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DEVELOPMENT AND CHARACTERIZATION OF A MICROFLUIDIC SYSTEM TO MODEL THE
TRANSENDOTHELIAL MIGRATION MECHANISM OF THE LYME DISEASE PATHOGEN Borrelia burgdorferi
by
Michele Bergevin
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Mechanical & Industrial Engineering and Institute of Biomaterials & Biomedical Engineering
University of Toronto
© Copyright by Michele Bergevin 2017
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Development and Characterization of a Microfluidic System to Model the Transendothelial Migration Mechanism of the
Lyme Disease Pathogen Borrelia burgdorferi
Michele Bergevin
Master of Applied Science
Department of Mechanical and Industrial Engineering and Institute of Biomaterials and Biomedical Engineering
University of Toronto
2017
Abstract
Blood-borne bacteria like the Lyme disease pathogen Borrelia burgdorferi cause
infection by migrating across the vascular endothelial barrier into target tissues. The
mechanisms by which this occurs are poorly understood, largely because model systems
inadequately mimic the in vivo environment or are too inefficient to dissect mechanisms.
This unmet need is addressed in this thesis by the development of a microfluidic system
and live cell imaging methods to model and study transendothelial migration of bacteria
in vitro under physiologically relevant conditions. Real-time transmigration kinetics of B.
burgdorferi across intact endothelium were obtained, for the first time, under static and
flow conditions. Validation studies confirmed that B. burgdorferi transmigrate actively,
with similar kinetics to conventional Transwell systems under static conditions.
Additionally, physiological shear stress conditions appeared not to significantly alter
transmigration kinetics. These data were uniquely obtainable with the microfluidic
platform, supporting its utility for studying extravasation of blood-borne pathogens of
worldwide significance.
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Acknowledgments
To my supervisors, colleagues, and friends, an immense thank you for all your support and critical feedback over the years, which have greatly helped to shape the contribution I present here.
To my family, who has been instrumental and exceptional in supporting me throughout everything— such gratitude, appreciation and love are beyond measure, in a realm in which words fail to convey.
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Table of Contents Acknowledgments .................................................................................................................... iii Table of Contents ..................................................................................................................... iv
List of Figures ........................................................................................................................... vi Introduction ................................................................................................................................ 1
Literature Review ............................................................................................... 3
1.1 Lyme disease bacterium and pathogenicity features ......................................... 3
1.1.1 Lyme disease ........................................................................................................... 3
1.1.2 B. burgdorferi morphology and motility ..................................................................... 4
1.1.3 Life dominated by viscosity ...................................................................................... 6
1.2 Endothelial cells ..................................................................................................... 7
1.2.1 Background .............................................................................................................. 7
1.2.2 Shear stress effects on transendothelial migration .................................................. 9
1.3 Bacterial-host cell interactions ........................................................................... 10
1.3.1 Applicable insights from leukocyte emigration ....................................................... 10
1.4 Existing experimental models of bacterial transmigration .............................. 11
1.4.1 Static in vitro studies .............................................................................................. 11
1.4.2 In vivo extravasation studies .................................................................................. 13
1.4.3 Microfluidics appeal ................................................................................................ 14
1.4.3.1 Advantages of microfluidics ........................................................................... 14
1.4.3.2 Types of microfluidic transmembrane models ............................................... 15
1.4.3.3 Importance of endothelial cell confluency in transmigration models .............. 17
1.4.3.4 Requirements for a microfluidic-based extravasation model ......................... 18
Thesis Objectives ............................................................................................ 19
2.1 Overall objectives ................................................................................................. 19
2.2 Research Hypotheses .......................................................................................... 19
2.3 Research Aims ..................................................................................................... 19
2.3.1 Aim 1 ...................................................................................................................... 19
2.3.2 Aim 2 ...................................................................................................................... 20
2.3.3 Aim 3 ...................................................................................................................... 20
Microfluidic Model of Spirochete Transendothelial Migration ................... 21
3.1 Introduction .......................................................................................................... 21
3.2 Methods ................................................................................................................. 23
3.2.1 Transmembrane device design and fabrication ..................................................... 23
3.2.2 Cultivation of endothelial cells and preparation for imaging ................................... 24
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3.2.3 Preparation of B. burgdorferi and beads for imaging ............................................. 24
3.2.4 Immunofluorescence microscopy ........................................................................... 25
3.2.5 Static Transwell experiments ................................................................................. 25
3.2.6 Microfluidic transmembrane device experiments ................................................... 26
3.2.7 Automated object quantification in z-series ............................................................ 27
3.2.8 Statistical analysis .................................................................................................. 27
3.3 Results and Discussion ....................................................................................... 27
3.3.1 Design of microfluidic transmembrane device to study bacterial extravasation ..... 27
3.3.2 Assessment of endothelial barrier integrity in microfluidic transmembrane devices ......................................................................................... 28
3.3.3 Development of methods to detect and quantify transmigration of individual bacteria ................................................................................................................... 29
3.3.4 Comparison of B. burgdorferi transendothelial migration kinetics in microfluidic membrane devices and a conventional Transwell model under static conditions .. 32
3.3.5 B. burgdorferi transendothelial migration kinetics in microfluidic devices under physiological shear stress conditions ........................................................... 34
3.3.6 Conclusions ............................................................................................................ 37
Conclusion and Recommendations ............................................................... 38
4.1 Conclusion ............................................................................................................ 38
4.2 Future directions .................................................................................................. 39
4.2.1 Incorporation of more robust techniques for ensuring endothelial monolayer integrity ................................................................................................. 39
4.2.1.1 Better control of the ambient environment ..................................................... 39
4.2.1.2 Device design modification ............................................................................ 40
4.2.1.3 TEER measurements to monitor endothelium confluency ............................. 41
4.2.2 Examination of preconditioning effects on transendothelial migration ................... 42
4.2.3 Investigation of endothelial heterogeneity effects on bacterial extravasation ........ 43
4.2.4 Study of additional extravasation effectors ............................................................. 44
4.3 Final remarks ........................................................................................................ 44
References ............................................................................................................................... 46
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List of Figures
Figure 1. Host vectors of the Lyme disease pathogen B. burgdorferi, and susceptible organ systems in an infected human. ............................................................................................ 4
Figure 2. Confocal microscopy image of GFP-expressing B. burgdorferi .................................. 5
Figure 3. Longitudinal schematic of B. burgdorferi. (Reprinted with permission, Charon, NW, et al. 2012.) ....................................................... 5
Figure 4. Select phenotypic differences between vascular endothelial cells. (Reprinted with permission, Aird, WC. 2007.) ..................................................................... 7
Figure 5. Time-lapse images of actin filaments within an endothelial cell monolayer exposed to 15 dyn/cm2, illustrating cell alignment with flow direction by 24 h. (Reprinted with permission, Galbraith, CG, et al. 1998.) .................................................... 8
Figure 6. The stages of leukocyte transendothelial migration. (Reprinted with permission, Vestweber, D. 2015.) .............................................................. 9
Figure 7. The multistage process of B. burgdorferi transendothelial migration. (Reprinted with permission, Norman, M, et al. 2008.) ....................................................... 10
Figure 8. Schematic representations of membrane-based and extracellular matrix-containing microfluidic devices for transmigration studies that support shear flow. (Reprinted with permission, Bogorad, MI, et al. 2015.) ..................................................... 16
Figure 9. In vitro model to study endothelial transmigration of bacteria under physiological shear stress. ...................................................................................................................... 29
Figure 10. Focal depth, sensitivity and accuracy of imaging-based bacterial quantification in microfluidic devices.. ......................................................................................................... 31
Figure 11. Validation of microfluidic B. burgdorferi transmigration system under static conditions.. ............................................................................................................... 34
Figure 12. B. burgdorferi transmigration through endothelial monolayers in microfluidic devices at physiological shear stress ................................................................................ 35
Figure 13. Proposed device design modifications.. .................................................................. 41
Figure 14. An example of Ag/AgCl wire electrodes incorporated into the fabrication of a PDMS transmembrane microfluidic device to evaluate endothelial confluency via TEER measurements. (Reprinted with permission from Douville, NJ, et al. 2010.) ............................................... 42
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Introduction
Blood-borne bacteria have evolved countless strategies to evade the host immune
system, resulting in systemic dissemination of the cardiovascular system— the greatest
cause of mortality in bacterial infections. Similar to leukocyte transendothelial migration,
host-pathogen interactions involve multiple stages to counter the shear stress of blood
flow prior to escaping the vasculature, known as extravasation. Like all microorganisms
that traverse the cardiovascular system, bacteria have adapted many techniques, both
passive and active, for thriving in a viscous-dominated microenvironment1 and invading
surrounding target tissues. Spirochetes in particular, are known for their remarkable
swimming ability,2 due to their unique morphologies3–6 and motility,7–13 and are known to
invade nearly every tissue in the human body, including the fetus via transplacental
entry,14–16 and the brain and cerebral spinal fluid via the blood-brain barrier.17–20 Much
progress has been made in characterizing adhesion mechanisms responsible for the
initial stages of host-pathogen interactions. However, the final steps in bacterial
dissemination – transendothelial migration, and passage into surrounding target tissues
– still pose many questions, in large part because the model systems used to study
bacterial extravasation poorly mimic the in vivo vascular environment or are too inefficient
to fully dissect mechanisms.
Bacterial extravasation is a complex process, and to properly study such first requires
individual review of the major concepts that play a role. Only then, are we prepared to
investigate the biomechanical mechanisms of extravasation, which are characterized by
the interdependent relationships between these individual factors. This background is
provided in the next chapter and reviews the following concepts, which also provide
rationale for particular features of the microfluidic system developed for this thesis:
(1) the role of bacterial motility in a viscous-dominated microenvironment, and
specifically, the adaptive features of the Lyme disease spirochete B. burgdorferi,
(the model organism for this study);
(2) the structure and function of endothelial cells, including sensitivity to fluid shear
stress;
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(3) what is known about bacterial dissemination mechanisms, with a focus on the latter
stage related to extravasation; and
(4) relevant experimental models, and their respective advantages and limitations.
