THE EFFECTS OF DEVELOPMENTAL EXPOSURE TO THE ORGANOCHLORINE PESTICIDE DIELDRIN ON SUSCEPTIBILITY TO PARKINSON’S DISEASE By Sierra L Boyd A DISSERTATION Submitted to Michigan State University in fulfillment of the requirements for the degree of Pharmacology and Toxicology- Environmental Toxicology-Doctor of Philosophy 2023 ABSTRACT Parkinson’s disease (PD) is the fastest-growing neurological disease worldwide, with increases outpacing aging and occurring most rapidly in recently industrialized areas, suggesting a role of environmental factors. Exposure to the organochlorine pesticide dieldrin is a risk factor for sporadic PD. In a model of increased PD susceptibility, mice exposed to dieldrin during development show a male-specific increased susceptibility to MPTP (a dopaminergic (DAergic) toxicant) as adults, and adult male mice exposed to dieldrin during development show increased susceptibility to synucleinopathy induced by α- synuclein (α-syn) preformed fibrils (PFFs), with dieldrin-induced exacerbation of PFF-induced deficits in motor behavior and dopamine (DA) turnover. We hypothesize that dieldrin-induced epigenetic modification during development causes changes in gene expression and phenotype that persist into adulthood, altering the sensitivity to Parkinsonian insults and contributing to the development of PD. Specifically, we hypothesized that alterations in DA handling contribute to the observed changes and assessed vesicular monoamine transporter 2 (VMAT2) function and DA release in this dieldrin/PFF two-hit model. Using a developmental dieldrin/PFF two-hit model, vesicular 3H-DA uptake assays and fast-scan cyclic voltammetry (FSCV) were performed 4 months post-PFF injection. Dieldrin induced an increase in DA release in striatal slices in PFF-injected animals, but no change in VMAT2 activity. These results suggest that developmental dieldrin exposure increases a compensatory response to synucleinopathy-triggered striatal DA loss. These findings are consistent with silent neurotoxicity, where developmental exposure to dieldrin primes the nigrostriatal striatal system to have an exacerbated response to synucleinopathy in the absence of observable changes in typical markers of nigrostriatal dysfunction and degeneration. The epigenome is a potential mediator of this relationship between developmental exposures, increased neuronal vulnerability, and adult disease. In support of this, we recently identified sex-specific differential methylation patterns in response to developmental dieldrin exposure, suggesting exposure establishes a sex-specific poised epigenetic state early in life that modulates adult susceptibility to neurotoxicity. Candidate genes with developmental dieldrin-induced differential modification include Nr4a2, a transcription involved in DAergic development, and Ephb2, a receptor tyrosine kinase that regulates axonal guidance during neuronal development. Using a 3D human neurosphere model, we have shown that modification of these candidate genes during proliferation alters the DAergic trajectory of these neurospheres later in differentiation and modifies a key marker of DAergic vulnerability to toxicity. Suggesting that these observed epigenetic modifications to candidate genes, NR4A2 and EPHB2 during development alter the DAergic differentiation in developing neurons which may modify susceptibility to toxicity later in life. Overall, data from this project investigates mechanisms in which developmental exposure to dieldrin may induce functional changes in phenotype that alter Parkinson’s disease susceptibility. In loving memory of Richard A. Souser iv ACKNOWLEDGEMENTS I am filled with gratitude for the many individuals who have played a pivotal role in this journey. Foremost, my sincere thanks go to my advisor, Alison Bernstein, for her mentorship, and guidance over my project for the past four years. I am equally thankful to my co-advisor, Nick Kanaan, whose patience, flexibility, and guidance have greatly contributed to my academic growth. With support from my advisors, I have honed my bench techniques, cultivated project management skills, sharpened my critical thinking, and developed as a more resilient and adept scientist. I would also like to extend gratitude to my committee members, Caryl Sortwell, Colleen Hegg, and Cheryl Rockwell, whose insights and guidance have significantly shaped the trajectory of my thesis. I owe a profound thank you to my lab colleagues, both past and present, whose unwavering support has been the foundation of my graduate studies. I express my gratitude to Allyson Cole-Strauss, Joe Kochmanski, Nathan Kuhn, Mathew Benskey, Benjamin Combs, and Tessa Grabinski for their patience, encouragement, and willingness to share knowledge. I would also like to acknowledge the Translational Neuroscience Department and the Department of Pharmacology and Toxicology at Michigan State University for providing an enriching and collaborative environment for the pursuit of my degree. To my family and friends, I owe much gratitude for providing a supportive foundation and inspiring me to persevere in the face of challenges. Special mention goes to my sister, Michelle Boyd, and my father, Robert Boyd, for demonstrating the traits of a curious and insightful scientist. My mother, Carla Boyd, for her unconditional support, v patience, and encouragement throughout my life. Lastly, I express my greatest appreciation to my husband, Thomas O’Hara, whose unwavering support has been a constant throughout my undergraduate and graduate journey and beyond. Thank you for your everlasting support and encouragement. vi PREFACE At the time this dissertation was written, Chapter 2 was a published manuscript in the Journal of Toxicological Sciences. Chapters 3 and 4 are being prepared as separate manuscripts. All data for published figures for Chapter 2 are available in the Dryad Data Repository. GraphPad Prism files can be viewed in a free Viewer mode. R is freely available. All projects were preregistered using OSF Registries. Figures were created in BioRender. vii TABLE OF CONTENTS LIST OF ABBREVIATIONS ............................................................................................. x Chapter 1: Introduction .................................................................................................... 1 Parkinson’s disease: Overview .................................................................................... 2 Neuropathology ............................................................................................................ 4 Parkinson’s disease treatments ................................................................................... 8 Risk factors of Parkinson’s disease ............................................................................. 9 Environmental Risk Factors in Parkinson’s Disease .................................................. 16 Epigenetics ................................................................................................................ 19 Synaptic and vesicular integrity in Parkinson’s Disease ............................................ 24 Compensatory mechanisms in Parkinson’s disease .................................................. 30 Parkinson’s disease models....................................................................................... 35 Dieldrin ....................................................................................................................... 45 New approach methodologies .................................................................................... 55 Goals of the current research ..................................................................................... 60 REFERENCES .......................................................................................................... 63 Chapter 2: Developmental exposure to the Parkinson’s disease-associated organochlorine pesticide dieldrin alters dopamine neurotransmission in α-synuclein pre-formed fibril (PFF)-injected mice ............................................................................. 97 Abstract .................................................................................................................... 100 Introduction .............................................................................................................. 101 Methods ................................................................................................................... 106 Results ..................................................................................................................... 112 Discussion................................................................................................................ 116 REFERENCES ........................................................................................................ 128 Chapter 3: α-synuclein preformed fibrils do not seed aggregation or induce toxicity in LUHMES or SH-SY5Y 3D neurospheres .................................................................... 140 Abstract .................................................................................................................... 141 Introduction .............................................................................................................. 142 Methods ................................................................................................................... 148 Results ..................................................................................................................... 160 Discussion................................................................................................................ 166 REFERENCES ........................................................................................................ 174 Chapter 4: EPHB2 and NR4A2 regulate dopaminergic differentiation and markers of dopaminergic vulnerability in neurospheres, but not MPP+-induced toxicity................ 183 Abstract .................................................................................................................... 184 Introduction .............................................................................................................. 185 Methods ................................................................................................................... 190 Results ..................................................................................................................... 201 Discussion................................................................................................................ 216 REFERENCES ........................................................................................................ 233 viii Chapter 5: Conclusions ............................................................................................... 243 Overview .................................................................................................................. 244 Developmental dieldrin exposure primes the nigrostriatal system for an exacerbated response to synucleinopathy.................................................................................... 245 Failure to recapitulate the dieldrin/PFF two-hit model using in vitro 3D neurospheres model ....................................................................................................................... 249 Linking the role of developmental dieldrin-induced differentially modified candidate genes and the exacerbation of Parkinsonian toxicity ............................................... 250 Concluding Remarks ................................................................................................ 257 REFERENCES ........................................................................................................ 259 ix α-syn 5-HT 5mC 5hmC LIST OF ABBREVIATIONS α-Synuclein Serotonin 5-methylcytosine 5-hydroxymethylcytosine 6-OHDA 6-hydroxydopamine AADC AMPA COMT CpG D1R D2R DA DAergic DAT DNAMT DNT DOPAC DOPAL EPHB1 EPHB2 FBS FSCV L-aromatic amino acid decarboxylase α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid Catechol-O-methyltransferase Cytosine nucleotides before guanines Dopamine 2-like receptor Dopamine 1-like receptor Dopamine Dopaminergic Dopamine transporter DNA methyltransferases Developmental neurotoxicity 3,4-Dihydroxyphenylacetic acid Dihydroxyphenylacetaldehyde Ephrin type-B-receptor 1 Ephrin type-B-receptor 2 Fetal bovine serum Fast scan cyclic voltammetry x GABA GBA1 GPe GPi GWAS HSPG HVA iPSC L-DOPA LB LRRK2 LUHMES MAO MPP+ MPTP NAC NE NAM NAc NGS NMDA NR4A2 Nurr1 Gamma-aminobutyric acid Glucocerebrosidase Globus pallidus externus Globus pallidus internus Genome-wide association study Heparan sulfate proteoglycan Homovanillic acid Induced pluripotent stem cells Levodopa Lewy body Leucine rich-repeat kinase 2 Lund University Human Mesencephalic Cells Monoamine oxidase 1-methyl-4-phenyl pyridinium 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine Non-amyloid-β-component Norepinephrine New approach methodologies Nucleus accumbens Normal goat serum N-methyl-D-aspartate Nuclear receptor subfamily 4 group A member 2 Nuclear receptor related-1 xi OC pSyn PD PBDEs PCBs PFF PFOS PINK1 POP ROS SNP SDS SN SNpc STN TBS Organochlorine Phosphorylated α-Synuclein Parkinson's Disease polybrominated diphenyl ethers polychlorinated biphenyls Pre-formed fibrils Perfluorooctane sulfonic acid Phosphatase and tensin homolog-induced putative kinase 1 Persistent organic pollutant Reactive oxygen species Single nucleotide polymorphism Sodium dodcyl sulfate Substantia nigra Substantia nigra pars compacta Subthalamic nucleus Tris-buffered saline TBS-Tx Tris-buffered saline-Triton-X TEM TET TH VTA VMAT2 VSP35 Transmission electron microscopy Ten eleven translocase Tyrosine hydroxylase Ventral tegmental area Vesicular monoamine transporter 2 Vacuolar protein-sorter-35 xii Chapter 1: Introduction 1 Parkinson’s disease: Overview Demographics Parkinson’s disease (PD) is the most common movement disorder, the second most common neurodegenerative disease, and the fastest-growing neurological disorder worldwide (Dorsey et al. 2007). The primary risk factor for PD is age with an incidence of 47-77 per 100,000 for 45–65-year-olds and 108-212 per 100,000 in the population over 65 years of age (Willis et al. 2022). The prevalence of PD is continuing to rise, and the number of people with PD is expected to double between 2005 and 2030 (Dorsey et al. 2007). Only 5-10% of PD cases are caused by monogenically inherited mutations; the remaining large majority of sporadic (or idiopathic) cases are caused by a complex combination of genetic and environmental factors (Pang et al. 2019) Supporting a role of environmental factors, the greatest increases in PD prevalence are occurring in recently industrialized regions, consistent with a link between compounds associated with industrialization and PD risk (Dorsey et al. 2007). Clinical symptoms PD is clinically defined by the cardinal motor symptoms which include bradykinesia or slowed movements, rigidity, resting tremor, and postural instability (Postuma et al. 2015; Postuma et al. 2016). While diagnosis typically occurs after the onset of motor symptoms, it is thought that disease progression begins before these symptoms appear with a long prodromal phase. This prodromal phase precedes the onset of motor symptoms, often by decades, and is characterized by a range of nonmotor symptoms (Postuma and Berg 2016; Heinzel et al. 2019; Armstrong and Okun 2020). These include REM sleep behavior disorder and other sleep disorders, depression, anxiety, 2 constipation, and other gastrointestinal problems, olfactory loss, cognitive impairment, and autonomic dysfunction (Iranzo et al. 2021; Jo et al. 2021; Miglis et al. 2021; Zhang et al. 2022; Zolfaghari et al. 2022; Barone et al. 2023). Autonomic dysfunction can range from GI disturbances like constipation to urinary urgency, blood pressure variability, and orthostatic hypotension (Armstrong and Okun 2020). Sex differences Epidemiological studies suggest that there are sex differences for both the incidence and symptomology of PD, particularly for sporadic PD. In general, there is a higher prevalence of PD in males with a male-to-female ratio of 1.9 (Van Den Eeden et al. 2003). For males, there is 19.0 per 100,000 for an age-adjusted incidence rate, compared to 9.9 per 100,000 for females (Van Den Eeden et al. 2003). Women diagnosed with PD have a 26% lower risk of death compared to men (Schootman 2012). There are also some identified sex-specific differences in genetic risk factors in PD. For example, there is an increased prevalence of specific risk alleles and polymorphisms such as the apolipoprotein E4 allele, Monoamine Oxidase B (MAO-B) allele, and the Rs1113666 GAPDH polymorphism (Raheel et al. 2023). In females, there is a higher prevalence of mutations in the PD-associated gene Leucine rich-repeat kinase 2 (LRRK2) (Raheel et al. 2023). Variants of the LRRK2 mutations result in a sex- specific display of symptoms. For example, females with the G2385R variant tend to have a reduced risk of autonomic dysfunction, while males present a decreased risk of cognitive impairment (Raheel et al. 2023). In addition, both PD motor and non-motors symptoms present differently between male and female patients. Specifically, women tend to have less severe rigidity and similar 3 rates of resting tremor and bradykinesia, but higher rates of postural instability, depression, anxiety, sleep disorders, fatigue, pain, restless leg syndrome, tremor, and worse side effects in response to the PD therapeutic Levodopa (L-DOPA) (Scott et al. 2000; Shulman and Bhat 2006; Subramanian et al. 2022). Male patients with PD tend to present motor symptoms earlier and progress more rapidly compared to female patients (Scott et al. 2000; Shulman