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Charcot-Marie-Tooth disease type 1E: follow-up studies on a screen for therapeutic small molecules and PMP22-interacting proteins
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Charcot-Marie-Tooth disease type 1E: follow-up studies on a screen for therapeutic small molecules and PMP22-interacting proteins
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Content
Charcot-Marie-Tooth disease type 1E:
Follow-up studies on a screen for therapeutic small
molecules and PMP22-interacting proteins
by
Yutai Zhao
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 MEDICINE)
December 2018
Copyright 2018 Yutai Zhao
i
Acknowledgements
I would like to thank my mentor, Dr. Pragna Patel whose guidance has helped me to learn
a lot of things during the Master’s degree education at University of Southern California. I have
learnt how to define a problem and design experiments to address it, to maintain records of my
experiments, to think critically and to organize my data for oral and written presentations. I want
to express my gratitude to Dr. Kian Kani and Steve Swenson for serving on my thesis defense
committee. I am grateful for the guidance that Dr. Kani gave me with many of my co-IP
experiments. I am also thankful to Dr. Katrin Tiemann for sharing her previous experience with
western blotting and co-IP experiments.
I would like to thank Sofya Abazyan and Yuting Cheng for teaching me several
techniques in the lab including Western analysis, transfection, immunohistochemistry and
confocal microscopy. I also want to thank Dr. Ruchi Bajpai and members of her lab – Susan
Smith, Kaivalya Shevade, and Varsha Neelakanthan – for their help with reagents and in trouble-
shooting several of my experiments. I would like to thank Dr. Sunju Choi and Dr. Creighton for
guidance and reagents. I would like to thank Dr. Jianfu Chen and Mei for their advice on the LC3
and p62 western blotting experiments. I would like to thank Dr. Diana Rigueur for teaching me
how to perform immunohistochemistry.
Finally, I want to thank my family from all parts of the world for supporting and
encouraging me always.
ii
Table of Contents
Acknowledgements .................................................................................................................................. i
List of Figures ........................................................................................................................................ iii
Abbreviations .......................................................................................................................................... v
Abstract .................................................................................................................................................. 1
Chapter 1 Introduction ............................................................................................................................. 3
1.1 Charcot-Marie-Tooth (CMT) disease and peripheral myelin protein 22 (PMP22) ...................... 3
1.2 Autophagy ................................................................................................................................ 9
1.3 Small molecule screen for candidate therapeutics for CMT1E/CMT1A ................................... 12
1.4 Protein interactors of PMP22 .................................................................................................. 15
1.5 Proximity-labeling strategy to identify PMP22 interactors ....................................................... 19
1.6 The candidate novel interactor of PMP22: WDR81 ................................................................. 22
Chapter 2 Materials and Methods .......................................................................................................... 23
2.1 Cell culture ............................................................................................................................. 23
2.2 Transfection and Transduction ................................................................................................ 23
2.3 Treatment of cells with lactacystin, 3-methyladenine, and MG132 .......................................... 24
2.4 GFP-LC3 puncta analysis ....................................................................................................... 25
2.5 Antibodies .............................................................................................................................. 26
2.6 Western analysis ..................................................................................................................... 26
2.7 Co-immunoprecipitation experiments ..................................................................................... 29
Chapter 3 Results .................................................................................................................................. 31
3.1 Effect of a proteasomal inhibitor and an autophagy inhibitor on the ability of compounds to
reduce aggregates in the L16P-PMP22-RFP stable cell line ............................................................... 31
3.2 Evaluation of the ability of the compounds to induce autophagy using a GFP-LC3 HeLa
indicator cell line ............................................................................................................................... 45
3.3 Confirmation of the results of the mass spectrometric analysis to identify novel protein
interactors of PMP22 ......................................................................................................................... 50
3.4 Evaluation of the ability of compounds to induce autophagy by quantifying the level of LC3-II
and p62 ............................................................................................................................................. 59
Chapter 4 Discussion ............................................................................................................................. 62
References ............................................................................................................................................ 69
iii
List of Figures
Figure 1. Structure of a typical peripheral neuron
Figure 2. PMP22-associated pathologies
Figure 3. CMT1A is a protein misfolding disorder/protein trafficking disorder
Figure 4. Schematic diagram of autophagy clearing aggregates
Figure 5. Flow chart of screen for small molecules that reduce PMP22-RFP aggregates
Figure 6. Schematic diagram of peripheral myelin showing the known protein components and
their interactions
Figure 7. Proximity-dependent biotinylation of cellular proteins with BioID2
Figure 8. Pilot experiment to determine optimal doxycycline concentration for induction of
transgene expression
Figure 9. L16P-PMP22-RFP HeLa cells before and after flow cytometry
Figure 10. Effect of lactacystin and 3-MA on aggregates in L16P-PMP22-RFP HeLa cells
Figure 11. Optimization of concentrations for compounds and inhibitors in L16P-PMP22-RFP
HeLa cell aggregate assay
Figure 12. Effect of lactacystin and 3-MA on the ability of analog compounds to reduce
aggregates in L16P-PMP22-RFP HeLa cells (second attempt)
Figure 13. Alternative proteasomal inhibitor MG132
Figure 14. Effect of lactacystin, MG132 and 3-MA on the ability of analog compounds to reduce
aggregates in L16P-PMP22-RFP HeLa cells
Figure 15. Optimization of loperamide and chloroquine concentrations for the GFP-LC3 puncta
assay
iv
Figure 16. Representative images from the GFP-LC3 puncta assay for autophagy with
loperamide treatment in the presence and absence of chloroquine
Figure 17. Compounds USC1-46, USC3-4 and USC3-27 appear to induce autophagy in GFP-
LC3 HeLa cells
Figure 18. WDR81 expression in RT4 Schwann cells, HeLa cells and various transgenic HeLa
and RT4 cell lines
Figure 19. Endogenous and transient expression of WDR81
Figure 20. Lack of expression of PMP22-BioID2-myc
Figure 21. Western blot analysis to detect expression of PMP22-RFP and WDR81
Figure 22. Optimization of Lipofectamine 3000 transfection with respect to DNA amount and
cell confluency using the vector, pTRIPZ-RFP
Figure 23. Immunoprecipitation with anti-HA Sepharose beads
Figure 24. Immunoprecipitation with anti-RFP antibody and protein G agarose beads
Figure 25. Effects of compounds on autophagy markers quantified by western blot
v
Abbreviations
BioID2 human codon-optimized Aquifex aeolicus biotin ligase
CMT Charcot-Marie-Tooth
CANX calnexin
CX32 connexin 32
DMEM Dulbecco’s modified Eagle’s medium
DSS Dejerine-Sottas syndrome
ER endoplasmic reticulum
ERAD endoplasmic reticulum-associated degradation
FBS fetal bovine serum
gp78/AMFR autocrine motility factor receptor
Hrd1/SYVN1 synoviolin
HNPP hereditary neuropathy with liability to pressure palsy
MBP myelin basic protein
NCV nerve conduction velocity
PMP22 peripheral myelin protein 22
PRX periaxin
RER1 retention in endoplasmic reticulum sorting receptor 1
RIPA radioimmunoprecipitation assay
SC Schwann cell
wt wild-type
Lact lactacystin
3-MA 3-Methyladenine
CQ chloroquine
Lop loperamide
Dox doxycycline
DMSO dimethyl sulfoxide
HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
DPBS Dulbecco's phosphate-buffered saline
HBSS Hank's Balanced Salt Solution
WDR81 WD repeat-containing protein 81
PEI polyethylinimine
RawIntDen raw integrated granule intensity
1
Abstract
Charcot-Marie-Tooth (CMT) disease is the most common peripheral nerve disease.
CMT1A, the most frequent type of subtype CMT1, results from the overexpression of peripheral
myelin protein 22 (PMP22). The less frequent subtype CMT1E results from point mutations in
PMP22. Demyelination of peripheral nerves due to a Schwann cell defect caused by these
mutations results in a symmetrical reduction of nerve conduction velocity in all extremities. In
normal Schwann cells, over 80% of wild-type PMP22 is degraded by the proteasome. Excessive
or mutant PMP22 is retained in the endoplasmic reticulum and forms aggregates in the cytoplasm.
Treatment with rapamycin activates autophagy and clears the aggregates and improves
myelination in the PMP22-overexpressing mice. Therefore, the reduction of these aggregates could
have therapeutic benefit to patients.
The first aim of my thesis was to characterize the most active analogs of small molecules
that were identified in a small molecule screen for agents that reduce aggregates formed by
expression of PMP22 bearing an L16P mutation fused to red fluorescent protein (RFP). These
analogs, USC 1-46, USC 1-48, USC 3-4 and USC 3-27 were found to reduce aggregates in L16P-
PMP22-RFP expressing cells. This reduction was inhibited by the autophagy inhibitor, 3-
methyladenine but was not inhibited by the proteasomal inhibitor, lactacystin, suggesting that they
are autophagy inducers. Further experiments confirmed that these compounds could induce the
formation of autophagosomes evident as puncta in a HeLa cell line stably expressing GFP-LC3.
The second aim of my thesis was to conduct co-immunoprecipitation experiments to determine if
WDR81, a candidate protein interactor with PMP22 identified in a BioID2 proximity-labeling
screen did indeed interact with PMP22. These experiments were not successful because of very
2
low expression of the PMP22-BioID2-myc as well as PMP22-RFP proteins in both RT4 Schwann
cells and HeLa cells.
3
Chapter 1
Introduction
1.1 Charcot-Marie-Tooth (CMT) disease and peripheral myelin protein 22
(PMP22)
CMT (Charcot-Marie-Tooth) disease is the most common disease of the peripheral
nerves with over 2.8 million people affected all over the world. There are over 80 genes in many
different pathways that are associated with CMT (Gutmann and Shy, 2015). The disease was
named after Jean-Martin Charcot, Pierre Marie, and Howard Henry Tooth who contributed to its
first description as “hereditary neuropathy” in 1886 (Gutmann and Shy, 2015). The patients
suffer from a foot and hand deformity due to slowly progressive distal muscle atrophy, so they
may have difficulties in grabbing objects and walking. Since the sensation is impaired and the
deep tendon reflexes are diminished, patients are more likely to get injured unconsciously.
CMT1, the more frequent subtype of CMT, is an autosomal dominant neuropathy
characterized by demyelination of Schwann cells that causes a symmetrical reduction of nerve
conducting velocity in all four extremities. Schwann cells wrap around the axon of the neuron
and form myelin which insulates a nerve. Each Schwann cell wraps around a single segment of
an axon and produces the myelin sheath. The gaps on the axon between individual Schwann cells
without myelin are called nodes of Ranvier while the myelinated segments are internodes. The
nodes of Ranvier allow a nerve impulse to jump from node to node allowing conduction to occur
much faster than a bare nerve fiber. Therefore, demyelination significantly down-regulates the
nerve conduction ability of an axon.
4
Figure 1. Structure of a typical peripheral neuron
Schwann cell wraps around the axon with its lipid-rich plasma membrane to form 20-
30 layers, resulting in the myelin sheath covering about 1 mm of the axon. The few
proteins retained in myelin include PMP22, P0, CX32 (connexin 32) and MBP
(myelin basic protein). Much of the aqueous, cytosolic material is excluded from this
structure. Gaps between Schwann cells that are unmyelinated are called the nodes of
Ranvier and are critical in saltatory conduction of a nerve impulse.
5
CMT1 is subdivided into subtypes classified as CMT1A to CMT1E. About 50% of
CMT1 falls into the subtype CMT1A which is caused by a duplication of a 1.4 Mb DNA
sequence on chromosome 17p11.2-12 (Lupski et al., 1991; Raeymaekers et al., 1991). The gene
PMP22 was mapped within this duplication (Patel et al., 1992), and over-expression of Pmp22 in
rodent models causes pathology similar to CMT1 (Meyer Zu Horste and Nave, 2006) indicating
that it is caused by the overexpression of PMP22. Affected patients show muscle atrophy and
loss of sensation in the lower limbs. The nerve conduction velocities for all limbs can drop to as
low as 20 m/s compared to unaffected individuals who have a velocity of about 100 m/s.