The goal of this thesis is to address the unmet needs of bacterial extravasation models
through the development of a transmembrane microfluidic system and live cell imaging
methods to model and study transendothelial migration of bacteria in vitro under
physiologically relevant conditions.
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Literature Review
1.1 Lyme disease bacterium and pathogenicity features
1.1.1 Lyme disease
Lyme disease, caused by the spirochete Borrelia burgdorferi is the most common
arthropod-borne zoonotic disease in the northern hemisphere,21–23 and can colonize
invertebrates, birds, reptiles, and mammals (Fig. 1). In warm-blooded species, the
bacterium persists in small animals like rodents, to large mammals like deer and humans.
By 2020 it is projected that 80% of Canadians will be living in the newly expanded habitat
of B. burgdorferi-transmitting tick species.24 These spirochete bacteria, unique for their
waveform morphology and agility, have been isolated from virtually every organ and
tissue in the human body. When an infected tick bites a human, the bacteria take
advantage of the tick salivary gland secretions that numb the skin to delay an acute host
inflammatory reaction, and penetrate the skin undetected by the host immune system to
disseminate throughout the body (Fig. 1). Within a week, the bacteria can embed in
joints, muscles, the heart and brain.25,26 Presently, 70% of untreated Lyme disease
victims suffer the effects of bacterial dissemination and infection of the various
organs.25,26 While these manifestations rarely result in fatality, chronic symptoms can
persist that severely impact both the quality of life for the individual and the burden on
the overall healthcare system making Lyme disease a serious public health problem. We
know that upon entering the host B. burgdorferi disseminate via the bloodstream to cause
widespread infection of host tissues. However, there is great concern about our lack of
understanding of how B. burgdorferi actually migrate to sites within the body, causing
disease and sometimes persistent, treatment-refractory conditions.27–29
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Figure 1. Host vectors of the Lyme disease pathogen B. burgdorferi, and susceptible organ systems in an infected human.
1.1.2 B. burgdorferi morphology and motility
Borrelia burgdorferi are highly invasive30 spirochete bacteria that cause multi-systemic
Lyme disease if not appropriately treated with antibiotics.31,32 Spirochete bacteria are
known for distinct motility and long, skinny, sinusoidal morphology resulting from internal
flagella (Fig. 2).
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Figure 2. Confocal microscopy image of GFP-expressing B. burgdorferi. (A) Bacteria flowed through microfluidic system at 0.75 dyn/cm2. (B) Bacteria in phosphate-buffered saline on a glass slide.
B. burgdorferi are ~20 µm in length by ~0.3 µm in diameter,33 and have a flat-wave
morphology33,34 (wavelength ~3.2 µm, amplitude ~0.8µm).33 The main components of
the bacterium include an elastic inner cell body (Fig. 3: protoplasmic cell cylinder)
bounded by a cell membrane that is surrounded by a flexible outer membrane. A
periplasmic space (20-40 nm thick) exists in between the inner cell membrane and outer
membrane, where internal flagella reside, (Fig. 3).
There are 7-11 internal flagella attached at either end of the cell body within the
periplasmic space that wrap around the cell body in a helical structure, and bend back
Figure 3. Longitudinal schematic of B. burgdorferi. (Reprinted with permission, Charon, NW, et al. The unique paradigm of spirochete motility and chemotaxis. Annual Rev Microbio 66 (2012). 349-70.)
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towards opposite ends of the cell, partially overlapping in the central region, causing the
elastic cell body to bend into a planar sinusoidal waveform,33,34 (modeled in Dombrowski,
et al. 2009 and Vig & Wolgemuth, 2012).10,35 Rotation of the flagella result in spirochete
motility,8,36,37 with each flagellum attached to its own motor and through the flow of
charge, adjacent motors coordinate rotation on respective ends of the cell to produce
torque,10,34,38–40 resulting in traveling waves along the cell body and in turn, translocation.
1.1.3 Life dominated by viscosity
The cardiovascular system serves as the expressway for B. burgdorferi to efficiently
navigate to target host tissue, and as such, mechanics play a major role in terms of
hydrodynamic forces, adhesive forces, and transport behavior.41 B. burgdorferi are
proficient at countering shear stress due to blood flow to in turn adhere to endothelial
surfaces and transmigrate without being eliminated by immune cells. These bacteria
penetrate the endothelial barrier predominantly in the postcapillary venules,42 where the
shear force is typically ~1 dyn/cm2. Relative to the average swimming velocity of B.
burgdorferi in the absence of fluid flow,7,34 the blood flow velocity is about three orders
of magnitude greater. However, since these swimming microorganisms live at very small
Reynolds numbers (Re)f ~10-3,41 the inertial effects of blood flow play no part in motility;
instead the bacteria must rely on mechanical motion via motorized flagella for net
displacement. This swimming capability of B. burgdorferi is a key distinguishing feature
from leukocytes that may explain differences in extravasation mechanisms despite
having several similar initial steps in hematogenous dissemination (discussed later on).
f Reynolds number compares the magnitudes of inertial and viscous forces in a given flow, where 𝑅𝑒 =𝜌𝑈𝐿/𝜇, and 𝜌= fluid density, U= fluid speed, L= bacteria length, and µ= fluid viscosity.
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1.2 Endothelial cells
1.2.1 Background
Endothelial cells line the inside of blood and lymphatic vessels, and are crucial for barrier
integrity between the vessel lumen and surrounding tissue. Endothelia also play major
roles in hemostatic maintenance, blood flow rheology, permeability, and trafficking
surveillance of immune cells and microorganisms that navigate through the
vasculature.43 Endothelia are constantly subjected to hemodynamic forces from blood
flow,44 with different flow patterns and rates dictated by location within the vascular
system. These heterogeneous biomechanical forces, namely due to shear stress,
influence all aspects of endothelia, from structure and function43,45–47 to gene expression
to crosstalk interactions with molecular and cellular structures encountered at the surface
(Fig. 4).
Figure 4. Select phenotypic differences between vascular endothelial cells. VVOs: vesiculo-vacuolar organelles, which provide extravasation routes for macromolecules. (Reprinted with permission, Aird, WC. Phenotypic heterogeneity of the endothelium. Circ Res 100 (2007): 158-73.)
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Endothelia from different vascular beds express unique proteins, but two common
markers for endothelial boundaries are platelet/endothelial cell adhesion molecule
(PECAM)-1 (also known as CD31),48 and vascular endothelial (VE)-cadherin,49,50 which
serve as target validation markers in vitro to ensure endothelial integrity.
Structurally speaking, endothelia exposed to high laminar shear stress levels, such as in
arteries, elongate and align with blood flow; contrarily, in capillaries and veins, endothelia
have a cobblestone appearance (reviewed thoroughly in Aird 2007a).43 That said,
cultured endothelia can alter their morphology and orientation when exposed to various
shear stresses within in vitro flow chamber systems, as exemplified in Figure 5 from
Galbraith et al., 1998,51 due to spatial reorganization of the cell cytoskeleton. Such
morphological changes can affect endothelial functionality, such as transmigration
efficiencies.
Figure 5. Time-lapse images of actin filaments within an endothelial cell monolayer exposed to 15 dyn/cm2, illustrating cell alignment with flow direction by 24 h. (Reprinted with permission, Galbraith, CG, et al. Shear stress induces spatial reorganization of the endothelial cell cytoskeleton. Cytoskeleton 40 (1998): 317-30.)
Endothelial functionality is variable and caters to the needs of the underlying tissue. In
postcapillary venules specifically, inducible permeability and trafficking of leukocytes52
and blood-borne pathogens53 predominantly occur, due to a relative abundance of
transport-related organelles (e.g., caveollae and vesiculo-vacuolar organelles, VVOs)
and low shear stress levels (≤3 dyn/cm2).43,47
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1.2.2 Shear stress effects on transendothelial migration
Endothelial cells play an active role in cell passage across vascular barriers, as
demonstrated with leukocyte diapedesis.54–58 Transmigration is commonly a multi-stage
process, as seen with leukocyte migration, tumor cell metastasis, stem cell homing, and
endothelia-pathogen dissemination interactions, (Fig. 6).
Figure 6. The stages of leukocyte transendothelial migration. (Reprinted with permission, Vestweber, D. How leukocytes cross the vascular endothelium. Nat Rev Immun 15 (2015): 692-704.)
In the early 1990s, adherent neutrophils were shown to trigger a signaling cascade within
the endothelium that promoted passage through the vascular barrier.59 This seminal
discovery demonstrated that endothelial cells play an active role in facilitating migration
of cellular structures across the barrier. Soon after, many more endothelial surface
markers were implicated in adhesion and transmigration,56,57,60,61 including PECAM-1,62
VE-cadherin,63 intercellular adhesion molecule 1 (ICAM-1),64 vascular adhesion
molecule 1 (VCAM-1),64 junctional adhesion molecules (JAMs),65 CD99,66 and
endothelial cell-selective adhesion molecule (ESAM).67 Transendothelial migration is
regulated by different regions of the apical surface and intercellular junctions, which are
sensitive to cell stiffness68 and shear stress, which has been shown to initiate
phosphorylation and internalization of proteins, such as VE-cadherin69,70 to increase
vascular permeability. Hemodynamic forces were also identified as being essential for
mechanosignaling via endothelial cytoskeletal restructuring, to promote surface
adhesion sites and transient passage through the vascular barrier.61,71–74
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1.3 Bacterial-host cell interactions
1.3.1 Applicable insights from leukocyte emigration
Hematogenous dissemination of spirochetes is similar to that of leukocytes in many
ways, 53,42,75,76,52 as illustrated in Figure 7.
Figure 7. The multistage process of B. burgdorferi transendothelial migration. (Reprinted with permission, Norman, M, et al. Molecular mechanisms involved in vascular interactions of the Lyme disease pathogen in a living host. PLoS Pathog 4 (2008): e1000169.)