and Bhat 2006; Subramanian et al. 2022). Neuropathology Two pathological hallmarks are required for a definitive PD diagnosis upon post-mortem analysis: the presence of Lewy bodies (LB) that contain α-synuclein (α-syn) and the loss of dopaminergic (DAergic) neurons in the substantia nigra pars compacta (SNpc). LBs are intracellular protein inclusions composed primarily of aggregated α-syn. In addition, up to 70 other proteins were identified in LBs, many of which are involved in phosphorylation, mitochondrial, lysosomal, autophagy, and microtubule pathways (Wakabayashi et al. 2007a; Power et al. 2017). Degeneration of DA neurons and the resulting loss of striatal DA underlies the primary motor symptoms through disruption of the basal ganglia. Degeneration of the nigrostriatal pathway In a healthy brain, the basal ganglia circuit is responsible for controlling motor movement through an interaction between the nigrostriatal pathway and the thalamocortical circuitry (Figure 1.1A). In a non-parkinsonian state, DAergic neurons from the SNpc innervate the striatum, and they activate both the direct and indirect pathways (Obeso et al. 2000; Mehler-Wex et al. 2006; Wu et al. 2012; Blandini 2014). In the direct pathway, inhibitory GABAergic neurons project from the striatum to the globus 4 pallidus internal (GPi), reducing the inhibition of the thalamus and further activating the motor cortex to initiate motor movements. In the indirect pathway, GABAergic neurons from the striatum inhibit the globus pallidus external (GPe) which activates inhibitory GABAergic neurons projecting to the subthalamic nuclei (STN) which inhibits the excitatory glutamatergic neurons in the STN. These STN neurons provide excitatory input to the GPi, resulting in more inhibition of the thalamus less activation of the motor cortex, and inhibition of motor movements (Figure 1.1A). Together, the direct and indirect pathways provide opposing signals for the control of movement. In PD, the nigrostriatal DAergic neurons degenerate leading to progressive loss of DAergic signaling to the striatum. Nigrostriatal terminals are significantly decreased and almost completely diminished in 4 years post-PD diagnosis (Kordower et al. 2013). The Figure 1.1. Basal ganglia circuitry. A) Basal ganglia circuitry in healthy individuals. B) Basal ganglia in individuals with Parkinson’s disease. Made in BioRedner. nigral cell bodies have also degenerated at this same time point but to a much lesser extent (approximately 50-90% loss). This suggests that nigrostriatal DAergic neuron 5 terminals innervating the striatum are lost before DAergic cell bodies of the nigra supporting the idea of the dying back hypothesis where dysfunction and the loss of striatal terminals precede loss of cell bodies (Kordower et al. 2013). This leads to decreased signaling through the direct pathway and increased signaling through the indirect pathway. Together, this produces reduced inhibition (via the direct pathway) and increased activation (via the indirect pathway) for the GPi and STN. This increased inhibitory output from the GPi and STN reduces activity in the thalamus and decreases thalamic activation of the motor cortex (Figure 1.1B). Thus, the net outcome of SNpc degeneration in PD is reduced activation of the motor cortex and impairment of motor control. (Obeso et al. 2000; Sharman et al. 2000; Mehler-Wex et al. 2006; Wu et al. 2012; Maiti et al. 2017; Blandini et al.; Riederer et al.). Lewy bodies For post-mortem diagnosis of PD, LBs must be found in DAergic neurons of SNpc, but the distribution of LBs is more widespread, particularly in other monoaminergic neurons, as well as other structures in both the central and peripheral nervous systems (Pollanen et al. 1993; Spillantini et al. 1997). The distribution and neuropathological staging of LB progression during PD were well described by Braak and others (Braak et al. 2003; Braak et al. 2004; Braak and Del Tredici 2017). During the preclinical phase before motor symptom onset, LBs are localized to the olfactory bulbs, dorsal motor nuclei in the vagal and glossopharyngeal nerves in the brainstem, pontine tegmentum (locus coeruleus, magnocellular nucleus of the reticular formation, and lower raphe nuclei). As motor symptoms begin to appear, LB neuropathology can be found in the pedunculopontine nucleus, the cholinergic 6 magnocellular nuclei of the basal forebrain, the SNpc, the hypothalamus, portions of the thalamus, and begins to appear in the mesocortex. In later stages of the disease, LB pathology extends into neocortical regions and may contribute to cognitive impairments observed in the latest stages of the disease (Braak et al. 2003; Braak et al. 2004; Braak and Del Tredici 2017). LBs have also been found in the peripheral nervous system in sciatic nerves, the enteric nervous system, and throughout the gastrointestinal system, including in the appendix (Beach et al. 2010; Gelpi et al. 2014; Killinger et al. 2018; Killinger and Labrie 2019). Alpha-synuclein protein α-syn is the major component of LBs (Spillantini et al. 1997; Spillantini et al. 1998). It is a 140 amino acid protein encoded by the gene SNCA that belongs to the synuclein protein family along with β- and γ-synucleins and is highly expressed in the human brain (Goedert 2001; Marques and Outeiro 2012; Bridi and Hirth 2018). α-syn contains 3 domains: the N-terminal amphipathic region, the hydrophobic non-amyloid-β component (NAC), and the C-terminal acid tail domain (Maries et al. 2003; Bridi and Hirth 2018). The N-terminal amphipathic region mediates binding to phospholipids with a preference for high curvature, resulting in α-syn localization to presynaptic and vesicular membranes (Middleton and Rhoades 2010; Jensen et al. 2011; Pranke et al. 2011; Busch et al. 2014; Xu et al. 2016). The 12 amino acids comprising the NAC domain of α-syn are the key mediators in α-syn aggregation (Biere et al. 2000; Lee et al. 2002; Lee and Lee 2002; Giasson et al. 2003; Jucker and Walker 2013; Jucker and Walker 2018). Notably, β-synuclein lacks the NAC region, and β-synuclein aggregation is not observed (Cheng et al. 2011). The C-terminal acidic tail domain is known to be 7 important in calcium binding, chaperone activity, and protection against oxidative stress and α-syn aggregation. (Kim et al. 2002; Park et al. 2002; Albani et al. 2004; Chandra et al. 2005; Cheng et al. 2011; Games et al. 2014; Chaari et al. 2016; Sharma and Priya 2017). In addition to α-syn, which is the major component of LBs, many other types of proteins and lipids were identified within LBs. LBs have a high lipid content, and this is likely because they contain high amounts of membrane-bound structures related to autophagosomes, lysosomes, and lipid membrane fragments (Goldman et al. 1983; Wakabayashi et al. 2007b; Beyer et al. 2009; Shahmoradian et al. 2019). Other components such as mitochondria, protein aggregates, cytoskeletal elements, and vesicles also contribute to LBs (Goldman et al. 1983; Wakabayashi et al. 2007b; Beyer et al. 2009; Shahmoradian et al. 2019). Parkinson’s disease treatments Currently, there are no disease-modifying therapies to delay or prevent the progress of PD (Armstrong and Okun 2020). However, there are several DA and non-DA-based therapies for the treatment of motor symptoms (Lee and Yankee 2022). Levodopa (L- DOPA) is the gold standard for PD therapy (Armstrong and Okun 2020; Lee and Yankee 2022). There are also nonselective DA agonists that are used to activate D1 and D2 receptors to treat motor symptoms (Armstrong and Okun 2020; Lee and Yankee 2022). Monoamine oxidase inhibitors including COMT inhibitors work to inhibit the metabolism of DA and L-DOPA (Lee and Yankee 2022). These therapeutics are used to increase DA levels, activate DA receptors, or inhibit the metabolism of DA to restore DA and improve motor symptoms of PD (Lee and Yankee 2022). In addition to DA therapies, 8 Anticholinergic pharmacological treatments have also been used to treat motor symptoms by reducing acetylcholine to treat tremors in PD. These therapies are choline receptor antagonists to restore the homeostasis between DA and acetylcholine which is disrupted in PD (Lee and Yankee 2022). More recently, these anticholinergic treatments have been largely replaced by L-DOPA or other dopaminergic agonist therapies (Armstrong and Okun 2020; Lee and Yankee 2022). Another treatment option for severe PD that is untreated by traditional pharmacological treatments is deep brain stimulation, which is an implant used to stimulate the basal ganglia via electrical stimulation (Lee and Yankee 2022). Deep brain stimulation can improve both motor and non-motor symptoms and can improve bradykinesia, tremor, and rigidity. However, deep brain stimulation is less effective at treating gait disturbances, balance, and speech impairments. Overall, pharmacological, and surgical treatments are used to diminish motor symptoms and some non-motor symptoms of PD. However, there are no available disease-modifying treatments for preventing or inhibiting the progression of the disease(Lee and Yankee 2022). Risk factors of Parkinson’s disease Age is the primary risk factor for PD, but there are several genetic and environmental risk factors for the disease (Zaman et al. 2021). Together, these factors implicate multiple molecular mechanisms of PD etiology including mitochondrial dysfunction, oxidative stress, protein aggregation, disrupted protein clearance, and neuroinflammation serving as intrinsic risk factors (Zaman et al. 2021). 9 Genetics Only 5-10% of PD cases are caused by inherited monogenic mutations, with the majority (>90%) of sporadic or idiopathic cases arising from a combination of genetic and environmental factors. Genetic cases of PD are caused by highly penetrant, rare mutations that follow Mendelian inheritance patterns. In contrast, sporadic cases are caused by the combination and interaction of common genetic polymorphisms with weak to moderate effect sizes and environmental exposures. Thus, there is a range of genetic variants underlying PD etiology from common polymorphisms with modest effects to rare highly penetrant variants (Blauwendraat et al. 2020). Autosomal dominant PD genes SNCA encodes α-syn, which, in addition to being the major component of LBs, is thought to play a role in regulating synaptic vesicles, synaptic plasticity, and regulating lipids (Steece-Collier et al. 2002; Shulman et al. 2011; Klein and Westenberger 2012). It is thought that α-syn is natively unfolded and can fibrillate to assume the β-pleated sheet conformation observed in LBs. While it remains unclear if the fibrils themselves, protofibrils, or other intermediates in the fibrilization pathway, or the loss of soluble α- syn are pathogenic in PD, the accumulation and aggregation of α-syn is a defining feature of most forms of PD. The most common α-syn point mutations, including A30P, A53T, A53E, E46K, H50Q, and G51D, are located in the N-terminal domain and are associated with early-onset PD (Bridi and Hirth 2018). Multiple mutations within the N-terminal domain and duplication or triplication of the SNCA locus can cause familial non-genetically inherited forms of PD, but mutations in SNCA are also associated with an increased risk of sporadic PD. 10 The autosomal-dominant A53T mutation can accelerate this fibrilization process. The missense mutation A30P accelerates the conversion of monomeric α-syn to oligomeric protofibril forms but does not play a role in the formation of fibrils (Conway et al. 2000). Both the A30P and A53T mutations induce neuronal toxicity by disrupting and permeabilizing cell membranes through pore-like formations (Steece-Collier et al. 2002). Duplication and triplication of the SNCA locus also cause familial PD and the severity of PD progression in these cases correlates with the number of copies of the SNCA locus (Lill 2016). PD cases caused by SNCA autosomal dominant mutations typically present with a similar clinical phenotype amongst all mutations with varying severity in SNCA multiplications. In the early stages, patients are L-DOPA responsive, however, over time L-DOPA loses effectiveness and patients experience severe rigidity and dementia. SNCA autosomal dominant cases present with widespread α-syn pathology in neurons and glia throughout the brainstem and cerebrum (Puschmann 2013). In addition to SNCA, there are several other autosomal dominant PD-causing genes. In the US and Europe, LRRK2 is the most commonly mutated gene in both familial and sporadic PD (Zimprich et al. 2004; Nuytemans et al. 2010; Funayama et al. 2023). LRRK2 has both kinase and GTPase functions. At least 6 pathogenic mutations in LRRK2 were identified, and the most common LRRK2 mutation is Gly2019Ser which was identified in 1% of idiopathic or sporadic PD cases and 4% in familial (Lill 2016). The clinical phenotype of LRRK2 familial PD is late-onset, L-Dopa responsive (Brice 2005). Interestingly, the pathological characteristics associated with familial LRRK2 PD vary dramatically even between family members. Specifically, some patients show typical PD-associated α-syn containing LBs, some show tau pathology, and other cases 11 do not present with any α-syn or tau pathology. However, nigrostriatal degeneration is prominent amongst almost all LRRK2 autosomal dominant cases (Brice 2005). Variants in the Vacuolar protein sorter-35 (VSP35) protein a confirmed causative of autosomal dominant PD (Lill 2016; Funayama et al. 2023). The function of the VPS35 protein is to facilitate the retrograde trafficking of proteins from endosomes to the trans- Golgi network, and the VPS35 variants are thought to result in disrupted vesicular formation, impaired autophagy, and lysosomal function (Lill 2016). The p.Asp620Asn variant was first identified in a Swiss family with late-onset autosomal dominant PD with incomplete penetrance (Sassone et al. 2021). PD cases with the p.Asp620Asn variant presented with a tremor-predominant, slowly progressive, and L-Dopa-responsive form of the disease. Other variants of the VPS35 have since been identified resulting in a similar clinical phenotype (Williams et al. 2017). Autosomal recessive PD genes Mutations in the Parkin gene are involved in early onset genetic forms of PD, in particular, Parkin from the PARK2 locus mutant carriers is the most common cause of juvenile forms of PD (Klein and Westenberger 2012). PARK2 encodes the Parkin protein, a ubiquitin-E3-ligase playing a role in ubiquitination and is recruited by the mitochondrial protein, phosphatase, and tensin homolog-induced putative kinase 1(PINK1) protein together promoting selective degradation of damaged mitochondria via mitophagy (Klein and Westenberger 2012; Konovalova et al. 2015). The most frequent autosomal recessive mutation is Parkin, and approximately 8.6% of patients diagnosed with early onset PD at the age of 50 or less have a Parkin mutation. PINK1 mutations 12 account for 3.7% of PD cases, the majority of mutations are nonsense or missense mutations(Lill 2016). The least common autosomal recessive gene associated with PD is DJ-1 which occurs in 0.4% of PD cases and is most commonly found with point or structural mutations, and Figure 1.2. Schematic showing PD genetic risk variants. Monogenic autosomal dominant mutations causing PD are listed in blue, and other autosomal recessive mutations are listed in purple and genetic risk variants are in green. Genes shown here are representative of the etiology of PD and does not include every gene, mutation, or variant. Made in BioRedner. deletions are rare (Lill 2016; Funayama et al. 2023). A more recently identified autosomal recessive gene, DNAJC6 encodes Auxilin, a clathrin-associated protein involved in vesicular trafficking associated with early onset. These autosomal recessive genes have an average age of onset of less than 30 years (Lill 2016). 