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Exploration of the role of ARHGEF10 in human disease

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Exploration of the role of ARHGEF10 in human disease

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Content Exploration of the role of
ARHGEF10 in human disease
By
Taylor Stucky
Mentor: Dr. Amy Merrill

A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
MASTER OF SCIENCE
(Biochemistry and Molecular Biology)
May 2018

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ACKNOWLEDGMENTS
I would like to thank my mentor, Dr. Amy Merrill, for her continued support and guidance and for
letting me pick a thesis topic that holds a special place in my heart. I would like to thank my
committee members, Dr. Pragna Patel and Dr. Baruch Frenkel for their comments and suggestions.
I would also like to thank my laboratory for their constant encouragement, especially Joanna Salva
and Lauren Bobzin for always making me smile and for turning bad days into good ones. I would
especially like to thank my parents for their never ending love and support and for encouraging
me throughout this process. And finally, I would like to thank all of my friends for believing in me
and for always being willing to listen to me talk about my project even when they had no idea what
I was talking about.

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TABLE OF CONTENTS
Acknowledgments………………………………………………………………………………..1
Abstract…………………………………………………………………………………………...3
Chapter 1. RhoGEFs and RhoGTPases….……………..………………………………………4
1.1 RhoGTPases: What they are and how they relate to RhoGEFs.……..…………………...4
1.2 Understanding RhoGEF structure and function……………….…….....….……………...8
Chapter 2. The Structure, Function, and Disease Mechanisms of ARHGEF10………........11
Chapter 3. ARHGEF10-related Disorders and Diseases……....……………………………..18
3.1 Charcot-Marie-Tooth (CMT) Disease.…………………….....…………………………19
3.2 Other Neuropathies….…………………..………………………………………………23
3.3 Cancer.....…….………………………………………………………………………….24
3.4 Neuropsychiatric and developmental disability disorders……………………………....26
3.5 Ischemic Stroke..….….………………………………………………………………....29
Chapter 4. Animal Models…………………………………………………………………..…30
4.1 The Leonberger dog as a model for CMT associated with ARHGEF10 …….…...…....31
4.2 ARHGEF10 transgenic mouse models ………………………………………………....33
References……………………………………………………………………………….………38

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ABSTRACT
Rho guanine nucleotide exchange factors (RhoGEFs) are known for their role as catalysts of Rho
family small guanosine triphosphatase (Rho GTPase) activation. RhoGTPases act as molecular
switches, playing a critical role in regulating the actin cytoskeleton, therefore affecting many
pathways involved in development and disease. With a recent link made between different
RhoGEFs and RhoGTPases in neurodegenerative disease, Rho guanine nucleotide exchange factor
10 (ARHGEF10) has become a new focus of study. While the function of ARHGEF10 is not
completely understood, its function is related to several human diseases including
neurodegenerative diseases, cancer, neuropsychiatric disorders, and stroke. In this literature
review, I analyze what is known about the structure and function of ARHGEF10 and discuss its
mechanistic role in disease, particularly in the context of neurodegenerative disease. In Chapter 1,
I evaluate what is known about RhoGTPases and RhoGEFs in general, examining structure,
function, and disease implication. In Chapter 2, I assess the structure, function, and mechanisms
of ARHGEF10 specifically. In Chapter 3, I review the diseases ARHGEF10 is involved in, with
special focus on Charcot-Marie-Tooth disease, a peripheral neuropathy affecting 1 in 2500 people.
In Chapter 4, I review the animal models currently used in the study of ARHGEF10-related
diseases and discuss how these models can help further our understanding of ARHGEF10 function.
ARHGEF10 is a critical gene in the future of disease research, and this review will underscore why
it should be studied more in depth.

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Chapter 1. RhoGEFs and RhoGTPases
Rho family small guanosine triphosphatases (Rho GTPases) are molecular switches that play a key
role in regulating the actin cytoskeleton. Rho guanine nucleotide exchange factors (RhoGEFs)
control RhoGTPases by converting RhoGTPases from their inactive (GDP-bound) state to their
active (GTP-bound) state. In Chapter 1.1, I look at RhoGEFs in the context of RhoGTPases, paying
special attention to the RhoA-related subfamily. In Chapter 1.2, I cover the general structure and
function of RhoGEFs. Recent studies have focused on the importance of RhoGEFs and
RhoGTPases in neurodegenerative disease with new data suggesting the importance of Rho
guanine nucleotide exchange factor 10 (ARHGEF10). By first understanding what is known about
RhoGEFs and RhoGTPases in general, we can better delve into the unique properties of
ARHGEF10 and how it affects neurodegenerative disease.
1.1 RhoGTPases: What they are and how they relate to RhoGEFs
It is nearly impossible to talk about RhoGEFs without doing so in the context of RhoGTPases.
RhoGEFs and RhoGTPases play a role in many systems but are best studied in the actin
cytoskeleton and in the nervous system, making both RhoGEFs and RhoGTPases important
subjects of study for development and disease fields. RhoGTPases are members of the Ras
superfamily, which are GTP-binding proteins that act as molecular switches for different cellular
processes (Feltri et al., 2008). They have a roughly 13 amino acid, α-helical, small GTPase domain
that is critical for GTPase function as well as two switch regions, known as switch 1 and switch 2,
which, depending on conformation, control the state, active or inactive, of the RhoGTPase
(Karnoub AE). Most of the proteins are small, only 190 to 250 residues long. RhoGTPases are
expressed in all eukaryotes, with 22 expressed in mammals (Wennerberg and Der, 2004; Wheeler
5

and Ridley, 2004). They are key regulators of morphology, movement, and behavior and are
involved in a number of pathways including gastrulation, neuronal development, muscle
development, immune response, as well as diseases including cancer, some mental retardation,
Amyotrophic Lateral Sclerosis (ALS), and faciogenital dysplasia, an X-linked skeletal dysplasia
(Etienne-Manneville and Hall, 2002; Schmidt and Hall, 2002). Originally, GTPases were known
for their effect on the actin cytoskeleton, but more recently their role in axonal development has
been a focus of study (Hall, 1998). RhoGTPases regulate different pathways by cycling through
inactive and active states depending on whether they are GDP or GTP bound, respectively. These
molecular “switches” are controlled by GEFs, GTPase activating proteins (GAPs), and GDP
dissociation inhibitors (GDIs), but for the purpose of this review, I will focus on the relationship
between GTPases and GEFs (Figure 1), mainly the RhoA subfamily and ARHGEF10,
respectively (Schmidt and Hall, 2002; Shibata et al., 2016; Wennerberg and Der, 2004).
The RhoGTPase subgroup consists of eight subfamilies including RhoA-related (RhoA, RhoB,
RhoC), Rac1-related (Rac1, Rac2, Rac3, RhoG), Cdc42-related (Cdc42, TC10, TCL, Chp/Wrch-
2, Wrch1), Rnd (Rnd1, Rnd2, RhoE/Rnd3), RhoBTB, TTF/RhoH, RhoD/Rif, and Miro (Miro-1
and Miro-2) (Feltri et al., 2008). Rho A, Rac1, and Cdc42 are the most studied (Wennerberg and
Der, 2004). ARHGEF10 targets the RhoA-related subfamily, which consists of RhoA, RhoB, and
RhoC. They share about 85% sequence homology but have differing roles in development and
Figure 1. Schematic of the RhoGTPase GTP activation by a GEF. GEFs catalyze the exchange of GDP for GTP,
activating the GTPase. Figure adapted from Schmidt and Hall, 2002 and Stankiewicz and Linseman, 2014.
6

disease, as well as differences in subcellular localization (Wennerberg and Der, 2004; Wheeler
and Ridley, 2004). Rho A is found mainly in the cytosol with some localized to the plasma
membrane, RhoB is found in the plasma membrane and in endosomes, and Rho C is found in the
cytosol and in perinuclear structures (Adamson, 1992; Michaelson et al., 2001; Wang et al., 2003;
Wennerberg and Der, 2004). Rho activity is critical to maintain focal adhesions in actin
cytoskeleton organization (Hall, 1998). RhoA specifically is also necessary to maintain proper cell
migration and RhoB is believed to be important in cell proliferation (Liu et al., 2001; Sit and
Manser, 2011). In development, knockout mouse studies showed that RhoB is not critical in early
development as RhoB
-/-
mice were still viable, though the exact function of RhoB is not well
understood (Prendergast, 2001; Wennerberg and Der, 2004; Wheeler and Ridley, 2004). RhoB
may not play a critical role in development like RhoA and C, but it is critical in endosomal
trafficking which sets RhoB apart from Rho A and C (Wheeler and Ridley, 2004). As far as disease
models, cancer studies have implicated Rho A, RhoB and RhoC in cancer development (Wheeler
and Ridley, 2004). Otherwise, not much is known about the function of RhoC. The overarching
theme is that Rho A, B, and C do not play redundant roles, but the distinct roles in each system
and the exact binding partners are not fully understood. Rhos can have differential binding
preferentiality, and the function of each Rho may depend partially on binding efficiency and
partially on localization (Wennerberg and Der, 2004). ARHGEF10 interacts with all three;
however, the differing effects of these interactions are not completely obvious. Future studies on
Rho binding partners may better elucidate the mechanisms by which RhoGTPases control different
signaling pathways and could be good targets for a myriad of disease therapies.
Relevant to ARHGEF10, is the role of GTPases in neurodegenerative disease. Within the Rho
family of GTPases, RhoA-related activation and Rac1-related activation work opposite each other,
7

