University of Southern California Dissertations and Theses

The modulation of dynamin and receptor endocytosis machinery using elastin-like polypeptides

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The modulation of dynamin and receptor endocytosis machinery using elastin-like polypeptides

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Content THE MODULATION OF DYNAMIN AND RECEPTOR ENDOCYTOSIS MACHINERY
USING ELASTIN-LIKE POLYPEPTIDES

by
Hugo Avila

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirement of the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL AND TRANSLATIONAL SCIENCES)

May 2022

Copyright 2022 Hugo Avila
ii

Dedication

To my family
To my parents for their risk and sacrifice
To my brothers for setting the example
To my kids for teaching me patience

iii

Acknowledgements

This thesis exists with the help of everyone invested in my success, from before I
knew I could do it to when I realized I could.
I would like to thank Dr. Andrew MacKay for his patient mentoring that provided a
mold and room for me to grow in - his style of mentorship pushed me to thrive as an
independent scientist, all the while offering advice and motivation when it was needed.
His lab leadership made this Ph.D. experience a fruitful and enjoyable adventure. This
appreciation also extends to my thesis committee members, Dr. Sarah Hamm-Alvarez
and Dr. Curtis Okamoto. Their support has been invaluable, especially their insights on
trafficking and imaging. This specific skillset directly led to my career opportunity outside
of USC and I appreciate their role in this.
Thanks also goes to the current and previous MacKay lab members, many of
whom were also friends and taught me the essentials of the work contained herein.
Thanks to Shruti Kakan, Dr. Jordan Despanie, Alvin Phan, Shin-Jae Lee, Dr. Zhe Li, Dr.
Santosh Peddi, Dr. Aida Kouhi, Dr. Hao Guo, and Dr. Changrim Li. Special appreciation
goes to Dr. David Tyrpak for his expertise of imaging rubbing off on me; to Dr. Anh Truong
for always having time to answer small technical questions and ‘coffee time’ discussions
that led to some of my best ideas; to Geetha Boddu for her big contributions to our shared
EGFR project and for teaching me how to be a better mentor; and to Dr. Mincheol Park
for being the first person to teach me how to work with ELPs. Their contribution to my
success is much appreciated.
I would also like to thank the people outside the lab. Thanks to the MESA and
MORE programs for being the nucleus to my scientific beginnings. Thanks to Wade
iv

Harper for his personal and academic encouragement, and for his advocacy for students
through the PGA. Also, thanks to the founding members of the ‘underground PGA’; Sam
Garza, Mario Alba, Minchang Choi, and Ryan Van Damme for the great company and
food. Their friendship made graduate school richer.
Thanks to my family, for whom without, I would not have been able to take the risk
of doing this. Thanks to my parents for the shelter they provided and their unconditional
support. Thanks to my brothers for paving the road. And finally, I would like to thank my
kids for their patience – that they may see this and be motivated to accomplish more.

v

Table of Contents
Dedication ........................................................................................................................ii
Acknowledgements ......................................................................................................... iii
List of tables ....................................................................................................................ix
List of figures ................................................................................................................... x
List of abbreviations ...................................................................................................... xiii
Abstract ........................................................................................................................... 1
Chapter 1: Introduction .................................................................................................... 4
1.1 Applications of elastin-like polypeptide technology ............................................. 4
1.2 Temperature-sensitive ELPs as intracellular switches ........................................ 5
1.3 ELPs as drug carriers ......................................................................................... 7
Chapter 2: Intracellular dynamin elastin-like polypeptides assemble dynasomes
associated with inhibition of epidermal growth factor internalization ............................... 9
2.1 Abstract .................................................................................................................. 9
2.2 Introduction .......................................................................................................... 10
2.3 Materials and methods ......................................................................................... 14
2.3.1 Construction of DNM2-ELPs .......................................................................... 14
2.3.2 Cell culture and transfection .......................................................................... 14
2.3.3 Western blot analysis ..................................................................................... 15
2.3.4 Fixed cell preparation .................................................................................... 15
2.3.5 Imaging and structural analysis ..................................................................... 16
2.3.6 Dynasore inhibitor assay and analysis ........................................................... 18
2.3.7 Live-cell imaging and analysis ....................................................................... 18
2.4 Results and discussion ........................................................................................ 20
2.4.1 Generation of thermo-responsive DNM2-ELPs from a PCDNA3.1 plasmid
capable of transfecting mammalian cells. ............................................................... 20
2.4.2 Expression of DNM2-ELPs in HEK 293T cells is confirmed by Western blot
and immunofluorescence. ....................................................................................... 20
2.4.3 DNM2-ELPs form distinct structures as a function of temperature. ............... 23
2.4.4 Orthogonal and mesh reconstruction of dynasomes show distinct lumen
contraction in Dynasome-S morphologies .............................................................. 26
2.4.5 Dynasome size depends on dynasore and temperature ................................ 28
2.4.6 Dynasomes appear morphologically independent from F-actin structures .... 30
vi

2.4.7 Dynasome formation is visualized in live-cells with a GFP-based surrogate
reporter ................................................................................................................... 32
2.4.8 Dynasome radius of curvature may depend on a balance between protein
folding of DNM2 and ELP domains. ........................................................................ 35
2.4.9 Dynasomes appear to inhibit EGF internalization .......................................... 38
2.4.10 Dynasomes do not appear to affect flot1/2 internalization or
macropinocytosis .................................................................................................... 40
2.4.11 Dynasomes colocalize with several organellar markers for endocytosis and
trafficking ................................................................................................................ 41
2.5 Conclusions ......................................................................................................... 44
2.6 Sequences and tables.......................................................................................... 45
Supplemental Table S1. Nucleotide sequence of DNM2 gBlock Gene Fragment. . 45
Supplemental Table S2. Amino acid sequences of DNM2 and GFP ...................... 46
DNM2. Sequence ID: NP_004936.2 ....................................................................... 46
GFP. Sequence ID: BAK26800.1............................................................................ 46
Chapter 3: Elastin-like polypeptide fusions to modulate intracellular signaling of EGFR
signaling in a heat dependent manner .......................................................................... 47
3.1 Abstract ................................................................................................................ 47
3.2 Introduction .......................................................................................................... 48
3.3 Materials and methods ......................................................................................... 52
3.3.1 Cell culture ..................................................................................................... 52
3.3.2 Plasmid DNA quality control .......................................................................... 52
3.3.3 Stable EGFR-GFP-ELP cell line generation .................................................. 52
3.3.4 Immunoblot assay .......................................................................................... 53
3.3.5 Live cell super resolution imaging and analysis ............................................. 54
3.3.6 MAPK kinetic assay and analysis .................................................................. 54
3.3.7 Real-Time quantitative PCR (RT-qPCR) optimization and EGFR pathway
array analysis.......................................................................................................... 56
3.3.8 Ingenuity pathway analysis ............................................................................ 57
3.4 Results and discussion ........................................................................................ 58
3.4.1 DNA quality control and expression ............................................................... 59
3.4.2 HEK-EGFR-V96 cells form puncta after mild heating .................................... 62
3.4.3 HEK-EGFR-V96 cell transition triggers downstream phosphorylation of
ERK1/2 ................................................................................................................... 63
vii

3.4.4 EGFR real time quantitative PCR gene array ................................................ 64
3.4.5 Ingenuity Pathway Analysis of gene array data ............................................. 69
3.5 Conclusion ........................................................................................................... 73
3.6 Sequences and tables.......................................................................................... 74
Table S3.1. Full EGFR, GFP, and ELP protein sequences .................................... 74
Chapter 4: Cell-surface GRP78 targeting enhances potency of rapamycin via an elastin-
like polypeptide drug carrier .......................................................................................... 76
4.1 Abstract ................................................................................................................ 76
4.2 Introduction .......................................................................................................... 77
4.3 Materials and methods ......................................................................................... 81
4.3.1 Cloning and sequencing ................................................................................ 81
4.3.2 X-5FA protein production and purification ...................................................... 82
4.3.3 Characterization of transition temperature (Tt) ............................................... 84
4.3.4 Characterization of nanoparticle radius by Size Exclusion Chromatography –
Multi-angle Light Scattering (SEC-MALS) and Dynamic Light Scattering (DLS) ..... 84
4.3.5 Exact mass determination by Matrix Assisted Laser Desorption/Ionization
Time of Flight (MALDI-TOF) ................................................................................... 85
4.3.6 Rapamycin drug loading ................................................................................ 85
4.3.7 Mammalian cell culture .................................................................................. 86
4.3.8 Flow cytometry and analysis .......................................................................... 86
4.3.9 Western blot and analysis .............................................................................. 87
4.3.10 Confocal imaging and analysis .................................................................... 89
4.3.11 Fluorescent degradation of 5FA and L-5FA ................................................. 90
4.4 Results and discussion ........................................................................................ 91
4.4.1 Plasmid DNA cloning and characterization .................................................... 92
4.4.2 Expression and biophysical characterization of X-5FA constructs reveal high
purity and low aggregation ...................................................................................... 92
4.4.3 csGRP78 association is assessed by flow cytometry .................................... 97
4.4.4 Rapamycin encapsulated X-5FA inhibits mTORC1 signaling ........................ 99
4.4.5 L-5FA significantly increases cellular exposure compared to untargeted 5FA
.............................................................................................................................. 102
4.4.6 Broad implications of csGRP78 targeting in the context of cancer therapeutics
.............................................................................................................................. 104
4.5 Conclusion ......................................................................................................... 107
viii

4.6 Sequences and tables........................................................................................ 108
Supplemental Table S1: Full amino acid sequences of A24, FKBP, 5FA, and X-5FA
.............................................................................................................................. 108
Chapter 6: Conclusions and future directions .............................................................. 112
6.1.1 Higher throughput methodology is needed to validate ELP-switch technology
.............................................................................................................................. 112
6.1.2 Receptor tyrosine kinase fusions to ELPs can expand drug target identification
capabilities ............................................................................................................ 114
6.1.3 Advancement of csGRP78 targeting ELPs .................................................. 115
6.1.4 ELPs as 3D biomaterials.............................................................................. 116
Bibliography ................................................................................................................ 119

ix

List of tables

Table 2.1 Summary of ELP fusion proteins evaluated in this work

17
Supplemental Table S2.1 Nucleotide sequence of DNM2 gBlock Gene
Fragment.

42
Supplemental Table S2.2 Amino acid sequences of DNM2 and GFP

43
Table 3.1. EGFR-ELP nomenclature and characteristics

56
Table 3.2: TaqMan mRNA Quantification (RQ) HEK-EGFR -V96 relative to
HEK-EGFR-A96

63
Table S3.1. Full EGFR, GFP, and ELP protein sequences

71
Table 4.1. 5FA shorthand sequences and Tt

78
Table 4.2. Biophysical characterization of 5FA constructs

91
Table 4.3: MALDI-TOF (M+XH)/X charge states

92
Supplemental Table S1: Full amino acid sequences of A24, FKBP, 5FA, and
X-5FA

105

x

List of figures

Figure 1.1: Intracellular fusions of ELP to functional proteins confer
temperature sensitive properties in the chimeric fusion.

2
Figure 1.2: ELP enhanced pharmacokinetics are driven by a larger
hydrodynamic radius, which protects it from glomerular filtration.

5
Figure 2.1: Temperature-sensitive DNM2-V96 undergoes phase-transition
above Tt.

10
Figure 2.2: Forward and reverse primers were used to validate DNM2-ELP
sequences to confirm successful insertion into a PCDNA3.1 mammalian
vector.

16
Figure 2.3: DNM2-ELP plasmid DNA and its expressed construct were
confirmed in HEK293T cells.

18
Figure 2.4: HA-DNM2-ELP expression is confirmed using α-HA and α-ELP
antibodies with indirect immunofluorescent microscopy.

19
Figure 2.5: Temperature-sensitive DNM2-V96 forms distinct vesicular
structures at different temperatures while temperature-insensitive DNM2-A96
does not.

20
Figure 2.6: Live cells expressing wtDNM2-pmCherry were imaged by confocal
microscopy to observe the effects of DNM2 overexpression during heating.

22
Figure 2.7: 3-dimensional orthogonal projections of DNM2-ELP show their
respective signal distribution on the -xyz axis using α-ELP secondary
immunofluorescence.

24
Figure 2.8: The diameter of DNM2-V96 structures decreases with temperature
and inhibition of Dynamin GTPase activity.

26
Figure 2.9: The formation of dynasome morphologies do not appear to be
driven by cytoskeletal dynamics.

28
Figure 2.10: Live cells expressing either GFP-V60 (single) or GFP-V60 and
DNM2-V96 (dual) were imaged by confocal microscopy to quantify the Tt of
DNM2-V96.

30
Figure 2.11: Dynasome contraction potentially occurs as a result of a tighter
radius of curvature.

33
xi

Figure 2.12: DNM2-V96, but not DNM2-A96 was able to inhibit EGF
internalization at 37°C in fixed HEK293T cells.

36
Figure 2.13: Dynasomes do not appear to affect flotillin1/2 or dextran
trafficking.

37
Figure 2.14: Formation of dynasomes resulted in colocalization of several
trafficking markers, including LAMP1, EEA1, RAB11, and CHC.

40
Figure 3.1: EGFR signaling can be activated via a ligand-free system using a
chimeric fusion of EGFR to a temperature sensitive ELP.

48
Figure 3.2: EGFR-GFP-ELP DNA was validated and used to generate stable
cell lines in HEK293T cells.

55
Figure 3.3: HEK293T cells transfected with EGFR-GFP-ELP mammalian
plasmid DNA were sorted by fluorescence to select positively expressing cells
over several cycles to generate stably expressing cells.

57
Figure 3.4: HEK293T cells stably expressing EGFR-GFP-A96 or EGFR-GFP-
V96 were heated and imaged by superresolution confocal microscopy to
characterize their transition properties.

58
Figure 3.5: HEK-EGFR-ELP cells were assayed at different timepoints by
immunoblotting to assess ERK1/2 and c-Fos phosphorylation.

60
Figure 3.6: RT qPCR was used to quantify effects of Tt on the EGFR pathway
using temperature-sensitive and -insensitive HEK-EGFR-ELP cells.

61
Figure 3.7: Ingenuity Pathway Analysis was used to compare the RT qPCR
analysis of EGFR-V96 signaling to existing gene expression datasets.
65

Figure 3.8: IPA analysis compared the RT qPCR data to compare to several
canonical pathways and how expression relates to disease and function in
biological systems and ranked using the -log(p-value) for relationships where
z-score > |2|.

68
Figure 4.1: X-5FA targeting to csGRP78 can deliver rapamycin to BT474 cells.

76
Figure 4.2: DNA quality control was verified to match by gel electrophoresis
and Sanger sequencing.

88
Figure 4.3: Expression of 5FA and X-5FA were verified along with phase
behavior.

90
xii

Figure 4.4: The shape and molecular weight of each expressed 5FA construct
was characterized by SEC-MALS, DLS, and MALDI-TOF to validate and
corroborate their MW and radii.

92
Figure 4.5: W-5FA and L-5FA undergo csGRP78 dependent cell association
by flow cytometry.

93
Figure 4.6. Rapamycin bound to W-5FA and L-5FA inhibit mTORC1 more
potently than untargeted drug.

95
Figure 4.7: GRP78 expression is attenuated after treatment with L-5FA-rapa in
a concentration dependent manner.
97
Figure 4.8: L-5FA significantly increases the cellular exposure compared to
untargeted 5FA by fluorescence microscopy.
100

xiii

List of abbreviations

AKT Protein kinase B
ANOVA Analysis of variance
AUC Area under the curve
CAV1 Caveolin-1
CDR Circular dorsal ruffles
CHC Clathrin heavy chain
CLC Clathrin light chain
csGRP78 Cell-surface glucose regulated protein 78
DLS Dynamic light scattering
DMEM Dulbelcco's Modified Eagle Medium
DNM Dynamin
dPBS Dulbecco's phosphate buffered saline
Dynasome-E, -L, or -S Dynasome-elongated, -large, or -small
EEA1 Early endosome antigen 1
EGF Epidermal growth factor
EGFR Epidermal growth factor receptor
ELK1 ETS like-1 protein
ELP Elastin-like polypeptide
5FA (FKBP-A24)4-FKBP
5FV (FKBP-V24)4-FKBP
A192 (VPGVG)192
A96 (VPGAG)192
EF (GFGVP)n
FAF FKBP-(VPGAG)192-FKBP
FSI FKBP-(VPGSG)48-(VPGIG)48
V60 (VPGVG)60
V96 (VPGVG)96
EPR Enhanced permeability and retention effect
ER Endoplasmic reticulum
ERK Extracellular signal-regulated kinase
FBS Fetal bovine serum
FKBP12 FK506-binding protein 12
Flot1/2 Flotillin 1/2
GFP Green fluorescent protein
GPCR G-protein coupled receptor
HSP Heat shock protein
ICAM-1 Intracellular adhesion molecule 1
IPA Ingenuity Pathway Analysis
ITC Inverse thermal cycling
xiv

JAK Janus kinase
LAMP1
Lysosomal associated membrane protein 1
MALDI-TOF Matrix assisted laser desorption/ionization time of flight
MAPK Mitogen-activated protein kinase
mTORC1 Mammalian target of rapamycin complex 1
MVB
multivesicular bodies
PI3K Phosphoinositide 3-kinase
PLCG1 Phospholipase C gamma 1
PM Plasma membrane
PRKC
Protein kinase C
PTEN Phosphatase and tensin homolog
Rab11 Ras-related protein 11
Rab7 Ras-related protein 7
rpS6
Ribosomal protein S6
RT qPCR Real time quantitative polymerase chain reaction
RP-HPLC
Reverse phase high performance liquid
chromatography
RTK Receptor tyrosine kinase
SEC-MALS
Size exclusion chromatography multi-angle light
scattering
STAT Signal transducer and activator of transcription
SubA Subtilase cytotoxin A
Tt
Transition temperature
VPS1 Vacuolar protein sorting protein 1
1

Abstract
Dynamin (DNM) is a family of large GTPases possessing a unique mechanical
ability to ‘pinch’ off vesicles entering cells. DNM2 is the most ubiquitously expressed of
the DNM family. I developed a novel tool based on elastin-like polypeptide (ELP)
technology to quickly, precisely, and reversibly modulate DNM2 structure. ELPs are
temperature-sensitive biopolymers that self-assemble into microdomains above sharp
transition temperatures (Tt). When linked together, DNM2 and a temperature-sensitive
ELP fusion organize into a range of distinct temperature-dependent structures above a
Tt, which were not observed with wild-type DNM2 or a temperature-insensitive ELP fusion
control. The structures comprised three different morphologies, which were prevalent at
different temperature ranges. The size of these structures was influenced by an inhibitor
of DNM2 GTPase activity, dynasore; furthermore, they appear to entrap co-expressed
cytosolic ELPs. The formation of these structures also coincide with inhibition of
fluorescently labelled epidermal growth factor (EGF) internalization. This work
demonstrates an unexpected diversity of morphologically distinct DNM2-ELP structures
fusions with a potential application in exploration of dynamin-dependent internalization.
Epidermal growth factor receptor (EGFR) is an important tyrosine kinase involved
in cancer biology. The study of EGFR signaling often relies on ligand activation to study
the downstream phosphorylation for the discovery of therapeutic targets. Ligand
activation of EGFR are subject to biased signaling pathways, and/or can result in
crosslinking with other ErbB partners. Using ligands, such as epidermal growth factor
(EGF), to study EGFR signaling limits the ability to decipher precise signaling pathways,
as they may result in biased signaling through differential RTK stabilization or formation
2

of hetero dimers. Prior development of a temperature-sensitive elastin-like polypeptide
(ELP) fusion to EGFR provided a useful tool to interrogate EGFR homo-cluster signaling;
however, a complete understanding of EGFR signaling of this model remains unknown.
Here, we expand the understanding of ELP-activated EGFR signaling using HEK293T
cells stably expressing EGFR-GFP-ELP that we achieved through recursive flow
cytometry. We demonstrate that GFP fusion is functional and sufficient to provide
selective pressure to identify stable transformants as well as image evidence of ELP-
dependent phase separation, clustering, or morphological changes by super resolution
microscopy, immunoblotting, and RT qPCR data processed by Ingenuity Pathway
Analysis. In addition to morphological changes to cell shape, these strategies revealed
signaling consistent with EGF ligand activation and cancer biology relevant to EGFR,
including activation of the ERK1/2, as well as significant upregulation FOS and JUN.
Rapalogues are powerful therapeutic modalities for breast cancer; however, they
suffer from low solubility and dose-limiting side effects. To overcome these challenges,
we developed a long-circulating drug carrier called 5FA, which contains rapamycin-
binding domains linked with elastin-like polypeptides. To target their potency towards
breast cancer, we here linked 5FA with four distinct peptides reported to engage the cell
surface form of the 78-kilodalton glucose regulated protein (csGRP78). To determine if
these peptides affected the carrier solubility, this library was characterized by light
scattering and mass spectrometry. To guide in vitro selection of the most potent functional
carrier for rapamycin, their uptake and inhibition of mTORC1 were monitored in a ductal
breast cancer model (BT474). Using flow cytometry to track cellular association, only the
targeted carriers enhanced cellular uptake and were susceptible to proteolysis by SubA,
3

which specifically targets csGRP78. The functional inhibition of mTOR was monitored by
Western blot for pS6K, whereby the best carrier L-5FA reduced mTOR activity by 3-fold
compared to 5FA or free rapamycin. L-5FA was further visualized using super-resolution
confocal laser scanning microscopy, which revealed that targeting increased exposure to
the carrier by ~8 fold. This study demonstrates how peptide ligands for GRP78, such as
the L peptide (RLLDTNRPLLPY), may be incorporated into protein-based drug carriers
to enhance potency.

