Characterization of the DJ-1 Knockout Rat Model of Parkinson's Disease

Characterization of the DJ-1 Knockout Rat Model of Parkinson’s Disease

A dissertation submitted to the Graduate School of the University of Cincinnati

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy (Ph.D.) in the Neuroscience Graduate Program of the College of Medicine

2019

By Tara Leigh Kyser B.S., Ursinus College

Advisor: Kim B. Seroogy, Ph.D. Committee Chair: Mark Baccei, Ph.D. Christina Gross, Ph.D. Michael Williams, Ph.D. David Yurek, Ph.D.

Abstract

Parkinson’s disease (PD) is a complex neurodegenerative disorder with a plethora of symptoms categorized as motor and non-motor. Historically, research on PD has focused mainly on degradation of the nigrostriatal pathway. However, degeneration of additional brainstem regions, including the locus coeruleus (LC) and dorsal raphe nucleus (DRN), and dysfunction of their associated noradrenergic and serotonergic neurotransmitter systems, respectively, also contribute to disease pathology. Nevertheless, the etiology of the vast majority of PD cases remains unknown. The overall goal of our work was to examine the relatively novel DJ-1 knockout (KO) rat model of PD in an effort to expand our knowledge of the manifestation and progression of PD. Complete loss of the protein DJ-1 leads to an autosomal recessive form of PD. The DJ-1 KO rat was created with the objective of generating an animal model with a more robust PD phenotype than seen previously in DJ-1 KO mice. Although a few studies on these mutant rats have noted some promising PD-like features, they have not always been in agreement. Here, we conducted a more thorough analysis of the DJ-1-deficient rat model, hypothesizing that we would uncover aberrant motor and non-motor behaviors, altered neurotransmitter levels and reduced neuronal survival in PD-relevant brain regions.

In Aim 1, we performed a battery of motor and non-motor tasks at various ages to expand the behavioral characterization of the DJ-1 KO rat. Consistent with a PD phenotype, the

DJ-1 KO rats demonstrated a reduction in rears, stride length, and grooming time, compared to wild-type (WT) control rats. However, the DJ-1-deficient rats took more steps than WT controls in several motor tasks, inconsistent with PD-like behavior. The non-motor findings were also mixed, in that DJ-1 KO rats exhibited deficits in short-term memory, but also better olfactory detection and increased sucrose intake during the sucrose preference task. In Aim 2, we examined monoamine levels using neurochemistry to determine if DJ-1 KO rats showed altered

i levels of monoamines in brain regions associated with PD. We used immunohistochemistry and unbiased stereology to examine the substantia nigra pars compacta, LC, and DRN for monoaminergic neuronal degeneration. Depending on age, we detected increases in the dopamine metabolite 3,4 dihydroxyphenylacetic acid in the striatum and of the serotonin metabolite 5-hydroxyindoleucetic acid in the ventral midbrain and hippocampus of DJ-1-deficient rats. Norepinephrine (NE) levels in the hippocampus of DJ-1 KO rats were lower than controls.

DJ-1 KO rats demonstrated reduced numbers of noradrenergic LC neurons than WT rats and a loss of serotonergic neurons in the DRN, regardless of age. In Aim 3, because of the association of neuroinflammation with PD, we evaluated activated microglia in several PD- related brain regions in DJ-1 KO rats. Only the LC displayed activated microglia when compared to WT rats, suggesting limited involvement of detrimental microglial mechanisms in the DJ-1- deficient brain.

Overall, DJ-1-deficient rats demonstrate a PD-like phenotype in several behavioral, neurochemical and morphological aspects of the disease. Moreover, the data suggest that DJ-1

KO rats will be particularly useful in investigating prodromal stages of PD.

iii

Acknowledgements

Over the course of my dissertation I have had people who have given me guidance and support, and I would like to thank these individuals. First, I would like to thank my advisor Dr. Kim

Seroogy. Thank you for allowing me to join the lab. I appreciate all the guidance you have given me and for allowing me to follow my interests in the lab. Thank you for all the advice you have given me and for making me a better scientist.

I wish to thank my committee members Mark Baccei, Michael Williams, Nina Gross, and David

Yurek for all of their helpful suggestions and individual guidance. I want to thank Mark Baccei for being the head of my committee and helping me through the graduation process. I appreciate at his advice and support as both a committee member and director of the

Neuroscience Graduate Program. I would like to thank Michael Williams for his help with the behavioral testing as well as statistical analysis. Thanks to Nina Gross for being on my committee and all her thoughtful questions that made my dissertation better. Lastly, I would like thank David Yurek for traveling the long distance to the University of Cincinnati for the committee meetings and for sharing your vast knowledge of Parkinson’s disease

I would like to thank the Neuroscience Graduate Program for accepting me into the program. I want to thank the past (Deb Cummins and Sharon Weber) and present (Ana Madani) program coordinators and manager for their help with a lot of the paperwork and for making sure I turned everything in on time. Thank you to the past (Jim Herman and Kim Seroogy) and present (Mark

Baccei) program directors for allowing me the opportunity to conduct research at UC. Also, thanks to my fellow students for shared knowledge, encouragement, and the good times we shared.

To members of the Seroogy Lab, past and present, thank you for all of your help in lab and without you I would not have gotten this far. Kerstin Lundgren, thank you for being the anchor in lab and teaching me a lot of valuable laboratory techniques such as in situ hybridization. To

Ann and Sarah, thank you for all the laughs and being very supportive lab mates. I would like to thank all of the undergraduates who helped me over the years, and most especially Adam

Dourson for helping me greatly in the last couple years of my dissertation work. Importantly, I wish to acknowledge the financial support of NIH and the James J. and Joan A. Gardner Family

Center for Parkinson's Disease and Movement Disorders.

Last, but not least, I would like to thank my family, friends, and dog Ollie. Thanks to my mom and dad for having faith in me and being supportive of my pursuits. To my Aunt Colleen and

Grandmom, thank you for driving all the way out to Cincinnati to support me during my defense.

And to the rest of my family who could not make it out, thank you for your love and encouragement. To my dog, Ollie, thank you for all the cuddles and being the best dog a person could ask for. Thanks to Becky Bailey, for going through this graduate student process with me and listening to me when I needed it the most. To Kenton Woodard, thank you for picking me up when I was down and for always being there for me no matter how far we are from each other. Last, but definitely not least, thanks to Amanda Stover. I really could not have gotten through this whole process without you. You are there for me through thick and thin, making me laugh and letting me know that you have faith in me when I had lost faith in myself. I look forward to being there for you while you go through your own dissertation process.

Table of Contents

Abstract i

Acknowledgements iv

List of Tables and Figures 3 Abbreviations 5

Chapter 1: Introduction

Parkinson’s disease 10

Risk factors for Parkinson’s disease 16

Animal models 22 The substantia nigra pars compacta and Parkinson’s disease 35

The dorsal raphe nucleus and Parkinson’s disease 38 The locus coeruleus and Parkinson’s disease 41 Olfaction and Parkinson’s disease 43 Depression and Parkinson’s disease 44

Anxiety and Parkinson’s disease 45 Cognitive Impairment and Parkinson’s disease 46 DJ-1 and Parkinson’s disease 47 Objectives 50 Specific Aims 50

References 51 Chapter 2: Characterization of Motor and Non-Motor Behavioral Alterations in the Dj-1 (PARK7) Knockout Rat

Abstract 132 Introduction 133 Methods 136

Results 143 Discussion 156 References 164

Chapter 3: Altered Monoamine Levels and Cell Degeneration of Monoaminergic Nuclei

Abstract 178 Introduction 179

Methods 182

Results 186

Discussion 193 References 201

Chapter 4: Evaluation of Activated Microglia in Aged DJ-1 Knockout Rats

Abstract 211

Introduction 212 Methods 216 Results 219

Discussion 224 References 227 Chapter 5: General Discussion Discussion 239 Limitations and Caveats 244

Future Studies/Conclusions 246 References 247

List of Tables and Figures

Chapter 1

Table 1. List of known non-motor symptoms in Parkinson’s disease 13

Table 2. Braak staging of Lewy body pathology 14

Table 3. Environmental risk factors associated with Parkinson’s disease 20

Table 4. Genetic risk factors of Parkinson’s disease 21

Chapter 2 Figure 1. Evaluation of spontaneous activity in DJ-1 KO and WT rats 145 at 4, 7, and 13 months of age.

Figure 2. Assessment of sensorimotor changes during the adhesive 146 removal task at 4,7, and 13 months of age for WT and DJ-1 KO rats Figure 3. Evaluation of postural instability in the adjusting step task at 4, 147 7, and 13 months of age for WT and DJ-1 KO rats

Figure 4. Analysis of gait changes in WT and DJ-1 KO rats at 2 and 13 148 months of age

Figure 5. Assessment of olfactory detection in the buried pellet task at 151 16 months of age for WT and DJ-1 KO rats

Figure 6. Evaluation of short-term memory in novel/place recognition 152 task for WT and DJ-1 KO rats at 4.5 and 15 months of age

Figure 7. Analysis of learned immobility during the forced swim task at 153 6 months of age for WT and DJ-1 KO rats

Figure 8. Evaluation of anxiety-like behavior using the elevated plus 154 maze for WT and DJ-1 KO rats at 4, 8, and 17 months of age

Figure 9. Evaluation of anhedonia using the sucrose preference test in 155 WT and DJ-1 KO rats at 9 months of age

Chapter 3

Figure 1. Levels of monoamines and their metabolites in the striatum of 188 WT and DJ-1 KO rats at 5 and 9 months of age

Figure 2. Monoamines and their metabolites concentrations in the 189 ventral midbrain of DJ-1 KO and WT rats at 5 and 9 months of age

Figure 3. Concentrations of monoamines and their metabolites in DJ-1 190 KO and WT rats in the hippocampus at 5 and 9 months of age

Figure 4. Monoamines and their metabolites in the prefrontal cortex in 191 DJ-1 KO and WT rats at 5 and 9 months of age

Figure 5. Unbiased stereological cell counts of TH+ neurons in the 194 substantia nigra pars compacta of DJ-1 KO and WT rats at 5, 9, and 17 months of age

Figure 6. TPH+ and NeuN+ stereological cell counts in the dorsal raphe 195 nucleus of DJ-1 KO and WT rats at 5 ,9, and 17 months of age

Figure 7. Unbiased stereological cell counts of TH+ and NeuN+ cells in 196 the locus coeruleus of DJ-1 KO and WT rats at 5, 9, and 17 months of age

Chapter 4

Figure 1. Analysis of microglia in the striatum of DJ-1 KO and WT rats 220 at 17 months of age

Figure 2. Analysis of microglia in the substantia nigra pars compacta 221 of 17-month-old WT and DJ-1 KO rats

Figure 3. Analysis of microglia in the dorsal raphe nucleus of WT and 222 DJ-1 KO rats at 17 months of age

Figure 4. Analysis of microglia in the locus coeruleus of 17-month-old WT 223 and DJ-1 KO rats

List of abbreviations

5HIAA 5-hydroxyindoleacetic acid

5HT 5-hydroxytryptamine; serotonin

6-OHDA 6-hydroxydopamine

AD Alzheimer’s disease

ANOVA Analysis of variance aSyn Alpha-synuclein

BBB Blood-brain barrier

COMT Catechol-O-methyltransferase

CSF Cerebrospinal fluid

CVS Chronic variable stress

D1 Dopamine receptor D1

D2 Dopamine receptor D2

D3 Dopamine receptor D3

DA Dopamine

DAB Diaminobenzidine

DAT Dopamine transporter

DBS Deep brain stimulation

DOPAC 3,4 dihydroxyphenylacetic acid

DRN Dorsal raphe nucleus

DSM-V Diagnostic and Statistical Manual of Mental Disorders, 5th Edition

EEG Electroencephalogram

EPM Elevated plus maze

5 fMRI Functional magnetic resonance imaging

GAD General anxiety disorder

GP Globus pallidus

GPe Globus pallidus externus

GPi Globus pallidus internus

H2O2 Hydrogen peroxide

HPA Hypothalamic-pituitary-adrenal

Iba-1 Ionized calcium binding adaptor molecule 1

IMM Inner membrane of the mitochondria

KO Knockout

LB Lewy bodies

LC Locus coeruleus

L-DOPA Levodopa

LN Lewy neurites

LPS Lipopolysaccharide

LRRK2 Leucine rich repeat kinase 2

LTP Long term potentiation

MAO-B Monamine oxidase-B

MCI Mild cognitive impairment

MFB Medial forebrain bundle

MPP+ 1-methyl-4-phenylpyridinium

MPTP 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mRNA Messenger RNA

MSN Medium spiny neurons

6 mtDNA Mitochondrial DNA

NE Norepinephrine

NET Norepinephrine transporter

NeuN Neuronal nuclei

NHS Normal horse serum

NMS Non-motor symptoms

OB Olfactory bulb

OMM Outer membrane of the mitochondria

PB Phosphate buffer

PD Parkinson’s disease

PDGFB platelet-derived growth factor subunit B

PFA Paraformaldehyde

PFC Prefrontal cortex

PINK1 PTEN induced putative kinase 1

Prnp Prion protein gene

RBD Rapid eye movement behavior disorder

REM Rapid eye movement

ROS Reactive oxygen species

SEM Standard error of the mean

SERT Serotonin transporter

SN Substantia nigra

SNpc Substantia nigra pars compacta

SNr Substantia nigra pars reticulata

STN Subthalamic nucleus

TH Tyrosine hydroxylase

Thy1 Thymus cell antigen 1

TNFα Tumor necrosis factor-alpha

TPH Tryptophan hydroxylase

USV Ultrasonic vocalizations

VA/VL Ventral anterior/ventral lateral nuclei of the thalamus

VMAT-2 Vesicular monoamine transporter 2

VTA Ventral tegmental area

WT Wild type

Chapter 1

Introduction

Parkinson’s disease The main symptoms of Parkinson’s disease (PD) were first described by Dr. James

Parkinson in 1817; today, PD is the second-most common neurodegenerative disorder. About

10 million people are affected by PD worldwide, and this number is predicted to double by 2050

(Schapira, 2009). PD negatively impacts the quality of life of those with the disease, and creates a huge economic burden for both the afflicted persons, and their caregivers (Balestrino and Martinez-Martin, 2017; Keranen et al., 2003; Weintraub et al., 2008; Mosley et al., 2017;

Riedel et al., 2010). Although it is recognized that PD is a slow, progressing disease with a vast array of symptoms, the underlying cause of the disorder remains unknown.

Traditionally, PD is considered a motor disorder because of the prominence of motor deficits and their relationship to the pathological hallmarks of the disease. The cardinal motor deficits, bradykinesia, postural instability, resting tremors, and rigidity, are manifest in varying degrees upon diagnose of PD (Fahn, 1999; Rascol, 2000). Motor deficits occur primarily due to loss of the dopaminergic neurons in the substantia nigra pars compacta (SNpc) which project to the dorsal striatum. This loss of dopaminergic neurons in the SNpc is one of the pathological hallmarks of Parkinson’s (Albin et al., 1989; Gibb, 1991; Wichmann and DeLong, 2003;

Wakabayashi et al., 2013). Once diagnosis of PD occurs about 80% of the dopamine (DA) content in the striatum, and approximately 60% of dopamine cells in the SNpc, are gone (Schulz and Falkenburger, 2004). Loss of dopaminergic neurons in the SNpc is characteristic of

Parkinson’s, but the SNpc also presents with another classic histopathological hallmark.

Lewy bodies are cytoplasmic globular, fibrillar spheres composed mainly of protein, and are a histological characteristic of PD expressed in the SNpc (Braak et al., 2003a; Burre et al.,

2010; Wakabayashi et al., 2013; Lunati et al., 2018). The protein with the highest content in LB is alpha-synuclein (aSyn), but there also can be other molecules such as PD-linked gene products [DJ-1, PTEN induced putative kinase 1 (PINK1), parkin, and leucine rich repeat kinase

2 (LRRK2)], mitochondrial-related proteins, and molecules associated with the ubiquitin- proteasome system and autophagy (Wakabayashi et al., 2013). Alpha-synuclein is expressed throughout the brain, and although its physiological role in neurons is still poorly understood, it is thought to play a role in dopamine synthesis, learning, synaptic plasticity, and vesicle dynamics

(Lotharius and Brundin, 2002; Sidhu et al., 2004). The sequence of events directing aSyn from the cytoplasm to LBs is still not quite understood. It is hypothesized that LBs may function as a protective measure against misfolded aSyn oligomers and fibrils that are toxic to the cell

(Conway et al., 2000; Goldberg and Lansbury, 2000; Eschbach and Danzer, 2014). However, whether LBs are cytoprotective or deleterious to the cell remains unresolved. Moreover, there are not only LBs found in the PD brain, but also Lewy neurites (LN) which are present in the axons and dendrites of neurons (Spillantini et al., 1998; Braak et al., 2003a; Del Tredici and

Braak, 2016; Goedert et al., 2017). Although the SNpc presents with the pathological hallmarks of PD, which lead to the classic motor deficits, another group of symptoms of PD is important to disease etiology.

A collection of deficits, known as the non-motor symptoms (NMS), also need to be studied to begin to understand PD. There is a long list of NMS that are involved, for example, in autonomic dysfunction, sleep disturbances, neuropsychiatric disorders, and sensory dysfunction

(Fahn, 1999; Rascol, 2000; Hou and Lai, 2007; Riedel et al., 2010; Balestrino and Martinez-

Martin, 2017) (Table 1). Although documentation of NMS has occurred since Dr. Parkinson’s seminal paper (Parkinson, 2002), they were not carefully considered until the early 2000s when the impact of NMS was measured (Garcia-Ruiz et al., 2014). About 90% of all individuals with

PD suffer from NMS, and these symptoms are said to have a greater impact on the quality of life than motor deficits (Riedel et al., 2010; Chaudhuri et al., 2006,2011; Balestrino and Martinez-

Martin, 2017). It is suggested that NMS, such as depression, anxiety, olfactory deficits, rapid eye movement behavior disorder (RBD), and constipation, precede clinical diagnosis, which is

11 when motor deficits can finally be detected (Cummings, 1992; Nilsson et al., 2001; Abbott et al.,

2001; Ponsen et al., 2004; Richard, 2005; Postuma and Montplaisir, 2006; Aarsland et al.,

2009).Studies on post-mortem tissue in patients in different stages of PD show regions associated with the NMS develop LBs prior to the SNpc which is associated with the motor deficits used for clinical diagnosis.. As stated previously, LBs are a histological hallmark of PD, and studies have found a progressive distribution of LBs throughout the central, peripheral, and enteric nervous systems. The stages of LB progression are known as Braak staging, and there are currently six stages (Table 2). Other brain nuclei, such as the locus coeruleus (LC) and dorsal raphe nucleus (DRN), also present with LBs and LNs in parkinsonian brains. Specifically, the LC exhibits Lewy pathology at Braak stage 2, when symptoms like mood changes manifest, whereas the SNpc displays LBs at stage 3. Thus, regions such as the LC and DRN, implicated in the manifestation of NMS, are also important to the study of disease etiology because of early expression of Lewy pathology. (Wakabayashi et al., 1988; Wakabayashi and Takahashi, 1997;

Braak et al., 2003a; Orimo et al., 2007; Djaldetti et al., 2009; Hawkes et al., 2010; Del Tredici and Braak, 2012; Del Tredici and Braak, 2016). The LC is the main source of the neurotransmitter norepinephrine (NE) (also known as noradrenaline), and the dorsal raphe nucleus is the main source of serotonin (5-hydroxytryptamine; 5HT) in the brain, and dysfunction of both brain regions is strongly associated with PD (Braak et al., 2003a; Hawkes et al., 2010; Postuma et al., 2012; Balestrino and Martinez-Martin, 2017). Beyond histological evidence of these and other brain regions being associated with PD, dopamine replacement therapies, which help alleviate motor symptoms, have poor efficacy when it comes to treating

NMS, emphasizing the importance of going beyond the study of just dopamine in PD (Fahn,

1999; Rascol, 2000; Zgaljardic et al., 2004). Thus, it is critical to continue studying neurotransmitters beyond dopamine, not only to narrow down the cause of PD, but because current dopamine replacement therapies only have an impact on a narrow scope of the disease.

Table 1. A list of known non-motor symptoms in Parkinson’s disease. Modified from Hou and

Lai ( 2007).

Table 2. Braak staging of Lewy pathology with accompanying clinical symptoms. Bolded nuclei will be discussed in detail in this dissertation. Modified from Del Tredici and Braak (2016).

Braak Location of Lewy bodies and Symptoms Stages neurites Stage 1 olfactory bulb, anterior olfactory No symptoms to hyposmia and nucleus, motor nucleus of the vagal autonomic dysfunction nerve, intermediate reticular zone Stage 2 peripheral parasympathetic and Hyposmia, autonomic dysfunction sympathetic nerves, peripheral (e.g. gastrointestinal, urinary autonomic ganglia, medullary symptoms), disturbed sleep, nuclei, lower raphe nuclei, locus parasomnias, mood changes coeruleus Stage 3 tegmental pedunculopontine Disturbed sleep and possible early nucleus, substantia nigra pars phase motor dysfunction: asymmetric compacta, spinal cord centers, tremor, rigidity, hypokinesia upper raphe nuclei (e.g. dorsal raphe nucleus), magnocellular nuclei of the basal forebrain, hypothalamic tuberomammillary nucleus, central nucleus of the amygdala Stage 4 midline and intralaminar nuclei of Early phase motor dysfunction: tremor, the thalamus, anteromedial rigidity, hypokinesia temporal cortex (transentorhinal and entorhinal regions, hippocampal formation) Stage 5 cortical areas for regulation of Late phase motor disability: autonomic functions, high-order fluctuation, falls, wheelchair bound or sensory association areas, bedridden. prefrontal fields Cognitive impairment Stage 6 first-order sensory association areas Late phase motor disability: and premotor fields, primary fluctuation, wheelchair bound or sensory and primary motor areas bedridden Cognitive impairment, dementia

Therapies

Current PD treatments remain dopamine-centric, and no current therapy is able to slow the relentless progression of the disease. In the 1950s, a series of concurrent events led to the discovery of the dopamine precursor, levodopa (L-dopa), the first Parkinson’s treatment (Fahn,

2015; Przedborski, 2017). The events unfolded with the discovery of dopamine in the brain finding high concentrations of dopamine in the striatum (Bertler and Rosengren, 1959; Sano et al., 1959; Carlsson, 1959), discovering dopamine deficits in PD patients (Ehringer and

Hornykiewicz, 1960), finding L-dopa recovered low dopamine levels induced by reserpine

(depletes monoamines) in rabbits (Carlsson et al., 1957), and finally testing of L-dopa in PD patients (Birkmayer and Hornykiewicz, 1961). L-dopa, to this day, continues to be the gold standard of treatment because of its ability to cross the blood-brain barrier (BBB) and its effectiveness in reducing motor symptoms (Poewe, 2009; Bastide et al., 2015; Muthuraman et al., 2018). However, L-dopa can have major side effects upon prolonged treatment. Within 5 years of starting L-dopa, approximately 80% of Parkinson’s patients will exhibit L-dopa induced dyskinesias (LID). There are also sudden changes in mobility, the wearing off phenomenon, and continual decreases of the duration of L-dopa’s effectiveness (Lesser et al., 1979; Rajput et al., 1984; Espay, 2010). As stated previously, L-dopa has little to no effect on NMS (Fahn,

1999; Rascol, 2000; Zgaljardic et al., 2004). Alarmingly, L-dopa can exacerbate NMS such as sleep disorders, hallucinations, and depression (Choi et al., 2000; Brodsky et al., 2003; Negre-

Pages et al., 2010; Zhu et al., 2013). New drugs targeting the dopamine system, such as dopamine D2 receptor agonists, and inhibitors of monoamine oxidase-B (MAO-B) and catechol-

O-methyl transferase (COMT), emerged in response to the adverse effects of L-dopa. MAO-B and COMT are enzymes involved in the breakdown of dopamine, and can be used alone or with

L-dopa to help make the dosage last longer. Despite how these other drugs were used, however, there was still worsening or development of new dyskinesias as well as low efficacy

15 on NMS (Tarazi et al., 2014; Bastide et al., 2015; Li et al., 2016). Alternatives to dopamine therapies such as adenosine receptor antagonists, serotonergic agonists, and glutamate antagonists are being considered, based mainly on circuitry of the basal ganglia, rather than other brain regions affected by PD (Poewe et al., 2012; Tarazi et al., 2014). Other treatments besides pharmacotherapies have been developed as well. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and internal part of the globus pallidus (GPi) has been effective in preventing motor fluctuation and dyskinesias in PD patients. Both of these DBS-targeted regions are part of the basal ganglia, however, only a small percentage of those with PD qualify for DBS. Also, some studies have shown that DBS can have a negative effect on NMS such as cognitive functioning and apathy (Fasano et al., 2012; Bastide et al., 2015). Cheaper therapeutic alternatives such as exercise, mindfulness meditation, and music therapy have seen some positive results, but they are insufficient to alleviate symptoms for the long-term (Li, S. et al.,

2016). To find better therapies that target both the motor and non-motor symptoms, there needs to be a better understanding of how the environment and genetics contributes to disease etiology.

Risk Factors for Parkinson’s disease

Environmental

Most people with PD have what is known as sporadic (idiopathic) PD, meaning there is no family history of the disease, along with unknown etiology. However, evidence points to a complex interaction between environmental and genetic risk factors for disease manifestation

(Braak et al., 2003b; Ramsden et al., 2001). There is a long list of environmental risk factors that both increase and decrease the risk of PD (Table 3) (Kalia and Lang, 2015; Bellou et al.,

2016). Age is strongly correlated with Parkinson’s, and aging increases the risk of disease (Li et al., 1985; Mayeux et al., 1992; Benito-Leon et al., 2003; de Lau and Breteler, 2006). A sharp increase in disease risk occurs around the age of 60, and the age of onset of sporadic

Parkinson’s occurs around the age of 65 (de Lau and Breteler, 2006). Aging leads to increases in free radicals, lipid peroxidation, DNA damage, inflammation, mitochondrial damage, and protein oxidation, leaving neurons more vulnerable to acute and chronic diseases (Harman,

1956; Valko et al., 2007). Besides aging, stress, specifically chronic stress, can have an impact on PD (Smith et al., 2002; Hemmerle et al., 2012; Djamshidian and Lees, 2014). Stress is defined as a sudden physiological, physical, social, or environmental change that is perceived or imposed, and can be negative or positive (Herman and Cullinan, 1997; Dalle and Mabandla,

2018). The response to stress is adaptive and involves changes in multiple systems, but most prominently the hypothalamic-pituitary adrenal (HPA) axis which helps bring the body back into homeostatic balance through a cascade of neuroendocrine changes. However, a prolonged stress response leads to physiological abnormalities, which can contribute to disease states, like Parkinson’s (Herman and Cullinan, 1997; Hemmerle et al., 2012). Several studies found that severe psychological stress from the holocaust and being a prisoner of war increases the risk of PD (Gibberd and Simmonds, 1980; Salganik and Korczyn, 1990). A case report described that a woman developed early-onset PD potentially due to a major stress event (Zou et al., 2013). Beyond possibly contributing to the cause of PD, stress can exacerbate motor behaviors and increase impulsive behavior in PD patients (Djamshidian et al., 2011). In our lab, we showed that chronic variable stress (CVS) can exacerbate the degeneration of DA neurons in a rat neurotoxin model of PD (Hemmerle et al., 2014a). Chronic variable stress involves mild stressors presented unpredictably over an extended period of time. CVS induces changes in the HPA axis similar to what occurs in the stress response in humans (Herman et al., 1995;

Willner, 2005). Several other studies examined stressors in rodent models of PD and also found these stressors had an impact on the dopaminergic system (Keefe et al., 1990; Howells et al.,

2005; Smith et al., 2008; Janakiraman et al., 2016).

