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New approaches for precisely engineering heterotypic muscle tissues by naturally and synthetically controlling cell fate

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New approaches for precisely engineering heterotypic muscle tissues by naturally and synthetically controlling cell fate

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NEW APPROACHES FOR PRECISELY ENGINEERING
HETEROTYPIC MUSCLE TISSUES BY NATURALLY
AND SYNTHETICALLY CONTROLLING CELL FATE

by
NATHAN CHO

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA

In Partial Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOMEDICAL ENGINEERING)

MAY 2020

Copyright 2020 Nathan Cho

ii
Dedication
To my mom who constantly poured love into me and prayed for my physical, mental, and
spiritual health daily. Thank you for listening to me at least once a week via phone call and for
being such an amazing mom.
To my dad who worked 365 days a year to financially support the family, yet never
complained about how exhausted he was. Thank you for showing me what endurance looks like –
I needed that to complete my Ph.D.
To my grandparents who have been praying for me nonstop and providing words of
wisdom whenever I went back home for break. I hope you are proud and I pray for your continual
health.
Finally and most importantly, to my Father in Heaven who knew me before I was born,
who guided me through the ups and downs for twenty-seven (and a half) years, and will continue
to pour His agape love into my life. Soli Deo Gloria.

iii
Abstract
To efficiently pump blood throughout the body, the myocardial tissue in the heart is
composed primarily of longitudinally aligned cardiac myocytes that rhythmically contract with
supporting fibroblasts that synthesize the extracellular matrix (ECM). When pathological events
occur, such as myocardial infarction, the myocardium undergoes chemical, mechanical, and
electrical alterations due to changes in the cellular phenotypes and architecture of cardiac myocytes
and fibroblasts. In particular, post-infarct remodeling of the myocardium increases ECM rigidity,
production of transforming growth factor beta-1 (TGF-b1), and disorganization of myocyte
alignment. These post-infarct changes are postulated to affect interactions between myocytes and
fibroblasts and overall cardiac function, but these phenomena are poorly understood because
existing in vitro models have a limited ability to recapitulate cell-cell interactions reminiscent of
the native human myocardium. To address this, our goal is to develop new approaches for
engineering heterotypic, spatially organized striated muscle tissues with mechanical, biochemical,
and/or synthetic control over cell fate. First, we will measure the relative effects of mechanical and
biochemical cues on human cardiac fibroblast differentiation by introducing TGF-β1 to fibroblasts
cultured on polydimethylsiloxane (PDMS) substrates of varying rigidities. Next, we will develop
a novel approach to spatially dictate cell fate and generate heterotypic skeletal muscle tissues by
combining synthetic biology and substrate micropatterning. This new approach will enable further
studies into how fibroblast-myocyte interactions contribute to cardiac disease progression and are
regulated by physical changes in the microenvironment. Collectively, our research establishes new
tools related to controlling cell fate using various natural and synthetic cues. Our approaches can
be applied to engineer sophisticated striated muscle tissues for in vitro applications, such as

iv
discovery and testing of new therapeutic targets and translation to regenerative medicine in the
long-term.

v
Table of Contents

Dedication ...................................................................................................................................... ii
Abstract ......................................................................................................................................... iii
Table of Figures ........................................................................................................................... vii
Table of Tables ............................................................................................................................ xv
Chapter 1 Introduction ................................................................................................................ 1
1.1. Cardiac Myocytes and Fibroblasts in Healthy Myocardium .................................... 2
1.1.1. Cardiac Myocytes in Healthy Myocardium ....................................................... 2
1.1.2. Cardiac Fibroblasts in Healthy Myocardium ..................................................... 4
1.2. Disease Progression of Myocardial Infarction ......................................................... 5
1.2.1. Myocardial Infarction Leads to Fibrosis (Stage 1) ............................................ 6
1.2.2. Cardiac Fibrosis Leads to Pump Failure and Arrhythmias (Stage 2) ................ 8
1.3. Existing Approaches to Investigate Cardiac Myocyte-Fibroblast
Interactions .................................................................................................................... 10
1.3.1. In Vivo and Ex Vivo Studies ........................................................................... 11
1.3.2. In Vitro Studies ................................................................................................ 12
1.4. Outlook ................................................................................................................... 15
1.5. Objective and Aims ................................................................................................ 16
Chapter 2 TGF-β1 Dominates Extracellular Matrix Rigidity for Inducing
Differentiation of Human Cardiac Fibroblasts to Myofibroblasts ......................................... 18
2.1. Introduction ............................................................................................................ 18
2.2. Materials and Methods ........................................................................................... 21
2.2.1. Fabrication of Tunable PDMS Substrates ....................................................... 21
2.2.2. Cell Culture ...................................................................................................... 22
2.2.3. Immunostaining ............................................................................................... 23
2.2.4. Microscopy and Image Analysis ..................................................................... 23
2.2.5. Gene Expression Analysis ............................................................................... 24
2.2.6. Statistics ........................................................................................................... 24
2.3. Results .................................................................................................................... 25
2.3.1. Effects of ECM Ligand, Serum Concentration, and TGF-b1
Concentration on Human Cardiac Fibroblast Adhesion and Differentiation ............ 25
2.3.2. Regulation of Cardiac Myofibroblast Differentiation by TGF-b1
and ECM Rigidity ...................................................................................................... 28

vi
2.3.3. Expression of Fibroblast- and Myofibroblast-Associated Genes
due to TGF-b1 and ECM Rigidity ............................................................................. 32
2.3.4. Reversibility of Myofibroblast Phenotype ...................................................... 35
2.4. Discussion .............................................................................................................. 36
Chapter 3 Spatially Dictating Cell Identity in Heterotypic Striated Muscle
Tissues by Combining Microcontact Printing and Synthetic Notch Receptors .................... 43
3.1. Introduction ............................................................................................................ 43
3.2. Materials and Methods ........................................................................................... 48
3.2.1. Photolithography and Soft Lithography .......................................................... 48
3.2.2. Fabrication of Micropatterned PDMS-Coated Coverslips .............................. 49
3.2.3. Engineering Synthetic Cell Lines .................................................................... 50
3.2.4. Cell Culture and Live Imaging ........................................................................ 50
3.2.5. Immunostaining ............................................................................................... 51
3.2.6. Microscopy and Image Analysis ..................................................................... 52
3.2.7. Statistical Analysis .......................................................................................... 53
3.3. Results .................................................................................................................... 53
3.3.1. Optimization of Fabricating Scaffolds Microcontact Printed
with GFP Ligands ...................................................................................................... 53
3.3.2. Selective Transcriptional Activation of mCherry-myoD in
SynNotch Cells by GFP Ligands ............................................................................... 57
3.3.3. Maturation of Transdifferentiated Myoblasts into Multi-Nucleated
Skeletal Myotubes within GFP Region ..................................................................... 60
3.3.4. Spatially Controlled Transcriptional Activation of myoD-mCherry
on Various Patterned Surfaces ................................................................................... 62
3.4. Discussion .............................................................................................................. 63
Chapter 4 Concluding Remarks and Future Work ................................................................. 69
4.1. Chemical and Biomechanical Cues Regulate Human Cardiac Fibroblast
Differentiation into Myofibroblasts .............................................................................. 70
4.2. Combination of Microcontact Printing and Synthetic Notch Receptors
Generates Spatially Defined Heterotypic Tissues ......................................................... 72
4.3. Limitations and Future Directions .......................................................................... 73
4.4. Final Conclusions ................................................................................................... 76
References .................................................................................................................................... 78
Acknowledgements ..................................................................................................................... 89

vii
Table of Figures

Figure 1-1. Schematic of sarcomeric shortening in cardiac myocytes.
Globular myosin heads bind to an actin filament, move towards the center of the
sarcomere (contraction), and then detach when ATP binds (relaxation). This cycle
continues only in the presence of ATP and sufficient level of calcium ions in the
sarcoplasm. Adapted from Principles of Anatomy and Physiology (ed. 11e). ............................... 2
Figure 1-2. Action potential propagation through connexin 43.
(A) Diagram of the cardiac conduction system. Adapted from McMaster Physiology
Review. (B) Above: mouse cardiac myocytes coupled via connexin 43 throughout
the tissue. Scale: 20 μm. Adapted from
1
. Below: rat cardiac myocyte pair island
reveals connexin 43 localization at the longitudinal ends of the cells. Scale: 25 μm.
Adapted from
5
. ................................................................................................................................ 3
Figure 1-3. Cross-section of a healthy rabbit ventricular myocardium.
Confocal microscopy image of a healthy rabbit ventricular myocardium reveals
spindle-like cardiac fibroblasts (blue) interspersed between the aligned cardiac
myocytes (red). Myomesin: red, Vimentin: blue, Connexin 43: green. Scale: 20 μm.
Adapted from
6
. ................................................................................................................................ 5
Figure 1-4. Schematic of the wound healing response after myocardial infarction.
Myocardial repair is categorized into three phases. Phase 1: Hypoxia induces cardiac
myocyte death and the resulting inflammation response involves recruitment of
macrophages and neutrophils. Phase 2: Fibroblasts differentiate into myofibroblasts and
proliferate to the site of injury to deposit excessive ECM proteins, such as collagen.

viii
Phase 3: A stiff, fibrotic tissue is formed and composed of lingering myofibroblasts.
Adapted from
7
. ................................................................................................................................ 6
Figure 1-5. Physiological changes in the ventricular myocardium after infarction.
The healthy ventricular myocardium exhibits highly aligned cardiac myocytes in a
microenvironment with an elastic modulus of about 10 kPa. However, the fibrotic
myocardium displays a disarray of cardiac myocytes with over a five-fold increase
in ECM rigidity. Scale: 100 μm. Adapted from Wikipedia and
9
. ................................................... 8
Figure 1-6. Action potential propagation disruption in the infarcted ventricular
myocardium leads to arrhythmias.
Various types of cardiovascular diseases, including myocardial infarction, cause
the uniform wave of electrical conduction to become disrupted. The action potential
wave scatters in a zigzag pattern and some conduction paths becomes bidirectional,
resulting in re-entry and eventually arrhythmias. Scale: 100 μm. Adapted from
4
. ......................... 9
Figure 1-7. Current in vitro platforms for modeling neonatal rat cardiac co-culture.
(A) Cardiac myocytes and myofibroblasts were isotropically cultured, and confocal
microscopy image reveals Cx43 between the two cell types. α-actinin: red,
α-SMA: green, Cx43: yellow. Scale: 30 μm. Adapted from
8
. (B) A region of
myofibroblasts was surrounded by cardiac myocytes in a “sandwich” formation, which
introduced propagation delay at the interface. Scale: 50 μm. Adapted from
4, 10
.
(C) A rectangular network of stacked cardiac myocytes and myofibroblasts exhibited
Cx43 and Cx45 between the two cell types. Scale: 5 μm. Adapted from
11, 12
. ............................. 13
Figure 2-1. Image processing techniques and experimental timeline.
(A) Representative raw and thresholded images of nuclei, actin, and α-SMA in

ix
untreated and TGF-β1 treated human cardiac fibroblasts (scale bars: 200 μm).
(B) Experimental timeline for culturing cardiac fibroblasts with reduced serum
and TGF-β1 treatment. .................................................................................................................. 26
Figure 2-2. Optimization of ECM ligand and serum concentration for human
cardiac fibroblast culture.
Human cardiac fibroblasts were seeded onto high PDMS-coated coverslips coated
with the indicated ECM ligand. After one day, serum levels were reduced to the
indicated levels and cells were treated with 10 ng/mL TGF-β1 for five days,
followed by staining and imaging. Cell density (A), actin coverage (B), and
α-SMA/actin coverage (C) was quantified (n=1). ........................................................................ 27
Figure 2-3. Optimization of TGF-β1 concentration.
Human cardiac fibroblasts were seeded onto high PDMS-coated coverslips coated
fibronectin. After one day, serum was reduced to 0.1% and cells were treated with
0, 2, or 10 ng/mL TGF-β1 for one, three, and five days, following by staining and
imaging. Cell density (A), actin coverage (B), and α-SMA/actin coverage
(C) was quantified (n=1). .............................................................................................................. 27
Figure 2-4. Cell morphology and α-SMA expression due to ECM rigidity
and TGF-β1 treatment.
Representative images of human cardiac fibroblasts cultured for five days on low,
moderate, and high PDMS-coated coverslips with or without 2 ng/mL TGF-β1
(blue: nuclei, green: actin, red: α-SMA, scale bars: 25 μm). ........................................................ 28
Figure 2-5. Quantification of cell morphology and α-SMA expression due
to ECM rigidity and TGF-β1 treatment.

x
Human cardiac fibroblasts were cultured on low, moderate, and high PDMS-coated
coverslips with or without 2 ng/mL TGF-β1 for one, three, and five days. Cells were
immunostained and cell density (A), actin coverage (B), and α-SMA/actin coverage
(C) were quantified from immunostained images (n = 4, bars indicate mean +/-
standard error of the mean, *p< 0.05 and **p< 0.01 according to one-way ANOVA
and Tukey’s test for multiple comparisons.) ................................................................................. 30
Figure 2-6. Relative changes in gene expression due to ECM rigidity and
TGF-β1 treatment.
Human cardiac fibroblasts were cultured on low, moderate, and high PDMS-coated
coverslips with or without 2 ng/mL TGF-β1 for one, three, and five days. RT-PCR
was used to quantify the relative expression of (A) ACTA2, (B) POSTN, (C) FAP,
(D) FSP1, and (E) GJA1. All data was normalized to high PDMS control group on
Day 1. (n = 4, bars indicate mean +/- standard error of the mean, *p< 0.05 and
**p< 0.01 according to one-way ANOVA and Tukey’s test for multiple comparisons.) ............ 34
Figure 2-7. Quantification of cell morphology and α-SMA expression after
re-plating untreated and TGF-β1-treated cells in the absence of TGF-β1.
On Day 3, untreated and TGF-β1-treated cells on high PDMS coverslips were
trypsinized, re-plated onto high PDMS coverslips, and maintained without TGF-β1
for an additional two and seven days. Cells were immunostained and cell density (A),
actin coverage (B), and α-SMA/actin coverage (C) were quantified from
immunostained images (n = 4, bars indicate mean +/- standard error of the mean,
*p< 0.05 and **p< 0.01 according to one-way ANOVA and Tukey’s test for
multiple comparisons.) .................................................................................................................. 35

xi
Figure 3-1. Microcontact printing for dictating cell adhesion and architecture
of engineered cardiac tissues.
Neonatal rat cardiac myocytes were seeded onto PDMS-coated coverslips
microcontact printed with fibronectin and exhibited the alignment of the lanes.
DAPI: blue, F-actin: green, sarcomeric α-actinin: red. Scale: 50 μm. Adapted from
2
. ................ 44
Figure 3-2. Synthetic notch receptor (synNotch) engineering and selective
transdifferentiation of synNotch fibroblasts into skeletal myotubes.
(A) Diagram of the Notch signaling pathway elucidates the ligand-receptor
interaction, proteolytic cleavages of the receptor, and repression or activation of
transcription factor(s). Adapted from
3
. (B) Modification of the naturally expressed
Notch receptor and its signaling pathway by modulating the input to regulate
user-defined output. (C) Selective transdifferentiation of engineered synNotch cells
with a myoD transcription factor module into skeletal myotubes in the area conducive
to ligand-receptor binding. Scale: 50 μm. Adapted from
13
. ......................................................... 46
Figure 3-3. Culturing synNotch cells on microcontact printed surfaces.
Schematic of microcontact printing GFP onto PDMS-coated coverslips and
engineering synNotch cells to seed onto the printed surfaces to generate spatially
organized skeletal myotubes interspersed with undifferentiated synNotch cells. ........................ 49
Figure 3-4. High concentration of fibronectin attenuates mCherry expression
in synNotch cells.
Live images of engineered murine fibroblasts (synNotch cells) cultured for two days
on PDMS-coated coverslips with microcontact printed GFP lanes and backfilled with

xii
no fibronectin (A), 1 μg/mL, or 10 μg/mL of fibronectin (B) (scale bars: 100 μm).
Images captured in collaboration with Alexander March (Leonardo Morsut’s lab). ................... 54
Figure 3-5. Microfluidic patterning to modularly deposit fibronectin and GFP
to activate mCherry expression in synNotch cells.
(A) Schematic of microfluidic patterning of fibronectin and GFP onto PDMS-coated
coverslips. (B) Immunostained images of GFP and FN that shows the negative region
of FN that was patterned surrounded by GFP lanes created by microfluidic flow
through the channels (scale bars: 200 μm). .................................................................................. 55
Figure 3-6. Microcontact printing after evaporation of GFP solution to
transcriptionally activate myoD-mCherry and mature transdifferentiated
synNotch cells.
SynNotch cells were cultured on PDMS-coated coverslips microcontact printed
with evaporated GFP. (A) Live images of the GFP lanes and myoD-mCherry
expression of synNotch cells after one day in culture (scale bar: 500 μm).
(B) Immunostained images of the GFP lanes, myoD-mCherry, sarcomeric α-actinin,
and merged channels of synNotch cells after three days in culture (scale bar: 200 μm).
Images captured in collaboration with Alexander March (Leonardo Morsut’s lab). ................... 56
Figure 3-7. Selective myoD-mCherry expression in synNotch cells in direct
contact with GFP ligands.
Quarter-circle live images of engineered murine fibroblasts (synNotch cells) were
cultured for four hours (A) and 24 hours (B) on PDMS-coated coverslips with no GFP,
GFP droplet, and microcontact printed (μCP) GFP (scale bars: 500 μm). Images
captured in collaboration with Alexander March (Leonardo Morsut’s lab). ................................ 57

xiii
Figure 3-8. Quantification of nuclei count and myoD-mCherry expression
after 24 hours due to the presence of GFP ligands. SynNotch cells were cultured
on PDMS-coated coverslips with no GFP, GFP droplet, and microcontact printed
GFP for 24 hours. (A) Immunostained images of synNotch cells inside and outside
of the GFP area (blue: nuclei, red: myoD-mCherry, scale bars: 100 μm).
Cell density (B) and myoD-mCherry coverage (C) were then quantified from
images (n = 4 or 5, bars indicate mean of the data set, ***p< 0.0001 compared
to FN inside and all the outside conditions, according to one-way ANOVA and
Tukey’s test for multiple comparisons.). Data collected in collaboration with
Alexander March and Mher Garibyan (Leonardo Morsut’s lab). ................................................. 59
Figure 3-9. Cell morphology and quantification of cell density and
sarcomeric α-actinin-positive expression after five days due to the
presence of GFP ligands.
SynNotch cells were cultured on PDMS-coated coverslips with no GFP,
GFP droplet, and microcontact printed GFP for five days. (A) Representative
immunostained images of synNotch cells inside and outside the GFP region
(blue: nuclei, gray: sarcomeric α-actinin, scale bars: 100 μm). (B) Cell density
comparing Day 1 and 5 and (C) sarcomeric α-actinin coverage were quantified from
immunostained images (n = 1 or 2, bars indicate mean of the data set). Data collected in
collaboration with Alexander March and Mher Garibyan (Leonardo Morsut’s lab). ................... 61
Figure 3-10. Spatially controlled myoD-mCherry expression of synNotch
cells along concentric circle regions of GFP ligands.
Live images of microcontact printed GFP concentric circles and myoD-mCherry

xiv
expression of synNotch cells that were cultured for four 24 hours on PDMS-coated
coverslips (scale bars: 200 μm). Images captured in collaboration with Mher Garibyan
(Leonardo Morsut’s lab). .............................................................................................................. 62
Figure 4-1. Natural and synthetic cues to generate physiologically relevant
in vitro heterotypic striated muscle tissues.
Diagram of the interplay between the chemical and biomechanical cues that
regulate human cardiac fibroblast differentiation into myofibroblasts and the
synthetic cues with architecture that generates spatially precise heterotypic
skeletal muscle tissues. ................................................................................................................. 77

xv
Table of Tables

Table 2-1. Two-way ANOVA p-values (n = 4). Data for all conditions was
normally distributed, as determined by the Kolmogorov-Smirnov test. *p<0.05. ....................... 31

1
Chapter 1 Introduction
Cardiovascular disease is currently the leading cause of death in the United States,
responsible for one of every four deaths annually
14
and costing approximately $320 billion in
medical expenditures, which are projected to double in the next two decades
15
. Myocardial
infarction, a main subset of cardiovascular disease, occurs due to an occlusion of an artery that
results in the death of downstream cardiac myocytes, which are the muscular cells in the
myocardium
7
. Consequently, an inflammatory response is triggered and cardiac fibroblasts, which
are the supporting cells of the myocardium, proliferate to the site of injury, form a fibrotic scar to
replace the dead myocytes, and contributes to pathological remodeling in the ventricle
16
. Past
studies have elucidated deleterious mechanical and electrical changes in cardiac function due to
ventricular remodeling
17
. Interactions between cardiac myocytes and fibroblasts at the infarct
region of the diseased myocardium are postulated to be one of the many sources for post-infarction
consequences but have not been fully established. This shortcoming is attributed in part to a lack
of physiologically relevant in vitro platforms that can best recapitulate the inherently
heterogeneous cardiac infarct region.
In this chapter, we will review the physiology and cellular phenotypes of the healthy
ventricular myocardium, and how these are adversely affected during the various stages of
myocardial infarction. Then we will discuss the current models for studying cardiac co-cultures
and their respective limitations. These studies are the motivation for the experiments conducted in
this dissertation.