13 Genetic Risk Factors for sporadic PD Candidate gene and genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with increased risk of PD (Lill 2016). A recent meta-analysis of GWAS studies from European ancestry samples identified 78 genomic regions and 90 independent genome-side risk signals associated with PD (Nalls et al. 2019). The recent meta-analysis by Nalls et al. found SNCA as one of the top hits (consistent with other GWAS) and some of the other top hits include LRRK2, glucocerebrosidase (GBA1), bone marrow stromal cell antigen 1, 3- methylcrotonyl-CoA Carboxylase subunit 1, Transmembrane Protein 175, and Microtubule-associated protein tau. Both LRRK2 and SNCA were identified as genetic risk variants for sporadic PD, and the same mutations can be monogenically inherited and can cause autosomal dominant PD (Satake et al. 2009; Simón-Sánchez et al. 2009). Homozygous GBA1 carriers develop the lysosomal disorder, Gaucher disease; both heterozygotes and homozygotes have an increased risk of PD. GBA1 is a lysosomal protein involved in protein clearance, specifically α-syn protein (Funayama et al. 2023). The risk of PD is higher in those homozygous and heterozygous making GBA1 a major risk factor for PD (Avenali et al. 2020). Tau protein the primary component of neurofibrillary tangles, a pathological hallmark in many forms of dementia, is occasionally found in postmortem brains with PD and can be found in up to 50% of cases with Lewy Body Dementia (Arima et al. 1999; Chin et al. 2020). Genetic risk factors alone are not causative of PD because these variants only show moderate association with PD. Genetic risk factors alone are not causative of PD because these variants only show moderate association with PD. Only a small portion of PD cases are 14 monogenically inherited, and the remaining proportion of PD cases is due to a combination of common genetic risk variants and environmental factors (Figure 1.2). Gene-Environment Interactions As mentioned above, only 5% of cases are due to monogenically inherited mutations. Therefore, interactions between these identified genetic risk factors that are common amongst the population must be interacting with environmental factors resulting in increased risk of the disease. Therefore, gene-environment interaction in PD must be studied to better understand this interaction (Lill 2016). A study completed by Hill-Burns et al. investigated to identify genes that interact with smoking (Hill-Burns et al. 2013). Using genome-wide interaction analysis in nicotine-exposed Drosophila and humans, the gene SV2C was identified as a gene-smoking interaction in PD. The SV2C gene encodes synaptic vesicle glycoprotein 2C which functions to regulate vesicle stability and trafficking. Nicotine has also been found to increase DA release from synaptic vesicles. Based on these results and the known functions of SV2C may play an important role in PD as a gene-smoking interactor (Hill-Burns et al. 2013). Another study by Hazma et al. identified GRIN2A as an interacting gene involved in coffee consumption and reduced risk of PD (Hamza et al. 2011). Here, a genome-wide association and interaction study was completed to test single nucleotide polymorphisms on the effect of smoking and PD risk. Here, the rs4998386 mutation in GRIN2A was identified as a top hit. The GRIN2A encodes the NMDA-glutamate receptor subunit which is involved in excitatory transmission and was shown to reduce excitotoxicity serving as neuroprotective (Hamza et al. 2011). Although these types of 15 studies are difficult to replicate, they do provide important insight into gene-environment interactions and their relevance in PD (Lill 2016). Environmental Risk Factors in Parkinson’s Disease Protective factors Meta-analysis results show that there are specific factors that serve as a protective factor, reducing the risk of PD. Specifically, it was shown that coffee intake, smoking, and alcohol reduce the risk of PD (Noyce et al. 2012). It has also been found that certain prescription drugs are negatively associated with PD such as calcium channel blockers and anti-inflammatory drugs (Noyce et al. 2012). Other lifestyle factors that are thought to be protective against PD include a diet low in dairy, diets with high antioxidant content, and high physical activity levels (Jiang et al. 2014; Yang et al. 2015; Talebi et al. 2022). Figure 1.3. Parkinson’s disease risk factors. Made in BioRedner. 16 Environmental risk factors In addition to this, head injury, constipation, mood disorders, and the use of beta- blockers were also found to be positively associated with PD. Specific environmental factors including rural living, farming/agriculture occupations, drinking well water, and use of pesticides are significantly associated with increased risk of PD (Noyce et al. 2012). Persistent organic pollutants Epidemiological studies show an association between exposure to persistent organic pollutants (POPs) and an increased risk of PD (Tanner and Langston 1990; Semchuk et al. 1992; Le Couteur et al. 1999; Priyadarshi et al. 2000; Ritz and Yu 2000; Tanner and Aston 2000; Priyadarshi et al. 2001; Ascherio et al. 2006; Brown et al. 2006; Steenland et al. 2006; Elbaz et al. 2009; Wirdefeldt et al. 2011; Caudle et al. 2012; Freire and Koifman 2012). POPs are a class of pollutants that include industrial chemicals polychlorinated biphenyls (PCBs), polybrominated diphenyl eithers (PBDEs), perfluorooctane sulfonic acid (PFOS), pesticides, and industrial by-products (Alharbi et al. 2018). POPs are known to bio-accumulate into the soil and lipid-rich tissues due to their lipophilic nature, low volatility, and slow degradation. Exposure to POPs can result in various effects on health such as hormonal disruption, cancer, cardiovascular disease, effects on the immune system reproductive harm, and neurological disease and disorders (Alharbi et al. 2018). Case-control studies along with many others have shown that there is an increased risk of PD with POP exposure (Weisskopf et al. 2010). 17 Industrial toxicants Industrial contaminants include a broad range of chemicals that can result in exposure via occupational or contaminated food products, and in recent years these chemicals have been linked to PD risk (Steenland et al. 2006; Caudle et al. 2012; Goldman 2014). Many classes of industrial compounds are thought to contribute to PD risk including organohalogens, PCBs, PBDEs, PFOS, metals, nanoparticles, trichloroethylene, and solvents (not all of which are POPs) (Caudle et al. 2012). PCBs have demonstrated a significant association with PD in both human and animal studies by inducing changes in oxidative stress, calcium homeostasis, and DA stasis. PBDEs are associated with PD risk in animal studies with similar mechanisms of action to PCBs. A variety of metals including iron, copper, manganese, lead, and mercury exposure have a significant association showing changes in oxidative stress, and metal-specific effects on α-syn fibrilization, DA homeostasis, mitochondrial dysfunction, or calcium homeostasis. Nanoparticles result in oxidative stress and signs of neuroinflammation in animal studies, but there is no reported association of these effects on humans currently. Solvents such as trichloroethylene, hexane, etc. have a significant association with PD based on both animal and human studies showing oxidative stress, mitochondria dysfunction, calcium homeostasis disruptions, and α-syn aggregation. Compounds associated with industrial manufacturing show a significant effect on PD risk by disrupting crucial processes in DAergic neurons. Pesticides Pesticide exposure is another major risk factor for idiopathic PD. Whereas, pesticides are known to contribute to PD, but are not considered a causative agent. Early research 18 focused on the pesticide paraquat because it shares structural similarities to MPP+ and results in similar toxicological effects. More recently, other pesticides such as maneb, dithiocarbmates, pyrethroids, rotenone, and organochlorines have also been studied as possible agents contributing to PD (Moretto and Colosio 2011). One such compound is dieldrin, an organochlorine pesticide that is associated with an increased risk of PD in both epidemiological and mechanistic studies resulting in almost a 2-fold increased risk of PD (Fleming et al. 1994; Corrigan et al. 1998; Corrigan et al. 2000; Kanthasamy et al. 2005; Hatcher et al. 2007; Weisskopf et al. 2010; Moretto and Colosio 2011). The genetic and environmental factors that contribute to PD converge at common mechanisms such as mitochondrial dysfunction, oxidative stress, and impaired protein degradation (Fleming 2017). Although monogenetic mutations only account for a small proportion of PD, the identified genetic risk variants from GWAS studies have identified hundreds of commonly occurring variants increasing the risk of PD (Nalls et al. 2019). Together genetic risk variants and environmental risk factors can interact synergistically to contribute to disease risk and progression (Steece-Collier et al. 2002; Bellou et al. 2016; Fleming 2017) (Figure 1.3). Epigenetics Epigenetics is defined as a set of mechanisms that regulate gene expression without modifying the DNA sequence itself and are meiotically and mitotically heritable in dividing cells (Berger et al. 2009; Dupont et al. 2009). Generally, epigenetics refers to a set of three major mechanisms: 1) histone modifications and the regulation of chromatin structure, 2) covalent modifications of DNA, and 3) non-coding RNA-mediated mechanisms that affect gene expression and/or the other epigenetic mechanisms 19 (Marques et al. 2011; Marques and Outeiro 2013). Epigenetic marks are sensitive to the environment and play a critical role in the regulation of gene expression; thus, they are thought to be a potential mediator of the relationship between genes, the environment, and disease (Bollati and Baccarelli 2010; Faulk and Dolinoy 2011; Allis and Jenuwein 2016; Cavalli and Heard 2019). DNA modifications One of the most well-studied epigenetic marks is the covalent modification of the fifth position of cytosine in DNA (5-methylcytosine, 5mC) by DNA methyltransferases (DNMTs) (Moore et al. 2013). More recently, further oxidation of 5mC to 5- hydroxymethylation (5hmC) by the ten-eleven translocase (Tet) family of enzymes was recognized as a critical epigenetic mark, particularly in stem cells and the brain Figure 1.4. DNA methylation biochemical pathway. Made in BioRedner. 20 (Tahiliani et al. 2009; Kriaucionis and Tahiliani 2014; Cheng et al. 2015; Rasmussen and Helin 2016; Parker et al. 2019; Shekhawat et al. 2021); Tahiliani et al., 2009) (Figure 1.4). Each of these marks has a distinct set of “writers” and “readers” that catalyze their generation and recognize these marks such that they play a critical role in the regulation of gene expression (Cheng et al., 2015). 5hmC is thought to be particularly important in the central nervous system and the response to neurotoxicants, where 5hmC is highly enriched with levels 10-fold higher than levels in stem cells (Cheng et al., 2015; Globisch et al., 2010; Kochmanski & Bernstein, 2020). Mounting evidence indicates that exposure to environmental toxicants is associated with epigenetic changes and altered trajectories of age-related epigenetic changes, particularly for DNA modifications (Baccarelli and Bollati 2009; Bollati and Baccarelli 2010; Faulk and Dolinoy 2011; Lardenoije et al. 2015; Lardenoije et al. 2018; Cavalli and Heard 2019). Of relevance to this dissertation, previous work has found that developmental dieldrin exposure results in differential DNA methylation on several genes (Joesph Kochmanski et al. 2019). DNA modifications occur most often on cytosine nucleotides before guanines (a CpG dinucleotide) (Moore et al. 2013; Kriaucionis and Tahiliani 2014). Approximately 70% of gene promoters are located within CpG islands and methylation of CpG islands and within promoters can result in stable silencing of gene expression. In the gene body, DNA methylation contributes to cell-specific gene expression and regulation (Moore et al. 2013). Th e role of 5hmC is yet unclear, however, there are high expression levels of 5hmC in the brain; there is a ten-fold increase in 5hmC expression in the brain as compared to embryonic stem cells (Kochmanski and Bernstein 2007; Cheng et al. 2015). In 21 transcriptionally active genes in neuronal tissue, 5mC expression is reduced, however, 5hmC is elevated in active genes. Epigenetic reprogramming DNA methylation is a vital part of mammalian development. Two rounds of epigenetic reprogramming during embryogenesis and gametogenesis occur to reset the zygote or germ cells for further differentiation (Bollati and Baccarelli 2010; Faulk and Dolinoy 2011; Smallwood and Kelsey 2012) (Figure 1.5). During gametogenesis, the genome- wide DNA methylation is erased in primordial germ cells. Following sex determination, there is an asymmetrical sex-specific re-methylation that occurs. After fertilization, a second wave of demethylation occurs. In the male embryo, methylation begins during meiosis and the epigenetic landscape is established before birth. However, in females, the primordial germ cells remain unmethylated and are later established with each estrous During global cycle. this, Figure 1.5. Epigenetic reprogramming in development. The y-axis shows relative DNA methylation levels. Th x-axis shows phases of development. The blue line represents the paternal genome. The pink represents maternal genome. The green dashed line represents imprinted genes. Early in gametogenesis, there is a universal demethylation followed by a sex-specific re-methylation. After fertilization ther is a symmetrical demethylation followed by re-methylation during embryogenesis. Made in BioRedner. 22 demethylation occurs across the genome except at imprinted genes (Kappil et al. 2015). Following fertilization, the paternal genome is demethylated rapidly, and the maternal genome is erased more slowly. With cell-lineage determination, DNA methylation is re- established in the developing embryo (Bollati and Baccarelli 2010; Faulk and Dolinoy 2011; Smallwood and Kelsey 2012). Due to the dynamics of the DNA methylation landscape, developmental periods are particularly sensitive to environmental influences and can mediate disease susceptibility. Developmental Origins of Health and Disease Hypothesis Exposure to various solvents, metals, and pesticides is involved in PD risk. Developmental exposure to these compounds may affect disease risk later in life (Heindel and Vandenberg 2015; Baird et al. 2017). The developmental origins of the health and disease hypothesis state that there are certain sensitive periods such as pre- and peri-natal periods that are exceptionally sensitive to environmental exposures that may impact disease trajectory later in life (Baird et al., 2017; Heindel & Vandenberg, 2015). Epigenetic mechanisms, such as DNA modifications contribute to this increased sensitivity to the environment during developmental phases. Epigenetics in PD It is thought that epigenetics play an important role in the development of PD since environmental factors are a major component of the etiology of PD, and epigenetic marks are sensitive to the environment (Tsalenchuk et al. 2023). Many studies have investigated the epigenetic effects of several environmental exposures in human PD. In summary, these studies have shown several differential DNA methylation marks in PD cases as a result of exposure to various factors including coffee consumption, vitamin 23 E, PD drugs, lead, organochlorine pesticides, organophosphate pesticides, heavy metals, manganese, and exercise (Reviewed Tsalenchuk et al. 2023). Epigenetic studies have shown that the SNCA gene may have differential epigenetic regulation in PD. Specifically, some studies have shown a reduction in SNCA methylation in the SN of PD patients (Jowaed et al. 2010; Matsumoto et al. 2010). Histone modifications resulting in SNCA silencing and histone deacetylase inhibitors have proven efficacy in neuroprotection against PD in several in vivo models (Kontopoulos et al. 2006; Outeiro et al. 2007; Kidd and Schneider 2010; Monti et al. 2010; Song et al. 2010; Jin et al. 2011; Kidd and Schneider 2011; Chen et al. 2012). Other PD-associated genes such as LRRK2 and Parkin have also been shown to have differential- epigenetic regulation in PD cases, many of which are related to differential regulation of micro-RNAs (Asikainen et al. 2010; Gehrke et al. 2010). Others have noted differential modification and variant expression of genes that function in the cycle of methylation and demethylation including DNA methyltransferase 1 and Ten-eleven- translocase-1 in PD patients (Desplats et al. 2011; Shu et al. 2019). These epigenetic modifications associated with environmental factors and PD-related genes show that epigenetic mechanisms are a crucial link between environmental exposures, PD risk genes, and the development of disease. Synaptic and vesicular integrity in Parkinson’s Disease The Dopaminergic synapse As discussed above, nigrostriatal degeneration is a pathological hallmark of PD and is thought to underly the motor symptoms of the disease. The main synapse that is lost when this pathway degenerates is the synapse of nigral DA neurons onto medium spiny 24 neurons in the striatum. Within the presynaptic terminal of these synapses, the vesicular packaging of DA into vesicles by type II vesicular monoamine transporter (VMAT2) serves two key functions: to package DA into vesicles for release into the synaptic cleft and to protect the cell from cytosolic DA. For DA release, the arrival of an action potential at the synaptic terminal triggers a calcium influx. Cytosolic calcium binds to synaptotagmin proteins on the vesicle to initiate vesicular fusion with the pre-synaptic membrane resulting in the release of vesicular contents into the synaptic space (Bellani et al. 2010). Synaptic DA can be cleared from the synapse via DAT on the presynaptic terminal and re-packaged into vesicles via VMAT2. Synaptic DA can bind to post-synaptic receptors including D1-like (D1R) and D2-like (D2R) or D2R located on the pre-synaptic membrane functioning as autoreceptors. The machinery of the DAergic synapse is essential for maintaining DA homeostasis, and disruption in the synaptic machinery can result in DAergic dysfunction. Cytosolic DA levels are primarily regulated by the transport of DA by the DAT and VMAT2. Synaptic vesicles within DA neurons also prevent DA oxidation and enzymatic breakdown of toxic metabolites by sequestering cytosolic DA in the acidic environment of the vesicle (Alter et al., 2013). When not readily packaged into vesicles, cytosolic DA can undergo enzymatic deamination or autoxidation to form harmful, reactive metabolites including H2O2, 3,4-Dihydroxyphenylacetaldehyde (DOPAL), DA quinones, 25 Figure 1.6. The dopaminergic synapse. Tyrosine is converted to L-DOPA by Tyrosine hydroxylase which is the rate limiting enzyme in DA syntehsis. L-DOPA is converted to DA by DOPA decarboxylase. DA is packaged into synpatic vesicles via VMAT2 which can bind to the membrane and release DA upon an action potential. Synaptic dopamine can bind to D1-like or D2-like receptors. D1 is a Gαs located on the post-synaptic terminal. D2 is a Gαi located on the post-synaptic terminal and the pre-synaptic terminal where it can function as an autoreceptors. Synaptic dopamine and the DA metabolite, DOPAC can be taken up by surrounding astrocytes and degraded to form the metabolites, HVA. Synpatic DA can also be taken up into the synaptic terminal via the DAT. Cytosolic dopamine can be autoxidized or enzymatically degraded into toxic metabolites. Synaptic dopamine and the DA metabolite, DOPAC can be taken up by surrounding astrocytes and degraded to form the metabolites, HVA. Made in BioRedner. and