Besides stress and aging, many other environmental factors such as pesticides, herbicides, and manganese can contribute to PD by causing mitochondrial dysfunction through the inhibition of complex I of the mitochondrial transport chain. Also, these toxins lead to an increase in cellular oxidative stress. Both inhibition of complex I and oxidative stress occur in the brains of those with PD, and are thought to contribute to disease etiology (Cotzias and

Greenough, 1958; Schapira et al., 1990; Betarbet et al., 2000; Jenner, 2001; Jenner, 2003;

Zhang et al., 2003; Sherer et al., 2007; Aschner et al., 2009). Pesticide and herbicide exposures are the most well-known environmental risk factors other than the ones discussed above. Because of a similar pathophysiology, many studies have examined the role of pesticides in PD (Mostafalou and Abdollahi, 2017). Rural living and farming create a greater risk for PD because people in these areas and occupations are exposed to organophosphates like pesticides (Gorell et al., 1998; Di Monte et al., 2002). Increasing exposure to pesticides proportionally increases the risk of PD (Ascherio and Schwarzschild, 2016). Beside the cellular mechanisms listed previously, pesticide exposure can induce misfolding of alpha-synuclein, alter dopamine levels, and increase oxidative stress (Dick, 2006; Carboni and Lingor, 2015).

Rotenone is a pesticide that is correlated with PD and was found to induce PD-like dopaminergic changes in rats (Heikkila et al., 1985; Bastias-Candia et al., 2019). Other than pesticide exposure, herbicide exposure can increase the risk of PD by as much as 3- or 4-fold

(Jenner and Olanow, 1998). Paraquat is an herbicide and any exposure leads to an increased risk of Parkinson’s (Naylor et al., 1995). Paraquat was first discovered to induce dopamine depletion in frogs, but it mostly has been used in rodents as a model of PD (Barbeau et al.,

1985; Bastias-Candia et al., 2019). Although environmental factors play a role in PD, genetic factors also contribute to disease etiology.

Genetic

About 10-15% of PD patients have an inherited form of Parkinson’s, and it is these cases that have helped us uncover genetic risk factors in the entire PD population (Sherer et al.,

2002; Farrer, 2006). There is a long list of genes discovered in families with inherited forms of the disease, either by highly penetrant monogenetic or Mendelian forms of inheritance (Table 4)

(Lunati et al., 2018). Currently, the predominant autosomal dominant genes are SNCA and

LRRK2 (leucine rich repeat kinase 2) (Bonifati, 2014). In 1997, the first genetic mutation known to cause PD was identified: the SNCA gene (Polymeropoulos et al., 1997). The SNCA gene encodes the protein alpha-synuclein (aSyn). As stated previously, aSyn is the main component of LBs, the histological characteristic of PD. LRRK2 is one of the most common causes of

Parkinson’s, with the frequency in sporadic PD about 0.5-2%, and 5% of cases of inherited PD

(Gilks et al., 2005; Kachergus et al., 2005; Tomiyama et al., 2006; Lesage et al., 2009). LRRK2 functions in the lysosomal pathway and autophagy, and both processes are dysfunctional in PD

(Alessi and Sammler, 2018). The predominant autosomal recessive genes are parkin, PINK1, and DJ-1 (Bonifati, 2014). In general, all three are involved in maintaining proper mitochondrial function and in protecting against cellular stress. As previously stated, mitochondrial dysfunction and cellular stress are thought to underlie PD (Ryan et al., 2015). All of these genes will be discussed in further detail below.

Table 3. A list of environmental risk factors associated with Parkinson’s disease. Bolded factors indicate an increased risk of PD. Unbolded factors are associated with decreased risk of

Parkinson’s. The gray factors are those that are unknown to be beneficial or detrimental, or that only moderation will lead to a decreased risk, but excess leads to an increased risk of PD.

[Modified from (Kalia and Lang, 2015) and (Bellou et al., 2016).]

Environmental Risk Factors Alcohol intake Coffee drinking Smoking Outdoor work Tea drinking Physical activity Manganese exposure Welding Hydrocarbon exposure Farming Organic solvents Pesticides Herbicides Rural living Well water drinking Diabetes mellitus Head injury Hypertension Gout Aspirin Non-aspirin NSAIDs Acetaminophen Ibuprofen use Beta-blockers Calcium channel blockers General anesthesia Oral contraceptives Statins Hormone replacement therapy Copper Iron Age

Table 4 List of genetic risk factors of Parkinson’s disease. Disease onset and clinical phenotype are relative to idiopathic PD. [Modified from (Lunati et al., 2018)].

Gene Inheritance Disease onset Clinical phenotype LRRK2 AD/AR Late Typical

*SNCA AD Early/Late Typical/Atypical

VPS35 AD Early Typical

ATXN2 AD Early Typical GCH1 AD Early Typical

DNAJC13 AD Late Typical

TMEM230 AD Late Typical

UCHL1 AD Early Typical

RIC3 AD Early or late Typical

HTRA2 AD Late Typical

GIGYF2 AD Early Typical

CHCHD2 AD Early or late Typical EIF4G1 AD Late Typical PTRHD1 AR Early Atypical PODXL AR Juvenile Typical PRKN AR Juvenile or early Typical PINK AR Juvenile or early Typical

DJ1 AR Juvenile or early Typical

ATP13A2 AR Juvenile Atypical

PLA2G6 AR Juvenile or early Atypical

FBXO7 AR Juvenile Atypical

*DNAJC6 AR Juvenile/Early Typical/Atypical

SPG11 AR Juvenile Atypical SYNJ1 AR Early Atypical VPS13C AR Early Atypical RAB39B XLD Early for men Typical or Atypical Late for women Typical Typical GBA AD Early or late

*= disease onset and clinical phenotype depend on mutation

AD=autosomal dominant

AR-autosomal recessive XLD= X-linked dominant

Animal models

Parkinson’s disease animal models are based upon environmental and genetic risk factors, which, as discussed above, both contribute to the complexity of PD etiology. Animal models do not completely mimic PD, but the combined knowledge gained from each model can help aid in the discovery of not only new therapies, but also the etiology of PD itself. Although there are many different model organisms used in PD research, here we will focus on rodent

(rat and mouse) models, because these are, by far, the animals used the most. We will discuss the two major toxin-based models, 6-hydroxydopamine (6OHDA) and 1-methyl-4-phenyl-

1,2,3,6-tetrahydropyridine (MPTP). Because the present dissertation research incorporates a genetic rat model of PD, we will focus on several of the major genes associated with PD: aSyn,

LRRK2, parkin, PINK1, and DJ-1.

Toxin-based

The 6OHDA rat is one of the most used PD models because it mimics the pathology and symptomology of the motor deficits (Simola et al., 2007). The chemical 6OHDA was first discovered in 1959 and is the structural analog of both dopamine and NE (collectively known as catecholamines) but is toxic to these type of neurons (Senoh and Wiktop, 1959; Simola et al.,

2007). The neurochemical cannot cross the BBB, so to have an effect on the brain region or pathway of interest, it must be intracranially injected directly into the target area (Luthman et al.,

1989). Once in the brain, 6OHDA is taken up by the dopamine transporter (DAT) and norepinephrine transporter (NET) because of its similar conformation to dopamine and NE. The

DAT and NET are located on the presynaptic terminal, so 6OHDA gets taken up at the axon bouton, travels retrogradely up the axon, accumulates in the cell bodies of catecholaminergic neurons, and eventually leads to neuronal toxicity and degeneration by disrupting neuronal

22 homeostasis (Luthman et al., 1989; Van Kampen et al., 2000; Simola et al., 2007). One way

6OHDA creates neurotoxicity is through oxidative stress. Catabolism of 6OHDA generates hydrogen peroxide (H2O2) which breaks down and forms reactive oxygen species (ROS). ROS produce structural damage and metabolic dysfunction eventually leading to cell death (Cohen,

1984; Cadet and Brannock, 1998; Palumbo et al., 1999; Blum et al., 2001). It is also believed

6OHDA interferes with mitochondrial complex I, however, the mechanism for that is not as well- defined (Glinka and Youdim, 1995; Simola et al., 2007). As stated in the previous section, oxidative stress and mitochondrial damage are prominent in PD, and can be induced by many of the environmental toxins associated with PD; therefore, 6OHDA is a good toxin to use to study these cellular changes (Schapira et al., 1990; Jenner, 2003). The severity of the cellular damage, neuronal degeneration, and behavioral deficits depends on the location of the intracranial injection and the concentration of 6OHDA used. With respect to the 6OHDA rat model of PD, the ultimate target is the nigrostriatal pathway of the basal ganglia to induce dopamine loss and motor deficits (Simola et al., 2007). In 1968, the first use of 6OHDA in the rat, bilateral injections directly into the substantia nigra resulted in a high mortality rate and severe deficits. Eventually, the same group began performing unilateral injections into the median forebrain bundle (MFB), a neural pathway that carries the ascending axons of the dopaminergic mesotelencephalic system, including the nigrostriatal pathway. Injection of

6OHDA into the MFB also induced dopaminergic neuronal loss in the substantia nigra; unilateral injections were done so that rotational behavior could be used to assess the effectiveness of the neurotoxic lesion (Ungerstedt and Arbuthnott, 1970). A unilaterally lesioned 6OHDA rat was given either apomorphine or amphetamine to induce rotational behavior. Apomorphine is a dopamine agonist and caused the 6OHDA rat to rotate contralateral to the lesion.

Amphetamine is a stimulant that induces higher dopamine levels via uptake or diffusion into dopamine terminals, and a 6OHDA rat will rotate toward the ipsilateral (lesioned) side (Simola et al., 2007). Today, rotational behavior is not used as much as previously because of the effect

23 the injected drugs can have on other motor behavior measurements used to assess PD (Mandel and Randall, 1985). Also, there needs to be a relatively severe lesion to induce rotational behavior; effects of a mild 6OHDA lesion cannot be quantified using this assay (Hudson et al.,

1993; Deumens et al., 2002). The unilateral 6OHDA rat is still a popular model, in part because the contralateral side of the brain can serve as an internal control (Schober, 2004). Also, other tests to measure the 6OHDA rat’s akinesia were devised such as the forelimb asymmetry and adjusting step tests (Schallert et al., 1979; Olsson et al., 1995; Schallert et al., 2000). Besides administration into the SNpc and MFB, injections of 6OHDA into the striatum also lead to dopamine depletion and neuronal loss. Each injection site has its advantages and disadvantages. Rarely is 6OHDA injected directly into the SNpc because the lesion is acute, unlike PD, and accidental damage to the substantia nigra pars reticulata (SNr) and ventral tegmental area (VTA) is a high probability. Injection into the MFB or striatum results in a more progressive lesion because these regions contain the axons and/or axon terminals of dopaminergic neurons of the SNpc, so degeneration occurs at a slower rate. However, 6OHDA injected into the MFB can lead to feeding and drinking issues, and it is not as slowly progressive a lesion as 6OHDA injected into the striatum (Simola et al., 2007). At present, the most optimal

6OHDA rat model is the intrastriatal 6OHDA partial-lesion model which leads to a relatively progressive degeneration (over ~8 weeks) of dopaminergic neurons in the SNpc (Sauer and

Oertel, 1994; Kirik et al., 1998; Hemmerle et al., 2014), and by titrating the dose of the neurotoxin, a certain percentage of dopaminergic cells are spared from the injury. This intrastriatal progressive lesion model is believed to better mimic idiopathic PD (Deumens et al.,

2002), at least with respect to nigrostriatal degeneration.

Several studies have used bilateral injections of 6OHDA into the striatum in an attempt to recapitulate some of the NMS in addition to the motor deficits. Such studies have found cognitive deficits, anhedonia, anxiety, and stress coping, as well as changes in other

24 neurotransmitter systems (Ferro et al., 2005; Tadaiesky et al., 2008; Santiago et al., 2010). In addition to a reduction of dopamine, several studies have found decreases in serotonin and norepinephrine in the striatum in various 6-OHDA partial-lesion models (Uretsky and Iversen,

1970; Santiago et al., 2010; Vieira et al., 2019). However, it is not known if these behavioral and neurochemical changes are due to the toxin itself, or in response to the loss of dopamine.

Furthermore, some NMS develop during the pre-clinical stage of PD, and the 6OHDA rat represents a later stage model. In general, the 6OHDA rat model has been important to understanding the involvement of the nigrostriatal pathway in PD, and finding therapeutic agents to promote survival of injured dopamine neurons. However, drawbacks include that it does not result in aSyn inclusions or have a protracted period (several months) of degeneration.

Moreover, it is clear that PD involves more than just dysfunction of dopamine and the SNpc

(McDowell and Chesselet, 2012).

The other major neurotoxin PD model is the MPTP mouse, a model first used to induce dopamine cell death and motor deficits. MPTP was first discovered in the early 1980s when drug users began exhibiting Parkinson’s-like symptoms (Davis et al., 1979; Langston et al.,

1983). MPTP is able to pass through the BBB (therefore it can be injected systemically) and is converted to 1-methyl-4-phenylpyridinium (MPP+) by monoamine-oxidase B (MAO-B) in striatal and nigral astrocytes. It is this MPP+ cation that is toxic to dopaminergic neurons. Once released by the astrocytes, MPP+ is taken up into dopaminergic neurons via the DAT.

Accumulation of this neurotoxin leads to blockage of the mitochondrial electron transport chain complex I and increases in ROS (Langston et al., 1983; Javitch et al., 1985; Nicklas et al., 1985;

Madras et al., 2006; Cui et al., 2009; Rappold and Tieu, 2010). This neurotoxin is primarily used in mice because rats are less sensitive and are more resistant to its effects. Plus, mice only needed to be injected intraperitoneally, but rats would need MPTP injected directly into the

SNpc. The reason for the differences in rat and mice exposed to MPTP is not well understood

(Giovanni et al., 1994; Blandini and Armentero, 2012). The motor behaviors these MPTP- treated mice display include decreased locomotion, decreased stride length, and poor performances on the pole and rotarod tests (Le et al., 2014). Like the 6OHDA rat, studies investigating behaviors related to the NMS were examined in the MPTP mouse. Several studies have shown olfactory impairment, sleep disruption, gastrointestinal dysfunction, and cognitive deficits (Monaca et al., 2004; Anderson et al., 2007; Laloux et al., 2008; Vuckovic et al., 2008;

Prediger et al., 2010; Moretti et al., 2015; Aguiar et al., 2016; Yadav et al., 2017). However, the

NMS-related behaviors were only transient in nature which makes it hard to be able to study these changes. Also like the 6OHDA rat, MPTP mice display a later stage of the disease when motor deficits actually emerge, whereas some NMS occur pre-clinical diagnosis (McDowell and

Chesselet, 2012; Le et al., 2014). Nevertheless, MPTP mice sometimes have been found to have LB-like inclusions (Meredith et al., 2008). Overall, neurotoxin models of PD have been instrumental in finding neuroprotective therapeutics for the nigrostriatal system and for ameliorating motor deficits. However, PD-related NMS involve other brain regions and additional neurotransmitter systems and occur in the prodromal stage of PD, therefore it is important to also employ genetic-based models to better address the etiology of the disease.

Genetic-based

As mentioned, genetic rodent models of Parkinson’s disease are based on genes found in families with inherited forms of PD, and it is hoped that these models can help find underlying causes of PD. The first gene discovered to be associated with PD was SNCA, which codes for the protein aSyn (Polymeropoulos et al., 1997). To date, six point mutations of the gene have been found in various families with inherited forms of the disease: A30P, E46K, H50Q, G51D,

A53E and A53T. All of the mutations are 100% penetrant, and it is rare to have this autosomal dominant form of PD (Polymeropoulos et al., 1997; Kruger et al., 1998; Zarranz et al., 2004;

Gasser, 2009; Lees et al., 2009; Lesage et al., 2013; Proukakis et al., 2013; Pasanen et al.,

2014). These point mutations are all found on the N-terminal domain and likely have effects on membrane binding (Bussell and Eliezer, 2001; Villar-Pique et al., 2016). The mutations may destabilize aSyn, leading to misfolding, which leads to increases in aggregation (Bertoncini et al., 2005; Sahay et al., 2015). Of all the point mutations, A53T, A30P, and E46K transgenic mouse models have been created and studied (Dawson et al., 2010; Koprich et al., 2017).

Along with point mutations, duplication or triplication of the SNCA gene leads to autosomal dominant familial PD (Singleton et al., 2003). Transgenic mouse models overexpressing human aSyn and mouse aSyn have been generated (Fleming et al., 2004; Chandra et al., 2005;

Dawson et al., 2010; Rieker et al., 2011; Koprich et al., 2017). Several other transgenic mouse models incorporate truncated forms of aSyn, such as truncation of the C-terminal (Tofaris et al.,

2006; Wakamatsu et al., 2008; Daher et al., 2009).

Different promoters have been used to introduce the aberrant forms of aSyn into specific neuronal populations, of which the most common pan-neuronal promoters include human platelet-derived growth factor subunit B (PDGFB), mouse thymus cell antigen 1 (Thy1), and mouse Prnp (major human prion gene) promoter (Koprich et al., 2017). The promoter for tyrosine hydroxylase (TH), the rate limiting enzyme for dopamine and NE synthesis, has been used to direct aSyn expression to catecholaminergic neurons (Koprich et al., 2017). The multiple different promoters and mutations lead to phenotypic and cellular differences among aSyn models of PD. Most, but not all, transgenic mouse models demonstrate intracellular inclusions (van der Putten et al., 2000; Richfield et al., 2002; Gispert et al., 2003; Yavich et al.,

2005; Wakamatsu et al., 2008; Daher et al., 2009; Chesselet et al., 2012). Typically, aSyn transgenic mice with the TH promoter do not express intracellular inclusions (Matsuoka et al.,

2001). Notably, most aSyn mouse studies have not observed degeneration of the dopaminergic neurons of the SNpc (Masliah et al., 2000; Rockenstein et al., 2002; Neumann et al., 2002; Lee et al., 2002; Richfield et al., 2002; Fleming et al., 2004; Chandra et al., 2005; Rothman et al.,

2013). A few more recent investigations, however, of previously studied aSyn transgenic mouse models, and of new aSyn models, have reported ~35% loss of nigral dopaminergic neurons around 8 months of age or later (Lin et al., 2012; Kachroo and Schwarzschild, 2012;

Janezic et al., 2013; Finkelstein et al., 2016; Koprich et al., 2017). Although most aSyn mouse models do not exhibit dopaminergic cell loss, striatal abnormalities are evident such as reductions of TH immunostaining, dopamine levels, and dopamine release, and increases in

DAT expression (Richfield et al., 2002; Tofaris et al., 2006; Chesselet, 2008; Daher et al., 2009;

Kurz et al., 2010; Clark et al., 2010; Hansen et al., 2013; Kim et al., 2015). The striatal changes could be induced by the toxicity of the aSyn aggregates, but also from aSyn interference with mitochondria. Mice overexpressing human aSyn are more sensitive to paraquat, an herbicide that damages mitochondrial complex I (Norris et al., 2007). Transgenic mice overexpressing

A53T aSyn have damage to mitochondrial DNA which leads to degradation of mitochondria

(Martin et al., 2006). Where there are aSyn inclusions in the brain, there is often neuroinflammation as well (Neumann et al., 2002; Giasson et al., 2002; Lee et al., 2002; Cabin et al., 2005; Emmer et al., 2011).

As with the striatal abnormalities, motor phenotypes and severity vary greatly between the aSyn models of PD. In general, aSyn mice with the prnp promoter demonstrate the most severe motor impairments, but these animals also express a spinal cord pathology that is not seen in PD (Koprich et al., 2017). Motor deficits seen in aSyn mice include decreases in locomotion and rearing, reduced time on the rotarod, and smaller stride length; these deficits can worsen with age, as is the case in PD (Masliah et al., 2000; Giasson et al., 2002; Lee et al.,

2002; Rockenstein et al., 2002; Neumann et al., 2002; Fleming et al., 2004; Chandra et al.,

2005; Wakamatsu et al., 2008; Emmer et al., 2011; Paumier et al., 2013; Rothman et al., 2013;

Amschl et al., 2013).

Besides striatal abnormalities and motor dysfunction, some aSyn models exhibit non- motor behaviors. Inclusions of aSyn can be found in the olfactory bulb, neocortex, and hippocampus (Fleming et al., 2008; Lin et al., 2009; Koob et al., 2010; Price et al., 2010;

Shaltiel-Karyo et al., 2013). Several studies have noted degeneration in the neocortex and the hippocampus (Lin et al., 2009; Koob et al., 2010; Price et al., 2010; Shaltiel-Karyo et al., 2013).

Cognitive deficits have been observed in several aSyn models (Nuber et al., 2008; Freichel et al., 2007; Lim et al., 2010; Paumier et al., 2013; Games et al., 2014). Anxiety-like behavior has been shown to both increase (Rothman et al., 2013; Farrell et al., 2014) and decrease (George et al., 2008; Graham and Sidhu, 2010; Yamakado et al., 2012; Paumier et al., 2013). Olfactory impairment (Fleming et al., 2008; Hansen et al., 2013; Zhang, S. et al., 2015) and constipation

(Wang et al., 2008; Wang et al., 2012; Noorian et al., 2012) can occur, however, these changes do not precede the motor deficits (Koprich et al., 2017). Thus, as illustrated above, there is a lot of variability amongst aSyn transgenic mouse models.

The other major autosomal dominant gene in PD is LRRK2 (PARK8), also known as dardarin (Alessi and Sammler, 2018). As stated previously, LRRK2 is involved in lysosomal and autophagy pathways. LRRK2 familial forms of PD mostly resemble sporadic PD with late onset of PD and Lewy bodies (Xiong et al., 2017). The protein has both kinase and GTPase activity, and it is in these domains that most of the LRRK2 mutations occur (Biskup and West, 2009).

The most common LRRK2 mutations are G2019S and R1141G. There are several types of rodent models used to study LRRK2, and these include knockout (KO) and transgenic mouse and rat models. Knockout models are used because there is a question of LRRK2 pathology being due to loss of function, although mutations are thought to cause gain of function (Xiong et al., 2017). The LRRK2 KO mouse model does not present with dopaminergic neuronal loss or nigrostriatal dysfunction (Andres-Mateos et al., 2009; Lin et al., 2009; Tong et al., 2010; Herzig et al., 2011; Hinkle et al., 2012). Unexpectedly, LRRK2 KO mice are not sensitive to MPTP

(Andres-Mateos et al., 2009) and only one study found aSyn accumulation (Tong et al., 2010).

Most studies found no motor deficits, but one study did observe abnormal exploratory behavior

(Hinkle et al., 2012). Transgenic mice express either wild-type (WT) or mutant (G2019S and

R1141G) LRRK2 (Li et al., 2009; Lin et al., 2009; Tong et al., 2009; Li et al., 2010; Melrose et al., 2010; Herzig et al., 2011; Ramonet et al., 2011; Daher et al., 2012; Chen et al., 2012; Tsika et al., 2014; Liu et al., 2015; Beccano-Kelly et al., 2015; Garcia-Miralles et al., 2015; Yue et al.,

2015). Most transgenic LRRK2 mice exhibit changes in the dopaminergic system and nigrostriatal function (Chen et al., 2012; Beccano-Kelly et al., 2015; Yue et al., 2015; Liu et al.,

2015; Tong et al., 2009; Li et al., 2009; Ramonet et al., 2011; Li et al., 2010; Melrose et al.,

2010). Moreover, two studies have found age-dependent neurodegeneration of the SNpc; both used the G2019S mouse line with the same promoter (Chen et al., 2012; Ramonet et al., 2011).

In one of these studies, a 20% decrease in nigral dopaminergic neurons was seen at 20 months of age (Ramonet et al., 2011), whereas the other observed nigral degeneration beginning at 12 months, with maximal cell loss (50%) at 16 months (Chen et al., 2012). Only a few studies have found deficits in motor behavior (Ramonet et al., 2011; Chen et al., 2012; Li et al., 2009), and surprisingly, several studies observed hyperactivity (Lin et al., 2009; Li et al., 2010). Non-motor behaviors have not been studied very much in LRRK2 transgenic mice. However, a few studies reported cognitive deficits in these animals (Beccano-Kelly et al., 2015; Sloan et al., 2016;

Adeosun et al., 2017), whereas other studies in these mice examining non-motor behaviors noted none (Bichler et al., 2013). As with aSyn, there are a lot of variants of LRRK2 that have been associated with PD, and it’s possible that these variations could lead to a range of differences among LRRK2 studies.

Manipulating rat genetics has only recently been achieved, resulting in a few rat KO and transgenic models of LRRK2. Unfortunately, LRRK2 KO rats appear to lack a PD-like phenotype (Baptista et al., 2013; Ness et al., 2013; Daher et al., 2014). Moreover, these mutant

30 rats are resistant to insults that would normally induce dopaminergic cell death (Daher et al.,

2014). Several transgenic rat lines have been created using overexpression of WT LRRK2 and the mutations G2019S, R1441C, and R1441G. None of these models exhibit neurodegeneration of the SNpc (Zhou et al., 2011; Walker et al., 2014; Lee et al., 2015; Shaikh et al., 2015; Sloan et al., 2016). Two studies involving G2019S and R1441C mutants found that these rats stay on the rotarod for a shorter period of time compared to WT rats (Walker et al.,

2014; Sloan et al., 2016). Additional motor behavioral testing revealed no other differences compared to controls. Regarding non-motor behavior, one study observed impairment of short- term spatial memory in the alternating t-maze (Sloan et al., 2016). Taken together, rodent models of LRRK2 demonstrate varying degrees of aberrant motor behavior and a wide range of nigrostriatal system dysfunction, but most exhibit no degeneration of the SNpc.