The initial onset of dissemination, occurring predominantly within the postcapillary
venules, serves as a means for the bacterium/leukocyte to slow down and counter the
shear force of blood flow. Both cell types engage in an initial transient tethering step
followed by a longer lasting rolling (leukocyte)/dragging (bacterium) phase. Leukocytes
are recruited during acute or chronic inflammatory conditions through chemical signaling
via chemokines, and guided by selectin proteins expressed on the endothelial surface.
Following the rolling phase, integrins expressed on the leukocyte surface target
endothelial receptors like ICAM-1 or VCAM-1 in order to arrest, a precursor step to the
crawling phase. While crawling, leukocytes are directed towards an attractant, either
chemical (chemotaxis)56,61 via chemokines, or mechanical68,77 through intracellular actin
arrangements that produce desirable cell stiffness to aid in adhesion.
B. burgdorferi utilize a similar mechanism to stabilize along the vascular wall, but through
different molecular components. The bacterium initiates tethering and dragging steps
through adhesion proteins like BBK3278 that bind to host fibronectin and
glycosaminoglycans42,75,78,79 to foster stationary adhesion.
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Prior to the final stage of transendothelial migration, both the bacteria and leukocytes are
secured along the vascular wall through a force-dependent catch bond mechanism.41,79–
82 At this point, cell shape is altered to facilitate strong adhesion and in turn, endothelial
penetration; leukocytes flatten-out their circular shape into a more motile and polarized
form, and B. burgdorferi rotate from an edge-on to flat orientation79 to increase surface
area exposure to endothelia. The final stage in hematogenous dissemination
(extravasation), occurs predominantly through paracellular routes,42,64,83–86 but
occasionally via transcellular means.61,87–89 Cellular stiffness is thought to influence
transmigration routes, based on a theory that leukocyte diapedesis is dictated by the
least resistant pathway.90 Also, leukocytes with impaired crawling capabilities have
shown a preference for the transcellular pathway.56,68
Endothelial cells are polar91 and express proteins asymmetrically during
transmigration,92 which could explain differences seen in vitro in B. burgdorferi
transmigration rates initiated from the apical versus basal sides of the endothelium.93
Still, this final phase of emigration for both cell types is the least understood. There have
been numerous recent findings in molecular mechanisms that guide leukocyte
transendothelial migration,56,60,61 and will likely provide new insights into the B.
burgdorferi extravasation mechanism(s). For this reason, experimental models used for
leukocyte transmigration studies have greatly influenced designs for investigating
endothelial-bacteria interactions.94,95
1.4 Existing experimental models of bacterial transmigration
1.4.1 Static in vitro studies
Static models of transendothelial migration provided original insight into B. burgdorferi
transport kinetics,87–89,93,96 and identified expression of adhesion factors on host and
pathogen surfaces that facilitated barrier penetration.97 There is, however, empirical
discrepancies from the early transmigration studies regarding whether B. burgdorferi
predominantly transmigrate via paracellular42 or transcellular87–89,96 routes, namely due
to differences in experimental setups. These initial studies observed bacterial
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interactions with endothelial cells grown to confluence overnight on tissue culture treated
plastic surfaces, under static conditions.89,93,96 In this model, B. burgdorferi adhesion to
and internalization by endothelial cells increased with time (from 24 to 48 hours), with
adhesion occurring ~1.3-fold more often than internalization, and the latter requiring
actin-polymerization within endothelia.89 B. burgdorferi was reported to have degraded,
however, when internalization was not merely transient. Consistently observed across
studies though, was a 2-fold increase in the number of bacteria adhered to the
endothelial monolayer when comparing a 2 hr versus 4 hr coincubation period. There is
also universal consensus that particular outer surface bacterial proteins, yet to be
identified, were crucial in endothelial adhesion, and that the mechanisms for adhesion
and internalization were distinct but not necessarily independent.
Subsequent B. burgdorferi transendothelial migration studies extended the static well
plate model to incorporate porous membrane (Transwell) inserts upon which endothelial
cells were grown to establish a monolayer through which bacteria could migrate from the
input chamber to the collection well. It is important to note that endothelial monolayer
integrity was not rigorously evaluated during these experiments, potentially
misrepresenting the transmigration rates. For example, in Comstock & Thomas, 1989
and 1991, trypan blue was used to evaluate endothelial cells,87,88 but this dye only
evaluates cell viability, not cell health nor monolayer integrity, which are crucial
components for a transmigration study. While the 1989 study did incorporate
transendothelial electrical resistance (TEER) measurements to measure integrity of the
endothelial monolayer, the target used to establish confluency: 13 Ω·cm2, was not
compared to an already established value for endothelial confluency, and the number of
days permitted to establish confluency was not specified in the methods. As a reference
point, it has been shown that endothelia permitted to achieve confluence over a 48-72 hr
period in culture can generate TEER values up to 37 Ω·cm2.98 Control experiments were
performed with heat-killed B. burgdorferi at 60˚C to test if the endothelial monolayer
prevented diffusion of dead bacteria (implying an intact barrier), but I have observed that
bacteria lyse at temperatures above 50˚C (unpublished data), preventing conclusions
about their locations within the Transwells. Critiques aside, after a 2 hr coincubation
period with primary endothelial cells, an average 3.6% of the initial number of B.
burgdorferi were identified in the collection well via dark-field microscopy (DFM),87 and
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after 4 hr, 7.5-9.6% via DFM (depending on the study87,88 and bacterial strain) and 7.7%
via radioactivity measurement of labeled B. burgdorferi.87
These in vitro studies serve as the foundation for B. burgdorferi transport kinetics through
an endothelium. However, as noted previously, extravasation is a highly dynamic
process that involves shear stress activated endothelia.61,73 Incorporating physiologically
relevant hemodynamic forces into an in vitro model would cultivate an endothelium that
better mimics in vivo conditions,99,100 allowing for better mechanistic dissection of
transendothelial migration.
1.4.2 In vivo extravasation studies
Mouse models infected with B. burgdorferi have greatly elucidated bacteria-host cell
interactions within the vasculature via real-time intravital microscopy.42,83,101,102 These
studies identified molecular and biomechanical similarities between B. burgdorferi and
leukocyte hematogenous dissemination.42,52,75,83 Additionally, it was shown that the
spirochete bacterium traverses the endothelial barrier via paracellular means ~70% of
the time,42 and that endothelial penetration can occur in less than a second, but similar
to lymphocyte transendothelial migration,103 complete passage through the barrier takes
an average 10 min, during which time much remains unknown. Intravital microscopy
experiments pose several challenges though. Capturing live transmigration was
extremely rare: ≤3 transmigrated bacteria at each of 10 time points over a 20 hr period.83
Additionally, when comparing wildtype and experimental strains of bacteria in these live-
mouse models, only 1-2 transmigrated bacteria were observed by 24 hr for either strain,83
despite inoculating mice with 102-106-fold higher concentrations of bacteria than typically
measured in humans with Lyme borreliosis.104,105 Hence, there is a need for in vitro
systems that can capture complete transmigration events much more frequently, in a
controlled but physiologically relevant setting.
In summary, we know that endothelial adhesion is a precursor step to B. burgdorferi
transendothelial migration. Static in vitro models involving various setups have
comprehensively shown that B. burgdorferi are capable of penetrating tissue types of
varying density from extracellular matrix, to harvested amnion membranes, to endothelial
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monolayers via transcytosis and intercellular routes. Motility also appears to be
necessary for transendothelial migration.88,89 Furthermore, endothelial cells have been
shown to facilitate transcytosis through cytoskeletal remodeling.89 Drawing from the
various advantages of past models, the logical next step in characterizing bacterial
extravasation is the development of an in vitro system that frequently captures the highly
dynamic process under physiologically relevant conditions, thereby providing
substantially more data for mechanistic analysis.
1.4.3 Microfluidics appeal
1.4.3.1 Advantages of microfluidics
Standard microfluidic flow chamber models, consisting of a polydimethylsiloxane
(PDMS) microchannel adhered to a glass substrate for endothelial cell growth, offer the
added advantage over static systems of generating laminar flow that yields predictable
shear stress on cell monolayers.106 Incorporating fluid flow into in vitro models of
representative organ systems such as the gut100 and circulatory system107 revealed
results that were unobtainable under static conditions and much more representative of
in vivo behavior. In consideration of the vascular system, in vitro models that support
the application of physiological shear stress enable endothelial phenotype, morphology
and functionality that closely resemble native structures,106,108,109 and have been used to
study shear stress-dependent aspects of pathogen interactions with the endothelium.
For example, using a flow chamber model to mimic hemodynamic shear stress, Harker
et al., 2014, illustrated that Toxoplasa gondii interactions with and penetration of
endothelia were enhanced under physiological shear stress conditions.110 Furthermore,
by incorporating shear stress into the model system, a key protein (MIC2) was identified
that mediates T. gondii adhesion. Ebady et al., 2016, through the incorporation of shear
stress via a flow chamber system, identified a catch-bond mechanism incorporated by B.
burgdorferi to initiate endothelial interactions,79 which may serve as a precursor to
transendothelial migration. While standard flow chamber microdevices are adequate
with their single channel to study cell surface interactions, their solid substrate hinders
bacterial transmigration and does not enable the visibility and access above and below
the endothelial barrier required for mechanistic studies.
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Multichannel microfluidic systems are more appropriate for extravasation
studies106,109,111 in that the channels can be designed and fabricated relatively quickly,
supporting microenvironments that better mimic in vivo anatomy and physiology. All
features of such systems are completely customizable, including: channel dimensions,
membrane components that separate channels, materials (e.g. fluid, gel matrix, etc.),
cell types, and flow rates inputted into designated channels. Furthermore, these systems
can be adapted to microscopy to support live cell imaging. Implementation of microfluidic
transmembrane systems exist in a wide array of biomedical applications as an invaluable
tool prior to in vivo studies.
1.4.3.2 Types of microfluidic transmembrane models
There are two types of microfluidic-based designs that have been implemented for
transendothelial migration studies,111,112 as illustrated in Figure 8. The main
distinguishing factors between these two types of systems are the orientation of the
endothelial monolayer, and the substrate that cells are cultured on.