superoxide (Alter et al. 2013). When the ratio of DAT to VMAT2 increases, more DA can enter the pre-synaptic terminal via DAT, but there is less VMAT2 available to sequester cytosolic DA resulting in increased cytosolic DA and increased DA-related 26 toxicity. On the other hand, a decreased DAT: VMAT2 ratio would decrease the susceptibility to DA-related toxicity as less DA can enter the terminal via DAT, but more DA is capable of being sequestered by VMAT2. A lowered ratio of DAT: VMAT2 ultimately reduces cytosolic DA concentrations and lowers the potential for DA autoxidation and toxic metabolite formation (Miller et al. 1999)(Figure 1.6). The functions of α-synuclein at the synapse α-syn is primarily found in neurons and plays a role in many neuronal functions including regulation of synaptic transmission, mitochondrial homeostasis, gene expression, protein phosphorylation, and fatty acid binding. Within neurons, α-syn is primarily localized in presynaptic terminals where it interacts with synaptic vesicles, suggesting that α-syn is involved in regulating DA neurotransmission and homeostasis (Perez et al. 2002; Yavich et al. 2004a). α-syn was found to interact with almost all the proteins involved in DA synthesis and handing. In multiple studies, a-syn was shown to inhibit tyrosine hydroxylase (TH) activity and DA synthesis, modulate DAT activity and localization, and increase the amount of VMAT2 on vesicles, (Bellani et al., 2010; Bridi & Hirth, 2018; Cheng et al., 2011; Roy, 2017; Venda et al., 2010). α-syn is a negative regulator of TH activity and DA synthesis. Overexpression of α-syn inhibits TH activity, whereas downregulation of α-syn enhances TH activity and DA synthesis (Cheng et al. 2011). It is suggested that α-syn may bind to the serine residues in the N-terminus of TH when TH is in a dephosphorylated state and preventing TH phosphorylation or activation, therefore reducing TH activity (Cheng et al. 2011). In addition to regulating DA synthesis, α-syn is thought to facilitate synaptic transmission by maintaining and regulating vesicle trafficking and mediating vesicular docking and 27 exocytosis (Larsen et al. 2006; Mosharov et al. 2009; Scott and Roy 2012a; Choi et al. 2013; Vargas et al. 2014; Wang et al. 2014). Monomeric α-syn reversibly binds and interacts with vesicle membranes and maintains recycling pool vesicles in primary neuronal culture. Consistent with this, α-syn null mice show decreased DA stores (Davidson et al. 1998; Abeliovich et al. 2000; Scott and Roy 2012b). α-syn also mediates synaptic vesicle clustering in the presynaptic terminal in a Ca2+-dependent manner. Treatment with DA exacerbates synaptic clustering of synaptic vesicles only (Burré et al. 2014) Overall, physiologically normal α-syn plays an important role in mediating synaptic vesicle clustering and inducing the SNARE complex formation resulting in the regulation of neurotransmitter release (Burré et al., 2014; Cabin et al., 2002; Choi et al., 2013; Diao et al., 2013; Fouke et al., 2021; V. Gao et al., 2023; Gaugler et al., 2012; Lautenschläger et al., 2018; D. Scott & Roy, 2012; Vargas et al., 2014; L. Wang et al., 2014; Yavich et al., 2004a). α-syn regulates DA synthesis by interacting with the enzymes TH and L-aromatic amino acid decarboxylase (AADC) modulating the synthesis of DA (Peng et al. 2005; Tehranian et al. 2006; Rietdijk et al. 2017). Mice with α-syn null mutation (loss of function mutation) display an increased rate of vesicular refilling, but stable DA release upon repeated electrical stimulations compared to mice with normally expressed α-syn (Yavich et al. 2004). On the other hand, overexpression models of α-syn results in reduced DA release, reduced size and density of the recycling pool, and altered organization of synaptic vesicles (Larsen et al. 2006; Nemani et al. 2010). 28 Dopamine-α-synuclein cycle DA and α-syn can both result in neurotoxic byproducts themselves, and they also feed into a circle of neurotoxicity where DA and α-syn interact and exacerbate the toxic effects of each other (Venda et al. 2010; Roy 2017). Cytosolic DA levels must be closely maintained in DAergic neurons. If not properly maintained, cytosolic DA can be autoxidized or enzymatically degrading forming toxic intermediates that can be detrimental to the integrity and function of DAergic neurons (Alter et al. 2013; Wong et al. 2019). The function of α-syn is closely tied to maintaining synapses, specifically vesicular trafficking and neurotransmitter packaging, synthesis, and release (Venda et al. 2010; Roy 2017). Therefore, if α-syn expression or function is altered, this will result in effects on DA handling. Since DAergic synapses are tightly regulated, a change in α-syn could result in disrupted DA release, packaging, synthesis, and cytosolic DA concentrations (Alter et al. 2013; Wong et al. 2019). On the other hand, changes in DA signaling can also mediate effects on α-syn. DA mishandling resulting in increased DA autoxidation Figure 1.7. Interactions between dopamine and α-synuclein. Made in BioRedner. 29 and toxic intermediates can induce oxidative damage on α-syn which could affect α-syn folding and aggregation. Therefore, this interaction between DA and α-syn is crucial for maintaining properly functioning DA synapses (Roy 2017) (Figure 1.7). Compensatory mechanisms in Parkinson’s disease Compensatory changes in the nigrostriatal system in DA are defined by increases in DAergic activity including DA release, DA turnover, DA uptake, and TH activity following PD-related degeneration (Hornykiewicz 1966; Bernheimer et al. 1973; Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Liang and Jiang 1991; Zigmond et al. 1993; Moore and Zigmond 1994; Bezard and Gross 1997; Zigmond 1997; Zigmond et al. 1998; Bezard et al. 2001; Bustos et al. 2004; Blesa et al. 2017; Bezard and Gross). Early compensatory changes in the nigrostriatal system that precede neurotoxicity and degeneration are well-documented in human PD, multiple animal models of PD, and most recently reported in a norepinephrine deficit model (Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Zigmond et al. 1993; Moore and Zigmond 1994; Zigmond 1994; Bezard and Gross 1997; Zigmond 1997; Zigmond et al. 1998; Molina-Mateo et al. 2017; Iannitelli et al. 2023). These compensatory mechanisms were observed in multiple neurotransmitter systems. Early compensatory increases in DA precede DA dysfunction and degeneration In both the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 6- hydroxydopamine (6-OHDA), which are neurotoxicants that are extensively used to model DAergic loss and degeneration, there appears to be an early compensatory increase in many aspects of the nigrostriatal system that precedes DA loss and DA 30 neuron death (Onn et al. 1986; Zhang et al. 1988; Graham et al. 1990; Snyder. GL et al. 1990; Liang and Jiang 1991; Alexander et al. 1993; Zigmond et al. 1993; Rozas et al. 1998; Bezard, Dovero, Prunier, Ravenscroft, Chalon, Guilloteau, Alan R Crossman, et al. 2001). A model of DAergic depletion via MPTP in non-human primates showed an upregulation of TH immunoreactive neurons in the striatum by 3.5-fold compared to controls, which may show that nigrostriatal neurons are capable of compensation (Betarbet et al. 1997). In a rat striatal slice lesioned with 6-hydroydopamine, there are significant increases in stimulation-induced DA release compared to controls suggesting that remaining striatal terminals compensate for 6-OHDA-induced depletion of DA neurons (Snyder. GL et al. 1990). In rats lesioned with 6-OHDA, there is an increase in the presence of striatal DA terminal 4 months post-lesion compared to immediately after lesion as well as increases in levels of TH, DA, and 3,4-Dihydroxyphenylacetic acid (DOPAC) content compared to control rats (Onn et al. 1986). In 6-OHDA lesioned rats at 1-month post-lesion, there was only a 17.2% increase in DA content suggesting that the remaining striatal terminals likely undergo compensatory physiological changes to increase synthesis and release of DA (Onn et al. 1986) These findings are consistent with other monoaminergic models, including norepinephrine (NE), which shares similar synaptic machinery to DA neurons. In a model of NE degeneration in the locus coeruleus, there are significant increases in NE turnover and signaling as well as behavioral phenotypes despite the loss of NE neurons (Iannitelli et al. 2023). This increase in DA activity that precedes DA loss and degeneration may be due to the regulation of DA receptors. In the MPTP model of DAergic degeneration, there is an early upregulation of the D2R binding in striatal neurons which occurs only at a time 31 point before the most severe motor deficits (Bezard et al. 2001). D2R density in the striatum was shown to increase in a variety of models of DA depletion (Graham et al. 1990; Alexander et al. 1993; Decamp et al. 1999; Aubert et al. 2005; Chefer et al. 2008; Sun et al. 2013; Blesa et al. 2017). Serotonergic signaling Some research suggests that an upregulation of serotonergic innervation in the striatum may play a role in these compensatory increases in DA signaling (Zhou et al. 1991; Gaspar et al. 1993; Rozas et al. 1998; Maeda et al. 2003; Mounayar et al. 2007; Gagnon et al. 2016; Blesa et al. 2017; Wile et al. 2017). In differentiated PC12 cells, dieldrin exposure increased tryptophan hydroxylase transcript expression, the rate- limiting step in serotonin (5-HT) synthesis, and a decrease in expression of genes related to 5-HT storage, degradation, and several 5-HT receptors (Slotkin and Seidler 2008). Most of the 5-HT-containing neurons are in the raphe nuclei which make projections throughout the basal ganglia, including the SNpc and the striatum (Di Matteo et al. 2008). Striatal increases in 5-HT concentrations were shown to facilitate DA release from nigrostriatal neurons in a variety of rat microdialysis studies (Blandina et al. 1989; Bonhomme et al. 1995; De Deurwaedere et al. 1996; Reed et al. 2013). Serotonergic projection in the striatum has also been implicated in PD, specifically in the context of L-DOPA treatment and facilitating L-DOPA-induced dyskinesias since 5-HT neurons are capable of storing and releasing DA (Carta et al. 2007; Reed et al. 2013). Models of DA depletion induced by 6-OHDA and MPTP in several animal models including neonatal and adult rats as well as adult non-human primates show sprouting of serotonergic neurons innervating the striatum post-lesioning (Zhou et al. 1991; 32 Gaspar et al. 1993; Karstaedt et al. 1994; Rozas et al. 1998; Maeda et al. 2003; Mounayar et al. 2007; Gagnon et al. 2016; Pagano et al. 2018; Jiménez-Sánchez et al. 2020). Glutamatergic signaling Evidence suggests glutamate signaling is likely involved since glutamatergic signaling regulates DA synthesis and release via N-methyl-D-aspartate (NMDA) receptors in the SN forming a negative feedback loop (Zigmond 1994; Bustos et al. 2004). In line with this, glutamatergic synapse remodeling and altered vesicular glutamate transporter were observed in animal models of PD and postmortem PD brains (Smith et al. 2009; Villalba et al. 2015; Villalba and Smith 2018). In differentiated PC12 cells, treated with dieldrin, there is a significant increase in transcript expression relating to glutamatergic signaling (Slotkin and Seidler 2009). These results in PC12 paralleled the effects of the organophosphate, chlorpyrifos, which is known to exert toxic effects by promoting excitotoxicity (Slotkin and Seidler 2009; Rush et al. 2010). Dieldrin-treated cells resulted in a significant increase in genes encoding for ionotropic receptors in response to dieldrin such as gria1 (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) 1), grin1 (NMDA 1), and grina (NMDA-associated protein) (Slotkin and Seidler 2009). Ionotropic receptors such as NMDA and AMPA are thought to contribute to excitotoxicity because they are ligand-gated ion channels permeable to Ca2+, a driver of oxidative stress and cell death (Dong et al. 2009). It has also been proposed that enhanced sub- thalamic nucleus signaling observed in PD could result in exacerbated glutamatergic signaling in surviving DA neurons which results in excitotoxicity (Sharman et al. 2000; 33 Obeso et al. 2004; Mehler-Wex et al. 2006; Wu et al. 2012; Blandini et al.; Riederer et al.). Excitotoxicity In the basal ganglia, GABAergic neurons from the striatum innervate structures in the indirect pathway and ultimately serve as a negative regulator to glutamatergic neurons that play a role in initiating signaling to the motor cortex to control motor movements (Obeso et al. 2000; Wu et al. 2012; Maiti et al. 2017; Blandini et al.; Riederer et al.). The upregulation of glutamatergic signaling promotes excitotoxicity by activating the glutamatergic NMDA receptor, which can also promote Ca2+ overabundance (Caudle and Zhang 2009; Ambrosi et al. 2014; Blandini 2014; Wang et al. 2020). High levels of Ca2+ in the mitochondrial or cytoplasm can result in the formation of reactive oxygen species (ROS) and reactive nitrogen species which can induce mitochondrial dysfunction (Ambrosi et al., 2014; Post et al., 2018). Elevated levels of ROS impair ATP production by inhibiting the function of several steps in the mitochondrial electron transport chain and overall excitotoxicity. Ca2+ overabundance can also activate pro- apoptotic factors and open the mitochondrial permeability transition pore leading to the release of cytochrome C and neuronal death (Ambrosi et al. 2014). Excitotoxicity was an observed factor contributing to PD-related pathogenesis. Degeneration of nigrostriatal DAergic neurons disinhibition to the STN which promotes hyperexcitation of glutamatergic neurons projecting from the STN to the GPe, GPi, and SNpc (Rodriguez-Farre and Suñol 1995; Bezard and Gross 1998; Caudle and Zhang 2009; Blandini 2014). Understanding DA-related compensatory mechanisms provides important insight into ways in which development exposures may induce lasting 34 changes in synaptic function in DAergic nigrostriatal neurons. A variety of PD models were instrumental in studying many of the potential mechanisms underlying PD-related compensatory DA responses. Parkinson’s disease models Genetic models Many genetic models of PD target genes linked to familial, monogenic forms of the disease including SNCA, LRRK2, DJ-1, PINK1, and PRKN (Shimohama et al. 2003; Blandini and Armentero 2012; Blesa et al. 2012; Jagmag et al. 2016). Due to the central role of α-syn in PD, many models were made targeting SNCA (Lill 2016). These include a range of α-syn overexpression models or models that express the mutant form of α- syn, including the disease-linked mutations A53T, A30P, and E46K. Nigrostriatal degeneration, Lewy-like inclusions, and motor impairments are inconsistent among these α-syn models and few show all three of these features (Shimohama et al. 2003; Blandini and Armentero 2012; Blesa et al. 2012; Jagmag et al. 2016). These models are variable in how closely they mimic important aspects of the disease, but few show nigrostriatal degeneration, α-syn pathology, and motor impairments. The A53T mutant mice produce inclusions resembling LBs, and motor impairment, but generally do not produce overt nigrostriatal loss. The A30P mouse model produces LB-like inclusions, does not produce nigrostriatal degeneration, and some studies have shown motor impairments, but this seems to be promoter-specific. Expressing an E56K α-syn transgene inserted into the ROSA26 locus did not produce α-syn inclusions, nigrostriatal degeneration, or motor impairments (Shimohama et al. 2003; Blandini and Armentero 2012; Blesa et al. 2012; Jagmag et al. 2016). In LRRK2 mouse models, it was reported 35 that the R1441G and R1441C variants produce motor impairments, but no effects on PD hallmarks (Nuytemans et al. 2010; Jagmag et al. 2016). However, The G2019S variant was shown to induce nigrostriatal loss and variable effects on motor phenotypes, but no formation of LB-like inclusions. However, exon 1, 29, and 30 of LRRK2 have resulted in inclusion formation (Nuytemans et al. 2010; Jagmag et al. 2016). Only a few Parkin exon deletion models have shown significant motor impairments. DJ-1 exon 2 deletion and exon 7 inactivation models show motor impairments, but no PD-like pathology (Jagmag et al. 2016). Only a few of these genetic models result in PD- associated pathology and motor impairments, and many of the results are variable between promoters used and between research groups. A transgenic model that successfully recapitulates many of these key aspects of PD is the VMAT2LO mouse model that expresses ∼5% of normal VMAT2 levels (Caudle et al. 2007; Miller et al. 2011; Alter et al. 2013; Lohr et al. 2016). VMAT2LO mice display age- associated nigrostriatal dopamine degeneration, increased accumulation of α-syn, progressive non-motor, and L-DOPA-responsive motor deficits, and extranigral monoaminergic dysfunction and degeneration (Caudle et al. 2007; Miller et al. 2011; Alter et al. 2013; Lohr et al. 2016). Neurotoxicant models In addition to genetic models, toxicant models that induce DAergic loss and degeneration were developed. Classic toxicant models include (6-OHDA), (MPTP), rotenone, and paraquat (Jagmag et al. 2016). 6-OHDA is a metabolite of DA that was used to model certain aspects of PD (Blesa et al. 2012). Due to the resemblance of DA, 6-OHDA is a substrate for several catecholaminergic transporters including the 36 norepinephrine transporter and DAT allowing its entry into DAergic and noradrenergic neurons (Martin et al. 1976; Blesa et al. 2012). Once in the neuron, cytosolic 6-OHDA accumulates and undergoes auto-oxidation inducing the formation of reactive oxygen species, catecholamine quinones, and hydrogen peroxide resulting in oxidative stress and degeneration of affected neurons (Simola et al. 2007; Jagmag et al. 2016). 