The main autosomal recessive genes for PD are parkin (PARK2), PINK1 (PARK6), and

DJ-1 (PARK7). Mutant models of PD for these genes include either KOs, or transgenic with some truncated form of the gene to prevent the proteins from being functional (Dawson et al.,

2010). In this dissertation, we will be using the DJ-1 KO rat model, so we will go into further detail into the DJ-1 protein and rodent models in a separate section. Japanese families with an autosomal recessive inherited form of juvenile PD were the first families found to have parkin mutations (Kitada et al., 1998). Today, over 120 different parkin mutations have been reported to reduce parkin functioning (Scott et al., 2017). PINK1 mutations were first discovered in consanguineous families with early-onset PD (Valente, Abou-Sleiman et al., 2004; Valente,

Salvi et al., 2004). Many types of PINK1 mutations have been discovered in inherited and sporadic forms of PD, and include missense, nonsense, and frameshift mutations (Schulte and

Gasser, 2011). PINK1 is a serine/threonine kinase that acts as a sensor for the mitochondria.

There have been various reports of its location in the outer membrane of the mitochondria

(OMM), inner membrane of the mitochondria (IMM), and the cystol. PINK1 interacts with parkin,

31 and recruits parkin to the mitochondria (Silvestri et al., 2005; Clark et al., 2006; Zhou et al.,

2008; Jin et al., 2010; Narendra et al., 2010; Matsuda et al., 2010; Becker et al., 2012; Nguyen et al., 2016; Pickrell and Youle, 2015). Parkin is an E3 ubiquitin ligase which functions to help an E2 ubiquitin enzyme tag an un-needed or damaged protein with ubiquitin to mark it for the proteasome for degradation. Parkin is recruited by PINK1 to the OMM to mark mitochondria for degradation by autophagy (Dawson et al., 2010; Zhang et al., 2016; Clark et al., 2006; Pickrell and Youle, 2015; Nguyen et al., 2016). In general, the overall role of parkin and PINK1 is for mitochondrial quality control. Mitochondrial control consists of fission/fusion, mitochondrial transport, mitochondrial biogenesis and mitophagy. The relevance to PD, of course, is that mitochondrial dysfunction is strongly associated with the disease (Scott et al., 2017). PINK1 and parkin are implicated in mitochondrial fission/fusion, however studies in different cell lines have shown both pro-fission and pro-fusion effects (Chen and Chan, 2009; Scarffe et al., 2014).

PINK1/parkin also plays a role in mitochondrial biogenesis by increasing mitochondria DNA

(mtDNA) replication (Kuroda et al., 2006). Lastly, both parkin and PINK1 play a major role in protection against oxidative stress (Wang et al., 2011; Charan and LaVoie, 2015). However, the functions of PINK1 and parkin have been studied primarily in in vitro models, therefore PINK1 and parkin KO models may not necessarily express these alterations.

Parkin KO mice do display mitochondrial respiratory defects, markers of oxidative damage, and changes in mitochondrial morphology in the nigrostriatal system (Goldberg et al.,

2003; Palacino et al., 2004; Pinto et al., 2018). Yet, parkin KO mice do not display any loss of dopamine neurons of the SNpc (Goldberg et al., 2003; Itier et al., 2003; Von Coelln et al., 2004;

Perez and Palmiter, 2005; Zhu et al., 2007; Oyama et al., 2010; Aguiar et al., 2013; Rial et al.,

2014; Sanchez et al., 2014). Nonetheless, there is a spectrum of changes in dopamine parameters in the nigrostriatal system of these mice. For example, studies show increases in extracellular dopamine in the striatum (Goldberg et al., 2003; Itier et al., 2003), decreases in

32 dopamine release (Oyama et al., 2010), or no changes at all in nigrostriatal dopamine (Perez and Palmiter, 2005; Von Coelln et al., 2004; Aguiar et al., 2013; Sanchez et al., 2014). Also, the nigrostriatal system of parkin KO mice is not vulnerable to MPTP or 6OHDA as would be expected in a Parkinson’s model (Perez et al., 2005; Aguiar et al., 2013). Very few studies have observed motor deficits in parkin KO mice, and, if so, deficits are very minimal (Goldberg et al.,

2003; Zhu et al., 2007). Aberrant exploratory behavior (Zhu et al., 2007) and an increase in the number of foot slips on the challenging beam task were found compared to WT controls

(Goldberg et al., 2003). Other studies conducted a battery of motor behavioral tests and discerned no motor dysfunction (Perez and Palmiter, 2005; Rial et al., 2014). However, there are some cellular changes and behaviors associated with the NMS in the parkin KO mice. One study found a loss of LC neurons and decreases in NE (Von Coelln et al., 2004), but another reported no changes in NE levels (Perez and Palmiter, 2005). Additionally, impairment of hippocampal long term potentiation (LTP) has been shown in parkin KO mice (Rial et al., 2014).

A few studies have examined non-motor behaviors in these KO mice. Zhu et al. (2007) observed thigmotaxis in parkin KO mice, a sign of anxiety-like behavior. Rial et al. (2014) ran several non-motor tests, including olfactory detection, elevated-plus maze (anxiety-like behavior), tail suspension (depressive-like behavior), but found that parkin KO mice performed poorly only in object location tasks and the modified Y-maze (cognitive dysfunction). Perez et al. (2005), in contrast, found no indication of cognitive deficits. Thus, parkin KO mice do not have a robust PD phenotype, nor do these mice consistently display changes in the dopaminergic or noradrenergic systems.

The parkin KO rat is a newer model, and, to date, these mutant rats do not display any behavioral deficits or loss of nigral dopaminergic neurons (Dave et al., 2014). However, the parkin-deficient rat is being used for proteomic studies, including identifying substrates of parkin, which helps to better elucidate cellular and molecular mechanisms associated with parkin

(Kurup et al., 2015). Thus, both rat and mouse parkin KO model do not exhibit a robust PD phenotype, and there is no consensus as to what, if any, changes occur in nigrostriatal dopamine.

PINK1 KO mice and rats have contrasting phenotypes. PINK1 KO mice exhibit mitochrondrial dysfunction, in particular, deficits in mitochondrial respiration (Gautier et al.,

2008; Gispert et al., 2009). Studies of striatal dopamine in PINK1 KO mice have revealed no changes (Kitada et al., 2007; Sanchez et al., 2014) or a decrease in striatal dopamine content

(Gispert et al., 2009). Motor deficits in this model are minimal, and impairments occur in open- field measures of spontaneous activity and gait (Gispert et al., 2009; Glasl et al., 2012). Apart from the nigrostriatal system, cannabinoid receptor dysfunction, excitatory presynaptic changes in hippocampal neurons, and denervation of 5HT neurons have been observed (Glasl et al.,

2012; Feligioni et al., 2016; Madeo et al., 2016). The only non-motor deficit to occur in PINK1

KO mice is disrupted olfaction (Glasl et al., 2012). Like PINK1 KO mice, PINK1 KO rats also have defects in mitochondrial respiration. But, unlike mice, PINK1-deficient rats display aSyn aggregates in various brain regions (Grant et al., 2015; Villeneuve et al., 2016). Motor deficits occur in PINK1 KO rats as early as 4 months of age. Impairments in motor behavior occur in spontaneous locomotor activity in the open field test, reduction of hindlimb grip strength, and increased errors on the tapered beam (Dave et al., 2014; Grant et al., 2015). The only non- motor deficit tested in PINK1 KO rats, to date, is ultrasonic vocalizations (USV), in which dysfunction occurs as early as 2 months of age (Grant et al., 2015). Although, as stated above,

PINK1 and parkin KO mice do not display a strong PD-like phenotype, these models are still useful in examining mitochondrial pathology in PD. The PINK1 and parkin KO rat models are newer, and, accordingly, further research needs to be done on changes in non-motor behaviors and alterations in relevant neurotransmitter systems (i.e. NE and 5HT) in addition to dopamine.

The substantia nigra pars compacta and Parkinson’s disease

The substantia nigra pars compacta is an intrinsic brain nucleus of basal ganglia circuitry. The basal ganglia consist of a number of subcortical nuclei that modulate cortical activity (Alexander and Crutcher, 1990; Hoover and Strick, 1999). Although the primary role of the basal ganglia is motor control, other roles include motor learning, executive function and behaviors, and emotions (Lanciego et al., 2012). The nuclei of the basal ganglia are involved in a number of parallel loops which consists of oculomotor, prefrontal, limbic, and motor circuits

(Alexander et al., 1986; Alexander and Crutcher, 1990). All of the loops begin with input from the cortex to the striatum (caudate and putamen), go through different pathways to the globus pallidus internus (GPi) or the substantia nigra pars reticulate (SNpr), which are the output nuclei of the basal ganglia, and finally, to the thalamus or other brain nuclei (Gale et al., 2008).

Cortical inputs come from limbic, associative, sensory, and motor areas which include brain regions such as the prefrontal cortex (PFC), pre-motor cortex, motor cortex, sensorimotor cortex, and the parietal cortex (Alexander et al., 1986; Haber, 2003; Draganski et al., 2008).

These afferents are mainly glutamatergic (excitatory) and project onto the GABAergic

(inhibitory) medium spiny neurons (MSN) of the striatum (Wilson, 1987). With many inputs and functions, the basal ganglia maintain a high degree of spatial topographical functionality. For example, the posterior putamen is involved in sensorimotor functions, the caudate and anterior putamen with associative functions, and the ventral striatum with limbic functions (Nakano et al.,

2000). In PD, the focus is on the motor loop of the basal ganglia which consists of the posterior putamen, GP, SN, subthalamic nucleus (STN), and motor nuclei of the thalamus (Gale et al.,

2008). The motor loop effects initiation and execution of goal directed, and habitual, voluntary motor movements (Redgrave et al., 2010). There are two pathways: the direct pathway that initiates movement and the indirect pathway that suppresses movement (Albin et al., 1989a;

DeLong, 1990). The dopaminergic neurons of the SNpc projects to the forebrain striatum

(caudate and putamen) and affect both the direct and indirect pathways. In the direct pathway, the putamen projections inhibit the GPi, which prevents the tonic inhibition of the ventral anterior/ventral lateral (VA/VL) nuclei of the thalamus. The VA/VL then transmits excitatory signals to the motor cortex for movement initiation. In the indirect pathway, the putamen inhibits the GP externus (GPe), which releases the neurons of the STN from tonic inhibition. Cells from the STN activated the GPi, and then those neurons lead to inhibition of the VA/VL and the cortex which leads to decreased movement (Albin et al., 1989a). Loss of dopaminergic neurons of the SNpc leads to an imbalance in the direct and indirect pathways of the motor loop. Dopamine has a neuromodulatory effect on the postsynaptic excitability of MSN via dopamine receptors, and pre-synaptic inhibition of glutamate striatal release through dopamine receptors on the corticostriatal terminals (Bamford et al., 2004; Gale et al., 2008; Gerfen and

Surmeier, 2011). The direct and indirect pathways are differentially affected by dopamine because the dopamine 1 receptors (D1), in the direct pathway, are excited by dopamine, whereas the dopamine 2 receptors (D2), in the indirect pathway, are inhibited (Gerfen et al.,

1990). Loss of dopamine causes the direct pathway to be less active, meaning the striatum does not inhibit the GPi, leading the GPi to inhibit the VA/VL (motor nuclei). The indirect pathway is more active in PD. Striatal neurons become more active without dopamine inhibition, leading to increase inhibition of the GPe. The GPe then disinhibits the STN, allowing the STN to activate the GPi, which increases inhibition of the VA/VL. Subsequently, reduced

VA/VL signaling to the motor cortex results in motor deficits (Aizman et al., 2000). The indirect and direct pathways may seem straightforward, but it is now recognized there are sub-sets of connections that are important. For example, the SNpc projects to the STN and GPe, and regulates other modulatory neurons (e.g. acetylcholinergic striatal interneurons) (Redgrave et al., 2010). Hence, the SNpc is integral to proper functioning of the basal ganglia.

The SNpc is not the only dopaminergic nucleus in the brain, but it is the only one greatly affected by PD. The SNpc mainly contains dopamine neurons, but approximately 29% are

GABAergic, based on animal research (Nair-Roberts et al., 2008). The greatest loss of dopamine neurons is in the ventrolateral SNpc, and most dopamine innervation is in the posterior putamen (Kish et al., 1988; Fearnley and Lees, 1991). Most nigral dopaminergic neurons contain the pigment neuromelanin. In postmortem tissue, it is easy to distinguish a PD versus healthy brain because of the loss of neuromelanin (Ehringer and Hornykiewicz, 1998).

Imaging analyses of brains of PD patients confirms those with PD have lower striatal dopamine content (Kaasinen and Vahlberg, 2017) than healthy age-matched controls.

The SNpc and adjacent ventral tegmental area (VTA) both are dopaminergic nuclei in the ventral midbrain, but the dopamine neurons of the VTA are more resistant to degeneration than the nigral cells (Dauer and Przedborski, 2003). Although there is less than a 3% difference in gene expression between these two regions, those differences may be the key to SNpc vulnerability (Grimm et al., 2004). Dopamine neurons of the SNpc possess long, branched, unmyelinated axons with many transmitter-release sites (de Lau and Breteler, 2006).

Mitochondrial oxidative stress is high in dopamine axons, and one of the ways to reduce oxidative stress is reduction of axonal arborization (Pacelli et al., 2015). In addition, longer axons can leave neurons vulnerable to aSyn propagation and toxicity (Zharikov et al., 2015).

Another feature that potentially leads to increased dopamine cell vulnerability is the long, broad action potentials that maximize calcium entry and slow rhythmic activity (Bean, 2007). Cytosolic dopamineis toxic itself, and can contribute to SNpc vulnerability (Surmeier, 2018). Inputs from the STN or striatum could add stress to dopamine neurons. Striatal denervation is greater than somal loss in the SNpc in the early stages of PD. This early denervation points to retrograde degeneration of dopamine neurons (Cheng et al., 2010). Ultimately, it is likely a combination of

37 all the above scenarios that contributes to the enhanced susceptibility of the SNpc to neurodegeneration in PD.

The dorsal raphe nucleus and Parkinson’s disease

The DRN is the main source of 5HT in the brain. Functions attributed to the DRN include cognition, emotional behavior (including depression and anxiety), motor behavior, regulation of circadian rhythm, etc. (Gerson and Baldessarini, 1980; Berger et al., 2009; Benarroch, 2009a).

The DRN is a part of a collection of nuclei called the raphe nuclei that span the midbrain, pons, and medulla oblongata (Dahlström and Fuxe, 1964). The DRN is located in the ventral periaqueductal grey matter of the mesencephalon, and the caudal end passes into the pons

(Michelsen et al., 2008). In humans, the DRN contains about 235,000 neurons, with approximately 165,000 being serotonergic cells (Baker et al., 1990,1991). Other neuroactive substances in the DRN include dopamine (Yoshida et al., 1989), GABA (Nanopoulos et al.,

1982), excitatory amino acids (e.g. glutamate) (Clements et al., 1987), and neuropeptides (van der Kooy et al., 1981; Uryu et al., 1992; Petit et al., 1995; Kozicz et al., 1998). Numerous afferent and efferent pathways are connected with the DRN. There are both ascending and descending efferent pathways, with the ascending efferents being the most numerous. The three main ascending projections include the dorsal, medial, and ventral pathways. With respect to PD, the two most important are the dorsal and ventral pathways because they project to most of the forebrain and the striatum (caudate and putamen). The descending pathways mainly target the cerebellum, lower brainstem (e.g. locus coeruleus), and spinal cord (Michelsen et al., 2008). Afferents to the DRN include glutamatergic and GABAergic inputs from areas including the PFC and SN (Soiza-Reilly and Commons, 2014). Projections to and from the DRN are organized topographically, such that sub-regions of the DRN (i.e. rostral, dorsal, ventral, ventrolateral, interfascicular, and caudal) control different functions (Baker et al., 1990). The rostral DRN projects to regions such as the striatum (Steinbusch et al., 1980), STN (Canteras et

38 al., 1990), SN (Imai et al., 1986), and motor cortex (Waterhouse et al., 1986). Rostral DRN function is mainly motor because, for example, chronic voluntary exercise in rats leads to changes in serotonin transporter (SERT) and receptors in this region (Greenwood et al., 2005).

The dorsal part of the DRN receives afferents from brain regions associated with emotional behavior such as the ventral orbitofrontal and infralimbic cortices, central nucleus of the amygdala, bed nucleus of the stria terminalis, and several hypothalamic nuclei (Peyron et al.,

1998). Efferents from dorsal DRN project to regions that help regulate emotional states (e.g. hippocampus, LC, PFC) (Imai et al., 1986; Van Bockstaele et al., 1993). In particular, the dorsal

DRN is important in stress-, depression- and anxiety-related circuitry (Commons et al., 2003).

Anxiogenic drugs increase c-fos expression in the dorsal DRN, and stressors like social defeat and uncontrollable stress activate the dorsal DRN as well (Gardner et al., 2005; Abrams et al.,

2005; Amat et al., 2005). Afferents to the ventral portion of the DRN are similar to those of the dorsal sub-region (Peyron et al., 1998; Lee et al., 2003). Efferents project to regions such as the striatum (Steinbusch et al., 1980), and frontal, sensorimotor, motor, and visual cortices

(Waterhouse et al., 1986). Likely, the 5HT neurons of the ventral sub-region, are involved in motor function and complex cognitive tasks. For example, chronic voluntary exercise in rats modulates 5HT receptor mRNA levels (Greenwood et al., 2005). Afferents to the ventrolateral part of the DRN originate from brainstem and forebrain regions associated with autonomic control, such as the fight or flight response and emotional behavior that involves changes in muscle tone. Efferents form reciprocal connections to the brain regions the ventrolateral DRN receives afferents from (Hale and Lowry, 2011). Ventrolateral DRN serotonergic neurons respond to panic-inducing stimuli (Johnson et al., 2005). The interfascicular portion of the DRN receives inputs from the preoptic area (thermosensory pathway) and the LC (Kim et al., 2004;

Nakamura and Morrison, 2010). Interfascicular efferents project to areas such as the hippocampus and PFC. The function of this subregion seems to be associated with cognitive and emotional processing and thermal and visual stimuli (Hale and Lowry, 2011). Lastly, the

39 caudal subregion of the DRN receives afferents from the medial PFC and portions of the hypothalamus (Lee et al., 2003). Efferents project to brain areas including the hippocampus, amygdala, and LC (Imai et al., 1986). Like the dorsal subregion, the caudal DRN serves important roles in stress and anxiety. For example, serotonergic neurons are activated by anxiogenic drugs and social defeat (Abrams et al., 2005; Gardner et al., 2005). Overall, the

DRN is involved in motor, cognitive, and emotional circuits of the brain, all of which can be dysfunctional in PD. Understanding of the connections of the DRN helps us comprehend its role in PD.

The DRN and its neurotransmitter 5HT are a part of PD pathology. The DRN heavily innervates the nuclei of the basal ganglia, regions intimately involved in Parkinson’s and particularly in the motor symptoms. In humans, as the disease advances, serotonergic transmission decreases because the DRN and other nuclei degenerate (Halliday et al., 1990;

Kerenyi et al., 2003). Serotonin, its metabolite 5-hydroxyindoleacetic acid (5HIAA), SERT, and the 5HT1A receptor are decreased in nuclei of the basal ganglia in PD (Scatton et al., 1983;

Kerenyi et al., 2003; Guttman et al., 2007; Ballanger et al., 2012). Toxin-based animal models mimicking nigrostriatal deficits also present with changes in the serotonergic system. Several studies of the 6OHDA rat observed reduction in striatal 5HT and 5HIAA (Brannan et al., 1990;

Karstaedt et al., 1994). Increases of 5HT receptors and of neuronal firing of 5HT neurons of the midbrain raphe nuclei in a unilateral 6OHDA rat model were detected (Numan et al., 1995;

Wang et al., 2009). However, some 6OHDA rat studies report unaltered 5HT and 5HIAA levels

(Breese et al., 1984; Gil et al., 2010). The variability of changes in the serotonergic system in the 6OHDA rat models may be due to differences in the experimental paradigms. The 6OHDA rat may not be the best model to study the relationship of 5HT and PD (Huot et al., 2011).

Besides motor symptoms, the DRN and 5HT contribute to the NMS of Parkinson’s disease. PD patients have lower 5HIAA cerebrospinal fluid (CSF) levels than age-matched

40 controls. But PD patients with depression have lower levels of CSF 5HIAA than those with PD that do not have mood changes (Mayeux et al., 1986; Kostic et al., 1987). Reduction of neurons in the ventrolateral and caudal subregions of the DRN occurs in individuals with PD and dementia (Chan-Palay et al., 1992). Serotonergic dysregulation is also associated with sleep issues in PD (Wilson et al., 2018). Recapitulation of serotonergic dysfunction in genetic rodent models has been difficult. A double KO of parkin and DJ-1 in mice leads to increases in 5HT

(Hennis et al., 2014). In contrast, in an A53T aSYN transgenic mouse model, brainstem 5HT was decreased (Deusser et al., 2015). However, another study using these latter mutant mice did not observe any serotonergic changes (Graham and Sidhu, 2010). New animal models need to be developed to study the role of 5HT and the DRN in PD.

The locus coeruleus and Parkinson’s disease

The LC is the main source of NE in the brain. Functions attributed to the LC are cognition, arousal/wakefulness, vigilance, pain modulation, and rapid eye movement (REM) sleep behavior (Gesi et al., 2000; Berridge and Waterhouse, 2003; Espay et al., 2014). The LC is located in the upper dorsolateral pontine tegmentum of the brainstem, adjacent to the fourth ventricle. The nucleus is only a small cluster of about 15,000-32,000 neurons, but has extensively branched axons that project to multiple cortical, subcortical, brainstem, and spinal cord nuclei. It is the only source of NE for the neocortex, hippocampus, cerebellum and most of the thalamus (Aston-Jones and Cohen, 2005). Norepinephrine has either an excitatory or inhibitory effect depending on its receptor. The α1 and β adrenergic receptors are excitatory and the α2 adrenergic receptors are mainly inhibitory (Benarroch, 2009b). The efferent projections of the LC can be divided into 3 main pathways: ascending, cerebellar, and descending

(Szabadi, 2013) . Because of the extensive LC efferent projections, only connections pertinent to this dissertation will be discussed. The LC is the only source of NE in the neocortex, with diffuse and rich innervation throughout the structure. There is a close correlation between LC

41 activity and NE release into the neocortex (Gatter and Powell, 1977; Loughlin et al., 1982). Due to its high concentration of α1 receptors, NE is excitatory in the cortex (Domyancic and Morilak,

1997). Electroencephalogram (EEG) data confirm that LC activation leads to increased cerebral cortical activity (Berridge and Foote, 1991). There is also dense NE innervation of the central and basal nuclei of the amygdala, which controls fear and anxiety responses and emotional memory formation and retrieval (Fallon et al., 1978; Damasio, 1998; Chen and Sara, 2007).

The LC is also the only source of NE for the hippocampus, and its involvement in learning and memory (Sara and Devauges, 1988; Sullivan et al., 1994; Fu et al., 1999). In the diencephalon, the thalamus receives strong excitatory LC projections (Ishikawa and Tanaka, 1977; Jones et al., 1985). The role of NE in the thalamus includes promotion of wakefulness and modulation of pain (McCormick et al., 1991; Westlund et al., 1991). The LC also projects to the brainstem, elaborating efferents to the DRN, with an excitatory influence (Pan et al., 1994). Besides efferent projections, the LC receives numerous afferent projections. These afferents include reciprocal pathways from the regions to which the LC projects (Aston-Jones et al., 1991).

Similar to that of the DRN, consideration of LC inputs and outputs helps us better understand the role it plays in PD.

Evidence for LC/NE dysfunction in PD comes from both human and animal studies. The

LC is one of the earliest nuclei to degenerate in PD, and, acordingly, it is thought to play a role in the pre-clinical manifestation of NMS. About 70% of the neurons of the LC are absent in postmortem PD brains (van Dijk et al., 2012). Fluctuations in attention in PD patients matches with fluctuations in NE release (McKeith et al., 1996; Troster, 2008). Enhancing NE signaling improves cognitive performance in PD patients (Weintraub et al., 2010). Postural hypotension is partly relieved by the oral NE precursor droxidopa (Schrag et al., 2015). Using [11C]RTI-32

PET imaging, depressed PD patients had lower NE transporter binding than non-depressed PD patients (Remy et al., 2005). Several PD rodent models demonstrate importance of the LC and

NE in Parkinson’s pathology. In MPTP-treated mice and 6OHDA-treated rats, additional lesioning of the LC leads to enhanced dopaminergic neuronal degeneration, lower dopamine levels, and poorer motor performance compared to rodents with just the nigrostriatal lesion

(Nishi et al., 1991; Marien et al., 1993; Shin et al., 2014; Rampersaud et al., 2012). Many of the transgenic and KO rat PD models have not displayed alterations in the LC/NE system, or have not been evaluated yet for such changes. On study found that parkin KO mice displayed LC cell loss and decrease in NE levels (Von Coelln et al., 2004), but another did not (Perez and

Palmiter, 2005). Nonetheless, it is important to continue to generate new genetic PD animal models that at least display neurodegeneration in one of the three major nuclei (SNpc, DRN,

LC) and a more robust PD phenotype to uncover the cause of and/or identify novel therapeutic targets for PD. In this dissertation, we will be examining the SNpc, DRN, and LC for neurodegeneration, decreases in monoamine levels, and non-motor and motor aberrant behavior in a novel rat model of PD.

Olfaction and Parkinson’s disease

Loss of olfactory faculties occurs early in neurodegenerative diseases such as

Alzheimer’s disease (AD) and Parkinson’s, and could possible an early biomarker of PD

(Mesholam et al., 1998; Doty, 2012). Olfaction is clinically correlated with PD, REM sleep, and mild cognitive impairment (MCI). Both MCI and REM sleep disorders are present in PD (Driver-

Dunckley et al., 2014; Huang et al., 2016; Doty, 2017). Approximately 50-90% of people with

PD have some kind of olfactory deficit (Doty et al., 1988; Ponsen et al., 2004). The olfactory bulb (OB) seems particularly susceptible to LBs because of their presence in the OB at early stages of the disease. However, the reason for this vulnerability is still unknown (Braak et al.,

2003a; Rey et al., 2018). Hyposmia is the most common form of olfactory defect, but a minor portion of those with PD experience anosmia (Doty et al., 1988; Rey et al., 2018). Olfactory detection, discrimination, and identification all depend on central processing, and all are

43 severely affected in PD (Doty, 2012). Functional magnetic resonance imaging (fMRI) studies of

PD patients given olfactory stimuli express less activity in the hippocampus and amygdala

(Westermann et al., 2008). Dopamine, norepinephrine, and serotonin all make contributions to olfaction, although the specific roles of some of these neurotransmitters are not clearly established (Doty, 2012). Both the LC and DRN send efferent projections to the OB (Michelsen et al., 2008; Szabadi, 2013). Interestingly, although the OB locally synthesizes its own dopamine within the periglomerular cells (Gall et al., 1987), there is minor distant dopaminergic input from the SN (Hoglinger et al., 2015).

