UCH-L1 AS A SUSCEPTIBILITY FACTOR FOR NIGROSTRIATAL AND MESOLIMBIC
DOPAMINE NEURONS AFTER NEUROTOXICANT EXPOSURE AND AGING
By
Brittany Michele Winner

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Pharmacology and Toxicology - Environmental Toxicology - Doctor of Philosophy
2017

ABSTRACT
UCH-L1 AS A SUSCEPTIBILITY FACTOR FOR NIGROSTRIATAL AND MESOLIMBIC
DOPAMINE NEURONS AFTER NEUROTOXICANT EXPOSURE AND AGING
By
Brittany Michele Winner
Parkinson disease (PD), the second most prevalent neurodegenerative disorder, is
most commonly diagnosed in elderly individuals and is characterized by manifestation
of motor deficits such as bradykinesia, postural instability, resting tremor, and shuffling
gait. The motor symptoms of PD arise when dopamine (DA) neurons in the nigrostriatal
DA (NSDA) pathway degenerate, which are involved in regulating voluntary motor
coordination via the basal ganglia pathway. NSDA neurons are progressively lost in the
disease, which has no known cure. Other DA neuronal pathways in the central nervous
system are less affected by neuronal death, however: mesolimbic DA (MLDA) neurons
are less vulnerable to PD. Therefore, we seek to understand how MLDA neurons resist
degeneration. Since Lewy bodies, which are proteinaceous deposits of misfolded and
aggregated proteins, are the hallmark pathology of PD, we predict that major deficits in
protein degradation are involved in development and progression of PD. A gene found
mutated in a rare case of familial PD called ubiquitin carboxy-terminal hydrolase L1
(UCHL1) is involved in one of the major mechanisms of protein degradation, the
ubiquitin proteasome system (UPS) and functions as a deubiquitinating enzyme to
maintain pools of available monomeric ubiquitin. UCH-L1 is decreased in the SN of
mice exposed to the neurotoxicant, MPTP. MPTP exposure in rodents recapitulates loss
of DA and oxidative stress observed in patients with PD and can also be used to
recapitulate the differential susceptibility of NSDA and MLDA neurons. The goal of this

dissertation research was to investigate the role of UCH-L1 in influencing susceptibility
of NSDA and MLDA neurons to acute neurotoxic insult, and if aging plays a role in
determining vulnerability of NSDA and MLDA neurons or expression and function of
UCH-L1. UCH-L1 expression and function are maintained in non-susceptible MLDA
neurons, which corresponds to the pattern of MLDA susceptibility to MPTP exposure.
UCH-L1 expression is not affected by advanced age in either NSDA and MLDA
neurons, but UPS function is impaired in both cell body regions with advanced age.
These studies shed light on the potential contribution of the PD-linked neuronal
deubiquitinating enzyme UCH-L1 to selective vulnerability in PD.

ACKNOWLEDGEMENTS

I have so many people to thank for helping me along this journey, which sometimes felt
akin to Frodo’s journey to Mount Doom with the One Ring. He needed a whole
Fellowship to get there relatively unscathed, and then a crazy old wizard flying on
eagles to get him back. Quotes are from the fantastic movie adaptations of J.R.R.
Tolkien’s Lord of the Rings trilogy.
Although sometimes my graduate school journey felt like I didn’t know the sheer depth
of what I had gotten myself into, I must thank my undergraduate mentor, Dr. Ilona
Petrikovics, for suggesting the quest. She saw potential in me when I did undergraduate
research in her lab, and she’s the reason I decided to do a PhD in Toxicology in the first
place. Thank you, Ilona!
Next, I must thank the wizards who outlined what I needed to do and where I needed to
go to complete my journey: my mentors, Dr. Keith Lookingland and Dr. John Goudreau.
Sometimes the voyage seemed too daunting and I often thought I wasn’t cut out for the
it, but these benevolent forces used their powers for good and helped me along the
way—sometimes with good, sound advice, and other times with cryptic hints that I
wasn’t prepared at the time to understand. The quote by Gandalf is so appropriate than
with you: “A wizard is never late, Frodo Baggins. He arrives precisely when he means
to.” Thank you, Keith and John, for not giving up on me when I wanted to flee, and by
being patient with me when I lost patience with myself.

iv

In addition, I would like to thank the other members of my guidance committee who
were kind enough to help guide me along this journey: Dr. Michelle Mazei-Robison and
Dr. James Galligan. Michelle and Jim, thank you so much for your advice, for sitting
through all my committee meetings, for making sure I knew my stuff, and finally, for
reading this document. My experience was richer having you on my thesis committee.
Now, the important lovely elves who sacrificed time for me: Dr. Anne Dorrance, our
graduate program director, and Dr. Stephanie Watts, all around awesome unofficial
science/life coach! Anne was always there for me in her office with her famous box of
never-ending tissues, telling me not to give up and sympathizing with my various woes
as well as sometimes helping to make sure I got paid. Stephanie read some of my
writing to make sure it made sense, and graciously offered use of the equipment I
dearly needed (not to mention the chocolate and fancy hand soap!). These fantastic
ladies made the journey more bearable, and the gifts they gave me along the way
reminded me of Galadriel’s gift to Frodo: “May it be a light to you in dark places, when
all other lights go out.” Thank you, Anne and Stephanie, for being a light to me in the
dark times of my journey.
Next, Frodo wouldn’t have gotten out of Rivendell (let’s be honest, Hobbiton!) without a
great squad by his side. I would like to thank the previous members of the
Goudreau/Lookingland laboratory: Dr. Bahareh Behrouz, Dr. Chelsea Tiernan, Dr.
Matthew Benskey, Dr. Tyrell Simkins, Dr. Hae-young Hawong, Dr. Joseph Patterson,
and Dr. Teri Lansdell. Each member of this unique and fun Fellowship gave scientific
advice and helped me grow into the explorer/scientist I needed to be to complete this
quest—and are still helpful today! Special thanks to Teri for putting up with me the
v

longest in the lab and enduring my shenanigans—from the misguided saltine cracker
challenge to running circles around the lab holding the perforated ribbons of the dot
matrix paper we use for our HPLC printer—and being a fantastic role model. Thank you
all, most excellent Fellowship, for helping me on my quest.
There isn’t a convenient Tolkien metaphor for who I’d like to thank next, but I do want to
express my thanks to the entire Pharmacology and Toxicology Department. To Beverly,
Wendy, Erica, Michelle, Rosie, Diane, Stephen, Brian, Brad, Rick, and everyone else
who has helped me get things done (say, if Frodo needed to register for classes and he
consistently forgot to do it every single semester…): thank you so much for making the
Pharm/Tox department a functional and fun place for me to spend all of my time. To all
of the Pharm/Tox graduate students I’ve gotten to know over the years: ya’ll are
fantastic, and keep being fantastic forever! So many of you became close friends, and
our camaraderie truly lifted my spirits as I trudged toward my goal. Each of you inspired
me with your fervor for your own quests.
Although family wasn’t as big of a deal in Frodo’s life (he was close to Bilbo, but his
parents died when he was small), I wouldn’t have gotten anywhere without mine. My
mother, Billie Winner-Davis, has been my biggest enthusiast my whole life; she
embarrassingly calls me her Firework (after that Katy Perry song) and is convinced that
I can do anything astronomically difficult, like finish a PhD/throw a magical ring into a
fiery mountain. Her encouragement kept me going when I was ready to quit, seriously.
My father, the late Ronald Winner, also inspired me to be anything I wanted to be. He
told me once, when I had come home in elementary school with a failing grade on a
math test that everyone else in my class had failed, “don’t judge your performance by
vi

how everyone else is doing—only focus on yourself and what you can do.” These words
served me well through this journey and my life. My stepfather, Gary Davis, is a cool
character like Aragorn and selflessly made sure that I had everything I needed to be a
functional person, which often included many, many keychain flashlights that came in
handy during those hours I spent using various fluorescent microscopes in the dark.
And then there’s my sister, Reality Winner, who is indescribable, but has always
supported my endeavors. She tells everyone that her “sister is going to cure
Parkinson’s,” which I wish were true, but it’s touching she believes in me that much.
Thank you to all my family. I love you more than words. This Dissertation is dedicated to
you.
Finally, Frodo would never have made it through the final stretches of the journey to
Mordor, arguably the most difficult part of the journey, without his best pal Sam. The
Sam in my life—my best friend—is also my husband, Christopher John. You know that
part in the third movie where Sam carries Frodo up to Mount Doom (if you haven’t seen
it yet, you really should!)? Chris has done that and more for me in my time in graduate
school, which is amazing considering that his also has his own mountain to scale and
quest to yet complete. I am so fortunate to have such a wonderful husband in Chris, and
I know for sure I would never have been able to do any of this without him. I love you,
C-Ro! <3

vii

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................... xi
LIST OF FIGURES............................................................................................. xii
KEY TO ABBREVIATIONS ............................................................................ xviii
Chapter 1: General Introduction ....................................................................... 1
History and motor symptoms of PD ................................................................... 1
Non-motor dysfunction in PD and Braak staging ............................................... 2
Current therapies for PD ................................................................................... 3
Mutations that cause PD ................................................................................... 5
Genetic risk factors for PD ................................................................................ 6
Environmental risk factors for PD ...................................................................... 7
Selective vulnerability of central DA neurons to PD .......................................... 7
Vulnerability of DA neuronal populations to models of neurodegeneration ..... 11
Protein degradation pathways in PD ............................................................... 12
Deubiquitinating enzymes in the UPS and UCH-L1 ........................................ 14
UCH-L1 in PD ................................................................................................. 16
Gracile axonal dystrophy (gad) phenotype ...................................................... 20
nm3419 mouse phenotype .............................................................................. 21
Regulation of UCH-L1 expression in neurons ................................................. 22
UCH-L1 in AD ................................................................................................. 22
Goals of this Dissertation ................................................................................ 23
Specific aims ................................................................................................... 26
REFERENCES ................................................................................................ 26
Chapter 2: Materials and Methods .................................................................. 37
Animals, drugs, and brain tissue collection ..................................................... 37
Preparation of crude synaptosomes ................................................................ 39
Bicinchoninic acid assay for protein concentrations ........................................ 39
Neurochemical analyses via HPLC-ED ........................................................... 40
Immunoblot analyses ...................................................................................... 40
Immunohistochemistry .................................................................................... 43
Confocal analysis of colocalization .................................................................. 43
DCF-DA assay ................................................................................................ 44
MN9D cell culture and drug treatment ............................................................. 44
Cytotoxicity assay............................................................................................ 45
UCH-L1 hydrolase activity ............................................................................... 45
Cayman total glutathione measurements ........................................................ 46
Abcam GSH/GSSG ratio measurements ........................................................ 46
HA-Ub-VME DUB labeling assay .................................................................... 46

viii

Statistical analyses .......................................................................................... 47
REFERENCES ................................................................................................ 48
Chapter 3: Oxidative Stress, Dopaminergic Phenotypic Markers, and UCH-L1
Expression in NSDA and MLDA Neurons after Exposure to Acute MPTP .. 51
Introduction .................................................................................................. 51
Results ......................................................................................................... 52
Oxidative stress in brain regions containing NSDA vs. MLDA neurons ........ 52
Differential susceptibility of NSDA and MLDA neurons to MPTP:
DA, DOPAC, and TH .................................................................................... 57
UCH-L1 and mono-Ub in MLDA neurons after MPTP exposure .................. 64
Total glutathione concentrations in brain regions containing NSDA and MLDA
neurons ........................................................................................................ 66
Expression of UCH-L1 in NSDA and MLDA neurons ................................... 69
Discussion .................................................................................................... 82
Summary and conclusions ........................................................................... 84
REFERENCES ............................................................................................. 85
Chapter 4: Effects of Neurotoxicant and UCH-L1 Inhibitor in MN9D Cells and ST
Synaptosomes, and a Potential Interaction between UCH-L1 and Parkin with
Relevance to Autophagy ................................................................................. 88
Introduction .................................................................................................. 88
Results ......................................................................................................... 92
MN9D expression of DA phenotypic markers and UCH-L1 .......................... 92
Effects of MPTP on UCH-L3 and USP14 in NSDA neurons in vivo ........... 104
Effects of MPTP on UCH-L1 expression in NSDA axon terminals ............. 108
Relationship between UCH-L1 and parkin ................................................. 116
Discussion .................................................................................................. 126
Summary and conclusions ......................................................................... 129
REFERENCES ........................................................................................... 130
Chapter 5: Effects of Inhibition of UCH-L1 on Susceptibility of NSDA and MLDA
Neurons to Neurotoxicant Exposure ............................................................ 134
Introduction ................................................................................................ 134
Results ....................................................................................................... 136
Characterization of effects of LDN-57444 under basal conditions .............. 136
Effects of LDN-57444 on susceptibility of NSDA and MLDA neurons to
MPTP ......................................................................................................... 148
Discussion .................................................................................................. 168
Summary and conclusions ......................................................................... 172
REFERENCES ........................................................................................... 174
Chapter 6: Effects of Aging on DA Metabolic Homeostasis in NSDA and MLDA
Neurons and Susceptibility to MPTP Toxicity ............................................. 177
Introduction ................................................................................................ 177
Results ....................................................................................................... 179

ix

Aged mice have less stored DA in the NAc, but astroglial metabolism of
DA remains intact ....................................................................................... 179
Acute MPTP exposure decreases DA, DOPAC, and astroglial DA
metabolites in ST and NAc of both young and aged mice .......................... 185
Total and phosphorylated TH are decreased in the ST but not the NAc
after MPTP in young and aged mice .......................................................... 188
DAT is decreased in the ST, but not the NAc, after MPTP while VMAT2
is unchanged in both young and aged mice treated with MPTP ................. 188
Discussion .................................................................................................. 191
Summary and conclusions ......................................................................... 196
REFERENCES ........................................................................................... 198
Chapter 7: Effects of Aging on UCH-L1 Expression and Function in Brain Regions
Containing NSDA and MLDA Neurons ......................................................... 203
Introduction ................................................................................................ 203
Results ....................................................................................................... 205
UPS and UCH-L1 function and expression in NSDA and MLDA neurons
in aged mice exposed to MPTP ................................................................. 205
UPS function and UCH-L1 expression in ST synaptosomes from young
and aged mice following acute MPTP exposure ........................................ 205
UPS impairment, UCH-L1 expression and function in SN and VTA
in aged mice ............................................................................................... 210
Effects of MPTP on UCH-L1 expression in the SN and VTA of young
and aged mice ............................................................................................ 210
Discussion .................................................................................................. 216
Summary and conclusions ......................................................................... 218
REFERENCES ........................................................................................... 220
Chapter 8: General Discussion ..................................................................... 223
Differential regulation of UCH-L1 in regions containing NSDA and MLDA
neurons ..................................................................................................... 223
Possible contribution of UCH-L1 function in autophagy ............................ 228
Use of the UCH-L1 inhibitor LDN-57444 in vivo ........................................ 230
Effects of aging on susceptibility of NSDA and MLDA neurons ................. 232
Effects of aging on UPS and UCH-L1 function .......................................... 234
Future directions........................................................................................ 237
Conclusions ............................................................................................... 237
REFERENCES .......................................................................................... 239

x

LIST OF TABLES

Table 2.1.

Primary and secondary antibodies used for Western blotting.42

Table 5.1.

Mono-Ub and total Ub proteins in the ST ............................ 144

Table 5.2.

Mono-Ub and total Ub proteins in the NAc .......................... 145

Table 5.3.

Mono-Ub and total Ub proteins in the SN ............................ 146

Table 5.4.

Mono-Ub and total Ub proteins in the VTA .......................... 147

Table 5.5.

Injection paradigm for LDN + MPTP study .......................... 150

Table 5.6.

UCH-L1 protein expression in the ST .................................. 154

Table 5.7.

UCH-L1 protein expression in the NAc ................................ 155

Table 5.8.

UCH-L1 protein expression in the SN.................................. 156

Table 5.9.

UCH-L1 protein expression in the VTA................................ 157

Table 5.10.

Mono-Ub and total Ub protein in the ST .............................. 158

Table 5.11.

Mono-Ub and total Ub protein in the NAc ............................ 159

Table 5.12.

Mono-Ub and total Ub protein in the SN .............................. 160

Table 5.13.

Mono-Ub and total Ub protein in the VTA ............................ 161

xi

LIST OF FIGURES

Figure 1.1.

DA Metabolism and Common Pharmacological Therapeutics
for PD .................................................................................... 4

Figure 1.2.

Mouse brain diagrams highlighting NSDA (top, red) and
MLDA (bottom, blue) neuronal pathways .............................. 8

Figure 1.3.

Importance of protein clearance mechanisms in PD ........... 13

Figure 1.4.

Mechanisms of mono-Ub recycling by UCH-L1 ................... 15

Figure 2.1.

Images from the online Allen Brain Atlas
(mouse.brain-map.org) ........................................................ 38

Figure 3.1.

Ex vivo ROS production in ST (white) and NAc (teal)
lysates. ................................................................................ 53

Figure 3.2.

In vivo ROS levels in the ST (white) and NAc (teal)
6 after MPTP exposure. ....................................................... 54

Figure 3.3.

DA in the ST 6 h post MPTP exposure................................ 56

Figure 3.4.

DA in the ST (white) and NAc (teal) 24 h after
MPTP exposure ................................................................... 58

Figure 3.5

DOPAC in the ST (white) and NAc (teal) 24 h after
MPTP exposure .................................................................... 60

Figure 3.6.

DOPAC/DA ratio in the ST (white) and NAc (teal) 24 h
after MPTP exposure............................................................ 61

Figure 3.7.

Total TH protein expression in the ST (white) and NAc
(teal) 6 h after MPTP exposure. ............................................ 62

Figure 3.8.

Total TH protein expression in the ST (white) and NAc
(teal) 24 h after MPTP exposure………………………………..63

Figure 3.9.

UCH-L1 protein expression in the ST (white) and NAc
(teal) 6 h after MPTP exposure ............................................. 65

Figure 3.10.

UCH-L1 protein expression in the ST (white) and NAc
(teal) 24 h after MPTP exposure ........................................... 68

xii

Figure 3.11.

UCH-L1 protein expression in the SN after MPTP
exposure ............................................................................... 70

Figure 3.12.

UCH-L1 protein expression in the VTA after MPTP
exposure ............................................................................... 71

Figure 3.13.

Mono-Ub protein expression in the ST (white) and NAc
(teal) 24 h after MPTP exposure ........................................... 72

Figure 3.14.

Mono-Ub protein expression in the SN 24 h after MPTP
exposure ............................................................................... 73

Figure 3.15.

Mono-Ub protein expression in the VTA 24 h after MPTP
exposure ............................................................................... 74

Figure 3.16.

Total GSH concentrations in the ST (white) and NAc (teal) .. 75

Figure 3.17.

Total GSH concentrations in the SN (white) and VTA (teal) .. 76

Figure 3.18.

Immunohistochemical staining for UCH-L1 and TH in the
SN (white dashed oval) and VTA (white dotted circle) .......... 77

Figure 3.19.

Percent of TH and UCH-L1 positive neurons in the SN
24 h after MPTP .................................................................. 78

Figure 3.20.

Percent of TH and UCH-L1 positive neurons in the VTA
24 h after MPTP .................................................................. 79

Figure 3.21.

Pearson’s correlation coefficient values for co-localization
of UCH-L1 and TH signal in the SN (white) and VTA (teal) ... 80

Figure 3.22.

Mander’s overlap correlation values for co-localization
of UCH-L1 and TH signal in the SN (white) and VTA (teal) .. 81

Figure 4.1.

Images of differentiated MN9D cells: phase contrast (top left),
TH (top right), DAT (bottom left) and UCH-L1 (bottom right) 94

Figure 4.2.

DA content in MN9D cells exposed to various concentrations
of MPP+ at 2 and 8 h………………………………………..…..95

Figure 4.3.

DA and DOPAC concentrations in MN9D cells exposed
to 100 µM MPP+ for 2 h ........................................................ 96

Figure 4.4.

UCH-L1 expression in MN9D cells exposed to various
concentrations of MPP+ at 2 h (left) and 8 h (right) ............... 97

xiii

Figure 4.5.

UCH-L1 hydrolase activity in MN9D cells 2 h after
100 µM MPP+ exposure........................................................ 98

Figure 4.6.

DA (left) and DOPAC (right) in MN9D cells treated with
MPP+, LDN-57444, or a combination for 2 h ........................ 99

Figure 4.7.

DOPAC/DA ratio in MN9D cells treated with MPP+,
LDN-57444, or a combination for 2 h.................................. 101

Figure 4.8.

DA concentration in MN9D cells exposed to various
inhibitors for 2 h .................................................................. 102

Figure 4.9.

TH protein in MN9D cells exposed to various
inhibitors for 2 h ................................................................... 103

Figure 4.10.

Cytotoxicity profile of MN9D cells exposed to various
inhibitors for 2 h ................................................................... 106

Figure 4.11.

LC3B-II protein in MN9D cells exposed to various
inhibitors for 2 h ................................................................... 107

Figure 4.12.

Diagram showing three relevant DUBs in the context
of mono-Ub recycling: UCH-L1, UCH-L3, and USP14 …….109

Figure 4.13.

UCH-L3 staining in TH neurons in the SN of mice .............. 110

Figure 4.14.

USP14 staining in TH neurons in the SN of mice ................ 111

Figure 4.15.

UCH-L3 levels in the mouse SN 24 h after
MPTP exposure ................................................................... 112

Figure 4.16.

USP14 levels in the mouse SN 24 h after
MPTP exposure ................................................................... 113

Figure 4.17.

UCH-L1 (left) and mono-Ub (right) protein levels in ST
synaptosomes various time points after acute MPTP
exposure .............................................................................. 114

Figure 4.18.

Pearson correlation analysis of UCH-L1 and mono-Ub
levels after acute MPTP exposure ....................................... 115

Figure 4.19.

UCH-L1 protein expression in the SN of WT (black) and
Park2-/- (red) mice various points after single injection
of MPTP ............................................................................... 117

xiv

Figure 4.20.

UCH-L1 protein expression in the SN of WT (white)
and Park2-/- (red) mice .........................................................118

Figure 4.21.

Mono-Ub protein expression in the SN of WT (white)
and Park2-/- (red) mice ........................................................ 119

Figure 4.22.

K48-linked ubiquitinated proteins in the SN of WT (white)
and Park2-/- (red) mice exposed to MPTP ............................ 120

Figure 4.23.

LC3B-II protein levels in ST synaptosomes between WT
(black) and Park2-/- (red) mice at various time points after
MPTP injection .................................................................... 122

Figure 4.24.

p62 protein levels in the SN between WT (black) and
Park2-/- (red) mice 24 h after MPTP injection....................... 123

Figure 4.25.

p62 protein levels in ST synaptosomes between WT (black)
and Park2-/- (red) mice at various time points after
MPTP injection ………………………………………………...124

Figure 4.26.

hsc70 protein levels in the SN between WT (black) and
Park2-/- (red) mice 24 h after MPTP injection ...................... 125

Figure 5.1.

The UCH-L1 inhibitor LDN-57444 is predicted to
cross the blood brain barrier (BBB) .................................... 138

Figure 5.2.

Injection paradigm for LDN dose response study ............... 139

Figure 5.3.

DA (left) and DOPAC (right) concentrations in the ST
following saline VH, DMSO VH, 0.5 mg/kg LDN,
or 5 mg/kg LDN .................................................................. 140

Figure 5.4.

DOPAC/DA ratio in the ST after saline VH, DMSO VH,
and 0.5 and 5 mg/kg LDN ................................................... 141

Figure 5.5.

DA (left) and DOPAC (right) concentrations in the NAc
following saline VH, DMSO VH, 0.5 mg/kg LDN,
or 5 mg/kg LDN ................................................................. 142

Figure 5.6.

DOPAC/DA ratio in the NAc after saline VH, DMSO VH,
and 0.5 and 5 mg/kg LDN………..…………………………....143

Figure 5.7.

Proposed mechanism of action of the UCH-L1 inhibitor
LDN in the context of UCH-L1 activity and the UPS ............ 149

xv

Figure 5.8.

DA concentrations in the ST of mice and various drug
treatments ………………………………………………………152

Figure 5.9.

DA concentrations in the NAc of mice and various drug
treatments ........................................................................... 153

Figure 5.10.

Gel image representing Ub-VME DUB labeling assay
for the ST and NAc ............................................................. 162

Figure 5.11.

Gel image representing Ub-VME DUB labeling assay
for the SN and VTA ............................................................ 163

Figure 5.12.

Reduced GSH concentration in the ST .............................. 164

Figure 5.13.

Reduced GSH concentration in the NAc ............................ 165

Figure 5.14.

Reduced GSH concentration in the SN .............................. 166

Figure 5.15.

Reduced GSH concentration in the VTA ............................ 167

Figure 6.1.

DA and DOPAC concentrations and DOPAC/DA
ratio in ST (A, C, E) and NAc (B, D, F) in Young,
Mature, Old, and Aged mice ............................................... 180

Figure 6.2.

HVA and 3-MT concentrations after MPTP in Young
and Aged ST (A, C) and NAc (B, D) ................................... 183

Figure 6.3.

DA and DOPAC concentrations after MPTP in Young
and Aged ST (A, C) and NAc (B, D) ................................... 184

Figure 6.4.

Ser40 p-TH and total TH protein levels in ST (A, C) and
NAc (B, D) ........................................................................... 186

Figure 6.5.

DAT and VMAT2 protein levels in ST (A, C) and
NAc (B, D) .......................................................................... 187

Figure 6.6.

COMT protein levels in ST (A, C) and NAc
(B, D)……………………………………………………………..189

Figure 6.7.

Overview of neuronal synthesis of DA and astrocyte
metabolism .......................................................................... 190

Figure 7.1.

Total Ub protein in the ST ................................................... 206

Figure 7.2.

Total Ub protein in the NAc ................................................. 207

xvi

Figure 7.3.

Total Ub proteins in ST synaptosomes............................... 208

Figure 7.4.

UCH-L1 protein in ST synaptosomes .................................. 209

Figure 7.5.

Total Ub protein in the SN and VTA in Young
and Aged mice ................................................................... 211

Figure 7.6.

UCH-L1 protein in the SN and VTA in Young
and Aged mice…………………………………....…………….212

Figure 7.7.

Mono-Ub protein in the SN and VTA in Young
and Aged mice .................................................................... 213

Figure 7.8.

UCH-L1 protein in the SN Young and Aged mice
treated with VH or MPTP ..................................................... 214

Figure 7.9.

UCH-L1 protein in the VTA Young and Aged mice
treated with VH or MPTP ..................................................... 215

Figure 8.1.

Summary of major findings in this Dissertation .................... 236

xvii

KEY TO ABBREVIATIONS

α-syn

Alpha synuclein

AAV

Adeno-associated virus

ALP

Autophagy lysosome pathway

AD

Alzheimer’s disease

ANOVA

Analysis of variance

ARC

Arcuate nucleus

ATP13A2

ATPase type 13A2

BCA

Bicinchoninic acid

CMA

Chaperone mediated autophagy

CNS

Central nervous system

COMT

Catechol-O-methyl transferase

DA

Dopamine

DAergic

Dopaminergic

DAT

Dopamine transporter

DCF-DA

2’-7’-Dichlorofluorescin diacetate

DDC

DOPA decarboxylase

DJ-1

Protein deglycase DJ-1

DMSO

Dimethylsulfoxide

DOPA

Dihydroxyphenylalanine

DOPAC

3,4-dihydroxyphenylacetic acid

FBX07

F-box protein 7
xviii

GAPDH

Glyceraldehyde phosphate dehydrogenase

gad

Gracile axonal dystrophy

GLP-1

Glucagon-like peptide 1

GSH

Reduced glutathione

GSSG

Oxidized glutathione

Hsc70

Heat shock protein 70

HTRA2

High temperature requirement protein A2

HVA

Homovanillic acid

HPLC-ED

High pressure liquid chromatography-electrochemical detection

IHC

Immunohistochemistry

K

Lysine

Lamp-2A

Lysosomal associated membrane protein 2A

LC3

Microtubule associated protein 1A/1B-light chain 3

LDN-57444

5-Chloro-1-[(2,5-dichlorophenyl)methyl]-1H-indole-2,3-dione 3(O-acetyloxime)

Levodopa

Levo-dihydroxyphenylalanine

LRRK2

Leucine-rich repeat kinase 2

MAO-B

Monoamine oxidase B

MAPT

Microtubule associated protein tau

ME

Median eminence

MLDA

Mesolimbic dopamine

MN9D

Mouse neuroblastoma cells clone 9D

MPP+

1-methyl-4-phenylpyridinium

xix

MPTP

1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine

MSN

Medium spiny neuron

3-MT

3-methoxytyramine

NAc

Nucleus accumbens

NSDA

Nigrostriatal dopamine

Park2

Parkin

Park2-/-

Parkin deficient

PD

Parkinson disease

p62

Sequestome-1

PINK1

PTEN-induced putative kinase 1

PLA2G6

Phospholipase A2 Group 6

ROS

Reactive oxygen species

SN

Substantia nigra

SNCA

Human alpha synuclein gene

ST

Striatum

STN

Subthalamic nucleus

TH

Tyrosine hydroxylase

TIDA

Tuberoinfundibular dopamine

UCH-L1

Ubiquitin carboxy-terminal hydrolase L1

UCH-L3

Ubiquitin carboxy-terminal hydrolase L3

Ub

Ubiquitin

UPS

Ubiquitin proteasome system

USP14

Ubiquitin specific protease 14
xx

VMAT2

Vesicular monoamine transporter 2

VPS35

Vacuolar protein sorting 35

VTA

Ventral tegmental area

xxi

Chapter 1: General Introduction
History and motor symptoms of PD
Two hundred years before the completion of this Dissertation, the physician Dr. James
Parkinson wrote the first comprehensive description of Parkinson disease (PD): his
Essay on the Shaking Palsy. Dr. Parkinson observed his own patients and citizens of
London exhibiting a host of distinctive motor disturbances (Parkinson, 1817) that
physicians now use to diagnose PD. Dr. Parkinson termed the disease “paralysis
agitans.” Later, Dr. Jean-Martin Charcot renamed the disorder “Parkinson’s disease” in
honor of Dr. Parkinson and to recognize that Dr. Parkinson was the first to medically
describe the disorder’s symptoms in detail. The progression of PD is characterized by
motor dysfunction such as bradykinesia (slowness of movement), postural instability,
resting tremor and shuffling gait, and is most commonly diagnosed in elderly patients (>
65 years old) (Gelb et al., 1999). Neurodegenerative diseases are expected to increase
dramatically in the United States and worldwide as the population ages (Brown et al.,
2005), and aging is the greatest risk factor for developing PD (Calne and William
Langston, 1983). Accumulation of oxidative stress with aging is expected to play a large
role in development and progression of the disease (Liu and Mori, 1999).
The motor symptoms associated with PD are caused by the specific degeneration of
nigrostriatal (NS) dopamine (DA) neurons in the substantia nigra (SN) (Hornykiewicz,
1966), which regulate motor coordination in the basal ganglia pathway by releasing DA
in the striatum (ST) to synapse on D1 and D2 DA receptors on medium spiny neurons
(MSNs). DA functions in both the direct (mediated by D1 receptor activation) and
indirect (mediated by D2 receptor activation) pathways and allows the motor cortex to
1

execute appropriate motor programs. However, when DA neurons in the SN
degenerate, DA signaling in the ST is lost, and tonic activity of the globus pallidus
internus prevents initiation of voluntary motor function, leading to the hallmark motor
dysfunctions characteristic of PD.
Non-motor dysfunction in PD and Braak staging
In addition to motor dysfunction in PD, there are non-motor symptoms that often
precede motor symptoms. These early non-motor disturbances include constipation,
hyposmia (loss of smell), and sleep disturbances (Chaudhuri et al., 2006). There are DA
neurons in the enteric nervous system (ENS), and as these neurons degenerate,
complications in gastrointestinal motility become apparent (Singaram et al., 1995). One
hypothesis is that PD originates in the ENS (Braak et al., 2006), since constipation is an
early common non-motor manifestation of PD and deposition of alpha synuclein (α-syn)
known as Lewy bodies has been observed in the ENS of PD patients (Wakabayashi et
al., 1988). The vagus nerve is hypothesized to be the avenue through which
pathological α-syn gains access to the central nervous system (CNS) (Ulusoy et al.,
2013). In fact, due to the spread and propagation of α-syn aggregates throughout the
brain, PD has been proposed to be a prion-like disorder (Brundin et al., 2010).
In Braak staging (Braak et al., 2003), pathology is first manifested in the lower
brainstem, chiefly in the medulla oblongata and dorsal motor nucleus of the vagus nerve
degeneration (Stage I), which strengthens the evidence for pathology arising first in the
ENS and traveling through the vagus nerve to the CNS. In Stage II, the raphe nucleus
(the major site of serotonin neuronal cell bodies in the CNS) and locus coeruleus (the

2

major site of norepinephrine neuronal cell bodies in the CNS) are affected.
Degeneration of the raphe nucleus and locus coeruleus contribute to development of
depression and autonomic defects in PD patients (Alexander, 2004). The midbrain is
affected in Stage III, particularly the SN, leading to the canonical motor symptoms and
diagnostic criteria for PD. In Stages IV, V, and VI, pathology spreads to various areas of
the cortex, resulting in cognitive impairment and dementia (Dubois and Pillon, 1996).
These non-motor symptoms are considered to be just as devastating if not more to
patients with PD (Chaudhuri et al., 2006) and present a significant burden on general
well-being and family members of those afflicted.
Current therapies for PD
Current therapeutics for PD address the motor symptoms of the disease but do not halt
or slow the progression of the disease, and are not disease-modifying. Levodopa or LDOPA is the most commonly prescribed drug to treat parkinsonism and is employed as
DA replacement therapy, often in combination with other drugs that prevent peripheral
metabolism of L-DOPA (such as a catechol-O-methyl (COMT) inhibitor, entacapone and
the DA decarboxylase (DDC) inhibitor, carbidopa). DA itself does not cross the bloodbrain barrier, but L-DOPA crosses it easily. In addition, DA replacement with L-DOPA
rather than tyrosine bypasses the rate-limiting enzyme for DA synthesis, tyrosine
hydroxylase (TH) (Fig. 1). Another symptom-modifying approach to treating
parkinsonism is deep brain stimulation (DBS). DBS involves implanting a pacemakerlike device with an electrode in the brain to stimulate various parts of the basal ganglia
pathway, such as the subthalamic nucleus (STN) to compensate for the loss of DA and
allow patients to move freely (Group, 2001). Finally, transplantation of human fetal DA
3

Figure 1.1. DA Metabolism and Common Pharmacological Therapeutics
for PD. DA is synthesized within the axon terminal (green) from tyrosine to LDOPA via TH. After synthesis, DA is packaged into vesicles by vesicular
monoamine transporter 2 (VMAT2) and released into the synapse, where DA
can bind to D1 or D2 receptors in MSNs. DA replacement with L-DOPA (blue)
is often used in conjunction with COMT or DDC inhibitors (entacapone and
carbidopa, respectively, in blue) to prevent peripheral metabolism of L-DOPA.

4

neurons has had some success (Li et al., 2016), but transplanted DA neurons often fall
victim to the same disease mechanisms responsible for the destruction of original
NSDA neurons (Li et al., 2008). In addition, DA grafts do not prevent degeneration of
non-DA neuronal populations affected by the disease and do not alleviate non-motor
symptoms (Politis et al., 2012). Perhaps the fetal graft option is not the most desirable
disease-modifying therapeutic intervention. To date, no disease-modifying treatments
for PD are available, which represents a major unmet need in patients affected
worldwide. A clinical trial involving a promising type 2 diabetes drug, exenatide, has
recently been highlighted as effective for reducing motor symptoms in PD patients
during “off” periods (Athauda et al., 2017). Exenatide is capable of crossing the bloodbrain barrier and acts as a glucagon-like peptide 1 (GLP-1) receptor agonist. Whether
exenatide slows or halts progression of PD is yet to be determined.
Mutations that cause PD
The vast majority of PD cases are idiopathic, meaning that a specific cause cannot be
attributed to development of the disease. However, several monogenic mutations that
cause PD have been identified and given a “PARK” locus designation. Autosomal
dominant point mutations in the gene for leucine-rich repeat kinase 2 (LRRK2, PARK8)
(Zimprich et al., 2004) are the most common cause of familial late-onset PD. Autosomal
dominant mutations in the gene for α-syn (SNCA, PARK1-4) (Polymeropoulos et al.,
1997) also cause PD. The involvement of α-syn is impossible to ignore: triplication of
the α-syn gene has also been shown to cause PD (Singleton et al., 2003). An
autosomal dominant mutation in the gene for ubiquitin carboxy-terminal hydrolase L1
(UCHL1, PARK5) was identified in two members of a German family with PD (Leroy et
5

al., 1998). A rare cause of PD, an autosomal dominant mutation in vacuolar sortingassociated protein 35 (VPS35) has recently been identified (Zimprich et al., 2011).
There are many more recessively inherited mutations that cause PD, however.
Mutations in the E3 ligase parkin (PARK2) are the most common cause for autosomal
recessive juvenile parkinsonism (Kitada et al., 1998). The gene for PTEN-induced
putative kinase 1 (PINK1, PARK6) has also been found to be mutated in PD (Valente et
al., 2004). A mutation in the gene for protein degylcase DJ-1 (DJ-1, PARK7) caused
autosomal recessive PD (Bonifati et al., 2003). A lysosomal type 5 P-type ATPase
(ATP13A2, PARK9) is mutated in PD (Ramirez et al., 2006). A serine protease called
Omi/HTRA2 (PARK13) is also mutated in PD (Strauss, 2005). A phospholipase A2
(PLA2G6, PARK14) mutation causes young onset PD (Lu et al., 2012). F-box protein 7
(FBXO7, PARK15) was found to be mutated in familial PD (Di Fonzo et al., 2009). By
investigating pathways affected by these relatively rare mutations that cause PD, we
can understand which mechanisms are especially vital in protecting DA neurons from
degeneration.
Genetic risk factors for PD
Although monogenic forms of PD are rare, genetic risk factors that contribute to
incidence of idiopathic PD have been identified through genome-wide association
studies. One such genetic risk factor is a mutation in β-glucocerebrosidase A (GBA)
which increases the risk of developing PD (Goker-Alpan et al., 2004). Mutation in GBA
causes Gaucher’s disease in which lysosomal storage is compromised by accumulation
of mutated GBA protein (Hruska et al., 2008). Single nucleotide polymorphisms and

6

variants in SNCA and mutations in the MAPT gene (coding for microtubule associated
protein tau) were detected in a genome-wide association study in patients with PD
(Davis et al., 2016). Interestingly, the genetic testing company 23andMe has recently
been approved by the FDA to test customer’s DNA and disclose two risk factors for
developing PD: the G2019S variant in LRRK2 and the N370S variant in GBA. In
addition, there are genetic factors that are also associated with the age-at-onset of
familial PD (Hill-Burns et al., 2016).
Environmental risk factors for PD
In addition to genetic risk factors for development of PD, environmental risk factors have
also been identified that affect incidence of PD (Klingelhoefer and Reichmann, 2015).
Since the GI tract and olfactory bulb, both sites affected by PD, are avenues through
which exposure to potentially harmful chemicals can take place, environmental
exposure is predicted to play a role in PD. These environmental factors include
exposure to herbicides and pesticides, as well as drinking well water (Gorell et al.,
1998). Most notoriously, lipophilic pesticides such as the organochloride dieldrin
(Fleming et al., 1994) and herbicides rotenone and paraquat (Tanner et al., 2011) are
thought to be especially toxic because they inhibit Complex I of the mitochondria and
cause oxidative stress. Air pollution is also implicated in a host of human diseases, and
increased oxidative stress is caused by certain volatile chemicals (Kampa and
Castanas, 2008). While no conclusive studies have definitively linked development to
PD to air pollution, exposure to toxic chemicals in the air could plausibly contribute to
development of PD. In addition, a role for the gut microbiome has been proposed and

7

Figure 1.2. Mouse brain diagrams highlighting the NSDA (top, red)
and MLDA (bottom, blue) neuronal pathways. Images were modified
from the Allen brain atlas (mouse.brain-map.org). In the NSDA pathway,
DA neurons from the SN in the midbrain project to the ST. In the MLDA
pathway, DA neurons from the VTA in the midbrain project to the NAc.