6-OHDA must be stereotactically injected directly into the SNpc, medial forebrain bundle, or the striatum because it is hydrophilic and will not cross the blood-brain barrier (Simola et al. 2007; Jagmag et al. 2016) (Jagmag et al. 2016). Injection of 6-OHDA results in unilateral degeneration of DAergic and noradrenergic projections, depending on the injection site, resulting in motor impairments including dyskinetic limb movements, and asymmetrical rotation induced by DA-releasing agents like amphetamine. However, 6- OHDA models do not produce Lewy-like aggregates (Luthman et al. 1989; Simola et al. 2007; Blandini et al. 2008; Jagmag et al. 2016). MPTP and its active metabolite, 1-methyl-4-phenylpyridinium (MPP+), were widely used as in vivo and in vitro models of PD, respectively. The MPTP model is often used to study the effects of DAergic depletion because of its robust ability to deplete striatal DA and lesion nigrostriatal neurons (Blesa et al. 2012; Blesa and Przedborski 2014; Jagmag et al. 2016). MPTP is not neurotoxic itself but can enter the brain where it is metabolized by MAO-B in astrocytes to MPP+ (Jagmag et al. 2016). MPP+ is selectively toxic to DAergic neurons because of its high affinity for the DAT and significantly lower affinity to other monoaminergic transporters. In the cytosol, MPP+ can be sequestered via VMAT2 into synaptic vesicles or it can concentrate in the mitochondria (Rarnsaysb and Singers 1986). MPP+ is a mitochondrial complex 1 inhibitor and is thought to kill 37 DAergic cells by inhibiting ATP production and stimulating superoxide radical formation (Jagmag et al. 2016). While MPP+ can affect all DAergic neurons throughout the brain, neurons in the SNpc are more susceptible than DA neurons in the ventral tegmental area, mimicking selective vulnerability seen in PD (Varastet et al. 1994; Blesa et al. 2011; Blesa et al. 2012). A wide range of animal models using MPTP were developed. In these models, MPTP is given by several different routes, including oral gavage, various types of injections, and direct stereotaxic injection into the brain. Compared to 6-OHDA, a benefit of the MPTP model is that can be administered systemically due to its lipophilicity. Dosing paradigms also vary by dose, duration, and frequency of administration. One of the most common, reliable, and reproducible lesions is caused by its systemic sub-cutaneous or intraperitoneal administration. In general, MPTP does not induce α-syn aggregation in rodents, and α-syn pathology has only been observed in some non-human primate MPTP models (Jackson-Lewis and Przedborski 2007; Blesa et al. 2012). Similarly, motor impairments are typically present in non-human primates MPTP models but less apparent in mice. Due to the lack of astrocytes in many cell culture models, the active metabolite MPP+ is used as an in vitro model of PD since MPTP in vivo is metabolized by MAO-B in astrocytes. In cells expressing DAT, MPP+ induces robust degeneration by entering the cell via DAT and inhibiting complex 1 of the electron transport chain (Lopes et al. 2017). MPP+ is an established model of DAergic degeneration in a variety of cell models including primary dopamine cultures from mice and rats, organotypic slice cultures, induced pluripotent stem cells (iPSCs), and cell lines including Lund University Human 38 Mesencephalic Cells (LUHMES), SH-SY5Y, MN9D, PC12, and N27 cells (Lopes et al. 2017). N′-dimethyl-4,4′-bipyridinium dichloride (paraquat) is one of the most widely used herbicides worldwide and was developed into a PD model (Tanner et al. 2011; Jagmag et al. 2016). Due to paraquat’s apparent structural similarity to MPTP and DA, it was thought that paraquat similarly induces degeneration via DAT-mediated uptake, but this mechanism was called into question (Richardson et al. 2005; Miller 2007). However, paraquat does cross the blood-brain barrier, enter DAergic neurons, induce reactive oxygen species, oxidative stress, and eventually neurodegeneration via a non-DAT- mediated mechanism (Richardson et al. 2005; Miller 2007). In mice, direct injection into the brain produces more consistent toxicity than systemic administration, which does not yield consistent results. While injection of a strong oxidant directly into nigral neurons produced degeneration of these cells, it remains controversial whether or not this model is toxicologically relevant to human PD (Miller 2007). Rotenone is a naturally occurring compound, occurring in several species of plants, that is used as an insecticide (Betarbet et al. 2000; Tanner et al. 2011; Jagmag et al. 2016). Like MPP+, rotenone is a mitochondrial complex 1 inhibitor that can easily enter the brain. Chronic systemic administration in rodents results in a slow and selective degeneration of nigrostriatal DAergic neurons, Lewy-like aggregates, and PD-like motor impairments. Because rotenone is lipophilic and can cross the blood-brain barrier, it can be administered systemically without a need for stereotaxic injection. However, rotenone exposure is associated with high mortality rates, making it difficult to replicate as a PD model (Tanner et al. 2011; Jagmag et al. 2016). 39 Most neurotoxicant models produce rapid degeneration failing to mimic the protracted course of the disease. There is also a lack of consistency and often a lack of formation of LB-like inclusions. In models where LB-like inclusions are formed, this is often due to supraphysiological levels of oxidative stress. Therefore, these neurotoxicant models can be used for studying DAergic degeneration and the effects of DA loss but are not ideal for investigating environmental exposures in PD as well as the pathogenesis of sporadic PD (Blesa et al. 2012). Alpha-synuclein pre-formed fibril model of PD Many PD therapeutics fail clinical trials partly because the PD models used during in vivo testing fail to model the key pathological hallmarks of the disease (Jagmag et al. 2016). Therefore, new work was aimed at improving PD models by reproducing both nigrostriatal degeneration and Lewy bodies. More recently, the α-syn pre-formed fibrils (PFFs) model of PD was used to mimic both synucleinopathy and DAergic degeneration (Luk et al. 2012; Paumier et al. 2015; Patterson et al. 2019). Unlike other models, such as 6-OHDA and MPTP, the PFF model recapitulates the slow progression of PD, the pathological hallmarks, and PD-like motor deficits (Luk et al. 2012; Paumier et al. 2015; Patterson et al. 2019). In the PFF model, recombinant α-syn monomers are used to form α-syn PFFs through a 7-day fibrilization process. Before use, α-PFFs are sonicated to form ~50 nm fragments, which is the optimal length for seeding α-syn inclusions. When PFFs are injected into rodent brains or applied to cell cultures, they are taken up into synaptic terminals. Within the synaptic terminal, they seed the formation of soluble, endogenous α-syn into insoluble phosphorylated inclusions that resemble Lewy-bodies in that they are 40 proteinase-K resistant, contain amyloid structure, are ubiquitinated, detergent-insoluble, and contain α-syn phosphorylated at serine 129 (pSyn) (Volpicelli-Daley et al. 2011; Luk et al. 2012). Eventually, this leads to neuronal dysfunction and degeneration within the context of normal physiological levels of endogenous α-syn. SNCA knock-out animals are also not susceptible to PFF-induced pathology, indicating that PFFs mechanisms of action are through the recruitment of endogenous α-syn (Luk et al. 2012). The mechanisms by which α-PFFs enter cells are not fully understood, but some evidence suggests they are internalized via endocytosis, micropinocytosis, and/or tunneling nanotubules (Valdinocci et al. 2017). Internalized α-syn PFFs were found to colocalize with markers of early endosomes like Rab5 suggesting PFF uptake via endocytosis potentially mediated by clathrin/dynamin-1 (Eisbach and Outeiro 2013; Bieri et al. 2018). Early studies suggested that lymphocyte-activation gene 3, which is a member of the immunoglobulin superfamily of receptors with known functions as an inhibitory receptor on T-cells may mediate PFF uptake via receptor-mediated endocytosis, but more recent studies found that lymphocyte-activation gene 3 is not expressed in human or murine neurons (Emmenegger et al. 2021). Another potential mechanism for PFF uptake is through micropinocytosis, an actin- dependent mechanism that facilitates membrane ruffling mediated by the cell surface marker, heparan sulfate proteoglycan (HSPG) (Valdinocci et al. 2017; Bieri et al. 2018; Rodriguez et al. 2018). HSPGs are a cell surface and extracellular matrix protein thought to bind PFFs and promote uptake via late endosomes or lysosomes (Valdinocci et al. 2017; Bieri et al. 2018; Rodriguez et al. 2018). Transmembrane 9 superfamily member 2 is another endosomal marker that is one of the highest expressed genes in 41 the brain, and its highest activity is in the substantia nigra and may be involved in α-syn PFF uptake (Schimmöller et al. 1998; Wadman 2016; Valdinocci et al. 2017). FACS- based genome-wide CRISPR/Cas9 knockout screening identified Transmembrane 9 superfamily member 2 because of its role in regulating the expression of HSPG biosynthesis (Vanderperre et al. 2023). Other studies have investigated the role of neurexins, a presynaptic cell adhesion protein, and sodium and potassium ATPase as another mechanism involved in PFF uptake (Bieri et al. 2018; Rodriguez et al. 2018). This model was initially developed in mice and was later replicated in rats (Luk et al. 2012; Patterson et al. 2019). In mice, intrastriatal injection of PFFs results in pale cytoplasmic diffuse and neuritic inclusions 1-month in the substantia nigra, cortex, and olfactory bulbs, regions connecting to the striatum (Luk et al. 2012). Nigral inclusions peak at 1-month and then decline as nigrostriatal neurons begin to degenerate (Luk et Figure 1.8. Schematic showing the timecourse of the α-synuclein PFF model in mice. The x axis shows the months post-PFF injection. Y axis shows the percent of control. The purple line represents the relative changes in DA turnover. The orange line shows SN neurons containing pSyn aggregates. The green shows relative changes in SN TH immunoreactive neurons. The blue represents changes in striatal DA levels. The red shows changes in motor behavior. Made in BioRedner. 42 al. 2012). At 2 months post-injection, there is a significant decrease in striatal levels of DA and the DA metabolites DOPAC and homovanillic acid (HVA) (Gezer et al. 2020). Also, at 2 months post-injection there is an increase in DA turnover indicated by the ratio of HVA: DA and a female-specific increase in the ratio of DOPAC: DA (Gezer et al. 2020)(Figure1.8). By 3 months post-injection, the inclusions become dense and perinuclear and are found in the thalamus, amygdala, and contralateral cortex. At 3 months post-injection, there are significant reductions in striatal DA concentration and a significantly reduced latency to fall on the wire hang test (Luk et al. 2012). At 6 months post-injection, striatal TH and DAT expression is significantly decreased (Luk et al. 2012). There is also a more significant decrease in TH immunoreactive neuron loss in male mice compared to female mice at 6 months post-injection (35% compared to 20% loss respectively) (Gezer et al. 2020). Striatal DA, DOPAC, and HVA levels are significantly reduced in both male and female mice. Additionally, there is a significant increase in DA turnover indicated by increased ratios of DOPAC: DA and HVA: DA in both sexes at 6 months post-injection (Gezer et al. 2020). Motor behavioral impairments are also observed at 6 months post-PFF injection. There is a significant decrease in the rotarod and wire hang test (Luk et al. 2012). 6-months post-PFF injections, the number of steps was significantly reduced and the number of errors per step was significantly increased in male mice. However, there were no significant differences in female mice injected with PFFs on the challenging beam (Gezer et al. 2020). This combination of effects shows a DA deficit and a Parkinsonian-like phenotype, showing a sex-specific difference in the PFF model (Figure 1.8). 43 PFF-induced pathology from intrastriatal injections seems to be selective to the nigrostriatal pathway and brain regions with structural connectivity to the injection site. However, other DAergic populations, such as the ventral tegmental area are not affected by intrastriatal PFF injections because of the location of PFF injection and because nigrostriatal neurons are specifically vulnerable to toxicity (Luk et al. 2012). This model has also been replicated in rats. The overall sequence of events is similar, but the aggregation and degeneration may be more pronounced in rats. In addition, rats show some effects contralateral to the injection site with degeneration of nigral DAergic neurons and striatal TH terminals in the striatum at 6 months post-injection (Patterson et al. 2019). Contralateral degeneration has not been observed in mice, but it may appear at unmeasured later time points. Neuroinflammation has also been studied in the rat PFF model. Reactive microglia and major histocompatibility complex-II expression levels form near psyn-positive inclusions in the nigra and follow a similar temporal pattern as the appearance and disappearance of inclusions (Duffy et al. 2018). The α-syn PFF model has also been successfully recapitulated in iPSCs and primary rodent neuronal cultures (Luk et al. 2009; Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014; Gao et al. 2019a; Ross et al. 2020a). Many aspects of the in vivo model can be recapitulated in these cells, including the formation of phosphorylated inclusions and compact puncta, mitochondrial dysfunction, oxidative stress, deficits in neuronal excitability, increased autophagy, loss of synaptic markers, and eventual degeneration of neurons (Luk et al. 2009; Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014; Ross et al. 2020a). Specifically, initial work was done in primary hippocampal neurons because of their high levels of α-syn. In this system, phosphorylated inclusions are 44 present 4 days after PFF application and compact puncta form by 7 days. At 14 days post-treatment, 20-30% of treated primary hippocampal neurons degeneration, showing mitochondrial oxidant stress, deficits in neuronal excitability, increased autophagy, and loss of synaptic markers (Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014). Additional work has applied the PFF model to SH-SY5Y cells to study aggregate clearance pathways and PFF-induced mitochondrial dysfunction (Perfeito et al. 2014; Choi et al. 2018; Gao et al. 2019b; Ross et al. 2020b; Pantazopoulou et al. 2021; Feng et al. 2022; Lin et al. 2022). Multiple-hit Hypotheses in PD The majority of PD cases are sporadic and are thought to be caused by a combination of common genetic risk variants and environmental exposures which suggests that a combination of insults is required for disease development (Sulzer 2007). Therefore, multiple hit models can be used to study the effects of factors that may not cause PD on their own, but instead prime the system for increased susceptibility to another insult or hit. This multiple-hit model is often used to study the effects of environmental factors on disease risk (Sulzer 2007). Previous work has established a two-hit dieldrin/MPTP model, and this has recently been extended to include a dieldrin/PFF model to study the effects of developmental dieldrin exposure on PD risk (Richardson et al. 2006a; Gezer et al. 2020). Dieldrin Dieldrin Overview Dieldrin is an organochlorine pesticide that was associated with increased sporadic PD risk in epidemiological, post-mortem, and mechanistic studies (Tanner and Langston 45 1990; Semchuk et al. 1992; Fleming et al. 1994; Le Couteur et al. 1999; Priyadarshi et al. 2000; Ritz and Yu 2000; Tanner and Aston 2000; Priyadarshi et al. 2001; Kanthasamy et al. 2005; Ascherio et al. 2006; Brown et al. 2006; Richardson et al. 2006a; Steenland et al. 2006; Hatcher et al. 2007; Elbaz et al. 2009; Weisskopf et al. 2010; Moretto and Colosio 2011; Tanner et al. 2011; Wirdefeldt et al. 2011; Caudle et al. 2012; Freire and Koifman 2012; Gezer et al. 2020). Since dieldrin was phased out in the 1970s and 1980s, the potential for new, acute exposure to dieldrin is low. However, the health effects of past exposures will continue for decades as the population currently diagnosed with PD and those that will develop PD in the next 20-30 years were likely exposed to dieldrin before its phase-out (de Jong et al. 1997; Jorgenson 2001; Meijer et al. 2001; Kanthasamy et al. 2005). Dieldrin in vitro studies In vitro approaches were used to test the direct effects of dieldrin on DAergic toxicity using a variety of cell lines. Collectively, these studies show that at high doses, there are dieldrin-induced effects on DAergic neurons resulting in increased toxicity and degeneration, and some effects were observed on α-syn (Figure 1.9). Relevant to synucleinopathy, rat mesencephalic N27 cells overexpressing α-syn resulted in proteasomal dysfunction and eventually apoptosis, and this effect was exacerbated by dieldrin exposure (Sun et al. 2005). Dieldrin exposure (30 μM) affects the ubiquitin-proteasome system by decreasing proteasomal activity in a dose- dependent manner and this effect is more pronounced in cells overexpressing α-syn. This suggests that dieldrin may exacerbate α-syn related proteasomal and apoptotic responses playing a role in PD pathology (Sun et al. 2005). 