Depression and Parkinson’s disease

Studies reporting the frequency of depression in PD range from 10-50%, which is higher than the incidence of depression in the general population. The range depends on the parameters of the study, but, nevertheless, depression among the PD population still goes under-reported (Cummings, 1992; Burn, 2002; Goodarzi et al., 2016) and cannot be explained as a psychosocial reaction to disease diagnosis alone (Ishihara and Brayne, 2006). Depression is considered a risk factor for PD and often occurs in the pre-clinical stage of the disease

(Gustafsson et al., 2015). About 20% of PD patients already have depression when diagnosed with PD (Shiba et al., 2000). Diagnosis of depression in PD depends on the criteria for major depression, but other symptoms of Parkinson’s overlap (e.g. sleep disturbances) with the

Diagnostic and Statistical Manual of Mental Disorders (DSM-V) entry for major depression

(Marsh et al., 2006; Schintu et al., 2012). Depression in PD is somewhat different from major depression. Irritability, sadness, dysphoria, pessimism, and suicidal ideation are more frequent in PD depression, while guilt, self-blame, feelings of failure, and suicide attempts are less typical

(Burn, 2002). Overall, co-morbid depression has a substantial negative impact on the quality of life for PD patients (Baquero and Martin, 2015). The neurotransmitters most associated with depression in PD are DA, NE, and 5HT (Snyder and Ferris, 2000). As mentioned above,

44 depressed PD patients exhibit lower NET binding than non-depressed PD patients (Remy et al.,

2005). Also, striatal DAT binding is lower in depressed PD patients compared to those without depression (Vriend et al., 2014). Both the LC and DRN modulate emotional behavior through their efferent and afferent pathways to brain regions associated with depression (e.g. limbic cortex, PFC) (Michelsen et al., 2008; Szabadi, 2013). In postmortem PD brain tissue, individuals who suffered from depression have greater neurodegeneration of the LC and DRN compared to those who did not (Ehgoetz Martens and Lewis, 2017). Moreover, in an animal model, our lab has found that chronic stress-induced depression concurrent with neurotoxin (6-

OHDA)-induced neurodegeneration exacerbates the behavioral dysfunction and degeneration of nigrostriatal dopaminergic neurons (Hemmerle et al., 2014). In general, depression in PD has been understudied and requires much further basic and translational research.

Anxiety and Parkinson’s disease

Anxiety occurs in approximately 40% of PD patients and contributes to increase disability and poor quality of life (Richard, 2005; Dissanayaka et al., 2014). People with PD experience a higher incidence of anxiety than age-matched controls (Picillo et al., 2013). Less attention has been paid to anxiety compared to other NMS, like depression, so anxiety in PD is still poorly understood. Currently, anxiety disorders reported by PD patients include generalized anxiety disorder (GAD), social phobia, and anxiety disorder, not otherwise specified (NOS)

(Dissanayaka et al., 2014). The most common complaints are an inability to relax, restlessness, feeling tense, and worrying thoughts (Mondolo et al., 2007). Dopamine, norepinephrine, and serotonin all are involved in the pathology of anxiety in Parkinson’s (Prediger et al., 2012). A relationship exists between anxiety and PD motor functioning, especially postural control, due to the connections between brain regions associated with posture and emotion/fear (Macht et al.,

2005; Balaban and Thayer, 2001). Studies using fMRI indicate a perturbation of the dopaminergic input to the amygdala in PD patients with abnormal emotional expression (Benke

45 et al., 1998). Both the LC and DRN are important for the regulation of anxiety. Degeneration of the LC and DRN in PD results in reduction of NE and 5HT which leads to enhanced anxiety

(Leentjens et al., 2006; Benarroch, 2009b). Individuals with PD also exhibit susceptibility to panic attacks induced by an adrenergic receptor antagonist (Richard et al., 1999). Thus, as a whole, decreases in DA, NE, and 5HT all contribute to anxiety in PD.

Cognitive Impairment and Parkinson’s disease

Dementia occurs in approximately 60-83% of those with late stage PD (Aarsland et al.,

2001; Buter et al., 2008; Halliday et al., 2008). As with AD, those with Parkinson’s begin with

MCI, and slowly graduate to dementia (Pedersen et al., 2017). At clinical diagnosis, some PD patients already exhibit MCI, and about a third at diagnosis will display a subtle cognitive impairment (Broeders et al., 2013). Cognitive functions affected in the early stages of

Parkinson’s include memory, visuospatial processing, executive functions, and attention

(Cronin-Golomb and Braun, 1997; Dujardin et al., 1999; Lewis et al., 2003; Troster, 2008;

Bronnick et al., 2011). Deficits in working memory and attentional-executive functioning are the most common in those without dementia (Muslimovic et al., 2005; Mamikonyan et al., 2009).

Fluctuation in attentional ability occurs in about 90% of PD patients (McKeith et al., 1996;

Troster, 2008). Dopamine and norepinephrine both majorly influence cognitive impairment.

Executive functioning, memory, visuospatial perception, and language are influenced by the basal ganglia, therefore loss of dopamine in PD is detrimental to these cognitive functions

(Monchi et al., 2000; Weintraub et al., 2010). In PET imaging studies, striatal dopamine levels correlate with executive functioning in those with PD. Noradrenergic projections to the PFC help enact working memory, learning, and attention, particularly when it comes to the ability to explore and recognize novelty (Espay et al., 2014). In non-demented PD patients, inhibition of

NE neurotransmission decreases attention and overall cognitive performance. Increasing NE synthesis partially reverses the cognitive deficits (Bedard et al., 1998). Moreover,

46 noradrenergic reuptake blockers can improve cognitive function in PD patients (Weintraub et al.,

2010; Foltynie et al., 2004). Overall, loss of NE and dopamine in PD contribute to cognitive impairment in PD.

DJ-1 and Parkinson’s disease

In this dissertation research, we will be assessing the DJ-1 KO rat for parkinsonian-like behavioral changes, degeneration of the SNpc, LC, and DRN, and decreases in the concentrations of NE, DA, and 5HT in brain regions associated with PD. DJ-1 (name of both the gene and protein) is a 189 amino-acid protein that is a part of the ThiJ/PfpI superfamily of proteins (Bonifati et al., 2003). The protein is highly conserved and homologs can be found in all aerobic species (Cookson, 2012). First discovered as an oncogene, the DJ-1 protein was absent in Dutch and Italian families with an autosomal recessive form of PD. DJ-1 is located on chromosome 1p36, and the Dutch family mutation was missing exons 1-5. The Italian family had a substitution of a highly conserved leucine with a proline at the 166 position (Bonifati et al.,

2003; Taira et al., 2004). After these initial discoveries, other missense, frame-shift, and splice- site mutations were identified (Hague et al., 2003). Mutations found in familial forms of PD prevent homodimerization of DJ-1, which renders the protein inactive (Miller et al., 2003;

Olzmann et al., 2004).

DJ-1 is involved in a diverse number of biological processes, but much of DJ-1 functioning is still not understood. DJ-1 is found in almost all tissues and cells, mainly in the cytosol, mitochondria, and nucleus (Cookson, 2010). The most widely accepted role of DJ-1 is prevention of oxidative stress. Three highly conserved cysteine residues help DJ-1 act as an auto-sensor of oxidative stress, of which the most important is Cys106. The cysteine residues are oxidized by reactive oxygen species (ROS) to maintain redox homeostasis. In addition,

47 oxidative stress induces DJ-1 to relocate to the mitochondria, which may be the site of its neuroprotective activities (Taira et al., 2004; Canet-Aviles et al., 2004; Junn et al., 2009). Very little of the total DJ-1 activity, however, involves this auto-sensor function. Most likely, DJ-1 has a signaling role in coordinating cellular responses to oxidative stress (Cookson, 2010). Various studies report that DJ-1 acts similar to a peroxiredoxin (Andres-Mateos et al., 2007), stabilizes antioxidant transcription factors (Clements et al., 2006), functions in histone deacetylation

(Hardy et al., 2006), act as a protein chaperone (Shendelman et al., 2004), acts as a protease

(Olzmann et al., 2004), functions in apoptosis (Junn et al., 2005), and upregulates glutathione synthesis (Zhou and Freed, 2005). Besides oxidative stress, cell culture studies noted connections between DJ-1 levels and mitochondrial indices. A decrease in cellular DJ-1 leads to mitochondrial fragmentation, and DJ-1 counteracts this fragmentation by interacting with p53

(Ottolini et al., 2013). Loss of DJ-1 in cells drives impaired mitochondrial dynamics, whereas overexpression of the protein improves mitochondrial functioning (Krebiehl et al., 2010; Zhang et al., 2016). DJ-1 activity is also linked to microglia. Microglia deficient in DJ-1 exhibit an increase in inflammatory cytokines and an increase in activation. It is hypothesized that DJ-1 operates as an “off” signal to microglia in high cellular stress situations to prevent microglia neurotoxicity (Trudler et al., 2014; Kim et al., 2013). Moreover, DJ-1-deficient cells exhibit reduced phagocytosis of aSyn by microglia (Nash et al., 2017). Elevation of oxidative stress, mitochondrial damage, and microglial activation, as described here for DJ-1-deficient cells in culture, also occurs in the PD brain (Schapira et al., 1990; Jenner, 2003). Thus, it is important to examine DJ-1 KO rodents to determine if lack of DJ-1 leads to a PD-like phenotype.

Exploring the role of DJ-1 in PD using KO rodent models has led to mixed results when it comes to expressing a PD-like phenotype. DJ-1 was first knocked out in mice, and the motor deficits observed in mice range from none to moderate. Notably, DJ-1 KO mice do not exhibit neurodegeneration or decreases in monoamines (Chen et al., 2005; Yamaguchi and Shen,

2007; Manning-Bog et al., 2007; Chandran et al., 2008; Pham et al., 2010; Rousseaux et al.,

2012). Although numerous DJ-1 KO mice studies have examined motor behavior, only one evaluated behavior related to NMS in which DJ-1 KO mice exhibited deficits in the novel object recognition task, a measure of short-term memory and attention (Pham et al., 2010). However, there was no neurodegeneration of nigral or extranigral regions, and no changes in either 5HT or NE levels (Pham et al., 2010).

Several years ago, the Michael J. Fox Foundation for Parkinson’s Research and Horizon

Discovery joined forces to create DJ-1 KO rats to determine if this species expressed a more robust PD phenotype than mice. Results from the first published study indicate that, compared to WT controls, DJ-1-deficient rats exhibit some motor deficits which include decreases in rearing frequency, open field mobility, and grip strength, as well as an increase in errors on the tapered beam (Dave et al., 2014). Testing of non-motor behaviors was not conducted in this study. In addition, loss of dopamine (TH-immunoreactive) neurons of the SNpc, increases in striatal dopamine, and decreases in striatal 5HT levels were reported at 8 months of age (Dave et al., 2014). However, monoamine levels were not measured in any other brain regions, and evaluation of total neuron numbers (i.e. via Neu-N or Nissl cell counts) was not performed in the

SNpc to verify frank neuronal degeneration versus simply TH phenotypic loss. Another study corroborated that DJ-1 KO rats make errors during the tapered beam task, as well as demonstrate dysfunctional ultrasonic vocalizations and impaired tongue motor performance

(Yang et al., 2018). A decrease in the number of TH-positive cells was also reported in the LC, but, again, counts of the total number of neurons lost in the LC were not conducted, and unbiased stereology methods were not used (Yang et al., 2018). Although the LC is known to contribute to NMS in PD, non-motor behaviors were not assessed in that study. Thus, a more complete characterization of motor and non-motor behaviors, neurotransmitter levels and neuronal survival in PD-related brain regions in DJ-1 KO rats is warranted.

Objectives

This dissertation examines the DJ-1 KO rat model to determine if there are alterations in motor and non-motor behaviors, changes in monoamine levels in various brain regions, and neurodegeneration or phenotypic loss in PD-relevant brain regions (SNpc, LC, and DRN), compared to age-matched WT control rats. Given the association of DJ-1 and microglial function, we will also probe the LC, DRN, SNpc, and striatum for increases in active microglia.

We hypothesize that DJ-1-deficient rats will exhibit both motor and non-motor behavioral deficits, reduced monoamine levels, neurodegeneration of the SNpc, LC, and DRN, and increases in activated microglia.

Specific Aims

Aim 1: Characterize the behavioral phenotype of the DJ-1 KO rat.

Aim 2: Determine if DJ-1 KO rats have decreases in monoamine levels and enhanced neurodegeneration in brainstem monoaminergic nuclei.

Aim 3: Determine if DJ-1 KO rats have increased numbers of activated microglia in aged DJ-1

KO rats.

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Chapter 2

Characterization of Motor and Non-Motor Behavioral Alterations in the Dj-1 (PARK7) Knockout Rat

This chapter is based on the following publication:

Kyser TL, Dourson AJ, McGuire JL, Hemmerle AM, Williams MT, Seroogy KB (2019) Characterization of motor and non-motor behavioral alterations in the Dj-1 (PARK7) knockout rat. Journal of Molecular Neuroscience 69:298-311. https://doi.org/10.1007/s12031-019-01358-0

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Abstract Parkinson’s disease is a neurodegenerative disorder that encompasses a constellation of motor and non-motor symptoms. The etiology of the disease is still poorly understood because of complex interactions between environmental and genetic risk factors. Using animal models to assess these risk factors may lead to a better understanding of disease manifestation. In this study, we assessed the Dj-1 knockout (KO) genetic rat model in a battery of motor and non-motor behaviors. We tested the Dj-1 KO rat, as well as age-matched wildtype

(WT) control rats, in several sensorimotor tests at 2, 4, 7, and 13 months of age. The Dj-1- deficient rats were found to rear and groom less, and to have a shorter stride length than their

WT counterparts, but to take more forelimb and hindlimb steps. In non-motor behavioral tasks, performed at several different ages, we evaluated the following: olfactory function, anxiety-like behavior, short-term memory, anhedonia, and stress coping behavior. Non-motor testing was conducted as early as 4.5 months and as late as 17 months of age. We found that Dj-1 KO animals displayed deficits in short-term spatial memory as early as 4.5 months of age during place preference testing, as well as impaired coping strategies in the forced swim test, which are consistent with a parkinsonian-like phenotype. In some instances, effects of chronic stress were evaluated in the Dj-1-deficient rats, as an initial test of an environmental challenge combined with a genetic disposition for PD. Although some of the results were mixed with differential effects across several of the behaviors, the combination of the changes we observed indicates that the Dj-1 KO rat may be a promising model for the assessment of the prodromal stage of Parkinson’s disease, but further evaluation is necessary.

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Introduction Parkinson’s disease (PD) is the second-most common neurodegenerative disorder, with approximately 10 million people afflicted with the disease worldwide (Schapira, 2009). For diagnosis of PD, four cardinal motor deficits are manifest to varying degrees: bradykinesia, rigidity, resting tremors, and postural instability. The loss of dopaminergic neurons within the substantia nigra pars compacta (SNpc) leads to these motor changes (Fahn, 1999; Rascol,

2000). In addition, there is another group of symptoms, collectively known as the non-motor symptoms (NMS), which are largely unresponsive to dopamine or dopamine replacement therapies. Non-motor symptoms are thought to result from dysfunction and/or degeneration of regions such as the locus coeruleus (LC) and dorsal raphe nucleus (DRN), which are the main sources of norepinephrine (NE) and serotonin (5-hydroxytryptamine; 5-HT), respectively, in the brain. Depression, anxiety, cognitive impairment, sleep disruption, orthostatic hypotension, constipation, olfactory deficits, etc. are all categorized as NMS (Fahn, 1999; Rascol, 2000;

Riedel et al., 2010; Balestrino and Martinez-Martin, 2017). Many NMS have a high occurrence in the PD population. For example, depression affects about 50% of the PD population, while anxiety affects about 40% (Cummings, 1992; McDonald et al., 2003; Chaudhuri et al., 2006;

Schrag and Taddei, 2017). Moreover, some NMS, for example, olfactory dysfunction, constipation and depression, can occur prior to PD diagnosis (Cummings, 1992; Aarsland et al.,

2009; Richard, 2005). Together, both motor and non-motor symptoms greatly impact the quality of life of individuals with PD. Although there are treatments to partially alleviate symptoms, neurodegeneration and disease progression are unremitting and the etiology of the disease is still unknown (Rascol, 2000; Balestrino and Martinez-Martin, 2017).

Whereas most cases of Parkinson’s disease are sporadic, about 5-10% are caused by genetic mutations alone. It is believed that these inherited forms of PD could aid in determining overall PD etiology and in identifying potential therapies (Sherer et al., 2002; Farrer, 2006). The

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DJ-1, or PARK7, gene is one of almost two dozen genes now associated with the development of PD (see Deng et al., 2018 for recent review). More than 15 years ago, Dutch and Italian families were found to have an autosomal recessive inherited form of PD, with a loss of function mutation within the DJ-1 gene (Bonifati et al., 2003). Moreover, individuals with sporadic PD exhibit lower levels of the DJ-1 protein in both their saliva and cerebrospinal fluid (CSF) (Hong et al., 2010; Herbert et al., 2014; Masters et al., 2015), suggesting a potential role for DJ-1 dysfunction in idiopathic PD. DJ-1 is a highly conserved protein with multiple functions, including neuronal oxidative stress protection, protein folding, mitochondrial protection, as a transcriptional co-factor, as a protein chaperone, and in reduction of neuroinflammation (Taira et al., 2004; Kim et al., 2005; Zhou et al., 2006; Andres-Mateos et al., 2007; Blackinton et al.,

2009; Krebiehl et al., 2010; Cookson, 2012). Mitochondrial dysfunction, oxidative stress and neuroinflammation are all implicated in PD, highlighting the possible role of DJ-1 deficiency in disease development and progression.

Genetic animal models were generated to help decipher the role of DJ-1 in PD etiology and pathophysiology. However, use of Dj-1 knockout (KO) rodent models has led to mixed results regarding expression of a PD-like phenotype. Mice that lack DJ-1 have alterations in the nigrostriatal dopaminergic system including increased dopamine content in the striatum, increased dopamine re-uptake rates, and mild to moderate sensorimotor impairments (Chen et al., 2005; Yamaguchi and Shen, 2007; Manning-Bog et al., 2007; Chandran et al., 2008; Pham et al., 2010; Rousseaux et al., 2012). Others have found that disruption of DJ-1 function alters evoked dopamine release in striatal slices and causes an increased sensitivity to the neurotoxin

MPTP (Goldberg et al., 2005; Kim et al., 2005). Thus, although mouse Dj-1 KO models do exhibit some neurochemical and motor alterations of the nigrostriatal system, somewhat surprisingly, loss of nigral dopaminergic neurons, the hallmark feature of PD, is not observed.

In the only study that examined non-motor behavior, Dj-1 KO mice exhibited deficits in the novel

134 object recognition, a measurement of short-term memory and incidental learning (Pham et al.,

2010).

Recently, in an effort to optimize genetic models for PD, a novel Dj-1 knockout rat model was generated (Dave et al., 2014). The Dj-1 KO rat exhibits some motor deficits, including decreases in rearing frequency and hindlimb grip strength compared with wildtype (WT) controls

(Dave et al., 2014). In contrast to Dj-1 KO mice, a significant loss of dopaminergic neurons was observed in the substantia nigra pars compacta in the DJ-1-deficient rats at 8 months of age

(Dave et al., 2014). Another recent study reported that, compared with WT animals, Dj-1 KO rats took longer to traverse the tapered balance beam, but, conversely, made fewer errors during the task (Yang et al., 2018). In addition, this group found that Dj-1 KO rats displayed ultrasonic vocalization deficits and impaired oromotor (tongue) performance (Yang et al., 2018).

However, in neither of these studies of the DJ-1-deficient rat were non-motor behavioral abnormalities evaluated.

The purpose of the present study was to provide a more thorough characterization of both motor and non-motor behavioral alterations in the Dj-1 KO rat. We therefore performed a battery of behavioral tests at various ages, ranging from 2 to 17 months of age. The ages of the rats for the behavioral tests were primarily based on previously published data, in particular those of Dave et al. (2014) who described loss of dopamine cells in the SNpc at 8 months of age in the Dj-1 KO rats. Here, we conducted behavioral testing both before and after this 8- month time point to determine if both motor and non-motor alterations were observed in the Dj-

1-deficient rats, as seen in PD. In general, rat ages correspond to human ages as follows: 6- month-old rats correspond to 18 years in humans, 12 months corresponds to 30 years, and 18 months corresponds to 45 years (Andreollo et al., 2012). Although our time points do not parallel the period of idiopathic PD, in which the average age of onset is around 65 years old, in the familial form of this disease (e.g. absence of Dj-1), the average age of onset is 30 years old.

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Accordingly, the timeline used in this study is more in line with the familial form of PD. In addition to several sensorimotor assays, we conducted the buried pellet test to assess olfactory function; the elevated-plus maze to assess anxiety-like behavior; the novel/place recognition to test short-term memory; the sucrose preference test to assess anhedonia; and the forced swim test to evaluate stress coping. In addition, to test the dual-hit hypothesis of PD (gene x environment), beginning at 7 months of age, the rats were subdivided into groups that were subjected to a regimen of chronic stress as an environmental challenge. We hypothesized that compared with age-matched WT animals, Dj-1 KO rats would display deficits in both motor and non-motor behaviors.

Methods Animals Dj-1 KO and age-matched WT male Long-Evans rats were purchased from Horizon

Discovery (Boyertown, PA). Due to the variable availability of the KO rats, two separate cohorts were purchased and tested in the behavioral assays. The first cohort of DJ-1 KO and WT rats

(n=20/group) underwent several behavioral tests and was then subjected to 4 weeks of chronic variable stress (CVS) between 7 and 8 months of age. This cohort now consisted of 4 groups

(WT/No CVS, WT/CVS, Dj-1 KO /No CVS, Dj-1 KO/CVS; n=10 rats/group) which were evaluated in further behavioral tasks. This first cohort of animals underwent the following behavioral tests: spontaneous activity, adhesive removal, adjusting step, gait (2, 4, 7, and 13 months of age), elevated plus maze (8 and 17 months of age), sucrose preference and novel/place recognition (15 months of age), and buried pellet (17 months of age). The second cohort of rats (n=14/group), which did not undergo CVS, was used to assess non-motor behavior in younger rats (novel/place recognition, forced swim test, elevated plus maze; 4 and 6 months of age) and sacrificed at 9 months of age for collection of brain tissue for separate

136 studies. All animals were kept under a 12:12 light: dark cycle, with food and water available ad libitum, unless otherwise specified. The age at which

Spontaneous Activity The spontaneous activity test measures spontaneous motor activity of animals including: forelimb steps, hindlimb steps, rears, and grooming time (Schallert et al., 2000; Fleming et al.,

2004). Rodents were tested during the dark cycle under fluorescent lighting at 4, 7, and 13 months of age (n=10-20 animals/group). Rats were placed in a clear plastic cylinder (38.1 cm height 25.4 cm diameter). The cylinder was on a glass pane (30.48 cm x 30.48 cm), and the camera was positioned below to assess steps. All rats were recorded for 5 min in the cylinder.

Blinded observers scored the number of forelimb and hindlimb steps, the number of rears, and the amount of time animals groomed during the 5-min time period.

Adhesive Removal Task

This task measures sensorimotor behavior, as previously described (Schallert et al.,

1982,1983; Fleming et al., 2004). Testing was performed during the light cycle. WT and Dj-1 KO animals (n=10-20/group) were tested at 4, 7, and 13 months of age. Animals were placed in the testing room in cages for 1 h prior to testing. Rats were tested in their home cage, while their cage mate was placed in a new cage to prevent interference during testing. An adhesive sticker

(1.27-cm diameter, Microtube Tough Spots®, Research Products International Corps, Mount

Prospect, IL) was folded around the inner part of each forepaw. The contact time of the sticker started once rats were placed in their home cage, and ended at initial contact of the rat’s mouth on the sticker. If the rat did not make contact within 60 s, the trial was ended, and the next rat was tested. A trial consisted of testing both the left and right forepaws for each rat. Three trials were completed per animal. Time to initial contact was observed and recorded by an observer blinded to the group condition.

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Adjusting Step Test

This test measures postural stability (Schallert et al., 1979) and was conducted during the light cycle at 4, 7, and 13 months of age (n=10-20 rats/group). A 90-cm length of tape was placed on a table. Animals were held so that only one forepaw could be used to bear its weight.

The exposed forelimb was placed on the table, and the tester moved the animal parallel to the tape. One trial consisted of moving the animal along the full length of the tape. To test the right forelimb, the animals were moved to the right, and vice versa for the left. Two trials were done per limb, with about 5-10 s between trials (Schallert et al., 1979; Olsson et al., 1995; Chang et al., 1999). All trials were video recorded, and the number of steps taken per trial was evaluated by a blinded observer.

Gait Analysis

Gait was measured using the length of the stride of the animal at 2 or 13 months of age

(n=10-20/group). Testing was done during the light cycle. Animals were placed in the testing room for 1 h to habituate to the room. Animals were generally housed in pairs, however, since each animal was tested individually, one animal was placed in a new cage while the other was tested. A 35.56 cm x 21.56 cm white sheet of paper was placed on the table with two cages flipped upside-down on either side of the paper to create a “lane”. At one of the end of the paper, the home cage was flipped over on its side to encourage the rat to walk down the lane toward its home cage. Each animal was trained to move down the “lane” toward their home cage. Once it was confirmed animals could go through the lane without stopping, the trials began. The hind paws of the animal were painted with non-toxic paint (Crayola®, Easton, PA), and animals walked down the lane into the home cage. If an animal stopped while on the sheet of paper, a mark was placed on the paper where the animal stopped, and the stride lengths after the stop were not used in the final measure. Two trials were done in succession for each animal. Stride length was measured in centimeters between one paw print on the page to the

138 immediate paw print after it (Schallert et al., 1978; Fleming et al., 2004). The stride lengths were averaged per trial; each trial was averaged to get a mean stride length. The maximum difference stride length was recorded for each trial by taking the shortest stride length and subtracting it from the largest stride length. The maximum difference stride length was averaged between the two trials to get a final maximum difference stride length. Scorers were blinded to the phenotype of the rats.