CMT1E is less frequent seen in roughly 5% of CMT1 cases but is more severe than
CMT1A, although this early-onset neuropathy can show heterogeneity in phenotypes ranging
from mild to severe. It is caused by missense mutations in PMP22 (Roa et al., 1993). Two point
mutations in CMT1E, L16P and G150D are perfectly represented by two mutant mouse strains,
Trembler and Trembler
J
, respectively(Meyer Zu Horste and Nave, 2006).
Hereditary neuropathy with liability to pressure palsies (HNPP) is an autosomal dominant
neuropathy caused by a deletion of the same CMT1A interval on chromosome 17p11.2-12
(Chance et al., 1993) or by point mutation in PMP22 (Nicholson et al., 1994). The disease
usually has an onset during adolescence and patients suffer from episodic or recurrent focal
sensory loss and muscular weakness with atrophy. Since the deletion involves the same region
on chromosome 17, only one copy of PMP22 is left but the disease is much milder than CMT1A
and CMT1E which have an additional normal or mutant copy of PMP22, respectively. In rare
cases, HNPP can be caused by a point mutation resulting in a loss-of-function of PMP22
6
(Nicholson et al., 1994). In summary, HNPP is a consequence of haploinsufficiency for PMP22
caused by a deletion or by a loss-function mutation in PMP22.
Figure 2. PMP22-associated pathologies
Duplication of a 1.4 Mb region on chromosome 17p11.2-12 including the PMP22 gene
is associated with CMT1A while point mutations in PMP22 cause CMT1E. Deletion
of the 1.5 Mb in the same region results in HNPP which can also be caused by a loss-
of function point mutations in PMP22. These findings indicate that PMP22 gene
dosage is very critical for the normal functioning of Schwann cells. (PMP22* =
PMP22 with a point mutation; the orange and green blocks represent a 17 kb repeat
sequence that flanks the duplication/deletion interval.)
7
PMP22 is a tetraspan-membrane protein of Schwann cell that is an essential structural
component of myelin comprising 2-5% of total myelin protein. A cross section of myelin is
shown in Figure 3 and PMP22 can be seen in red PMP22 has key roles in myelin formation and
maintenance, and Schwann cell proliferation and differentiation (Li et al., 2013). Mouse models
that over-express PMP22 (Huxley et al., 1996; Sereda et al., 1996) or PMP22 bearing a point
mutation [eg.Trembler(Tr), Trembler-J(Tr-J)] (Meyer Zu Horste and Nave, 2006) represent the
disease phenotype in mice. In these models, excessive or defective PMP22 overwhelms the
degradation by the ubiquitin-proteasome system and accumulates in cytosolic aggregates and is
retained in the ER, and results in less PMP22 on the Schwann cell membrane (Fortun et al.,
2003; Tobler et al., 1999). Misfolded mutant protein also causes intracellular retention of wild-
type protein (Tobler et al., 1999). The low level of PMP22 protein on Schwann cell is likely to
contribute to the demyelination phenotype. Treatment with rapamycin can activate autophagy
and improve myelination in Tr-J and in the PMP22-overexpressing mice (Rangaraju et al., 2010).
8
.
Figure 3. CMT1A is a protein misfolding disorder/protein trafficking disorder
80% of wild-type PMP22 in normal Schwann cells is degraded in the proteasome with
only about 20% folded properly and trafficked to the membrane. In Schwann cells of
patients with CMT1A and CMT1E which express excessive and mutant PMP22
respectively, the protein forms aggregates and is retained in ER presumably resulting
in decreased amount of PMP22 protein within the SC plasma membrane, and therefore
likely contributing to the pronounced demyelinating phenotype.
9
1.2 Autophagy
Autophagy is a process that cells use to degrade and recycle cellular components, such as
proteins and organelles. The process is initiated by the formation of a subcellular double
membrane structure called a phagophore and it engulfs the components that need to be degraded.
Cellular proteins including LC3 assemble on the membrane and the phagophore expands to a
vesicle called an autophagosome. The autophagosome fuses with a lysosome to form an
autolysosome and allows lysosomal enzymes to degrade the components. The materials degraded
from those components can therefore be recycled and LC3 returned to the cytoplasm. 3-
methyladenine (3-MA) inhibits autophagy by inhibiting the formation of autophagosomes while
chloroquine (CQ) inhibits the fusion of the autophagosome and lysosome.
LC3 is an autophagosome indicator. This protein is normally in the cytoplasm but
assembles on the membrane of autophagosomes. After the autophagosomes fuse with lysosomes,
LC3 dissembles and returns to the cytoplasm. A stable HeLa cell lines that expresses GFP-LC3
fusion protein was obtained from Dr. Wen-Xing Ding (University of Kansas). This fusion of
GFP to LC3 allows marking of autophagosomes as puncta which can be counted and used to
evaluate autophagy. CQ can inhibit the fusion and cause more autophagosomes and therefore,
more puncta. An autophagy inducer will increase the number of autophagosomes and in the
present of CQ, the GFP-LC3 will not dissemble and thus, result in more visible puncta.
Autophagy completes a flux starting from the formation of phagophore and ending with
the fusion of the autophagosome with the lysosome and degradation of the contents. When CQ is
present, autophagy flux cannot be completed due to the inhibition of the fusion of the
autophagosome and lysosome. Even if autophagy is induced and more autophagosomes are
10
generated, which can be seen as puncta in the GFP-LC3 HeLa cell line, the contents will not be
degraded since the enzymes are still in lysosomes which are not fused to the autophagosomes.
The cytoplasmic form of LC3 is LC3-I and when it assembles on the autophagosomes
and is conjugated with phosphatidylethanolamine, it called LC3-II. LC3-II has a higher
molecular weight but runs faster than LC3-I probably because of its increased hydrophobicity
(Klionsky et al., 2016). Since both LC3-I (about 14 kDa) and LC3-II (about 16 kDa) can be
detected by western blotting, it is possible to quantify the amount of LC3-I and LC3-II to
evaluate the activity of autophagy. Increased autophagy activity should result in increased levels
of LC3-II.
The measurement of autophagy flux is necessary in cases where one needs to know if
autophagy has really degraded cell components. SQSTM1/p62 is the autophagy indicator by
which one can monitor autophagy flux. The function of p62 is to link LC3 to ubiquitinated
substrates (Bjørkøy et al., 2005). When p62 and the ubiquitinated substrates linked to it are
incorporated into autophagosomes, they get degraded in autolysosomes. Since we do not know
which substrates may be degraded by autophagy, p62 can be a great indicator of autophagy flux.
In comparison, LC3-II levels only indicate the level of autophagosomes. In combination, higher
activity of autophagy flux should be characterized by an increased level of LC3-II and a
decreased level of p62.
11
Figure 4. Schematic diagram of autophagy clearing aggregates
The induction of autophagy is initiated by the formation of the double membrane
phagophore and the assembling of LC3. The phagophore expands and engulfs
aggregates and forms a vesicle called the autophagosome. This step can be inhibited
by 3-MA. The autophagosome then fuses with a lysosome to form the autolysosome
and allows enzymes in the lysosome to degrade aggregates. This fusion can be
inhibited by CQ. The fusion causes LC3 to disassemble and be released.
12
1.3 Small molecule screen for candidate therapeutics for CMT1E/CMT1A
Cell lines stably expressing PMP22-RFP or L16P-PMP22-RFP. The Patel lab
previously created lentiviral vectors that express PMP22 fused to a red fluorescent protein (RFP)
reporter driven by a doxycycline-inducible CMV promoter. Stable RT4 Schwann (rat) and HeLa
cell lines expressing either wild-type PMP22-RFP or L16P-PMP22-RFP were created. Since
over-expression of PMP22 has been known to cause apoptosis, it was reasoned that regulated
expression of the cDNA would allow us to circumvent this problem. Expression of the fusion
proteins results in the formation of aggregates. The L16P mutation is more prone to aggregate
formation and requires a much lower dose of doxycycline and a shorter interval of induction. The
wild-type PMP22-RFP initially shows an even distribution but begins to form aggregates as the
induction time lengthens. A stable line expressing only RFP showed bright fluorescence
throughout the cytoplasm (data not shown). For the small molecule screen, the more extreme
phenotype with L16P-PMP22 was preferred so as to allow reproducible results and hence, we
conducted all further studies with the stable line expressing the mutant protein. Since protein
trafficking has been implicated in the PMP22 over-expressing mouse model, any molecule
discovered in a screen with the mutant PMP22-RFP fusion could be tested with the wild-type
PMP22-RFP fusion line as well and could be of benefit in CMT1A. Rapamycin, an inducer of
autophagy, has been shown to improve processing of PMP22 and increase the abundance of
myelin internodes in both PMP22- overexpressing mice and in Tr-J mice (Rangaraju et al.,
2010). Expression of mutant PMP22-RFP was induced and examined after treatment with
rapamycin for aggregate formation. The effect of vinblastine, a microtubule inhibitor which has
been known to exacerbate symptoms in CMT1 patients (www.hnf-cure.org) was also examined.
Rapamycin treatment decreased the integrated granule intensity which is a measure of aggregate
13
formation by 85%, thus validating the read-out for the high-throughput screen. Vinblastine
treatment increased the integrated granule intensity by 40%. These results are shown in Figures
3B and 3C.
32,000 compounds were previously screened at the UCLA core. For the screen outline in
Figure 3A, L16P-PMP22-RFP HeLa cells were plated in 384 well plates and induced with 0.2
µg/ml doxycycline for 24 hours. Meanwhile, cells were treated with compounds and the positive
control used initially was 0.2 µM rapamycin and later, switched to the autophagy inducer,
loperamide (also identified independently in a pilot screen with the PMP22 cell line). After 24
hours, nuclei were stained with 0.5 µg/ml Hoechst 33342 and fixed with 4% formaldehyde.
Images were taken on a high throughput epifluorescence microscope(ImageXpress; Molecular
Devices, Inc.). Three fields were imaged from each well at the UCLA core and analyzed using
MetaXpress software. The integrated granule intensities (RawIntDen) per cell was used as a
measurement for the amount of aggregates. Compounds were cherry-picked that reduced
aggregates by ≥70% and yielded a Z-score of <2.6, and they were then subjected to a 20-point
IC50 screen in triplicate . This resulted in the identification of 22 lead compounds. These
compounds had an IC50 <10 µM which meant that they reduced aggregates by 50% when
treated with a compound at a concentration of 10 µM or less. They were also neither toxic to the
cells monitored by nuclei number, nor did they reduce aggregates by inhibiting transcription or
translation which was proven by a luciferase assay conducted on a stable Chinese hamster
overall cell line expressing luciferase under the control of a CMV promoter (Wong et al., 2005).
Three compounds, USC1, USC3 and USC12 representing unique scaffolds that were in common
with several of the primary hits in the screen were selected for analog synthesis for further
analysis. These analogs are the subject of my first Specific Aim.
14
Figure 5. Flow chart of screen for small molecules that reduce PMP22-RFP aggregates
Panel A: 32,000 compounds were screened at the UCLA core. After cherry-picking, 62
compounds that induce more than 30% reduction of aggregates, were selected. From this
set, 22 lead compounds were identified with undetectable toxicity and an IC50 less than 10
µM. They were tested in a secondary assay and then three scaffolds were selected for analog
synthesis. Four analogs that I focused on are highlighted in the bottom. Panel B: Confocal
microscopy image of the L16P-PMP22-RFP HeLa cells induced with doxycycline and
treated with vinblastine and rapamycin. Doxycycline induced the expression of the fusion
protein. Vinblastine is a chemotherapy drug known to exacerbate CMT symptoms .