2
1.1. Cardiac Myocytes and Fibroblasts in Healthy Myocardium
The human heart is composed of four main chambers: left and right atria and ventricles,
which are connected to arteries and veins that transport blood across the whole body. Two of the
main cell types in the ventricles are cardiac myocytes, which are the striated muscle cells that
generate contractile forces, and fibroblasts, which are the supporting cells that synthesize the
extracellular matrix (ECM). In this section, we will highlight the main functions of both cardiac
myocytes and fibroblasts in the healthy ventricular myocardium, as well as key structural features
of the tissue.

1.1.1. Cardiac Myocytes in Healthy Myocardium
Cardiac myocytes, which are the muscular cells of the heart, are responsible for pumping
blood throughout the whole body via contractile forces. The myocardium, which is a layer of the
heart wall composed of muscular tissue, is distinct in the atria and the ventricles. The ventricular
myocardium is significantly thicker and has a slower rate of active tension generation and
relaxation than the atrial
myocardium
18
, which
indicates that there is a
higher density of cardiac
myocytes generating
greater contractile forces in
the ventricles for pumping
blood. Cardiac myocytes
have sarcomeres, which
Figure 1-1. Schematic of sarcomeric shortening in cardiac myocytes. Globular
myosin heads bind to an actin filament, move towards the center of the sarcomere
(contraction), and then detach when ATP binds (relaxation). This cycle continues
only in the presence of ATP and sufficient level of calcium ions in the sarcoplasm.
Adapted from Principles of Anatomy and Physiology (ed. 11e).

3
consists of repeating units of actin filaments and myosin heads, that shorten when myosin heads
bind to actin filaments and results in contraction (Figure 1-1). Prior to myosin-actin binding, a
coil protein called tropomyosin covers the myosin binding sites on the actin filament. However, if
the intracellular calcium ion concentration is between 10 nM and 100 μM
19
, there are enough ions
that can bind to tropomyosin and alter the structural conformation of this protein to reveal the actin
binding sites. In addition, surrounding ATP molecules are hydrolyzed, which reinforces binding
of ATP to the actin filament. As the myosin heads bind to actin, there is movement towards the
center of the sarcomere, which
induces contraction. Finally,
when another ATP molecule
binds to the myosin heads, the
myosin-actin binding
dissociates, and sarcomeres
enter a resting state. Both ATP
molecules and sufficient level of
calcium ions in the sarcoplasm
need to be present for
subsequent contractions to
occur.
For cardiac myocytes in
the ventricular myocardium to
overcome the large aortic
pressure, the cells need to be
Figure 1-2. Action potential propagation through connexin 43. (A)
Diagram of the cardiac conduction system. Adapted from McMaster
Physiology Review. (B) Above: mouse cardiac myocytes coupled via
connexin 43 throughout the tissue. Scale: 20 μm. Adapted from
1
. Below: rat
cardiac myocyte pair island reveals connexin 43 localization at the
longitudinal ends of the cells. Scale: 25 μm. Adapted from
5
.

4
longitudinally aligned and contract in a synchronous manner
20, 21
to generate maximal force and
pump blood throughout the whole body. This synchronization originates from action potentials
fired from the sinoatrial node in the right atrium, which rapidly propagate to the atrioventricular
node and splits into the left and right bundle branches where the ventricles are located
22, 23
(Figure
1-2A). Action potentials are transmitted through gap junction proteins, which allow intercellular
transport of various ions and electrical signals
24
to couple adjacent cardiac myocytes. Connexin 43
(Cx43), the most abundant gap junction expressed by cardiac myocytes in the ventricular
myocardium
25
, is localized along the longitudinal ends of adjacent cells called intercalated discs
5

(Figure 1-2B). As the electrical conduction propagates across the sarcomeres of ventricular
cardiac myocytes, the cells become depolarized and release calcium ions from the sarcoplasmic
reticulum
26
. An increase in the intracellular calcium concentration alters the conformation of
tropomyosin, as mentioned earlier, which allows the cells to contract efficiency and maintain
constant blood flow in the body.

1.1.2. Cardiac Fibroblasts in Healthy Myocardium
Although cardiac myocytes occupy most of the volume of the ventricular myocardium,
non-muscle cells such as endothelial cells, fibroblasts, pericytes, and smooth muscle cells
constitute approximately two-thirds of the total number of cells in the tissue
27-29
. Fibroblasts, which
are stromal cells that primarily synthesize the ECM network, are the predominant non-muscle cells
in the ventricular myocardium
30
. The ECM is composed of fibrillar collagens (types I and III),
basement membrane collagen IV, fibronectin, laminin, and proteoglycans
31
, which help maintain
the structural integrity of the myocardium and regulate cellular functions such as proliferation,
migration, differentiation, and adhesion
32
. As there is a constant turnover of the ECM, the

5
fibroblasts continuously synthesize matrix proteins
4
and maintain the rigidity of the myocardium
at about 10 – 15 kPa
33, 34
. Fibroblasts are interspersed throughout the myocardium and reside
between highly aligned cardiac myocytes (Figure 1-3).
Cx43 expression in cardiac myocytes is well established, but whether cardiac fibroblasts
can express and utilize Cx43 has remained
unknown. One study revealed coupling via
Cx40 between adjacent cardiac fibroblasts
and via Cx45 between a fibroblast and
myocyte in a healthy rabbit sinoatrial
node
35
. However, most studies agree that in
the healthy ventricular myocardium, cardiac
fibroblasts are not electrically excitable, but
they exhibit electrophysiological
characteristics such as resting membrane
potential and outwardly rectifying ionic
currents
36, 37
. Thus, there are still many unresolved questions related to interactions between
cardiac myocytes and fibroblasts in healthy ventricular myocardium. These uncertainties are
currently difficult to address due to the lack of a model systems for investigating interactions
between two cell types in a physiologically relevant microenvironment.

1.2. Disease Progression of Myocardial Infarction
When the heart suffers from a myocardial infarction, which is a subset of cardiovascular
disease that results in the death of cardiac myocytes downstream of a blocked artery, the cellular
Figure 1-3. Cross-section of a healthy rabbit ventricular
myocardium. Confocal microscopy image of a healthy rabbit
ventricular myocardium reveals spindle-like cardiac
fibroblasts (blue) interspersed between the aligned cardiac
myocytes (red). Myomesin: red, Vimentin: blue, Connexin 43:
green. Scale: 20 μm. Adapted from
6
.

6
phenotypes and physiology of the ventricle change progressively. In this section, we will elaborate
in detail how the functions of cardiac myocytes and fibroblasts are altered in each stage of post-
infarction, as well as how the physiology of the ventricular myocardium is modified.

1.2.1. Myocardial Infarction Leads to Fibrosis (Stage 1)

Myocardial infarction occurs when ventricular myocytes downstream of an occluded
coronary artery undergo irreversible cell death due to ischemia. Since cardiac myocytes have
limited regenerative capacity, an inflammatory response is triggered, which is the first amongst
three phases of myocardial repair
38
(Figure 1-4). The inflammatory response involves the
recruitment of macrophages and neutrophils
39, 40
. Macrophages are a subset of white blood cells
that clear cellular debris via phagocytosis and neutrophils are the most abundant type of white
blood cells that secrete various cytokines and growth factors to activate downstream signaling
processes. In particular, neutrophils secrete transforming growth factor beta-1 (TGF-β1), which is
a cytokine that binds to type II TGF-β receptors and activates the TGF-β/Smad pathway in cardiac
fibroblasts
41
. Smad proteins are activated by phosphorylation of type I TGF-β receptors and
translocate to the nucleus to upregulate transcription of ECM proteins and alpha smooth muscle
Figure 1-4. Schematic of the wound healing response after myocardial infarction. Myocardial repair is
categorized into three phases. Phase 1: Hypoxia induces cardiac myocyte death and the resulting inflammation
response involves recruitment of macrophages and neutrophils. Phase 2: Fibroblasts differentiate into
myofibroblasts and proliferate to the site of injury to deposit excessive ECM proteins, such as collagen. Phase 3: A
stiff, fibrotic tissue is formed and composed of lingering myofibroblasts. Adapted from
7
.

7
actin (α-SMA), which is a major component of contractile microfilaments selectively expressed in
myofibroblasts
42, 43
. Consequently, cardiac fibroblasts differentiate into their activated derivatives
called myofibroblasts and will deposit more ECM molecules and generate contraction.
Myofibroblasts exhibit a phenotype intermediate to fibroblasts and smooth muscle cells
44
. In the
second and third phases of repair, myofibroblasts proliferate to the site of injury and deposit ECM
molecules at an accelerated rate to form a stiff scar tissue, which provides mechanical stability to
compensate for myocyte loss
7, 45
. Scar tissue formation is observed in other organs such as the
skin
46
and lungs
47
after injury, which follow a similar wound healing response.
An excessive amount of ECM proteins deposited by the fibroblasts
48
abnormally thickens
the ventricular wall, which is known as cardiac fibrosis
49
. In addition to an accelerated rate of
deposition, the ECM composition of the ventricular myocardium becomes significantly different.
In the healthy ventricular myocardium, laminin and fibronectin constitute more than half of the
ECM composition. However, after an infarction, collagen I and fibronectin synthesis rates greatly
increase during the initial maturation phase of the wound healing response
39, 50
. After three weeks,
the ECM composition becomes dominated by solely collagen I (57%)
51
. As a result, the rigidity of
the ventricular myocardium significantly increases and the separation between the bundles of
cardiac myocytes increases, which correlates to the disorganization of the uniaxially aligned
sarcomeres. Increased stiffness is known to promote further fibroblast differentiation into
myofibroblasts, which suggests a positive reinforcement of the activated phenotype. In other
organs or minor injuries, myofibroblasts undergo apoptosis after the repairs are finalized. However,
cardiac myofibroblasts can persist within the fibrotic scar tissue for about twenty years
52
, in which
the cells continually provide structural support to bridge the healthy regions of the myocardium.
Fibrosis results in over a five-fold increase in myocardial rigidity (> 50 kPa)
53
and disarray of

8
highly aligned cardiac
myocytes
54
(Figure 1-5).
Although both TGF-β1 and
increased ECM rigidity
influence myofibroblast
formation and its prolonged
duration in the myocardium,
the relative contribution of
the biomechanical and
chemical cues to fibroblast
activation remains unclear.
As cardiac fibrosis is the first stage of post-myocardial infarction, there is a need to elucidate the
specific mechanism of cardiac fibroblast-to-myofibroblast transition for development of more
effective therapeutic interventions.

1.2.2. Cardiac Fibrosis Leads to Pump Failure and Arrhythmias (Stage 2)
Although the scar tissue provides mechanical stability to the injured myocardium, cardiac
fibrosis causes downstream remodeling of the tissue, which results in both mechanical and
electrical dysfunction. The increase in matrix stiffness triggers ventricular dilation, which is an
enlargement of the chamber that increases the volume of blood ejected from the ventricle, in order
to compensate for the decreased compliance of the myocardial wall
55
. In particular, the myocyte
length significantly increases and sarcomeres are added in series to individual myocytes to reduce
the thickness of the ventricular wall
56
. As a result, cardiac output is temporarily rescued, but
Figure 1-5. Physiological changes in the ventricular myocardium after
infarction. The healthy ventricular myocardium exhibits highly aligned
cardiac myocytes in a microenvironment with an elastic modulus of about 10
kPa. However, the fibrotic myocardium displays a disarray of cardiac
myocytes with over a five-fold increase in ECM rigidity. Scale: 100 μm.
Adapted from Wikipedia and
9
.

9
eventually the
contraction generated
by cardiac myocytes
plummets due to
volume overload,
which ultimately leads
to complete pump
failure
17
(Figure 1-6).
Furthermore,
the disarray of cardiac
myocytes from
fibrosis results in a loss of Cx43 at the intercalated discs due to relocalization of these proteins to
the lateral membrane, which has a lower Cx43 concentration than the discs
57, 58
. Disruption of
Cx43 distribution amongst the surviving myocytes in the infarct region leads to arrhythmias, which
correspond to interference in the synchrony of action potential propagation. Although there are
three sources of cardiac arrhythmias
59
, the most common cause of arrhythmias regarding
myocardial infarction is re-entry
60
. Consequently, the uniform wave of synchronous action
potentials propagating from the sinoatrial node towards the ventricular myocardium becomes
disarrayed and nonuniform
4
. The conduction begins to exhibit a zigzag formation to travel through
the Cx43 of unaligned, adjacent cardiac myocytes
61
or experiences a unidirectional conduction
block within the collagenous region
4, 62
(Figure 1-6). Both activation patterns are abnormal and
increase the likelihood of re-entry, as the disruption in conduction pathway leads to bidirectional
conduction. Re-entry results in an interference of action potential propagation, which can offset
Figure 1-6. Action potential propagation disruption in the infarcted ventricular
myocardium leads to arrhythmias. Various types of cardiovascular diseases,
including myocardial infarction, cause the uniform wave of electrical conduction to
become disrupted. The action potential wave scatters in a zigzag pattern and some
conduction paths becomes bidirectional, resulting in re-entry and eventually
arrhythmias. Scale: 100 μm. Adapted from
4
.

10
the regular heartbeat rhythm and cause sudden cardiac arrest
63
. Since cardiac myofibroblasts
residing in the scar tissue are in direct contact with cardiac myocytes within the infarct region, the
question of myocyte-fibroblast coupling resurfaces. Although most studies claim that cardiac
myocytes and fibroblasts do not electrically couple pre-infarction, whether fibroblasts and/or
myofibroblasts can express Cx43 and electromechanically couple to myocytes post-infarction has
been a major controversial topic for the past couple decades
64-67
. The question of heterotypic
electromechanical coupling between cardiac myocytes and fibroblasts/myofibroblasts has yet to
be answered primarily due to limitations of current in vitro cardiac tissue models integrating the
two cell types in a physiologically relevant orientation.

1.3. Existing Approaches to Investigate Cardiac Myocyte-Fibroblast
Interactions
Despite the plethora of knowledge regarding cardiac fibroblasts and myocytes pre- and
post- infarction, the precise role of fibroblasts/myofibroblasts in cardiovascular disease and their
interactions with neighboring cardiac myocytes is still mostly unknown. One reason for this
shortcoming is that the current models for studying cardiac myocyte-fibroblast interactions do not
fully recapitulate important physical and architectural aspects of healthy and fibrotic myocardium.
Specifically, the lack of spatially precise organization of the two cell types hinder development of
current therapies. In this section, we will delve into existing models for investigating this cellular
coupling and their respective limitations.

11
1.3.1. In Vivo and Ex Vivo Studies
In vivo and ex vivo models are mainly used by researchers to study myocardial pathology
in a holistic perspective since the cardiac cells remain integrated with the intact heart, which allows
native myocyte-fibroblast interaction to be studied. Amongst various in vivo and ex vivo studies,
there have been debates whether cardiac fibroblasts/myofibroblasts can form gap junctions with
neighboring cardiac myocytes. For example, one study has shown via immunohistochemistry that
cardiac myocytes and fibroblasts/myofibroblasts do not form gap junctions after a myocardial
infarction, but myofibroblasts do electrically couple to other myofibroblasts
68
. On the other hand,
several studies have shown that although Cx43 is not expressed in healthy fibroblasts
69
, the gap
junction protein is upregulated in myofibroblasts and is localized between cardiac myocytes and
myofibroblasts post-infarction
35, 70
. Furthermore, silencing Cx43 in myofibroblasts reduced
arrhythmogenesis as electrical coupling between the two cardiac cell types were disrupted
71
.
Overall, literature has been inconclusive regarding myocyte-fibroblast interactions.
Despite the advantage of utilizing in vivo and ex vivo models to study myocardial infarction,
they have intrinsic limitations that need to be addressed. Firstly, these models do not allow
researchers to isolate specific microenvironmental factors, such as ECM rigidity and tissue
alignment, that play important roles post-infarction. For example, if researchers were to induce a
myocardial infarction in a mouse and monitor ventricular remodeling, they would be unable to
conclude that one extracellular factor predominantly drives this process over the other factors. This
shortcoming prevents researchers from understanding the differential effects of mechanical
parameters after an infarction, which in turn hinders development of effective therapies that target
specific biochemical signaling pathways. Essentially, there is a tradeoff between complexity and
specificity when studying the disease. Secondly, almost all in vivo experiments regarding the heart

12
are conducted in animals, such as rats, mice, sheep, and canine. There are many ethical dilemmas
in conducting studies on a live human heart, as well as an extremely limited supply of donated
functional hearts. Although animal models are easier to procure, there is limited translation of the
studies to human patients as myocyte-fibroblast interactions post-infarction in humans may be
significantly different from what is observed in animals. Thus, the disparity in cardiac interactions
between species attenuates the relevance of current therapies to human patients. Finally,
conducting in vivo experiments in animals is relatively expensive, time consuming, and low-
throughput in terms of drug screening.

1.3.2. In Vitro Studies
In order to address the limitations of in vivo and ex vivo models, in vitro models have been
commonly utilized by researchers. An in vitro system involves isolating cells from animal or
human tissues, culturing the cells on plastic petri dishes or other substrates, and conducting various
experiments. These models allow researchers to study selective microenvironmental parameters
independently, utilize human-derived cell types in many cases, reduce costs of experimental design,
and obtain higher throughput. Thus, the mechanisms regarding intra- and intercellular changes in
healthy and diseased tissue can be elucidated, which provides a groundwork for effective therapies.
Two-dimensional in vitro models provide greater control of imaging, cell culturing, and
conducting electrophysiological measurements in examining the interaction between neonatal rat
cardiac myocytes and fibroblasts/myofibroblasts. Most studies obtain primary cardiac myocytes
and fibroblasts from one- or two-day-old neonatal rats by excising the ventricles, dissociating the
tissues, and separating the two cell types via pre-plating. In one study, a mixture of cardiac
myocytes and myofibroblasts
8
were uniformly seeded and immunostained for Cx43 (Figure 1-

13
7A). Cx43 was localized at the border, which confirmed the electrical coupling between the two
cell types in an isotropic condition. However, this system was unable to recapitulate the uniaxial
alignment of cardiac myocytes in the native myocardium, which limited physiological relevance.
To incorporate spatial organization, studies have micropatterned lanes of collagen and seeded the
heterotypic cells in a sequential manner
10, 11
. One form of micropatterning is the “sandwich”
technique, in which certain areas of the collagen lanes were temporarily blocked with adhesive
tape and removed after cardiac myocytes were seeded in the exposed region. Subsequently, the
tape was removed and cardiac myofibroblasts were seeded onto the remaining areas, which
resulted in myofibroblasts sandwiched between regions of cardiac myocytes (Figure 1-7B).
Electrophysiological assays
revealed a delay in electrical
propagation at the
myofibroblast border, which
quantitatively corresponded
to decreased conduction
velocity. The “sandwich”
co-culture attempted to best
mimic the cross-section of
an infarct zone, in which
aligned cardiac myocytes
and myofibroblasts would
be in direct contact at the
border. The second mode of
Figure 1-7. Current in vitro platforms for modeling neonatal rat cardiac co-
culture. (A) Cardiac myocytes and myofibroblasts were isotropically cultured,
and confocal microscopy image reveals Cx43 between the two cell types. α-
actinin: red, α-SMA: green, Cx43: yellow. Scale: 30 μm. Adapted from
8
. (B) A
region of myofibroblasts was surrounded by cardiac myocytes in a “sandwich”
formation, which introduced propagation delay at the interface. Scale: 50 μm.
Adapted from
4, 10
. (C) A rectangular network of stacked cardiac myocytes and
myofibroblasts exhibited Cx43 and Cx45 between the two cell types. Scale: 5 μm.
Adapted from
11, 12
.