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Figure 8. Schematic representations of membrane-based and extracellular matrix (ECM)-containing microfluidic devices for transmigration studies that support shear flow. (A) PDMS-based bilayer device that sandwiches a porous membrane cultured with endothelia. This type of system can support embedded electrodes for transendothelial electrical resistance. (B) PDMS-based side-by-side multi-channel system in which the central ECM-channel is sandwiched by parallel neighboring channels containing desired cell types. (Reprinted with permission, Bogorad, MI, et al. Review: in vitro microvessel models. Lab Chip 15 (2015): 4242-55.)
The first type of system (Fig. 8A) supports axial transmigration and is based on two
microchannels that sandwich a porous membrane cultured with a horizontal endothelial
monolayer.94,113,114 A second cell type can be co-cultured on the opposing side of the
membrane.100,115 Flow is typically introduced into the channel that generates shear
stress on the apical surface of the endothelia, (although flow is possible in both
channels). The other channel is typically maintained under static conditions with
whatever desired medium: fluid,94,114 gel-matrix,113 or even air.100,115 Advantages to this
system are the option of embedding electrodes for TEER measurements; adding
additional features on either side of the bilayer as the Ingber lab has done to impose
mechanical strain on the cell monolayer to simulate breathing in a lung model115 and
peristaltic motion in a gut model;100 and the means to compare to data from static models
that incorporate identical types of membrane (e.g. Transwells). Concerns about this style
17
of membrane system have been raised regarding the inability to perform live cell imaging
(namely due to opaque membrane materials, which were previously the only available
option),111 and effects of gravity on transmigration rates,95 but the model we developed
in this thesis addressed both issues and will be discussed in Ch.4.
The second type of system (Fig. 8B) supports transmigration in the lateral direction, and
is based on multiple side-by-side channels in which the central channel mimics the
extracellular matrix (ECM), and an endothelia monolayer is established on the vertical
wall adjacent to one side of the ECM channel, where PDMS pillars line the channel
boundary to prevent ECM leakage. The channel on the opposite side may contain
another cell type, a chemoattractant, etc., and the ECM may be co-cultured with a second
cell type. These types of systems are popular for modeling angiogenesis and cancer cell
migration,112,116,117 as well as leukocyte migration.95 The advantage to this system is that
a porous membrane is not necessary to establish a cell monolayer. However, the pillars
are a design limitation by serving as barriers to transmigration, due to the ≤200 µm
separation distance requirement to prevent ECM leakage.111
1.4.3.3 Importance of endothelial cell confluency in transmigration models
A fully confluent endothelial monolayer is crucial for the viability of these systems, to
ensure that transmigration is not occurring through holes within the monolayer. While
the spatial resolution of imaging technologies has improved drastically over the years,
this type of qualitative measure is not sufficient as a standalone means to evaluate
endothelial monolayer integrity. Several alternative techniques have been incorporated
into these transmembrane devices to quantitatively monitor endothelial integrity prior to
and during an experiment, including endothelial viability dyes (e.g. Calcein AM),94,118–120
which do not actually address confluence, permeability tests,114 submicron microsphere
analysis (as performed in this thesis), and TEER measurements99,119 via embedded
electrodes. TEER measurements are considered the gold-standard for confluence
evaluation in blood-brain barrier models, and are therefore a desirable feature in
microfluidic systems. However, considering electrode sensitivity to noise and placement,
each TEER-based system needs to establish its own target value for comparison sake
18
when validating endothelial confluence, and this is not always correctly done.93,119 Post-
confluent endothelial cultivation in vitro up to 48 hours has also been shown to greatly
improve maturation of the monolayer and the intercellular junctions.99,121 With respect to
B. burgdorferi dissemination, culturing endothelial cells to two days post-confluence had
the added benefit of reproducing interactions rates79 comparable to in vivo studies within
the post-capillary venules.42,83
1.4.3.4 Requirements for a microfluidic-based extravasation model
To complete our understanding of B. burdorferi extravastion, we need a model that fully
captures bacteria entering and exiting the endothelial barrier, but most importantly, under
physiologic shear stress conditions. There is substantial evidence that in vivo findings
can only be recapitulated in in vitro systems that include physiological shear stress
conditions.94,95,112,115–117,122 The Simmons lab developed a microfluidic transmembrane
device as a physiologically relevant in vitro model to evaluate endothelial permeability,114
monocyte extravasation,94 and shear-mediated endothelial paracrine signaling,113 and in
all cases, new insights were gained as a result of shear stress exposure. For example,
Srigunapalan et al., 2011 showed an increase in monocyte adhesion and diapedesis
directly in response to shear stress conditions.94 The Kamm lab investigated shear
stress effects on cancer cell extravasation using a microfluidic model and revealed that
physiologic shear stress levels had a 1.5-fold decrease in extravasation rates, a 2.4-fold
decrease in endothelial cell permeability, and further penetration of cancer cells into the
surrounding matrix when compared to static conditions.116
In this thesis, I adapted the Simmons lab transmembrane microfluidic device to model
and image in real-time B. burgdorferi transendothelial migration under conditions that
mimic key aspects of the native microvascular environment. Ultimately, this model is
expected to provide insight into the extravasation mechanism of not only B. burgdorferi
but also other blood-borne pathogens, thus serving as a means for developing
improved therapeutics and preventative measures targeting infectious diseases of
worldwide significance.
19
Thesis Objectives
2.1 Overall objectives
To develop an imaging compatible microfluidic system that recapitulates spirochete
transendothelial migration under physiological flow conditions, as a means to study
the dynamics and mechanisms of B. burgdorferi extravasation.
2.2 Research Hypotheses
(1) A microfluidic system can mimic key features of the vascular environment
(including a confluent endothelial monolayer and relevant shear forces) to study
the B. burgdorferi extravasation mechanism.
(2) A microfluidic transmembrane system can support live cell imaging of B.
burdorferi extravasation and provide a comprehensive analysis of
transendothelial migration kinetics.
2.3 Research Aims
2.3.1 Aim 1
To develop an optically transparent microfluidic transmembrane device that enables
real-time visualization of B. burgdorferi interacting with and migrating across a fully
confluent endothelial barrier. This aim required the following components:
• refined fabrication techniques to generate repeatable and representative data;
• development and maintenance of a fully confluent endothelial monolayer, to
ensure transmigration occurred through trans- or paracellular routes, and not
through holes in the monolayer;
• device flexibility such that input and collection channels could be independently
accessed or manipulated;
20
• an imaging protocol to capture full depth of both channels within a single 3D
image;
• support of both static and fluid flow conditions, in order to investigate shear stress
effects;
• development of a repeatable and accurate automated counting protocol to
objectively quantify transmigration kinetics over time.
2.3.2 Aim 2
To validate the microfluidic system as a model for transendothelial migration by
verifying that transmigration kinetics obtained from the microfluidic system under
static conditions were comparable to gold standard in vitro methods. This aim
required the following components:
• statistical comparison of bacterial transmigration kinetics under static conditions
between the novel microfluidic system and Transwell plates (a common
traditional in vitro model);
• statistical comparison of transendothelial migration kinetics under static
conditions within the microfluidic system between B. burgdorferi and
microspheres of comparable diameter.
2.3.3 Aim 3
To evaluate the applicability of the model system to investigate shear stress effects
on bacterial extravasation. This aim required comparison of transmigration rates
between B. burgdoferi and microsphere beads under a physiologically relevant shear
stress condition.
21
Microfluidic Model of Spirochete Transendothelial Migration
3.1 Introduction
Systemic dissemination of pathogens via the cardiovascular system is associated with
most mortality due to bacterial infection. Many disseminating bacteria can interact stably
with vascular surfaces, even in the face of blood flow-induced shear stress, and migrate
out of vessels to extravascular tissues, an invasive process referred to as
extravasation.123–125 Pathogen extravasation can establish secondary sites of infection
in critical organs such as brain, heart and liver, as well as many other tissues including
bone and joints.125
Live imaging in animal vasculature (intravital microscopy, IVM) has provided important
insight into the dissemination and extravasation mechanisms of several
pathogens.42,83,75,78,102,101 A key advantage of IVM permits observation of individual
extravasating pathogens in real-time under native shear stress conditions. However, IVM
is time-, labor- and cost-intensive. Since pathogen extravasation is a rare event (e.g.,
<0.1% of bacteria-endothelial interactions in postcapillary venules42,83), studying this
process in vivo requires intravenous injection of large numbers of microbes, which can
induce rapid inflammatory responses associated with changes in cardiovascular function
and blood flow.126 Furthermore, intravascular clearance of microbes by blood-filtering
organs such as liver can make it challenging to study extravasation independent of the
confounding effects of immune clearance.127 Developing in vitro tools to study bacterial
extravasation under physiological shear stress conditions would facilitate mechanistic
studies of this important step in infectious disease progression.
One disseminating pathogen that has been studied quite intensively in the vascular
environment is Borrelia burgdorferi, a highly motile blood-borne bacterium with a flat sine
wave morphology that can invade many organs and tissues,128 resulting in Lyme disease.
Advantages of studying B. burgdorferi as a model organism include a fully sequenced
genome, ease of culturing unlike its toxic syphilis-causing spirochete counterpart
Treponema pallidum, an ability to traverse the endothelium without causing damage, and
22
similarities to other circulating cells regarding hematogenous dissemination mechanisms
that suggest potential universal applications from studying B. burgdorferi extravasation.