Treatment with rapamycin which is an autophagy inducer, results in a significant reduction
of aggregates. Panel C: Integrated granule intensity from the confocal images analyzed with
ImageJ software. Vinblastine increased aggregates by 40% and rapamycin decreased them
by 85%. (All data were generated by Sunju Choi.)
15
1.4 Protein interactors of PMP22
Most proteins perform their function by interactions with other macromolecules such as
DNA, RNA or other proteins. Mutations in a protein may cause changes in its property as well as
changes in its interaction domains. Therefore, a mutated protein may lose its function due to the
loss of its ability to interact with other proteins. The proteins interacting with PMP22 may be
involved in the transportation, degradation or functions of PMP22. For example, the interaction
of PMP22 with the mutant myelin protein, P0 is altered and affects the maintenance of compact
myelin (Hasse et al., 2004). Also, in normal Schwann cells, 80% of PMP22 is degraded by the
proteasome (Pareek et al., 1997) and mutant PMP22 may have impaired interactions with
proteins related to degradation and form protein aggregates. Several proteins have been shown to
interact with PMP22 and proteins involved in these pathways could be potential therapeutic
targets as they show altered abilities to interact with mutant PMP22 and hence, induce pathology.
Therefore, the discovery of novel protein interactors associate with PMP22 and mutant PMP22
can contribute to the development of new therapies. The known interactors of PMP22 are briefly
discussed below.
Peripheral myelin protein zero (P0)
P0 is the major protein component of peripheral nerve myelin comprising 50% of the
total protein (Greenfield et al., 1973). P0 is the first protein found to interact with PMP22. It was
identified by immunoprecipitation followed by mass spectrometry and western blotting (D'Urso
et al., 1999). The removal of N-terminal sugar chains did not affect this interaction and the
interaction could also be detected in co-expressed HeLa cells which suggests that protein
16
glycosylation is not a key factor for the interaction (D'Urso et al., 1999). P0 and PMP22 are
found to co-localize on the cell plasma membrane (D'Urso et al., 1999). P0 and PMP22 function
in the maintenance of compact myelin in inherited peripheral neuropathies (Suter and Patel,
1994). Point mutation of P0 also causes the demyelination of peripheral nerves. Mutations in P0
are associated with CMT1, Dejerine–Sottas syndrome (DSS), and congenital hypomyelination
(CH) (Hasse et al., 2004; Warner et al., 1996). Thus, P0 interaction with PMP22 play a vital role
in myelin formation and maintenance.
Calnexin (CANX)
Calnexin, a non-glycosylated type I transmembrane protein on the endoplasmic reticulum
serves as a chaperone. It was found to interact with newly-synthesized PMP22. Calnexin
interacts with PMP22 transiently in normal mice; in vitro studies on sciatic nerves from mice
with the TremblerJ (L16P) mutation, L16P-Pmp22 showed a prolonged association with CANX
compared to the wild-type protein (Dickson et al., 2002). Since CANX is a resident protein on
the ER, this fact may partially explain the fact that PMP22 is retained in ER and forms
aggregates in the cytoplasm instead of trafficking to the cell membrane. The turnover of CANX
could also be impaired by longer interaction with mutant PMP22 and thus, may not serve as a
chaperone efficiently. As a result, other cellular processes may also be negatively influenced and
contribute to the symptoms.
17
Figure 6. Schematic diagram of peripheral myelin showing the known protein
components and their interactions
Proteins known to be within the Schwann cell that are structural components of myelin
are PMP22, P0, CX32 (connexin 32, a gap junction protein), PRX (periaxin) and MBP
(myelin basic protein). Extracellular regions are shown as white background.
Homophilic interactions of PMP22 as well as P0 and heterophilic interactions between
PMP22 and P0 are shown. The grey background represents the intracellular region.
18
E3 ubiquitin-protein ligase synoviolin (Hrd1/SYVN1)
Mutant PMP22 is retained the in ER but the mechanism is still unclear. It has been found
that ER- localized E3 ubiquitin ligase synoviolin (Hrd1/SYVN1) and gp78/AMFR mediate ER-
associated degradation (ERAD) of mutant PMP22 (Hara et al., 2014). Knockdown of Hrd1 and
gp78 significantly increase the retention of wild-type or mutant PMP22 in the ER. Co-
immunoprecipitation experiments confirmed the interaction of these ubiquitin ligases with
PMP22 with either of two mutations, L16P or G150D . Hrd1/SYVN1 mediates ERAD of both
L16P-PMP22 and G150D-PMP22 while the other ubiquitin ligase, gp78/AMFR, mediates
ERAD for G150D-PMP22 (Hara et al., 2014). Hrd1/SYVN1 was also found to bind to wild-type
PMP22-GFP at low affinity (Hara et al., 2014).
Retention In Endoplasmic Reticulum Sorting Receptor 1 (RER1)
RER1 is a membrane protein located in the Golgi apparatus and is involved in the
retention and retrieval of ER proteins. RER1 is a candidate interactor of PMP22. Knockdown of
RER1 in cells where PMP22 bearing mutations is retained in the ER results in PMP22 being
increasingly released from the ER (Hara et al., 2014). Co-immunoprecipitation experiments
confirmed that in wild-type and mutant PMP22-GFP stable HEK293T cell lines, transfected
FLAG-tagged mouse Rer1 binds to PMP22-GFP especially in the ER/cis-Golgi form (Hara et al.,
2014). The knockdown of chaperone CANX mentioned earlier has an additive effect on the
release of L16P-PMP22 from the ER, compared to the knockdown of each gene separately (Hara
et al., 2014).
19
In conclusion for CANX, Hrd1/SYVN1 and RER1, evidence suggests that the retention
of L16P-PMP22 in the ER is mediated by the ER-resident chaperone, CANX and Golgi
apparatus-resident, RER1 retention/retrieval system, and its degradation is carried out by
Hrd1/SYVN1 mediated-ERAD.
α6β4 integrin and laminin complex
Myelination of peripheral nerves is delayed in the absence of PMP22 in Schwann cells
and the axon-Schwann cells profiles show loose basal lamina (Amici et al., 2006). This fact
suggests that PMP22 is involved in the interaction between Schwann cells and the extracellular
matrix. PMP22 and β4 integrin are co-expressed on the surface of Schwann cells and in co-
immunoprecipitation experiments, PMP22 is shown to interact with β4 and also α6 integrin
together with laminin (Amici et al., 2006). β4 integrin serves as the linkage between Schwann
cells and the basal lamina. However, with significantly reduced PMP22 in PMP22-deficient
mice, β4 integrin level also decreased severely (Amici et al., 2006). Thus, PMP22 is a key
protein involved in the interactions of Schwann cells and extracellular environments by
interacting with α6β4 integrin and laminin.
1.5 Proximity-labeling strategy to identify PMP22 interactors
As described before, mutation of PMP22 may impair its interaction with other proteins
and undermine the degradation and form aggregates. It is important to identify the altered
interactors between wild-type PMP22 and mutant PMP22. If confirmed, interactors that have
20
different behavior with mutant PMP22 compared to the wild-type may be a possible target for
therapies.
A former lab member, Yuting Cheng used the BioID method to screen and identify novel
protein interactors. BioID, a humanized bacterial biotin ligase was fused to PMP22 and the
vector used to make a stable line. In the presence of biotin, any protein that interacts with PMP22
within the cell, even transiently or indirectly, would have its lysine residues biotinylated by
BioID. The biotinylated proteins can be easily isolated by affinity purification and subjected to
mass spectrometric analysis to identify candidate interactor proteins. Yuting created the cell lines
expressing either PMP22-BioID-myc or RFP-BioID-myc (as a control), treated them with biotin
and prepared cell extracts. The biotinylated proteins were isolated and subjected to mass
spectrometric analysis in collaboration with Dr. Kian Kani. Analysis of the mass spec data
identified, two candidate interactor proteins: WDR81 and WNK. The second Specific Aim of my
thesis is aimed at confirming the interaction with WDR81.
21
Figure 7. Proximity-dependent biotinylation of cellular proteins with BioID2
BioID2 is fused with a bait protein PMP22 and the fusion protein is expressed in cells.
After treatment with biotin for 16+ hours to the cells, any protein that interacts with
the fusion protein within a 10 nm distance will get its lysine residues biotinylated.
These proteins are isolated and subjected to mass spectrometric analysis.
22
1.6 The candidate novel interactor of PMP22: WDR81
WDR81 is a BEACH (beige and Chediak–Higashi) and WD40-repeat containing protein.
The BEACH domain is about 300 amino acids in length and is involved in cellular vesicle
trafficking and receptor signaling. BEACH was first discovered as the gene responsible for
Chediak–Higashi syndrome (Jogl et al., 2002). WD40-repeat proteins are usually found in
eukaryotes with functions including cell signaling, transcription, cell cycle and autophagy
(Stirnimann et al., 2010).
WDR81 functions as a complex with WDR91, and plays a role in endosomal degradation
of tetherin and EGFR (Rapiteanu et al., 2016). Knock-out of WDR81 causes swollen tetherin-
positive vesicles and enlarged endosomes and lysosomes, which impairs the degradation of
tetherin and EGFR through lysosomal pathways (Rapiteanu et al., 2016).
WDR81 plays a role in autophagy. It binds to ubiquitinated proteins and facilitates their
recognition by p62 (Liu et al., 2017). It also facilitates the linking of LC3 to ubiquitinated
proteins and therefore, promotes the removal of ubiquitinated protein through autophagy (Liu et
al., 2017). Based on these facts, association of WDR81 with PMP22 aggregates could be a
reasonable hypothesis.
23
Chapter 2
Materials and Methods
2.1 Cell culture
HEK293T and RT4D6P2T cells (Tomozawa and Sueoka, 1978) were cultured in 1X
DMEM medium (Gibco) with 10% Fetal Bovine Serum (Omega), and antibiotic-antimycotic
solution (Gibco; 100 units/ml of penicillin, 100 µg/ml of streptomycin, and 0.25 µg/ml of
Amphotericin B) in an atmosphere at 37 ℃ containing 5% CO2. Transgenic cells bearing various
genes cloned into the vector pTRIPZ were cultured in the medium above with 1µg/ml
puromycin.
2.2 Transfection and Transduction
Transient transfection: Lipofectamine™ 3000 (Life Technologies, Carlsbad, CA) was
used for transfection. Transfection was performed in the evening and the medium was changed
the next morning after approximately 18 hours to prevent toxicity. Twenty-four hours after
changing the medium, expression of the transgene was induced with 1µg/ml doxycycline if
needed. Forty-eight hours later, cells were lysed and extract prepared.
Lentivirus transduction: HEK293T cells were co-transfected with wild-type
PMP22_BioID_myc_pTRIPZ or RFP_BioID_myc_pTRIPZ, VSVG, PPAX and CMVΔR8 at a
10:2:1:1 ratio using polyethylinimine (PEI). Vector and packaging plasmids were added to 500
µl DMEM; separately 2 µl PEI per µg of DNA was added to 500 µl DMEM. After incubation for
24
15 minutes at room temperature, the DNA was added to the PEI, mixed, incubated for 20
minutes at room temperature and the solution added to HEK293T cells cultured in a 10 cm dish.
The medium was changed the next morning to prevent toxicity. Forty-eight hours after changing
the medium, the supernatant containing the virus was collected from the plate. Debris was
removed from the medium by centrifugation at 2500rpm for 10 min. To transduce RT4D6P2T
cells cultured in a 6-well plate with the virus, medium was removed and 500 µl DMEM
containing 10 µg/ml polybrene was added followed by incubation for 30 minutes at 37
0
C. Two
mls of the supernatant containing the virus was added to each well. After two days, cells were
resuspended and cultured in medium containing 1.5 µg/ml puromycin to allow selection of cells
retaining stably integrated wild-type PMP22_BioID2_myc or RFP_BioID_myc_pTRIPZ vectors
in the genome. Medium was changed every 3-4 days and ~ 10 days later, the puromycin-resistant
colonies were pooled and examined for expression of the transgene.