8

differences in gut bacteria were associated with severity of motor dysfunction in PD
patients (Scheperjans et al., 2015).
Selective vulnerability of central DA neurons to PD
Although NSDA neurons are lost over time as PD progresses, other DA neurons in the
brain are spared: tuberoinfundibular (TI) DA neurons and mesolimbic (ML) DA neurons
resist degeneration (Braak and Braak, 2000). TIDA neurons have cell bodies located in
the arcuate nucleus (ARC) and axon terminals in the median eminence (ME) and are
involved in DA-mediated regulation of prolactin secretion (Lookingland and Moore,
2005). MLDA neurons have cell bodies in the ventral tegmental area (VTA) of the
midbrain and axon terminals in the nucleus accumbens (NAc) ventral to the ST (Fig.
1.2) and function in the reward pathway to stimuli such as food and drugs. MLDA
neurons are also implicated in addiction.
MLDA neurons are often compared to NSDA neurons since they are phenotypically and
anatomically similar, and are regulated by DA receptor-mediated mechanisms
(Demarest and Moore, 1979). There is evidence that a link between the two DA
systems in limbic control of motor activation exists (Mogenson et al., 1980), highlighting
a potential interaction between NSDA and MLDA function. Additionally, neuronal
pathways that are physically or functionally linked are predicted to be affected similarly
by Lewy pathology in PD (Braak et al., 2003). One main physiological difference
between NSDA and MLDA neurons that is predicted to affect susceptibility to
neurodegeneration involves calcium spiking and the fact that NSDA neurons express
more L-type (Cav1) Ca2+ channels than MLDA neurons, which can drastically affect how

9

much Ca2+ enters the cell (Philippart et al., 2016). This difference also highlights the
importance of calbindin, a key Ca2+ binding protein that confers the ability of MLDA
neurons to buffer intracellular Ca2+. Since NSDA neurons do not express high levels of
calbindin (Foehring et al., 2009), unrelenting influx of Ca2+ into the cytoplasm can
initiate the apoptotic cascade (Nagley et al., 2010) and promote production of reactive
oxygen species (ROS). One promising drug trial for the calcium channel blocker
isradipine is underway to determine efficacy in PD patients.
In PD, DA loss is more pronounced in the putamen of PD patients versus other
regions in the ST (Kish et al., 1988). In a study aimed at comparing regional
differences in neurotransmitter uptake systems, [3H] mazindol uptake was found to
be decreased in both the ST and NAc of PD patients, with slightly more loss of [ 3H]
mazindol uptake in the ST (-75%) compared to the NAc (-65%) (Chinaglia et al.,
1992). DA transport insufficiency in the NAc may partially explain why elderly
patients with PD display deficits in reward processing (Schott et al., 2007), but does
not explain why MLDA neurons do not degenerate. Physiologically, both NSDA and
MLDA neurons use DA as the key neurotransmitter, which has been linked to
production of toxic DA adducts (Caudle et al., 2007; Hastings et al., 1996) and ROS.
Previous studies have examined differences between NSDA and MLDA neurons
and how their dissimilarities translate into differential susceptibility between the two
DA neuron populations (Surmeier et al., 2017). How MLDA neurons resist
degeneration is an important question that, if answered, could lead to new
therapeutics to slow or halt the progression of PD.

10

Vulnerability of DA neuronal populations to models of neurodegeneration
The molecule 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) has been used
extensively in PD research to model oxidative stress-mediated specific degeneration of
DA neurons. Discovered as a contaminant in the synthesis of illicit substances, MPTP
caused parkinsonian symptoms in people who consumed the contaminated drugs
(Langston et al., 1983). Dr. J. William Langston, a physician treating the afflicted
patients, identified MPTP as the cause of toxicity (Langston et al., 1984) and developed
the first in vivo MPTP model using squirrel monkeys (Langston et al., 1984). MPTP is
highly lipophilic and easily crosses the blood-brain barrier. Once in the brain, it is
metabolized in glial cells by monoamine oxidase B (MAO-B) to its active metabolite, 1methyl-4-phenylpyridinium (MPP+), which has high affinity for the DA transporter (DAT).
Since MPP+ selectively enters DAT expressing neurons, it is considered a specific DA
neuron toxicant. Specific central DA neuronal degeneration could be replicated in mice
(Sonsalla and Heikkila, 1986), and an MPTP mouse model was born.
MPP+ was discovered to inhibit Complex I of the mitochondria (Mizuno et al., 1986),
preventing ATP production and leading to apoptotic cell death. Mitochondrial
dysfunction is hypothesized to play a major role in development of PD (Schapira et al.,
1990). Additionally, MPP+ causes oxidative stress (Johannessen et al., 1986), which
can damage organelles and cytosolic proteins, leading to widespread dysfunction and
can trigger cell death. Oxidative stress is thought to be a major factor in many
neurodegenerative diseases and is heavily implicated in PD (Blesa et al., 2015). While
neurotoxicant treated mice have limitations in modeling every aspect of PD, the MPTP

11

model of DA depletion and oxidative stress can recapitulate differential susceptibility
between NSDA and MLDA neurons (Behrouz et al., 2007; Hung and Lee, 1998).
The differential susceptibility of MLDA and NSDA neurons observed in toxicant models
has also been demonstrated in transgenic rodent models of PD-like pathology (Maingay
et al., 2006). In addition, studies in nonhuman primates have also recapitulated the
resistance of VTA DA neurons to MPTP (Dopeso-Reyes et al., 2014). MLDA neurons
are not susceptible to damage in rats after rAAV-mediated overexpression of α-syn in
the ventral midbrain (Maingay et al., 2006), which indicates MLDA neurons are
resistant to neurodegeneration elicited by distinct, but likely convergent etiologies of PD.
Since we have a model that recapitulates oxidative stress and selective DA loss, we can
use MPTP to recapitulate the differential susceptibilities of NSDA and MLDA neurons in
mice and examine pathways involved in determining vulnerability or resistance.
Protein degradation pathways in PD
A hallmark pathology of PD is the presence of Lewy bodies in NSDA neurons, which are
proteinaceous deposits of α-syn (Baba et al., 1998; Spillantini et al., 1997), ubiquitin
(Kuzuhara et al., 1988), and components of the ubiquitin proteasome system (UPS),
suggesting that PD pathology is profoundly linked to disruption in protein homeostasis
(Fig. 1.3). Within the family of human genes with the PARK denotation, two code for
proteins involved in the UPS such as UCH-L1 (PARK5) and parkin (PARK2). Although
diverse mechanisms of cellular dysfunction are implicated in development and
progression of PD, deficits in the ability of neurons to maintain protein homeostasis are
especially evident.

12

Figure 1.3. Importance of protein clearance mechanisms in PD. In the left panel,
A, a neuron is shown with functional UPS and autophagy pathways and can degrade
excess α-syn. Also shown is the secretion of α-syn from neurons to other neurons,
astrocytes, or microglia, which also must control the amount of α-syn. In the right
panel, B, a neuron with impaired UPS and autophagy shows abnormal accumulation
of α-syn which can spread to other cell types, causing neuroinflammation and
eventually neurodegeneration. From Lee et al., 2014 (Lee et al., 2014).

13

The UPS is one of the major pathways of protein degradation in the cell that clears
damaged and misfolded proteins in a selective manner. In the UPS, substrates are
tagged with polyubiquitin (poly-Ub) chains by successive actions of E1 activating and
E2 conjugating enzymes passing activated ubiquitin to E3 ubiquitin ligases, which form
K48-linked Ub chains attached to a substrate one monomer at a time. The poly-Ub
substrate can be degraded by the 26S proteasome. The other major protein
degradation pathway is autophagy or the autophagy lysosome pathway (ALP) that is
also implicated in PD. Rather than requiring the use of a poly-Ub tag to target
substrates to the ALP, a form of the ALP called macroautophagy can occur without
substrate specificity, which is in contrast to the UPS. In chaperone mediated autophagy
(CMA), another type of autophagic degradation, proteins must contain a specific amino
acid motif (KFERQ) to be substrates (Bandyopadhyay et al., 2008). The PD-related
protein α-syn is linked to dysfunction of CMA in that it is routinely degraded by CMA, but
can impair CMA-mediated degradation of other substrates in its mutant form (Cuervo et
al., 2004). Emerging evidence suggests that the UPS and ALP could be functionally
linked: if one pathway is impaired, the other may be upregulated in a compensatory
attempt to maintain proteostasis (Ross and Pickart, 2004).
Deubiquitinating enzymes in the UPS and UCH-L1
Fine-tuning the specificity of UPS activity are de-ubiquitinating (DUB) enzymes, which
are diverse in structure and remove either polymeric Ub (poly-Ub) or monomeric Ub
(mono-Ub) as well as perform other functions to modify or mature Ub itself (Todi and
Paulson, 2011). In humans, there are five known families of DUBs which are also
conserved in mice: UCH (ubiquitin carboxy-terminal hydrolases), USP (ubiquitin-specific
14

Figure 1.4. Mechanisms of mono-Ub recycling by UCH-L1. The pool of available
mono-Ub can be activated and passed along by E1 and E2 ligases and attached onto
a protein substrate for degradation by an E3 ligase. The Ub chain is elongated (a
chain of K48-linked Ub destines the protein for destruction) and the protein is
degraded by the 26S proteasome. If the Ub chain is not removed before degradation
of the substrate by a different DUB, UCH-L1 can recover mono-Ub attached to peptide
fragments to replenish the pool of mono-Ub. Additionally, UCH-L1 has high affinity for
mono-Ub and can bind and stabilize mono-Ub to prevent it from degradation.

15

proteases), OTU (ovarian tumor proteases), Josephins, and JAMM/MPN+. UCH, USP,
OTU and Josephin enzymes are cysteine proteases while JAMM/MPN+ DUBs are zinc
metalloproteases (Eletr and Wilkinson, 2014). Of the three known UCH enzymes, UCHL1 is the most studied in the context of neurodegenerative diseases (notably PD and
Alzheimer disease (AD)) because in the brain it is expressed selectively in neurons.
With an extremely knotted structure thought to provide protection against proteasomal
degradation (Virnau et al., 2006), UCH-L1 hydrolyzes the bond between the C-terminus
of small peptide substrates and the Ub monomer (Wilkinson et al., 1989). The main
function of the enzyme is to replenish pools of free mono-Ub to be recycled in the UPS,
which it can accomplish via its hydrolase activity and its ability to bind and sequester
mono-Ub to protect it from degradation (Osaka et al., 2003) (Fig. 1.4). A role for UCHL1 in cancer has been well-reviewed (Hurst-Kennedy et al., 2012) and will not be further
discussed here.
UCH-L1 in PD
UCH-L1, also known as protein gene product (PGP) 9.5, was first described in 1989 as
a neuron specific DUB (Chen et al., 2010) enzyme that comprises 1-2% of total soluble
brain protein (Wilkinson et al., 1989). Due to its abundance in the nervous system,
staining for UCH-L1 is used as a pan-neuronal marker (Thompson et al., 1983). UCHL1 contains a catalytic triad composed of a cysteine at position 90, an aspartate at
position 176, and a histidine at position 161 responsible for the cysteine protease
hydrolytic activity of the enzyme (Das et al., 2006). The first indication that UCH-L1
plays a role in the pathogenesis of PD came almost ten years later in 1998 when an
autosomal dominant mutation was found in two members of a German family diagnosed
16

with PD (Leroy et al., 1998). The affected siblings had an isoleucine to methionine
substitution in position 93 (I93M) in UCH-L1 which later was found to decrease the
hydrolase activity of the enzyme by 50% (Setsuie et al., 2007). Accordingly, loss of
UCH-L1 hydrolase function was predicted to result in the parkinsonian phenotype of the
original patients. The I93M mutation also increased the incidence of aggregation of
UCH-L1 and caused the protein exhibit characteristics of being oxidatively modified
(Kabuta et al., 2008). Although mutations causing PD are rare and represent a minority
of clinical cases, immunohistochemical (IHC) staining for UCH-L1 is observed in Lewy
bodies of idiopathic PD patients (Lowe et al., 1990). This relationship between loss of
UCH-L1 expression and incidence of PD led to the designation of the UCHL1 human
gene as PARK5.
A mutation within the domain that binds ubiquitin in UCH-L1 which resulted in a
substitution from glutamine to alanine in position 7 (GLU7ALA) caused early onset
neurodegeneration in three siblings of a consanguineous union, resulting in optical
nerve atrophy and blindness (Bilguvar et al., 2013). This mutation renders UCH-L1 less
able to bind to ubiquitin and results in a dramatic decrease in hydrolase activity
(reported to be greater than 100-fold reduction) (Bilguvar et al., 2013). Taken together,
mutations in the UCHL1 gene in humans are linked to PD (I93M) and are causative in
an early-onset neurodegenerative disease (GLU7ALA) suggest that UCH-L1 protein
function (UPS related or otherwise) is extremely important in the nervous system. It is
interesting to note, however, that two mutations in the Uchl1 gene cause two very
different neurodegenerative phenotypes in human patients.

17

A common polymorphism found in humans, S18Y (Zhang et al., 2000), is linked to
decreased incidence of PD. Further studies showed that the S18Y mutation confers
antioxidant activity (Xilouri et al., 2012) to the protein, but the association between the
polymorphism and the incidence of PD is controversial (Mellick and Silburn, 2000).
Nevertheless, multiple forms of UCH-L1 have distinct hydrolase activities and diverse
reported functions, especially in transgenic mouse models engineered to explore the
possibilities of isoforms and splice variants. While the possibility of a protective
polymorphism of UCH-L1 being associated with lower risk for PD is intriguing, it has not
been explored much further in published literature.
These findings lead to the hypothesis that loss of UCH-L1 hydrolase activity could
contribute to the pathogenesis and progression of PD. After acute MPTP in mice, UCHL1 was discovered to be decreased in the SN but was maintained in the ARC (Benskey
et al., 2012), which was the first inkling that maintenance of UCH-L1 could confer
protection in resilient DA neurons while loss of UCH-L1 could be a factor that promotes
susceptibility. However, expression of UCH-L1 in MLDA neurons was not yet known. In
transgenic mice expressing the I93M mutation of UCH-L1, neurodegeneration is
prominent in the NSDA system (Setsuie et al., 2007), illustrating the effects of the
mutation on the ability of UCH-L1 to function as a DUB. However, in a neuronal cell line
where UCH-L1 is mutated with a substitution of cysteine to serine in position 90 which
prevents hydrolase activity, mono-Ub levels remain intact, which is evidence that the
ability of UCH-L1 to bind and stabilize mono-Ub may be more important than its
hydrolase activity to maintain mono-Ub within the cell (Osaka et al., 2003).

18

Another important DUB contributor to mono-Ub levels within neurons is USP14, a
ubiquitin specific protease that is associated with the proteasome which is also
responsible for recycling mono-Ub (B J Walters et al., 2008). Although both UCH-L1
and USP14 contribute to recycling of mono-Ub, they do so in different ways and have
been hypothesized to therefore regulate separate pools of mono-Ub (B J Walters et al.,
2008). Nevertheless, there is much literature linking UCH-L1 to the free available pool of
mono-Ub and measuring mono-Ub is considered an important index of UCH-L1
function.
In addition to its ubiquitin hydrolase activity, UCH-L1 possesses ligase activity requiring
dimerization of the protein (Liu et al., 2002). This novel activity of UCH-L1 has been
described as a “toxic gain of function” because UCH-L1 ubiquitinates α-syn via K63linked chains which prevents proteasomal degradation of α-syn (and may target α-syn
for other pathways or protein trafficking). Additional potential substrates of UCH-L1
ligase activity have not yet been identified. Although UCH-L1 ligase activity was
demonstrated in vitro, it remains unconfirmed in vivo.
The E3 ubiquitin ligase parkin was demonstrated to regulate UCH-L1, ubiquitinating it
via K63-linked chains to signal degradation by autophagy (McKeon et al., 2014). In the
study, UCH-L1 levels were elevated in parkin deficient mice (McKeon et al., 2014). The
consequences of parkin regulating UCH-L1 have not been fully explored in vivo, but
perhaps in certain conditions such as during oxidative stress it is beneficial for the E3
ligase function of parkin to predominate over the DUB function of UCH-L1. In this
scenario, UCH-L1 directly opposes parkin by removing mono-Ub from parkin substrates
and therefore preventing subsequent addition of poly-Ub chains. UCH-L1 would rescue
19

both the substrate and mono-Ub, thereby preventing degradation of the substrate and
increasing the mono-Ub pool simultaneously. Although this relationship and its
consequences on UPS activity have yet to be fully explored in vivo, the possible
interplay between two PD-related gene loci could represent an interesting new angle
connecting two important players in the UPS to progression of PD.
Gracile axonal dystrophy (gad) phenotype
A spontaneous (and rather fortuitous) mutation in a mouse colony at the Jackson
Laboratory occurred in a mouse termed gad for gracile axonal dystrophy (Saigoh et al.,
1999). These mice displayed hind limb atrophy preceded by loss of sensory input and a
“dying back” phenotype in the gracile tract occurring late in development until the
animals die after 5-6 months of age. A mutation in the Uchl1 gene where two exons (7
and 8) are deleted was discovered which appeared to primarily affect the gracile
nucleus located in the medulla oblongata (Saigoh et al., 1999). This deletion results in a
truncated non-functional version of UCH-L1, as the mutation affects a central histidine in
the catalytic triad (His161).
One hypothesis for the reason why deletion of UCH-L1 causes degeneration specifically
in the gracile tract leading to degeneration in the gracile nucleus (as opposed to a
parkinsonian phenotype, for example) is that loss of UCH-L1 function preferentially
affects the longest axons in the central nervous system (Oda et al., 1992) due to its
apparent effects on axonal transport (Ichihara et al., 1995) and that the mice do not live
long enough for other neurons to be affected. In the case of PD where NSDA neurons

20

degenerate, it is plausible that these neurons could also suffer from a lack or decrease
in UCH-L1 protein as a product of aging, though this hypothesis has yet to be tested.
Although the molecular cause of neurodegeneration due to loss of functional UCH-L1 in
the gad mice has not been fully explored, mice with the mutation exhibit increased
oxidative stress (Goto et al., 2009). One clue about the function of UCH-L1 revealed by
the gad mice was that mice lacking UCH-L1 displayed reduced amount of mono-Ub in
brain lysates, emphasizing the role of UCH-L1 in maintaining the mono-Ub pool (Osaka
et al., 2003).
nm3419 mouse phenotype
The nm3419 mouse, a relatively new example of a mammal in which the Uchl1 gene is
altered, possesses a mutation that causes loss of 78 amino acids in the C-terminus
resulting in a non-functional version of UCH-L1 protein (Walters et al., 2008). Recently,
the loss of UCH-L1 hydrolase function in the nm3419 mouse has been shown to cause
selective motor neuron degeneration (with no loss in sensory function) (Jara et al.,
2016). Although much of the mouse’s phenotype with regard to UPS function has not
been characterized, it is considered to be a UCH-L1 null model and future studies
should distinguish the consequences of loss of UCH-L1 function by mutation.
Interestingly, the nm3419 mice and gad mice do not have identical phenotypes, which
would be expected if the degenerative phenotype was caused by a simple loss of UCHL1 function. Additional characterization (and perhaps targeting of specific neuronal
populations) of loss of UCH-L1 function is needed to fully understand the degenerative
phenotype differences between nm3419 and gad mice.

21

Regulation of UCH-L1 expression in neurons
Not much has been published about how UCH-L1 gene expression is regulated. At the
time of this publication, there is one report that demonstrated that a long noncoding
RNA antisense to UCH-L1 promotes expression of UCH-L1 (Carrieri et al., 2015). In the
study, an antisense UCH-L1 lncRNA increased UCH-L1 transcription (Carrieri et al.,
2015). Importantly, a novel transcription factor for UCH-L1 was identified: Nurr 1
(Carrieri et al., 2015). Nurr1 is heavily involved in differentiation of dopaminergic
neurons and required for developing the DA neuronal phenotype (Saucedo-Cardenas et
al., 1998). The fact that a DA neuron specific transcription factor binds to the UCH-L1
promoter suggests potentially differential regulation of UCH-L1 depending on neuronal
type, which has previously not been discovered. Future studies into UCH-L1 regulation
should further examine this interesting possibility.
UCH-L1 in AD
The role of UCH-L1 in AD is less well-studied compared to PD. At the time of writing this
dissertation, there was no published evidence that mutations in UCH-L1 can cause or
contribute to development or progression of AD in humans. Since UCH-L1 is highly
expressed in neuron cell bodies but considerably more abundant in axons and
synapses, UCH-L1 is likely highly important in synaptic transmission. Indeed, UCH-L1
had been shown to be necessary to maintain the neuromuscular junction (Chen et al.,
2010) especially synaptic structure (Cartier et al., 2009). One of the first indications that
UCH-L1 could contribute to AD was the finding of downregulation and oxidative
modification of UCH-L1 in brains of patients diagnosed with AD (Choi et al., 2004).

22

Furthermore, the amount of soluble UCH-L1 negatively correlated with the number of
neurofibrillary tangles: a decrease in soluble UCH-L1 was associated with an increased
number of neurofibrillary tangles (Choi et al., 2004). It is unclear whether this
relationship between UCH-L1 and neurofibrillary tangles relates to UCH-L1’s
involvement in proteasomal degradation of tau, but it is a possibility.
A major protective role for UCH-L1 against β-amyloid toxicity was discovered when
UCH-L1 was overexpressed in a mouse model of AD, which restored synaptic function
in brain slices from AD mice and from mice treated with β-amyloid oligomers (Gong et
al., 2006). In addition, UCH-L1 overexpression improved the ability of the AD mice to
retain contextual learning (Gong et al., 2006). In fact, overexpression of UCH-L1 in vivo
rescued AD-like deficits in mice (Zhang et al., 2014). These findings were the first to
describe a role for UCH-L1 in preserving cognition in AD but also suggest a broader role
in synaptic structure and plasticity, which has potentially widespread relevance in the
nervous system. Future studies will shed brighter light on the emerging role of UCH-L1
and other DUBs in pathogenesis and prognosis of AD.
Goals of this Dissertation
As a highly abundant DUB in neurons UCH-L1 clearly has important functions within the
nervous system with respect to proteolytic pathways, synaptic structure, and structure of
the neuromuscular junction. However, the role of UCH-L1 in neuronal susceptibility to
PD is less clear. The following specific aims were proposed to better understand the
role of UCH-L1 as a potential susceptibility factor in NSDA and MLDA neurons in mice
exposed to MPTP.

23

Central Hypothesis: Maintenance of UCH-L1 expression and function is an important
factor that decreases the susceptibility of MLDA neurons and the decrease in UCH-L1
expression contributes to the susceptibility of NSDA neurons to acute MPTP. UCH-L1
expression and activity promotes UPS homeostasis by maintaining pools of free monoUb.
AIM 1: Oxidative Stress, Dopaminergic Phenotypic Markers, and UCH-L1 Expression in
NSDA and MLDA neurons after Exposure to Acute MPTP
Hypothesis: NSDA neurons are more susceptible to acute MPTP treatment than MLDA
neurons and are predicted to have increased markers of oxidative stress. DA and TH
are decreased to a greater extent in the NSDA neurons compared to MLDA neurons in
mice exposed to acute MPTP. UCH-L1 expression is predicted to be maintained in
MLDA neurons but decreased in NSDA neurons after acute MPTP.
AIM 2: Effects of Neurotoxicant and UCH-L1 Inhibitor in MN9D Cells and ST
Synaptosomes, and a Potential Interaction between UCH-L1 and Parkin with Relevance
to Autophagy
Hypothesis: Neurotoxicant treatment in MN9D cells is predicted to cause a decrease in
intracellular DA and UCH-L1 expression and function. The UCH-L1 inhibitor is predicted
to cause a decrease in DA phenotype in MN9D cells. UCH-L1 is predicted to decrease
in ST synaptosomes, as they are the axon terminals of the vulnerable NSDA neurons.
UCH-L1 is predicted to be elevated in parkin deficient mice, since parkin has been
previously demonstrated to downregulate UCH-L1 expression. The upregulation of
UCH-L1 in parkin deficient mice is predicted to increase autophagy.
24

AIM 3: Effects of Inhibition of UCH-L1 on Susceptibility of NSDA and MLDA Neurons to
Neurotoxicant Exposure
Hypothesis: UCH-L1 inhibition in NSDA and MLDA neurons is expected to increase the
sensitivity of these neurons to acute MPTP exposure with respect to a decrease in DA
and TH. With UCH-L1 inhibition, MLDA neurons will be rendered susceptible to acute
MPTP exposure.
AIM 4: Effects of Aging on DA Metabolic Homeostasis in NSDA and MLDA Neurons and
Susceptibility to MPTP Toxicity
Hypothesis: DA phenotype in NSDA and MLDA neurons is predicted to be decreased
with normal aging, and aged mice are predicted to be more susceptible to acute MPTP
in both NSDA and MLDA neurons.
AIM 5: Effects of Aging on UCH-L1 Expression and Function in Brain Regions
Containing NSDA and MLDA Neurons
Hypothesis: UCH-L1 expression is predicted to decrease with normal aging in regions
containing NSDA and MLDA neurons. Aged MLDA neurons are expected to become
susceptible to a decrease in UCH-L1 expression after acute MPTP.

25

REFERENCES

26

REFERENCES

Alexander, G.E., 2004. Biology of Parkinson’s disease: pathogenesis and
pathophysiology of a multisystem neurodegenerative disorder. Dialogues Clin.
Neurosci. 6, 259–80.
Athauda, D., Maclagan, K., Skene, S.S., Bajwa-Joseph, M., Letchford, D., Chowdhury,
K., Hibbert, S., Budnik, N., Zampedri, L., Dickson, J., Li, Y., Aviles-Olmos, I.,
Warner, T.T., Limousin, P., Lees, A.J., Greig, N.H., Tebbs, S., Foltynie, T., 2017.
Exenatide once weekly versus placebo in Parkinson’s disease: a randomised,
double-blind, placebo-controlled trial. Lancet. doi:10.1016/S0140-6736(17)31585-4
Baba, M., Nakajo, S., Tu, P.H., Tomita, T., Nakaya, K., Lee, V.M., Trojanowski, J.Q.,
Iwatsubo, T., 1998. Aggregation of alpha-synuclein in Lewy bodies of sporadic
Parkinson’s disease and dementia with Lewy bodies. Am. J. Pathol. 152, 879–84.
Bandyopadhyay, U., Kaushik, S., Varticovski, L., Cuervo, A.M., 2008. The chaperonemediated autophagy receptor organizes in dynamic protein complexes at the
lysosomal membrane. Mol. Cell. Biol. 28, 5747–63. doi:10.1128/MCB.02070-07
Behrouz, B., Drolet, R.E., Sayed, Z. a., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–598.
doi:10.1016/j.neuroscience.2007.05.007
Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Bilguvar, K., Tyagi, N.K., Ozkara, C., Tuysuz, B., Bakircioglu, M., Choi, M., Delil, S.,
Caglayan, A.O., Baranoski, J.F., Erturk, O., Yalcinkaya, C., Karacorlu, M., Dincer,
A., Johnson, M.H., Mane, S., Chandra, S.S., Louvi, A., Boggon, T.J., Lifton, R.P.,
Horwich, A.L., Gunel, M., 2013. Recessive loss of function of the neuronal ubiquitin
hydrolase UCHL1 leads to early-onset progressive neurodegeneration. Proc. Natl.
Acad. Sci. U. S. A. 110, 3489–94. doi:10.1073/pnas.1222732110
Blesa, J., Trigo-Damas, I., Quiroga-Varela, A., Jackson-Lewis, V.R., 2015. Oxidative
stress and Parkinson’s disease. Front. Neuroanat. 9, 91.
doi:10.3389/fnana.2015.00091
Bonifati, V., Rizzu, P., van Baren, M.J., Schaap, O., Breedveld, G.J., Krieger, E.,
Dekker, M.C.J., Squitieri, F., Ibanez, P., Joosse, M., van Dongen, J.W., Vanacore,
N., van Swieten, J.C., Brice, A., Meco, G., van Duijn, C.M., Oostra, B.A., Heutink,
P., 2003. Mutations in the DJ-1 Gene Associated with Autosomal Recessive Early27

Onset Parkinsonism. Science (80-. ). 299, 256–259. doi:10.1126/science.1077209
Braak, H., Braak, E., 2000. Pathoanatomy of Parkinson’s disease. J. Neurol. 247 Suppl,
II3-10. doi:10.1007/PL00007758
Braak, H., de Vos, R.A.I., Bohl, J., Del Tredici, K., 2006. Gastric α-synuclein
immunoreactive inclusions in Meissner’s and Auerbach’s plexuses in cases staged
for Parkinson’s disease-related brain pathology. Neurosci. Lett. 396, 67–72.
doi:10.1016/j.neulet.2005.11.012
Braak, H., Del Tredici, K., Rüb, U., De Vos, R.A.I., Jansen Steur, E.N.H., Braak, E.,
2003. Staging of brain pathology related to sporadic Parkinson’s disease.
Neurobiol. Aging 24, 197–211. doi:10.1016/S0197-4580(02)00065-9
Brown, R.C., Lockwood, A.H., Sonawane, B.R., 2005. Neurodegenerative Diseases: An
Overview of Environmental Risk Factors. Environ. Health Perspect. 113, 1250–
1256. doi:10.1289/ehp.7567
Brundin, P., Melki, R., Kopito, R., 2010. Prion-like transmission of protein aggregates in
neurodegenerative diseases. Nat. Rev. Mol. Cell Biol. 11, 301–7.
doi:10.1038/nrm2873
Calne, D., William Langston, J., 1983. AETIOLOGY OF PARKINSON’S DISEASE.
Lancet 322, 1457–1459. doi:10.1016/S0140-6736(83)90802-4
Carrieri, C., Forrest, A.R.R., Santoro, C., Persichetti, F., Carninci, P., Zucchelli, S.,
Gustincich, S., 2015. Expression analysis of the long non-coding RNA antisense to
Uchl1 (AS Uchl1) during dopaminergic cells’ differentiation in vitro and in
neurochemical models of Parkinson’s disease. Front. Cell. Neurosci. 9, 114.
doi:10.3389/fncel.2015.00114
Cartier, A.E., Djakovic, S.N., Salehi, A., Wilson, S.M., Masliah, E., Patrick, G.N., 2009.
Regulation of synaptic structure by ubiquitin C-terminal hydrolase L1. J. Neurosci.
29, 7857–68. doi:10.1523/JNEUROSCI.1817-09.2009
Caudle, W.M., Richardson, J.R., Wang, M.Z., Taylor, T.N., Guillot, T.S., McCormack,
A.L., Colebrooke, R.E., Di Monte, D.A., Emson, P.C., Miller, G.W., 2007. Reduced
Vesicular Storage of Dopamine Causes Progressive Nigrostriatal
Neurodegeneration. J. Neurosci. 27, 8138 LP-8148.
Chaudhuri, K.R., Healy, D.G., Schapira, A.H., 2006. Non-motor symptoms of
Parkinson’s disease: diagnosis and management. Lancet Neurol. 5, 235–245.
doi:10.1016/S1474-4422(06)70373-8
Chen, F., Sugiura, Y., Myers, K.G., Liu, Y., Lin, W., 2010. Ubiquitin carboxyl-terminal
hydrolase L1 is required for maintaining the structure and function of the
neuromuscular junction. Proc. Natl. Acad. Sci. 107, 1636–1641.
doi:10.1073/pnas.0911516107
Chinaglia, G., Alvarez, F.J., Probst, A., Palacios~ Ii, J.M., 1992. Mesostriatal and
28

Mesolimbic Dopamine Uptake Binding Sites Are Reduced in Parkinson’S Disease
and Progressive Supranuclear Palsy: a Quantitative Autoradiographic Study Using
[3H]Mazindol. Neuroscience 49, 317–327. doi:10.1016/0306-4522(92)90099-N
Choi, J., Levey, A.I., Weintraub, S.T., Rees, H.D., Gearing, M., Chin, L.-S., Li, L., 2004.
Oxidative modifications and down-regulation of ubiquitin carboxyl-terminal
hydrolase L1 associated with idiopathic Parkinson’s and Alzheimer’s diseases. J.
Biol. Chem. 279, 13256–64. doi:10.1074/jbc.M314124200
Cuervo, A.M., Stefanis, L., Fredenburg, R., Lansbury, P.T., Sulzer, D., 2004. Impaired
degradation of mutant alpha-synuclein by chaperone-mediated autophagy. Science
305, 1292–5. doi:10.1126/science.1101738
Das, C., Hoang, Q.Q., Kreinbring, C. a, Luchansky, S.J., Meray, R.K., Ray, S.S.,
Lansbury, P.T., Ringe, D., Petsko, G. a, 2006. Structural basis for conformational
plasticity of the Parkinson’s disease-associated ubiquitin hydrolase UCH-L1. Proc.
Natl. Acad. Sci. U. S. A. 103, 4675–80. doi:10.1073/pnas.0510403103
Davis, A.A., Andruska, K.M., Benitez, B.A., Racette, B.A., Perlmutter, J.S., Cruchaga,
C., 2016. Variants in GBA , SNCA , and MAPT influence Parkinson disease risk,
age at onset, and progression. Neurobiol. Aging 37, 209.e1-209.e7.
doi:10.1016/j.neurobiolaging.2015.09.014
Demarest, K.T., Moore, K.E., 1979. Comparison of dopamine synthesis regulation in the
terminals of nigrostriatal, mesolimbic, tuberoinfundibular and tuberohypophyseal
neurons. J. Neural Transm. 46, 263–277. doi:10.1007/BF01259333
Di Fonzo, A., Dekker, M.C.J., Montagna, P., Baruzzi, A., Yonova, E.H., Correia Guedes,
L., Szczerbinska, A., Zhao, T., Dubbel-Hulsman, L.O.M., Wouters, C.H., de Graaff,
E., Oyen, W.J.G., Simons, E.J., Breedveld, G.J., Oostra, B.A., Horstink, M.W.,
Bonifati, V., 2009. FBXO7 mutations cause autosomal recessive, early-onset
parkinsonian-pyramidal syndrome. Neurology 72, 240–5.
doi:10.1212/01.wnl.0000338144.10967.2b
Dopeso-Reyes, I.G., Rico, A.J., Roda, E., Sierra, S., Pignataro, D., Lanz, M., Sucunza,
D., Chang-Azancot, L., Lanciego, J.L., 2014. Calbindin content and differential
vulnerability of midbrain efferent dopaminergic neurons in macaques. Front.
Neuroanat. 8, 146. doi:10.3389/fnana.2014.00146
Dubois, B., Pillon, B., 1996. Cognitive deficits in Parkinson’s disease. J. Neurol. 244, 2–
8. doi:10.1007/PL00007725
Eletr, Z.M., Wilkinson, K.D., 2014. Regulation of proteolysis by human deubiquitinating
enzymes. Biochim. Biophys. Acta 1843, 114–28. doi:10.1016/j.bbamcr.2013.06.027
Fleming, L., Mann, J.B., Bean, J., Briggle, T., Sanchez-Ramos, J.R., 1994. Parkinson’s
disease and brain levels of organochlorine pesticides. Ann. Neurol. 36, 100–3.
doi:10.1002/ana.410360119

29

Foehring, R.C., Zhang, X.F., Lee, J.C.F., Callaway, J.C., 2009. Endogenous Calcium
Buffering Capacity of Substantia Nigral Dopamine Neurons. J. Neurophysiol. 102,
2326–2333. doi:10.1152/jn.00038.2009
Gelb, D., Oliver, E., Gilman, S., 1999. Diagnostic criteria for Parkinson disease. Arch.
Neurol. 56, 33–39.
Goker-Alpan, O., Schiffmann, R., LaMarca, M.E., Nussbaum, R.L., McInerney-Leo, A.,
Sidransky, E., 2004. Parkinsonism among Gaucher disease carriers. J. Med.
Genet. 41, 937–940. doi:10.1136/jmg.2004.024455
Gong, B., Cao, Z., Zheng, P., Vitolo, O. V, Liu, S., Staniszewski, A., Moolman, D.,
Zhang, H., Shelanski, M., Arancio, O., 2006. Ubiquitin hydrolase Uch-L1 rescues
beta-amyloid-induced decreases in synaptic function and contextual memory. Cell
126, 775–88. doi:10.1016/j.cell.2006.06.046
Gorell, J.M., Johnson, C.C., Rybicki, B.A., Peterson, E.L., Richardson, R.J., 1998. The
risk of Parkinson’s disease with exposure to pesticides, farming, well water, and
rural living. Neurology 50, 1346–50.
Goto, A., Wang, Y.L., Kabuta, T., Setsuie, R., Osaka, H., Sawa, A., Ishiura, S., Wada,
K., 2009. Proteomic and histochemical analysis of proteins involved in the dyingback-type of axonal degeneration in the gracile axonal dystrophy (gad) mouse.
Neurochem. Int. 54, 330–338. doi:10.1016/j.neuint.2008.12.012
Group, T.D.-B.S. for P.D.S., 2001. Deep-Brain Stimulation of the Subthalamic Nucleus
or the Pars Interna of the Globus Pallidus in Parkinson’s Disease. N. Engl. J. Med.
345, 956–963. doi:10.1056/NEJMoa000827
Hastings, T.G., Lewis, D.A., Zigmond, M.J., 1996. Role of oxidation in the neurotoxic
effects of intrastriatal dopamine injections. Proc. Natl. Acad. Sci. 93, 1956–1961.
Hill-Burns, E.M., Ross, O.A., Wissemann, W.T., Soto-Ortolaza, A.I., Zareparsi, S.,
Siuda, J., Lynch, T., Wszolek, Z.K., Silburn, P.A., Mellick, G.D., Ritz, B., Scherzer,
C.R., Zabetian, C.P., Factor, S.A., Breheny, P.J., Payami, H., 2016. Identification of
genetic modifiers of age-at-onset for familial Parkinson’s disease. Hum. Mol. Genet.
0, ddw206. doi:10.1093/hmg/ddw206
Hornykiewicz, O., 1966. Dopamine (3-hydroxytyramine) and brain function.
Pharmacol.Rev. 18, 925–964.
Hruska, K.S., LaMarca, M.E., Scott, C.R., Sidransky, E., 2008. Gaucher disease:
mutation and polymorphism spectrum in the glucocerebrosidase gene (GBA). Hum.
Mutat. 29, 567–583. doi:10.1002/humu.20676
Hung, H.-C., Lee, E.H.., 1998. MPTP Produces Differential Oxidative Stress and
Antioxidative Responses in the Nigrostriatal and Mesolimbic Dopaminergic
Pathways. Free Radic. Biol. Med. 24, 76–84. doi:10.1016/S0891-5849(97)00206-2
Hurst-Kennedy, J., Chin, L.S., Li, L., 2012. Ubiquitin C-terminal hydrolase L1 in
30

tumorigenesis. Biochem. Res. Int. 2012. doi:10.1155/2012/123706
Ichihara, N., Wu, J., Hua Chui, D., Yamazaki, K., Wakabayashi, T., Kikuchi, T., 1995.
Axonal degeneration promotes abnormal accumulation of amyloid β-protein in
ascending gracile tract of gracile axonal dystrophy (GAD) mouse. Brain Res. 695,
173–178. doi:10.1016/0006-8993(95)00729-A
Jara, J.H., Schultz, M.C., Manuel, M., Stanford, M.J., Gautam, M., Klessner, J.L.,
Sekerkova, G., Heller, D.B., Cox, G.A., 2016. Absence of UCHL 1 function leads to
selective motor neuropathy 331–345. doi:10.1002/acn3.298
Johannessen, J.N., Adams, J.D., Schuller, H.M., Bacon, J.P., Markey, S.P., 1986. 1methyl-4-phenylpyridine (MPP+) induces oxidative stress in the rodent. Life Sci. 38,
743–749. doi:10.1016/0024-3205(86)90589-8
Kabuta, T., Furuta, A., Aoki, S., Furuta, K., Wada, K., 2008. Aberrant interaction
between Parkinson disease-associated mutant UCH-L1 and the lysosomal receptor
for chaperone-mediated autophagy. J. Biol. Chem. 283, 23731–8.
doi:10.1074/jbc.M801918200
Kampa, M., Castanas, E., 2008. Human health effects of air pollution. Environ. Pollut.
151, 362–367. doi:10.1016/j.envpol.2007.06.012
Kish, S.J., Shannak, K., Hornykiewicz, O., 1988. Uneven Pattern of Dopamine Loss in
the Striatum of Patients with Idiopathic Parkinson’s Disease. N. Engl. J. Med. 318,
876–880. doi:10.1056/NEJM198804073181402
Kitada, T., Asakawa, S., Hattori, N., Matsumine, H., Yamamura, Y., Minoshima, S.,
Yokochi, M., Mizuno, Y., Shimizu, N., 1998. Mutations in the parkin gene cause
autosomal recessive juvenile parkinsonism. Nature 392, 605–8. doi:10.1038/33416
Klingelhoefer, L., Reichmann, H., 2015. Pathogenesis of Parkinson disease—the gut–
brain axis and environmental factors. Nat. Rev. Neurol. 11, 625–636.
doi:10.1038/nrneurol.2015.197
Kuzuhara, S., Mori, H., Izumiyama, N., Yoshimura, M., Ihara, Y., 1988. Lewy bodies are
ubiquitinated. Acta Neuropathol. 75, 345–353. doi:10.1007/BF00687787
Langston, J., Ballard, P., Tetrud, J., Irwin, I., 1983. Chronic Parkinsonism in humans
due to a product of meperidine-analog synthesis. Science (80-. ). 219, 979–980.
doi:10.1126/science.6823561
Langston, J.W., Forno, L.S., Rebert, C.S., Irwin, I., 1984. Selective nigral toxicity after
systemic administration of 1-methyl-4-phenyl-1,2,5,6-tetrahydropyrine (MPTP) in
the squirrel monkey. Brain Res. 292, 390–4.
Langston, J.W., Irwin, I., Langston, E.B., Forno, L.S., 1984. 1-Methyl-4-phenylpyridinium
ion (MPP+): Identification of a metabolite of MPTP, a toxin selective to the
substantia nigra. Neurosci. Lett. 48, 87–92. doi:10.1016/0304-3940(84)90293-3
31