The earliest studies of B. burgdorferi extravasation examined bacterial transmigration
across endothelial monolayers cultivated under static conditions,18,87,96,129 often on
porous Transwell membranes.18,87,129 Subsequent IVM studies examined interactions
with and extravasation in postcapillary venules in skin, joints and liver, and found that
extravasation is rapid (<150 ms to penetrate endothelial lining of vessels, ~10 min to fully
escape), and depends on bacterial motility.42,75,78,83,101 Additionally, B. burgdorferi
dissemination and associated bacterial molecules have been studied in population
spreads of bioluminescent bacteria via whole body imaging,130,131 intravenous phage
display approaches for identifying candidate bacterial adhesion molecules,132 and
quantitative PCR-based monitoring of bacterial association with host tissues in short-
term intravenous inoculation models.133,134 More recently, flow chamber-based live cell
imaging systems that recapitulate B. burgdorferi-vascular interaction properties in vivo
have been used to determine that initial interactions are stabilized by a catch bond
mechanism as shear stress increases,79,135 and to identify novel host and bacterial
molecules supporting endothelial interactions of different spirochetes including Borrelia
species and T. pallidum.136,137 In vivo studies found that B. burgdorferi extravasation
rates depend on the vascular bed,42,83,101,102 suggesting unique mechanisms for
particular tissue types that vary greatly in endothelial cell properties and shear stress
conditions.47 It would be invaluable to have tools that could dissect extravasation
mechanisms for specific endothelial cell types under controlled environments.
Microfluidic models of the vasculature are well-suited to this end, as they can be
configured to model extravasation under flow. Leukocyte and circulating cancer cell
transendothelial migration have been studied in self-assembled 3D microvascular
endothelial networks138,117,116,139 or in side-by-side microchannels,95,140–144 in which cells
migrate from one channel across a vertical endothelial monolayer into a second channel
containing a hydrogel. While microvascular networks mimic many aspects of in vivo
vasculature, their geometric complexity prevents precise control over shear stress and
hinders imaging at the spatiotemporal resolution necessary for real-time visualization of
bacterial transmigration. Side-by-side platforms address many of these limitations owing
to their planar geometry, but hinder real-time evaluation of endothelium confluency and
23
disrupt endothelial barrier integrity due to posts required for hydrogel retention within the
central channel.
An alternative microfluidic configuration sandwiches an optically transparent, porous
Transwell-like membrane between two microchannels (Fig. 9A). An endothelial
monolayer is cultivated on the membrane and medium containing circulating cells is
perfused over the endothelial apical surface at precisely-controlled physiological shear
rates. Cells migrating from the input channel through the endothelium into the collecting
channel can be imaged through a thin coverglass base. To date, this device design has
been used to study transendothelial migration of cancer cells120 or leukocytes,94,115 which
are relatively large, slow-moving, and tend to associate with the endothelium after
extravasation. In contrast, extravasating bacteria are small, fast-moving, and free-
swimming, and therefore require confocal microscopy approaches that enable high
spatiotemporal resolution through the entire depth of the collection channels for accurate
quantification. The goal of this study was to establish a physiologically relevant
microfluidic model, and real-time image acquisition and analysis methods that permit
accurate, automated counting of small, motile bacteria during transendothelial migration
as a means to dissect the extravasation mechanisms.
3.2 Methods
3.2.1 Transmembrane device design and fabrication
As previously described,94,113 device microchannels (input: 2.5 cm x 2 mm x ~200 µm,
overlapping region of collection: 2 cm x 2 mm x 500 µm, LxWxH) were fabricated from
polydimethylsiloxane (PDMS, 10:1) (Sylgard 184, Dow Corning, Midland, MI USA) using
standard soft lithography. Input and collection microchannels were fabricated using
molded SU-8 (SU-8 50, Newton, MA USA) and aluminum masters, respectively. After
overnight curing at 65-70 °C and insertion of holes for inlet and outlet tubing, trimmed
and cleaned microchannel slabs were bonded to a track-etched, transparent
polyethylene terephthalate (PET) membrane with 3 µm diameter pores obtained from
Transwell chambers (Falcon, Corning/VWR International, Mississauga, ON Canada)
using PDMS:toluene mortar (5:4). Mortar vortexed 5 min in a glass vial was spin coated
24
(65 s at 1500 rpm) onto a clean glass slide (50 mm x 75 mm), microchannel slabs were
mortar-stamped for 1 min before assembly with the PET membrane, and devices were
dried under weight (~2 kg) at room temperature (RT °C) for 3 d, followed by bonding of
No. 1 cover glass (24 mm x 60 mm; ThermoFisher Scientific, Ottawa, ON Canada)
plasma treated for 1 min (PE-100 Plasma System, Plasma Etch Inc., Carson City, NV,
USA) to the device bottom. PDMS adaptors for tubing (PE-190, i.d. 1.19 mm, o.d. 1.7
mm; Intramedic Clay Adams/Becton Dickinson, Mississauga, ON Canada) inserted into
channel ports were anchored to device surface by plasma treatment, application of
viscous, semi-cured PDMS, and drying at RT °C.
3.2.2 Cultivation of endothelial cells and preparation for imaging
Before seeding with endothelial cells (ECs), device channels were ethanol-sterilized and
coated with 160 µg/ml bovine plasma fibronectin (bFn; Sigma-Aldrich Canada, Oakville,
ON) for 2 h as described,94 followed by incubation at 37°C/5% CO2 for 1 h. Early passage
(maximum 4 passages) primary human umbilical vein endothelial cells (HUVEC;
Clonetics/Lonza, Mississauga, ON, Canada) cultivated as previously described79 were
resuspended to 2x106 cells/ml in cultivation medium and injected into input channels to
achieve seeding densities of ~4x104 cells/cm2. Medium was replaced at 8 h and every
12 h thereafter until 2 d after cells reached confluence (3-4 d total). Immediately before
imaging, endothelia were labeled with CellMask Deep Red (649/666 nm) plasma
membrane live cell imaging dye (ThermoFisher) as described,79 both channels were
flushed with 37°C Hanks buffered saline (HBSS; ThermoFisher) containing 10% heat-
inactivated fetal bovine serum (FBS; Sigma), and collection channel ports were plugged
with vacuum grease. Transwell chambers incorporating the same membrane used in
microfluidic devices were coated with bFn as described above, seeded with 1x106
HUVEC (~4x104 cells/cm2) and cultivated to 2 d post-confluence with daily medium
replacement (3 d total). Endothelia for Transwell experiments were not fluorescently
labeled.
3.2.3 Preparation of B. burgdorferi and beads for imaging
As described,79 GFP-expressing B31-derived ML23 infectious GCB966 Borrelia
burgdorferi78,145 was cultivated, prepared for imaging, and resuspended to 4x107/ml in
25
37°C HBSS/10% FBS. Bacteria were counted in Petroff-Hausser chambers (Hausser
Scientific 3900, ThermoFisher). Before device injection, 2% w/v 0.22 µm 580/605 nm
fluorescent carboxylate-modified microspheres (ThermoFisher) were vortexed 1 min,
diluted to 4.5 x 108/ml in 37°C HBSS/10% FBS, vortexed 1-2 min, and mixed 3-5 times
with a syringe and 18G needle.
3.2.4 Immunofluorescence microscopy
HUVEC monolayers rinsed with 37 ˚C magnesium- and calcium-containing phosphate-
buffered saline (PBS+/+; ThermoFisher) were fixed in ice-cold methanol for 15 min at -20
˚C, rinsed with magnesium- and calcium-free PBS (PBS-/-; ThermoFisher), blocked 20
min 37 ˚C in PBS-/- containing 3% w/v bovine serum albumin (BSA; Sigma), incubated
37 ˚C 1 h with 3 µg/ml anti-VE-cadherin polyclonal antibody (Abcam, Toronto, ON
Canada, Cat. ab33168) in PBS-/-/3% BSA, washed with 5 ml PBS-/-, blocked 30 min RT
°C with 10% heat-inactivated goat serum (Sigma) in PBS-/-, then incubated 1 h RT°C in
darkness with 0.025 µg/ml Alexa Fluor 488-conjugated goat anti-rabbit IgG antibody
(ThermoFisher) in PBS-/-/10% goat serum, washed with 5 ml PBS-/- then 5 ml distilled
water, mounted in Lerner Aqua-mount Mounting Medium (ThermoFisher) and stored 4˚C
in darkness until imaging. VE-cadherin immunofluorescence was visualized using a
Leica SP8 confocal microscope (Leica Microsystems, Wetzlar, Germany) in conventional
scanning mode, with 25X 0.95 NA objective (1.5X zoom), 0.36 AU pinhole, HyD detector
(100 gain), x10 frame averaging, at 488/499-742 nm (ex/em).
3.2.5 Static Transwell experiments
One ml 37 °C incubation medium (HBSS/10% FBS) containing 4x107 bacteria (3
independent cultures) was added to HUVEC-coated transmembrane inserts (“input”) and
1 ml incubation medium alone was added to wells (“collection”), followed by 37 °C/5%
CO2 incubation for duration of experiments. Every 30 min 100 µl samples from input and
collection wells were transferred to a 96-well plate containing triplicate 2-fold serial
dilutions of known numbers of GCB966 bacteria in incubation medium (“standards”:
range: 7.8x103-4x106 bacteria) and fluorescence intensities were measured using a
Clariostar Monochromator Microplate Reader (BMG Labtech, Guelph, ON Canada).
After subtracting background fluorescence of incubation medium, numbers of bacteria in
26
samples from input and collection wells were calculated from lines fit to the linear signal
region for standards (R2>0.99). Transmigration was calculated as the percentage of all
bacteria (input and collection samples combined) in collection channels.
3.2.6 Microfluidic transmembrane device experiments All equipment except syringe pumps used for injection/perfusion (models: NE-1000, NE-
300; New Era Pump Systems, Farmingdale, NY USA) was placed on the microscope air
table, and ambient temperature was maintained at 29° C throughout experiments using
a heat lamp. Bacteria or beads were initially injected at 3.7 ml/h using a 20 ml syringe
(Norm-Ject LS; ThermoFisher) connected to primed Tygon tubing (formulation 2375, i.d.
1.59 mm, o.d. 3.18 mm; VWR). For static experiments, input channel ports were sealed
after injection with vacuum grease. 3D datasets (z-series) encompassing the full depth
of input and collection channels were immediately acquired at 3 non-overlapping
positions (technical replicates) at the midpoint of input channels (t= 0 h) to measure input
channel height. Flow rates, Q [cm3/s], required to achieve wall shear stress,𝜏+=1
dyn/cm2 at endothelial surfaces were calculated from the channel width, W = 2 mm, and
average input channel height, H [µm], calculated from triplicate measurements, as
described:146
where 𝑚 = 1.7 + 0.5 3+
45.6; n = 2; and
viscosity, µ = 8.705 x 10-3 dyn s/cm2.
Z-series encompassing the full depth of devices were acquired at 3 positions/timepoint
over 4 h, then triplicate z-series were captured under static conditions to count total
bacteria in input and collection channels (tendpoint). Z-series with a depth of ~800 µm were
acquired simultaneously in green (bacteria: 500-520 nm), orange (beads: 572-620 nm)
and dark red (endothelia: 650-770 nm) channels (488, 561, 633 nm lasers, respectively)
in 512 x 512 pixel bidirectional resonant mode (gain 100, pinhole size 1.0 AU), using a
Leica upright SP8 tandem scanner spectral confocal microscope equipped with HyD
detectors, a 25x 0.95 NA long working range water-immersion objective, and Leica
acquisition software (LAS). Pixel and voxel dimensions were respectively (0.607 µm)2
and ~0.73 µm3 for bacteria (1.5X zoom, 1.98 µm z-step size), and (0.182 µm)2 and ~0.03
µm3 for beads (5X zoom, 0.99 µm z-step size). Image acquisition frame rates in xy were
~26 fps, but in z were ~7 fps due to time required for axial repositioning. Total z-series
𝑄 = 𝜏+(𝑊𝐻;)2𝜇
>𝑚
𝑚 + 1? @
1𝑛 + 1
B,
27
acquisition times for bacteria and beads were ~1 and 2 min, respectively.
3.2.7 Automated object quantification in z-series Bacteria and beads were counted in input and collection channels at t=0 and tendpoint, and
in collection channels only at intervening timepoints, using surface volume (grain size=
0.7 µm, min intensity= 40, min volume= 10 µm3) and spot (xy= 0.65 µm2, min intensity=
53) tools, respectively and IMARIS software v.8.3.1 (Bitplane AG, Zurich, Switzerland).
Minimum intensity values for object counting were determined by measuring average
background intensity in devices before injection of bacteria and beads. Images used for
quantification were not subjected to post-processing. Mean fold differences in object
numbers measured by automated quantification compared to known numbers of input
bacteria and beads were respectively 1.12 ±0.22 and 1.11 ±0.42 (SD). Objects were
assigned to the collection channel if their centroid position lay below the z-plane marking
the bottom of the endothelial monolayer, defined using the ortho slicer tool. Objects with
centroids above this plane were assigned to the input channel. Transmigration was
calculated as the number of objects in the collection channel expressed as a percentage
of total objects counted in input and collection channels at tendpoint. Best fit transmigration
rate curves were obtained by linear regression (timepoints 0-4 h and 1-2.5 h for static
and flow experiments, respectively).
3.2.8 Statistical analysis
Statistical analysis and linear regression curve-fitting were performed in GraphPad Prism
v.7.0 (GraphPad Software, La Jolla, CA USA) using tests indicated in figure legends.
3.3 Results and Discussion
3.3.1 Design of microfluidic transmembrane device to study bacterial extravasation
To study bacterial extravasation under physiologically relevant conditions, a thin, porous,
optically transparent polyethylene terephthalate (PET) membrane was embedded
between two PDMS-based microchannels (Fig. 9A,B). This provided a compartmental
28
design enabling visualization in both channels, up to a depth of ~1.2 mm using a long
working range objective (Fig. 9A,B).
3.3.2 Assessment of endothelial barrier integrity in microfluidic transmembrane devices
Endothelial barrier integrity is critical to studying bacterial extravasation, because most
bacteria are very small (<1 µm diameter).41 The diameter of the B. burgdorferi cell body
is especially thin (~0.3 µm diam, ~0.8µm amplitude).33 As a result, establishing and
maintaining monolayer integrity is especially important for studying extravasation of this
pathogen. To monitor monolayer confluence during extended imaging experiments, two
day post-confluent monolayers99,121 (Fig. 9C, left) were stained immediately before
imaging with a live cell imaging plasma membrane dye (Fig. 9C, middle) that is non-toxic
to endothelia and does not disrupt B. burgdorferi-endothelial interactions under
physiological shear stress.79 Maintaining endothelia in a post-confluent state promotes
maturation and intercellular junction formation, as well as B. burgdorferi-endothelial
interactions under physiological shear stress conditions.79,99,121 The live cell imaging dye
permitted monitoring of monolayer integrity throughout experiments, and distinguished
between input and collection chambers in z-series acquired by confocal microscopy.
Monolayers visualized with this dye were similar to monolayers visualized by more
conventional, immunofluorescence-based staining for the adherens junction protein VE-
cadherin 50 (Fig. 9C right panel). We also confirmed that bacteria were uniformly
distributed in the axial planes throughout the input channel, suggesting no preferential
transport routes through the endothelial monolayer (Fig. 9D).
29
Figure 9. In vitro model to study endothelial transmigration of bacteria under physiological shear stress. (A) Microfluidic device, top view: PDMS input and collection channels sandwiching a porous, transparent membrane (blue box) coated with endothelia grown to 2 days post-confluence. White squares: imaging sites. (B) Cross-sectional schematic showing GFP-expressing B. burgdorferi (green) migrating from input to collection channels through endothelial monolayer stained with non-toxic live cell imaging plasma membrane dye (orange) and membrane (dashed black line). Red arrow: flow direction. At each imaging site, 3D z-series encompassing the full depth of input (~200 µm) and collection (~600 µm) channels were acquired at ~7 fps (~26 fps in xy) in 2 channels simultaneously, using a resonant scanning confocal microscope equipped with a high numerical aperture (NA) long working-distance (LWD) water-immersion objective. (C) Post-confluent endothelial monolayers in devices visualized by phase contrast microscopy (left: before experiments), resonant scanning confocal microscopy of live cells stained with plasma membrane (PM; middle: during experiments) and immunofluorescence (IF) staining for endothelial junction protein VE-cadherin in fixed cells (right: after experiments). Scale bars: 500 µm (phase contrast), 30 µm (PM, IF). (D) Representative maximum intensity projection image (MIP: left) and corresponding xy positions of bacteria (right: 25-75% interval boxplots) in the input channel from a 3D dataset captured under static conditions. Z-series were captured before experiments to measure input channel depth and calculate flow rates required to achieve shear stress of 1 dyn/cm2 at the endothelial surface, and confirm uniform distribution of bacteria.
3.3.3 Development of methods to detect and quantify transmigration of individual bacteria
B. burgdorferi extravasation is a rare event42,83 and studying this process requires
sensitive detection methods. Additionally, B. burgdorferi swims through liquid medium
30
at ~4 µm/s.34 Therefore, accurately quantifying transmigration of this motile bacterium
required the ability to perform simultaneous three-dimensional imaging of bacteria and
endothelia at image acquisition rates that were faster than bacterial swim speed. Using
a resonant scanner microscope equipped with a long working range objective and
multiple detectors, we were able to simultaneously visualize B. burgdorferi expressing
green fluorescent protein (GFP) and endothelia at 30 frames/s in xy dimensions, and ~14
µm/s (~7 frames/s) in the z dimension (Fig. 10A, left panel). Individual bacteria in input
and collection channels of devices were identified by volume-based object identification
(Fig. 10A, right panel).
To assess the sensitivity of imaging-based methods for enumerating B. burgdorferi, we
compared bacterial counts in devices to numbers of bacteria that could be measured by
a fluorescent plate reader, the standard method used for quantifying cellular
transmigration in conventional Transwell-based transmigration assays (Fig. 10B). This
comparison showed that imaging-based bacterial counting methods were >10,000 times
more sensitive than plate reader-based methods.
To determine the precision of imaging-based bacterial counting in microfluidic devices,
we compared covariance within technical replicates for counts obtained either by imaging
devices or in Petroff-Hausser chambers, (used to measure B. burgdorferi concentrations
just prior to experiments), and found that more precise counts resulted from the imaging-
based method (Fig. 10C).
We also evaluated accuracy of the imaging-based quantification method by comparing
the actual to expected numbers of bacteria, with the latter based on volume and
concentration of input bacteria per z-series as measured by Petroff-Hausser chambers
(Fig. 10D). This analysis showed that imaging-based counting identified all bacteria
added to devices, and that variation in actual vs. expected values for this method were
within the range of variation attributable to the error rate of Petroff-Hausser counting (Fig.
10D).
Therefore, we concluded that imaging-based methods for counting B. burgdorferi in
microfluidic devices were accurate, precise, and substantially more sensitive than
conventional plate reader-based detection methods.
31
Figure 10. Focal depth, sensitivity and accuracy of imaging-based bacterial quantification in microfluidic devices. (A) Sample z-series MIP showing B. burgdorferi transmigration through endothelia (red) after 1.5 h of flow (left), and isosurface-rendered
32
bacteria identified in the input (yellow) and collection (blue) channels of the same z-series by volumetric object counting. Scale bar: 100 µm. (B) Sensitivity comparison of imaging- and plate reader-based bacterial quantification methods. Orange line: background fluorescence intensity of perfusion buffer in plate reader. Inset: magnified view of region in upper graph indicated by dashed box. Fluorescence intensity values for bacteria counted in 3D imaging datasets were extrapolated from standard intensity vs. bacterial number curves from plate reader samples. (C-D) Precision and accuracy of bacterial counting by volumetric object identification in z-series. In (C) the coefficient of variation (CV) for triplicate z-series acquired at multiple locations in each microfluidic device was compared to CV for bacterial counts in Petroff-Hausser counting chambers (PHCC) used to measure input numbers of bacteria. NS = not significant (P >.05; two-tailed t-test). N= 3 independent microfluidic devices, 3 independent bacterial cultures (PHCC). (D) Numbers of bacteria counted by volumetric object identification in input channels under no-flow conditions before experiments (“actual”) compared to numbers of bacteria expected within each z-stack based on input numbers calculated from PHCC measurements. Gray shading: CV of PHCC counts (i.e., expected input measurement variation). All figure summary values: mean ±SD. In (B) most error bars are too small to be visible.
3.3.4 Comparison of B. burgdorferi transendothelial migration kinetics in microfluidic membrane devices and a conventional Transwell model under static conditions
Transmigration of B. burgdorferi across endothelial monolayers is typically measured in
Transwell chambers under static (no-flow) conditions.87–89 To compare B. burgdorferi
transendothelial migration kinetics in microfluidic membrane devices and Transwell
chambers, we measured transmigration over a 4 hr period in both systems under static
conditions (Fig. 11). We did not extend our studies beyond 4 hr because visible holes
began appearing in some monolayers in microfluidic devices by 5 hr after injection of
bacteria (data not shown). To monitor monolayer integrity in microfluidic membrane
devices over the full duration of experiments, we also measured non-specific penetration
of endothelial barriers by fluorescent beads with a diameter (0.2 µm) that is smaller than
the thickness of the B. burgdorferi cell body (~0.3 µm diam).33 Beads in input and
collecting channels of microfluidic devices were counted using area-based enumeration
methods similar to the imaging-based methods used to enumerate B. burgdorferi in these
devices. Small numbers of bacteria and beads were observed near the membrane in
33
collection channels immediately after injection (Fig. 11A: t = 0 hr), possibly because
higher pressure in the input channel than in the collection channel during injection initially
forced some bacteria and beads through small gaps between the membrane and walls
of the devices. Although bead numbers in collection channels appeared to increase
somewhat over time, values at 0 and all subsequent time points post-injection did not
differ significantly (p>0.22). This implied that although there was some non-specific
transport of beads into collection channels immediately following injection, monolayers
remained largely impermeable and intact under static conditions for up to 4 hr after
injection.
By contrast, the transmigration rate for bacteria was 3.92-fold greater than that of beads
under static conditions (3.80 ±0.45 % per hr vs. 0.97 ±0.10 % per hr, respectively;
p<0.05), with significant differences in the fractions of transmigrated bacteria vs. beads
at 1.5 hr and 4 hr post-injection (p<0.05) (Fig. 11B). Since our quantification methods
counted intact bacteria that had passed through monolayers to reach collection channels
(i.e. not bacteria that were simply associated with monolayers), this implied that bacteria
actively migrated through monolayers. Rates of bacterial transmigration in microfluidic
devices and the Transwell system did not differ significantly (3.80 ±0.45 % per hr vs. 3.01
±1.07 % per hr, respectively; p=0.57), indicating that these systems were functionally
similar with respect to bacterial transmigration. Importantly, transmigration rates for
Transwells were also similar to previously observed B. burgdorferi endothelial
transmigration rates in static Transwell devices over a comparable period (2.4% per hr).87
Collectively, these data showed that B. burgdorferi transendothelial migration in
microfluidic and Transwell devices was comparable under static conditions.
34
Figure 11. Validation of microfluidic B. burgdorferi transmigration system under static conditions. (A) Numbers of bacteria and 0.2 µm beads at indicated z-positions and timepoints in collection channels of 3 independent microfluidic devices/group (composite numbers for 3 devices). Orange line: endothelial cell (EC) monolayer position. (B) Mean ±SEM percentages of total bacteria and beads per device located in collection channels at indicated timepoints, calculated as a percentage of total numbers measured in input and collection channels at t= 4 h by imaging-based counting method. Transwell: percentage of total bacteria counted by plate reader in collection chambers of conventional Transwell devices. N=3 independent bacterial and endothelial cultures per group. Statistics: repeated measures 2-way ANOVA, Holm-Sidak post-test. *P < .05 (beads vs. bacteria within timepoint in both Transwell and microfluidic devices).
3.3.5 B. burgdorferi transendothelial migration kinetics in microfluidic devices under physiological shear stress conditions
Finally, to determine how physiological shear stress affected transendothelial migration
of B. burgdorferi, we measured transmigration rates for bacteria and control beads
perfused over endothelial monolayers at flow rates that generated a shear stress of 1
dyn/cm2 at the monolayer surface (Fig. 12). This shear stress is typical in the
postcapillary venules where B. burgdorferi extravasates in vivo,42 and is also the shear
stress at which B. burgdorferi interactions with endothelial monolayers in flow chambers
are most abundant.79 B. burgdorferi transendothelial migration was delayed in
35
microfluidic devices under shear stress (Fig. 12), and occurred later than under static
conditions (Fig. 11). However, from 1 hr post-injection, transmigration rates under shear
stress were 3.5-fold greater for bacteria than beads (4.94 ±0.84 % per hr vs 1.42 ±0.35
% per hr, respectively; p<0.05), and were comparable to transmigration rates under static
conditions (p=0.38 for B. burgdorferi). Therefore, despite the delayed onset of
transmigration under flow, once this process started it appeared to be as efficient as
transmigration under static conditions. By 4 hr post-injection, holes began appearing in
endothelial monolayers in some devices (data not shown), which likely accounted for
increased accumulation of beads and bacteria in collection channels in some replicates
(Fig. 12B).
Figure 12. B. burgdorferi transmigration through endothelial monolayers in microfluidic devices at physiological shear stress (1 dyn/cm2). (A) Composite numbers of bacteria and beads at indicated z-positions and timepoints in collection channels of 3 independent devices/group. Orange line: endothelial cell (EC) monolayer. (B) Mean ± SEM percentage of total bacteria and beads in collection channels at indicated timepoints, expressed relative to total counts in input and collection channels at t= 4 h after cessation of flow. Under flow, holes in the endothelial monolayer began appearing at 4 h, affecting statistical comparisons between groups at this timepoint. N=3 independent bacterial, endothelial cultures and devices per group. Statistics: repeated measures 2-way ANOVA, Holm-Sidak post-test. *P < .05 vs beads within timepoint.
36
There are several possible explanations for the delayed B. burgdorferi transmigration
observed in experiments conducted under shear stress. The simplest explanation is that
bacteria settled onto endothelia under static conditions, increasing the probability of
endothelial contact and early transmigration. It is also possible that B. burgdorferi
transendothelial migration under flow requires changes in the expression, activation
and/or localization of endothelial cell surface adhesion molecules, or proteases and
adherens junction components that regulate endothelial permeability. This hypothesis is
consistent with previous observations that exposure of cultured endothelial cells to live
B. burgdorferi and isolated B. burgdorferi surface lipoproteins promotes leukocyte
transmigration147,148 and induces expression and activation of endothelial surface
receptors and proteases that regulate leukocyte recruitment and transmigration,
including E-selectin, VCAM-1, ICAM-1, matrix metalloproteases, and plasminogen
activators and plasminogen activator receptors17,148–151. Furthermore, exposing
endothelial monolayers to shear stress induces rapid changes in the composition,
organization and cytoskeletal anchoring of permeability-regulating endothelial adherens
junction proteins such as VE-cadherin50,74,152,153. Thus, delayed transmigration of B.
burgdorferi under flow was potentially mediated by shear stress-dependent changes in
endothelial barrier function.
Finally, it is possible that shear stress-dependent changes in B. burgdorferi properties
such as surface molecule expression promoted transendothelial migration of bacteria at
later time points, although no studies to date have examined the effects of shear stress
on protein expression and localization in this bacterium. It is also important to note that
although B. burgdorferi extravasation is observed immediately upon intravenous
inoculation of bacteria in the dermal postcapillary venules of mice42 extravasation is not
observed in the vascular bed of joints until 24 hr after inoculation.83 Thus, it is likely that
factors specific to the endothelia in different tissues also influence B. burgdorferi
transendothelial migration.
37
3.3.6 Conclusions
To address the limitations of current bacterial extravasation models, we engineered an
imaging-compatible transmembrane microfluidic device that enables analysis of B.
burgdorferi interactions with and penetration of endothelia cultivated under physiological
fluid shear forces. Utilizing fluorescence microscopy to optimize imaging parameters,
and highly-sensitive post-processing software tools to create analysis algorithms, real-
time transmigration kinetics of B. burgdorferi across intact endothelium were obtained,
for the first time, under static and flow conditions. Validation studies confirmed that B.
burgdorferi transmigrate actively, with similar kinetics to conventional Transwell systems
under static conditions. Furthermore, transendothelial migration rates did not appear to
be significantly altered by physiological shear stress despite B. burgdorferi sensitivity to
shear stress for initial hematogenous dissemination interactions. These data were
uniquely obtainable with the microfluidic platform, supporting its utility for studying the
biomechanical contributions of B. burgdorferi extravasation. The flexible design and
ease-of-fabrication features further support this device as an appropriate universal model
for extravasation studies, including transmigration of alternate blood-borne pathogens
and microscopic molecules, to in turn facilitate development of more effective
therapeutics and preventative measures targeting infectious diseases of worldwide
significance.
38
Conclusion and Recommendations
4.1 Conclusion
The goal of this thesis was to develop and characterize a novel transmembrane system
that combined microfluidics- and imaging-based approaches as a platform for
investigating the effect of shear stress on bacterial extravasation. Ultimately, the
intention is to apply this system to the mechanistic contributions of bacterial motility and
chemotaxis for extravasation studies. This device design has extensive flexibility with
respect to: transmembrane material and pore size, adhesion protein coating(s), and ease
of access to both channels, including cell types and flow rates introduced. In getting to
this point though, many challenges were encountered in terms of the ability to:
• Visually distinguish asymmetric, microscopic, motile objects;
• Capture rare transmigration events in real time, and in sufficient numbers for proper
quantitative analysis;
• Ensure a confluent endothelial monolayer to prevent non-specific transmigration;
• Quantify objects in distinct compartments above/below the endothelial monolayer;
• Mimic vascular shear stress conditions;
• Manipulate design easily & inexpensively.
The final product accomplished the following:
• Real-time simultaneous visualization of different object types via multi-wavelength
imaging;
• High spatial & temporal resolution to distinguish submicron motile objects;
• Transparent, porous membrane that supports cell growth and migration;
• Long working distance capability (~ 1 mm) to quantify transmigration;
• Flow functionality to recapitulate physiological shear stress conditions;
• Simple design with compartmental access.
39
Still, in working through solutions to said challenges, many alternative ideas came to
mind that were not able to be implemented due to a lack of time. Described below are
recommended improvements that would make for a more robust system.
4.2 Future directions
4.2.1 Incorporation of more robust techniques for ensuring endothelial monolayer integrity
Figure 13A illustrates the current collection feature, where the intention was to maximize
the surface area of the overlapping region between the input and collection channels, to
in turn maximize capturing transmigration events. Due to the smaller field of view of the
objective (0.1 mm2) relative to the overlapping area of the monolayer (40 mm2), it was
impossible to directly identify by sight breaches within the endothelium. In parallel
experiments I used control beads to monitor average rates of disruption of monolayers
over time. When issues with monolayer confluence arose, either by direct observations
of holes or large influxes of bacteria/beads, the device was discarded. Such events
occurred both prior to the start of the experiment and at time points along the 4 hr duration
of a running experiment, resulting in data that had to be discarded due to concern that
majority of bacteria/beads transported via holes.
I propose the following solutions to improve: the endothelial monolayer integrity, the utility
of the microfluidic device, and the features to monitor cell confluence over time.
4.2.1.1 Better control of the ambient environment
Endothelial cells are sensitive to changes in their microenvironment. For example,
reduction in temperature by just a few degrees Celsius resulted in the cells immediately
pulling apart and holes forming within the monolayer (directly observed via confocal
microscopy using live cell plasma membrane dye). Traditionally, live cell imaging of in
vitro devices is performed on an inverted microscope with an incubator adapted to the
stage to maintain desired temperature and CO2 levels. My experiments used an upright
confocal microscope, which required flipping over the device for imaging, and prevented
the use of commercial stage incubators designed for inverted microscopes. An external
heat lamp was directed at the device for the duration of an experiment, but ambient
40
temperatures were not permitted to exceed ~29˚C, otherwise the microscope would
overheat leading to technical problems. When there were long wait times between
imaging time points, the devices were placed in an incubator at 37˚C/5% CO2. Ideally
though, the devices should be manipulated and moved around as little as possible for
the duration of an experiment. In future iterations of these types of experiments, I would
recommend using an infusion warmer (which was unavailable during experiments
performed for this thesis) at a minimum if imaging on an upright microscope. Better still,
would be to develop a customized solution or adapt a commercial product to ensure
temperature and CO2 levels are maintained at 37˚C/5% CO2 to better mimic in vivo
conditions.
4.2.1.2 Device design modification
Some microfluidic models that incorporate a porous membrane align the input and
collection channels perpendicularly.111 However, the design implemented in this thesis
oriented the two channels in a parallel fashion, as illustrated in Figure 13A, with the
intention of maximizing the overlapping surface to in turn capture as many transmigration
events as possible, which is an inherent limitation with intravital imaging models.42,83 As
mentioned earlier though, there were issues with this design that only became apparent
after culturing endothelia and performing the transmigration experiments. The proposed
modification in Figure 13B aims at addressing said issues by increasing the utility of a
device by creating multiple interconnected collection wells, each with a 500 µm diameter,
that are uniformly spread out along the underside of the input channel. If the endothelial
monolayer were to become breached atop any of these wells, that region would not be
imaged while the other wells would remain viable for the remainder of the experiment.
These collection wells could easily by qualitatively evaluated because the surface area
is comparable to the field of view of the objective. Additionally, the collection wells could
be accessed independently of the input channel via dedicated in/outlet ports, as with the
current design. Lastly, 3D datasets could be repeatedly acquired in the same XYZ
orientation over time much more reliably with the proposed design versus the current
system.
41
Figure 13. Proposed device design modifications. (A) Top down view of the current layout, where the majority of the underlying collection channel (blue) overlaps the input channel (yellow); the gray dashed box represents the PET membrane. (B) Top down view of the proposed layout, where the input channel (yellow) and PET membrane (pink dotted box) remain unchanged, but the collection channel (blue) is altered to ensure overlapping input/collection regions maintain a fully confluent endothelial monolayer through which transmigration is not impacted by monolayer integrity breaches elsewhere along the input channel. (Bi) Cross-section view of the proposed layout.
4.2.1.3 TEER measurements to monitor endothelium confluency
In addition to modifying the layout of the collection channel, I would recommend
incorporating into the design an electrode-embedded impedance-measuring system to
conveniently and quantitatively monitor cell barrier integrity in real-time without disrupting
or damaging the endothelium, as suggested in Douville et al., 2010, and illustrated in
Figure 14.99 This type of data may also enable comparisons with past studies under
static conditions that performed TEER measurements,87 although differences in
detection sensitivity between Transwell setups and microfluidic systems would have to
be considered.119
42
Figure 14. An example of Ag/AgCl wire electrodes incorporated into the fabrication of a PDMS transmembrane microfluidic device to evaluate endothelial confluency via TEER measurements. (Reprinted with permission from Douville, NJ, et al. Fabrication of two-layered channel system with embedded electrodes to measure resistance across epithelial and endothelial barriers. Anal Chem 82 (2010): 2505-11. Copyright 2010 American Chemical Society)
4.2.2 Examination of preconditioning effects on transendothelial migration
Hemodynamic shear stress on the endothelium triggers molecular events that facilitate
transcellular and paracellular migration of leukocytes,61 including increased vascular
permeability via VE-cadherin phosphorylation,63,154 increased adhesion via cytoskeletal
rearrangement61 due to increased cell stiffness, and expression of ICAM-1155,156 and
VCAM-1156 that guide transient passage through the vascular barrier. Therefore, it would
be useful to establish an endothelial monolayer that recapitulates in vivo morphology,
metabolism, and gene expression by preconditioning endothelia at physiological shear
stress levels108 prior to introducing B. burgdorferi.
43
It is recommended that preconditioning be performed with the appropriate endothelial
cell growth medium (EGM-2 supplemented with bullet kit, Lonza) by cultivating
endothelia at 1 dyne/cm2 for 24-48 hours.51,94 While there was not sufficient time to
complete these experiments, I did determine that B. burgdorferi incubated in the
endothelial growth medium for 22 hours at 37⁰C in 5% CO2 (conditions for culturing
endothelia, as opposed to B. burgdorferi culturing conditions, which requires BSK-II
medium157 at 35⁰C in 1.5% CO2) can replicate (data not shown), suggesting that these
conditions may not adversely affect bacterial viability.
4.2.3 Investigation of endothelial heterogeneity effects on bacterial extravasation
As discussed earlier in the literature review, endothelial cells from different organ beds
are exposed to characteristic biomechanical and biochemical cues unique to their
respective microenvironments, resulting in distinct phenotypes and functionalities that
may indirectly facilitate or hinder bacterial extravasation. Of particular interest are the
blood-brain18–20,129 and transplacental14–16 barriers that are efficient at blocking pathogen
transmigration. Spirochetes, however, are one of the rare bacterial exceptions,
penetrating both types of barriers without causing damage to the endothelium.
Incorporating these sources of endothelia into the transmembrane system would
hopefully elucidate the underlying mechanisms at work.
High endothelial cells that line the high endothelial venules (HEVs)158 within the lymphatic
system, akin to postcapillary venules of the vascular system, would also be valuable to
study in this model. HEVs are where lymphocytes extravasate from the vascular system
into lymph nodes. Considering the similarities between leukocyte and spirochete
transmigration42,83,158 (discussed in Ch. 2 Literature Review), HEVs may serve as an
alternative gateway to blood vessels for B. burgdorferi to penetrate target host tissue.
44
4.2.4 Study of additional extravasation effectors
While there is still no comprehensive understanding of the biophysical and molecular
mechanisms involved in B. burgdorferi extravasation, the following factors may affect
extravasation and should be explored further, at varying physiological shear stress
levels, within this transmembrane system: chemotactic agents (e.g. attractants: serum159
and L-aspartate,160 repellent: glycerol160) and bacterial motility (e.g. mutations in CheX
or CheY3 that impair translational motility).161,162 It would be interesting to also explore
effects of bacterial inoculation concentrations on transendothelial migration rates,
considering in vitro static models have showed diminishing returns in transmigration
frequency for initial densities exceeding 108 bacteria/ml.89,96
4.3 Final remarks
Overall, the development and characterization of this optically-compatible microfluidic
system as an in vitro tool for studying bacterial extravasation under more physiologically
relevant conditions is a step forward in understanding the incredible complexity and
adaptability of the B. burgdorferi spirochete. The true value of this system, however, will
be recognized once it is adopted into common practice for biological research.
Historically, biologists have been slow to adopt microfluidic technologies for several
reasons. First, is the potential issue of adverse PDMS effects on cell cultures.163,164
Thus, there is value in modifying the device design from a PDMS-based platform to
polystyrene plastic. Currently there are several students in the Simmons lab that are
pursuing this approach.
Second, there is criticism about non-physiological stiffness95 of the membranes used to
support endothelial monolayers, and the ability of endothelia to penetrate 3 µm pore
diameters to form bilayers.165 Leukocyte studies, however, have shown successful
migration across these unintentional cell-membrane-cell bilayers.165 Specifically, no
statistical differences were found in comparing neutrophil transmigration rates through
endothelia cultivated on non-biological porous membranes and amniotic membranes.165
That said, future generations of the microfluidic system developed in this thesis should
45
consider these issues, in terms of the mechanistic contribution of endothelial polarity to
bacterial extravasation. Furthermore, basement membranes should also be
characterized in the microfluidic transmembrane system (regardless if the design
includes a membrane as in Fig. 8A or is side-by-side as in Fig. 8B), to ensure that the
vascular barrier model better mimics in vivo parameters.
A commercial transmembrane system has recently become available through ibidi (µ-
Slide Membrane ibiPore Flow), but it is very expensive (~$500/device) considering that
these devices cannot be reused and a single device only represents one biological
replicate. Regardless, there is clearly an interest in these types of microsystems, and
hopefully the contributions from this thesis will expedite development to improve
accessibility and use for those performing live cell transmigration studies.
46
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