Rho causing neuronal death and Rac neuronal survival (Stankiewicz and Linseman, 2014). I will
focus on the RhoA-related subfamily as these are the substrates of ARHGEF10. Rho A is better
characterized than RhoB and C in neuronal development (Stankiewicz and Linseman, 2014). It
most likely has cell-type specific function during neuronal development as different knockdown
studies got different results depending on cell type; however, knock-in studies did suggest that
RhoA affects neural stem cell proliferation as these mice had increased numbers of neurons (Sanno
et al., 2010; Stankiewicz and Linseman, 2014). RhoA
-/-
neurons did not migrate properly due to
issues with the actin cytoskeleton, suggesting that RhoA also affects migration (Cappello et al.,
2012; Stankiewicz and Linseman, 2014). While RhoB is less studied, there is evidence that it also
affects neuronal development with minor impairments to memory and neuronal branching, but in
line with previous studies, RhoB is probably important in very specific areas of development
(Stankiewicz and Linseman, 2014; Wheeler and Ridley, 2004). Different neurodegenerative
diseases and traumas have been shown to be due to mutations in various RhoGTPases and
RhoGEFs including ALS, Alzheimer’s disease, Charcot-Marie-Tooth (CMT) disease, Spinal Cord
Injury, and Cerebral Ischemia and reperfusion, suggesting a critical role for RhoA-related GTPases
and RhoGEFs, like ARHGEF10, in neuronal development and maintenance. It will be important
to look at affected pathways that intersect in these diseases to choose the best proteins or pathways
to target when assessing treatment options to neurodegenerative diseases. It is plausible that the
pathways causing these diseases intersect or overlap significantly by way of RhoGEFs and
RhoGTPases. Future studies working out these disease mechanisms will prove extremely valuable
in both our basic understanding of the biology and disease studies. It is clear from examining the
RhoA-related GTPases and RhoGTPases in general that RhoGEFs, and ARHGEF10 specifically,
cannot be discussed without having a basic knowledge of RhoA, RhoB, and RhoC. Any
8

understanding of disease mechanism or normal development due to ARHGEF10 must be reviewed
in the context of these GTPases. With a clearer understanding of RhoGTPases and their interaction
with RhoGEFs, we can now review the structure and function of RhoGEFs.
1.2 Understanding RhoGEF structure and function
In order to talk about ARHGEF10, it is important to understand the structure and function of
RhoGEFs in general. As was covered in Chapter 1.1, they are accessory proteins, which catalyze
the exchange of GDP to GTP in RhoGTPases, thus activating a cellular response (Abiko et al.,
2015; Mohl et al., 2006). There are roughly 70 known RhoGEFs, including ARHGEF10, in the
Dbl family, so named for the first known mammalian GEF, Dbl. Dbl was found to contain a
conserved domain of roughly 200 residues, now known as the Dbl homology (DH) domain
(Rossman et al., 2005; Schmidt and Hall, 2002). This domain is responsible for GEF activity by
acting as the site of catalysis for the exchange of GDP for GTP in RhoGTPases (Eva and Aaronson,
1985; Hart et al., 1994; Rossman et al., 2005; Schmidt and Hall, 2002). The DH domain is
comprised of 10-15 α- and 310 –helices that form a “chaise lounge” structure (Rossman et al., 2005;
Soisson et al., 1998). DH domains are characterized by three conserved regions known as CR1, 2,
and 3 which are α-helices that make up the majority of the GTPase-binding surface (Schmidt and
Hall, 2002). Other than these three regions, DH domains can share less than 20% of their sequence
(Rossman et al., 2005; Schmidt and Hall, 2002). The DH domain conformation, however, is highly
conserved among Dbl family GEFs (Schmidt and Hall, 2002). The “chair back” of the DH domain
and the β2 and 3 strands of the GTPase mostly orchestrate DH selectivity. These structures vary
greatly among different GEFs and GTPases, allowing for binding specificity (Rossman et al.,
2005). In most RhoGEFs, DH domains are found next to a Pleckstin Homology (PH) domain,
which is believed to localize the GEF to the plasma membrane and aid in GEF activity (Rossman
9

et al., 2005; Verhoeven et al., 2003). PH domains are made up of roughly 100 amino acid
sequences and bind to the lipid products of phosphatidylinositol 3-kinase (Rossman et al., 2005).
The DH and PH domains, form an L-shaped structure as seen in the well-characterized GEF, SOS1,
in Figure 2; however, I will discuss how this may not be the case in ARHGEF10 (Rossman et al.,
2005; Soisson et al., 1998). Besides the DH and PH domain, GEFs have domains unique to their
specific role (Rossman et al., 2005). Understanding the structure of specific GEFs can help in
determining their function and what pathways they affect. Future studies that look to characterize
the structure of specific RhoGEFs, especially those that are found to play a role in disease, will
help in our understanding of the different functions of RhoGEFs and in what pathways they
partake.
Figure 2. Ribbon structure of the GEF, human SOS1 (Son of Sevenless homolog 1). PH domain is in yellow,
DH domain is in blue, and linker is in red. CR1, 2, and 3 are labeled to show conserved regions (Schmidt and
Hall, 2002; Soisson et al., 1998).
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Understanding structure helps in uncovering function, though often the function of a protein is
more complicated than a one-protein, one-pathway model. More is known about the function of
RhoGTPases than of RhoGEFs, but one known role of several RhoGEFs, including ARHGEF10,
is in proper morphology of vascular endothelial cells (Abiko et al., 2015). RhoGEFs are involved
in the process of vascular endothelial cell rearrangement instigated by mechanical pressure on the
cells due to blood flow (Abiko et al., 2015; Jufri et al., 2015). Since so many RhoGEFS are
involved, it is difficult to parse apart the role of each individually and it was beyond the scope of
this study; however, it was found by knockdown studies that at least 11 RhoGEFs with varying
GTPase targets and domain structures all affect this process. This study mused that ARHGEF10,
along with four other RhoGEFs that all target RhoA, are important in “reassembly of focal
adhesions and stress fibers perpendicular to the stretch axis” (Abiko et al., 2015). As this study is
less than three years old, it is apparent that our understanding of RhoGEF function is still lacking
in many ways. RhoGEFs definitely function in more systems than just proper morphology of
vascular endothelial cells, but often times the RhoGTPases in these pathways are studied for
specific mechanism instead, leaving a gap in the RhoGEF knowledge. Through more recent
studies, we are starting to understand the general systems that RhoGEFs affect and how they act
through GTPases; however, the specific role that each RhoGEF plays in each system is far from
understood. Interestingly, RhoGEFs outnumber RhoGTPases in mammals by more than 3 times,
suggesting that regulation of RhoGTPases by RhoGEFs is more complicated than a simple GEF-
GTPase interaction, and may rely on localization or other protein interactions (Schmidt and Hall,
2002). Clearly much is still to be learned about how RhoGEFs operate and their role in regulating
RhoGTPases. Though some RhoGEFs are better understood than others, ARHGEF10 is one that
is particularly not well understood, despite its prevalence in a multitude of human diseases. As I
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will discuss in this review, ARHGEF10 is an extremely relevant RhoGEF to modern medicine and
deserves to be given more attention in the literature.
Chapter 2. The Structure, Function, and Disease Mechanisms
of ARHGEF10
Though ARHGEF10 has been studied for over 20 years, the overall understanding of its structure
and function is still not well worked-out. Studies have linked mutant ARHGEF10 to slowed nerve
conduction velocities, CMT disease, other polyneuropathies, cancer, neuropsychiatric disorders
including schizophrenia, addiction, and suicidal tendencies, developmental disabilities, and
ischemic stroke, but the mechanisms behind these diseases have not been elucidated (Beutler et
al., 2014; Boora et al., 2015; Chaya et al., 2011; Clive et al., 2016; de Toro-Martín et al., 2017;
Huang et al., 2010; Jungerius et al., 2008; Kalsi et al., 2016; Li et al., 2017; Matsushita et al., 2010;
Shi et al., 2017; Tabares-Seisdedos and Rubenstein, 2009; Yin et al., 2011; Zee et al., 2014).
ARHGEF10 has thus far only been found in vertebrates, making understanding its function an
even more important topic of study, as it is most likely a highly specific RhoGEF. This is
implicated by the wide array of human diseases caused by aberrant ARHGEF10 signaling
(Verhoeven et al., 2003). Recent literature is beginning to shed light on the structure of
ARHGEF10 and how it specifically functions as a RhoGEF, though there is still much to be
learned.
ARHGEF10 is located on chromosome 8p23 (Verhoeven et al., 2003). Chromosome 8p is thought
to be a region connected to neuropsychiatric disorders as well as other diseases such as cancer,
which makes ARHGEF10 a fascinating disease target of study (Clive et al., 2016; Tabares-
Seisdedos and Rubenstein, 2009). The mouse orthologue, Gef10, (Figure 3) was used to show that
12