2.3 Treatment of cells with lactacystin, 3-methyladenine, and MG132
Twenty-thousand cells from the stable cell line expressing L16P-PMP22-RFP were
plated in each well of a 24 well plate and allowed to settle for at least 24 hours at 37°C with 5%
CO2. Expression of the transgene was induced by treatment with 1 µg/ml of doxycycline for ~20
- 24 hours. Cells were either uninduced, induced with doxycycline or -induced with doxycycline
in the presence of various inhibitors. The autophagy inhibitor 3-methyladenine (3-MA, Sigma, St
Louis, MO) was freshly dissolved in culture medium 1 hour before use at 37°C. The
concentration of 3-MA (10 mM) used in this study is the same as that used in studies by other
investigators was determined experimentally (see Results) and was not toxic to the cells as
25
determined in preliminary experiments. Similarly, experiments were conducted to determine the
optimal concentration of lactacystin and MG132 to use. To analyze the effects of lactacystin,
MG132 and 3-MA on PMP22-RFP aggregate accumulation, inhibitors were added when gene
expression was induced with doxycycline. Twenty-four hours later, nuclei were stained with 1
µg/ ml of Hoechst 33342 for 30 mins and the medium replaced with dye-free DMEM with 10%
fetal calf serum. Live cell images were recorded from five fields in each well with a Leica
DMI3000 B fluorescence microscope at 20X magnification. Raw integrated granule intensity per
cell was calculated using Image J software.
2.4 GFP-LC3 puncta analysis
A stable HeLa cell line expressing GFP-LC3 (Ni et al., 2011) was flow-sorted to enrich
for GFP-positive cells. Each well of a 24 well plate was seeded with this cell and allowed to
settle for at least 24 hours at 37°C with 5% CO2. The autophagy assay was optimized with
loperamide. The concentration of chloroquine was also tested to determine the optimal
concentration and length of treatment. Test compounds being assayed were added to the cells
and 3 hours before ending the treatment, 10 µM chloroquine was added to some of the wells. At
the end of the treatment period, nuclei were stained with 1 µg/ml of Hoechst 33342. Images were
recorded from five fields per well with a Leica DMI3000 B fluorescence microscope at 20X
magnification. Puncta number per cell were determined using the “Find Maxima” feature in
Image J software. Imaging was done either live or after fixation of cells with 4% formaldehyde.
26
2.5 Antibodies
The following antibodies were used: rabbit anti-myc tag antibody (Cell Signaling, Danvers,
MA), rabbit anti-WDR81 antibody (Abclonal, Woburn, MA), rabbit anti-p62 antibody (Cell
Signaling, Danvers, MA), rabbit anti-LC3 antibody (Cell Signaling, Danvers, MA), mouse anti-
beta-actin antibody (Cell Signaling, Danvers, MA), mouse anti-RFP antibody (Origene, Rockville,
MD), anti-rabbit HRP-conjugated secondary antibody (Promega Scientific, Madison, WI), anti-
mouse HRP-conjugated secondary antibody (Tonbo, San Diego, CA), rabbit anti-HA (Cell
Signaling, Danvers, MA), rabbit anti-HA agarose bead (Cell Signaling, Danvers, MA), goat anti-
Mouse IgG, peroxidase-conjugated light chain specific secondary antibody(115-035-174, Jackson
ImmunoResearch Labs, West Grove, PA), and peroxidase-conjugated monoclonal mouse anti-
rabbit light chain specific secondary antibody (211-032-171, Jackson ImmunoResearch Labs,
West Grove, PA).
2.6 Western analysis
Cells from a 10 cm dish were washed with PBS 3 times and collected with 300-600 µl lysis
buffer (1% Triton X-100, 0.5% deoxycholate, 0.2% SDS, 50 mM Tris, 150 mM NaCl, pH 7.5).
Before using, protease inhibitors (Roche Applied Science) was added to the lysis buffer at 1:6 v/v.
Resuspended cells were sonicated at 40°C three times for 5 sec with a 2 sec pulse. The cells were
placed on ice for 20 min. They were then spun at 14000 rpm for 10 min in the microcentrifuge in
the cold (4°C) room. The supernatant was then collected. Protein concentration was determined
using the Bio-Rad protein assay reagent kit (Bio-Rad Laboratories, Hercules, CA).
27
Western analysis using nitrocellulose membranes (for most of the proteins): Twenty
µg of total protein was mixed with 5 µl of SDS-PAGE loading buffer (NuPAGE LDS Sample
Buffer 4X: 1:4 v/v, 2-Mercaptoethanol: 1:100 v/v) and electrophoresed using a MINI-PROTEAN
II electrophoresis system from Bio-Rad on discontinuous gels comprising a 4% stacking and a 10%
resolving SDS-PAGE gels. When western analysis involved the high molecular-weight protein,
WDR81 an 8% resolving SDS-PAGE gel was used. Electrophoresis was conducted at 150V
constant voltage for 75 min or until the dye had almost run out of the gel. Proteins were transferred
to nitrocellulose membranes (0.45 µm, Bio-Rad) for 1 hour at 98V constant voltage using a Bio-
Rad Semi-Dry Blotting apparatus in transfer buffer (25 mM Tris pH 8.8, 192 mM glycine, 20%
v/v methanol). For transfer of high molecular weight proteins, transfer was conducted for 2 hours
at 98V. The membranes were stained with Ponceau to check for efficacy of transfer and integrity
of proteins and then blocked with 5% fat free milk in TBST (140 mM NaCl, 25 mM Tris-HCl pH
7.6, 0.1% v/v Tween-20) for 1 hour at RT or 30 minutes at 37
0
C with shaking if room temperature
was below 200C. After blocking, the membranes were incubated overnight at 4°C with the primary
antibody at a 1:2000 dilution. The membranes were washed with TBST three times for 10 mins
each and incubated for 1 hour at RT with an HRP-conjugated secondary antibody diluted 1:5000
in 5% milk in TBST. Bands were detected using Pierce™ ECL Western Blotting Substrate. If
needed, membranes were stripped for 30 mins in mild stripping buffer (15 g glycine, 1 g SDS, 10
ml Tween-20, fill with H2O to 1L) and incubated with 5% fat free milk in TBST for 1h.
Western analysis using PVDF membranes: For proteins of MW less than 25 kDa, e.g.
LC3, western blotting was conducted using PVDF membrane as outlined here. Ten µg of total
protein in SDS-PAGE loading buffer (NuPAGE LDS Sample Buffer 4X: 1:4 v/v) was heated for
5 min at 95
0
C. After heating, tubes were put on ice for 1 min and spun for 2 min at 13,000 rpm.
28
The samples were loaded and separated using a MINI-PROTEAN II electrophoresis system from
Bio-Rad on discontinuous gels comprising a 4% stacking and a 13% resolving SDS-PAGE gels.
Electrophoresis was conducted at 146V constant voltage for 75 min or until the dye almost ran out
of the gel. Proteins were transferred to PVDF membranes (0.2 µm, Bio-Rad) for 1 hour at 150mA
constant current using a Bio-Rad Semi-Dry Blotting apparatus in transfer buffer (3.03g tris base,
14.41g glycine, 200ml 100% methanol and the volume made up to 1L with H2O. The transfer
buffer was kept at -20
0
C to pre-cool during the SDS-PAGE. Before transfer (right after setting up
the SDS-PAGE), the PVDF membrane was soaked in methanol for 1 min until the membrane got
more transparent. The membrane was then soaked in transfer buffer while the SDS-PAGE gel was
running. After transfer, the membrane was soaked in methanol and dried for 2 min. It was cut and
labeled and then soaked again for 1 min in methanol and washed with TBST for 5 min. The
membrane was blocked with 1% fat free milk in TBST (25 mM Tris7.4, 150 mM NaCl, 2.7 mM
KCl, 0.8% Tween 20 in H2O) for 1 hour at RT. After blocking, the membrane was incubated
overnight at 4°C with the primary antibody at a 1:2000 dilution. The membrane was washed with
TBST three times for 10 mins each and incubated for 1 hour at RT with an HRP-conjugated
secondary antibody diluted 1:10,000 in 1% milk in TBST. Bands were detected using Pierce™
ECL Western Blotting Substrate. If needed, the membrane was stripped for 30 mins in mild
stripping buffer (15 g glycine, 1 g SDS, 10ml Tween-20 and made up to 1 L with H2O) and
incubated with 1% fat free milk in TBST for 1 h.
29
2.7 Co-immunoprecipitation experiments
The cell extract for co-immunoprecipitation experiments was made as described above
under Western analysis except that 10% glycerol was added to the lysis buffer to maintain protein
interactions. The protein complex was immunoprecipitated by antibody and then captured with
protein A/G beads or directly immunoprecipitated by antibody-conjugated beads. Details of
specific experimental conditions are provided below.
Co-immunoprecipitation of myc-tagged PMP22 with WDR81. Each 100 µg protein extract
was incubated with 50 µl of Pierce Anti-c-Myc Magnetic Beads. Beads were separated using a
magnetic stand and then washed with TBST five times for 1 min with rotation at room temperature.
The initial supernatant (unbound) and all supernatants from the wash steps were saved for later
analysis. The co-immunoprecipitated protein was eluted from the beads by adding 100 µl of
NuPAGE® LDS Sample Buffer (4X) (Thermo-Scientific) and heated at 95-100⁰C for 10 minutes.
Co-immunoprecipitation of PMP22-RFP with WDR81-HA. 1 mg of lysate protein was
used in each co-immunoprecipitation reaction with Sera-Mag SpeedBead Protein A/G (GE
Healthcare). Lysates were pre-cleared by incubation with 50 µl of the beads at 4⁰C for 30 min with
rotation. The beads were separated with a magnetic stand and the supernatant was collected. 5 µg
of mouse anti-RFP antibody (Origene, Rockville, MD) was added to the pre-cleared lysates and
incubated at 4⁰C overnight with rotation. On the next day, 100 µl of beads were added to the co-
immunoprecipitation reaction and incubated at room temperature for 2 hours with rotation. The
beads were collected with a magnetic stand and the supernatant kept aside. The beads were washed
five times with TBST for 1 min with rotation at room temperature. The output protein was eluted
from the beads by adding 50 µl of Sample Buffer and heated at 95-100⁰C for 10 minutes. 75 µg
30
of protein from the precleared lysates was loaded on the gel to represent the input sample.
Approximately 20% of the supernatant and 25 µl of output sample collected in the sample buffer
was loaded on the gel.
To improve the yield of proteins co-immunoprecipitated with PMP22-RFP, I conducted
additional experiments with protein A/G agarose beads as follows: 1 mg of lysates was used in
each co-immunoprecipitation reaction. Lysates were pre-cleared in 50 µl of the beads in 4⁰C for
30 min with rotation. After centrifugation of the tube at 3000g for 3 min, the supernatant was
collected and kept aside. 5 µg of mouse anti-RFP antibody (Origene, Rockville, MD) was added
to the pre-cleared lysates and incubated at 4⁰C overnight with rotation. On the next day, 50 µl of
beads was added to the co-immunoprecipitation reaction and incubated at 4⁰C for 2 hours with
rotation. The beads were collected by centrifugation at 3000g for 1 min at 4⁰C and the supernatant
saved. The beads were washed 5 times with lysis buffer for 1 min with rotation at 4⁰C. The output
protein was eluted from the beads by adding 50 µl of sample Buffer and heated at 95-100⁰C for
10 minutes. Sample loading was similar to that described for the Sera-Mag beads experiment above.