Lee, H.-J., Bae, E.-J., Lee, S.-J., 2014. Extracellular α--synuclein-a novel and crucial
factor in Lewy body diseases. Nat. Rev. Neurol. 10, 92–8.
doi:10.1038/nrneurol.2013.275
Leroy, E., Boyer, R., Auburger, G., Leube, B., Ulm, G., Mezey, E., Harta, G.,
Brownstein, M.J., Jonnalagada, S., Chernova, T., Dehejia, A., Lavedan, C., Gasser,
T., Steinbach, P.J., Wilkinson, K.D., Polymeropoulos, M.H., 1998. The ubiquitin
pathway in Parkinson’s disease. Nature. doi:10.1038/26652
Li, J.-Y., Englund, E., Holton, J.L., Soulet, D., Hagell, P., Lees, A.J., Lashley, T., Quinn,
N.P., Rehncrona, S., Björklund, A., Widner, H., Revesz, T., Lindvall, O., Brundin,
P., 2008. Lewy bodies in grafted neurons in subjects with Parkinson’s disease
suggest host-to-graft disease propagation. Nat. Med. 14, 501–3.
doi:10.1038/nm1746
Li, W., Englund, E., Widner, H., Mattsson, B., van Westen, D., Lätt, J., Rehncrona, S.,
Brundin, P., Björklund, A., Lindvall, O., Li, J.-Y., 2016. Extensive graft-derived
dopaminergic innervation is maintained 24 years after transplantation in the
degenerating parkinsonian brain. Proc. Natl. Acad. Sci. 113, 6544–6549.
doi:10.1073/pnas.1605245113
Liu, J., Mori, a, 1999. Stress, aging, and brain oxidative damage. Neurochem. Res. 24,
1479–97.
Liu, Y., Fallon, L., Lashuel, H.A., Liu, Z., Lansbury, P.T., 2002. The UCH-L1 Gene
Encodes Two Opposing Enzymatic Activities that Affect ␣ -Synuclein Degradation
and Parkinson ’ s Disease Susceptibility 111, 209–218.
Lookingland, K.J., Moore, K.E., 2005. Chapter VIII Functional neuroanatomy of
hypothalamic dopaminergic neuroendocrine systems. Handb. Chem. Neuroanat.
21, 435–523. doi:10.1016/S0924-8196(05)80012-0
Lowe, J., McDermott, H., Landon, M., Mayer, R.J., Wilkinson, K.D., 1990. Ubiquitin
carboxyl-terminal hydrolase (PGP 9.5) is selectively present in ubiquitinated
inclusion bodies characteristic of human neurodegenerative diseases. J. Pathol.
161, 153–160. doi:10.1002/path.1711610210
Lu, C.-S., Lai, S.-C., Wu, R.-M., Weng, Y.-H., Huang, C.-L., Chen, R.-S., Chang, H.-C.,
Wu-Chou, Y.-H., Yeh, T.-H., 2012. PLA2G6 mutations in PARK14-linked youngonset parkinsonism and sporadic Parkinson’s disease. Am. J. Med. Genet. Part B
Neuropsychiatr. Genet. 159B, 183–191. doi:10.1002/ajmg.b.32012
Maingay, M., Romero-Ramos, M., Carta, M., Kirik, D., 2006. Ventral tegmental area
dopamine neurons are resistant to human mutant alpha-synuclein overexpression.
Neurobiol. Dis. 23, 522–32. doi:10.1016/j.nbd.2006.04.007
McKeon, J.E., Sha, D., Li, L., Chin, L.-S., 2014. Parkin-mediated K63-polyubiquitination
targets ubiquitin C-terminal hydrolase L1 for degradation by the autophagylysosome system. Cell. Mol. Life Sci. doi:10.1007/s00018-014-1781-2
32

Mellick, G.D., Silburn, P. a., 2000. The ubiquitin carboxy-terminal hydrolase-L1 gene
S18Y polymorphism does not confer protection against idiopathic Parkinson’s
disease. Neurosci. Lett. 293, 127–130. doi:10.1016/S0304-3940(00)01510-X
MIZUNO, Y., SONE, N., SAITOH, T., 1986. Dopaminergic neurotoxins, MPTP and
MPP+, inhibit activity of mitochondrial NADH-ubiquinone oxidoreductase. Proc.
Japan Acad. Ser. B Phys. Biol. Sci. 62, 261–263. doi:10.2183/pjab.62.261
Mogenson, G.J., Jones, D.L., Yim, C.Y., 1980. From motivation to action: Functional
interface between the limbic system and the motor system. Prog. Neurobiol. 14,
69–97. doi:http://dx.doi.org/10.1016/0301-0082(80)90018-0
Nagley, P., Higgins, G.C., Atkin, J.D., Beart, P.M., 2010. Multifaceted deaths
orchestrated by mitochondria in neurones. Biochim. Biophys. Acta - Mol. Basis Dis.
1802, 167–185. doi:http://dx.doi.org/10.1016/j.bbadis.2009.09.004
Oda, K., Yamazaki, K., Miura, H., Shibasaki, H., Kikuchi, T., 1992. Dying back type
axonal degeneration of sensory nerve terminals in muscle spindles of the gracile
axonal dystrophy (GAD) mutant mouse. Neuropathol. Appl. Neurobiol. 18, 265–
281. doi:10.1111/j.1365-2990.1992.tb00789.x
Osaka, H., Wang, Y.L., Takada, K., Takizawa, S., Setsuie, R., Li, H., Sato, Y.,
Nishikawa, K., Sun, Y.J., Sakurai, M., Harada, T., Hara, Y., Kimura, I., Chiba, S.,
Namikawa, K., Kiyama, H., Noda, M., Aoki, S., Wada, K., 2003. Ubiquitin carboxyterminal hydrolase L1 binds to and stabilizes monoubiquitin in neuron. Hum. Mol.
Genet. 12, 1945–1958. doi:10.1093/hmg/ddg211
Parkinson, J., 1817. Essay on the Shaking Palsy. Printed by Whittingham and Rowland
for Sherwood, Neely, and Jones, London.
Philippart, F., Destreel, G., Merino-Sepúlveda, P., Henny, P., Engel, D., Seutin, V.,
2016. Differential Somatic Ca&lt;sup&gt;2+&lt;/sup&gt; Channel Profile in Midbrain
Dopaminergic Neurons. J. Neurosci. 36, 7234 LP-7245.
Politis, M., Wu, K., Loane, C., Quinn, N.P., Brooks, D.J., Oertel, W.H., Bjorklund, A.,
Lindvall, O., Piccini, P., 2012. Serotonin Neuron Loss and Nonmotor Symptoms
Continue in Parkinson’s Patients Treated with Dopamine Grafts. Sci. Transl. Med.
4, 128ra41-128ra41. doi:10.1126/scitranslmed.3003391
Polymeropoulos, M.H., Lavedan, C., Leroy, E., Ide, S.E., Dehejia, A., Dutra, A., Pike, B.,
Root, H., Rubenstein, J., Boyer, R., Stenroos, E.S., Chandrasekharappa, S.,
Athanassiadou, A., Papapetropoulos, T., Johnson, W.G., Lazzarini, A.M., Duvoisin,
R.C., Di Iorio, G., Golbe, L.I., Nussbaum, R.L., 1997. Mutation in the alphasynuclein gene identified in families with Parkinson’s disease. Science 276, 2045–
7.
Ramirez, A., Heimbach, A., Gründemann, J., Stiller, B., Hampshire, D., Cid, L.P.,
Goebel, I., Mubaidin, A.F., Wriekat, A.L., Roeper, J., Al-Din, A., Hillmer, A.M.,
Karsak, M., Liss, B., Woods, C.G., Behrens, M.I., Kubisch, C., 2006. Hereditary
33

parkinsonism with dementia is caused by mutations in ATP13A2, encoding a
lysosomal type 5 P-type ATPase. Nat Genet 38, 1184–1191. doi:10.1038/ng1884
Ross, C. a., Pickart, C.M., 2004. The ubiquitin-proteasome pathway in Parkinson’s
disease and other neurodegenerative diseases. Trends Cell Biol. 14, 703–711.
doi:10.1016/j.tcb.2004.10.006
Saigoh, K., Wang, Y., Suh, J., Yamanishi, T., 1999. Intragenic deletion in the gene
encoding ubiquitin carboxy-terminal hydrolase in gad mice. Nat. … 23, 47–51.
Saucedo-Cardenas, O., Quintana-Hau, J.D., Le, W.-D., Smidt, M.P., Cox, J.J., De
Mayo, F., Burbach, J.P.H., Conneely, O.M., 1998. Nurr1 is essential for the
induction of the dopaminergic phenotype and the survival of ventral mesencephalic
late dopaminergic precursor neurons. Proc. Natl. Acad. Sci. 95, 4013–4018.
Schapira, A.H. V., Cooper, J.M., Dexter, D., Clark, J.B., Jenner, P., Marsden, C.D.,
1990. Mitochondrial Complex I Deficiency in Parkinson’s Disease. J. Neurochem.
54, 823–827. doi:10.1111/j.1471-4159.1990.tb02325.x
Scheperjans, F., Aho, V., Pereira, P.A.B., Koskinen, K., Paulin, L., Pekkonen, E.,
Haapaniemi, E., Kaakkola, S., Eerola-Rautio, J., Pohja, M., Kinnunen, E., Murros,
K., Auvinen, P., 2015. Gut microbiota are related to Parkinson’s disease and
clinical phenotype. Mov. Disord. 30, 350–358. doi:10.1002/mds.26069
Schott, B.H., Niehaus, L., Wittmann, B.C., Schütze, H., Seidenbecher, C.I., Heinze,
H.J., Düzel, E., 2007. Ageing and early-stage Parkinson’s disease affect separable
neural mechanisms of mesolimbic reward processing. Brain 130, 2412–2424.
doi:10.1093/brain/awm147
Setsuie, R., Wang, Y.-L., Mochizuki, H., Osaka, H., Hayakawa, H., Ichihara, N., Li, H.,
Furuta, A., Sano, Y., Sun, Y.-J., Kwon, J., Kabuta, T., Yoshimi, K., Aoki, S., Mizuno,
Y., Noda, M., Wada, K., 2007. Dopaminergic neuronal loss in transgenic mice
expressing the Parkinson’s disease-associated UCH-L1 I93M mutant. Neurochem.
Int. 50, 119–29. doi:10.1016/j.neuint.2006.07.015
Singaram, C., Gaumnitz, E.A., Torbey, C., Ashraf, W., Quigley, E.M.., Sengupta, A.,
Pfeiffer, R., 1995. Dopaminergic defect of enteric nervous system in Parkinson’s
disease patients with chronic constipation. Lancet 346, 861–864.
doi:10.1016/S0140-6736(95)92707-7
Singleton, A.B., Farrer, M., Johnson, J., Singleton, A., Hague, S., Kachergus, J.,
Hulihan, M., Peuralinna, T., Dutra, A., Nussbaum, R., Lincoln, S., Crawley, A.,
Hanson, M., Maraganore, D., Adler, C., Cookson, M.R., Muenter, M., Baptista, M.,
Miller, D., Blancato, J., Hardy, J., Gwinn-Hardy, K., 2003. α-Synuclein Locus
Triplication Causes Parkinson’s Disease. Science (80-. ). 302.
Sonsalla, P.K., Heikkila, R.E., 1986. The influence of dose and dosing interval on
MPTP-induced dopaminergic neurotoxicity in mice. Eur. J. Pharmacol. 129, 339–
45.
34

Spillantini, M.G., Schmidt, M.L., Lee, V.M.-Y., Trojanowski, J.Q., Jakes, R., Goedert, M.,
1997. [alpha]-Synuclein in Lewy bodies 388, 839–840.
Strauss, K.M., 2005. Loss of function mutations in the gene encoding Omi/HtrA2 in
Parkinson’s disease. Hum. Mol. Genet. 14, 2099–2111. doi:10.1093/hmg/ddi215
Surmeier, D.J., Obeso, J.A., Halliday, G.M., 2017. Selective neuronal vulnerability in
Parkinson disease. Nat. Rev. Neurosci. 18, 101–113. doi:10.1038/nrn.2016.178
Tanner, C.M., Kamel, F., Ross, G.W., Hoppin, J.A., Goldman, S.M., Korell, M., Marras,
C., Bhudhikanok, G.S., Kasten, M., Chade, A.R., Comyns, K., Richards, M.B.,
Meng, C., Priestley, B., Fernandez, H.H., Cambi, F., Umbach, D.M., Blair, A.,
Sandler, D.P., Langston, J.W., 2011. Rotenone, Paraquat, and Parkinson’s
Disease. Environ. Health Perspect. 119, 866–872. doi:10.1289/ehp.1002839
Thompson, R.J., Doran, J.F., Jackson, P., Dhillon, a P., Rode, J., 1983. PGP 9.5--a
new marker for vertebrate neurons and neuroendocrine cells. Brain Res. 278, 224–
228. doi:10.1016/0006-8993(83)90241-X
Todi, S. V, Paulson, H.L., 2011. Balancing act: deubiquitinating enzymes in the nervous
system. Trends Neurosci. 34, 370–82. doi:10.1016/j.tins.2011.05.004
Ulusoy, A., Rusconi, R., Pérez-Revuelta, B.I., Musgrove, R.E., Helwig, M., WinzenReichert, B., Monte, D.A. Di, 2013. Caudo-rostral brain spreading of α-synuclein
through vagal connections. EMBO Mol. Med. 5, 1119–1127.
doi:10.1002/emmm.201302475
Valente, E.M., Abou-Sleiman, P.M., Caputo, V., Muqit, M.M.K., Harvey, K., Gispert, S.,
Ali, Z., Del Turco, D., Bentivoglio, A.R., Healy, D.G., Albanese, A., Nussbaum, R.,
González-Maldonado, R., Deller, T., Salvi, S., Cortelli, P., Gilks, W.P., Latchman,
D.S., Harvey, R.J., Dallapiccola, B., Auburger, G., Wood, N.W., 2004. Hereditary
Early-Onset Parkinson’s Disease Caused by Mutations in PINK1. Science (80-. ).
304, 1158–1160. doi:10.1126/science.1096284
Virnau, P., Mirny, L. a., Kardar, M., 2006. Intricate knots in proteins: Function and
evolution. PLoS Comput. Biol. 2, 1074–1079. doi:10.1371/journal.pcbi.0020122
Wakabayashi, K., Takahashi, H., Takeda, S., Ohama, E., Ikuta, F., 1988. Parkinson’s
disease: the presence of Lewy bodies in Auerbach’s and Meissner’s plexuses. Acta
Neuropathol. 76, 217–221.
Walters, B.J., Campbell, S.L., Chen, P.C., Taylor, A.P., Schroeder, D.G., Dobrunz, L.E.,
Artavanis-Tsakonas, K., Ploegh, H.L., Wilson, J.A., Cox, G.A., Wilson, S.M., 2008.
Differential effects of Usp14 and Uch-L1 on the ubiquitin proteasome system and
synaptic activity. Mol. Cell. Neurosci. 39, 539–48. doi:10.1016/j.mcn.2008.07.028
Walters, B.J., Campbell, S.L., Chen, P.C., Taylor, a. P., Schroeder, D.G., Dobrunz,
L.E., Artavanis-Tsakonas, K., Ploegh, H.L., Wilson, J. a., Cox, G. a., Wilson, S.M.,
2008. Differential effects of Usp14 and Uch-L1 on the ubiquitin proteasome system
35

and synaptic activity. Mol. Cell. Neurosci. 39, 539–548.
doi:10.1016/j.mcn.2008.07.028
Wilkinson, K.D., Lee, K.M., Deshpande, S., Duerksen-Hughes, P., Boss, J.M., Pohl, J.,
1989. The neuron-specific protein PGP 9.5 is a ubiquitin carboxyl-terminal
hydrolase. Science 246, 670–673. doi:10.1126/science.2530630
Xilouri, M., Kyratzi, E., Pitychoutis, P.M., Papadopoulou-Daifoti, Z., Perier, C., Vila, M.,
Maniati, M., Ulusoy, A., Kirik, D., Park, D.S., Wada, K., Stefanis, L., 2012. Selective
neuroprotective effects of the S18Y polymorphic variant of UCH-L1 in the
dopaminergic system. Hum. Mol. Genet. 21, 874–89. doi:10.1093/hmg/ddr521
Zhang, J., Hattori, N., Leroy, E., Morris, H.R., Kubo, S.I., Kobayashi, T., Wood, N.W.,
Polymeropoulos, M.H., Mizuno, Y., 2000. Association between a polymorphism of
ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) gene and sporadic Parkinson’s
disease. Park. Relat. Disord. 6, 195–197. doi:10.1016/S1353-8020(00)00015-8
Zhang, M., Cai, F., Zhang, S., Zhang, S., Song, W., 2014. Overexpression of ubiquitin
carboxyl-terminal hydrolase L1 (UCHL1) delays Alzheimer’s progression in vivo.
Sci. Rep. 4, 7298. doi:10.1038/srep07298
Zimprich, A., Benet-Pagès, A., Struhal, W., Graf, E., Eck, S.H., Offman, M.N.,
Haubenberger, D., Spielberger, S., Schulte, E.C., Lichtner, P., Rossle, S.C., Klopp,
N., Wolf, E., Seppi, K., Pirker, W., Presslauer, S., Mollenhauer, B., Katzenschlager,
R., Foki, T., Hotzy, C., Reinthaler, E., Harutyunyan, A., Kralovics, R., Peters, A.,
Zimprich, F., Brücke, T., Poewe, W., Auff, E., Trenkwalder, C., Rost, B., Ransmayr,
G., Winkelmann, J., Meitinger, T., Strom, T.M., 2011. A Mutation in VPS35,
Encoding a Subunit of the Retromer Complex, Causes Late-Onset Parkinson
Disease. Am. J. Hum. Genet. 89, 168–175. doi:10.1016/j.ajhg.2011.06.008
Zimprich, A., Biskup, S., Leitner, P., Lichtner, P., Farrer, M., Lincoln, S., Kachergus, J.,
Hulihan, M., Uitti, R.J., Calne, D.B., Stoessl, A.J., Pfeiffer, R.F., Patenge, N.,
Carbajal, I.C., Vieregge, P., Asmus, F., Müller-Myhsok, B., Dickson, D.W.,
Meitinger, T., Strom, T.M., Wszolek, Z.K., Gasser, T., 2004. Mutations in LRRK2
Cause Autosomal-Dominant Parkinsonism with Pleomorphic Pathology. Neuron 44,
601–607. doi:10.1016/j.neuron.2004.11.005

36

Chapter 2: Materials and Methods
Animals, drugs, and brain tissue collection
Mice were either bred in house (GFP-TH, Park2-/-; Parkin KO) or purchased from
Jackson Labs. All mice were either transgenic on a C57bl6j background or wild type
(WT) C57bl6j. Mice were housed in a temperature (22 ± 1 ºC) and light controlled (12 h
light/dark cycle) room and provided with food and water ad libitum. The Michigan State
University Institutional Animal Care and Use Committee approved all experiments using
live animals (AUF 10/14-183-00). For studies presented in Chapters 6 and 7, young
mice were 3-8 months old, mature mice were 9-12 months old, old mice were 12.5-14
months old, and aged mice were 22-28 months old.
In studies involving acute MPTP, mice were injected with either saline VH or 20 mg/kg
MPTP (Santa Cruz) dissolved in saline (s.c.). For studies involving LDN-57444 (Tocris),
mice were injected with either DMSO VH (Sigma) or LDN-57444 (0.5 mg/kg or 5 mg/kg)
dissolved in DMSO (i.p.). For all other studies, mice were 8-10 weeks old.
Mice were randomly assigned to study groups. Upon completion of all experimental time
points, mice were decapitated via guillotine and the brain rapidly removed and placed
on ice. If no ST synaptosomes were collected, brains were frozen on labeled squares of
aluminum foil rostral end up on dry ice and stored at -80 ºC until further analysis. Brains
were sliced to 500 µm coronal sections using a cryostat at -9 ºC and sections were
placed on a labeled glass slide. Based on brain morphology using the Mouse Brain
Atlas (Paxinos and Franklin, 2004) tissue punches were microdissected for the ST (18
gauge round), NAc (18 gauge round),
37

Figure 2.1. Images from the online Allen Brain Atlas (mouse.brain-map.org). Top
images represent the cell body (SN, left) and axon terminal (ST, right) regions of NSDA
neurons. Lower images represent the cell body (VTA, left) and axon terminal (NAc,
right) regions of MLDA. White space in the tissue (designated by arrows) represents the
microdissected neurons sampled from a mouse coronal brain section.

38

SN (21 gauge round), and VTA (18 gauge round) (Fig. 2.1) and placed in buffer
appropriate for downstream analyses and stored at -80 ºC until further use.
Preparation of crude synaptosomes
Chilled fresh brains were sectioned using a brain matrix (Zivic Instruments) at 1 mm
thick slices onto a cold stainless steel razorblade. Synaptosomes were isolated from the
ST tissue according to a method modified from Dunkley (Dunkley et al., 2008).
Unilateral dorsal ST (approximately 75-100 µg) was collected in 1 mL homogenization
buffer (300 mM Sucrose, 10 mM HEPES, 1 mM EGTA, pH 7.4 at 4 °C) and
homogenized with a pre-chilled Teflon/glass homogenizer by 10 strokes over ice,
resting each sample on ice after 5 strokes. The homogenizer was rinsed with an
additional 1 mL of MIB and homogenates were transferred to 2 mL microcentrifuge
tubes and centrifuged at low speed (1000 x g) for 10 min. After centrifugation, the
supernatant was retained in a separate tube and centrifuged at 17,968 x g at 4 °C for 10
min in fixed-angle rotor. The resulting P2 pellets were re-suspended in 100 μL sucrose
buffer (300 mM sucrose and 10 mM HEPES, pH 7.4 at 4 °C). Synaptosomes were
stored at -80 ºC until further use.
Bicinchoninic acid assay for protein concentrations
The reagents (bicinchoninic acid and copper sulfate) were mixed in a ratio of 50:1 and
used to analyze protein content per sample. Samples were diluted as follows: 48 µL of
ddH2O to 2 µL (1:25 dilution) of sample for Western blotting and 25 μL of ddH2O to 25
μL (1:1 dilution) of sample for neurochemistry analysis. Serial dilutions of bovine serum
albumin (BSA) were used as standards (500 ng/µL, 250 ng/µL, 125 ng/µL… etc.).
39

Samples mixed with BCA reagent were incubated for 15 min at 60 °C and protein
concentrations were determined by a Tecan Infinite M1000 Pro Microplate Reader.
Neurochemical analyses via HPLC-ED
Tissue samples in acidic HPLC tissue buffer (0.1 M phosphate, 0.1 M citrate buffer, pH
2.5) were sonicated for three short bursts and centrifuged at 10,000 x g for 1 min at 4
ºC. Resulting supernatants were prepared by diluting in tissue buffer up to 100 µL.
Mobile phase for detection of neurochemicals was 10% methanol, 0.02% SOS, pH 2.65.
Sample content of DA, 3,4-hydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA)
and 3-methoxytyramine (3-MT) was determined by high pressure liquid chromatography
coupled with electrochemical detection (HPLC-ED) and the concentration of
neurochemicals was expressed in nanogram (ng) per milligram (mg) protein.
Immunoblot analyses
Micropunch or cell culture lysates were processed and Western blots were
performed as previously described (Benskey et al., 2012). Briefly, tissue or cells were
collected in ice cold 1 X RIPA containing phosphatase and protease inhibitors (Thermo)
and sonicated for 20 s twice. Samples were centrifuged at 10,000 x g for 10 min and the
supernatant was removed and placed in a new labeled tube. Protein content per sample
was determined via BCA assay. Five or 10 µg protein was loaded in each well of a 420% precast gel (BioRad) diluted in 4X sample buffer (BioRad) containing 5% v/v βmercaptoethanol and separated by electrophoresis. After the run was complete, the
proteins on the gel were transferred to a PVDF membrane by activating the PVDF in
methanol for 20 s and washing in ddH2O. The membrane and thick paper blocks were
40

soaked in transfer buffer for 15 min and assembled onto the transfer cell. A semi-dry
transfer method was used to transfer the proteins from the gel to the PVDF membrane
where 15 V were applied for 30 min.
Upon completion of the transfer, the membrane was air-dried for 1 h and blocking was
performed for 1 h with 5% non-fat milk. After blocking, membranes were probed with
various primary antibodies in 5% BSA in TBS-T at 4 ºC overnight, shaking (Table 2-1).
Membranes were rinsed and incubated at room temperature with appropriate secondary
antibodies in 5% non-fat milk in TBS-T for 1 h, shaking. Signal was visualized using a
PICO or FEMTO Chemiluminescence substrate (ThermoFisher) kit on a LI-COR
Odyssey imager. Bands from each lane of the protein of interest were normalized to the
loading controls β-actin or GAPDH using Image Studio version 5.2.

41

Table 2.1. Primary and secondary antibodies used for Western blotting
Target

Host

Dilution

UCH-L1

Rabbit

1:1000

Product Number
Cell Signaling
11896S

TH

Rabbit

1:1000

Millipore MAB152

Ser40 p-TH

Rabbit

1:1000

Cell Signaling 2791

Ubiquitin

Rabbit

1:500

Cell Signaling

DAT

Rat

1:1000

Millipore MAB369

VMAT2

Rabbit

1:1000

Millipore AB1598

COMT

Rabbit

1:1000

Abcam ab126618

UCH-L3

Rabbit

1:1000

Cell Signaling 8141

USP14

Rabbit

1:1000

Cell Signaling
11931
GAPDH

Mouse

1:4000

Rabbit

Goat

1:4000

Sigma G8795
Cell Signaling
7074S

Mouse

Horse

1:4000

42

Cell Signaling 7076

Immunohistochemistry
For IHC experiments, mice were perfused with 0.9% saline followed by 4%
paraformaldehyde in 0.1 M phosphate buffer. Brains were removed and placed in 4%
paraformaldehyde to continue fixation overnight at 4 ºC. When brains sunk to the
bottom of the glass container, brains were cryoprotected in 0.1 M phosphate buffer
containing 20% sucrose. Brains were sliced at 20 µm in a cryostat at -21 ºC and freefloating sections were stored in 0.5 M phosphate buffer (PB) in 12-well culture dishes.
Sections in each well were 100 µm apart.
Free-floating sections were permeabilized in 0.5 M phosphate buffer containing 0.1%
Triton X-100 (PB-TX) and blocked in 5% BSA for 1 h. Sections were incubated in
primary antibody overnight in 5% BSA PB-TX at 4 ºC with shaking. The next day,
sections were rinsed in PB-TX and incubated in secondary antibody for 1 h at room
temperature. Next, sections were rinsed in PB-TX with a final rinse in PB before
mounting. Brain sections were delicately mounted onto slides subbed with gelatin and
coverslipped with anti-fade mounting medium (Invitrogen) and allowed to dry overnight.
Slides were stored at 4 ºC until imaging.
Confocal analysis of colocalization
Slides were imaged using a FV1000 Olympus inverted confocal microscope. A Cy3
conjugated secondary antibody (Jackson Immunoresearch) was used to visualize UCHL1 staining in brain sections using a 543 nm laser for excitation. An Alexa Fluor 488
conjugated secondary antibody was used to visualize TH staining using a 488 nm laser
for excitation. Sequential Kalman averaging was employed during acquisition. A z43

series of 20 µm depth through the tissue was captured (average of 8 slices) and the
Pearson’s and Mander’s coefficients for colocalization of the fluorophores were
collected using unbiased thresholding where experimenter was blinded to treatment
group and compared between VH and MPTP treatment.
DCF-DA assay
For ex vivo measurement of ROS production, tissue from the ST and NAc was removed
from mice (n=3), lysed, and exposed to either VH or 1 µM H2O2 for 30 min at 37 ºC.
Samples were then assayed for DCF-DA fluorescence. Samples were diluted in 10 µM
DCF-DA reagent and incubated at 37 ºC for 1 h. Samples were plated in a black 96 well
plate and relative fluorescence measured at Ex 485/Em 520.
In tissue from MPTP-treated mice, the ST and NAc were dissected fresh and processed
for the DCF-DA assay. Samples were diluted in 10 µM DCF-DA reagent and incubated
at 37 ºC for 1 h. Samples were plated in a black 96 well plate and relative fluorescence
measured at Ex 485/Em 520.
MN9D cell culture and drug treatment
MN9D immortalized cells were cultured in DMEM containing 10% of fetal bovine serum
(FBS) and 1 mM n-butyrate and grown on plates (6, 12, 96 well plates) coated with 50
µg/mL poly-D-lysine (PDL) for 5-7 days to ensure a differentiated phenotype. Cells were
maintained in a 37°C, 5% CO2 incubator and fed every other day. Differentiated MN9D
cells were treated with the following concentrations of MPP+ dissolved in culture media:
0, 50, 100, and 200 µM in 12 or 6 well plates (n=6 wells per group). MPP+ exposure on

44

media was allowed to continue for 2 h or 8 h (n=6 wells per group). Additional wells
were used for subsequent ICC staining and analysis.
Cytotoxicity assay
The cytotoxicity of the MPP+ treatment was evaluated using a CytoTox-ONE kit from
Promega. Briefly, cells were plated in 96 well plates at a corresponding density as the
treatment groups and treated identically. Immediately before the reaction, medium
containing serum was removed and replaced with serum-free medium. Reagents from
the kit were mixed and applied to the cells. Ten minutes later, the reaction was stopped
and the plate was assayed for fluorescent resorufin product, the amount of which is
proportional to lactate dehydrogenase (LDH) leaked from dead cells. LDH release is a
common indicator of membrane permeability associated with cell death (Cummings et
al., 2004).
UCH-L1 hydrolase activity
ST synaptosomes placed in UCH-L1 assay buffer (100 mM NaCl, 0.5 mM EDTA, 50
mM HEPES pH 7.5) containing 0.1% Triton X-100 and sonicated for 20 s twice.
Samples were centrifuged at 10,000 x g for 10 min and supernatant was placed into a
new tube. One µg protein per sample was plated in duplicate in a black 384-well plate
with 1 mM DTT and 0.5 µM Ub-AMC substrate. Kinetic readings for AMC fluorescence
(Ex/Em 380/460 nm) were collected over 30 min and the RFU/min slope was
determined and compared between groups.

45

Cayman total glutathione measurements
Total glutathione (GSH + GSSG) was measured using a kit from Cayman. Briefly,
samples were deproteinized using metaphosphoric acid. Once samples were
deproteinated and neutralized, the assay was performed according to kit instructions.
The data was collected as end point absorbance values at 405 nm and expressed as
µM total glutathione per µg protein.
Abcam GSH/GSSG ratio measurements
Brain tissue samples in 1 X RIPA were deproteinized using a kit from Abcam. Briefly, 2
µL cold trichloroacetic acid was added to each sample and samples were allowed to
incubate on ice for 15 min. Tubes were centrifuged at 12,000 x g for 5 min and the
supernatant was transferred to a new tube. Samples were then neutralized by adding 2
µL Neutralization Solution and incubated on ice for 5 min. Samples were stored at -80
ºC before use in the GSH/GSSG assay.
The GSH/GSSG ratio was performed using a kit from Abcam. Briefly, samples were
diluted in PBS/0.5% NP-40 and placed in two 384-well plates (one for GSH and one for
GSH + GSSG). Results were obtained using a fluorescence microplate reader with an
excitation of 490 and emission of 520 nm. Resulting concentrations of GSH and GSSG
were normalized to protein values and expressed as µM GSH or µM GSSG per µg
protein.

46

HA-Ub-VME DUB labeling assay
HA-Ub-VME substrate was purchased from UBPBio and reconstituted according to
product instructions. Samples in 1 X RIPA containing no protease or phosphatase
inhibitors were prepared as if for Western blot. Ten µg of sample was used in the assay
and diluted to 20 µL with labeling buffer (50 mM Tris pH 7.4, 5 mM MgCl2, 250 mM
sucrose, 1 mM DTT, 1 mM ATP). Samples were incubated with 0.5 µM HA-Ub-VME at
37 ºC for 1 h and prepared for Western blotting. Samples were run on 4-20% gels and
transferred to PVDF. Membranes were probed for UCH-L1.
Statistical analyses
All statistical analyses were performed using SigmaPlot v. 12 software. In studies where
only one factor is examined (i.e., drug treatment or age), a one-way ANOVA was
performed with a post hoc Holm-Sidak test to determine if there is a statistically
significant difference between groups (p < 0.05). For experiments containing two factors
(such as genotype and treatment or age and treatment), a two-way ANOVA was
performed with a post hoc Holm-Sidak test to determine if there is a statistically
significant difference between groups (p < 0.05). At least 6 mice per sample group were
used for each analysis to yield a power of ≥ 80%. Outliers in each experimental group
were removed before statistical analysis using a Grubbs outlier test
(graphpad.com/quickcalcs/Grubbs1.cfm) for significance level p < 0.05. All graphical
representations of data denote the mean + SEM. Refer to each individual chapter and
figure legends for final n values.

47

REFERENCES

48

REFERENCES

Cummings, B.S., Schnellmann, R.G., Schnellmann, R.G., 2004. Measurement of cell
death in mammalian cells. Curr. Protoc. Pharmacol. Chapter 12, Unit 12.8.
doi:10.1002/0471141755.ph1208s25
Dunkley, P.R., Jarvie, P.E., Robinson, P.J., 2008. A rapid Percoll gradient procedure for
preparation of synaptosomes. Nat. Protoc. 3, 1718–1728.
doi:10.1038/nprot.2008.171
Paxinos, G., Franklin, K.B.J., 2004. The Mouse Brain in Stereotaxic Coordinates, 2nd
ed. Elsevier Science.

49

Chapter 3: Oxidative Stress, Dopaminergic Phenotypic Markers, and UCH-L1
Expression in NSDA and MLDA Neurons after Exposure to Acute MPTP
Introduction
In PD, NSDA neurons progressively degenerate while MLDA neurons are spared
(Braak and Braak, 2000). This differential susceptibility is likely influenced by a number
of different factors, including vulnerability to oxidative stress, which is heavily implicated
in development and progression of PD (Sun and Chen, 1998). However, one factor yet
to be examined in detail is expression of PD-linked proteins in pathways known to be
compromised in both human PD and animal models. UCH-L1 is differentially expressed
between NSDA and TIDA neurons after acute MPTP exposure: UCH-L1 is decreased in
the SN but maintained in the ARC 24 h after MPTP (Benskey et al., 2012), suggesting
that UCH-L1 maintenance in TIDA neurons could protect these neurons from
neurotoxicant-induced injury. However, there are caveats associated with comparing
NSDA and TIDA neurons, namely that they are somewhat phenotypically dissimilar:
TIDA neurons do not express much DAT (Meister and Elde, 1993), while NSDA
neurons highly express the transporter. DAT expression is a major factor in determining
MPTP susceptibility, since MPP+ is taken up by DAT into DA neuron terminals. The two
populations also differ in terms of axon length: axons are much shorter in TIDA neurons
compared to NSDA and MLDA neurons. In addition, NSDA and MLDA neuronal activity
is mediated by DA autoreceptors (Lookingland and Moore, 2005).
Therefore, since TIDA and NSDA neurons are so different, the third type of DA neurons
in the CNS, the MLDA neurons, should be evaluated in relation to their response to

51

acute MPTP. Previous studies have established that MLDA neurons are less
susceptible to damage from both chronic (Hung and Lee, 1998) and acute (B. Behrouz
et al., 2007) MPTP with respect to DA loss, but individual pathways such as the UPS
have not yet been studied to determine what factors (such as dysfunction in protein
degradation) could contribute to the resistance of MLDA neurons to neurotoxicant
exposure and PD. The purpose of these studies was to determine if UCH-L1 expression
is maintained in MLDA neurons after acute MPTP.
Results
Oxidative stress in brain regions containing NSDA vs. MLDA neurons
Because MPP+, the active metabolite of MPTP, causes oxidative stress and an increase
in ROS (Johannessen et al., 1986), we predict that the differential susceptibilities of
NSDA and MLDA neurons could be linked to differential production of ROS. We first
used an ex vivo approach to compare production of ROS in ST and NAc tissue by
hydrogen peroxide (H2O2). Fig. 3.1 shows that H2O2 produces different amounts of
ROS in tissue from the ST and NAc. This approach directly delivers the oxidant to the
tissue, so no questions of tissue penetration impede interpretation of the response. The
same amount of H2O2 produced more ROS in equal amounts of tissue from the ST than
in the NAc, suggesting that the antioxidant capacity of the NAc is likely greater than in
the ST. The greater antioxidant capacity in the NAc could explain why these neurons
are less susceptible, since the response of DA neurons to toxicant-induced acute
oxidative stress is predicted to play a substantial role in development and

52

Figure 3.1. Ex vivo ROS production in ST (white) and NAc (teal) lysates. Five
mice were decapitated and the brains sectioned fresh (n=5). The ST and NAc
were microdissected. Tissue was lysed and treated with 1 µM H2O2. A DCF-DA
assay for detection of ROS was performed and the resulting fluorescence in
relative fluorescence units (RFU) was normalized to protein content. Data is
plotted as mean + SEM. Asterisk (*) indicates difference from respective (-)H2O2
control, whereas pound (#) represents difference from ST (+)H2O2 via Repeated
Measures ANOVA and post hoc Holm-Sidak test.