ARHGEF10 is expressed ubiquitously in mammals (Verhoeven et al., 2003). ARHGEF10 has at
least two splice variants, but up to 5 predicted sequences (Mohl et al., 2006; UniProt, 2017). The
functional difference in the isoforms has yet to be determined and may make an interesting point
of further study as more mutations that result in different diseases are found. One could speculate
that the isoform affected determines the type or severity of the disease.
As far as protein structure is concerned, it is accepted that ARHGEF10 contains a DH domain like
other Dbl family GEFs; however, other domains are still debated (Aoki et al., 2009; Shibata et al.,
2017; UniProt, 2017). Though normally having a DH domain would also mean having a PH
domain, multiple studies were either unable to detect or detected a highly unusual PH domain in
ARHGEF10 (Mohl et al., 2006; Verhoeven et al., 2003). One study stated the presence of a PH
domain, based on the Mohl et al. (2006) study. However, the Mohl et al. (2006) study specifically
states that if there is a PH domain, it is highly unusual. To our knowledge, no other studies have
definitively found ARHGEF10 to have a PH domain, but the presence of the domain is still highly
controversial in the study of ARHGEF10 (Aoki et al., 2009). Having a definitive understanding of
whether or not the PH domain is present in ARHGEF10 could greatly aid in understanding its
localization and function as a GEF.
As the presence of other domains in each RhoGEF depends on the function of each GEF, and not
much is known about ARHGEF10 function, it is impossible to assume the presence of other
specific domains. There are a couple domains mentioned in some of the ARHGEF10 literature,
Figure 3. Human and mouse ARHGEF10 and Gef10 genomic alignment. Dark grey represents DH domain
(Verhoeven et al., 2003).
13

including a WD40-like domain. WD40 domains are extremely common in eukaryotes and are
made up of a repetitive motif of around 40 residues with highly conserved GH dipeptides. They
form a β-propeller and are highly interactive, functioning as adaptors in protein-protein and
protein-DNA interactions (Chao Xu, 2011). ARHGEF10 is also widely considered to have two
transmembrane segments or α-helices at the C-terminus; however, subcellular localization studies
show ARHGEF10 in the cytosol, specifically in cytoplasmic vesicles (Mohl et al., 2006; Shibata
et al., 2017). Due to the results from these studies, the function of the transmembrane helices is
not understood. It is possible they play a role when ARHGEF10 is in an activated state as some
GEFs are known to redistribute from the cytoplasm to the membrane during activation, but this
has not been studied specifically in ARHGEF10 (Mohl et al., 2006; Schmidt and Hall, 2002).
Future studies focusing on ARHGEF10 localization during activation may make the role of the α-
helices more obvious. In a study utilizing a naturally occurring dog model, an ARHGEF10
mutation caused a truncation of the protein which the paper concluded removed a WD40-like
domain as well as the two transmembrane segments, leading to polyneuropathy in the animals
(Ekenstedt et al., 2014; Yu et al., 2000). From this, we can conclude that either the WD40-like
domain, the transmembrane segments, or the two in conjunction play an integral role in the proper
function of ARHGEF10, though the exact function of the protein in polyneuropathy still remains
unclear.
With all of this domain data taken together, the overall domain sequence for ARHGEF10 most
likely resembles the diagram presented for Gef10 in Figure 4. It should be noted, however, that
the year following the study this domain sequence was proposed in, a study came out claiming
ARHGEF10 contains a post synaptic density protein (PSD95), Drosophila disc large tumor
suppressor (Dlg1), and zonula occludens-1 protein (zo-1) (PDZ) domain at the C-terminus (García-
14

Mata and Burridge, 2007). PDZ domains are 90 amino acid domains which modulate protein-
protein interactions, aiding specifically in signal transduction (García-Mata and Burridge, 2007;
Lee and Zheng, 2010). They are common in RhoGEFs; however, this study fails to cite either their
methods for determining this domain or other papers in which they found this information for
ARHGEF10 specifically (García-Mata and Burridge, 2007). A recent study claims that the DH
domain and a PDZ binding motif are the only distinct structures in ARHGEF10, but previous
studies along with the UniProt protein database (UniProtKB - O15013 (ARHGA_HUMAN))
claim the domains shown in Figure 4 (García-Mata and Burridge, 2007; Mohl et al., 2006; Shibata
et al., 2017; UniProt, 2017). Clearly, the structure of ARHGEF10 is still debated and further
research needs to be done to understand the exact domain structure of the protein.
In addition to the structure, the function of ARHGEF10 as a RhoGEF is not well understood. More
recent studies have started to elucidate the roles of ARHGEF10, but as it is a ubiquitously
expressed protein and affects many different diseases and systems, there may be many functions
for the protein. One function of ARHGEF10 first started to come to light when a study examined
the genetics of a family with a non-progressive and mild clinical phenotype of slowed nerve
conduction and thinned myelin sheaths. Their mutation did not fit any of the known genetic
Figure 4. Proposed domain sequence for canonical Gef10. Numbers represent amino acid (aa) residues. There
are two transmembrane segments (TM), a Dbl homology (DH) domain, an unusual (if existent) pleckstrin
homology (PH?) domain, and a WD40-like (WD40) domain (Mohl et al., 2006; Schmidt and Hall, 2002).

15

mutations for CMT disease, a peripheral neuropathy also characterized by these phenotypes (De
Jonghe et al., 1999; Verhoeven et al., 2003). Analysis of mutations in the family showed a C  T
missense mutation in exon 3 of ARHGEF10, leading to a Thr109Ile change in ARHGEF10
(Verhoeven et al., 2003). Though Thr109 is not part of the DH domain, after sequence alignment
with orthologues in macaque, puffer fish, and mouse, it was shown to be a conserved residue,
meaning the mutation likely affected the normal function of the protein (Verhoeven et al., 2003).
Since RhoGTPases are known to be involved in determining neuronal morphology, it is plausible
that ARHGEF10 affects nerve conduction velocity and myelination through affecting the
activation of one or more RhoGTPases (Etienne-Manneville and Hall, 2002). The family study
was able to conclude that ARHGEF10 most likely plays a role in proper peripheral nerve
development, though the exact mechanism was not in the scope of the study (Verhoeven et al.,
2003). Though one general function for ARHGEF10 is now understood, the detailed mechanism
is still not fully elucidated, leaving us mostly in the dark as to how ARHGEF10 actually regulates
peripheral nerve development.
Later studies looked at ARHGEF10 in more mechanistic detail, though not for nerve conduction
specifically, and linked its cellular function to Rab6 and Rab8 membrane trafficking. Rabs, also
members of the Ras superfamily, function as molecular switches as well. Membrane trafficking is
critical to cellular function and Rabs play a pivotal role in ensuring specificity and directionally of
trafficking (Shibata et al., 2016; Shibata et al., 2017). Using an antibody against ARHGEF10 along
with overexpression and knockdown studies, it was determined that ARHGEF10 localizes to
exocytotic vesicles containing both Rab6 and 8 (Shibata et al., 2016). 60% of ARHGEF10 positive
vesicles contained Rab6 or 8, and an interaction was confirmed by an immunoprecipitation assay
of overexpressed ARHGEF10 with Rab6 and Rab8. When Rab6 was knocked down, ARHGEF10
16

