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Mechanisms that dictate beta cells’ response to stress in the context of genetic mutation, pregnancy, and infection

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Mechanisms that dictate beta cells’ response to stress in the context of genetic mutation, pregnancy, and infection

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Content Mechanisms that Dictate Beta Cells’ Response to Stress
in the Context of Genetic Mutation, Pregnancy, and Infection
by
Katelyn Millette
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(DEVELOPMENT, STEM CELLS, AND REGENERATIVE MEDICINE)
May 2022
Copyright 2022 Katelyn Millette
Acknowledgements
Thank you to my mentor Dr. Senta Georgia for supporting me in more ways than just my
science. The way that you have encouraged me (and your other mentees) to take ownership of
our projects has made me confident to share my ideas and data interpretation in rooms with
scientists far senior to me. I could fill the page with gratitude towards you.
My committee members, who have given me valuable advice and guidance since day one of my
PhD. I am lucky to have you in my corner.
Thank you to My CHLA family, who let me borrow reagents, commiserate about the annals of
negative data, and for making me feel like I belong. To Dr. Mark Frey, for taking a chance on me
as both a PhD student and lecturer in your programs, and for my tough skin during presentations.
Dr. Anna Kamitikahara, Dr. Mohit Dave, and Dr. Esteban Fernandez for both your help with
experiments and your friendship. To my adoptive postdoc (now faculty) Dr. Cambrian Liu for
editing documents that got me here, taking on my sequencing analysis, career development
advice, and for sharing cheese. I technically have a lot of people to thank for sharing cheese with
me.
From my cohort, the overwhelmingly supportive girls’ group who made sure that no one felt
alone in their insecurities, failures, or celebrations in academia. A special thank you to Rosanna
Calderon for more than I can write here.
My family for being patient and understanding when I missed events, I wish I could have
attended.
ii
To Dr. Tod Lauer for all his support and perspective.
Thank you, Raul Figueroa, for helping me turn things I am nervous about into things I look
forward to. For spending numerous weekends in the lab, including part of Valentine’s day 2018
helping me get the first images of my patient’s cells making insulin. For imparting statistical
analysis knowledge on me. I couldn’t have dreamed up a better partner to have during my PhD.
My brother, Grae Matzek, for 13 years of pep-talks. I’m incredibly lucky to have you in my life.
To my Mom, who doesn’t care what degree I have or job I get as long as I am happy and
fulfilled. Thank you for letting me come to a new city all alone at 18 so I could become who I
am.
iii
Table of Contents
Acknowledgements ii
List of Tables v
List of Figures vi
Abstract viii
Chapter 1: Introduction 1
Diabetes Current Treatments and State of Research 1
Beta Cell Differentiation 3
Beta Cell Replication 6
Beta Cell Response to Viral Infection 7
References 9
Chapter 2: Severe NEUROG3 mutation underlies pancreatic endocrine 14
and exocrine insufficiency
Introduction
15
Results
16
Discussion
19
References
21
Materials and Methods
23
Figures
27
Supplemental Figures
33
Chapter 3: Exogenous lactogenic signaling stimulates beta cell replication 43
in vivo and in vitro
43
4 5
4 7
4 8
51
53
Introduction
Results
Discussion
Materials and Methods
References
Figures
Supplemental Figures
5 8
Chapter 4: SARS-CoV2 infects pancreatic beta cells in vivo and induces cellular 5 9
and subcellular disruptions that reflect beta cell dysfunction
61
62
6 7
6 9
75
7 9
Introduction
Results
Discussion
Materials and Methods
References
Figures
Supplemental Figures
84
Chapter 5: Future Perspectives
86
Part 1: NEUROG3 as a Pancreatic Progenitor Specifier
86
Part 2: Do SARS-CoV-2 infected beta cells recover, or die?
90
Part 3: Does Pregnancy Confer an Epigenetic Memory on Beta Cells?
91
References
References 96
List of Tables
Chapter 2
Supplementary Table 1. Small molecule concentrations for media stages 5 and 6. ............... ................3 9
Supplementary Table 2. List of Taqman probes used for qRT-PCR analysis. ....................... ................40
Supplementary Table 3. Antibody information used for immunofluorescent staining. .......... ................41
Supplementary Table 4. Antibody information used for flow cytometry. .............................. ................42
Chapter 3
Table 1. Experimental design and nomenclature of in vivo treatment groups. ............................. ...........53
v
List of Figures
Chapter 2
Figure 1. Generation of an induced pluripotent patient-specific NEUROG3
NULL
stem cell line and
isogenic mutation correction by CRISPR-Cas9 gene editing…………………………….....……..……..27
Figure 2. NEUROG3
NULL
cells have decreased expression of the pancreatic progenitor cell marker
NKX6.1. ……………………………………………………………………………………….…..….….28
Figure 3. NEUROG3
NULL
cells do not differentiate into beta-like cells in vitro. ……….…………..…..30
Figure 4. Exocrine pancreatic insufficiency may be a consequence of diminished pancreatic
progenitor cell competence. ……………………………………………………………………………...32
Supplementary Figure 1. Patient’s c-peptide measurements become undetectable over time................34
Supplementary Figure 2. NEUROG3
NULL
and NEUROG3
CORR
cells are karyotypically normal and
pluripotent. ………………………………………………………….………………………………....…35
Supplementary Figure 3. NEUROG3
NULL
and NEUROG3
CORR
pluripotent stem cells can
differentiate into all 3 cell lineages. ……………………………………………………………….….....36
Supplementary Figure 4. NEUROG3
NULL
and NEUROG3
CORR
lines differentiate into definitive
endoderm similarly. ……………………………………………………………………...………………37
Supplementary Figure 5. Exocrine pancreatic insufficiency may be a consequence of diminished
pancreatic progenitor cell competence. ………………………………..……………………………...…38
Chapter 3
Figure 1. Pseudopregnancy promotes beta-cell mass expansion in parous mice. …………….…..…….54
Figure 2. Pregnancy hormones induce beta-cell proliferation but not hypertrophy in mice. ….……..…55
Figure 3. E2 and PL induce STAT5 signaling in pseudopregnancy model. ………………...……….…56
Figure 4. In-vitro pseudopregnancy model promotes beta-cell replication in human islets and INS1E
cells. …………………………………………………………….........................……………………..…57
Supplementary Figure 1. Experimental design and nomenclature for in vitro treatment groups...........58
Chapter 4
Figure 1. SARS-CoV-2 directly infects beta-cells in vivo. ………..............................……..……..……79
Figure 2. SARS-COV-2 infection induces beta cell atrophy. ……….........................……..……..….….80
vi
Figure 3. Beta cells from SARS-COV-2 subjects are significantly degranulated. ……...….....…..…….81
Figure 4. Beta cells from SARS-COV-2 inoculated subjects have ultrastructural hallmarks
of beta cell stress. ………............................................................................................…………....……..82
Figure 5. Beta cells from SARS-COV-2-inoculated subjects have a glycolytic metabolic signature......83
Supplemental Figure 1. ACE2 expression in the Rhesus Macaque pancreas…………..…....…..…......84
Supplemental Figure 2. Fasting glucose & insulin measurements for control and post-acute subjects..85
Chapter 5
Figure 1. NGN3
NULL
line produces less pancreatic endoderm..............................................................87
Figure 2. NGN3
NULL
lines have NOTCH dysregulation...........................................................................88
Figure 3. SWI/SNF targets downregulated in NGN3
NULL
lines during early pancreogenesis..................89
vii
Abstract
Beta cells make up 1-4% of our pancreas, and loss or dysfunction of beta cells can be a catalyst for
diabetes. While there are a unique set of environmental and genetic factors that can predispose humans to
diabetes, all of these factors converge onto a common mechanism of pathogenesis: damage to the beta-
cell population, which does not recover. To improve public health and treatments related to diabetes, it is
therefore essential to understand key molecular pathways regulating beta cell differentiation,
regeneration, and susceptibility to injury. This dissertation studies primary examples of important
endogenous and exogenous regulators of the beta-cell population.
To understand how human beta cells differentiate, we studied the role of neurogenin-3 (NGN3).
We applied a beta-cell differentiation protocol that guides patient-specific induced pluripotent stem cells
to a pancreatic endocrine fate. To assess the requirement for NGN3 we isolated and differentiated stem
cells from a pediatric patient with a genetic form of diabetes caused by a mutation in NGN3. To generate
congenic control samples, we used CRISPR-Cas9 to correct the patient's mutation in vitro. While NGN3
is critical for beta-cell differentiation in mice, clinical and basic research data show that humans have
compensatory mechanisms of beta-cell differentiation that confers normal endocrine function during early
life. However, most NGN3-null patients lose beta-cell function and become diabetic during mid-
childhood. We found that this patient’s NGN3-null cells could not achieve proper endocrine
differentiation in vitro. Although NGN3 is classically believed to function only in the final stage of
endocrine differentiation, surprisingly, this patient’s NGN3-null cells also could not establish competent
pancreatic progenitor cells earlier in differentiation, resulting in a ten-fold decrease in the patient's
exocrine pancreas. These results support a novel function for NGN3 in early pancreatic progenitor
specification. Our in vitro work has been directly translated into patient care because we both predicted
the patient’s undiagnosed pancreatic insufficiency and were able to ameliorate their disease upon
therapeutic intervention.
viii
Beta cells rarely replicate as a response to injury or disease but do so rapidly during pregnancy.
The molecular mechanisms that regulate beta-cell replication during pregnancy are not fully understood
but leveraging these cellular processes might help create drug therapies to help push beta cells to replicate
in diabetic patients. While previous groups have relied on hormone receptor knockout and overexpression
transgenic models to study pregnancy-induced beta-cell replication, our models are the first to allow
researchers to investigate phenotypic changes induced by exogenous administration of the hormones
themselves, a clinically relevant modality. To understand how beta cells regenerate, we developed in vivo
and vivo models to study regeneration during pregnancy. We found that pseudopregnancy, induced by a
cocktail of hormones, resulted in beta cell replication in human islets in vitro and in parous mice in vivo.
Mechanistically, these cells induce STAT5 nuclear translocation resulting in beta cell replication.
In addition, we studied beta-cell responses to SARS-CoV-2 infection. While virus-induced
diabetes has been described in case reports and mouse models before, the limitations of collecting in vivo
human data have hindered our ability to understand the cellular and molecular mechanisms behind disease
progression. Here we used a novel in vivo non-human primate model and found that SARS-CoV-2-
infected beta cells are atrophied, have insulin degranulation, exhibit severe metabolic disruption caused
by unstructured mitochondria, and demonstrate reduced oxidative phosphorylation and increased
glycolysis. Importantly, although the subjects’ lung function returned to normal in the post-acute phase of
the disease, their beta cells became progressively more damaged and did not regenerate, suggesting that
the damaging effects of SARS-CoV-2 can persist in the pancreas after the acute respiratory infection.
In summary, this dissertation reveals fundamental new knowledge on the development,
regeneration, and viral susceptibility of pancreatic beta cells. Our hope is that this research will inspire
new avenues to help prevent and treat diabetes.
ix
Chapter 1: Introduction
Diabetes Current Treatments and State of Research
Glucose homeostasis is modulated by insulin and glucagon produced by beta and alpha cells on
the pancreas, respectively. The loss or dysfunction of pancreatic beta cells results in diabetes. Type 1
diabetes is the loss of functional beta cells and is due to autoimmune destruction of the beta cells.
Sometimes mature onset diabetes of the young (MODY) is miscategorized as type 1 diabetes, MODY is
result of genetic mutations that disrupt beta cell development and survival. In type 2 diabetes the body
either does not produce enough insulin, or the other cell types in the body resists insulin. Beta cell
dysfunction results from continuous beta cell stress; and these stressors can be things like poor diet or
exercise, illness, or an overall decrease in beta cell mass. Insulin restoration is key in treating any form of
diabetes.
While diabetes research has long centered around treatment options, because of the chronic and
extensive burden of disease, finding a cure and developing new prevention methods are of the highest
priority. There is a steady rise in diabetic patients each year. The International Diabetes Federation found
that 1 in 11 people have diabetes worldwide, and the greatest disease burden lies on low- and middle-
income individuals
1
. When access to lifesaving insulin injections, healthy food options, and educational
materials are unavailable, patients develop serious secondhand complications like diabetic ketoacidosis
(DKA), necrosis, heart disease, and premature death. Furthermore, there is an increased disease burden on
pregnant people with diabetes. Researchers have shown that offspring from these untreated pregnant
patients have an increased chance of being overweight and developing type 2 diabetes (T2D), creating a
vicious cycle.
While diabetes outcomes substantially improved upon the discovery of insulin, the field continues
to search for long term treatments that decrease the cost and secondary risks and increase life
expectancy
2
. Insulin injections are a powerful treatment for diabetes for those who can afford them, but
they have a short half-life, and some consider the multiple tests and injections invasive. One of the more
1
recent treatment options available to diabetic patients is the addition of a glucagon-like peptide-1 receptor
agonist (GLP1-RA) alongside standard insulin injections
3,4,5
. GLP1-RAs work by improving insulin
secretion; however, the inclusion of an additional pharmaceutical agent in a patient’s treatment regimen
incurs significant expense and burden.
The only long-term treatment options for patients with diabetes, whole pancreas transplantation
or a cadaveric islet transplant, are incredibly rare and not considered the standard of care. Clinical trials
have shown that only 40% of whole pancreas transplant patients are free of diabetes and diabetic
complications after five years
6,7
. Similarly, patients who receive islet transplantations have varying levels
of exogenous insulin independence
8,9
. The greatest contributor to the decline in insulin independence for
either whole pancreas or islet transplantation over time is autoimmune destruction of the islets
10
. While
some patients tolerate transplanted islets for over 15 years, others required as many as three
transplantation surgeries within five years
11,12
. As with any transplantation, the challenges of these
treatment options include the limited availability of tissue and the requirement for lifelong immune
suppression to avoid graft vs host disease. When these challenges are combined with their limited long-
term efficacy, these surgeries are not realistic options for pediatric patients.
Chapters Two and Three of this dissertation investigate mechanisms of beta cell differentiation
and regeneration. These studies are directly relevant to potential new cellular replacement therapies for
patients with diabetes. Induced pluripotent stem cell (iPSC) derived beta cells have been touted as a
solution to the problems observed in cadaveric islet transplants: iPSCs promise an endless supply of
donor islets, and the ability to genetically engineer the cells to evade immune destruction
10
. With a fuller
understanding of beta-cell differentiation pathways in vitro, including the expanded role of endocrine fate
specifiers such as neurogenin-3 (NGN3, also known as NEUROG3) in early pancreatic development
defined here, the field will be able to generate patient-specific beta-cell grafts with greater efficiency.
Another method of cellular replacement therapy could involve promoting the proliferation of existing beta
cells in vivo. The ability of pregnancy-related hormones to naturally induce beta-cell proliferation is
studied here; this could guide the development of therapeutic strategies that mimic these regeneration-
2
association signals. To develop robust and functional beta cell replacement therapies we must understand
how beta cells differentiate and replicate, and therefore must understand their developmental origins and
the gene expression patterns that govern them.
During development, the pancreas begins as two buds from the distal foregut endoderm. The
dorsal and ventral buds develop separately for 2-3 weeks in humans and expand their pancreatic
progenitor cell population
13
. All mature exocrine and endocrine pancreas cell-types originate from this
self-renewing pancreatic progenitor population marked by PDX1 and NKX6.1. Pancreatic progenitor
cells remain multipotent and in a state of self-renewal through Notch signaling; dysregulation of the
Notch pathway results in a depleted pancreatic progenitor pool. For this reason, the production of
pancreatic progenitor cells represents a critical stage in beta cell differentiation protocols, and many labs
have worked to improve the size and competence of this population
14–16
. The choice of whether to
differentiate or self-renew is governed by a lateral inhibitory network, in which cells with high Notch
activity downregulate NGN3, driving self-renewal, and neighboring cells with low levels of Notch
signaling upregulate NGN3, driving endocrine differentiation
17,18
. Endocrine progenitors with high levels
of NGN3 activate NEUROD1, which then activates insulin expression
19
. Cells that are negative for
NGN3 but expressing other cues become the exocrine tissue, responsible for secreting digestive enzymes,
or the ductal tissue, responsible for carrying the digestive enzymes to the duodenum.
Beta Cell Differentiation in Vitro
Due to the limited availability of early human embryonic tissues and ethical concerns, in vitro
induced pluripotent stem cell (iPSC) differentiation studies bridge the gap in our understanding of early
human pancreas development and allow us to glean insights into the molecular mechanisms that govern it.
Despite potential differences in source material, standard beta-cell differentiation protocols all activate
and inhibit the same major pathways and are approximately 28 days long
14–16
. Importantly, all protocols
mirror human pancreas development to the best of our understanding
20
. A current obstacle to using
3
patient-specific iPSC derived beta-cells as a cellular replacement therapy for diabetic patients is the lack
of mature beta-like cells by the end of the protocol. The original stem-cell derived beta cell protocols do
not respond to glucose until three months post-implantation in a mouse model, suggesting that they are
immature and that our differentiation protocols are incomplete
14
.
One way to increase the population of beta-like cells by the end of the differentiation protocol is
to purify the NGN3+ cell population, however this method is requires a fluorescent tag on NGN3, and is
thus not practical for the use in autologous cell transplantation
21
. A more accessible purification step can
occur at the pancreatic progenitor population by FACS sorting glycoprotein 2+ (GP2) cells. GP2 is a cell
surface marker produced specifically by pancreatic progenitor cells. Purifying these GP2+ cells resulted
in twice the number of cells becoming INS+ by the end of the protocol
22,23
. Additional protocols have
been published that help mature the beta cell population to become glucose responsive in vitro. One
method showed that simply differentiating the cells in 3D clusters to recapitulate both embryonic
development, and later, islet morphology promoted the maturation of stem cell derived beta cells
24,25
.
While this is an exciting finding, one caveat to clustering cells is the creation of a hypoxic environment in
the center of the cluster, leading to cell death. Another problem about differentiating cells while they are
in clusters is that the cells on the outside have more access to nutrients than the cells on the inside, and
therefore not all cells have the same signals. One method to mature the beta cells while they are
undergoing a planar differentiation is the addition of the small molecule H1152, a ROCKII inhibitor.
Ghazizadeh et. al. used H1152 during stage 6 of the Kieffer 2014 protocol and increased both the number
of beta cells and their maturation
26
.
Despite the pitfalls surrounding beta-cell maturity at the end of the protocol, researchers have
used these in vitro systems to uncover novel divergent roles of genes between human and rodent
pancreatic development
27
. More recently, researchers have used iPSCs as a tool to study genetic
mutations found in patients to understand the molecular mechanisms between genotype and patient
phenotype
28,29
. Danwei Huangfu’s group used both TALEN and CRISPR/Cas9 gene editing to delete
4
eight transcription factors (PDX1, RFX6, ARX, NGN3, PTF1A, HES1, GLIS3, and MNX1) from human
embryonic stem cells
30
. In contrast to the Wells study, the Haungfu NGN3-/- hESCs were able to
generate a small percentage of c-peptide+ stem cell derived beta cells. This suggests there are alternative
pathways to human beta-cell development that do not require NGN3, and that NGN3 is not just necessary
for endocrine differentiation, but also beta-cell maturation. This is a potentially divergent role of NGN3 in
humans and mice that could only be elucidated with the use of gene editing. More recently, the same
group used human pluripotent stem cells to investigate how haploinsuffiency of GATA6 impairs human
pancreatic progenitor formation and has identified a dose-dependent requirement for GATA4 in pancreatic
progenitor cell formation
28
. Taken together, these studies support the use of human pluripotent stem cells
as a model for investigating genetic basis of human pancreatic, endocrine, and beta-cell differentiation. It
will be interesting to see if iPSCs from patients with these genetic mutations exhibit the same phenotypes
as the CRISPR/Cas9 models and if they can be corrected and used as isogenic stem cell derived beta cells
capable of restoring glucose homeostasis.
Another example of this comes from human iPSC studies from cell lines that are derived from
patients with mutations in NGN3. NGN3 accumulation marks a critical developmental timepoint for beta
cell differentiation, but mouse and human studies have shown divergent requirements for the protein.
While Ngn3 null mice die hours after birth, human patients display a wide range of phenotypes based on
the severity of their mutation and its impact on the function of the protein
18,31,32
. Patients with amino-
acid substitutions in NGN3 develop diabetes, and endocrine-specific disease, while patients with non-
functional proteins display both endocrine and exocrine clinical phenotypes
29
. Clinical presentations of
both endocrine and exocrine dysfunction suggest that NGN3 has an unexplored role in pancreatic
organogenesis upstream of endocrine specification in humans. These studies validate that beta cell
differentiation protocols are a powerful tool both clinically and for basic science research.
Using a unique combination of two published protocols (Rezania 2014 and Stem Cell
Technologies), I demonstrate in Chapter Two that iPSCs derived from a NGN3-deficient diabetic patient
5
exhibit fundamental defects in early pancreatic endoderm and progenitor differentiation. These early
progenitor defects resulted clinically in both endocrine impairment and exocrine pancreatic insufficiency.
This in vitro work has been directly translated into patient care. This finding, and the mechanisms that
underlie it, cannot be modeled in mice due to developmental differences between the two species.
Moreover, these findings suggest that fine-tuning the patterns of NGN3 expression and protein function in
early pancreatic development could improve the yields of pancreatic differentiation protocols, with
relevance to cellular replacement therapies.
Beta Cell Replication
While our iPSC studies are aimed at cellular transplantation therapies to treat diabetes, another
potential therapy is replicating the patient’s existing beta cells in vivo. Beta-cell replication is rare; the
two physiological phases during which our bodies experience the greatest increase in beta cell mass are
development and pregnancy
33
. These increases in beta cell mass are triggered by different stimuli.
Developmental beta-cell mass expansion occurs via pancreatic progenitor cell replication mediated by
Notch signaling; subsequent accumulation of NGN3 results in exit from the cell cycle and transcription
of endocrine-related genes
26,27,34,35,
.
During pregnancy, the expectant mother is highly insulin resistant This insulin resistance is the
result of many factors including adipose tissue, placental growth, and pregnancy hormones, one of which
is the insulin blocking effects of placental lactogen
36
.To respond to the new metabolic demands of
pregnancy, beta cells must undergo multiple rounds of expansion, involution, and regeneration
36,37
.
Mouse models demonstrated that beta-cell replication in pregnancy occurs when placental lactogen binds
to prolactin receptor (Prlr). The resulting signaling cascade induces the translocation of Stat5 to the
nucleus and the transcription of target factors important for beta cell survival, function, and proliferation
38–41,42
. The failure to expand beta cell mass (BCM) during pregnancy results in gestational diabetes,
which affects 1 in 6 pregnancies worldwide
1
. However, safety concerns and ethical protections for
pregnant women and the fetus complicate our ability to understand the mechanisms that govern beta-cell
replication during human gestation.
6
In Chapter Three, we present in vivo murine and in vitro human models of the pregnancy milieu.
These models represent novel methods to study beta cell proliferation in response to pregnancy-related
hormones. We believe these models can be used to create and test new therapies that expand beta-cell
mass in vivo.
Beta Cell Response to Viral Infection
Preventing patients from developing diabetes is equally as important as finding a cure. However,
to prevent the disease we need to understand the types of environmental exposures that can injure beta
cells and the stages and molecular cascades underlying beta cell dysfunction. These insights may help
determine the best ways to stop further destruction of the beta cell population. One way to study diabetes
disease progression is by modeling virus-induced diabetes.
One of the first groups to demonstrate that viral infection could result in diabetes did so by
isolating a Coxsackievirus B4 virus from a pediatric patient who had new onset diabetes and diabetic
ketoacidosis, and inoculating mice with the virus
43
. They found that 50% of the infected mice rapidly
developed diabetes and found both immune infiltration of islets and necrosis of the pancreas.
Interestingly, some mice were protected from the onset of diabetes, an observation that translates to the
human population as well. Since then, researchers have tried to understand how viruses can induce beta
cell stress and trigger autoimmune cascades leading to beta-cell destruction
44–47
. Beta-cell stress and
dysfunction are characterized by decreased beta cell mass due to apoptosis or de-differentiation,
decreased insulin secretion due to beta cell atrophy or aberrant intercellular trafficking, and decreased
metabolic output by mitochondria including a metabolic shift away from oxidative phosphorylation
48–50
.
Relevant to the COVID-19 pandemic during which I write this dissertation, the SARS-CoV-1 and
2 viruses have disproportionately affected diabetic patients. Specifically, these patients exhibit worsened
symptoms of SARS or COVID-19, increased incidence of diabetic complications during infection, and
higher mortality rates
51–53
. While retrospective studies on patients with SARS showed worse outcomes in
diabetic patients, there were no studies to determine whether the virus acted directly on beta cells or
7
whether it acted by triggering autoimmune destruction
51,52
. Recently, case reports have described a
subset of patients with COVID-19 who present with new onset diabetes and diabetic ketoacidosis (DKA),
a life-threatening complication that results from the body breaking down fats for energy in the absence of
insulin
54,27
. These reports suggest that these SARS-family viruses may affect glucose homeostasis, and
therefore provide researchers with an additional tool to study mechanisms of beta-cell stress and injury.
In Chapter Four we used non-human primates infected with SARS-CoV-2 to study the
pathogenesis of new onset diabetes. We found severe metabolic changes to infected samples and observed
hallmark signs of beta cell stress and dysfunction that worsened over time. Importantly, we show that this
phenotype is a result of direct infection of beta cells. By electron microscopy we see disruptions in both
the mitochondrial and endoplasmic reticulum (ER) ultrastructure. While we were the first to show these
ultrastructural aberrations in beta cells, the SARS-CoV-2 S protein has been shown to tether to the ER
and uses it to create double membrane vesicles
56
. In silico and protein studies have demonstrated that the
5′- and 3′-untranslated regions of SARS-CoV-2 contained mitochondrial localization signals, and
that multiple SARS-CoV-2 proteins interact with mitochondrial activity proteins
57,58
. One such protein
is ORF9b, which localizes to the mitochondria and results in mitochondrial elongation and the
accumulation of reactive oxygen species
59,