14
micropatterning was depositing a network of collagen lanes and stacking a monolayer of
myofibroblasts on top of pre-seeded cardiac myocytes (Figure 1-7C), which promoted alignment
of cardiac myocytes and interactions with adjacent myofibroblasts. Myofibroblasts were able to
propagate action potentials from cardiac myocytes
67
and were immunostained to show Cx43
expression between the two cell types
11
, which provided evidence for heterotypic coupling.
Furthermore, on a biochemical and genetic level, electrical coupling increased with exogenous
TGF-β1 treatment
72
, whereas lentiviral knockdown of the Cx43 gene in myofibroblasts have
attenuated coupling with cardiac myocytes
73
. Collectively, most in vitro studies indicate the
presence of Cx43 between cardiac myocytes and myofibroblasts.
Despite the many advantages of in vitro systems, the current models exhibit some intrinsic
limitations. First, almost none of the studies were conducted with human-derived cardiac myocytes
and fibroblasts. Most of these experiments were conducted with primary neonatal rat cardiac cells,
which do not translate well to studying cardiac fibrosis in humans. Additionally, neonatal
mammalian hearts are able to fully regenerate after an infarction and maintain the quiescent
myocyte and fibroblast interactions as observed in the healthy heart
74, 75
, which further confounds
the translation to adult patients who typically suffer from this disease. Second, current
micropatterning techniques allowed the cells to exhibit either the “sandwich” organization or
separate monolayers stacked on top of each other. Although researchers were able to incorporate
alignment in studying the electrical coupling of myocytes and fibroblasts/myofibroblasts, the
“sandwich” method is a series of isolated lanes, which does not fully recapitulate the continuous
sheet of fibroblasts interspersed between aligned cardiac myocytes. Furthermore, this method
utilized adhesive tape to block specific regions of the lanes, which limited the spatial resolution
needed to generate in vitro ventricular tissues with precision. For the other micropatterned

15
platforms, the fact that these two cell types are on different planes prevent other
microenvironmental factors, such as ECM rigidity and dynamic mechanical forces, to affect these
cells uniformly. As we want to recapitulate the native microenvironment as accurately as possible,
there is a need for a two-dimensional in vitro platform that generates heterotypic, spatially
organized striated muscle tissues with user control over various microenvironmental cues that
affect cell fate.

1.4. Outlook
As described previously, the remodeling of the ventricular myocardium after an infarction
results in an increase of ECM rigidity, disorganization of the longitudinally aligned cardiac
myocytes, and potential electrical coupling between myocytes and fibroblasts/myofibroblasts. The
ECM is composed of primarily collagen I fibers due to excessive protein synthesis of
myofibroblasts that persist in the fibrotic scar tissue. The substantial increase in rigidity results in
ventricular dilation to compensate for the decreased compliance of the myocardial wall, which
disrupts the alignment and plummets cardiac output. On a cellular level, the relative contribution
of biochemical and mechanical cues that drive fibroblast differentiation into myofibroblast is
nebulous, which convolutes the development of effective therapies. Furthermore, the shift in ECM
composition and disarray of cardiac myocytes result in an electrical interference of action
potentials that lead to arrhythmias and potential heart failure. The specific electromechanical
mechanism behind the interaction of cardiac myocytes and fibroblasts/myofibroblasts remains
elusive, mainly due to limitations of existing models.
Previous systems are unable to fully recapitulate the infarct border due to intrinsic
limitations regarding lack of human relevance, poor spatial organization of cardiac co-cultures,

16
and lack of incorporation of certain microenvironmental parameters. However, tissue engineering
techniques, such as microcontact printing, in conjunction with synthetic biology can potentially
address these issues and provide a more biomimetic platform. By incorporating ECM rigidity,
cellular alignment, biochemical factors, and synthetic cues, we can determine how these
microenvironmental cues individually and/or synergistically affect cardiac fibroblast phenotypes
and alter cell fate in general. In order to understand the big picture of the interaction between
cardiac fibroblasts/myofibroblasts and myocytes, we need to (1) elucidate the specific biological
mechanisms driving fibroblast differentiation into myofibroblasts and (2) engineer a platform that
can control cell fate to generate spatially organized striated muscle tissues that best recapitulate
the native microenvironment, such as a healthy and diseased myocardium.

1.5. Objective and Aims
As explained in previous sections, cardiac fibrosis and remodeling drive changes in the
microenvironment that affect cardiac fibroblast and myocyte phenotypes. However, the relative
contribution of microenvironmental parameters that affect fibroblasts/myofibroblasts and their
interaction with cardiac myocytes remain unclear due to limitations of existing in vitro cardiac co-
culture models. Thus, our goal is to develop new tools for precisely engineering heterotypic muscle
tissues by controlling fibroblast fate with natural and synthetic cues. We will first identify the
chemical and biomechanical cues that regulate human cardiac fibroblast differentiation into
myofibroblasts. Then, we will utilize synthetic cues to regulate transdifferentiation of fibroblasts
into striated muscle cells to engineer heterotypic muscle tissues with spatial precision.
Understanding natural and synthetic cues for controlling fibroblast fate allows us to generate
heterotypic muscle tissues with physiologically relevant parameters, such as heterotypic cell-cell

17
interactions, native architecture, ECM rigidity, and biochemical signaling pathways, to resolve
limitations of current in vitro models. This project will elucidate the interplay of
microenvironmental cues that are present in pathological remodeling and a novel approach using
synthetic cues to engineer improved in vitro striated muscle models for drug discovery and
therapeutics.

18
Chapter 2 TGF-β1 Dominates Extracellular Matrix Rigidity
for Inducing Differentiation of Human Cardiac Fibroblasts to
Myofibroblasts
Aim 1: Identify the effects of ECM rigidity and TGF-β1 on human cardiac fibroblast
differentiation into myofibroblasts.

2.1. Introduction
Ventricular myocardium consists of cardiac myocytes embedded in an extracellular matrix
(ECM) network synthesized and maintained primarily by cardiac fibroblasts. After many forms of
injury, cardiac fibroblasts and their activated derivatives, myofibroblasts, play a critical role in the
wound healing response. For example, after a myocardial infarction, cardiac myocytes
downstream of an occluded coronary artery undergo injury that can progress to apoptosis. This
initiates an inflammatory response and recruitment of macrophages and neutrophils
39, 40
.
Neutrophils secrete various cytokines and growth factors, including transforming growth factor
beta 1 (TGF-b1), which binds to TGF-b receptors and activates the TGF-b/Smad pathway in
fibroblasts
76
. Smad proteins translocate to the nucleus and upregulate transcription of ECM
proteins and alpha smooth muscle actin (α-SMA), a critical component of contractile
microfilaments expressed in myofibroblasts
42, 43
. Consequently, myofibroblasts deposit more
ECM molecules and are more contractile than quiescent fibroblasts, exhibiting a phenotype
intermediate to fibroblasts and smooth muscle cells
44
. After an infarction, activated myofibroblasts
proliferate, contract, and deposit ECM molecules at the site of injury, ultimately forming stiff,
fibrotic tissue
45
and providing mechanical stability to compensate for any loss of myocytes
7
. In

19
other tissue types, such as skin, myofibroblasts typically undergo apoptosis after repairing minor
injuries
77
. However, myofibroblasts persist in the myocardium due to the nominal regeneration of
cardiac myocytes. These lingering myofibroblasts can contribute to many pathological outcomes
78,
79
, including arrhythmias by interfering with cardiac myocyte cell-cell communication
64-67
.
Although cardiac myofibroblasts are known to contribute to many injury responses and
pathological remodeling processes in the ventricle, the cues that induce the differentiation of
human cardiac myofibroblasts from fibroblasts are still incompletely understood. In animal
models, TGF-b1 has been shown to activate the differentiation of fibroblasts to myofibroblasts
and contribute to cardiac hypertrophy and fibrosis
80, 81
. Similarly, exogenous TGF-b1 applied in
vitro has been shown to induce myofibroblast differentiation in skin, lung, kidney, and cardiac
fibroblasts
43, 46, 47, 82, 83
. Mechanical stimuli have also been shown to activate the fibroblast to
myofibroblast transition. For example, the in vitro differentiation of bronchial
84
, valvular
85
, and
cardiac
86
fibroblasts to myofibroblasts increases with increasing rigidity of the substrate,
suggesting that fibrotic scar tissue, which is deposited by myofibroblasts themselves, could
positively reinforce myofibroblast phenotypes. Other forms of mechanical stimulation, including
cyclic stretch
87
and perpendicularly-applied forces
88
, have also been shown to induce
differentiation of cardiac fibroblasts into myofibroblasts. Additionally, increased substrate rigidity
has been shown to promote the TGF-b1-induced differentiation of bronchial
89
and portal
90

fibroblasts to myofibroblasts, suggesting that chemical and biomechanical cues can have
combinatorial, or potentially synergistic, effects on fibroblast-myofibroblast phenotypes.
However, the relative contributions of TGF-b1 and ECM rigidity to cardiac fibroblast-
myofibroblast differentiation has not been established, which is important for delineating the
microenvironmental cues that have the greatest impact and potential as therapeutic targets after

20
myocardial injury. Additionally, most studies with cardiac fibroblasts to date have been limited to
primary rodent fibroblasts, which may not translate to humans.
Our objective was to determine how increases in ECM rigidity and TGF-b1 exposure
independently and jointly regulate human cardiac fibroblast-myofibroblast phenotype. We chose
these two cues because they are both present in injured myocardium and have previously been
shown to independently induce differentiation of fibroblasts to myofibroblasts, although primarily
in non-human cell types
86, 91
. First, we cultured primary human cardiac fibroblasts on coverslips
coated with polydimethylsiloxane (PDMS) of three distinct elastic moduli, treated cells with TGF-
b1, and quantified α-SMA expression over time by immunostaining and quantitative real-time
PCR (RT-PCR). Overall, our results indicate that α-SMA expression on the gene and protein level
is more dominantly regulated by exogenous TGF-b1 compared to substrate rigidity. We also used
RT-PCR to quantify expression of other proposed fibroblast/myofibroblast markers, such as
periostin. However, the secondary markers that we evaluated were less robustly regulated by TGF-
β1 compared to α-SMA. Due to the proposed role of cardiac fibroblasts/myofibroblasts in
arrhythmogenesis, we also quantified the expression of GJA1, which encodes for connexin 43
(Cx43) protein. However, we did not identify any significant differences in GJA1 expression due
to TGF-b1 or matrix rigidity. Finally, to determine if myofibroblast phenotype is reversible, we
re-plated myofibroblasts activated by TGF-b1 onto new coverslips and maintained them without
TGF-b1, which led to a partial reversal to the fibroblast phenotype. Collectively, these results
provide new insights into how human cardiac fibroblast and myofibroblast phenotypes are
differentially regulated by chemical and biomechanical cues present in pathological cardiac
microenvironments. These data can contribute to the identification of new therapeutic targets for
slowing or reversing the transition of fibroblasts to myofibroblasts, which could ultimately

21
minimize fibrosis. Additionally, the approaches we developed to dictate human cardiac fibroblast
and myofibroblast phenotypes can be leveraged for future in vitro studies, such as co-culturing
with cardiac myocytes or engineering more precise multi-cellular human cardiac disease models.

2.2. Materials and Methods
2.2.1. Fabrication of Tunable PDMS Substrates
Three types of polydimethylsiloxane (PDMS) with distinct elastic moduli were prepared
using Sylgard 184 silicone elastomer and Sylgard 527 silicone dielectric gel (Dow Corning,
Midland, MI, USA). Pure Sylgard 184, referred to as high, was prepared by mixing the base
component with the curing agent at a 10:1 mass ratio. Pure Sylgard 527, referred to as low, was
prepared by mixing components A and B at a 1:1 mass ratio. A 1:20 mass ratio of Sylgard 184 and
Sylgard 527, referred to as moderate, was also prepared, similar to previous studies
92-94
. Each
substrate was mixed and degassed using a planetary centrifugal mixer (AR-100, Thinky, Japan)
and spin-coated onto 25 mm diameter glass coverslips (Electron Microscopy Sciences, Hatfield,
PA, USA) using a G3P-8 spincoater (Specialty Coating Systems, Indianapolis, IN, USA), as
described previously
20
. PDMS-coated coverslips were treated with ultraviolet ozone cleaner
(Jelight Company Inc., Irvine, CA, USA) for eight minutes, uniformly coated with 150 µL of
human fibronectin (50 µg/mL, Corning, Corning, NY, USA) or rat tail collagen type I (200 µg/mL,
Corning) for two minutes, rinsed with PBS, and maintained at room temperature until seeded with
cells on the same day.

22
2.2.2. Cell Culture
Primary human cardiac fibroblasts (Lot 3131, Cell Applications Inc., San Diego, CA, USA)
were thawed into a 75 cm
2
cell culture flask with fibroblast growth medium, consisting of low
glucose DMEM (1 g/L glucose) supplemented with 10% v/v fetal bovine serum (FBS) (Gibco,
Waltham, MA, USA) and 1% v/v penicillin-streptomycin solution (10,000 U/mL penicillin,
10,000 µg/mL streptomycin). Cells were passaged at 90% confluence into 175 cm
2
cell culture
flasks by incubating the cells with trypsin-EDTA for four minutes at room temperature,
immediately adding trypsin neutralizing solution, centrifuging the cell solution at 300 g for five
minutes, and re-suspending the cell pellet in fibroblast growth medium. These cells were
subsequently seeded onto PDMS coverslips in six-well plates at a density of 36,500 cells/cm
2
and
serum-arrested with 0.1% or 0.5% serum the following day. Cells used for experiments were
between passages four and eight. After an additional 48 hours, TGF-b1 (2 or 10 ng/mL, R&D
Systems, Minneapolis, MN, USA) was added to select wells. Media was replenished every 48
hours, including the re-application of TGF-b1 for treated wells.
For re-plating experiments, TGF-b1-treated and untreated fibroblasts maintained on high
PDMS-coated coverslips for six days were dissociated with trypsin-EDTA for two minutes.
Constructs were placed in the incubator for one minute during dissociation to enhance cell
detachment. The trypsin solution was immediately neutralized with trypsin neutralizing solution
and the cell solution was centrifuged at 300 g for five minutes at 4
°
C. The supernatant was aspirated
and 2 mL of growth media was added to re-suspend the cell pellet. The cells were seeded onto new
PDMS-coated coverslips of high stiffness and serum-arrested with 0.1% serum the following day.

23
2.2.3. Immunostaining
Cells were fixed with 4% paraformaldehyde for ten minutes and subsequently
permeabilized with 0.2% Triton X-100 solution for ten minutes. Fixed cells were incubated with
a monoclonal mouse anti-a-SMA (1:200, Thermo Fisher Scientific, Waltham, MA, USA) primary
antibody overnight at 4
o
C. After PBS rinses, cells were incubated with DAPI (1:200, Life
Technologies, Waltham, MA, USA), Alexa Fluor 488 Phalloidin (1:200, Life Technologies), and
Alexa Fluor 546 goat anti-mouse secondary antibody (1:200, Life Technologies) for 90 minutes at
room temperature. Coverslips were mounted onto glass slides with a drop of ProLong Gold Anti-
Fade Mountant (Life Technologies), and sealed with nail polish.

2.2.4. Microscopy and Image Analysis
High-resolution fluorescent images were captured using a 60X oil objective on a Nikon C2
point-scanning confocal microscope. Lower-resolution fluorescent images at nine locations
dispersed across the coverslips were captured using a 20X air objective on a Nikon Eclipse Ti-S
inverted fluorescent microscope and an Andor Zyla scientific CMOS camera. A 2x2 tile scan with
15% overlap was utilized to increase sampling area (total field of view: 1.56 mm x 1.32 mm).
To analyze tile scan images, a custom macro was written in ImageJ to automatically count
the total number of nuclei per field of view based on DAPI fluorescence. A Gaussian Blur (value
of 4.0) was first applied to blur the image and minimize variances in pixel color exposure. Next,
manual thresholding of the image was used to generate a black background with white ellipses
corresponding to nuclei. The Watershed function was applied to delineate and separate overlapping
nuclei. The Analyze Particles function was used to set the size range of the particles from 20 μm
2

to infinity to ensure only nuclei were counted and small background noise was omitted. Manual

24
thresholding of actin and a-SMA images was used to quantify the total actin-positive pixels and
the total a-SMA-positive pixels, respectively. These values were divided by the total number of
pixels in the image to determine actin and a-SMA coverage, respectively.

2.2.5. Gene Expression Analysis
mRNA transcripts were isolated and collected using the Aurum Total RNA Mini Kit (Bio-
Rad, Hercules, CA, USA). mRNA concentrations and 260/280 ratios were measured with a
Nanodrop (Thermo Fisher Scientific). As needed, a SpeedVac Concentrator (Thermo Fisher
Scientific) was used to increase mRNA concentration. Only mRNA concentrations above 90 ng/μL
and 260/280 ratios above 2.0 were used for cDNA synthesis. cDNA was then synthesized via
reverse transcription using the iScript Reverse Transcription Supermix for RT-qPCR kit (Bio-Rad)
and was stored at -80
o
C. qPCR was performed by mixing SsoAdvanced Universal SYBR Green
Supermix (Bio-Rad), cDNA, and various primers (Bio-Rad) into a 384-well PCR plate, according
to the instructions of the manufacturer. The plate was inserted into the CFX384 Touch Real-Time
PCR Detection System (Bio-Rad) to obtain cycle threshold (Ct) data sets for each condition. Gene
expression was normalized relative to the housekeeping gene GAPDH. Average expression values
were computed using the standard comparative Ct method, as described previously
95
.

2.2.6. Statistics
All data sets were first validated for normality using the Kolmogorov-Smirnov test in
MATLAB (MathWorks, Natick, MA, USA). The data were then analyzed using one-way and/or
two-way ANOVA followed by Tukey’s test for multiple comparisons in MATLAB, with a set to

25
0.05. Data for each condition was gathered from at least four independent experiments and
multiple regions of interest per sample were collected and averaged for image analysis.

2.3. Results
2.3.1. Effects of ECM Ligand, Serum Concentration, and TGF-b1 Concentration on Human
Cardiac Fibroblast Adhesion and Differentiation
To determine the independent and combined effects of substrate rigidity and TGF-b1 on
the phenotype of primary human cardiac fibroblasts, we first established our experimental
parameters in a series of pilot experiments. To determine the optimal ECM ligand for long-term
cell adhesion, we coated high PDMS coverslips with 50 µg/mL of human fibronectin or 200 μg/mL
rat tail collagen type I. We seeded substrates with primary human cardiac fibroblasts and, after one
day, reduced FBS levels to 0.1% or 0.5%. We tested these two levels of FBS because high-serum
can cause uncontrolled myofibroblast differentiation due to the presence of many confounding
molecules in FBS, but low-serum can compromise cell adhesion. Next, we treated cells with 10
ng/mL TGF-b1 (a relatively high dose) and stained cells for nuclei, actin, and a-SMA after five
days. To characterize cell phenotypes, we quantitatively analyzed our immunostained images
(Figure 2-1A). To access cell density, we applied a threshold to images of nuclei and quantified
nuclei per mm
2
. Because myofibroblasts are morphologically flatter and more elongated compared
to small, spindle-like fibroblasts
96, 97
, we also quantified actin coverage as proxy for cell size. As
shown in Figures 2-2A and 2-2B, cell density and actin coverage were similar in both FBS
concentrations, but were much lower on collagen I compared to fibronectin. Next, we quantified
α-SMA/actin coverage because α-SMA is only expressed by myofibroblasts and therefore α-
SMA/actin coverage reflects the percentage of myofibroblasts. α-SMA/actin coverage was high in

26
all conditions, as expected due to TGF-β1 treatment. Additionally, α-SMA/actin coverage was
independent of ECM ligand and serum concentration (Figure 2-2C), suggesting that myofibroblast
differentiation was unaffected by either variable. Thus, based on these pilot experiments, we
selected fibronectin as our ECM ligand and 0.1% serum to maximize cell adhesion and minimize
proliferation and any other confounding effects of serum.
Previous studies have utilized TGF-b1 concentrations ranging from 2 to 10 ng/mL and
maintained fibroblasts and myofibroblasts anywhere from two to five days
46, 47, 98-100
. Thus, we
next characterized the effects of 2 and 10 ng/mL TGF-b1 over five days in culture to establish the
optimal dosing and time course of TGF-β1 activation. As shown in Figure 2-3A, cell density was
Figure 2-1. Image processing techniques and experimental timeline. (A) Representative raw and thresholded
images of nuclei, actin, and α-SMA in untreated and TGF-β1 treated human cardiac fibroblasts (scale bars: 200 μm).
(B) Experimental timeline for culturing cardiac fibroblasts with reduced serum and TGF-β1 treatment.

27
relatively similar between control and 2 and 10 ng/mL of TGF-β1, with a slight decrease over time
in culture in all conditions. However, actin (Figure 2-3B) and a-SMA/actin (Figure 2-3C)
coverage in both TGF-β1 conditions were similar and higher than the control condition, suggesting
that 2 and 10 ng/mL TGF-β1 have a similar effect on myofibroblast differentiation. Additionally,
nearly all cells were differentiated after three and five days of treatment. Given these results, we
selected 2 ng/mL TGF-β1 and five days of treatment as the upper limit for remaining experiments.
Figure 2-2. Optimization of ECM ligand and serum concentration for human cardiac fibroblast culture. Human
cardiac fibroblasts were seeded onto high PDMS-coated coverslips coated with the indicated ECM ligand. After one
day, serum levels were reduced to the indicated levels and cells were treated with 10 ng/mL TGF-β1 for five days,
followed by staining and imaging. Cell density (A), actin coverage (B), and α-SMA/actin coverage (C) was quantified
(n=1).
Figure 2-3. Optimization of TGF-β1 concentration. Human cardiac fibroblasts were seeded onto high PDMS-
coated coverslips coated fibronectin. After one day, serum was reduced to 0.1% and cells were treated with 0, 2, or
10 ng/mL TGF-β1 for one, three, and five days, following by staining and imaging. Cell density (A), actin coverage
(B), and α-SMA/actin coverage (C) was quantified (n=1).