Buried Pellet Test

This task measures olfactory detection, as previously described. (Nathan et al., 2004;

Fleming et al., 2008; Alberts and Galef, 1971). Testing was done on 16-month old animals with n= 7-10 animals/group. Prior to testing, animals were given 2-3 pellets per cage (food deprived), so that they achieved 90% body weight, and maintained that weight for 2 days prior to testing.

To maintain 90% body weight throughout the study, each cage was given about 1-2 pellets each day. Animals were placed in the testing room for 1 h prior to testing. Testing was done in a clean cage with 3 cm of bedding. Bedding was replaced, and the cage was cleaned using 70% ethanol, between animals. The cage was baited with a piece of cereal (Cap’N Crunch®) along the perimeter of the cage (not in a corner) at a depth of about ½ cm. Each rat was placed in the cage and had to locate the treat. The latency (s) to find the treat once the rat was placed in the cage was recorded. Five total trials were done per animal, with 1 trial done per day. On the 6th day, a control trial was done by placing the treat on top of the bedding. This trial was used to assure that differences in motility were not influencing the data outcome. Trials were averaged for each animal, resulting in a final mean latency to finding the treat. Scorers were blinded.

Novel Object/Place Recognition

This test measures short-term object and place recognition memory (Brown et al., 2010).

Testing was done at 4.5 (cohort 2, n= 14/group) or 15 months of age (cohort 1, n=7-10/group).

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Before testing, objects were tested with rats not included in the study to ensure one object was not more interesting to the animals than the other. These pre-test animals spent equal amounts of time with each object (data not shown). Test animals were placed in a plastic bin (82.6 x 50.2 x 47.3 cm, Sterlite®, Sterlite Corporation, Townsend, MA) for 30 min/day for 2 days prior to testing to habituate animals to the testing arena. On the test day, three different trials (sample, test trial 1, test trial 2) of 10 min each were conducted for each animal, with approximately 50 min elapsing between each trial. Each trial was video-recorded and rated by a blinded observer.

The sample trial consisted of placing two of the same objects in the test area, and the time spent with each object for each animal was recorded. Test trial 1 measured an animal’s reaction to a novel object, testing memory and attention. This test had the object from the previous sample trial (familiar) and a new object (novel). In test trial 2, the familiar object from test trial 1 was moved to the opposite quadrant, becoming the moved object, while the novel object from test trial 1 was the stationary object. This trial tests place recognition and short-term memory.

Objects and the test arena were cleaned after every trial with 70% ethanol. Times spent with each object were recorded by blinded observers.

Forced Swim Test

This test was used to measure learned immobility, as previously described. (Overstreet,

2002; Wulsin et al., 2010). Rats were tested at 6 months of age (n=14/group). Animals were placed in a cylindrical clear plastic container (45-cm depth, 20-cm diameter; Braintree Scientific,

Braintree, MA). The water level was 31 ± 3 cm with a water temperature of 24 ± 2°C. Animals were video-recorded for 5 minutes, and scored. Scorers were blinded to the genotype of the animal. The time immobile and time to initial mobility were scored in seconds.

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Elevated Plus Maze

This test was used to measure anxiety-like behavior (Lister, 1987), and was conducted at 4.5 (cohort 2, n=14/group), 8 (cohort 1 n=7-10/group), or 17 (cohort 1, n=7-10/group) months of age. Animals were initially placed in the center of the elevated plus maze (arm length =

51.5cm; curb height = 1.5cm; wall height = 48cm) (Braintree Scientific) and video-recorded for 5 min. A blinded observer scored the time spent in the open arm, closed arm, and center of the maze. The percent time in open was calculated as open time/ (open time + closed time), since rats will spend considerable time in the center (Braun et al., 2011).

Sucrose Preference Test

This test was used to measure anhedonia, as described (Beeler et al., 2009). Nine- month-old animals were tested with an n=10/group. Animals were individually housed for the duration of this experiment. Two water bottles were introduced to each rat’s cage before testing began to habituate them to having 2 bottles. Once testing began, one bottle had water and the other had sucrose. The following concentrations of sucrose were tested: 0%, 0.2%, 5%, 10%, and 15%. Each concentration was tested for 3 days. Each day, the bottles were switched to prevent placement bias, and each bottle was weighed daily and recorded. The intake of sucrose over the 3-day period was recorded, and those scores were recorded and averaged to arrive at a mean intake per animal per concentration.

Chronic Variable Stress

We followed a standard CVS protocol as described previously by us (Hemmerle et al.,

2014b) and others (e.g., (Herman et al., 1995; Willner, 2005) and was administered for 4 weeks beginning between 7-8 months of age. Groups of DJ-1-deficient and WT control rats were subjected to a stress regimen which consisted of rats being exposed to one of seven stressors

[cold (2h), vibration (1h), crowding (6/cage, overnight), hypoxia (9% oxygen, 1 h), isolation (1

141 cage, overnight), cold swim (10 min), warm swim (20 min)] for 4 weeks (Herman et al., 1995).

Stressors were administered twice daily, once in the morning and once in the afternoon, irregularly timed. To prohibit habituation, the stressor sequence was varied and unpredictable to the subjects, but was consistent between iterations of stress exposure in all experiments. Non-

CVS controls consisted of groups of rats that were handled briefly each day (Herman et al.,

1995; Hemmerle et al., 2014).

Statistical Analysis

Data were analyzed using mixed linear ANOVA models with a restricted maximum likelihood method (SAS Proc Mixed, SAS Institute 9.4 TS, Cary, NC). Kenward-Roger first order adjusted degrees of freedom were estimated. Fixed factors were genotype or stress. The repeated measure factor in the bracing, cylinder, dot, and EPM tests was age and in the sucrose preference it was percent sucrose. The repeated measures ANOVAs were fit to the autoregressive moving average covariance structure. Significant interactions were further analyzed using slice-effect ANOVAs within Proc Mixed. A t-test (Proc t-test) was done for gait analysis data at 2 months, for the novel object/place recognition data at 4.5 months, the forced swim data, and the elevated plus maze data at 4 months. A Satterthwaite correction was used for those t-tests that did not have equal variances. Significance was set at p ≤ 0.05 (2-tailed).

Data are presented as least square mean (Proc Mixed data) or ordinary means (t-test data) ±

SEM.

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Results

Spontaneous Activity

At 4 and 7 months of age, a Genotype x Age ANOVA showed the number of rears were reduced for Dj-1 KO rats. There was a main effect of genotype (F(1, 33) = 11.65, p < 0.002)

(Figure 1A, inset) and age (F(1, 32.6) = 22.07, p < 0.0001), but no interaction (F(1, 32.6) = 1.15, p < 0.30) (Figure 1A). For the 13-month-old rats, a Genotype x Stress ANOVA, showed no effect of genotype (F(1,29) = 2.54, p < 0.13), stress (F(1,29) = 1.51, p < 0.24), or the interaction

(F(1,29) = 0.15, p < 0.71) (Figure 1A).

For the forelimb steps at 4 and 7 months, there were effects of genotype (F(1,36.1) =

50.04, p < 0.0001) (Figure 1B, inset), age (F(1,35.9) = 9.69, p < 0.004), and the interaction

(F(1,35.9) = 7.8, p < 0.009). At 4 and 7 months of age, Dj-1 KO rats stepped more than their

WT counterparts (p < 0.0001 and p < 0.0005, respectively), but the difference was greater at 4 months (Figure 1B). At 13 months of age, Dj-1 KO rats took more steps than WT rats as shown by a main effect of genotype (F (1,29) = 12.01, p < 0.002). At 13 months there was no effect of stress (F(1,29) = 0.18, p < 0.68) or the interaction (F(1,29) = 0.13, p < 0.73) (Figure 1B).

For hindlimb steps at 4 and 7 months of age, there was a main effect of genotype

(F(1,35.9) = 27.95, p < 0.0001), but no main effect of age (F(1,35.4) = 1.37, p < 0.26), and no interaction (F(1,35.4) = 0.63. p < 0.44). Dj-1 KO animals took more hindlimb steps than their

WT counterparts (Figure 1C, inset). At 13 months, there was a main effect of genotype (F(1,29)

= 17.78, p < 0.0002), but no effect of stress (F(1,29) = 2.81. p < 0.11) or the interaction (F(1,29)

= 0.01, p < 0.99). (Figure 1C). Dj-1 KO rats took more hindlimb steps than controls.

At 4 and 7 months of age, Dj-1 KO rats groomed less than WT rats as demonstrated by a main effect of genotype (F(1,36.3) = 7.21, p < 0.02) (Figure 1D, inset). There was no effect of

143 age (F(1,36.1) = 0.05, p < 0.82) or the interaction (F(1,36.1) = 0.23, p < 0.64). At 13 months of age, Dj-1 KO animals groomed less than their WT counterparts, main effect of genotype

(F(1,29) = 12.03, p < 0.002) (Figure 1D). There was also a main effect of stress (F(1,29) =

10.15, p < 0.004) but no interaction (F(1,29) = 1.83, p < 0.19). Regardless of genotype, the rats that received CVS exhibited more grooming than rats without CVS.

Adhesive Removal

A Genotype x Age ANOVA at 4 and 7 months showed no effect of genotype (F(1,36) =

0.33, p < 0.58), age (F(1,36) = 0.94, p < 0.35), or the interaction (F(1,36) = 0.37, p < 0.56)

(Figure 2). The Genotype x Stress ANOVA at 13-months demonstrated no effect of genotype

(F(1,28) = 0.30, p < 0.60), stress (F(1,28) = 0.81, p < 0.39), or the interaction (F(1,28) = 0.07, p

< 0.81) (Figure 2).

Adjusting Step Test

A Genotype x Age ANOVA for adjusting steps at 4 and 7 months showed effects of genotype (F(1,36.1) = 56.87, p<0.0001) (Figure 3, inset), age (F(1,36.1) = 278.4, p<0.0001), and the interaction (F(1,36.1) = 7.8, p < 0.009). The number of steps overall decreased with age, and the Dj-1 KO rats took more adjusting steps than their WT counterparts at both 4 and 7 months of age with a larger difference at 7 months (Figure 3). At 13 months, a Genotype x

Stress ANOVA showed there was a main effect of genotype (F(1,27) = 44.24, p < 0.0001), but no effect of stress (F(1,27) = 0.02, p < 0.91) or the interaction (F(1,27) = 0.20, p < 0.67). Dj-1

KO animals took more adjusting steps than controls (Figure 3).

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Figure 1. Spontaneous Activity

Fig. 1 Spontaneous activity of Dj-1 KO and WT rats at 4 (n=20/group), 7 (n=20/group), and 13

(n=7-10/group) months of age. A. At 4 and 7 months of age there is a main effect of genotype;

Dj-1 KO rats rear less than control rats. There is no difference in the number of rears from the

13-month-old rats. B. Dj-1 KO rats take more forelimb steps than their WT counterparts at 4, 7, and 13 months of age. C. At 4 and 7 months, a main effect of genotype shows Dj-1 KO rats take more hindlimb steps than WT rats. Dj-1 KO rats also take more hindlimb steps than control rats at 13 months of age. D. At 4 and 7 months of age there is a main effect of genotype; Dj-1 KO animals groom less than WT animals. Dj-1 KO rats also groom less than controls at 13 months of age. Insets, main effect of genotype for the 4- and 7-month-old rats. *p<0.05; **p<0.01;

***p<0.0001; ****p<0.00001

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Figure 2. Adhesive Removal

Fig. 2 Assessment of sensorimotor changes during the adhesive removal task at 4

(n=20/group), 7 (n=20/group), and 13 (n=7-10/group) months of age for WT and Dj-1 KO rats.

There is no difference in time of adhesive sticker removal at any age between Dj-1 KO and WT rats.

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Figure 3. Adjusting Step

Fig. 3 Evaluation of postural instability in the adjusting step task at 4 (n=20/group), 7

(n=20/group), and 13 (n=7-10/group) months of age for WT and Dj-1 KO rats. At 4 and 7 months of age, there is a main effect of genotype and an interaction. Dj-1 KO rats take more adjusting steps than control rats at both 4 months and 7 months of age. Dj-1 KO animals take more adjusting steps than WT animals at 13 months of age. Inset, main effect of genotype for 4 and 7 months of age. **p<0.01; ***p<0.0001; ****p<0.00001

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Figure 4. Gait Analysis

Fig. 4 Analysis of gait changes in WT and Dj-1 KO rats at 2 (n=20/group) and 13 (n=7-10/group) months of age. A. Dj-1 KO rats show no difference in stride length compared to controls at 2 months of age, but do exhibit a smaller stride length compared to WT rats at 13 months of age.

B. At 2 months, but not 13 months, of age, Dj-1-deficient rats have a smaller maximum difference in stride length compared to WT controls. **p<0.01

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Gait Analysis

At 2 months of age, we detected no difference in stride length between Dj-1 KO and WT rats (t(38) = -1.50, p < 0.15). At 13 months, there was an effect of genotype (F(1,28) = 12.95, p

< 0.002), but no effect of stress (F(1,28) = 0.13, p < 0.73) and no interaction (F(1,28) = 0.001, p< 0.99) (Figure 4A). Dj-1 KO rats had a shorter stride length compared with controls.

At 2 months, the Dj-1 KO animals had a smaller maximum difference than WT animals

(t(38) = -3.25, p < 0.003). At 13 months of age, maximum difference was similar between Dj-1

KO and WT rats. There was no effect of genotype (F(1,28) = 0.36, p < 0.56) or the interaction

(F(1,28) = 0.14, p < 0.71) (Figure 4B). There was an effect of stress (F(1,28) = 7.17, p < 0.02).

Regardless of genotype, the CVS rats had a greater maximum stride difference than rats that did not receive CVS (mean ± SEM: No CVS = 4.54 ± 0.44 and CVS = 6.14 ± 0.41).

Buried Pellet

A Genotype x Stress ANOVA at 16 months of age showed an effect of genotype (F

(1,25) = 13.96, p < 0.001) and the interaction (F(1,25) = 4.95, p=0.04), but no effect of stress

(F(1,25) = 2.16, p=0.16). The Dj-1 KO rats had a shorter latency to find the treat compared with controls, however this was affected by CVS. There was no difference between genotypes in rats that did not receive CVS, however for rats that received CVS, the Dj-1 KO rats found the treat faster than controls (Figure 5).

Novel Object/Place Recognition

A preference score for novel object and novel place was used for analysis and defined as (novel object/place - familiar/stationary) / (novel object/place + familiar/stationary). At 4.5 months of age for novel object preference, the Dj-1 KO rats preferred the novel object more

149 than controls (t(23) = 2.08, p < 0.05). At 15 months of age, a Genotype x Stress ANOVA found no difference in preference between Dj-1 KO and WT animals with no effect of genotype

(F(1,23) = 0.46, p=0.5), stress (F(1,23) = 2.22, p=0.15), or the interaction (F(1,23) = 1.86, p=0.19) (Figure 6A).

For novel place preference at 4.5 months, Dj-1 KO rats did not show a place preference compared with WT rats that preferred the moved object (t(23) = -3.21, p < 0.004). Similarly, at

15.5 months of age, the Dj-1 KO rats showed no novel place preference, whereas WT rats preferred the moved object as shown by an effect of genotype (F(1,22) = 11.72, p < 0.003) but no interaction (F( 1,22) = 0.56, p < 0.47) (Figure 6B). There was a main effect of stress (F(1,23)

= 6.45, p < 0.02) with the CVS rats showing novel place preference but not the non-CVS rats

(means ± SEM: NO CVS = -7.97 ± 7.13; CVS = 17.19 ± 6.89).

Forced Swim Test

Dj-1 KO animals spent more time immobile during the testing period than controls

(t(16.6) = 4.05, p < 0.0009) (Figure 7A). Dj-1 KO animals were quicker to become immobile compared with WT controls (t(24) = -2.09, p < 0.05) (Figure 7B ).

Elevated Plus Maze

At 4 months of age, there was no difference for the percent time spent in the open arm between Dj-1 KO and WT rats (t(21) = -0.4, p < 0.70). A Genotype x Stress x Age ANOVA for

8- and 17-month-old animals, demonstrated no differences in the percent time spent in the open arm between Dj-1 KO rats and WT controls. There was no effect of genotype (F(1,30.6 )= 2.01, p=0.17), age (F(1,29.7) = 2.97, p=0.10), stress (F(1,30.6) = 0.51, p=0.50), nor any interaction

(Figure 8).

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Figure 5. Buried Pellet

Fig. 5 Evaluation of olfactory detection in the buried pellet task at 16 months of age for WT

(n=20) and Dj-1 KO (n=20) rats. Dj-1 KO rats have a shorter latency time than controls.

Between WT/CVS and Dj-1 KO/CVS groups, WT/CVS rats take longer to find the treat than control rats. Inset, main effect of genotype. ***p<0.0001

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Figure 6. Novel Object/ Place Recognition

Fig. 6 Evaluation of short-term memory in the novel/place recognition task for WT and Dj-1 KO animals at 4.5 (n=14/group) and 15 (n=7-10/group) months of age. A. Novel object preference:

At 4.5 months of age, Dj-1 KO rats prefer the novel object more so than control rats. At 15 months of age, there is no difference in preference score between Dj-1 KO and WT rats. B.

Novel place preference: Dj-1 KO rats prefer the stationary object, whereas WT rats prefer the moved object, at both 4.5 and 15 months of age. *p<0.05; **p<0.01

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Figure 7. Forced Swim

Fig. 7 Evaluation of learned immobility during the forced swim task at 6 months of age for WT

(n=14) and Dj-1 KO (n=14) rats. A. Dj-1 KO rats spend more time immobile during the testing period than their WT counterparts. B. Dj-1 KO rats have a shorter latency to first bout of immobility than WT rats. *p<0.05; ***p<0.001

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Figure 8. Elevated Plus Maze

Fig 8 Evaluation of anxiety-like behavior using the elevated plus maze for WT and Dj-1 KO rats at 4 (n=14/group), 8 (n=7-10/group), and 17 (n=7-10/group) months of age. There is no difference in percentage of time spent in the open arm of the maze at any of the tested ages between WT and Dj-1 KO rats.

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Figure 9. Sucrose Preference

Fig 9 Evaluation of anhedonia using the sucrose preference test for WT (n=20) and Dj-1 KO

(n=20) rats at various concentrations of sucrose at 9 months of age. A. Dj-1 KO rats drink more sucrose than controls at 5%, 10%, and 15% sucrose concentrations. B. Examining non- stressed animals only, Dj-1 KO rats drink more sucrose than WT rats at 5% and 10% concentrations. C. In stressed animals, Dj-1 KO rats drink more sucrose than control rats at

5%,10%, and 15% concentrations. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001

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Sucrose Preference Test

For the sucrose preference test a Genotype x Stress x Sucrose percentage ANOVA showed an effect of genotype (F(1,38.8) = 24.50, p < 0.0001), sucrose percentage (F(4,113) =

127.48, p < 0.0001), genotype x sucrose percentage (F(4,113) = 18.01, p < 0.0001), and an interaction among all three factors (F(4,113) = 2.63, p < 0.04). No effects of stress (F(1,38.8) =

1.76, p < 0.2), genotype x stress (F(1,38.8) = 0.34, p< 0.58), or stress x sucrose percentage

F(4,113) = 0.76, p < 0.57) were found. Slice-effect ANOVAs for genotype x sucrose showed that the Dj-1 KO rats drank more sucrose than controls at 5%, 10%, and 15% sucrose concentrations (Figure 9A). Slice-effect ANOVAs for genotype x sucrose x CVS showed that with no CVS, the Dj-1 KO animals drank more sucrose than WT animals at 5% and 10% sucrose concentrations (Figure 9B). For rats undergoing CVS, the Dj-1 KO rats had higher sucrose intake than controls at 5%, 10%, and 15% sucrose concentrations (Figure 9C).

Discussion

In the present study, we assessed Dj-1 KO rats for a number of behaviors compared with age-matched WT controls. In spontaneous activity we found, as with previous rodent studies, a decrease in rearing behavior, however the DJ-1 KO rats also exhibited more forelimb and hindlimb steps than controls, showing that the activity phenotype is more complex than a simple decrease in rearing. Dj-1 KO rats also displayed differential effects in other behaviors in which some would be considered deficits and others enhancements. Together, these findings may indicate that both dopaminergic and non-dopaminergic neurotransmitter systems are affected by lack of Dj-1.

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For face validity, it is important for a rodent model of PD to manifest motor deficits related to the disease process. Genetic mouse and rat models of PD (e.g. LRRK2, parkin, alpha-synuclein) present a wide array of motor dysfunction due to the genetic mutations, age of testing, differences in testing methods across labs, etc. (Francardo, 2018; Vingill et al., 2018).

For example, Dj-1 KO mice exhibit a range of motor deficits from no motor impairment to mild/moderate motor deficits (Goldberg et al., 2005; Kim et al., 2005; Chen et al., 2005;

Yamaguchi and Shen, 2007; Manning-Bog et al., 2007; Chandran et al., 2008; Rousseaux et al.,

2012). In this study, we conducted a number of motor tests to determine the breadth of motor changes in these Dj-1-deficient rats and to verify previously reported findings.

In studies that have employed the open field task to assess spontaneous locomotor activity, horizontal movement is measured using path length in open field. Path length is used to determine, in general, if an animal is hypo- or hyperactive (Goldberg et al., 2005; Kim et al.,

2005; Chen et al., 2005; Yamaguchi and Shen, 2007; Dave et al., 2014; Yang et al., 2018).

Here, in the spontaneous activity test, we measured horizontal movement using the number of forelimb and hindlimb steps taken during the five-minute period in a cylinder. This task was previously used for other PD rodent models (e.g. Schallert et al., 2000). Rodents with a PD-like phenotype are expected to take fewer steps than their WT counterparts because of changes in the dopaminergic system (Schallert and Tillerson, 2000; Fleming et al., 2004; Fleming et al.,

2013). We found that Dj-1 KO rats take more forelimb and hindlimb steps than their WT counterparts from 4 to 13 months of age. Interestingly, control forelimb steps were fairly consistent across the test times, whereas the Dj-1 KO rats showed decreased steps from 4 to

13 months. Perhaps if the Dj-1 KO rats were tested later, reductions in steps would have been apparent. We also found that Dj-1 KO animals take more steps during the adjusting step test.

One possible explanation for these results is an increase in dopamine content of the striatum, which has, in fact, been demonstrated in 8-month-old Dj-1 KO rats (Dave et al., 2014).

157

Moreover, some PD genetic mouse models, in addition to the Dj-1 KO rat model, also have transient increases in striatal dopamine (Goldberg et al., 2003; Kitada et al., 2009; Hennis et al.,

2014). Although such observations could be considered inconsistent with a PD-like phenotype, the reported enhancement of striatal dopamine in these models may reflect a transient compensatory mechanism. Finally, no significant differences in sensorimotor function were noted at any age in the adhesive removal test.

Consonant with a PD-like phenotype, we did find DJ-1 KO rats rear less at 4 and 7 months of age, have a reduction in grooming time at 13 months of age, and a shorter stride length at 13 months of age, compared with controls. These results are consistent with the decrease in rearing that was observed in the open field test of another Dj-1 KO rat study (Dave et al., 2014). Both rearing and grooming can be affected by emotionality (Archer, 1975; Walsh and Cummins, 1976), and may involve both dopamine and norepinephrine. In a rodent model, loss of norepinephrine led to motor behaviors similar to PD (Rommelfanger et al., 2007).

Lesioning of both the SNpc and LC leads to more severe motor deficits than lesioning of the

SNpc alone (Rampersaud et al., 2012). In humans, postural instability and gait freezing are affected by norepinephrine and denervation of the LC. Accordingly, dopamine replacement has less of an effect on postural instability and gait compared with the other motor deficits that develop (Bonnet et al., 1987; Agid et al., 1990; Grimbergen et al., 2009; Espay et al., 2014).

Thus, our mixed motor results may be explained by altered levels of both dopamine and norepinephrine in the present KO model. Interestingly, along with the reported decrease of TH cells in the SNpc of Dj-1 KO rats (Dave et al., 2014), loss of TH cells in the LC of 8-month-old

Dj-1-deficient rats has recently been described (Yang et al., 2018). Future analyses of the levels of these and other neurotransmitters in relevant brain regions are warranted to follow up on our behavioral findings.

158

We also performed a battery of behavioral tests associated with other PD symptoms in the Dj-1 KO rats. As stated previously, in addition to the well-known motor dysfunction in PD, there are a plethora of deficits grouped collectively as the non-motor symptoms in humans that have a substantial impact on the quality of life of those with PD (Riedel et al., 2010; Balestrino and Martinez-Martin, 2017). Only one study using Dj-1-deficient mice included tests other than activity and they were social discrimination and the novel object recognition task with a 24-h delay. In that study, 13-14-month-old Dj-1 KO male, but not female, mice displayed object recognition deficits (Pham et al., 2010), and at earlier ages, no deficits in social discrimination or object recognition were found for males or females. The few previous Dj-1 KO studies in rats have not examined non-motor deficits (Dave et al., 2014; Yang et al., 2018). In our study, we found several changes in behavior related to non-motor symptoms in rats lacking Dj-1.

Our results demonstrated a change in cognition, specifically short-term memory in the novel object/place preference. Dementia occurs in approximately 60-80% of individuals with PD at later stages of the disease (Aarsland et al., 2001; Buter et al., 2008; Halliday et al., 2008).

Parkinson’s patients can gradually deteriorate from mild cognitive impairment into dementia

(Pedersen et al., 2017). Moreover, at diagnosis, they may already exhibit mild cognitive impairment (Broeders et al., 2013). Cognitive functions affected by PD early in the disease state include memory, visuospatial processing, executive functions, and attention (Cronin-

Golomb and Braun, 1997; Dujardin et al., 1999; Lewis et al., 2003; Troster, 2008; Bronnick et al., 2011). In the present novel object/place recognition experiments, Dj-1 KO animals at 4.5 and 15 months of age showed abnormalities in short-term memory in test trial 2 (place preference). During the place preference phase of the novel object/place preference task, controls preferred the moved object (novel), but Dj-1 KO rats preferred the stationary (familiar).