60
. These findings, while not in beta cells, offer insights into
the cellular mechanisms that sarscov2 disrupts. Our novel model system can be used to not only to
understand the stages of COVID19, but also to understand the stages of beta cell stress and to determine
whether vaccination, or other disease-mitigating strategies, prevent diabetes.
Our lab studies the ways in which beta cells develop, replicate, and respond to injury so that we
can harness these intrinsic mechanisms and help create therapies for the treatment and prevention of
diabetes. Our translational approach to research has already had a direct impact on patient care. Because
each chapter in this dissertation focuses on a different aspect of beta cell biology, each chapter has its own
research question and significance to public health.
8
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9
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DOI: https: /doi.org/10.21203/rs.3.rs-456539/v1
License: @ C This work is licensed under a Creative Commons Attribution 4.0
International License.
14
Preprints are preliminary reports that have not undergone peer review. They
should not be considered conclusive, used to inform clinical practice, or
referenced by the media as validated information.
Katelyn Millette, USC
Yuhua Zheng, CHLA
Kyle Vogt, USC
Cambrian Liu, CHLA
Juliana Austin, CHLA
Shengmei Zhou, CHLA
Marin Martin, UCLA
Senta Georgia, CHLA
Severe NEUROG3 mutation underlies pancreatic endocrine and
exocrine insufficiency
Abstract
Patients with NEUROG3 mutations suffer from diabetes mellitus due to pancreatic
endocrinopathy and chronic malabsorptive diarrhea due to enteric endocrinopathy. We have identified a
severe truncation mutation in NEUROG3 (P39PfsX38) that results in pancreatic exocrine insufficiency
and significantly contributes to chronic malabsorptive diarrhea. We identified this novel phenotype by
interrogating induced pluripotent stem cells from the NEUROG3-P39PfsX38 patient's fibroblasts and an
isogenic "wild- type" control cell line generated via CRISPR-Cas9 gene editing. We discovered that
NEUROG3- P39PfsX38 lines failed to activate pancreatic progenitor and differentiated lineage markers,
suggesting that the mutation may disrupt pancreatic organogenesis and could result in endocrine and
exocrine dysfunction. Isogenic corrected cell lines differentiated into all pancreatic lineages. Clinical
assessments concluded that the patient has exocrine pancreatic insufficiency. Treatment with pancreatic
enzyme replacement therapy improved patient outcomes, including weight gain, fat absorption, and
resolution of fat-soluble vitamin deficiency. These results expose a novel role for NEUROG3 in human
pancreatic differentiation and illustrate how patient-specific stem cells can be used to interrogate
disease etiology and affect patient care.
Main Text
Patients with NEUROG3 mutations suffer from diabetes mellitus due to pancreatic
endocrinopathy and chronic malabsorptive diarrhea due to enteric endocrinopathy. The role of
NEUROGENIN3 (NEUROG3) as a master regulator of pancreatic and intestinal endocrine differentiation
has been modeled in detail using transgenic animals and human embryonic stem cells
1-8
. Animal
models with biallelic deletions of Neurog3 have no pancreatic or enteric endocrine cells and die within
hours after birth. Human embryonic stem cell models of NEUROG3-independent differentiation have
concluded that very few pancreatic endocrine cells can differentiate in the absence of NEUROG3, and
these differentiated cells are likely not functional
1,7,9,10
. In contrast, patients with NEUROG3 mutations
15
develop insulin-dependent diabetes, with onset ranging from 13 days to >23 years of age
11
. Patients also
develop severe generalized malabsorptive diarrhea that fails extensive dietary challenges in the
immediate postnatal period. It is thought that the clinical phenotypes are less severe than the deletion
models because the hypomorphic clinical mutations retain some functionality lost in the null model
systems.
We identified a 16-year-old male with a biallelic frameshift mutation in the NEUROG3 gene
(c117delC; P39PfsX38) that resulted in a truncated protein that is functionally null for any biochemical
activity
12
. At 2 weeks of age he was diagnosed with malabsorption and was temporarily managed with
parenteral nutrition. At nearly 3 years of age, he was admitted with a blood glucose of >600 mg/dL and
diagnosed with diabetes. He was negative for islet autoantibodies and his c-peptide levels declined over
time (Supplementary Fig 1). Immunohistochemical staining of endocrine cells on the subject's duodenal
biopsy was negative, confirming the null phenotype of the patient's mutation (Figure 1A). The contrast
between the phenotype of null model systems and our biochemically null P39PfsX38 subject's clinical
presentation suggests that the molecular mechanisms by which NEUROG3 regulates human pancreatic
cell differentiation are complex and require further investigation.
We created induced pluripotent stem cells (iPSCs) from the subject's fibroblasts to investigate
how the P39PfsX38 mutation affected pancreas differentiation. Native iPSC clones were referred to as
NEUROG3
NULL
. We replaced the mutated single exon of NEUROG3 with a wild-type copy of the exon in
the endogenous gene locus using CRISPR-Cas9 cellular engineering (Figure 1B)
13
. Corrected clones were
sequenced to verify biallelic correction of the mutation and were referred to as NEUROG3
CORR
(Figure 1C).
NEUROG3
NULL
and NEUROG3
CORR
iPSCs had normal karyotypes, expressed pluripotency markers, and had
low expression of common lineage markers (Supplementary Figure 2A-D). NEUROG3
NULL
and
NEUROG3
CORR
cells appropriately expressed endoderm, ectoderm, and mesoderm markers when
subjected to lineage-specific differentiation protocols (Supplementary Figure 3).
To identify the developmental stage at which the NEUROG3-P39PfsX38 mutation disrupted
16
human pancreas differentiation, we assessed the cell fates of NEUROG3
NULL
and NEUROG3
CORR
cells at
key steps of a reproducible beta cell differentiation protocol
14
. Both cell lines differentiated into
definitive endoderm at similar rates (Supplementary Figure 4). Next, we assessed the differentiation of
mature, competent pancreatic progenitor cells by the co-expression PDX1 and NKX6.1
15,16
.
Immunocytochemical staining and flow cytometry established that NEUROG3
NULL
cells differentiated
into similar numbers of PDX1 cells as NEUROG3
CORR
cells, but significantly fewer PDX1