28
2.3.2. Regulation of Cardiac Myofibroblast Differentiation by TGF-b1 and ECM Rigidity
To test the impact of ECM rigidity and TGF-β1 on the differentiation of human cardiac
fibroblasts to myofibroblasts, we next fabricated three types of PDMS-coated coverslips with
elastic moduli of 1.61 kPa, 27.4 kPa, and 2.68 MPa
94
, referred to as low, moderate, and high. These
substrates were selected because they roughly mimic the rigidity and/or mechanical load
experienced by fibroblasts in a developing heart, a healthy heart, and a fibrotic and/or pressure
overload heart
45, 101
. Based on our optimization experiments, we coated these coverslips with
human fibronectin, seeded them with primary human cardiac fibroblasts, and reduced serum to
0.1% after one day. After an additional two days in culture, we introduced 2 ng/mL of TGF-b1 to
select coverslips and immunostained both untreated and treated cells after an additional one, three,
and five days in culture (Day 1, 3, and 5), as shown in Figure 2-1B. Next, we captured high
resolution images to characterize α-SMA expression and localization. As shown in Figure 2-4, we
observed actin fibers in all cells in all conditions. In select cells, we also observed a-SMA signal
Figure 2-4. Cell morphology and α-SMA expression due to ECM rigidity and TGF-β1 treatment. Representative
images of human cardiac fibroblasts cultured for five days on low, moderate, and high PDMS-coated coverslips with
or without 2 ng/mL TGF-β1 (blue: nuclei, green: actin, red: α-SMA, scale bars: 25 μm).

29
co-localized with actin fibers, which is a hallmark of myofibroblasts. We also observed that most
cells treated with TGF-β1 were positive for a-SMA on low, moderate, and high PDMS substrates.
However, without TGF-β1 treatment, fewer than half the cells were positive for a-SMA on all
PDMS substrates. Additionally, cells treated with TGF-β1 qualitatively occupied more surface
area compared to untreated cells. Thus, TGF-β1 appeared to have a more substantial effect on
myofibroblast differentiation compared to ECM rigidity.
To quantify differences in phenotype, we next captured multiple lower resolution tile scans
to increase our sampling area and quantified nuclei density, actin coverage, and a-SMA/actin
coverage, as described above (Figure 2-1A). Within each time point, we first compared cell
density across all conditions using one-way ANOVA and multiple comparisons and found no
significant differences (Figure 2-5A). However, we did observe a general downward trend in cell
density with time, which is likely because the low-serum media arrested proliferation. We also
conducted a two-way ANOVA to quantify the independent effects of substrate rigidity and TGF-
b1 treatment on nuclei density (Table 2-1) and similarly found no significant differences at any
timepoint. These results suggest that neither substrate rigidity nor TGF-b1 treatment had a
significant impact on cell adhesion, proliferation, and/or apoptosis.
We next quantified actin coverage to characterize cell size. Based on one-way ANOVA
and multiple comparison analysis, we observed no significant differences after one day of TGF-
β1 treatment (Figure 2-5B). On Days 3 and 5, we observed several instances of statistically higher
actin coverage in TGF-b1 treated cells compared to untreated cells, but no differences due to
rigidity. Our two-way ANOVA analysis similarly demonstrated that actin coverage was regulated
by TGF-b1, but not ECM rigidity, on Days 3 and 5. Higher actin coverage combined with a
relatively similar nuclei count implies that cells treated with TGF-b1 had a larger surface area than

30
those without TGF-b1, which is consistent with a
myofibroblast phenotype in TGF-b1-treated cells.
We next compared a-SMA/actin coverage
within each timepoint because a-SMA is the most
widely-used marker for cardiac myofibroblasts.
On Day 1, our one-way ANOVA and multiple
comparison tests revealed that TGF-b1-treated
cells on high PDMS had significantly greater a-
SMA/actin coverage compared to all untreated
cells (Figure 2-5C), suggesting that high substrate
rigidity promoted TGF-b1-mediated
differentiation to myofibroblasts. Additionally, on
Day 3, cells on high PDMS without TGF-b1 had
higher a-SMA/actin coverage compared to cells
on moderate PDMS without TGF-b1, potentially
because high substrate rigidity promoted
myofibroblast differentiation, even without TGF-
b1. However, on Days 3 and 5, TGF-b1 was the
dominant regulator of fibroblast differentiation, as
all treated cells had significantly higher a-
SMA/actin coverage than all untreated cells,
independent of substrate rigidity. Our two-way
ANOVA analysis (Table 2-1) identified that a-
Figure 2-5. Quantification of cell morphology and
α-SMA expression due to ECM rigidity and TGF-
β1 treatment. Human cardiac fibroblasts were
cultured on low, moderate, and high PDMS-coated
coverslips with or without 2 ng/mL TGF-β1 for one,
three, and five days. Cells were immunostained and
cell density (A), actin coverage (B), and α-SMA/actin
coverage (C) were quantified from immunostained
images (n = 4, bars indicate mean +/- standard error of
the mean, *p< 0.05 and **p< 0.01 according to one-
way ANOVA and Tukey’s test for multiple
comparisons.)

31
SMA/actin coverage was regulated by TGF-b1 on Days 1, 3, and 5. However, substrate rigidity
regulated a-SMA/actin coverage on Day 3, suggesting that this parameter also has an impact,
although less prominent than TGF-β1. Collectively, these data suggest that the differentiation of
fibroblasts to myofibroblasts is regulated predominantly by TGF-b1 compared to ECM rigidity,
but that ECM rigidity potentially accelerates the differentiation process.

Table 2-1. Two-way ANOVA p-values (n = 4). Data for all conditions was normally distributed, as determined by the
Kolmogorov-Smirnov test. *p<0.05.

Day ECM Rigidity TGF-β1 Interaction
Cell Density
1 0.5316 0.8926 0.7083
3 0.3082 0.1459 0.8041
5 0.6812 0.1569 0.9875
Actin Coverage
1 0.1268 0.8791 0.7008
3 0.3607 <0.0001* 0.7373
5 0.7807 <0.0001* 0.9068
α-SMA/Actin Coverage
1 0.0655 <0.0001* 0.5635
3 0.0474* <0.0001* 0.0283*
5 0.3342 <0.0001* 0.1021
ACTA2 Relative
Expression
1 0.3255 <0.0001* 0.4763
3 0.6160 <0.0001* 0.7983
POSTN Relative
Expression
1 0.8103 <0.0001* 0.2997
3 0.6836 0.1872 0.4287
FAP Relative Expression
1 0.8928 0.0032* 0.3781
3 0.4506 0.0016* 0.0670
FSP1 Relative Expression
1 0.5935 <0.0001* 0.1548
3 0.5417 0.0172* 0.5088
GJA1 Relative Expression
1 0.8300 0.8398 0.2188
3 0.0953 0.9058 0.0609

32
2.3.3. Expression of Fibroblast- and Myofibroblast-Associated Genes due to TGF-b1 and ECM
Rigidity
To determine if ECM rigidity and/or TGF-b1 impact transcription, we first performed RT-
PCR on Days 1 and 3 to quantify expression of the ACTA2 gene, which encodes for a-SMA. Our
one-way ANOVA and multiple comparison analysis indicated that ACTA2 was significantly
upregulated in nearly all TGF-b1-treated cells on both Day 1 and Day 3 compared to untreated
cells, independent of substrate rigidity (Figure 2-6A). This result was corroborated with our two-
way ANOVA test (Table 1), which indicated that ACTA2 expression was regulated by TGF-b1,
but not substrate rigidity, on Days 1 and 3. Compared to our RT-PCR data, our immunostaining
results did not show stark distinctions due to TGF-b1 treatment as early as Day 1, but this could
be due to the delay between transcription and translation. Also unlike our immunostaining results,
we did not detect any differences in ACTA2 expression due to rigidity. However, the differences
we observed with immunostaining were relatively subtle and could be attributed to differences in
assay sensitivity. Thus, our RT-PCR data for ACTA2 is mostly consistent with our immunostaining
results for a-SMA, as both datasets suggest that TGF-b1 dominates over ECM rigidity in
differentiating human cardiac fibroblasts to myofibroblasts.
We also used RT-PCR to quantify expression of POSTN and FAP because these genes
have been proposed in the literature as markers of myofibroblasts. POSTN encodes for periostin,
an osteogenic protein commonly expressed in mesenchymal cells that interacts with structural
components of the ECM and is associated with fibrosis. Studies have shown that periostin is
expressed by myofibroblasts after myocardial infarction
102
and in dermal wounds
103
. On Day 1,
we observed increases in POSTN expression in TGF-β1 treated cells on moderate PDMS compared
to untreated cells on soft and moderate PDMS by one-way ANOVA and multiple comparisons

33
(Figure 2-6B). Our two-way ANOVA analysis revealed that POSTN expression is regulated by
TGF-b1 on Day 1, but not substrate rigidity (Table 2-1). On Day 3, we observed no differences in
POSTN expression by one-way or two-way ANOVA, suggesting that POSTN sensitivity to TGF-
β1 decreases over exposure time. FAP encodes for fibroblast activation protein (FAP), which has
been associated with proliferation and migration of activated stromal fibroblasts in human
carcinomas
104
. Myofibroblasts were also shown to express FAP after myocardial infarction in vivo
and in response to TGF-b1 in vitro
105
. In our study, the only statistical differences we observed
through one-way ANOVA and multiple comparisons was an increase in FAP expression in TGF-
b1-treated cells on low and moderate PDMS compared to untreated cells on moderate PDMS on
Day 3 (Figure 2-6C). However, our two-way ANOVA analysis indicated that FAP expression is
regulated by TGF-b1 on Day 1 and Day 3. Thus, in several instances, both POSTN and FAP
expression was higher in TGF-b1-treated cells compared to untreated cells, although results were
not as consistent as ACTA2.
We next measured FSP1 expression using RT-PCR. FSP1 encodes for fibroblast specific
protein-1 (FSP1), which promotes fibrosis and is shown to be upregulated in rat cardiac fibroblasts
after myocardial infarction
106
. However, FSP1 is also known to be expressed by many non-
fibroblast cell types after an infarction, including endothelial cells and hematopoietic cells
107
.
Thus, it is unclear if FSP1 is a robust marker for identifying fibroblasts versus myofibroblasts. Our
one-way ANOVA test revealed several decreases in FSP1 expression in TGF-b1-treated cells
compared to untreated cells (Figure 2-6D), but no differences on Day 3. Our two-way ANOVA
test indicated that FSP1 expression is regulated by TGF-b1 on both Day 1 and Day 3 (Table 2-1).
These results suggest that FSP1 expression is reduced due to TGF-β1 treatment in primary human
cardiac fibroblasts and mostly unaffected by matrix rigidity.

34

GJA1 encodes for Cx43, the major gap junction protein expressed by cardiac myocytes in
ventricular myocardium to facilitate cell-to-cell action potential propagation
108
. The ability of
fibroblasts and/or myofibroblasts to express Cx43 and form functional gap junction channels with
cardiac myocytes has been widely debated
64-67
. Thus, we used RT-PCR to investigate if GJA1
expression is impacted by TGF-β1 and/or matrix rigidity in human cardiac fibroblasts. Both our
Figure 2-6. Relative changes in gene expression due to ECM rigidity and TGF-β1 treatment. Human cardiac
fibroblasts were cultured on low, moderate, and high PDMS-coated coverslips with or without 2 ng/mL TGF-β1 for
one, three, and five days. RT-PCR was used to quantify the relative expression of (A) ACTA2, (B) POSTN, (C) FAP,
(D) FSP1, and (E) GJA1. All data was normalized to high PDMS control group on Day 1. (n = 4, bars indicate mean
+/- standard error of the mean, *p< 0.05 and **p< 0.01 according to one-way ANOVA and Tukey’s test for multiple
comparisons.)

35
one-way (Figure 2-6E) and two-way ANOVA (Table 2-1) analysis indicated no significant
differences in GJA1 expression between untreated and TGF-β1-treated cells at Day 1 or 3,
suggesting that fibroblasts and myofibroblasts in monoculture express similar levels of GJA1.

2.3.4. Reversibility of Myofibroblast Phenotype

Myofibroblasts are thought to de-differentiate into quiescent fibroblasts after
differentiation stimuli are removed
85, 109
. However, the extent of reversibility has not been
thoroughly investigated, especially in human cardiac myofibroblasts. To establish if human
cardiac myofibroblasts can de-differentiate, we first cultured fibroblasts for three days in the
absence and presence of TGF-b1 on high PDMS to generate fibroblasts and myofibroblasts,
respectively. Because ECM rigidity had a minimal impact on phenotype, we excluded this as a
variable for these experiments. Next, we trypsinized and re-plated the cells onto high PDMS-
coated coverslips and maintained them in the absence of TGF-b1. After an additional two and
seven days, we immunostained re-plated cells for nuclei, actin, and a-SMA and characterized
Figure 2-7. Quantification of cell morphology and α-SMA expression after re-plating untreated and TGF-β1-
treated cells in the absence of TGF-β1. On Day 3, untreated and TGF-β1-treated cells on high PDMS coverslips
were trypsinized, re-plated onto high PDMS coverslips, and maintained without TGF-β1 for an additional two and
seven days. Cells were immunostained and cell density (A), actin coverage (B), and α-SMA/actin coverage (C) were
quantified from immunostained images (n = 4, bars indicate mean +/- standard error of the mean, *p< 0.05 and **p<
0.01 according to one-way ANOVA and Tukey’s test for multiple comparisons.)

36
their phenotype using the image processing tools described above. Cell density was similar in all
conditions and did not significantly change over the seven days (Figure 2-7A). However, actin
coverage was significantly higher in cells pre-treated with TGF-β1 compared to untreated cells,
although the difference became smaller over time (Figure 2-7B). a-SMA/actin coverage was
significantly higher in cells pre-treated with TGF-b1 compared to untreated cells on Day 2 and
Day 7 (Figure 2-7C), although the differences were not as substantial compared to our earlier
experiments with sustained TGF-β1 treatment (Figure 2-5). These data indicate that
myofibroblasts partially maintain their phenotype for at least a week after re-plating and TGF-β1
withdrawal.

2.4. Discussion
In the myocardium, many forms of injury and pathological remodeling are associated with
increases in both ECM rigidity and TGF-b1 secretion by immune cells. However, the relative
contribution of each of these microenvironmental cues in the differentiation of human cardiac
fibroblasts to myofibroblasts has not been clearly established with existing in vivo and in vitro
models. To address this, we cultured primary human cardiac fibroblasts on tunable PDMS
substrates to control ECM rigidity and selectively treated cells with TGF-b1. Our results suggest
that the rigidity of the microenvironment has some subtle effects on differentiation, but overall,
TGF-β1 treatment dominates myofibroblast differentiation. These data suggest that the
differentiation of cardiac fibroblasts to myofibroblasts is more sensitive to inflammatory responses
after injury rather than increases in ECM rigidity secondary to fibrotic remodeling. We also
quantified the expression of several genes previously associated with fibroblasts or myofibroblasts
to establish their robustness as indicators of cell phenotype in vitro. Although some secondary

37
markers trended with one phenotype, ACTA2 was the only gene consistently regulated by TGF-β1
treatment.
In our study, we first used cell density, actin coverage, and α-SMA/actin coverage as
benchmarks to select an ECM ligand type, serum concentration, and TGF-β1 dose that maintained
cell adhesion and viability and minimized any confounding effects due to these factors. Based on
these data, we cultured cells on fibronectin instead of collagen I because cell adhesion was
substantially higher on fibronectin compared to collagen I. However, a-SMA/actin coverage was
similar on both substrates, which indicates that myofibroblast activation was unaffected by ECM
ligand. In many fibrotic conditions, such as after a myocardial infarction, both collagen I and
fibronectin are increased
39, 50
. Thus, both ligands represent aspects of the native cardiac
microenvironment. We also found that cell density, actin coverage, and α-SMA/actin coverage
was similar in 0.1% and 0.5% FBS and with 2 and 10 ng/mL TGF-β1, suggesting that our results
are likely independent of FBS and TGF-β1 concentrations within these ranges.
To delineate the impact of ECM rigidity and TGF-β1, we uniformly coated fibronectin
onto PDMS-coated coverslips with elastic moduli of 1.61 kPa, 27.4 kPa, and 2.68 MPa. These
values roughly correspond to developing myocardium, healthy myocardium
101, 110
, and
myocardium that is highly fibrotic and/or under high pressure overload
45, 111
, two conditions
commonly observed after an infarction and other forms of injury. Although PDMS has highly
synthetic properties, it is easier to controllably fabricate and handle for experimental measurements
(especially microscopy) compared to many ECM-derived biomaterials. Thus, we could monitor
fibroblast differentiation due to substrate rigidity and TGF-b1 in simple, yet relatively
physiologically-relevant, constructs. We found that cell density was constant across all conditions
at each time point, indicating that substrate rigidity and TGF-β1 had minimal impact on phenotypes

38
such as cell adhesion or proliferation. In several instances, actin coverage increased only due to
TGF-β1 treatment, suggesting that TGF-β1, but not ECM rigidity, induces an increase in cell size,
characteristic of myofibroblasts. We also found that TGF-β1 treatment caused an increase in
ACTA2 gene expression as early as Day 1. This was followed by a substantial increase in a-
SMA/actin coverage on Days 3 and 5 in TGF-β1 treated cells. ECM rigidity also had some subtle
effects on differentiation. For example, a-SMA/actin coverage was increased due to TGF-β1
treatment only on high PDMS on Day 1, suggesting that fibroblasts have increased sensitivity to
TGF-β1 on stiffer substrates and/or differentiate more rapidly on stiffer substrates. However,
overall, TGF-β1 had a much stronger effect on phenotype compared to ECM rigidity. Our data are
mostly in agreement with previous studies, which have also shown stark increases in a-SMA due
to TGF-b1
81, 99, 112, 113
.
Besides a-SMA, there are limited definitive markers that clearly distinguish cardiac
fibroblasts from myofibroblasts
114
. Here, we measured the expression of the genes for periostin
(POSTN), FAP (FAP), and FSP1 (FSP1) because they have each been postulated to be
differentially expressed by fibroblasts and myofibroblasts. Periostin is a secreted osteogenic
protein that interacts with the ECM and promotes wound repair. Several studies have shown that
cardiac myofibroblasts, but not fibroblasts, express periostin after injury in vivo
102, 115, 116
.
Similarly, periostin is up-regulated in dermal mouse myofibroblasts during cutaneous wound
repair in vivo
103
. In our experiments, we observed that POSTN expression was higher in TGF-b1
treated cells on Day 1, but these differences were attenuated by Day 3. This suggests that periostin
is acutely up-regulated in cardiac fibroblast/myofibroblasts after TGF-β1 exposure, but maybe not
for prolonged periods of time. Similar to periostin, FAP also promotes wound repair after an
infarction. Elevated FAP expression has been observed in rat cardiac myofibroblasts after

39
myocardial infarction in vivo and in human cardiac myofibroblasts after TGF-β1 treatment in vitro
105
. We observed that FAP expression was increased due to TGF-b1 treatment on both Day 1 and
Day 3 of treatment. Thus, although POSTN and FAP were not as consistently or strikingly
impacted by TGF-b1 treatment compared to α-SMA, they still trended with a myofibroblast
phenotype, suggesting they are relevant secondary markers for human cardiac myofibroblasts.
FSP1 encodes for FSP1, which has been shown to be expressed by rat cardiac fibroblasts
and up-regulated in injured myocardium in vivo
106, 117
. In our study, we observed a decrease in
FSP1 expression due to TGF-b1 treatment. The discrepancy in our data compared to previous in
vivo studies could be due to the number of additional factors and cues in vivo. For example, FSP1
has been shown to be expressed strongly by non-fibroblasts, such as endothelial cells and
hematopoietic cells, after myocardial injury
107
, which could confound the in vivo results.
Furthermore, our experiments were in primary human cardiac fibroblasts, whereas most previous
studies with this gene and protein were in rodents. Thus, more studies are needed to further
establish the role of FSP1 in human cardiac fibroblasts and myofibroblasts.
The ability of fibroblasts and/or myofibroblasts to couple to cardiac myocytes via Cx43
gap junction channels has been a relatively controversial topic. For example, in vivo and ex vivo
studies have shown that fibroblasts/myofibroblasts and cardiac myocytes do not form gap
junctions in healthy myocardium
69
or after myocardial infarction
68
. However, other studies have
shown that fibroblasts/myofibroblasts express Cx43
70
and conduct signals across scar tissue
71
after
an infarction. In vitro, fibroblasts
10
and myofibroblasts
67
have been shown to propagate action
potentials from cardiac myocytes, with an increase in coupling after TGF-β1-treatment
72
.
Furthermore, silencing Cx43 in myofibroblasts has been shown to reduce arrhythmogenesis in co-
culture models
73
. Collectively, most studies suggest that Cx43 is up-regulated in myofibroblasts

40
after myocardial injury, although this has been investigated primarily in rodent cells. Here, we
tested if GJA1 expression, which encodes for Cx43 protein, is up-regulated due to matrix rigidity
and/or TGF-β1 treatment in primary human cardiac fibroblasts. We found no significant difference
in GJA1 expression due to these two variables, which suggests that expression of GJA1 is similar
in human cardiac fibroblasts and myofibroblasts. However, one important consideration is that
expression of GJA1 in fibroblasts/myofibroblasts could be influenced by the presence of cardiac
myocytes, which are not present in our system. Additionally, our simplified in vitro system does
not recapitulate all the diverse cues present in vivo, which could have a more substantial impact
on GJA1 expression.
In many fibroblasts of non-cardiac origins, ECM rigidity and TGF-β1 have been shown to
jointly promote differentiation to myofibroblasts. For example, freshly-isolated rat portal
fibroblasts
90
, rat hepatic stellate cells
118
, and rat bronchial fibroblasts
89
have the highest expression
of myofibroblast markers when treated with TGF-β1 and cultured on stiffer surfaces. In our study,
we observed more subtle effects of ECM rigidity. For example, α-SMA/actin coverage was
significantly higher in TGF-β1 treated cells at our earliest time point only on the most rigid
substrate. Beyond this first timepoint, TGF-β1 activated myofibroblast differentiation equally on
all substrates. However, the previous studies mentioned above used rat fibroblasts at very early
passages, which was logistically impossible for our study because we used primary human cardiac
fibroblasts, which are in extremely limited supply. Thus, we were forced to expand our cells in
polystyrene flasks prior to experiments, which could have reduced their sensitivity to ECM
rigidity. Additionally, myofibroblast differentiation is likely distinct in fibroblasts from different
species and/or organs.