Co-immunoprecipitation of WDR81-HA with PMP22-RFP. 1 mg of lysates was used in
each co-immunoprecipitation reaction. 10 µl of anti-HA antibody conjugated Sepharose beads
(Cell Signaling) were added to the lysate and incubated at 4⁰C overnight with rotation. On the next
day, the beads were collected by centrifugation at 300 g centrifuge for 1 min at 4⁰C and the
supernatant kept aside. The beads were washed 5 times with lysis buffer for 1 min with rotation at
4⁰C. The output protein was eluted from the beads by adding 50 µl of Sample Buffer and heated
at 95-100⁰C for 10 minutes. Sample loading was similar to that described for the Sera-Mag beads
experiment above.
31
Chapter 3
Results
3.1 Effect of a proteasomal inhibitor and an autophagy inhibitor on the ability of
compounds to reduce aggregates in the L16P-PMP22-RFP stable cell line
The ability of selected analogs of compounds identified in the primary screen to identify
molecules that caused a reduction in cytoplasmic aggregates formed in a HeLa cell line
expressing PMP22 bearing the L16P mutation fused to RFP to induce autophagy was assessed
using the same assay used by Sunju Choi in the primary screen. Briefly, transgene expression
was induced in the presence of the analog and ~24 hours later, aggregates were visualized under
a fluorescence microscope and images from five fields captured for each well. The level of the
aggregates was determined by analysis of the images with the “Measure Raw Integrated Density
(RawIntDen)” function in ImageJ software.
3.1.1 Establishment of the optimal conditions for measuring the effect of compounds on
aggregates
(i) Optimization of the doxycycline concentration for induction of expression of the
transgene in the L16P-PMP22-RFP HeLa cell line
To determine the optimal doxycycline concentration that is abundant enough to be used
for examining aggregate reduction, 0.2 µg/ml, 0.5 µg/ml and 1 µg/ml doxycycline, respectively
was added to L16P-PMP22-RFP HeLa cells. The cells were then examined under a fluorescence
microscope (Keyence) with 20X magnification for live imaging. Also, to test if frequent freezing
32
and thawing would reduce the effect of doxycycline, an old and new vial of 1 mg/ml doxycycline
was tested under the same conditions.
Figure 8 shows that the new vial of doxycycline with 1 µg/ml concentration was most
efficient. This result showed that doxycycline should be aliquoted and steps should be taken to
avoid frequent freezing and thawing and that induction could be performed with doxycycline at a
concentration of 1 µg/ml.
33
Figure 8. Pilot experiment to determine optimal doxycycline concentration for
induction of transgene expression
L16P-PMP22-RFP HeLa cells were plated in a 24-well plate and induced with 0.2 µg/ml,
0.5 µg/ml and 1 µg/ml doxycycline from both old and new vials of doxycycline for 24
hours, shown as “old” or “new” plus concentration in x-axis. Each treatment was done in
duplicate wells. Nuclei were stained with Hoechst 33342 to allow estimation of cell
number. Five images were taken for each well by fluorescence microscopy. Images were
then analyzed by ImageJ to measure the integrated intensity of red pixels (RawIntDen of
red signal) which represented the amount and intensity of RFP signals. RawIntDen was
then divided by the number of nuclei of cells that expressed RFP. Panel A shows the non-
induced cells and Panel B shows the 1 µg/ml dox-induced cells. Panel C shows the
RawIntDen value for each batch of doxycycline. New vials of doxycycline have higher
performance in inducing aggregates.with1 µg/ml doxycycline treatment evaluated by
RawIntDen per cell which represent the intensity of PMP22-RFP aggregates signals per
cell. Nucleus were stained with Hoechest33342.
34
(ii) Flow sorting to enrich for L16P-PMP22-RFP expressing HeLa cells
It was noted during the experiments that the L16P-PMP22-RFP HeLa cells seemed to
lose expression due to transgene silencing. Therefore, cells were induced overnight with 1µg/ml
of doxycycline and flow sorted to enrich for transgene-expressing cells. Figure 9 shows images
of L16P-PMP22-RFP HeLa cells before (Panel A) and after flow sorting at the Flow Cytometry
Core Facility, USC Stem Cell Center (Panel B). The cells after flow sorting had much higher
percentage of expressing cells. L16P-PMP22-RFP HeLa cells were flow-sorted twice during
these experiments to ensure that most of the cells were expressing the transgene.
Figure 9. L16P-PMP22-RFP HeLa cells before and after flow cytometry
L16P-PMP22-RFP HeLa cells were plated in 10 cm dish for 24 hours and then
induced for 24 hours with 1 µg/ml doxycycline and subjected to flow cytometry. The
top 5% cells expressing RFP were collected. Panel A shows cells before flow sorting
and panel B shows cells after sorting. Images were captured by fluorescence
microscopy.
35
3.1.2 Effect of proteasomal and autophagy inhibitors on formation of L16P-PMP22-RFP
aggregates
To determine the pathways by which the compounds reduce aggregates, a proteasome
inhibitor lactacystin (Lact) and an autophagy inhibitor 3-methyladenine (3-MA) were used. Our
rationale was that if a compound is an autophagy inducer, it should result in a reduction of
aggregates in the cells, even in the presence of lactacystin, but would not do so in the presence of
3-MA.
(i) Determination of the time that treatment should made to reduce aggregates
A pilot experiment was conducted to determine if the treatment with the compounds
should be done simultaneously as transgene induction or after a period of transgene induction to
allow accumulation of aggregates. I found that it was better to treat the cells with the compound
along with the inducing agent for 24 hours for best results and this is the approach I used for the
remainder of the experiments.
(ii) Initial experiments to determine the effect of proteasomal and autophagy inhibitors on
aggregate formation
The cells were plated in 24-well plates at 2 X10
4
cells per well with 0.5 ml medium
containing 1 µg/ml puromycin. After 24 hours, cells were induced with 1 µg/ml doxycycline and
treated with compounds and inhibitors. The experiment was conducted in duplicate plates.
Twenty-four hours later, cells were prepared for imaging. I previously used confocal microscopy
for this set of experiments, but I found the results were much better when live imaging was
performed with a fluorescence microscope. To perform live imaging, cells were stained with 0.5
36
µg/ml Hoechst 33342 directly in the medium. Ten minutes later, medium was aspirated and cells
washed with DPBS. Then, 0.5 ml of imaging medium (DMEM without phenol red, 5% FBS,
10mM HEPES-KOH pH7.5) was added and the cells were ready for imaging.
Figures 10A and B show a sample image after treatment with the compound USC 3-
27.Treatment with USC 3-27 caused a reduction of aggregates when cells were induced by
doxycycline. This means that USC 3-27 has the ability to reduce L16P-PMP22-RFP aggregates.
Figures 10 C and D show that when 3-MA, an autophagy inhibitor is present, USC 3-27 loses its
ability to reduce aggregates, but in Figures 10E and F, the proteasomal inhibitor lactacystin did
not show a similar inhibition of USC 3-27. A RawIntDen analysis was performed with ImageJ
and the resulting data shows that all compounds have the ability to reduce aggregates, and this
ability can be inhibited by 3-MA but not lactacystin. Both 3-MA and lactacystin treatment alone
show increasing numbers of aggregates, suggesting that they are effective inhibitors, while
compounds USC 1-46, USC 1-48, USC 3-4 and USC 3-27 all induce autophagy and reduce
L16P-PMP22-RFP aggregates.
In the first few experiments, a Keyence microscope was used at 20X magnification
because that was the highest magnification achievable with 24-well plates. In most of the
following experiments, I used a Leica fluorescence microscope was used because it allowed up
to 40X magnification for 24-well plates and thereby resulting in more clear and reliable results.
37
Figure 10. Effect of lactacystin and 3-MA on aggregates in L16P-PMP22-RFP HeLa cells
Panel A-F: Fluorescence images of cells induced with 1 µg/ml doxycycline and treated with 10 µM
USC3-27 and 10 µM lactacystin or 5 mM 3-MA for 24 hours. Nuclei were stained with Hoechst 33342
to allow estimation of cell number. Five images were taken for each well by fluorescence microscopy.
Images were then analyzed by ImageJ to measure the integrated intensity of red pixels (RawIntDen of
red signal) which represented the amount and intensity of RFP signals. RawIntDen was then divided by
the number of nuclei of cells that expressed RFP. Panel A: no treatment other than induction; cells were
induced without any additional reagents. Insert image represent the non-induction cells. Panel B:
treatment with USC 3-27 compounds and induction. Panel C: treatment with 3-MA and induction; Panel
D: treatment with USC3-27 plus 3-MA and induction; Panel E: treatment with lactacystin and induction;
Panel F: treatment with USC3-27 plus lactacystin and induction. USC3-27 treatment could reduce
aggregates in cell (panel A and B). USC 3-27 could reduce aggregates in the presence of lactacystin
(panel E and F) but it did not do so in the presence of 3-MA (panel C and D). Panels G and H show
analysis from two individual experiments. The results suggest that USC 1-46, USC 1-48, USC 3-4 and
USC 3-27 are autophagy inducers. Test for statistical significance was done by two-sample unequal
variance (heteroscedastic) Student's t-Test with one tail. *: p<0.05, **:p<0.01.
38
(iii) Optimization of the concentrations of compounds, and proteasomal and autophagy
inhibitors
In normal Schwann cells, more than 80% of PMP22 is degraded through the proteasomal
pathway. Therefore, in the presence of lactacystin, which inhibits the proteasomal pathway, a
very large amount of aggregates appeared in the cell. This large number of aggregates may put
the cell in an unhealthy state and also result in an increase in RFP aggregates. The unhealthy
cells were more likely to perform unevenly in regards to their ability to degrade the aggregate
and hence caused higher standard deviation within the group. The overexpression of RFP will
underestimate the intensity of higher signals.
To optimize the concentration of compounds, proteasomal and autophagy inhibitors, a
range of concentrations were selected and used to treat L16P-PMP22-RFP HeLa cells for 24
hours. The criteria to determine the concentration of the inhibitors was that the cells should not
show any evidence of toxicity including apoptosis and that the RawIntDen should show no
significant differences between the groups that were treated with two inhibitors. The doxycycline
concentration was also determined at 1µg/ml so that the baseline of aggregate was acceptable for
evaluating increasing and decreasing. These results are shown in Figure 11. Based on these
results, the concentration of compounds at 10 µM and of lactacystin and 3-MA at 2.5 µM and 10
mM, respectively, was chosen for the subsequent experiments.
39
Figure 11. Optimization of concentrations for compounds and inhibitors in L16P-PMP22-
RFP HeLa cell aggregate assay
L16P-PMP22-RFP cells were plated in 24-well plates for 24 hours and then treated with
compounds, inhibitors and doxycycline for 24 hours. Nuclei were stained with Hoechst 33342 to
allow estimation of cell number. Five images were taken for each well by fluorescence
microscopy. Images were then analyzed by ImageJ to measure the integrated intensity of red
pixels (RawIntDen of red signal) which represented the amount and intensity of RFP signals.
RawIntDen was then divided by the number of nuclei of cells that expressed RFP. Panel A shows
the optimization of USC 3-27 concentration. Aggregates show a dose-dependent reduction in
aggregates. Treatment with USC3-27 and lactacystin (either 2.5 or 5 µM) appeared to inhibit
reduction. Treatment with USC3-27 and either 10 or 15 mM 3-MA completely inhibited the
action of the compound on aggregates present. Panel B is the optimization of lactacystin and 3-
MA. The reason for this is because in Figure 10 (H), 10 µM lactacystin treatment showed too
much inhibition that resulted in high standard deviations and 5 mM 3-MA showed less inhibition
than that seen with lactacystin. Here, 2.5 µM lactacystin was already able to increase aggregates
and a higher concentration of (10mM) 3-MA was needed to show the same level of inhibition.