/NKX6.1
competent pancreatic progenitor cells (9% vs 24% by flow cytometry, respectively, n=6, p<0.001; Figure
2A-B). Quantitative PCR confirmed that the expression of PDX1 was similar in both cell lines, but
NEUROD1 expression, a NEUROG3-dependent transcription factor, was significantly decreased in
NEUROG3
NULL
cells (Figure 2C, p<0.05, n=4). Expression of the NEUROG3-independent pro-endocrine
gene MAFB was unchanged (Figure 2C).
To understand the global impact of the P39PfsX38 mutation on the differentiation of pancreatic
progenitor cells, we assessed the RNA-transcriptome of NEUROG3
NULL
and NEUROG3
CORR
pancreatic
progenitor cells. We normalized the expression profiles against pluripotent H1 embryonic stem cells.
As expected, pluripotency genes were enriched in the H1 cells, whereas genes involved in endodermal
fate commitment were similarly enriched in both NEUROG3
NULL
and NEUROG3
CORR
cell lines. However,
the expression profiles of NEUROG3
NULL
and NEUROG3
CORR
cells diverged among genes associated with
the pancreatic progenitor cell fate (Figure 2D).
Next, we attempted to differentiate both NEUROG3
NULL
and NEUROG3
CORR
cell lines into the
pancreatic beta-like cell lineage (BLCs) (Figure 3A). Immunocytochemistry revealed that NEUROG3
NULL

cells could not generate significant numbers of BLCs in vitro, while NEUROG3
CORR
cells differentiated
readily (Figure 3B). Rare NEUROG3
NULL
endocrine cells were polyhormonal and did not coexpress c-
peptide and NKX6.1, (Figure 3B)
15,16
. We quantified the number of c-peptide cells present in both the
NEUROG3
NULL
and NEUROG3
CORR
BLCs.
17
Less than 1% of NEUROG3
NULL
BLCs were c-peptide

, while 22.24% of NEUROG3
CORR
BLCs were c-peptide
(Figure 3C, p<=0.02, n=5). INS transcripts were very low in NEUROG3
NULL
BLCs, but were highly expressed
in NEUROG3
CORR
BLCs (Figure 3D, p<0.001, n=3-5). We measured the insulin secretory index, which is the
ratio of insulin secreted at high glucose and low glucose, in NEUROG3
NULL
and NEUROG3
CORR
BLCs
cultured as 3D clusters for 3 days in vitro using a static glucose-stimulated insulin secretion assay. We
then transplanted clusters under the kidney capsule of NSG mice to facilitate maturation. After 12 weeks,
we measured human insulin levels in the plasma of mice that were fasted then subjected to a glucose
challenge (Figure 3E). Before transplantation, neither NEUROG3
NULL
nor NEUROG3
CORR
cell clusters
appropriately increased insulin secretion in response to glucose (see pre- implant bars, Figure 3E). 12
weeks after transplantation, NEUROG3
CORR
cells mounted a mature human insulin secretory response to
glucose, while NEUROG3
NULL
cell response was still immature (see post- implant bars in Figure 3E).
Because NEUROG3
NULL
iPSCs did not differentiate efficiently into BLCs and did not express mature
pancreatic progenitor cell markers, we hypothesized that these cells might have a diminished capacity to
differentiate into the pancreatic exocrine lineages. To this end, we assessed exocrine differentiation.
NEUROG3
CORR
cells were able to differentiate into acinar and ductal cells, while far fewer NEUROG3
NULL

cells were positive for the exocrine lineages (Supplementary Figure 5). This raised the possibility that the
patient's mutation might compromise pancreatic progenitor cell contribution to organogenesis in vivo and
that the subject may have undiagnosed exocrine pancreatic insufficiency (EPI). Chronic malabsorptive
diarrhea is a shared clinical manifestation of enteric anendocrinosis and EPI. EPI's formal diagnosis
includes chronic malabsorptive diarrhea, low fecal elastase levels, and diminished exocrine secretory
response to hormone stimulation. Diagnostic secretin-enhanced magnetic resonance
cholangiopancreatography (MRCP) of the subject's pancreas indicated it was hypoplastic (Fig 4A,
Supplementary video 1). Quantification of pancreatic volume from MRCP revealed a 5-fold decrease in
18
the patient's pancreatic volume index compared to the average index of age-matched control subjects
(Figure 4B). The patient's fecal elastase level was very low and exocrine pancreatic function tests
(EPFT) revealed decreased exocrine pancreatic enzyme levels after secretin stimulation (Figure 4B)
17-19
.
The subject was diagnosed with clinical EPI and started pancreatic enzyme replacement therapy (PERT)
to treat EPI. He demonstrated weight gain, fat absorption, and resolved fat-soluble vitamin deficiency
with PERT treatment.
Discussion
The assumption that NEUROG3 is essential but not required for human pancreatic endocrine
differentiation has evolved from studies that concluded that most clinically relevant NEUROG3
mutations are hypomorphic and has been supported by clinical reports indicating that affected subjects
have some residual pancreatic endocrine function for varying lengths of time
1,9,11,20
. The novel
NEUROG3- P39PfsX38 mutation that is the subject of this study