41
In general, myofibroblasts are thought to de-differentiate into quiescent fibroblasts when
differentiation stimuli, such as TGF-b1 or mechanical stress, are removed. For example, α-SMA
expression decreased in cultured synovial fibroblasts after removal of exogenous TGF-β1
96
.
However, in this study, expression levels were still higher than quiescent fibroblasts, suggestive
of an incomplete reversal of phenotype. Similarly, valvular myofibroblasts cultured on stiff
surfaces reduced a-SMA expression when matrix stiffness was decreased
85
. Our data is consistent
with these studies, as we also observed a partial reversibility in myofibroblast phenotype after we
re-plated TGF-b1-treated cells onto new substrates and excluded TGF-b1 from the culture media.
Our rationale for transferring our cells to a new platform was two-fold. First, the cells often
detached from their substrates after approximately one week, which is insufficient time to treat
cells with TGF-b1 to activate differentiation, withdraw TGF-b1, and monitor de-differentiation.
Second, we are interested in controllably generating cardiac fibroblasts and myofibroblasts in
culture and then re-plating them on new substrates for additional downstream experiments, such
as co-culture with cardiac myocytes. However, our results suggest that TGF-b1 must be sustained
to maintain high levels of differentiated myofibroblasts.
As mentioned above, one limitation of our study is that we did not incorporate cardiac
myocytes that coexist with fibroblasts in the native myocardium and likely have an impact on
fibroblast/myofibroblast phenotype. However, for this study, our goal was to minimize the number
of variables and focus on how ECM rigidity and TGF-b1 specifically impact fibroblast
differentiation. Future studies will focus on investigating interactions between human cardiac
myocytes and fibroblasts/myofibroblasts. We also neglected to investigate the impact of other
cytokines, such as tumor necrosis factors and interleukin proteins that are also secreted by

42
neutrophils during inflammation and likely also affect human cardiac myofibroblast
differentiation
119
. These are also important topics for follow-up studies.
In summary, we investigated the independent and combined effects of ECM rigidity and
TGF-b1 on the phenotype of primary human cardiac fibroblasts. Our findings demonstrate that
differentiation to myofibroblasts is predominantly regulated by TGF-b1 treatment rather than
ECM rigidity. This suggests that targeting the TGF-b/Smad signaling pathway could have
therapeutic potential to minimize fibrosis after an infarction, even in rigid, fibrotic
microenvironments. Additionally, fibroblasts and myofibroblasts are key players in many
physiological and pathological process in the myocardium, but have been mostly excluded from
in vitro studies. Here, we established parameters for robustly generating human cardiac
myofibroblasts in vitro. This approach can be used for controlled in vitro studies to further
investigate the coupling between myocytes, fibroblasts, and myofibroblasts, for example. By
controlling the phenotype of fibroblasts and myofibroblasts, these cells can also be selectively
incorporated into more physiologically-relevant in vitro models of healthy and diseased
myocardium “on a chip”, which have many applications for human disease modeling and drug
screening.

43
Chapter 3 Spatially Dictating Cell Identity in Heterotypic
Striated Muscle Tissues by Combining Microcontact Printing
and Synthetic Notch Receptors
Aim 2: Engineer heterotypic skeletal muscle tissues by culturing cells expressing
synthetic notch receptors on scaffolds microcontact printed with synthetic ligands.

3.1. Introduction
Human tissues consist of multiple cell types arranged in specific orientations relative to
each other to optimize tissue function. Tissues range in complexity with several cell types
interacting synergistically within their microenvironment. As mentioned above, in human
ventricular myocardium, uniaxially aligned cardiac myocytes are interspersed with cardiac
fibroblasts, which are responsible for synthesizing the extracellular matrix (ECM) and wound
healing after injury
120, 121
. Although these are the two major cell types constituting the ventricular
myocardium, there is also an intricate vascular network that supply oxygen and nutrients to the
tissue
122, 123
. Endothelial cells that line the blood vessels are known to closely interact with cardiac
myocytes
124
to regulate myriad of myocardial tissue functions. As there is a need for improved in
vitro platforms that recapitulate the native ventricular myocardium, spatial organization of distinct
cell types is critical for tissue engineering.
Spatial control over the placement of individual cell types on a platform is crucial for
studying cell-cell interactions in healthy and diseased tissues. In order to best capture the
microenvironment of any heterotypic multi-cellular tissue in vitro, the various cell types must be
spatially organized in a physiologically relevant orientation. Microcontact printing is a technique

44
that has been optimized to dictate adhesion and architecture of engineered tissues. This process
involves fabricating geometric micropatterns on a silicon wafer via standard photolithography and
casting a tunable elastomer such as polydimethylsiloxane (PDMS) onto the patterned wafers to
obtain stamps with the desired features
125
. The surface of the PDMS stamps are coated with an
ECM protein and when inverted onto a surface, the protein layer will exhibit the micropatterns.
Subsequently, when the cells are seeded onto the surface, there will be preferential adherence to
the micropatterned protein regions. Microcontact printing has been utilized to spatially organize
cardiac myocytes
2, 94
that closely mimics the uniaxial alignment exhibited in the native
myocardium (Figure 3-1). Although the cells successfully adhered to the patterned regions, a
limitation of microcontact printing is the difficulty of culturing more than one cell type with spatial
precision. Many studies utilizing microcontact printing focus on culturing only one cell type
because majority of cells will non-selectively adhere to ECM proteins and there would be an issue
of controlling the architecture of a tissue with multiple cell types. Microcontact printing is a robust
Figure 3-1. Microcontact printing for dictating cell adhesion and architecture of engineered cardiac tissues.
Neonatal rat cardiac myocytes were seeded onto PDMS-coated coverslips microcontact printed with fibronectin and
exhibited the alignment of the lanes. DAPI: blue, F-actin: green, sarcomeric α-actinin: red. Scale: 50 μm. Adapted
from
2
.

45
technique for spatially dictating placement of cells, but the inability to generate heterotypic tissues
is a pitfall that needs to be addressed for development of physiologically relevant healthy and
diseased in vitro models.
As these heterotypic interactions are vital in the myocardium, some studies incorporated
both cell types, in which the cells were seeded either as a heterogeneous, isotropic mixture
8
or
sequentially via physical barriers that allowed one type to be seeded in the non-blocked regions
and then the other after the barriers have been removed
10, 126, 127
. Although these cardiac co-culture
models attempted to improve the engineering of cardiac tissues, none of these systems were able
to precisely generate a confluent tissue of uniaxially aligned myocytes surrounded by fibroblasts.
Furthermore, the PDMS stencils that are utilized to block specific regions of the surface have a
relatively low printing resolution, which are in units of millimeters compared to micrometers.
Micrometer-level resolution is crucial because the average width of a human cardiac myocyte is
20 μm
128
and in order for spatial alignment to be effective, the dimensions must also be within the
same order of magnitude. Although previous studies have investigated cell-cell interactions
between cardiac myocytes and fibroblasts/myofibroblasts, engineered heterotypic cardiac tissues
with high spatial organization and resolution have yet to be developed.
Synthetic biology is a prominent research area that aims to redesign native genetic
networks in cells for user-defined control over various biological processes, such as synthesis of
various compounds or cellular differentiation
129
. Recently, a novel tool called synthetic notch
receptor (synNotch) has been developed to control cell identity in a multi-cellular system
13
. Notch
signaling pathway is a highly conserved cell signaling system in mammalian cells to regulate
embryonic development
130
. Notch receptors are transmembrane proteins composed of an
intracellular and extracellular domain and bind to specific membrane-bound ligands on

46
neighboring cells for regulating cell-cell communication. When the ligand binds to the receptor,
two proteolytic cleavages separate the two Notch receptor domains, and the inner domain
translocates to the nucleus and engages in transcription regulation
131
(Figure 3-2A). SynNotch
redesigns the Notch receptor and its signaling pathway with user-defined inputs (receptor and
ligand) to generate a user-defined output (transcription factor regulating cellular phenotype)
(Figure 3-2B). In this study, synNotch was engineered in mouse fibroblasts, referred to in this
dissertation as synNotch cells, to transdifferentiate them into multi-nucleated skeletal myotubes.
The synNotch cells had a CD19 receptor that would regulate transcription of myogenesis master
regulator, myoD, when bound to a complementary CD19 ligand. To activate synNotch, cells with
membrane-bound CD19 were first seeded onto a small region of the surface and then a monolayer
of synNotch cells were seeded directly on top. Only in the small region where the two cell types
Figure 3-2. Synthetic notch receptor (synNotch) engineering and selective transdifferentiation of synNotch
fibroblasts into skeletal myotubes. (A) Diagram of the Notch signaling pathway elucidates the ligand-receptor
interaction, proteolytic cleavages of the receptor, and repression or activation of transcription factor(s). Adapted from
3
.
(B) Modification of the naturally expressed Notch receptor and its signaling pathway by modulating the input to
regulate user-defined output. (C) Selective transdifferentiation of engineered synNotch cells with a myoD
transcription factor module into skeletal myotubes in the area conducive to ligand-receptor binding. Scale: 50 μm.
Adapted from
13
.

47
came in physical contact were the synNotch cells able to transdifferentiate into skeletal myotubes
surrounded by undifferentiated cells (Figure 3-2C). From one cell type, this platform resulted in
an engineered tissue of two cell types with control over cell identity. Despite the novel approach
to generate heterotypic tissues, this model did not have the spatial resolution needed for skeletal
muscle tissues that capture cell-cell interactions on the scale of tens of microns. Since the cells are
seeded in the form of a droplet, the only way to control the specific dimensions of ligand
distribution is by the volume of the droplet deposited, which is not as accurate as microcontact
printing with user-defined pattern dimensions. Additionally, in vivo skeletal myotubes are
precisely aligned with fibroblasts interspersed throughout the fibers, which the study was not able
to recapitulate.
Our hypothesis is that we can engineer heterotypic tissues with spatial control over cell
identity by culturing synNotch cells on scaffolds microcontact printed with synNotch ligands.
Combining the advantages of microcontact printing and synNotch will provide a novel platform
that can be used to address the limitations of current in vitro co-culture models. Skeletal muscle is
the target for our experiments because the synNotch cells only need one master transcription factor
(myoD) for successful transdifferentiation
132, 133
, compared to cardiac tissue needing multiple
transcription factors
134-136
. Additionally, skeletal muscle tissue has a similar architecture to the
myocardium, in which uniaxially aligned muscle myofibers are embedded in connective tissue
synthesized by neighboring fibroblasts, which are responsible for maintaining structural integrity
in both healthy and diseased tissues
137-139
. First, we cultured synNotch cells with a GFP receptor
and an myoD-mCherry transcription factor module on PDMS-coated coverslips printed with GFP
ligand. Then, we assessed the activation of mCherry in synNotch cells by quantifying mCherry
expression at various conditions and locations after 24 hours. Furthermore, we quantified

48
sarcomeric a-actinin for these cells after five days. Overall, our results suggest that mCherry and
sarcomeric a-actinin expressions are significantly higher in cells directly contacting GFP
compared to the cells cultured in absence of GFP ligands. Our data provide new insight into how
cell identity can be spatially dictated in heterotypic tissues by culturing synNotch cells on scaffolds
microcontact printed with synNotch ligands.

3.2. Materials and Methods
3.2.1. Photolithography and Soft Lithography
Standard photolithography and soft lithography techniques were used to fabricate the
master wafer and polydimethylsiloxane (PDMS) stamps
20, 94, 125
. Briefly, silicon wafers were
cleaned with a nitrogen gun, spin-coated with hexamethyldisilazane (Sigma-Aldrich, St. Louis,
MO, USA) first and then with SU-8 2005 negative photoresist (MicroChem, Westborough, MA,
USA), and baked according to manufacturer instructions. Then, the wafers were exposed to UV
light through a photolithographic mask with features such as 60 and 120 μm wide patterns
separated by 100 μm (referred to as 60 x 100 and 120 x 100, respectively) using a Karl-Suss MJB3
mask aligner. The wafers were submerged in developer solution to dissolve away non-crosslinked
photoresist and subsequently silanized overnight in a vacuum desiccator with 30 μL of
trichloro(1H, 1H, 2H, 2H-perfluorooctyl)silane (Sigma-Aldrich). PDMS stamps were fabricated
by mixing the base component and the curing agent of Sylgard 184 (Dow Corning, Midland, MI,
USA) at a 10:1 mass ratio, degassing with a planetary centrifugal mixer (AR-100, Thinky, Japan),
and casting the mixture onto the etched wafer in a 150 mm petri dish. PDMS was further degassed
in a vacuum desiccator, cured overnight at 65
o
C, and cut into square stamps that had the
micropatterns. These stamps were utilized in the preliminary experiments. On the other hand,

49
circular isotropic PDMS stamps were prepared for majority of the experiments by silanizing a
featureless silicon wafer.

3.2.2. Fabrication of Micropatterned PDMS-Coated Coverslips
To fabricate PDMS-coated coverslips, we prepared Sylgard 184 PDMS, spin-coated the
mixture onto 18 mm diameter glass coverslips (Electron Microscopy Sciences, Hatfield, PA, USA)
using a G3P-8 spincoater (Specialty Coating Systems, Indianapolis, IN, USA), and cured overnight
at 65
o
C. After preparation, these coverslips are stored at room temperature until the experiments
are conducted. PDMS stamps (patterned and isotropic) are sonicated in 95% ethanol, dried, and
coated with 40 – 150 μL of recombinant green fluorescent protein (GFP, 100 μg/mL), which
depended on the surface area of the PDMS stamps. GFP solution was provided by the Lim
Laboratory at University of California, San Francisco, and was incubated on the stamps for at least
two hours in room temperature until the solution has completely evaporated. PDMS-coated
coverslips were treated with ultraviolet ozone in a cleaner (Jelight Company Inc., Irvine, CA,
USA) for eight minutes. Stamps were then rehydrated in water, dried, and gently inverted onto the
treated coverslips to transfer the GFP. The stamps were carefully removed, and the printed
Figure 3-3. Culturing synNotch cells on microcontact printed surfaces. Schematic of microcontact printing GFP
onto PDMS-coated coverslips and engineering synNotch cells to seed onto the printed surfaces to generate spatially
organized skeletal myotubes interspersed with undifferentiated synNotch cells.

50
coverslips were uniformly coated with 100 μL of human fibronectin (5 µg/mL, Corning, Corning,
NY, USA), rinsed with PBS, and maintained at 4
o
C until seeded with cells (Figure 3-3).

3.2.3. Engineering Synthetic Cell Lines
Two plasmids, one for the receptor (synNotch anti-GFP transgene) and one for the
transgene (TRE_mCherry, pGK_BFP or TRE_myoD_mCherry, pGK_BFP), were transfected into
C3H mouse embryonic fibroblasts using a Lipofectamine LTX with Plus Reagent kit (Thermo
Fisher Scientific, Waltham, MA, USA). Transfected cells were cultured in virus for three days and
then sorted using fluorescence activated cell sorting (FACS) for double positive cells. First, the
cells are sorted for Alexa 647 fluorescent marker conjugated to an antibody targeting the synNotch
receptor (Alexa 647 + anti-Myc). Second, cells are FACS sorted for pGK_BFP, which corresponds
to a constitutively expressing promoter in the transgene. The double positive cells confirm the
presence of both Alexa 647 + anti-Myc and pGK_BFP, which yields a high purity of synthetically
engineered cells (synNotch cells).

3.2.4. Cell Culture and Live Imaging
SynNotch cells were cultured in growth medium, consisting of high glucose DMEM (4.5
g/L glucose) (Gibco, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS)
(Gibco). Cells were passaged every two days at 80% confluence into 75 cm
2
cell culture flasks.
The microcontact printed PDMS-coated coverslips were immobilized into individual wells of 12-
well plates using 5 µL of Dow Corning 111 O-Ring Silicone Lubricant (Dow Corning).
Subsequently, synNotch cells were seeded onto the coverslips at a density of 156,500 cells / 200
µL droplet to selectively coat the surface area of the coverslip with the micropatterns. The samples

51
are incubated at 37
o
C for 90 minutes to promote adhesion, and then 1 mL of growth medium is
gently added to the wells and placed back into the incubator for the duration of the experiment
(Figure 3-3). Cells used for the experiments were all under passage 35 to ensure stability of the
transfected modules. Furthermore, since cells are highly sensitive to shear stress, media was not
replenished since seeding.
Live images of the synNotch cells were captured with a BZX-710 inverted fluorescent
microscope equipped with a stage-top incubator (5% CO2, 37
o
C) (Keyence, Japan) to maintain
proper cell culture conditions. Images were obtained after four, 24, and 120 hours using a 2X air
objective at the same location that displays a quarter-circle of GFP or a representative location that
best captures the cellular phenotype for the lane and concentric circle micropatterns.

3.2.5. Immunostaining
Cells were fixed with either 4% paraformaldehyde (Day 1 samples) or -20
o
C methanol
(Sigma-Aldrich) (Day 5 samples) for ten minutes and subsequently permeabilized with 0.2%
Triton X-100 throughout the immunostaining procedure. Fixed cells were incubated with
monoclonal mouse anti-sarcomeric α-actinin (1:200, Sigma-Aldrich) primary antibody in blocking
solution, which consisted of 10% normal goat serum (Life Technologies, Waltham, MA, USA)
and 0.1% bovine serum albumin (HyClone, Chicago, IL), overnight at 4
o
C. After PBS rinses, cells
were incubated with DAPI (1:200, Life Technologies) and Alexa Fluor 647 goat anti-mouse
secondary antibody (1:200, Life Technologies) in the same blocking solution for 90 minutes at
room temperature. Coverslips were mounted onto glass slides with a drop of ProLong Gold Anti-
Fade Mountant (Life Technologies) and sealed with nail polish.

52
3.2.6. Microscopy and Image Analysis
Stained cells were imaged at nine locations dispersed across each coverslip (five inside of
the GFP circle and four outside) using a 20x air objective on a Nikon Eclipse Ti-S inverted
fluorescent microscope and an Andor Zyla scientific CMOS camera. A customs macro in ImageJ
was used to count the total number of nuclei per field of view based on DAPI fluorescence, as
described previously
140
. Endogenously expressed mCherry and immunostained sarcomeric a-
actinin images were analyzed by systematic thresholding of the 546 and 647 channels in ImageJ,
respectively. For the mCherry image analysis, the brightness/contrast was adjusted so the
minimum value was set to 300 to reduce the background and enhance the mCherry fluorescence.
Then a Gaussian Blur of 4.0 was then applied to minimize variances due to pixel color exposure.
The thresholding was systematically computed by determining the pixel value that best represents
the raw image, identifying the pixel value that corresponds to the distinct peak, and quantifying a
threshold constant that is dependent on ideal value, peak value, maximum threshold value with the
equation below:

k (threshold constant) =
1234567348
94:19;9
(1)

This value was constant across all images, so the equation (1) was rearranged to quantify the ideal
value for subsequent images. This value was the minimum threshold value, which ensured that the
same displacement from the peak was obtained while accounting for the different maximum
threshold values between images. A similar protocol was used for sarcomeric a-actinin image
analysis, with the exception of setting the minimum value of brightness/contrast to 200, which
reduced the high background noise while increasing the sarcomeric a-actinin signal. These values

53
were divided by the total number of pixels in the image to determine mCherry and sarcomeric a-
actinin coverage, respectively.