However, during the novel object phase (test trial 1), Dj-1 KO rats at 4.5 months of age displayed a higher preference for the novel object than WT animals, but this was not seen at 15

159 months of age. As in our study, an investigation in Dj-1 KO mice study examined cognitive deficits by performing the novel object recognition task. Testing was done on these mice at 6-7 months and 13-14 months of age. Deficits in short-term memory and attention were exhibited only in the 13-14-month-old Dj-1 KO mice (Pham et al., 2010). Thus, cognitive impairments appear earlier in the Dj-1 KO rat model compared to the mouse model, consistent with the observation that PD patients can express cognitive deficits very early on in the disease state

(Broeders et al., 2013).

In the buried pellet test, a measure of olfaction, the Dj-1 KO rats found the pellet faster than the WT controls at 16 months of age. In humans, olfactory deficits are one of the earliest manifestations of neurodegenerative diseases (Mesholam et al., 1998; Doty, 2012). In PD, the incidence of olfactory impairment ranges from 50-90%, and is considered a potential pre-clinical biomarker (Doty et al., 1988; Ponsen et al., 2004; Boesveldt et al., 2008). However, our results suggest that Dj-1 KO rats may actually having better olfactory detection than their WT counterparts at 16 months of age. Dopamine, norepinephrine, and serotonin all make contributions to olfaction, although the specific roles of some of these neurotransmitters are undefined (Doty, 2012). In the Dave et al. (2014) study, increases in serotonin, as well as dopamine, levels were detected in the striatum of Dj-1-deficient rats at 8 months of age. Thus, lack of DJ-1 leads to changes in multiple neurotransmitters at least in the striatum; the possibility arises that similar alterations occur in other brain regions, such as the olfactory system, which may influence olfactory function.

We conducted several tests to examine anxiety- and depressive-like behaviors, and we found some unexpected results that need further exploration. Anxiety is estimated to affect approximately 40% of the PD population (Richard, 2005). We performed the elevated-plus maze to assess anxiety-like behavior, and found no differences between Dj-1 KO rats and WT controls, at either 4, 8, or 17 months of age. To assess depressive-like symptoms, we

160 conducted the sucrose preference test. This test measures anhedonia which is a core feature of depression (Beeler et al., 2009). Although we observed no signs of anhedonia, we did find that Dj-1 KO rats drank more sucrose at various concentrations, with and without stress playing a factor. The increases in water and sucrose intake may indicate some abnormality in the neuroendocrine system. Neuroendocrine abnormalities are associated with PD, and in particular, with the NMS (Chaudhuri et al., 2006). For example, PD is associated with type-II diabetes (Sandyk, 1993; Aviles-Olmos et al., 2013). Along with our present anhedonia findings, we (data not shown) and others (Yang et al., 2018) found Dj-1 KO rats weighed more than their

WT counterparts, another indication of changes in the neuroendocrine system. Further evaluation of anhedonia via sucrose intake or saccharine intake, as well as measures of neuroendocrine function, in Dj-1 KO rats appears warranted.

Lastly, we found that rats deficient in DJ-1 spend more time immobile, and are quicker to become immobile, in the forced swim task at 6 months of age. The forced swim test was first used to evaluate the efficacy of anti-depressants (Porsolt et al., 1977,1978) and, in the past, had been defined as a means to assess depressive-like behavior. However, new work suggests a reinterpretation. For example, factors such as age, weight, gender, and diet can all influence the test (Bogdanova et al., 2013). The forced swim test is now thought to be better tailored for assessing stress coping and adaptation in an uncontrollable situation. Accordingly, the forced swim task measures active coping (when a rat tries to escape), and passive coping (when the rat is immobile) (Molendijk and de Kloet, 2015; de Kloet and Molendijk, 2016). Our results, thus, indicate that Dj-1 KO animals cope differently than WT animals when exposed to stressful situations.

Finally, with respect to CVS treatment in this study, stress has been hypothesized to contribute to the neuropathology of PD and to exacerbate parkinsonian symptoms (Smith et al.,

2002; Hemmerle et al., 2012). Indeed, in a neurotoxin-based model of PD we have found that

161

CVS exacerbates nigral neurodegeneration and associated behavioral deficits (Hemmerle et al.,

2014). Notably, stress provides an environmental challenge that can potentially synergize with pre-existing genetic risk to aggravate the disease process. This gene x environment interaction invokes the dual-hit hypothesis of PD (e.g. (Boger et al., 2010; Peng et al., 2010) in which genetic predisposition for PD combines with an environmental stressor as a “trigger” to reveal or accelerate disease onset or progression. At present, however, little is known regarding the effects of life stress/adversity in genetic models of PD, and particularly in the present DJ-1- deficient mutant rats. Here, as described above, we found the effects of 4 weeks of CVS treatment starting at ~7 months of age were relatively limited among all the behaviors evaluated in the Dj-1 KO rats. For example, regarding motor activity, effects of CVS were only found for grooming and maximum stride difference in which all rats subjected to CVS, regardless of genotype, demonstrated increases in the respective motor behavior. In other behavioral tests, effects of CVS were restricted to enhancement of novel place preference and swifter performance in the buried pellet test in the Dj-1 KO rats only. Perhaps the most curious findings regarding CVS administration were noted in the sucrose preference test in which CVS-treated

DJ-1-deficient rats drank more sucrose at several concentrations compared with WT controls.

Taken together, these mixed findings are difficult to interpret and may reflect the timing and extent of the CVS regimen, the severity of the stressors (CVS is also known as chronic mild stress; (Willner, 2005), as well as the length of time between the end of the CVS treatment and the performance of the behavioral task (sometimes many months). Additional studies of stress challenge to the Dj-1 KO rats using alternative CVS paradigms, experimental timelines, etc. are warranted to better address the dual-hit hypothesis of PD in this genetic rat model.

Overall, the current study is among the first to characterize both motor and non-motor behaviors in the Dj-1 KO rat model of PD. Although we found mixed results in both types of behaviors with respect to a PD-phenotype, several non-motor behavioral alterations, in

162 particular, are consistent with early-stage parkinsonian-like features. Thus, Dj-1 KO rats may be a good model for the prodromal stage of PD, although further analysis of this model is needed.

In ongoing studies of the Dj-1-deficient animals, to determine if changes in neurotransmitter systems underlie aberrant behavior, we are analyzing the levels of monoamines in brain structures associated with PD, and further examining neurodegeneration in key regions. Such investigations will allow us to further establish if the Dj-1 KO rat is an appropriate model in which to study the early stages of PD.

Acknowledgements

We are grateful to Dr. Sheila Fleming for expert training in several of the behavioral tasks. This work was supported by the Kerman Family Fund, the Selma Schottenstein Harris Lab for

Research in Parkinson’s, the Gardner Family Center for Parkinson’s Disease and Movement

Disorders, and the Parkinson’s Disease Support Network - Ohio, Kentucky and Indiana. AMH was supported by National Institutes of Health grant T32 DK059803.

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All protocols were approved by the University of Cincinnati

Institutional Animal Care and Use Committee.

163

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176

Chapter 3

Altered Monoamine Levels and Cell Degeneration of Monoaminergic Nuclei

in the DJ-1 Knockout Rat

177

Abstract

Parkinson’s disease (PD) is a complex disorder involving degeneration of multiple brain regions and dysfunction of dopamine (DA), norepinephrine (NE), and serotonin (5- hydroxytryptamine; 5HT) neurotransmitter systems. Although loss of striatal DA and DAergic neurons of the midbrain substantia nigra pars compacta (SNpc) are key hallmarks of PD, other regions, such as the locus coeruleus (LC) and dorsal raphe nucleus (DRN), exhibit neuronal loss as well, leading to decreases in NE and 5HT, respectively. Here, we examined the concentrations of DA, 5HT, NE, and their metabolites using high performance liquid chromatography in the relatively new DJ-1 knockout (KO) rat model of PD. Measurements were obtained from the DJ-1 KO and control wild-type (WT) rats at 5 and 9 months of age in the striatum, ventral midbrain, hippocampus, and prefrontal cortex (PFC), targets of the monoaminergic nuclei. We hypothesized that DA, 5HT, and NE levels would be decreased in these PD-related regions. We also conducted unbiased stereological cell counts of tyrosine hydroxylase (TH)+ neurons (marker of DA neurons in the SNpc, and of NE neurons in the LC), and of tryptophan hydroxylase (TPH)+ cells (marker of 5HT neurons in the DRN), to assess possible neurodegeneration in the SNpc, LC, and DRN during chronological aging (at 5, 9, and

17 months of age). We found higher levels of the DA metabolite 3,4-dihydroxyphenylacetic acid

(DOPAC) in the striatum, higher concentrations of the 5HT metabolite 5-hydroxyindoleacetic acid (5HIAA) in the ventral midbrain and hippocampus, and lower levels of NE in the hippocampus of DJ-1-deficient rats compared to WT rats. Although, compared to WT rats, loss of DA neurons in the SNpc was not observed at any age, the number of NE neurons in the LC was lower in DJ-1 KO rats regardless of age, and a progressive loss of 5HT neurons was observed in the DRN of the DJ-1-defcient rats. Overall, the results suggest that the DJ-1 KO rat may be a good early-stage PD model, particularly for the study of monoaminergic systems traditionally associated with non-motor symptoms of the disease.

178

Introduction

Historically, Parkinson’s disease (PD) research has focused mainly on dopamine (DA) and the nigrostriatal system. However, over the years it has been recognized that other regions and neurotransmitter systems, for example the noradrenergic locus coeruleus (LC) and serotonergic dorsal raphe nucleus (DRN), are dysfunctional as well. Loss of DA content in the striatum and degeneration of DA neurons of the midbrain substantia nigra pars compacta

(SNpc) are key pathological hallmarks of PD (Albin et al., 1989; Gibb, 1991; Wichmann and

DeLong, 2003). This loss of DA leads to motor symptoms, which need to develop for clinical diagnosis of PD (Fahn, 1999; Rascol, 2000). Although motor symptoms and maladaptive changes in the nigrostriatal pathway are prominent in and pivotal to PD, a plethora of other symptoms, called the non-motor symptoms (NMS), accompany the disorder.

The NMS greatly impact the quality of life of PD patients, in part because these symptoms are typically resistant to DA therapies (Fahn, 1999; Rascol, 2000; Riedel et al., 2010;

Balestrino and Martinez-Martin, 2017). Two extra-nigral regions associated with NMS are the

LC (main source of NE in the brain) and the DRN [main source of serotonin or 5- hydroxytryptamine (5HT) in the brain]. The LC contributes to multiple functions, such as cognition, via its connections to regions including the hippocampus and prefrontal cortex (PFC)

(Szabadi, 2013; Espay et al., 2014). The DRN is involved in functions such as emotion, motor behavior, and cognition through its efferent and afferent connections to other brain regions including the PFC and basal ganglia (Berger et al., 2009; Benarroch, 2009). Emotion and cognition are both dysfunctional in PD (Hou and Lai, 2007; Balestrino and Martinez-Martin,

2017). Approximately 70% of the neurons in the LC have degenerated, as measured in post- mortem PD tissue, and serotonergic neurotransmission decreases as neurodegeneration advances in the DRN (Halliday et al., 1990; van Dijk et al., 2012). Therefore, understanding the

179 role of these monoaminergic nuclei and transmitters in disease pathogenesis will help advance knowledge of the etiology and progression of PD.

To better understand the roles of various neurotransmitters and brain regions in PD etiology, genetic rodent models have been utilized. However, these rodent models, to date, have not exhibited robust neurodegeneration or changes in multiple neurotransmitter systems.

Even more recent alpha-synuclein (aSyn) genetic mouse models have not exhibited neurodegeneration (Masliah et al., 2000; Rockenstein et al., 2002; Neumann et al., 2002; Lee et al., 2002; Richfield et al., 2002; Fleming et al., 2004; Chandra et al., 2005; Rothman et al.,

2013), nor loss of DA (Richfield et al., 2002; Tofaris et al., 2006; Chesselet, 2008; Daher et al.,

2009; Kurz et al., 2010; Clark et al., 2010; Hansen et al., 2013; Kim et al., 2015). Moreover, thus far, no observable degeneration of the LC or DRN, or loss of NE or 5HT, has been reported in these models. Another genetic model, the parkin knockout (KO) mouse, does not exhibit nigral neurodegeneration, and there is no consensus on whether DA content is increased or decreased in this model (Goldberg et al., 2003; Oyama et al., 2010). Degeneration of the LC and decreases in NE were reported in one study (Von Coelin et al., 2004), but no such changes were detected in another (Perez and Palmiter, 2005). Thus, the state of research using current genetic mouse models of PD remains indeterminate.

In this chapter, we will highlight DJ-1 KO rodent models of PD, but will focus our research on the more recently developed DJ-1 rat KO model. Most DJ-1 KO mouse studies have not observed neurodegeneration or robust changes in neurotransmitter systems. To date, no studies of the DJ-1 KO mouse have noted neurodegeneration of the SNpc (Goldberg et al.,

2005; Chen et al., 2005; Yamaguchi and Shen, 2007; Manning-Bog et al., 2007; Chandran et al., 2008; Pham et al., 2010; Rousseaux et al., 2012). Regarding DA levels, most investigations have found no differences in striatal DA concentration between DJ-1 KO and WT mice (Kim et al., 2005; Yamaguchi and Shen, 2007; Manning-Bog et al., 2007; Chandran et al., 2008; Pham

180 et al., 2010; Rousseaux et al., 2012). Of note, however, one study detected increases in striatal

DA content in DJ-1 KO mice at 6 and 11 months of age, and increases in DA release at 4 months of age (Chen et al., 2005). Alterations in evoked DA overflow in the striatum were also measured in DJ-1 null mice (Goldberg et al., 2005). Overflow represents the kinetic balance between DA release and uptake, thus, DA neurotransmission was dysfunctional in these mutant mice. With respect to the LC and DRN, only one mouse study noted degeneration of the LC, however, these mice were backcrossed several times on a C57BL/6J background (Rousseaux et al., 2012). As yet, no investigations have reported any changes in either NE or 5HT levels in

DJ-1-deficient mice.

Because the DJ-1 mice do not exhibit DA loss, DA neurodegeneration, or changes in NE and 5HT neurotransmission, new genetic models of PD were sought. As described earlier in

Chapters 1 and 2, DJ-1 was deleted in the rat to determine if this species would be superior to mice in expressing neurodegeneration and neurotransmitter changes, as well as other aberrant features, similar to those seen in PD. Here, we will analyze these DJ-1-deficient rats for alterations in monoamine neurotransmitters (DA, NE, and 5HT) and neurodegeneration of related brainstem nuclei (SNpc, LC, and DRN). Few studies have examined the nigrostriatal system or brainstem nuclei of the DJ-1 KO rat. Dave et al. (2014) reported a significant decrease in the number of tyrosine hydroxylase (TH)+ cells in the SNpc in DJ-1 KO rats compared to wild-type (WT) controls at 8 months of age. Analysis of the total loss of neuronal cells, however, was not conducted to determine if the loss reflected a phenotypic loss of TH or frank neuronal degeneration. Dave et al. (2014) also observed higher concentrations of DA and

5HT in the striatum of DJ-1 KO rats compared to WT rats at 8 months of age.

Neurodegeneration was not assessed in extra-nigral brain regions, nor were monoamine levels measured in any other brain region besides the striatum (Dave et al., 2014). More recently, a study found a decrease in the number of TH+ cells in the LC of DJ-1 KO rats at 8 months of

181 age, but again, total numbers of neurons were not counted and stereological techniques were not employed (Yang et al., 2018). Thus, much remains to be determined regarding the status of

PD-relevant monoaminergic neurotransmitter systems in rats deficient in DJ-1. The reason for time points we used in this study were the same as the reasons described for chapter 2. In this chapter, we will test the hypothesis that, compared to WT controls, DJ-1 KO rats will exhibit aberrant levels of monoamines (DA, NE, 5HT) and their metabolites in several forebrain target regions (striatum, PFC, and hippocampus) and the ventral midbrain. We also hypothesize that

DJ-1 KO rats will exhibit enhanced neurodegeneration of brainstem monoaminergic nuclei

(SNpc, LC, and DRN). Our goal is to determine if DJ-1 KO rats, compared to previous genetic rodent PD models, better mimic a parkinsonian-like phenotype that encapsulates systems involved in both motor and non-motor symptoms of PD.

Methods

Animals DJ-1 KO and age-matched wild-type (WT; Long-Evans) male rats were purchased from

Horizon Discovery (Boyertown, PA). Rats from each genotype were examined at 5

(n=20/group), 9 (n=14/group), and 17 (n=10/group) months of age. All animals were kept under a 12:12 light: dark cycle, with food and water available ad libitum, unless otherwise specified. All procedures and protocols were approved by the University of Cincinnati Institutional Animal

Care and Use Committee. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

182

High Performance Liquid Chromatography (HPLC)

Cohorts of WT and DJ-1 KO animals at 5 months (n=8/group) and 9 months (n=8/group) of age were live decapitated, and the following brain regions were dissected bilaterally: PFC, striatum, hippocampus, and ventral midbrain. Brain regions were rapidly frozen using dry ice, and placed in conical tubes. All tissue was stored at -80°C until performance of HPLC. High- performance liquid chromatography was used to measure levels of monoamines (DA, NE, 5HT), and their metabolites [3,4-Dihydroxyphenylacetic acid (DOPAC) for DA; 5-hydroxyindoleacetic acid (5-HIAA) for 5HT] in each region, as described previously (Gutierrez et al., 2017; Bailey et al., 2019). Briefly, brain tissue was sonicated in 0.1N of perchloric acid and centrifuged at

20,800 RPM at 4°C for 13 minutes. The supernatant was loaded onto a Dionex UltiMate® 3000

Analytical Autosampler (Thermo Fisher Scientific, Waltham, MA). The mobile phase was MD-

TM Mobile Phase (Thermo Fisher Scientific) and consisted of 89% water, 10% acetonitrile, and

1% sodium phosphate monobasic (monohydrate). The flow rate was set at 0.5 ml/min at 28°C.

The ESA 5840 pump, with a flow rate of 0.9 ml/min set at 28°C, was connected to a Supelco

Supelcosil LC-18 column (15 cm x 4.6 mm, 3 µm; Sigma, St. Louis, MO). The guard cell was set to +350 mV, and the Coulochem III electrochemical detector was set to -150 mV for E1 and

+250 mV for E2. Neurotransmitter standards for DA, DOPAC, 5HT, 5-HIAA, and NE were pre- calculated and serially diluted, as described previously (Gutierrez et al., 2017; Bailey et al.,

2019). Data analysis was conducted using 2-way ANOVA and Bonferonni post-hoc analysis.

Immunohistochemistry

At 5 (n=6/group), 9 (n=6/group), and 17 (n=7-10/group) months of age, WT and DJ-1 KO rats were anesthetized with sodium pentabarbitol (Euthasol®, Virbac Animal Health, Fort Worth,

TX) and transcardially perfused using 300ml of saline, then 300ml of 4% paraformaldehyde

(PFA) (Sigma). Brains were extracted, post-fixed overnight in 4% PFA, and placed in 30% sucrose solution until the brains sunk to the bottom of the jar. The following regions from each

183 brain were sectioned: substantia nigra pars compacta (SNpc), dorsal raphe nucleus (DRN), and locus coeruleus (LC). These regions were identified based on the Paxinos and Watson rat brain atlas (Paxinos and Watson, 1986), and all regions were sectioned at 50-µm thickness using a sliding microtome. The SNpc and DRN were cut in a 1:12 series, whereas the LC was cut in a

1:4 series. Sections were placed in cryoprotectant until processing for immunohistochemistry, according to our previously published protocols (Seroogy et al., 1994; Hemmerle et al., 2014).

1:8000 dilution of tyrosine hydroxylase (TH) (MAB318; Millipore, Temecula, CA) monoclonal antibody was used for the SNpc and LC. Tyrosine hydroxylase is the rate-limiting enzyme for all catecholamines, used here to visualize the dopaminergic and noradrenergic cells in the SNpc and LC, respectively. The DRN sections were exposed to a 1:1000 dilution of tryptophan hydroxylase (TPH) monoclonal antibody (013M4789; Sigma); TPH is the rate-limiting enzyme for serotonin biosynthesis, used here to visualize serotonergic cells of the DRN. Alternate sections from all regions were immunostained with a NeuN monoclonal antibody (1:200 dilution;

MAB377; Millipore), a biomarker of neuronal nuclei and, thus, a general marker of all neurons.

All sections were placed in the primary antibody solution overnight.

Following the overnight incubation, sections were washed with 1% PB, blocked for 10 minutes in a 2% NHS blocking solution, and then placed in biotinylated polyclonal secondary antibody (horse anti-mouse IgG; BA-2000; Vector Laboratories) for 1 hour. The secondary antibody solution consisted of 1% NHS and a 1:200 dilution of the anti-mouse secondary antibody. Sections were washed in 1% PB and incubated in streptavidin-biotin-horseradish peroxidase solution (ABC kit; Vector Laboratories) for 30 minutes. Sections were washed in 50

184 mM Tris solution and developed in diaminobenzidine tetrahydrochlroide (DAB; Vector

Laboratories) containing 0.3% H2O2 for colorimetric visualization of the immunostained cells

(Seroogy et al., 1994; Hemmerle et al., 2014). The sections were then rinsed in Tris buffer, mounted onto Superfrost plus microslides (VWR, Batavia, IL), and air-dried overnight. The next day, the sections were dehydrated through a series of ethanols, cleared in Hemo-De (VWR), and coverslipped in Pro-Texx Mounting Medium (Lerner Laboratories).

Stereology

Cell estimates were determined using unbiased stereological techniques (Stereo

Investigator v.10.51, MFB Bioscience, Williston, VT), as previously described (West, 1993;

Hemmerle et al., 2014). Representative samples (5-6 sections/region) of the SNpc, DRN, and

LC were used for cell counts. The sections were viewed on an Olympus BX-60 microscope

(Melville, NY) using a CCD video camera (HV-C20, Hitachi, San Jose, CA). Regions of interest

(SNpc, DRN, and LC) were outlined using the contour function at 1.25X (SNpc and DRN) and

2X (LC) magnifications. The grid size for the areas of interest were the following: 120x100µm for the SNpc, 100x100 for the DRN, and 80x80 for the LC. Cell counts were conducted using the optical fractionator function with an optical dissector size of 50x50µm and guard zones of 2µm.

The Gundersen correction was used to calculate the coefficient of error for each animal and was

0.10 or lower (West, 1993; Hemmerle et al., 2014). The data were analyzed using a 2-way

ANOVA with a Bonferonni post-hoc test. Data are presented as mean ± SEM. Significance is considered at P < 0.05.

185

Results

Monoamines

We measured DA, DOPAC, 5HT, 5HIAA, and NE levels in the striatum, ventral midbrain,

PFC, and hippocampus of DJ-1 KO and WT rats at 5 and 9 months of age. We found several changes in monoamine levels in the striatum (Figure 1). Only a main effect of age

(F(1,27)=10.01 p<0.01) was observed for DA (Figure 1A), but for its metabolite DOPAC, there was both an interaction of genotype and age (F(1,27)=5.714 p<0.05) and a main effect of genotype (F(1,27)=13.59 p<0.01) (Figure 1B). DJ-1 KO rats, overall, have a higher concentration of DOPAC, compared to their WT counterparts. DJ-1 KO animals show an increase in DOPAC levels from 5 to 9 months of age, and at 9 months, DJ-1 KO rats exhibit a higher concentration of DOPAC in the striatum than WT rats. Main effects of age

(F(1,27)=5.104 p<0.05) and genotype (F(1.27)=8.503 p<0.01) were detected in the DOPAC/DA ratio between WT and DJ-1 KO rats at either age (Figure 1C). Overall, DJ-1 KO rats exhibit a higher DOPAC/DA ratio than WT rats. For both 5HT (F(1,25)=25.14 p<0.0001) and 5HIAA

(F(1,27)=122.1 p<0.0001), only differences in concentrations based on age were detected in the striatum (Figure 1D and E). No differences were observed in the 5HIAA/5HT ratio (Figure 1F).

Only a main effect of age (F(1,26)=13.26 p<0.01) was detected for NE levels in the striatum at 5 and 9 months of age (Figure 1G).

In the ventral midbrain, no differences were detected in DA, DOPAC, 5HT, or NE levels or in DOPAC/DA or 5HT/5HIAA ratios in DJ-1-deficient rats compared to age-matched WT rats

(Figure 2A-D; 2F-G). However, we observed a main effect of genotype (F(1,26)=4.921 p<0.05) for the metabolite 5HIAA (Figure 2E). DJ-1 KO rats, overall, exhibit a higher concentration of

5HIAA than WT rats in the ventral midbrain.

186

In the hippocampus, DA and DOPAC were below the limits of detection by HPLC. For

5HT in the hippocampus, we observed a main effect of age (F(1,27)=46.64 p<0.0001) (Figure

3A). Main effects of age (F(1,26)= 162.8 p<0.0001) and genotype (F(1,26)=4.52 p<0.05) were detected for 5HIAA concentrations (Figure 3B). No changes were detected in the 5HIAA/5HT ratio between DJ-1 KO and WT rats (Figure 3C). In general, DJ-1 KO rats exhibit higher hippocampal 5HIAA levels than their WT counterparts. For NE concentration, we observed main effects of both age (F(1,27)=18.82 p<0.001) and genotype (F(1,27)=30.05 p<0.0001)

(Figure 3D). Overall, DJ-1 KO animals show a lower concentration of hippocampal NE compared to WT animals.

In the PFC, we were unable to detect DA and its metabolite because the levels were too low to detect. We observed main effects of age for 5HT (F(1,26)=90.41 p<0.0001), 5HIAA/5HT

(F(1,26)=9.006 p<0.01), and NE (F(1,27)=9.325 p<0.01) (Figure 4A,C-D). No changes were detected for 5HIAA in the PFC between DJ-1 KO and WT rats (Figure 4B).

Stereological Cell Counts

Stereological cell counts were obtained to determine whether there was a difference in neurodegeneration within the SNpc, DRN and LC between the WT and DJ-1-deficient rats during aging.

SNpc

In the SNpc, there was no significant difference in the number of TH+ cells between DJ-1 KO and WT rats at either 5, 9, or 17 months of age (Figure 5). Given these negative results, Neu-

N+ cells were not counted in this region.

187

Figure 1. Striatal monoamine levels

Fig. 1 Levels of monoamines and their metabolites in the striatum of WT (n=7-8) and DJ-1 KO

(n=7-8). A. Only a main effect of age is detected. B. There is a main effect of genotype, and overall, DJ-1 KO rat exhibit a higher concentration of DOPAC. Also, there is an interaction between genotype and age, where DJ-1 KO rats have significantly higher DOPAC levels than

WT animals at 9 months of age, and DOPAC concentration increase for DJ-1 KO rodents between 5 and 9 months of age. C. Overall, DJ-1 KO animals have a higher DOPAC/DA ratio than their WT counterparts, and there also is a main effect of age. D. No significant differences in 5HT levels for genotype, but there is a main effect of age. E. No differences in 5HIAA levels between DJ-1 KO and WT rats at either age, but there is a main effect of age. F. No significant changes in 5HIAA/5HT ratio between either genotype or age. G. A main effect of age is detected. Values represent mean ± SEM; *p<0.05, **p<0.01.