localization to vesicles decreased, and knockdown of ARHGEF10 led to improper localization of
Rab8, meaning ARHGEF10 localizes in a Rab6-dependent manner and aids in proper localization
of Rab8. Rab8 is known to be important for many cell functions including establishing cell
polarity, and it is plausible that ARHGEF10 mediates establishment of cell polarity through
association with Rab8 (Hattula et al., 2002; Shibata et al., 2016; Shibata et al., 2017). However,
DH domain mutants specific to GEF function versus DH domain truncation showed that the DH
domain, but not GEF activity, controlled localization of ARHGEF10 to the vesicles. Therefore,
the later experiments do not answer how ARHGEF10 functions as a GEF. Based on assays
examining mutant RhoA, the study concluded that ARHGEF10 does not act as a GEF in this
transport pathway but rather as a scaffolding protein (Shibata et al., 2016). The conclusion of this
study that GEF activity is not necessary for localization seems plausible based on the experiments,
though I am skeptical in their conclusion that the DH domain is necessary. A DH domain
truncation would most likely affect the overall protein structure in more ways than just affecting
the DH domain, and it is possible that protein conformation plays a large role in ARHGEF10’s
ability to localize to the vesicles. Perhaps truncating the DH domain alters the conformation and
makes it impossible for Rab6 to recognize ARHGEF10. Further studies would need to be done to
understand why changing the DH domain but not GEF activity alters ARHGEF10’s ability to
localize to vesicles; however, from this study we learned that ARHGEF10 functions in membrane
trafficking which is critical in proper cellular function, even though the function of ARHGEF10
as a GEF is still not well understood. It is possible that ARHGEF10 still uses its GEF
characteristics in membrane trafficking, just not for localization, as it seems unlikely that a known
GEF would function in a completely non-GEF manner. Further studies on ARHGEF10 as both a
17

scaffolding protein and as a GEF could help bridge the gap between the Rab and Rho systems and
help us understand how ARHGEF10 functions in cellular pathways.
Some is known about the pathway in which ARHGEF10 controls RhoA signaling. However, the
study that published these results has been questioned by later studies that did not get similar
results, including differences in protein domain structure. This study looked at cell division
specifically, with no mention of signaling in the context of membrane trafficking, though this was
not the goal of the study. Through a pull-down assay, they showed that ARHGEF10 functions as
a GEF for RhoA, which is known to play a role in cytokinesis and mitosis. Localization studies
showed that ARHGEF10 and RhoA were localized to centrosomes in HeLa cells during G1/S and
M phases (Aoki et al., 2009). This led to the assumption that ARHGEF10 may help control cell
division. Knockdown studies were used to reduce centrosome-localized ARHGEF10 and as a
result spindle formation was irregular. The same results occurred when RhoA was knocked down,
but constitutive RhoA rescued ARHGEF10 knockdowns, suggesting ARHGEF10 functions
upstream of RhoA. Based on how ARHGEF10 knockdown cells progress through the cell cycle,
it is likely that ARHGEF10 regulates RhoA during interphase. Through immunoprecipitation
assays, localization studies, and knockdown studies, ARHGEF10 was also shown to interact with
the motor protein Kinesin family member 3B (KIF3B) which functions in chromosome movement.
Though there may be some sort of KIF3B-ARHGEF10-RhoA pathway regulating centrosome
formation, it is also possible KIF3B acts through a separate mechanism (Aoki et al., 2009). Further
studies need to be done focusing on the relationship between ARHGEF10 and KIF3B to confirm
a regulation pathway. It should be noted that other studies did not see ARHGEF10 localized to the
centrosomes, though this may be a reflection on antibody or cell culture differences (Shibata et al.,
2016). Unless there is a specific isoform of ARHGEF10 that localizes to centrosomes and this is
18

why it was not detected by later studies, this seems unlikely. This would be worth investigating to
understand possible functional differences between the isoforms. Though this study shed new light
on the GEF properties of ARHGEF10, the exact mechanism that ARHGEF10 functions in during
cell division is still unclear.
Overall, our understanding of the exact structure and function of ARHGEF10 is lacking. Though
the structure is beginning to be understood, there are still domains in question and better knowing
the true structure could help in understanding protein function. Progress is starting to be made in
understanding the function of ARHGEF10 in membrane trafficking and the role as a GEF in cell
division; however, how this all fits together into mechanisms and how this leads to disease remains
a mystery. For nerve conduction, studies are beginning to think about the link between nerve
myelination and membrane trafficking, which is a good starting point for relating function and
disease (Shibata et al., 2017). Future studies focusing on specifically following ARHGEF10 during
membrane trafficking using different disease mutants may help elucidate the function of
ARHGEF10. As a whole, there is still much room for exploration on the structure and function of
ARHGEF10.
Chapter 3: ARHGEF10-related Disorders and Diseases
ARHGEF10 has been linked to many types of diseases, as it is critical across different organ
systems for development and homeostasis. This section will touch on diseases including Charcot-
Marie-Tooth (CMT) disease, other neuropathies, cancer, neuropsychiatric disorders, and ischemic
stroke. Here, I will focus on the role of ARHGEF10 in CMT, as the role of this gene in
neurodegenerative disease has become a new topic of study in recent years.

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3.1 Charcot-Marie-Tooth (CMT) Disease
Recent studies focusing on ARHGEF10 have brought to light the important role of this gene in
neurodevelopment. The link between ARHGEF10 and neurodevelopment has stemmed from the
finding that mutations in ARHGEF10 cause CMT disease. CMT is the most common inherited
neuropathy with a prevalence in the United States and European populations of 1 in 2500 people
(Skre, 1974). In the more than 120 years since its discovery, over 90 genes and counting have been
associated with the disease (Pisciotta and Shy, 2018). CMT is a heterogeneous disease, with
different mutations in the same gene sometimes giving rise to different phenotypes and mutations
in different genes giving rise to the same phenotypes. This has made the genetics behind CMT
incredibly fascinating yet difficult to understand (Pareyson, 1999). Clinically, CMT is
characterized by distal muscle weakness and atrophy leading to foot drop and abnormal gait, foot
deformities including hammer toes, decreased tendon reflexes, and distal sensory loss. The severity
of these symptoms can vary greatly between individuals. (Pareyson, 1999; Stendel et al., 2007).
CMT is categorized by types 1, 2, 3, 4, and X, the most common being CMT1 (Nelis et al., 1998;
Noto et al., 2015). The disease can be either demyelinating or axonal. CMT1 is comprised of the
autosomal dominant demyelinating cases, CMT2 is the dominant axonal cases, CMT3 is an
extremely rare early onset demyelinating type, CMT4 is autosomal recessive cases, and CMTX is
the X-linked type (Pisciotta and Shy, 2018). Whether CMT is axonal or demyelinating can be
determined through nerve conduction studies (NCS). Nerve conduction velocities (NCV) of
<38m/s are demyelinating type and those >38m/s are axonal type (Noto et al., 2015). Patients with
NCVs that fall close to 38m/s are often considered to have intermediate CMT as is common in
CMTX (Noto et al., 2015; Pareyson, 1999). As ARHGEF10 affects myelin and patients with
ARHGEF10 CMT have moderately slowed NCVs, ARHGEF10-associated CMT could be either
20