3.2.7. Statistical Analysis
All measurements were tested for normality using the Lilliefors test. The normally
distributed data sets were then analyzed using one-way ANOVA followed by Tukey’s test for
multiple comparisons in MATLAB, with α set to 0.05. Data sets that were not normally distributed
were analyzed using Kruskal-Wallis test followed by Tukey’s test for multiple comparisons in
MATLAB, with α set to 0.05. Data was collected from an average of multiple regions per sample
from at least four independent experiments.

3.3. Results
3.3.1. Optimization of Fabricating Scaffolds Microcontact Printed with GFP Ligands
Since this study is the first to integrate microcontact printing and synNotch system, we
started by selecting a relatively high GFP concentration (100 μg/mL) and an incubation protocol
similar to previous studies with microcontact printing fibronectin
2, 141
. This specific GFP
concentration was selected because we wanted to ensure that the PDMS-coated coverslips would
have a sufficient amount of protein transferred from the PDMS stamps. Furthermore, the PDMS
stamps that were utilized had rectangular lane patterns and the synNotch cells utilized for these
pilot tests would only transcribe mCherry (TRE_mCherry transgene) when activated to verify that
the cells were activated in the presence of GFP. We captured high magnification live images of
GFP, mCherry, and brightfield channels after two days in culture, as shown in Figure 3-4A. We
observed that all the cells were localized along the lanes where GFP ligands were printed with

54
mCherry expression.
Although the synNotch
cells successfully
transcribed mCherry,
the cells were only
adhered to the areas
with mCherry
expression. We desired
to obtain a confluent
tissue of cells with
selective activation of
mCherry along the
lanes. We then backfilled our GFP printed coverslips with a few concentrations of fibronectin to
determine the optimal GFP-to-fibronectin ratio that would promote both uniform cell adhesion on
surface and selective mCherry activation (Figure 3-4B). We observed uniform cell adhesion for
both concentrations of fibronectin, but an apparent decrease in mCherry expression for the
condition with 10 μg/mL, which indicates that fibronectin reinforces cell adhesion with an upper
threshold that attenuates mCherry expression. Thus, synNotch cells effectively expressed mCherry
at a GFP concentration of 100 μg/mL and fibronectin concentration below 10 μg/mL.
Although microcontact printing parameters were established, there were some
inconsistencies with mCherry expression of synNotch cells across experiments. An alternative
avenue we explored was utilizing microfluidic patterning of GFP. Instead of being able to print
only one protein with conventional microcontact printing, this new method utilizes a PDMS device
Figure 3-4. High concentration of fibronectin attenuates mCherry
expression in synNotch cells. Live images of engineered murine fibroblasts
(synNotch cells) cultured for two days on PDMS-coated coverslips with
microcontact printed GFP lanes and backfilled with no fibronectin (A), 1
μg/mL, or 10 μg/mL of fibronectin (B) (scale bars: 100 μm). Images captured
in collaboration with Alexander March (Leonardo Morsut’s lab).

55
with indented micropatterns that has microfluidic properties to flow a protein of interest
142
.
However, the negative region of the PDMS device can be directly coated with a protein similar to
microcontact printing, which provides the flexibility to introduce two different proteins that do not
overlap. We prepared this by coating the device with fibronectin using established protocols
143, 144
,
inverting the device onto PDMS-coated coverslips, and flowing GFP through the microfluidic
channels (Figure 3-5A). Subsequently, we immunostained the coverslips with fibronectin to verify
the presence of fibronectin in the negative space alternating with the GFP lanes (Figure 3-5B).
However, we had difficulty having synNotch cells express myoD-mCherry (new cell line with
TRE_myoD-mCherry transgene) along the microfluidic GFP lanes, which was similar to our initial
microcontact printing pilot experiments. Despite the benefits and potential of microfluidic
Figure 3-5. Microfluidic patterning to modularly deposit fibronectin and GFP to activate mCherry expression
in synNotch cells. (A) Schematic of microfluidic patterning of fibronectin and GFP onto PDMS-coated coverslips.
(B) Immunostained images of GFP and FN that shows the negative region of FN that was patterned surrounded by
GFP lanes created by microfluidic flow through the channels (scale bars: 200 μm).

56
patterning, we decided to rewind and optimize the conventional microcontact printing due to a
higher number of successful experiments with synNotch cells selectively expressing myoD-
mCherry.
To maximize protein adsorption onto the PDMS stamps, we extended the GFP incubation
to completely evaporate the solution and concentrate the ligand on the stamps. Additionally, we
utilized the new synNotch cells with myoD-mCherry transgene to test transdifferentiation into
skeletal myotubes. We captured low magnification live images of the GFP and myoD-mCherry
channels and discovered distinct, bright lanes of GFP compared to the initial experiments of less
incubation time and robust myoD-mCherry expression of cells along the lanes after one day of
culture (Figure 3-6A). We then immunostained the samples and took higher magnification images
of sarcomeric α-actinin, the hallmark characteristic of mature skeletal myotubes
145
, in addition to
GFP and myoD-mCherry after three days of culture (Figure 3-6B). We observed the co-
localization of sarcomeric α-actinin and myoD-mCherry in the synNotch cells in direct contact
Figure 3-6. Microcontact printing after evaporation of GFP solution to transcriptionally activate myoD-
mCherry and mature transdifferentiated synNotch cells. SynNotch cells were cultured on PDMS-coated
coverslips microcontact printed with evaporated GFP. (A) Live images of the GFP lanes and myoD-mCherry
expression of synNotch cells after one day in culture (scale bar: 500 μm). (B) Immunostained images of the GFP lanes,
myoD-mCherry, sarcomeric α-actinin, and merged channels of synNotch cells after three days in culture (scale bar:
200 μm). Images captured in collaboration with Alexander March (Leonardo Morsut’s lab).

57
with GFP ligands, which suggests that the GFP evaporation method should be utilized for
subsequent experiments.

3.3.2. Selective Transcriptional Activation of mCherry-myoD in SynNotch Cells by GFP Ligands
To test the efficiency and reproducibility of mCherry-myoD activation of synNotch cells
on microcontact printed GFP, we prepared PDMS-coated coverslips and compared printing an 8
mm circular area of GFP to adding a 40 μL droplet of GFP directly onto the coverslip.
Subsequently, we coated these coverslips with human fibronectin not only to promote cell
adhesion, but also to mimic microenvironmental cues that are known to reinforce skeletal myoblast
differentiation into multi-nucleated myotubes
146, 147
. We seeded the coverslips with synNotch cells
and monitored the myoD-mCherry fluorescence throughout the first 24 hours of culture. We
captured low magnification, quarter-circle images of GFP, myoD-mCherry, and brightfield
channels after four and 24 hours of seeding to have an enlarged sampling area, as shown in Figure
3-7. Although the cells were uniformly adhered across the coverslip, we observed no myoD-
Figure 3-7. Selective myoD-mCherry expression in synNotch cells in direct contact with GFP ligands. Quarter-
circle live images of engineered murine fibroblasts (synNotch cells) were cultured for four hours (A) and 24 hours (B)
on PDMS-coated coverslips with no GFP, GFP droplet, and microcontact printed (μCP) GFP (scale bars: 500 μm).
Images captured in collaboration with Alexander March (Leonardo Morsut’s lab).

58
mCherry expression inside the GFP region after four hours of culture (Figure 3-7A). After 24
hours of culture, there appeared to be myoD-mCherry fluorescence within the GFP region, but
minimally outside of the circular boundary, indicated by the dotted lines, for both the droplet and
microcontact printed conditions (Figure 3-7B). Furthermore, we did not detect any myoD-
mCherry signal in the fibronectin only condition, which confirmed that direct contact with GFP is
required to drive myoD-mCherry expression and microcontact printing is an effective means of
introducing GFP ligands on surfaces. Thus, synNotch cells appeared to have successfully
expressed myoD-mCherry by 24 hours and validated the robustness of these genetically
engineered cells.
To quantify the observed phenomenon, we next captured higher resolution images to
quantify cell density and myoD-mCherry-positive signal for the various conditions. We only
immunostained our cells for nuclei after 24 hours of culture because myoD-mCherry was
expressed endogenously, and we captured several images both inside and outside of the GFP
region (Figure 3-8A). Across the different conditions and coverslip locations, we first compared
cell density using one-way ANOVA and multiple comparisons and found no significant
differences (Figure 3-8B). This suggests that cell viability is not affected by the presence of GFP
and solely influenced by the presence of uniform fibronectin coating in all the samples. We then
analyzed the myoD-mCherry fluorescence across each condition and location because we wanted
to quantitatively assess the two GFP procedures in successfully activating synNotch cells (Figure
3-8C). Based on one-way ANOVA and multiple comparison, we observed no statistical difference
between the two GFP conditions, which indicates that microcontact printing can activate synNotch
cells just as robustly as directly coating GFP on a surface. Additionally, we observed significantly
higher myoD-mCherry signal for cells in direct contact with GFP than in the absence of GFP, both

59
outside the circular
boundaries and throughout
the fibronectin control.
Higher myoD-mCherry-
positive signal combined
with similar nuclei count
verified that the
fluorescence is not an
artifact of the number of
cells in the field of view but
solely attributed to the
transcriptional activation
of synNotch cells in the
presence of GFP.
Collectively, these data
suggest that the myoD-
mCherry activation of
synNotch cells is regulated
by the GFP ligand-receptor interactions and that microcontact printing GFP is a viable tool for
selectively synthesizing the desired transcription factor.

Figure 3-8. Quantification of nuclei count and myoD-mCherry expression
after 24 hours due to the presence of GFP ligands. SynNotch cells were cultured
on PDMS-coated coverslips with no GFP, GFP droplet, and microcontact printed
GFP for 24 hours. (A) Immunostained images of synNotch cells inside and outside
of the GFP area (blue: nuclei, red: myoD-mCherry, scale bars: 100 μm). Cell
density (B) and myoD-mCherry coverage (C) were then quantified from images (n
= 4 or 5, bars indicate mean of the data set, ***p< 0.0001 compared to FN inside
and all the outside conditions, according to one-way ANOVA and Tukey’s test for
multiple comparisons.). Data collected in collaboration with Alexander March and
Mher Garibyan (Leonardo Morsut’s lab).

60
3.3.3. Maturation of Transdifferentiated Myoblasts into Multi-Nucleated Skeletal Myotubes within
GFP Region
Although we were able to quantify the presence of myoD-mCherry, we cannot infer that
mCherry is simultaneously expressed with myoD, the key transcription factor in the
transdifferentiation of synNotch cells into skeletal myoblasts. To determine if the myoD-
mCherry expressing synNotch cells are phenotypically skeletal myoblasts, we cultured the cells
for four additional days, immunostained them for both nuclei and sarcomeric α-actinin, and
captured the same set of images inside and outside the GFP region as mentioned before (Figure
3-9A). Sarcomeric α-actinin appears to be present only within the GFP region in both the droplet
and printed conditions, which suggests that the synNotch cells in direct contact with GFP have
matured to skeletal myotubes. Subsequently, we compared the cell density between Days 1 and 5
in both coverslip locations, and quantified the sarcomeric α-actinin-positive signal for Day 5,
which is indicative of multi-nucleated myotubes derived from differentiating myoblasts.
93, 145

One-way ANOVA and multiple comparison analysis indicated a significant decrease in cell
density for the conditions with no GFP present, both outside of the circular boundaries and
throughout the fibronectin control (Figure 3-9B). In general, cell viability tends to decrease as
time progresses, but when skeletal myoblasts are cultured on fibronectin-coated surfaces and
interacting with neighboring myoblasts, cell proliferation is increased to promote multi-nucleated
myotube formation
146, 148
. Furthermore, we observe a significantly higher sarcomeric α-actinin
coverage for cells in direct contact with GFP than the other conditions, which is similar to the

61
myoD-mCherry data (Figure 3-9C). These cells have elongated morphology with multiple
nuclei localized throughout the sarcomeres, which is a hallmark phenotype of skeletal
myotubes
149
. These results confirm that the synNotch cells transdifferentiated into functional
myoblasts that fused into multi-nucleated myotubes and that we can control cell identity in multi-
cellular tissues by culturing synNotch cells on scaffolds microcontact printed with GFP.

Figure 3-9. Cell morphology and quantification of cell density and sarcomeric α-actinin-positive expression
after five days due to the presence of GFP ligands. SynNotch cells were cultured on PDMS-coated coverslips with
no GFP, GFP droplet, and microcontact printed GFP for five days. (A) Representative immunostained images of
synNotch cells inside and outside the GFP region (blue: nuclei, gray: sarcomeric α-actinin, scale bars: 100 μm). (B)
Cell density comparing Day 1 and 5 and (C) sarcomeric α-actinin coverage were quantified from immunostained
images (n = 1 or 2, bars indicate mean of the data set). Data collected in collaboration with Alexander March and
Mher Garibyan (Leonardo Morsut’s lab).

62
3.3.4. Spatially Controlled Transcriptional Activation of myoD-mCherry on Various Patterned
Surfaces
To recapitulate the native architecture of other tissue types and/or conduct various
functional assays with spatial precision at a heterotypic cell interface, we microcontact printed
GFP of various-shaped patterns to expand our platform for broader, versatile applications. For
example, we printed concentric circles of GFP onto our PDMS-coated coverslips, seeded
synNotch cells, and captured low-magnification live images of the GFP and myoD-mCherry
channels after 24 hours (Figure 3-10). As expected, synNotch cells expressed myoD-mCherry
mainly within the GFP concentric circle regions, which indicates that GFP can be deposited as
other patterns besides circles and rectangular lanes.

Figure 3-10. Spatially controlled myoD-mCherry expression of synNotch cells along concentric circle
regions of GFP ligands. Live images of microcontact printed GFP concentric circles and myoD-mCherry
expression of synNotch cells that were cultured for 24 hours on PDMS-coated coverslips (scale bars: 200
μm). Images captured in collaboration with Mher Garibyan (Leonardo Morsut’s lab).

63
3.4. Discussion
In striated muscle tissues, the alignment of the muscle cells (cardiac myocytes or skeletal
myotubes) and their interactions with surrounding fibroblasts are two essential features of the
native microenvironment that current in vitro models have difficulty recapitulating. Microcontact
printing allows spatially precise placement of cells but is difficult to culture more than one cell
type, and synNotch is utilized to dictate cell fate in multi-cellular tissues but has limited spatial
resolution and provides no architectural cues. To address this, we combined the two methods and
cultured synNotch cells on surfaces microcontact printed with GFP ligands to engineer
heterotypic skeletal muscle tissue with spatially defined architecture. Our results suggest that
microcontact printing GFP ligands transcriptionally activates myoD-mCherry expression in
synNotch cells to transdifferentiate into skeletal myoblasts that subsequently fuse into multi-
nucleated myotubes. These data suggest that microcontact printing synNotch ligands is a robust
technique for inducing gene expression in synNotch cells, and cell identity can be spatially
dictated in multi-cellular tissues to generate heterotypic tissues. Overall, this study can contribute
to the engineering of striated muscle tissues with physiologically relevant cell-cell interactions
and spatial orientation for basic research, regenerative medicine, and in vitro disease modeling.
In our study, we first captured live images of GFP, mCherry, and brightfield channels to
determine the GFP and fibronectin concentrations that promoted uniform cell adhesion and
induced mCherry expression in synNotch cells. Based on the degree of mCherry expression, we
assessed that 100 μg/mL of GFP was sufficient to transcriptionally activate mCherry, but the
cells were only adhered along the GFP lanes in the absence of fibronectin. Although GFP has
been mainly utilized as a common fluorescent reporter conjugated to proteins for evaluating
cellular phenotypes and/or subcellular functions
150, 151
, it may also exhibit some cell adhesion

64
properties in vitro, as indicated by the localization of synNotch cells selectively along the GFP
lanes. As we wanted a confluent coverage of cells to generate heterotypic tissues, introducing
ECM proteins such as fibronectin would help promote cell adhesion
152
outside of the GFP
regions. The images demonstrated that 10 μg/mL of fibronectin backfill on microcontact printed
coverslips completely resolved the non-selective cell adhesion but decreased mCherry signal.
GFP molecules exhibit a molecular mass of 27 kDa with a highly-folded tertiary structure
153, 154
,
which most likely are overshadowed by fibronectin proteins that are nearly 20 times the size of
GFP (~500 kDa)
155
. Thus, fibronectin concentration must be lowered to minimize the attenuation
of mCherry expression, while promoting uniform cell adhesion. As 1 μg/mL of fibronectin did
not provide uniform cell coverage as 10 μg/mL, we selected 5 μg/mL of fibronectin to achieve
full confluency of the synNotch cells and detect mCherry signal similar to the 1 μg/mL
condition.
Although we aimed to optimize the GFP and fibronectin concentrations for microcontact
printing, we experienced cell delamination and inconsistent mCherry expression in synNotch
cells. This issue emerged most likely because 5 μg/mL of fibronectin is a relatively low
concentration used for microcontact printing
2, 143, 156
and potentially weak adsorption of GFP on
PDMS stamps, which lowers transfer efficiency. An alternative solution was to utilize
microfluidic patterning to print fibronectin along the negative space and flow GFP through
microchannels exhibiting lanes. Microfluidics is a robust, commercial technology for processing
various biofluids, drug discovery, and diagnostics
157, 158
. Specifically, microfluidic patterning has
been shown to be beneficial for spatially controlling deposition of various proteins on the
surface
142
. This platform will not only eliminate the GFP masking effect as the two protein areas
are distinct with no overlap, but also provide a means of coating the surface directly with GFP

65
instead of transferring with PDMS. Our immunostained images clearly illustrated the alternating
fibronectin negative areas with the GFP lanes, but when the synNotch cells were seeded onto the
platform, they were unable to express myoD-mCherry on the GFP regions. This shortcoming
may be attributed to the generally low internal volume of microfluidic devices (~0.01 – 10
μL)
159, 160
than the volume of GFP needed to coat our PDMS stamps (40 – 150 μL), resulting in
significantly less GFP deposition and below the threshold for transcriptional activation in
synNotch cells.
As the current protocols for microcontact printing and microfluidic patterning are not
optimal for depositing GFP ligands, we maximized the transfer of GFP onto the surface by
evaporating the GFP solution. Protein solution evaporation has been widely studied to
concentrate the protein for micro/nano patterning
161, 162
. Our live and immunostained images
demonstrate a successful transfer of GFP lanes, myoD-mCherry expression, and fusion of
transdifferentiated skeletal myoblasts into myotubes. This suggests that GFP solution
evaporation on PDMS stamps is a robust method of depositing GFP with control over spatial
organization.
To reduce the complexity of the system and delineate a clear boundary between the GFP
region and the non-printed surrounding, we transitioned from lanes to a circular micropattern.
SynNotch cells that were cultured on GFP printed lanes expressed myoD-mCherry, but the
fluorescence was also detected in between the lanes that had no GFP coverage. Skeletal
myoblasts are known to migrate on fibronectin-coated surfaces at early stages of myogenesis to
promote differentiation into myotubes
146, 163
. These cells may have migrated outside of the GFP
regions after transdifferentiation but considering that the rectangular width of the lanes is nearly
identical to the separation gap (120 μm width vs. 100 μm gap), we cannot verify this hypothesis.