46 At lower concentrations of dieldrin (2.5 μM and 25 μM), there is a significant reduction in energy metabolism via Seahorse XFe24 analysis. It was further found that dieldrin- induced mitochondria impairments were likely related to endoplasmic reticulum (ER) stress as the transcripts for ER-related apoptotic genes were significantly increased (Schmidt et al. 2017). Similarly, dieldrin treatment has promoted caspase-3-dependent activity resulting in DNA fragmentation and apoptosis in PC12 cells, a rat pheochromocytoma cell line (Kitazawa et al. 2003). Dieldrin treatment also generates reactive oxygen species and increases lipid peroxidation in PC12 cells (Kitazawa et al. 2001). Dieldrin has higher selectivity for DAergic PC12 cells compared to pancreatic α- endocrine and human cortical GABAergic neuron cells when comparing cell viability in cells treated with dieldrin. Dieldrin exposure displaces DA and results in a concentration-dependent increase in DA and the DOPAC release in DAergic, PC12 cells (Kitazawa et al. 2001). In a model of primary mesencephalic neuronal cultures from rats Figure 1.9. Summary of dieldrin in vitro studies. Made in BioRedner. 47 and mice, dieldrin exposure (0.01 -100 μM) resulted in a concentration-dependent decrease in DAergic and GABAergic neurons. However, GABAergic neurons were less sensitive to dieldrin than DAergic neurons. Supporting this, plasma membrane uptake of tritium-labeled DA was significantly reduced by dieldrin compared to tritium-labeled GABA uptake (Sanchez-Ramos et al. 1998). Overall, this data indicates that dieldrin is selectively toxic to DAergic neurons, although the concentrations of dieldrin used in these in vitro studies may not be relevant to concentrations of dieldrin in human exposure. Dieldrin in vivo studies Chronic dieldrin exposure results in reduced levels of DA, norepinephrine, and serotonin through multiple brain structures and models. Specifically, in an oral dieldrin exposure paradigm in rats (50 ppm for 8 weeks), NE concentrations were reduced in several brain areas including the hippocampus, striatum, oblongata, and pons between 2- and 4 weeks post-treatment. At 8 weeks, NE levels returned to normal or above normal throughout the brain regions (Wagner and Greene 1978). In-ring doves exposed to dieldrin (200ppm) reduced levels of DA levels as well as NE levels in ring dove brains (Heinz et al. 1980). Similarly, chronic dietary exposure (30ppm of dieldrin) to mallard ducks resulted in 5-HT, NE, and DA concentrations in brains (Sharma et al. 1977). Further evidence confirms that dieldrin exposure results in alterations in the nigrostriatal pathway and DA handling (Hatcher et al. 2007). In a mouse model of chronic dieldrin (up to 3mg/kg) administration, there is an observed reduction in striatal DA metabolites including DOPAC and HVA concentrations. Additionally, there were significant decreases in striatal DAT expression and uptake. In addition to DA mishandling, dieldrin 48 also affected oxidative stress by inducing increases in striatal levels of cysteinyl- catechol, protein carbonyls, α-syn, and redox potential of glutathione (Hatcher et al. 2007). Overall, this shows that dieldrin exposure can induce changes in the DAergic systems, and as mentioned above DA handling is finely tuned and any perturbation to the system can be detrimental to the neuron. Dieldrin mechanisms of action of adult dieldrin exposure Dieldrin is thought to exert its toxic effects by targeting and inhibiting GABAA receptors causing an inhibition of Cl- influx (Pomps et al. 1993; Rodriguez-Farre and Suñol 1995; Ikeda et al. 1998; le Corronc et al. 2002; Le Corronc et al. 2002; Vale et al. 2003; Zhao et al. 2003; Heusinkveld and Westerink 2012). Prenatal exposure to dieldrin reduces expression of GABAA receptor subunit mRNA expression as well as reduced binding capacity of GABAA receptors in the rat brainstem (Narahashi et al. 1995; Liu et al. 1997; Brannen et al. 1998; Liu et al. 1998). Dieldrin exposure can also alter Ca2+ signaling and activity. Specifically, dieldrin exposure can modulate calmodulin-dependent and independent Ca2+ ATPase activity which can impair Ca2+ metabolism and signaling in rat synaptosomes and heart sarcoplasmic reticulum (Mehrotra B.D. et al. 1988; Mehrotra B.D. et al. 1989). Dieldrin also induces oxidative stress, and this is particularly relevant in the nigrostriatal system. Supporting this, dieldrin exposure was shown to increase cysteinyl-DOPAC and cysteinyl-DA, increase protein carbonyls, and reduce the redox potential for glutathione, specifically in the striatum (Hatcher et al. 2007). Synthesis and degradation of DA can result in hydrogen peroxide, reactive oxygen species, autoxidation, or the formation of toxic DA intermediates like DA-quinones. DA-quinones can react with sulfhydryl groups 49 resulting in exacerbated oxidative damage resulting in the formation of cysteinyl- adducts which were shown to be increased by dieldrin exposure (Hatcher et al. 2007). Dieldrin exposure in PC12 cells has also been shown to produce a dose-dependent decrease in mitochondrial membrane potential, an increase in lactic acid dehydrogenase activity, and an increase in ROS generation indicating worsened oxidative stress (Kitazawa et al. 2001). DAergic neurons are specifically sensitive to oxidative stress and have a particularly low antioxidant capacity, dieldrin exposure exacerbates this oxidative stress which can impair the function of DA neurons and result in degradation (Hatcher et al. 2007). Developmental dieldrin exposure model In this dissertation, we utilize a previously established developmental dieldrin exposure model that was designed to mimic human exposures at a critical developmental period (Richardson 2006, Kochmanski 2019, Gezer 2020). In this model, male mice developmentally exposed to dieldrin show an increased susceptibility later in life to the DAergic toxicant, MPTP, and synucleinopathy induced by α-syn PFFs. In this model, female mice are fed dieldrin before mating and throughout mating, gestation, and Figure 1.10. Developmental dieldrin exposure paradigm. Female mice are fed dieldrin (0.3mg/kg) or vehicle prior to mating and throughout lactation. Offspring are developmentally exposed through the placenta and breast milk. Made in BioRedner. 50 lactation at doses of 0.3 mg/kg of dieldrin (Richardson et al. 2006) (Figure 1.10). This exposure paradigm is based on the developmental origins of the health and disease hypothesis described above, which states that environmental exposures during critical periods of development affect disease risk and trajectory later in life (Heindel and Vandenberg 2015; Baird et al. 2017). PD is a disease of the aged, but given the long prodromal phase, the neurodegenerative process likely begins decades before clinical diagnosis, therefore, exposures early in life may contribute to sporadic PD. It is unknown if the mechanisms of action for developmental dieldrin exposure are the same as adult exposure to dieldrin. However, these early developmental changes may produce a poised state of silent neurotoxicity, where the effects of early life exposures are unmasked by challenges later in life, the cumulative effects of exposures over the lifespan, or the effects of aging (Cory-Slechta et al. 2005; Kraft et al. 2016). Likewise, dieldrin exposure does not cause overt toxicity by traditional measures on its own but increases the vulnerability to future insults. In previous studies using this model, male offspring at 12 weeks of age showed increased vulnerability in both MPTP and the α-syn PFF model (Richardson 2006; Gezer 2020). At 12 weeks after birth, the developmentally exposed offspring males showed a significant increase in DAT and VMAT2 protein in dieldrin-exposed (0.3 mg/kg) animals before MPTP administration. This increase in DAT and VMAT2 was exacerbated in male offspring. There was also an increase in nuclear receptor related-1 (Nurr1) and paired-like homeodomain transcript factor 3 mRNA which are two nuclear transcription factors that regulate DAT and VMAT2 expression, but only at higher concentrations of dieldrin (1 and 3 mg/kg) and more so in female mice. Striatal DA 51 turnover was also significantly increased by developmental dieldrin exposure. Specifically, the DOPAC/DA ratio was increased at all doses ranging from 0.3 to 3 mg/kg only in male mice. Overall, it shows that developmental dieldrin exposure increased DA dysfunction and increased DAT, VMAT2, and Nurr1 levels in male offspring at 12 weeks of age. Although there was an increase in DAT, VMAT2, and NURR1 levels at a lesser extent in female mice developmentally exposed to dieldrin, DA turnover was not affected at any dose in female mice (Richardson et al. 2006). This indicates that there is a male-specific exacerbation to developmental dieldrin exposure resulting in increased DA mishandling and turnover. To determine the risk of developmental dieldrin exposure to PD, Richardson et al. developed a two-hit developmental dieldrin/MPTP model. In this model, female mice are exposed to dieldrin, and the developmentally exposed offspring are administered MPTP (2 injections of 10mg/kg MPTP subcutaneously). Dieldrin exposure exacerbated the MPTP-induced loss of striatal DA in a dose-dependent manner in mice, and this effect was greater in male mice (Richardson et al. 2006). The ratio of DAT: VMAT2 was significantly increased at 0.3 mg/kg only in male mice, indicating increased DAergic vulnerability to toxicity (Richardson et al. 2006). To recapitulate these findings in a model of synucleinopathy, Gezer et al. used a developmental dieldrin/α-syn PFF model where PFFs were intrastriatally injected in developmentally exposed mice at 3 months of age. There was no significant dieldrin- induced effect on PFF-induced nigral phosphorylated-synuclein at 1 and 2 months post- PFF injection (Gezer et al. 2020). At 6 months post-PFF injection, when PFF induced significant DAergic degeneration, there was no effect of dieldrin on nigral neuronal 52 counts or TH-immunoreactive neurons. At 2 and 6 months post-PFF injection, striatal DA and DA metabolite levels were measured using HPLC to assess DA turnover. At 6 months post-PFF injection, but not 2 months, there was a dieldrin-induced increase in the ratio of HVA: DA in male mice indicative of increased DA turnover. The challenging beam assessment was used as a more sensitive measure of motor coordination. In this test, mice are placed on a beam covered in grates and must walk across the beam toward their home cage. Closer to the home cage, the beam becomes narrower and the time to traverse, the number of steps, and the number of errors are recorded (Figure 1.11A). A combination of all three factors indicates the severity of DAergic deficit. Dieldrin on its own does not lead to deficits on the challenging beam similar to vehicle/saline injected animals. The vehicle-exposed animals injected with PFFs showed fewer steps and more errors per step indicating a worsened DA deficit compared to control. Male mice developmentally exposed to dieldrin and injected with PFFs showed a significant increase in the time to traverse the beam, more steps, but fewer errors/step since they had more time to compensate for errors. This combination of effects shows that developmental dieldrin exposure exacerbates PFF-induced motor impairments and deficits in DA handling in male mice (Gezer et al. 2020)(Figure 1.11B). This shows that developmental dieldrin exposure may prime the nigrostriatal system for PD-related toxicity induced by either MPTP or PFFs and that male mice may have heightened susceptibility. In conclusion, this data aligned with previous MPTP data showing a dieldrin-induced male-specific exacerbation to Parkinsonian toxicity resulting in a worsened motor deficit and increases in DA mishandling. 53 The levels of glial fibrillary protein (GFAP), a mark of astrological proliferation, and α-syn levels were also exacerbated by MPTP in dieldrin-exposed animals in a dose- dependent manner (Richardson et al. 2006). In line with this, developmental dieldrin exposure induced effects on neuroinflammatory genes and pathways in a sex-specific manner (Gezer et al. 2020). In conclusion, these data aligned with previous MPTP data showing a dieldrin-induced male-specific exacerbation to parkinsonian toxicity resulting Figure 1.11. Motor behavioral deficits identified in the dieldrin/PFF two-hit model. A) Schematic describing the challenging beam motor coordination assessment. B) Overview of the identified motor deficits (time to traverse, total steps, and errors/step) and severity of DA deficits dieldrin/PFF animals and controls. Made in BioRedner. 54 in a worsened motor deficit and increases in DA mishandling. Mechanisms underlying this dieldrin-associated increase in susceptibility remain incompletely defined and are the main focus of this dissertation. The epigenome is a potential mediator of the relationship between developmental dieldrin exposure, increased neuronal vulnerability, and adult disease. We previously characterized changes in DNA modifications in developmentally exposed offspring (Kochmanski 2019). We found that dieldrin exposure established a sex-specific poised epigenetic state early in life and hypothesize that this may mediate susceptibility to PD- related neurotoxicity in adulthood (Kochmanski et al., 2019). Specifically, using the same developmental dieldrin exposure paradigm, we performed reduced representation bisulfite sequencing on DNA isolated from the midbrain and identified 115 differentially methylated CpGs in males and 478 in female 3-month-old, developmentally exposed C57BL/6 mice. There was also many sex-specific differential expression in protein- coding transcripts associated with DAergic development (Kochmanski et al., 2019). This suggests that developmental dieldrin-induced differential modification of genes associated with DAergic development may contribute to and underly the dieldrin- induced exacerbations of MPTP and PFFs. Genes identified in this study are the source of candidate genes explored in Chapter 4 of this dissertation. New approach methodologies While animal models traditionally provide the most physiologically relevant system to model disease, in vivo experiments have several limitations. They can be time- consuming, expensive, and resource-intensive, require large numbers of animals, have high variability, and lack translation from animal models to humans (Bal-Price 2018). 55 New approach methodologies (NAMs) are methods designed to replace animal testing in assessing chemical or drug toxicity and offer advantages for neurotoxicity testing, disease modeling, and drug screening (Hogberg et al. 2013; Anderson et al. 2021). Multiple NAMs were developed to screen chemicals for developmental neurotoxicity (DNT) and additional methods in this area are needed as an efficient and translatable approach to assess DNT (Bal-Price 2018). The ability to use cells of human origin is a major advantage of NAMs and may be more translatable in modeling human disease and toxicity than in vivo rodent models. More than 90% of compounds in clinical trials for drug development fail because of effects that were not observed in vivo testing, partly due to species differences (Hogberg et al. 2013). Human-derived cells can be used for in vitro NAMs at increasing levels of complexity, ranging from adherent cells to organoids. As a result, recent work was aimed at developing and advancing in vitro new approach methodologies (NAMs) to screen chemicals for their toxicological effects, especially for DNT testing (Carstens et al. 2022). Developing NAMs for DNTs requires a battery of assays to investigate several neurodevelopmental processes. For example, a battery of assays that measure neurite outgrowth, ATP assays, proliferation, apoptosis, neural network formation, and synaptogenesis was developed by the U.S. EPA to evaluate chemicals for potential DNT (Carstens et al. 2022). Human-derived cells can be used for in vitro NAMs at varying levels of complexity, ranging from adherent cells to organoids. While human stem cells derived from embryonic, umbilical, bone marrow, or central nervous tissues can be differentiated into a diverse set of neuronal types, there are ethical issues and issues of availability that limit their utility (Hogberg et al. 2013). As an 56 alternative, iPSCs from fibroblasts or adult somatic cells can be reprogrammed into an embryonic stem cell-like state via the induction of pluripotent genes (Ye et al 2013). iPSCs can be further differentiated into to form different types of neuronal populations including glial populations (Hogberg et al. 2013) However, generating iPSCs is difficult and only a small fraction of cells is reprogrammed after pluripotent induction. In addition, differentiating mature glial cells and neurons has proven to have low reproducibility and can be both time-consuming and expensive (Hogberg et al. 2013). Therefore, multiple groups have developed NAMs using differentiated immortalized cell lines that have technical advantages. In addition, differentiating these cells into 3D neurospheres can improve survival, model cell-to-cell interactions and synapse formation, and recapitulate neuronal activity such as network activity and activity seen in in vivo models (Hogberg et al. 2013; Anderson et al. 2021). Recent advances show that three-dimensional (3D) neuronal models are better at recapitulating the complexity of the central nervous system than 2D adherent cell models. One advantage is that the synaptic interactions and cell morphology are more physiologically relevant in 3D cultures compared to traditional monolayer cultures (Hogberg and Smirnova 2022). 