40
(iv) The effect of compounds on aggregate formation in the presence of lactacystin at 2.5 µM
and 3-MA at 10 mM
Once optimal concentrations of compounds and inhibitors was established, L16P-
PMP22-RFP-expssing HeLa cells were treated with the various analogs at 10 µM concentration
in the presence of 5 mM lactacystin or 10 mM 3-MA and the effect on aggregates determined.
These results seen in Figure 12 showed that treatment with the compounds caused a reduction of
aggregates, that treatment with the compounds in the presence of lactacystin does cause a
decrease in the aggregates, and that treatment with the compounds with 3-MA, an autophagy
inhibitor, appears to inhibit the ability of the compounds to cause a reduction in aggregates.
These results thus suggest that compounds USC1-46, USC1-48, USC3-4, and USC3-27 could be
autophagy inducers, and that it is through this activity that the compounds reduce L16P-PMP22-
RFP aggregates in the cytoplasm.
41
dox
USC1-46
USC1-48
USC3-4
USC3-27
Lact
USC1-46+Lact
USC1-48+Lact
USC3-4+Lact
USC3-27+Lact
3-MA
USC1-46+3-MA
USC1-48+3-MA
USC3-4+3-MA
USC3-27+3-MA
0
50000
100000
150000
Treatm ent
RawIntDen/cell
** **
**
**
*
*
**
*
*
*
NS
NS
NS
*
Figure 12. Effect of lactacystin and 3-MA on the ability of analog compounds to
reduce aggregates in L16P-PMP22-RFP HeLa cells (second attempt)
L16P-PMP22-RFP cells were plated in 24-well plates for 24 hours and then treated
with 10 µM compounds, 2.5 µM lactacystin, 10 mM 3-MA and 1 µg/ml doxycycline
for 24 hours. Nuclei were stained with Hoechst 33342 to allow estimation of cell
number. Five images were taken for each well by fluorescence microscopy. Images
were then analyzed by ImageJ to measure the integrated intensity of red pixels
(RawIntDen of red signal) which represented the amount and intensity of RFP signals.
RawIntDen was then divided by the number of nuclei of cells that expressed RFP.
These results suggest that USC 1-46, USC 1-48, USC 3-4 and USC 3-27 are
autophagy inducers since they were able to reduce aggregates in L16P-PMP22-RFP
HeLa cells and this reduction was inhibited by the autophagy inhibitor 3-MA but could
not be inhibited by the proteasomal inhibitor lactacystin. Test for statistical
significance was done by two-sample unequal variance (heteroscedastic) Student's t-
Test with one tail. *: p<0.05, **:p<0.01.
42
(v) Comparison of the effects of proteasomal inhibitors lactacystin and MG132 on
aggregates formation
The experiments to determine the effect of the proteasomal inhibitor, lactacystin tended
to give variable results An experiment was therefore conducted to determine the effect of
lactacystin at two different concentrations on aggregates and to compare the results with the
effect of a new proteasomal inhibitor MG132. The results shown in Figure 13, indicate that
lactacystin at 5 µM concentration yielded results similar to 1 µM MG132. Based on these results,
1 µM MG132 was a new candidate for proteasomal inhibition in future experiments.
0.00
20000.00
40000.00
60000.00
80000.00
100000.00
120000.00
140000.00
160000.00
180000.00
200000.00
no dox
dox
1-46
1-48
3-4
3-27
2.5uM Lact
5uM Lact
1uM MG132
2.5uM MG132
5uM MG132
10 mM 3-MA
Figure 13. Alternative proteasomal inhibitor MG132
Lactacystin sometimes shows loss of inhibition, so an alternative proteasomal inhibitor
MG132 was chosen to allow better inhibition of the proteasome. Also, the higher 5
µM concentration of lactacystin was selected for the same purpose. L16P-PMP22-RFP
cells were plated in 24-well plates for 24 hours and the treated with 10 µM
compounds, 2.5 µM and 5 µM lactacystin, 1 µM, 2.5 µM, 5 µM MG132, 10 mM 3-
MA and 1 µg/ml doxycycline for 24 hours. Nuclei were stained with Hoechst 33342 to
allow estimation of cell number. Five images were taken for each well by fluorescence
microscopy. Images were then analyzed by ImageJ to measure the integrated intensity
of red pixels (RawIntDen of red signal) which represented the amount and intensity of
RFP signals. RawIntDen was then divided by the number of nuclei of cells that
expressed RFP. Results show that to generate considerable but not an overwhelming
amount of aggregates, 5 µM lactacystin or 1 µM MG132 should be used.
RawIntDen/cell
43
(vi) Determination of the effect of lactacystin at 5 µM and MG132 at 1 µM on aggregates
formation
As stated in the legend to Figure 13, the proteasomal inhibitor lactacystin tended to give
variable results. Hence, a different proteasomal inhibitor, MG132 was tested for its effect on the
action of the compounds. The experiment shown in Figure 12 was repeated with the lactacystin
replaced by 1 µM MG132. These results show that proteasomal inhibition does not affect the
ability of the compounds to reduce aggregates but inhibition of autophagy with 3-MA inhibits
the ability of the compounds to reduce aggregates.
44
Figure 14. Effect of MG132 and 3-MA on the ability of analog compounds to
reduce aggregates in L16P-PMP22-RFP HeLa cells
L16P-PMP22-RFP cells were plated in 24-well plates for 24 hours and then treated
with 10 µM compounds, 1 µM MG132, 10 mM 3-MA and 1 µg/ml doxycycline for 24
hours. Nuclei were stained with Hoechst 33342 to allow estimation of cell number.
Five images were taken for each well by fluorescence microscopy. Images were then
analyzed by ImageJ to measure the integrated intensity of red pixels (RawIntDen of
red signal) which represented the amount and intensity of RFP signals. RawIntDen
was then divided by the number of nuclei of cells that expressed RFP. Compounds
show effects in significantly reducing aggregates and these effect could be inhibited
by autophagy inhibitor 3-MA and could not be inhibited by proteasomal inhibitor
MG132, suggesting that these compounds reduce aggregates through autophagy. 5 µM
lactacystin showed no effect on aggregates and result not present here. Test for
statistical significance was done by two-sample unequal variance (heteroscedastic)
Student's t-Test with one tail. *: p<0.05, **:p<0.01.
45
3.2 Evaluation of the ability of the compounds to induce autophagy using a GFP-
LC3 HeLa indicator cell line
To see if USC1-46, USC1-48, USC3-4 and USC3-27 really induce autophagy, we
decided to check if those compounds actually induce the autophagy process. LC3 is an
autophagosome indicator. This protein is normally in the cytoplasm but will assemble on the
membrane of autophagosomes in the process of autophagy. After the autophagosomes fuse with
lysosomes, LC3 will dissemble and return to cytoplasm. This fusion of GFP to LC3 allows
marking of autophagosomes as puncta which can be counted and this is one of the ways in which
autophagy is assessed.
(i) Optimization of the GFP-LC3 autophagy assay by varying chloroquine and loperamide
concentrations
To optimize the conditions, I treated cells with different concentrations of loperamide
(Lop) and chloroquine (CQ). High concentration of loperamide seems to saturate the
autophagosome and CQ treatment does not significantly increase the number of puncta. With a
lower concentration of loperamide, I can see that there is a gradual increase in the number of
puncta as the concentration of CQ is increased. Also, high concentrations of CQ show dominant
effects on puncta number and longer treatment times show loss of the effects of CQ when its
concentration is low. I did a similar set of experiments with each of the analogs as well to
determine the best concentration of the drug and chloroquine to use. The final conditions
selected based on the results shown in Figure 15 were: 2.5 µM for all compounds and
loperamide, and 10 µM for CQ. The treatment times selected were 18 hours for all compounds, 6
hours for loperamide, and 3 hours for CQ.
46
Figure 15. Optimization of loperamide and chloroquine concentrations for the
GFP-LC3 puncta assay
Several combination of different concentration of loperamide and CQ were tested with
GFP-LC3 cells. GFP-LC3 cells were plated in 24-well plates for 24 hours and then
treated with different concentrations of loperamide for 6 hours. 3 hours prior to the
imaging, different concentrations of CQ were added to the cells. Cells were then live
imaged by fluorescence microscopy at 40X magnification and autophagosomes were
counted as GFP puncta and then divided by cell number. The results show that high
concentration of loperamide saturate the autophagosome and CQ treatment did not
increase the number of puncta. At a lower concentration of loperamide, there is a
gradual increase in the number of puncta with increasing concentration of CQ. Also,
high concentrations of CQ show dominant effects on puncta number even were there
was no other treatment. 2.5 µM of loperamide and 10 µM for CQ were thus, chosen
for later experiments.
47
(ii) Establishment of imaging assay to measure GFP-LC3 puncta using a positive control
compound, loperamide
Measurement of puncta in the GFP-LC3 cell line is an accepted approach to determine
the ability of a compound to induce autophagy. I first attempted to use confocal microscopy for
this purpose but did not obtain useful results. I therefore, used fluorescence microscopy-aided
imaging of non-fixed cells whose nuclei had been stained with Hoechst 33342 to determine the
number of cells. Unlike the RFP signals, the GFP signals do not always form clear puncta and
instead exhibit green fluorescence as background in the cytoplasm. Therefore, the “Measure Raw
Integrated Density (RawIntDen)” function in ImageJ is not useful because it counts the intensity
of any pixel that is present in the green channel. Due to this, the “Find Maxima” function in
ImageJ was chosen instead for use in this experiment. “Find Maxima” can find the pixels with
peak intensity relative to the background. Each puncta represents an autophagosome.
Figure 16. Representative images from the GFP-LC3 puncta assay for autophagy
with loperamide treatment in the presence and absence of chloroquine
Panel A: untreated GFP-LC3 HeLa cells show very few puncta per cell; Panel B shows
increased puncta when treated with 2.5 µM loperamide. Panel C shows further increase
in puncta when treatment with 2.5 µM loperamide is followed by addition of 10 µM of
CQ. The puncta number increased with loperamide treatment and the puncta number
increase caused by CQ showed that loperamide is an autophagy inducer.
48
(iii) Treatment of GFP-LC3 cell line with compounds results in puncta formation
An autophagy inducer should show significant ability to increase the number of
autophagosomes, which in this experiment, appear as GFP puncta (Figure 16 A,B). The cells
may also lose expression of GFP-LC3 and flow sorting may concentrate the cells with too much
GFP-LC3 expression, which brightens the background of the cytoplasm as stated before. I used
the cell line I got from Dr. Wen-Xing Ding’s lab originally. The puncta number was divided by
the nuclei number with GFP signal expression to get puncta per cell.
(iv) Chloroquine treatment of GFP-LC3 cell line exposed to compounds results in increased
puncta formation
The international criteria (Klionsky et al., 2016) for autophagy research requires testing
of compounds with and without chloroquine (CQ) treatment before determining if the compound
is an autophagy inducer. Chloroquine inhibits the fusion of autophagosomes and lysosomes,
which means that autophagosomes will not get degraded and that GFP-LC3 will be retained on
the membrane of it. The induction of autophagy may not be monitored by GFP-LC3 puncta
accurately because the autophagy flux includes the fusion of autophagosomes with lysosomes
and the disassembly of LC3 from autophagosomes. Therefore, by inhibiting this process, the
number of GFP puncta per cell can be a good indicator for autophagy activity.
Figure 16 shows the puncta formation by adding compounds and CQ to the cells.
Increased puncta were evident in GFP-LC3 cells upon treatment with compounds and more
puncta were generated when CQ was added together with compounds. Results suggest that
USC1-46, USC1-48, USC3-4 and USC3-27 induce autophagy through the generation of
autophagosomes. However, USC1-48 treatment alone did not pass the t-test for an increase of
49
autophagosome puncta upon treatment with CQ, though CQ treatment did result in a greater
increase of puncta compared to USC1-48 treatment alone upon visual examination of the images
and quantitative analysis of the data.