66
As the circular micropattern would simplify the system to address our supposition, we
microcontact printed an 8 mm diameter circle of GFP onto our PDMS-coated coverslips and
compared myoD-mCherry expression for synNotch cells cultured on printed coverslips to those
cultured on coverslips directly deposited with a circular droplet of GFP, as shown before
13
. We
observed that myoD-mCherry coverage was significantly higher in cells directly contacting the
GFP ligands and cell density remained constant across all conditions and locations on Day 1,
which collectively suggest that most of the cells reside within the GFP region and do not migrate
outside of the circular boundary. Furthermore, there was no difference in myoD-mCherry
coverage between the two GFP conditions, which validates the robustness of microcontact
printing that is similar to directly placing GFP ligand on the surface.
In addition to myoD-mCherry coverage, we need to quantify sarcomeric α-actinin to
conclude that the synNotch cells were successfully transdifferentiated into skeletal myoblasts.
Since we have limited evidence that mCherry corresponds to the induction of skeletal myoblasts,
we indirectly addressed this question by immunostaining for sarcomeric α-actinin, which is a
definitive marker of myoblasts fusing into elongated myotubes
93, 164
. Our data reports that cell
density remains constant for the cells cultured within the GFP circles between Days 1 and 5, but
cell viability in absence of GFP decreased. This suggests that GFP promotes cell adhesion, as
implied in the first preliminary experiment, while the cells in other conditions and locations have
delaminated. Similar to myoD-mCherry coverage, sarcomeric α-actinin coverage was also
elevated in cells residing within the GFP circle, irrespective of the GFP deposition technique,
which emphasizes the reliability of microcontact printing GFP and indicates the formation of
skeletal myotubes, confirming the successful transdifferentiation of synNotch cells. Thus, a

67
heterotypic striated muscle tissue with spatial control was engineered by combining microcontact
printing and synNotch.
One limitation of our study is the lack of human relevance in our synNotch system, as our
synNotch cells are transfected murine embryonic fibroblasts and the heterotypic interactions
between the undifferentiated synNotch cells and the induced skeletal myotubes may differ in
humans and mice. However, our goal was to simplify our system and utilizing human-derived
fibroblasts would have bottlenecked our study due to the significantly poor efficiency of
transdifferentiation of human fibroblasts into skeletal myotubes
132, 165
. Since there are very few
studies investigating the transdifferentiation of human fibroblasts into myotubes, we will
optimize our platform in the future when there are more effective protocols established. We also
utilized embryonic fibroblasts, which does not translate well for studying various skeletal muscle
diseases affecting adult patients, such as amyotrophic lateral sclerosis
166
. Furthermore, fetal and
adult fibroblasts in the skin
167
and tendons
168
are known to be phenotypically distinct, as the fetal
fibroblasts are more proliferative than adult fibroblasts, which likely attributes to the migratory
propensity observed in our study. However, adult fibroblasts exhibit similar complexity to
human-derived fibroblasts, as several transcription factors are needed in addition to MYOD. The
tradeoff between streamlined results of transdifferentiating non-human, embryonic fibroblasts
and incorporating human development with limited information is not viable.
In summary, we engineered a novel platform for generating heterotypic skeletal muscle
tissue with spatial control over cell fate. Our findings indicate that synNotch cells can
transcriptionally activate myoD-mCherry and fuse into multi-nucleated skeletal myotubes in
response to microcontact printed GFP ligands. This approach can be leveraged for engineering
improved cardiac co-culture models, as cardiac and skeletal muscle tissues have similar

68
architecture. In the context of cardiac myocytes, mouse and human fibroblasts have been
transdifferentiated into functional, mature cardiac myocytes with expression of three to five
major cardiac transcription factors
135, 169
. If synNotch cells can be genetically engineered to
express the cardiac transcription factors in the intracellular domain and an anti-GFP synthetic
receptor in the extracellular domain, then we can selectively transdifferentiate synNotch cells
into cardiac myocytes via micropatterning GFP in lanes. This will subsequently result in induced
cardiac myocytes interspersed with undifferentiated fibroblasts, which recapitulates the native
spatial organization of the ventricular myocardium. Furthermore, this platform can be expanded
to other heterotypic tissue types as we can microcontact print various GFP patterns to best mimic
the architecture and cell-cell interactions of those tissues. By controlling both the architecture
and cell identity, we can design more physiologically-relevant in vitro models for healthy and
diseased tissues, which can be applied to disease modeling and drug screening.

69
Chapter 4 Concluding Remarks and Future Work
The microenvironment of a healthy ventricular myocardium regulates the synchronous
contractile force generated by cardiac myocytes. Cardiac fibroblasts are responsible in
maintaining the homeostasis of the extracellular matrix, which provides a relatively soft and
compliant environment for the uniaxially aligned cardiac myocytes to contract and efficiently
pump blood throughout the body. However, pathological remodeling perturbs the
microenvironment indicated by changes in chemical and biomechanical features. Cytokines are
secreted immediately after an infarction
175
and the ECM rigidity of the ventricular myocardium
increases
53
, which results in a phenotypic change of cardiac fibroblast into their activated
counterpart, myofibroblasts
140
. Cell-cell interactions are essential in both healthy and diseased
cardiac tissues, but current models lack the uniaxial alignment of cardiac tissue
8, 176
, tunable
biomaterial scaffolds that are physiologically relevant
177
, and/or heterotypic cell population of
the tissue
2, 94
.
Skeletal muscle tissue has a similar architecture and cell-cell interactions to the
ventricular myocardium, as uniaxially aligned skeletal myotubes are surrounded by
fibroblasts
139
. The spatially organized interactions between the myotubes and fibroblasts are
known to regulate myogenesis and muscle repair
178
. However, current skeletal muscle in vitro
platforms are limited by the same features of the cardiac models
93, 137, 179
. Synthetic biology has
recently been utilized to control cell fate by genetically modifying fibroblasts to
transdifferentiate into skeletal myotubes through synthetic ligand-receptor interactions. Since
only one transcription factor is needed to drive this change in cell fate, direct reprogramming of
fibroblasts into skeletal myotubes has been used as the starting point
180, 181
. This platform
presented synthetic cues to generate a heterotypic tissue on a surface.

70
An in vitro model that can modularly control various microenvironmental parameters,
both naturally and synthetically induced, to drive changes in cell fate is needed to address the
current limitations of engineered striated muscle tissues. In this dissertation, we evaluated
microenvironmental cues that alter cell fate to generate precisely engineered heterotypic striated
muscle tissues. In particular, we determined the relative contribution of chemical and
biomechanical cues in driving human cardiac fibroblast differentiation to myofibroblasts. This
finding will allow us to differentially control the cellular phenotype for improving in vitro
models of healthy and diseased ventricular myocardium. Additionally, we utilized synthetic
biology to spatially dictate cell identity in multi-cellular tissues for engineering more biomimetic
skeletal muscle tissue. We controlled these various microenvironmental parameters by preparing
surfaces coated with tunable biomaterial substrates (biomechanical), exogenously introducing
chemicals that affect cell differentiation (chemical), and/or genetically modifying cells to
selectively drive transdifferentiation via ligand-receptor binding (synthetic). Subsequently, we
identified and quantified phenotypical changes in cells using fluorescent microscopy, image
analysis, and molecular biology assays.

4.1. Chemical and Biomechanical Cues Regulate Human Cardiac Fibroblast
Differentiation into Myofibroblasts
In Chapter 2, we systematically identified the relative contribution of ECM rigidity and
TGF-β1 in regulating human cardiac fibroblast differentiation into its contractile counterpart,
myofibroblasts. We spin-coated polydimethylsiloxane (PDMS) of three elastic moduli on glass
coverslips to recapitulate the mechanical loads experienced in developmental, healthy, and
pathological ventricular myocardium. We have selected PDMS as our biomaterial substrate for

71
its tunability of elastic modulus and relatively easy fabrication. Human cardiac fibroblasts were
then seeded onto these various PDMS-coated coverslips with or without TGF-β1, as described in
Figure 2-1.
We quantified for cell density, actin coverage, and a-SMA/actin coverage, and our
results indicated a significantly higher actin and a-SMA/actin coverages on TGF-β1-treated
cells, irrespective of the ECM rigidity (Figure 2-2 and Figure 2-3). Furthermore, the cell density
remained constant, which in conjunction with a higher actin coverage suggested an increase in
cellular surface area, a hallmark characteristic of myofibroblast morphology
182
. We validated
these results with various gene expression quantifications (Figure 2-4). Finally, myofibroblasts
experienced partial reversal of its contractile phenotype after re-plating and removing TGF-β1,
which indicated that TGF-β1 was necessary in maintaining high levels of differentiated cells.
Our results collectively suggest that TGF-β1 predominantly regulates the differentiation of
human cardiac fibroblasts into myofibroblasts.
Understanding which microenvironmental cue has a greater effect in human cardiac
myofibroblast formation is crucial for developing effective therapeutic targets to combat cardiac
fibrosis. We highlighted how TGF-β1 is an important parameter to consider when controlling
cardiac fibroblast fate for in vitro studies, especially in engineered heterotypic cardiac tissue.
These data clarify the ambiguity surrounding the roles of the chemical and biomechanical cues in
regulating cardiac fibroblast differentiation from previous reports and potentially contribute to
improving models of pathological myocardium.

72
4.2. Combination of Microcontact Printing and Synthetic Notch Receptors
Generates Spatially Defined Heterotypic Tissues
In Chapter 3, we developed a novel technique of combining conventional microcontact
printing and fibroblasts genetically modified with synthetic notch receptors (synNotch cells) that
enabled us to spatially control transdifferentiation of cells into skeletal myoblasts. As with the
fibroblast study in Chapter 2, we utilized spin-coated PDMS coverslips as our platform and then
microcontact printed various patterns of GFP, which is the ligand that would drive skeletal
myoblast formation in synNotch cells if in direct contacted. The prior synNotch study has shown
that synNotch cells become skeletal myoblasts that subsequently mature into myotubes when in
contact with an isotropic coating of ligands
13
. However, this project is the first to microcontact
print ligands directly on a surface to transcriptionally activate synNotch cells with higher
resolution and precision.
We were able to compare microcontact printing GFP to placing a droplet of GFP on the
PDMS-coated coverslips, in order to assess the efficacy of the former technique. When synNotch
cells that express a synthetic GFP receptor and a myoD-mCherry gene were seeded onto the
various coverslips, the cells residing in the GFP region for both the droplet and microcontact
printed conditions were activated after 24 hours, as indicated by the mCherry fluorescence
(Figure 3-5 and Figure 3-6). The cells cultured either outside of the GFP region or in the absence
of GFP had no mCherry expression, which validated the proper functionality of these genetically
modified cells. Furthermore, the synNotch cells that expressed mCherry also began to express
sarcomeric α-actinin, the cytoskeletal marker exhibited by matured, multi-nucleated skeletal
myotubes
145
(Figure 3 – 7). Collectively, our results indicated that microcontact printing GFP is a
viable tool for controlling cell fate in a multi-cellular tissue with spatial precision.

73
For the first time, we developed an in vitro platform that utilizes both microcontact
printing and synthetic biology to spatially dictate transdifferentiation of fibroblasts and precisely
engineer heterotypic skeletal muscle tissues. In general, this novel method provides a robust way
of modulating and integrating ECM rigidity, tissue architecture, and heterotypic cell-cell
interactions, as a tool to help improve the limitations posed in current in vitro striated muscle
tissue models. This platform can be expanded to incorporate micropatterns of various sizes and
shapes, which allows versatility in generating specific tissues with physiologically relevant
architecture.

4.3. Limitations and Future Directions
As illustrated by the work presented in this dissertation, we contributed to elucidating the
various microenvironmental cues that regulate cell fate to engineer precise heterotypic striated
muscle tissues. We resolved the ambiguity surrounding the relative contribution of chemical and
biomechanical cues in driving human cardiac fibroblast differentiation into myofibroblasts in a
pathological context. Additionally, we presented the first in vitro platform that combines both
microcontact printing and synthetic notch receptors, which has potential to address the intrinsic
limitations of previous striated muscle co-culture models. As insightful as our results may be, our
studies have shortcomings that must be considered for future directions.
One limitation in the fibroblast study is not integrating cardiac myocytes in the
fibroblast/myofibroblast system. Since the native human myocardium is highly dependent on
these heterotypic cell-cell interactions for optimal function, the absence of myocytes may have
impacted the phenotype of the fibroblasts. As there is difficulty in obtaining primary human
cardiac myocytes for both ethical reasons
183
and limited organ donors
184, 185
, we should expand

74
our system to incorporate human cardiac myocytes from either directed differentiation from
various human stem cell sources
186-188
or direct reprogramming of fibroblasts
135, 171, 172
. We will
then be able to accurately evaluate the phenotypic changes in human cardiac fibroblasts and
provide additional findings in hopes of improving in vitro disease models of human ventricular
myocardium.
Another shortcoming is the lack of human relevance in our synNotch system, since
murine embryonic fibroblasts are genetically modified to generate our spatially defined
heterotypic skeletal muscle tissue. As we aim to engineer a more physiologically relevant healthy
skeletal muscle tissue or potentially utilize our platform for in vitro disease modeling that
translate to human patients who suffer from various skeletal muscle debilitations
189-191
, the
absence of human cells may confound our results. However, most studies have utilized rodent
fibroblasts and there have been very few studies transdifferentiating human fibroblasts into
skeletal myotubes
165, 180
. Although myoD is the sole regulatory transcription factor in direct
reprogramming of rodent fibroblast into skeletal myotubes, the efficiency in human fibroblasts is
significantly lower unless a secondary transcription factor is co-expressed with myoD
132, 165
.
Despite the challenges, we should aim to utilize human fibroblasts modified with the secondary
transcription factor to obtain an engineered heterotypic skeletal muscle tissue with human
relevancy.
Furthermore, our fibroblast and synNotch studies are both two-dimensional (2D) models,
which does not fully recapitulate the three-dimensional (3D) architecture in native striated
muscle tissues. Several studies have engineered 3D models of the ventricular myocardium
176, 192,
193
and skeletal muscle tissue
194, 195
to generate a more physiologically relevant
microenvironment. Although higher-scale models are more biomimetic, generally 3D systems

75
are more difficult to image, require a large number of cells, need a longer time period to
fabricate, and increase the complexity in user control over microenvironmental cues that are
easier to regulate in 2D
196, 197
. Our work illustrated how we can control cell fate to precisely
engineer heterotypic striated muscle tissues through chemical, biomechanical, 2D architectural,
and synthetic cues. Once we have improved on the versatility and efficacy of our systems, we
should explore how to translate our findings to 3D, which would provide even greater findings
for basic research, in vitro modeling, and regenerative medicine applications.
A future study in development is microcontact printing GFP ligands exhibiting various
sizes and shapes of micropatterns and studying how synNotch cells would be selectively
transdifferentiated in the GFP regions. As mentioned before, both ventricular myocardium and
skeletal muscle tissue are striated, which means that the respective muscle units are uniaxially
aligned and surrounded by fibroblasts that help optimize the tissue functions. One micropattern
we are utilizing is rectangular lanes, in which GFP ligands will be arranged directionally and
subsequently generate induced skeletal myotubes surrounded by undifferentiated fibroblasts.
This system would integrate the tunable biomaterial substrate (PDMS), 2D architecture (GFP
micropatterned lanes), and synthetic tools (synNotch modules) to generate a spatially defined
heterotypic skeletal muscle tissue. Furthermore, we plan on utilizing this platform to
transdifferentiate synNotch cells into cardiac myocytes, which is a more complex process that
requires three or more transcription factors
135, 136, 198
. Since the ventricular myocardium has a
similar architecture and heterotypic cell types to skeletal muscle, this study would bridge the
limitations that are currently posed for engineered striated muscle. Other designs such as
concentric circles and squares will also be explored to demonstrate the versatility of our platform

76
by precisely generating other heterotypic, non-striated tissue types and/or dictating cell-cell
interactions in a specific orientation for various functional assay.

4.4. Final Conclusions
The ventricular myocardium and skeletal muscle are highly organized tissues that are
characterized by an intricate interplay of various microenvironmental cues and heterotypic cell-
cell interactions to efficiently pump blood and engage in voluntary movement, respectively.
Identifying the effects of chemical, biomechanical, architectural, and synthetic parameters to
control cell fate and precisely engineer heterotypic striated muscle tissues in 2D are critical in
discovering new therapeutic targets and improving in vitro systems for healthy/diseased
modeling (Figure 4-1). Collectively, our data elucidates how the microenvironment can be
engineered to control cell fate and addresses the common pitfalls of current in vitro striated
muscle co-culture models.
Our work indicated that between the chemical (TGF-β1) and biomechanical (various
PDMS elastic moduli) cues, the chemical cue predominantly regulates human cardiac fibroblast
differentiation into myofibroblasts in fibrosis. Biomechanical forces appeared to have an initial
impact in synergy with TGF-β1, but that role was superseded by the chemical regulation.
Synthetic cues are novel modifications to fibroblasts in selectively activating skeletal muscle
transdifferentiation marker, myoD, when the cells come in direct contact with complementary
ligands. Microcontact printing ligands work just as robustly as direct addition of the ligands on a
surface, which provides us leverage in combining the spatial resolution of tissue engineering
techniques with the modularity of synthetic biology. Although this study focused on skeletal

77
muscle tissues, due to the convenience of engineering one transcription factor, we can translate
this platform to cardiac tissues, as well as other heterotypic tissues.
This dissertation elaborates on several microenvironmental cues that are essential to
consider when designing an engineered striated muscle tissue, as well as incorporating two
distinct research areas to develop a novel technique for generating physiologically relevant
tissues. Although there are some limitations in our studies that need to be addressed in the near
future, we have contributed to in vitro modeling through our findings. The day when the
microenvironmental features of 2D heterotypic tissue models can work in conjunction and
translate effectively their 3D counterparts is not too far away.

Figure 4-1. Natural and synthetic cues to generate physiologically relevant in vitro heterotypic striated muscle
tissues. Diagram of the interplay between the chemical and biomechanical cues that regulate human cardiac fibroblast
differentiation into myofibroblasts and the synthetic cues with architecture that generates spatially precise heterotypic
skeletal muscle tissues.

78
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Acknowledgements
My first words of gratitude are to my Father God in Heaven, who rejoiced with me during
the victories of my life and wept with me during the most difficult times of my life. The fact that
I even made it to the finish line of my Ph.D. career was by His grace alone. Your love is evident
from all the sanctification I went through during the past six years, and the beloved people You
have placed in my life. Thank You for reminding me to look to You whenever life gets tough,
especially when the situation in front of me appears bleak. Your love is greater than the sum of my
shortcomings, the obstacles that I have faced, and even the blessings I have received. I hope my
Ph.D. will be used for Your Kingdom and that I’ll continue to do Your will in my life. So I sing,
“Hallelujah, I’ll live my life in remembrance. Hallelujah, Your promise I won’t forget.”
My heart goes out to Dr. Megan McCain, who took me under her wings January 2015. I
remember taking her course during Fall 2014 and falling in love with the field of tissue engineering.
I know I wasn’t the brightest researcher and I had lots of struggles along the way, even to the point
of considering whether to drop the Ph.D program on multiple occasions. However, you never failed
to encourage me during the darkest moments of my life and sympathized with me, which made
me look to you as a life mentor as well. Your trust in me, ranging from brainstorming for my
projects to guest lecturing for one of the BME 410 classes, has pivoted me towards becoming an
independent, ambitious scientist. Even though I won’t be heading towards the path of research, the
time I had in the Laboratory for Living Systems Engineering was definitely worth it. I give it a 11
out of 10!
Dr. Leonardo Morsut, thank you for being on my qualifying exam and defense committees,
as well as my amazing collaborator. Whenever I visited HSC, you would welcome me and make
me feel like I am an integral part of your lab. Your passion for synthetic biology and tissue

90
engineering has motivated both me and Alex to work hard on the project. Your optimism and
energy to have weekly (or at least biweekly) meetings via Skype is admirable. These past three
years have been quite a journey and I can’t thank you enough for your guidance and support.
Dr. Michael Khoo, thank you for serving in my qualifying exam and defense committees.
I remember taking your BME 511 course in Spring 2015 and enjoying the content of the class. I
appreciated the jokes that you would make during class, as a 3:30PM class was difficult getting
through without some humor and fun. Coding is one of my weaknesses and your class helped me
to overcome my fear of using MATLAB. Additionally, you are one of the kindest professors I
have met, both inside and outside of class settings. Thank you for your time and support!
I would like to also thank my other qualifying committee members, Dr. Keyue Shen and
Dr. Eunji Chung. Your labs are basically “sister” labs to the McCain lab and through both of you,
I got to meet wonderful colleagues who I discussed science with over meals/dessert. Both of you
have personally been so kind to me and willing to answer questions that I had. I wish all the best
for both of you in your careers as tenure-track faculty, and I know we will be communicating more
frequently for the upcoming teaching labs.
Mischal Diasanta – you are truly an MVP in my heart. I remember coming into your office
in August 2014, completely unaware that I needed to have D-clearances for the classes I couldn’t
enroll in. Instead of calling me out, you were very patient and helped me step-by-step on starting
my Ph.D. career at USC. I remember when you said you were moving up to the Bay Area, I was
both happy and sad because I knew you got a great job lined up, but at the same time, you wouldn’t
be present at USC for my defense. All the times I talked with you for GSBME and randomly about
how good Filipino dessert is (ube ice cream is so amazing), you always listened and laughed with
me. I can’t wait to meet up with you when I come back home for the holidays. God bless you!