CMT1 or an intermediate CMT. One study showed that a patient with a novel mutation in
ARHGEF10 was originally diagnosed with CMT2 but had both moderately slowed NCVs and
increased cross-sectional area of peripheral nerves. These characteristics were found consistent
among CMT1A patients as well, lending evidence to the argument that ARHGEF10 CMT is most
likely CMT1 (Noto et al., 2015). Since ARHGEF10 is associated with CMT1, this subtype will be
the focus of this CMT review.
A handful of studies have looked at the connection between ARHGEF10 and CMT disease, but
the mechanism through which mutations in ARHGEF10 causes the CMT phenotype is largely
elusive. CMT1A is the most common form of CMT and it is caused by a duplication affecting
PMP22, a gene that codes for peripheral myelin protein on chromosome 17p12 (Lupski et al.,
1991; Raeymaekers et al., 1991; Roa et al., 1991). Insight into the role of ARHGEF10 has been
examined from the perspective of PMP22, which has been the focus of much CMT research at this
point. Since PMP22 has been associated with both point mutations and copy number variant
mutations, the effects of ARHGEF10 duplications on CMT disease were examined. Though
ARHGEF10 was found to have duplications affecting either exon 2 or intron 11 in multiple CMT
patients, the copy number variants were found in the general population as well, making
duplication an unlikely cause of CMT (Huang et al., 2010). It is more likely that point mutations
affecting ARHGEF10 cause the CMT phenotype. Several de novo point mutations have been found
in ARHGEF10 CMT patients, the most well-known being the T109I/T332I mutation (Chaya et al.,
2011; Verhoeven et al., 2003). The mutation was found in a family with moderately slowed NCVs
and thin myelin sheaths. Although this family did not present clinically with the typical symptoms
of CMT disease, their symptoms were the first to link ARHGEF10 to peripheral nerve development
and maintenance, and this family is usually cited as a CMT family in the literature (Verhoeven et
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al., 2003). The original study refers to this mutation as T109I, but a later study following up on the
mechanism refers to it as T332I (Chaya et al., 2011; Verhoeven et al., 2003). The sequencing of
ARHGEF10 was revised after the original paper, thus changing the amino acid from 109 to 332,
so I will refer to the mutation as T332I for consistency (Chaya et al., 2011). The T332I mutation
is located in a conserved negative regulatory region in the N terminus, so the mutation causes
constituent activation of GEF activity in ARHGEF10. This was determined through truncation
mutant studies. A mutation causing an N-terminal truncation modified morphology in HEK293T,
HeLa, and Schwann cells by increasing cell contraction. However, RhoA-Rho-kinase (ROCK)
inhibitor inhibited this contraction, leading to the conclusion that cell contraction is regulated by
Rho-ROCK signaling. A pulldown assay was used to show that the truncation mutants give rise to
increased ARHGEF10-RhoA activity. RhoB and RhoC activity were also increased. The N-
terminal region normally represses GEF activity; however, the specific amino acid sequence that
represses GEF activity was not known. They narrowed down the range of the deletion by creating
smaller truncations that did not have the same effects on GEF activity. Through this approach they
narrowed down the region of GEF repression to amino acids 212-332. However, transfecting N-
terminal mutation cells with amino acids 212-332 did not rescue the contraction phenotype,
suggesting that amino acids 212-332 are necessary but not sufficient for GEF activity repression.
While the exact mechanism of how this truncation leads to slowed NCVs is not fully elucidated,
it is hypothesized based on the experiments above that the mutation impairs myelination by
activating Rho-ROCK signaling which in turns leads to shortening of Schwann cell process
extensions (Chaya et al., 2011). This study is monumental as it is one of the first studies to look
at the mechanism of how a ARHGEF10 mutation leads to a disease phenotype. Future work
expanding on this study and examining other mutations will be instrumental not only in
22

understanding the normal function of ARHGEF10 in neurodevelopment, but also in leading
towards treatments for ARHGEF10-associated disease, particularly neuropathies like CMT
disease. It should be noted that Rho GTPase activity has been shown to be important for proper
myelination of the peripheral nervous system, so it is not far-fetched that ARHGEF10 would affect
the nervous system in this way (Stendel et al., 2007).
Another important note on CMT pathology is that endocytic recycling plays a role in
demyelination. In CMT4 patients, mutations in SH3TC2 have been shown to disrupt
SH3TC2/Rab11 interactions, disrupting endocytic recycling, and causing impaired myelin
formation (Roberts et al., 2010; Stendel et al., 2010). It is possible that some ARHGEF10 mutations
affect membrane trafficking as well since ARHGEF10 aids in the proper localization of Rab8 in
vesicles (Shibata et al., 2016). Studies focusing specifically on the effect of ARHGEF10-Rab8
interactions in Schwann cells would help elucidate if this has a role in the CMT disease process.
It is possible that different ARHGEF10 mutations cause pathology in different ways, as it is
common for mutations in the same gene to cause different types of neuropathy (Pareyson, 1999).
Specific mutations will need to be analyzed to understand the mechanism or mechanisms by which
ARHGEF10 mutations cause CMT.
CMT disease is caused by a wide array of gene mutations, covering at least 90 genes. Advances in
genetic testing are unveiling new CMT genes and helping us understand the pathways involved in
neurodegeneration. Many of the genes involved in CMT, including ARHGEF10, can also give rise
to other neuropathies (Pareyson, 1999). By studying ARHGEF10 mutations found in CMT
patients, we can start to uncover the role of ARHGEF10 in myelination, eventually leading to
treatments not just for CMT but for other neuropathies as well.

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3.2 Other Neuropathies
CMT disease makes up the hereditary polyneuropathies, but there are also acquired
polyneuropathies. One of the main acquired neuropathies is seen in cancer patients and is known
as chemotherapy-induced peripheral neuropathy (CIPN). As CIPN is nearly impossible to predict,
recent studies have looked at the genetic variants found in CMT for clues as to why some patients
get CIPN and others do not (Beutler et al., 2014). In a case study of a 52 year old woman who
developed muscle weakness, atrophy, some sensory loss, and reduced reflexes after administration
of vincristine, it was found that the woman had the PMP22 duplication that is hallmark of CMT1A
(Hildebrandt et al., 2000). The duplication was also found in a 55 year old woman with breast
cancer after administration of docetaxel, trastuzumab, and pertuzumab caused her to develop
numbness and sensory loss in the extremities, decreased tendon reflexes, high arched feet, and foot
drop (Kourie et al., 2017). In cases like these, chemotherapeutic agents can be the catalyst for
underlying CMT to arise. This makes screening patients for known CMT disease genes important
for choosing the best cancer treatment options. As ARHGEF10 is a CMT-associated disease gene,
it has been studied as a potential risk gene for CIPN. Though different cancer drugs have been
studied, paclitaxel has been the main drug of focus in studies that include ARHGEF10 (Beutler et
al., 2014; Boora et al., 2015). Beutler et al. (2014) assessed 49 CMT genes for CIPN association
after paclitaxel. Two genes, PRX and ARHGEF10 were found to be associated. Specifically, three
ARHGEF10 single nucleotide variants (SNVs), rs9657362, rs2294039, and rs17683288 were
associated. Of these, rs9657362 had the strongest effect as a protective allele. Rs17683288 was
also protective, while rs2294039 was a risk allele (Beutler et al., 2014). These SNVs were
confirmed by different methods in a later study (Boora et al., 2015). The protective ARHGEF10
SNVs make potential therapeutic targets. If drugs targeting ARHGEF10 SNVs can be used to
24

combat CIPN, they can be given alongside paclitaxel to mitigate the side effects (Beutler et al.,
2014). A recent critical review of CIPN studies looked at the methodology of the above studies
and determined that the ARHGEF10 SNVs are indeed good candidates for future research and
CIPN prevention (Cliff et al., 2017). After examining studies showing allelic variability in
ARHGEF10, a recent study looked at the effects of paclitaxel on ARHGEF10 mRNA expression
in rats to help understand the mechanism causing CIPN. The rats were given paclitaxel and
measured with the von Frey and acetone test for mechanical allodynia and cold hyperalgesia, pain
related CIPN symptoms, respectively. Spinal cord samples were used to measure mRNA levels of
Arhgef10 but no differences in mRNA level were found in the paclitaxel rats (Yamashita et al.,
2017). This suggests that mRNA level of ARHGEF10 is not a factor in paclitaxel-induced CIPN,
though this does not mean that ARHGEF10 is not an important risk factor in CIPN. It is possible
that the variants change the way ARHGEF10 or proteins in pathways that ARHGEF10 affects
interact with paclitaxel without modifying the amount of ARHGEF10 present. Future studies
assessing these interactions and ARHGEF10 as a potential target of preventative medicine for
CIPN could reduce the likelihood of getting CIPN from cancer drugs like paclitaxel. As CIPN is
extremely deleterious to a patient’s life, often permanently, any advances towards CIPN
prevention are significant.
3.3 Cancer
Any gene that serves as an oncogene or tumor suppressor generally plays a role in cancer, and
ARHGEF10 is no exception. Though the mechanism of ARHGEF10-related cancer is not well
understood, many studies in different types of cancer have shown ARHGEF10 to be an important
factor in cancer risk and progression. ARHGEF10 is located on chromosome 8p which is one of
the most commonly altered genomic regions across many types of cancer (Cooke et al., 2008;
25