4

Chapter 1: Introduction

This dissertation is broken down into three main components, each pertaining to a
project I undertook in the MacKay lab. Each chapter will discuss in detail the rationale,
methodology, and results of their respective development. Chapters 2 and 3 are
comprised of the work on the intracellular-switches projects, relating to developing a tool
to study dynamin-mediated endocytosis and EGFR signaling. Chapter 4 will detail the
work on a targeted drug delivery carrier of rapamycin to an emerging target in oncology.
These projects are connected by their reliance on elastin-like polypeptide (ELP)
technology. More specifically, they rely on the temperature-sensitive nature of ELPs to
study the inner workings of cells or their pharmacokinetic properties to improve
therapeutic efficacy as a drug carrier.
1.1 Applications of elastin-like polypeptide technology

ELPs are a temperature-sensitive protein at the heart of these projects. They are
comprised of a pentameric repeat of amino acids, VPGXGn, where the X-guest amino
acid residue can be replaced by other amino acids. Modification of these parameters
change ELP properties as well as determine their nomenclature. An ELP with an X-guest
amino residue of valine (V) that is repeated along with the pentamer 96-times, is called
V96. An alanine substitution repeated 96 times is called A96, and so on. What makes
ELPs compelling is the versatile nature. They can be genetically engineering to
manipulate ELP properties to accomplish different behaviors. By making the X-guest
amino acid residue more hydrophobic, ELPs can be designed to phase-transition within
physiological temperatures, while a less hydrophobic moiety would remain soluble.
Additionally, the length of the chain, n can be increased or decreased to decrease or
5

increase the transition-temperature (Tt), respectively. Additionally, proteins can be
genetically-encoded, which might confer a broad range of added functionality spanning
therapeutics to biologic tools. This important characteristic drives the design process for
the ELPs described in this dissertation, and how they were used to study endogenous
biological processes or encapsulate a drug in a potential new therapeutic against cancer.
1.2 Temperature-sensitive ELPs as intracellular switches

By fusing functional proteins of interest to heat-responsive ELPs, their temperature-
sensitive properties are conferred to the chimeric fusion. Under mild heating conditions,
these fusions self-assemble into microdomains inside mammalian cells and can perturb
the endogenous biology of their functional fusion inside cells (Fig. 1.1). This property was
Figure 1.1: Intracellular fusions of ELP to functional proteins confer temperature
sensitive properties in the chimeric fusion. On the left, green fluorescent protein
(GFP) is fused to a a small ELP (V60) below the transition temperature. Signal remains
fluorescent and diffuse inside the cell. On the right, puncta form as bright fluorescent
points above transition, which signals the visual change of microdomain formation
inside HEK293T cells.
6

demonstrated through several fusions, including fusions to clathrin-light chain (CLC)
1
,
caveolin (CAV1)
2
, or epidermal growth factor (EGFR)
3
. These fusions were independently
characterized and found to affect their respective biology in unique ways. For example,
phase-transition of temperature-sensitive ELP-CLC inhibited clathrin-mediated
endocytosis while CAV1-ELP potentiated it. EGFR-ELP clustering was able to activate a
signaling cascade without the need of a ligand.
These tools represent important additions to the scientists’ toolbelt. The current
chemical and biologic tools that exist can have direct impact on the desired biological
process of interest, but often suffer from inherent limitations. Biologic tools like gene
knockdown or dominant-negative lack temporal control and may result in unintended
upregulation of alternative pathways that may confound observations. Chemical tools
may be faster-acting, but often suffer from off-target effects. Chimeric fusions to ELPs
allow for a fast-acting temperature-activated switch can quickly induce a phase-transition
with the respective effector protein. This allows for a precise and quick activation or
deactivation of the desired biology that may lead to a better understanding of the
intricacies of the biological system they study.
The dynamin project was developed as a tool to study dynamin biology. It was initially
hypothesized to only inhibit endocytosis. Chapter 2 will discuss these results, which
demonstrated that their fusions formed interesting vesicular structures termed
‘dynasomes’ that coincided with inhibition of an internalization pathway dependent on its
biology. Chapter 3 will discuss the analysis of kinase signaling of a fusion to EGFR.
Previous characterization illustrated how it can be activated using a heat activated
mechanism; however, the breadth of its downstream biology remained largely unknown.
7

This chapter will discuss physical characterization and a bioinformatic analysis of several
genes associated with canonical EGFR signaling, as well as provide insights into cancer
signaling biology.
1.3 ELPs as drug carriers

ELPs have also been explored as drug delivery vehicles for cancer, ocular disease,
and other diseases. Therapeutically-relevant proteins have been fused to ELPs for tissue
targeting with enhanced pharmacokinetic performance (Fig. 1.2)
4
. Other formulations
have engineered functional domains with the ability to encapsulate free-drug that would
otherwise result in toxic side-effects or be inefficiently cleared before accumulation in
tumor tissue
4-9
. The increase in half-life of an ELP bound drug is aided by the increased
hydrodynamic radius that protect from glomerular filtration. This project takes advantage
of these behaviors through a drug-encapsulating formulation with enhanced targeting to
an emerging cancer phenotype. This project details the development of a small library of
peptides fused to an ELP carrier, termed 5FA, which is the most recent iteration of several
FK506 binding proteins fused to ELPs (FKBP-ELPs) as rapamycin loaded formulations.
Chapter 5 describes this work in greater detail, as well as its place along the generational
improvements over previous FKBP-ELP iterations. It describes the ligand selection
process through identification of enhanced targeting to cells presenting a marker for
cancer-induced ER stress, cell-surface glucose regulated protein-78 (csGR78). The data
provides rationale for further study in an in-vivo animal model and adoption to a depot-
forming 5FV formulation for further development.

8

Figure 1.2: ELP enhanced pharmacokinetics are driven by a larger
hydrodynamic radius, which protects it from glomerular filtration. 1)
Unconjugated/free-drugs are often systemically cleared before enough can
accumulate in target tissue to be therapeutically relevant. By fusion or encapsulation
to ELPs, they can be protected from solubility issues or fast clearance. Additionally,
they may be targeted through genetically encoded targeting moieties for enhanced
delivery to relevant tissues.
9

Chapter 2: Intracellular dynamin elastin-like polypeptides assemble dynasomes
associated with inhibition of epidermal growth factor internalization
2.1 Abstract

Dynamin (DNM) is a family of large GTPases possessing a unique mechanical
ability to ‘pinch’ off vesicles entering cells. DNM2 is the most ubiquitously expressed of
the DNM family. I developed a novel tool based on elastin-like polypeptide (ELP)
technology to quickly, precisely, and reversibly modulate DNM2 structure. ELPs are
temperature-sensitive biopolymers that self-assemble into microdomains above sharp
transition temperatures (Tt). When linked together, DNM2 and a temperature-sensitive
ELP fusion organize into a range of distinct temperature-dependent structures above a
Tt, which were not observed with wild-type DNM2 or a temperature-insensitive ELP fusion
control. The structures comprised three different morphologies, which were prevalent at
different temperature ranges. The size of these structures was influenced by an inhibitor
of DNM2 GTPase activity, dynasore; furthermore, they appear to entrap co-expressed
cytosolic ELPs. The formation of these structures also coincide with inhibition of
fluorescently labelled epidermal growth factor (EGF) internalization. This work
demonstrates an unexpected diversity of morphologically distinct DNM2-ELP structures
fusions with a potential application in exploration of dynamin-dependent internalization.
10

2.2 Introduction

Elastin-like polypeptides (ELPs) are a class of temperature-sensitive proteins
derived from tropoelastin. ELPs are biocompatible and can quickly and reversibly phase
separate above a tunable transition temperature (Tt) inside cells. They are composed of
an amino acid repeat sequence (VPGXG)n whereby the identity of X and n strongly
determine Tt. When fused to effector proteins, their temperature-sensitive properties are
conferred to the chimeric fusion. Previously, this approach has been used to generate
molecular switches for clathrin light chain (CLC)
1
, caveolin1 (CAV1)
2
, and epidermal
growth factor (EGFR)
3
. Genetically encoded ELP fusions were observed to reversibly
form microdomains above their respective Tt. The appearance of condensed spherical
morphologies was also shown modulate the biological function of their respective effector
protein
1-3
, which serves as a proof-of-concept platform technology for studying other
effector proteins, like Dynamin (DNM).
DNM proteins are a large 100 kDa GTPase canonically known to regulate vesicular
scission of endocytic vesicles from the inner cell-membrane
10
, and implicated in the
neurodegenerative disease Charcot Marie Tooth syndrome
11
. The DNM family of proteins
are comprised of DNM1, DNM2, and DNM3. While DNM1 and DNM3 are highly
expressed in neuronal and testes cells, DNM2 is ubiquitously expressed across all cell
types
12
. Its role is well-established within clathrin-mediated endocytosis; however, much
remains to be explored about its role in other pathways, such as caveolin- and flotillin-
mediated endocytosis
13, 14
, and in regulating f-actin structures
15-17
. A DNM2-ELP fusion
could modulate spatial organization of DNM2 by exploiting the ELP phase-transition.
Understanding the characteristics of its temperature-mediated structural reorganization
11

would serve as a useful tool to study the intricacies of DNM2’s heterogeneous
constituents implicated in its biology, as well as their implication in diseases.
The current set of molecular tools available to study DNM2 biology are potentially
limited by their mode of application. For example, overexpression of the dominant-
negative mutant (DNM2-K44A) and or use of siRNA knockdown to DNM2 require an
incubation period of 24-hrs. This time between treatment and effect may introduce
difficulty in discriminating between the direct effects on internalization pathways by DNM2
versus indirect secondary effects. For instance, primary effects on clathrin-mediated
endocytosis due to reduced DNM2 function can elicit compensatory upregulation of
pinocytosis
18
or unintendedly affect cell morphology
13, 19
. One solution to this challenge
was the use of a faster-acting small molecule inhibitor, dynasore. However, this suffers
from off-target binding to other GTPases and is attenuated by serum proteins and/or trace
detergents commonly used in assays
20, 21
. The DyngoTM series of DNM2 inhibitors are
analogues of dynasore introduced as alternative solutions; however, they also share
similar limitations that extend beyond inhibition of DNM
20
.
These challenges support the development of a novel tool that can modulate DNM
biology. Here, I have engineered a probe to modulate DNM assembly using ELP
technology. Above Tt, a temperature-sensitive fusion called DNM2-V96 can assemble a
range of unique vesicular structures I term ‘dynasomes’ and elicit important questions
about their biological/physiological relevance (Fig. 2.1). This manuscript characterizes
the properties of these ‘dynasomes,’ as well their ability to inhibit internalization of
epidermal growth factor (EGF), but not fluid phase endocytosis or flotillin1/2
internalization. Additionally, dynasomes were found to colocalize with a panel of proteins
12

involved in trafficking biology, indicating a possible broad range of effects to other
biological pathways.
13

Figure 2.1: Temperature-sensitive DNM2-V96 undergoes phase-transition above
Tt. The temperature sensitive properties of V96 drive the formation of vesicular
dynasomes inside HE293T cells, ranging from elongated, large spherical, or small
reticular morphologies.
14

2.3 Materials and methods

2.3.1 Construction of DNM2-ELPs

The DNM2 DNA sequence was obtained by the National Center for Biotechnology
Information (NCBI, Bethesda, MD) and was synthesized as a gBlock gene fragment
(Table S2.1) by Integrated DNA Technologies (IDT, Coralville, IA). The sequence
contained XbaI and NdeI restriction sites at terminal ends for digest and ligation into
pET25b(+) A96 or V96 vectors previously generated by recursive directional ligation
22
.
DNM2-ELP fragments were then cut with XbaI and EcoRI (#R0145S, #R3101S, New
England Biolabs, Ipswich, MA) and inserted into an empty pcDNA3.1(+) mammalian
vector downstream of HA and FLAG-tag sequences. DNA sequences of both DNM2-A96
and DNM2-V96 were verified by diagnostic restriction digest and Sanger sequencing
(Genewiz, South Plainfield, NJ).
2.3.2 Cell culture and transfection

HEK 293T cells (#CRL-11268, ATCC, Manassas, VA) were maintained in
Dulbecco’s Modified Eagle Medium (DMEM) (#11995065, ThermoFisher Scientific,
Waltham, MA) supplemented with 10% fetal bovine serum (FBS) (#35-010-CV, Corning,
Corning, NY) in a T-75 flask (#4616, Laguna Scientific, Laguna Niguel, CA) at 37°C in a
5% CO2 humidified Symphony 5.3A tissue culture incubator (#98000-366, VWR, Radnor,
PA). Cells were sub-cultured to 80-90% confluence and washed with Dulbecco’s
phosphate-buffered saline (dPBS) (#25-508, Genesee, San Diego, CA) before
dissociating with 0.05% trypsin (#25300-120, ThermoFisher Scientific, Waltham, MA).
Cells were resuspended in fresh media and subcultured in either 6- or 12-well plates for
transfection. Transfection used Lipofectamine 3000 (#L3000015, ThermoFisher
15

Scientific, Waltham, MA) following the manufacturer’s protocol with DNM2-ELP plasmid
DNA, then incubated in an Isotemp tissue culture incubator (#FICO3500TABB, GS
Laboratory Equipment, Asheville, NC) at 30°C for 72 hrs before assay.
2.3.3 Western blot analysis

HEK 293T cells subcultured in 6-well plates (#25-105, Genesee, San Diego, CA)
were grown to 70% confluency before transfection with either DNM2-V96 or DNM2-A96
plasmid DNA. After a 72 hr incubation, cells were lysed for immunoblotting following
methods previously described
3
. Antibodies directed against ELPs (AK1)
23
were diluted
1:1000 in 5% bovine serum albumin (BSA) (#A9647-50G, Sigma-Aldrich, St. Louis, MO),
then tagged with 1:5000 dilution of α-mouse HRP-linked antibodies (#7076S, Cell
Signaling Technologies, Danvers, MA). The PVDF membrane was visualized on an
iBright FL1000 imaging system (ThermoFisher Scientific, Waltham, MA).
2.3.4 Fixed cell preparation

HEK 293T cells were subcultured to 12-well plates with cover slips coated in poly-
D-lysine. After transfection with DNM2-V96 or DNM2-A96, cells were fixed at different
temperatures and labelled for indirect immunofluorescence
2
. Briefly, 72-hrs post-
transfection, cells were placed at 4°C for 1-hr to solubilize the ELPs. Cells were then
incubated in DMEM containing 10% FBS at the indicated temperature using a heat block
(#IC25, Torrey Pines Scientific, Carlsbad, CA). Temperature was monitored a thermal
probe (#CP254765, Cole Parmer: Digi-Sense, Vernon Hills, IL) for 1 hr and quickly fixed
with 4% paraformaldehyde (#43368-9M, Alfa Caesar, Haverhill, MA) for 15 mins.
Coverslips were then incubated in 50 mM ammonium chloride for 5 mins, washed 3 times
with dPBS, and permeabilized with 0.1% Triton X-100 (#9002-93-1, Sigma-Aldrich, St.
16

Louis, MO) for 15 mins. Cells were washed another 3 times with dPBS for 3 mins, then
blocked with 1% BSA for 1 hr at room temperature (RT). Cells were incubated with 1:100
AK1 anti-ELP antibody
23
in 1% BSA at 4°C overnight, and washed 3 times with dPBS for
5 mins before incubation with 1:100 goat α-mouse AlexaFluor 488 (#A-11001,
ThermoFisher Scientific, Waltham, MA) in 1% BSA at RT for 1-hr. The coverslips were
incubated with DAPI (#D1306, ThermoFisher Scientific, Waltham, MA) with a final
concentration of 5 µg/ml for 5 mins and washed with dPBS 5 times for 5 mins each.
Coverslips were mounted with ProLong Gold Antifade (#P36934, ThermoFisher
Scientific, Waltham, MA) mounting media on glass slides and cured overnight at RT.
2.3.5 Imaging and structural analysis

HEK 293T cells expressing either DNM2-A96 or DNM2-V96 cells were fixed and
labeled by indirect immunofluorescence as described above. For 2-dimensional analysis,
at least three images were acquired at each temperature (4, 20, 30, 35, and 40°C) with a
LSM880 confocal microscope (ZEISS Microscopy, Jena, Germany). Images were
acquired in LSM Fast Mode with a 488 nm multiline argon laser and processed for
Airyscan super-resolution quality. Individual cells were scored according to the
appearance of one of 5 distinct morphologies at each temperature: ‘diffuse’, ‘puncta’,
‘Dynasome-Elongated (E)’, ‘Dynasome-Large (L)’, or ‘Dynasome-Small (S)’. ‘Diffuse’
morphology is defined by a lack of distinct boundaries of the expressed DNM2-ELP
fluorescence with distribution along the plasma membrane (PM) or within the cytosol and
can appear cloudy or amorphous. ‘Puncta’ morphology is defined as small bright points
with distinct boundaries and no visible lumen. ’Dynasome-E’ morphology is defined as
thin rod-like structures with a lumen lined by DNM2-ELP. ‘Dynasome-L’ is defined by large
17

round structures, appearing as large vacuole-like vesicles lined with DNM2-ELP.
‘Dynasome-S’ morphology is defined as round compartmental structures like ‘Dynasome-
L’ that appear as smaller bundles with interconnected lumens.
The five possible states observed in either DNM2-A96 or DNM2-V96 groups were
ranked from lower to higher rank according to the proportion at which they appear at each
temperature. If a particular morphology appears at a higher temperature, it is ranked
above one that appears more at a lower temperature. For example, the Dynasome-S
morphology appears at a higher proportion at higher temperatures than the Dynasome-L
morphology. As such, if a cell contains both the Dynasome-L and Dynasome-S
morphologies, it would be characterized as Dynasome-S based on the hierarchy.
Proportions and other statistical parameters were calculated and plotted in GraphPad
Prism (La Jolla, CA, http://www.graphpad.com). Dynasome-L and Dynasome-S
morphology diameters were quantified with the straight-line tool in FIJI
24
. Their diameters
were then collected in GraphPad and plotted as a mean with standard deviation per
temperature. ANOVA with Tukey multiple comparisons test was done on each
temperature data set.
Fixed cells were visualized with 3-dimensional imaging. Cells were prepared as
previously described, but at 4 and 37°C. Z-stacks were acquired with a LSM880 confocal
microscope (ZEISS Microscopy, Jena, Germany) in LSM Fast Mode with Airyscan super-
resolution using a 488 nm argon multiline laser. Cells were selected in 2-dimensions and
their z-range was determined using DAPI signal. Optimal interval between slices were set
to satisfy Nyquist over-sampling criteria. Orthogonal projections and 3-dimensional voxel
18

reconstruction were also performed with Zen Black 2.3 (ZEISS Microscopy, Jena,
Germany).
2.3.6 Dynasore inhibitor assay and analysis

Cells were transfected with DNM2-V96 as described above and then serum
starved in DMEM for 24-hrs before being treated with either 0 µM or 80 µM Dynasore
(#D7693-5MG, Sigma-Aldrich, St. Louis, MO) at 37°C for 30 mins. Cells were then fixed
and stained as described above for imaging using Airyscan on the LSM880. The diameter
of DNM2-V96 structures were measured in cells treated with 0 µM or 80 µM dynasore
semi-automatically using FIJI. Images were converted to binary projections for automatic
analysis of all structures via the particle analysis function. Data was collected and
analyzed on Graphpad Prism version 7.0.
2.3.7 Live-cell imaging and analysis

HEK 293T cells were seeded onto 35-mm glass bottomed dishes (P35G-0-10-C,
MatTek Corporation, Ashland, MD) pre-coated with poly-D-lysine (P0899-10MG, Sigma,
St. Louis, MO) at 10 mg/ml. Cells were transfected with either DNM2-pmCherryN1
(Addgene plasmid #27689; http://n2t.net/addgene:27689; RRID: Addgene_27689)
25
,
GFP-V60, or GFP-V60 and DNM2-V96 as previously described
2, 3
. After a 72-hr
expression period, cells were incubated on ice for 30 mins. Plates were mounted in a
heating insert PS1 (Zeiss Microscopy, Jena, Germany) and heated using a refrigerated
circulator (#AP07R-40, PolyScience, Niles, Illinois). Temperature was maintained with an
Incubator XLmulti S1 DARK LS (Zeiss Microscopy, Jena, Germany) and monitored using
the unit’s internal probe. Media was replaced with ice cold imaging solution (#A14291DJ,
Life Technologies, Carlsbad, CA) after ice cold dPBS wash. Cells were heated from a
19

starting temperature range between 10 to 15°C and up to a maximum of 45°C within 20
mins. Superresolution images were acquired at least once per min on a LSM880 confocal
microscope and focused with Zeiss Definite Focus 2. Temperatures were recorded
manually and compared to the sudden appearance of bright structures. Individually
observed Tt’s were analyzed in GraphPad using Student’s unpaired t-test between both
conditions.

Figure 2.2: Forward and reverse primers were used to validate DNM2-ELP
sequences to confirm successful insertion into a PCDNA3.1 mammalian vector.
A) A DNM2 gBlock gene fragment was ligated into pET25b (+) ELP E.coli plasmids
using sticky ends generated by XbaI and NdeI digests. DNM2-ELP fragments were
then generated with subsequent XbaI and EcoRI digests and ligated into a PCDNA3.1
mammalian vector. B) Sanger sequencing with CMV-F, T7, and BGH-R forward and
reverse primers were used to verify successful insertion of DNM2-A96 and C) DNM2-
V96.

20

2.4 Results and discussion

The membrane trafficking community has developed several useful tools to study
DNM2, but they are limited by their speed and specificity. Here, I present a potential new
peptide-based approach based on a DNM2 fusion to an ELP.
2.4.1 Generation of thermo-responsive DNM2-ELPs from a PCDNA3.1 plasmid
capable of transfecting mammalian cells.

The first step in the development of this tool was to clone human DNM2 into an
ELP backbone and insert it into a mammalian expression vector, PCDNA3.1 (Table 2.1).
Forward and reverse Sanger sequencing at the N- and C-termini were used to validate
sequences for expression (Fig. 2.2AB). Diagnostic digests with EcoRI and XbaI flanking
the DNM2-ELP sequence were used to confirm the approximate band size of the cloned
construct (Fig. 2.3A).
Table 2.1 Summary of ELP fusion proteins evaluated in this work.
Nomenclature Amino acid sequence
1
Intracellular Tt (°C)
2
Molecular Weight (kDa)
3

DNM2-V96 FLAG-HA-DNM2-
G(VPGVG)96Y
23.13 140.5
DNM2-A96 FLAG-HA-DNM2-
G(VPGAG)96Y
NA 137.8
GFP-V60 GFP-G(VPGVG)60Y 37.59 52.3
1
DNM2 and GFP sequences are available in supplementary table S2.
2
Observed mean transition temperature by live cell imaging.
3
Estimated molecular weight based on the amino acid sequence open reading frame using
Snapgene Software 5.3.2.

2.4.2 Expression of DNM2-ELPs in HEK 293T cells is confirmed by Western blot
and immunofluorescence.

After successful cloning of DNM2-ELPs into a mammalian plasmid, DNM2-ELP
expression was verified in HEK 293T cells by Western blot and superresolution confocal
microscopy using an anti-ELP antibody (AK1) (Fig. 2.3). The expected molecular weight
of DNM2-A96 and DNM2-V96 are 137.8 kDa and 140.5 kDa, but they were measured
21

within a reasonable difference at 150 kDa. The SDS gel was loaded with equivalent lysate
protein, but sensitivity differences of AK1 to different ELPs has been reported (Fig. 2.3B).
To visually confirm expression of DNM2-V96, cells were fixed at 18 and 37°C and imaged
using super-resolution confocal microscopy. DNM2-V96 was expected to form
amorphous microdomains above Tt
1-3
, but instead they formed highly organized vesicular
structures (Fig. 2.4A). A heterogenous collection of vesicular structures lined with DNM2-
ELP signal were observed at higher temperatures, thus defined as ‘transitioned’.
To confirm intact expression of the DNM2-ELP sequence, the HA tag at the N-
terminus and ELP-chain at the C-terminus were identified by antibody and subsequent
indirect immunofluorescence. Signal overlap from the HA-tag and ELP-chain at each
temperature was quantified by quantifying colocalization MCC
26
(Fig. 2.4B). The overlap

Figure 2.3: DNM2-ELP plasmid DNA and its expressed construct were confirmed
in HEK293T cells. A) PCDNA3.1 plasmid construction was confirmed by single and
double restriction enzyme digestion with either EcoRI or EcoRI and XbaI. The double
digest produced two fragments, one of which contained its 4,083 bp open reading
frame for DNM2-A96 and DNM2-V96. B) Protein expression from each plasmid was
confirmed using Western blot against cell lysates in HEK293T cells using an α-ELP
primary antibody. Both fusions ran near their expected molecular weight (Table 2.1)
near the 150 kDa protein marker.

22

in signal between the HA tag and the ELP chain were nearly identical at both tested
temperatures. The mean Mander’s Correlation Coefficient (MCC was calculated at 0.94
(± 0.04) at 18°C and 0.94 (± 0.05) at 37°C, confirming successful full expression in cells.
A Student’s t-test was used to show no changes to the MCC between temperatures (p >
0.9999), indicating no effects on fusion integrity above Tt. While the relative level of
expression after transient transfection was higher for DNM2-A96, both the temperature
sensitive DNM2-V96 and insensitive control were identified in cellular lysates at the
expected MW (Fig. 2.3B).

Figure 2.4: HA-DNM2-ELP expression is confirmed using α-HA and α-ELP
antibodies with indirect immunofluorescent microscopy. A) HEK293T cells
expressing DNM2-V96 (yellow arrow) are shown to form temperature-dependent
assembly of large intracellular vesicles at 37°C, but not at 18°C. At 18°C, fluorescent
signal appears as small points distributed along the PM. Signals are highly overlapped
at either temperature. B) Overlap between α-ELP (green) and α-HA (red) fluorescent
signals were quantified by colocalization in FIJI, confirming a high MCC for DNM2-V96
at 18°C and 37°C (MCC = 0.93 and 0.93). Each point represents a single cell.
23

2.4.3 DNM2-ELPs form distinct structures as a function of temperature.
Figure 2.5: Temperature-sensitive DNM2-V96 forms distinct vesicular structures
at different temperatures while temperature-insensitive DNM2-A96 does not.
HEK293T cells were transfected with either DNM2-A96 or DNM2-V96, fixed at 4, 20,
30, 35, or 40°C, and stained for indirect immunofluorescence. A) After Airyscan
superresolution imaging, five distinct morphologies were observed between
temperature-sensitive and -insensitive DNM2-ELPs. Diffuse and puncta morphologies
are indistinguishable between DNM2-A96 and DNM2-V96, whereas Dynasome-E,
Dynasome-L, and Dynasome-S morphologies only appear with DNM2-V96 at 20°C
and above. B) DNM2-A96 does not appear to transition at any temperature between
4 to 40°C, while C) DNM2-V96 appears to transition at about 20°C. D) The morphology
of DNM2-ELP can be characterized as one of five possibilities between 4 to 40°C, but
only puncta and diffuse morphologies appear in cells expressing DNM2-A96 at any
temperature – no instance of Dynasome-E, Dynasome-L, or Dynasome-S
morphologies. E) In cells expressing DNM2-V96, the diffuse and puncta morphologies
appear at or below 20°C. The Dynasome-E morphology only appears at 20°C. The
Dynasome-L morphology begins to appear at 20°C and peaks at 30°C before falling
off at higher temperatures. The Dynasome-S morphology begins to appear at 35°C
and dominates by 40°C.
24

Next, DNM2-ELP (A96 and V96) expression was quantified at different
temperatures (Fig. 2.5). From the structures observed in the trial experiment,
morphologies were hypothesized to appear at different proportions in a temperature
dependent manner. Additionally, it was unknown if additional structures would be
observed between 18°C and 37°C, so cells were transfected and fixed at a broad range
of temperatures (4, 20, 30, 35 or 40°C) to capture distinct morphologies. ‘Non-
transitioned’ cells reflecting temperature-independent assemblies were defined based on
the observed morphologies of DNM2-A96 at 4°C and used as a baseline. DNM2-A96
transfected cells revealed either bright ‘puncta’ or ‘diffuse’ staining at all observed
temperatures. The combination of puncta and diffuse morphologies constituted 100% of
all observations (Fig. 2.5B). On the other hand, cells expressing DNM2-V96
demonstrated evolving temperature-dependent morphologies that were classified into
three differentiated structures above 20°C.
The emergence of long rod-like vesicles lined with DNM2-V96 at 20°C were noted
and categorized as the elongated dynasome morphology, (Dynasome-Elongated (E)).
Dynasome-E structures appeared at a proportion of 17.7 ± 4.9% of transfected cells only
at 20°C. At this same temperature, large round vesicular morphologies (Dynasome-
Large (L)) were observed in 15 ± 2.7% of cells. The remaining cell morphologies (67.3%)
were non-transitioned diffuse or puncta morphologies. At 30°C, non-transitioned
morphologies constituted a mean total of 3 ± 5.2% of DNM2-V96 transfected cells while
Dynasome-L morphologies dominated observations by appearing in 90 ± 10.5% of cells
at 30°C. The Dynasome-Small (S) structures with smaller, overlapping, and
interconnected lumens constituted the remaining proportion of structures (7 ± 12.1%). By
25

35°C, the Dynasome-S morphology grew in proportion to a total of 68 ± 4.6% while the
Dynasome-L morphology decreased to 32 ± 4.6% of cells. This trend continues to 40°C
with the dominance of the Dynasome-S morphology, accounting for a proportion of 81.7
± 6.5% of cells while the Dynasome-L morphology accounts for a proportion of 18.7 ± 6%.
In summary, DNM2-V96 begins to assemble intracellular structures above 20°C, which is
Figure 2.6: Live cells expressing wtDNM2-pmCherry were imaged by confocal
microscopy to observe the effects of DNM2 overexpression during heating.
Transfected HEK293T cells were heated from 15
o
C to 44
o
C. Images were taken at
different intervals. The initial state of wtDNM2-pmCherry is not structurally distinct from
the final state at higher temperatures. The formation of ‘dynasome’ morphologies were
not observed. Signal appears diffuse throughout, confirming that dynasomes are not
formed by overexpression of DNM2. Rather, dynasomes are dependent on ELP Tt.
26

nearly complete by 30°C (Fig. 2.5E). No temperature dependent change in DNM2-A96
morphology was observed at any temperature.
The formation of dynasomes appears to be dependent on ELPs since they only
appeared in cells expressing DNM2-V96 and not DNM2-A96. To confirm whether
formation of dynasomes was dependent on ELPs, wtDNM2-pmCherry was
overexpressed and heated as images were taken. To date, we are unaware of any reports
indicating this would result in the formation of structures similar to dynasomes. If
temperature and overexpression of DNM2 drive dynasome formation, we would observe
them form in live cells. Instead, none were observed at any temperature (Fig. 2.6),
providing stronger evidence that dynasomes are driven by ELPs.
2.4.4 Orthogonal and mesh reconstruction of dynasomes show distinct lumen
contraction in Dynasome-S morphologies

Orthogonal projections and mesh reconstructions were used to better visualize 3-
dimensional cellular structures formed by DNM2-A96 and DNM2-V96. Representative
images were chosen to display expression and key transition characteristics of DNM2-
ELPs. Orthogonal projection of DNM2-A96 at 37°C and DNM2-V96 at 4°C show diffuse
or puncta spatial distribution. On the xy-axis, DNM2-ELP distribute along the plasma
membrane or in the cytoplasm - corroborated on the xz- and xy- axis. (Fig. 2.7A and 7B).
At 37°C, DNM2-V96 generally forms two distinct morphologies, the Dynasome-L and -S
morphologies. The xy-, xz-, and yz-axis show the large lumen of a Dynasome-L structure
above the nucleus and the Dynasome-S morphology below. The scale of their difference
is displayed in the 3-dimensional mesh model, which also exhibits interconnected lumens.
Differentiating between structures was achieved by differentiating the more spatially
27

imposing Dynasome-L from the smaller Dynasome-S, which are clearly shown in both an
orthogonal projection and a 3D mesh reconstruction (Fig. 2.7C).

Figure 2.7: 3-dimensional orthogonal projections of DNM2-ELP show their
respective signal distribution on the -xyz axis using α-ELP secondary
immunofluorescence. A) An orthogonal projection (left) of DNM2-A96 at 37°C shows
non-transitioned (diffuse and puncta) morphologies within the same cell. Signal is
distributed along the plasma membrane and within the cytosol. A mesh reconstruction
corroborates this interpretation (right). B) The orthogonal projection (left) of DNM2-V96
at 4°C shows non-transitioned morphology like DNM2-A96, which was corroborated
with a mesh reconstruction (right). C) In contrast, the orthogonal projection (left) of
DNM2-V96 incubated at 37°C shows both Dynasome-L and –S morphologies. The
round morphology of Dynasome-L contrasts significantly with the smaller,
interconnected Dynasome-S morphology. The -yx and –xz slice windows show the
formation of a large spherical structure lined with DNM2-V96 and an empty lumen. The
mesh reconstruction (left) conveys the interconnected lumens of the Dynasome-S.
28

2.4.5 Dynasome size depends on dynasore and temperature

Having characterized the temperature-dependent assembly of three distinct
dynasome morphologies, we next assessed if their properties depend on GTPase activity
by treatment with dynasore (Fig. 2.8). Compared to an untreated cell (Fig. 2.8A), there
was a dramatic reduction in the assembly of dynasomes in cells treated with 80 µM
dynasore (Fig. 2.8B). Reduction in apparent size appears to be an effect by dynasore
inhibition of DNM2. Manually quantifying this effect as in Fig. 3 required magnification of
individual cells, which is impractical with a large dataset. To overcome this limitation,
dynasome diameters were instead measured automatically from binary projections of
structures. The average dynasome diameter in untreated cells at 37°C was 0.41 µm
±0.33, which is comparable to the average diameter quantified in untreated cells at 40°C
at 0.40 ± 0.27 µm (Fig. 2.8C). After dynasore treatment, the average diameter of
structures shrank to at 0.33 µm ±0.24 (Fig. 2.8D), suggesting that dynasome self-
assembly depends on the activity of DNM2. This study demonstrates that dynasore
clearly influences the self-assembly of dynasomes and implicates the GTPase function
of DNM2 in the formation of dynasome structures.
While most cells displayed just a single dynasome phenotype, some cellular
characteristics were difficult to distinguish from each other. For example, Dynasome-S
cells have clusters of small vesicular structures, while Dynasome-L cells are defined by
large singular vesicular structures. Given these defining characteristics, the diameters
detected by image analysis reflect contributions from both Dynasome-S and Dynasome-
L. As shown above, a qualitative rubric was used to categorically distinguish these
morphologies (Fig. 2.5); however, that approach relies on arbitrary visual judgements. To
29

complement that analysis and quality control this assessment of dynasore, we manually
Figure 2.8: The diameter of DNM2-V96 structures decreases with temperature
and inhibition of Dynamin GTPase activity. HEK393T cells were transiently
transfected and incubated with or without dynasore or at different temperatures.
Dynasomes were stained using secondary immunofluorescence (white) and imaged
using confocal microscopy. The diameters for a large dataset of these structures were
estimated using image analysis. Nuclei were stained with DAPI (Blue). A) At 37°C
Dynasome-S morphologies are predominant. B) After incubation with 80 µM dynasore,
the size of vesicular structures collapses. C) As temperature increases, the mean
diameter of dynasome morphologies decreased significantly (****p<0.0001, ANOVA,
Tukey post hoc). D) Having validated that this image analysis reflects the trend
observed with temperature, this approach was used to compare the diameter of
structures with and without dynasore. Dynasore treatment significantly decreased the
diameter (p < 0.0001, two-tailed unpaired t-test).
30

measured the diameters of each structure as a function of temperature (Fig. 2.8C). The
diameter of dynasomes decreased sharply from 20 to 30°C, and then again from 30 to
35°C, but not between 35 and 40°C. This trend mirrors the observations and analysis
described by their categorical variables where Dynasome-L species shifted to Dynasome-
S as temperature increases (Fig. 2.5E).
2.4.6 Dynasomes appear morphologically independent from F-actin structures

While our experiments show that dynasome assembly is both temperature-
sensitive and capable of forming at least three distinct intra-cellular morphologies, it is
unclear how their assembly affects the overall cytoskeleton. For example, Dynasome-S
morphologies share some similarities to circular dorsal ruffles (CDR). CDRs are unique
plasma-membrane structures, which have been observed using F-actin tracking to form
and close within 30-mins of stimulation
15
. CDR size and shape are qualitatively similar to
dynasomes formed by DNM2-V96. CDR transient structures are defined by and
dependent on F-actin and have previously been found colocalized with the actin ring
15
.
The relationship between DNM2-ELPs and CDRs is unclear. To screen for overlapping
effects on cellular biology, While DNM and F-actin are involved in common cell biology
17
,
the relationship between cells expressing DNM2-V96 were co-labelled with fluorescent
phalloidin as well as antibody against ELP. If dynasome self-assembly relies on an F-
actin template, F-actin might be expected to form rings similar to CDRs above Tt. This
was not observed. Below Tt (4°C), DNM2-V96 overlaps with cytosolic F-actin near the
31

periphery of the cell (Fig. 2.9A). Above Tt (37°C), DNM2-V96 formed dynasomes in the
cytoplasm, while F-actin remained concentrated at the plasma membrane. Accordingly,
the colocalization between F-actin and DNM2-V96 significantly decreased with dynasome
assembly; furthermore, there was no obvious effect of dynasomes upon the morphology
of F-actin. Both the decrease in colocalization and the absence of F-actin assembly
peripheral to dynasomes suggests that dynasomes rely on an independent self-assembly

Figure 2.9: The formation of dynasome morphologies do not appear to be driven
by cytoskeletal dynamics. HEK293T cells were transiently transfected with DNM2-
V96 and stained by secondary immunofluorescence for actin (red), ELP (green), or
nuclei(blue) upon incubation above Tt (40°C) or below Tt (4°C). A) Below Tt, cells
expressing DNM2-V96 show overlap in ELP and F-actin near the periphery of the
cytosol. Diffuse and puncta morphology distributed in the cytoplasm did not overlap as
highly with F-actin. B) Above Tt, F-actin remained at the plasma membrane while non-
overlapping dynasome structures formed in the cytoplasm. C) Comparing the whole-
cell colocalization (MCC) of both channels to quantify overlap indicates that their
localization decreases significantly upon dynasome assembly (*p =0.02). This reflects
the cytoplasmic localization of assembled dynasomes, which is clearly distinct from
the strong plasma-membrane association observed for F-actin structures. Dynasome
assembly does not appear to significantly change the F-actin structural morphology.
32

process (Fig. 2.9B). Visually, dynasomes and F-actin are spatially averse above Tt, which
is consistent with a decrease in colocalization indicated by the MCC (Fig. 2.9C).
2.4.7 Dynasome formation is visualized in live-cells with a GFP-based surrogate
reporter

While fixed cells facilitate exquisite characterization of cells at specific
temperatures, we cannot exploit the rapid thermo-responsiveness of ELPs to characterize
their behavior. ELPs are visually sensitive to changes in temperature as small as 1°C, so
live cell imaging would allow for dynamic visualization of transitional structures missed in
fixed-cells incubated at selected temperatures. Our group has developed methodology
for indirectly visualizing ELP assembly using a co-expressed fluorescent reporter. Co-
expressing DNM2-V96 with a surrogate reporter, GFP-V60 enables visualization of
DNM2-V96 microdomains in live-cells
2, 3
. GFP-V60 was expressed in HEK 293T cells and
cooled before heating at a steady rate to obtain images at consistent intervals (Fig. 2.10).
By itself, GFP-V60 assembled microdomains above a mean temperature of 37.6 ± 4.0°C
(n = 18) (Fig. 2.10A). When co-expressed with DNM2-V96, the assembly temperature of
GFP-V60 significantly (p<0.0001, Student T-test) decreased to a mean Tt of 21.8 ± 4.2°C
(n = 22) (Fig. 2.10B). Co-expressed DNM-V96 resulted a lower observed transition
compared to the shorter-chained GFP-V60, which is consistent with ELP dependence on
chain length (Fig. 2.10C). Unexpectedly, the vesicular morphologies observed by fixed-
cell studies were not observed.
While the general globular shapes observed in live-cells resembles those in fixed-
cell studies, it was unclear if the core of globular structures contained a mixture of miscible
DNM2-V96 and GFP-V60. Other ELP temperature-sensitive fusions; CAV1-ELP and
33

EGFR-ELP were similarly characterized and were observed to form miscible

Figure 2.10: Live cells expressing either GFP-V60 (single) or GFP-V60 and DNM2-
V96 (dual) were imaged by confocal microscopy to quantify the Tt of DNM2-V96.
A) Two individual HEK293T cells transfected with GFP-V60 were heated from 13.3 to
44.3°C over 20 minutes to show Tt’s of 37.2 and 43.5°C. B) Cells transfected with GFP-
V60 and DNM2-V96 were heated from 15.9°C to 44.1°C (showing 36.4°C max) to show
a Tt of 19.3°C. C) Multiple cells were evaluated three independent temperature ramps,
and the transition temperature in each was evaluated. The mean Tt between single
(n=18) and dual transfected (n=22) cells show a statistically significant difference (****p
< 0.0001). Single transfected cells transitioned at a mean of 37.9°C (± 4.0 n = 18) with
a 95% CI between 35.64 to 39.5°C, while dual transfected cells transitioned at a mean
of 21.8°C (±4.2, n = 22) with a 95% CI between 21.3 to 25.0°C. This is consistent with
the assembly of transitioned cells in Fig. 2.5C. D) Fixed cell imaging was used to
confirm the association of DNM2-V96 and GFP-V96 following incubation at 37°C.
Orthogonal projections were visualized by indirect immunofluorescent microscopy by
α-HA (red) and α-GFP antibodies (green) illuminate the formation of distinct GFP-V60
microdomains encapsulated within DNM2-V96 Dynasome-S structures.

34

microdomains with GFP-V60. For example, CAV1-V96 formed very large amorphous
structures localized at the plasma membrane, which were highly colocalized with GFP-
V60. The morphology of the surrogate reporter in live-cell characterization was similar to
the morphology observed in fixed-cells imaged by 3-dimensional super resolution
confocal microscopy
2
. Co-expression of EGFR-V96 and GFP-V60 or single expression of
EGFR-GFP-V96 formed smaller round microdomains that are indistinguishable from each
other in fixed and live-cells
3
. Given that context, the result of co-expression between
DNM2-V96 and GFP-V60 was especially surprising.
The difference in Tt between singly and co-expressed DNM2-V96 suggests that
DNM2-V96 affects the spatial organization of GFP-V60. Based on previous observations,
dynasome structures were expected to be directly stained by GFP-V60 co-expression,
but they instead appeared as two immiscible fractions. DNM2-V96 still forms vesicular
structures above Tt, but they do not appear to be miscible with GFP-V60. Instead, GFP-
V60 is encapsulated within the lumina of the formed structures (Fig. 2.7D). In a different
study, miscibility in mixed ELP populations were recently characterized
27
. The Tt of ELP
mixtures in a water-in-oil emulsion revealed staggered phase-separation into immiscible
ELP microdomains. ELPs with different characteristics were programmed to transition
from miscible or immiscible mixtures with distinctly observed Tt’s corresponding to
separate ELPs in the mixture. Our live-cell co-expression experiments are more nuanced
because the reorganization of DNM2-V96 appears to entrap GFP-V60 without inducing
colocalization. The behavior of this mixture appears to be influenced by dynasome
formation because V96 fusions to other effector proteins like CAV1 or EGFR form a single
structure where they colocalize with GFP-V60. This suggests that dynasome-based
35

assembly with other ELP species is more complex than ELP-ELP coacervation. Rather,
dynasomes and/or DNM2 biology aids in the selective entrapment of GFP-V60 through
some interaction beyond the scope of this report.
2.4.8 Dynasome radius of curvature may depend on a balance between protein
folding of DNM2 and ELP domains.

ELP fusions to intracellular CLC, CAV1, EGFR, and GFP self-assemble into
condensed microdomains above Tt, and colocalize with GFP-V60 in live cells. In contrast,
the striking formation of three distinct dynasome structures does not match the
morphology observed for these other fusions. Instead, DNM2-V96 forms lamellar
structures similar to those observed with diblock polypeptide fusions
28
. For example, an
amphiphilic diblock ELP comprised of a glutamic acid region (GEGVP)n and a
phenylalanine rich region (GFGVP)n fused together (EF) promote spontaneous formation
of a bilayer with a hydrophobic core and a hydrophilic exterior
29
, analogous to amphiphilic
DNM2-V96, driving dynasome self-assembly (Fig. 2.1).
To our knowledge, DNM2-V96 is the first polymer fusion to direct self-assembly of
DNM2-mediated vesicular structures inside mammalian cells. While the ELP diblock
fusions offer insight into self-assembly, the evolution of Dynasome-L to Dynasome-S is
mysterious. The scission mechanism of DNM may offer insight into this nuanced
behavior. Vacuolar protein sorting protein 1 (VPS1) is a DNM-like protein expressed in
yeast that shares N-terminus GTPase and C-terminus GTPase effector domain homology
with DNM. It is a key regulator of fusion and fission events
30
. For example, a ΔVPS1
mutation results in a vacuolar fission defect that leads to an accumulation of multivesicular
bodies (MVBs) similar in appearance to the Dynasome-L morphology. wt-VPS1
expression rescued the fission defect, suggesting that GTPase activity contracts vesicle
36

size
31
. Thus, it would follow that dynasome curvature and diameter is regulated by the
GTPase biology of DNM2; however, dynasomes are smaller after treatment with
dynasore (Fig. 2.8), which contradicts a model suggesting a decrease in dynasome
curvature is driven by GTPase contraction. Nevertheless, it is possible that a relaxed
DNM2-V96 state may promote dynasome curvature and a smaller diameter.
The role that DNM2 plays in dynasome evolution might be explained by ELP phase
transition. At the Tt, ELPs self-assemble after a conformational change in its backbone
that favors hydrophobic intramolecular interactions between residue hydrogens and the
backbone
32
. ELPs assemble an amorphous, optically-clear liquid phase; however, with
additional heating many ELPs adopt a rigid, crystalline phase. This is commonly observed
during purification of ELPs and their fusion proteins. As such, it is plausible that the

Figure 2.11: Dynasome contraction potentially occurs as a result of a tighter
radius of curvature. A) A balance between temperature-dependent ELP self-
assembly and DNM2 biochemistry drives the formation of dynasome structures.
Dynasome-L self-assembles a lamellar phase that encloses a larger diameter, B) but
as temperature increases, the average radius of curvature for DNM2-V96 decreases
until the Dynasome-S morphology is dominant.

37

conversion from Dynasome-L to Dynasome-S is temperature-dependent and reflects an
additional phase change within the ELP-rich lamellar phase. If this were the case for
DNM2-V96, then ELP lamellae below 35°C would be less rigid than above. An increased
crystallinity of the ELP-phase reduces the radius of curvature, which collapses
Dynasome-L into smaller Dynasome-S vesicles. Therefore, it is reasonable that changes
in dynasome curvature might be due to a balancing act between DNM2 and V96 (Fig.
2.11).
Functionalized intracellular ELP fusions have previously been reported to form
coacervates above their respective Tt. In contrast, heated DNM2-V96 forms organized
vesicular dynasomes with a much more significant hollow interior. Nonetheless, this
reorganization shows that ELP dynamin fusions do self-sequester, similar to V96-CLC
microdomains. The V96-CLC clathrin platform inhibits CME by sequestering endogenous
clathrin heavy chain, which is necessary for internalization. In the case of clathrin, this
prevented endocytosis of two GPCRs above the phase transition temperature
1
. We
present strong microstructural evidence that dynasome organizations forms similar, albeit
more distinctive assemblies. Similarly, dynasomes have the potential to sequester DNM2-
V96 further away from CME machinery, which may prevent a key scission step for
vesicles undergoing either CME or CAVME
33
or secretion from the trans-golgi network
34
.
Additionally, DNM2-V96 may be of use in answering questions about DNM’s role in less-
characterized pathways, such as flotillin mediated endocytosis
35
. As such, the rapid
assembly of dynasomes has potential applications to study and modulate a variety of
dynamin-dependent biological processes.
38

2.4.9 Dynasomes appear to inhibit EGF internalization

The above represents the work submitted for publication to ACS
Biomacromolecules, focusing primarily on the structures that form and attempting to
understand the mechanisms driving their formation. The dependence of temperature on
the different morphologies belies the central question to the ELP switches projects: Does
their appearance correspond to a biological response? We saw that dynasomes formed
at around 22°C using live and fixed-cell approaches, which change in a predictable
manner all the way up to 37°C. For this reason, we tested whether dynasomes
correspond to a decrease in internalization via a dynamin-dependent mechanism at 37°C.
As such, cells expressing DNM2-A96 or DNM2-V96 were treated with fluorescently
labelled EGF and challenged with dynasore. Cells were imaged in 3D super resolution
microscopy and scored on whether they EGF and EGFR was internalized (Fig. 2.12).
Under all conditions, EGFR and EGF were highly colocalized, whether EGF was
internalized or not. Dynasore is a well-characterized small molecule inhibitor of DNM,
which was observed in our assay to aptly inhibit internalization of EGF in DNM2-A96 cells.
As expected, when not challenged with dynasore, EGF had little trouble being localized
to the cytoplasmic region of the cell (Fig. 2.12A). Large clusters of EGF colocalized with
EGFR are evident in most cells, whereas it was not the case when treated with dynasore.
These two conditions represent controls for how to assess internalization in cells
expressing DNM2-V96. EGF internalization in DNM2-V96 cells were very clearly similar
to DNM2-A96 cells treated with dynasore, but not without. EGF was averse to localization
to the cytoplasm in the presence of dynasomes, suggesting that their formation inhibited
internalization (Fig. 2.12A). Their presence is incidental. Statistical analysis looking at
39

cells scored for internalization were compared to each other using ANOVA with a Tukey
correction. Comparison between EGF internalization DNM2-A96 without dynasore and
DNM2-V96 indicated a statistically significant difference (p < 0.0001) in the proportion of
cells exhibiting the internalization phenotype. DNM2-A96 cells with and without dynasore
were also statistically significantly different from each other (p = 0005); however,
comparison between DNM2-V96 cells and DNM2-A96 cells treated with dynasore yielded
no statistically significant differences (p = 0.65).
Figure 2.12: DNM2-V96, but not DNM2-A96 was able to inhibit EGF
internalization at 37°C in fixed HEK293T cells. A) In DNM2-A96 cells without
dynasore, EGF colocalized EGFR as well as exhibited evidence for internalization by
3-dimensional superresolution microscopy. After treatment with dynasore, EGF and
colocalized EGFR were not observed to internalize the cell. The same phenotype was
observed in HEK293T cells with the dynasome morphology without the need for
dynasore. B) ANOVA analysis between all groups and Tukey correction revealed
statistically significant differences in the proportion of internalized EGF between all
conditions (p < 0.0005, n=3) except between DNM2-A96 + dynasore and DNM2-V96,
indicating they share similar levels of inhibited internalization.
40

2.4.10 Dynasomes do not appear to affect flot1/2 internalization or
macropinocytosis

DNM biology spans a broad spectrum of biological processes. A natural follow-up
question to the previous data is if dynasomes affects other internalization pathways. To
address this idea, macropinocytosis and flotillin biology were assayed by following the
fate of dextran 70 and flot1/2 after the formation of dynasomes. Dynasomes were initially
thought to be a rogue biological process that was activated by their formation. We tested

Figure 2.13: Dynasomes do not appear to affect flotillin1/2 or dextran trafficking.
A) Formation of dynasomes do no colocalize with flot1/2 at 37°C or inhibit its
internalization. Flot1/2 signal appears within the cytoplasm without being seemingly
being affected by dynasomes. B) Dynasomes also do not appear to inhibit
macropinocytosis at 37°C. Fluorescently labelled dextran 70 appears within the
cytoplasm in the presence of dynasomes.
41

for colocalization with f-actin to rule out formation of CDRs, which were found to not be
associated (Fig. 2.9). We then turned to the possibility that these structures might be
activating a macropinocytosis-like event due to their large unconventional size. We
treated cells with a substrate for macropinocytosis (dextran 70) and did not observe
meaningful colocalization with any dynasome structures. Moreover, dextran 70 did not
appear to be affected by dynasome formation, so they appear to be neither encapsulated
within dynasome structures nor were they negatively affected. Both processes appear to
be unrelated (Fig. 2.13B). Flot1/2 was also observed to remain a neutral participant in
the formation of dynasomes. Dynasomes were neither colocalized with flot1/2 nor did they
appear to prevent flot1/2 from internalizing into the cell. Fractions of flot1/2 were observed
at the cell periphery and within the cytoplasm (Fig. 2.13A). While a formal statistical
analysis was not conducted for these studies, preliminary results indicate a lack of effect
by DNM2-V96 on their biology. Future work should use an inhibitor of macropinocytosis,
amiloride, as well as use cholera toxin subunit B as a substrate for FME. Rather than
relying on the suggestive visual information, a formal quantitative study would properly
quantify the results in an unbiased mathematical approach.
2.4.11 Dynasomes colocalize with several organellar markers for endocytosis and
trafficking

While we presume that formation of dynasomes directly prevent the CME
machinery from acting on substrate internalization, this was not directly demonstrated.
The MacKay lab previously demonstrated that phase-transition of V96-CLC in HEK293T
cells resulted in a pulldown of several other proteins, namely clathrin heavy chain (CHC)
and early endosome antigen-1 (EEA1)
1
. CLC and CHC form dimers as part of the
triskelion before forming the clathrin cage around budding vesicles. Colocalization
42

between V96-CLC microdomains with CHC makes sense from a biological perspective
since they directly interact. It was thus concluded that microdomains sequester other
components of the internalization machinery and contribute to the inhibition of CME. The
same question was asked pertaining the dynamin biology. A panel of antibodies against
several trafficking proteins was used to screen for potential colocalization with
dynasomes, including EEA1 (early endosome), Rab7 (early and late endosome), Rab11
(recycling endosome), CHC (early endosome), LAMP1 (lysosomal trafficking), and
Golgin97 (protein secretion) (Fig. 2.14). Colocalization was calculated for DNM2-A96
and DNM2-V96 above and below Tt for each of the markers indicated; however, only a
select few markers were reorganized around dynasome structures. MCC was quantified
and appeared as signal overlap between the endogenous proteins and DNM2-V96 (Fig.
2.14A). The level of colocalization was compared between temperature-sensitive DNM2-
V96 and temperature-insensitive DNM2-A96 at 4°C and 40°C. Statistically significantly
higher MCC was observed in DNM2-V96 cells at 40°C compared to all other conditions
for lysosomal-associated membrane protein 1 (LAMP1) (Fig. 2.14B), early endosome
antigen 1(EEA1) (Fig. 2.14C), Ras-related protein 11 (Rab11) (Fig. 2.14D), and clathrin
heavy chain (CHC) (Fig. 2.14E), but not for golgin or Rab7 markers. These data indicate
that several endogenous trafficking proteins associated with early endosomes or
lysosomal trafficking are reorganized by dynasome organelle; however, it is unclear what
their biological implications are, or what the nature of the (direct or indirect) physical
interactions with dynasome structures are. Previous colocalization studies of V96-CLC
showed that transition and overlap with CHC and Rab5 contributed towards inhibition of
CME by sequestering some of its necessary endogenous components. It is possible that
43

EGF internalization is inhibited by a similar mechanism, but more studies are necessary
to elucidate the mechanisms of the complex biology occurring around dynasomes.

Figure 2.14: Formation of dynasomes resulted in colocalization of several
trafficking markers, including LAMP1, EEA1, RAB11, and CHC. A) Endogenous
expression of proteins colocalized around dynasomes to various degrees. The top
panel indicates low colocalization while the bottom panel is indicative of high
colocalization. B-E) Several makers were colocalized using MCC to between
temperature-insensitive and -sensitive DNM2-A96 and -V96 at 4 and 40°C,
respectively. Comparisons between dynasome forming conditions to non-dynasome
forming conditions yielded statistically significant levels of colocalization for markers of
lysosomal trafficking, endosomal recycling, and vesicle internalization by CME.
44

2.5 Conclusions

Here, we conclude that a novel temperature-sensitive DNM2-ELP fusion forms
three distinct intracellular dynasomes at temperatures above 19.3°C. Unexpectedly, the
dynasomes pass through a range of morphologies from elongated tubes to large spherical
vesicles, and then smaller interconnected vesicles. This process was inhibited by
dynasore, a DNM2 GTPase inhibitor, which suggests the DNM domain retains
biochemistry relevant to assembly. Despite a linkage between f-actin biology and
dynamin, dynasomes exclude f-actin and had little effect on F-actin cellular morphology.
Interestingly, dynasome assembly efficiently entraps cytosolic GFP-ELP within minutes.
In addition to the temperature-dependent assembly of dynasomes, their rapid activation
appear to inhibit EGFR internalization, but not flot1/2 or macropinocytosis.

45

2.6 Sequences and tables

Supplemental Table S1. Nucleotide sequence of DNM2 gBlock Gene Fragment.
gttgttgttttctagaatgggcaaccgcgggatggaagagctgatcccgctggtcaacaaactgcaggacgccttcagctc
catcggccagagctgccacctggacctgccgcagatcgctgtagtgggcggccagagcgccggcaagagctcggtgct
ggagaacttcgtgggccgggacttccttccccgcggttcaggaatcgtcacccggcggcctctcattctgcagctcatcttct
caaaaacagaacatgccgagtttttgcactgcaagtccaaaaagtttacagactttgatgaagtccggcaggagattgaa
gcagagaccgacagggtcacggggaccaacaaaggcatctccccagtgcccatcaaccttcgagtctactcgccacac
gtgttgaacttgaccctcatcgacctcccgggtatcaccaaggtgcctgtgggcgaccagcctccagacatcgagtacca
gatcaaggacatgatcctgcagttcatcagccgggagagcagcctcattctggctgtcacgcccgccaacatggacctgg
ccaactccgacgccctcaagctggccaaggaagtcgatccccaaggcctacggaccatcggtgtcatcaccaagcttga
cctgatggacgagggcaccgacgccagggacgtcttggagaacaagttgctcccgttgagaagaggctacattggcgtg
gtgaaccgcagccagaaggatattgagggcaagaaggacatccgtgcagcactggcagctgagaggaagttcttcctc
tcccacccggcctaccggcacatggccgaccgcatgggcacgccacatctgcagaagacgctgaatcagcaactgac
caaccacatccgggagtcgctgccggccctacgtagcaaactacagagccagctgctgtccctggagaaggaggtgga
ggagtacaagaactttcggcccgacgaccccacccgcaaaaccaaagccctgctgcagatggtccagcagtttggggt
ggattttgagaagaggatcgagggctcaggagatcaggtggacactctggagctctccgggggcgcccgaatcaatcg
catcttccacgagcggttcccatttgagctggtgaagatggagtttgacgagaaggacttacgacgggagatcagctatgc
cattaagaacatccatggagtcaggaccgggcttttcaccccggacttggcattcgaggccattgtgaaaaagcaggtcgt
caagctgaaagagccctgtctgaaatgtgtcgacctggttatccaggagctaatcaatacagttaggcagtgtaccagtaa
gctcagttcctacccccggttgcgagaggagacagagcgaatcgtcaccacttacatccgggaacgggaggggagaa
cgaaggaccagattcttctgctgatcgacattgagcagtcctacatcaacacgaaccatgaggacttcatcgggtttgcca
atgcccagcagaggagcacgcagctgaacaagaagagagccatccccaatcaggtgatccgcaggggctggctgac
catcaacaacatcagcctgatgaaaggcggctccaaggagtactggtttgtgctgactgccgagtcactgtcctggtacaa
ggatgaggaggagaaagagaagaagtacatgctgcctctggacaacctcaagatccgtgatgtggagaagggcttcat
gtccaacaagcacgtcttcgccatcttcaacacggagcagagaaacgtctacaaggacctgcggcagatcgagctggc
ctgtgactcccaggaagacgtggacagctggaaggcctcgttcctccgagctggcgtctaccccgagaaggaccaggc
agaaaacgaggatggggcccaggagaacaccttctccatggacccccaactggagcggcaggtggagaccattcgc
aacctggtggactcatacgtggccatcatcaacaagtccatccgcgacctcatgccaaagaccatcatgcacctcatgat
caacaatacgaaggccttcatccaccacgagctgctggcctacctatactcctcggcagaccagagcagcctcatggag
gagtcggctgaccaggcacagcggcgggacgacatgctgcgcatgtaccatgccctcaaggaggcgctcaacatcatc
ggtgacatcagcaccagcactgtgtccacgcctgtacccccgcctgtcgatgacacctggctccagagcgccagcagcc
46

acagccccactccacagcgccgaccggtgtccagcatacacccccctggccggcccccagcagtgaggggccccact
ccagggccccccctgattcctgttcccgtgggggcagcagcctccttctcggcgcccccaatcccatcccggcctggaccc
cagagcgtgtttgccaacagtgacctcttcccagccccgcctcagatcccatctcggccagttcggatccccccagggatt
cccccaggagtgcccagcagaagaccccctgctgcgcccagccggcccaccattatccgcccagccgagccatccct
gctcgacggtggtcatatgccgtctcctcgag
Supplemental Table S2. Amino acid sequences of DNM2 and GFP
DNM2. Sequence ID: NP_004936.2
GNRGMEELIPLVNKLQDAFSSIGQSCHLDLPQIAVVGGQSAGKSSVLENFVGRDFLPR
GSGIVTRRPLILQLIFSKTEHAEFLHCKSKKFTDFDEVRQEIEAETDRVTGTNKGISPVPI
NLRVYSPHVLNLTLIDLPGITKVPVGDQPPDIEYQIKDMILQFISRESSLILAVTPANMDLA
NSDALKLAKEVDPQGLRTIGVITKLDLMDEGTDARDVLENKLLPLRRGYIGVVNRSQKD
IEGKKDIRAALAAERKFFLSHPAYRHMADRMGTPHLQKTLNQQLTNHIRESLPALRSKL
QSQLLSLEKEVEEYKNFRPDDPTRKTKALLQMVQQFGVDFEKRIEGSGDQVDTLELSG
GARINRIFHERFPFELVKMEFDEKDLRREISYAIKNIHGVRTGLFTPDLAFEAIVKKQVVK
LKEPCLKCVDLVIQELINTVRQCTSKLSSYPRLREETERIVTTYIREREGRTKDQILLLIDI
EQSYINTNHEDFIGFANAQQRSTQLNKKRAIPNQVIRRGWLTINNISLMKGGSKEYWFV
LTAESLSWYKDEEEKEKKYMLPLDNLKIRDVEKGFMSNKHVFAIFNTEQRNVYKDLRQI
ELACDSQEDVDSWKASFLRAGVYPEKDQAENEDGAQENTFSMDPQLERQVETIRNLV
DSYVAIINKSIRDLMPKTIMHLMINNTKAFIHHELLAYLYSSADQSSLMEESADQAQRRD
DMLRMYHALKEALNIIGDISTSTVSTPVPPPVDDTWLQSASSHSPTPQRRPVSSIHPPG
RPPAVRGPTPGPPLIPVPVGAAASFSAPPIPSRPGPQSVFANSDLFPAPPQIPSRPVRI
PPGIPPGVPSRRPPAAPSRPTIIRPAEPSLLD
GFP. Sequence ID: BAK26800.1
ASKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWP
TLVTTFSYGVQCFSRYPDHMKRHDFFKSAMPEGYVQERTISFKDDGNYKTRAEVKFE
GDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYITADKQKNGIKANFKIRHNIEDGS
VQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGM
DELYK

47

Chapter 3: Elastin-like polypeptide fusions to modulate intracellular signaling of
EGFR signaling in a heat dependent manner

3.1 Abstract

Epidermal growth factor receptor (EGFR) is an important tyrosine kinase involved
in cancer biology. The study of EGFR signaling often relies on ligand activation to study
the downstream phosphorylation for the discovery of therapeutic targets. Ligand
activation of EGFR are subject to biased signaling pathways, and/or can result in
crosslinking with other ErbB partners. Using ligands, such as epidermal growth factor
(EGF), to study EGFR signaling limits the ability to decipher precise signaling pathways,
as they may result in biased signaling through differential RTK stabilization or formation
of hetero dimers. Prior development of a temperature-sensitive elastin-like polypeptide
(ELP) fusion to EGFR provided a useful tool to interrogate EGFR homo-cluster signaling;
however, a complete understanding of EGFR signaling of this model remains unknown.
Here, we expand the understanding of ELP-activated EGFR signaling using HEK293T
cells stably expressing EGFR-GFP-ELP that we achieved through recursive flow
cytometry. We demonstrate that GFP fusion is functional and sufficient to provide
selective pressure to identify stable transformants as well as image evidence of ELP-
dependent phase separation, clustering, or morphological changes by super resolution
microscopy, immunoblotting, and RT qPCR data processed by Ingenuity Pathway
Analysis. In addition to morphological changes to cell shape, these strategies revealed
signaling consistent with EGF ligand activation and cancer biology relevant to EGFR,
including activation of the ERK1/2, as well as significant upregulation FOS and JUN.

48

3.2 Introduction

The epidermal growth factor receptor (EGFR) and its kindred activator, epidermal
growth factor (EGF)
36
are important in studying cancer pathology and therapeutic target
discovery. Mutant and aberrant expression have been associated with several cancers in
different human tissue
37
. EGFR belongs to the ErbB family of receptor kinases (RTK) and
is responsible for regulating cell growth, survival, proliferation, and differentiation.
Induction of EGFR signaling by EGF (or other ligands) results in homo- and hetero-
dimerization with other ErbB RTKs
38
. There are no viable ligand-based strategies to
isolate the effects of EGFR homo-activation that exclude the nuanced effects of hetero-
dimerization with other RTKs. For example, EGFR and ErbB2 (HER2) can form
heterodimers in the presence of EGF. Additionally, similar to G-protein coupled receptors
(GPCRs), ligand biasing can affect EGFR signaling kinetics by differentially binding to the
receptor domain
39
. In this context, EGFR pathway analysis using ligand-based
approaches limits our control over downstream signaling. The complex nature of RTK
signaling has provoked interest in developing tools that can interrogate EGFR biology
with precise temporal control.
As one example, optogenetic fusions with light-sensitive domains induce
dimerization of RTKs with light, which activate pERK1/2 signaling
40
. Other approaches
have relied on magnetic nanoparticles that activate apoptosis via cell death receptor 4 or
cytoskeleton remodeling with rho-GTPases
41
. These approaches are effective tools that
can activate cell signaling with greater control; however, they require specialized
equipment to adequately control induction. More recently, our research group developed
49

a simple and reversible heat-activated system that can be stimulated by mild heating in a
standard cell culture incubator using elastin-like polypeptides (ELPs).
ELPs are biopolymers with a temperature sensitive phase-transition property that
allows them to form ‘coacervates’ in solution or ‘microdomains’ within a cell. They self-
assemble in response to subtle increases in temperature after crossing a transition
temperature (Tt). The most well-studied ELPs are comprised of a VPGXGn monomer
motif, which can be engineered to exquisitely control their specific Tt through their guest
amino acid residue (X), or by changing the length of the ELP
42
. This property has been
used in development of several intracellular switches that can reorganize intracellular
fusions to dynamin2
43
or perturb the endogenous biology of effector proteins like clathrin
light chain
1
or caveolin1
2
. Similarly, EGFR fusions to a temperature sensitive ELP have
demonstrated a downstream activation of pERK1/2 without the need of a ligand. While
this approach aptly established a method to study EGFR signaling with precise control
3
,
it was limited by transient transfection, which only accounted for about 20% of total cells.
This prevented analysis of whole cell populations, which will be necessary to adapt this
technique to plate-based assays. While image-based analysis of transfected cells
enabled direct observation of activity, transient transfection prevented the exploration of
downstream gene activation as cell mixtures contain significant populations of
untransformed, wild-type cells.
Here, we describe the generation and characterization of stable fluorescent EGFR-
ELP cell lines that we use for RT qPCR analysis. We show that temperature-sensitive
EGFR-GFP-ELP (V96) forms microdomains and leads to phosphorylation of pERK1/2 in
a heat dependent manner. In contrast, a temperature-insensitive EGFR-GFP-ELP (A96)
50

does not (Fig. 3.1). We then use these cell lines to illustrate the downstream effects of
temperature-mediated activation of EGFR to study changes to gene expression involved
in EGFR signaling pathways. Additionally, we compare these data to known EGFR
signaling phenomena using Ingenuity Pathway Analysis (IPA)
44
.

51

Figure 3.1: EGFR signaling can be activated via a ligand-free system using a
chimeric fusion of EGFR to a temperature sensitive ELP. a) When EGFR is fused
to temperature-insensitive A96, EGFR signaling remains inactive at 37°C; however, b)
addition of a ligand (EGF) can activate downstream signaling via the MAPK (Erk1/2)
pathway. c) When EGFR is fused to a temperature-sensitive V96, EGFR signaling can
be activated without a ligand by mild heating above its Tt (~31.6°C) after induction of
EGFR-ELP clustering.

52

3.3 Materials and methods

3.3.1 Cell culture

HEK293T (ATCC, #CRL-11268) cells were maintained in culture conditions as
previously described
43
. Stock cells were thawed in warm Dulbecco’s Modified Eagle
Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and plated in a 25-
cm
2
flask. Cells were incubated at 37°C in a humidified tissue culture incubator and
maintained with 5% CO2 until reaching 80-90% confluence. Cells were passaged with
warm 0.05% trypsin and maintained in a 75-cm
2
flask.
3.3.2 Plasmid DNA quality control

Plasmid EGFR-GFP-ELP DNA was generated as previously described
3
and
characterized by Sanger sequencing and restriction digests. DNA was sent for
sequencing with third-party vendor (Genewiz, San Diego, CA) using CMV-F and BGH-R
primers and alignment with expected DNA sequences on Snapgene v5.3 software
(Chicago, IL). Digests were performed with either XbaI (NEB, Ipswich, MA, #R0145S) and
HindIII (NEB, #R0104S), XbaI and NotI (NEB, #R0189S), or XbaI. Bands were assessed
on a 1% agarose gel and compared to expected sizes predicted by Snapgene software.
3.3.3 Stable EGFR-GFP-ELP cell line generation

Confirmed EGFR-GFP-ELP mammalian plasmid DNA was used to produce stably
expressing HEK293T cell lines (HEK-EGFR-ELP). After reaching 70-80% confluence on
a 75-cm
2
plate, HEK293T cells were transfected with 17.5 µg of EGFR-GFP-ELP (ELP: -
A96 or -V96) plasmid DNA using the Lipofectamine
TM
3000 protocol and reagents
(Thermofisher, Waltham, MA, #L3000-015) as previously described
3
. After transfection,
cells were incubated in Opti-MEM reduced serum media (Thermofisher, #31985062) at
53

30°C for 48-hrs. After incubation, expression was confirmed by epifluorescent imaging
and sorted by flow cytometry on a BD Aria Fusion (BD Biosciences, Franklin Lanes, NJ).
Distribution of fluorescent signal was estimated from a sample of 10-20,000 cells and
used to collect the top 10-40% of fluorescent population. Cells were plated and grown to
70-80% confluence to repeat sorting (4x) until consistent fluorescence was observed after
a month of cell maintenance in complete DMEM supplemented with 10% fetal bovine
serum (FBS) at 30°C with 5% CO2. Stocks from successful sorting populations were used
for subsequent assays.
3.3.4 Immunoblot assay

At 90% confluence, HEK293T, HEK-EGFR-A96, and HEK-EGFR-V96 cells were
lysed with chilled RIPA buffer spiked with 1x protease inhibitor (Thermofisher, #78442).
Lysate protein concentrations were quantified using a Pierce
TM
BCA Protein Assay Kit
(Thermofisher, #23227) and used to load 25 ug of protein to a 4-20% Mini-Protean TGX
precast gel (Bio-Rad, #4561095). After electrophoresis separation, gels were transferred
on an iBlot2 Dry Blotting device (Invitrogen) to a proprietary nitrocellulose membrane
(Invitrogen, #IB23001). Membranes cut in half and blocked in 5% BSA tris-buffered saline
with 0.1% tween (TBST) for 1-hr at ambient temperature. Membranes were then
incubated separately in 1:1000 rabbit anti-EGFR (Cell Signaling Technology, Danvers,
MA, #4267S) or 1:1000 mouse anti-GAPDH (Cell Signaling Technology, #2118S) in 5%
BSA TBST at 4°C on a shaker overnight. Secondary HRP conjugated antibodies (1:5000)
against rabbit (Cell Signaling, #7074S) or mouse (Cell Signaling, #7076S) were used to
incubate for 1-hr at ambient temperature. Membranes were placed together and imaged
54

by chemiluminescence with ECL reagent (Prometheus Protein Biology Products, San
Diego, CA, #20-301B) in an iBright imaging system (Thermofisher).
3.3.5 Live cell super resolution imaging and analysis

HEK-EGFR-ELP (-A96 and -V96) cells were subcultured to 35-mm glass bottom
dishes pre-coated with poly-D-lysine (MatTek, Ashland, MA, #P35GC-010-C). Cells were
starved in serum-free DMEM at 30°C overnight. Media was replaced with 1x Live Cell
Imaging Solution (Thermofisher, #A14291DJ) at 4°C and maintained on ice. Plates were
imaged on an LSM880 confocal microscope (Zeiss Microscopy, Jena, Germany).
Temperature was maintained using a PS1 mount (Zeiss Microscopy) controlled via a
refrigerated circulator (PolyScience, Niles, IL, #AP07R-40). A temperature ramp was
initiated from a minimum temperature of 15°C to a max of 42°C at a rate of 1°C/min while
super resolution images were automatically acquired using Zeiss Definite Focus 2. Cells
were analyzed for the appearance of puncta structures where the first appearance
denotes each individual cell’s Tt, as previously described
43
. Cells were characterized as
the sum of transitioned cells at each given temperature as a proportion of the total:
𝑃 𝑇 = 𝑃 0
+ 𝑃 1
+ 𝑃 2
+ ⋯ 𝑃 𝑛 Eq. 3.1
Where PT is the total proportion of transitioned cells at a given temperature (T), which is
the sum of the proportion of transitioned cells at each temperature 1°C bin (Pn) within the
corresponding calculated temperature range (20-40°C).
3.3.6 MAPK kinetic assay and analysis

Upon reaching 70-80% confluence in 6-well plates, HEK-EGFR-ELP (-A96 and -
V96) cells were starved in serum-free DMEM (-FBS) at 30°C. After an overnight
incubation, media was replaced with starved media at 4°C for 30-mins, which was then
55

replaced by warm serum-starved media at 37°C for lysate collection. HEK-EGFR-A96
cells were treated with and without 1 ng/mL EGF while HEK-EGFR-V96 cells were treated
without. Lysates were collected at 0, 10, 20, 40, 80, and 160-min post-incubation at 37°C.
The general immunoblot assay protocol was performed as described above. After
blocking in 5% BSA TBST, membranes were incubated in either 1:1000 rabbit anti-
phospho-p44/p42 MAPK (Erk1/2) (Cell Signaling Technology, #4370S), rabbit anti-
phospho-c-Fos (Ser32) (Cell Signaling Technology, #5348S), or mouse anti-GAPDH
overnight at 4°C. Membranes were washed in TBST and then incubated in anti-rabbit or
anti-mouse HRP conjugated as described above. After secondary incubation,
membranes were washed in TBST and imaged on an iBright imaging system. Membranes
were stripped with Restore
TM
Western Blot Stripping Buffer (Thermofisher, #21059) after
each HRP imaging step. Phosphorylation was quantified with FIJI using the gel analyzer
function. Phosphorylation intensity of samples at each timepoint were normalized relative
to GAPDH and as a ratio to normalized phosphorylation at the 0-min time point using the
following formula:
fpERK =
(𝐼 𝑝𝐸𝑅𝐾 ,𝑠𝑎𝑚𝑝𝑙𝑒 )/(𝐼 𝐺𝐴𝑃𝐷𝐻 ,𝑠𝑎𝑚𝑝𝑙𝑒 )
(𝐼 𝑝𝐸𝑅𝐾 ,0𝑚𝑖𝑛 )/(𝐼 𝐺𝐴𝑃𝐷𝐻 ,0𝑚𝑖𝑛 )
Eq. 3.2
Where (IpERK,sample)/(IGAPDH,sample) represents the phosphorylation of pERK1/2 relative to
GAPDH of the sample, and (IpERK,0min)/(IGAPDH,0min) represents the phosphorylation of
pERK1/2 relative to GAPDH at the 0-min time point, and fpERK represents relative
phosphorylation of pERK1/2.

56

3.3.7 Real-Time quantitative PCR (RT-qPCR) optimization and EGFR pathway
array analysis

HEK-EGFR-ELP cells were grown to 80% confluence and starved in serum-free
media. After overnight incubation at (30°C), cells were cooled to 4°C for 30-min before
moving back to 37°C. Total mRNA was extracted using PureLink
TM
RNA Mini Kit
(Thermofisher, #12183018A) following standard manufacturer instructions at 30 or 60-
min timepoints. After mRNA extraction, a cDNA library was generated using a high-
capacity reverse-transcription kit (Thermofisher, #4368814) on a Rad MyCycler (Bio-Rad,
Hercules, CA). PCR master mix (Bioland Scientific, Paramount, CA, #QP03-01)
containing PowerPCR
TM
Hot Start Taq DNA polymerase, PCR buffer, dNTPs, SYBR
GreenI fluorescent dye, Mg
2+
, and ROX reference dye, was mixed with cDNA samples
and 10 µM primers (c-Fos-F, c-Fos-R, c-Jun-F, Myc-F, Myc-R, GAPDH-F, and GAPDH-
R) according to manufacturer protocol on a QuantStudio 12K Flex Real-Time PCR
System (Thermofisher). ΔCT values were calculated as the difference between the CT of
GAPDH and gene of interest (FOS, JUN, or MYC):
ΔC TTIME = CTGAPDH – CTGENE Eq. 3.3
Where ΔCTTIME refers to the normalized threshold for individual genes within each
timepoint for comparison. Data was displayed as ΔC TTIME to identify the smaller values;
however, the comparison between ΔCT60min and ΔCT30min was validated using the Pfaffl
method for relative mRNA quantification (RQ)
45
:
RQTIME =
2
𝛥𝐶𝑇 (60𝑚𝑖𝑛 )
2
𝛥𝐶𝑇 (30𝑚𝑖𝑛 )
Eq. 3.4
Where RQTIME describes relative quantification of ΔΔC T60min compared to calibrator
ΔΔC T30min to show increase in RNA levels between both time points. Data was used to
57

determine peak effect from mRNA extraction time points to run subsequent cDNA
quantification on a TaqMan
TM
Array, Human EGF Pathway, Fast 96-well (Thermofisher,
#4418774) following the standard manufacturer protocol. Relative Quantification (RQ)
was calculated as the fold-change expression of HEK-EGFR-V96 relative to HEK-EGFR-
A96 using Eq. 3.5.
RQELP =
2
𝛥𝐶𝑇 (𝑉 96)
2
𝛥𝐶𝑇 (𝐴 96)
Eq. 3.5
Where ΔCTELP is the difference between GAPDH and the gene of interest for each HEK-
EGFR-ELP sample. The RQ values were then used to generate figures on GraphPad
software (San Diego, CA) to visually compare differences.
3.3.8 Ingenuity pathway analysis

Ingenuity pathway analysis software was used to compare our dataset to other
datasets. Core expression analysis was performed to measure fold change and pathway
enrichment in 90 human genes with direct and indirect relationships to the EGFR
pathway, not including reference housekeeping genes. Default color coding was
maintained per software visual output, where red is highly upregulated, pink is
upregulated, orange is predicted behavior, and yellow is inconsistent within the dataset.
Graphs showing pathway enrichment was generated from IPA directly, while canonical
pathway analysis and disease/function annotation were generated from raw data for
categories with z-values above |±2|. Data were scored by significance and plotted in order
as -log(p-value).

58

3.4 Results and discussion

The development of ELP tools have the potential to simplify interrogation of cellular
processes. Unlike the light-sensitive tools or magnetic nanoparticles, this approach does
not require specialized LED light emission and measurement equipment or rely on
microinjections. ELP fusions can be genetically encoded to express in a wide variety of

Figure 3.2: EGFR-GFP-ELP DNA was validated and used to generate stable cell
lines in HEK293T cells. a) PCDNA3.1-EGFR-A96 and –V96 were validated by
restriction digests. A combination of digests were used to confirm expected fragment
sizes with i) XbaI and HindIII, ii) XbaI and NotI, or iii) only XbaI. b) The plasmid map
shows the cut sites and sequence fragments represented on the agarose gel, as well
as the expected expression of our ELP fusion. c) Western blot analysis was used to
confirm the full expression of EGFR-GFP-ELP after transfection into HEK293T cells.
Antibodies against EGFR and GAPDH were used to validate expression.
59

cell systems and do not require specialized equipment, making them a versatile option
that can grant precise spatial-temporal control of the biology associated with fused
proteins. Here, the development of stable HEK-EGFR-ELP cell lines have expanded our
ability to probe ELP-mediated effects on the EGFR pathway that were previously not
possible. Using these stably transformed cell lines, whole cell populations can now be
probed to extract genome-wide effects related to triggering EGFR biology, which span
from basic understanding of molecular signaling pathways to the identification of novel
therapeutic targets with relevance to cancer, development, and other diseases.
3.4.1 DNA quality control and expression

Our first step was to quality control the DNA that would be used to transfect wt-
HEK293T cells and generate stable cell lines (Fig. 3.2). EGFR-GFP-ELP was validated
by diagnostic enzyme digests using three different cut sites to confirm the presence of
the three key sequences necessary for our constructs. HindIII, XbaI, and NotI were used
in different combinations to reveal the correct band sizes for the -A96 and -V96 fusion
pairs (Fig. 3.2a). The first two lanes represent digests with XbaI and HindIII, which result
in 3 distinct strands approximately ~3650 bp (EGFR), ~2280 bp (GFP + ELP), and ~4930
bp (backbone) relative to the 1 kbp ladder. The third and fourth lane represent digests
with XbaI and NotI, which yield two strands sized 8580 bp (backbone + EGFR) and 2280
bp (GFP + ELP). The final lanes represent a single cut with XbaI, which confirms the
Table 3.1. EGFR-ELP nomenclature and characteristics
Nomenclature Sequence MW (kDa) Tt (C°)
EGFR-GFP-A96 EGFR-GFP-(VPGAG)96Y 199.2 NA
EGFR-GFP-V96 EGFR-GFP-(VPGVG)96Y 201.9 31.5
1
Full FASTA sequences available in Table S3.1
2
MW determined with Snapgene software
3
Tt calculated from live cell experiments
60

expected ~10.8 kbp of the entire strand (Fig. 3.2b). After approximate plasmid size
confirmation, EGFR and ELP sequences were verified by Sanger sequencing using
forward and reverse primers flanking the open reading frame (Table 3.1) and used to
transfect HEK293T cells for stable cell line generation.
48-hrs post-transfection, cells were checked for fluorescence by epifluorescent
microscope to visually confirm expression. Immunoblotting against EGFR was used to

Figure 3.3: HEK293T cells transfected with EGFR-GFP-ELP mammalian plasmid
DNA were sorted by fluorescence to select positively expressing cells over
several cycles to generate stably expressing cells. a-b) The top 20-40%
fluorescent singlet cells were selected and collected over several cycles. c) EGFR-
GFP-A96 cells were confirmed by epifluorescent microscopy after a month of selection
in culture to ensure expression for subsequent assays. d) EGFR-GFP-V96 cells were
also confirmed and used for subsequent assays.

61

assess full expression of EGFR-GFP-ELP. Lanes containing EGFR-GFP-A96 and -V96
Figure 3.4: HEK293T cells stably expressing EGFR-GFP-A96 or EGFR-GFP-V96
were heated and imaged by superresolution confocal microscopy to
characterize their transition properties. a) Cells expressing temperature-insensitive
EGFR-GFP-A96 were not observed to undergo phase transition within a physiological
range of temperatures; however, b) cells expressing temperature-sensitive EGFR-
GFP-V96 were observed to form microdomains starting at an average temperature of
31.6°C (n=3). C) The proportion of cells displaying puncta between temperature
sensitive and insensitive EGFR-GFP-ELPs were compared to each other. Cells
expressing EGFR-GFP-V96 began forming puncta starting at 27°C and peaked at
about 34°C, while cells expressing EGFR-GFP-A96 were not observed to form a
significant proportion of microdomains. c) The mean transition temperature of EGFR-
GFP-V96 was analyzed by ANOVA to show a non-statistically significant difference
between each of the triplicate runs (p=0.23, n=3).

62

fusions appeared below the 250 kDa reference ladder as expected (~200 kDa) with a
fainter band underneath matching endogenous EGFR (~175 kDa) in the -A96 lane (Fig.
3.2c). To enrich cells, HEK293T cells were sorted weekly by flow cytometry to subculture
the top 10-40% of fluorescent cells. Over several selection cycles (Fig. 3.3), cells
displaying sustained expression for a month were considered to be stably expressing and
used for subsequent assays and analysis.
3.4.2 HEK-EGFR-V96 cells form puncta after mild heating

As such, the next step we took was to verify the expected phase-transition of ELPs.
Previously, we reported a median Tt of 32.8°C
3
for EGFR-V96 using an indirect method
the MacKay lab developed, which has been applied in characterizing several ELP
fusions
46
. Here, we directly quantify microdomain formation using a GFP flanked between
EGFR and ELP. This allowed for direct measurement of Tt by live-cell super resolution
confocal microscopy without the need for a surrogate reporter (Fig. 3.4). As expected,
HEK-EGFR-A96 cells did not display transition characteristics at any temperature up to
the max observed temperature near 40°C (Fig. 3.4a). Conversely, HEK-EGFR-V96 cells
displayed Tt characteristics that we were able to quantify by noting a stark and sudden
appearance of bright puncta at the cell periphery and within the cytoplasm (Fig. 3.4b).
HEK-EGFR-A96 did not meaningfully form puncta; however, we quantified the proportion
at which puncta formed as a proportion of the total using Eq. 3.1 to compare both
populations of cells. Very few HEK-EGFR-A96 cells (0.037 ± 0.018, n=3) formed puncta,
while 100% of HEK-EGFR-V96 cells formed puncta by 34°C (Fig. 3.4c) with a mean Tt
calculated at 31.6°C (± 0.8, n=3) (Fig. 3.4d). These data clearly indicate that HEK-EGFR-
V96 transition dominates the population below 37 °C, while HEK-EGFR-A96 does not.
63

This is within 1.2°C of the mean and 95% CI of our previous report on EGFR-V96 that
lacks a GFP fusion
3
. The mean temperature of observed puncta in HEK-EGFR-A96 cells
was not calculated because the proportion of cells with puncta was not significant.
3.4.3 HEK-EGFR-V96 cell transition triggers downstream phosphorylation of
ERK1/2

The assumption is that EGFR-GFP-V96 coacervation triggers signaling events
downstream of an EGFR signaling cascade, which was confirmed with increased
phospho-Erk1/2 above Tt. Thus, we expected stably expressing cells to confirm
phospho-Erk1/2 phospho-c-Fos to increase in HEK-EGFR-V96 cells, but not in HEK-
EGFR-A96 cells heated to 37 °C. This was tested by assaying Erk1/2 phosphorylation by
immunoblotting different time points. Lysates from HEK-EGFR-A96 cells (negative
control) and HEK-EGFR-V96 cells were collected above Tt and compared to each other
(Fig. 3.5). HEK-EGFR-A96 cells did not demonstrate activated phospho-Erk1/2, while
HEK-EGFR-V96 cells did, as expected (Fig. 3.5a). Phosphorylation was quantified using

Figure 3.5: HEK-EGFR-ELP cells were assayed at different timepoints by
immunoblotting to assess ERK1/2 and c-Fos phosphorylation. Relative
phosphorylation was compared between HEK-EGFR-V96 and -A96 to show a distinct
increase in ERK1/2 phosphorylation, as well as a subtle increase in c-Fos
phosphorylation. Phosphorylation appeared to increase from 0-min to 10-min all the
way through the end of the 160-min assay only for -V96 cells.
64

Eq. 3.2 to compare EGFR signal activation between both stable cell lines. Curves were
generated comparing relative Erk1/2 phosphorylation which showed a HEK-EGFR-V96
response that peaks between 10-20-mins. At the same intervals, no activation was noted
in HEK-EGFR-A96 cells (Fig. 3.5b).
3.4.4 EGFR real time quantitative PCR gene array

After demonstrating that phospho-Erk1/2 is recapitulated in stably expressing
cells, the system-wide effects of EGFR activation were explored by RT-qPCR (Fig. 3.6).

Figure 3.6: RT qPCR was used to quantify effects of Tt on the EGFR pathway
using temperature-sensitive and -insensitive HEK-EGFR-ELP cells. a) RNA
extraction for RT qPCR was optimized by collecting at 30- and 60-min to compare the
relative expression of FOS, JUN, and MYC above Tt between both time points ΔCT30-
min versus ΔΔCT60-min. The data suggests a moderate increase of JUN and MYC
mRNA at 60-min, with a significant jump in FOS. b) This time point was used to assess
several downstream targets of the EGFR pathway using an array of genes. Most
genes were upregulated (85 of 90) above Tt, with exception of MUC1 (x0.91), RRAS
(x0.90), PIK3C2A (x0.85), RHOG (x0.79), and RELB (x0.72). While PIK3C2A was
downregulated, every other PI3K isoform was upregulated to various degrees.
Additionally, several transcription factors were upregulated, including FOS (x1134.6)
and JUN (x13.60). The full list of genes is located in Table 3.2.
65

First, the timing on sample collection were optimized by manually verifying which RNA
extraction time point best captured downstream biology of EGFR signaling. The ΔCT-
values for JUN, FOS, and MYC at 60-min time point were compared to a 30-min time
point. The lower ΔCT values represent higher mRNA values, which were slightly higher
at 60-mins for JUN and MYC, but significantly different at 60-mins (Fig. 3.6a). As such,
mRNA samples at 60-min were used to quantify a broad array of canonical genes
associated with EGFR downstream signaling. Expression of a total of 90 genes were
quantified, including several housekeeping genes for reference. Gene expression was
quantified using Eq. 3.3 to compare the fold difference between temperature-sensitive
HEK-EGFR-V96 cells and temperature-insensitive HEK-EGFR-A96 cells at the 60-min
time point using the Pfaffl method
45
. While a few genes were slightly downregulated, the
vast majority of genes were upregulated (Fig. 3.6b).
The results of the EGFR pathway RT qPCR array were consistent with known
EGFR biology. The expected upregulation of the canonical components of the EGFR
machinery, including genes for EGF, EGFR, and the MAPK pathway are non-
controversial (Table 3.2). Moreover, the data generally shows that there is a broad
increase in gene activation above Tt. The canonical EGFR pathway relies on RAS/RAF
activation of downstream MAPK
47
. All MAPK isoforms were upregulated to some degree,
while seemingly being biased towards MAP3K and MAPK8, both downstream
components of RAS/RAF. BRAF and RAF1 were also upregulated, while ARAF was not
in this dataset. Different isoforms of Raf act in distinct fashion and may be differentially
regulated in cancer
48
. These components are upstream of AP-1 complexes comprised of
homo- and hetero-dimers of JUN and FOS, which have also been targeted to produce
66

Table 3.2: TaqMan mRNA Quantification (RQ) HEK-EGFR-V96 relative to HEK-
EGFR-A96
Gene RQ Gene RQ Gene RQ
ABI1 3.27 MAP2K1 1.16 PRKCE 1.89
AKT1 1.63 MAP2K2 1.14 PRKCG 1.18
AKT2 0.99 MAP2K4 1.16 PRKCQ 3.70
AKT3 1.47 MAP2K7 1.18 PRKCZ 1.23
ARAF 1.01 MAP3K1 1.94 PTK2 1.88
BRAF 1.53 MAPK1 1.17 PXN 1.44
CAV1 1.34 MAPK10 0.96 RAB5A 1.50
CAV2 1.33 MAPK3 1.23 RAC1 1.59
CBL 1.22 MAPK8 1.60 RAF1 1.48
CDH1 1.44 MAPK9 1.02 RASA1 1.44
CHUK 1.00 MRAS 2.24 REL 1.43
CSK 1.13 MUC1 0.91 RELA 1.94
CTNNB1 1.57 MYC 3.56 RELB 0.72
DIRAS3 1.37 NCK1 1.59 RHOA 1.18
EGF 2.01 NFKB1 1.31 RHOB 1.57
EGFR 2.48 NKFB2 1.10 RHOC 0.97
ELK1 1.58 NRAS 0.95 RHOG 0.79
EPS8 1.43 PAK1 1.45 RND3 3.09
ERBB2 1.30 PDPK1 2.29 RRAS 0.90
FOS 1134.62 PIK3C2A 0.85 RRAS2 2.02
GAB1 2.09 PIK3C2B 2.62 SHC1 1.07
GRB2 1.39 PIK3CA 0.96 SHC3 1.96
HRAS 1.25 PIK3CB 1.49 SOS1 1.51
IKBKB 1.47 PIK3CD 1.28 SOS2 1.24
IKBKE 1.88 PIK3R1 2.52 SRC 1.86
IKBKG 1.24 PIK3R2 1.31 STAT1 1.43
JAK1 1.54 PLCG1 1.58 STAT3 1.10
JAK2 1.60 PRKCA 1.14 VAV1 1.24
JUN 13.59 PRKCB 1.65 VAV2 2.13
KRAS 1.54 PRKCD 1.51 VAV3 1.35
Bold values are highly upregulated. Italicized values are downregulated isoforms.
67

inactive AP-1 complexes to suppress breast cancer proliferation
49
. In this context,
MAPK/ERK1/2 signaling appears to be responsible for amassing a strong JUN and FOS
transcription response downstream of this signaling branch, which may be delayed
relative to what was observed in immunoblotting data that showed peak phosphorylation
between 10-20-mins.
Relative to other upregulated genes, JUN and FOS represent an outsized
response – by up to a three order of magnitude increase. This is likely the result of a
convergence of several factors upstream of this cell response. Another highly upregulated
downstream transcription factor is ELK1, which is activated downstream by ERK1/2
50
.
Together, JUN, FOS, and ELK1 are part of a common signaling branch downstream of
HRAS. Additionally, ELK1 is predicted to be upregulated downstream of protein kinase C
(PRKC) signaling, which is activated through IP3/DAG/Ca
2+
second messenger signaling.
Incidentally, phospholipase kinase C-γ1 (PLCG1), another substrate of EGFR signaling
is upregulated upstream
51
. It acts on IP3 via second messengers to act on PRKC and its
upregulated isoforms, most notably the PRKCQ isoform. PRKC expression is complex in
cancer and studies often fail to differentiate between isoforms
52
, which require further
study. Thus, despite producing an important signal in this assay, the significance of
PRKCQ prominence in HEK-EGFR-V96 upregulation is unclear. Along with the above,
PI3K/Akt signaling is also upregulated downstream of EGFR activation. While AKT1 and
AKT3 are upregulated, AKT2 expression remains stable above Tt. AKT isoforms have
been reported to play different roles
53, 54
. Similarly, some PI3K isoforms were also
upregulated and displayed complex isoform regulation. Specifically, PIK3C2A was slightly
downregulated while the remaining were upregulated
55
. The expression differences might
68

be indicative of cell-specific and/or EGFR homo-activation characteristics. The HEK-
EGFR-ELP system here displays a specific expression profile that can serve as a model
system to assay inhibitors of targets in the EGFR pathway that are selective to specific
isoforms
53
. It is possible that there are specific changes to the gene upregulation profile
driven by EGFR homo-dimerization, which would differ from a ligand-based approach.
EGF-EGFR binding can result in crosstalk between different RTKs, which way mediate a
different response that is the result of this nuance similar to GPCR transactivation of

Figure 3.7: Ingenuity Pathway Analysis was used to compare the RT qPCR
analysis of EGFR-V96 signaling to existing gene expression datasets.
Temperature activated signaling in HEK-EGFR-V96 cells is representative of EGF-
activated EGFR signaling in available datasets. The ELP-mediated signaling
schematic of EGFR displays gene functionality, location, and regulation. The color
shades are related to gene regulation with green for upregulation and red for
downregulation. This data summarizes IPA findings showing upregulation of
transcription factors c-JUN and c-FOS.

69

EGFR
56
. It also lacks direct control over how individual RTKs crosslink to initiate EGFR
signaling
39
. This system demonstrates a simple and versatile proof-of-concept model for
application to different RTKs and/or different cell types. This technology may better mimic
cancer signaling of isolated RTKs, including those with unknown ligands.
3.4.5 Ingenuity Pathway Analysis of gene array data

To better understand how the expression profile of HEK-EGFR-V96 relates to
known EGFR signaling, this data was compared to EGFR signaling databases using
Ingenuity Pathway Analysis (Fig. 3.7). The data validates observations by providing visual
insight into the EGFR signaling pathway. For example, this clarifies the relationship
between different genes in the array relative to their position in the pathway, along with
how the dataset compares to others. The overall upregulation of EGFR-related pathways
is not surprising; however, it was also noted here that while this result was expected, the
level of activity was greater than database values. Generally, values were modestly
higher for the vast majority of genes in this assay, which recapitulates the observations
with the Western blot experiments showing that ELP-activated signaling led to robust
phosphorylation of ERK1/2 and FOS. It is interesting that while this data shows a
generally higher response, JUN and FOS are highly upregulated according to IPA.
Several upregulated signaling branches downstream of EGFR are upregulated,
including the MAPK/ERK, JAK/STAT, AKT/PI3K, and the PLCG1 pathways. The
downstream transcription factors in the IPA canonical pathways chart suggests others
like STAT1/3 or ELK1-complexes would play more significant roles relative to their
upstream signaling partners; however, the data reveal an impressive convergence on
FOS and JUN. The Western blot data would suggest higher levels of ELK1 downstream
70

of phospho-ERK1/2 compared to modest phospho-c-FOS. Instead, the immunoblotting
data does not support the observations made by RT qPCR. These differences appear to
be fueled by differential sensitivities of antibody binding. Thus, the relative relationships
and not their absolute values can be used to interpret total expression. The RT qPCR
data was useful in understanding the total level of expression of several key players with
greater sensitivity than immunoblotting techniques. The array data is significantly more
sensitive and informative than immunoblotting assays when comparing the relative
expression levels. These data were used to compare to several canonical pathways in
the IPA database, as well as to annotate how HEK-EGFR-V96 expression relates to
function and disease. These data are not surprising, suggesting that signaling can be
quickly activated by heating cells beyond their Tt in HEK-EGFR-V96 cells, but not HEK-
EGFR-A96 cells. While the specific players that are activated are revealed by the array
and subsequent IPA analysis, the biological pathways they share relate to might provide
deeper insights into signaling phenotype (Fig. 3.8). Upon activation by heat, signaling
shares similarities to several canonical pathways, including upregulation of renin-
angiotensin signaling and several RTK signaling pathways. Interestingly, these data
indicate a negative similarity to PTEN and apoptosis signaling, which reinforces the
positive relationships indicating a high level of activity downstream of EGFR activation
(Fig. 3.8a). On a biological scale, these data can be annotated for function and disease
relationships. They resemble the biology of cancer with high -log(p-value) of cancer
survival, proliferation, and viability characteristics. Similarly, these data are negatively
associated with characteristics for cancer cell death and cancer apoptosis (Fig. 3.8b).
71

Knowledge of RTK signaling is lagging behind that of G-protein coupled receptors
(GPCRs). The increased understanding of GPCR signaling has led to developments in
research and drug development. Strategies to study RTKs have lagged behind. Using
ligands to study signaling is complicated by several factors, but mainly variations in dose-
response curves or lack of precise RTK activation. The differential activation of signaling
response is modulated by RTK dimerization, which may include a heterogenous
Figure 3.8: IPA analysis compared the RT qPCR data to compare to several
canonical pathways and how expression relates to disease and function in
biological systems and ranked using the -log(p-value) for relationships where z-
score > |2|. a) The relationship of HEK-EGFR-V96 signaling to several canonical
pathways is visualized from a selection of top similarities in the IPA data base.
Signaling is related to renin-angiotensin signaling and several ERBB pathways,
including downregulated PTEN and apoptosis signaling. b) The expression profile of
HEK-EGFR-V96 cells was then used to generate relationships to system wide biology,
which suggest similarities to cancer signaling, growth, proliferation, and tumor invasion
characteristics. Cell death and apoptosis characteristics were found to be negatively
associated with the RT qPCR dataset.

72

combination of components and responses. Precise control of RTK dimerization can be
a valuable tool in understanding the nuance of the downstream signaling for EGFR and
other RTKs. The development and characterization of an ELP-mediated tool to activate
signaling serves as a proof of concept for application of this technology to other RTK
signaling systems, which can be applied to advance the understanding of the ERBB
family of receptors, fibroblast growth factor receptors, insulin receptors, and platelet
derived growth factor receptors, among others. While there are tools available to
investigate signaling in different RTK systems, ELPs can be theoretically applied to all of
them to generate a precise understanding of the mechanisms that underpin their biology.
This in turn can lead to novel target identification for the development of therapeutics to
treat dysregulated RTK signaling.

73

3.5 Conclusion

RTK signaling is important for therapeutic target discovery. While much attention
has been paid to understanding GPCR biology, RTK biology remains relatively
unexplored. Here, we outline an approach to activate EGFR signaling that mimics cancer
signaling models without the need for a ligand. Specifically, this system can be activated
with heat within a narrow temperature range to bias signaling towards EGFR homo-
clustering. The system was able to activate a signaling cascade that touched on several
of EGFR signaling branches that together support its function as a cell model for cancer
target discovery. The expression profile activated by mildly heating cells above their Tt
generated a statistically significant similarity to several canonical signaling pathways
including patterns that overlap with several cancer phenotypes from tumor cell
proliferation, tumor cell survival, tumor cell movement, and tumor cell metastasis. The list
of features is expansive. This discovery serves as a proof-of-concept for the use of ELP
technology to study other RTKs as tools to shed light on unknown targets in disease early
drug development pipelines.

74

3.6 Sequences and tables

Table S3.1. Full EGFR, GFP, and ELP protein sequences
EGFR:
MRPSGTAGAALLALLAALCPASRALEEKKVCQGTSNKLTQLGTFEDHFLSLQRMFNNC
EVVLGNLEITYVQRNYDLSFLKTIQEVAGYVLIALNTVERIPLENLQIIRGNMYYENSYAL
AVLSNYDANKTGLKELPMRNLQEILHGAVRFSNNPALCNVESIQWRDIVSSDFLSNMS
MDFQNHLGSCQKCDPSCPNGSCWGAGEENCQKLTKIICAQQCSGRCRGKSPSDCC
HNQCAAGCTGPRESDCLVCRKFRDEATCKDTCPPLMLYNPTTYQMDVNPEGKYSFG
ATCVKKCPRNYVVTDHGSCVRACGADSYEMEEDGVRKCKKCEGPCRKVCNGIGIGE
FKDSLSINATNIKHFKNCTSISGDLHILPVAFRGDSFTHTPPLDPQELDILKTVKEITGFLLI
QAWPENRTDLHAFENLEIIRGRTKQHGQFSLAVVSLNITSLGLRSLKEISDGDVIISGNK
NLCYANTINWKKLFGTSGQKTKIISNRGENSCKATGQVCHALCSPEGCWGPEPRDCV
SCRNVSRGRECVDKCNLLEGEPREFVENSECIQCHPECLPQAMNITCTGRGPDNCIQ
CAHYIDGPHCVKTCPAGVMGENNTLVWKYADAGHVCHLCHPNCTYGCTGPGLEGCP
TNGPKIPSIATGMVGALLLLLVVALGIGLFMRRRHIVRKRTLRRLLQERELVEPLTPSGE
APNQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKE
ILDEAYVMASVDNPHVCRLLGICLTSTVQLITQLMPFGCLLDYVREHKDNIGSQYLLNW
CVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGAEEKEYHAEGGK
VPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIPASEISSILEKGERLP
QPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPT
DSNFYRALMDEEDMDDVVDADEYLIPQQGFFSSPSTSRTPLLSSLSATSNNSTVACID
RNGLQSCPIKEDSFLQRYSSDPTGALTEDSIDDTFLPVPEYINQSVPKRPAGSVQNPVY
HNQPLNPAPSRDPHYQDPHSTAVGNPEYLNTVQPTCVNSTFDSPAHWAQKGSHQISL
DNPDYQQDFFPKEAKPNGIFKGSTAENAEYLRVAPQSSEFIGA
Linker:
SRVAT
eGFP:
MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPW
PTLVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKF
EGDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDG
75

SVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLG
MDELYK
Linker 2:
SGLTGAMG
A96:
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGY
V96:
VPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGV
GVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPG
VGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVP
GVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGV
PGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVG
VPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGV
GVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPG
VGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVP
GVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGVPGVGY

76

Chapter 4: Cell-surface GRP78 targeting enhances potency of rapamycin via an
elastin-like polypeptide drug carrier

4.1 Abstract

Rapalogues are powerful therapeutic modalities for breast cancer; however, they
suffer from low solubility and dose-limiting side effects. To overcome these challenges,
we developed a long-circulating drug carrier called 5FA, which contains rapamycin-
binding domains linked with elastin-like polypeptides. To target their potency towards
breast cancer, we here linked 5FA with four distinct peptides reported to engage the cell
surface form of the 78-kilodalton glucose regulated protein (csGRP78). To determine if
these peptides affected the carrier solubility, this library was characterized by light
scattering and mass spectrometry. To guide in vitro selection of the most potent functional
carrier for rapamycin, their uptake and inhibition of mTORC1 were monitored in a ductal
breast cancer model (BT474). Using flow cytometry to track cellular association, only the
targeted carriers enhanced cellular uptake and were susceptible to proteolysis by SubA,
which specifically targets csGRP78. The functional inhibition of mTOR was monitored by
Western blot for pS6K, whereby the best carrier L-5FA reduced mTOR activity by 3-fold
compared to 5FA or free rapamycin. L-5FA was further visualized using super-resolution
confocal laser scanning microscopy, which revealed that targeting increased exposure to
the carrier by ~8 fold. This study demonstrates how peptide ligands for GRP78, such as
the L peptide (RLLDTNRPLLPY), may be incorporated into protein-based drug carriers
to enhance potency.

77

4.2 Introduction

Rapamycin is a macrolide with structural and mechanistic similarities to
everolimus, which is approved for combination therapies of hormone-receptor positive
breast cancer. The BOLERO-2 clinical trial strongly supported efficacy of this rapalogue;
however, it suffered from significant adverse events
57, 58
. Post-approval, these issues
continue to limit patient drug adherence with low oral bioavailability and solubility that
have impacted other major clinical studies
58, 59
. This highlights the need to develop
delivery strategies that improve their therapeutic value. One strategy to improve aqueous
drug solubility is to hide hydrophobic molecular structures inside an inclusion complex.
Rapalogues form a complex with FK506-binding protein (FKBP12), the cognate binding
partner of FK506. When bound to FKBP, rapamycin solubility is improved without
preventing its targeting of the mechanistic/mammalian target of rapamycin complex 1
(mTORC1)
60
.
The MacKay lab has developed several FKBP-rapalogue formulations fused to
elastin-like polypeptides (ELPs), which improve rapalogue solubility and extend plasma
half-life, possibly by reducing glomerular filtration
61
. ELPs are biocompatible biopolymers
comprised of a pentameric repeat of amino acids (VPGXG)n that are soluble below a
transition temperature (Tt), but form coacervates with mild heating. This can be exploited
to isolate pure ELPs cellular lysates. This phase can be modulated by hydrophobicity of
guest amino-acid residue, X, length of pentameric repeat, n, or concentration
42
. The
Mackay lab has used these design considerations to engineer FKBP-ELPs as soluble
systemic or sustained-release rapamycin formulations. For example, the first-generation
FKBP-ELP formulation fused FKBP (F) to a diblock ELP. It was comprised of hydrophilic
78

(VPGSG)48 adjacent to a hydrophobic (VPGIG)48 (FSI) and formed spherical
nanoparticles above its Tt
62
. This formulation suppressed tumor growth in a breast cancer
xenograft model, while also reducing side effects compared to a free-rapamycin control
5,
63
. A next generation formulation, termed “Berunda polypeptide” (FAF), was engineered
to increase rapamycin payload by inserting two FKBP domains at the N- and C- termini
of soluble (VPGAG)192 (A192). By retaining drug solubility during subcutaneous
administration, it increased tumor accumulation and outperformed the FSI carrier in a
breast cancer xenograft model
6
. To improve on the FAF design and enhance drug loading
capacity, we next incorporated up to five FKBP repeats per polymer linked by four V24
blocks, (VPGVG)24, to generate 5FV. This 5FV formulation formed a depot at the injection
site for extended release in a mouse model of Sjogren’s Syndrome
9
.
More recently, our team’s FKBP-ELP formulations have improved on previous
designs by including a targeting moiety of cell surface motifs. For example, an integrin-
targeting moiety was incorporated via an RGD-SI/FSI mixture that improved on the
previous FSI formulation via RGD moieties displayed at the nanoparticle corona
4, 8
. Other
formulations fused an A192 to intercellular adhesion molecule 1 (ICAM-1) targeting
peptide, which enhanced accumulation in the inflamed lacrimal glands of non-obese
diabetic mice
64
. This FKBP-ELP formulation developed in this work now optimizes the
targeting of a high-capacity, soluble ELP called 5FA. To do so, we target the 78-kilodalton
glucose-regulated protein (GRP78), which is a key molecular chaperone. Encoded by the
HSPA5 gene, this protein is also referred to as BiP or HSPA5. GRP78 belongs to a class
of stress-induced chaperones within the heat shock protein (HSP) family, which primarily
reside in the endoplasmic reticulum (ER)
65
. While ER-localized GRP78 is ubiquitous,
79

Figure 4.1: X-5FA targeting to csGRP78 can deliver rapamycin to BT474 cells. X-
5FA targets csGRP78 primarily via the W and L ligand while carrying rapamycin bound
to several FKBP domains. Exogenous cleavage by protease SubA blocks csGRP78-
dependent cell surface targeting. After ligand binding, X-5FA-rapa is internalized into
the cell. Rapamycin reaches its intracellular target mTOR and inhibits downstream
signaling via pS6K and rpS6 to inhibit downstream effects (mRNA translation).
80

a fraction translocates to the cell surface under ER stress, termed cell-surface GRP78
(csGRP78). GRP78 is commonly upregulated in cancer cells
66, 67
, whereby ER-stress
increases csGRP78
21
. Importantly, cancer cells that are aggressive or have acquired
resistance to treatment further increase csGRP78, thus making it a valuable target for
cancer therapeutics or conduits for cancer-specific drug delivery
68
. Ligands (W, L, P6,
and P13)
69, 70
targeting csGRP78 have been identified with high binding affinities and
represent viable strategies to target therapeutic payloads
4, 71
. Here, we present the
development of this small library of ligand-targeted rapamycin carriers (X-5FA). We
describe evidence showing expression and purification using the ELP platform, as well
as characterization for ligand dependent internalization and downstream biological effects
via mTOR inhibition by rapamycin (Fig. 4.1).

81

4.3 Materials and methods

4.3.1 Cloning and sequencing

5FA was generated by recursive ligation as previously described
9
, which yields an
open reading frame expressing the amino acid sequence indicated in Table 4.1. Forward
and reverse 5’ phosphorylated DNA oligonucleotide sequences encoding GRP78
targeting peptides (X = W, L, P6, or P13) were synthesized by Genewiz Inc. (South
Plainfield, NJ) and annealed in water at 94°C for 2-min and cooled to ambient
temperature. Prior to ligation, the 5FA plasmid was digested by NdeI (New England
BioLabs (NEB), #R0111S), dephosphorylated with alkaline phosphatase (NEB, #M0290),
and purified by gel extraction (Qiagen, #). The annealed oligonucleotides inserts were
ligated into linear 5FA vector using T4 DNA ligase (NEB, #M0202) at a 1:3 ratio overnight
at 16°C.
Table 4.1. 5FA shorthand sequences and Tt
Protein Amino acid sequence
1
Tt (°C)
2

5FA M-(FKBP (VPGAG24))4 FKBP 54.1
W-5FA M-WIFPWIQL-VPGAGM-(FKBP (VPGAG24)4 FKBP 51
L-5FA M-RLLDTNRPLLPY-VPGAGM-(FKBP (VPGAG24)4 FKBP 52.4
P6-5FA M-RLLDTNRPFLRY-VPGAGM-(FKBP (VPGAG24)4 FKBP 52.7
P13-5FA M-RLLDTNRPFLFY-VPGAGM-(FKBP (VPGAG)24)4 FKBP 50.2
1
FKBP and A24 sequences are available in the supplemental table S1.
2
Tt was experimentally observed at 5 μM in PBS.

Electrocompetent ClearColi BL21 (DE3) cells (Lucigen, #60810-2) were
transformed with ligated X-5FA, or 5FA plasmid DNA by electroporation in a BTX 600
electroporation system using 1 mm electroporation cuvettes (BTX, #45-0134). Briefly, 25
µL of BL21 cells were aliquoted to electroporation cuvettes and gently mixed with 1 µL of
plasmid DNA by tapping. Electroporation pulse was performed at 10 µF, 600 Ω, and 1800
V. Transformed cells were diluted in a 1.5 mL microcentrifuge tube with 975 µL pre-
82

warmed Expression Recovery Medium (Lucigen, #80030-1) and incubated at 37°C 1-hr
at 225 RPM. Volumes between 50-200 µL of transformed cells were spread on 15 g/L
agar (Amresco, #J637) plates supplemented with 25 g/L Luria Broth (LB) (Sigma,
#L3522) and 1x carbenicillin (Gold Biotechnology, #C-103-100) by aseptic technique.
Plates were incubated at 37°C until bacterial colonies appeared, which were individually
isolated in a 5 mL LB/carbenicillin culture. From each sample, 0.5 mL of turbid culture
media was taken and mixed 1:1 with glycerol and water, and stored as stocks in -80°C.
The remaining culture was incubated at 37°C

for 18-hr at 225 RPM and used to isolate
plasmid DNA with a QIAPrep Spin Miniprep kit (Qiagen, #27106). Transformed cell
plasmid DNA sequences were verified by Sanger sequencing (Genewiz, South Plainfield,
NJ) using a T7-F primers. Diagnostic digests with XbaI (NEB, #R0145S) or XbaI and
EcoRI-HF (NEB, #R3101S) were used to evaluate size of NDA loaded on a 1% agarose
gel (Invitrogen, #16500-500). Band sizes of 7900 bp, 5413 bp and 2487 bp were
simulated in Snapgene and confirmed by gel electrophoresis compared to a 1 kb DNA
ladder (NEB, #N3232S). DNA purity was verified by UV-Vis spectroscopy for a 260/280
ratio between 1.80-2.00 (Nanodrop, manufacturer). Stocks meeting quality control criteria
above were kept and used for subsequent steps.
4.3.2 X-5FA protein production and purification

X-5FA transformed stocks were grown in a starter culture of 50 mL LB
supplemented with 1x carbenicillin. After 8-hrs at 37°C

at 225 RPM, cells were transferred
to 950 mL LB and incubated in the same conditions and monitored until reaching an OD600
between 0.6-0.8 to start induction with 0.5x IPTG. After culturing at ambient temperature
for 18-hrs and 225 RPM, cells were centrifuged at 4500 xg for 15-min at 4°C. Cell pellets
83

were resuspended in 35 mL cold PBS (Genesee Scientific, #25-508) and sonicated on
ice for 3-min with a 10-sec on 20-sec off cycle. Cell lysate was supplemented with 0.5%
polyethylenimine (Sigma, #MKCK1840) and incubated on ice for 20-min with occasional
mixing. Cell supernatant was collected after centrifugation at 10K xg for 15-min at 4°C
and purified for ELPs as previously described by inverse thermal cycling (ITC)
4, 42
.
Briefly, each ITC cycle consisted of cell supernatant solution heated to 37°C and
spiked with 5 M NaCl in 1 M increments up to 2.5 M until precipitate forms. Precipitated
solution was then centrifuged at 10K xg for 12-min at 37°C and the supernatant was
discarded. The cell pellet was maintained on ice while resuspended by pipetting magnetic
stirring. After precipitate is resuspended, the solution was centrifuged at 16K xg and cell
and supernatant collected to repeat up to three ITC cycles for 95%+ purity. Absorbance
(OD380) was measured by nanodrop in a 1:4 mix with 8 M guanidine chloride (6 M final)
and used to calculate protein concentration using Beer’s law. Extinction coefficients were
calculated from protein sequence using the ExPASy ProtParam Tool (Table 4.1). After
ITC purification, a fraction of purified X-5FA was labelled using an NHS-rhodamine
labelling kit (Thermofisher, #46406). NHS-rhodamine was dissolved in DMSO (Invitrogen,
#D12345) and incubated with protein at a 3x molar excess overnight at 4°C. Unbound
rhodamine was removed by desalting using 7K MWCO Zeba Spin Desalting Columns
(Thermofisher, #89889) following manufacturer centrifugation protocol. Labelling
efficiency was calculated by measuring absorbance on nanodrop of rhodamine (OD555)
and protein (OD350). Purified ELP (5FA-Rh and X-5FA-Rh) was confirmed by gel
electrophoresis on a 4-20% gradient Mini-Protean TGX precast gel (Bio-Rad
Laboratories, #456-1095) loaded with 5 µg from each rhodamine-labelled sample and a
84

Precision Plus Protein Kaleidosope Protein Standard (Bio-Rad Laboratories, #1610375).
Bands were visualized by Bio-Safe Coomasie staining (Bio-Rad Laboratories, #1610786)
and fluorescent detection of rhodamine on an iBright FL1000 system.
4.3.3 Characterization of transition temperature (Tt)

Purified protein samples (5FA, W-5FA, L-5FA, P6-5FA, and P13-5FA) were diluted
to 5 µM, 2.5 µM, 1.25 µM, 0.625 µM, and 0.3125 µM in separate quartz Tm microcells
(Beckman Instruments, #523878). Absorbance (OD350) was measured on a Beckman
Coulter DU800 spectrophotometer at an analytical wavelength of 350 nm while heated
from 30 to 75°C by a temperature controller at a rate of 1°C /min. OD350 was sampled
every 0.3°C to calculate the first derivative of each curve to identify the Tt of each sample.
Data were transferred to GraphPad for visualization.
4.3.4 Characterization of nanoparticle radius by Size Exclusion Chromatography –
Multi-angle Light Scattering (SEC-MALS) and Dynamic Light Scattering (DLS)

For DLS, 50 µL of purified protein samples (5FA and X-5FA) were diluted to 5 µM
and filtered through low protein binding 0.2 µm filters (Pall Life Sciences, #4602) and
plated on a clear-bottom 384-well microplate (GreinerOne, # 82051-294) in triplicate. To
each well, 15 µL of mineral oil (Ward’s Science, #470301-505) was added to protect from
evaporation. Samples were incubated at room temperature and sampled on a Wyatt
DynaPro DLS plate reader. Data were used to measure the hydrodynamic radius (Rh).
For SEC-MALS, each protein was diluted to 10 µM in 500 µL of PBS and were passed
through a 0.2 µm filter. A Shodex protein KW-803 (8.0 mm ID x 300 mm) column was
equilibrated with PBS before introducing a BSA control at 5 mg/mL and samples above.
The control and samples were observed on three detectors for each separated fraction:
85

a SYC-LC1200 UV detector at 280 nm, a Dawn Heleos MALS detector, and an Optilab
rEX differential refractometer.
4.3.5 Exact mass determination by Matrix Assisted Laser Desorption/Ionization
Time of Flight (MALDI-TOF)

Purified protein samples were crashed out in a 1:6 acetone mixture at -20°C for 1-
hr, followed by centrifugation. The process was repeated 3x before air drying and
resuspension in 10 µL water. Sample was mixed with β-mercaptoethanol (Sigma-Aldrich,
#M6250) in a 1:3 ratio and boiled at 95°C for 15-mins before spotting with 2’,6’-
dihydroxyacetophenone (Sigma-Aldrich, #37468) on a MALDI-TOF target plate (Bruker,
#8280781) and air dried. Samples were measured on a raplifleX MALDI-TOF system.
Mass was calculated on Flex Analysis 4.0 software (Bruker Corp., Billerica, MA).
4.3.6 Rapamycin drug loading

Rapamycin powder (LC Laboratories, #R-5000) was dissolved in DMSO and
slowly added in 10x stoichiometric excess to X-5FA with continuous stirring at 4°C. After
30-min, samples were centrifuged at 13K xg for 15-min at 4°C

to remove free insoluble
rapamycin. The supernatant was subsequently dialyzed using X membranes with PBS at
4°C in a 1:300 volume ratio with buffer replenishment of at least 3x over the course of 24-
hr. Each X-5FA-rapamycin (X-5FA-R) sample were then passed through Acrodisc
®

Mustang
®
E Membrane filters (Pall Corporation, #MSTG25E3) at 4°C. To evaluate the
rapamycin loading efficiency, a standard curve was generated by reverse-phase high-
performance liquid chromatography (RT-HPLC) on a C-18 column with free-rapamycin
concentrations ranging between 500-1.95 µM. The area under the curve (AUC) for
sample peaks were measured and correlated to known rapamycin concentrations and
used to evaluate sample loading concentrations. Protein concentrations were then
86

compared to rapamycin concentrations and used to generate a loading ratio for each
sample (rapamycin µM/protein µM).
4.3.7 Mammalian cell culture

Mammary gland breast duct cells (BT474) (ATCC, #HTB-20) were cultured at 37°C
and 5% CO2 conditions in Hybri-Care Medium (ATCC, #46-X) supplemented with 10%
FBS (Corning Inc., #35-011-CV) and 1.5 g/L NaCHO3 (EMD, #SX0320-1) adjusted to a
pH of 7.2 with HCl. Media was replenished every 2 days and subcultured after reaching
80 to 90% confluence; briefly, cells were detached in minimal volume of pre-warmed
0.25% trypsin-EDTA (Gibco, #25200-056) for 5-min at 37°C and centrifuged to form a
pellet. Cells were resuspended in fresh media and passaged to a 75-cm
2
flask, 6-well,
12-well, or 96-well plates for assaying. Cells line stocks were stored in a 5% anhydrous
DMSO (Invitrogen, #D12345)/media solution at -170°C. Fresh cell stocks from the same
lineage were used for each experiment.
4.3.8 Flow cytometry and analysis

BT474 cells were seeded on two 6-well plates for cells with and without subtilase
cytotoxin A (SubA) treatment; SubA+ cells were treated with SubA media (Hybricare
media, +10% FBS, +0.2 µg/mL SubA) at approximately 50% confluence. Cells were
incubated at 37°C

until reaching 70-80% confluence and starved in SubA media (Hybri-
Care, -FBS, +0.2 µg/mL SubA) 24-hr before ELP treatment. SubA- cells were not treated
with SubA and were starved in standard Hybri-Care media (Hybri-Care, -FBS, -SubA) for
24-hr alongside SubA+ cells. Both group of cells were washed and treated with either
5FA-Rh or X-5FA-Rh at 5 µM, 5FA-Rh at 20 µM, or unstained, then incubated at 37°C for
3-hr. Cells were centrifuged and resuspended in 200 µL FACS buffer (PBS + 2% FBS)
87

and passed through a strainer (BD Biosciences, #352235) before data acquisition on a
BD Fortessa X-20. Instrument signal was gated using positive control (20 µM 5FA-Rh)
and an untreated negative control as references. Gating on FlowJo identified positive from
background signal, and singlets from doublets. Conditions were applied to all samples
and used to extract positive internalization events as a proportion of total. 100,000 sample
events were recorded for each treatment condition and analyzed on FlowJo (FlowJo LLC,
Ashland, OR) and Graphpad.
4.3.9 Western blot and analysis

BT474 cells were subcultured on 6-well plates (Genesee Scientific, #25-105) and
grown to 80-90% confluence. A dose-response assay was conducted by incubating with
either 0, 0.1, 1, 10, 100, or 1000-nM rapamycin, 5FA-R, or X-5FA-R (X = W, L, P6, or
P13) for 2-hr at 37°C in a 5% CO2 incubator. A kinetic assay was performed by incubating
cells with 1-nM of rapamycin, 5FA-R, or X-5FA for either 0, 15, 30, 60, or 120-min at 37°C

in a 5% CO2 incubator. For both experiments, media was aspirated and washed with 4°C

PBS before incubating with 100 µL RIPA buffer (Thermofisher, #89901) spiked with 1x
protease inhibitor (Thermofisher, #78442) on ice. Cell monolayers were manually
removed using a cell scraper (VWR, #10062-904) and vortexed before deep freezing in
individual microcentrifuge tubes at -80°C. After freezing for 1-hr, cells were thawed,
vortexed, and centrifuged at 13K xg at 4°C for 15-min. Protein was isolated in supernatant
and quantified using a Pierce
TM
BCA Protein Assay Kit (Thermofisher, #23227). Briefly,
albumin concentrations were generated from a standard (Thermofisher, #23209) against
protein samples quantified at OD562 in triplicate. Protein concentrations were quantified
and used to calculate 30 µg to load on a 4-20% gradient Mini-Protean TGX precast gel.
88

After separation, blots were transferred to a nitrocellulose membrane using an iBlot2 NC
stack (Invitrogen, #IB23001) on an iBlot 2 Dry Blotting System. Membranes were blocked
in 5% BSA (Sigma, #A9647) dissolved in 1x tris-buffered saline adjusted to pH 7.4 and
spiked with 0.1% tween-20 (TBST) (Santa Cruz Biotechnology, #sc-29113) for 1-hr at
ambient temperature. Membranes were then incubated in rabbit α-phospho-rpS6
(Ser235/236) (Cell Signaling Technology, #2211) diluted 1:1000 in 5% BSA overnight at
4°C with gentle shaking. After washing with 1x TBST in triplicate, membranes were
incubated with secondary α-rabbit IgG HRP-linked antibody (Cell signaling, #7074S)
diluted to 1:5000 in 5% BSA for 1-hr at ambient temperature. Blots were briefly incubated
in a 1:1 luminol and peroxide solution (Prometheus Protein Biology, #GSC-925-D10,
#GSC-929-D10) and immediately imaged on a ChemiDoc
®
to detect chemiluminescent
signal. Membranes were stripped using Restore
TM
Western Blot Stripping Buffer
(Thermofisher, #21059) for 15-mins at ambient temperature and washed in 1x TBST.
Membranes were re-blocked in 5% BSA and incubated in Ms α-GAPDH (Cell Signaling
Technology, #97166) and α-Ms IgM HRP (Cell Signaling, #7076S) chemiluminescence
repeating the protocol for phospho-rpS6 visualization. Raw data for the integrated density
of rpS6 phosphorylation was normalized to GAPDH using FIJI
24
. For each lysate, a
relative phosphorylation, frps6 was calculated as follows:
𝑓 𝑟𝑝𝑆 6
=
(𝐼 𝑟𝑝𝑆 6,𝑠𝑎𝑚𝑝𝑙𝑒 −𝐼 𝑏𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 )/(𝐼 𝐺𝐴𝑃𝐷𝐻 ,𝑠𝑎𝑚𝑝𝑙𝑒 −𝐼 𝑏𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 )
(𝐼 𝑟𝑝𝑆 6,𝑧𝑒𝑟𝑜 −𝐼 𝑏𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 )/(𝐼 𝐺𝐴𝑃𝐷𝐻 ,𝑧𝑒𝑟𝑜 −𝐼 𝑏𝑎𝑐𝑘𝑔𝑟𝑜𝑢𝑛𝑑 )
Eq. 4.1
Where Irps6,sample, Irps6,zero, IGAPDH,sample, IGAPDH,zero, and Ibackground are the integrated
densities from an ROI on each western blot over the rpS6 sample, sample at zero
(concentration or time), the GAPDH for each sample, the GAPDH at zero, and a
background ROI on the image respectively. Relative phosphorylation data was analyzed
89

on GraphPad (GraphPad, San Diego, CA) by comparing AUC of curves for each
formulation. Statistical significance was tested using global ANOVA of the log-
transformed AUCs followed by Tukey’s multiple comparisons test.
4.3.10 Confocal imaging and analysis

Poly-D lysine (Sigma, #P0899) treated cover slips (VWR, #483830-046) were
plated with BT474 cells in complete Hybri-Care media and cultured to 70% confluence.
Cells were starved without FBS for 24-hr before treatment with 5 µM of either 5FA, L-5FA,
or neither at 4°C for 1hr. Cells were either fixed or incubated at 37°C

for 3-hr and then
fixed as previously described
2, 46
; cells were fixed in 4% paraformaldehyde (Alfa Aesar,
#43368) and neutralized in 50 mM ammonium chloride (Alfa Aesar, #L05181). Cells were
permeabilized with triton X-100 (Sigma, #T8787) and then blocked in 1% BSA (Sigma,
#A9647) before an overnight incubation in 1:100 mouse α-ELP primary antibody at 4°C
23
.
Cells were then incubated in 1:100 chicken α-mouse AF647 secondary antibody
(Invitrogen, #A21463) overnight at 4°C before staining with 1x DAPI (Thermofisher,
#D1306). Cells were mounted in glass slides (VWR, #48311-703) in fluoromount
(Diagnostic Biosystems, #K024) and cured overnight protected from light at ambient
temperature. Cells were imaged at 630x in super-resolution (SR) on a Zeiss confocal
microscope in LSMFast mode in 3-dimensions using Nyquist sampling. Images were
deconvoluted by Airyscan processing in Zen 2 (Black Edition) and visualized in Zen 2
(Blue Edition) by orthogonal projection and 3-dimensional mesh reconstruction.
Acquisition settings remained consistent between for each temperature condition.
Internalization was quantified in FIJI by comparing total signal intensity within cells at each
treatment condition for comparison at each temperature condition.
90

4.3.11 Fluorescent degradation of 5FA and L-5FA

BT474 cells were seeded in 10% FBS Hybri-Care media on poly-D lysine treated
35-mm glass bottom plates (MatTek, #P35GC-0-10-C) and incubated until reaching 70%
confluence. Cells were starved for 24-hr and treated with 5 µM of either 5FA or L-5FA for
imaging by epifluorescent microscopy between 0 to 240-hr at different time points. Total
rhodamine fluorescence was measured after background subtraction and normalized to
number of cells per frame. Cells were counted as nuclei count, which were automatically
counted in FIJI using watershed segmentation from a binary image. Average fluorescence
was graphed in GraphPad.

91

4.4 Results and discussion

The goal of this study is to optimize the first csGRP78 targeted ELP-based carriers
for rapalogues by: 1) utilizing five FKBP domains to increase rapalogue loading capacity;
and 2) identifying a complementary peptide ligand for targeting csGRP78 relevant to

Figure 4.2: DNA quality control was verified to match by gel electrophoresis and
Sanger sequencing. A) The 5FA amino acid sequence is comprised of an FKBP-A24
sequence repeated 4x and capped with a 5
th
FKBP. The X-ligand at the N-terminus of
5FA makes X-5FA, substituted by either the W-, L-, P6-, or P13- ligands able to bind
GRP78. B) Cloned constructs were verified by gel electrophoresis with fragments
matching approximate expected sizes from after digestion by XbaI and EcoRI. As such,
the double digests shows the isolated 5FA or X-5FA insert (approximate 3200 bp) and
an empty plasmid vector (approximate 5500 bp). The size of vector is confirmed by the
inclusion of the empty pET25b vector control. C) Successful ligation of X-ligand to the
5FA backbone was further verified by Sanger sequencing using a T7-F primer. Distinct
ligands at the N-termini of 5FA were verified successfully with 100% query matching.

92

breast cancer (Fig. 4.2). Validating these parameters from a library of X-5FA candidates
was accomplished after their cloning, expression, purification, and physical
characterization by SDS, DLS, UV-vis, and MALDI-TOF. Their functional targeting was
evaluated in vitro by imaging, flow cytometry, and Western blot of downstream of
mTORC1 inhibition by rapamycin (rpS6) to assess their dependence on csGRP78
binding.
4.4.1 Plasmid DNA cloning and characterization

The first step in generating X-5FA constructs relied on a previously-reported 5FA
plasmid-encoded gene
9
, to which oligonucleotide cassettes were ligated that encode
several ligands for csGRP78 (W, L, P6, or P13) (Fig. 4.2A). These peptides were reported
to have high affinity to csGRP78
70
; however, it was unclear if fusion to the 5FA backbone
would have a detrimental effect on expression, solubility, or ligand binding to cell-surface
receptors. Plasmid DNA encoding 5FA were quality controlled by UV-Vis
Spectrophotometry, diagnostic restriction digestion, and Sanger sequencing. From
successful ligation products, we verified DNA band size using a double enzymatic
digestion to confirm they retain the full sequence for 5FA and X-5FA near 3.2 kbp (Fig.
4.2B). After confirming DNA quality and approximate band size, N-terminal Sanger
sequencing was used to verify correct sequence alignment of X-ligands upstream to 5FA
(Fig. 4.2C).
4.4.2 Expression and biophysical characterization of X-5FA constructs reveal
high purity and low aggregation

Purified DNA from correctly-matched sequences were subsequently cultured for
protein expression from ClearColi
TM
, which is an engineered cell line that produces a
truncated lipopolysaccharide. ELPs display temperature-dependent phase behavior that
93

were used for purification using sequential heating-and-cooling cycles, which yielded a
purity range between 90-98% with yields between 10-25 mg/L. After labelling with NHS-
rhodamine, band purity was verified experimentally by SDS-PAGE (Fig. 4.3A).
Bands run slightly higher than the expected values predicted in the open reading
frame (Table 5.2). When compared to X-5FA, 5FA runs subtly lower as expected,
Figure 4.3: Expression of 5FA and X-5FA were verified along with phase
behavior. A) 5FA and X-5FA constructs were purified by thermal cycling. The
approximate size and purity of ELP constructs were verified by SDS-PAGE. B) NHS-
rhodamine consistently labelled these ELPs, enabling fluorescent imaging. C) The
transition characteristics of 5FA and X-5FA were compared at 5 μM showing a slight
trend of lower Tt of X-5FA constructs relative to untargeted 5FA. D) Higher
concentration of all ELP constructs indicated an inverse relationship to Tt at a range
between 0.3-5 μM. Tt remained at physiological temperatures at all concentrations in
the tested range.
94

suggestive of successful ligand expression on 5FA. The W-5FA lane contained a
prominent band in the 250 kDa range of an unknown origin; however, it does not represent
a significant proportion of impurity relative to the total band intensity (Table 4.2). Each
construct shares sequence similarity through their 5FA domains with the only difference
attributed to the X-ligand. Using optical density, their phase diagrams were quantified as
a function of temperature and concentration. While there were small differences in Tt
between the fusion proteins, they followed no obvious trend, and all constructs are
expected to remain soluble within physiological temperatures (Fig. 4.3C). From this range
of concentrations, we can extrapolate that X-5FA will remain soluble at concentrations
relevant to cellular uptake (5 uM) and inhibition of mTOR (10 nM) (Fig. 4.3D), like previous
generation of FKBP-ELP formulations
8
.
After confirming the expression and purity of each 5FA formulation, we
characterized them by SEC-MALS, DLS, and MALDI-TOF (Fig. 4.4). For all five fusions,
SEC-MALS revealed that the majority of UV-Vis absorbance eluted from the column at a
retention time consistent with an ~100 kDa protein. In-line observation of this purified
peak revealed an absolute molecular weight on the order of a monomer, albeit slightly
Table 4.2. Biophysical characterization of 5FA constructs
5FA W L P6 P13
Expected MW (kDa)
1
95.7 97.2 97.6 97.7 97.7
MALDI-TOF MW (kDa)
2
95.5 97.5 97.7 97.6 97.9
SEC-MALS MW (kDa)
3
125.7 128.9 131.8 132.7 125.6
DLS Rh (nm) 3.75±0.77 3.51±1.13 3.83±0.62 5.03±0.17 3.66±0.27
SDS-PAGE MW (kDa)
4
104.8 108.7 115.5 115.1 113.5
SDS-PAGE Purity
5
0.98 0.93 0.98 0.98 0.90
1
MW calculated from open reading frame using Snapgene, version 5.3

2
MW calculated by MALDI-TOF using FlexAnalysis, version 4.0
3
MW calculated by SEC-MALS using Astra, version 6.1
4
MW of SDS band calculated in reference to ladder using ImageJ, version 1.51k
5
Protein band purity was quantified on ImageJ, version 1.51k
95

larger than expected (Fig. 4.4A). To clarify this ambiguity, MALDI-TOF was employed to
measure the exact mass, which clearly displayed clean spectra peaks A, B, and C,
Table 4.3: MALDI-TOF (M+XH)/X charge states

Charge state 5FA (Da) W (Da) L (Da) P6 (Da) P13 (Da)
(M+1H)/1 95527.9 97486.5 97657.5 97549.2 97852.3
(M+2H)/2 47684.5 48845.3 48976 48899 48904.7
(M+3H)/3 32178.1 32558.2 32606.2 32617 32485.6

Figure 4.4: The shape and molecular weight of each expressed 5FA construct
was characterized by SEC-MALS, DLS, and MALDI-TOF to validate and
corroborate their MW and radii. A) SEC separation yielded monomer fractions
between 8.0-8.4. B) The molecular weights of each construct and purity were by
MALDI-TOF, which show peaks at the appropriate location for each fusion (Table
5.2), accurate for m/z for single, double, and triple charge states. C) Their radii were
measured by DLS with virtually all samples falling below 10 nm to indicate their
solubility at 37°C; however, a small fraction of peaks was detected near 100 nm for
W, L, and P6-5FA.
96

representing (M+H), [M+2H]/2, and [M+3H]/3 for each formulation, respectively (Fig.

Figure 4.5: W-5FA and L-5FA undergo csGRP78 dependent cell association by
flow cytometry. Internalization of rhodamine-labeled W, L, P6, and P13 fused to 5FA
was evaluated in BT474 cells treated with and without SubA (0.2 µg/mL). A) An
unstained negative control was used to define a lower gating baseline for detectable
cell association, while an B) untargeted rhodamine-labeled control (5FA) at 20 µM was
used to define an upper gating baseline for higher cell association. C-F) Cells treated
with or without SubA were treated with X-5FA (5 µM). Cells treated with SubA were
indistinguishable from the negative controls. G) Untargeted 5FA (5 µM) internalization
is low relative to targeted X-5FA (low SubA effect). H) Signal below the upper baseline
(20 µM 5FA) was cutoff in samples A-G to clarify differences between groups.
Internalization of W and L-5FA were significantly higher than P6 and P13-5FA. Mean
± SD (n=3). *p<0.05, **p <0.005, ***p<0.0005, ****p<0.00005
97

4.4B). Calculated masses corresponded closely to their respective charge states (Table
4.3). To determine the hydrodynamic radius of these fusions in solution, DLS was
employed to confirm that the major species by mass had a radius close to that expected
for monomeric proteins, similar to 5FA (~4 nm) (Fig. 4.4C). Together, these data indicate
that these constructs remain freely dispersed in solution without forming significant
oligomers, which might have altered their receptor binding and cellular internalization.
4.4.3 csGRP78 association is assessed by flow cytometry

The next series of studies compared the biological functions of this library, with
respect to GRP78 targeting and mTOR inhibition. The first step was to determine the
relative efficacy of our targeting ligand to each other and to an untargeted control in the
absence or presence of SubA
72
, a protease known to cleave GRP78 between Leu(416)
– Leu(417)
73
. If targeted X-5FA became dependent on csGRP78 for internalization, this
would be revealed by a decline in internalization for cells treated with protease compared
to those without treatment (Fig. 4.5). Two internal controls were generated to compare a
lower (negative control) and upper signal baseline (untargeted rhodamine-labeled 5FA)
for comparison (Fig 4.5A-B). The difference in internalization between X-5FA constructs
with and without SubA is striking. After protease treatment, there was virtually no signal
in cells treated with SubA for all X-5FA constructs, which become indistinguishable from
the negative control. The proportion of cells with positive signal above the lower baseline
(negative control) was statistically significant for W, L, P6, and P13 after treatment with
SubA (Fig. 4.5C-F) but was not the case for untargeted 5FA. Internalization of 5FA was
low and minimally affected by SubA compared to any targeted X-5FA (Fig. 4.5G). To
assess which csGRP78 targeting ligand is more effective, signal above the 20 µM 5FA
98

upper baseline was compared (Fig. 4.5B), showing a significant difference between W-
and L-5FA compared to other conditions (Fig. 4.5H). Comparing W and L-5FA, we see
Figure 4.6. Rapamycin bound to W-5FA and L-5FA inhibit mTORC1 more
potently than untargeted drug. BT474 cells were treated with rapamycin at various
concentrations and times. Upon obtaining cell lysates, mTORC1 inhibition was
assessed by western blot of rpS6 phosphorylation (upper bands) using GAPDH as a
control (lower bands). The relative phosphorylation was estimated (Eq. 4.1). A-B) After
treatment at concentrations between 0-1000 nM for 120 mins at 37°C, Free
Rapamycin was effective at concentrations above 10 nM. In contrast, untargeted 5FA,
and W and L-5FA-rapamycin were maximally effective between 1-10 nM, ~ an order
of magnitude better. P6 and P13-5FA-rapamycin were the least effective, with
complete inhibition above 100 nM. C) The AUC was quantified for each curve and
compared against by ANOVA. Statistical significance was detected between Free
Rapamycin every other carrier formulation. D-E) Cells were next treated at 1 nM and
lysates were obtained after indicated incubations. W and L-5FA-rapamycin inhibited
mTOR almost completely by 120 min. F) To quantify this difference, the AUC under
the relative-expression vs. time curve were compared, which showed that only W-5FA
and L-5FA significantly decreased the AUC compared to free Rapamycin (n=3 per
group, **p<0.005). Mean ± SD.
99

roughly equivalent internalization.
While SubA failed to alter the uptake of unmodified 5FA, it was possible that SubA
would induce off-target effects downstream of GRP78 proteolysis. For example, on some
cell lines SubA induces endoplasmic reticular-associated degradation (ERAD) with
treatment concentrations of 1 ug/mL for 24- or 48-hr, which promoted apoptosis and
inhibited global protein synthesis
74
. In contrast, another report found no effects to
trafficking and toxicity after treatment with 1 µg/mL SubA for 72-hrs
73
. A third report
similarly found no toxicity to cells after treatment at 0.1 µg/mL for 48-hrs
69
. Either way,
the striking decrease of X-5FA internalization in cells treated with SubA relative to
untargeted 5FA internalization suggests cell-association for the entire library is csGRP78
dependent (Fig. 4.5).
4.4.4 Rapamycin encapsulated X-5FA inhibits mTORC1 signaling

After establishing that all X-5FA constructs successfully target csGRP78, we
hypothesized that the most effective carrier for rapamycin among them would suppress
mTORC1 more potently than free drug. Rapamycin, either free or bound to 5FA, is already
potent at a lower concentration (10 nM) than used above to assess cell-association by
flow cytometry (~5 mM). Many reports have described successful inhibition of mTORC1
via binding by rapamycin in diverse animal and cell models
75
. As such, we first assessed
a range of concentrations to find an optimal effective dose before taking a minimum
effective dose to assess their kinetics in BT474 cells (Fig. 4.6). Free Rapamycin was less
effective than targeted W- and L- 5FA-rapamycin, which began to show efficacy at
concentrations as low as 0.1 nM to 1 nM. Surprisingly, untargeted 5FA-rapamycin was
better than two of the targeted carriers (P6- and P13-5FA-rapamycin), with efficacy
100

manifesting only at 10 nM and above (Fig. 4.6A). P6-5FA-rapamycin and Free
Rapamycin were similarly effective at 10 nM and above while P13-5FA was only effective
at 100 nM and above. It is possible that an intermediate concentration below 100 nM
would be effective, but this is orders of magnitude above that required for either the W-
and the L-5FA-rapamycin formulations (Fig. 4.6B). To quantify this effect, the areas under
each curve (AUC) were compared by ANOVA/post-hoc testing to identify significant
differences between formulations (Fig. 4.6C). Rapamycin has been implicated in

Figure 4.7: GRP78 expression is attenuated after treatment with L-5FA-rapa in a
concentration dependent manner. After samples from a concentration-based assay
were imaged for rpS6 and GAPDH (Fig. 6A), the membrane was blocked with 5%
BSA and incubated with anti-BiP/GRP78 rabbit mAb (Cell Signaling Technologies Inc.,
Boston, MA, Part #3177) overnight at 4°C. A) Images were acquired after incubation
with anti-rabbit horse radish peroxidase and imaged on an iBright system. The relative
expression of GRP78 and rpS6 at each concentration were normalized to GAPDH and
quantified as a ratio to 0 nM. While rpS6 phosphorylation appears to significantly
decrease with increasing L-5FA-rapa concentration (~1 nM), GRP78 is marginally
affected beginning at (~100 nM). B) GRP78 appears to slightly decrease relative to
GAPDH, but not directly proportional to a decrease in rpS6 phosphorylation. The data
confirms reports in literature that suggest exposure to rapamycin affects mTORC1-
dependent expression of GRP78. This effect appears to be at a range beyond the
relevant therapeutic concentration for rpS6 phosphorylation.

101

modulating GRP78 via the mTOR axis. One report treated human neuroblastoma cells
with 10 nM rapamycin and found a decrease in rpS6 phosphorylation as well as a
decrease in GRP78 expression
76
. To probe this in the context of our assay, GRP78 was
interrogated after treatment with L-5FA-rapamycin at a range of concentrations (0, 1, 10,
100, and 1000 nM). While increasing L-5FA-rapamycin concentrations did have an
obvious effect on rpS6 phosphorylation, only a minor effect was noted for GRP78
expression (Fig. 4.7). At the therapeutically relevant concentration range in this assay,
GRP78 was not attenuated. From these data, we determined that a minimum
concentration of 1 nM was sufficient for lead candidates, W and L-5FA-rapamycin;
therefore, we further explored the kinetics of their mTOR inhibition by tracking
dephosphorylation of rpS6 over time. Since P6 and P13-5FA-rapamycin do not inhibit
mTORC1 at this concentration, they were omitted from this kinetic assay (Fig. 4.6D).
Consistently with the concentration-based assay, W and L-5FA-rapamycin showed the
fastest kinetic effect with 50% attenuation by 30-mins. In contrast, free rapamycin and
untargeted 5FA-rapamycin required 60-min to reach a similar level. By the 2 hrs, W- and
L-5FA-rapamycin were almost fully inhibited, while untargeted 5FA-rapamycin and free
Rapamycin showed higher levels of p-rpS6 (Fig. 4.6E). The AUC of each curve was then
used to compare their potency in triplicate. Only W- and L-5FA-rapamycin achieved
significantly lower AUC compared to Free Rapamycin. Other comparisons were not
significant (Fig. 4.6F). These results mirror the observations in the SubA flow cytometry
experiments that show both W- and L-5FA-rhodamine are better at targeting csGRP78
for internalization. While rhodamine-labeled carriers required much higher concentrations
102

to be detected by this flow cytometry, despite the nuances between experimental
approaches their differences are evident across a broad range of concentrations.
4.4.5 L-5FA significantly increases cellular exposure compared to untargeted 5FA

Functional differences between W and L-5FA are minor. For example, physical
characterization of both W and L-5FA by DLS and SEC-MALS show very similar particle
sizes and similar performance in internalization and mTOR targeting. From these
observations, L-5FA is only narrowly better than W-5FA; however, another consideration
is that purification of L-5FA by ELP-mediated phase separation delivered a significantly
better yield (24 mg/L bacterial culture). While both candidates provided clean final
samples (Fig. 4.3B), L-5FA expression was consistently 6-fold higher than W-5FA after
several purification cycles. As such, L-5FA was selected as a good candidate to visualize
its intracellular fate compared to 5FA (Fig. 4.8). We can infer from flow cytometry and
Western blot data that L-5FA is readily internalized compared to untargeted 5FA, so it
was not surprising to see a discrepancy in membrane binding by L-5FA-rhodamine at 4°C
compared to untargeted 5FA. An abundance of cell-surface L-5FA was detected without
noticeable signal on the inside of cells, indicating that L-5FA was only bound to the
membrane without internalization (Fig. 4.8A). At 37°C, cells treated with 5FA display
some internalization, but nothing comparable to the significantly higher amount of L-5FA.
Internalization was inferred as peri-nuclear signal within the cytosol. 5FA staining was
modest compared to L-5FA, which appears proportional levels of bound material
observed at 4°C (Fig. 4.8B). To compare the intracellular fate of each formulation, the
duration of cell-associated fluorescence was tracked over 10-days. Signal appears
constant over the first 16-hr for both, while displaying the expected differences in total
103

signal before dropping off after 36-hrs. Signal then begins to slowly decrease up to the

Figure 4.8: L-5FA significantly increases the cellular exposure compared to
untargeted 5FA by fluorescence microscopy. A-B) BT474 cells were treated with
5 µM of unlabeled 5FA or L-5FA and fixed at 4 and 37°C. Cells were visualized by 3-
dimensional super resolution laser scanning confocal microscopy. Targeted L-5FA
was present on the membrane at a higher abundance at 4°C as well as inside the cell
at 37°C, which are consistent with ligand-dependent enhancement of uptake
compared to 5FA. C) Degradation and/or export of the probe after internalization was
characterized in live cells by epifluorescence microscopy, which was quantified by
image analysis. Rhodamine-labeled 5FA and L-5FA were visualized in BT474 cells to
calculate average fluorescence per cell over time. These data show consistently higher
L-5FA cell association; furthermore, they suggest similar degradation kinetics between
both constructs. D) Although degradation kinetics appear to be similar, because L-5FA
starts at such an elevated cell-association, it yields a significantly higher exposure
(AUC) to the rhodamine probe over a 240-hr period (n=3 per group, *p=0.001).
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experimental endpoint at 240-hr (Fig. 4.8C). These data show that there is a significant
effect from the L-ligand over time, which supports the flow cytometry and Western blot
experimental data showing that csGRP78 targeting successfully biases this formulation
for internalization into BT474. Even after internalization, by comparing the area under the
curve (AUC) of both formulations, the relative exposure to drug carried by L-5FA was 8-
fold greater than that by 5FA (Fig. 4.8D). This is nearly an order of magnitude higher than
5FA, which may explain the potency enhancement found in the rpS6 dephosphorylation
assays (Fig. 4.6).
4.4.6 Broad implications of csGRP78 targeting in the context of cancer
therapeutics

The identification of csGRP78 has important implications for a broad spectrum of
cancers; furthermore, the results herein suggest that it may be generally enhance the
potency of small molecules that inhibit mTORC1 or other pathways. This manuscript
specifically demonstrates this effect using a protein-based carrier for rapamycin; however,
other strategies could also benefit from this approach to develop targeted drug carriers.
Recent examples include targeting of cells undergoing high levels of ER stress using a
csGRP78 antibody. The PAT-SM6 antibody binds csGRP78, which is tumor-specific and
directly induces a modest pro-apoptotic effect
77
. This led to a phase I clinical trial in
multiple myeloma relapse patients
78
; however, the efficacy of PAT-SM6 depends on
synergism with multiple cytotoxic agents like bortezomib and lenalidomide
79
. More
recently, another antibody formulation, Mab159 IgG, inhibited the PI3K/Akt axis in a
murine model, which was associated with caspase 8 and 9 mediated apoptosis
80
. Other
approaches targeting csGRP78 have relied on small peptides with high-binding affinities.
One study developed a targeting strategy with the W peptide by fusing it to SubA to cleave
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csGRP78, which was used as a basis for the flow cytometry work in this study
73
. Another
study encapsulated doxorubicin in a liposome formulation decorated with W-peptides.
This formulation inhibited proliferation of HUVECs activated along the ERK1/2 pathway
by vascular endothelial growth factor
81
. Other small peptides targeting csGRP78 have
been explored to target PEG-PLA nanoparticles that encapsulate paclitaxel. The
SNTRVAP peptide successfully targeted glioma cells
82
, while the GIRLRG peptide
successfully targeted an irradiated breast cancer cell line
83
.
Here, we’ve advanced the csGRP78 targeting toolset with an ELP-based system.
The flexibility of the ELP backbone has been explored in several therapeutic indications
using peptide-based targeting ligands. Notably, these include the Attachment Driven
Assembly of Micelles (ADAM) ELPs developed by Chilkoti and coworkers
84
, which are
assembled around a core of peptides covalently linked with hydrophobic small-molecule
chemotherapeutics. Drug conjugation to these ELPs leads to stable colloids, which have
can be further enhanced through protein ligands at their exterior, such as an anti-EGFR1
single-chain nanobody called EgA1
85
. Improvement of untargeted 5FA by addition of a
targeting ligand is supported by enhancements observed in previous generation FKBP-
ELP formulations. Inclusion of integrin targeting functionality into the FSI nanoparticle
increased its exposure to target tissues and led to successful tumor accumulation in an
MDA-MB-468 xenograft model even with a 3-fold less rapamycin concentration
4
, similar
to RGD and ICAM targeted formulations
4, 8, 64
. Here, we provide evidence in support of
csGRP78 targeting with a rapamycin payload to a broad population of cancer cell types
undergoing ER stress
67
. While we provide direct evidence in BT474 cells, the flexibility of
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the FKBP-ELP system allows it to be engineered for a variety of other therapeutic
indications with a diverse set of PK considerations.

107

4.5 Conclusion

This report is the first to confirm the viability of a targeted 5FA platform and
supports further development as a depot formulation targeting tumor tissue within range
of a subcutaneous injection. The enhancing effect of csGRP78 ligands play an important
role in the targeting of the soluble X-5FA that may further enhance rapamycin delivery in
a 5FV system as well. We have developed a next generation FKBP-ELP rapamycin
carrier that successfully targets breast cancer ductal cells (BT474) in a csGRP78
dependent manner. We show that this high-capacity carrier system can be loaded with
rapamycin and delivered to its intracellular target, mTORC1 to inhibit its downstream
substrate, rpS6. Incidentally, cancer cells are subjected to both extrinsic and intrinsic ER
stress, which constitutively upregulates GRP78 expression and its translocation to the
cell surface, opening an opportunity to potentially target a broad subset of cancer cells.
The results of this report support the development of a novel carrier system targeting
csGRP78 via a soluble 5FA system as well as other potential FKBP-ELP fusions.

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4.6 Sequences and tables

Supplemental Table S1: Full amino acid sequences of A24, FKBP, 5FA, and X-5FA
A24 (VPGAG24):
G VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG
VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG VPGAG
VPGAG VPGAG VPGAG VPGA
FKBP:
G
VQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRG
WEEGVAQMSVGQRAKLTI SPDYAYGATGHPGIIPPHATLVFDVELLKLE
5FA:
MGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVI
RGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATLVFDVELLKLEGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFKFMLG
KQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATLVFDVELLKLEGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFK
FMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATLVFDVELLKL
EGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRN
KPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATLVFDV
ELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSS
RDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATL
VFDVELLKLE
109

W-5FA:
MWIFPWIQLVPGAGMGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRD
RNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHATLVF
DVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFD
SSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHA
TLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGK
KFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIP
PHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLE
DGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGH
PGIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYT
GMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTI
SPDYAYGATGHPGIIPPHATLVFDVELLKLE
L-5FA:
MRLLDTNRPLLPYVPGAGMGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDS
SRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHAT
LVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKK
FDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPP
HATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLED
GKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHP
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GIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTG
MLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGAT
GHPGIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVV
HYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTI
SPDYAYGATGHPGIIPPHATLVFDVELLKLE
P6-5FA:

MRLLDTNRPFLRYVPGAGMGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFD
SSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHA
TLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGK
KFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIP
PHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLE
DGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGH
PGIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYT
GMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYG
ATGHPGIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTC
VVHYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTI
SPDYAYGATGHPGIIPPHATLVFDVELLKLE
P13-5FA:

111

MRLLDTNRPFLFYVPGAGMGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDS
SRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPPHAT
LVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKK
FDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHPGIIPP
HATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAG
VPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTGMLED
GKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGATGHP
GIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVP
GAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGV
PGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVVHYTG
MLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYGAT
GHPGIIPPHATLVFDVELLKLEGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGA
GVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVPG
AGVPGAGVPGAGVPGAGVPGAGVPGAGVPGAGVQVETISPGDGRTFPKRGQTCVV
HYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTI
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Chapter 6: Conclusions and future directions

My work spanning the last five years have exhibited some interesting applications
of ELPs as an emerging biotechnology platform. Here we show three distinct ELP projects
with fusions to functional proteins to modify and/or probe endogenous biological
pathways, or to target peptides against an oncology target as a novel drug delivery
application.
6.1.1 Higher throughput methodology is needed to validate ELP-switch
technology

In chapter 2, I showed that temperature-sensitive V96 can trigger the formation of
interesting vesicular structures (termed dynasomes) with an ability to 1) inhibit
EGF/EGFR endocytosis after dynasome formation that also 2) colocalizes with several
trafficking proteins. The implication of these findings are important to understanding
DNM2 biology and the substrates it may impact. Several open questions remain about
the involvement of DNM on different internalization pathways. Flotillin internalization
remains controversial with respect to its dependence on DNM, with different studies citing
contradictory involvement. These differences can be attributed to controversy on whether
flotillin is actually just an accessory protein that acts on several distinct processes. From
this perspective, the ability of DNM to act on it is dependent on what processes flotillin
acts as an accessory. This remains to be explored further and speaks to the importance
of development of technologies that can probe a broad set of endocytosis pathways.
ELP fusions like CLC-ELP, CAV1-ELP, and DNM2-ELP are the first-steps into
what could be a family of ELP-based tools to scale up assays that systematically explore
biological questions. Work on our fusions have relied on an imaging-based pipeline that
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can directly identify cells with positive expression, and with the aid of evolving and
sophisticated imaging/analysis platforms, can yield significant amounts of useful spatial
data
24, 26
. Algorithms have been developed to quickly identify cell boundaries and
determine whether contents have been internalized or remain bound to the cell
membrane, if at all. These results can help answer questions about how different
trafficking pathways respond to various stimuli in different cell lines to address questions
pertaining to disease and drug delivery. However, the scale at which data would need to
be generated would be limited by the bandwidth of the acquisition/analysis pipeline. To
mitigate this limitation, cell lines would be able to supplement imaging approaches by
increasing statistical power through higher throughput methods.
One example is the use of flow cytometry to assess internalization of a
fluorescently labelled ligand. Using controls for the different possible endpoints of a
ligand’s fate, the assay can test whether a substrate is internalized by comparing the
pulse shape analysis (PulSA). This quantifies the pulse width and height of a signal to
determine localization patterns within cells
86
. Using internal control, it can be determined
whether a probe is membrane bound, cytoplasmic, or internalized. These data can quickly
scale beyond imaging-based approaches with faster data turnaround that flip reliance on
imaging data as the primary dataset. Spatial imaging data is important as a confirmational
approach that can be used to validate higher-throughput methods, which can examine
cell counts orders of magnitude greater that the best imaging approaches. Development
of ELP-fusion cell lines would allow for experimental designs in 96-well plate formats that
can test the sensitivity of several substrates of several endocytosis pathways and yield
useful data on a faster time scale. ELP fusions to effector proteins necessary for their
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respective endocytosis pathways can be activated to challenge the internalization of
several substrates at different concentrations to determine their affinity towards specific
internalization pathways, which carries big implications for pharmaceutical drug
development and delivery.
6.1.2 Receptor tyrosine kinase fusions to ELPs can expand drug target
identification capabilities

In chapter 3, we used EGFR-ELP cell lines to explore the biology of heat activated
EGFR signaling, which is an important RTK in cancer signaling. These cells demonstrated
that they could mimic the signaling profile of cancer cells without the use of ligands.
Ligands like EGF or epiregulin can be used to activate signaling to initiate downstream
signaling pathways, often with distinct phenotypes that are determined by the stabilization
of dimers. EGF forms stable dimers between pairs that result in a transient cascade that
give rise to a proliferation phenotype. On the other hand, epiregulin forms weakly bonded
dimers that triggers sustained signaling downstream and a cell differentiation
phenotype
39
. The HEK-EGFR-ELP cell lines demonstrated an ability to trigger signaling
from a short heating interval, which we might presume to be closely related to the effects
of EGF/EGFR signaling. There might be some differences caused by clustering of EGFR-
ELP fusions, but our IPA analysis revealed that they share a statistically significant
similarity to EGF, ErbB, Her2, and ErbB4 signaling pathways. They share similar signaling
branches that validates the use of EGFR-ELP clustering as a model for drug target
discovery implications to all RTK signaling pathways. Similar to the idea of expanding
ELP-based tools to study endocytosis, developing a line of ELP fusion to RTKs bares the
potential to teach us more about their biology. For example, ErbB2 (HER2) has no natural
ligand aside from some artificially developed ones
87
. A HER2-ELP system could be a
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useful model to study HER2 without artificial ligands, primary cancer cells, or a HER2
expression cells line. A line of RTK-ELP fusions would allow for heat-activated clustering
that can activate signaling in several less-studied signaling branches. Different targets
can be challenged with candidate drugs to study their effectiveness relative to the RTK-
ELP signaling system used. Development of a wide array of RTK-ELP fusions stands to
improve the ability of researchers to study RTK signaling. Target identification can be
accomplished by mimicking the signaling that best correlates with the disease model of
interest, which may advance therapeutic development of diseases stemming from RTK
dysregulation.
6.1.3 Advancement of csGRP78 targeting ELPs

In chapter 4, we described advancement of FKBP-ELP technology and how each
generation offered improvements in rapamycin drug delivery. We demonstrated the ability
of a targeted 5FA carrier to inhibit mTORC1. The results support the use of csGRP78
targeting as an approach for ELP-based drug carriers. The target represents a versatile
targeting alternative that can be biased in a broad range of cancers, including
development of sustained release FKBP-ELP formulations. 5FV was shown to be a useful
carrier for rapamycin in an ocular disease model, which compared systemic untargeted
5FA to depot-forming untargeted 5FV and found better lacrimal gland targeting
9
. Our
report indicated that fusion of short peptide ligands greatly improve their potential ability
to target tumor tissue. We saw improvements over untargeted 5FA, which bodes well for
a novel 5FV formulation that when untargeted performed better than 5FA for ocular eye
delivery. The versatility of ELPs would allow for csGRP78 targeting ligands to other ELP
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formulations, including to diblock formulations that might be better suited to take
advantage of the enhanced permeability retention (EPR) effect.
Another area of interest is emerging data indicating a connection between SARS-
CoV-2 internalization and csGRP78. Recent data demonstrated spike protein receptor
binding domain (RBD) is recognized and internalized in a CME dependent manner
88
.
Cells were challenged with siRNA knockdown and chemical inhibitors to confirm a
dependence. Generally, it is accepted that SARS-CoV-2 RBD is recognized by the ACE2
receptor, but recent studies have demonstrated that csGRP78 can also recognize the
RBD and internalize it. Structural analysis showed similarities between a csGRP78 ligand,
Pep42 to the RBD, to explain experimental data suggesting a tight fit into the substrate
binding domain of csGRP78
89
. A bioinformatic analysis of the docking site between RBD
and csGRP78 recapitulated these findings with SARS-CoV-2 and other coronavirus
strains
90
. Given the above, the internalization pathway of the W- and L-5FA constructs
used in our assays would presumably enter through a CME-dependent process; however,
it is unclear if internalization would be similar due to the diversity in csGRP78 targeting
ligand sequences. Additionally, the FKBP-ELP formulation (FAF) was demonstrated to
enter cells through a macropinocytosis process without evidence of receptor
7
. It is
possible there are competing internalization pathways that are determined by kinetics of
individual pathways. Future studies could elucidate between internalization pathways to
potentially model how different X-5FA constructs are internalized. It would be of interest
to use ELP-switches tools to determine how a CME or DNM2 switch would test each
construct to determine their individual sensitivities.
6.1.4 ELPs as 3D biomaterials

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ELPs are biocompatible, biodegradable, and result in minimal immune response.
The VPGXG sequence can be modified to achieve desired biomaterial properties. Aside
from acting in a drug delivery capacity, ELPs have been engineered as biomaterials for
2D and 3D tissue scaffolds. A 2D matrix was deposited through ELP fusions with an-RGD
containing peptide from laminin α1 chain. Above their Tt, strong fibroblast cell attachment
was observed
91
. Another application designed ELPs to act as 3D scaffolds for
chondrocytes by trapping them above their respective Tt, which promoted
chondrogenesis. Additionally, this biomaterial was used as a scaffold for an extracellular
matrix and stem cells, which were then able to be differentiated into chondrocytes without
the need of growth factors.
92
Similarly, a vascular application was developed using
peptide as grafts to increase cell adhesion of vascular endothelial cells. The incorporation
of lysine residues into the ELP was able to improve cell-ELP interaction for better
adhesion.
93
Potential improvements to this concept can be achieved through the use of
3D bioprinting technologies, which remain largely unexplored in the ELP biomaterials
space. One group which was able to recapitulate building vascular scaffolds using an
elastin-like recombinamer as a bioink using an extruder deposition method.
94

ELPs have a broad potential of applications, ranging from scaffolds for 2D and 3D
tissue engineering, as intracellular tools to study biology, and as drug carriers. ELP
switches have been used to manipulate intracellular proteins to study their function. While
imaging has been a useful modality to explore ELP-based switches, their potential will be
realized with the use of plate-based assays that can probe large cell populations to
answer important questions about their relevant biology with confidence. ELP-based
carriers also have a broad potential of possibilities with manipulation of their sequence to
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alter their properties for efficient delivery of small molecule drugs. The application of
csGRP78 targeting ligands presents an exciting opportunity to delivery drugs on the ELP-
backbone, which may potentially lead to important breakthroughs to target cancer and
other diseases.

119

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Creator Avila, Hugo (author)

Core Title The modulation of dynamin and receptor endocytosis machinery using elastin-like polypeptides

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Pharmaceutical and Translational Sciences

Degree Conferral Date 2022-05

Publication Date 11/02/2022

Defense Date 02/23/2022

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

Tag dynamin 2,elastin-like polypeptide,epidermal growth factor receptor,glucose regulated protein 78,mammalian target of rapamycin,OAI-PMH Harvest,phase transition,rapamycin

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Language English

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Advisor MacKay, John Andrew (committee chair), Hamm-Alvarez, Sarah (committee member), Okamoto, Curtis (committee member)

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