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William Yang, you are such an eccentric figure. I remember when I met you for the first
time, you would constantly laugh at your own jokes and overuse the phrase “just kidding”. But I
realized shortly afterwards, you did that to create a welcoming, down-to-earth environment, which
I greatly appreciate. Thank you so much for helping me with GSBME-related events, as well as
figuring out the defense document signatures. I’m going to miss stopping by your office just to say
hello and seeing all the amazing flyers you make weekly for Tea Time. I know the BME
department is in good hands, so I hope you will continue to make an impact on other graduate
students as much as you did with me. I’ll probably still stop by since I’m only three buildings
down, so I guess it’s not even a goodbye.
Alex March, my fellow Pokemon and coffee buddy, you are literally the weirdest person I
have ever met. You get excited over the littlest things and don’t use any social media platform, as
if you are still stuck in the 90s. Also, I cringed whenever you dug through your bag of spinach,
carrots, lettuce, or whatever rabbit food you brought to UPC during collaboration days, but then I
remembered you grew up as a forest boy. But most importantly, you are the person who gave me
energy whenever I would feel exhausted from conducting countless number of experiments that
day. You are the buddy who wants to grab lunch at the Keck hospital and breakfast burritos during
the times I arrived early. I’m so happy to hear you got an amazing job in Pasadena doing virus
science. I know for sure I’ll hit you up soon. Take care bro and bless up!
Davi Leite, my number 0 in the hypothetical Hunger Games story we expanded on for a
few years, your brain has more storage than our lab backup system. You know literally ALL the
countries in the world by name and their capitals, soccer players from the past few decades, any
historical fact that is of minimal relevance to life, and random science trivia. As much as I joke
around with you that you are my first target in a dystopian battle royale, you are one of the closest

92
friends amongst my work community. All those nights that we discussed philosophy, religion, and
ethics, as well as sharing about our life struggles – I would not trade that for anything. You
supported me in my spiritual journey by coming to hear my testimony at church, as well as to
KCM Friends Night. Finally, you came out to all GSBME meetings to support and are always
taking initiative to help people, in both lab and non-academic settings. You are amazing and I wish
you all the best in your postdoc career at Northwestern University. I shall see you soon in Chicago!
Nethika (Tika Masala) Ariyasinghe, I remember our awkward conversation when I saw
you eating meat and I asked whether Indians are allowed to eat meat. And then I found out you are
Sri Lankan… But boy we came a long way from that conversation. The endless discussions of
what restaurants and dessert places are hot, as well as the boba runs that we had – those were some
amazing memories that I will cherish forever. Also, thank you always for being so kind to me and
for giving me life advices whenever I felt down. I feel like I could be myself in front of you and
know that you won’t judge me. You are an amazing person and I wish you all the best in both your
academic career and personal life. We shall get boba very soon!
Andrew Petersen, the man who claims he likes coffee but actually only drinks milk with a
dash of coffee and survives on basic food like potatoes, eggs, bread, peanut butter, and beans, we
went through one heck of a ride together. I remember both of us starting off our Ph.D. program in
different labs, but our paths converged when we joined the McCain lab because we found interest
in studying tissue engineering. I also remember getting Panda Express together before Dr. Finley’s
class and attempting to fight the food coma that hit hard during class. We submitted our first paper
around the same time and passed our qualifying exams together in a span of a few months. We
started together and I know that you will be finishing up soon too. You are a unique human being
who cares a lot about the small details, and frankly gets distracted too easily. I love you a lot bro!

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Joycelyn (not Jocelyn but Joyce + Lyn) Yip, who calls you by your full name anymore?
JY, I remember the second day I met you and imaged some samples with you, you roasted me for
attending UCLA and would not let that down for the longest time. I always thought you were
intimidating, and I was thinking, “oh boy, I don’t think we will be good friends…” But how wrong
I was. You are an amazing friend to me and have supported me in so many things I did. I know
that you will continue to support me even as I start my full-time job as the teaching lab manager.
Thanks for all the times you invited me over to your place for steak and for bringing those amazing
blackcurrant gummy candies from Hong Kong. Best of luck wrapping up your Ph.D. and starting
your job at McKinsey in the near future!
Jeffrey (J-Free) Santoso, you are literally the definition of a frenemy. You roast me like I
am a rotisserie chicken sold at Costco and have no hesitation in calling out ALL my mistakes.
Your favorite phrases “so beast” and “get rekt” have unfortunately been engrained in my brain and
I find myself constantly saying them. I hate you so much, but I also love you so much. As much
as you push my buttons, you are the first one who I ask to go eat lunch/dinner with and on boba
runs. You helped me with moving apartments, driving me to the airport on many occasions, and
also planning many GSBME events that I had difficulty juggling. You provided me academic info
about skeletal muscle, as well as video game info on how to be good at Pokemon and Fire Emblem.
Even though they are seldom, I appreciate the life talks we had and all the encouragement that you
provided (emphasizing SELDOM). You are a good man and I hope to hang with you even after
Ph.D., which who knows how long you will be roasting me.
Megan Rexius-Hall, you are such an amazing baker and scientist. These are two things I
think of because your baked goods are so delicious and also your advice for clarifying experimental
protocols (qPCR, microfluidic device, clean room, etc.) were very helpful. You and Lance joined

94
the Vine Church shortly after you started in our lab and I know both of you became vital members
of the church, specifically in the Grapeseed Ministry. You are the only person I know who loves
bubblegum ice cream and prefers artificial banana flavor over the natural fruit. You are the one
who introduced me to Bubly sparkling water and now I am hooked – blackberry flavor is so good!
All the interactions in lab and the conversations we had on the way to small group and summer
VBS have made me grow closer to you. I pray that you will find a great academic position in the
near future and hopefully stay in LA (although it seem like you would want to go somewhere else)!
Patrick Vigneault, my one and only French-Canadian coffee buddy, it’s only been a little
over a year but I feel like I got so close to you. Maybe it’s our common love for Columbian medium
roast or that one time we went to Copa Vida together after getting some Japanese ramen (not the
Maruchan you eat for lunch in lab). In an academic setting, you have been so helpful as you are
willing to answer any questions I have (hence I go to you first) and also to assist me in lab tasks.
Thanks to you, our lab finally has an established protocol for hiPSC differentiation into cardiac
myocytes, which so many of us tried to do but could not get it to work robustly. Not only are you
super smart, but you are also one of the nicest people I have ever met in my life. You always try
to put on a smile even though you are exhausted and provide help whenever people need it. God
bless you, Alexandra, and future Patrick Jr (or Patricia)!
Shadi Razipour, my one and only undergraduate student I had in the six years I was in the
Ph.D. program, you are so amazing. I still remember asking you to help me spincoat PDMS-coated
coverslips, image coverslips, and conduct cell count, only for you to approach me asking me to do
more hands-on lab tasks. I felt (and still feel) bad about not giving you a more independent project,
but I hope you can forgive the struggling Ph.D. student who had a difficult time figuring out what
even he had to do. Even in my shortcomings, you were always so patient and kind to me. Thank

95
you for the birthday goodie bag that you provided with the honey from Arkansas and Swedish Fish
(yummm) and also for inviting me to your graduation dinner (the kebabs were delicious). I hope
you are doing well! I miss you.
Natalie Khalil, Divya Gupta, Nina Maxey, and Mher Garibyan – you four are the future
generation of the McCain lab. Each of you have been so kind to me and made my final year of the
Ph.D. program enjoyable. Observing the passion you all have for research has rekindled the fire
that I initially had, which is especially important for getting this dissertation and defense
preparation done. I hope you enjoy every step of the Ph.D. program and despite the difficulties
that you will face (trust me, there will be a good amount), stay strong and rejoice in the little things.
My advice is to find a community that you can belong to outside of work. This will provide a nice
balance between work and social life. Best of luck to everyone and I will visit frequently!
Jonathan Wang, Deborah Chin, and Noah Trac – I love being the fourth member of the
Chung lab. Thanks for all the lunch and dinner breaks that we had together. Lowkey, I wished that
you guys stayed in DRB, since it’s kind of a pain to walk over to MCB just to strike a conversation.
You guys are awesome to hang out with and I hope that we can continue to do so even after I move
three buildings down. I wish all the best for you guys as you progress in your Ph.D. career. Quick
summary: Jon is the nicest member amongst the three and my old BMES roommate, Debs is pretty
high maintenance but yet very down-to-earth and easy to approach, and Noah is my Persona 5
buddy who loves boba as much as I do.
Yuta Ando, I miss having you as my roommate. As much as I may have annoyed you when
we lived together, I really liked living with you. I’ll miss all the times we went to karaoke together
and sang our hearts out, despite not being kpop stars. The amount of hard work I see you do every

96
day in lab is very respectful and I know that you will be a successful scientist in the near future. I
hope you stay in LA, so we can continue to hang out. Best of luck finishing your Ph.D. bro!
Lewis Chen, you have been my best friend since 7
th
grade. I remember being in the same
homeroom as you in Mrs. Fung’s class and becoming chill-pill buddies. Even as we went to
different high schools, you accepted Jesus Christ as your Lord and Savior in 10
th
grade and started
attending Golden Gate Presbyterian Church. I was so thankful to go to church with my best friend.
Even after I moved to LA in September 2010, we still kept in touch and continue to hang out with
each other. I know you went through a lot since then and I’m so sorry that I wasn’t able to
physically be there to support you, but I’m thankful that I was able to pray for you and call you. I
cherish all the times we met up in San Francisco when I went home for the holidays and the times
you came down to LA to visit me (16 tacos from Ave 26 was nuts). I can’t wait to see what God
has in store for us. Fifteen years of friendship is just the beginning my friend. God bless!
Hyun-Gyum Shin, you are my other best friend who I met at UCLA in 2010. I remember
when we were placed in Jeff Hong’s small group together and I used to think “oh man, who is this
conceited kid”. God definitely humbled you throughout your years in college and I’m so glad I
was able to play a role in your spiritual growth. I never would have thought that one AIM message
I sent summer 2011 after your major surgeries would have solidified our friendship for the next
nine years. I’m not going to lie – there were many times I had difficulty talking with you because
you were way too direct in what you said and felt condescending. However, I know you changed
a lot since then and that all the harsh things you said was to ultimately keep me accountable as a
fellow Christian brother. I miss the times we gathered weekly to share about our lives and got
Everest breakfast burritos. I’m so thankful for you and I know that God will do wonderful things
with your life. I’ll continue to pray for you!

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Hans Kim, you are literally one of my closest friends (and I mean literally since we see
each other at least twice a week). I remember meeting you at a UCLA CCM event in September
2012 and thinking “who is this kid”. I felt like we really didn’t hang out with each other until I
persuaded you to join The Vine in 2014. I’m so thankful you decided to stay because we naturally
began to have deeper conversations and went to so many boba places after church (from It’s Boba
Time to Boba Guys to Wushiland). You are definitely unique in that you have such a huge heart
for serving people. You actually care a lot about what people are going through and are always
willing to help out with set-up, clean-up, and leading praise even though many people do not
contribute. Your resilience and love for people always motivate me to do the same and to pour my
life into the people around me. Thank you for everything and many more years to come.
Pastor Eliot and Jinna Luongo, you two are my role models. Both of you always invite me
over to your home and treat me like a VIP guest. I’m always so grateful for the hospitality, love,
and concern for me. Titus, Cara, and Lydia are so cute and I know that they are growing up well
because you two have been such wonderful parents to them. God has blessed me immensely with
you two in my life. Eliot, I know that you love me so much and are willing to hear every struggle
I go through. All the times I called you because I was going through spiritual stagnation and the
times we talked in person over boba (which you always bought for me), I will never forget the
love that you poured into me. Jinna, you never fail to ask me how my week has been. Whenever I
see you and can tell you are so exhausted, you always smile and say that everything is moving
along well. Furthermore, you try to make it to every youth group event despite how crazy your
schedule is. You are literally a supermom and I’m so humbled to know that I’m serving alongside
someone who God is using mightily. Love you two so much!

98
Pastor Kyung Kang, you are a very important mentor figure to me. I remember the youth
group was not in the most ideal state when you arrived in August 2018, but yet you always
encouraged me to keep up the hard work and pour into them. Additionally, you would do your best
to meet up with every person at church individually and have bought me lunch several times since
then. Your passionate, powerful voice when you preach gets me excited to hear God’s message
and that passion is manifested during our youth group staff meetings. Thank you for overseeing
the youth group and constantly praying for us. God has so much in store for you and I’m excited!
James and Unice Wee, you two are so awesome. Not only is your daughter the cutest thing
in the world, but also you two take such good care of me. All the times that you invited me over
to your home and for treating me to dinner, as well as being one of the first youth group staff, that
meant so much to me. The youth group definitely grew because of the love that you two poured
into the ministry. James, thank you for being a big brother figure in my life. I strive to be like you
spiritually and socially. Unice, thank you for being the older sister figure to me. You are so funny,
yet savage whenever we talk. I love serving with you two and can’t wait for what God has in store
for your family!
Eddie Kim and Nuel Jun, thank you so much for serving youth group. In the time that we
were in dire need of youth group teachers, you two were prayerfully deciding to join the ministry.
I haven’t gotten the chance to talk to you two before then, but I definitely have gotten closer to
both of you. I miss the board game small group, since I was able to bond with you two over semi-
competitive games and discussion of previous week’s sermon. I can see your passion for the youth
group and for God’s Word whenever we serve together. Eddie, thank you for teaching the youth
group with me. Even though you may be soft-spoken, your actions speak louder than words and I
am truly blessed. Nuel, thank you for being so kind to me. I think the first time we talked together

99
was the first small group session and you welcomed me into your home. I felt awkward because I
did not know you and Eddie well but I was able to assimilate quickly because of your kindness. I
look forward to continuously serving with you two!
Maddie Yi, Jonah Yi, Hannah Yi, Faith Chang, Hope Chang, Zachary Roh, Kristyn Roh,
Olivia Ip, Ella Hwang, Samuel Chai, Matthew Heur, and Aaron Kang – thank you for being my
wonderful youth group students! Your energy and smiles have brought me so much joy during the
past year. For the older students, we went through a lot of changes together, some good and some
difficult. Thank you for sticking through with the youth group and for constantly encouraging me.
I pray that God will continue to bless your lives. For the younger students, I know it must have
been difficult to acclimate to the new environment. But you did it! I pray that you will continue to
love God and follow His ways in all that you do.
The Vine Church family, I don’t know where I would be without your constant love,
accountability, and prayers. I remember joining The Vine in November 2010, but I honestly did
not feel like I belonged until closer to 2017. I think serving in youth group as a teacher has changed
the way I think and I’m so grateful for the everyone I met. The past couple retreats reminded me
that although we have more room to grow, we are indeed family. Thank you for everything and I
hope that our local church will represent Christ in all we do. Belong, believe, become.
USC KCM, I’m so thankful that you welcomed me (only graduate student) into your group.
I remember how difficult it was to fit in the first year I joined KCM. I wanted to leave, but yet
there was a tugging in my heart to keep praying for everyone and continuing to be a mentor figure.
I couldn’t understand why that was, but five years down the line, I can see why God has placed
me in KCM. My heart for missions increased significantly and I was reminded of my conviction
to serve collegians post-grad. The praise teams that led worship during GMs, Monday Night Prayer

100
events (both attending and serving), relational outreach events, and campus-wide KCM events –
every single thing has brought me joy and spiritual maturity. I know I won’t be able to serve much
longer, but I’m so blessed to be a part of the community. May God’s love and protection be on this
campus ministry forever.
Rebecca Cho, my sister and closest friend, thank you for being present in my life. I
remember growing up, we used to argue so much and had myriad of conflicts because of our
personality differences and immaturity. But now, I am beyond thankful for the love that has been
built up. I know I grew more as a person since I went to college and you did as well when you
went to UC Davis. Our vacations to Korea, Canada, and Japan were awesome and I’m so glad I
had a travel buddy who is willing to try delicious food with me, as well as post countless number
of pictures/videos on Instagram. I know it must be difficult in culinary school, but by the time you
read this, you will be most of the way through. God has blessed with you a passion for baking and
you make some dang good cookies (and probably many more pastries now that you are
professionally trained). I hope you move back to the West Coast soon and/or start your own bakery
in Korea so I have a reason to visit the country. Regardless of what happens, God has a great plan
for you and will protect you in all that you do. Love you!
The next two paragraphs for my parents and grandparents will be in Korean. But before I
transition to the last part of acknowledgements, I want to give a quick shoutout to all my relatives
(aunts, uncles, cousins), friends, and whoever else had impact in my life during my Ph.D. career.
I apologize for not having enough space to write, but please know that I am truly blessed to have
everyone in my life. God bless you all!
사랑하는 엄마랑 아빠, 저를 27 년을 귀하게 키워주셔서 감사합니다. 어릴때부터 사랑으로
품어주셨고 자라면서도 계속 응원해주셔서 감사합니다. 엄마, 제가 어릴때 말이 많았지만 그래도

101
끝까지 들어주고 같이 놀아줘서 지금 제가 이렇게 자란것 같아요. 그리고 제가 공부를 열심히
하면 너무 기뻐해줘서 제가 더 열심히 했던것 같아요. 비가 올때마다 저를 학교에서 픽업해주고
(가까이 있는데도) 맛있는 음식 만들어준게 생각이 나네요. 2010 년에 UCLA 갔을때 노란색
자켓입은 아들이 손을 흔들었을때가 벌써 9 년전이에요. 그래도 다행이 LA 에 자주 놀어오니깐
저는 좋아요. 아직도 “아들 괜찮니” 하면서 전화 혹은 카톡이 올때마다 너무 행복해요. 대학원에
있으면서 힘들때 늘 위로해주고 하나님을 바라봐라 얘기할때 제 신앙도 많이 성장한것 같아요.
아빠, 제가 전화를 자주 드리지 않지만, 저는 꼭 기도하고 있어요. 서울가든에서 벌써 20 년넘게
가족을 위해서 일하고 있는데 얼마나 힘들까 상상이 안되요. 아무리 피곤해도 집에 올때마다
미소를 지우며 저한데 인사하는게 아주 존경스러워요. 저도 피곤하지만 그래도 티를 안 내는게
중요하구나라고 배웠고 힘들지만 조금만 더 견디자라고 결심했어요. 저를 위해서 기도하는거 잘
알고있고 더 멋진 아들이 될수 있게 열심히 노력할게요. 아직도 많이 부족하지만, 그래도 너무
감사해요. 엄마, 아빠 사랑하고 감사합니다!
할머니, 할아버지 – 저 박사학 공부 끝났습니다. 지금까지 저를 위해서 늘 기도해주시고
손자대해서 좋을 얘기를 해주셨다는것 대해서 너무 감사합니다. 대학원에 있으면서 할머니하고
할아버지가 자랑스러워 할 수 있게 열심히 공부를 했습니다. 생각보다 6 년이 아주 빨리
지나갔습니다. 어릴때부터 저를 위해서 기도해주신게 많이 도움된것 같습니다. 샌프란시스코
놀러갈때마다 성장한 모습을 보여드릴 수 있어서 저는 너무 기쁩니다. 제 졸업식을 참석할 수
있어서 저는 하나님께 늘 감사드립니다. 계속 건강할 수 있게 제가 기도하겠습니다. 할머니,
할아버지 너무 너무 사랑합니다!!

Abstract (if available)

Abstract To efficiently pump blood throughout the body, the myocardial tissue in the heart is composed primarily of longitudinally aligned cardiac myocytes that rhythmically contract with supporting fibroblasts that synthesize the extracellular matrix (ECM). When pathological events occur, such as myocardial infarction, the myocardium undergoes chemical, mechanical, and electrical alterations due to changes in the cellular phenotypes and architecture of cardiac myocytes and fibroblasts. In particular, post-infarct remodeling of the myocardium increases ECM rigidity, production of transforming growth factor beta-1 (TGF-β1), and disorganization of myocyte alignment. These post-infarct changes are postulated to affect interactions between myocytes and fibroblasts and overall cardiac function, but these phenomena are poorly understood because existing in vitro models have a limited ability to recapitulate cell-cell interactions reminiscent of the native human myocardium. To address this, our goal is to develop new approaches for engineering heterotypic, spatially organized striated muscle tissues with mechanical, biochemical, and/or synthetic control over cell fate. First, we will measure the relative effects of mechanical and biochemical cues on human cardiac fibroblast differentiation by introducing TGF-β1 to fibroblasts cultured on polydimethylsiloxane (PDMS) substrates of varying rigidities. Next, we will develop a novel approach to spatially dictate cell fate and generate heterotypic skeletal muscle tissues by combining synthetic biology and substrate micropatterning. This new approach will enable further studies into how fibroblast-myocyte interactions contribute to cardiac disease progression and are regulated by physical changes in the microenvironment. Collectively, our research establishes new tools related to controlling cell fate using various natural and synthetic cues. Our approaches can be applied to engineer sophisticated striated muscle tissues for in vitro applications, such as discovery and testing of new therapeutic targets and translation to regenerative medicine in the long-term.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Spatially controlled tissue differentiation using the synthetic receptor SynNotch

PDF

Engineering a post-infarct human myocardium on a chip to reveal oxygen-dependent crosstalk in cardiac fibroblasts and myocytes

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Engineering 2D & 3D microphysiological systems for interrogating skeletal muscle tissues

Asset Metadata

Creator Cho, Nathan (author)

Core Title New approaches for precisely engineering heterotypic muscle tissues by naturally and synthetically controlling cell fate

School Viterbi School of Engineering

Degree Doctor of Philosophy

Degree Program Biomedical Engineering

Publication Date 02/04/2020

Defense Date 12/04/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag cardiac,ECM rigidity,fibroblasts,GFP,heterotypic,microcontact printing,natural cues,OAI-PMH Harvest,skeletal muscle,striated muscle tissues,synNotch cells,synthetic biology,synthetic cues,TGF-B1

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor McCain, Megan (committee chair), Khoo, Michael (committee member), Morsut, Leonardo (committee member)

Creator Email chonatha@usc.edu,krn.nacho@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-265129

Unique identifier UC11673230

Identifier etd-ChoNathan-8140.pdf (filename),usctheses-c89-265129 (legacy record id)

Legacy Identifier etd-ChoNathan-8140.pdf

Dmrecord 265129

Document Type Dissertation

Rights Cho, Nathan

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA