with the addition of active pressure regulation, severely hindering experimental throughput.
Therefore, a more simplistic method to stabilize flowrate was still considered.
Figure 24 – Active PID control is able to successfully stabalize the flow using volumetric flowrate data from the volume sensor as feedback. The PID controller however is only able to regulate a single well, and requires a complex setup (such as a PC and a sensor) to properly function.
Well volume (μL)
Time (s)
58
4.4.3 Resistance Increase – filter paper or channel design
Flowrate is a function of two controllable components: pressure gradient and channel dimensions. The
pressure head poses a large influence on the pressure gradient when the pressure required to generate
desired flowrates is on the same level of magnitude as the generated hydrostatic pressure. Therefore,
applying pressure orders of magnitude higher than that of the hydrostatic pressure will overwhelm any
effects caused by the decaying pressure head. However, in order to compensate for the drastic increase
in pressure, channel resistances must be increased accordingly.
The original channel prototypes only need 200 - 720 Pa to achieve desirable flow rates; increasing the
pressure gradient at least 70 fold (to reduce the error due to changing hydrostatic pressure from 69 % to
1%) requires a 70 fold increase in resistance to maintain the desired flowrates. Such an increase in
resistance can be achieved by either substantially decreasing channel dimensions or adding a separate
fluid resistor before or after the microfludic channels. Reducing channel dimensions would violate the
primary requirements (section 3.5), so the remaining option is to add secondary microfludic ‘resistors’ to
reduce flowrate in order to compensate for the increase in the pressure gradient.
My first attempt to increase channel resistances was to redesign channel layout to include short
serpentine regions before and after the primary channels (Figure 25). The resistive portions of the
channels amounted to ~12 mm of narrow cross sections (100 x 50 μm) which substantially increased the
required pressure gradient (Figure 26). Although the resistive channels proved to be effective when
implemented into the prototype, the channel design caused great flowrate variability across the device.
This was due to the channel height variability across the wells, which was a limitation of the soft
lithography technique during master fabrication (section 4.1.1). Furthermore, the majority of the
59
channels (where the cells would be grown) experience high negative pressures (~-5 kPa) which is an
inaccurate model of the vasculature, where cells are normally exposed to 10-16 kPa of positive pressure.
Figure 25 – Revised channel profile. The new channel incorporates 2 resistive branches which produce enough resistance to slowdown the flow and enforce a higher pressure gradient which theoretically should diminish flowrate variability caused by the hydrostatic pressure decay. A) AutoCAD model of the revised channel. Blue ring indicates which channel areas are visible my well plate reader. B) Aluminum cast mold of the revised channel profile used for hot-embossing polystyrene channels.
Figure 26 – COMSOL simulations of the new channel profile. A) The negative pressure needed to produce desirable flowrates increased from 700 Pa to 10 kPa, well over the range of hydrostatic pressure. B) Shear stress distribution in the new channel profile remained the same as in the initial channel profile.
A B
A B
60
Another method for hindering fluid flow was to design a completely new resistive layer (module). Having
a separate module that can be easily interchanged to modulate resistance is not only advantageous for
the end user, but also in the early stages of the device prototypes. Semi-permeable membranes are
great at imposing large amounts of flow resistance over a short distance. Furthermore, there is a large
market of available membranes of different sizes which are readily available. Therefore, placing a
membrane or a filter between the channel layer and the outlets provides a simple solution for the
current problem. Choosing an appropriate filter/membrane material was done experimentally by testing
an array of commercially available products. Fisherbrand qualitative plain - P2 Grade brand filter paper
was chosen due to its ability to generate an appropriate amount of resistance to achieve desirable flow
speeds (Figure 27).
Figure 27 – Well volume is finally able to decrease linearly over the duration of 3 hours. The filter paper provides enough resistance to require pressure ranges of 10-30 kPa, negating any undesired effects caused by the hydrostatic pressure.
61
4.4.4 Flow-rate variability across wells
Although the filter membrane conveniently eliminates flow-rate variability over time caused by the
hydrostatic pressure in every well, it is not without its problems. Currently, the majority of ‘cake’ type
filters (such as filter paper) have an inherent ability to filter and accrue micro-bubbles. The retained
bubbles gradually increase the flow resistance, causing the flowrate to decay. This phenomenon begins
to occur only in long term experiments, making the filter membrane a viable solution for shorter-term
experiments. Bubbles also form when the filter membrane is first immersed under liquid. Therefore, the
filter module must be degassed prior to flow experiments to remove as many bubbles as possible.
The degassing process helps to remove the majority of the bubbles which are initially trapped in the
membrane, however desiccating the device under non-viscous liquids (water) causes boiling which
prevents total membrane wetting. The leftover air bubbles act as an additional flow resistors with an
uneven distribution from well to well. The results shown in Figure 28, which were obtained by
measuring leftover volume in each well after a 3 hr study, show that the flowrate can deviate by as
much as 105.8 % in a single 96 well assay. This is a major drawback to the system which hinders the
platform to be employed for high shear stress studies. However this absolute variability in shear stress is
still an acceptable error in low shear stress assays (1 – 2 dynes/cm2).
62
Figure 28 – Shear stress variability across 94 simultaneous conditions. The data was collected using the upscaled 96 well version (section 4.5) by measuring the remaining volume after a 3 hour experiment. A) Shear stress/flowrate variation in each channel. Some cases show flowrate deviation as high as 105.8%. B) Shear stress histogram across all 94 conditions.
4.5 96-well upscale
After thorough characterization of the initial prototype and successful monocyte adhesion assays
performed on the 12-well device (section 5.2), a 96-well prototype was fabricated. The new prototype
had all of the original modules and an array of additional components which will be described in this
section. The new system was comprised of three new subsystems, each with modular and
interchangeable parts (Figure 29). Each subsystem was designed for various steps in the assay, with the
channel module being continuously interchanged between the subsystems. Similarly to the original
prototype each sub-system required assembly and fastening together using 6 bolts, one for each corner
of the platform and 2 more that were located at the center of the device replacing 2 wells (leaving only
94 functioning wells). The 6 clamping sites on the base blocks (extruded pegs) also served as guiding pins
to help the user align the modules/layers and assemble the device with ease.
Shear stress (dyne/cm2)
Number of channels
Shear stress (dyne/cm2) A B
63
Figure 29 – System block diagram, along with all the sub-systems and their modules. Each sub-system employs a unique well block and a base plate. The channel module is shared across all sub-systems
4.5.1 Channel module: 2.0
Figure 30 – Channel module fabricated from polystyrene by hot-embossing fabrication methods using an aluminum mold (section 4.1.2)
Several improvements have been made to the 94 well channel module: the channel substrate,
fabricated out of PS, was initially covered with an adhesive mask, which was designed to be peeled away
Shallow well block Deep well block Re-circulatory
well block
Base plate
Base plate
Re-circulatory base plate
Channel module (shared between 3 sub-systems)
Filter membrane
Cell seeding sub-system Flow sub-system Conditioning sub-system
Microfludic high throughput screening platform
A B
64
prior to flow assay to remove the cells which undesirably settled outside of microchannels (Figure 31).
Furthermore, a PDMS gasket was cast around the channel module to further prevent any leaking across
wells during the cell seeding/feeding phases.
4.5.1.1 Cell seeding mask
The mask was cut from a sheet of adhesive polyvinyl chloride (PVC, Avery® Clear Inkjet Labels) using VLS
laser cutter. It was then bonded to the channel substrate to cover all but the straight portions of every
channel. Aligning the mask with the polystyrene substrate was done by utilizing the base block’s 6
locator pins.
Although the mask membrane successfully prevented any cells (outside of microchannels) from being
crushed during device assembly, the peeling process occasionally left behind small amounts of (auto-
fluorescent) adhesive (Figure 31-C) around the channel walls which may have caused artifacts in well
plate reader outputs.
Figure 31 – Cell seeding mask characterization. ECs were grown on the channel substrate with or without the mask. The cells were stained with Calcein AM (2 μM, Invitrogen) and Hoechst 33342 (2 µg/mL, Invitrogen). A) Cells grown on polystyrene channels without the mask adhere to areas outside the channel. B) Cells grown on polystyrene channels with the presence of the mask. After cells reach confluency, the mask is peeled away, and the channel was imaged. The cells only reside inside the channels. C) Leftover adhesive after mask removal. The adhesive is invisible under brightfield
A B C
65
microscopy, but auto-flouresces in the red spectrum. This induces artifacts when imaging cells which have been stained with fluorophores that emit in the red wavelength.
4.5.1.2 PDMS gasket
The 96 well-channel polystyrene substrate was created using a machined aluminum master. The
machining process, unlike SU-8 soft lithography, produced a rougher surface which was then transferred
to the channel layer via hot embossing (Figure 32). Although the increased surface roughness was not
drastic enough to disturb the fluid flow, the small surface imperfections were able to guide fluid across
wells during the cell culture/treatment phase. This was a major drawback for experimental protocols
that required long term cell treatment (such as pre-treating ECs with TNFα prior to flow). Therefore, in
order to prevent any micro-leaks, the channel layers were covered in PDMS to form a tight gasket
around the surface imperfections using the protocol described below.
Figure 32 – Surface of hot embossed polystyrene channels. A) The milling action (during mold fabrication) produces a circular pattern in the surface finish, while B) grinding/polishing the channel surfaces on the mold with sand paper to produces a scarred surface.
The PDMS gasket was performed using the following process (Figure 33): 1. The PS channel substrate (fabrication process described in section 4.1.2) was plasma treated for 3
minutes using a Harrick Plasma expanded plasma cleaner 2. A solution of PDMS and crosslinker (1:10 mixing ratio) was poured on the polystyrene substrate and
degassed to allow the PDMS to fill every surface imperfection 3. The top surface was then covered with a glass sheet to form a flat surface on top which was
necessary for equal pressure distribution during device assembly
A B
66
4. The PDMS was then cured at 80˚C for 4 hours, and the glass slide was delaminated from the channel-PDMS assembly
5. Using a 5 mm hole punch, 96 holes were cut in the PDMS gasket above every channel
Figure 33 - PDMS gasket fabrication process. 1) PS channels (coated with cell seeding mask) and a glass wafer are thoroughly washed using isopropanol to remove any debris on both surfaces. The PS channels were then plasma treated in Harrick Plasma expanded plasma cleaner for 3 minutes. 2) PDMS + cross linker were poured on both surfaces and then degassed to remove any trapped bubbles between the PDMS and the PS substrate. 3) Rubber spacers (of identical height) were placed in the master which was then covered by the glass wafer in order to produce an equal thickness PDMS substrate with flat surfaces. 4) The PDMS was baked for 4 hours and only the glass wafer was carefully delaminated from the cured PDMS. 5) Holes were punched over every channel to expose their surfaces.
4.5.2 Cell seeding subsystem
The cell seeding subsystem (Figure 34) was composed of a short PMMA well block, open microfludic
channel layer and an aluminum base block that allowed bottom imaging. This subsystem was necessary
at the start of the experiment and at the post processing stage of the study. The well block covered the
channel layer, allowing the user to only access the straight portions of each channel (Figure 6) for the
initial cell seeding stage. Together, the well block and the base provide rigid supports against which
PS Channels Glass wafer Cell mask
PDMS
Spacers
Cured PDMS
1)
2)
3)
4)
5)
67
large clamping pressure can be applied to allow the PDMS gasket to effectively prevent any leaks
between wells.
Figure 34 – Cell seeding subsystem. A) Assembled view of the final device. B) Exploded view showing all the modules in the sub-system (gaskets are not shown)
The subsystem was also designed for post experimental imaging. The channel layer was loaded back into
the system (post experimentation) to be used in the same manner as a 96 well plate. The device was
then placed into a well plate reader or imaged using upright or inverted microscopy.
4.5.3 Flow subsystem
The shear flow subsystem (Figure 35) was designed for short term experiments with 94 separate
conditions. This system was an upscale of the initial 12 well prototype and was comprised of the same
modules. The deep well block housed a reservoir of reagents that were be pumped through the channel
layer and the base plate into the vacuum manifold. The base plate and the deep well block together
functioned as a clamp the pressed the inlet and the channel layers together to form complete
microfludic channels.
Shallow
well block
Base plate
Channel
module
A B
68
Figure 35 - Flow subsystem. A) Assembled view of the final device on a vacuum manifold. B) Exploded view showing all the modules in the sub-system (gaskets and vacuum manidold are not shown)
The paper membrane (used to inhibit flow rates) was comprised of 94 individual filter disks punched
from Fisherbrand filter paper (grade: P2) that were held together by adhesive membranes cut from PVC
using VLS laser cutting system (Figure 36)
Figure 36 – Filter membrane layer. A) 94 separate filter disks are held together by 2 PVC membranes. B) Cross section view of a single filter section. A hole is cut above and below each filter disk to allow flow through the filter.
The PMMA deep well block and stainless steel base plate were machined in the University of Toronto
machine shop. The inlet layer was machined using the VLS laser cutting system, and is composed of 3
Filter disk
Adhesive membranes
Deep well
block
Base plate
Channel
module
Filter
membrane
A B
A B
69
layers (top to bottom): a PMMA sheet to maintain rigidity, a silicone gasket to conform to the channel
layer surface and a transparent PVC membrane to prevent the silicone gasket from invading and
blocking off shallow channels during flow. The vacuum manifold was purchased from GenElute™ (96
Vacuum Manifold).
4.5.4 Conditioning subsystem
Some experiments require that the endothelial cells be pre-conditioned under flow-induced shear stress
prior to treatment. Flow conditioning allows the cells to better acclimate to the shear induced
environment before being tested during the main experiment. Therefore, to increase the system’s range
for possible experiments, a conditioning sub-system was fabricated to satisfy one of the secondary
requirements (allow for long term cell culture and shear conditioning). This subsystem was again
comprised of a well block and a base block which together clamped the channel layer to form complete
microfludic channels.
Figure 37 - Conditioning subsystem. A) Assembled view of the final device. B) Exploded view showing all the modules in the sub-system (gaskets are not shown)
Re-circulatory
well block
Re-circulatory
base plate
Channel
module
A B
70
The PMMA well block was fabricated in a similar fashion as well blocks in other sub-systems, however
this block required a large shared volume reservoir above the wells where the all the media was mixed
together (Figure 37). Similarly, the aluminum base block has a large shared volume reservoir
underneath. As the media/reagents were pumped from the well block through the microfludic channels,
the media was then collected and pooled underneath the base block. The media was pumped out of the
base block (generating negative pressure underneath the base block and in turn driving the flow) and
was then re-circulated back into the well block reservoir via a peristaltic pump.
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5: Device validation and pilot studies
With the device fabricated and characterized, the next step was to demonstrate its capabilities by
performing an assay that would resemble a drug screening study. In order to highlight the importance of
mimicking key micro-environments and what effects they may have on experimental outputs, I designed
an experiment that would test the effects of shear stress (vs. static) on the response of drug activated
endothelial cells. By directly comparing the results gathered from the microfluidic platform versus data
recorded from a static well plate, I would be able to demonstrate the differences resulted from using a
static well plate to test new drugs/reagent and motivate the importance of using the new microfludic
platform instead of the ‘standard’ static culture plastics.
There are a variety of assays which can be tested with the new platform. Shear flow assays are
particularly relevant because the HTS system can induce controlled shear flow. A monocyte adhesion
study, a popular shear flow assay, was chosen for a proof of concept and platform validation experiment
due to the presence of multiple vascular microenvironmental factors (multiple cell types, shear flow,
biochemical stimulus). Tumor necrosis factor α (TNFα), a cytokine that is known to induce an
inflammatory response in ECs and make them more adhesive to monocytes, was chosen as a ‘drug
candidate’ to see its effects on monocyte adhesion during flow and static conditions.
5.1 Well plate reader sensitivity
5.1.1 Methods
A limitation with using polymer substrates in fluorescence well plate readers is that most polymers
autofluorescence in wavelengths that are commonly used for cell-based assays [99]. This imposes a
minimum detectable fluorescence limit, below which cell fluorescence is indistinguishable from noise
due to polymer autofluorescence. This fluorescence limit translates to a minimum number of cells,
72
which in turn indirectly translates into the minimum required channel surface areas of the platform. If
the channels are too small, there may be too few cells for the plate reader to distinguish them from
background signal.
In order to determine the minimum resolution of a standard fluorescence well plate reader (PHERAstar
HTS Microplate Reader), ECs were seeded in a standard 96 well plate (all wells) at a density of 350
cells/mm2. The ECs were allowed to grow to confluence over 24 hours. Afterwards, monocytes (THP-1
cell line) were suspended in PBS +/+ at a density of 10 million cells/mL and stained with Calcein AM (2
μM, Invitrogen) for 30 minutes. The fluorescently labeled monocytes were centrifuged (175 Gs for 5
minutes) and re-suspended in EC culture media (90 % M-199 + 10% FBS, Sigma) at different
concentrations (60 – 20,000 cells/mL; 50 μL per well) and added to the 96 well plate containing ECs. The
monocytes were allowed to settle and adhere to ECs for one hour, after which the wells were rinsed
with PBS +/+ to remove unbound monocytes. The well plate was then scanned in the HTS Microplate
Reader (PHERAstar).
5.1.2 Results
The minimum number of cells that the plate reader was able to distinguish from noise was 300 cells/well
or 8 cells/mm2 (Figure 38). Typical monocyte (THP-1 cell line) adhesion assays result in 1400 to 1600
monocytes/mm2 (depending on activation and flowrates) that were firmly adhered to underlying ECs
during flow [60].
73
Figure 38 – Results from pilot well plate reader sensitivity assay. A) Flourescently labeled monocytes (calcein AM, 2 μM) were added to 36 wells at a varying concentration (60 – 20,000 cells/mL). The well plate was incubated for an hour and scanned using a tabletop plate reader. B) A well that had at least 10 cells/mm2 was distiguishable from a well with no flourescently labelled cells in a plate reader. C and D) Wells were then imaged under a florescent microscope in order to accurately determine the number of cells in each well.
Noise (0 cells)
A
B C
D
74
5.2 Monocyte adhesion assay
5.2.1 Methods: assay in microfluidic platform
Monocyte adhesion to TNFα-treated ECs was tested in the HTS platform and static well plates. To
prepare the HTS platform, the polystyrene channel substrate, along with the cell seeding mask, was
placed in the cell seeding sub-system (section 4.5.2). Each well was rinsed with 100% ethanol to fully
wet the channels, then 75% ethanol to sterilize each well. Finally each well was then washed with PBS
+/+ followed by 20 minute UV exposure to fully sterilize the system. The PBS was aspirated and replaced
with 50 μL of plasma fibronectin solution (100 μg/mL). After allowing the fibronectin to fully adsorb onto
the channel surface over one hour, the wells were again rinsed with PBS. Primary porcine aortic
endothelial cells (PAECs) were seeded onto the surface of every channel at a density of 350 cells/mm2.
The cells were allowed to fully adhere and achieve confluence over 24 hours, after which the cells were
activated with different concentrations of TNFα (0 – 1000 ng/mL, n = 7-8/concentration, R&D Systems)
over duration of 4 hours. The ECs were once again rinsed in PBS +/+ and stained with Cell Tracker Red
(0.5 μM, Sigma) for 30 minutes, then were given a final rinse in PBS +/+. The channel substrate was then
removed from the cell seeding subsystem and placed into the shear flow sub-system (section 4.5.3).
Meanwhile, THP-1 cells (a monocyte cell line) were suspended in PBS +/+ at a density of 10 million
cells/mL and stained with Calcein AM (2 μm, Invitrogen) for 30 minutes. The cells were then spun down
at 175 Gs for 5 minutes and resuspended in endothelial cell culture media (90 % M199 media + 10 %
FBS, Invitrogen) at a density of 1 million cells/mL. 500 μL of the monocyte cell suspension was added to
every well (aside from control wells) in the assembled shear flow sub-system.
The platform was then placed on a vacuum manifold (in a cell culture incubator), which produced 9 kPa
of negative pressure, enough to drive the flow at a rate of 0.758 – 1.52 μL/min resulting in 1-2
dynes/cm2 of shear stress across all wells. After 3 hours, the pressure was reduced to atmospheric and
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the platform was removed from the vacuum manifold. The channel layer was once again removed from
the subsystem and placed in the imaging subsystem (section 4.5.2). The results were imaged using
standard, bench-top fluorescence plate reader (HTS Microplate Reader, PHERAstar) and fluorescent
microscopy (Olympus TH4-100 inverted microscope).
5.2.2 Methods: assay in static well plates
The same monocyte adhesion assay was performed in a standard polystyrene 96 well plate using a
standard monocyte adhesion protocol published by Millipore (Appendix C) and the cells and reagents
used in the flow study. Similar to the protocol described above, fibronectin was deposited into each well
(100 μg/mL) and incubated for one hour. The fibronectin solution was then aspirated and each well was
rinsed with PBS +/+. PAECs were seeded at a density of 350 cells/mm2 and were allowed to grow to
confluence over 24 hours. Afterwards, the ECs were treated with the same TNFα concentrations as in
the flow experiment (0 – 1000 ng/mL) for 4 hours. The activated cells were then rinsed with PBS for the
final time, and a 100 μL solution of fluorescently labeled monocytes (1 million cells/mL, methodology
provided in section 5.2) was added to every well (aside from control wells, which only received EC
culture media). The monocytes were allowed to settle and adhere to ECs for 30 minutes after which the
remaining suspended monocytes were aspirated and rinsed away with PBS +/+. The plates were imaged
using standard tabletop fluorescence well plate reader (HTS Microplate Reader, PHERAstar) and
fluorescent microscopy (Olympus TH4-100 inverted microscope).
5.2.3 Statistical analysis
Fluorescent intensity data recorded from the well plate reader were normalized using a natural
logarithmic transformation. Data were grouped together based on TNFα activation concentration to
form data sets of 7-8 samples with the exception of no TNFα treatment conditions, which had a sample
size of 23. The data groups were tested using a one way ANOVA analysis coupled with Fisher post-hoc
76
comparison in order to determine statistical significance. All data are reported as mean ± standard error
with p < 0.05 considered statistically significant.
5.2.4 Results and discussion
Imaging the monocytes using a well plate reader showed a clear increase in adhered monocytes with
increasing TNFα activation doses (Figure 39). Both the flow and static cases showed an exponential
increase of monocyte retention with TNFα treatment, with significantly more adhesion with TNFα
concentrations of 100 ng/mL (flow) and 50 ng/mL (static) than with 1 ng/mL (p = 0.046 flow; p < 0.001
static). However, ECs subjected to flow showed a continuous incline in monocyte adhesion to the TNFα
dose range from 0.01 to 100 ng/mL whereas the static condition showed more of a jump from 1 ng/mL
to 50 ng/mL. Furthermore, unlike the sigmoid saturation curve generated in the flow case, the static
condition fluorescence intensity plateaued at concentrations greater than 50 ng/mL, except at 1000
ng/mL, which had significantly lower adhesion (p < 0.001). Finally, monocytes adhered under flow
showed a dose dependency between 0 and 50 ng/mL of TNFα activation (Figure 39-D), whereas the
monocytes in the static well plate showed no dose dependencies to TNFα activation in that range
(Figure 39-B).
A monocyte adhesion assay performed in a static well plate is difficult to relate to an in vivo system due
to such drastic differences in the environments. Monocytes were only given 30 minutes to interact and
adhere to the ECs residing on the bottom of the well plate in the static assay, whereas the flow study
lasted for 3 hours. However, unlike the static case, a single monocyte can spend as little as 4.5 seconds
in a micro-channel drastically reducing its residency time compared to the monocytes which float in a
static well for 30 minutes. Despite the difference in the two environments, saturation of monocyte
adhesion (between static vs. flow) occurred at similar TNFα concentrations (50 ng/mL for static and 100
ng/mL, Figure 40) suggesting that monocyte adhesion was majorly influenced by the TNFα
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Figure 39 – Flourescence intensity and distribution across the device recorded by the well plate reader after monocyte adhesion assay. Each row had an equal TNFα activation concentration (n = 7 or 8) with 12 different conditions (12 columns). A and B) Assay perfomed in a static well plate. C and D) Assay performed in flow sub-system. Data are shown as mean ± standard error.
concentration rather than flow condition or residency time. Several published monocyte adhesion
studies report saturation of monocyte-EC adhesion at much lower TNFα concentrations. A study in
which monocytes were suspended for only 15 minutes over TNFα activated ECs showed a saturation of
monocyte adhesion at a TNFα dose of only 5 ng/mL [100]. A similar experiment achieved saturation at 1
ng/mL of TNFα dose in as little as 10 minutes [101]. In fact studies that have explored TNFα effects at
A B
C D
78
the high doses used here are rare, yet still show complete saturation of monocyte adhesion below 0.05
ng/mL [102]. Discrepancies between previous studies and mine may have resulted from different cell
types present in my experiment (PAECs and THP-1 monocyte cell line) than the ones used in previously
mentioned studies (human umbilical vein endothelial cells (HUVECs), primary peripheral blood
mononuclear cells or U-937 cell lines). The wide range of TNFα activation concentrations (0.05 – 5
ng/mL) that result in monocyte adhesion saturation reported in previous studies suggests that the assay
is very sensitive to test conditions (such as mentioned above) and not readily comparable across labs.
Figure 40 – A) Relationship between TNFα activation concentration and resulting florescence intensity reading per channel. Dashed line shows results obtained from static well plate and solid line shows results obtained from shear flow; * p = 0.046, ** p < 0.001. B and C) fluorescent microscopy images of channels after flow assay. The monocytes outside of the channels borders (represented by yellow dotted lines) were seen to be introduced during post assay device disassembly. This can be avoided by aspirating the remaining media (with monocytes) from the wells after the experiment and replacing it with a washing buffer then again inducing shear flow for a short duration to rise the channels of any unbound monocytes.
Fluorescence intensity (x104)
TNFα activation concentration (ng/mL)
* ** ** A
B
C
79
Although the sigmoid dose response curve is common in the static condition assay [100-102], the
sudden drop in monocyte adhesion with 1000 ng/mL TNFα has not yet been reported, mostly because
the majority of the studies never test such high concentrations. Therefore, the reason for this
phenomenon still remains unclear.
TNFα mediated endothelial-monocyte interactions have been previously investigated in vitro [60, 103],
but majority of studies have focused on the effects of variable shear stress rather than a dose response
to TNFα concentrations.Notably, the gradual increase in monocyte adhesion to TNFα activation range of
0.01 to 100 ng/mL under flow compared to the jump from 1 to 50 ng/mL in the static well plate possibly
suggestis that laminar shear stress does indeed decrease inflammatory cell adhesion to ECs [103-105];
or that the ECs may be more adhesive in the static condition (without TNFα activation), whereas under
flow, they are not adhesive unless stimulated with TNFα. Another likely possibility is that continuous
shear flow simply shears off any monocytes with weak adhesion to ECs permitting only monocytes with
strong bonds to remain adhered. This phenomenon is clearly shown in the no-monocyte condition
between both (flow vs. static) assays (Figure 38 B and D). The static assay shows a significant difference
(p < 0.001) between the fluorescence reading in wells that had no monocytes added (negative control,
row 12 - Figure 39 B) and wells with monocytes but no TNFα (rows 3, 6 and 9), whereas under flow
(Figure 39 D) there were no differences between the no-monocyte control case and 0 ng/mL TNFα
treatment (with monocytes). This suggests that static assay is susceptible to background noise (weakly
adhered monocytes) and changes in lower TNFα concentrations are more readily detected under flow
(although they were not statistically different in the validation experiments reported here).
It is important to note that main studies that examine shear flow effects usually condition the ECs with
long-term shear flow. Pre-conditioning the cells to physiological shear stresses usually results in a
80
reduction in inflammatory response [103]. These effects could be studied in the future with the HTS
platform by using the conditioning sub-system.
5.3 Cell conditioning with long-term shear stress
5.3.1 Methods
Endothelial cells are usually conditioned in flow environments over a substantial period of time, typically
for 48 hours. Because of the immense volumes that pass through the channels during this process, the
only practical way to condition the cells was to use re-circulatory flow.
Endothelial cells were cultured on channels using the methodology described in section 5.2, after which
the channel substrate was placed into the re-circulatory flow subsystem. A flow loop that consisted of a
peristaltic pump and flow dampener (Figure 41) was set up in order to generate constant shear stress
across the endothelium. The ECs were conditioned for 48 hours under a nominal shear stress of 5
dynes/cm2.
Figure 41 – Re-circulatory flow loop used for long-term cell shear stress conditioning experiment. The media is pumped out of the subsystem, into the flow dampener which converts pulsatile flow to continuous uninterrupted flow. The media leaves the dampener and enters the peristaltic pump. The pump then guides the media back into the conditioning subsystem.
After completing the assay, the channel substrate was removed from the re-circulatory platform and
placed back in the cell culture sub-system. At this point, the cells could have been used for further
experimentation (such as a monocyte adhesion assay), however to validate and characterize the re-
Conditioning subsystem
Flow dampener Peristaltic pump
81
circulatory subsystem, the cells were stained with 2 μM calcein AM (Invitrogen) and 8 μM ethidium
homodimer (Invitrogen) in order to determine cell viability after 48 hours of flow. The cells were imaged
using fluorescent microscopy.
5.3.2 Results
Endothelial monolayers remained confluent post 48 hour conditioning, with majority of the cells
remaining viable, proving the subsystem is capable of long term cell culture (Figure 42 A). ECs in some
wells however, were not confluent after 48 hours (Figure 42 B). This could have either resulted from
cells in some regions never reaching confluence prior to the experiment, or cell death during the 48
hour shear flow (dead cells would have been washed away). ECs could not have been imaged under
regular bright field microscopy prior to conditioning due to the rough channel surface, and fluorescently
labeling cells prior to shear flow may have caused some cell death. The effects of pre-conditioning
endothelial cells before a monocyte adhesion assays, however, has not been performed in this thesis.
Figure 42 – Live dead stain of endothelial cells after flow condotion assay. The cells were sheared for 48 hours at 5 dynes/cm2, then stained with 2 μM calcein AM (Invitrogen) and 8 μM ethidium homodimer (Invitrogen) for 20 minutes. A) majority of ECs remained viable and confluent after 2 day conditioning assay. B) Some channel regions did not have confluency after cell conditioning assay.
A B
82
6: Conclusions
The main objective of the thesis was to design and build a system capable of mimicking essential
vascular micro-environments, and yet still allowing high-throughput experimentation in hopes to
eventually replace the static well plate model used in drug screening assays. The system currently is
capable of inducing shear flow to cells cultured on the device, providing them with physiological micro-
environments that the static well plate lacks.
Key requirements such as compatibility with well plate reader and liquid handling systems were driving
factors in the initial concept of the system. The HTS platform closely resembles a 96 well plate and can
be used in the automated machinery, which can drastically improve experimental throughput, although
from a user’s point of view device assembly and disassembly can be a hassle when performing several
assays per day.
Overall, the benefits of testing reagents in a more physiological environment outweigh the few
drawbacks in the system. As the results indicated, monocyte adhesion differs depending whether the
assay has been performed in a static plate or under shear flow. In particular, there was less monocyte
adhesion under shear flow and the assay was more sensitive to small changes in drug-induced adhesion,
although without statistical significance in these pilot experiments.
6.1 Future recommendations
The current prototype is capable of producing the required shear stresses of 0-5 dynes/cm2; for some
shear inducing assays (reviewed in [106]), higher shear stresses representative of the arterial system ( 1
to 20 dynes/cm2) might be desired. The platform can induce higher flow rates (τ > 5 dynes/cm2) by
controlling the pressure in the vacuum manifold, however due to the reasons described in section 4.4.4
83
the platform can produce flowrate variations/error across the device up to 105%; so generating high
shear stresses (eg. 10 dynes/cm2) will induce high error in shear stress precision (10 – 20 dynes/cm2).
Therefore there is a need for a better flow resistor. Theoretically, a membrane with a single opening
(hole) can provide enough resistance to achieve constant flow rates, while avoiding problems such as
bubble formation. Any cells or bubbles that get stuck in the single opening will be forced through by the
pressure across the opening, which is not the case in the current filter membrane (multiple openings
lower the pressure gradient across a single blocked portion). The problem with this solution arises when
trying to fabricate a membrane with a single opening. Using COMSOL software, I was able to identify
that the required hole size must be 8-10 µm in diameter to produce enough resistance to achieve
desired flowrates (Figure 43). There are numerous possible fabrication methods that are capable of
producing these holes (such as dry etching or fine laser machining), however the tolerances on the hole
diameters between the 94 wells must be extremely tight to avoid further flowrate variability.
Figure 43 – A) CFD analysis of pressure drop across a (50 µm high) channel with new membrane. B) The membrane hole was modeled as a 10 µm diameter, 250 µm long tube. 11.4 kPa of pressure is needed to drive the flow at the maximum desired shear stress (5 dynes/cm2).
Outlet
Base
Inlet
Outlet
Base A B
84
Fabricating polystyrene channels using machined molds is a fast and inexpensive method for producing
channel modules. However CNC milling produces a rough finish on the surface of the mold and the
channels. Figure 44 shows the surface imperfections of a single channel. Not only do these
imperfections produce leaking from one well to another (explained in section 4.5.1.2), but they also may
influence cell adhesion and growth. This can be seen in Figure 42, where the confluent EC monolayer
aligned in the direction of the surface scarring during a 48 hour conditioning assay. Furthermore, the
surface imperfections make it very difficult to see adhered cells under bright field microscopy. . A
method of producing masters (such as SU-8 soft lithography with optimized parameters to reduce
feature spatial variability) or channels with a smoother surface could definitely improve the device
functionality and make it easier to use.
Figure 44 – Channel surface roughness. PDMS channels were cast using methods described in section 4.1.2 and imaged using AFM techniques.
X direction
Y direction
Surface height (µm)
85
To further validate the impact of using shear flow environments (vs. static), experiments using drug
libraries can be performed using the HTS platform. The device has not yet been tested with a liquid
handling system, so appropriating the device to be used for drug discovery would have to be the next
step. Drugs families such as statins have been shown to have different effects on EC regulation of
inflammatory response factors (such as vascular cell adhesion molecule – 1 [VCAM-1] and Krueppel-like
factor 2 [KLF2]) and monocyte adhesion when tested on sheared ECs versus ECs that have been cultured
in static conditions [107, 108]. Therefore, these drugs can be used as a drug screening validation
experiment to contrast the effects of using a static well plate versus the new platform. Furthermore,
using the shear flow conditioning sub-system, the system can be used to perform experiments that
study the effects of drugs on pre-conditioned ECs.
86
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Appendix A - Channel dimension
calculations
Given parameters:
Maximum volume held in a single well/reservoir (Vmax) = 2 mL
Maximum required shear stress (τmax) = 5 dynes/cm2 (0.5 Pa)
Maximum flow study duration (tmax) = 3 hours (10,800 s)
Dynamic viscosity of water (μW) = 8.90 × 10−4 Pa·s
Shear stress formula:
To minimize shear stress variation across the channel, h/w must be below 1/3; resulting in n = 2 and m =
14.23 (h = 50 or 100 µm, w = 500 µm)
Sear stress variation:
2% change in height may cause 4% change in shear due to exponential relationship of shear to channel
height
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Appendix B – SU-8 fabrication protocol
The SU-8 masters were all fabricated in the Emerging Communications Technology Institute (ECTI) cleanroom facility. Ensure an ample supply of cleanroom wipes is available and is placed on the wet bench area where the work will be performed. This is to quickly clean up accidental spills of chemicals. Use digital hotplates and ensure they are level. Use cleanroom wipes as spacers, if needed. Before starting, it is highly recommended that the glass slides be cleaned with Piranha solution (separate procedure), to clean the glass surface of any organic residues.
Seed layer fabrication (~7 μm) 1. Rinse slides with acetone and IPA, and blow dry with nitrogen. 2. Perform a dehydration bake by heating the slides to 180 °C for 20 min and allow the slides to cool
with the hotplate to ~60 °C. 3. Using a plastic pipette, drop a few mL of SU-8 5 onto the surface of the slides. Angle the slides to
coat them fully. 4. Spin coat the slides using the following protocol:
a) Step 1: 5 s, 500 RPM, 88 ACL b) Step 2: 30 s, 500 RPM, 88 ACL c) Step 3: 15 s, 3000 RPM, 528 ACL d) Step 4: 30 s, 3000 RPM, 528 ACL
5. Prebake the slides at 65 °C for 2 min and at 95 °C for 5 min, respectively. 6. Allow the slides to cool with the hotplate to ~60 °C. 7. Using a photomask, expose the slides with UV light for 2 s by selecting the FLOOD-6 option on the
mask aligner. 8. Post-bake the slides at 65 °C for 1 min and at 95 °C for 4 min, respectively. 9. Allow the slides to cool with the hotplate to ~60 °C. 10. Develop the slides in SU-8 developer for 2 min. 11. Rinse with IPA (NOT acetone) and blow dry with nitrogen. Ensure that no white deposits are present
on the surface. If this is the case, place the slides in developer for an additional 5 min. 12. Hard-bake at 180 °C for 30 min.
Feature fabrication (50 μm or 100 μm, depending on SU-8 type) 1. Rinse seed-layer slides with IPA (NOT acetone), and blow dry with nitrogen. 2. Perform a dehydration bake by heating the slides to 180 °C for 20 min and allow the slides to cool
with the hotplate to ~60 °C. 3. Pour enough SU-8-25 for 50 μm high features or SU-8-50 for 100 μm high features (either from the
bottle or from an aliquot) onto the surface of the slides to partially coat it. Burst any bubbles with a 20-gauge needle, as needed.
4. Spin coat the slides using the following protocol: a) Step 1: 5 s, 500 RPM, 88 ACL a) Step 2: 30 s, 500 RPM, 88 ACL b) Step 3: 5 s, 1000 RPM, 352 ACL c) Step 4: 33 s, 1000, 352 ACL
5. Prebake the slides at 65 °C for 10 min and at 95 °C for 30 min, respectively.
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6. Allow the slides to cool with the hotplate to ~60 °C. 7. Using a photomask, expose the slides with UV light for 9 s (50 μm), or 30 s (100 μm) by selecting the
SOFT-30 option on the mask aligner. 8. Post-bake the slides at 65 °C for 1 min (50 μm) or 2 min (100 μm), and at 95 °C for 6 min (50 μm) or
15 min (100 μm), respectively. 9. Develop the slides in SU-8 developer for ~10 min (50 μm) or ~20 min (100 μm). 10. Rinse with IPA (NOT acetone) and blow dry with nitrogen. Ensure that no white deposits are present
on the surface. If this is the case, place the slides in developer for an additional 5 min. 11. Hard-bake at 180 °C for 1 hr.
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Appendix C – Millipore monocyte
adhesion assay
Preparation of Endothelial Cells Perform the following steps in a sterile hood Prepare Endothelial cell line for investigation as desired. The following procedure is a suggestion for preparing endothelial cells used in cell layer formation. Human umbilical vein endothelial cells (HUVECs) from ATCC® (CRL-1730) or Cambrex(CC-2519) were used for generating endothelial adhesion activity data for this assay. 1. Use cells that are at least 80-100% confluent. 2. Visually inspect cells before harvest, taking note of relative cell numbers and morphology. 3. Wash cells 2 times with sterile PBS or HBSS. 4. Add 5 mL Harvesting Buffer (see Materials Not Supplied) per 100 mm dish and incubate at 37°C for
5-15 minutes. 5. Add 10-20 mL of Quenching Medium or Endothelial Cell Growth Medium (see Materials Not
Supplied) to inactivate trypsin/EDTA from Harvesting Buffer and gently pipet the cells off the dish. 6. Centrifuge cells gently to pellet (400 x g, 5-10 minutes). 7. Carefully remove media from pellet. 8. Gently resuspend the pellet in 1-5 mL of Quenching Medium or Endothelial Cell Growth Medium,
depending upon the size of the pellet. Optimum cell density may be determined by titration of the cells. Often it is best to harvest a greater number of cells than is needed.