results in a truncated protein with no
functional activity; therefore these experiments served as an opportunity to interrogate the molecular
and clinical consequences of a truly "null" human phenotype
12
. Our study has concluded that the loss of
NEUROG3 function has consequences upstream of endocrine differentiation and is important in the
pancreatic progenitor cell population during organogenesis.
Prior studies of NEUROG3 have mostly limited its role as a master endocrine transcription factor
for the pancreas and the intestine. Mouse studies have concluded that the competence of Neurog3 cells
can change over time. It has been shown that Neurog3 cells can contribute to all pancreatic lineages early
in development. As organogenesis progresses, Neurog3 cells are specified and required for endocrine
lineage differentiation. The delamination and formation of NEUROG3-endocrine islet structures are
important for exocrine branching morphogenesis late in development, but does not affect exocrine
differentiation
7,10,21
. Our data suggest that NEUROG3 plays a role in human pancreatic progenitor
competence and is critical for differentiation into both the endocrine and exocrine compartments.
19
While some of our results mirror reports that NEUROG3-deficient embryonic stem cell lines
cannot make mature pancreatic endocrine cells in vitro
1,3,9
, we are the first to show that transplantation of
NEUROG3
NULL
cells under the kidney capsule results in minimal BLC maturation. This suggests that in
vivo maturation creates a milieu that can facilitate NEUROG3-independent pancreatic endocrine
maturation in a manner that in vitro protocols cannot recapitulate. This may explain why patients with
NEUROG3 mutations are born with some functional pancreatic endocrine capacity but lose the capacity to
secrete insulin over time; insufficient and immature NEUROG3-null beta cells may lose the capacity to
produce minimal c-peptide as metabolic demands for insulin increase with body mass and age.
Taken together, we conclude that our patient-specific iPSC model revealed that NEUROG3 is
essential for human pancreatic progenitor cell competence. It is possible that EPI may result from a
fundamental defect of pancreatic progenitor cell competence in patients with severe NEUROG3
mutations. Clinically, malabsorptive diarrhea due to the underlying enteric endocrinopathy may mask the
possibility that EPI significantly contributes to diarrhea. Our observation is also supported by a report
documenting that other patients with NEUROG3 mutations have hypoplastic pancreas
11
. Thus, patients
with NEUROG3 mutations should be routinely screened for hyperglycemia and EPI and prescribed
insulin and enzyme replacement therapy as appropriate.
Acknowledgments
We would like to thank Esteban Fernandez and the CHLA Molecular Imaging Core for assisting
with images acquired and analyzed for this manuscript. We would like to thank the Grikscheit Lab at
CHLA for their technical assistance with transplantation surgeries. We would like to thank Annie Wu of
the Bridges to Stem Cell Careers program at Pasadena City College, Andrew Salas of the Stem Cell Core at
CHLA and Chang Tong of the Chang Stem Cell Engineering Core at the Broad Stem Cell Center of USC for
their technical assistance with the derivation and propagation of the iPSC lines used in this study.
M.G.M is supported by DK083762, DK41301, DK085535 and DK118640. S.G. is supported by the Larry
20
L. Hillblom Foundation, The Harvey Family Foundation, The Paul Lester Foundation, the California
Institute for Regenerative Medicine DISC1-08868, and The Saban Research Institute.
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22
Methods
Human Subjects
All studies were approved and completed in accordance with CHLA Institutional Review Board. Skin
fibroblasts were collected from the patient and reprogrammed into induced pluripotent stem cells using a
vector-free approach
22
. To generate a corrected control cell line, we used CRISPR-Cas9 to excise the gene by
targeting guide RNAs to the single exon of NEUROG3 and designed a HDR plasmid to facilitate
homologous recombination of a wild-type copy of NEUROG3 into the endogenous gene locus (see Figure
1B)
13
. Clones were sequenced to verify the correction of the mutation and excision of the selection gene
(see Figure 1C). Experimental results are expressed using independent differentiations from a minimum
of 2 independent clones per line.
MRI analysis
Pancreata were manually outlined in each MRI plane with ImageJ software. Pancreas volume was 3D
reconstructed and quantified with Arivis Vision4D v2.12.3 software.
Human Pluripotent Stem Cell Culture and Differentiation
The stem cell core at Children's Hospital Los Angeles provided the H1 embryonic stem cell line,
licensed from WiCell. All human pluripotent stem cells were cultured using feeder-free conditions on
plates coated in Vitronectin (StemCell Technologies) or Geltrex (Gibco) and fed with mTESR complete
media (Stem Cell Technologies). Differentiation of planar hPSCs was initiated when the cells reached
90% confluency using the STEMdiff Pancreatic Progenitor (Stem Cell Technology cat#05120) to
produce pancreatic progenitor cells. Cells were subjected to differentiation cocktails from Rezania et al.
to progress through the pre-endocrine and immature beta-like cell stages
23
.
Karyotyping
G-band karyotyping was performed on two clones per genotype. Banding method (resolution): g-banding
23
(500~550) number of cells counted: 20, number of cells analyzed: 20, number of cells karyotyped: 5.
RNA Isolation and qPT-PCR
RNA was extracted using Invitrogen Ambion RNA purification kit (#AM1924). cDNA was generated
using Takara Primescript RT Master Mix (#RR036A). Taqman Gene Expression Master Mix (#4369016)
and the AP biosystems gene expression probes and Step One real-time PCR machine. H1 pluripotent cells
were used as a relative quantitative reference. GAPDH was used as the housekeeping gene. The entire
probe list can be found in Supplementary Table 2.
RNA sequencing
RNA was extracted using Invitrogen Ambion RNA purification kit (#AM1924) and samples sequence by
Quick Biology Inc. FASTQ files corresponding to the pancreatic progenitor stage from NGN3NULL and
NGN3CORR samples were pseudoaligned, using kallisto
24
, to the human transcriptome to obtain
transcript per million (tpm) abundance estimates. To compare expression levels of selected genes,
abundance estimates were merged with archived transcriptomic profiles (series GSE41009 on the NCBI
Gene Expression Omnibus) of H1 embryonic stem cells
25
. A linear normalization factor was computed
from the median values in the distribution of abundance estimates across all transcripts from H1 cells
and our NGN3-targeted cell lines. To select genes related to pluripotency, endoderm specification, and
pancreatic differentiation, gene ontology pathways corresponding to these keywords were manually
merged and curated. The resulting subset of abundance estimates was filtered to exceed an absolute log2
fold change of >0.3 of differential expression and scaled before generating heatmaps in R.
Flow Cytometry Analysis
Cells were dissociated with TrypLE and DNAse, and stained with fixable viability dye 450 (BD) in
dPBS with Y27632 (72304) for 12 minutes and washed 2x with PBS 0.2% BSA. Single cells were fixed
24
with fixation/permeabilization buffer from BD (#554722) and washed 2x with Perm/Wash buffer
(#554723). Cells were stained with stage-specific conjugated antibodies overnight in wash buffer and
washed 2x with PBS 0.2%BSA, resuspended in PBS 0.2%BSA and analyzed on LSRII at the Saban
Research Institute Flow Cytometry Core. Approximately 10,000 cells were analyzed per sample. Plots
were analyzed on Flowjo version 10. Cells were gated to exclude debris, non-single cells, and non-viable
cells. A list of flow antibodies and their dilutions is found in Supplementary Table 3.
Immunocytochemsitry
8-well chamber slides were washed with PBS and fixed with 4% PFA in PBS for 15 minutes. Chambers
were washed 3x with PBS and left in PBS sodium azide at 4 degrees until ready to stain. Cells were
permeabilized with TBS 0.4% triton for 20 minutes and washed with TBS tween for 3 minutes. Chambers
were blocked with 0.2% Tween 20/3% IgG-free BSA/Tris-buffered solution for 30 mins at room temp.
Primary antibodies were incubated overnight in 4C. Chambers were washed 2x with TBS tween.
Secondary antibodies were applied at 1:500 for 30 minutes at room temperature. Chambers were washed
with TBS tween 2x and TBS 1x. Slides were mounted with DAPI mounting media (Vector Labs) and
imaged. All images were acquired at the TSRI imaging core. A list of primary antibodies and their
dilutions is found in Supplementary Table 4.
Kidney Capsule Transplantation
All animal studies were approved and completed in accordance with CHLA Institutional Animal Care
and Usage Committee. 8-12 week old NSG mice were anesthetized and prepped for surgery using aseptic
techniques. Dermal and muscle incisions exposed the kidney. The kidney was lifted out of the body
cavity using forceps and a 27G butterfly needle was used to inject beta-like cell cluster or human islets
under the kidney capsule. The kidney was reinserted into the body cavity and the muscle and dermal
layers sutured. Animals were given analgesic relief and monitoring post-surgery.
25
Hormone Content and Metabolic Analysis
Glucose Stimulated Insulin Secretion
In vitro GSIS was performed on beta cell-like clusters with two technical replicates per
differentiation. N=3-4 independent differentiations per cell line. GSIS was performed as previously
described.
Human plasma Insulin Assay
12 weeks post transplantation of beta-like spheres under the kidney capsule, mice were fasted overnight.
Blood glucose was measured using a standard glucometer. Mice were injected with 3mg/kg glucose.
Serum was collected in silicone-coated serum gel tubes (BD Microtainers 365967) before glucose
injection and 30 minutes post-injection. Serum samples were kept on ice and centrifuged for 3 minutes at
10,000 g. Serum was stored at -20
O
C until analysis.
Insulin Concentration
GSIS and plasma samples were analyzed for insulin content using Alpco's Ultrasensitive Insulin Elisa
kit (80-INSHUU-E01.1).
Statistical Analysis
Experiments were carried out at least three times and presented as the average values ± SD. Statistical
analyses were performed with GraphPad Prism (GraphPad Software). The difference between
samples was compared by the two-tailed Student's t-test and was considered significant at p < 0.05.
26
Figures
Figure 1. Generation of an induced pluripotent patient-specific NEUROG3NULL stem cell line and
isogenic mutation correction by CRISPR-Cas9 gene editing. (A) Immunohistochemistry of duodenal
biopsy specimens from the subject and age-matched control. Chromogranin A staining (brown), a
marker for endocrine cells, is absent from the subject's sample. (B) Targeting strategy for CRISPR-
mediated gene editing. (C) Sanger sequencing of select clones for NEUROG3NULL and
NEUROG3CORR cells indicated the biallelic correction of the P39Psfx38 mutation.
27
Figure 2 NEUROG3NULL cells have decreased expression of the pancreatic progenitor cell marker
NKX6.1. (A) Immunocytochemistry of pancreatic progenitor cells for PDX1 (red) and NKX6.1 (green)
in NEUROG3NULL and NEUROG3CORR cells. PDX1 levels are consistent between the cell lines, but
28
NKX6.1 is decreased in NEUROG3NULL cells. (B) Quantification of flow cytometry shows that
NKX6.1 PDX1 competent pancreatic progenitor cells are decreased in NEUROG3NULL cell line. n=6. (C)
Quantitative PCR to measure gene expression for PDX1 as a pancreatic progenitor marker, NEUROD1 as a
NEUROG3- dependent pre-endocrine marker, and MAFB as a NEUROG3-independent markers. n=6-8.
(D) Heatmap of select pluripotency, endoderm, and pancreatic progenitor gene expression. n=2 per cell
line. Data normalized to pluripotent H1 cells. ***p<0.001.
29
Figure 3
30
Figure 3. NEUROG3NULL cells do not differentiate into beta-like cells in vitro. (A) Schematic of the
differentiation protocol. The PancDiff kit from Stem Cell Technologies was used to differentiate
pluripotent stem cells to the pancreatic progenitor cell stage. Protocols from Rezania et al. (2014) were
employed to differentiate pancreatic progenitor cells into BLCs. (B) Representative
immunocytochemistry images of the BLC stage for PDX1 (red) and NKX6.1 (green) in NEUROG3NULL
and NEUROG3CORR cells. PDX1 levels are consistent between the cell lines, but NKX6.1 is decreased in
NEUROG3NULL cells. (C) Quantification of flow cytometry experiments indicates fewer differentiated
c-peptide cells from the NEUROG3NULL cell line. n=5. (D) Quantitative PCR to measure INS gene.
expression. n=3-5. (E) Glucose-stimulated insulin secretion and plasma insulin assays indicate that
NEUROG3NULL cells do not have a mature secretory response to glucose challenge in vitro (pre-
implantation) or in vivo (post-transplantation). n=3-5, *p<0.05, **p<0.01, ***p<0.001.
31
Figure 4. Exocrine pancreatic insufficiency may be a consequence of diminished pancreatic progenitor
cell competence. (A) Amylase (green) and Cyotkeratin19 (red, marker for ductal cells) is are decreased in
NEUROG3NULL cells when compared to NEUROG3CORR cells differentiated into the exocrine lineages.
MRCP images of the subject and age-matched control. Control subject clinical characteristics are fall
within the normal reference range stated within the literature. (B) Clinical measurements of subject and
32
age-matched normal controls (values referenced in the literature, 21-23). All measures of exocrine
pancreatic morphology and function are abnormally low.
Supplementary Files
This is a list of supplementary files associated with this preprint. Click to download.
SuppVideo.mov
SupplementaryInformation.docx
33
34
Supplementary Figure 1: Patient's c-peptide measurements become undetectable over time.
Measurements of subject's random fed insulin levels during regularly scheduled clinical visits.
35
Supplementary Figure 2: NEUROGNULL and NEUROGCORR cells are karyotypically
normal and pluripotent. (A) Karyotyping of representative clones of induced pluripotent stem cell
lines created for this study. (B) Flow cytometry plots for OCT3/4 and SSEA4 expression in iPSC
lines. n=6. (C) Expression of markers for mesoderm (MESP), endoderm (SOX17), and ectoderm
(OTX2) show comparably low expression relative to pluripotent H1 embryonic stem cells
maintained under the same experimental conditions n=6-8.
36
Supplementary Figure 3: NEUROG3NULL and NEUROG 3CORR pluripotent stem cells
can differentiate into all 3 cell lineages. Gene expression for SOX17 (endoderm), OTX2
(ectoderm), and PECAM (mesoderm). After lineage-specific induction protocols, the
expression of lineage-specific genes are increased relative to undifferentiated H1 embryonic
stem cells n=2-6, and includes 2 technical replicates per independent differentiation.
37
Supplementary Figure 4: NEUROG3NULL and NEUROG3CORR differentiate into
definitive endoderm, similarly. (A) Flow cytometry for SOX17 and CXCR4 expression.
Quantification between lines shows there is no significant difference in the definitive endoderm
population between the two lines. n=8. (B) Immunocytochemsistry for sox17 (RED) shows
uniform staining of cells in both NEUROG3NULL and NEUROG3CORR cell lines.
38
Supplementary Figure 5: Exocrine Pancreatic insufficiency may be a consequence of diminished
pancreatic progenitor cell competence. Amylase (green, marker for acinar cells) and Cytokeratin19
(red, marker for ductal cells) are decreased in NEUROGNULL cells when compared to
NEUROG3CORR cells.
Supplementary Table 1: Small Molecule concentrations for media stages 5 and 6
Small Molecule
Concentration Manufacturer Identifier
ALK5 Inhibitor II 10 µM Enzo ALX-270-445
g-Secretase Inhibitor
100 nM Millipore Sigma
565789
Heparin 10 µg/ml Sigma H3149
ITS-X 1:200 ThermoFisher 51500056
LDN193189 100 nM Stem Cell Technologies 72144
Retinoic Acid 0.05 µM Sigma
R2625
SANT1 0.25 µM Tocris 1974
T3 1 µM Millipore Sigma 64245
Zinc Sulfate 10 µM Sigma z0251
39
Supplementary Table 2: List of Taqman probes used for RT-PCR analysis
Gene Assay ID
CHGA Hs00154441_m1
CXCR4 Hs00607978_s1
GAPDH Hs99999905_m1
GCG Hs00174967_m1
INS Hs00355773_m1
ISL1 Hs00158126_m1
MAFB Hs00534343_s1
MESP1 Hs00251489_m1
NANOG Hs02387400_g1
NEUROD1 Hs00159598_m1
NGN3 Hs00360700_g1
NGN3 Hs01875204_s1
NKX6.1 Hs00232355_m1
OCT4 Hs01895061_u1
OTX2 Hs00222238_m1
PAX4 Hs00173014_m1
PAX6 Hs00240871_m1
PCSK1 Hs01026107_m1
PDX1 Hs00236830_m1
PECAM1 Hs00169777_m1
SOX17 Hs00751752_s1
40
Supplementary Table 3: Antibody information used for
immunofluorescent staining.
Antibody Dilution Manufacturer Identifier
rat anti-CPEP 1:50 DSHB GN-ID4-s
mouse anti-Glucagon 1:250 Sigma G2654
guinea pig anti-
Insulin
1:500 DAKO A0564
mouse anti-NKX6.1 1:50 DSHB
F55A10-
s
rabbit anti-OCT4 1:400
Cell Signaling
Technology
2840
goat anti-PDX1 1:200 R&D AF2419
goat anti-SOX17 1:250 R&D AF1924
41
Supplementary Table 4: Antibody information used for flow cytometry.
Antibody
Dilutio n
Manufacturer Identifier
AF 488 Mouse IgG1 k Isotype
Control
1:10 BD Biosciences 557721
AF 647 Mouse IgG1 k Isotype
Control 1:10 BD Biosciences 557714
PE Mouse IgG1 k Isotype Control 1:20 BD Biosciences 554680
rat anti-CPEP (unconjugated) 1:20 DSHB GN-ID4-s
PE Mouse anti-Human CD184 1:20 BD Biosciences 555974
Fixable Viability Stain 450 1:1000 BD Biosciences 562247
AF 647 Mouse anti-NKX6.1 1:10 BD Biosciences 563338
AF 488 Mouse anti-OCT3/4 1:10 BD Biosciences 560217
AF 488 Mouse anti-PDX1 1:10 BD Biosciences 562274
AF 647 Mouse anti-SOX17 1:10 BD Biosciences 562594
AF 647 Mouse anti-SSEA-4 1:20 BD Biosciences 560796
42
Chapter 3
Exogenous Lactogenic Signaling Stimulates Beta Cell Replication In
Vivo and In Vitro
Abstract
Because patients recently diagnosed with T1D and patients with T2D have residual beta cell mass, there
is considerable effort in beta cell biology to understand the mechanisms that drive beta cell expansion as a
potential cellular therapy for regenerating patients’ lost beta cells. Both mouse and human studies have
established that beta cell mass expansion occurs rapidly during pregnancy. To investigate the mechanisms
of beta-cell mass expansion during pregnancy we developed novel in vivo in vitro systems of
pseudopregnancy. Our models demonstrate that pseudopregnancy promotes beta-cell mass expansion in
parous mice, and this expansion is driven by beta-cell proliferation rather than hypertrophy. Importantly,
estradiol, progesterone, and placental lactogen induce STAT5 signaling in pseudopregnancy model,
demonstrating that this model successfully recapitulates pregnancy induced beta cell replication. We then
created an in vitro model of pseudopregnancy and found that the combination of estradiol and placental
lactogen induced beta cell replication in human islets and rat insulinoma cells. Therefore, beta cells both
in vitro and in vivo have an increase in proliferation when subjected to the pseudopregnancy cocktail
compared to groups treated with estradiol or placental lactogen alone. The pseudopregnancy models
described here may help inform novel methods of inducing beta cell replication in patients with diabetes.
Introduction
During pregnancy, the expectant mother is highly insulin resistant. This insulin resistance is the result of
many factors including adipose tissue, placental growth, and pregnancy hormones, one of which is the
insulin blocking effects of placental lactogen
1
. To respond to the increased metabolic demands of
pregnancy, female beta cells must undergo expansion; over the course of a lifetime, multiple pregnancies
mean that female beta cells must undergo multiple rounds of expansion and evolution. While the increase
43
in maternal blood glucose aids fetal growth, failure to sufficiently expand functional beta-cell mass can
result in gestational diabetes (GD), thereby complicating the pregnancy and delivery. Women have a 2-
9% chance of being diagnosed with gestational diabetes during their first pregnancy, however the risk
changes during subsequent pregnancies
2
. If the mother was not diagnosed with gestational diabetes
during her first pregnancy, the risk of GD drops significantly with her second pregnancy. However,
women previously diagnosed with GD have up to 63% (depending on compounding risk factors) risk of
GD reoccurrence
3,4,5
. These clinical data suggest that beta cells that successfully adapted to insulin
demands during a previous pregnancy are able do so again during additional pregnancies. Therefore, it is
imperative that we understand the mechanisms that regulate beta cell expansion during pregnancy.
Exploiting these mechanisms could have a significant impact on developing therapies to expand beta cells
in vivo for patients with all forms of diabetes.
The mechanism of human beta cell expansion during pregnancy is debated in the field, and
research is limited to in vitro islet culture and epidemiological studies on mothers with SNPs in PRLR
6,7
.
Mouse models have concluded that increases in maternal beta cell proliferation are mediated by
lactogenic signaling via prolactin (PRL) and placental lactogen (PL) through the prolactin receptor
(PRLR).Overexpression of PRLR in mouse beta cells stimulates beta-cell replication and increases beta-
cell mass, while insufficient lactogen signaling restricts the capacity of beta cells to expand during
pregnancy resulting in gestational diabetes
8
. Mechanistically, PRL binds to PRLR and activates STAT5
signaling; this increases the transcription of factors important for beta cell proliferation, function and
survival
9, 10
. While there is in-vitro evidence that PL levels are responsible for the increase in insulin
secretion observed during human pregnancy, the mechanisms behind these findings remain largely
unstudied
10, 11
.
While the models of PRL overexpression and PRLR activation have been informative, their
conclusions are confounded by multiple factors in the endogenous pregnancy milieu.
8,

12, 13,

14,

15
. For
instance, litter size dictates exposure to PL expression during pregnancy, making it impossible to titrate
PL concentrations in vivo to understand how PL activates PLR signaling in vivo. The chemical induction
44
of pregnancy standardizes PL exposure and allows the accurate comparison of treatment groups
16
. To
leverage the natural BCM expansion seen during gestation, we created novel in vitro and in vivo that
replicate the hormonal milieu of pregnancy. We developed a model of the hormonal pregnancy milieu by
administering a cocktail of estradiol (E2), progesterone (PR), and placental lactogen (PL). We repeated a
variation of this hormone cocktail in vitro using rat INS1 cell line and dispersed human islets from
healthy female donors. Beta cells both in vitro and in vivo showed an increase in proliferation markers
when subjected to the pseudopregnancy cocktail. Here we show that these models can be used to answer
mechanistic questions about beta-cell replication and the beta cell’s response to pregnancy.
Results
Pseudopregnancy promotes beta-cell proliferation in multiparous mice in-vivo
Estrogen, progesterone, and placental lactogen rise and fall throughout pregnancy to stimulate physiologic
support for the mother and fetus. Interestingly, human islets treated with E2 alone has been shown to
protect the islets from cell death whereas treating with PL alone increases BrdU incorporation and insulin
secretion in both female and male human islets
11,17
. To better understand the synergistic effect of these
hormones on beta cell adaptation during pregnancy, Estradiol (0.5mg) and Progesterone (10mg) tablets
were surgically implanted subcutaneously on day 0, and from days 7-10 mice received two injections of
PL per day. Mice were sacrificed on day 11 (Table 1). We used eight treatment groups in total to
understand the requirement for E2 and PL during beta-cell mass expansion of both parous and nulliparous
mice, a description of which can be found in table 1.
To assess whether our pseudopregnancy model mimicked the effects of natural pregnancy on
islets, we quantified beta-cell area from both parous and nulliparous female cohorts. Controls from
nulliparous and parous mice had no significant difference in beta cell area. The beta cell area of
nulliparous mice treated with the cocktail was not statistically different from untreated control mice.
Parous mice treated with the pseudopregnancy cocktail (PEP) however had almost a twofold increase in
beta cell area compared to treated nulliparous mice (Figure 1). To assess whether the increase in beta cell
45
area was due to proliferation or beta-cell hypertrophy, we stained histological sections with either insulin
and the replication marker Ki67 or insulin and E-cadherin (Figure 2). Histological analysis confirmed that
the increase in beta cell area was due to the proliferation of beta cells. Parous pseudopregnant mice had a
163.7% increase in proliferation compared to the nulliparous control. We also saw increases in
proliferation with the addition of E2 and P in both nulliparous and parous females; however, these
increases in proliferation do not translate into increased beta-cell mass except in the PEP cohort. These
proliferation increases may suggest that either the replicative cells are not maintained or there is
incomplete replication. Beta-cell hypertrophy was quantified by measuring cell area as marked by E-
cadherin; examples of beta-cell area analysis can be found in figure 2D. There was no significant
difference in beta-cell area between pseudopregnant groups (Figure 2). Parous mice who did not have an
induction of pseudopregnancy had a statistically significant smaller beta-cell area than all other cohorts.
Many studies have shown that adaptive beta-cell proliferation is mediated by PRL stimulating
PRLR. When PRL binds to PRLR, the downstream target genes important for beta-cell proliferation,
function, and survival are upregulated. This is mediated through STAT5 activation and translocation into
the nucleus.
18

19
. To understand if the increase in beta cell proliferation was mediated though this pathway
in our pseudopregnancy model, we performed immunofluorescent staining for both PRLR and STAT5.
We found that PRLR expression increases with exposure to PL regardless of previous pregnancies (Figure
3). These results indicate that beta cells respond to PL by increasing PRLR receptor expression. Next, we
investigated whether STAT5 signaling was activated. We found an increased amount of nuclear STAT5
accumulation in the mice exposed to both estradiol and placental lactogen, regardless of previous
pregnancy (Figure 3). The increased expression of PRLR, nuclear STAT5 accumulation, beta-cell
replication, and BCM expansion are consistent with beta-cells response to pregnancy and suggests that
our in vivo pseudopregnancy cocktail models the in vivo beta cell response to pregnancy in mice.
46
Pseudopregnancy induces beta-cell replication in vitro.
To determine whether our model of in-vitro pseudopregnancy was useful in other species and in male
islets, we tested the cocktail on rat insulinoma cell line INS1E. We found the E2+PL treatment results in a
1.43-fold increase in EdU incorporation relative to the control, suggesting that male beta cells may also
positively respond to these hormonal cues (Figure 4). Our in vitro pseudopregnancy model induces beta
cell replication reliably regardless of cell line gender.
While there is evidence in mouse models that placental lactogen signaling plays a critical role in
regulating beta cell proliferation during pregnancy in mice, there have not been practical ways to study
whether this occurs during human pregnancy. One in vitro study found an increase in insulin secretion
and beta-cell replication in mouse, rat, and human islets in vitro in the presence of placental lactogen and
placental lactogen receptor
11
. We sought to mimic beta cells response to pregnancy in vitro by treating
human islets from non-diabetic female donors with a pseudopregnancy cocktail containing E2 (10
-8
M)
and PL (500ng/mL). Islets were dispersed, plated, and treated with E2 for four days; PL and EdU, a
marker for cellular proliferation, were added in days three and four. Cells were fixed on day five. The
description of experimental groups can be found in supplementary figure 1. We performed this
experiment with two different donor samples and technical replicates. Our data suggests that while PL
alone promotes moderate Edu incorporation, the combination of E2 and PL induces a 127% increase in
beta cell replication as marked by Edu incorporation (Figure 4).
Discussion
Here we present a novel model of lactogenic signaling that can be used to study the mechanisms of beta-
cell proliferation. While previous studies have relied on knockout receptor and overexpression transgenic
models, these are the first models that allows researchers to investigate phenotypic changes based on
signaling through the hormones themselves.
47
Fully mature beta cells rarely replicate unless presented with a physiological stress. This model
sought to replicate the hormonal milieu of pregnancy without the confounding factor of insulin resistance
to study the hormonal mechanisms that mediate beta cell proliferation. In our model, we measured
increases in beta-cell proliferation and beta cell mass in pseudopregnant parous mice, consistent with the
beta cell mass expansion seen during pregnancy. The increase in beta-cell mass in PEP mice is due to the
proliferation of existing beta cells rather than expansion of beta-cell size. Our results suggest that a
previous pregnancy leads to enhanced capacity for beta-cell proliferation in subsequent pregnancies. It is
possible that pregnancy results in epigenetic changes that facilitate proliferation in subsequent
pregnancies; this concept has been illustrated in the mammary gland and warrants further in vivo and ex
vivo investigation.
These findings are significant since understanding endogenous regeneration mechanisms will be
important in understanding how to induce beta-cell replication in vivo. Functional tests, such as
intraperitoneal glucose tolerance test and insulin tolerance test, are needed to evaluate whether this
increase in beta-cell mass translates into differences in glucose sensitivity. In the future, we plan to train
the computational model with experimental data, with the end goal to predict system dynamics in
response exogenous hormone treatments. This could lead to the development of novel therapeutic
strategies to expand beta cell mass.
Methods
Mice
C57BL/6 female mice (Jackson labs), all 16 weeks of age at beginning of experiments. Parous mice were
all retired breeders after two or more litters and nulliparous had never been pregnant.
48
Pellet implantation and PL injections
Estradiol (0.5mg) and Progesterone (10mg) tablets are surgically inserted subcutaneously between the
shoulder blades on Day 0. On Day 7, the mice received intraperitoneal PL injections 2x daily with
0.5ug/100uL/mouse for 4 days. Injections are given once in AM and once in PM, 10-12hrs.
Histology
Pancreata were fixed in 4% PFA, embedded in paraffin and sectioned at 5um onto charged slides. Slides
were rehydrated using toluene and decreasing concentrations of ethanol. We used a microwave and citrate
buffer method of antigen unmasking, 0.4% triton x100 TBS for permeabilization, and blocked non-
specific staining using 2%BSA +0.2%tween in TBS. All primary antibodies were incubated overnight at
4C, and all secondary antibodies were incubated for 30 minutes at room temperature.
Antibodies used: Insulin (DAKO, #A0564), PRLR (Bioss, # bs-6445R), E-cadherin (Cell Signaling,
#24E10), STAT5.
Histology quantification
Beta-cell mass: Tile scanned 5x images were stitched and analyzed in FIJI/ImageJ for analysis. Images
were cropped using the freehand selections tool to exclude lymph nodes and blood vessels. We then set
the image to binary and dilate settings before measuring the area for the DAPI and Insulin channels
separately. We then divided the insulin channel area by the DAPI channel area and multiplied by 100 to
get Beta-cell mass percentage. N=3-6.
Beta-cell area: Islets stained for E-cadherin and Insulin were imaged at 20x and analyzed in FIJI/ImageJ.
We used the freehand selections tool to follow the E-cadherin outline of individual cells in an islet and
used the fill tool to fill in the cells. We then measured the area of the filled in cells.
49
Cell Culture
The INS1E cell line was maintained in RPMI 1640 supplemented with glutamine, 10% FBS, 1% sodium
pyruvate, 1% penicillin/streptomycin, and 0.1% beta mercapotoethanol. Cells were split at 70%
confluency.
Human islets (Prodo labs) were washed twice upon arrival and cultured in RPMI 1640 supplemented with
10% FBS, 1% Glutamax, 1% penicillin/streptomycin, and 1mM nicotinamide. Islets were dispersed using
TryplE between 24-48hrs after arrival for experimental procedure.
In Vitro Experimental procedure
INS1E cells were seeded at 20,000 cells/cm
2
. Human islets were seeded at for an optimal 40-50% starting
confluency. The day after seeding cells were rinsed with PBS and media was refreshed. On day 1 we
added 10
-8
M E2, we changed this media and added fresh E2 on day 2. On days 3, 4, and 5 we added fresh
E2 and PL (10
-8
M, 500ng/mL respectively). During our media change on day 5 we added 25uM of Edu
for human islets and 10uM Edu for INS1E cells (Click-iT Edu Kit, Cat. # C10646) and incubated for 4
hours. We included an untreated control well, as well as a positive control well treated with CHIR99021
on days 3-5.
Statistical Analysis
All statistical analysis was performed using Graphpad Prism 8. For experiments where samples had equal
variance, a one- way ANOVA was used, followed by two-tailed t-test to compare individual groups with
control groups. We used the Kruskal-Wallis non-parametric test for experiments where samples had
unequal variance.
50
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15. Arumugam, R., Fleenor, D. & Freemark, M. Knockdown of prolactin receptors in a
pancreatic beta cell line: effects on DNA synthesis, apoptosis, and gene expression.
Endocrine 46, 568–576 (2014).
16. Soares, M. J. & Talamantes, F. Genetic and Litter Size Effects on Serum Placental Lactogen
in the Mouse. Biol. Reprod. 29, 165–171 (1983).
17. Contreras, J. L. et al. 17β-Estradiol protects isolated human pancreatic islets against
proinflammatory cytokine-induced cell death: molecular mechanisms and islet
functionality1. Transplantation 74, 1252–1259 (2002).
18. Friedrichsen, B. N., Galsgaard, E. D., Nielsen, J. H. & Møldrup, A. Growth Hormone- and
Prolactin-Induced Proliferation of Insulinoma Cells, INS-1, Depends on Activation of
STAT5 (Signal Transducer and Activator of Transcription 5). Mol. Endocrinol. 15, 136–148
(2001).
19. Fujinaka, Y., Takane, K., Yamashita, H. & Vasavada, R. C. Lactogens Promote Beta Cell
Survival through JAK2/STAT5 Activation and Bcl-XL Upregulation. J. Biol. Chem. 282,
30707–30717 (2007).
52
Figures
(N) Nulliparous (P) Parous
(NE) + Estradiol/Progesterone (PE) + Estradiol/Progesterone
(NP) + Placental Lactogen (PP) + Placental Lactogen
(NEP) + Estradiol/Progesterone/Placental lactogen (PEP) + Estradiol/Progesterone/Placental lactogen
Table 1. Experimental design and nomenclature of in vivo treatment groups. Nulliparous and parous
female mice were subdivided into 8 different groups comprised of 3-6 mice and received either an
estradiol tablet implantation, placental lactogen injections, or both. Control animals underwent a sham
experiment and PBS injections. Nomenclature describes the treatments and abbreviations used in
subsequent figures.
53
Figure 1.
Figure 1. Pseudopregnancy promotes beta-cell mass expansion in parous mice.
A) Representative pancreata stained with Insulin(magenta) and DAPI (blue) from each treatment group,
5x tile images stitched using ImageJ. B) Quantification of beta-cell mass (insulin/DAPI ratio); n=3-6,
*p=0.02 using Kruskal-Wallis non-parametric test.
E2 E2 PL PL E2 +
PL
E2 +
PL
ctrl ctrl
A
B
Nulliparous Parous
*
54
Figure 2.
Figure 2. Pregnancy hormones induce beta-cell proliferation but not hypertrophy in mice.
A) Immunohistochemical staining for the replication marker Ki67 (red) and insulin (green) at 20x
magnification. B) Statistical analysis of Ki67+ beta cells; n=3-5, *p=0.01 using Kruskal-Wallis non-
parametric test. C) No change in beta-cell area was found in any group; ANOVA p= 0.09, n=3. D) Islets
stained with E-cadherin; white blocked cells are representative of beta cell area quantification method
(see methods section for in-depth explanation).
E2 E2 PL PL E2 +
PL
E2 +
PL
ctrl ctrl
Nulliparous Parous
A
B
Parous
Nulliparous
Control E2 only PL only E2+PL
C
D
DAPI/E-cadherin
Parous
Nulliparous
Control E2 only PL only
E2+PL
E2 E2 PL PL E2 +
PL
E2 +
PL
ctrl ctrl
Nulliparous Parous
55
Figure 3.
Figure 3. E2 and PL induce STAT5 signaling in pseudopregnancy model.
A) Immunohistochemical staining for PRLR in nulliparous (top) and parous (bottom) mouse islets.
Animals exposed to 3 days of placental lactogen have increased expression of the prolactin receptor. B)
STAT5 accumulates in the nucleus of beta cells that have been exposed to both estradiol and placental
lactogen. Arrowheads show minimal accumulation while white arrows show maximal accumulation.
DAPI/PRLR
Parous
Nulliparous
Control
E2 only PL only E2+PL
Parous
Nulliparous
Control E2 only PL only E2+PL
A
B
56
Figure 4.
Figure 4. In-vitro pseudopregnancy model promotes beta-cell replication in human islets and INS1E
cells. A) Representative immunocytochemistry showing EdU incorporation (red) in beta cells (green)
from the INS1E cell line. B) Significant differences were found between INS1E control group and E2+PL
group (p< 0.05) as well as between PL and E2+PL (p< 0.05) n = 3. C) Representative
immunocytochemistry showing EdU incorporation (red) in beta cells (green) from dispersed female
human islets. D) no significance; n = 3.
Ctrl PL
E2 E2 + PL
DAPI/Insulin/EdU
A
Insulin/EdU
Ctrl
PL
E2 E2 + PL
B
C
D
INS1E
Human Islets
57
Supplementary Figure 1. Experimental design and nomenclature for in vitro treatment groups. Media
was refreshed daily.
Day 0 Day 1 Days 3-4
Day 5
C E2
PL E2 + PL
E2
E2
PL
E2
E2 PL
PL
E2
E2 PL
EdU
C = Control
E2 = Estradiol only
PL = Placental Lactogen only
E2 + PL= Estradiol and Placental Lactogen
58
59
SARS-CoV2 infects pancreatic beta cells in vivo and induces
cellular and subcellular disruptions that reflect beta cell
dysfunction
Katelyn Millette, USC
Janielle Cuala, USC
Peiyu Wang, USC

Carolyn Marks, USC
Veronica Woo, USC
Maya Hayun, USC
Harismar Kang, USC
Martin Martin, UCLA
Sangeeta Dhawan, City of Hope
Lily Chao, CHLA
Scott Fraser, USC
Jason Junge, USC
Mark Lewish, Bioqual
Senta Georgia, CHLA
Preprints are preliminary reports that have not undergone peer review.
They should not be considered conclusive, used to inform clinical
practice, or referenced by the media as validated information.
Keywords: COVID-19, SARS-CoV2, Diabetes, Type 2 Diabetes, Beta cell Injury, Non-human primates
DOI: https: /doi.org/10.21203/rs.3.rs-592374/v1
License: @ C This work is licensed under a Creative Commons Attribution 4.0 International License.
Read Full License
60
Abstract
Increasing evidence of new-onset diabetes during the COVID19 pandemic indicates that the
SARS-CoV2 virus may drive beta-cell dysfunction leading to diabetes, but it is unclear if it is a primary
or secondary effect. Here, we present evidence of SARS-CoV-2 infection of pancreatic beta cells in vivo
using a robust and reproducible non-human primates model of mild to moderate COVID19 pathogenesis.
Pancreas from SARS-CoV-2 infected subjects were positive for the SARS-CoV2 spike protein by
immunohistochemistry and structures indicative of viral replication were evident by electron microscopy.
Total beta cell area was decreased in SARS-CoV-2-infected pancreas, attributable to beta cell atrophy.
Beta cell granularity was decreased. These histologic phenotypes persisted beyond the duration of the
clinical disease course. Detailed electron microscopy of SARS-CoV-2 infected beta-cells revealed
ultrastructural hallmarks of beta cell stress that are seen in islets of patients with Type 2 diabetes,
including disrupted mitochondria and dilated endoplasmic reticulum. To assess the metabolic status of
beta cells from SARS-CoV-2- infected subjects, we used fluorescence life-time imaging to measure the
ratio of free and bound NADH as a surrogate of glycolytic and oxidative metabolism. We report an
increase in free NADH levels, suggesting that beta cells from SARS-CoV-2-infected subjects adopt a
more glycolytic metabolic profile. Taken together, we conclude that SARS-CoV-2 infection induces beta
cell stress that may compromise beta-cell function beyond the duration of the disease course. This raises
the possibility that the beta cell stress and injury may have clinical implications of the long-term future
health of patients that have recovered from COVID19.
Introduction
Since the beginning of the SARS-CoV-2 pandemic, there has been a concern about the possibility
of infection precipitating the new onset diabetes (1-5). It has been postulated that there may be a
bidirectional relationship between COVID19 and diabetes, but it is unclear if that relationship can be
directly attributed to loss of beta cell function after SARS-CoV-2 infection of cells, or due to indirect
beta cell stress from increased insulin resistance, steroid treatment, and global inflammation. Several
61
high profile reports have provided conflicting results about the presence of ACE2, TMPRSS2, and SARS-
CoV-2 in the beta cells of infected patients (6-10). While these reports have been very informative,
they are limited by the difficulty in acquiring patient tissue and that the available post-mortem tissues
are limited to patients who have expired due to severe illness. Because most illness from SARS-CoV-2
infection is not severe, it is critical to identify a reproducible model system to study the effects of
SARS-CoV-2 infection on beta cells during and after the disease course.
SARS-CoV-2 infects the beta cells of NHP in vivo
During the SARS-CoV-2 pandemic, non-human primates have proven to be a consistent, robust, and
reproducible model for studying COVID19 disease pathophysiology and for preclinical evaluation of
vaccines and therapeutics (11-25). It has been reported that rhesus macaques infected
intranasally/intratracheally with SARS-CoV-2 show a mild to moderate disease pathology consistent
with the overwhelming majority of human COVID19 cases. We capitalized on our access to this model
system to evaluate the effects of mild/moderate COVID19 di sease pathogenesis on beta cells in vivo. We
obtained the pancreas from adult Rhesus Macaques inoculated with SARS-CoV-2 and of uninfected adult
macaques collected at necropsy. We evaluated cellular histology, subcellular ultrastructure, and metabolic
signatures to assess if SARS-CoV-2 infected beta cells in vivo and whether SARS-CoV-2 infection resulted
in aberrant cellular pathology characteristic of functional beta cell impairment.
As previously reported, adult rhesus macaques (6 to 12 years of age) were inoculated with 1.1 x
10
6
plaque-forming units (PFU) of SARS-COV-2 administered as 1 ml intranasally and 1 ml
intratracheally (13, 15, 16). In this model, viral RNA levels peak at 2 days post inoculation (dpi).
Interstitial viral pneumonia is present and resolves by around 4 dpi. Clinical disease course is resolved by
around 12dpi (16). To assess if there was an acute effect of SARS-COoV-2 infection on beta cells and
if it resolved by the end of the disease course, we evaluated the pancreas collected at necropsy during
the acute phase (7-10dpi, n=3) and in the post-acute phase (14dpi, n=4) of the disease course. The
62
pancreas from 3 uninfected adult macaques and 2 pregnant macaques infected with the Zika virus
served as controls (26).
Because there have been conflicting reports about the robustness of ACE2 and TMPRSS2
expression in human islets, we sought to identify if either transcript was present in the islets of rhesus
macaques. We interrogated a publicly available single cell sequencing data set from multiple organs of
the rhesus macaque (27). Cells were clustered into organ specific clusters, and the both ACE2 and
TMPRSS2 were present in the pancreas cluster. We then clustered cells into pancreatic cell subtypes.
ACE2 and TMPRSS2 expression was highest in beta cells (Supplemental Figure 1A). We confirmed
ACE2 expression in beta cells by immunohistochemistry. ACE2 expression was low but present in most
beta cells; a subset of cells exhibited robust expression (white arrows, Supplemental Figure 1B).
After establishing that ACE2 was present in the beta cells of this system, we used
immunohistochemistry to detect the SARS-COV-2 nucleocapsid protein in the islets of acute or post-
acute pancreas. Because SARS-CoV2 RNA is no longer detectable in the bronchioalveolar fluid of post-
acute subjects by Day 14, it was unclear if the infection would be present only during the acute phase
or would resolve by the post- acute phase (16). Islets from acute and post-acute pancreas were
positive for the nucleocapsid protein (Figure 1A). Controls tissues were negative for nucleocapsid
protein expression. To confirm the presence of the virus in acute and post-acute islet cells, we used
transmission electron microscopy to assess if viral particles were present in beta cells from inoculated
subjects. Beta cells were identified by the characteristic halos around secretory granules. Viral
particles were present in 4 of the 4 samples assessed by electron microscopy. An active viral
replication complex was also present and contained structures that were representative of multiple
stages of viral particle assembly (Figure 1B, red box and red arrows) (28). We noted characteristic
double membrane vesicles inside of the profusion replication complex are also hallmarks of SARS-
CoV2 infection we also present (Figure 1B, blue box and blue arrows) (29).
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SARS-CoV2 infection drives a massive loss of beta cell mass
Previous reports suggested that SARS-CoV infection may cause beta cell injury, and other reports
have suggested that certain viral infections can cause beta cell loss (30-34). We quantified fractional
beta cell area in the control and infected NHP pancreas to determine if SARS-CoV-2 infection resulted in
beta cell loss. Tissue was collected from the head, body, and tail of the pancreas and beta cell area was
quantified as insulin
+
pixels divided by total tissue area pixels. Representative images are shown in
Figure 2A. Pregnant Zika-infected macaques were excluded from this analysis because pregnancy drives
temporary increases in beta cell mass (35, 36). Total beta cell area from acute and post-acute pancreas
beta cell area averaged approximately 1.8%, while total beta cell area in control pancreas was
approximately 3.8% (n=3-4, p<0.05, Figure 2B). Because it was not clear if the loss in beta cell area was a
result of decreased number or decreased size of beta cells (37), we measured the proportion of beta and
alpha cells per islet. We found that the percentage of beta cell area per islet did not change (Figure 2C),
which suggested that either beta cell atrophy or pan-islet apoptosis could have been driving this
phenotype. Neither control, acute, or post-acute beta cells expressed cleaved caspase-3, a marker of
apoptosis (data not shown). To measure cellular atrophy, we measured individual beta cell area in each
subject (n=300 cells per group). Cellular boundaries were marked with r.-actin staining. We used Image
J to trace and calculate individual cell size. Mean beta cell size decreased by 18% in the acute phase when
compared to control and by 29% when comparing the post-acute beta cells to those from controls.
Within inoculated subjects, individual beta cell size continued to decreased between the acute and the
post acute phase, suggesting that SARS-CoV-2 infection continued to drive beta cell atrophy after disease
resolution. We measured fasting serum insulin and glucose levels prior to necropsy in a small number of
subjects (Supplemental Figure 2). Control subjects (n=2) had very low fasting glucose levels. 4 of 8
inoculated animals had glucose levels 60mg/dL, which has been characterized as dysmetabolic
(metabolically normal <60mg/dL, dysmetabolic 60-100mg/dL, diabetic >100mg/dL) (38). Of those 4
animals, 3 also had elevated serum insulin levels (>45mU/ml, dark gray bars).
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SARS-CoV2 infection induces subcellular ultrastructure indicative of diminished beta cell function
Because primates infected with SARS-CoV2 are restricted to BSL3 restricted facilities and these
subjects were all participants in other studies, we were not able to pursue in vivo beta cell function
studies, such as glucose tolerance tests or hyperglycemic/euglycemic clamp studies, to measure how
SARS-CoV2 may affect beta cell function. To maximize information we can discern from the tissues we
have available, we examined beta cell ultrastructure to assess if the viral infection induced any
ultrastructural markers of beta cell stress or dysfunction.
Close examination of beta cells during individual beta cell size measurement revealed that
atrophied beta cells had a degranulated appearance. Degranulation has been proposed to be a driving
cause of beta cell deficits in the context of metabolic stress (39, 40). To discern if atrophied beta cells
from SARS-CoV2 inoculated pancreas were degranulated, we visualized granular density using super-
resolution fluorescence microscopy. Insulin granules were evenly distributed and filled most of the
beta cell cytoplasm in control tissues (Figure 3A-A ). In both acute and post-acute beta cells, insulin
granules were concentrated in speckles and large areas of the cytoplasm were devoid of insulin granules
(Figure 3A-A ,purple boxed insets and white arrows). We used ImageJ to determine the density of
granules per square um of insulin area in an islet, then used our previous measurements of beta cell size
(Figure 2) to estimate how many granules were present per beta cell. We measured a 66% decrease in
insulin granularity between control and inoculated islets (n=10-20 islets per condition, p<0.001).
Within the inoculated samples, there was no difference in granularity between the acute and post-acute
time points.
To more closely examine the subcellular ultrastructure of the cytoplasm, we imaged control,
acute, and post-acute beta cells by transmission electron microscopy. Beta cells from control
pancreas exhibited normal ultrastructure, including dense insulin granulation, dense mitochondria,
compact endoplasmic reticulum, and minimal vacuolization (Figure 4A). During the acute phase,
we detected beta cells that were less electron dense than surrounding cells. These cells had increased
65
vacuole-like spaces, dilated endoplasmic reticulum, and distended cristae within the mitochondria
(Figure 4). In less electron dense cells, convoluted membranes predominated the cytoplasms and
mitochondria membranes were disrupted. These hallmark attributes mirror observations in beta
cells that are undergoing metabolic stress (41-43).
SARS-CoV2 infection shifts markers of cellular metabolism toward a glycolytic profil.e
The ultrastructural evidence of beta cell stress, and specifically of mitochondria disruption,
raised the possibility these SARS-CoV2 could induce changes in beta cell metabolism. Recent reports
concluded that SARS-CoV2 infection in shifts cells towards a more glycolytic metabolism to provide
building blocks for viral replication (44). It has been argued that beta cells from Type 2 diabetic patients
show a shift in cellular metabolism from oxidative phosphorylation towards glycolysis and that shifts in
towards glycolysis can decrease insulin secretion (45). We sought to measure cellular metabolism of beta
cells in fixed pancreas from control and SARS-CoV2 inoculated animals.
We developed a novel method to use fluorescence lifetime imaging (FLIM) to measure the levels
of NADH in formalin-fixed paraffin embedded beta cells as a proxy measurement of cellular
metabolism. FLIM measures the lifetime of excited NADH: unbound NADH exhibits short lifetimes (r
= 0.4 ns) and is a byproduct of glycolysis; enzyme-bound NADH exhibits a far longer lifetime (r =1.2 -
3.7 ns (46) dependent on the bound enzyme and is a substrate of oxidative phosphorylation (47, 48).
This ~10x difference allows FLIM to offer a measure of the glycolytic vs oxidative status of a cell that
persists even after fixation and histological processing. We used immunohistochemistry to identify
insulin producing cells on slides, then used a 2-photon laser to collect the lifetimes of the secondary
antibody for insulin and the autofluorescence of NADH. The distribution of NADH lifetimes within
the beta cells of an image is represented on the phasor plot. The closer the phasor plot s centroid is to
the relative position of free NADH on the circle, the higher the glycolytic metabolism of the cell.
Figure 5A presents insulin masks, NADH intensity masks, and phasor plots from three representative
islets. To capture the glycolytic vs oxidative status of each islet, we averaged the modes of the
66
centroids for each islet per individual pancreas, and plotted the coordinates on a 2D plot (Figure 5B;
n=10 islets from 3-5 pancreas per experimental group). We observed that the centroid plots for the acute
and post-acute samples clustered separately from the control samples.
We next sought to understand if the separation of the sample populations on the phasor plots
represented a change in beta cell metabolism. We calculated each islet s glycolytic coefficient to
report the proportion of NADH from glycolysis and identify cells as primarily glycolytic or primarily
oxidative (49). Using this estimation, a higher glycolytic coefficient would represent more free
NADH in the islet, suggestive of more glycolytic metabolism. We found that both uninfected control
samples and zika- infected samples had a similar glycolytic coefficients (Figure 5C, pregnant- blue
triangles, non-pregnant- blue circles). There was a 23% increase in the glycolytic coefficient in islets
from the acute pancreas, suggesting that these cells employed a more glycolytic metabolism. Islets
from the post-acute pancreas had a slightly lower glycolytic coefficient that was still significantly
different from control samples. This indicates that beta cell metabolism may begin to recover in the
post-acute phase of COVID19 pathogenesis. Because our study ended 14 days after infection, we were
unable to measure if and when beta cell metabolism could return to baseline.
Discussion
Because the number of patients who have recovered by COVID19 continues to rise, it is
imperative to understand if SARS-CoV2 infection causes cellular disfunction that may compromise
the long-term health of survivors. Since the beginning of the COVID19 pandemic, commentaries,
case reports, and primary data have driven speculation about the possibility of SARS-CoV2 causing
a direct or indirect injury to pancreatic beta cells. This has been difficult to address in affected
patients because of the inaccessibility of living human pancreatic tissue; it is also difficult to assess
in human autopsy samples because of poor tissue quality due to post-mortem autolysis. To address
this controversy, we have interrogated the pancreas from a rhesus macaque model of COVID19
pathogenesis that mirrors mild to moderate human COVID19 disease progression, which accounts for
67
the vast majority of all COVID19 infections. Because primates are the closes relatives to humans,
this model has the advantage of being a system that reflects human disease progression better than
other animals. It also more accurately reflects the severity of most COVID19 cases, thus being an ideal
model for understanding how COVID19 may affect the broad spectrum of patients with the disease,
not just the most severely ill.
We demonstrated that SARS-CoV-2 can be detected in pancreatic beta cells after intranasal and
intratracheal inoculation with the virus, therefore, SARS-CoV-2 can infect pancreatic beta cells in vivo.
This is consistent with reports of SARS-CoV-2 infecting human islets in vitro and autopsy samples (9,
50- 52), but in conflict with other reports that argue that the canonical receptors for SARS-CoV2
expression are not expressed in human islets (6, 7). After extensive measurements of beta cell area,
islet composition, and individual beta cell size, we also concluded that beta cell atrophy accounts for a
decrease in beta cell area. Super-resolution and ultrastructural analysis indicated that beta cells are
degranulated and displayed hallmark signs of beta cell stress.
It was reported that SARS-CoV2 infection can shift cellular metabolism towards glycolysis as a
means of making metabolites available to support viral replication (44). It has also been reported that
increased glycolytic metabolism decreases insulin secretion (45). We used a novel approach to FLIM
to assess if SARS-CoV2 infection shifted beta cell metabolism towards a glycolytic profile. The
quantitative analysis of FLIM imaging determined that there are higher amounts of free NADH in the
islets of inoculated subjects, thus suggesting a more glycolytic metabolic profile. Our data documents
a minor but significant decrease in NADH levels during the post-acute period, suggesting that beta cell
metabolism may be able to recover over time. This data, coupled with evidence of direct infection of
beta cells by the virus, support the conclusion that SARS-CoV2 has a direct effect on beta cell function.
One limitation of this study is our inability to test beta cell function after SARS-CoV2
inoculation to measure the impact of viral infection on beta cell function directly. Because these
subjects were part of ongoing studies for pre-clinical pharmaceutical trials, we were unable to perform
68
glucose tolerance tests and measure insulin secretion. Nonetheless, previously published reports have
determined that in vitro infection of islets with SARS-CoV2 decreases glucose stimulated insulin
secretion. Our reporting of beta cell atrophy, beta cell degranulation, and disruption of subcellular beta
cell ultrastructure are shared with and supported by the studies that have reported beta cell dysfunction
after SARS-CoV2 infection in vitro (50).
As millions of patients have recovered from COVID19, it is critical to understand if beta cells
were injured by SARS-CoV2 infection and if they recover from injury. It is documented that patients
with Type 2 diabetes have elevated insulin requirements during hospitalization for COVID19 and that
hyperglycemia is a comorbidity of COVID19 infection. Our own group has recently reported a
concerning spike in children presenting with new onset type 2 diabetes in diabetic ketoacidosis during
the COVID19 pandemic. Ketoacidosis can be a clinical indicator of acute beta cell loss of function
(53). Our data shows that SARS-CoV2 infection can induce beta cell stress, which generally leads to
beta cell dysfunction, and it is not clear that beta cells recover from that stress in the immediate post-
acute phase after disease resolution. Further studies are required to understand if that beta cells can
recover after the initial injury from SARS-CoV2 infection, which could have implications for the
future health of millions who have recovered from COVID19.
Materials and Methods
All experiments using tissues from SARS-CoV2-inoculated or ZIKA-infected subjects were inactivated
with 4% formaldehyde. All experiments were approved by Children s Hospital Los Angeles Biosafety
committee. All animal studies were conducted in compliance with all relevant local, state, and federal
regulations and were approved by the Bioqual Institutional Animal Care and Use Committee (IACUC).
Animals and Study Design
Rhesus Macaque model: Non-human primate models consisted of thirteen outbred, Indian-origin adult
(between 3-7 years old) male rhesus macaques (Macaca mulatta) housed at Bioqual, Inc (Rockville, MD).
69
The rhesus macaques were randomly stratified into three groups of three animals each. The first study
inoculated nine animals with SARS-CoV-2 with a total 1mL dose of 1.1x10
6
plaque forming units
(PFU) The 1 mL doses were administered via either the intranasal (0.5 mL per nostril) or intratracheal
routes. Animals were then observed for signs of disease. Veterinary staff performed semi-quantitative
clinical assessments based on four categories: clinical appearance, dyspnea, recumbency, and
responsiveness. Animals were then assigned for necropsies on days 7-10 (acute, N=3) or day 14 (post-
acute, N=4) post- inoculation.
SARS-CoV-2 stock: The SARS-CoV-2 USA-WA1/2020 stock from the BEI Resource (NR-42281; Lot
370033175; courtesy of Natalie Thornburg, Centers for Disease Control) was used and propagated on
Vero E6 cells. The viral challenge stock was then harvested on day 5 post infection at 90% cytopathic
effect (CPE). Whole-genome sequencing confirmed 100% identity with the parent virus sequence
(GenBank MN985325.1; courtesy David O Connor, Shelby O Connor, University of Wisconsin).
Histology
Pancreata were cut into head, mid, and tail sections and embedded into paraffin blocks. Blocks were
sectioned into 7 micron slices on charged slides.
Slides were stained as previously described with the exception of the ACE2 and Nucleocapsid stains,
which were performed using a pressure cooker and citrate buffer for unmasking rather than a
microwave and citrate buffer. All slides were and mounted with ProLong Diamond Antifade (Thermo
Fisher cat# P36961). The complete antibody list can be found in supplementary table 1.
In-situ Hybridization and co-IF
We followed the RNAscope® Multiplex Fluorescent Reagent Kit v2 (ACDbio) protocol for paraffin
70
sections. Protease plus for 20 mins. 845701 RNAscope® Probe - V-nCoV2019-S-sense. Immediately
following the opal secondary steps, we incubated slides in blocking buffer (BSA, tween, tbs) for 1
hour, followed by overnight insulin staining. The next day, slides were washed and incubated with a
secondary antibody and DAPI, washed, and mounted.
Transmission Electron Microscopy (TEM) Sample Preparation and Imaging
Pancreatic beta-cell ultrastructure was imaged using the Talos TEM. Briefly, pancreatic tissue samples
(control, acute, and post-acute) were in 4% paraformaldehyde in PBS, then in 2.5% glutaraldehyde and 2
% paraformaldehyde in 0.1M HEPES and postfixed in 1% osmium tetroxide overnight. The fixed
samples were stained with 1% uranyl acetate for an hour and dehydrated with an increasing percentage of
ethanol solutions. Propylene oxide (PO) was used as a transition fluid and embedded with a medium
resin hardness using the Embed 812 kit (EMS) which polymerized at 60 degrees Celsius for a minimum
of 18 hours. Ultrathin sections (80nm) were obtained using a Leica UC6 ultramicrotome. Once mounted
on grids, sections were treated with 3% H2O2, then stain ed with lead citrate followed by uranyl acetate.
The stained sections were examined using Talos F200C TEM operated at 80kV. Images were taken with a
mounted Ceta Camera. N=2-4 biological samples per condition.
Microscopy
Fluorescence images were acquired with a DM4000B microscope equipped with 20x/0.7 HC PL APO
and 40x/0.85 HCX PL APO objective lenses and DFC360 FX camera (Leica Microsystems, Buffalo
Grove, IL). Fluorescence excitation and emission bands were as follows: 360/40 and 470/40 nm for
DAPI; 480/80 and 527/60 nm for Alexa Fluor 488; 546/12 and 600/40 nm for Cy3; and 620/60 and
700/76 for Alexa Fluor 647. Pixel sizes were 0.323 µm for 20x and 0.161 µm for 40x images. The
system was controlled with LAS X 3.6 software.
71
Confocal images were acquired with an LSM 710 system mounted on an AxioObserver.Z1 microscope
equipped with 20x/0.8 Plan-APOCHROMAT and 63x/1.4 oil Plan-APOCHROMAT objective lenses (Carl
Zeiss Microscopy, White Plains, NY). Fluorescence excitation lasers and emission detection ranges were
as follows: 405 nm/406-480 nm for DAPI; 488 nm/490-550 nm for Alexa Flour 488; and 555 nm/560-
620 nm for Cy3. Voxel sizes were 0.3 x 0.3 x 1.0 µm for 20x and 0.1 x 0.1 x 0.3 µm for 63x images.
The system was controlled by ZEN 2011 software.
Fluorescence Lifetime Imaging Microscopy (FLIM) was performed on SP8 DIVE FALCON spectral
multi- photon FLIM microscope (Leica Microsystems, Germany) using 40x/1.10 N.A. water immersion
objective. NAD(P)H was excited with a Spectra-Physics Insight 3X ultrafast IR laser at 740 nm, 0.8mW
average power, and 4 frame accumulations per optical section. The Alexa dyes were excited using
860nm wavelength with the same Spectra-Physics laser. Images were collected at 1024 x 1024 resolution
and 2.0 zoom. N= 3-5 biological samples and >14 islets per condition.
Super Resolution Imaging and Processing
Slides were stained as previously described with monoclonal rabbit anti-glucagon (Abcam, ab92517)
and polyclonal guinea pig anti-insulin (Dako, A0564) for primary antibody incubation and polyclonal
Goat AF594 anti-rabbit and donkey AF647 anti-guinea pig, respectively (ThermoFisher, A-11012;
Abcam, ab150187) all at 1:500 dilution. They were then imaged on a Leica Stellaris 8 Confocal
Microscope with an integrated Lightning detection using a 67x oil immersion objective. The Alexa
dyes were excited at 593nm and 647nm. Images were collected at 5192 x 5192 and 0.75 zoom. Insulin
stained (AF647) images were then processed on Fiji ImageJ using the "Find Maxima" function with a
prominence set to greater than 10 to obtain the count of particles of green signal within the image.
Next, the threshold for the images were adjusted to capture the insulin positive cells. With the new
binary image, the pixels were dilated with 50 iterations and 4 counts. Areas of the insulin stained parts
of the image were measured using the "Analyze Particles" function with the size (µm2) set at 0-
72
Infinity and circularity from 0.00-1.000. The results are summarized with the total amount of particles
and their combined total area. The average size of a beta cell nucleus (6.9µm2, Saisho et al. 2013) was
subtracted from the average beta cell size obtained from the previously mentioned analysis to acquire
beta cell cytoplasmic area for each condition (control=103.217, acute=84.3932, and post-
acute=71.0426). To obtain the final unit of particles per beta- cell, the count of particles was divided by
the cytoplasmic area. One-way ANOVA was used to determine significant differences between each
condition.
Image Analysis
Islet Composition: We imaged a minimum of 10 islets per biological sample, with 3-4 biological
samples per treatment group. Statistical significance was determined using an ordinary one-way ANOVA.
Beta-Cell Area: Tile scanned 5x images were stitched and analyzed in FIJI/ImageJ for analysis. Images
were cropped using the freehand selections tool to exclude lymph nodes and blood vessels. We then set
the image to binary and dilate settings before measuring the area for the DAPI and Insulin channels
separately. We then divided the insulin channel area by the DAPI channel area and multiplied by 100
to get Beta-cell mass percentage. N=3-4.
Beta-Cell Size: Islets stained for beta-actin and Insulin were imaged at 20x and analyzed in FIJI/ImageJ.
We used the freehand selections tool to follow the beta-actin outline of individual cells in an islet and
used the fill tool to fill in the cells. We then measured the area of the filled in cells. N=3-4 biological
samples, with over 380 individual beta cells measured per timepoint. Statistical significance was
determined using an ordinary one-way ANOVA.
FLIM Processing
To analyze the metabolic signature for each cell type in the islet, masks for regions of pancreatic alpha
73
cells and pancreatic beta cells are created from the microscopic images of the GLUC and INS staining
respectively by thresholding. masks were then preprocessed to fill the cytoplasms of cells and exclude
the nucleus. Each mask was applied to the field of view to extract lifetime information from beta cells
and alpha cells separately. We used the mode of the resulting phasor clusters to represent the sample to
minimize the effect of contaminating fluorescent species such as lipofuscin. We calculate the
glycolytic coefficient and the major contributing enzyme by drawing a line from the phasor position
representing free NADH (0.4 ns) through each cluster s mode and extrapolate to an intersection with
the universal circle. We refer to this line as a metabolic trendline. The glycolytic coefficient falls out
from the linear properties of the phasor; the fractional distance of the mode along the trendline chord
(all metabolic trendlines have a length of 1). The closer the mode is to the free NADH phasor position,
the higher the glycolytic coefficient. Major contributing enzymes are determined based on known
lifetimes at the extrapolated ends of each metabolic trendline intersecting the universal circle. One-way
ANOVA was used to determine significant differences between each condition. N= 3-5 biological
samples and >30 islets per condition.
Acknowledgements
Thank you to Esteban Fernandez and the Molecular Imaging Core at The Saban Research Institute at
CHLA for expertise in image acquisition and quantification. Thank you to the CoVEN Collaboratory
for primate experimental design expertise, and specifically to Emma Mohr and David O Connor of the
University of Wisconsin for providing the Zika-infected primate tissues. Thank you to the Oregon
National Primate Research Center and the Wisconsin National Primate Research Center for providing
additional control tissues. M.G.M is supported by DK083762, DK41301, DK085535 and DK118640.
S.D. is supported by HIRN New Investigator Award (NIH NIDDK UC4 104162), DK120523 and Wanek
Family Foundation to Cure Type 1 Diabetes. S.G. is supported by the American Diabetes Association 7-
20-COVID- 173, The Harvey Family Foundation, The Paul Lester Foundation, The Saban Research
Institute.
74
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Figures
Figure 1
SARS-CoV-2 directly infects beta-cells in vivo. (A) Representative images of immunofluorescent
staining for SARS-CoV-2 nucleocapsid protein (red) and insulin (green) in control and inoculated NHPs.
SARS-CoV- 2 nucleocapsid protein was not detected in control tissues. SARS-CoV-2 protein is not
present in every beta cell and it is also present in non-beta islet cells. (B) Representative transmission
electron microscopy of an islet from an acute subject. White lines delineate cell borders. Less-electron
dense beta cell has distended borders and encompasses a viral replication complex. Red and blue box
insets are high magnification of selected areas. Note viral particles at various stages of maturity inside
of the vacuoles of the replication complex (red arrows). Double membraned vacuoles are also
hallmarks of viral replication (blue arrows).
79
Figure 2
SARS-COV-2 infection induces beta cell atrophy. (A) Representative 5x tile-scan image masks of
pancreas stained with insulin (magenta) and DAPI (blue). (A ) Quantification of tile-scan images
revealed that pancreas from SARS-COV-2 infected subjects had a 56% decrease in beta cell area (n= 3-4
biological samples per group, *p=0.031 as determined by a one-way ANOVA, *p=0.039 ctrl vs acute by
two-tailed t- test, and *p=0.040 ctrl vs post-acute by two- tailed t-test). (B) Representative images of the
immunofluorescent staining for beta cells (insulin, green) and alpha cells (glucagon, red) in islets of
SARS-CoV2 inoculated monkeys show normal islet composition. Purple inset boxes are small areas
magnified to illustrate outline to quantify beta cell size. (B ) NHPs had no statistically significant
difference in beta cell composition between time points as determined by a one-way ANOVA (n= 3-4
biological samples per group, each dot represents one islet). (B") Quantification of beta cell size beta
cell size in control and infected pancreata (n=380-529 beta cells measured from 3-4 biological samples
per group. p values determined by a one-way ANOVA ****p<0.0001 and unpaired t-test (ctrl vs acute
****p<0.0001), (ctrl vs post-acute ****p<0.0001).
80
Figure 3
Beta cells from SARS-COV-2 subjects are significantly degranulated. (A) Immunohistochemical
staining for insulin and glucagon of representative islets that were imaged using super-resolution
microscopy. (A ) High-magnification images purple boxed areas in (A). White arrows highlight large
areas in the cytoplasm with reduced insulin staining in pancreas from SCV-inoculated subjects. (B)
Quantification of beta cell granulation revealed a greater than 60% decrease in granulation between
control and acute/post-acute islets (n=10-20 islets per group from at least 3 different subjects. Each dot
represents 1 islet. Two-way ANOVA with Turkey s multiple comparisons, **** p<0.001)
81
Figure 4
Beta cells from SARS-COV-2 inoculated subjects have ultrastructral hallmarks of beta cell
stress. Low magnification transmission electron microscopy images highlight multiple cells within
islets. Note that the control islet cells contain abundant insulin secretory granules, while acute and
post- acute cells are degranulated. (dER) The intraluminal space of the rough endoplasmic reticulum is
distended in the acute and post-acute beta cells. (Vacuolization) While cytoplasmic vacuoles are
present in control beta cells, vaculoles in the acute and post-acute pancreas are much larger and have
internal membranes. (Mitochondria) Mitochondria in the control sample are abundant, large, and have
densely packed cristae. Mitochondria from the acute and post-acute pancreas have distended cristae
and are frequently ruptured.
82
Figure 5
Beta cells from SARS-COV-2-inoculated subjects have a glycolytic metabolic signature. (A)
Representative lifetime images of insulin immunohistochemical staining (red mask) and NADH
autofluorescence (Intensity mask). In the intensity mask, red pixels indicate a longer NADH lifetime,
blue pixels represent a shorter NADH lifetime. Insulin mask was used to filter out the signal from
other cell types present in the islets. Beta cell NADH lifetimes were transformed onto phasor plots.
(B) The modes of islet phasor plots for each experimental subject were averaged and plotted onto a G
vs. S graph. (C) The ratio of free NADH per islet was calculated. N=10 islets per subject, 3 subjects per
group).
83
Supplemental Figure 1
Supplemental Figure 1: ACE2 expression in the Rhesus Macaque pancreas. (A) Single cell RNA-seq
analysis shows that both TMPRSS2 and ACE2 are expressed in pancreatic cell types. TMPRSS2 and ACE2
transcript expression were assigned to the pancreatic cell subtypes, as identified by cell-type specific
marker expression. (B) Representative images of the immunofluorescent staining for ACE2 (red) and
Insulin (green) in control, acute, and post-acute pancreas. White arrows denote beta cells with increased
ACE2 expression.
84
Supplemental Figure 2
Supplemental Figure 2: Fasting glucose and insulin measurements for control and post-
acute subjects. Serum samples taken immediately prior to necropsy were used to measure
glucose and insulin. MK305.3 and MK 305.4 were control samples, all others were inoculated
with SARS-COV-2 14 days prior to necropsy.
85
Chapter 5
Future Perspectives
In this final chapter I provide an extended discussion for the projects described. An inevitable truth in
science is that each piece of interesting data unearths numerous unanswered questions. Here I offer my
perspectives on future directions that may uncover the mechanisms behind the phenotypes we presented.
Part 1: Neurog3 as a Pancreatic Progenitor Specifier
NEUROGENIN3 (NGN3) is a basic helix-loop-helix transcription factor that is essential for pancreatic
endocrine development in mice, and important in human
1–3
. Structure- function studies show that
truncation mutations at the DNA binding domain and nuclear localization domain, such as the one found
in the CHLA patient, result in a functionally null protein
4,5
. Human NGN3 was previously believed to
only be expressed during the endocrine progenitor stage, as is seen in mouse
6,7
. However, clinical
presentations of both endocrine and exocrine dysfunction suggest that NGN3 has an unexplored role in
pancreatic organogenesis upstream of endocrine specification in humans
4,8–12
. I detected a low level of
NGN3 expression at the pancreatic endoderm stage during the differentiation of our patient specific and
H1 ESC cell lines. Strikingly, the NGN3
NULL
lines had a decrease in the pancreatic endoderm markers
GATA4 and GATA6 (Figure 1), suggesting that NGN3 may be acting to regulate early pancreatic
endoderm differentiation. At the pancreatic progenitor stage of differentiation, I found a depleted
pancreatic progenitor cell population and a dysregulation in Notch signaling NGN3
NULL
lines, suggesting
that these cells are not capable of self-renewal driven by Notch. My preliminary data suggest that NGN3
is a lead candidate transcription factor for establishing competent pancreatic progenitor cells. One
explanation could be that NGN3 is required to establish the human pancreatic progenitor cell population
by directly increasing GATA4/6 expression during the pancreatic endoderm stage, and by regulating the
Notch pathway during the pancreatic endoderm and progenitor stages. Another explanation could be that
86
NGN3 is indirectly responsible for these changes in gene expression through chromatin remodeling
complexes.
Exploring NGN3 as a transcriptional
activator in early pancreogenesis
GATA6 is a crucial transcription factor for
gastrulation, early pancreatic development,
and beta-cell maturation
13
. Since there is no
difference in definitive endoderm markers
between NGN3
NULL

cells and NGN3
CORR
cells (Chapter 2, Supplemental Figure 4), we
believe that GATA4/6 dysregulation is
occurring during the pancreatic endoderm
stage and coincides with the onset of NGN3
expression. Recent studies have shown that
even a heterozygous loss of function mutation in GATA6 results in a decrease in NKX6.1+ pancreatic
progenitor cells, and extremely low beta-cell differentiation
14
. In vitro, the heterozygous GATA6
mutations also resulted in a decrease in GATA4 mRNA, which may explain the decrease we see in
GATA4 expression of our NGN3
NULL

lines. As the pancreas develops, GATA4 is expressed in exocrine
cells while GATA6 remains active in beta cells. It is not known whether NGN3 binds to the GATAs,
however, both GATA6 and GATA4 have multiple e-boxes 500bp upstream of the transcriptional start
site, which are known binding sites of NGN3. Based on this, one hypothesis is that NGN3 increases
GATA6 expression by binding directly to an e-box located upstream of the GATA6 transcriptional start
site. The potential protein-DNA interactions between NGN3 and GATA6 can be analyzed by running a
chromatin immunoprecipitation experiment.
Figure 1. NGN3
NULL
line produces less pancreatic
endoderm. (A) The NGN3
NULL
line expresses fewer
RNA transcripts per million for both GATA4 and GATA6
compared to the NGN3
CORR
line. (n=2). (B) There is a
statistically significant decrease between
GATA4+/GATA6+ double positive populations between
NGN3
NULL
and NGN3
CORR
(68.75 ±6.35 and
88.57±2.17).
87
Pancreatic endoderm progenitors then differentiate into pancreatic progenitor cells, these cells
remain multipotent and in a state of self-renewal through Notch signaling. Dysregulation of the Notch
pathway results in a depleted pancreatic progenitor pool. In typical development, cells with decreased
Notch signaling accumulate NGN3, a critical inducer of pancreatic endocrine cell development
15,16
.
NGN3 adjacent cells have an activated notch pathway and will remain multipotent. This lateral inhibition
has been shown to be crucial for proper pancreatic development. While it’s been shown that Neurogenin
family members bind to Dll1 to increase its expression during neurogenesis, it is not clear if that is the
dominant mechanism during the pancreatic endoderm and pancreatic progenitor stages in human
17
. My
preliminary data suggests that there is
a dysregulation of the Notch pathway
at both the pancreatic endoderm and
pancreatic progenitor stages in
NGN3
NULL
cell lines (Figure 2). One
hypothesis is that low level NGN3
regulates the Notch pathway by
activating the expression of DLL1 during the pancreatic endoderm and progenitor stages to establish a
competent pancreatic progenitor population. The potential role of NGN3 and NOTCH signaling during
the pancreatic endoderm stage of development can be investigated by using multicolor RNAscope in situ
hybridization technology and immunofluorescent staining protocols to determine if NOTCH1/HES1 and
DLL1/NGN3 are enriched in distinct but neighboring cells. These cells can be imaged 3D at the
pancreatic endoderm and pancreatic progenitor stages. To test whether this lateral inhibition is functional,
the NGN3
CORR

and H1 cells can be treated with the gamma- secretase inhibitor DAPT throughout the
pancreatic endoderm stage (3 days) to mimic the dysregulated Notch pathway displayed in the NGN3
NULL
lines. DAPT is a known suppressor of Notch signaling and is used during the pancreatic endocrine
progenitor stages of beta-cell differentiation protocols to allow for accumulation of NGN3 in the cell.
Figure 2. NGN3
NULL
lines have NOTCH dysregulation. RNA-
sequencing shows NGN3
NULL
lines have a striking decrease in

DLL1 and
HES1 at the pancreatic endoderm (PE) stage. Absence of NGN3 results in
an increase in NOTCH1 expression at the pancreatic progenitor (PP) stage.
(n=2).
88
Exploring NGN3 as a pioneer transcription factor in early pancreogenesis
While transcription factors bind directly to DNA to increase the transcription of a particular gene or set of
genes, pioneer transcription factors are capable of initiating chromatin opening events
18,19
. They can bind
to closed chromatin and recruit chromatin remodeling complexes like SWI/SNF
20, 21
. This permits the
binding of transcription factors at sites nearby that control cell fate. Bulk RNAseq of our NGN3
NULL
and
NGN3
CORR
lines revealed that SWI-SNF targets are the most downregulated genes through the pancreatic
endoderm, pancreatic progenitor, and endocrine progenitor stages in the NGN3
NULL
cells (Figure 3). This,
along with the global decrease in markers important for pancreatic endoderm and pancreatic progenitor
cell types, leads us to
hypothesize that NGN3 may be a
pioneer transcription factor that
is responsible for recruiting
SWI/SNF to pancreas-specific
enhancer sites in the genome to
create a chromatin landscape
required to specify pancreatic
progenitor cells. An important
experiment to test this hypothesis
would be to use single cell RNA
and single cell ATAC sequencing to understand gene expression dynamics underlying pancreatic cell
specification. Specifically, we will analyze chromatin accessibility near the potential NEUROG3 targets.
Combined enhancer activity, gene expression, and cell type specificity would allow inference of direct vs
indirect targets of NEUROG3.
Figure 3. SWI/SNF targets downregulated in NGN3NULL lines during early
pancreogenesis. Gene Set Enrichment Analysis (GSEA) was used to compare the
transcriptome of from pancreatic endoderm (S3), pancreatic progenitor (S4) and
endocrine progenitor (S5) between NGN3
NULL
and NGN3
CORR
cell lines.
NGN3
NULL
cells have a significant decrease in SWI-SNF chromatin remodeling
targets.
89
Part 2: Do SARS-CoV-2 infected beta cells recover, or die?
Our lab demonstrated that beta cells in non-human primates infected with SARS-CoV-2 had distended
endoplasmic reticulum (ER), and ruptured mitochondria that were in a state of glycolysis. Normal
functioning beta cells have high metabolic demand and usually operate under oxidative phosphorylation
(OXPHOS) to generate efficient and abundant amounts of ATP. Additionally, antioxidants created during
the OXPHOS process are important for removing reactive oxygen species (ROS) that build up in beta
cells. When considering what long-term effects COVID19 might have on patients it is important to note
that ER stress, glycolytic cell metabolism, and ROS are all implicated in the development of type 2
diabetes
22–26
.
There may be compounding insults that cause the mitochondrial dysfunction we observed in SARS-
CoV-2 infected beta cells. It is possible, as was demonstrated in human microglial cells in vitro, that
SARS-CoV-2 localizes to the mitochondria and results in elongated and ruptured membranes
27
. This
destruction might then result in the increase in reactive oxygen species, and a transition from an
OXPHOS state to a glycolytic state in metabolism. Additionally, studies of both SARS-CoV-2 S protein
and other SARS viruses show the virus tethers to the ER and uses it to form a double membrane layer to
shield from immune attack
28,29
. The tethering results in ER structure abnormalities, which slow or halt the
production of important proteins like those used for mitochondrial function.
The concerning shift in metabolism from OXPHOS to glycolysis brings about the possibility of these
beta cells eventually becoming cancerous. Otto Warburg first observed this metabolic shift in cancer cells
in the 1920’s. Recently, there has been some debate among cancer biologists about whether the Warburg
effect is reversable or whether it is even is heterogeneous within a single tumor
30–32,33
. There is also
debate about whether the metabolic shift is a direct result of mitochondrial structure defect, or whether
glycolysis is actively suppressing OXPHOS which later leads to mitochondrial structure defect
34
. If this
is the case in our SARS-CoV-2infected beta cells, the glycolytic pathway might be activated prior to
90
mitochondrial injury, and actively suppresses the OXPHOS pathway, leading to an increase in ROS.
Why exactly the beta cells shift towards this glycolytic metabolism remains to be investigated.
While it is a possibility that pancreatic beta cells in a prolonged state of glycolysis may become
cancerous, a hallmark of pancreatic beta cell tumors are high levels of circulating amylin, which we did
not see during our immunofluorescent stain for amylin. While it is possible that this could occur at later
timepoint beyond our study interval, I believe that the cells are more likely to die off than become
cancerous.
Interestingly we did not see evidence of apoptosis either. However, multiple studies have shown that
beta cells with ER dysfunction, as we see in our samples, are more likely to suppress the apoptosis
pathway temporarily and initiate the autophagy pathways in an attempt to save beta cell mass
35
.
Apoptosis, or programmed cell death, is a critical mechanism for removing dysfunctional cells from a
given tissue. Autophagy on the other hand, is the mechanism for degrading and recycling damaged and
dysfunctional organelles and proteins. This mechanism can protect cells from apoptosis and is common in
cells with poor regenerative capacity such as neurons, heart cell types, and beta cells. Further studies are
required to understand if that beta cells can recover after the initial injury from SARS-CoV2 infection,
and if they do, what are the mechanisms that govern this recovery? It is also critical to understand
whether vaccination prevents beta cell stress and dysfunction in subjects that are exposed to SARS-CoV-
2.
Part 3: Does Pregnancy Confer an Epigenetic Memory on Beta Cells?
While replication is uncommon in fully mature beta cells, beta cell mass expansion is critical during
pregnancy. We see greater beta-cell mass in pseudopregnant parous (PEP) mice, consistent with the
increase observed during pregnancy. The increase in beta-cell mass in PEP mice is due to the
proliferation of existing beta cells rather than expansion of beta-cell size. Our results suggest that a
previous pregnancy leads to enhanced beta-cell regeneration, and that multiparity endows protective
91
affects that allow for the increase in beta-cell mass. Replication of beta cells is therefore likely
orchestrated in part by epigenetic changes that occur during pregnancy.
In a paper from dos Santos et. al., they found that mammary glands from parous mice increased
the amount of ductal branching in response to pseudopregnancy more robustly than nulliparous mice
36
.
These parous mice also had a loss of DNA methylation at Stat5a, a gene important in cell replication.
Their experiments demonstrated that the first pregnancy primes DNA methylation patterns that are re-
activated during subsequent pregnancies. An important experiment for our lab will be to perform bisulfite
sequencing on isolated islets collected from our in vivo model of pseudopregnancy. Then, we can use the
findings to identify epigenetic changes that prime beta cell proliferation. We believe we will see similar
observations in beta cells as dos Santos et al found in mammary gland tissue. We hypothesize that
multiparous beta cells are primed to regenerate more effectively because epigenetic changes during a first
round of pregnancy remodels the epigenome to be prepared for future pregnancies. We expect that this
epigenetic memory does not drive beta cell expansion in the absence of signals but rather amplifies gene
activation and adaptive expansion of beta cell mass in response to lactogens and estrogen. These findings
may offer an inducible way to increase beta cell proliferation without the introduction of constructs
necessary to drive overexpression with potentially oncogenic proliferative factors.
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Abstract (if available)

Abstract Beta cells make up 1-4% of our pancreas, and loss or dysfunction of beta cells can be a catalyst for diabetes. While there are a unique set of environmental and genetic factors that can predispose humans to diabetes, all of these factors converge onto a common mechanism of pathogenesis: damage to the beta cell population, which does not recover. To improve public health and treatments related to diabetes, it is therefore essential to understand key molecular pathways regulating beta cell differentiation, regeneration, and susceptibility to injury. This dissertation studies primary examples of important endogenous and exogenous regulators of the beta-cell population. To understand how human beta cells differentiate, we studied the role of neurogenin-3 (NGN3). We applied a beta-cell differentiation protocol that guides patient-specific induced pluripotent stem cells to a pancreatic endocrine fate. To assess the requirement for NGN3 we isolated and differentiated stem cells from a pediatric patient with a genetic form of diabetes caused by a mutation in NGN3. To generate congenic control samples, we used CRISPR-Cas9 to correct the patient's mutation in vitro. While NGN3 is critical for beta-cell differentiation in mice, clinical and basic research data show that humans have compensatory mechanisms of beta-cell differentiation that confers normal endocrine function during early life. However, most NGN3-null patients lose beta-cell function and become diabetic during midchildhood. We found that this patient’s NGN3-null cells could not achieve proper endocrine differentiation in vitro. Although NGN3 is classically believed to function only in the final stage of endocrine differentiation, surprisingly, this patient’s NGN3-null cells also could not establish competent pancreatic progenitor cells earlier in differentiation, resulting in a ten-fold decrease in the patient's exocrine pancreas. These results support a novel function for NGN3 in early pancreatic progenitor specification. Our in vitro work has been directly translated into patient care because we both predicted the patient’s undiagnosed pancreatic insufficiency and were able to ameliorate their disease upon therapeutic intervention. ❧ Beta cells rarely replicate as a response to injury or disease but do so rapidly during pregnancy. The molecular mechanisms that regulate beta-cell replication during pregnancy are not fully understood but leveraging these cellular processes might help create drug therapies to help push beta cells to replicate in diabetic patients. While previous groups have relied on hormone receptor knockout and overexpression transgenic models to study pregnancy-induced beta-cell replication, our models are the first to allow researchers to investigate phenotypic changes induced by exogenous administration of the hormones themselves, a clinically relevant modality. To understand how beta cells regenerate, we developed in vivo and vivo models to study regeneration during pregnancy. We found that pseudopregnancy, induced by a cocktail of hormones, resulted in beta cell replication in human islets in vitro and in parous mice in vivo. Mechanistically, these cells induce STAT5 nuclear translocation resulting in beta cell replication. ❧ In addition, we studied beta-cell responses to SARS-CoV-2 infection. While virus-induced diabetes has been described in case reports and mouse models before, the limitations of collecting in vivo human data have hindered our ability to understand the cellular and molecular mechanisms behind disease progression. Here we used a novel in vivo non-human primate model and found that SARS-CoV-2- infected beta cells are atrophied, have insulin degranulation, exhibit severe metabolic disruption caused by unstructured mitochondria, and demonstrate reduced oxidative phosphorylation and increased glycolysis. Importantly, although the subjects’ lung function returned to normal in the post-acute phase of the disease, their beta cells became progressively more damaged and did not regenerate, suggesting that the damaging effects of SARS-CoV-2 can persist in the pancreas after the acute respiratory infection. In summary, this dissertation reveals fundamental new knowledge on the development, regeneration, and viral susceptibility of pancreatic beta cells. Our hope is that this research will inspire new avenues to help prevent and treat diabetes.

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Asset Metadata

Creator Millette, Katelyn (author)

Core Title Mechanisms that dictate beta cells’ response to stress in the context of genetic mutation, pregnancy, and infection

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Development, Stem Cells and Regenerative Medicine

Degree Conferral Date 2022-05

Publication Date 01/05/2022

Defense Date 09/27/2021

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

Tag Diabetes,endocrinology,OAI-PMH Harvest,pancreatic beta cell,stem cell

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Ryan, Amy (committee chair), Georgia, Senta (committee member), Patel, Pragna (committee member)

Creator Email millette@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC110455716

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