Tabares-Seisdedos and Rubenstein, 2009). Chromosome 8p has many oncogenes and tumor
suppressors, and loss of heterozygosity of 8p has been correlated with metastasis in several types
of cancers (Tabares-Seisdedos and Rubenstein, 2009). Loss of heterozygosity of ARHGEF10
specifically is common in tumor tissue of sporadic colorectal cancer, which is the second most
lethal form of cancer (Druliner et al., 2018). Understanding how ARHGEF10 loss of
heterozygosity affects tumor formation and progression will be critical in personalized treatment
for aggressive cancers like colorectal cancer. Loss of ARHGEF10 was also seen in pancreatic
adenocarcinoma, the cancer with the highest mortality, often due to late detection (Birnbaum et
al., 2011). Using ARHGEF10 loss as a biomarker could help in earlier detection, leading to a better
chance at successful treatment and survival. Understanding that ARHGEF10 functions as a tumor
suppressor is critical in understanding its role in cancer. This was shown in breast cancer where a
C  T point mutation in exon 19 was found to cause a histidine to tyrosine substitution in a highly
conserved region in DU4475 cells, a breast cell line, where the other copy of the gene was deleted
(Cooke et al., 2008). Additionally, multiple mutations in ARHGEF10 have been found in the 639V
urinary tract epithelial cell line. Specifically, two different biallelic point mutations were found to
inactivate ARHGEF10, leading to loss of tumor suppressor function (Williams et al., 2010). Since
ARHGEF10 is a tumor suppressor that affects many types of cancer, and since it is in a genomic
region that is frequently disturbed in cancers, ARHGEF10 is an excellent candidate gene for future
studies relating to targeted therapy and personalized medicine.
The more we learn about cancer, the more it becomes clear that pathways, not individual genes,
are what cause and affect the progression of cancer (Wood et al., 2007). RhoGTPases, including
RhoA and RhoB, have been implicated in multiple types of cancers, including the extremely lethal
cutaneous melanoma and brain tumors (Forget et al., 2002; Liu et al., 2017; Mazieres et al., 2004).
26

As RhoGTPases control cell division and motility, in addition to other functions, it is no surprise
that deregulation of RhoGTPases has been implicated in melanoma metastasis. One possible
mechanism is that mutations in ARHGEF10 affect Sp1 binding, leading to an increase in
ARHGEF10 transcription, and therefore an increase in RhoA expression (Liu et al., 2017).
Increased RhoA expression has been correlated with colon, lung, and breast cancers; however, loss
of RhoA as well as RhoB was inversely correlated with brain tumor malignancy, with the less
RhoA and B present, the worse the tumor grade (Forget et al., 2002). Loss of RhoB was also shown
in lung cancer (Mazieres et al., 2004). This addresses the importance of tissue type and how
different mutations and pathways may affect different types of cancers in different ways. By
understanding the mechanisms ARHGEF10 affects and what its role is in different tissue types,
we can move towards personalized, targeted medicine for cancer as well as earlier detection using
ARHGEF10 and its related GTPases as markers. As often cancers become lethal due to late
detection, being able to have reliable biomarkers is a critical next step in cancer prevention and
treatment.
3.4 Neuropsychiatric and developmental disability disorders
Chromosome 8p and ARHGEF10 specifically have been tied to a myriad of neuropsychiatric
disorders and developmental disabilities (Tabares-Seisdedos and Rubenstein, 2009; Verhoeven et
al., 2003). Many of these are associations and the actual effect of ARHGEF10 is still unknown.
Here I will discuss the neuropsychiatric and developmental disability disorders associated with
ARHGEF10.
Patients with a deletion in chromosome 8p23 have developmental delay, intellectual disability,
microcephaly, ASD, attention-deficit/hyperactivity disorders, and mildly dysmorphic features.
The 8p23 deletion region contains the genes DLGAP2, CLN8, CSMD1, and ARHGEF10, though
27

CSMD1 is not deleted in every patient. These genes are expressed in the brain and their proteins
are associated with neurodevelopment, suggesting a mechanistic link to developmental disabilities,
but the role of each individual gene is not understood. Loss of function of each of these genes
alone is not sufficient to cause the phenotypes shown in these patients, so it is likely that these
genes regulate a similar process during neurodevelopment (Shi et al., 2017). While there are strong
associations between these genes and developmental disabilities, the mechanisms of disease for
chromosome 8p23 deletion syndrome is still a mystery. Without hard evidence, it is difficult to
say that ARHGEF10 for sure plays a role in contributing to this phenotype. Further studies
examining smaller deletions would be helpful to understand which genes contribute to
neurobehavioral development.
In addition to developmental disabilities, ARHGEF10 has been associated with neuropsychiatric
disorders including schizophrenia. Abnormal myelination has been shown in patients with
schizophrenia and because ARHGEF10 is believed to be involved in proper myelination, it is a
candidate gene for schizophrenia (Davis et al., 2003). One genome-wide association study found
a weak association between the ARHGEF10 SNP, rs11136442, and schizophrenia in an association
study of myelin-related genes (Jungerius et al., 2008). One of the issues with neuropsychiatric
disorder studies and schizophrenia specifically is that current literature on the relationship between
ARHGEF10 and these disorders is based on a small number of primarily association studies.
Therefore, the significance of these associations and how ARHGEF10 mutations cause these
diseases is not understood (Tabares-Seisdedos and Rubenstein, 2009). Future studies will need to
take the next step in studying disease mechanisms of ARHGEF10. Knockout animal models will
be helpful in future studies to see if ARHGEF10 is necessary and/or sufficient to cause
schizophrenia. Additionally, schizophrenia has been shown to lead to decreased cancer risk, so it
28

is possible that ARHGEF10 works through a common mechanism between cancer and
schizophrenia (Tabares-Seisdedos and Rubenstein, 2009). Following up on this relationship has
the potential to impact both fields of study.
One study has also correlated ARHGEF10 with addiction, specifically heroin addiction. Heroin
dependence is caused by changes in the neurons of the brain, so studies on addiction have focused
on genes involved in the nervous system (Nestler and Aghajanian, 1997). In a study of 398 heroin
addicts and 169 controls of Han Chinese descent, a Versatile Gene-based Association Study was
used to find genes associated with addiction, including a region covering ARHGEF10 (p < 3.5 x
10
-5
) (Kalsi et al., 2016). Though this study claims ARHGEF10 as a top candidate gene,
ARHGEF10 was only found to be related through association analysis. It is plausible that
ARHGEF10 is linked to heroin dependence if it indeed plays a role in other neuropsychiatric
disorders, but with only one association study it is impossible to make any claims about the
relationship between ARHGEF10 and dependence. Studies that go beyond associations would
need to be performed to understand more specific mechanisms behind heroin addiction and how
ARHGEF10 is related to addiction.
In addition to addiction, there is a small amount of evidence supporting ARHGEF10 as a gene
involved in suicide risk. It was found that a DNA methylation mark in the spindle- and
kinetochore-associated protein 2 (SKA2) gene is associated with suicide (Jerry Guintivano et al.,
2014). This group then created an epigenetic interaction biosignature of SKA2-interacting markers
and found within a 72 probe interaction biosignature that three of these probes, including
ARHGEF10, were significant across all cohorts and may therefore be associated with suicide risk
(Clive et al., 2016). There is not much evidence supporting ARHGEF10 as a suicide risk gene
besides chromosome 8p being linked to neuropsychiatric disorders and ARHGEF10 being
29

associated with the interaction biosignature across all of the studied cohorts. It is possible that
ARHGEF10 plays a role in suicide risk, though right now there is no hard evidence suggesting
this. How this biosignature can be used in practical study is unclear, but if there is the possibility
to increase suicide prevention then follow-up studies may be worthwhile.
Overall, the connection between ARHGEF10 and neuropsychiatric and developmental disability
disorders is a few association studies with no hard evidence for a ARHGEF10 role in these
diseases. Future research investigating more specifically the mechanisms behind how ARHGEF10
causes these disorders could lead to a better understanding of the role ARHGEF10 plays. Finding
a mechanism in one disease could help make great strides in understanding many neuropsychiatric
and developmental disability disorders or at least give us clues of where to look next.
3.5 Ischemic Stroke
Though environment and lifestyle factor in to stroke risk, more recent data has shown that there is
also an important genetic component in some types of stroke, including thrombotic stroke, a
subtype of ischemic stroke (Li et al., 2017). Ischemic stroke is widely studied as it accounts for
nearly 87% of all strokes (Benjamin et al., 2017). Multiple genome-wide association studies
(GWAS) have looked at ARHGEF10 SNPs in Caucasian, Han Chinese, and Japanese populations
and found different intronic SNPs that are associated with risk of ischemic stroke (Li et al., 2017;
Matsushita et al., 2010; Yin et al., 2011; Zee et al., 2014). How these SNPs affect gene function is
mostly unclear, though a little bit is known about two specific SNPs. One SNP, rs4376531, has
been shown to alter transcriptional regulation through altered Sp1 binding, enhancing ARHGEF10
transcriptional activity (Matsushita et al., 2010). The hypothesis is that enhanced ARHGEF10
transcription leads to higher RhoA activity, thus activating the Rho-ROCK pathway. Increased
ROCK activity is seen in patients with ischemic stroke (Matsushita et al., 2010; Zee et al., 2014).
30

A different intronic SNP of ARHGEF10, rs2280885, increases delta-6 (D6D) activity and plasma
triglyceride (TG) levels. D6D activity and TG levels have been previously correlated and TG levels
are a risk factor for ischemic stroke. However, the mechanism of how ARHGEF10 expression
alters D6D activity and plasma TG levels is unclear (de Toro-Martín et al., 2017; Freiberg et al.,
2008). From these association studies, we have learned that across different ethnicities,
ARHGEF10 is important in contributing to the genetic component of ischemic stroke risk. These
studies can help contribute to prevention of stroke if the mechanism is better understood in the
future. As the Rho-ROCK pathway has been implicated in ischemic stroke, targeting this pathway
to reduce ROCK signaling in at-risk patients could potentially help reduce stroke rates. However,
as ROCK signaling is important in many systems, studies involving animal models would be
required to know if this is even a viable method of prevention and if there are off-target effects.
Currently, stroke is a leading cause of death and there are very few options for prevention and
treatment, making advancements in stroke biology incredibly pertinent to modern medicine (Li et
al., 2017). Following up on these association studies and understanding the mechanism by which
ARHGEF10 affects ischemic stroke susceptibility will be a critical next step towards stroke
prevention. Stroke-like episodes have also been seen in patients with CMTX, so understanding the
mechanism by which ARHGEF10 affects ischemic stroke will prove helpful in understanding
ARHGEF10-associated CMT and neurological disease (Sagnelli et al., 2014).
Chapter 4: Animal Models
ARHGEF10 is not a very well-studied gene and as a result there are not many animal models. In
this chapter, I discuss the naturally occurring canine model as well as transgenic mouse models for
ARHGEF10. I will look at the Leonberger dog as a model for human CMT disease and discuss
how this model can be useful in furthering CMT research. Then, I will discuss the current status
31

of the ARHGEF10 knockout mouse model and some potential future directions for ARHGEF10
mouse modeling.
4.1 The Leonberger dog as a model for CMT disease associated with ARHGEF10
It can often be difficult to find animal models that mimic human disease, particularly naturally
occurring models. Few animal models have been used to study ARHGEF10-associated diseases,
and they generally require the use of transgenic animal models. However, there is a naturally
occurring dog model for ARHGEF10-associated CMT disease. Leonberger dogs have been shown
to inherit a polyneuropathy (PN) that is clinically similar to CMT in humans, with phenotypes
including a high-stepping gait, overall weakness, muscle atrophy due to denervation, a lack or
lessening of tendon reflexes, and in some cases laryngeal paralysis which can be noticed by a
change in the pitch of bark and shortness of breath (Becker et al., 2017; Ekenstedt et al., 2014;
Granger, 2011). Though the human phenotype varies, a typical CMT phenotype includes muscle
weakness in the distal limbs, foot drop, and sensory loss (Granger, 2011). Several types of CMT
also present with abnormal vocal cords, possibly due to laryngeal paralysis (Aboussouan et al.,
2007). As Leonbergers typically only live 8-10 years, this dog model can be used to better study
the progression, histology, and mechanism of ARHGEF10 CMT.
Until relatively recently, it was unclear what genes caused canine PN. A GWAS study of 52 PN
and 41 control Leonbergers revealed a loss-of-function ARHGEF10 deletion (Ekenstedt et al.,
2014). This 10bp deletion spanning intron and exon 17 of ARHGEF10 removes the normal splice
site, forcing the use of a downstream alternate splice site. Due to the frame shift and premature
stop codon, both the long and short forms of the protein are truncated by over 50%, deleting a
WD40-like domain as well as two transmembrane domains (Ekenstedt et al., 2014; Shelton et al.,
2011). Since the mutation truncates the protein and deletes multiple domains, it is thought that the
32

mutation causes a loss of ARHGEF10 function, leading to improper axon myelination (Ekenstedt
et al., 2014). Future in vitro and in vivo studies on the effect of mutating the WD40-like and
transmembrane domains versus other domains of the protein will help elucidate how the structure
of ARHGEF10 relates to function during myelination.
Studying Leonbergers that were both homozygous and heterozygous for the ARHGEF10 mutation
showed varying degrees of phenotype severity. In a group of 206 Leonbergers with PN, 44.4% of
early onset (less than 3 years of age) cases were due to a homozygous ARHGEF10 mutation and
21.8% of all PN cases were due to a heterozygous ARHGEF10 mutation. The homozygous dogs
had a younger average age of onset and were more likely to be severe than the heterozygotes
(Ekenstedt et al., 2014). When first discovered, the ARHGEF10 frame-shift mutation accounted
for over 20% of PN cases in Leonbergers. However, since breeders have become aware of the
mutation, that number has dropped to 11% as of 2017 (Becker et al., 2017). The mutation does,
however, make up most cases of severe early-onset PN (Ekenstedt et al., 2014). Understanding
why this particular mutation affects age of onset and severity in comparison to other mutations
could help bridge the gap in knowledge of how ARHGEF10 fits into the story of peripheral nerve
development and membrane trafficking. RhoA would be a good target of study in working out the
mechanism of ARHGEF10-associated PN and CMT since Rho A is a known substrate of
ARHGEF10.
The mode of inheritance for Leonberger PN has been debated. When the disease was first
discovered, it was believed to be X-linked recessive as more males than females were
symptomatic; however, an autosomal recessive mode of inheritance was not ruled out (Ekenstedt
et al., 2014; Shelton et al., 2003). It is now understood that PN, like CMT, is caused by more than
one gene mutation and mode of inheritance varies depending on the mutation and the country of
33

origin of the dogs (Becker et al., 2017; Granger, 2011; Hultin Jäderlund et al., 2011). PN caused
by the ARHGEF10 mutation most likely has an autosomal recessive pattern of inheritance,
although this has not been definitively confirmed (Ekenstedt et al., 2014). Looking for other gene
mutations that are found in both Leonberger PN and CMT could help both in understanding CMT
and in discovering a molecular pathway through which ARHGEF10 works to affect peripheral
nerve development.
As the Leonberger breed was created by crossing several large breeds, the ARHGEF10 mutation
was also looked for in these breeds. A juvenile-onset PN due to the same ARHGEF10 mutation
was found in Saint Bernards, so it is reasonable to believe that the mutation was passed down to
the Leonberger breed through the Saint Bernard (Becker et al., 2017; Shelton et al., 2011).
Studying the Saint Bernard breed in more detail could serve as a good secondary dog model and
may teach us more about the effect of ARHGEF10 on peripheral nerve development. Due to the
clinical similarities, PN in Leonbergers, and potentially Saint Bernards, makes a good animal
model for CMT disease, and future studies of the canine ARHGEF10 deletion can help in
understanding of both canine and human ARHGEF10-associated neuropathy.
4.2 ARHGEF10 transgenic mouse models
Although there is no known naturally occurring ARHGEF10 mutations for mice like for the
Leonberger dogs, mice are a useful model due to the ability to make transgenic mice. Mouse
models for ARHGEF10 have not been studied in great detail and no transgenic ARHGEF10 mice
can be bought through The Jackson Laboratories (JAX) at this time. However, there is one lab in
Taiwan that has recently created their own Arhgef10 knockout mouse model and published using
this mouse (Lu et al., 2017a; Lu et al., 2017b). A null was created by removing exons 4 and 5 of
Arhgef10 using the Cre-loxP system (Figure 5) (Lu et al., 2017b). Mouse exons 4 and 5 are not
34

part of the DH domain, the domain that controls GEF activity, but the deletion causes a frame shift
mutation that renders the protein nonfunctional (Lu et al., 2017b). The study in which these mice
were used focused on the role of ARHGEF10 in platelet function. Though the null mice had no
difference in platelet numbers, there was decreased ability of platelets to aggregate (Lu et al.,
2017b). Assays including a platelet aggregation assay, coimmunoprecipitation, RhoA activity
assay, and a tail bleeding assay, led to the conclusion that ARHGEF10 inhibits platelet function
while also protecting against stroke by inhibiting arterial thrombus formation (Lu et al., 2017b).
Without a mouse model, this study would have been much more difficult, if not impossible, to
complete. Theoretically, platelets could have been isolated from wildtype mice and ARHGEF10
could have been knocked out through a system such as CRISPR-Cas9. However, these methods
could have affected the results as the platelets would already have been formed when ARHGEF10
was knocked out, possibly leaving residual ARHGEF10 function, and platelets would have been
Figure 5. The Cre-loxP system was used to remove exons 4 and 5 in generating Arhgef10
-/-
mice (Lu et al.,
2017b).
35

studied in isolation instead of as part of the larger system in which they function. In vitro studies
are often unable to answer the same questions as in vivo studies, and in this case many of the assays
performed would not have been possible without the Arhgef10 null mouse. Using a mouse model
is a simpler method of study that gives more relevant information on how ARHGEF10 affects the
system. After this initial study, the laboratory applied the use of the Arhgef10 knockout mouse
model to Autism Spectrum Disorder (ASD) based on finding an ASD patient with a deletion in
chromosome 8p23, where ARHGEF10 is located. The mice showed symptoms of human ASD,
making ARHGEF10 a candidate gene for ASD (Lu et al., 2017a). This is a great advancement as
ASD is a popular topic of study due to its prevalence, and understanding the genes and factors that
cause ASD is currently missing in the literature. Additionally, ASD is one of the symptoms of the
patient with a deletion in chromosome 8p23 (see Chapter 3.4). Advancements like those made
using the Arhgef10 knockout mouse can help us better understand which genes cause specific
phenotypes and why, especially in cases where several genes are affected. To our knowledge
Arhgef10 knockout mice have not been studied for other phenotypes such as neuropathy, but
applying these mice to other systems we know ARHGEF10 is involved with could prove extremely
useful. Having a mouse model allows much faster advances in the study of ARHGEF10 and in
understanding its role in different systems and diseases.
In terms of readily available ARHGEF10 mouse models, there are several ES lines utilizing gene
trapping to create mutated forms of ARHGEF10, including ones that can be used as reporter lines.
However, none of these lines have been turned into mice yet (Blake JA, 2017). JAX does currently
have an ARHGEF10 knockout reporter mouse line in the works, but the phenotypes have not been
assessed and the colony is still in the founding stages. This model is an Arhgef10
tm1.1(KOMP)Vlcg
,
meaning it is a targeted mutation (tm1.1) created in partnership with the Knockout Mouse Project
36

(KOMP) using a Velocigene cassette to create a deletion (Vlcg) (The Jackson Laboratory, 2018).
The deletion is just short of 30,000 bp long on chromosome 8, removing almost the entire Arhgef10
gene. Though phenotype data is not yet available on this strain, it is thought that these mice will
be useful in studies on myelination as ARHGEF10 is known to affect nerve conduction velocity
via improper myelination (The Jackson Laboratory, 2018). Assuming this mouse functions as a
true Arhgef10 null, there should be implications for several systems, not just myelination as
ARHGEF10 affects a myriad of systems and diseases. There is still a ways to go before this can be
used as a standard Arhgef10 mouse model, but ideally this mouse can one day be used to work out
the mechanisms in which ARHGEF10 functions. Since understanding the mechanisms through
which ARHGEF10 works is a gap in the literature, completion of and easy access to a ARHGEF10
mouse model will greatly impact the field and lead to large strides in our understanding of
ARHGEF10 and the diseases caused by aberrant ARHGEF10 signaling.
Once a null mouse model for ARHGEF10 is characterized and more widespread, the opportunities
for more specific Arhgef10 mouse models are nearly limitless. Mice affecting specific disease
mutations could prove useful in disease study. For example, making a mouse with the mutation
found in ARHGEF10-associated CMT disease could lead to an understanding of the mechanism
behind neurodegeneration. Additionally, mouse models that knock out specific domains, like the
DH domain, could help in understanding how ARHGEF10 works as a GEF and as a scaffolding
protein, and what domains are important for different aspects of ARHGEF10 function. Since
ARHGEF10 is so important at different points in development and in homeostasis, an inducible
knockout could prove useful in figuring out the role of ARHGEF10 in different systems and at
different stages of development. One thing that should be noted is that across mouse strains SNPs
in Arhgef10 are pretty common, so it is important to take strain into account when using mice to
37

study ARHGEF10. For the knockout models this should not be as important, but for future models
that are more specifically mutated, this could prove to be a confounding factor. Overall, a lot of
work is still to be done in creating transgenic mouse models for ARHGEF10, but the possibilities
are exciting and will open up a whole new world of understanding.

38

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Abstract (if available)

Abstract Rho guanine nucleotide exchange factors (RhoGEFs) are known for their role as catalysts of Rho family small guanosine triphosphatase (Rho GTPase) activation. RhoGTPases act as molecular switches, playing a critical role in regulating the actin cytoskeleton, therefore affecting many pathways involved in development and disease. With a recent link made between different RhoGEFs and RhoGTPases in neurodegenerative disease, Rho guanine nucleotide exchange factor 10 (ARHGEF10) has become a new focus of study. While the function of ARHGEF10 is not completely understood, its function is related to several human diseases including neurodegenerative diseases, cancer, neuropsychiatric disorders, and stroke. In this literature review, I analyze what is known about the structure and function of ARHGEF10 and discuss its mechanistic role in disease, particularly in the context of neurodegenerative disease. In Chapter 1, I evaluate what is known about RhoGTPases and RhoGEFs in general, examining structure, function, and disease implication. In Chapter 2, I assess the structure, function, and mechanisms of ARHGEF10 specifically. In Chapter 3, I review the diseases ARHGEF10 is involved in, with special focus on Charcot-Marie-Tooth disease, a peripheral neuropathy affecting 1 in 2500 people. In Chapter 4, I review the animal models currently used in the study of ARHGEF10-related diseases and discuss how these models can help further our understanding of ARHGEF10 function. ARHGEF10 is a critical gene in the future of disease research, and this review will underscore why it should be studied more in depth.

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Asset Metadata

Creator Stucky, Taylor (author)

Core Title Exploration of the role of ARHGEF10 in human disease

School Keck School of Medicine

Degree Master of Science

Degree Program Biochemistry and Molecular Medicine

Publication Date 04/27/2018

Defense Date 03/14/2018

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

Tag ARHGEF10,cancer,Charcot-Marie-Tooth Disease,CMT,genetics,ischemic stroke,membrane trafficking,nerve conduction,neuropathy,OAI-PMH Harvest,peripheral neuropathy,protein,rare disease,RhoGEF,RhoGTPase

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Merrill, Amy (committee chair), Frenkel, Baruch (committee member), Patel, Pragna (committee member)

Creator Email taylor.stucky12@gmail.com,tstucky@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-496015

Unique identifier UC11268556

Identifier etd-StuckyTayl-6284.pdf (filename),usctheses-c40-496015 (legacy record id)

Legacy Identifier etd-StuckyTayl-6284.pdf

Dmrecord 496015

Document Type Thesis

Format application/pdf (imt)

Rights Stucky, Taylor

Type texts

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

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

Repository Name University of Southern California Digital Library

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