9. Count cells and bring to a volume that provides a concentration of 1.0 –2.0 x 106 cells/mL with growth
10. OPTIONAL: If pretreatment of Endothelial Cells is desired, add compound(s) (cytokines, pharmacological agents, etc.) at this time.
Preparation of Calcein AM Labeled Test Cells Perform the following steps in a sterile hood Prepare cell line for investigation as desired. The following procedure is a suggestion for preparing leukocytic cell lines used in cell adhesion. Note: Use Calcein AM labeled cells within 4 –12 hours. 1. Use cells that are at least 80-100% confluent. 2. Visually inspect cells before harvesting, taking note of relative cell numbers and morphology. 3. Dissociate adherent or non-adherent cell lines to be tested into separate, single cell suspensions. 4. Dilute the leukocyte cell suspension(s) to 5 mL. 5. Add 12.5 μL of Calcein AM to the cell suspension(s) for a 2.5 μM
final concentration. Mix gently by inversion. 6. Incubate the cells in a 37°C CO2 incubator for 30 minutes. 7. Centrifuge cells gently to pellet (400 xg, 5-10 minutes). 8. Carefully remove the media from the cell suspension(s). Note: The cell pellet(s) should have a bright
yellow appearance. 9. Wash each labeled cell line with 5-10 mL of PBS or HBSS. Pipette to resuspend and wash the cells
thoroughly. 10. Centrifuge cells gently to pellet (400 xg, 5-10 minutes). Carefully remove and discard the wash. 11. Repeat wash 2-3 times until all residual Calcein AM is removed.
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12. After the last wash, gently resuspend the cells in 1-5 mL of Assay Buffer, depending upon the size of the cell pellet.
13. Count the cells and bring to a volume that provides a concentration of 0.5 –2.0 x 106 cells/mL with Assay Buffer or media. Note: Resuspend the cells if they stand too long and settle prior to using them.
Assay Instructions Perform the following steps in a sterile hood Note: Prepare cell lines and reagents for investigation as desired. The following procedure is a suggestion for performing leukocyte-endothelial cell adhesion. This procedure is intended as a guide. The user is encouraged to define their experimental parameters when evaluating endothelial adhesion. 1. Rehydrate the desired number of plate wells with 100 μL of EGM per well and incubate the plate at
room temperature until the cell suspensions are ready. 2. Spin the final single endothelial cell suspension down one more time and gently resuspend in EGM.
See Cell Harvesting. 3. Prepare endothelial cells to desired concentration in EGM. A common starting range is 0.5 to 5.0 x
105 cells/mL. 4. Add 100 μL of the endothelial cell suspension to each plate well to be tested. It is recommended
that you seed 5,000 to 50,000 endothelial cells per well and prepare enough wells to assay each sample in duplicate or triplicate.
5. Incubate the plate for 48-72 hrs at 37°C in a CO2 incubator. During the incubation, monitor the cell growth microscopically to ensure cell viability, morphology and uniformity.
6. Change the media every 24-48 hours. Optional: Perform cell starvation if desired. Incubate endothelial cells with basal media (EBM) with 1-2% serum for 4-24 hours prior to
7. activation. 8. After incubation, gently discard or aspirate the media from the wells. Note: Do not allow wells to
dry. 9. Add 100 μL of Cycloheximide or Actinomycin D solutions to control wells. 10. Add 100 μL of media to the non-treated wells. 11. Cover and incubate the plate 30 minutes at 37°C in a CO2 incubator. 12. Activate the endothelial cells by adding 10 μL of Tumor Necrosis Factor alpha or Interleukin-1 beta
to the appropriate test wells. This dilutes the TNFalpha and IL-1beta to a final concentration range of ~1-100 ng/mL.
13. Cover and incubate the plate at 37°C in a CO2 incubator for 2-6 hours. 14. Carefully remove 75-100% (~75 μL) of the solution from the wells and discard. Note: Do not allow
wells to dry. 15. Gently wash each well 1-2 times with 200 μL per well of Assay Buffer. Remove each 200 μL wash and
discard. Try to leave about 20% (~50 μL) of Assay Buffer per well when aspirating/removing the last wash solution so the cells remain hydrated at all times. Note: If performing endothelial adhesion blocking studies with a blocking mAb, go to step 15. If not performing endothelial adhesion blocking with a blocking mAb, go to step 17.
16. Add adhesion-blocking mAb to the appropriate final concentration per well. 17. Cover and incubate the plate at 37°C in a CO2 incubator for an appropriate time (~30-60 minutes).
Optional: The user may co-incubate the blocking mAb with the test cell line. 18. Prepare test cell suspension as desired. Add 100 μL of test cell suspension (~50,000 to 200,000) to
each well. See Preparation of Calcein AM Labeled Cells.
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19. Cover and incubate the plate 30 minutes at 37°C in a CO2 incubator. 20. After the incubation period, verify microscopically that the test cells have settled onto the
endothelium. 21. Carefully aspirate 75% of the solution from the wells and discard. 22. In order to remove test cells with non-specific binding, gently wash each well 2-3 times with 200 μL
per well of Assay Buffer. Remove each 200 μL wash and discard. Try to leave about 50-100 μL of Assay Buffer per well when aspirating/removing the wash solution so majority of the endothelial/test cell adhesion is maintained, and only nonspecifically bound test cells are removed. Note: Use caution when washing as forceful pipetting can dislodge cells and affect assay results.
23. After washing, leave 100 μL of Assay Buffer in each well. 24. Read the plate with a fluorescence plate reader using 485/530 nm excitation/emission filter sets.