188

Figure 2. Monamine levels in the ventral midbrain

Fig. 2 Monoamines and their metabolites concentrations in the ventral midbrain of DJ-1 KO and

WT rats at 5 and 9 months of age (n=7-8/group). A. No changes in DA levels in the ventral midbrain. B. There is no significant difference of DOPAC levels for DJ-1 KO rats. C. No differences in the DOPAC/DA ratio. D. No changes in the concentration of 5HT. E. A main effect of genotype shows DJ-1 KO rats have a significantly higher concentration of 5HIAA compared to WT rats. F. No significant difference of the 5HIAA/5HT ratio observed. G. No changes in NE levels. Values represent mean ± SEM; *p<0.05.

189

Figure 3. Hippocampal monamine levels

Fig. 3 Concentrations of monoamines and their metabolites in DJ-1 KO and WT rats (n=7-

8/group) in the hippocampus at 5 and 9 months of age. A. For 5HT, there is a main effect of age. B. There is both a main effect of age and genotype for 5HIAA. DJ-1 KO rats have a higher concentration of 5HIAA than WT rats. C. No changes are detected for the 5HIAA/5HT ratio. D. There is a main effect of both age and genotype for NE. Compared to WT rats, DJ-1

KO rats have a significantly lower concentration of NE at both 5 and 9 months of age. Values represent mean ± SEM; *p<0.05, ****p<0.0001.

190

Figure 4. Monamine levels in the PFC

Fig. 4 Monamines and their metabolites in the PFC in DJ-1 KO (n=7-8) and WT (n=7-8) rats at

5 and 9 months of age. A. Main effect of age is detected for 5HT levels. B. No significant differences are discerned for 5HIAA concentrations. C. There is a main effect of age for the

5HIAA/5HT ratio. D. A main effect of age is observed for NE. Values represent mean ± SEM.

191

DRN

In the DRN, we found an interaction between genotype and age regarding the number of TPH+ cells (F(2,26)=7.405 p<0.01), and a main effect of age (F(2,26)=7.67 p<0.01) (Figure 6A and

6C). The number of TPH+ neurons were significantly higher in DJ-1 KO rodents at 5 months of age, but the number of TPH+ cells decreased over time in these animals. Because we found an interaction, we then evaluated the number of NeuN+ cells to determine if there was phenotypic loss of TPH or actual neuronal degeneration. Again, there was an interaction (F(2,26)=4.48 p<0.05) between genotype and age, and a main effect of age (F(2,26)=12.08 p<0.001) (Figure

6B). Although there was no significant difference between DJ-1 KO and WT animals at 5 months of age, we did observe DJ-1 KO rats lost NeuN+ cells between ages 5 and 17 months of age, similar to what we have observed for the TPH+ cell counts. This indicates frank neuronal degeneration of the 5HT neurons rather than simply phenotypic loss of TPH expression.

The number of TH+ and NeuN+ cells in the LC was counted at 5, 9, and 17 months of age

(Figure 7). We found an interaction between genotype and age for the TH+ neuron counts

(F(2,22)=6.186 p<0.01) ( Figure 7A and 7C). At 17 months of age, DJ-1 KO rats exhibited less

TH+ cells than their WT counterparts, and between 5 and 17 months of age, only DJ-1 KO animals lost TH+ cells. Also, we detected a main effect of genotype (F(2,22)=5.393 p<0.05) and age (F(2,22)=11.96 P<0.001). Because we observed differences in the number of TH+ cells between DJ-1 KO and WT rats, we also examined NeuN+ cells in the LC to determine if true degeneration occurred (Figure 7B). We found no interaction for the NeuN+ cell counts, but we did find a main effect of age (F(2,22)=17.96 p<0.0001) and genotype (F(2,22)=11.69 p<0.01).

192

Discussion In this study investigating PD-related neurotransmitter differences between WT and DJ-

1-deficient rats, we examined the levels of monoamines and their metabolites at several ages in several forebrain and midbrain regions. Our main findings indicate that there is an increase in

DOPAC in the striatum which leads to a main effect of genotype for the DOPAC/DA ratio.

Somewhat surprisingly, we found, overall, that DJ-1 KO rats exhibit a higher concentration of

5HIAA in both the ventral midbrain and hippocampus. Additionally, we determined that DJ-1 KO rats have a significantly lower concentration of NE compared to their WT counterparts. We also assessed whether neurodegeneration occurs in the SNpc, DRN, and LC during aging to a greater extent in the DJ-1 KO rats versus WT rats. Contrary to a previous report (Dave et al.,

2014), we did not observe TH+ cell loss in the SNpc of DJ-1 KO rats compared to WT rats, ranging from 5 to 17 months of age. We did find a progressive loss of 5HT cells in the DRN from 5 to 17 months of age. A similar age-related loss of NE neurons of the LC was not observed, but we determined, overall, that DJ-1 KO rats have less NE neurons in the LC, compared to WT rats.

A previous study also analyzed DA levels via HPLC in striatal tissue from DJ-1 KO and

WT rats, at 4, 6, and 8 months of age (Dave et al., 2014). That study reported increased striatal

DA concentration, as well as a reduced number of TH+ cells in the SNpc of DJ-1-deficient rats, compared to WT control rats, at 8 months of age (Dave et al., 2014). Our findings are in contrast to Dave et al. (2014) in that we did not observe any changes in striatal DA at 5 or 9 months of age, nor loss of nigral TH+ neurons up to 17 months of age. We did, however, detect a progressive increase in striatal DOPAC levels from 5 to 9 months of age, with 9-month-old DJ-

1 KO rats having a higher concentration of DOPAC compared to their WT counterparts. It should be noted that Dave et al. (2014) also examined TH immunostaining in the striatum of the

DJ-1 KO and WT rats at 8 months of age and found no differences between the 2 groups (i.e.

193

Figure 5. Substantia nigra pars compacta

Fig. 5 Unbiased stereological cell counts of TH+ neurons in the substantia nigra pars compacta of DJ-1 KO and WT rats (n=6-10/group) at 5, 9 and 17 months of age. No changes in the number of TH+ cells were found for either genotype or age. Values represent mean ± SEM.

194

Figure 6. Dorsal raphe nucleus

Fig. 6 TPH+ and NeuN+ stereological cell counts in the DRN for DJ-1 KO and WT (n=6-

10/group) at ages 5, 9, and 17 months. A. There is an interaction between genotype and age for TPH+ neurons of the DRN. At 5 months of age, DJ-1 KO rats exhibit a significantly higher number of TPH+ cells compared to controls. Between the ages of 5 and 9 months and 5 and 17 months, DJ-1 KO animals exhibited a decrease in the number of TPH+ cells. B. An interaction occurs between genotype and age for NeuN+ cells. DJ-1 KO rats have a significant decrease in the number of NeuN cells from ages 5 to 9 months and 5 to 17 months. C. Low powered images of TPH+ cells in the DRN at 5 and 17 months of age. Values represent mean ±SEM;

*p<0.05, ***p<0.001.

195

Figure 7. Locus coeruleus

Fig. 7 Unbiased stereological cell counts of TH+ and NeuN+ cells in the LC of DJ-1 KO and WT rats (n=6-10/group) at 5, 9, and 17 months of age. A. There is an interaction between genotype and age for the TH+ neuron counts. At 17 months of age, DJ-1 KO rats exhibit less

TH+ cells than their WT counterparts. From 5 to 17 months, DJ-1 KO animals have a progressive loss of TH+ cells. A main effect of genotype is observed, and DJ-1 KO rats have less TH+ neurons than WT rats. B. A main effect of genotype was found, where DJ-1 KO rats have a lower number of NeuN+ cells than WT. C. Low power images of TH+ cells in the LC at

5 and 17 months of age. Values represent mean ± SEM; *p<0.05, *p<0.0001.

196 no reduction in TH immunoreactivity in the DJ-1 KO rats), a seemingly incongruent result given the reported ~50% decrease in nigral TH neurons at the same age. Another irregularity in the earlier study (Dave et al., 2014) is that the number of counted TH+ cells in the SNpc far exceeded previous published data (by 2- to 3-fold) for the number of TH+ neurons in this structure (e.g. Healey-Stoffel et al., 2013; Tapias et al., 2013; Hemmerle et al., 2014; present study). The authors explained this discrepancy via the use of differing stereological methodologies (Dave et al., 2014), but the data still remain a conundrum.

Pre- and postsynaptic dopaminergic markers of the nigrostriatal pathway have also been examined in the DJ-1-deficient rats. Although no differences were found in the density of dopamine transporters (DAT) between DJ-1 KO and WT rats, vesicular monoamine transporter

2 (VMAT2), D2 receptor, and D3 receptor densities were all increased in the striatum of 8- month-old DJ-1 KO animals (Sun et al., 2013). Taken together, the increase in striatal DOPAC levels, VMAT2 and DA receptors suggests that DJ-1 KO rats possess abnormal DA neurotransmission. Future studies employing other techniques (i.e. microdialysis, in vivo electrochemistry) should be conducted to provide an enhanced in vivo analysis of dopamine dynamics in the DJ-1-deficient striatum.

This study is the first to examine cell loss in the DRN, as well as 5HT concentrations in brain regions in addition to the striatum, in DJ-1 KO rats. As stated previously, the DRN degenerates in PD, and as cellular loss progresses, decreases in 5HT neurotransmission occur

(Halliday et al., 1990; Kerenyi et al., 2003). Dave et al. (2014) found a decrease in striatal 5HT content of DJ-1 KO rats at 8 months of age, findings inconsistent with ours in that we did not observe decreases in 5HT levels at either 5 or 9 months of age. We did discover that, compared to WT rats, DJ-1 KO rats exhibit a higher concentration of 5HIAA in both the ventral midbrain and hippocampus at both ages. The DRN heavily innervates the nuclei of the basal ganglia, and 5HIAA is reduced in basal ganglia post-mortem brain tissue from PD patients

197

(Scatton et al., 1983; Kerenyi et al., 2003). The DRN also extends efferents to the hippocampus, and likely is involved with cognitive tasks (Hale and Lowry, 2011). The decreases in 5HIAA measured in post-mortem brain tissue were obtained from patients at end stages of the disease. Therefore, with respect to our current results, it is possible that earlier stages of the disease may reflect an increase in 5HIAA as a compensatory mechanism for cellular damage that occurs in the DRN. Also, increases in the 5HT metabolite and not 5HT itself may be due to changes in the metabolic breakdown of 5HT or transmission of the metabolite back to the neuron, but further analysis would need to be done. We did find an interaction between genotype and age for both TPH+ and NeuN+ cell counts. Thus, together, these data indicate a change of the 5HT neurons of the DRN in DJ-1 KO rats between the ages of 5 and 17 months. It will be important to continue future studies examining 5HT and 5HT metabolite changes in other brain regions associated with PD, as well as to analyze serotonin neurotransmission using different in vivo techniques as noted above for DA.

The present investigation is also the first to examine NE levels in several PD-related brain regions in the DJ-1 KO rat. We found that DJ-1 KO rats have a lower concentration of NE in the hippocampus compared to their WT counterparts at both 5 and 9 months of age. The LC is the source of NE for the hippocampus, and is involved in arousal and memory formation and retrieval (Sara and Devauges, 1988; Sullivan et al., 1994; Fu et al., 1999). In non-demented PD patients, inhibition of NE neurotransmission decreases attention and overall cognitive performance; increasing NE synthesis reverses the cognitive impairments (Bedard et al., 1998).

Consonant with the neurochemical findings, and we found a progressive decrease during aging in the number of NE (TH+) neurons in the LC of DJ-1 KO rats as compared to WT rats. These data are consistent with those of a recent study that also reported reduced TH+ cells in the LC of DJ-1-deficient rats (Yang et al., 2018). Our results show an interaction between age and genotype, where DJ-1 KO rats gradually lose TH+ cells over our assessment time periods, and

198 have less TH+ cells than WT rats at 17 months of age. Statistically, we did not find an interaction between genotype and age with the NeuN+ cell counts. (Fig. 7). However, when considering the actual cell counts, both TH+ and NeuN+ cells are lower by approximately 800-

900 cells in DJ-1 KO rats compared to WT rats, suggesting true neuronal degeneration rather than simply TH phenotypic downregulation. Yang et al. (2018) reported TH+ cell loss in DJ-1

KO rats in the LC at 8 months of age, whereas we did not find significance until 17 months of age. Potential caveats are that Yang et al. (2018) only examined the LC at one age, did not employ unbiased stereological techniques, and did not perform NeuN+ cell counts to determine if phenotypic changes or true cellular loss occurred. In Chapter 2 of this dissertation, one of the most prominent non-motor behavioral dysfunctions observed in the DJ-1 KO rats was deficits in attention and memory as revealed in the novel object/place recognition task. Together, our cellular, neurochemical and behavioral data suggest that DJ-1 KO rats exhibit PD-like changes in NE, LC degeneration, and associated cognitive deficits.

The present study provides a more complete picture of changes in noradrenergic, serotonergic and dopaminergic systems in rats deficient in DJ-1. Key hallmarks of PD include decreases in striatal dopamine content and loss of DA neurons of the SNpc. However, clinical diagnosis of PD normally ensues when ~80% of the DA content is lost in the striatum, and 50-

60% of the cells degenerate in the SNpc (Schulz and Falkenburger, 2004). Prior to diagnosis, aberrant changes are not only occurring in the nigrostriatal dopaminergic system, but also in the noradrenergic and serotonergic monoaminergic systems as well, as indicated, for example, by

NMS (such as depression and anxiety) manifesting prior to diagnosis (Cummings, 1992;

Richard, 2005). Braak staging uses the histopathological hallmark of PD, Lewy bodies (LBs), to determine the stage of PD in post-mortem brains, and shows LBs manifest in extra-nigral brain regions (e.g. LC) prior to appearing in the SNpc (Braak et al., 2013). Although Braak staging may explain how NMS such as depression and anxiety manifest prior to motor deficits, cognitive

199 dysfunction was always considered to occur in late Braak stages of PD because LBs are apparent in the neocortex at that time (Braak et al., 2003; Hawkes et al., 2010; Del Tredici and

Braak, 2016). Here, in the DJ-1 KO rat model, we have demonstrated cell degeneration in the

LC and aberrant changes in hippocampal NE which may underlie the subtle cognitive deficits observed in a third of the PD population at clinical diagnosis (Broeders et al., 2013). Overall, our findings suggest that the DJ-1 KO rat is a good model for the study of early or prodromal stages of PD, perhaps prior to diagnosis.

Acknowledgments

The work in this chapter was performed in collaboration with the following colleagues at the

University of Cincinnati and Cincinnati Children’s Hospital Medical Center: Adam J. Dourson,

Ann M. Hemmerle, PhD, Arnold Gutierrez, PhD, Michael T. Williams, PhD, and Charles V.

Vorhees, PhD.

200

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209

Chapter 4

Evaluation of Activated Microglia in Aged DJ-1 Knockout Rats

210

Abstract It is well known that neuroinflammation plays a significant role in Parkinson’s disease

(PD) pathology. Microglia, the immune cells of the brain, are more active under abnormal physiological conditions and proliferate with neuroinflammation. In the PD brain, increases in active microglia are observed in several regions associated with the disease. Several genes associated with PD play a part in the increase of activated microglia. One of those genes, DJ-1, protects against oxidative stress, and loss of this protein leads to an increase in reactive oxygen species, eventually leading to neuroinflammation and overactive microglia. Here, we hypothesized that DJ-1 knockout (KO) rats would have increases in microglial numbers and alterations in microglial morphology in brain structures associated with PD neuropathology, including the striatum, substantia nigra pars compacta, dorsal raphe nucleus, and locus coeruleus. Morphological changes in microglia from DJ-1-deficient rats were detected only in the locus coerulus, in which enlarged microglial somal area was measured, as compared to wild-type rats. No differences were found numbers of microglia in any of the brain regions examined nor in morphological changes in regions other than the locus coeruleus. These results suggest limited involvement of microglia in morphological or physiological changes associated with the aged DJ-1 KO brain.

211

Introduction Neuroinflammation plays a major role in the pathogenesis of neurodegenerative diseases, such as Parkinson’s and Alzheimer’s diseases (Aktas et al., 2007; Henneman et al.,

2009; Perry, 2012). Neuroinflammation can be induced by biological mechanisms, such as oxidative stress, or by glial reactivity, such as via microglial activation. Microglial overactivation leads to chronic neuroinflammation and contributes to neuronal degeneration (McGeer and

McGeer, 2004a; Niranjan, 2014; Tansey and Romero-Ramos, 2019). Similarly, overactive microglia in neuropsychiatric disorders, like depression, can lead to the depletion of monoamines and associated dysfunction (Catena-Dell'Osso et al., 2013; Leonard, 2014).

Although acute neuroinflammation is beneficial to neuronal repair after injury, chronic neuronal inflammation contributes to an increase in brain damage and degeneration (Lucas et al., 2006;

Lee et al., 2019). Inflammation is the body’s natural response to an injury or insult. In the brain, there is no involvement of antibodies, and little to no involvement of T-cells, as in the peripheral nervous system. The brain inflammatory response mainly depends on the synthesis of cytokines and the phagocytic ability of microglia (McGeer and McGeer, 2004b). In Parkinson’s disease (PD) patients, high levels of various cytokines are present in the serum, possibly reflecting their presence in the brain (Peter et al., 2018; Zeuner et al., 2019). Also, epidemiological studies suggest that anti-inflammatory drugs like Ibuprofen slightly protect individuals against the risk of developing PD (Rees et al., 2011). Here, we will focus on the potential role of altered microglia in the DJ-1 KO rat model of PD.

Microglia are the immune cells of the brain and constitute 5-10% of the total number of cells in the brain, with densities varying per brain region (Lawson et al., 1992; Savchenko et al.,

2000; Aguzzi et al., 2013; Li and Barres, 2018). Normally, microglia are in a resting state in the adult brain, but upon changes in the microenvironment, such as an insult, microglia alter their proliferation rates (increase), morphology ( i.e. larger soma, less processes), phagocytotic

212 activity, presentation of antigens, release of inflammatory factors (i.e. cytokines and chemokines), and production of superoxide anions (Cuadros and Navascues, 1998; McGeer and McGeer, 2004a; Kettenmann et al., 2011; Gomez-Nicola et al., 2013; Sierra et al., 2013;

Jimenez-Ferrer et al., 2017). Under normal conditions, microglia are involved in synaptic plasticity, remodeling, and circuitry integrity, but once the inflammatory response is triggered, microglia are “distracted” by surveillance and can become hyperactive, with excessive inflammation ultimately being degenerative. Such “distracted” microglia that eventually perpetuate the inflammatory response can contribute to disease states including neuropsychiatric and neurodegenerative disorders (Churchward et al., 2019).

The substantia nigra pars compacta (SNpc) is a critical brain region in PD neuropathology. This ventral mesencephalic nucleus exhibits relatively dense numbers of microglia: ~12% of the cells in the SNpc are microglia (Albin et al., 1989a; Lawson et al., 1990).

Because of the importance of the role of the SNpc in PD, and its high microglial content, most research has focused on this region. For example, in the PD brain, the SNpc contains high levels of human leukocyte antigen DR (HLA-DR) and the cytokine tumor necrosis factor alpha

(TNFa), both indicators of increases in active microglia (McGeer et al., 1988; Boka et al., 1994).

However, with the recognition of PD-related non-motor symptoms (NMS) and the associated brain regions, microglia activation has been studied in extra-nigral areas. As stated previously in this dissertation, alpha-synuclein (aSyn)-containing Lewy bodies (LBs) are the histopathological markers of PD. In addition to the SNpc, LBs can be found in many brain nuclei associated with PD, such as the locus coeruleus (LC) and dorsal raphe nucleus (DRN), and these aggregates are thought to contribute to neuroinflammation and cell death (Braak et al., 2003; Tansey and Romero-Ramos, 2019). Accordingly, studies indicate PD brains have increased active microglia in extra-nigral regions such as the hippocampus, cortex, and LC

(Bertrand et al., 1997; Imamura et al., 2003; Ouchi et al., 2005; Iannaccone et al., 2013; Doorn

213 et al., 2014). Along with these findings in humans, microglia have been examined in rodent models of Parkinson’s to determine the role of microglia in disease pathology.

Several genetic rodent models of PD exhibit increases in active microglia. Mutations in the leucine-rich repeat kinase 2 (LRRK2; PARK8) gene cause prominent autosomal dominant familial forms of PD (Hernandez et al., 2016), and may also cause sporadic PD. LRRK2 is highly expressed in immune cells and is proposed to play a major role in the immune system

(Hakimi et al., 2011; Cook et al., 2017). In vitro studies with primary microglia from LRRK2 knockdown mice observe a decrease in the pro-inflammatory cytokine tumor necrosis factor-a

(TNF-a), whereas mice with the LRRK2 R1441G mutation exhibit an increase in TNF-a

(Gillardon et al., 2012; Moehle et al., 2012). Injection of the endotoxin lipopolysaccharide (LPS), which induces an immune response, into mice overexpressing LRRK2 leads to long-term loss of dopaminergic neurons of the SNpc, compared to controls (Kozina et al., 2018). The SNCA

(PARK1) gene, the major causative gene for familial PD, encodes the protein aSyn

(Polymeropoulos et al., 1997). As noted above, aSyn aggregation leads to neuroinflammation, cell dysfunction and neurodegeneration (Braak et al., 2003a; Tansey and Romero-Ramos,

2019). For example, one study showed that injection of human aSyn into the hippocampus led to widespread aSyn inclusions (hippocampus, cortex, amygdala, thalamus, and hypothalamus) months after the injection, and areas with the inclusions displayed higher glial activation (Sacino et al., 2014). However, in mice overexpressing human aSyn under the Thy-1 promoter, activated microglia occurred only in the SNpc and striatum, although human aSyn was distributed throughout the brain (Watson et al., 2012). Alpha-synuclein transgenic mice with the

A30P mutation demonstrated increased active microglia in both the cortex and hippocampus, whereas mice expressing a truncated form of human aSyn showed an increase in microglia in the SNpc and olfactory bulb (Gomez-Isla et al., 2003; Tofaris et al., 2006). Thus, the status of neuroinflammation, particularly with respect to microglia, in genetic rodent PD models remains

214 unclear. In our study, we will assess microglial activation and number in mutant rats lacking the

DJ-1 (PARK7) gene.

Loss of the DJ-1 gene leads to an autosomal recessive familial form of PD. DJ-1 is found in almost all cell types and has many physiological roles (Cookson, 2010). But, the most well-known role of the protein is prevention and neuroprotection against oxidative stress.

Oxidative stress can produce increases in neuroinflammation (Taira et al., 2004; Canet-Aviles et al., 2004; Junn et al., 2009). Notably, evidence suggests a close association of DJ-1 with microglia. DJ-1-deficient microglia exhibit an increase in inflammatory cytokines and an increase in microglial activation (Trudler et al., 2014). It has been hypothesized that DJ-1 is an

“off” signal to microglia in high cellular stress situations to prevent microglia neurotoxicity

(Trudler et al., 2014; Kim et al., 2013). Moreover, knockdown of DJ-1 in a microglial cell line resulted in changes in autophagy-dependent degradation of several proteins (Nash et al., 2017).

In DJ-1 KO mice injected with LPS, there was an increase in chemokines and cytokine content in the SNpc compared to control mice given LPS (Chien et al., 2016). This was accompanied by an increase in nigral dopaminergic cell death in the DJ-1-deficient mice (Chien et al., 2016).

However, another study failed to replicate these data, in that DJ-1 KO mice given LPS responded similarly to control mice given the endotoxin, with no differences in the number of microglia in the SNpc between groups (Nguyen et al., 2013). Excluding these few studies, no other reports of increased or activated microglia in DJ-1 KO rodents have appeared to date. In the present study, we assessed the number of microglia using stereological techniques and determined their activation state (somal size) in the striatum, SNpc, LC and DRN of 17-month- old DJ-1 KO rats. We hypothesized that the aged DJ-1-deficient rats would exhibit enhanced numbers of microglia and increased perikaryal size in several brain regions that are dysfunctional in PD.

215

Methods

Animals DJ-1 knockout (KO) and aged-matched wild-type (Long-Evans) rats were purchased from Horizon Discovery (Boyertown, PA) at approximately 9-12 weeks of age. Animals were evaluated at 17 months of age (n=10/group). These rats had undergone behavioral testing (but not chronic variable stress) earlier in experiments in Chapter 2. All animals were kept under a

12:12 light: dark cycle, with food and water available ad libitum, and were housed 2 per cage.

All procedures and protocols were approved by the University of Cincinnati Institutional Animal

Care and Use Committee. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Immunohistochemistry

At 17 months of age, several animals died prior to this time point, reducing the group numbers of n=7-10/group. WT and DJ-1 KO rats were anesthetized with 1ml each of a 1:1 dilution of sodium pentabarbitol (Euthasol®, Virbac Animal Health, Fort Worth, TX) and transcardially perfused using 300ml of saline, then 300ml of 4% paraformaldehyde (PFA)

(Sigma). Brains were extracted, post-fixed overnight in 4% PFA, and placed in 30% sucrose solution until the brain sunk to the bottom of the jar. The following regions were sectioned in each brain: striatum, SNpcv, DRN and LC. These regions were identified based on the Paxinos and Watson (1986) rat atlas, and all regions were sectioned at 50-µm thickness using a sliding microtome. The SNpc, DRN, and STR were cut in a 1:12 series, whereas the the LC was cut in a 1:4 series. Sections were placed in cryoprotectant until processing for immunohistochemistry, according to our previously published protocols (Hemmerle et al., 2014).

216

Sections were washed in 0.1M phosphate buffer solution (PB) (Sigma), placed in 0.3% solution of hydrogen peroxide (Sigma) for 10 minutes and then blocked using 10% normal horse serum (NHS) (Vector Labs, Burlingame, CA) for 1 hour. The sections were then placed in a primary antibody solution of, 0.2% Triton X-100 (Sigma), 1% NHS, and the primary antibody directed against ionized calcium-binding adaptor molecule 1 (Iba-1) (biomarker of microglia) at a dilution of 1:2000 (Wako Pure Chemical Industries, Ltd., Osaka, Japan). All sections were placed in the primary antibody solution overnight on a shaker at 4oC.