Figure 17. Compounds USC1-46, USC3-4 and USC3-27 appear to induce autophagy in
GFP-LC3 HeLa cells
GFP-LC3 cells were plated in 24-well plates for 24 hours and then treated with four
compounds at 2.5 µM for 18 hours. 6 hours prior to the imaging, 2.5 µM loperamide was
added to the cells. 3 hours prior to the imaging, 10mM CQ was added to the cells. Cells were
then live imaged by fluorescence microscopy at 40X magnification and autophagosomes
were counted as GFP puncta and then divided by cell number. Comparison treatment images
for compounds with and without CQ are shown in panel A. Compounds alone increase GFP
puncta and additional puncta appear when CQ is present. Panel B is the graph of puncta per
cell for each group, suggesting that USC 1-46, USC 3-4 and USC 3-27 are autophagy
inducers. Although there was a significant increase of puncta by adding CQ to the cells
compared to USC1-48 alone, USC 1-48 itself did not show a statistically significant increase
of puncta compared to the non-treatment group. Test for statistical significance was done by
two-sample unequal variance (heteroscedastic) Student's t-Test with one tail. *: p<0.05,
**:p<0.01.
50
3.3 Confirmation of the results of the mass spectrometric analysis to identify
novel protein interactors of PMP22
As mentioned in the Introduction, Yuting Cheng had established the reagents to use
BioID2-tagging of PMP22 to identify protein interactors. Mass spec analysis by Dr. Kian Kani
identified a candidate protein, WDR81 that may interact with PMP22. My goal was to
demonstrate if the interaction of WDR81 with both wild-type and mutant PMP22 was bona fide
using co-immunoprecipitation.
(i) Examination of the quality of anti-WDR81 antibody (ABclonal)
The first antibody purchased for WDR81 from Novo Bioscience did not recognize a
protein of the expected size of 211 kDa. A second antibody was obtained from ABclonal
Technology (Woburn, MA). This antibody was used for western analysis of RT4 rat Schwann
cells, HeLa cells and several transgenic cell lines as indicated in Figure 17.
Figure 18. WDR81 expression in RT4 Schwann cells, HeLa cells and various
transgenic HeLa and RT4 cell lines
EndogenousWDR81 (211kDa) identified with anti-WDR81 antibody from ABclonal.
The signal for WDR81 was clear but not equivalent among L16P-PMP22-RFP HeLa
cells, RT4 Schwann cells and PMP22-BioID2 RT4 Schwann cells. Unfortunately, the
samples ran abnormally in lanes 1, 2 and 3 and the signal is hence seen as
discontinuous bands of WDR81.The β-actin detection also failed for an unknown
reason.
51
(ii) Transient expression of WDR81 construct (pHRSIN.pSFFV WDR81 pSV40 Blast) from
Prof. Paul Lehner's lab, Cambridge University
To ensure higher WDR81 expression in RT4 Schwann cells, WDR81 constructs were
acquired from Prof. Paul Lehner's lab and one of the constructs that expresses WT WDR81 was
used to transiently transfect RT4 cells using Lipofectamine 3000. WDR81 expression was
confirmed as shown in Figure 18.
Figure 19. Endogenous and transient expression of WDR81
Transfections of WDR81 expression vector were performed on RT4 Schwann cells,
and an RT4 Schwann cell line stably transfected with PMP22-BioID2-myc to obtain
higher expression of WDR81 for the co-immunoprecipitation experiments. WDR81
was also co-transfected with RFP-BioID2-myc control vector in RT4 Schwann cells.
Western analysis with the anti-WDR81 antibody revealed expression of the protein in
untransfected RT4 cells as well as those co-transfected with a WDR81 expression
vector in various transgenic cell lines. Since multiple bands were recognized with the
transfection of WDR81, I later chose the vector that expressed WDR81-HA so that
WDR81 could be detected with an anti-HA antibody.
52
(iii) Co-IP with anti-myc magnetic beads
I initiated the co-IP experiments starting with a stable cell line created by Yuting Cheng
that had been transfected with a PMP22-BioID2-myc vector. The extract was used for a co-IP
experiment which did not yield any results. I therefore, examined the extracts for expression of
the transgene using the myc antibody. As shown in Figure 19, unfortunately, this cell line
appeared to have lost transgene expression as I was unable to detect a signal with the myc
antibody. Transient transfection with the wild-type PMP22 fusion gene and two mutant PMP22
genes fused to BioID2-myc also gave a poor signal. I also ran extract from RT4 cells transiently
transfected with RFP-myc and noted that this vector yielded a strong signal in the same blot.
53
Figure 20. Lack of expression of PMP22-BioID2-myc
In panel A, RT4 cells that were transfected with wild-type and mutant PMP22-BioID2-
myc did not show any expression of transgenes compared to RFP-BioID2-myc
transfected RT4 cells. Repeat experiments (panel B) show low expression of
transfected PMP22-BioID2-myc and the RT4 Schwann cell line that used to stably
express PMP22-BioID2-myc also did not show strong expression, compared to the
robust signal of RFP-BioID2-myc obtained in the same experiment (not shown in this
figure due to the very high signal at the same exposure).
A
B
54
(iv) Alternative strategy to test PMP22 interaction with WDR81
Since the BioID2 fusions with PMP22 did not express well, an alternate strategy was
attempted with a construct where wild-type PMP22 was fused with RFP. I sought to transiently
express it in RT4 cells and use the extract for the co-IP experiment. Additionally, since the
WDR81 antibody recognized multiple bands, another construct received from Dr. Paul Lehner
that expresses WDR81 with 3X HA tags was used. WDR81 could be detected or
immunoprecipitated during immunoprecipitation by the anti-HA antibody. To test if RFP-
PMP22 can be detected by anti-RFP antibodies as well, a stable RT4 cell line that express RFP-
PMP22 was grown and analyzed by western blotting. WDR81 transfection and expression was
also tested by the anti-WDR81 antibody initially and by the anti-HA antibody in later
experiments.
Figure 21. Western blot analysis to detect expression of PMP22-RFP and WDR81
PMP22-RFP was detectable by western blot with anti-RFP antibody in the RT4 rat
stable Schwann cell line with an PMP22-RFP transgene when induced by doxycycline
for 24 hours,. The expression was relatively low when compared to that of RFP-
BioID2-myc transiently transfected in RT4 Schwann cells. Both endogenous and
transfected WDR81 could be detected by an anti-WDR81 antibody.
55
(a) Examination of expression of WDR81 and RFP in cell lines (stable and transient)
Polyethyleneimine (PEI) was used for several transfection experiments and it was noted
that although transfection of WDR81-HA and calnexin expression vectors was effective, the
expression of PMP22-RFP and RFP vectors was not as good. I therefore, used Lipofectamine
3000 and optimized the amount of DNA that was required for
transfection in RT4 cells or HeLa cells using a pTRIPZ-RFP expression vector l. The effect of
cell confluency and DNA concentration on the efficiency of transfection was examine by
fluorescence microscopy. The results shown in Figure show that initiating transfection when
RT4 cells were 50% confluent and a DNA concentration of 1 or 1.5 µg in a six-well dish gave
the best results. Extrapolating these results, RFP and PMP22-RFP transfection require 10 µg of
DNA in a10 cm dish but the transfection of WDR81-HA and CANX could remain at 5 µg per 10
cm dish to reduce the toxicity of Lipofectamine when the cells needed to be co-transfected with
two expression constructs.
56
Figure 22. Optimization of Lipofectamine 3000 transfection with respect to DNA
amount and cell confluency using the vector, pTRIPZ-RFP
Two cell densities and three DNA amounts were tested in RT4 rat Schwann cells and
HeLa cells for expression after transfection with Lipofectamine 3000. The cell density
refers to the confluency prior to conducting transfection. The DNA amount refers to
the amount of DNA in each well of 6-well plates. Fluorescence microscopy
examination shows cells were confluent upon imaging and that RT4 Schwann cells
transfected with 1 µg or 1.5 µg DNA when cells are 50% confluent express the highest
level of RFP.
57
(b) Co-IP result
Co-immunoprecipitation experiments conducted as described in Methods did not show
any evidence of PMP22-RFP co-immunoprecipitated with WDR81-HA immunoprecipitation
using either anti-RFP or anti-HA. The immunoprecipitation itself worked with both the RFP and
HA antibodies as shown in Figures 22 and 23. Note that although HA immunoprecipitation
worked for WDR81-HA, RFP immunoprecipitation only worked for RFP-BioID2-myc, which
has been confirmed to be strongly expressed in RT4 cells by transfection (see Figure 21).
However, both immunoprecipitations did not exhaust the target protein from the supernatant
(unbound) and did not concentrate the target protein in the output, which is also a not good sign.
Figure 23. Immunoprecipitation with anti-HA Sepharose beads
To examine if anti-HA immunoprecipitation works, the protein sample made from
RT4 Schwann cells transfected with PMP22-RFP and WDR81-HA was subjected to an
immunoprecipitation experiment. WDR81-HA could be immunoprecipitated by anti-
HA Sepharose beads and detected by anti-HA antibody. However, the
immunoprecipitation output failed to concentrate the target protein and the supernatant
samples were accidently discarded and were hence, not available for analysis.
58
Figure 24. Immunoprecipitation with anti-RFP antibody and protein G agarose
beads
Anti-RFP immunoprecipitation shows that RFP-BioID2-myc could be
immunoprecipitated by anti-RFP antibody and then recovered with protein G agarose
beads. However, the protein sample used here was RFP-BioID2-myc RT4 Schwann
cells extract, which was known to express high levels of transgenic protein. The
protein was probed with an anti-myc antibody. It is unclear why so many bands were
obtained Immunoprecipitation output also failed to concentrate the target protein and
could not exhaust it from the supernatant.
59
3.4 Evaluation of the ability of compounds to induce autophagy by quantifying
the level of LC3-II and p62
In the absence of autophagic activity, LC3 stays in the cytoplasm as LC3-I, with a
molecular weight of about 14 kDa. During autophagy, LC3 assembles on the membrane of
autophagosomes as LC3-II, which has a molecular weight of about 16 kDa. Therefore, by
quantifying the level of LC-II, we can assess the activity of autophagy. The level of p62 is also
an autophagy indicator. p62 is degraded through autophagy so lower levels of p62 correspond to
higher activities of autophagy.
Following the protocol from Dr. Mei Yang in Dr. Jianfu Chen’s lab at USC, western
blotting was done and probed with an anti-p62 antibody and an anti-LC3 antibody. Cell lysates
were made from the cells that were the untreated control and from cells that were treated with 10
µM USC3-27 for 3 hours, 6 hours or 24 hours. Since starvation is an efficient way to induce
autophagy, HeLa cell and L16P-PMP22-RFP HeLa cell were starved with HBSS for 2 hours and
lysates made as positive control. Figure 24 shows the western results for the 3 hours treatment
time point.
Results showed doublet bands of p62 which is abnormal but in the correct size range.
Also, the amount of p62 was not quite equal among groups and even within the same treatment
duplicates, while β-actin were approximately at the same level. The first hypothesis of the reason
causing this effect was the transfer process. Proteins were transferred to 0.22 µm pore size PVDF
membrane which is designed for transfer of small molecular weight proteins, since I also wanted
to evaluate LC3-II levels which has a molecular of 14 kDa.
60
Later, I tried 0.45 µm pore size nitrocellulose membrane for the top part of the gel where
p62 should reside and also tried a longer transfer time. Results were poor and not only for p62,
but LC3 also significantly lost signal during the experiments even though I used the same
protocol for the LC3 part and tried different samples I made for the 3 hour, 6 hour and 24 hour
treatment to avoid freezing and thawing. Though I unexpectedly lost signal for LC3, I figured
out that the membrane that worked best for p62 analysis was 0.45 µm pore size PVDF
membrane. This is reasonable since PVDF membrane in general, has better performance
compared to nitrocellulose membrane and a 0.45 µm pore is capable of transferring larger
proteins.