53

Figure 3.2. In vivo ROS levels in the ST (white) and NAc (teal) 6 after MPTP
exposure. ROS was measured using a DCF-DA assay in ST and NAc from either
VH or MPTP treated mice. ST VH n=7; ST MPTP n=10; NAc VH n=8; NAc MPTP
n=10. Six hours after injection, mice were decapitated and the ST and NAc
microdissected from fresh brain tissue. The DCF-DA assay was performed to
yield relative amounts of ROS between brain regions and treatments. Data is
plotted as mean + SEM. No statistically significant differences were detected
between treatment groups (p > 0.05) via two-way ANOVA.

54

progression of PD (Sun and Chen, 1998). A limit of this technique is that we currently do
not know if the antioxidant capacity within the neurons themselves is increased, or
whether it could be due to glial cells present in the NAc. Next, since the peak
concentration of MPP+ in the ST occurs at 6 h (Benskey et al., 2012), in vivo production
of ROS was examined in the ST and NAc 6 h after MPTP exposure. In Fig. 3.2, the
amount of DCF-DA fluorescence was found to be equivalent between brain regions and
between treatment groups. This result is somewhat unexpected based on previous
research with chronic MPTP, where increased lipid peroxidation and other markers of
oxidative stress were evident in the ST but not the NAc (Hung and Lee, 1998). It
appears that MPTP exposure results in the same amount of ROS generation between
the ST and NAc at the 6 h time point. However, just because ROS levels are not
elevated does not indicate that ROS-induced damage did not occur, since one of our
indices of DA neuronal damage, DA levels in the ST, was decreased at 6 h (Fig. 3.3).
Furthermore, since microdissected ST and NAc tissue includes MSNs and glial cells, a
change in the production of ROS specifically in axon terminals of DA neurons is less
likely to be detectable with the present methods. One way to specifically examine
endpoints in NSDA axon terminals is to prepare synaptosomes (Dunkley et al., 2008),
or pinched off axon terminals using special homogenization steps with buffers that
create a sphere from the tip of an axon. However, this technique is limited by the
amount of tissue available and cannot be used with much smaller brain regions like the
NAc (~20 µg protein from bilateral punches). It is readily done with the ST, however,
and axon-terminal specific analyses in the ST are presented in Chapter 4 of this
dissertation.

55

Figure 3.3. DA in the ST 6 h post MPTP exposure. Mice were injected with VH
(n=10) or MPTP (n=9) and killed 6 h later. The ST was dissected and DA was
measured via HPLC-ED. Data is plotted as mean + SEM. Asterisk (*) signifies a
significant difference where p < 0.05 via t-test.

56

Differential susceptibility of NSDA and MLDA neurons to MPTP: DA, DOPAC, and TH
The MPTP model of DA depletion recapitulates early events thought to underlie
mechanisms related to loss of NSDA neurons in PD. In a paper published previously by
our laboratory, DA is not decreased in the NAc to the same extent as the ST after acute
MPTP (Behrouz et al., 2007). We sought to replicate this differential responsiveness of
MLDA and NSDA neurons and to further examine DA metabolism and expression of
TH, the rate-limiting enzyme of DA synthesis. In Fig. 3.4 (Left Panel), DA is decreased
in the both the ST and NAc 24 h after MPTP exposure. However, the extent of DA loss
is greater in the ST compared to the NAc, which can be more easily seen by expressing
the data as percent control Fig. 3.4 (Right Panel). Since the ST and NAc are located in
similar regions of the brain, it is also likely that the ST and NAc are exposed to the same
concentration of MPTP, since MPTP is lipid soluble and readily penetrates the BBB.
Therefore, MLDA neurons are resistant to loss of DA after MPTP exposure. These
results make sense in the context of antioxidant response if MLDA neurons are able to
mount a more successful defense of ROS compared to NSDA neurons in the ex vivo
experiment with equal amounts of hydrogen peroxide.
The primary intracellular metabolite of DA, DOPAC, is an index of DA that has been
released, recaptured, and metabolized by MAO-B in presynaptic axon terminals (Meiser
et al., 2013). In Fig. 3.5, DOPAC is decreased in both the ST and NAc to an equal
extent, reflecting less DA release after acute MPTP exposure in both regions. This
result makes sense if DA is being displaced from synaptic vesicles by MPP+ since it
cannot be released unless packaged (Sulzer et al., 2016). The DOPAC/DA

57

Figure 3.4. DA in the ST (white) and NAc (teal) 24 h after MPTP exposure. Mice were
injected with VH or MPTP and killed 24 h later. The ST and NAc were dissected and DA
was measured via HPLC-ED. ST VH n=9; ST MPTP n=8; NAc VH n=10; NAc MPTP
n=10. Data is plotted as mean + SEM. Asterisk (*) signifies a significant difference from
respective VH control where p < 0.05 via two-way ANOVA with post hoc Holm-Sidak test.
Pound sign (#) or ampersand (&) signifies a significant difference from ST MPTP via twoway ANOVA with post hoc Holm-Sidak test.

58

ratio is an index of the rate of DA release, reuptake and metabolism relative to
packaging into synaptic storage vesicles. The DOPAC/DA ratio is elevated in the NAc
compared to the ST under basal conditions (Fig. 3.6), reflecting a higher rate of DA
release in the NAc compared to the ST. MPTP caused a decrease in the DOPAC/DA
ratio in the NAc but not the ST (Fig. 3.6).
TH, the rate-limiting enzyme of DA synthesis, is an important phenotypic marker for DA
neurons and is highly expressed in both the ST and NAc. Previous studies have shown
that TH expression is impaired in the ST after MPTP (Benskey et al., 2012), but the
effects of MPTP on TH expression in the NAc has not been examined. Total TH in the
ST and NAc 6 h (Fig. 3.7) and 24 h (Fig. 3.8) after MPTP was measured. Six h after
MPTP exposure, TH expression is not changed in the ST or NAc (Fig. 3.7). However,
24 h after MPTP exposure, TH is decreased in both the ST and NAc, but to a lesser
extent in the NAc (Fig. 3.8). Loss of TH protein expression likely is associated with the
loss of DA stores in axon terminals, since more DA synthesis would be impaired with a
deficiency of this key catalytic enzyme responsible for DA synthesis. These results
show that MLDA neurons are more resilient to MPTP-induced decreases in DA stores
and TH expression.

59

Figure 3.5. DOPAC in the ST (white) and NAc (teal) 24 h after MPTP exposure.
Mice were injected with VH or MPTP and killed 24 h later. The ST and NAc were
dissected and DOPAC was measured via HPLC-ED. ST VH n=9; ST MPTP n=8;
NAc VH n=10; NAc MPTP n=10. Data is plotted as mean + SEM. Asterisk (*)
signifies a significant difference from respective VH control. where p < 0.05 via twoway ANOVA with a post hoc Holm-Sidak test. Pound sign (#) signifies a significant
difference from ST MPTP via two-way ANOVA with a post hoc Holm-Sidak test.

60

Figure 3.6. DOPAC/DA ratio in the ST (white) and NAc (teal) 24 h after
MPTP exposure. Mice were injected with VH or MPTP and killed 24 h later.
The ST and NAc were dissected and DA and DOPAC were measured via
HPLC-ED. ST VH n=9; ST MPTP n=8; NAc VH n=10; NAc MPTP n=10.
Data is plotted as mean + SEM. Asterisk (*) signifies a significant difference
from ST VH control where p < 0.05 via two-way ANOVA and a post hoc
Holm-Sidak test. Pound sign (#) signifies a significant difference from NAc
VH via two-way ANOVA and a post hoc Holm-Sidak test.

61

TH

VH
H

MPTP

VH

MPTP

GAPDH

Figure 3.7. Total TH protein expression in the ST (white) and NAc (teal) 6
h after MPTP exposure. Mice were injected with VH or MPTP and killed 6 h
later (n=10 each group). The ST and NAc were dissected and total TH protein
was measured via Western blot. Data is plotted as mean + SEM. No
statistically significant differences were detected in either brain region or
treatment group (p > 0.05) via two-way ANOVA with post hoc Holm-Sidak test.

62

Figure 3.8. Total TH protein expression in the ST (white) and NAc (teal)
24 h after MPTP exposure. Mice were injected with VH or MPTP and
killed 24 h later. The ST and NAc were dissected and total TH protein was
measured via Western blot. ST VH n=10; ST MPTP n=9; NAc VH n=10;
NAc MPTP n=9. Data is plotted as mean + SEM. Asterisk (*) signifies a
significant difference from respective VH control. where p < 0.05 via twoway ANOVA and post hoc Holm-Sidak test. Pound sign (#) signifies a
significant difference from ST MPTP where p < 0.05 via two-way ANOVA
and post hoc Holm-Sidak test.

63

UCH-L1 and mono-Ub in MLDA neurons after MPTP exposure
Twenty four h after MPTP exposure, UCH-L1 is decreased in the SN (Benskey et al.,
2012), which is the cell body region of NSDA neurons that degenerate in PD. However,
the expression of UCH-L1 protein in the ST and NAc has not been reported. UCH-L1
expression in the ST and NAc is not changed 6 h (Fig. 3.9) or 24 h (Fig. 3.10) after
MPTP exposure.
The decrease in UCH-L1 in the SN was recapitulated over time after a single injection of
MPTP in Fig. 3.11. Prior to the present experiments, the expression of UCH-L1 had not
been examined in MLDA neurons, whether in the cell body region (VTA) or the axon
terminal region (NAc). UCH-L1 protein expression was measured at various time points
after MPTP exposure and was found to be maintained after neurotoxicant-induced injury
in the VTA (Fig. 3.12). The ability to maintain UCH-L1 expression in the VTA may
confer resistance to MLDA neurons to MPTP. Since UCH-L1 was decreased in the SN
but maintained in the VTA 24 h after MPTP exposure, the 24 h time point was
considered to be the most relevant and was used for subsequent experiments.
The main function of UCH-L1 activity is to replenish pools of free mono-Ub, which can
be activated by E1 and E2 ligases and passed to an E3 ligase, which attaches Ub to
protein substrates (Ciechanover, 1994) Therefore, it is hypothesized that if UCH-L1
levels decrease, so should levels of mono-Ub. In Fig. 3.13, mono-Ub was not changed
in the ST or NAc 24 h after MPTP exposure, which is congruent with maintenance of
UCH-L1 expression in the two brain regions 24 h after MPTP. However, in the SN,
mono-Ub was decreased 24 h after MPTP exposure (Fig. 3.14).

64

Figure 3.9. UCH-L1 protein expression in the ST (white) and NAc (teal) 6 h
after MPTP exposure. Mice were injected with VH or MPTP and killed 6 h later
(n=10 each group). The ST and NAc were dissected and UCH-L1 protein was
measured via Western blot. Data is plotted as mean + SEM. No statistically
significant differences between brain region or treatment group were found (p >
0.05) via two-way ANOVA.

65

In contrast, 24 h after MPTP exposure, mono-Ub was not decreased in the VTA (Fig.
3.15). This congruence between UCH-L1 expression and levels of free mono-Ub in the
cell body region of MLDA neurons agrees well with the proposed function of UCH-L1.
Total glutathione concentrations in brain regions containing NSDA and MLDA neurons
The exact mechanism by which UCH-L1 could contribute to protection of MLDA
neurons is as yet unknown, but could involve a relationship of UCH-L1 to regulation of
reduced glutathione (GSH): UCH-L1 is predicted to have activity toward Ub-GSH and
can help scavenge free GSH (Rose and Warms, 1983). GSH is an important free
radical scavenger that is converted to its reduced form GSSG when encountering ROS.
Mice lacking functional UCH-L1 (gad phenotype) have less GSH in brain tissue
(Coulombe et al., 2014). Therefore, if UCH-L1 has a protective function to maintain
levels of GSH in mouse brain, it is predicted that we should observe that GSH
decreases when UCH-L1 decreases and GSH is maintained when UCH-L1 is
maintained.
Total GSH (both GSH + GSSG forms) was measured in NSDA and MLDA neurons 24 h
after MPTP. In the ST and NAc, no changes in total GSH concentration were observed
(Fig. 3.16). Similarly, in the SN and VTA, no changes in total GSH were observed after
MPTP (Fig. 3.17). These results are unexpected based on the findings in UCH-L1 null
mice (Coulombe et al., 2014) but can be explained by introducing two caveats: 1) the
phenotype of a UCH-L1 null mouse is expected to be much more severe than in a WT
mouse that still expresses functional (if reduced levels of) UCH-L1, so it could be
difficult to compare the magnitude of the response, and 2) the kit used for this assay

66

measures total GSH, which may not be the best indicator for perturbations of the GSH
antioxidant system. Rather, it would be better to use an assay that measures both GSH
and GSSG and can yield a GSH/GSSG ratio. Future measurements of GSH
homeostasis will utilize a kit that measures both forms of GSH.

67

Figure 3.10. UCH-L1 protein expression in the ST (white) and NAc (teal) 24 h
after MPTP exposure. Mice were injected with VH or MPTP and killed 24 h later
(n=10 each group). The ST and NAc were dissected and UCH-L1 protein was
measured via Western blot. Data is plotted as mean + SEM. No statistically
significant differences between brain region or treatment group were found (p >
0.05) via two-way ANOVA.

68

Expression of UCH-L1 in NSDA and MLDA neurons
Thus far, we have examined UCH-L1 protein expression in microdissected mouse brain
tissue containing cell bodies and axon terminals of NSDA and MLDA neurons. While the
sampling technique is relatively specific based on brain region morphology, these tissue
samples also contain glial cells and other non-TH neuron types. Fortunately, UCH-L1 is
expressed solely in neurons (Lowe et al., 1990), so glial expression of this DUB is not
an issue in this case. To determine if UCH-L1 protein expression is changing
specifically in DA neurons, dual labeling IHC can be used to visualize TH neurons and
UCH-L1 staining can be employed to relatively determine how many TH neurons
express UCH-L1 in the SN and VTA after MPTP. Fig. 3.18 shows UCH-L1 staining in
the SN and VTA. The results reveal that UCH-L1 is robustly expressed in both brain
regions co-localized in TH+ neurons under basal, control conditions.
Initial determination of UCH-L1 expression in the SN by IHC (Fig. 3.19) yielded the
finding that the percent of TH neurons expressing UCH-L1 decreased 24 h after MPTP.
This result is congruent with the microdissected tissue sample results and indicates that
the decrease in UCH-L1 in the SN observed 24 h after MPTP exposure is occurring in
the TH neurons present in the same brain region captured by the microdissection.
There was no difference in numbers of TH neurons after acute MPTP in either brain
region. Similarly, the percent of TH neurons expressing UCH-L1 was not changed in the
VTA (Fig. 3.20), which is similar to the observed result that UCH-L1 protein is not
altered after MPTP exposure in the VTA. The method of analyzing numbers of neurons
in images captured by an epifluorescence microscope was developed for ImageJ and
involved using thresholding for both size and
69

Figure 3.11. UCH-L1 protein expression in the SN after MPTP exposure. Mice
were injected with MPTP and killed various times after MPTP. The SN was
dissected and UCH-L1 protein was measured via Western blot. VH n=8; 2 h n=10;
4 h n=10; 8 h n=10; 12 h n=9; 24 h n=7. Data is plotted as mean + SEM. Asterisk
(*) signifies a significant difference from VH control where p < 0.05 via one-way
ANOVA with a post hoc Holm-Sidak test.

70

Figure 3.12. UCH-L1 protein expression in the VTA after MPTP exposure. Mice
were injected with MPTP and killed various times after MPTP (n=10 each group). The
VTA was dissected and UCH-L1 protein was measured via Western blot. Data is
plotted as mean + SEM. No significant difference was detected between groups (p >
0.05) via one-way ANOVA.

71

Figure 3.13. Mono-Ub protein expression in the ST (white) and NAc (teal) 24 h
after MPTP exposure. Mice were injected with VH or MPTP and killed 24 h later.
The ST and NAc were dissected and mono-Ub protein was measured via Western
blot. ST VH n=10; ST MPTP n=10; NAc VH n=10; NAc MPTP n=9. Data is plotted as
mean + SEM. No statistically significant differences between brain region or
treatment group were found (p > 0.05) via two-way ANOVA.

72

Figure 3.14. Mono-Ub protein expression in the SN 24 h after MPTP exposure.
Mice were injected with VH or MPTP and killed 24 h later (n=8 each group). The SN
was dissected and mono-Ub protein was measured via Western blot. Data is
plotted as mean + SEM. Asterisk (*) signifies a statistically significant difference
from VH control where p < 0.05 via t-test.

73

VH

MPTP

Mono-Ub
GAPDH

Figure 3.15. Mono-Ub protein expression in the VTA 24 h after MPTP
exposure. Mice were injected with VH or MPTP and killed 24 h later (n=10 each
group). The VTA was dissected and mono-Ub protein was measured via Western
blot. Data is plotted as mean + SEM. No statistically significant difference was
detected between groups (p > 0.05) via t-test.

74

Figure 3.16. Total GSH concentrations in the ST (white) and NAc (teal). Mice
were injected with VH or MPTP and killed 24 h later (n=10 each group). Brains
were removed and ST and NAc were dissected and assayed for total GSH (GSH
+ GSSG) content. Data is plotted as mean + SEM. No statistically significant
differences between brain region or treatment group were found (p > 0.05) via
two-way ANOVA.

75

Figure 3.17. Total GSH concentrations in the SN (white) and VTA (teal). Mice
were injected with VH or MPTP and killed 24 h later. SN VH n=9; SN MPTP n=10;
VTA VH n=8; VTA MPTP n=10. Brains were removed and SN and VTA were
dissected and assayed for total GSH (GSH + GSSG) content. Data is plotted as
mean + SEM. No statistically significant differences between brain region or
treatment group were found (p > 0.05) via two-way ANOVA.

76

Figure 3.18. Immunohistochemical staining for UCH-L1 and TH in the SN
(white dashed oval) and VTA (white dotted circle). Mice were perfused with
paraformaldehyde and brains sectioned at 20 µm. Brain sections were stained and
mounted onto slides. Slides were imaged using an Olympus FV1000 confocal
microscope. Top tier images are 10X magnification (scale bar = 200 µm). Middle
tier images are 20X magnification (scale bar = 100 µm). Bottom tier images are
40X magnification (scale bar = 50 µm).

77

Figure 3.19. Percent of TH and UCH-L1 positive neurons in the SN 24 h after
MPTP. Mice were injected with VH or MPTP and perfused 24 h later with
paraformaldehyde (n=4 each group). The brain was sectioned and stained for UCHL1. Images were analyzed using an ImageJ method to count double-labeled cells.
Data is plotted as mean + SEM. Asterisk (*) signifies a statistically significant
difference where p < 0.05 via t-test.

78

Figure 3.20. Percent of TH and UCH-L1 positive neurons in the VTA 24 h after
MPTP. Mice were injected with VH or MPTP and perfused 24 h later with
paraformaldehyde (n=5 each group). The brain was sectioned and stained for UCH-L1.
Images were analyzed using an ImageJ method to count double-labeled cells. Data is
plotted as mean + SEM. No significant difference between groups was detected (p >
0.05) via t-test.

79

Figure 3.21. Pearson’s correlation coefficient values for co-localization of UCH-L1
and TH signal in the SN (white) and VTA (teal). Mice were injected with VH or MPTP
and perfused 24 h later with paraformaldehyde. SN VH n=6; SN MPTP n=7; VTA VH
n=5; VTA MPTP n=6. The brain was sectioned and stained for UCH-L1. Images were
analyzed using FV1000 software to determine the PCC for overlap of UCH-L1 and TH
signal. Data is plotted as mean + SEM. No statistically significant difference was
detected between groups (p > 0.05) via two-way ANOVA.

80

Figure 3.22. Mander’s overlap correlation values for co-localization of UCH-L1
and TH signal in the SN (white) and VTA (teal). Mice were injected with VH or
MPTP and perfused 24 h later with paraformaldehyde. SN VH n=6; SN MPTP n=7;
VTA VH n=5; VTA MPTP n=5. The brain was sectioned and stained for UCH-L1.
Images were analyzed using FV1000 software to determine the MOC for overlap of
UCH-L1 and TH signal. Data is plotted as mean + SEM. No statistically significant
difference was detected between groups (p > 0.05) via two-way ANOVA.

81

intensity, where visualization of the fluorophore signal is only taken into account if it is
above a certain threshold and the region of signal corresponds to the actual size of a
neuron. A caveat for this method is that relatively thicker (20 µm) specimens imaged
using an epifluorescence microscope can show fluorescence bleed through, due to a
wide area of tissue being excited by the mercury lamp bulb. One way to get around this
issue is to use confocal microscopy.
The experiment was repeated and images captured via confocal microscopy. Images
were analyzed for co-localization of pixels corresponding to TH and UCH-L1 staining.
To measure the degree of co-localization, the Pearson’s correlation coefficient (PCC)
and Mander’s Overlap Coefficient (MOC) were analyzed for SN and VTA images and
between VH and MPTP treated mice (Fig. 3.21).
Discussion
In this chapter, evidence for differential response to MPTP between two differentially
susceptible DA neuron populations was presented. In addition, MLDA neurons showed
partial resistance to MPTP toxicity with respect to a decrease in DA and TH expression.
This observed decreased susceptibility to MPTP has been demonstrated both here and
in previous studies (Behrouz et al., 2007; Hung and Lee, 1998; Hung et al., 1995) and
likely involves a difference in MLDA neuron response to oxidative stress. Although the
actual production of ROS in ST and NAc are not different 6 h after MPTP, the response
to downstream effects of ROS toxicity could be different.
To understand pathways that could compensate in MLDA neurons to combat neurotoxic
injury, we examined a protein found to be mutated in rare familial PD—UCH-L1, a
82

neuron specific DUB. Although UCH-L1 expression is decreased in the SN, UCH-L1
protein is maintained in the VTA. This preservation of UCH-L1 expression is
accompanied by maintenance of UCH-L1 function, as evidenced by maintenance of free
mono-Ub levels after neurotoxicant exposure. However, there is a mismatch between
UCH-L1 changes between the cell body regions and the axon terminals: UCH-L1 is only
decreased in the SN rather than the ST. Since the axon terminal regions are considered
to be the primary site of action to MPP+ because MPP+ relies on DAT to enter the cell,
we would have predicted that UCH-L1 would be decreased in the ST as well as the SN.
UCH-L1 expression over time after MPTP in the axon terminals of NSDA neurons is
more closely examined in Chapter 4.
The number of DA neurons expressing UCH-L1 was decreased in the SN but not the
VTA 24 h after MPTP, matching the protein expression found in whole tissue and
demonstrating that the decrease in UCH-L1 protein observed in whole SN tissue is not
obscured by changes in UCH-L1 in other neuronal populations. However, the colocalization of TH and UCH-L1 signal was not changed in either region after MPTP
treatment. It should be noted that although PCC and MOC indices are widely accepted
as a valid method for determining co-localization of fluorophores (Dunn et al., 2011), it
may be of limited use in determine how many DA neurons express UCH-L1 because
these only determine that there is no difference in co-incidence of red and green pixels
between VH and MPTP treated mice. Accordingly, it would be expected that the number
of red pixels corresponding to UCH-L1 protein would decrease in brain sections from
MPTP-treated mice. But fluorescence intensity is not generally a good measure of
protein abundance, since there are many factors that can affect fluorescence intensity
83

(Dunn et al., 2011) that are independent of the amount of protein present (such as
binding affinity and abundance of the secondary antibody, which contains the
fluorophore). However, this method of determining the PCC and MOC with thresholding
is one way to avoid observer bias.
The most ideal method for determining numbers of TH neurons would be stereology
(West, 1999), but most investigators use stereology for bright field microscopic analysis
of tissues rather than fluorescence, and determination of dual-labeled cells is limited.
Therefore, the ImageJ method may be a new acceptable way to determine numbers of
neurons expressing a particular protein as evidenced by presence of a fluorophore. This
is the first time that UCH-L1 expression and function has been measured in the MLDA
neurons, especially in the context of neurotoxicant-induced stress. Maintenance of
UCH-L1 expression in the VTA may confer resistance of MLDA neurons to
neurotoxicant-induced injury. Further work to inhibit UCH-L1 will help to elucidate
whether this effect is UCH-L1 specific.
Summary and conclusions
In this chapter, we recapitulated the differential susceptibility of NSDA and MLDA
neurons to acute MPTP with respect to DA and TH expression. We also examined
response to oxidative stress by production of ROS. UCH-L1 was discovered to be
maintained in the VTA, both in whole tissue samples and in DA neurons by IHC. These
studies provide evidence that UCH-L1 is differentially regulated between NSDA and
MLDA neurons and maintenance of UCH-L1 is associated with decreased susceptibility
to MPTP.

84

REFERENCES

85

REFERENCES

Behrouz, B., Drolet, R.E., Sayed, Z.A., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–8.
doi:10.1016/j.neuroscience.2007.05.007
Behrouz, B., Drolet, R.E., Sayed, Z. a., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–598.
doi:10.1016/j.neuroscience.2007.05.007
Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Braak, H., Braak, E., 2000. Pathoanatomy of Parkinson’s disease. J. Neurol. 247 Suppl,
II3-10. doi:10.1007/PL00007758
Ciechanover, A., 1994. The ubiquitin-proteasome proteolytic pathway. Cell 79, 13–21.
doi:10.1016/0092-8674(94)90396-4
Coulombe, J., Gamage, P., Gray, M.T., Zhang, M., Tang, M.Y., Woulfe, J., Saffrey,
M.J., Gray, D.A., 2014. Loss of UCHL1 promotes age-related degenerative
changes in the enteric nervous system . Front. Aging Neurosci. .
Dunkley, P.R., Jarvie, P.E., Robinson, P.J., 2008. A rapid Percoll gradient procedure for
preparation of synaptosomes. Nat. Protoc. 3, 1718–1728.
doi:10.1038/nprot.2008.171
Dunn, K.W., Kamocka, M.M., McDonald, J.H., 2011. A practical guide to evaluating
colocalization in biological microscopy. AJP Cell Physiol. 300, C723–C742.
doi:10.1152/ajpcell.00462.2010
Hung, H.-C., Lee, E.H.., 1998. MPTP Produces Differential Oxidative Stress and
Antioxidative Responses in the Nigrostriatal and Mesolimbic Dopaminergic
Pathways. Free Radic. Biol. Med. 24, 76–84. doi:10.1016/S0891-5849(97)00206-2
Hung, H.C., Tao, P.L., Lee, E.H., 1995. 1-Methyl-4-phenyl-pyridinium (MPP+) uptake
does not explain the differential toxicity of MPP+ in the nigrostriatal and mesolimbic
dopaminergic pathways. Neurosci. Lett. 196, 93–6.
Johannessen, J.N., Adams, J.D., Schuller, H.M., Bacon, J.P., Markey, S.P., 1986. 186

methyl-4-phenylpyridine (MPP+) induces oxidative stress in the rodent. Life Sci. 38,
743–749. doi:10.1016/0024-3205(86)90589-8
Lookingland, K.J., Moore, K.E., 2005. Chapter VIII Functional neuroanatomy of
hypothalamic dopaminergic neuroendocrine systems. Handb. Chem. Neuroanat.
21, 435–523. doi:10.1016/S0924-8196(05)80012-0
Lowe, J., McDermott, H., Landon, M., Mayer, R.J., Wilkinson, K.D., 1990. Ubiquitin
carboxyl-terminal hydrolase (PGP 9.5) is selectively present in ubiquitinated
inclusion bodies characteristic of human neurodegenerative diseases. J. Pathol.
161, 153–160. doi:10.1002/path.1711610210
Meiser, J., Weindl, D., Hiller, K., 2013. Complexity of dopamine metabolism. Cell
Commun. Signal. 11, 34. doi:10.1186/1478-811X-11-34
Meister, B., Elde, R., 1993. Dopamine Transporter mRNA in Neurons of the Rat
Hypothalamus. Neuroendocrinology 58, 388–395. doi:10.1159/000126568
Rose, I.A., Warms, J.V.B., 1983. An enzyme with ubiquitin carboxy-terminal esterase
activity from reticulocytes. Biochemistry 22, 4234–4237. doi:10.1021/bi00287a012
Sulzer, D., Cragg, S.J., Rice, M.E., 2016. Striatal dopamine neurotransmission:
Regulation of release and uptake. Basal Ganglia 6, 123–148.
doi:10.1016/j.baga.2016.02.001
Sun, A., Chen, Y., 1998. Oxidative stress and neurodegenerative disorders. J. Biomed.
Sci. 65212, 401–414.
West, M.J., 1999. Stereological methods for estimating the total number of neurons and
synapses: issues of precision and bias. Trends Neurosci. 22, 51–61.
doi:10.1016/S0166-2236(98)01362-9

87

Chapter 4: Effects of Neurotoxicant and UCH-L1 Inhibitor in MN9D Cells and ST
Synaptosomes, and a Potential Interaction between UCH-L1 and Parkin with
Relevance to Autophagy
Introduction
One approach to the determination of whether expression of UCH-L1 in populations of
DA neurons influences susceptibility to neurotoxicant-induced injury is to use tools and
techniques targeting only NSDA neurons. This chapter takes a closer look at
mechanistic aspects of UCH-L1 function in an in vitro model of NSDA neurons and in
ST synaptosomes containing axon terminals of NSDA neurons. A potential interaction
between UCH-L1 and parkin is also investigated, with potential consequences for
another major avenue of protein degradation: the ALP.
The “MN9D” cell line is derived from a fusion of mouse mesencephalic DA neurons with
murine neuroblastoma cells (Choi et al., 1991), and is extensively used in PD research.
Utilization of this immortalized cell line affords many benefits to studying mechanisms of
DA neuronal loss in PD or MPTP toxicity because of its ease of neurotoxicant exposure
to a culture, the ease of collection of samples, the shorter time frame and less cost for
an experiment as compared to in vivo models, and last but certainly not least, the
conservation of rodent life while performing “proof of principle” experiments. MN9D cells
express high levels of TH and DAT (Choi et al., 1992), which are prerequisites for
evaluating MPP+ induced toxicity. The active metabolite of MPTP, MPP+, has been used
in MN9D cell cultures to examine its cytotoxic effect under varying conditions (Choi et
al., 1999). It is currently unknown if UCH-L1 is highly expressed in MN9D cells, and

88

further, if UCH-L1 expression is altered with MPP+ exposure. The purpose of studies
using MN9D cells described in this chapter is to determine if these cells model inhibition
of NSDA neuronal UCH-L1 expression after toxicant exposure. In addition,
pharmacological inhibitors of UCH-L1 and the UPS will be used to examine the effects
of UCH-L1 and proteasome inhibition on DA phenotypic markers.
A hallmark pathology of PD is the presence of Lewy bodies in NSDA neurons, which are
proteinaceous deposits of α-syn (Spillantini et al., 1997),(Baba et al., 1998) and Ub
(Meredith et al., 2004) linked to disruption in protein homeostasis. Indeed, within the
family of human genes with the PARK denotation, a few code for enzymes involved in
protein degradation such as UCH-L1 (PARK5) and parkin (PARK2). UCH-L1’s role in
maintaining proteasome function is not well understood, as it removes Ub from small
substrates and could potentially prevent proteasomal degradation of those substrates.
On the other hand, UCH-L1 helps to recycle free mono-Ub to be used by E3 ligases to
tag misfolded protein substrates. Parkin, a 465 amino acid protein, is an E3 ligase
(Shimura et al., 2000) responsible for tagging specific substrates with mono-Ub and
building poly-Ub chains that target substrates for degradation via the 26S proteasome.
In addition to its ligase activity, parkin has been shown to bind to the Rpn10 domain of
the 26S proteasome via its ubiquitin-like domain (UBL) to directly modulate 26S
proteasome activity (Um et al., 2010).
Although parkin’s PD-related substrates in vivo are only partially known, loss of
functional parkin causes widespread neurodegeneration in the human brain (Shimura et
al., 2000). Mutations in parkin are the second most common cause of autosomalrecessive juvenile parkinsonism (Kitada et al., 1998) and parkin has also been shown to
89

contribute to mitophagy (Narendra et al., 2008), which is a critical process of
mitochondrial quality control. In fact, recent evidence shows that parkin is critical for
recovery of SN neurons after mitochondrial stress (Pickrell et al., 2015). However, since
the generation of the parkin null mouse (Goldberg et al., 2003), a puzzling lack of
degenerative phenotype (Perez and Palmiter, 2005) has been observed in these mice,
begging the question of compensation since the mice have coped with lack of parkin
protein from birth. How these mice compensate for loss of UPS function and whether
that compensation involves down-regulation of UCH-L1 will be examined in this chapter.
Death of NSDA neurons is likely due at least in part to failure of both the UPS and the
ALP since pathology in PD is highly associated with aggregated proteins (Ross and
Poirier, 2004). The UPS and ALP represent the two major pathways of protein
degradation in the cell tasked with recycling amino acids from degraded proteins and
maintaining proteostasis. The 26S proteasome primarily degrades small, short-lived
proteins in a highly specific manner, requiring the use of a K48-linked poly-Ub chain
attached to a substrate protein to signal degradation (Thrower et al., 2000). It is
important to note that another form of the proteasome may play a role in degrading
proteins and aggregates: the 20S proteasome can degrade proteins that are not
ubiquitinated and can also degrade oxidatively modified proteins (Davies, 2001). In
contrast to 26S proteasome activity, macroautophagy, one of the pathways broadly
described as the ALP, is relatively non-selective and can degrade larger complexes or
even organelles, of which mitophagy (self-eating of mitochondria) is a prominent
example (Ross et al., 2015).

90

In another branch of the ALP pathway, chaperone mediated autophagy (CMA), proteins
containing a specific amino acid motif (KFERQ) bind to the chaperone hsc70, which
shuttles the substrate to the LAMP-2A receptor located on the exterior of the lysosome
which forms a multimeric complex to induce unfolding and endocytosis of the substrate
(Bandyopadhyay et al., 2008). An important protein relevant to PD, α-syn, has been
demonstrated to be degraded by CMA in its monomeric form and mutant forms of α-syn
impair the ability of CMA to clear other substrates (Cuervo et al., 2004).
A K63-linked poly-Ub chain may act to signal a protein to be degraded by
macroautophagy, but it is unclear whether these chains are required for all types and
situations of macroautophagy. It is also unclear which E3 ligase is responsible for
conjugating K63-linked chains on specific substrates though parkin has been shown to
create K63-linked poly-Ub chains, especially with respect to mitophagy (Olzmann and
Chin, 2008). Indeed, evidence of failure of the ALP has been shown in post-mortem
brain samples from PD patients where NSDA neurons display many autophagic
vacuoles (Anglade et al., 1997). Although the UPS and ALP were once considered
functionally separate, emerging evidence suggests that crosstalk between the two
systems exist such that if one pathway becomes dysfunctional, the other’s activity may
be upregulated to compensate to maintain proteostasis (Ross and Pickart, 2004).
Since degradation of substrates by the 26S proteasome canonically requires a K48linked poly-Ub chain, 26S proteasome function may be dependent on E3 ligases that
can perform this ubiquitination. In the case of parkin deficient mice, total UPS activity
has been shown in our laboratory to be decreased in the SN, suggesting that
proteasome activity is impaired in Park2-/- mice compared to wild-type mice (Lansdell,
91

2017). If 26S proteasome activity is at least partially dependent on parkin E3 ligase
activity and/or parkin UBL domain binding to the Rpn10 subunit (Um et al., 2010) and
parkin regulation of UCH-L1 plays a role, perhaps the ALP is upregulated to
compensate and degrade UPS substrates sans poly-Ub chains. This hypothesis will be
tested in this chapter.
Results
MN9D expression of DA phenotypic markers and UCH-L1
To determine if the MN9D cells grown and differentiated in our laboratory express DA
phenotypic markers after differentiation, IHC was performed to stain for TH, DAT, and
UCH-L1. Fig. 4.1 shows a phase contrast bright field image of differentiated MN9D cells
as well as MN9D cells stained for TH, DAT, and UCH-L1. It is critical for differentiated
MN9D cells to express DAT because it is the avenue through which the neurotoxicant
MPP+ can gain access to the cell and cause oxidative damage (Dauer and Przedborski,
2003). In addition, in order to use these cells as a model for NSDA neurons in vitro, they
also need to highly express UCH-L1. These results confirmed expression of these
proteins.
Next, MN9D cell cultures were treated with the neurotoxicant MPP+ to determine a
concentration dependent response with respect to depletion of DA levels. In Fig. 4.2,
incremental concentrations of MPP+ cause a corresponding increased loss of
intracellular DA content from MN9D cells at 2 h and 8 h, showing that the effects of
MPP+ in MN9D cells mirrors the effects of MPTP in mice. The lowest concentration of
MPP+ had no effect at 2 h, whereas the higher concentration did have an effect on

92

intracellular DA. Next, DA and DOPAC were measured in MN9D cells exposed to 100
µM MPP+ (Fig. 4.3). This decrease in intracellular DA was accompanied by a
concurrent decrease in UCH-L1 protein (Fig. 4.4) showing that MN9D cells closely
model the decrease in UCH-L1 protein in the NSDA neurons after neurotoxicant
treatment (Benskey et al., 2012) (Fig. 3.11). When UCH-L1 hydrolase activity was
analyzed, it was found that MPP+ does not appear to directly inhibit UCH-L1 activity in
MN9D cells (Fig. 4.5). Next, we sought to treat MN9D cells with the UCH-L1 inhibitor,
LDN-57444 (LDN) (Liu et al., 2003). We wanted to understand the effects of direct
inhibition of UCH-L1 would have on an in vitro model of NSDA neurons. When we
treated MN9D cells with MPP+, varying concentrations of LDN, and MPP+ + LDN, we
found that intracellular DA was decreased in MPP+, 5 µM LDN, and MPP+ + LDN
treatment groups (Fig. 4.6). These results point to potential toxicity of LDN or
impairment of UCH-L1 hydrolase activity on MN9D cells that cause perturbations of the
DA phenotype of the cells. The main metabolite of recaptured DA, DOPAC, however,
was not decreased with LDN treatment alone. DA was decreased only in the MPP +
treated and the MPP+ + LDN treated groups.

93

Figure 4.1. Images of differentiated MN9D cells: phase contrast (top left), TH (top
right), DAT (bottom left) and UCH-L1 (bottom right). MN9D cells were grown and
differentiated on glass coverslips coated with PDL and stained for TH, DAT, and UCH-L1.
Images were captured via an Olympus FV1000 confocal microscope.

94

Figure 4.2. DA content in MN9D cells exposed to various concentrations of
+
MPP at 2 and 8 h. Differentiated MN9D cells were grown on PDL-coated plates
+
and exposed to varying concentrations of MPP for 2 or 8 h (n=6 each group). Data
is plotted as mean + SEM and asterisk (*) indicates a significant difference from VH
control where p < 0.05 via one-way ANOVA and post hoc Holm-Sidak test.

95

Figure 4.3. DA and DOPAC concentrations in MN9D cells exposed to 100 µM
+
+
MPP for 2 h. Differentiated MN9D cells were treated with 100 µM MPP for 2 h and
collected for HPLC-ED analysis of DA and DOPAC (n=6 each group). Data is plotted
as mean + SEM and asterisk (*) indicates a statistically significant difference from
VH where p < 0.05 via t-test. The term “n.d.” indicates that DOPAC content was not
detectable.

96

Figure 4.4. UCH-L1 expression in MN9D cells exposed to various
+
concentrations of MPP at 2 h (left) and 8 h (right). Cells were differentiated
and treated with varying concentrations of MPP+ for 2 h and 8 h (n=6 each group).
UCH-L1 expression was measured via Western blot. Data is plotted as mean +
SEM and asterisk (*) indicates a statistically significant difference from VH control
where p < 0.05 via one-way ANOVA and post hoc Holm-Sidak test.

97

+

Figure 4.5. UCH-L1 hydrolase activity in MN9D cells 2 h after 100 µM MPP
+
exposure. Cells were differentiated and treated with 100 µM MPP and hydrolase
activity was measured (n=6). Data is plotted as mean + SEM and no statistically
significant differences between groups was detected (p > 0.05) via t-test.

98

+

Figure 4.6. DA (left) and DOPAC (right) in MN9D cells treated with MPP , LDN57444, or a combination for 2 h. Differentiated cells were treated with 100 µM
+
MPP , various concentrations of the UCH-L1 inhibitor LDN-57444, or a combination
+
of MPP and LDN (n=6 each group). DA and DOPAC were measured via HPLC-ED.
Data is expressed as mean + SEM and asterisk (*) indicates a statistically significant
difference between groups and VH control where p < 0.05 via one-way ANOVA and
a post hoc Holm-Sidak test.

99

Therefore, DA release was likely not affected by LDN treatment in MN9D cells even
though DA stores pools were depleted. The DOPAC/DA ratio was decreased with MPP+
treatment, but increased with LDN treatment (Fig. 4.7). LDN appears to have an effect
on DA homeostasis in MN9D cells that is distinct from effects of MPP+. Whether this
decrease in DA occurs specifically due to UCH-L1 inhibition is not known, since we did
not measure UCH-L1 function after exposure to LDN. Another possibility is that LDN is
having a non-specific effect on DA homeostasis, though the drug itself does not
decrease cell viability.
Since UCH-L1 is a DUB and is hypothesized to function within the UPS, the proteasome
inhibitor bortezomib (BZ) was used along with the autophagy inducer chloroquine (CQ)
to examine effects of major direct perturbations of the UPS and ALP on MN9D cells as
compared with inhibition of UCH-L1 hydrolase activity (Fig. 4.8). Although LDN
treatment did not alter intracellular DA concentrations in this experiment, the UPS
inhibitor BZ and the ALP inducer CQ caused a decrease in intracellular DA. None of
these inhibitors produced any changes in TH (Fig. 4.9), suggesting that a decrease in
availability of the key enzyme required for DA synthesis is not responsible for the
decrease in DA stores in these cells. The cytotoxicity profile of these inhibitors in MN9D
cells is not readily available in the literature, so we performed a cytotoxicity assay to
determine if these concentrations of inhibitors are toxic to MN9D cells. In fact, no other
groups have examined dynamics of the UPS or ALP in MN9D cells.

100

+

Figure 4.7. DOPAC/DA ratio in MN9D cells treated with MPP , LDN-57444, or
+
a combination for 2 h. Differentiated cells were treated with 100 µM MPP ,
various concentrations of the UCH-L1 inhibitor LDN-57444, or a combination of
+
MPP and LDN (n=6 each group). DA and DOPAC were measured via HPLC-ED
and the ratio between the two was calculated. Data is expressed as mean + SEM
and asterisk (*) indicates a statistically significant difference between groups and
VH control where p < 0.05 via one-way ANOVA and a post hoc Holm-Sidak test.

101

Figure 4.8. DA concentration in MN9D cells exposed to various inhibitors for
+
2 h. Differentiated cells were treated with 100 µM MPP , 5 µM LDN, 10 µM CQ,
100 nM BZ, and a combination of LDN + BZ (n=6 each group). DA and DOPAC
were measured via HPLC-ED and the ratio between the two was calculated. Data
is expressed as mean + SEM and asterisk (*) indicates a statistically significant
difference between groups and VH control where p < 0.05 via one-way ANOVA
and a post hoc Holm-Sidak test.

102

Figure 4.9. TH protein in MN9D cells exposed to various inhibitors for 2
+
h. Differentiated cells were treated with 100 µM MPP , 5 µM LDN, 10 µM
CQ, 100 nM BZ, and a combination of LDN + BZ (n=6 each group). TH
protein was measured via western blot. Data is expressed as mean + SEM
and asterisk (*) indicates a statistically significant difference between groups
and VH control where p < 0.05 via one-way ANOVA and a post hoc HolmSidak test.

103

In Fig. 4.10, we show that none of the inhibitors assayed previously caused cytotoxicity
at these doses in differentiated MN9D cells. Since CQ is an autophagy inducer, we
sought to measure target engagement of the drug by measuring the levels of
microtubule-associated protein 1 light chain 3 B-II (LC3B-II), a protein that is required
for autophagic degradation of substrates via the ALP. Indeed, CQ treatment caused an
increase in expression of LC3B-II (Fig. 4.11), which is conjugated to
phosphatidylethanolamine from LC3B-I and associates closely with the autophagosome
membrane, making it a good indication of the number of autophagosomes (Barth et al.,
2010).
These experiments show that MN9D cells replicate the results seen in mouse NSDA
neurons with respect to loss of DA after neurotoxicant treatment and loss of UCH-L1
expression. In addition, we have examined the effects of UCH-L1 and UPS inhibitors
and an autophagy inducer on DA concentration and phenotype without causing
cytotoxic effects.
Effects of MPTP UCH-L3 and USP14 in NSDA neurons in vivo
Although UCH-L1 is the most highly expressed DUB in the nervous system (Lowe et al.,
1990) other DUBs have similar functions with respect to recycling of mono-Ub within the
UPS (Fig. 4.12). UCH-L3 has a structure very similar to UCH-L3 and is >50%
homologous (Kurihara et al., 2001). USP14, on the other hand, is associated with the
26S proteasome and belongs to a different family than the DUB enzymes Loss of
USP14 function has also been linked to neurodegenerative phenotype (the ataxia
mouse) (Walters et al., 2008). The function of these other DUBs includes maintaining

104

the pool of free mono-Ub, so we sought to determine if these other DUBs are altered
after MPTP exposure in mice. In Figs. 4.13 and 4.14, both UCH-L3 and USP-14
(respectively) are expressed in TH SN NSDA neurons. After MPTP treatment protein
levels of UCH-L3 (Fig. 4.15) and USP14 (Fig. 4.16) were not altered in the SN,
suggesting that the decrease in mono-Ub observed after MPTP is likely related to the
decrease in UCH-L1 rather than UCH-L3 or USP14. These results confirm that UCH-L1
is the correct DUB to examine in the context of neurotoxicant-induced damage to NSDA
neurons.

105

Figure 4.10. Cytotoxicity profile of MN9D cells exposed to various inhibitors for 2 h.
+
Differentiated cells were treated with 100 µM MPP , 5 and 10 µM LDN, 50 and 100 nM
BZ, and 5 and 10 µM TCID (a UCH-L3 inhibitor) (n=6). A neutral red assay was performed
to determine if the concentrations of compounds caused significant cytotoxicity, where 1%
triton-x100 was used as a positive control. Data is plotted as mean + SEM. No significant
difference between compounds and VH control were detected (p > 0.05) via one-way
ANOVA.

106

Figure 4.11. LC3B-II protein in MN9D cells exposed to various inhibitors for 2
+
h. Differentiated cells were treated with 100 µM MPP , 5 µM LDN, MPP+ + LDN,10
µM CQ, 100 nM BZ, and LDN + BZ (n=6 each group). LC3B-II protein was
measured via western blot. Data is plotted as mean + SEM and asterisk (*) indicates
a statistically significant difference where p < 0.05 via one-way ANOVA and a post
hoc Holm-Sidak test.

107

Effects of MPTP on UCH-L1 expression in NSDA axon terminals
Thus far, expression of UCH-L1 has been measured in tissue microdissections from the
ST and SN of mice. However, a caveat of measuring protein expression from
microdissected ST tissue is that other cell types are present in the sample, so it may be
erroneous to infer specific changes occurring in NSDA axon terminals. One method to
isolate axon terminals is to produce synaptosomes (Dunkley et al., 2008), which are
pinched off axon terminals made by homogenizing tissue and using sucrose to allow the
membrane to fold, making a spherical shape and preserving terminal constituents
within. UCH-L1 and mono-Ub expression were measured in ST synaptosomes at
various times after in vivo MPTP injection (Fig. 4.17). UCH-L1 protein in ST
synaptosomes is decreased after 6 h and appears to recover by 24 h post MPTP
treatment. Similarly, mono-Ub protein levels closely follows that of UCH-L1 and the

108

Figure 4.12. Diagram showing three relevant DUBs in the context of mono-Ub
recycling: UCH-L1, UCH-L3, and USP14. UCH-L1 and UCH-L3 have very similar
functions, but UCH-L3 has not been demonstrated to bind and sequester mono-Ub,
which is the main difference between the proposed function of the two closely-related
DUBs. USP14, on the other hand, is closely associated with the 26S proteasome and
can remove Ub from substrates destined for proteasomal degradation.

109

Figure 4.13. UCH-L3 staining in TH neurons in the SN of mice. 20 µm thick mouse brain
sections were stained for TH and UCH-L3 and images were captured via epifluorescence
microscopy. Overlays for TH + UCH-L3 and a triple overlay including the nuclear stain DAPI
were generated.

110

Figure 4.14. USP14 staining in TH neurons in the SN of mice. 20 µm thick mouse brain sections were
stained for TH and USP14 and images were captured via epifluorescence microscopy. Overlays for TH +
USP14 and a triple overlay including the nuclear stain DAPI were generated.

111

Figure 4.15. UCH-L3 levels in the mouse SN 24 h after MPTP exposure. Mice
were treated with VH or acute MPTP and sacrificed 24 h later (n=10 each group).
Brains were removed and analyzed via western blot for UCH-L3 expression in the
SN. No statistically significant difference between groups was detected (p > 0.05) via
t-test.

112

Figure 4.16. USP14 levels in the mouse SN 24 h after MPTP exposure. Mice
were treated with VH or acute MPTP and sacrificed 24 h later (n=10 each group).
Brains were removed and analyzed via western blot for USP14 expression in the
SN. No statistically significant difference between groups was detected (p > 0.05)
via t-test.

113

Figure 4.17. UCH-L1 (left) and mono-Ub (right) protein levels in ST
synaptosomes various time points after acute MPTP exposure. Mice were killed
4, 6, 8, 12, or 24 h after a single injection of MPTP (n=10 each group). Levels of
UCH-L1 and mono-Ub were measured via western blot. Data is plotted as mean ±
SEM and asterisk (*) indicates a statistically significant difference between points
connected by lines where p < 0.05 via one-way ANOVA and a post hoc Holm-Sidak
test.

114

Figure 4.18. Pearson correlation analysis of UCH-L1 and mono-Ub
levels after acute MPTP exposure. Protein expression levels of UCHL1 and mono-Ub determined by western blotting were plotted on the x
and y axis and a correlation analysis was performed.

115

expression profiles of UCH-L1 and mono-Ub after acute MPTP are well correlated (Fig.
4.18).
Relationship between UCH-L1 and parkin
Since both UCH-L1 and parkin operate in the context of the UPS, it is conceivable that
these enzymes interact and potentially oppose each other’s actions since deubiquitination and ubiquitination are reverse processes. Indeed, it was demonstrated
that parkin can add poly-Ub to UCH-L1 via a K63-linked chain to target UCH-L1
degradation via autophagy (McKeon et al., 2014), suggesting that parkin may regulate
UCH-L1 expression and activity to promote 26S proteasome function. This proposed
mechanism to decrease UCH-L1 in cases where the neuron requires increased protein
degradation via the 26S proteasome could be an attempt at compensation under
conditions of oxidative stress, as UCH-L1 has been shown to decrease in the SN of
mice treated with MPTP (Benskey et al., 2012) (Fig. 3.11). On the other hand, in parkindeficient (Park2-/-) mice, UCH-L1 is not decreased in the SN (Fig. 4.19), pointing to the
fact that the decrease in UCH-L1 protein in the SN of WT mice may be parkin
dependent. In addition, Fig. 4.20 shows that under basal conditions, UCH-L1 in
elevated in the SN of Park2-/- mice. However, elevated levels of UCH-L1 in the SN did
not correspond to elevated levels of mono-Ub in Park2-/- mice (Fig. 4.21). These data
suggest that parkin may cause the decrease in UCH-L1 expression in conditions of
oxidative stress to promote 26S function, but that the levels of mono-Ub are not affected
in mice lacking parkin.

116

Figure 4.19. UCH-L1 protein expression in the SN of WT (black) and
-/Park2 (red) mice various points after single injection of MPTP. WT and
-/Park2 mice were injected with MPTP and sacrificed at various time points
(n=10 each group). Brains were sectioned and the SN was analyzed for
UCH-L1 expression via western blotting. Data is plotted as mean ± SEM
and asterisk (*) indicates a difference from VH control where p < 0.05 via
one-way ANOVA and a post hoc Holm-Sidak test.

117

-/-

Figure 4.20. UCH-L1 protein expression in the SN of WT (white) and Park2
-/(red) mice. WT and Park2 mice were sacrificed and brains were sectioned (n=10
each group). The SN was analyzed for UCH-L1 expression via western blotting.
Data is plotted as mean + SEM and asterisk (*) indicates a difference from WT SN
where p < 0.05 via t-test.

118

-/-

Figure 4.21. Mono-Ub protein expression in the SN of WT (white) and Park2
-/(red) mice. WT and Park2 mice were sacrificed and brains were sectioned (n=10
each group). The SN was analyzed for mono-Ub expression via western blotting.
Data is plotted as mean + SEM and no statistically significant differences were
detected between genotypes (p > 0.05) via t-test.

119

Figure 4.22. K48-linked ubiquitinated proteins in the SN of WT (white)
-/-/and Park2 (red) mice exposed to MPTP. WT and Park2 mice were
injected with MPTP and sacrificed 24 h later (n=10 each group). Brains were
sectioned and the SN was analyzed for K48-linked Ub-proteins via western
blotting. Data is plotted as mean + SEM and no statistically significant
differences were detected between genotypes (p > 0.05) via two-way ANOVA.

120

In the case of a toxic insult to the SN, with exposure to a neurotoxicant such as MPTP
(Langston et al., 1983) substrates and toxic proteins may overwhelm the UPS,
especially in the absence of functional parkin. In WT and Park2-/- mice exposed to
MPTP, levels of K48-linked proteins were not elevated (Fig. 4.22), suggesting that there
is likely no critical accumulation of Ub-substrates. However, minor perturbations in UPS
function are not likely to be measurable using this method, so perhaps 26S function is
still compromised in Park2-/- mice. We next investigated whether the ALP could be
upregulated in Park2-/- mice by measuring LC3B-II in the ST at various times after
MPTP treatment (Fig. 4.23). Park2-/- mice have more LC3B-II in ST synaptosomes
compared to WT under basal conditions, indicating the presence of more
autophagosomes. By 2 h after MPTP exposure LC3B-II expression was decreased to
that seen in WT mice, and this effect persisted for at least 24 h. However, increased
expression of LC3B-II could mean two very different things: either that the ALP is
induced, thereby creating more autophagosomes, or than the ALP is inhibited, and that
the autophagosomes do not break down properly and accumulate.
To distinguish between these possibilities, an important substrate of the ALP,
sequestome 1 (also known as p62), was measured to determine if inhibition of the ALP
occurs in the SN of Park2-/- mice since p62 accumulates when the ALP is inhibited
(Barth et al., 2010) (Fig. 4.24). Since p62 protein was not accumulated, we interpret this
result to mean that the ALP is not inhibited in Park2-/- mice and is likely upregulated. We
took this analysis further and looked over time after MPTP to ensure that the ALP was
not inhibited in ST synaptosomes (Fig. 4.25) and found that p62 expression in WT and
Park2-/- was constant over the time course measured. Finally, to give us an idea of
121

Figure 4.23. LC3B-II protein levels in ST synaptosomes between WT (black)
-/and Park2 (red) mice at various time points after MPTP injection. Mice were
injected with MPTP and killed at various time points after MPTP (n=10 each
group). Brains were removed and ST synaptosomes collected and analyzed for
LC3B-II expression via western blotting. Data is plotted as mean ± SEM and
asterisk (*) indicates statistically significant difference from WT VH where p < 0.05
via one-way ANOVA and a post hoc Holm-Sidak test.

122

Figure 4.24. p62 protein levels in the SN between WT (black) and Park2-/(red) mice 24 h after MPTP injection. Mice were injected with MPTP and killed at
24 h after MPTP (n=10 each group). Brains were removed and SN collected and
analyzed for p62 expression via western blotting. Data is plotted as mean + SEM
and no statistically significant differences were detected between genotypes and
drug treatment (p > 0.05) via two-way ANOVA.

123

Figure 4.25. p62 protein levels in ST synaptosomes between WT (black) and
Park2-/- (red) mice at various time points after MPTP injection. Mice were injected
with MPTP and killed at various time points after MPTP (n=10 each group). Brains were
removed and ST synaptosomes collected and analyzed for p62 expression via western
blotting. Data is plotted as mean ± SEM and no significant differences between groups
were detected (p > 0.05) via one-way ANOVA.

124

Figure 4.26. hsc70 protein levels in the SN between WT (black) and Park2-/(red) mice 24 h after MPTP injection. Mice were injected with MPTP and killed at 24
h after MPTP (n=10 each group). Brains were removed and SN collected and
analyzed for hsc70 expression via western blotting. Data is plotted as mean + SEM
and no statistically significant differences were detected between genotypes and drug
treatment (p > 0.05) via two-way ANOVA.

125

which arm of the ALP (CMA or macroautophagy) could be upregulated, we measured
hsc70, which is a vital chaperone used in CMA (Cuervo and Wong, 2014) (Fig. 4.26).
No differences in hsc70 expression between genotypes or neurotoxicant treatment were
found, suggesting that CMA is not the type of autophagy upregulated in Park2-/- mice.
Rather, it appears that macroautophagy is induced in Park2-/- mice, which could be a
key factor to why these mice do not have any overt neurodegenerative phenotype.

Discussion

MN9D cells were used to model NSDA neurons in vitro, with special relevance to UCHL1 expression after neurotoxicant exposure. MN9D cells express TH and DAT, which
are required for sensitivity to MPP+ exposure (Choi et al., 1999). Many analyses can be
performed on MN9D cells before attempting an in vivo study with rodents such as
treatment with the UCH-L1 inhibitor, LDN. Inhibition of UCH-L1 activity with LDN in
MN9D cells decreased DA concentration, though this effect was not repeated
consistently between experiments. However, treatment with LDN was not cytotoxic at
the concentrations used. Further study with the inhibitor in vivo may yield more
reproducible and relevant results. Studies employing LDN in vivo are described in
Chapter 6 of this Dissertation.
Although the MN9D cell line is among the most useful and relevant in vitro models for
murine ventral midbrain toxicity, it has a few inherent disadvantages. First, the cell line
is not commercially available and is nigh impossible to acquire, which also could mean
that each batch of MN9D cells distributed to collaborators are different. Second, the cell
126

line is a fusion of neuroblastoma cells and murine ventral midbrain DA neurons, which
means that it possesses qualities of each cell type. The neuroblastoma phenotype may
make the cell line likely to respond differently to toxic insult compared to in vivo DA
neurons. Third, the cell line is derived from murine cells, which may be quite different
from human NSDA neurons, considering that mice do not naturally develop PD. Despite
these caveats, MN9D cells are a decent model for NSDA neurons especially in their
response to neurotoxicant exposure and their use has contributed to the existing
evidence that a decrease in UCH-L1 expression accompanies oxidative stress in NSDA
neurons.
For the first time, UCH-L1 and mono-Ub protein were measured in ST synaptosomes,
which are isolated axon terminals of NSDA neurons. Although UCH-L1 is decreased in
the SN 24 h after MPTP (Fig 3.11), UCH-L1 is not decreased in ST synaptosomes 24 h
after MPTP. The fact that UCH-L1 appears to recover at 24 h in ST synaptosomes but
is decreased in the SN brings up a question about potential transport of UCH-L1 from its
synthesis site in the cell body region to the axon terminals, as if in an attempt to
compensate during injury. No information on how UCH-L1 is transported from the cell
body to the axon terminal is available in the literature, but it is reasonable to
hypothesize that UCH-L1 could be transported from the SN to the ST at an accelerated
rate in response to neurotoxic insult. Although purely conjecture at this point, it appears
that such efforts of NSDA neurons challenged with MPTP are futile and maintaining
UCH-L1 protein to the ST may not be sufficient to protect against toxicity. Therefore, a
better approach would be to pharmacologically inhibit UCH-L1 hydrolase activity in
MLDA neurons to determine if UCH-L1 is the factor that protects non-susceptible
127

neurons from injury. The results from using the UCH-L1 inhibitor LDN in vivo are
presented in Chapter 6.
A possible interaction between two UPS-related genes mutated in familial PD, UCH-L1
and parkin, was explored. A previous report in the literature suggested that parkin
activity causes degradation of UCH-L1 (McKeon et al., 2014), so we sought to explain
the functional consequences of absence of parkin in the context of this interaction.
UCH-L1 is not decreased in the SN of parkin deficient mice, suggesting that that parkin
may be important (and perhaps even necessary) for regulating UCH-L1 in the context of
MPTP-induced injury. In parkin deficient mice, UCH-L1 and macroautophagy are
upregulated in the SN, consistent with the hypothesis that dysregulation of the UPS in
the absence of parkin may be compensated for by upregulation of the ALP. Notably,
CMA, a specific type of autophagy, was not upregulated in parkin deficient mice.
Rather, it appears that macroautophagy, the ALP mechanism with less substrate
specificity than CMA, could be more useful for compensating for reduced UPS activity.
It is important to not only consider the UPS but also the ALP when examining pathways
mediating protein degradation, so this chapter also sought to understand the interplay of
these proteins in the context of autophagic protein degradation. The role of UCH-L1 in
the ALP is less clear and has not been fully studied, but if UCH-L1 removes Ub from
substrates to promote autophagic degradation in the face of UPS impairment, increased
UCH-L1 expression could be part of the mechanism by which Park2-/- mice compensate
for lack of parkin and consequentially, avoid a detrimental phenotype resembling
humans with mutated parkin.

128

Summary and conclusions
Taken together, these studies provide evidence for a unique role for UCH-L1 in
potentially mediating autophagic degradation of substrates in the absence of parkin, and
a hypothesis for how Park2-/- mice compensate for reduced UPS activity.

129

REFERENCES

130

REFERENCES

Anglade, P., Vyas, S., Javoy-Agid, F., Herrero, M.T., Michel, P.P., Marquez, J., MouattPrigent, A., Ruberg, M., Hirsch, E.C., Agid, Y., 1997. Apoptosis and autophagy in
nigral neurons of patients with Parkinson’s disease. Histol. Histopathol. 12, 25–31.
Baba, M., Nakajo, S., Tu, P.H., Tomita, T., Nakaya, K., Lee, V.M., Trojanowski, J.Q.,
Iwatsubo, T., 1998. Aggregation of alpha-synuclein in Lewy bodies of sporadic
Parkinson’s disease and dementia with Lewy bodies. Am. J. Pathol. 152, 879–84.
Bandyopadhyay, U., Kaushik, S., Varticovski, L., Cuervo, A.M., 2008. The chaperonemediated autophagy receptor organizes in dynamic protein complexes at the
lysosomal membrane. Mol. Cell. Biol. 28, 5747–63. doi:10.1128/MCB.02070-07
Barth, S., Glick, D., Macleod, K.F., 2010. Autophagy: assays and artifacts. J. Pathol.
221, 117–24. doi:10.1002/path.2694
Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Choi, H.K., Won, L. a, Kontur, P.J., Hammond, D.N., Fox, a P., Wainer, B.H.,
Hoffmann, P.C., Heller, a, 1991. Immortalization of embryonic mesencephalic
dopaminergic neurons by somatic cell fusion. Brain Res. 552, 67–76.
doi:10.1016/0006-8993(91)90661-E
Choi, H.K., Won, L., Roback, J.D., Wainer, B.H., Heller, A., 1992. Specific modulation of
dopamine expression in neuronal hybrid cells by primary cells from different brain
regions. Proc. Natl. Acad. Sci. 89, 8943–8947. doi:10.1073/pnas.89.19.8943
Choi, W.-S., Canzoniero, L.M.T., Sensi, S.L., O’Malley, K.L., Gwag, B.J., Sohn, S., Kim,
J.-E., Oh, T.H., Lee, E.B., Oh, Y.J., 1999. Characterization of MPP+-Induced Cell
Death in a Dopaminergic Neuronal Cell Line: Role of Macromolecule Synthesis,
Cytosolic Calcium, Caspase, and Bcl-2-Related Proteins. Exp. Neurol. 159, 274–
282. doi:10.1006/exnr.1999.7133
Cuervo, A.M., Stefanis, L., Fredenburg, R., Lansbury, P.T., Sulzer, D., 2004. Impaired
degradation of mutant alpha-synuclein by chaperone-mediated autophagy. Science
305, 1292–5. doi:10.1126/science.1101738
Cuervo, A.M., Wong, E., 2014. Chaperone-mediated autophagy: roles in disease and
aging. Cell Res. 24, 92–104. doi:10.1038/cr.2013.153
131

Dauer, W., Przedborski, S., 2003. Parkinson ’ s Disease : Mechanisms and Models 39,
889–909.
Davies, K.J.A., 2001. Degradation of oxidized proteins by the 20S proteasome.
Biochimie 83, 301–310. doi:10.1016/S0300-9084(01)01250-0
Dunkley, P.R., Jarvie, P.E., Robinson, P.J., 2008. A rapid Percoll gradient procedure for
preparation of synaptosomes. Nat. Protoc. 3, 1718–1728.
doi:10.1038/nprot.2008.171
Goldberg, M.S., Fleming, S.M., Palacino, J.J., Cepeda, C., Lam, H. a., Bhatnagar, A.,
Meloni, E.G., Wu, N., Ackerson, L.C., Klapstein, G.J., Gajendiran, M., Roth, B.L.,
Chesselet, M.F., Maidment, N.T., Levine, M.S., Shen, J., 2003. Parkin-deficient
Mice Exhibit Nigrostriatal Deficits but not Loss of Dopaminergic Neurons. J. Biol.
Chem. 278, 43628–43635. doi:10.1074/jbc.M308947200
Kitada, T., Asakawa, S., Hattori, N., Matsumine, H., Yamamura, Y., Minoshima, S.,
Yokochi, M., Mizuno, Y., Shimizu, N., 1998. Mutations in the parkin gene cause
autosomal recessive juvenile parkinsonism. Nature 392, 605–8. doi:10.1038/33416
Kurihara, L.J., Kikuchi, T., Wada, K., Tilghman, S.M., 2001. Loss of Uch-L1 and Uch-L3
leads to neurodegeneration, posterior paralysis and dysphagia. Hum. Mol. Genet.
10, 1963–70.
Langston, J., Ballard, P., Tetrud, J., Irwin, I., 1983. Chronic Parkinsonism in humans
due to a product of meperidine-analog synthesis. Science (80-. ). 219, 979–980.
doi:10.1126/science.6823561
Lansdell, T., 2017. THE ROLE OF PARKIN IN MAINTAINING PROTEASOME
ACTIVITY FOLLOWING NEUROTOXICANT EXPOSURE (Dissertation).
Liu, Y., Lashuel, H.A., Choi, S., Xing, X., Case, A., Ni, J., Yeh, L.A., Cuny, G.D., Stein,
R.L., Lansbury, P.T., 2003. Discovery of inhibitors that elucidate the role of UCH-L1
activity in the H1299 lung cancer cell line. Chem. Biol. 10, 837–846.
doi:10.1016/j.chembiol.2003.08.010
Lowe, J., McDermott, H., Landon, M., Mayer, R.J., Wilkinson, K.D., 1990. Ubiquitin
carboxyl-terminal hydrolase (PGP 9.5) is selectively present in ubiquitinated
inclusion bodies characteristic of human neurodegenerative diseases. J. Pathol.
161, 153–160. doi:10.1002/path.1711610210
McKeon, J.E., Sha, D., Li, L., Chin, L.-S., 2014. Parkin-mediated K63-polyubiquitination
targets ubiquitin C-terminal hydrolase L1 for degradation by the autophagylysosome system. Cell. Mol. Life Sci. doi:10.1007/s00018-014-1781-2
Meredith, G.E., Halliday, G.M., Totterdell, S., 2004. A critical review of the development
and importance of proteinaceous aggregates in animal models of Parkinson’s
disease: new insights into Lewy body formation. Parkinsonism Relat. Disord. 10,
191–202. doi:10.1016/j.parkreldis.2004.01.001
132

Narendra, D., Tanaka, A., Suen, D.-F., Youle, R.J., 2008. Parkin is recruited selectively
to impaired mitochondria and promotes their autophagy. J. Cell Biol. 183, 795–803.
doi:10.1083/jcb.200809125
Olzmann, J.A., Chin, L.-S., 2008. Parkin-mediated K63-linked polyubiquitination: a
signal for targeting misfolded proteins to the aggresome-autophagy pathway.
Autophagy 4, 85–7.
Perez, F.A., Palmiter, R.D., 2005. Parkin-deficient mice are not a robust model of
parkinsonism. Proc. Natl. Acad. Sci. U. S. A. 102, 2174–9.
doi:10.1073/pnas.0409598102
Pickrell, A.M., Huang, C.-H., Kennedy, S.R., Ordureau, A., Sideris, D.P., Hoekstra, J.G.,
Harper, J.W., Youle, R.J., 2015. Endogenous Parkin Preserves Dopaminergic
Substantia Nigral Neurons following Mitochondrial DNA Mutagenic Stress. Neuron
87, 371–381. doi:10.1016/j.neuron.2015.06.034
Ross, C.A., Poirier, M.A., 2004. Protein aggregation and neurodegenerative disease.
Ross, C. a., Pickart, C.M., 2004. The ubiquitin-proteasome pathway in Parkinson’s
disease and other neurodegenerative diseases. Trends Cell Biol. 14, 703–711.
doi:10.1016/j.tcb.2004.10.006
Ross, J.M., Olson, L., Coppotelli, G., 2015. Mitochondrial and Ubiquitin Proteasome
System Dysfunction in Ageing and Disease: Two Sides of the Same Coin? Int. J.
Mol. Sci. 16, 19458–76. doi:10.3390/ijms160819458
Shimura, H., Hattori, N., Kubo, S.I., Mizuno, Y., Asakawa, S., Minoshima, S., Shimizu,
N., Iwai, K., Chiba, T., Tanaka, K., Suzuki, T., 2000. Familial Parkinson disease
gene product, parkin, is a ubiquitin-protein ligase. Nat. Genet. 25, 302–305.
doi:10.1038/77060
Spillantini, M.G., Schmidt, M.L., Lee, V.M.-Y., Trojanowski, J.Q., Jakes, R., Goedert, M.,
1997. [alpha]-Synuclein in Lewy bodies 388, 839–840.
Thrower, J.S., Hoffman, L., Rechsteiner, M., Pickart, C.M., 2000. Recognition of the
polyubiquitin proteolytic signal. EMBO J. 19, 94–102. doi:10.1093/emboj/19.1.94
Um, J.W., Im, E., Lee, H.J., Min, B., Yoo, L., Yoo, J., Lübbert, H., Stichel-Gunkel, C.,
Cho, H.-S., Yoon, J.B., Chung, K.C., 2010. Parkin directly modulates 26S
proteasome activity. J. Neurosci. 30, 11805–14. doi:10.1523/JNEUROSCI.286209.2010
Walters, B.J., Campbell, S.L., Chen, P.C., Taylor, A.P., Schroeder, D.G., Dobrunz, L.E.,
Artavanis-Tsakonas, K., Ploegh, H.L., Wilson, J.A., Cox, G.A., Wilson, S.M., 2008.
Differential effects of Usp14 and Uch-L1 on the ubiquitin proteasome system and
synaptic activity. Mol. Cell. Neurosci. 39, 539–48. doi:10.1016/j.mcn.2008.07.028

133

Chapter 5: Effects of Inhibition of UCH-L1 on Susceptibility of NSDA and MLDA
Neurons to Neurotoxicant Exposure
Introduction
MLDA neurons are resistant to cell death in PD while NSDA neurons progressively
degenerate (Braak and Braak, 2000). The differential susceptibility between NSDA and
MLDA neurons can be recapitulated using the neurotoxicant MPTP (Behrouz et al.,
2007; Hung and Lee, 1998) (Figs. 3.4-3.6). To understand which pathways could be
protective in MDLA neurons and impaired in NSDA neurons, we examined the UPSrelated DUB, UCH-L1, which has been found to be mutated in familial PD (Leroy et al.,
1998). UCH-L1 is decreased in the SN 24 h after MPTP exposure while UCH-L1 is
maintained in the SN 24 h after MPTP exposure (Figs. 3.11 and 3.12). Since
maintenance of UCH-L1 protein expression is hypothesized to protect MLDA neurons
from neurotoxic injury, while loss of UCH-L1 expression contributes to vulnerability of
NSDA neurons, this idea implies that UCH-L1 hydrolase activity may provide a
protective function against neurotoxicity.
One way to influence UCH-L1 hydrolase activity without changing the amount of UCHL1 protein is to use a pharmacological inhibitor of UCH-L1. An inhibitor of UCH-L1 was
developed for the purpose of studying the role of UCH-L1 hydrolase activity in cancer
cell lines (Liu et al., 2003). UCH-L1 is neuron specific but has been found to be
ectopically expressed in some cancers and cancer-derived cell lines (Hurst-Kennedy et
al., 2012). The most potent inhibitor discovered in the study, LDN-57444, is an isatin
oxime compound that binds competitively and reversibly and targets the active site of

134

UCH-L1. Importantly, LDN-57444 shows a 28-fold higher specificity for UCH-L1 over its
closely related DUB UCH-L3 (Liu et al., 2003), which is important since the two DUBs
are thought to have distinct but potentially overlapping functions.
Once LDN-57444 became commercially available other groups began using it in
neurodegeneration research, especially with regard to AD and PD. One of the first AD
studies to use LDN-57444 to inhibit UCH-L1 examined synaptic transmission in
hippocampal slices and found that decreasing UCH-L1 impairs function of hippocampal
neurons (Gong et al., 2006). The consequences of LDN-57444 administration were
shown to be UCH-L1-specific since overexpressing UCH-L1 protein rescued the effects
of LDN-57444, demonstrating that UCH-L1 is necessary for synaptic transmission and
cognitive function (Gong et al., 2006). This study also examined UCH-L1 inhibition in
vivo using LDN-57444 and demonstrated reduced contextual learning in mice injected
with the UCH-L1 inhibitor (Gong et al., 2006). Another study showed that UCH-L1
inhibition in hippocampal neurons causes a decrease in synaptic spine density,
concurrent with a depletion of mono-Ub pools (Cartier et al., 2009). This decrease in
spine density translated to deficits in synaptic transmission and long-term potentiation
and strengthened the relationship between UCH-L1 and memory and cognition.
A study with relevance to PD from the same group used LDN-57444 in vivo and
observed that inhibition of UCH-L1 in mice expressing normal amounts of the PD-linked
protein α-syn caused an abnormal accumulation of α-synuclein (Cartier et al., 2012).
However, DA neuron-specific effects of LDN-57444 administration were not explored in
these previous studies. Since maintenance of UCH-L1 expression and function is
hypothesized to protect MLDA neurons from MPTP-induced injury, experiments
135

described in this chapter sought to determine if inhibition of UCH-L1 hydrolase activity
with LDN-57444 renders MLDA neurons more vulnerable to MPTP, and whether
inhibition of UCH-L1 would exacerbate the extent of MPTP-induced injury in NSDA
neurons.
Results
Characterization of effects of LDN-57444 under basal conditions
The compound LDN-57444 proved challenging to work with because it is highly
lipophilic and requires DMSO for its dissolution. On one hand, these physicochemical
properties of LDN-57444 are advantageous because it is predicted that LDN will readily
cross the BBB due to its high lipophilicity (Fig. 5.1) and that some proportion of LDN57444 administered to mice will reach the targeted brain regions. The BOILED egg
diagram modeled from compiled Swiss ADME pharmacokinetics data shows LDN57444 placement within the “yolk”, which signifies that it is predicted to cross the BBB
as plotted against the logP (lipophilicity) on the Y-axis and topological polar surface
area (TPSA) on the X-axis. Since LDN-57444 is highly lipophilic and has a relatively
small TPSA, it is predicted to cross the BBB. The “egg white” of the diagram signifies
human intestinal absorption (HIA). LDN-57444 is predicted to not be a substrate for pglycoprotein (PGP) present on the BBB, which can actively pump out drugs from the
brain (Daina and Zoete, 2016).
On the other hand, a disadvantage for using LDN-57444 is that DMSO is not a
commonly used vehicle for in vivo studies. DMSO can, however, be used in very small
amounts (i.e., < 100 µL) without substantial toxicity to the mouse (Kelava et al., 2011).

136

Therefore, a pilot study was performed that would examine the effects of DMSO
administration and two previously employed doses of LDN-57444: 0.5 mg/kg (Cartier et
al., 2012) and 5 mg/kg. Mice were injected at time zero and 4 h later mice

137

Figure 5.1. The UCH-L1 inhibitor LDN-57444 is predicted to cross the
blood brain barrier (BBB). Using SwissADME (SwissADME: a free web tool
to evaluate pharmacokinetics, drug-likeness and medicinal chemistry
friendliness of small molecules. Sci. Rep. (2017) 7:42717.) the
physicochemical properties of LDN-57444 were predicted. In particular, the
BOILED-Egg simulation was used to predict blood-brain barrier permeability of
LDN.

138

Figure 5.2. Injection paradigm for LDN dose response study. Mice were
injected with saline VH, DMSO VH, 0.5 mg/kg LDN, or 5 mg/kg LDN at time
point zero. Four h later, mice received a second injection of VH or LDN
identical to the first injection and sacrificed 4 h later.

139

Figure 5.3. DA (left) and DOPAC (right) concentrations in the ST following
saline VH, DMSO VH, 0.5 mg/kg LDN, or 5 mg/kg LDN. Mice received two
injections of LDN and were sacrificed as described in Fig. 5.2 (n=10 each group).
The ST was microdissected from brain tissue and analyzed via HPLC-ED for DA
and DOPAC. Data is plotted as mean + SEM. No significant differences between
groups were detected (p > 0.05) via one-way ANOVA.

140

Figure 5.4. DOPAC/DA ratio in the ST after saline VH, DMSO VH, and 0.5
and 5 mg/kg LDN. Mice received two injections of LDN and were sacrificed as
described in Fig. 5.2. The ST was microdissected from brain tissue and
analyzed via HPLC-ED for DA and DOPAC (n=10 each group). The DOPAC/DA
ratio was calculated. Data is plotted as mean + SEM. No significant differences
between groups were detected (p > 0.05) via one-way ANOVA.

141

Figure 5.5. DA (left) and DOPAC (right) concentrations in the NAc
following saline VH, DMSO VH, 0.5 mg/kg LDN, or 5 mg/kg LDN. Mice
received two injections of LDN and were sacrificed as described in Fig. 5.2.
The NAc was microdissected from brain tissue and analyzed via HPLC-ED for
DA and DOPAC (n=10 each group). Data is plotted as mean + SEM. Asterisk
(*) indicates statistically significant difference from DMSO VH where p < 0.05
via one-way ANOVA and a post hoc Holm-Sidak test.

142

Figure 5.6. DOPAC/DA ratio in the NAc after saline VH, DMSO VH, and
0.5 and 5 mg/kg LDN. Mice received two injections of LDN and were
sacrificed as described in Fig. 5.2. The NAc was microdissected from brain
tissue and analyzed via HPLC-ED for DA and DOPAC (n=10 each group).
The DOPAC/DA ratio was calculated. Data is plotted mean + SEM.
Asterisk (*) indicates a statistically significant difference from DMSO VH
where p < 0.05 via one-way ANOVA and a post hoc Holm-Sidak test.

143

Table 5.1. Mono-Ub and Total Ub proteins in the ST. Mice received two
injections of LDN and were sacrificed as described in Fig. 5.2. The ST was
microdissected from brain tissue and analyzed via western blotting for
mono-Ub and total Ub proteins (n=10 each group). Data (densitometry of
mono-Ub and total Ub compared to GAPDH loading control) is shown as
mean + SEM. No significant difference between groups was detected (p >
0.05) via one-way ANOVA.

144

Table 5.2. Mono-Ub and Total Ub proteins in the NAc. Mice received two
injections of LDN and were sacrificed as described in Fig. 5.2. The NAc was
microdissected from brain tissue and analyzed via western blotting for monoUb and total Ub proteins (n=10 each group). Data (densitometry of mono-Ub
and total Ub compared to GAPDH loading control) is shown as mean + SEM.
No significant difference between groups was detected (p > 0.05) via oneway ANOVA.

145

Table 5.3. Mono-Ub and Total Ub proteins in the SN. Mice received two
injections of LDN and were sacrificed as described in Fig. 5.2. The SN was
microdissected from brain tissue and analyzed via western blotting for monoUb and total Ub proteins (n=10 each group). Data (densitometry of mono-Ub
or total Ub compared to GAPDH loading control) is shown as mean + SEM.
No significant difference between groups was detected (p > 0.05) via oneway ANOVA.

146

Table 5.4. Mono-Ub and Total Ub proteins in the VTA. Mice received two
injections of LDN and were sacrificed as described in Fig. 5.2. The VTA was
microdissected from brain tissue and analyzed via western blotting for mono-Ub
and total Ub proteins (n=10 each group). Data (densitometry of mono-Ub and
total Ub compared to GAPDH loading control) is shown as mean + SEM. No
significant difference between groups was detected (p > 0.05) via one-way
ANOVA.

147

received a second injection. Four h after the second injection mice were sacrificed (Fig.
5.2).
First, potential toxicity to DA neurons was examined, since the inhibitor would not be
useful for future studies if it caused overt injury to DA neurons. As shown in Fig. 5.3, DA
and DOPAC in the ST were not affected by any drug treatments and DMSO did not
have an effect compared to saline VH. Similarly, the DOPAC/DA ratio is not affected by
drug treatments in the ST (Fig. 5.4). In the NAc, DA was not different between drug
treatments, but DOPAC was increased in the 5 mg/kg group (Fig. 5.5). This increase in
DOPAC in the NAc contributed to an increase in the DOPAC/DA ratio (Fig. 5.6)
suggesting increased activity of MLDA neurons in mice treated with 5 mg/kg LDN57444.
After establishing that DMSO and up to 5 mg/kg doses of LDN-57444 are not toxic to
either NSDA or MLDA neurons, we measured target engagement and UPS function by
measuring mono-Ub levels and total Ub conjugated proteins (total Ub). In the ST (Table
5.1), NAc (Table 5.2), SN (Table 5.3) and VTA (Table 5.4) mono-Ub levels or UPS
function were not affected by DMSO or either dose of LDN administration. Fig. 5.7
shows the point at which LDN-57444 is expected to act within the scheme of the UPS,
which is anticipated to decrease levels of available mono-Ub.
Effects of LDN-57444 on susceptibility of NSDA and MLDA neurons to MPTP
Next, the question of whether inhibition of UCH-L1 affects susceptibility to MPTP was
addressed. To do this, early events that occur following MPTP that would be related to
UCH-L1 function were examined (Table 5.5). At time zero, mice received a s.c. injection
148

Figure 5.7. Proposed mechanism of action of the UCH-L1 inhibitor LDN in
the context of UCH-L1 activity and the UPS. LDN is expected to inhibit UCHL1 hydrolase activity, one of the ways in which UCH-L1 is hypothesized to
replenish mono-Ub pools. However, the ability to bind and stabilize mono-Ub
may not be affected by the inhibitor, which could result in no loss of mono-Ub
when LDN is administered.

149

Table 5.5. Injection paradigm for LDN-57444 + MPTP study. Mice were
administered either saline VH or 20 mg/kg MPTP s.c. at time zero.
Immediately after mice were given an injection of either DMSO VH or 0.5
mg/kg LDN-57444 i.p. and 4 h later, mice were given a repeat of the same
drug injected i.p. Four h after the last injection, mice were sacrificed and brain
tissue processed for analyses of DA neurochemistry and protein expression.

Group

Injection 1

Injection 2

DMSO Saline

DMSO +
Saline

DMSO

LDN Saline

LDN + Saline

LDN

DMSO MPTP

DMSO +
MPTP

DMSO

LDN MPTP

LDN + MPTP

LDN

150

of either saline VH or 20 mg/kg MPTP, then immediately after received an i.p. injection
of either DMSO VH or 0.05 mg/kg LDN-57444. Four h later, mice received a second i.p.
injection of DMSO VH or 0.05 mg/kg LDN-57444 and were sacrificed 4 h after the
second injection and 8 h after MPTP. We used the lower dose of LDN to potentially
avoid inhibiting UCH-L3.
Fig. 5.8 shows DA concentrations in the ST. LDN-57444 treatment alone did not have
any effects on DA content in the ST. MPTP administration caused a decrease in DA,
which is expected at the 8 h time point (Behrouz et al., 2007). LDN-57444 blocked the
inhibitory effect of MPTP on ST DA concentrations. This result was recapitulated in the
NAc (Fig. 5.9).
Next, to ensure that any effects of LDN-57444 or MPTP on mono-Ub and UPS activity
are not simply due to decreased levels of UCH-L1 protein, UCH-L1 was measured in
each brain region. In the ST (Table 5.6), NAc (Table 5.7), SN (Table 5.8) and VTA
(Table 5.9) UCH-L1 protein was not affected by LDN-57444, MPTP, or the combination
of LDN-57444 and MPTP. This finding allows us to interpret any further results apart
from changes in UCH-L1 protein expression.
To address the question of target engagement and inhibition of the UPS, mono-Ub
levels and total Ub-proteins were measured via Western blot. In the ST (Table 5.10),
NAc (Table 5.11), SN (Table 5.12), and VTA (Table 5.13) mono-Ub and UPS function
remain unchanged in all groups. This result suggests that if inhibition of UCH-L1 has
occurred, there are no effects on mono-Ub or UPS activity. An alternative method to
measure target engagement is using a DUB labeling assay (Borodovsky et al., 2002). In

151

Figure 5.8. DA concentrations in the ST of mice and various drug treatments.
Mice were injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN.
Four h after mice received the second i.p. injection, mice were sacrificed and the ST
microdissected. DMSO + Saline n=9; LDN + Saline n=9; DMSO + MPTP n=6; LDN +
MPTP n=7. DA was measured via HPLC-ED. Data is plotted as mean + SEM and
asterisk (*) indicates a statistically significant difference from DMSO + Saline group
where p < 0.05 via one-way ANOVA with a post hoc Holm-Sidak test. Pound (#)
indicates statistically significant difference from DMSO + MPTP group where p <
0.05 via one-way ANOVA and a post hoc Holm-Sidak test.

152

Figure 5.9. DA concentrations in the NAc of mice and various drug treatments.
Mice were injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN.
Four h after mice received the second i.p. injection, mice were sacrificed and the
NAc microdissected. DMSO + Saline n=9; LDN + Saline n=10; DMSO + MPTP n=9;
LDN + MPTP n=9. DA was measured via HPLC-ED. Data is plotted as mean + SEM
and asterisk (*) indicates a statistically significant difference from DMSO + Saline
group where p < 0.05 via one-way ANOVA and a post hoc Holm-Sidak test. Pound
(#) indicates statistically significant difference from DMSO + MPTP group where p <
0.05 via one-way ANOVA and a post hoc Holm-Sidak test.

153

Table 5.6. UCH-L1 protein expression in the ST. Mice were injected with
saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in
Table 5.5. The ST was microdissected from brain tissue and analyzed via
Western blotting for UCH-L1 (n=10 each group). Data (densitometry of UCH-L1
compared to GAPDH loading control) is shown as mean ± SEM. No significant
difference between groups was detected (p > 0.05) via one-way ANOVA.

154

Table 5.7. UCH-L1 protein expression in the NAc. Mice were injected with
saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in
Table 5.5. The NAc was microdissected from brain tissue and analyzed via
Western blotting for UCH-L1 (n=10 each group). Data (densitometry of UCH-L1
compared to GAPDH loading control) is shown as mean ± SEM. No significant
difference between groups was detected (p > 0.05) via one-way ANOVA.

155

Table 5.8. UCH-L1 protein expression in the SN. Mice were injected with saline
or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in Table
5.5. The SN was microdissected from brain tissue and analyzed via Western
blotting for UCH-L1 (n=10 each group). Data (densitometry of UCH-L1 compared
to GAPDH loading control) is shown as mean ± SEM. No significant difference
between groups was detected (p > 0.05) via one-way ANOVA.

156

Table 5.9. UCH-L1 protein expression in the VTA. Mice were injected with saline or
20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in Table 5.5. The
VTA was microdissected from brain tissue and analyzed via Western blotting for UCHL1 (n=10 each group). Data (densitometry of UCH-L1 compared to GAPDH loading
control) is shown as mean ± SEM. No significant difference between groups was
detected (p > 0.05) via one-way ANOVA.

157

Table 5.10. Mono-Ub and total Ub protein in the ST. Mice were
injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg
LDN-57444 as described in Table 5.5. The ST was microdissected
from brain tissue and analyzed via Western blotting for UCH-L1
(n=10 each group). Data (densitometry of mono-Ub and total Ub
compared to GAPDH loading control) is shown as mean ± SEM. No
significant difference between groups was detected (p > 0.05) via
one-way ANOVA.

158

Table 5.11. Mono-Ub and total Ub protein in the NAc. Mice were
injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN57444 as described in Table 5.5. The NAc was microdissected from
brain tissue and analyzed via Western blotting for UCH-L1 (n=10 each
group). Data (densitometry of mono-Ub and total Ub compared to
GAPDH loading control) is shown as mean ± SEM. No significant
difference between groups was detected (p > 0.05) via one-way
ANOVA.

159

Table 5.12. Mono-Ub and total Ub protein in the SN. Mice were
injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg
LDN-57444 as described in Table 5.5. The SN was microdissected
from brain tissue and analyzed via Western blotting for UCH-L1
(n=10 each group). Data (densitometry of mono-Ub and total Ub
compared to GAPDH loading control) is shown as mean ± SEM.
No significant difference between groups was detected (p > 0.05)
via one-way ANOVA.

160

Table 5.13. Mono-Ub and total Ub protein in the VTA. Mice were
injected with saline or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg
LDN-57444 as described in Table 5.5. The VTA was
microdissected from brain tissue and analyzed via Western blotting
for UCH-L1 (n=10 each group). Data (densitometry of mono-Ub
and total Ub compared to GAPDH loading control) is shown as
mean ± SEM. No significant difference between groups was
detected (p > 0.05) via one-way ANOVA.

161

Figure 5.10. Gel image representing Ub-VME DUB labeling assay for the
ST and NAc. Mice were injected with saline or 20 mg/kg MPTP, DMSO VH or
0.5 mg/kg LDN-57444 as described in Table 5.5. Lysates from the ST and NAc
were incubated with the suicide substrate, Ub-VME (+) or with buffer. Samples
were denatured and run on a gel and membranes were probed for UCH-L1. No
qualitative difference between DMSO and LDN-57444 samples were observed.

162

Figure 5.11. Gel image representing Ub-VME DUB labeling assay for the
SN and VTA. Mice were injected with saline or 20 mg/kg MPTP, DMSO VH or
0.5 mg/kg LDN-57444 as described in Table 5.5. Lysates from the SN and
VTA were incubated with the suicide substrate, Ub-VME (+) or with buffer.
Samples were denatured and run on a gel and membranes were probed for
UCH-L1. No qualitative differences between DMSO and LDN-57444 were
observed.

163

Figure 5.12. Reduced GSH concentration in the ST. Mice were injected with saline or
20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in Table 5.5. The ST
was microdissected and assayed for reduced GSH. DMSO + Saline n=10; LDN + Saline
n=10; DMSO + MPTP n=8; LDN + MPTP n=9. The concentration of reduced GSH was
normalized to protein. Data is plotted mean + SEM. Asterisk (*) indicates a statistically
significant difference from DMSO + saline group and ampersand (&) indicates a
statistically significant difference from LDN + Saline group where p < 0.05 via one-way
ANOVA and a post hoc Holm-Sidak test.

164

Figure 5.13. Reduced GSH concentration in the NAc. Mice were injected with saline
or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in Table 5.5. The
NAc was microdissected and assayed for reduced GSH. DMSO + Saline n=7; LDN +
Saline n=9; DMSO + MPTP n=8; LDN + MPTP n=9. The concentration of reduced GSH
was normalized to protein. Data is plotted mean + SEM. Asterisk (*) indicates a
statistically significant difference from DMSO + saline group and ampersand (&)
indicates a statistically significant difference from LDN + Saline group where p < 0.05
via one-way ANOVA and a post hoc Holm-Sidak test.

165

Figure 5.14. Reduced GSH concentration in the SN. Mice were injected with saline or 20
mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN-57444 as described in Table 5.5. The SN was
microdissected and assayed for reduced GSH. DMSO + Saline n=10; LDN + Saline n=9;
DMSO + MPTP n=8; LDN + MPTP n=6. The concentration of reduced GSH was normalized to
protein. Data is plotted mean + SEM. No statistically significant differences were detected
between groups (p > 0.05) via one-way ANOVA.

166

Figure 5.15. Reduced GSH concentration in the VTA. Mice were injected with saline
or 20 mg/kg MPTP, DMSO VH or 0.5 mg/kg LDN as described in Table 5.5. The VTA
was microdissected and assayed for reduced GSH. DMSO + Saline n=8; LDN + Saline
n=10; DMSO + MPTP n=9; LDN + MPTP n=9. The concentration of reduced GSH was
normalized to protein. Data is plotted mean + SEM. Asterisk (*) indicates a statistically
significant difference from DMSO + saline group where p < 0.05 via one-way ANOVA
and a post hoc Holm-Sidak test.

167

this assay tissue lysates are incubated with the suicide inhibitor, Ub-VME. Ub-VME
attaches covalently to active DUBs, since Ub-VME can only bind if the active site is
unoccupied by an inhibitor. In the ST and NAc, the amount of inactive UCH-L1
appeared to be the same between DMSO- and LDN-57444-treated mice (Fig. 5.10).
Similarly, in the SN and VTA, LDN treatment did not have any effect on whether UbVME bound to UCH-L1 (Fig. 5.11).
The last endpoint in this experiment is reduced GSH, the levels of which are predicted
to be affected by UCH-L1 function (Rose and Warms, 1983). In Fig. 5.12, reduced GSH
levels are maintained in the LDN + saline group, but decreased in both groups exposed
to MPTP in the ST. A similar pattern is followed in the NAc (Fig. 5.13). In the SN,
however, reduced GSH is maintained following MPTP treatment (Fig. 5.14). In the VTA,
reduced GSH is not affected by LDN treatment but is decreased in mice exposed to
MPTP (Fig. 5.15).
Discussion
In this chapter, data from a dose response study with the UCH-L1 inhibitor LDN and a
study combining LDN drug treatment with MPTP exposure were presented. These
experiments sought to understand effects of UCH-L1 inhibition on both NSDA and
MLDA neurons, which has not previously been demonstrated in the literature. It was
hypothesized that a decrease in UCH-L1 activity would render MLDA neurons more
vulnerable to MPTP-induced oxidative injury, and that the effects of MPTP would be
exacerbated in NSDA neurons. LDN administration alone did not affect DA levels at

168

either doses (5 mg/kg or 0.5 mg/kg) administered and did not appear to have any overt
toxic effects.
However, LDN administration did increase the DOPAC/DA ratio in the NAc, which we
interpret as an increase in firing rate. Since there have been no previous reports in the
literature that UCH-L1 inhibition results in higher firing rate of neurons (in fact, the
opposite was demonstrated in hippocampal neurons and slices (Cartier et al., 2009;
Gong et al., 2006)). We surmise this result could be a nonspecific effect of the higher
dose of LDN, since it did not occur at the lower dose. It is possible that at the higher
dose of LDN, inhibition of UCH-L3 occurred, but this possibility is somewhat unlikely
based on the demonstrated specificity of the inhibitor for UCH-L1 over UCH-L3 (Liu et
al., 2003). In addition, UCH-L3 modulation has not previously been shown to have
effects on DA neurochemistry. LDN administration did not alter levels of mono-Ub or
UPS function, calling into question whether target engagement was achieved. Caveats
for interpretation of these data are discussed below.
Combination treatment with LDN and MPTP was used to determine if vulnerability of
MLDA neurons to MPTP was achieved with inhibition of UCH-L1. To our surprise, LDN
appeared to protect NSDA and MLDA neurons from loss of DA after MPTP exposure.
UCH-L1 inhibition in hippocampal neurons results in less synaptic activity and
deleterious effects in mice with respect to cognition and learning (Cartier et al., 2009;
Gong et al., 2006), which are in contrast to our results. LDN administration could
potentially have differential effects in different types of neurons, or differential effects on
neurotransmitter dynamics versus synaptic structure since only the latter has been
previously characterized in brain slices ex vivo and mice in vivo.
169

The observation that MLDA neurons are susceptible to loss of reduced GSH upon
MPTP exposure was also unanticipated, and even more surprising still is that reduced
GSH is not decreased in the SN. Previous studies employing chronic MPTP have
shown that MLDA neurons are less susceptible to lipid peroxidation than NSDA neurons
(Hung and Lee, 1998), which is a downstream consequence of oxidative stress,
highlighting a potential difference in antioxidant capacity between NSDA and MLDA
neurons. It is possible that at the acute time point and relatively low dose of MPTP
used, reduced GSH levels are not indicative of the overall response to oxidative stress.
In addition, with the techniques currently used to isolate tissue from the ST, NAc, SN,
and VTA, it cannot be definitively stated that the effects on reduced GSH are specifically
happening in NSDA or MLDA neurons. Contribution of glial GSH could be masking any
DA neuron-specific effects, even though UCH-L1 is only expressed in neurons. What is
clear, however, is that administration of LDN does not cause a decrease in reduced
GSH by itself in any of the brain regions examined. Assuming that UCH-L1 inhibition did
occur, these results suggest that UCH-L1 may not play a major role in regulation of the
available amount of reduced GSH in neurons.
The use of a pharmacological inhibitor appeared to be a promising strategy to modulate
UCH-L1 hydrolase activity without affecting total UCH-L1 protein levels. However, using
LDN to accomplish this goal has a few inherent caveats. One, the compound was
described as a reversible inhibitor (Liu et al., 2003), which means that perhaps it could
have dissociated from UCH-L1 at the time of collecting the brain tissue and tissue
processing and we simply missed the window of inhibition. Two, the effects of
administration of LDN on DA axon terminals could not be directly examined due to the
170

fact that the NAc is too small a brain region to generate adequate sample for
synaptosomes without pooling samples from multiple animals. Three, pharmacologically
inhibiting UCH-L1 may not have an impact on its ability to bind and sequester mono-Ub,
calling into question how useful the inhibitor may be to adequately model what effects
loss of UCH-L1 function could have in the context of MPTP-induced injury. However,
any changes in mono-Ub levels could be masked by glial cells. Our methods of target
engagement, while addressing possible functional consequences of inhibition of UCHL1, do not include measurements of LDN in mouse brain. Although we expect LDN to
distribute in brain tissue due to its high lipophilicity, we cannot definitively without a
shadow of a doubt say that in each mouse, LDN-57444 reached the brain region of
interest. However, we did see effects of LDN-57444 in mouse brain, which strongly
suggests that LDN-57444 did reach the targeted tissue.
The previously published study using LDN in vivo described a differential effect of UCHL1 inhibition depending on the genotype of the mice used: in WT animals, inhibition of
UCH-L1 caused UPS inhibition and subsequent accumulation of α-syn, while in α-syn
overexpressing mice, UCH-L1 inhibition was protective due to upregulation of
autophagic clearance of α-syn (Cartier et al., 2012). It is reasonable, therefore, to
surmise that perhaps UCH-L1 inhibition could have a protective function in pathological
conditions.
The contribution of UCH-L1 function in autophagic clearance was explored in Chapter
4, and it is not unreasonable to link a PD-related enzyme to the other major protein
degradation pathway. In this context, downregulation of UCH-L1 function could result in
upregulation of autophagy to promote degradation of toxic species, since we know that
171

MPTP causes an accumulation of Ub-proteins. The effects of LDN-57444 on autophagy
have not yet been studied in either NSDA or MLDA neurons.
Further characterization of this effect would help clarify these data, but during the
execution of the experiment unexpected toxicity of the combination of DMSO and MPTP
was observed, which resulted in approximately 30-40% mortality of animals. On the
other hand, DMSO alone did not cause any issues with endpoints measured or the
overall well-being of the animals in the experiment. This toxic effect of the combination
of DMSO and MPTP severely limits the feasibility of follow up experiments using the
UCH-L1 inhibitor in combination with MPTP unless development of a different vehicle
for LDN can be employed. Nevertheless, the results presented in this chapter have
demonstrated that LDN administration did not have the expected effect on mono-Ub
and UPS activity, but did appear to be protective against DA loss after MPTP in both
NSDA and MLDA neurons. Potential mechanisms for how inhibition of UCH-L1 could
protect DA neurons from MPTP are currently unclear but open to speculation.
Summary and conclusions
The UCH-L1 inhibitor, LDN-57444, was used in vivo to examine the effects of UCH-L1
inhibition in NSDA and MLDA neurons with respect to DA neurochemical and UPSrelated endpoints. LDN itself was not toxic to DA neurons in either brain region as
evidenced by no observed decrease in DA in either brain region with LDN treatment
alone. When combined with MPTP exposure, however, LDN-57444 was protective
against neurotoxicant-induced loss of DA in both brain regions. These results indicate

172

that the contribution of UCH-L1 activity to differential susceptibility of NSDA and MLDA
neurons is currently not clear and needs further investigation.

173

REFERENCES

174

REFERENCES

Behrouz, B., Drolet, R.E., Sayed, Z.A., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–8.
doi:10.1016/j.neuroscience.2007.05.007
Behrouz, B., Drolet, R.E., Sayed, Z. a., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–598.
doi:10.1016/j.neuroscience.2007.05.007
Borodovsky, A., Ovaa, H., Kolli, N., Gan-Erdene, T., Wilkinson, K.D., Ploegh, H.L.,
Kessler, B.M., 2002. Chemistry-Based Functional Proteomics Reveals Novel
Members of the Deubiquitinating Enzyme Family. Chem. Biol. 9, 1149–1159.
doi:10.1016/S1074-5521(02)00248-X
Braak, H., Braak, E., 2000. Pathoanatomy of Parkinson’s disease. J. Neurol. 247 Suppl,
II3-10. doi:10.1007/PL00007758
Cartier, A.E., Djakovic, S.N., Salehi, A., Wilson, S.M., Masliah, E., Patrick, G.N., 2009.
Regulation of synaptic structure by ubiquitin C-terminal hydrolase L1. J. Neurosci.
29, 7857–68. doi:10.1523/JNEUROSCI.1817-09.2009
Cartier, A.E., Ubhi, K., Spencer, B., Vazquez-Roque, R. a., Kosberg, K.A., Fourgeaud,
L., Kanayson, P., Patrick, C., Rockenstein, E., Patrick, G.N., Masliah, E., 2012.
Differential effects of UCHL1 modulation on alpha-synuclein in PD-like models of
alpha-synucleinopathy. PLoS One 7. doi:10.1371/journal.pone.0034713
Daina, A., Zoete, V., 2016. A BOILED-Egg To Predict Gastrointestinal Absorption and
Brain Penetration of Small Molecules. ChemMedChem 1117–1121.
doi:10.1002/cmdc.201600182
Gong, B., Cao, Z., Zheng, P., Vitolo, O. V, Liu, S., Staniszewski, A., Moolman, D.,
Zhang, H., Shelanski, M., Arancio, O., 2006. Ubiquitin hydrolase Uch-L1 rescues
beta-amyloid-induced decreases in synaptic function and contextual memory. Cell
126, 775–88. doi:10.1016/j.cell.2006.06.046
Hung, H.-C., Lee, E.H.., 1998. MPTP Produces Differential Oxidative Stress and
Antioxidative Responses in the Nigrostriatal and Mesolimbic Dopaminergic
Pathways. Free Radic. Biol. Med. 24, 76–84. doi:10.1016/S0891-5849(97)00206-2
Hurst-Kennedy, J., Chin, L.S., Li, L., 2012. Ubiquitin C-terminal hydrolase L1 in
tumorigenesis. Biochem. Res. Int. 2012. doi:10.1155/2012/123706
Kelava, T., Ćavar, I., Čulo, F., 2011. Biological actions of drug solvents. Period. Biol.
175

113, 311–320. doi:10.18054
Leroy, E., Boyer, R., Auburger, G., Leube, B., Ulm, G., Mezey, E., Harta, G.,
Brownstein, M.J., Jonnalagada, S., Chernova, T., Dehejia, A., Lavedan, C., Gasser,
T., Steinbach, P.J., Wilkinson, K.D., Polymeropoulos, M.H., 1998. The ubiquitin
pathway in Parkinson’s disease. Nature. doi:10.1038/26652
Liu, Y., Lashuel, H.A., Choi, S., Xing, X., Case, A., Ni, J., Yeh, L.A., Cuny, G.D., Stein,
R.L., Lansbury, P.T., 2003. Discovery of inhibitors that elucidate the role of UCH-L1
activity in the H1299 lung cancer cell line. Chem. Biol. 10, 837–846.
doi:10.1016/j.chembiol.2003.08.010
Rose, I.A., Warms, J.V.B., 1983. An enzyme with ubiquitin carboxy-terminal esterase
activity from reticulocytes. Biochemistry 22, 4234–4237. doi:10.1021/bi00287a012

176

Chapter 6: Effects of Aging on DA Metabolic Homeostasis in NSDA and MLDA
Neurons and Susceptibility to MPTP Toxicity
Introduction
Advanced age is the greatest risk factor for certain neurodegenerative diseases
including PD (Calne and William Langston, 1983). In PD, motor symptoms such as
bradykinesia, resting tremor, postural instability, and shuffling gait (Gelb et al., 1999)
occur due to loss of NSDA neurons (Hornykiewicz, 1966) which are vital for the proper
function of the basal ganglia pathway. Although NSDA neurons are lost over time as PD
progresses, other DA neurons are relatively spared: TIDA neurons and MLDA neurons
resist degeneration (Braak and Braak, 2000). DA loss is more pronounced in the
putamen of PD patients versus other regions in the ST (Kish et al., 1988). MLDA
neurons are often compared to NSDA neurons since they are phenotypically and
anatomically similar, with soma in the ventral midbrain and axon terminals in the ventral
striatum (Demarest and Moore, 1979). MLDA neurons in the VTA project to the NAc
and release DA as part of the reward pathway. How dissimilarities between NSDA and
MLDA neurons translate into differential susceptibility between the two DA neuron
populations has recently been well-reviewed (Surmeier et al., 2017). Despite the
available understanding about factors that underlie the differential susceptibility of
NSDA and MLDA neurons, few studies have focused on the role of aging.
Studies with the neurotoxicant MPTP have shown that aged mice demonstrate greater
motor deficits and have more loss of DA in the ST when compared to younger mice
following chronic MPTP exposure (Gupta et al., 1986). While neurotoxicant treated mice

177

have limitations in modeling every aspect of PD, the MPTP model of DA depletion and
oxidative stress can recapitulate differential susceptibility between NSDA and MLDA
neurons (Hung and Lee, 1998; Behrouz et al., 2007). The differential susceptibility of
MLDA and NSDA neurons observed in toxicant models has also been demonstrated in
transgenic rodent models of PD-like pathology. In addition, studies in nonhuman
primates have also recapitulated the resistance of VTA DA neurons to MPTP (DopesoReyes et al., 2014). MLDA neurons are not susceptible to damage in rats after rAAVmediated overexpression of α-syn in the ventral midbrain (Maingay et al., 2006), which
indicates MLDA neurons are resistant to neurodegeneration elicited by distinct, but
likely convergent etiologies of PD.
While these studies highlight intrinsic properties of MLDA neurons that enable survival
in PD, there are non-neuronal cells in the cell body and axon terminal regions that likely
play a role in differential responses to injury. While the synthesis and metabolism of DA
in the presynaptic DA neuron is well understood, the role of glial cells has only relatively
recently been appreciated and contribution of astrocytes to diseases such as PD should
be explored (Forno et al., 1992). Astrocytes express the catabolic enzymes MAO-B and
COMT and are the main non-neuronal cell type to metabolize DA (Levitt et al., 1982).
Some studies suggest that astrocyte-mediated DA metabolism removes excessive
synaptic DA, thus decreasing DA available for re-uptake, which would reduce
cytoplasmic DA in the axon terminal available for toxic DA adduct formation. Other
studies, however, indicate that astrocytes may also have pro-inflammatory functions
that could exacerbate neuron death (Teismann et al., 2003). Mice treated with chronic
MPTP display abnormal proliferation of astrocytes in the ST, a process known as
178

astrogliosis (Dervan et al., 2004). There is also emerging evidence that astrocytes may
play a role in MLDA mechanisms related to drug abuse (Miguel-Hidalgo, 2009). If
astrocytes safeguard MLDA neurons in aging and under neurotoxic stress, therapeutic
strategies to promote protective functions of astrocytes in regions affected by PD could
be developed.
The involvement of astrocytes in age-related decline of DA neuronal function in the NAc
has not yet been explored. To this end, a series of experiments in various ages of mice
were conducted to determine if DA synthesis, release, and metabolism are altered in
MLDA neurons or astrocytes from aged mice and whether MLDA neurons are rendered
susceptible to MPTP exposure with aging. We hypothesize that presynaptic synthesis
and metabolism of DA by astrocytes is preserved in the NAc in younger but not aged
mice, and that MLDA neurons are resistant to the effects of toxicant exposure in young,
but not aged mice. Our study addresses the contribution of presynaptic metabolism and
metabolism of DA by astrocytes in the aged NAc to better understand neuronal and
astrocyte susceptibility to aging.
Results
Aged mice have less stored DA in the NAc, but astroglial metabolism of DA remains
intact
We first sought to determine the basal neurochemical profile for DA in the NAc and ST
in young, mature, old and aged mice. In the ST, DA was not altered in any of the
various age groups compared to young control (Fig. 6.1A). In the NAc, however, DA is

179

Figure 6.1. DA and DOPAC concentrations and DOPAC/DA ratio in ST (A, C,
E) and NAc (B, D, F) in Young, Mature, Old, and Aged mice. Young, Mature,
Old, and Aged mice were decapitated, brains were sectioned, and ST (Young
n=7; Mature n=13; Old n=11; Aged n=10) and NAc (Young n=7; Mature n=13;
Old n=10; Aged n=10) were collected in tissue buffer for HPLC-ED analysis. DA
and DOPAC were measured and normalized to mg protein per sample.
Concentrations for DOPAC were divided by DA to give the DOPAC/DA ratio.
Data is expressed as mean + SEM. Data was analyzed via One-Way ANOVA
with post hoc Holm-Sidak test. Pound symbol (#) indicates statistically significant
difference (p < 0.05) from Young age group.

180

decreased in aged mice compared to young mice (Fig. 6.1B). The main metabolite of
recaptured DA by MAO-B, DOPAC, also decreased in an age-dependent manner in the
ST (Fig. 6.1C) and the NAc (Fig. 6.1D). The DOPAC/DA ratio is a measure of the
relative rate of DA metabolism via MAO-B compared to release, uptake and storage in
synaptic vesicles. The DOPAC/DA ratio is not changed in the ST (Fig. 6.1E) or the NAc
between age groups (Fig. 6.1F). This latter observation indicates that the rate of DA
metabolism relative to storage and release of recaptured DA from the synapse is not
affected by aging in DA axon terminals in either brain region.
Given the observed age-related decrease DA stored in the NAc, we next sought to
determine if synthesis and vesicular storage of DA in presynaptic axon terminals are
also decreased in the NAc and ST of aged mice compared to younger mice. Total TH
and Ser40 phosphorylated TH (p-TH) were measured in the NAc (Fig. 6.4). TH is the
rate-limiting enzyme of DA synthesis and requires phosphorylation of serine residue 40
to become active (Campbell et al., 1986). To determine if reuptake or vesicular storage
of DA could be affected by aging in the ST and NAc, DAT, and vesicular monoamine
transporter 2 (VMAT2) were measured. We observed no change in levels of these
proteins between young and aged mice in either brain region (Fig. 6.4 and Fig. 6.5).
Extraneuronal metabolism of DA released from the pre-synaptic axon terminal produces
HVA and 3-MT. To determine if age alters extraneuronal metabolism of released DA,
HVA and 3-MT were measured in young and aged mice (Fig. 6.2). HVA was decreased
with age in both the ST (Fig. 6.2A) and the NAc (Fig. 6.2B). 3-MT, however, was
decreased with age in the ST (Fig. 6.2C) but not in the NAc (Fig. 6.2D). These results
suggest that extraneuronal astrocyte metabolism of DOPAC to HVA by COMT or DA to

181

3-MT by MAO-B could be compromised in aged mice in the ST. In contrast, the
extraneuronal (astroglial) metabolism of released DA does not appear to be diminished
in the NAc as mice get older. We measured total COMT

182

Figure 6.2. HVA and 3-MT concentrations after MPTP in Young and Aged ST
(A, C) and NAc (B, D). Young and aged mice were treated with vehicle (VH) or
20 mg/kg MPTP and sacrificed 24 h later. Brains were sectioned and ST (Young
VH n=7; Young MPTP n=8; Aged VH n=10; Aged MPTP n=10) and NAc (Young
VH n=9; Young MPTP n=8; Aged VH n=8; Aged MPTP n=9) were collected in
tissue buffer for HPLC-ED analysis. HVA and 3-MT were measured and
normalized to mg protein per sample. Data is expressed as mean + SEM. Data
was analyzed via Two Way ANOVA with post hoc Holm-Sidak test. Asterisk (*)
indicates statistically significant difference (p < 0.05) from VH control, while pound
symbol (#) represents statistically significant difference from Young VH.

183

Figure 6.3. DA and DOPAC concentrations after MPTP in Young and Aged ST
(A, C) and NAc (B, D). Young and aged mice were treated with vehicle (VH) or 20
mg/kg MPTP and sacrificed 24 h later. Brains were sectioned and ST (Young VH
n=7; Young MPTP n=8; Aged VH n=10; Aged MPTP n=10) and NAc (Young VH
n=7; Young MPTP n=8; Aged VH n=10; Aged MPTP n=8) were collected in tissue
buffer for HPLC-ED analysis. DA and DOPAC were measured and normalized to
mg protein per sample. Data is expressed as mean + SEM. Data was analyzed via
Two Way ANOVA with post hoc Holm-Sidak test. Asterisk (*) indicates statistically
significant difference (p < 0.05) from respective VH control within age group, while
pound symbol (#) represents statistically significant difference from Young VH
control.

184

protein in the ST and NAc in young and aged mice and found no significant difference
between age groups (Fig. 6.6).
Acute MPTP exposure decreases DA, DOPAC, and astroglial DA metabolites in ST and
NAc of both young and aged mice
Next, mice were challenged with the neurotoxicant MPTP to determine if loss of DA
axonal stores in the NAc observed after MPTP exposure is exacerbated in aged mice.
Aged mice are not more sensitive to acute MPTP-induced loss of DA in the ST (Fig.
6.3A) but aged mice are less susceptible to loss of DA in the NAc compared to young
mice (Fig. 6.3B). Loss of DOPAC after MPTP is equivalent between age groups in the
ST (Fig. 6.3C) but the MPTP-induced decrease in DOPAC is reduced in the NAc of
aged mice (Fig. 6.3D). The diminished MPTP-induced loss of DA and DOPAC in the
NAc aged mice compared to young mice may reflect the combined effects of agedependent and MPTP-induced loss of DA and DOPAC. There may also be a lower limit
to the extent of DA and DOPAC loss that can be achieved with a single, acute 20 mg/kg
dose of MPTP. This lower limit for toxicant-induced DA impairment may represent a
resilient population of NAc DA neurons in advanced age.
A differential effect of MPTP was also observed in the astroglial metabolism of DA in the
MLDA and NSDA neurons. HVA, a direct metabolite of DOPAC, decreases in the ST of
both young and old mice following acute MPTP treatment (Fig. 6.2A). In the NAc,
however, HVA decreases in young mice treated with MPTP (Fig. 6.2B), but is not
further decreased in aged mice treated with MPTP. Following MPTP treatment, the
COMT DA metabolite 3-MT decreased in the ST of both young and aged mice (Fig.
6.2C) but was unchanged in the NAc of young or aged mice (Fig. 6.2D). The
185

Figure 6.4. Ser40 p-TH and total TH protein levels in ST (A, C) and NAc (B,
D). Young and aged mice were treated with vehicle (VH) or 20 mg/kg MPTP and
sacrificed 24 h later. Brains were sectioned and ST (Young VH n=8; Young MPTP
n=7; Aged VH n=10; Aged MPTP n=10) and NAc (Young VH n=8; Young MPTP
n=7; Aged VH n=10; Aged MPTP n=10) were collected in lysis buffer for Western
blot analysis. Representatives of immunoblots are shown in figure. Data is
expressed as mean + SEM and analyzed via Two Way ANOVA with post hoc
Holm-Sidak test. Asterisk (*) indicates statistically significant difference (p < 0.05)
from VH control.
186

Figure 6.5. DAT and VMAT2 protein levels in ST (A, C) and NAc (B, D). Young and
aged mice were treated with vehicle (VH) or 20 mg/kg MPTP and sacrificed 24 h later.
Brains were sectioned and ST (Young VH n=8; Young MPTP n=8; Aged VH n=10;
Aged MPTP n=9) and NAc (Young VH n=7; Young MPTP n=8; Aged VH n=9; Aged
MPTP n=10) were collected in lysis buffer for Western blot analysis. Representatives
of immunoblots are shown in figure. Data is expressed as mean + SEM and analyzed
via Two Way ANOVA with post hoc Holm-Sidak test. Asterisk (*) indicates statistically
significant difference (p < 0.05) from VH control.
187

unique MPTP-induced changes in HVA and 3MT in the ST and NAc of young and aged
mice suggests that extraneuronal metabolism of DOPAC and DA in astrocytes
are differentially regulated in these two brain regions in the context of acute neurotoxic
stress.
Total and phosphorylated TH are decreased in the ST but not the NAc after MPTP in
young and aged mice
Both Ser40 p-TH and total TH were decreased in the ST following MPTP treatment in
young and aged mice (Fig. 6.4A and Fig. 6.4C). In the NAc, however, total TH and
Ser40 p-TH expression was similar in saline and MPTP treated young and aged mice
(Fig. 6.4B and Fig. 6.4D). Therefore, the MPTP-induced decrease in DA observed in
the NAc is not due to a deficit in total or activated TH available for DA synthesis.
DAT is decreased in the ST, but not the NAc, after MPTP while VMAT2 is unchanged in
both young and aged mice treated with MPTP
DAT is susceptible to oxidative damage and toxic adduct formation. In addition to
synthesis and metabolism, cytoplasmic DA concentrations are regulated by the relative
capacity for DA uptake via DAT and vesicular storage via VMAT. In addition to recycling
synaptic DA, DAT is also the transporter through which the active MPTP metabolite,
MPP+ enters into DA neurons and astrocytes. Relative DAT levels reflect the axon
terminal DA uptake capacity. As such, measuring DAT expression can assess potential
mechanisms for age and region specific differential susceptibility to MPTP and oxidative
stress. DAT decreases in the ST following acute MPTP treatment (Fig. 6.5A). In
contrast, DAT expression in the NAc is similar in vehicle and MPTP treated mice (Fig.
6.5B). VMAT2 packages DA into synaptic

188

Figure 6.6. COMT protein levels in ST (A, C) and NAc (B, D). Young and aged mice
were treated with vehicle (VH) or 20 mg/kg MPTP and sacrificed 24 h later. Brains were
sectioned and ST (Young VH n=7; Young MPTP n=6; Aged VH n=9; Aged MPTP n=10)
and NAc (Young VH n=7; Young MPTP n=5; Aged VH n=9; Aged MPTP n=10) were
collected in lysis buffer for Western blot analysis. Representatives of immunoblots are
shown in figure. Data is expressed as mean + SEM and analyzed via Two Way ANOVA
with post hoc Holm-Sidak test. No significant differences were detected.

189

Figure 6.7. Overview of neuronal synthesis of DA and astrocyte metabolism.
DA synthesis occurs in a presynaptic neuron (green) and is metabolized or
packaged into vesicles and released into the synapse. DA is synthesized from
tyrosine by TH to L-DOPA, which is then metabolized to DA via dopa
decarboxylase (DDC). DA can then be metabolized by MAO to DOPAC, which can
be exported to astrocytes (blue) for further metabolism into HVA by COMT. If DA is
packaged into vesicles by VMAT2, it can be released into the synapse and bind to
receptors on the postsynaptic neuron (orange). DA can also be transported back
into the axon terminal by DAT. If DA is exported to the astrocyte, it can undergo
metabolism by COMT to 3-MT, which then can be metabolized by MAO to HVA.
Graphics were adapted from Servier Medical Art (www.servier.com) with a
Creative Commons Attribution 3.0 Unported License and edited for use in this
figure.

190

vesicles and reduces the amount of cytoplasmic DA available for oxidative conversion
to toxic molecules (e.g., dopamine quinones). VMAT2 was not altered in either brain
region in saline and MPTP treated young or aged mice (Fig.6.5C and Fig. 6.5D).
Discussion
Young animals are frequently used in experiments designed to understand PD, yet have
clear limitations in the study of a disease so closely associated with aging. We sought to
evaluate age-related changes in two groups of midbrain DA neurons differentially
affected in PD under basal conditions and following toxicant exposure to induce
oxidative damage. Presynaptic and extraneuronal DA metabolic pathways were
assessed in the brain regions containing the nerve terminals of the NSDA and MLDA
neurons, the ST and NAc, respectively (Fig. 6.7). First, we determined if presynaptic DA
metabolism and release are perturbed in aged mice. After investigating changes in DA
concentrations between the ST and NAc, we observed that DA was not changed with
age in the ST but was decreased in aged mice in the NAc. We examined levels of total
and Ser40 p-TH to determine if the shortage of DA stores could be linked to deficient
availability of the active form of the rate-limiting enzyme essential for DA synthesis. We
did not, however, observe an age-related decrease in p-TH or total TH in the NAc. As
such, it appears unlikely that impaired DA synthesis capacity is an explanation for the
age-related decrease in MLDA stores.
If synthesis of DA was unperturbed in aged NAc, then perhaps reuptake of DA and
presynaptic metabolism of DA to DOPAC increases with age, thus explaining the agedependent decrease in MLDA stores. Aged mice were found to have less DOPAC than
young mice. The majority of DOPAC is produced when DA is taken back up into the
191

axon terminal (Roth et al., 1976) and metabolized by MAO-B. Thus DOPAC represents
an indirect index of DA that has been released and recaptured by the presynaptic
neuron. Our observation that aged mice have lower DOPAC concentrations compared
to young mice suggests that aged mice release less DA or metabolize less
intraneuronal cytoplasmic DA. One study found that aged rats release less DA in the
NAc as measured by microdialysis, which is congruent with our results (Huang et al.,
1995). DA release is dependent on DA neuronal activity. The ratio of DOPAC/DA is an
index of DA metabolism or turnover that is independent of DA nerve terminal density
(Lookingland and Moore, 2005). Notably, the ratio of DOPAC/DA was similar in the NAc
of young and aged mice, which suggests that there is no age-related change in DA
turnover in MLDA neurons.
Changes in DA uptake or synaptic vesicular storage capacity, in part, regulate the pool
of cytoplasmic DA that is susceptible to oxidative conversion to toxic molecules
(Hastings et al., 1996). To understand whether reuptake or vesicular packaging could
affect the concentrations of DA or DOPAC, we measured DAT and VMAT2 in ST and
NAc after aging. No significant alterations in DAT and VMAT2 were found in aged mice
in either brain region. As such, presynaptic reuptake and synaptic vesicle
compartmentalization of DA are not affected by aging in the NAc.
If changes in presynaptic DA synthesis, release-reuptake and intraneuronal metabolism
cannot explain the age-dependent decline in mesolimbic DA stores, then alterations in
extraneuronal DA metabolism may play a role. We assessed extraneuronal metabolism
of DA by astrocytes. Impairment of these glial cells have been reported to contribute to
alterations in DA metabolism and progression of PD (Maragakis and Rothstein, 2006).

192

COMT within astrocytes metabolizes DOPAC to HVA. Measurement of HVA, therefore,
provides an index of glial metabolism of extraneuronal DOPAC (Schendzielorz et al.,
2013).
In the present study, both the ST and NAc experienced an age-related decrease in
HVA, which suggests that less DOPAC is being metabolized into HVA in astrocytes of
aged mice. The decrease in HVA could also reflect decreased glial COMT expression or
number of glial cells expressing COMT, but COMT protein levels were not decreased in
the ST or NAc of aged mice. Also, a prior study by Emsley and Macklis (2006) reported
there is approximately the same density of astrocytes in the ST and NAc (Emsley and
Macklis, 2006). Another DA metabolite, 3-MT, is the direct product of metabolism of DA
by COMT in astrocytes and represents an indirect index of DA release (Fig. 6.7). Since
3-MT was not decreased with aging in the NAc, there could be an increase in activity of
glial COMT (rather than increase in protein expression) to compensate for decreased
substrate. Our results indicate that astrocytes retain the ability to metabolize DA in the
NAc in aged mice.
Toxicant-induced oxidative stress results in a decrease in DA in the ST and NAc in
addition to loss of axon terminals of NSDA and MLDA neurons. Susceptibility to axon
terminal loss and cell body degeneration in NSDA neurons may increase with age
(McGeer et al., 1977). We specifically used the acute MPTP dosing paradigm to allow
investigation of DA axon terminal and local astrocyte responses in the absence of
significant neuronal loss or denervation. Early events occurring following oxidative injury
predispose neurons to eventual degeneration but also may represent potentially

193

reversible steps in the process that may be more amenable to disease modifying
therapeutic intervention.
We observed that a single acute dose of MPTP was similar in NSDA and MLDA
neurons in young and aged mice. With chronic, repeated exposure to MPTP, the
susceptibility of NSDA neurons does appear to increase with age MPTP (Gupta et al.,
1986). Chronic, repeated MPTP treatment eventually results in both ST axon terminal
and SN cell body loss, while a single acute MPTP treatment causes axon terminal
dysfunction but does not produce cell death at the time periods we examined.
DAT mediates the uptake of MPP+ and DAT expression is required for MPTP toxicity
(Gainetdinov et al., 2002). DAT expression depends, to a large extent, on the number of
DA axon terminals, but the overall and surface expression of DAT can change
independent of the density of DA nerve terminals (Nirenberg et al., 1996). In the present
study total DAT expression decreases to a similar extent in the ST after acute MPTP
treatment in both young and aged mice. DAT expression was also similar in saline and
MPTP treated mice in the NAc, regardless of age. As previously noted, the acute
MPTP paradigm we employ does not result in significant NSDA axon terminal loss
(Jackson-Lewis et al., 1995). Indeed, we observed no significant change in the
expression a more stable marker of DA nerve terminal density (VMAT2) (Vander Borght
et al., 1995) following acute MPTP treatment. Our findings, therefore, suggest that the
early and likely dynamic decline in ST DAT expression following acute oxidative injury is
not age dependent. Our results also provide some reassurance that capacity for MPP+
uptake via DAT does not change significantly with age and is not a likely confounding
factor for our observations.

194

It should be noted that measurement of total DAT protein expression does not always
parallel the DAT localized or expressed on the plasma membrane surface. This is an
important caveat, since the surface expression of DAT determines the true uptake
capacity of this transporter (Mortensen and Amara, 2003). Cytoplasmic DA available for
oxidative conversion to more toxic molecules would be expected to be low in brain
regions with high storage capacity (VMAT2) relative to re-uptake (DAT) (Uhl, 1998).
Basal expression of VMAT2 or the ratio of VMAT2/DAT are inversely correlated with the
susceptibility of different brain regions to MPTP (Hall et al., 2014; Lohr et al., 2016).
VMAT2 expression was not changed in either brain region in young or aged mice and
also did not change following acute MPTP treatment. This observation indicates there
was no age-dependent change in the capacity of NSDA and MLDA axon terminals to
store DA in synaptic vesicles. Direct or indirect measurement of VMAT2 is closely linked
to nerve terminal density. Since the acute MPTP model we employed in the current
study does not cause significant cell body or axon loss, then it is not surprising there
was no observed change in VMAT2 following MPTP treatment.
Taken together, the above findings indicate alterations in pre-synaptic DA metabolic
homeostasis do not appear to change with age in the NAc and are not likely to explain
the age-dependent decline in NAc DA stores. Age-dependent changes in astrocyte
metabolism of extraneuronal DA, however, may play a role. This is evidenced by
impairment of extraneuronal metabolism of DA to 3-MT in the ST, but not the NAc, and
that HVA produced by the metabolism of DOPAC via COMT and the conversion of 3MT
by MAO, decreases in both the ST and NAc with age.

195

Since DAT is expressed in astrocytes as well as presynaptic neurons (Schömig et al.,
1997), MPP+ can be taken up by astrocytes and cause oxidative damage. In the NAc,
however, no decrease in 3-MT was observed in mice exposed to MPTP. Our results
suggest that astrocytes could be playing a protective role in the NAc. Indeed, under
conditions of heightened oxidative stress, astrocytes may be overwhelmed and no
longer able to properly protect NSDA neurons terminating in the ST (Episcopo et al.,
2013). Perhaps exceeding the protective capacity of glial cells contributes to
neurodegeneration in PD. Consistent with this hypothesis, astrocytes are activated in
regions containing NSDA neuron in younger primates treated with MPTP, but this is
impaired in aged primates in association with impairment of striatal DA metabolism
(Kanaan et al., 2008). In the present study we observed that astrocyte metabolism is
relatively preserved in the NAc of aged mice and this maintained capacity for
extraneuronal DA metabolism may stabilize DA homeostasis by rapidly clearing
synaptic DA in MLDA neurons under conditions of oxidative stress-induced injury.

Summary and conclusions
This study was designed to test the hypothesis that MLDA neurons are less susceptible
to age-related deficits in DA synthesis, metabolism and reuptake compared to wellcharacterized NSDA neurons. We measured the components of presynaptic and
astrocyte DA synaptic homeostasis including metabolites, enzymes for synthesis, and
transporters to understand the impact of aging on DA homeostasis in MLDA and NSDA
neurons. We also exposed young and aged mice to acute neurotoxic insult to examine
how aged MLDA neurons cope with oxidative stress. We conclude that DA and DOPAC

196

loss in the NAc is consistent with a decrease in release of DA while DA synthesis
remains unaffected. As contributors to metabolism of DA released in the synapse,
astrocytes in the NAc retain the ability to metabolize DA into 3-MT, suggesting these
cells are capable of fulfilling their neuroprotective role in both young and aged mice. Our
study highlights the importance of DA metabolism in astrocytes, which introduces the
potential role of astrocytes in differential susceptibility of NSDA and MLDA neurons in
PD.

197

REFERENCES

198

REFERENCES

Behrouz, B., Drolet, R.E., Sayed, Z.A., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–8.
doi:10.1016/j.neuroscience.2007.05.007
Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Braak, H., Braak, E., 2000. Pathoanatomy of Parkinson’s disease. J. Neurol. 247 Suppl,
II3-10. doi:10.1007/PL00007758
Calne, D., William Langston, J., 1983. AETIOLOGY OF PARKINSON’S DISEASE.
Lancet 322, 1457–1459. doi:10.1016/S0140-6736(83)90802-4
Campbell, D.G., Hardie, D.G., Vulliet, P.R., 1986. Identification of 4 Phosphorylation
Sites in the N-Terminal Region of Tyrosine-Hydroxylase. J. Biol. Chem. 261, 489–
492.
Caudle, W.M., Richardson, J.R., Wang, M.Z., Taylor, T.N., Guillot, T.S., McCormack,
A.L., Colebrooke, R.E., Di Monte, D.A., Emson, P.C., Miller, G.W., 2007. Reduced
Vesicular Storage of Dopamine Causes Progressive Nigrostriatal
Neurodegeneration. J. Neurosci. 27, 8138 LP-8148.
Chinaglia, G., Alvarez, F.J., Probst, A., Palacios~ Ii, J.M., 1992. Mesostriatal and
Mesolimbic Dopamine Uptake Binding Sites Are Reduced in Parkinson’S Disease
and Progressive Supranuclear Palsy: a Quantitative Autoradiographic Study Using
[3H]Mazindol. Neuroscience 49, 317–327. doi:10.1016/0306-4522(92)90099-N
Dervan, A.G., Meshul, C.K., Beales, M., McBean, G.J., Moore, C., Totterdell, S.,
Snyder, A.K., Meredith, G.E., 2004. Astroglial plasticity and glutamate function in a
chronic mouse model of Parkinson’s disease. Exp. Neurol. 190, 145–156.
doi:10.1016/j.expneurol.2004.07.004
Dopeso-Reyes, I.G., Rico, A.J., Roda, E., Sierra, S., Pignataro, D., Lanz, M., Sucunza,
D., Chang-Azancot, L., Lanciego, J.L., 2014. Calbindin content and differential
vulnerability of midbrain efferent dopaminergic neurons in macaques. Front.
Neuroanat. 8, 146. doi:10.3389/fnana.2014.00146
Emsley, J.G., Macklis, J.D., 2006. Astroglial heterogeneity closely reflects the neuronal199

defined anatomy of the adult murine CNS. Neuron Glia Biol. 2, 175–86.
doi:10.1017/S1740925X06000202
Episcopo, F.L., Tirolo, C., Testa, N., Caniglia, S., Morale, M.C., Marchetti, B., 2013.
Reactive astrocytes are key players in nigrostriatal dopaminergic neurorepair in the
MPTP mouse model of Parkinson’s disease: focus on endogenous
neurorestoration. Curr. Aging Sci. 6, 45–55. doi:10.1093/pubmed/fdl064
Forno, L.S., DeLanney, L.E., Irwin, I., Monte, D. Di, Langston, J.W., 1992. Chapter 36:
Astrocytes and Parkinson’s disease. pp. 429–436. doi:10.1016/S00796123(08)61770-7
Gelb, D., Oliver, E., Gilman, S., 1999. Diagnostic criteria for Parkinson disease. Arch.
Neurol. 56, 33–39.
Gupta, M., Gupta, B.K., Thomas, R., Bruemmer, V., Sladek, J.R., Felten, D.L., 1986.
Aged mice are more sensitive to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine
treatment than young adults. Neurosci. Lett. 70, 326–331. doi:10.1016/03043940(86)90573-2
Hall, F.S., Itokawa, K., Schmitt, A., Moessner, R., Sora, I., Lesch, K.P., Uhl, G.R., 2014.
Decreased vesicular monoamine transporter 2 (VMAT2) and dopamine transporter
(DAT) function in knockout mice affects aging of dopaminergic systems.
Neuropharmacology 76, 146–155. doi:10.1016/j.neuropharm.2013.07.031
Hastings, T.G., Lewis, D.A., Zigmond, M.J., 1996. Role of oxidation in the neurotoxic
effects of intrastriatal dopamine injections. Proc. Natl. Acad. Sci. 93, 1956–1961.
Hornykiewicz, O., 1966. Dopamine (3-hydroxytyramine) and brain function.
Pharmacol.Rev. 18, 925–964.
Huang, R., Wang, C., Tai, M., Tsai, Y., Peng, M., 1995. NEUROSCIENCf IEHHIS 200,
61–64.
Hung, H.-C., Lee, E.H.., 1998. MPTP Produces Differential Oxidative Stress and
Antioxidative Responses in the Nigrostriatal and Mesolimbic Dopaminergic
Pathways. Free Radic. Biol. Med. 24, 76–84. doi:10.1016/S0891-5849(97)00206-2
Jackson-Lewis, V., Jakowec, M., Burke, R.E., Przedborski, S., 1995. Time course and
morphology of dopaminergic neuronal death caused by the neurotoxin 1-methyl-4phenyl-1,2,3,6-tetrahydropyridine. Neurodegeneration 4, 257–269.
doi:10.1016/1055-8330(95)90015-2
Jackson-Lewis, V., Przedborski, S., 2007. Protocol for the MPTP mouse model of
Parkinson’s disease. Nat. Protoc. 2, 141–51. doi:10.1038/nprot.2006.342
Kanaan, N.M., Kordower, J.H., Collier, T.J., 2008. Age and region-specific responses of
microglia, but not astrocytes, suggest a role in selective vulnerability of dopamine
neurons after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine exposure in monkeys.
Glia 56, 1199–1214. doi:10.1002/glia.20690
200

Kish, S.J., Shannak, K., Hornykiewicz, O., 1988. Uneven Pattern of Dopamine Loss in
the Striatum of Patients with Idiopathic Parkinson’s Disease. N. Engl. J. Med. 318,
876–880. doi:10.1056/NEJM198804073181402
Levitt, P., Pintart, J.E., Breakefieldt, X. 0, 1982. Immunocytochemical demonstration of
monoamine oxidase B in brain astrocytes and serotonergic neurons (central
nervous system/rat/monoamine) 79, 6385–6389.
Lohr, K.M., Chen, M., Hoffman, C.A., McDaniel, M.J., Stout, K.A., Dunn, A.R., Wang,
M., Bernstein, A.I., Miller, G.W., 2016. Vesicular Monoamine Transporter 2
(VMAT2) Level Regulates MPTP Vulnerability and Clearance of Excess Dopamine
in Mouse Striatal Terminals. Toxicol. Sci. 153, 79–88.
Lookingland, K.J., Moore, K.E., 2005. Chapter VIII Functional neuroanatomy of
hypothalamic dopaminergic neuroendocrine systems. Handb. Chem. Neuroanat.
21, 435–523. doi:10.1016/S0924-8196(05)80012-0
Maingay, M., Romero-Ramos, M., Carta, M., Kirik, D., 2006. Ventral tegmental area
dopamine neurons are resistant to human mutant alpha-synuclein overexpression.
Neurobiol. Dis. 23, 522–32. doi:10.1016/j.nbd.2006.04.007
Maragakis, N.J., Rothstein, J.D., 2006. Mechanisms of Disease: astrocytes in
neurodegenerative disease. Nat Clin Pr. Neurol 2, 679–689. doi:ncpneuro0355
[pii]\r10.1038/ncpneuro0355
McGeer, P.L., McGeer, E.G., Suzuki, J.S., 1977. Aging and Extrapyramidal Function.
Arch. Neurol. 34, 33–35. doi:10.1001/archneur.1977.00500130053010
Miguel-Hidalgo, J.J., 2009. The Role of Glial Cells in Drug Abuse. Curr. Drug Abuse
Rev. 2, 76–82.
Mogenson, G.J., Jones, D.L., Yim, C.Y., 1980. From motivation to action: Functional
interface between the limbic system and the motor system. Prog. Neurobiol. 14,
69–97. doi:http://dx.doi.org/10.1016/0301-0082(80)90018-0
Mortensen, O. V., Amara, S.G., 2003. Dynamic regulation of the dopamine transporter.
Eur. J. Pharmacol. 479, 159–170. doi:10.1016/j.ejphar.2003.08.066
Nirenberg, M.J., Vaughan, R.A., Uhl, G.R., Kuhar, M.J., Pickeli, V.M., 1996. The
Dopamine Transporter Is Localized to Dendritic and Axonal Plasma Membranes of
Nigrostriatal Dopaminergic Neurons. J. Neurosci. 76, 436–447.
Roth, R.H., Murrin, L.C., Walters, J.R., 1976. Central dopaminergic neurons: Effects of
alterations in impulse flow on the accumulation of dihydroxyphenylacetic acid. Eur.
J. Pharmacol. 36, 163–171. doi:10.1016/0014-2999(76)90268-5
Sawamoto, K., Nakao, N., Kobayashi, K., Matsushita, N., Takahashi, H., Kakishita, K.,
Yamamoto, A., Yoshizaki, T., Terashima, T., Murakami, F., Itakura, T., Okano, H.,
2001. Visualization, direct isolation, and transplantation of midbrain dopaminergic
neurons. Proc. Natl. Acad. Sci. U. S. A. 98, 6423–8. doi:10.1073/pnas.111152398
201

Schendzielorz, N., Oinas, J.-P., Myöhänen, T.T., Reenilä, I., Raasmaja, A., Männistö,
P.T., 2013. Catechol-O-Methyltransferase (COMT) Protein Expression and Activity
after Dopaminergic and Noradrenergic Lesions of the Rat Brain. PLoS One 8,
e61392.
Schömig, E., Russ, H., Staudt, K., Martel, F., Gliese, M., Gründemann, D., 1997. The
Extraneuronal Monoamine Transporter Exists in Human Central Nervous System
Glia. pp. 356–359. doi:10.1016/S1054-3589(08)60764-4
Schott, B.H., Niehaus, L., Wittmann, B.C., Schütze, H., Seidenbecher, C.I., Heinze,
H.J., Düzel, E., 2007. Ageing and early-stage Parkinson’s disease affect separable
neural mechanisms of mesolimbic reward processing. Brain 130, 2412–2424.
doi:10.1093/brain/awm147
Surmeier, D.J., Obeso, J.A., Halliday, G.M., 2017. Selective neuronal vulnerability in
Parkinson disease. Nat. Rev. Neurosci. 18, 101–113. doi:10.1038/nrn.2016.178
Teismann, P., Tieu, K., Cohen, O., Choi, D.-K., Wu, D.C., Marks, D., Vila, M., JacksonLewis, V., Przedborski, S., 2003. Pathogenic role of glial cells in Parkinson’s
disease. Mov. Disord. 18, 121–129. doi:10.1002/mds.10332
Uhl, G.R., 1998. Hypothesis: The role of dopaminergic transporters in selective
vulnerability of cells in Parkinson’s disease. Ann. Neurol. 43, 555–560.
doi:10.1002/ana.410430503
Vander Borght, T., Kilbourn, M., Desmond, T., Kuhl, D., Frey, K., 1995. The vesicular
monoamine transporter is not regulated by dopaminergic drug treatments. Eur. J.
Pharmacol. 294, 577–83.

202

Chapter 7: Effects of Aging on UCH-L1 Expression and Function in Brain Regions
Containing NSDA and MLDA Neurons
Introduction
A major theme of this Dissertation thus far has been comparing the response of NSDA
and MLDA neurons to neurotoxicant treatment in hopes that we can identify protective
pathways maintained in non-susceptible neurons to develop new disease modifying
therapeutics for PD. Therapeutics that halt or reverse neurodegeneration are currently
lacking and represent a major unmet need. One pathway known to be compromised in
PD is the UPS (Ross and Pickart, 2004), which is responsible for protein degradation.
Two proteins found mutated in familial PD, parkin (Kitada et al., 1998) and UCH-L1
(Leroy et al., 1998), are enzymes associated with the UPS. The association between
parkin and UCH-L1 mutations and PD highlights the importance of UPS-mediated
protein degradation in neurons. The focus of this Dissertation is UCH-L1, which is a
DUB shown to be important in maintaining available pools of mono-Ub (Setsuie and
Wada, 2007). In Chapter 3, we demonstrated that both UCH-L1 and mono-Ub are
decreased in the SN but maintained in the VTA 24 h after MPTP exposure. These
results lead to the hypothesis that maintenance of UCH-L1 could be protective in MLDA
neurons and that loss of UCH-L1 in NSDA neurons contributes to susceptibility to
MPTP.
One of the major risk factors for developing PD is advanced age, and data examining
DA metabolic homeostasis in aged NSDA and MLDA neurons was presented in
Chapter 6. The vast majority of idiopathic PD patients without mutations are diagnosed

203

in elderly patients (Calne and William Langston, 1983), which suggests that the aging
process could contribute to development and progression of PD. Indeed, oxidative
stress in the brain is increased with aging (Floyd et al., 2001), and since oxidative stress
is predicted to play a substantial role in development and progression of PD (Chen et
al., 2008; Sun and Chen, 1998), aging and PD appear to go hand in hand. However,
there is clearly a difference between neurodegeneration of NSDA neurons in PD and
normal age-related decline of NSDA neurons (Stark and Pakkenberg, 2004). Why some
elder patients develop PD while others do not is a critical question in neurodegenerative
research. Investigation of differentially susceptible DA neuronal populations represents
a valid approach to elucidate potentially protective mechanisms, such as UPS, that
could be targeted in the treatment of PD.
In Chapter 6, it was demonstrated that NSDA and MLDA neurons in young and old
mice are equally susceptible to acute MPTP exposure, and highlighted an important
protective role for NAc astrocytes that may account for maintenance of MLDA
resistance to toxicity. The function of the UPS, and in particular expression and function
of UCH-L1, has not been examined in differentially susceptible neuronal populations of
aged mice. In fact, no data is currently available in the literature describing the effects of
aging on UCH-L1 expression in NSDA and MLDA neurons. In this chapter, we sought to
determine if UCH-L1 expression or function are altered in aged mice, and whether
responses of aged mice to MPTP is associated with maintenance of UCH-L1
expression and function in the VTA.

204

Results
UPS and UCH-L1 function and expression in NSDA and MLDA neurons in aged mice
exposed to MPTP
In order to compare responses in brain regions containing NSDA and MLDA axon
terminals (the ST and NAc, respectively), whole tissue microdissection was employed.
UPS function in the ST (Fig. 7.1) is maintained between young and aged mice exposed
to MPTP. In the NAc, similarly, UPS function was not impaired in either age or treatment
group (Fig. 7.2).
UPS function and UCH-L1 expression in ST synaptosomes from young and aged mice
following acute MPTP exposure
Using ST synaptosomes, axon terminals from NSDA neurons were isolated to
specifically measure endpoints that may be masked by the presence of other neuronal
or glial populations in the brain region. Ub protein accumulation was measured in ST
synaptosomes and the UPS was found to be impaired in both age groups 24 h after
MPTP treatment (Fig. 7.3). Next, to determine if UCH-L1 expression is decreased with
aging and neurotoxicant treatment in axon terminals of NSDA neurons, UCH-L1 was
measured in ST synaptosomes in young and aged mice exposed to MPTP (Fig. 7.4).
UCH-L1 was not different in either age or neurotoxicant treatment groups.

205

Figure 7.1. Total Ub protein in the ST. Young (VH n=7; MPTP n=5) and Aged (VH
n=10; MPTP n=9) mice were injected with VH or MPTP and sacrificed 24 h later. The ST
was microdissected and total Ub proteins were measured via Western blotting. Data is
plotted as mean + SEM. No statistically significant differences were detected (p > 0.05)
via two-way ANOVA.

206

Figure 7.2. Total Ub protein in the NAc. Young (VH n=7; MPTP n=7) and Aged (VH
n=9; MPTP n=10) mice were injected with VH or MPTP and sacrificed 24 h later. The
NAc was microdissected and total Ub proteins were measured via western blotting.
Data is plotted as mean + SEM. No statistically significant differences were detected via
two-way ANOVA (p > 0.05).

207

Figure 7.3. Total Ub proteins in ST synaptosomes. Young (VH n=7; MPTP n=8) and
Aged (VH n=9; MPTP n=9) mice were injected with VH or MPTP and sacrificed 24 h
later. ST synaptosomes were prepared and total Ub was measured via Western
blotting. Data is plotted as mean + SEM and asterisk (*) indicates a statistically
significant difference where p < 0.05 via two-way ANOVA and a post hoc Holm-Sidak
test.

208

Young
VH

Aged

MPTP VH MPTP

UCH-L1
GAPDH

Figure 7.4. UCH-L1 protein in ST synaptosomes. Young (VH n=7; MPTP n=8) and
Aged (VH n=10; MPTP n=10) mice were injected with VH or MPTP and sacrificed 24
h later. ST synaptosomes were prepared and UCH-L1 was measured via Western
blotting. Data is plotted as mean + SEM. No statistically significant differences were
detected via two-way ANOVA (p > 0.05).

209

UPS impairment, UCH-L1 expression and function in SN and VTA in aged mice
To examine the effects of aging on UPS function under basal conditions in the SN and
VTA, accumulation of total Ub proteins was measured (Fig. 7.5). In both the SN and
VTA, aged mice showed increased total Ub proteins and there was no difference in the
extent of Ub accumulation between the two brain regions. To determine if expression of
UCH-L1 is decreased with advanced age, UCH-L1 protein expression was measured in
SN and VTA between young and aged mice (Fig. 7.6). There was no age-related
change in UCH-L1 protein in either brain region. UCH-L1 function was assessed by
measuring mono-Ub levels (Fig. 7.7) and there were no differences between brain
regions or age groups.
Effects of MPTP on UCH-L1 expression in the SN and VTA of young and aged mice
Although UCH-L1 expression and function do not appear to be impaired with normal
aging, it is of interest to determine if the decrease in UCH-L1 observed in the SN
(Benskey et al., 2012) (Fig. 3.11) in young mice is exacerbated in aged mice. When we
measured UCH-L1 in the SN in young and aged mice 24 h after MPTP exposure, we
found that UCH-L1 was decreased to the same extent in both young and aged mice
(Fig. 7.8). In the VTA, where UCH-L1 has previously been demonstrated to be
maintained 24 h after MPTP exposure (Fig. 3.12), UCH-L1 was measured in young and
aged mice exposed to MPTP. UCH-L1 expression was maintained in both young and
aged mice 24 h after MPTP expression (Fig. 7.9).

210

Figure 7.5. Total Ub protein in the SN and VTA in Young and Aged mice. Young
and Aged mice were sacrificed and the SN (Young n=7; Aged n=8) and VTA (Young
n=9; Aged n=9) were microdissected and total Ub proteins were measured via
western blotting. Data is plotted as mean + SEM and asterisk (*) indicates a
statistically significant difference between groups via two-way ANOVA and a post hoc
Holm-Sidak test.

211

Figure 7.6. UCH-L1 protein in the SN and VTA in Young and Aged mice.
Young and aged mice were sacrificed and the ST (Young n=9; Aged n=9) and
NAc (Young n=8; Aged n=8) were microdissected and UCH-L1 was measured via
western blotting. Data is plotted as mean + SEM. No statistically significant
difference was detected via two-way ANOVA (p > 0.05).

212

Figure 7.7. Mono-Ub protein in the SN and VTA in Young and Aged mice.
Young and aged mice were sacrificed and the SN (Young n=9; Aged n=5) and
VTA (Young n=5; Aged n=6) were microdissected and mono-Ub protein was
measured via western blotting. Data is plotted as mean + SEM. No statistically
significant difference was detected between groups via two-way ANOVA (p >
0.05).

213

Figure 7.8. UCH-L1 protein in the SN Young and Aged mice treated with VH or
MPTP. Young (VH n=7; MPTP n=6) and Aged (VH n=8; MPTP n=8) mice were sacrificed
and the SN was microdissected and UCH-L1 was measured via western blotting. Data is
plotted as mean + SEM. No statistically significant difference was detected via two-way
ANOVA (p > 0.05).

214

Figure 7.9. UCH-L1 protein in the VTA Young and Aged mice treated with VH or
MPTP. Young (VH n=8; MPTP n=8) and Aged (VH n=9; MPTP n=10) mice were
sacrificed and the VTA was microdissected and UCH-L1 was measured via western
blotting. Data is plotted as mean + SEM. No statistically significant difference was
detected via two-way ANOVA (p > 0.05).

215

Discussion
In this chapter, the effects of aging and MPTP exposure were determined in NSDA axon
terminals between young and aged mice. UPS function was estimated by measuring
total Ub proteins. When the UPS is impaired, a buildup of poly-Ub substrates occurs
(Canu et al., 2000) and we can compare the extent of accumulation between brain
regions, ages, and treatment groups. In ST synaptosomes in aged and young mice,
MPTP caused impairment of the UPS. This effect was not observed in ST
microdissected tissue, however. The discrepancy in these results points out an
important caveat for comparison between the ST and NAc in these studies, mainly
because we are unable to assay endpoints specifically in axon terminals in the NAc due
to the small size of the NAc in mice. In ST whole tissue, perhaps glial UPS function is
intact, which masks the impairment we see in ST synaptosomes.
Although both synaptosome preps and tissue microdissection approaches are useful
and provide insight into age and neurotoxicant exposure related impairments of UPS
function, we must use some caution in interpreting the response, because a lack of
impairment in the UPS in the NAc could also logically be due to glial cells. Similar to
UPS function, UCH-L1 was also not altered in ST synaptosomes from young and aged
mice exposed to MPTP. These results in young mice exposed to MPTP are congruent
with UCH-L1 expression in ST synaptosomes demonstrated in Chapter 4.
Because there was no increased susceptibility to MPTP in aged NSDA and MLDA
neurons in Chapter 6, we sought to determine if UPS function was altered with aging in
the SN and VTA. We found that the UPS is impaired with aging in both brain regions,

216

which is an unexpected finding based on the lack of UPS impairment with age in the ST
and NAc. Clearly, there are differences in UPS dynamics between the cell body regions
and axon terminal regions, especially with respect to UCH-L1 which is only differentially
regulated in the SN and VTA and maintained in axon terminal regions after MPTP
exposure. Whether this difference between cell body regions and axon terminals is due
to transport of UCH-L1 is unknown, since no mechanism for how UCH-L1 is transported
from cell body regions to axon terminals has been reported. The fact that the UPS was
impaired in both the SN and VTA with age demonstrates that aging impairs UPS activity
to a similar degree in both regions.
We predicted that the VTA would be resistant to age-dependent UPS impairment based
the resistance of MLDA neurons to MPTP, but this was not the case. Understandably,
the effect of acute MPTP on UPS is predicted to be much milder compared to the
effects a large age difference between mice could produce. When we measured UCHL1, we found no age-related decrease in UCH-L1 in either the SN or VTA. These results
indicate that although UCH-L1 expression was maintained in each region with aging,
total Ub proteins were increased with aging. To understand whether UCH-L1 function is
decreased in aged SN or VTA, we measured mono-Ub levels and did not detect a
difference in aged mice. Therefore, although UCH-L1 expression and function remain
intact in aged SN and VTA, UPS function is impaired and there is an accumulation of
Ub substrates. These results demonstrate an apparent disconnect between UCH-L1
expression and function with regard to UPS function and suggest that there are likely
other factors that mediate UPS activity in aging. Another question addressed in these
experiments is changes in UCH-L1 expression after MPTP in the cell body regions of
217

NSDA and MLDA neurons in aged mice. We wanted to know whether the decrease in
UCH-L1 protein in the SN would be exacerbated in aged mice or if the VTA is rendered
susceptible to loss of UCH-L1 expression with advanced age. The results showed that
UCH-L1 is decreased to a similar extent in the SN in young and aged mice 24 h after
MPTP exposure. Similarly, NSDA axon terminals also do not appear to be more
susceptible to acute MPTP exposure with advanced age. UCH-L1 expression is not
decreased in the VTA of aged mice 24 h after MPTP, suggesting that the resistance of
MLDA neurons to MPTP is not affected by advanced age. Although maintenance of
UCH-L1 expression is associated with decreased susceptibility to MPTP in MLDA
neurons (Chapter 3) aging still caused impairment of the UPS in the VTA, which
appears to be independent of UCH-L1 expression and function. Whether function of
UCH-L1 truly serves to promote UPS activity is not fully understood, especially in the
context of differential susceptibility and aging.
Summary and conclusions
This is the first study that has examined UCH-L1 expression and function and UPS
function in regions containing NSDA and MLDA neurons in aged mice exposed to
MPTP. Our data suggest that although UCH-L1 expression and function are maintained
in regions containing MLDA neurons, aging caused UPS impairment in both susceptible
and non-susceptible populations. Since mono-Ub pool levels may not directly influence
UPS activity (if the impairment is in the 26S proteasome, for example), the contribution
of UCH-L1 to promoting UPS function in aging and neurotoxicant treatment in the brain
regions studied is not yet clear. Further studies to elucidate if the 26S proteasome itself

218

is impaired should be conducted in aged animals and animals exposed to acute MPTP
toxicity.

219

REFERENCES

220

REFERENCES

Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Calne, D., William Langston, J., 1983. AETIOLOGY OF PARKINSON’S DISEASE.
Lancet 322, 1457–1459. doi:10.1016/S0140-6736(83)90802-4
Canu, N., Barbato, C., Ciotti, M.T., Serafino, A., Dus, L., Calissano, P., 2000.
Proteasome involvement and accumulation of ubiquitinated proteins in cerebellar
granule neurons undergoing apoptosis. J. Neurosci. 20, 589–99.
Chen, D., Wilkinson, C.R.M., Watt, S., Penkett, C.J., Toone, W.M., Jones, N., Bähler, J.,
2008. Multiple pathways differentially regulate global oxidative stress responses in
fission yeast. Mol. Biol. Cell 19, 308–317. doi:10.1091/mbc.E07
Floyd, R.A., Hensley, K., Takeda, A., Nunomura, A., Atwood, C.., Perry, G., al., et,
2001. Oxidative stress in brain aging. Implications for therapeutics of
neurodegenerative diseases. Neurobiol. Aging 23, 795–807. doi:10.1016/S01974580(02)00019-2
Kitada, T., Asakawa, S., Hattori, N., Matsumine, H., Yamamura, Y., Minoshima, S.,
Yokochi, M., Mizuno, Y., Shimizu, N., 1998. Mutations in the parkin gene cause
autosomal recessive juvenile parkinsonism. Nature 392, 605–8. doi:10.1038/33416
Leroy, E., Boyer, R., Auburger, G., Leube, B., Ulm, G., Mezey, E., Harta, G.,
Brownstein, M.J., Jonnalagada, S., Chernova, T., Dehejia, A., Lavedan, C., Gasser,
T., Steinbach, P.J., Wilkinson, K.D., Polymeropoulos, M.H., 1998. The ubiquitin
pathway in Parkinson’s disease. Nature. doi:10.1038/26652
Ross, C. a., Pickart, C.M., 2004. The ubiquitin-proteasome pathway in Parkinson’s
disease and other neurodegenerative diseases. Trends Cell Biol. 14, 703–711.
doi:10.1016/j.tcb.2004.10.006
Setsuie, R., Wada, K., 2007. The functions of UCH-L1 and its relation to
neurodegenerative diseases. Neurochem. Int. 51, 105–11.
doi:10.1016/j.neuint.2007.05.007
Stark, A.K., Pakkenberg, B., 2004. Histological changes of the dopaminergic
nigrostriatal system in aging. Cell Tissue Res. 318, 81–92. doi:10.1007/s00441004-0972-9
221

Sun, A., Chen, Y., 1998. Oxidative stress and neurodegenerative disorders. J. Biomed.
Sci. 65212, 401–414.

222

Chapter 8: General Discussion
Differential regulation of UCH-L1 in regions containing NSDA and MLDA neurons
PD is a debilitating neurodegenerative disease that has no known cure. No disease
modifying therapies are currently available to halt the degeneration of NSDA neurons
and spread of pathology throughout the brain. Current therapies for PD only address the
motor dysfunction and generally revolve around replacing DA. TIDA and MLDA
neurons, however, are invulnerable and less vulnerable to degeneration in PD,
respectively (Braak and Braak, 2000) and understanding how non-susceptible neurons
evade destruction is a major avenue of investigation. To study the differential
susceptibility between DA neuronal populations using a rodent model of oxidative stress
that targets DA neurons, we use the acute MPTP paradigm which recapitulates
vulnerability of NSDA neurons and resistance of TIDA and MLDA neurons (Behrouz et
al., 2007; Benskey et al., 2012, 2015; Hung and Lee, 1998).
Since resistant TIDA neurons lack high expression of DAT, have drastically different
axon lengths compared to NSDA neurons, are functionally dissimilar to NSDA neurons
and are regulated differently (Lookingland and Moore, 2005), comparisons between
NSDA and TIDA neurons are useful but may be limited. On the other hand, MLDA
neurons are very similar to NSDA neurons and more work has been done to
characterize the differential susceptibility between NSDA and MLDA neurons (Surmeier
et al., 2017).
In previous studies involving comparisons between NSDA and MLDA neurons, the
relevance of maintaining calcium homeostasis has been emphasized. Increased
223

cytosolic calcium can lead to apoptosis (Nagley et al., 2010). NSDA neurons are highly
metabolically active and experience an influx of high concentrations of cytosolic calcium
due to their abundance of L-type Ca2+ channels. MLDA neurons are also active, but
express lower levels of L-type Ca2+ channels (Philippart et al., 2016) and also express a
calcium binding protein called calbindin not expressed in the SN (Foehring et al., 2009)
that is thought to protect MLDA neurons from the effects of high cytosolic calcium. A
promising study for the calcium channel blocker isradipine to treat PD is currently in
clinical trial (Surmeier et al., 2017).
A pathological hallmark of PD is the presence of Lewy bodies in the SN containing high
amounts of α-syn (Spillantini et al., 1997). These cytosolic inclusions of misfolded
proteins also contain Ub and Ub-proteins (Kuzuhara et al., 1988), which suggests that
deficits in protein degradation could play a role in pathology of PD. Indeed, evidence of
UPS impairment has been demonstrated in post mortem brain tissue from PD patients
(McNaught and Jenner, 2001). Since UCH-L1 is a DUB mutated in familial PD (Leroy et
al., 1998), demonstrated to influence availability of mono-Ub pools (Nagamine et al.,
2010; Osaka et al., 2003), and by logical extension modulate UPS function, we have
sought to investigate the contribution of UCH-L1 to susceptibility of NSDA neurons and
non-susceptibility of MLDA neurons to acute MPTP exposure.
As demonstrated in Chapter 3 UCH-L1 protein is decreased in the SN 24 h after MPTP
exposure, a finding consistent with a previous report from our laboratory (Benskey et al.,
2012). In TIDA neurons, however, UCH-L1 was upregulated (Benskey et al., 2012),
leading to the hypothesis that UCH-L1 could contribute to resistance of TIDA neurons to
MPTP-induced toxicity manifested by a decrease in intracellular DA and TH expression.
224

The expression of UCH-L1 in MLDA neurons had not been previously investigated, so
we sought to characterize expression and function of UCH-L1 after MPTP exposure. As
predicted, UCH-L1 expression was maintained in the VTA 24 h after MPTP. This
maintenance of UCH-L1 protein was accompanied by maintenance of UCH-L1 function,
as measured by levels of mono-Ub protein. Therefore, we hypothesized that UCH-L1
expression and function contributed to the differential susceptibility of NSDA and MLDA
neurons to acute MPTP exposure.
The endpoints examined for determining differential susceptibility in the context of the
acute MPTP model are intracellular DA and TH expression, since a single injection of
20 mg/kg MPTP does not result in cell death. One of the mechanisms of MPTP toxicity
is displacement of DA in synaptic vesicles (Dauer and Przedborski, 2003), which results
in increased cytosolic DA where it can become deprotonated and metabolized to toxic
metabolites, resulting in oxidative stress and subsequent neuronal damage (Hastings et
al., 1996). After MPTP exposure, the extent of DA loss in the ST was greater than in the
NAc (Chapter 3)(Behrouz et al., 2007). This differential susceptibility is likely not due to
tissue penetration of MPTP, since cell body and axon terminal regions of NSDA and
MLDA neurons are in similar locations in the brain and MPTP easily crosses the bloodbrain barrier.
DAT expression, however, is predicted to play a role in susceptibility to MPP+ toxicity
because it is the avenue through which MPP+ gains access to the cytosol of DA neuron
axon terminals (Dauer and Przedborski, 2003). One study determined that DA uptake is
higher in the ST than the NAc (Marshall et al., 1990). Therefore, it was hypothesized
that differential susceptibility of DA neuronal populations to toxicant models of DA
225

selective neurodegeneration (i.e., 6-OHDA and MPTP) is related to expression of DAT
(Uhl, 1998). However, in a study that measured uptake of MPP+ specifically in the ST
and NAc after chronic direct infusion of MPP+, no differences in uptake were detected
(Hung et al., 1995), leading the authors to conclude that differential susceptibility
between NSDA and MLDA neurons is not due to reduced uptake of MPP + in the NAc. In
addition, other models have demonstrated that MLDA neurons are less susceptible to
neurodegeneration than NSDA neurons, including an rAAV overexpressing α-syn model
(Maingay et al., 2006). Although intracellular DA depletion may not be a perfect
endpoint to attempt to rescue using manipulations in pathways known to be affected in
PD, it is one way in which MPP+ differentially affects NSDA and MLDA neurons that is
not affected by uptake of MPP+.
The rate limiting enzyme of DA synthesis, TH, is also decreased in the ST to a greater
extent than the NAc after MPTP (Chapter 3). A decrease in TH in the NSDA could
logically result in decreased synthesis of DA, but with the effects of MPP+ on decreasing
intracellular DA by itself, any decreases in synthesis of DA could be masked by these
effects. Since MPP+ causes oxidative stress in mouse brain tissue (Johannessen et al.,
1986), reactive oxygen species within the cell could cause oxidation of TH. Oxidatively
damaged TH could become toxic to the cell, so therefore, oxidatively modified TH must
be degraded. The main degradation pathway involved in regulating turnover of TH is the
UPS (Congo Carbajosa et al., 2015). TH must be phosphorylated prior to UPSmediated degradation (Nakashima et al., 2011). However, if TH is primarily degraded by
the proteasome and UPS function becomes impaired, we would actually expect to see
more TH protein in regions where the UPS is inhibited, such as in ST synaptosomes
226

(Chapter 7). It is possible that the total amount of TH does not actually decrease in the
ST and NAc after MPP+ but is oxidatively modified, which could prevent the antibody
from binding to the protein. In any case, our second DA neuron specific endpoint for
comparing susceptibility between NSDA and MLDA neurons, TH expression, is
decreased to a greater extent than in the NAc 24 h after MPTP exposure.
Although DA and TH are used as DA specific endpoints measured after MPTP
exposure, a direct link between UCH-L1 and regulation of specific DA phenotype is not
apparent. Rather, since UCH-L1 functions within the scope of the UPS, we predict that
a decrease in UCH-L1 expression or function would result in UPS impairment. Indeed,
UPS function (as estimated by the accumulation of total Ub proteins) is impaired in ST
synaptosomes 24 h after MPTP (Chapter 7), while in whole NAc tissue UPS function is
maintained. UPS dysfunction has been demonstrated in regions containing NSDA
neurons (Lansdell, 2017). Unexpectedly, UCH-L1 function is not decreased in axon
terminal regions of NSDA neurons 24 h after MPTP (Chapter 3), however, and actually
recovers in ST synaptosomes after being decreased at 6 h (Chapter 4). An important
caveat for examining UPS function in the ST and NAc is that any changes in mono-Ub
or total Ub are likely masked by glial UPS function and do not reflect UPS function in DA
neuron terminals. These results demonstrate that UCH-L1 expression and function may
not directly influence UPS function and calls into question whether it would be logical to
attempt to rescue NSDA neurons by overexpressing UCH-L1 in the SN. If the SN
attempted to compensate for MPP+ induced toxicity by transporting UCH-L1 to the ST
and that compensation did not have any effect on susceptibility to loss of TH or

227

impairment of UPS function, then it appears that restoring UCH-L1 to the ST would be
no use.
Although we had predicted that levels of available mono-Ub likely influence proper
function of the UPS since substrates must be tagged with Ub to be degraded by the 26S
proteasome, dysfunction in the structure of the 26S proteasome itself could lead to
accumulation of poly-Ub substrates, which would not necessarily be affected by UCHL1 function. Oxidative modification of the proteasome has been demonstrated (Wang et
al., 2010). Therefore, even though UCH-L1 (and not other related DUBs, as shown in
Chapter 4) influences levels of mono-Ub in NSDA and MLDA neurons, impairment of
the UPS could occur at a different part of the pathway, which renders availability of the
mono-Ub pool potentially less relevant for promoting UPS function. Again, however, we
are unable to separate the effects on UPS and mono-Ub in glial cells versus axon
terminals. Mono-Ub is not only relevant for the UPS, however: K63-linked poly-Ub
chains are found on substrates destined for autophagic degradation (Tan et al., 2007).
Possible contribution of UCH-L1 function in autophagy
In Chapter 4, we examined the potential role of UCH-L1 in promoting autophagy in
parkin deficient mice. In the absence of parkin the UPS is impaired (Lansdell, 2017). In
addition, mitochondrial quality is also decreased in parkin deficient mice (Palacino et al.,
2004), which is predicted due to parkin’s role in regulating mitophagy (Damiano et al.,
2014). Despite these deficits, parkin deficient mice do not have an obvious parkinsonian
phenotype (Perez and Palmiter, 2005). Lifetime compensation for the loss of parkin are

228

expected to play a role in the apparent disconnect between the importance of parkin
function and relatively normal phenotype of the knock out mouse.
One obvious mechanism that could compensate for decreased UPS function in the
absence of parkin is upregulation of the ALP, which was demonstrated in Chapter 4.
Macroautophagy, rather than CMA, was found to be increased in parkin deficient mice
due to the observed increase in LC3B-II protein (signifying an increase in abundance of
autophagosomes) and no accumulation of p62 (signifying normal function of the ALP).
How UCH-L1 function could contribute to upregulation of autophagy is not directly
known, but one piece of the puzzle is how UCH-L1 is regulated directly by parkin: UCHL1 is ubiquitinated by parkin via a K63-linked poly-Ub chain to signal degradation of
UCH-L1 via autophagy (McKeon et al., 2014). It is thought that parkin downregulates
UCH-L1 in conditions of stress in order to prevent UCH-L1-mediated removal of Ub, a
function of UCH-L1 that could potentially interfere with UPS degradation of substrates.
Since parkin is an E3 ligase (Shimura et al., 2000), its activity is considered to oppose
the DUB function of UCH-L1. In absence of parkin, however, UCH-L1 expression is
elevated in the SN (Chapter 4), which coincides with upregulation of autophagy in
parkin deficient mice. In the face of UPS impairment, it may be beneficial to remove Ub
from substrates to allow them to be degraded by autophagy.
One paper demonstrated that UCH-L1 in its dimeric form in vitro can act as a ligase and
ubiquitinate α-syn via K63-linked poly-Ub chains, which would target the protein for
degradation by autophagy (Liu et al., 2002). The presence of dimeric UCH-L1 and its
ligase activity, however, has not been demonstrated in vivo. Also not clear is how
maintenance of mono-Ub pools by UCH-L1 function could contribute to protein
229

degradation by autophagy. Little is known about the feasibility of how UCH-L1 function
could contribute to autophagy and whether this influence involves regulation of monoUb pools. In a study using the UCH-L1 inhibitor LDN-57444, inhibition of UCH-L1 in
transgenic mice overexpressing α-syn resulted in protective effects mediated by
upregulation of autophagy (Cartier et al., 2012), essentially suggesting that UCH-L1
function under those particular conditions is detrimental rather than helpful in promoting
autophagy. Clearly, more work is needed to understand how UCH-L1 function could
relate to the ALP, but it is reasonable to think that UCH-L1 function could affect
autophagic degradation of protein substrates and that this mechanism is important for
compensation of loss of UPS activity.
Use of the UCH-L1 inhibitor LDN-57444 in vivo
Previous studies showed effects of LDN-57444 on synaptic structure and function in
mice (Cartier et al., 2012, 2009; Gong et al., 2006; Zhang et al., 2014). These previous
studies examined regions of the brain involved in memory and cognition with special
relevance to AD. We sought to determine if loss of UCH-L1 function would render
MLDA neurons more vulnerable to MPTP-induced toxicity and exacerbate susceptibility
of NSDA neurons. Although LDN-57444 administration had no effect on DA
homeostasis by itself, it exerted a protective effect against MPTP-induced loss of DA in
both NSDA and MLDA neurons (Chapter 5). A protective role for UCH-L1 inhibition has
already been demonstrated in pathological conditions (Cartier et al., 2012) with respect
to α-syn clearance via autophagy, but the relevance of such mechanisms relating to
susceptibility of DA neurons to neurotoxicant exposure is unknown in our acute MPTP

230

model, and we do not expect to induce α-syn pathology with an acute paradigm (Gibrat
et al., 2009).
The apparent effect of LDN-57444 administration on susceptibility to loss of DA after
MPTP could not be directly attributed to a decrease in UCH-L1 function because
attempts to measure target engagement were inconclusive, since the ability of UCH-L1
to bind and sequester mono-Ub may not be affected by LDN-57444 or obscured by
mono-Ub in other cells in tissue samples. Also currently unknown is how much LDN57444 distributes in mouse brain tissue after i.p. administration, and a potential time
course of events that affect its efficacy to reduce mono-Ub levels. One possibility, if
UCH-L1 inhibition did occur, is that UCH-L1 plays a different role in DA neurons
compared to previously studied hippocampal neurons. Synaptic structure and function is
regulated in part by UPS mediated protein turnover (Yi and Ehlers, 2005), and therefore
UCH-L1 can be hypothesized to play a role in UPS-mediated regulation at the level of
the synapse. However, a specific role for UCH-L1 in DA neuron synaptic activity has not
yet been established.
More research is needed to determine if there is a specific function of UCH-L1 with
special relevance to DA neuronal homeostasis. The original model of UCH-L1
deficiency, the gad mouse (Nagamine et al., 2010), while afflicted with
neurodegeneration in the gracile tract, has no parkinsonian phenotype and homozygous
animals for the mutation die prematurely after only 6 months of life. Interestingly, the
gracile tract contains the longest axons in the body, suggesting that UCH-L1 function is
important for maintenance of axonal structure. Indeed, UCH-L1 is critical for
maintenance of the neuromuscular junction (Chen et al., 2010). It is hypothesized that
231

perhaps if gad mice lived long enough, DA neurons would be affected by lack of UCHL1 function. In one German family, a mutation in UCH-L1 that resulted in a 50%
decrease in hydrolase activity (I93M) caused PD (Leroy et al., 1998). However, in
children with a different mutation in UCH-L1 (Glu7Ala), a completely different
phenotypic consequence of loss of UCH-L1 function is manifested, which the authors
termed “neurodegeneration with optical atrophy” (Bilguvar et al., 2013).
From these mouse models lacking UCH-L1 and from human patients with UCH-L1
mutations, it is clear that UCH-L1 expression is necessary for proper function of the
nervous system. It is possible that UCH-L1 fulfills a necessary function specifically in DA
neurons that is yet to be uncovered, or that mutated UCH-L1 has an increased
propensity to aggregate (Setsuie et al., 2007) in brain regions sensitive to perturbations
in the UPS and autophagy, which could explain why patients with I93M mutation in
UCH-L1 developed PD as opposed to a different neurodegenerative phenotype.
Effects of aging on susceptibility of NSDA and MLDA neurons
PD is a disease most commonly diagnosed in elderly patients, yet the majority of
preclinical models to test new therapies do not take aging into account. Increased
oxidative stress has been shown to occur with aging (Finkel and Holbrook, 2000), and
with the pathology of PD closely linked to oxidative stress, it is reasonable to surmise
that aged brains are more susceptible to development of PD due in part to age-related
accumulation of oxidative damage. In the studies presented in this Dissertation no
losses of DA, TH, DAT, or VMAT2 were observed in the ST of aged mice versus young
mice (Chapter 6). In the NAc, however, we did observe an age-related decrease in DA

232

(without effects on TH, DAT, or VMAT2) in the aged mice. This decrease in DA in the
aged NAc has been demonstrated before in rats (Huang et al., 1995).
In addition to potential effects of aging on DA neurons, aging could differentially affect
glia in the ST and NAc, particularly astrocytes. Astrocytes are expected to play a role in
DA metabolic homeostasis because they express MAO-B and COMT, which can uptake
and metabolize DOPAC and DA, respectively (Levitt et al., 1982). An excess in synaptic
DA is predicted to be harmful, since the incidence of DA adducts could increase and
cause toxicity (Hastings et al., 1996). Therefore, astrocyte role in metabolism of
extracellular DA is considered protective. We demonstrated in Chapter 6 that
astrocytes from the NAc, not the ST, retain the ability to metabolize DA into 3-MT (with
no changes in either region to COMT). The idea that astrocytes maintain their protective
function to prevent excess DA accumulation in the synapse is especially relevant when
we examine the susceptibility of aged MLDA neurons to acute MPTP.
The susceptibility of aged mice to chronic MPTP has been previously reported and
chronic MPTP exposure causes degeneration in both the SN and VTA in aged mice (to
a lesser extent in the VTA than the SN) (Gupta et al., 1986). However, no information is
available about the effects of a single dose of MPTP on differentially susceptible DA
neuron populations. To determine whether MLDA neurons are rendered more
susceptible to MPTP-induced damage, aged mice were acutely exposed to MPTP. As
seen in young mice, depletion of DA is more extensive in both young and aged ST
exposed to MPTP. However, aged MLDA neurons are still less susceptible to MPTP
exposure compared to ST neurons (Chapter 6) and are not made more vulnerable to
MPTP-induced injury.
233

One possibility as to why aged MLDA neurons retain their resistance to acute MPTP
exposure is that NAc astrocytes retain their ability to metabolize synaptic DA and
prevent DA-induced oxidative damage. Although the distribution of astrocytes between
the ST and NAc in young animals is equivalent (Emsley and Macklis, 2006), age-related
declines in astrocytes and their function have not been comprehensively examined in
the ST and NAc. These data reveal that, although most of the focus of attempting to
characterize and study mechanisms in NSDA and MLDA neurons that contribute to
differential susceptibility focus on the DA neurons, we must not forget about the
contributions of non-neuronal cells that could influence susceptibility.
Effects of aging on UPS and UCH-L1 function
No previous studies have been published reporting UCH-L1 expression in aged mice,
so we sought to determine if there are age-related decreases in UPS and UCH-L1
function. In axon terminals of NSDA neurons, the UPS is impaired in both young and
aged mice in the absence of alterations in UCH-L1 expression (Chapter 7). As
discussed above, maintenance of UCH-L1 function does not seem to always result in
maintenance of UPS function in ST synaptosomes. In microdissected ST and NAc
tissue, however, UPS function was intact. The most interesting age-related effects
occurred in the SN and VTA, where both regions experienced impairment of the UPS
with advanced age (Chapter 7). There was no age-related decline in UCH-L1 protein or
activity (as measured by mono-Ub levels) in the SN or VTA. The UPS has been shown
to be compromised with advanced age (Saez and Vilchez, 2014), but until now, UCH-L1
expression in aging neurons had not yet been examined. We conclude that UCH-L1
expression is not lost in brain regions containing NSDA or MLDA neurons.
234

By 24 h after MPTP exposure, UCH-L1 was decreased in both young and aged mice in
the SN (Chapter 7). In the VTA, however, MPTP exposure did not cause a decrease in
UCH-L1 in either age group. If our hypothesis was correct and UCH-L1 was a major
contributor to differences in NSDA and MLDA neuronal responses to toxicant exposure,
we would predict that increased susceptibility of MLDA neurons to MPTP would be
correlated with a decrease in UCH-L1 protein. The UCH-L1 expression in aged MLDA
neurons matches the decreased susceptibility to MPTP compared to the NSDA
neurons, but maintenance of UCH-L1 expression does not appear to protect aged
NSDA or MLDA neurons from age-related UPS impairment. Since UCH-L1 was
postulated above to have a potential role in promoting autophagy, perhaps maintenance
of UCH-L1 contributes to autophagic degradation of substrates rather than UPSmediated degradation. Autophagy is also decreased in aging (Cuervo, 2008), but has
not been examined in NSDA and MLDA neurons in the context of acute MPTP
administration. Further study is needed to understand how UCH-L1 may contribute to
UPS function with age, neurotoxicant treatment, and a potential compensation for UPS
impairment by promoting autophagy.

235

Figure 8.1. Summary of major findings in this Dissertation. This diagram
summarizes new information demonstrated regarding UPS and UCH-L1 function
after MPTP exposure and aging in regions containing NSDA and MLDA neurons.

236

Future directions

To directly test whether UCH-L1 protects MLDA neurons, an rAAV vector expressing an
siRNA to knock down UCH-L1 could be delivered to the VTA to determine if MLDA
neurons are made more susceptible to MPTP exposure. In addition, direct effects of
UCH-L1 modulation on mono-Ub levels could be examined. To assess the effects of
UCH-L1 knock out specifically in DA neurons, a DAT-Cre mouse could be used and the
loxP system employed to knock out UCH-L1. To determine if increasing autophagy
could protect DA neurons, administration of an autophagy inducer (such as rapamycin)
could be performed in vitro and in vivo to assess if reduced susceptibility of DA neurons
could be achieved. Finally, pharmacological enhancer of UCH-L1 could be used to
determine if enhancing UCH-L1 function would protect or reverse oxidative damage to
neurons in culture and in vivo.
Conclusions
In this Dissertation, a role for UCH-L1 in determining susceptibility of NSDA and MLDA
neurons was investigated. We demonstrated that UCH-L1 is differentially regulated in
NSDA and MLDA neurons exposed to MPTP. While maintenance of UCH-L1
expression and function were associated with reduced susceptibility to MPTP-induced
injury, UPS function did not appear to be affected by changes in UCH-L1 or it hydrolase
activity. A potential role for UCH-L1 in autophagy was also revealed, but more evidence
is needed regarding the mechanisms underlying this oxidative stress-induced shift in
proteostasis and how this changes with age. The effects of MPTP treatment and aging
on UPS and UCH-L1 function are summarized in Fig. 8.1.

237

The contribution of age-related effects in regions containing cell bodies and axon
terminals of NSDA and MLDA neurons was investigated and a potentially protective role
for NAc astrocytes in synaptic DA homeostasis was revealed. Although it is currently not
clear if UCH-L1 expression and function contribute to susceptibility between NSDA and
MLDA neurons, what is clear from studies on mice and humans lacking functional UCHL1 is that UCH-L1 is absolutely necessary for maintenance of normal function of the
central nervous system. Potential future therapeutic strategies to target UCH-L1 and
perhaps enhance its catalytic activity could be developed and tested for efficacy in
modulating protein degradation pathways such as the UPS and autophagy. One such
enhancer of UCH-L1 activity has been discovered but its effects on UCH-L1 were
modest (increased by 111%) (Mitsui et al., 2010). More potent pharmacological
modulators of UCH-L1 function should be investigated.

238

REFERENCES

239

REFERENCES

Behrouz, B., Drolet, R.E., Sayed, Z.A., Lookingland, K.J., Goudreau, J.L., 2007. Unique
responses to mitochondrial complex I inhibition in tuberoinfundibular dopamine
neurons may impart resistance to toxic insult. Neuroscience 147, 592–8.
doi:10.1016/j.neuroscience.2007.05.007
Benskey, M., Behrouz, B., Sunryd, J., Pappas, S.S., Baek, S.-H.H., Huebner, M.,
Lookingland, K.J., Goudreau, J.L., 2012. Recovery of hypothalamic
tuberoinfundibular dopamine neurons from acute toxicant exposure is dependent
upon protein synthesis and associated with an increase in parkin and ubiquitin
carboxy-terminal hydrolase-L1 expression. Neurotoxicology 33, 321–31.
doi:10.1016/j.neuro.2012.02.001
Benskey, M.J., Manfredsson, F.P., Lookingland, K.J., Goudreau, J.L., 2015. The role of
parkin in the differential susceptibility of tuberoinfundibular and nigrostriatal
dopamine neurons to acute toxicant exposure. Neurotoxicology 46, 1–11.
doi:10.1016/j.neuro.2014.11.004
Bilguvar, K., Tyagi, N.K., Ozkara, C., Tuysuz, B., Bakircioglu, M., Choi, M., Delil, S.,
Caglayan, A.O., Baranoski, J.F., Erturk, O., Yalcinkaya, C., Karacorlu, M., Dincer,
A., Johnson, M.H., Mane, S., Chandra, S.S., Louvi, A., Boggon, T.J., Lifton, R.P.,
Horwich, A.L., Gunel, M., 2013. Recessive loss of function of the neuronal ubiquitin
hydrolase UCHL1 leads to early-onset progressive neurodegeneration. Proc. Natl.
Acad. Sci. U. S. A. 110, 3489–94. doi:10.1073/pnas.1222732110
Braak, H., Braak, E., 2000. Pathoanatomy of Parkinson’s disease. J. Neurol. 247 Suppl,
II3-10. doi:10.1007/PL00007758
Cartier, A.E., Djakovic, S.N., Salehi, A., Wilson, S.M., Masliah, E., Patrick, G.N., 2009.
Regulation of synaptic structure by ubiquitin C-terminal hydrolase L1. J. Neurosci.
29, 7857–68. doi:10.1523/JNEUROSCI.1817-09.2009
Cartier, A.E., Ubhi, K., Spencer, B., Vazquez-Roque, R. a., Kosberg, K.A., Fourgeaud,
L., Kanayson, P., Patrick, C., Rockenstein, E., Patrick, G.N., Masliah, E., 2012.
Differential effects of UCHL1 modulation on alpha-synuclein in PD-like models of
alpha-synucleinopathy. PLoS One 7. doi:10.1371/journal.pone.0034713
Chen, F., Sugiura, Y., Myers, K.G., Liu, Y., Lin, W., 2010. Ubiquitin carboxyl-terminal
hydrolase L1 is required for maintaining the structure and function of the
neuromuscular junction. Proc. Natl. Acad. Sci. 107, 1636–1641.
doi:10.1073/pnas.0911516107
Congo Carbajosa, N.A., Carbajosa, N.A.L., Corradi, G., Verrilli, M.A.L., Guil, M.J., Vatta,
M.S., Gironacci, M.M., 2015. Tyrosine hydroxylase is short-term regulated by the
240

ubiquitin-proteasome system in PC12 cells and hypothalamic and brainstem
neurons from spontaneously hypertensive rats: possible implications in
hypertension. PLoS One 10, e0116597. doi:10.1371/journal.pone.0116597
Cuervo, A.M., 2008. Autophagy and aging: keeping that old broom working. Trends
Genet. 24, 604–12. doi:10.1016/j.tig.2008.10.002
Damiano, M., Gautier, C. a., Bulteau, A.L., Ferrando-Miguel, R., Gouarne, C., Paoli,
M.G., Pruss, R., Auchère, F., L’Hermitte-Stead, C., Bouillaud, F., Brice, A., Corti,
O., Lombès, A., 2014. Tissue- and cell-specific mitochondrial defect in Parkindeficient mice. PLoS One 9. doi:10.1371/journal.pone.0099898
Dauer, W., Przedborski, S., 2003. Parkinson ’ s Disease : Mechanisms and Models 39,
889–909.
Emsley, J.G., Macklis, J.D., 2006. Astroglial heterogeneity closely reflects the neuronaldefined anatomy of the adult murine CNS. Neuron Glia Biol. 2, 175–86.
doi:10.1017/S1740925X06000202
Finkel, T., Holbrook, N.J., 2000. Oxidants, oxidative stress and the biology of ageing.
Nature 408, 239–47. doi:10.1038/35041687
Foehring, R.C., Zhang, X.F., Lee, J.C.F., Callaway, J.C., 2009. Endogenous Calcium
Buffering Capacity of Substantia Nigral Dopamine Neurons. J. Neurophysiol. 102,
2326–2333. doi:10.1152/jn.00038.2009
Gibrat, C., Saint-Pierre, M., Bousquet, M., Lévesque, D., Rouillard, C., Cicchetti, F.,
2009. Differences between subacute and chronic MPTP mice models: investigation
of dopaminergic neuronal degeneration and α-synuclein inclusions. J. Neurochem.
109, 1469–1482. doi:10.1111/j.1471-4159.2009.06072.x
Gong, B., Cao, Z., Zheng, P., Vitolo, O. V, Liu, S., Staniszewski, A., Moolman, D.,
Zhang, H., Shelanski, M., Arancio, O., 2006. Ubiquitin hydrolase Uch-L1 rescues
beta-amyloid-induced decreases in synaptic function and contextual memory. Cell
126, 775–88. doi:10.1016/j.cell.2006.06.046
Gupta, M., Gupta, B.K., Thomas, R., Bruemmer, V., Sladek, J.R., Felten, D.L., 1986.
Aged mice are more sensitive to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine
treatment than young adults. Neurosci. Lett. 70, 326–331. doi:10.1016/03043940(86)90573-2
Hastings, T.G., Lewis, D.A., Zigmond, M.J., 1996. Role of oxidation in the neurotoxic
effects of intrastriatal dopamine injections. Proc. Natl. Acad. Sci. 93, 1956–1961.
Huang, R., Wang, C., Tai, M., Tsai, Y., Peng, M., 1995. Effects of age on dopamine
nrelease in the nucleus accumbens and amphetamine-induced locomotor activity in
rats. Neurosci. Lett. 200, 61–64.
Hung, H.-C., Lee, E.H.., 1998. MPTP Produces Differential Oxidative Stress and
Antioxidative Responses in the Nigrostriatal and Mesolimbic Dopaminergic
241

Pathways. Free Radic. Biol. Med. 24, 76–84. doi:10.1016/S0891-5849(97)00206-2
Hung, H.C., Tao, P.L., Lee, E.H., 1995. 1-Methyl-4-phenyl-pyridinium (MPP+) uptake
does not explain the differential toxicity of MPP+ in the nigrostriatal and mesolimbic
dopaminergic pathways. Neurosci. Lett. 196, 93–6.
Johannessen, J.N., Adams, J.D., Schuller, H.M., Bacon, J.P., Markey, S.P., 1986. 1methyl-4-phenylpyridine (MPP+) induces oxidative stress in the rodent. Life Sci. 38,
743–749. doi:10.1016/0024-3205(86)90589-8
Kuzuhara, S., Mori, H., Izumiyama, N., Yoshimura, M., Ihara, Y., 1988. Lewy bodies are
ubiquitinated. Acta Neuropathol. 75, 345–353. doi:10.1007/BF00687787
Lansdell, T., 2017. THE ROLE OF PARKIN IN MAINTAINING PROTEASOME
ACTIVITY FOLLOWING.
Leroy, E., Boyer, R., Auburger, G., Leube, B., Ulm, G., Mezey, E., Harta, G.,
Brownstein, M.J., Jonnalagada, S., Chernova, T., Dehejia, A., Lavedan, C., Gasser,
T., Steinbach, P.J., Wilkinson, K.D., Polymeropoulos, M.H., 1998. The ubiquitin
pathway in Parkinson’s disease. Nature. doi:10.1038/26652
Levitt, P., Pintart, J.E., Breakefieldt, X. 0, 1982. Immunocytochemical demonstration of
monoamine oxidase B in brain astrocytes and serotonergic neurons (central
nervous system/rat/monoamine) 79, 6385–6389.
Liu, Y., Fallon, L., Lashuel, H.A., Liu, Z., Lansbury, P.T., 2002. The UCH-L1 Gene
Encodes Two Opposing Enzymatic Activities that Affect ␣ -Synuclein Degradation
and Parkinson ’ s Disease Susceptibility 111, 209–218.
Lookingland, K.J., Moore, K.E., 2005. Chapter VIII Functional neuroanatomy of
hypothalamic dopaminergic neuroendocrine systems. Handb. Chem. Neuroanat.
21, 435–523. doi:10.1016/S0924-8196(05)80012-0
Maingay, M., Romero-Ramos, M., Carta, M., Kirik, D., 2006. Ventral tegmental area
dopamine neurons are resistant to human mutant alpha-synuclein overexpression.
Neurobiol. Dis. 23, 522–32. doi:10.1016/j.nbd.2006.04.007
Marshall, J.F., O’Dell, S.J., Navarrete, R., Rosenstein, A.J., 1990. Dopamine highaffinity transport site topography in rat brain: major differences between dorsal and
ventral striatum. Neuroscience 37, 11–21.
McKeon, J.E., Sha, D., Li, L., Chin, L.-S., 2014. Parkin-mediated K63-polyubiquitination
targets ubiquitin C-terminal hydrolase L1 for degradation by the autophagylysosome system. Cell. Mol. Life Sci. doi:10.1007/s00018-014-1781-2
McNaught, K.S.P., Jenner, P., 2001. Proteasomal function is impaired in substantia
nigra in Parkinson’s disease. Neurosci. Lett. 297, 191–194. doi:10.1016/S03043940(00)01701-8
Mitsui, T., Hirayama, K., Aoki, S., Nishikawa, K., Uchida, K., Matsumoto, T., Kabuta, T.,
242

Wada, K., 2010. Identification of a novel chemical potentiator and inhibitors of
UCH-L1 by in silico drug screening. Neurochem. Int. 56, 679–686.
doi:10.1016/j.neuint.2010.01.016
Nagamine, S., Kabuta, T., Furuta, A., Yamamoto, K., Takahashi, A., Wada, K., 2010.
Deficiency of ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1) leads to
vulnerability to lipid peroxidation. Neurochem. Int. 57, 102–110.
doi:10.1016/j.neuint.2010.04.015
Nagley, P., Higgins, G.C., Atkin, J.D., Beart, P.M., 2010. Multifaceted deaths
orchestrated by mitochondria in neurones. Biochim. Biophys. Acta - Mol. Basis Dis.
1802, 167–185. doi:http://dx.doi.org/10.1016/j.bbadis.2009.09.004
Nakashima, A., Mori, K., Kaneko, Y.S., Hayashi, N., Nagatsu, T., Ota, A., 2011.
Phosphorylation of the N-terminal portion of tyrosine hydroxylase triggers
proteasomal digestion of the enzyme. Biochem. Biophys. Res. Commun. 407, 343–
347. doi:10.1016/j.bbrc.2011.03.020
Osaka, H., Wang, Y.L., Takada, K., Takizawa, S., Setsuie, R., Li, H., Sato, Y.,
Nishikawa, K., Sun, Y.J., Sakurai, M., Harada, T., Hara, Y., Kimura, I., Chiba, S.,
Namikawa, K., Kiyama, H., Noda, M., Aoki, S., Wada, K., 2003. Ubiquitin carboxyterminal hydrolase L1 binds to and stabilizes monoubiquitin in neuron. Hum. Mol.
Genet. 12, 1945–1958. doi:10.1093/hmg/ddg211
Palacino, J.J., Sagi, D., Goldberg, M.S., Krauss, S., Motz, C., Wacker, M., Klose, J.,
Shen, J., 2004. Mitochondrial dysfunction and oxidative damage in parkin-deficient
mice. J. Biol. Chem. 279, 18614–18622. doi:10.1074/jbc.M401135200
Perez, F.A., Palmiter, R.D., 2005. Parkin-deficient mice are not a robust model of
parkinsonism. Proc. Natl. Acad. Sci. U. S. A. 102, 2174–9.
doi:10.1073/pnas.0409598102
Philippart, F., Destreel, G., Merino-Sepúlveda, P., Henny, P., Engel, D., Seutin, V.,
2016. Differential Somatic Ca&lt;sup&gt;2+&lt;/sup&gt; Channel Profile in Midbrain
Dopaminergic Neurons. J. Neurosci. 36, 7234 LP-7245.
Saez, I., Vilchez, D., 2014. The Mechanistic Links Between Proteasome Activity, Aging
and Age-related Diseases. Curr. Genomics 15, 38–51.
doi:10.2174/138920291501140306113344
Setsuie, R., Wang, Y.-L., Mochizuki, H., Osaka, H., Hayakawa, H., Ichihara, N., Li, H.,
Furuta, A., Sano, Y., Sun, Y.-J., Kwon, J., Kabuta, T., Yoshimi, K., Aoki, S., Mizuno,
Y., Noda, M., Wada, K., 2007. Dopaminergic neuronal loss in transgenic mice
expressing the Parkinson’s disease-associated UCH-L1 I93M mutant. Neurochem.
Int. 50, 119–29. doi:10.1016/j.neuint.2006.07.015
Shimura, H., Hattori, N., Kubo, S. i, Mizuno, Y., Asakawa, S., Minoshima, S., Shimizu,
N., Iwai, K., Chiba, T., Tanaka, K., Suzuki, T., 2000. Familial Parkinson disease
gene product, parkin, is a ubiquitin-protein ligase. Nat. Genet. 25, 302–5.
243

doi:10.1038/77060
Spillantini, M.G., Schmidt, M.L., Lee, V.M.-Y., Trojanowski, J.Q., Jakes, R., Goedert, M.,
1997. [alpha]-Synuclein in Lewy bodies 388, 839–840.
Surmeier, D.J., Obeso, J.A., Halliday, G.M., 2017. Selective neuronal vulnerability in
Parkinson disease. Nat. Rev. Neurosci. 18, 101–113. doi:10.1038/nrn.2016.178
Tan, J.M.M., Wong, E.S.P., Kirkpatrick, D.S., Pletnikova, O., Ko, H.S., Tay, S.-P., Ho,
M.W.L., Troncoso, J., Gygi, S.P., Lee, M.K., Dawson, V.L., Dawson, T.M., Lim, K.L., 2007. Lysine 63-linked ubiquitination promotes the formation and autophagic
clearance of protein inclusions associated with neurodegenerative diseases. Hum.
Mol. Genet. 17, 431–439. doi:10.1093/hmg/ddm320
Uhl, G.R., 1998. Hypothesis: The role of dopaminergic transporters in selective
vulnerability of cells in Parkinson’s disease. Ann. Neurol.
doi:10.1002/ana.410430503
Wang, X., Yen, J., Kaiser, P., Huang, L., 2010. Regulation of the 26S Proteasome
Complex During Oxidative Stress. Sci. Signal. 3.
Yi, J.J., Ehlers, M.D., 2005. Ubiquitin and Protein Turnover in Synapse Function.
Neuron 47, 629–632. doi:10.1016/j.neuron.2005.07.008
Zhang, M., Cai, F., Zhang, S., Zhang, S., Song, W., 2014. Overexpression of ubiquitin
carboxyl-terminal hydrolase L1 (UCHL1) delays Alzheimer’s progression in vivo.
Sci. Rep. 4, 7298. doi:10.1038/srep07298

244