Following the overnight incubation, sections were washed with 1% PB, blocked for 10 minutes in a 2% NHS blocking solution, and then placed in biotinylated polyclonal secondary antibody (horse anti-rabbit IgG; BA-2000; Vector Laboratories) for 1 hour. The secondary antibody solution consisted of 1% NHS and a 1:200 dilution of the anti-rabbit secondary antibody. Sections were washed in 1% PB and incubated in streptavidin-biotin-horseradish peroxidase solution (ABC kit; Vector Laboratories) for 30 minutes. Sections were washed in 50 mM Tris solution and developed in diaminobenzidine tetrahydrochlroide (DAB; Vector

Laboratories) containing 0.3% H2O2 for colorimetric visualization of the immunostained cells

(Hemmerle et al., 2014). The sections were then rinsed in Tris buffer, mounted onto Superfrost plus microslides (VWR, Batavia, IL), and air-dried overnight. The next day, the sections were dehydrated through a series of ethanols, cleared in Hemo-De (VWR), and coverslipped in Pro-

Texx Mounting Medium (Lerner Laboratories).

Stereology

Cell estimates were determined using Stereo Investigator (v.10.51, MFB Bioscience,

Williston, VT) and unbiased stereological methods, as previously described (West, 1993;

Hemmerle et al., 2014). Representative samples (5-6 sections/region) through the striatum,

SNpc, DRN, and LC were used for cell counts. The sections were viewed on an Olympus BX-60

217 microscope (Melville, NY) using a CCD video camera (HV-C20, Hitachi, San Jose, CA).

Regions of interest (striatum, SNpc, DRN, and LC) were outlined using the contour function at

1.25X (SNpc, DRN, striatum) and 2X (LC) magnifications. The grid size for the areas of interest were the following: 140X140 µm for the striatum, 90x90µm for the SNpc, 90x90 for the DRN, and 80x80 for the LC. Cell counts were conducted using the optical fractionator function with an optical dissector size of 50x50µm and guard zones of 2µm. The Gundersen correction was used to calculate the coefficient of error for each animal and was set at less than 0.10 (West, 1993;

Hemmerle et al., 2014). The data were analyzed using Student’s t-test. Data are presented as mean ± SEM. Significance is considered at P < 0.05.

Microglial Morphological Analysis

Microglial activation was assessed morphologically, and representative samples (5-6 sections/brain) for each region were used. Three random images were taken (60X magnification) from each section for all regions on an Olympus BX-51 microscope (Melville, NY) using a CCD video camera (HV-20, Hitachi). All visible microglia in the images were analyzed using Image J software (NIH). Somal area was used as a measure of microglial activation

(Perry et al., 2007). The scale was set to 1 pixel = 0.113 µm. Microglia were traced with the free-hand tool, and the somal area was then measured. All microglial perikaryal measurements taken from all the images for each region were averaged together to generate one score per region per rat brain. Animals in each group were averaged together to obtain a final average each for DJ-1 KO and WT rats. The data were analyzed using Student’s t-test.

218

Results

Striatum

Sections were processed immunohistochemically for Iba-1 to assess relative differences in microglial number and cell body area, which can be indicative of microglial activation. There was no significant difference in the number of striatal Iba-1+ cells between 17-month-old DJ-1

KO rats and their WT counterparts (Figure 1A). Similarly, no differences were observed for somal area between the genotypes (Figure 1B).

Substantia nigra pars compacta

In the SNpc, the number of Iba-1-immunolabeled cells was not significantly different in

DJ-1 KO versus WT rats (Figure 2A). Also, we observed no significant difference between the two groups in somal area (Figure 2B).

Dorsal raphe nucleus

The DJ-1-deficient and WT rats exhibited no significant differences in the number of Iba-

1-immunostained cells in the DRN at 17 months of age (Figure 3A). Likewise, the perikaryal areas of the two genotypes was similar in this brainstem nucleus (Figure 3B).

Locus Coeruleus

In the LC, the number of Iba-1+ microglia did not differ between DJ-1 KO and WT rats at

17 months of age (Figure 4A). However, we found that DJ-1 KO rats displayed a larger Iba-1+ somal area compared to their WT counterparts (Figure 4B).

219

Figure 1. Striatal Microglia

Fig 1. Analysis of microglia in DJ-1 KO and WT rats (n=10/group). A. There is no difference in the number of Iba-1+ cells in the striatum of WT and DJ-1 KO rats. B. No significant difference in Iba-1+ soma size between WT and DJ-1 KO rats was found. Values represent mean ± SEM.

220

Figure 2. SNpc Microglia

Fig. 2. Analysis of microglia in the SNpc of 17-month-old WT and DJ-1 KO rats (n=10/group).

A. No difference was found in the number of Iba-1-immunostained cells in WT versus DJ-1 KO rats. B. There was no significant difference in the size of Iba-1+ microglial perikaya between

DJ-1 KO and WT rats. SNpc, substantia nigra pars compacta. Values represent mean ± SEM.

221

Figure 3. DRN Microglia

Fig 3. Analysis of microglia in the DRN of WT and DJ-1 KO rats (n=10/group) at 17 months of age. A. No significant difference in the number of Iba-1+ cells was observed in the DRN of WT versus DJ-1 KO rats. B. There was no significant difference in microglial soma area between

DJ-1 KO rats and their WT counterparts. DRN, dorsal raphe nucleus. Values represent mean ±

SEM.

222

Figure 4. Locus Coeruleus Microglia

Fig. 4. Analysis of microglia in the locus coeruleus (LC) of 17-month-old WT and DJ-1 KO rats

(n=10/group). A. There was no significant difference of the number of Iba-1+ cells between WT and DJ-1-deficient rats. B. DJ-1 KO rats have a significantly larger somal area compared to

WT controls. C. Examples of high power images (60X magnification) of Iba-1-postiive cells in the LC of WT and DJ-1 KO rats. Note enlarged cell body in the right panel. Values represent mean ± SEM. *p<0.05 compared to WT.

223

Discussion

The present study examined the state of microglia in the striatum, SNpc, DRN, and LC of 17-month-old DJ-1 KO rats. We hypothesized we would detect an increase in the number of microglia, with larger somal areas, in DJ-1 KO rats compared to WT rats, due to the role DJ-1 plays in the prevention of oxidative stress and in microglial activation. Surprisingly, we only found differences in the LC, as evidenced by the increased area of microglial perikarya in the

DJ-1-deficient rats. This finding of activated LC microglia may be consistent with our results in

Chapter 3, in which we demonstrated NE neuronal degeneration in the LC of aged DJ-1 KO rats. One possible explanation for the LC microglia activation, albeit relatively minor, is that DJ-

1 is hypothesized as being active when under pathological conditions (Cookson, 2012; Biosa et al., 2017; Dolgacheva et al., 2019). Thus, the absence of DJ-1 in the KO rat may leave the LC vulnerable to both degeneration and aberrant microglial alterations.

One of the more established roles of DJ-1 is the prevention and protection against oxidative stress (Canet-Aviles et al., 2004; Taira et al., 2004; Kim et al., 2005; Zhou and Freed,

2005; Cookson, 2012). As noted above, oxidative damage can induce neuroinflammation, cell death, and activation of microglia. Loss of DJ-1 is thought to contribute to the above conditions

(Cookson, 2010). Nevertheless, DJ-1 may prevent oxidative stress and inflammation only under extremely abnormal conditions, so it is possible that a combination of both a DJ-1 deficiency and an environmental insult may need to co-occur to observe increases in inflammation and, thus, active microglia. DJ-1 KO mice administered LPS or MPTP exhibit increased sensitivity to oxidative stress; however, only when exposed to these ‘environmerntal’ toxins do DJ-1 KO mice then sustain enhanced loss of dopamine neurons in the SNpc compared to controls, as well as an increase in cytokines and chemokines (Kim et al., 2013; Chien et al., 2016). The glutathione system is the major cellular antioxidant system, and it is more efficient than DJ-1. Glutathione also exists at a much higher concentration in brain tissue than DJ-1. However, DJ-1 is a highly

224 conserved protein and can be found even in yeast, so undoubtedly DJ-1 has an important role to play in the cell. Thus, DJ-1 may have a somewhat subtle role in the prevention of oxidative stress, perhaps under more extreme conditions (Cookson, 2012).

Brain regions are differentially vulnerable to insults with respect to increases in active microglia and neuroinflammation. It has been established that nigral dopaminergic neurons are particularly vulnerable to insults due to factors such as their electrophysiological firing patterns and dopamine metabolism itself (Damier et al., 1999; Sulzer and Schmitz, 2007; Barzilai et al.,

2001; Gonzalez-Hernandez et al., 2010). This SNpc has one of the highest densities of microglia in the brain (Lawson et al., 1990). Moreover, nigral dopaminergic neurons have a high sensitivity to cytokine-induced cell death (McGuire et al., 2001). In our study, however, we did not find any differences in the number microglia in the SNpc between WT and DJ-1 KO rats.

This lack of altered microglial activation and numbers between DJ-1 KO and WT rats may be consistent with our lack of dopaminergic cell loss in DJ-1-deficient rats, as shown in Chapter 3.

Unlike dopamine, NE is a well-established neuroprotectant against neuroinflammation by decreasing inflammatory gene expression in microglia (Heneka et al., 2002; Marien et al.,

2004; Michelucci et al., 2009). In Alzheimer’s disease research, degeneration of the LC contributes to increase microglial dysfunction and activation because of the loss of NE. For example, lesions of the LC in rodent models of Alzheimer’s and Parkinson’s result in in glial- induced neuroinflammation (Heneka et al., 2010; Satoh and Iijima, 2019). We did find more active microglia in the LC of DJ-1 KO rats compared to controls, which may be consonant with our findings in Chapter 3 of NE cell loss in the LC and a decrease in NE in the hippocampus of

DJ-1 KO rats. It is possibly that NE dysfunction contributes to the actived microglia in the LC of the DJ-1-deficient rats. Future studies should examine, in particular, the hippocampus of the mutant rats for active microglia due to the lower levels of NE.

225

The serotoneric DRN system has a modulatory effect on microglia and cytokines and vice versa (Robson et al., 2017). Cytokines increase 5HT uptake activity, thereby decreasing

5HT signaling (Haase and Brown, 2015). Microglia express 5HT receptors, and 5HT can induce expression of several cytokines (Mahe et al., 2005; Kolodziejczak et al., 2015). Perhaps surprisingly, we did not find a difference in activated microglia between DJ-1 KO and WT rats, despite our findings of a loss of 5HT neurons in the DRN and altered levels of 5HIAA in DJ-1

KO rats. However, we did not detect changes in the neurotransmitter 5HT, itself, which may help explain the lack of microglial changes in the DRN.

Another factor contributing to microglial activation is age. Age is also strongly correlated with PD, with aging being the greatest risk factor for the disease (Li et al., 1985;

Mayeux et al., 1992; Benito-Leon et al., 2003; de Lau and Breteler, 2006). A sharp increase in disease risk occurs around 60 years of age, with the age of onset of sporadic Parkinson’s typically occuring around 65 (de Lau and Breteler, 2006). Aging is accompanied by chronic neuroinflammation, activated microglia, and increases in cytokines (Frank et al., 2006; Norden and Godbout, 2013; Lee and Wei, 2012) Microglia in an aged brain express more inflammatory markers than in a young brain, and once an insult challenges the immune system in an aged brain, there is prolonged activation (Wynne et al., 2009). In this study, we examined DJ-1 KO rats at 17 months of age expecting that, due to loss of DJ-1 and advanced age, we would likely uncover increases in activated microglia in several PD-related brain regions. Our results, however, with the exception of the LC, did not support this hypothesis, and instead suggest that lack of DJ-1 has limited influence over microglial activation and expression in the aged rat brain.

Acknowledgments

We are grateful to Adam J. Dourson for excellent technical assistance.

226

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Chapter 5

General Discussion

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Parkinson’s disease (PD) is a complex disorder with both motor and non-motor symptoms. Although degeneration of the dopaminergic (DA) neurons of the substantia nigra pars compacta (SNpc) is a key hallmark of PD, many other brain regions, such as the locus coeruleus (LC) and dorsal raphe nucleus (DRN), degenerate and contribute to disease pathology. Generation of rodent PD models, based on putative environmental and genetic causes of PD, allows for investigation into disease pathology and potential therapeutics. No animal model to date, however, has fully recapitulated PD. The DJ-1 knockout (KO) rat model, as focused upon in this dissertation, displays changes in several motor and non-motor-like symptoms, and exhibits neuronal degeneration in both the LC and DRN. In Chapter 2, we examined an array of both motor and non-motor behaviors in the DJ-1-deficient rats. In Chapter

3, we evaluated neurodegeneration in key brain regions associated with PD, as well as changes in monoamine neurotransmitters, in DJ-1 KO rats. Given the role of DJ-1 in cellular oxidative stress and functioning of microglia, in Chapter 4 we assessed possible enhanced microglial activation in aged rats lacking DJ-1, as determined morphologically and stereologically.

Together, the data reveal that the DJ-1 KO rat model demonstrates a PD-like phenotype in several behavioral, neurochemical and morphological aspects of the disease.

DJ-1 KO rats exhibit some Parkinson’s-like behavioral changes which are similar to those seen in other genetic rodent models (Chapter 2). We found that DJ-1 KO rats rear and groom less than WT rats, independent of age, indicating a PD-like phenotype. This finding is similar to that found in a previous study of DJ-1 KO rats (Dave et al., 2014). However, unlike the few other studies that examined DJ-1 KO rats (Dave et al., 2014; Yang et al., 2018), we found DJ-1 KO rats take more hind- and forelimb steps, which is an unexpected result. These mixed motor results could be a possible indication this model mimics a stage of PD prior to clinical diagnosis. Diagnosis of PD is dependent on the manifestation of cardinal motor deficits resulting from an approximate 50-60% loss of DA neurons in the SNpc (Fahn, 1999; Rascol,

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2000). With such substantial nigral cell loss at diagnosis, patients are already on the way to a full-blown disease state. Because cardinal motor deficits are necessary for diagnosis, at this time, we are unable to know which motor changes occur early on in the disease. Along with motor behaviors, our lab was among the first to examine non-motor behaviors in the DJ-1- deficient rats. We found that the mutant rats exhibit cognitive deficits in short-term memory, in the novel object recognition task as early as 4.5 months of age. Previously, two DJ-1 KO mouse studies assessed cognitive deficits using the novel object recognition task. Only 13-14-month- old DJ-1 KO mice were found to have short term memory and attentional deficits (Chandran et al., 2008; Pham et al., 2010). The other more recent DJ-1 KO rat studies did not examine non- motor deficits (Dave et al., 2014; Yang et al., 2018). Although cognitive deficits traditionally were assumed to manifest during late-stage PD, it is now appreciated that about a third of patients express some kind of subtle cognitive deficit at diagnosis (Broeders et al., 2013).

Cognitive functions affected in early PD include memory, visuospatial processing, executive functions, and attention (Cronin-Golomb and Braun, 1997; Dujardin et al., 1999; Lewis et al.,

2003; Troster, 2008; Bronnick et al., 2011). Considered together, our present motor and non- motor data raise the possibility that DJ-1 KO rats are displaying early-stage PD-like behaviors.

Along with the behavioral manifestations in PD, there are also changes in monoamine levels (dopamine, serotonin, and norepinephrine) and degeneration of the SNpc, LC, and DRN.

We therefore examined DJ-1 KO rats for both changes in monoamines and their metabolites in several PD-related brain regions (midbrain, striatum, hippocampus, prefrontal cortex) and degeneration of the above-mentioned brainstem monoaminergic nuclei (Chapter 3). Our study is the first to assess these monoamines in brain regions other than the striatum in DJ-1 KO rats.

In the striatum, we found that levels of the DA metabolite DOPAC are higher in DJ-1 KO rats at

9 months of age, and that between 5 and 9 months of age, DOPAC concentrations increase in

DJ-1 KO rats. Results from a previous study showed that vesicular monoamine transporter 2

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(VMAT2), D2 receptor, and D3 receptor densities were all increased in the striatum of 8-month- old DJ-1-deficient rats (Sun et al., 2013). These data together with our DOPAC results suggest that DJ-1 KO rats exhibit abnormal nigrostriatal DA neurotransmission, but further analysis is necessary to determine if these changes are consistent with similar changes in PD in humans.

Finally, it should be noted that our measurement of unaltered striatal DA in the DJ-1 KO rats

(Chapter 3) is in conflict with another study which reported increases in DA at 8 months of age in the mutant rats (Dave et al., 2014). The latter results are contradictory to what is observed in humans with PD (Albin et al., 1989; Gibb, 1991).

With respect to 5HT and its metabolites, we found that DJ-1 KO rats exhibit a higher concentration of the metabolite 5HIAA in both the ventral midbrain and hippocampus, only dependent on genotype. Again, whether these findings indicate parkinsonian-like changes in these DJ-1 KO rats remains unclear, but further investigation is warranted. A previous study reported increases in 5HT at 8 months of age in the striatum of the DJ-1-deficient rats (Dave et al., 2014); this is contradictory to what we found (Chapter 3), and to what occurs in PD (Mayeux et al., 1986; Kostic et al., 1987; Fox et al., 2009). In our study, we found that DJ-1 KO rats display significantly lower concentrations of NE compared to their WT counterparts in the hippocampus, regardless of age. Our findings are in line with decreased levels of NE observed in PD in humans. Norepinephrine is important to memory formation and retrieval in the hippocampus (Sara and Devauges, 1988; Sullivan et al., 1994; Fu et al., 1999). Accordingly, loss of NE can lead to deficits in memory functioning (Sara and Devauges, 1988; Sullivan et al.,

1994; Fu et al., 1999), consonant with our results showing cognitive dysfunction in the DJ-1 KO rats (Chapter 2).

In addition to monoamine levels, we ascertained if DJ-1 KO rats exhibited neuronal loss in the SNpc, DRN or LC, brainstem nuclei that degenerate in PD. Most genetic models do not demonstrate loss of DA neurons in the SNpc, the hallmark of PD. Here, we also did not detect

241 loss of nigral DA neurons in the mutant rats, up to 17 months of age (Chapter 3). These data contrast to those of Dave et al. (2014) which described loss of nigral TH+ cells in 8-month-old

DJ-1 KO rats. It should be noted that this latter study did not use stereological methods in their cell counts, nor were NeuN-labeled or even Nissl-stained cell counted in adjacent sections.

Thus, it remains open as to whether the reported decrease in TH+ cells in the DJ-1 KO rats reflected frank neuronal degeneration or simply phenotypic loss of TH expression.

This investigation is the first to examine the DRN for neurodegeneration in rodent genetic models of PD. As stated previously, the DRN undergoes cell loss in PD (Halliday et al.,

1990; Kerenyi et al., 2003). We found an interaction between genotype and age for both TPH+ and NeuN+ cell counts, indicating changes in DRN 5HT neurons in DJ-1 KO rats between the ages of 5 and 17 months. Lastly, we examined the number of NE neurons in the LC of DJ-1- deficient rats. Up to 70% of LC neurons are lost in post-mortem PD brains (van Dijk et al.,

2012). In our study, we found that DJ-1 KO rats lost significantly more TH+ cells between 5 and

17 months of age compared to their WT counterparts. But, both TH+ and NeuN+ cell counts had a main effect of genotype, in which DJ-1 KO rats exhibited lower counts for both. These data are in line with a recent study that reported greater TH+ cell loss in the LC of the DJ-1 KO rats at 8 months of age (Yang et al., 2018). No other ages were examined in that study. Moreover,

Yang et al. (2018) reported ~50% nigral TH+ cell loss, whereas we found only ~15% TH+ cell loss at in the 8-month-old DJ-1 KO rats. This discrepancy may reflect the different cell counting methods used by each group [i.e. we used unbiased stereological techniques, whereas Yang et al. (2014) did not]. Nevertheless, it’s clear that significant cell loss is sustained by the LC in DJ-

1-deficient rats compared to WT rats. This raises the possibility that the loss of NE cells in the

DJ-1 KO rats may underlie the cognitive deficits and lower NE concentration in the hippocampus that we described in Chapter 3. Overall, the DJ-1 KO rat model is the first PD model to exhibit cellular degeneration in both the LC and DRN.

242

Taking our findings from Chapters 2 and 3 together, the DJ-1 KO rat model may be a good model to study the manifestation of PD, as it likely represents the stage prior to diagnosis.

As stated earlier, the key hallmarks of PD are decreases in striatal dopamine content and degeneration of DA cells in the SNpc. Clinical diagnosis of PD typically occurs when about 80% of the dopamine content is lost in the striatum, and more than half of the DA neurons have degenerated in the SNpc (Schulz and Falkenburger, 2004). The stages of the disease that pre- date the cardinal motor deficits and DA loss, the so-called prodromal stage, may be more consistent with what we have observed in our genetic model. Unfortunately, at this time, we are unable to directly examine these prodromal stages in humans to support our findings in animal models. Nevertheless, the behavioral, neurochemical, and cellular changes we observed in our studies more closely resembles earlier stages of the progression of PD.

Lastly, we assessed the status of active microglia in DJ-1 KO rats to begin to determine if neuroimmune mechanisms in rats lacking DJ-1 are associated with the behavioral, neurochemical and cellular outcomes that we described in Chapters 2 and 3. Perhaps surprisingly, we found no changes in the number of microglia in brainstem monoaminergic between DJ-1 KO and WT rats at 17 months of age. However, we did determine morphologically that the LC exhibited more active microglia at 17 months of age, a finding that could be expected due to of the neuronal loss in the nucleus. Because DJ-1 plays a major role in prevention of oxidative stress and neuroinflammation (Cookson, 2010), we expected to see increases in numbers of microglia as well as more active microglia in the DJ-1 KO rats compared to WT rats. The fact that we found little evidence of microglial alterations in the aged

DJ-1-deficient rats suggests that the disruption of other cellular functions of DJ-1 (Zhou et al.,

2006; Chen et al., 2010) may be contributing to the cellular, neurochemical and behavioral changes we observed.

243

Limitations and Caveats

There are several limitations and caveats for our study. First, we only used male rats for this study. Males are at about 1.5 times greater risk of developing PD, but there are also sex differences in symptom development, including that women with PD are more likely to develop depression (DATATOP, 1989; Scott et al., 2000; Wooten et al., 2004; Shulman and Bhat, 2006).

Therefore, using female rats is warranted and may lead to different outcomes in some of the behavioral testing, such as in anhedonia. We also did not use littermate controls. Littermate controls are often preferred because they have the same genetic background and environmental exposures which eliminates these variables from being a potential basis for differences between the control and experimental groups (Holmdahl and Malissen, 2012). In our studies, because we did not use littermate controls, it is possible that such vartiables could contribute to the changes we observed. Another limitation of this study is that we did not examine aged rats per se. Rats between the ages of 22-24 months would correlate better with the advanced ages at which people are diagnosed with idiopathic PD (Andreollo et al., 2012).

Another caveat is that we did not perform all behavioral tests at all multiple time points to determine if DJ-1 KO rats manifest aberrant behaviors. For example, we only performed the sucrose preference task at 9 months of age; however, DJ-1 KO rats could have developed anhedonia prior to or after that time point. We observed some different outcomes compared to the previous DJ-1 KO rat studies possibly due to differences in timing of behavioral testing, timing of measuring neuronal loss in the SNpc and LC, and differing behavioral tests performed

(Dave et al., 2014; Yang et al., 2018).

For the cognitive testing in particular, we only performed the novel/place preference tasks, but other more extensive cognitive testing, including, for instance, the Morris and

Cincinnati water mazes, may garner more information regarding the dysfunction occurring in DJ-

1 KO rats. For example, because of dysfunction in procedural memory in PD patients (e.g. Clark

244 et al., 2014), one study used a cued Morris water maze in the bilateral 6-OHDA rat model of PD to demonstrate impaired performance of procedural memory in the lesioned rats compared to controls (Tadaiesky et al., 2008). Another group used a bilateral 6-OHDA model to evaluate spatial working memory in a spatial memory-specific water maze task (Ferro et al., 2005).

Besides water tasks, the operant runway test has been used to show attentional deficits in rats with a unilateral 6-OHDA lesion (Dowd et al., 2005). Attentional deficits also were measured using both nine-hole operant chambers and the five-choice serial reaction time task in PD models (Baunez and Robbins, 1999; Courtiere et al., 2011). Other tasks used in PD rodent models include the T-maze and Y-maze using different testing paradigms to measure alternation, spatial discrimination, and reversal learning (Taghzouti et al., 1985; Braga et al.,

2005). With respect to the lack of effects of chronic stress (CVS) on the majority of behaviors evaluated in the mutant rats, our timing of CVS and how long after CVS we conducted behavioral testing could account for the some of the negative findings. The CVS regiment was only conducted at 8 months of age, whereas behaviors were measured as far out as 16 months, long after any CVS-induced alterations may have dissipated. It behooves us in the future to perform CVS and then immediately conduct several behavioral tests to potentially observe more robust effects. In addition, the CVS paradigm is also termed “chronic mild stress” in that the stressors are considered relatively mild; accordingly, the intensity of the stressors we employed may have been insufficient to elicit measurable changes in behavior. A caveat for the stereological assessment of microglia may be the fact that we only examined rats at 17 months of age. Although age does play a role in microglia activation, earlier time points may have revealed a transient difference in the number of activated microglia in select brain regions.

245

Future Studies/Conclusions

The work described in this dissertation provides a good start to establishing the DJ-1 KO rat as a useful model for the study of early-stage PD. Examination of monoaminergic neurotransmitter concentrations needs to be examined further in depth by using microdialysis, and by assessing pre- and post-synaptic expression of receptors pertinent to neurotransmission of NE and 5HT, to further expand the DJ-1 KO rat as a relevant PD model. We barely touched the surface when it comes to assessing how DJ-1 is causing these behavioral and cellular changes in these animals, and further assessment of DJ-1’s lesser known mechanisms will need to be conducted in these rats. Because of the robust cognitive change and lower NE concentration in the hippocampus, this model may be useful in studying the hippocampus and associated functions in PD. As stated previously, cognitive changes were usually assumed to be late-stage, mainly because histological studies found Lewy bodies in the neocortex only at the end stages of PD (Braak et al., 2003; Hawkes et al., 2010). However, the LC, a region that degenerates in PD, is the only source of NE to the hippocampus, and is vital to attention and memory functions. Cognitive changes are now recognized as occurring early on in PD, and using the DJ-1 KO rat model to understand cognition in PD would be vital to expanding our understanding of the disorder, and potentially uncovering an early indicator of PD. Ultimately, we envision use the model to better understand early manifestation and progression of PD, and to aid in discovering new therapies for the debilitating disorder.

246

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