61
Figure 25. Effects of compounds on autophagy markers quantified by western
blot
LC3-II is the state of LC3 when it assembles on the membrane of autophagosomes, so
LC3-II level is positively correlated with autophagy activity, especially
autophagosome number. While p62 is degraded through autophagy exclusively, so p62
is negatively correlated with autophagy activity, especially autophagy flux. These
results did not show any evidence of autophagy induction or inhibition and repeated
attempts to confirm this were not successful.
62
Chapter 4
Discussion
Live cell imaging using inverted fluorescence microscope
The imaging of L16P-PMP22-RFP HeLa cells and GFP-LC3 HeLa cells was originally
done with confocal microscopy after growing the cells on cover slips. Unfortunately, several
problems including failing to detect signals and mounting medium background caused poor
results. Getting suggestions from experiments done by other labs and previous lab members,
imaging in plates works better and was more convenient for this type of data collection.
Following the protocol, I did experiments in both 96-well and 24-well plates and fixed
the cells using 4% paraformaldehyde. Results were much better than imaging with slides but the
frequent washing required during fixation washed most of the cells away and even in 24-well
plates with higher area per well, I found it hard to acquire five decent images. I could not plate
more cells per well to overcome the loss of cells because prior to the fixation, cells may have
overgrown and I wanted to avoid contact inhibition as it could affect aggregate formation.
I turned to live imaging later to avoid frequent washing. Cells were plated at lower
number so that they would not overlap with each other. It not only eliminated the contact
inhibition, but also avoided aggregates or puncta stacking together which would interfere with
data analysis where the most important part is signal “per cell”. Also, the cell number could not
be too low because I needed to take five images per well to get enough information.
Imaging was first done with a Keyence microscope. It is only capable of 20X
magnification for 24-well plates. It is designed for high throughput imaging but with low
63
magnification and low image quality which was not ideal for my studies especially for analysis
of GFP-LC3 puncta. The Leica microscope, with 40X magnification, was able to yield high
quality images but did not have the automated features of the Keyence microscope. I needed
more time for the Leica imaging so to stabilize the pH of the medium in the absence of CO2, I
added 10 mM HEPES pH 7.5 to buffer the medium and I used dye-free medium for imaging live
cells.
L16P-PMP22-RFP assay
L16P-PMP22-RFP is likely degraded mainly by the proteasome so the concentration of
lactacystin for other proteins as suggested in other papers could have caused an overwhelming
number of aggregates and also caused higher standard deviations. This, after optimization,
lactacystin concentration was decreased to 2.5 µM or 5 µM, and 3-MA was increased to 10 mM.
GFP-LC3 assay
The positive control, loperamide likely saturated puncta representing autophagosomes in
GFP-LC3 HeLa cells and the additive effect caused by CQ was therefore, not evident. I
therefore, optimized the concentration of loperamide necessary for its use as a positive control to
demonstrate increased puncta in the presence of chloroquine and to meet the international criteria
(Klionsky et al., 2016) for autophagy induction.
Image capture and ImageJ functions
For L16P-PMP22-RFP aggregates, pixel intensity was most important. Every little
change during image capturing such as laser intensity, exposure time or gain of signal could
significantly change the value of total RawIntDen in an image. I could not keep the same
64
parameters for every experiment because the RFP signal intensity varied in every set of
experiments, so that RawIntDen values were not comparable among experiments. All I could do
was keep parameters the same in terms of exposure time in a single experiment so that within an
experiment, the t-test was valid to evaluate statistical significance. The parameters needed to be
changed to mainly reflect the intensity of the RFP signal. The maximum value of a pixel in a
single channel is 255 and it was important to avoid exposure times that resulted in a large
number of pixels with an intensity of 255 as that indicated overexposure. Overexposure would
underestimate the difference between the highest intensity of pixels and that of lower pixels. I
therefore, chose to determine the exposure time with the wells that involved treatment with
inhibitors alone such as lactacystin and then, examine all the other wells with the same exposure
settings. I then used the “measure” tool in ImageJ to evaluate RFP signal intensity and divided it
by the number of nuclei to get a read-out on the aggregates.
GFP-LC3 HeLa cells have a strong GFP background in the cytoplasm and the number of
puncta were more relevant as a measure of autophagy than intensity. The “Find Maxima”
function was therefore the most suitable one for GFP-LC3 assay analysis. The imaging
parameter was set to barely show GFP puncta without a high GFP fluorescence background. The
“Find Maxima” tool counted pixels that had a higher intensity when compared to the surrounding
pixels, so it was important to set the appropriate threshold for analysis and was not changed
within an experiment. By setting the threshold in this manner, ImageJ could recognize puncta
with a much lower error rate compared to visual counting.
65
Transfection
Transfection with lipofectamine creates holes in the cell membrane and antibiotics in
medium can be toxic to cells if they are able to enter the cells. I therefore, avoided putting
antibiotics in the medium during transfection steps.
PEI transfection worked well for WDR81 and CANX transfections. Lipofectamine 3000
worked well for PTRIPZ-RFP, WDR81 and CANX but neither of them worked as well for
PMP22-PTRIPZ-RFP. This suggests that the PEI transfection failures may result only with
specific vectors. Interestingly, the RFP fluorescence signals could be seen clearly under the
microscope but RFP protein was oddly hard to detect by western blots, which proved to be a
significant barrier for the entire co-immunoprecipitation experiment.
Co-immunoprecipitation
Co-immunoprecipitation requires protein interaction to be maintained in cell lysates. As
suggested by Dr. Kian Kani, the cell lysate should be fresh and should not have been frozen prior
to the co-IP experiments. To stabilize the interactions, 10% glycerol was also added to the cell
lysis buffer.
Co-IP experiments were first done between PMP22-BioID2-myc with WDR81, but it was
hard to get cells expressing enough PMP22-BioID2-myc and I could not check the expression
after transfection by microscopy. The lab had a stable RT4 rat Schwann cell line expressing
PMP22-BioID2-myc made by Yuting Cheng but it lost expression. Neither my transient
transfection by Lipofectamine 3000 nor lentivirus transfection resulted in expression of PMP22-
BioID2-myc. Therefore PMP22-RFP was chosen in additional experiments.
66
The HA immunoprecipitation was done using anti-HA Sepharose beads. The RFP
immunoprecipitation was done with anti-RFP antibody and then with protein A/G magnetic
beads. I originally used protein A/G magnetic beads but I didn’t get any positive results. Then I
switched to protein G agarose beads because agarose beads have a higher capacity for
immunoprecipitation. Either protein A/G magnetic beads or protein G agarose beads could be
subject to a preclear step to eliminate the noise due to proteins that may get immunoprecipitated
by the beads themselves. Strong unexpected bands was sometimes seen for the output sample all
along the length of the lanes in the western blot and appeared to be strongest at the positions
corresponding to the heavy chain and light chain of IgG. Since I had already avoided using
antibodies from same species, it suggested that there was cross reactions between species
especially when a large amount of antibodies were used for the co-IP. The solution to this
problem was to use anti-light chain antibodies so that at least the area of the blot corresponding
to the molecular weight of the heavy chain would be devoid of interfering signals.
As stated under transfection problems, RFP-PMP22 expression level may not enough for
immunoprecipitation. Immunoprecipitation by HA immunoprecipitation worked and RFP
immunoprecipitation worked for RFP-BioID2-myc while immunoprecipitation of RFP-PMP22
with the RFP antibody did not show a signal even in the input. Immunoprecipitation should
exhaust target protein such that the supernatant should not have any unbound proteins but I was
never able to achieve this in any of my co-IP experiments. The reasons could be the ratio of input
protein and immunoprecipitation antibodies was not optimized, or the affinity between target
protein and antibody, or the affinity between antibody and protein A/G was undermined by some
condition or component. Thus, further optimization needed to be done before co-IP initiation.
67
RFP-PMP22 cleavage
RFP-PMP22, whether wild-type or mutant, easily forms aggregates in the cytoplasm and
is degraded in the proteasome and by autophagy. The degradation process may result in the
cleavage of RFP from PMP22 and cause misinterpretation of RFP signals. The L16P-PMP22-
RFP signal in a western blot may be actually RFP or partial RFP signal alone; thus, my reasoning
is that the measurement of RFP itself can actually reflect the amount of L16P-PMP22 that was
synthesized and retained in the cytoplasm because one RFP molecule corresponds to one L16P-
PMP22 molecule. However, this assumes that the cleavage of RFP from L16P-PMP22 is
occurring at the same levels in all the groups – untreated and treated – and if it is not, then my
results would not be reliable and could be skewed.
Thus, if RFP is indeed getting cleaved from PMP22, then this would unfortunately affect
the co-IP experiments and the western blots used to assess the co-IP results because I was using
RFP antibody to immunoprecipitate PMP22 and its associate partners. The cleavage would cause
the RFP alone to be immunoprecipitated instead of RFP-PMP22 and interactors with PMP22
would never be detected. So, in addition to the greatest challenge I had which was getting
adequate RFP-PMP22 expression, this possible issue of cleavage is the second concern. A good
antibody for PMP22 would be a better alternative for immunoprecipitating PMP22 and its
interactors.
Western blots for p62 and LC3
The first experiment I conducted to measure LC3-II and p62 levels were successful but I
was never able to reproduce them. I seemed to have problems with the transfer and my
duplicates were also not comparable. Dr. Jianfu Chen did tell us that this is a very tricky assay
68
and I followed their instructions carefully. I used both fresh extract as well as the original extract
but was not successful; I am not sure if repeated freeze-thaw of the original extract caused this or
there was some other issue that I did not identify.
69
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Abstract (if available)
Abstract
Charcot-Marie-Tooth (CMT) disease is the most common peripheral nerve disease. CMT1A, the most frequent type of subtype CMT1, results from the overexpression of peripheral myelin protein 22 (PMP22). The less frequent subtype CMT1E results from point mutations in PMP22. Demyelination of peripheral nerves due to a Schwann cell defect caused by these mutations results in a symmetrical reduction of nerve conduction velocity in all extremities. In normal Schwann cells, over 80% of wild-type PMP22 is degraded by the proteasome. Excessive or mutant PMP22 is retained in the endoplasmic reticulum and forms aggregates in the cytoplasm. Treatment with rapamycin activates autophagy and clears the aggregates and improves myelination in the PMP22-overexpressing mice. Therefore, the reduction of these aggregates could have therapeutic benefit to patients. ❧ The first aim of my thesis was to characterize the most active analogs of small molecules that were identified in a small molecule screen for agents that reduce aggregates formed by expression of PMP22 bearing an L16P mutation fused to red fluorescent protein (RFP). These analogs, USC 1-46, USC 1-48, USC 3-4 and USC 3-27 were found to reduce aggregates in L16P-PMP22-RFP expressing cells. This reduction was inhibited by the autophagy inhibitor, 3-methyladenine but was not inhibited by the proteasomal inhibitor, lactacystin, suggesting that they are autophagy inducers. Further experiments confirmed that these compounds could induce the formation of autophagosomes evident as puncta in a HeLa cell line stably expressing GFP-LC3. The second aim of my thesis was to conduct co-immunoprecipitation experiments to determine if WDR81, a candidate protein interactor with PMP22 identified in a BioID2 proximity-labeling screen did indeed interact with PMP22. These experiments were not successful because of very low expression of the PMP22-BioID2-myc as well as PMP22-RFP proteins in both RT4 Schwann cells and HeLa cells.
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Zhao, Yutai
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Core Title
Charcot-Marie-Tooth disease type 1E: follow-up studies on a screen for therapeutic small molecules and PMP22-interacting proteins
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Keck School of Medicine
Degree
Master of Science
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Biochemistry and Molecular Medicine
Publication Date
10/16/2020
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08/02/2018
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