3D models include spheroids, organoids, and organ-on- a-chip models. Spheroids are the simplest of these models and are clusters of one specific cell type that be used to investigate the role of a specific population of cells (Hogberg and Smirnova 2022). For example, spheroids generated from LUHMES cells can be differentiated into DAergic-like neurons to study PD (L. Smirnova et al. 2016; Harris et al. 2017a; Harris et al. 2018; Leite et al. 2019; Ko et al. 2020). Organoids contain a complex mixture of cells with a long differentiation process that more closely 57 recapitulates aspects of human neuronal development and maturation and better represents the architecture and connection in human brains (Hogberg and Smirnova 2022). Recent advances have incorporated vascularization, immune cells including microglia, cerebral spinal fluid secretion, and the blood-brain barrier into organoid models (Hogberg and Smirnova 2022). However, organoids are generally derived from induced pluripotent stem cells, which are highly variable in their reprogramming and differentiation resulting in low reproducibility and are expensive and labor-intensive (Hogberg et al. 2013). The most complex 3D models include microfluidic devices and brain-on-chip models. Microfluidic models use microchannels to provide gradients of different growth factors, chemokines, or other substances to 3D neurospheres or organoids to model controlled microenvironments (Hogberg et al. 2013; Alépée 2014; Anderson et al. 2021; Hogberg and Smirnova 2022). Brain-on-a-chip models are similar to organoids but may include compartmentalized neuronal chambers, microfluidic devices, and organized cellular layers to model different neuronal interactions (Amirifar et al. 2022). The blood-brain barrier has commonly been modeled using brain-on-a-chip technology to capture the neurovascular, neurons, glia, and synaptic connections (Amirifar et al. 2022; Hogberg and Smirnova 2022). Brain-on-a-chip models are superior at modeling in vivo complexity and cellular interactions to screen toxicants or pharmaceutical compounds (Amirifar et al. 2022; Hogberg and Smirnova 2022) However, there are some limitations with complex models, including low reproducibility, difficulty with scaling the appropriate proportions of cell populations, complications with co-culture of different cell types, and the associated high cost and labor (Amirifar et al. 2022). In Chapters 3 and 4 of this 58 dissertation, we utilized 3D neurospheres derived from Lund Human Mesencephalic (LUHMES) cells and SH-SY5Y cells because of the well-documented protocols for differentiation into DAergic-like cells. LUHMES cells are a human mesencephalon-derived cell line that can be differentiated into morphologically and biochemically mature DA-like neurons and are increasingly used for in vitro research (Lotharius et al. 2002; Lotharius et al. 2005; Scholz et al. 2011a; Pöltl et al. 2012; Schildknecht et al. 2013; Krug et al. 2014; X.M. Zhang et al. 2014a; Efremova et al. 2015; Hirsch et al. 2015; Oliveira et al. 2015; Tong et al. 2017) These cells are derived from 8-week-old female human embryonic mesencephalic tissue (Smirnova et al., 2016) 3D LUHMES spheres were developed as a high- throughput toxicity screening platform to take advantage of the fact that 3D cell models show better differentiation and survival (L Smirnova et al. 2016; Harris et al. 2017b; Tong et al. 2017) After differentiation into 3D neurospheres, these cells express TH, DAT, VMAT2 and α-syn (Scholz et al. 2011b; L. Smirnova et al. 2016; Harris et al. 2017a; Lauter et al. 2020; Tüshaus et al. 2020). This cell model is well established and demonstrates robust performance in high-throughput neurotoxicity studies, including studies of rotenone, another neurotoxicant relevant to PD (Scholz et al. 2011c; Scholz et al. 2011b; X. Zhang et al. 2014; X.M. Zhang et al. 2014b; L. Smirnova et al. 2016; Harris et al. 2017a; Harris et al. 2018; Leite et al. 2019; Ko et al. 2020; Tong et al. 2020; Tüshaus et al. 2020; Yamaguchi et al. 2020; Leah et al. 2021; Nicolai et al. 2022; Tong et al. 2022; Ali et al. 2023; Capinha et al. 2023). SH-SY5Y is a sub-cell line of SK-N-SH cells, which are derived from a neuroblastoma from a 4-year-old female (Xicoy et al., 2017). Early characterization of SH-SY5Y cells 59 showed that the cells may have a catecholaminergic phenotype displaying enzymatic activity for both DA and norepinephrine such as TH, dopamine-β-hydroxylase, acetylcholinesterase, and choline acetyltransferase (Xicoy et al. 2017) Shipley et al. has developed methods to induce differentiation in SH-SY5Y cells with retinoic acid and specific growth factors to form a DAergic-like phenotype (Shipley et al. 2016). Goals of the current research The overall working hypothesis of this project is that developmental exposure to the organochlorine pesticide dieldrin alters PD risk by establishing a poised epigenetic state early in life that mediates susceptibility to Parkinsonian neurotoxicity in adulthood (Kochmanski et al. 2019) (Figure 1.12). These dieldrin-induced changes exacerbate PD-associated dysfunction in the nigrostriatal pathway and behavioral dysfunction (Richardson et al. 2006; Gezer et al. 2020). The overall goal of this project is to link the observed epigenetic modifications to functional differences in neuronal phenotype and neuronal susceptibility to synucleinopathy. The goal of this project is three-fold. 1) Analyze VMAT2-mediated DA uptake and neurotransmission in striatal terminals in the two-hit dieldrin/α-syn PFF model in vivo. (Chapter 2) 2) Adapt the α-syn PFF model for use in 3D LUHMES and SH-SY5Y neurospheres. (Chapter 3) 3) Test if differentially modified candidate genes mediate α-syn PFF- or MPP+- induced toxicity in 3D LUHMES neurospheres (Chapter 4) This project has characterized the separate and combined effects of dieldrin and synucleinopathy on functional measures of DA uptake, release, and vesicular packaging 60 in the striatum of mice and provides additional insight into the synaptic mechanisms underlying dieldrin-induced exacerbation of synucleinopathy-induced deficits. Through this project, we have also assessed the role of developmental dieldrin-induced differentially modified genes, Nuclear receptor subfamily 4 group A member 2 (NR4A2) and Ephrin Type-B receptor 2 (EPHB2) in DAergic differentiation and MPP+-induced toxicity in the 3D LUHMES cell model. This has addressed a gap in knowledge between epigenetic regulation and functional outcomes that alter neuronal vulnerability and disease susceptibility. Results from this project have generated important data regarding the effect of regulation of expression of these genes and provide new data to build on in future studies that explore the roles of those specific epigenetic changes. Combined with previous epigenetic data, these results can guide future studies that use epigenome editing to target genes that play a role in PD-related toxicity. 61 Figure 1.12. Working hypothesis for developmental dieldrin-induced exacerbation of parkinsonian toxicity. Developmental dieldrin exposure induces functional changes in the developing dopaminergic neurons in the offspring by inhibiting the chloride influx via GABAA receptors and increasing neuronal excitation. Dieldrin can induce changes in DNA methylation and gene expression which results in alterations n synaptic function. The addition of a second hit (the α-syn PFFs) results in dieldrin-induced exacerbation of PFF-induced synaptic deficits resulting in an exacerbated Parkinsonian phenotype specifically in male mice. Aim 1 of this dissertation assess the dieldrin-induced changes in synaptic and vesicular integrity using the dieldrin/PFF two-hit model in vivo. Aim 2 links differential gene expression to neuronal function and susceptibility in vitro. Made in BioRedner. 62 REFERENCES Abeliovich A, Schmitz Y, Fariñas I, Choi-Lundberg D, Ho WH, Castillo PE, Shinsky N, Verdugo JM, Armanini M, Ryan A, et al. 2000. Mice lacking alpha-synuclein display functional deficits in the nigrostriatal dopamine system. Neuron. 25(1):239–52. doi:10.1016/s0896-6273(00)80886-7. Albani D, Peverelli E, Rametta R, Batelli S, Veschini L, Negro A, Forloni G. 2004. Protective effect of TAT‐delivered α‐synuclein: relevance of the C‐terminal domain and involvement of HSP70. The FASEB Journal. 18(14):1713–1715. doi:10.1096/fj.04- 1621fje. Alépée N. 2014. State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology. ALTEX.:441–477. doi:10.14573/altex.1406111. Alexander GM, Schwartzman RJ, Grothusen JR, Brainard L, Gordon SW. 1993. Changes in brain dopamine receptors in MPTP parkinsonian monkeys followingL-dopa treatment. Brain Res. 625(2):276–282. doi:10.1016/0006-8993(93)91069-5. Alharbi OML, Basheer AA, Khattab RA, Ali I. 2018. Health and environmental effects of persistent organic pollutants. J Mol Liq. 263:442–453. doi:10.1016/j.molliq.2018.05.029. Ali N, Sane MS, Tang H, Compher J, McLaughlin Q, Jones CD, Maffi SK. 2023. 6- hydroxydopamine affects multiple pathways to induce cytotoxicity in differentiated LUHMES dopaminergic neurons. Neurochem Int. 170:105608. doi:10.1016/j.neuint.2023.105608. Allis CD, Jenuwein T. 2016. The molecular hallmarks of epigenetic control. Nat Rev Genet. 17(8):487–500. doi:10.1038/nrg.2016.59. Alter SP, Lenzi GM, Bernstein AI, Miller GW. 2013. Vesicular integrity in parkinson’s disease. Curr Neurol Neurosci Rep. 13(7). doi:10.1007/s11910-013-0362-3. Alvarez-Erviti L, Seow Y, Schapira AH, Gardiner C, Sargent IL, Wood MJA, Cooper JM. 2011. Lysosomal dysfunction increases exosome-mediated alpha-synuclein release and transmission. Neurobiol Dis. 42(3):360–367. doi:10.1016/j.nbd.2011.01.029. http://dx.doi.org/10.1016/j.nbd.2011.01.029. Ambrosi G, Cerri S, Blandini F. 2014. A further update on the role of excitotoxicity in the pathogenesis of Parkinson’s disease. J Neural Transm. 121(8):849–859. doi:10.1007/s00702-013-1149-z. Amirifar L, Shamloo A, Nasiri R, de Barros NR, Wang ZZ, Unluturk BD, Libanori A, Ievglevskyi O, Diltemiz SE, Sances S, et al. 2022. Brain-on-a-chip: Recent advances in design and techniques for microfluidic models of the brain in health and disease. Biomaterials. 285:121531. doi:10.1016/j.biomaterials.2022.121531. 63 Anderson WA, Bosak A, Hogberg HT, Hartung T, Moore MJ. 2021. Advances in 3D neuronal microphysiological systems: towards a functional nervous system on a chip. In Vitro Cell Dev Biol Anim. 57(2):191–206. doi:10.1007/s11626-020-00532-8. Arima K, Hirai S, Sunohara N, Aoto K, Izumiyama Y, Uéda K, Ikeda K, Kawai M. 1999. Cellular co-localization of phosphorylated tau- and NACP/α-synuclein-epitopes in Lewy bodies in sporadic Parkinson’s disease and in dementia with Lewy bodies. Brain Res. 843(1–2):53–61. doi:10.1016/S0006-8993(99)01848-X. Armstrong MJ, Okun MS. 2020. Diagnosis and Treatment of Parkinson Disease: A Review. JAMA - Journal of the American Medical Association. 323(6):548–560. doi:10.1001/jama.2019.22360. Ascherio A, Chen H, Weisskopf MG, O’Reilly E, McCullough ML, Calle EE, Schwarzschild MA, Thun MJ. 2006. Pesticide exposure and risk for Parkinson’s disease. Ann Neurol. 60(2):197–203. doi:10.1002/ana.20904. Asikainen S, Rudgalvyte M, Heikkinen L, Louhiranta K, Lakso M, Wong G, Nass R. 2010. Global microRNA Expression Profiling of Caenorhabditis elegans Parkinson’s Disease Models. Journal of Molecular Neuroscience. 41(1):210–218. doi:10.1007/s12031-009-9325-1. Aubert I, Guigoni C, Håkansson K, Li Q, Dovero S, Barthe N, Bioulac BH, Gross CE, Fisone G, Bloch B, et al. 2005. Increased D1 dopamine receptor signaling in levodopa- induced dyskinesia. Ann Neurol. 57(1):17–26. doi:10.1002/ana.20296. Avenali M, Blandini F, Cerri S. 2020. Glucocerebrosidase Defects as a Major Risk Factor for Parkinson’s Disease. Front Aging Neurosci. 12. doi:10.3389/fnagi.2020.00097. Baccarelli A, Bollati V. 2009. Epigenetics and environmental chemicals. Curr Opin Pediatr. 21(2):243–51. doi:10.1097/mop.0b013e32832925cc. Baird J, Jacob C, Barker M, Fall C, Hanson M, Harvey N, Inskip H, Kumaran K, Cooper C. 2017. Developmental Origins of Health and Disease: A Lifecourse Approach to the Prevention of Non-Communicable Diseases. Healthcare. 5(1):14. doi:10.3390/healthcare5010014. Barone DA, Sarva H, Hellmers N, Wang F, Xu Z, Krieger AC, Henchcliffe C. 2023. Neurologic and psychiatric features of impending neurodegeneration in iRBD. Clin Park Relat Disord. 9:100216. doi:10.1016/j.prdoa.2023.100216. Beach TG, Adler CH, Sue LI, Vedders L, Lue LF, White CL, Akiyama H, Caviness JN, Shill HA, Sabbagh MN, et al. 2010. Multi-organ distribution of phosphorylated α- synuclein histopathology in subjects with Lewy body disorders. Acta Neuropathol. 119(6):689–702. doi:10.1007/s00401-010-0664-3. 64 Bellani S, Sousa VL, Ronzitti G, Valtorta F, Meldolesi J, Chieregatti E. 2010. The regulation of synaptic function by α-synuclein. Commun Integr Biol. 3(2):106–109. doi:10.4161/cib.3.2.10964. Bellou V, Belbasis L, Tzoulaki I, Evangelou E, Ioannidis JPA. 2016. Environmental risk factors and Parkinson’s disease: An umbrella review of meta-analyses. Parkinsonism Relat Disord. 23:1–9. doi:10.1016/j.parkreldis.2015.12.008. http://dx.doi.org/10.1016/j.parkreldis.2015.12.008. Berger SL, Kouzarides T, Shiekhattar R, Shilatifard A. 2009. An operational definition of epigenetics: Figure 1. Genes Dev. 23(7):781–783. doi:10.1101/gad.1787609. Bernheimer H, Birkmayer W, Hornykiewicz O, Jellinger K, Seitelberger F. 1973. Brain dopamine and the syndromes of Parkinson and Huntington Clinical, morphological and neurochemical correlations. J Neurol Sci. 20(4):415–455. doi:10.1016/0022- 510X(73)90175-5. Betarbet R, Sherer TB, MacKenzie G, Garcia-Osuna M, Panov A V., Greenamyre JT. 2000. Chronic systemic pesticide exposure reproduces features of Parkinson’s disease. Nat Neurosci. 3(12):1301–1306. doi:10.1038/81834. Betarbet R, Turner. R, Chockkan V, DeLong MR, Allers KA, Walters J, Levey AI, Greenamyre JT. 1997. Dopaminergic Neurons Intrinsic to the Primate Striatum. The Journal of Neuroscience. 17(17):6761–6768. doi:10.1523/JNEUROSCI.17-17- 06761.1997. Beyer K, Domingo-Sàbat M, Ariza A. 2009. Molecular Pathology of Lewy Body Diseases. Int J Mol Sci. 10(3):724–745. doi:10.3390/ijms10030724. Bezard E, Dovero S, Prunier C, Ravenscroft P, Chalon S, Guilloteau D, Crossman Alan R., Bioulac B, Brotchie JM, Gross CE. 2001. Relationship between the Appearance of Symptoms and the Level of Nigrostriatal Degeneration in a Progressive 1-Methyl-4- Phenyl-1,2,3,6-Tetrahydropyridine-Lesioned Macaque Model of Parkinson’s Disease. The Journal of Neuroscience. 21(17):6853–6861. doi:10.1523/JNEUROSCI.21-17- 06853.2001. Bezard E, Dovero S, Prunier C, Ravenscroft P, Chalon S, Guilloteau D, Crossman Alan R, Bioulac B, Brotchie JM, Gross CE. 2001. Relationship between the Appearance of Symptoms and the Level of Nigrostriatal Degeneration in a Progressive 1-Methyl-4- Phenyl-1,2,3,6-Tetrahydropyridine-Lesioned Macaque Model of Parkinson’s Disease. Bezard E, Gross CE. 1998. Compensatory mechanisms in experimental and human Parkinsonism: towards a dynamic approach. Prog Neurobiol. 55(2):93–116. doi:10.1016/S0301-0082(98)00006-9. Biere AL, Wood SJ, Wypych J, Steavenson S, Jiang Y, Anafi D, Jacobsen FW, Jarosinski MA, Wu G-M, Louis J-C, et al. 2000. Parkinson’s Disease-associated α- Synuclein Is More Fibrillogenic than β- and γ-Synuclein and Cannot Cross-seed Its 65 Homologs. Journal of Biological Chemistry. 275(44):34574–34579. doi:10.1074/jbc.M005514200. Bieri G, Gitler AD, Brahic M. 2018. Internalization, axonal transport and release of fibrillar forms of alpha-synuclein. Neurobiol Dis. 109:219–225. doi:10.1016/j.nbd.2017.03.007. https://doi.org/10.1016/j.nbd.2017.03.007. Blandina P, Goldfarb J, Craddock-Royal B, Green JP. 1989. Release of endogenous dopamine by stimulation of 5-hydroxytryptamine3 receptors in rat striatum. J Pharmacol Exp Ther. 251(3):803–9. Blandini F. 2014. An update on the potential role of excitotoxicity in the pathogenesis of Parkinson disease Brain neurodegeneration View project Cerebellar Synaptic Plasticity View project. https://www.researchgate.net/publication/47349077. Blandini F, Armentero MT. 2012. Animal models of Parkinson’s disease. FEBS Journal. 279(7):1156–1166. doi:10.1111/j.1742-4658.2012.08491.x. Blandini F, Armentero MT, Martignoni E. 2008. The 6-hydroxydopamine model: News from the past. Parkinsonism Relat Disord. 14(SUPPL.2). doi:10.1016/j.parkreldis.2008.04.015. Blandini F, Nappi G, Tassorelli C, Martignoni E. Functional changes of the basal ganglia circuitry in Parkinson’s disease. www.elsevier.com/locate/pneurobio. Blauwendraat C, Nalls MA, Singleton AB. 2020. The genetic architecture of Parkinson’s disease. Lancet Neurol. 19(2):170–178. doi:10.1016/S1474-4422(19)30287-X. Blesa J, Juri C, Garcia-Cabezas MÁ, Adánez R, Sánchez-González MÁ, Cavada C, Obeso JA. 2011. Inter-hemispheric asymmetry of nigrostriatal dopaminergic lesion: A possible compensatory mechanism in Parkinson’s disease. Front Syst Neurosci.(NOVEMBER 2011). doi:10.3389/fnsys.2011.00092. Blesa J, Phani S, Jackson-Lewis V, Przedborski S. 2012. Classic and new animal models of Parkinson’s disease. J Biomed Biotechnol. 2012. doi:10.1155/2012/845618. Blesa J, Przedborski S. 2014. Parkinson’s disease: Animal models and dopaminergic cell vulnerability. Front Neuroanat. 8(DEC):1–12. doi:10.3389/fnana.2014.00155. Blesa J, Trigo-Damas I, Dileone M, del Rey NLG, Hernandez LF, Obeso JA. 2017. Compensatory mechanisms in Parkinson’s disease: Circuits adaptations and role in disease modification. Exp Neurol. 298:148–161. doi:10.1016/j.expneurol.2017.10.002. Bollati V, Baccarelli A. 2010. Environmental epigenetics. Heredity (Edinb). 105(1):105– 112. doi:10.1038/hdy.2010.2. Bonhomme N, De Deurwaèrdere P, Le Moal M, Spampinato U. 1995. Evidence for 5- HT4 receptor subtype involvement in the enhancement of striatal dopamine release 66 induced by serotonin: a microdialysis study in the halothane-anesthetized rat. Neuropharmacology. 34(3):269–279. doi:10.1016/0028-3908(94)00145-I. Braak H, Ghebremedhin E, Rüb U, Bratzke H, Del Tredici K. 2004. Stages in the development of Parkinson’s disease-related pathology. Cell Tissue Res. 318(1):121– 134. doi:10.1007/s00441-004-0956-9. Braak H, Del Tredici K. 2017. Neuropathological Staging of Brain Pathology in Sporadic Parkinson’s disease: Separating the Wheat from the Chaff. J Parkinsons Dis. 7(s1):S73–S87. doi:10.3233/JPD-179001. Braak H, Tredici K Del, Rüb U, de Vos RAI, Jansen Steur ENH, Braak E. 2003. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol Aging. 24(2):197– 211. doi:10.1016/S0197-4580(02)00065-9. Brannen KC, Devaud LL, Liu J, Lauder JM. 1998. Prenatal Exposure to Neurotoxicants Dieldrin or Lindane Alters tert-ButylbicyclophosphorothionateBinding to GABA<sub> A</sub> Receptors in Fetal Rat Brainstem. Dev Neurosci. 20(1):34–41. doi:10.1159/000017296. Brice A. 2005. Genetics of Parkinson’s disease: LRRK2 on the rise. Brain. 128(12):2760–2762. doi:10.1093/brain/awh676. Bridi JC, Hirth F. 2018. Mechanisms of α-Synuclein induced synaptopathy in parkinson’s disease. Front Neurosci. 12(FEB):1–18. doi:10.3389/fnins.2018.00080. Brown TP, Rumsby PC, Capleton AC, Rushton L, Levy LS. 2006. Pesticides and Parkinson’s disease - Is there a link? Environ Health Perspect. 114(2):156–164. doi:10.1289/ehp.8095. Burbulla LF, Song P, Mazzulli JR, Zampese E, Wong YC, Jeon S, Santos DP, Blanz J, Obermaier CD, Strojny C, et al. 2017. Dopamine oxidation mediates mitochondrial and lysosomal dysfunction in Parkinson’s disease. Science (1979). 357(6357):1255–1261. doi:10.1126/science.aam9080. Burré J, Sharma M, Südhof TC. 2014. α-Synuclein assembles into higher-order multimers upon membrane binding to promote SNARE complex formation. Proc Natl Acad Sci U S A. 111(40):E4274–E4283. doi:10.1073/pnas.1416598111. Busch DJ, Oliphint PA, Walsh RB, Banks SML, Woods WS, George JM, Morgan JR. 2014. Acute increase of α-synuclein inhibits synaptic vesicle recycling evoked during intense stimulation. Mol Biol Cell. 25(24):3926–3941. doi:10.1091/mbc.e14-02-0708. Bustos G, Abarca J, Campusano J, Bustos V, Noriega V, Aliaga E. 2004. Functional interactions between somatodendritic dopamine release, glutamate receptors and brain- derived neurotrophic factor expression in mesencephalic structures of the brain. Brain Res Rev. 47(1–3):126–144. doi:10.1016/j.brainresrev.2004.05.002. 67 Cabin DE, Shimazu K, Murphy D, Cole NB, Gottschalk W, McIlwain KL, Orrison B, Chen A, Ellis CE, Paylor R, et al. 2002. Synaptic Vesicle Depletion Correlates with Attenuated Synaptic Responses to Prolonged Repetitive Stimulation in Mice Lacking α-Synuclein. The Journal of Neuroscience. 22(20):8797–8807. doi:10.1523/JNEUROSCI.22-20- 08797.2002. Capinha L, Zhang Y, Holzer A-K, Ückert A-K, Zana M, Carta G, Murphy C, Baldovini J, Mazidi Z, Grillari J, et al. 2023. Transcriptomic-based evaluation of trichloroethylene glutathione and cysteine conjugates demonstrate phenotype-dependent stress responses in a panel of human in vitro models. Arch Toxicol. 97(2):523–545. doi:10.1007/s00204-022-03436-6. Carstens KE, Carpenter AF, Martin MM, Harrill JA, Shafer TJ, Paul Friedman K. 2022. Integrating Data from in Vitro New Approach Methodologies for Developmental Neurotoxicity. Toxicological Sciences. 187(1):62–79. doi:10.1093/toxsci/kfac018. Carta M, Carlsson T, Kirik D, Björklund A. 2007. Dopamine released from 5-HT terminals is the cause of L-DOPA-induced dyskinesia in parkinsonian rats. Brain. 130(7):1819–1833. doi:10.1093/brain/awm082. Caudle WM, Guillot TS, Lazo CR, Miller GW. 2012. Industrial toxicants and Parkinson’s disease. Neurotoxicology. 33(2):178–188. doi:10.1016/j.neuro.2012.01.010. http://dx.doi.org/10.1016/j.neuro.2012.01.010. Caudle WM, Richardson JR, Wang MZ, Taylor TN, Guillot TS, McCormack AL, Colebrooke RE, Di Monte DA, Emson PC, Miller GW. 2007. Reduced vesicular storage of dopamine causes progressive nigrostriatal neurodegeneration. J Neurosci. 27(30):8138–8148. doi:10.1523/JNEUROSCI.0319-07.2007. Caudle WM, Zhang J. 2009. Glutamate, excitotoxicity, and programmed cell death in parkinson disease. Exp Neurol. 220(2):230–233. doi:10.1016/j.expneurol.2009.09.027. Cavalli G, Heard E. 2019. Advances in epigenetics link genetics to the environment and disease. Nature. 571(7766):489–499. doi:10.1038/s41586-019-1411-0. http://dx.doi.org/10.1038/s41586-019-1411-0. Chaari A, Eliezer D, Ladjimi M. 2016. The C-terminal α-helices of mammalian Hsc70 play a critical role in the stabilization of α-synuclein binding and inhibition of aggregation. Int J Biol Macromol. 83:433–441. doi:10.1016/j.ijbiomac.2015.10.089. Chandra S, Gallardo G, Fernández-Chacón R, Schlüter OM, Südhof TC. 2005. α- Synuclein Cooperates with CSPα in Preventing Neurodegeneration. Cell. 123(3):383– 396. doi:10.1016/j.cell.2005.09.028. Chefer SI, Kimes AS, Matochik JA, Horti AG, Kurian V, Shumway D, Domino EF, London ED, Mukhin AG. 2008. Estimation of D2-like receptor occupancy by dopamine in the putamen of hemiparkinsonian monkeys. Neuropsychopharmacology. 33(2):270– 278. doi:10.1038/sj.npp.1301404. 68 Chen SH, Wu H, Ossola B, Schendzielorz N, Wilson B, Chu C, Chen SL, Wang Q, Zhang D, Qian L, et al. 2012. Suberoylanilide hydroxamic acid, a histone deacetylase inhibitor, protects dopaminergic neurons from neurotoxin‐induced damage. Br J Pharmacol. 165(2):494–505. doi:10.1111/j.1476-5381.2011.01575.x. Cheng F, Vivacqua G, Yu S. 2011. The role of alpha-synuclein in neurotransmission and synaptic plasticity. J Chem Neuroanat. 42(4):242–248. doi:10.1016/j.jchemneu.2010.12.001. http://dx.doi.org/10.1016/j.jchemneu.2010.12.001. Cheng Y, Bernstein A, Chen D, Jin P. 2015. 5-Hydroxymethylcytosine: A new player in brain disorders? Exp Neurol. 268:3–9. doi:10.1016/j.expneurol.2014.05.008. http://dx.doi.org/10.1016/j.expneurol.2014.05.008. Chin KS, Yassi N, Churilov L, Masters CL, Watson R. 2020. Prevalence and clinical associations of tau in Lewy body dementias: A systematic review and meta-analysis. Parkinsonism Relat Disord. 80:184–193. doi:10.1016/j.parkreldis.2020.09.030. Choi BK, Choi MG, Kim JY, Yang Y, Lai Y, Kweon DH, Lee NK, Shin YK. 2013. Large α- synuclein oligomers inhibit neuronal SNARE-mediated vesicle docking. Proc Natl Acad Sci U S A. 110(10):4087–4092. doi:10.1073/pnas.1218424110. Choi M-G, Kim MJ, Kim D-G, Yu R, Jang Y-N, Oh W-J. 2018. Sequestration of synaptic proteins by alpha-synuclein aggregates leading to neurotoxicity is inhibited by small peptide. PLoS One. 13(4):e0195339. doi:10.1371/journal.pone.0195339. Conway KA, Lee S-J, Rochet J-C, Ding TT, Williamson RE, Lansbury PT. 2000. Acceleration of oligomerization, not fibrillization, is a shared property of both α-synuclein mutations linked to early-onset Parkinson’s disease: Implications for pathogenesis and therapy. Proceedings of the National Academy of Sciences. 97(2):571–576. doi:10.1073/pnas.97.2.571. Corrigan FM, Lochgilphead CL, Shore RF, Daniel SE, Mann D. 2000. Organochlorine insecticides in substantia nigra in parkinson’s disease. J Toxicol Environ Health A. 59(4):229–234. doi:10.1080/009841000156907. Corrigan FM, Murray L, Wyatt CL, Shore RF. 1998. Diorthosubstituted Polychlorinated Biphenyls in Caudate Nucleus in Parkinson’s Disease. Exp Neurol. 150(2):339–342. doi:10.1006/exnr.1998.6776. le Corronc H, Alix P, Hue B. 2002. Differential sensitivity of two insect GABA-gated chloride channels to dieldrin, fipronil and picrotoxinin. www.elsevier.com/locate/jinsphys. Le Corronc H, Alix P, Hue B. 2002. Differential sensitivity of two insect GABA-gated chloride channels to dieldrin, fipronil and picrotoxinin. J Insect Physiol. 48(4):419–431. doi:10.1016/S0022-1910(02)00061-6. 69 Cory-Slechta DA, Thiruchelvam M, Richfield EK, Barlow BK, Brooks AI. 2005. Developmental pesticide exposures and the Parkinson’s disease phenotype. Birth Defects Res A Clin Mol Teratol. 73(3):136–139. doi:10.1002/bdra.20118. Le Couteur D, McLean A, Taylor M, Woodham B, Board P. 1999. Pesticides and Parkinson’s disease. Biomed Pharmacother. 53(3):122–130. doi:10.1016/S0753- 3322(99)80077-8. Davidson WS, Jonas A, Clayton DF, George JM. 1998. Stabilization of α-Synuclein Secondary Structure upon Binding to Synthetic Membranes. Journal of Biological Chemistry. 273(16):9443–9449. doi:10.1074/jbc.273.16.9443. Decamp E, Wade T, Schneider JS. 1999. Differential regulation of striatal dopamine D1 and D2 receptors in acute and chronic parkinsonian monkeys. Brain Res. 847(1):134– 138. doi:10.1016/S0006-8993(99)02015-6. Desplats P, Spencer B, Coffee E, Patel P, Michael S, Patrick C, Adame A, Rockenstein E, Masliah E. 2011. α-Synuclein Sequesters Dnmt1 from the Nucleus. Journal of Biological Chemistry. 286(11):9031–9037. doi:10.1074/jbc.C110.212589. De Deurwaerdère P, Bonhomme N, Lucas G, Le Moal M, Spampinato U. 1996. Serotonin Enhances Striatal Dopamine Outflow In Vivo Through Dopamine Uptake Sites. J Neurochem. 66(1):210–215. doi:10.1046/j.1471-4159.1996.66010210.x. Diao J, Burré J, Vivona S, Cipriano DJ, Sharma M, Kyoung M, Südhof TC, Brunger AT. 2013. Native α-synuclein induces clustering of synaptic-vesicle mimics via binding to phospholipids and synaptobrevin-2/VAMP2. Elife. 2013(2). doi:10.7554/eLife.00592. Dong XX, Wang Y, Qin ZH. 2009. Molecular mechanisms of excitotoxicity and their relevance to pathogenesis of neurodegenerative diseases. Acta Pharmacol Sin. 30(4):379–387. doi:10.1038/aps.2009.24. Dorsey ER, Constantinescu R, Thompson JP, Biglan KM, Holloway RG, Kieburtz K, Marshall FJ, Ravina BM, Schifitto G, Siderowf A, et al. 2007. Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology. 68(5):384–386. doi:10.1212/01.wnl.0000247740.47667.03. Duffy MF, Collier TJ, Patterson JR, Kemp CJ, Luk KC, Tansey MG, Paumier KL, Kanaan NM, Fischer LD, Polinski NK, et al. 2018. Lewy body-like alpha-synuclein inclusions trigger reactive microgliosis prior to nigral degeneration. J Neuroinflammation. 15(1). doi:10.1186/s12974-018-1171-z. Dupont C, Armant D, Brenner C. 2009. Epigenetics: Definition, Mechanisms and Clinical Perspective. Semin Reprod Med. 27(05):351–357. doi:10.1055/s-0029-1237423. Van Den Eeden SK, Tanner CM, Bernstein AL, Fross RD, Leimpeter A, Bloch DA, Nelson LM. 2003. Incidence of Parkinson’s disease: Variation by age, gender, and race/ethnicity. Am J Epidemiol. 157(11):1015–1022. doi:10.1093/aje/kwg068. 70 Efremova L, Schildknecht S, Adam M, Pape R, Gutbier S, Hanf B, Bürkle A, Leist M. 2015. Prevention of the degeneration of human dopaminergic neurons in an astrocyte co-culture system allowing endogenous drug metabolism. Br J Pharmacol. 172(16):4119–4132. doi:10.1111/bph.13193. Eisbach SE, Outeiro TF. 2013. Alpha-Synuclein and intracellular trafficking: Impact on the spreading of Parkinson’s disease pathology. J Mol Med. 91(6):693–703. doi:10.1007/s00109-013-1038-9. Elbaz A, Clavel J, Rathouz PJ, Moisan F, Galanaud JP, Delemotte B, Alpérovitch A, Tzourio C. 2009. Professional exposure to pesticides and Parkinson disease. Ann Neurol. 66(4):494–504. doi:10.1002/ana.21717. Emmenegger M, De Cecco E, Hruska‐Plochan M, Eninger T, Schneider MM, Barth M, Tantardini E, de Rossi P, Bacioglu M, Langston RG, et al. 2021. LAG3 is not expressed in human and murine neurons and does not modulate α‐synucleinopathies. EMBO Mol Med. 13(9):1–20. doi:10.15252/emmm.202114745. Faulk C, Dolinoy DC. 2011. Timing is everything: The when and how of environmentally induced changes in the epigenome of animals. Epigenetics. 6(7):791–797. doi:10.4161/epi.6.7.16209. Feng C, Flores M, Dhoj C, Garcia A, Belleca S, Abbas DA, Parres-Gold J, Anguiano A, Porter E, Wang Y. 2022. Observation of α-Synuclein Preformed Fibrils Interacting with SH-SY5Y Neuroblastoma Cell Membranes Using Scanning Ion Conductance Microscopy. ACS Chem Neurosci. 13(24):3547–3553. doi:10.1021/acschemneuro.2c00478. Fleming L, Mann JB, Bean J, Briggle T, Sanchez-Ramos JR. 1994. Parkinson’s disease and brain levels of organochlorine pesticides. Ann Neurol. 36(1):100–3. doi:10.1002/ana.410360119. Fleming SM. 2017. Mechanisms of Gene-Environment Interactions in Parkinson’s Disease. Curr Environ Health Rep. 4(2):192–199. doi:10.1007/s40572-017-0143-2. Fouke KE, Wegman ME, Weber SA, Brady EB, Román-Vendrell C, Morgan JR. 2021. Synuclein Regulates Synaptic Vesicle Clustering and Docking at a Vertebrate Synapse. Front Cell Dev Biol. 9. doi:10.3389/fcell.2021.774650. Freire C, Koifman S. 2012. Pesticide exposure and Parkinson’s disease: Epidemiological evidence of association. Neurotoxicology. 33(5):947–971. doi:10.1016/j.neuro.2012.05.011. Funayama M, Nishioka K, Li Y, Hattori N. 2023. Molecular genetics of Parkinson’s disease: Contributions and global trends. J Hum Genet. 68(3):125–130. doi:10.1038/s10038-022-01058-5. 71 Gagnon D, Gregoire L, Di Paolo T, Parent M. 2016. Serotonin hyperinnervation of the striatum with high synaptic incidence in parkinsonian monkeys. Brain Struct Funct. 221(7):3675–3691. doi:10.1007/s00429-015-1125-5. Games D, Valera E, Spencer B, Rockenstein E, Mante M, Adame A, Patrick C, Ubhi K, Nuber S, Sacayon P, et al. 2014. Reducing C-Terminal-Truncated Alpha-Synuclein by Immunotherapy Attenuates Neurodegeneration and Propagation in Parkinson’s Disease-Like Models. Journal of Neuroscience. 34(28):9441–9454. doi:10.1523/JNEUROSCI.5314-13.2014. Gao J, Perera G, Bhadbhade M, Halliday GM, Dzamko N. 2019a. Autophagy activation promotes clearance of α-synuclein inclusions in fibril-seeded human neural cells. Journal of Biological Chemistry. 294(39):14241–14256. doi:10.1074/jbc.RA119.008733. Gao J, Perera G, Bhadbhade M, Halliday GM, Dzamko N. 2019b. Autophagy activation promotes clearance of α-synuclein inclusions in fibril-seeded human neural cells. Journal of Biological Chemistry. 294(39):14241–14256. doi:10.1074/jbc.RA119.008733. Gao V, Briano JA, Komer LE, Burré J. 2023. Functional and Pathological Effects of α- Synuclein on Synaptic SNARE Complexes. J Mol Biol. 435(1). doi:10.1016/j.jmb.2022.167714. Gaspar P, Febvret A, Colombo J. 1993. Serotonergic sprouting in primate MTP-induced hemiparkinsonism. Exp Brain Res. 96(1):100–106. doi:10.1007/BF00230443. Gaugler MN, Genc O, Bobela W, Mohanna S, Ardah MT, El-Agnaf OM, Cantoni M, Bensadoun JC, Schneggenburger R, Knott GW, et al. 2012. Nigrostriatal overabundance of α-synuclein leads to decreased vesicle density and deficits in dopamine release that correlate with reduced motor activity. Acta Neuropathol. 123(5):653–669. doi:10.1007/s00401-012-0963-y. Ge P, Dawson VL, Dawson TM. 2020. PINK1 and Parkin mitochondrial quality control: a source of regional vulnerability in Parkinson’s disease. Mol Neurodegener. 15(1):20. doi:10.1186/s13024-020-00367-7. Gehrke S, Imai Y, Sokol N, Lu B. 2010. Pathogenic LRRK2 negatively regulates microRNA-mediated translational repression. Nature. 466(7306):637–641. doi:10.1038/nature09191. Gelpi E, Navarro-Otano J, Tolosa E, Gaig C, Compta Y, Rey MJ, Martí MJ, Hernández I, Valldeoriola F, Reñé R, et al. 2014. Multiple organ involvement by alpha-synuclein pathology in lewy body disorders. Movement Disorders. 29(8):1010–1018. doi:10.1002/mds.25776. Gezer AO, Kochmanski J, VanOeveren SE, Cole-Strauss A, Kemp CJ, Patterson JR, Miller KM, Kuhn NC, Herman DE, McIntire A, et al. 2020. Developmental exposure to the organochlorine pesticide dieldrin causes male-specific exacerbation of α-synuclein- preformed fibril-induced toxicity and motor deficits. Neurobiol Dis. 72 141(February):104947. doi:10.1016/j.nbd.2020.104947. https://doi.org/10.1016/j.nbd.2020.104947. Giasson BI, Forman MS, Higuchi M, Golbe LI, Graves CL, Kotzbauer PT, Trojanowski JQ, Lee VM-Y. 2003. Initiation and Synergistic Fibrillization of Tau and Alpha-Synuclein. Science (1979). 300(5619):636–640. doi:10.1126/science.1082324. Goedert M. 2001. The significance of tau and α-synuclein inclusions in neurodegenerative diseases. Curr Opin Genet Dev. 11(3):343–351. doi:10.1016/S0959- 437X(00)00200-8. Goldman JE, Yen S-H, Chiu F-C, Peress NS. 1983. Lewy Bodies of Parkinson’s Disease Contain Neurofilament Antigens. Science (1979). 221(4615):1082–1084. doi:10.1126/science.6308771. Goldman SM. 2014. Environmental toxins and Parkinson’s disease. Annu Rev Pharmacol Toxicol. 54:141–164. doi:10.1146/annurev-pharmtox-011613-135937. Graham WC, Clarke CE, Boyce S, Sambrook MA, Crossman AR, Woodruff GN. 1990. Autoradiographic studies in animal models of hemi-parkinsonism reveal dopamine D 2 but not D1 receptor supersensitivity. II. Unilateral intra-carotid infusion of MPTP in the monkey (Macaca fascicularis). Hamza TH, Chen H, Hill-Burns EM, Rhodes SL, Montimurro J, Kay DM, Tenesa A, Kusel VI, Sheehan P, Eaaswarkhanth M, et al. 2011. Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson’s Disease Modifier Gene via Interaction with Coffee. PLoS Genet. 7(8):e1002237. doi:10.1371/journal.pgen.1002237. Harris G, Eschment M, Orozco SP, McCaffery JM, Maclennan R, Severin D, Leist M, Kleensang A, Pamies D, Maertens A, et al. 2018. Toxicity, recovery, and resilience in a 3D dopaminergic neuronal in vitro model exposed to rotenone. Arch Toxicol. 92(8):2587–2606. doi:10.1007/s00204-018-2250-8. http://dx.doi.org/10.1007/s00204- 018-2250-8. Harris G, Hogberg H, Hartung T, Smirnova L. 2017a. 3D differentiation of LUHMES cell line to study recovery and delayed neurotoxic effects. Curr Protoc Toxicol. 2017(August):1–28. doi:10.1002/cptx.29. Harris G, Hogberg H, Hartung T, Smirnova L. 2017b. 3D Differentiation of LUHMES Cell Line to Study Recovery and Delayed Neurotoxic Effects. Curr Protoc Toxicol. 73:11.23.1-11.23.28. doi:10.1002/cptx.29. Hatcher JM, Richardson JR, Guillot TS, McCormack AL, Di Monte DA, Jones DP, Pennell KD, Miller GW. 2007. Dieldrin exposure induces oxidative damage in the mouse nigrostriatal dopamine system. Exp Neurol. 204(2):619–630. doi:10.1016/j.expneurol.2006.12.020. 73 Heindel JJ, Vandenberg LN. 2015. Developmental origins of health and disease: A paradigm for understanding disease cause and prevention. Curr Opin Pediatr. 27(2):248–253. doi:10.1097/MOP.0000000000000191. Heinz GH, Hill EF, Contrera JF. 1980. Dopamine and norepinephrine depletion in ring doves fed DDE, dieldrin, and Aroclor 1254. Toxicol Appl Pharmacol. 53(1):75–82. doi:10.1016/0041-008X(80)90383-X. Heinzel S, Berg D, Gasser T, Chen H, Yao C, Postuma RB. 2019. Update of the MDS research criteria for prodromal Parkinson’s disease. Movement Disorders. 34(10):1464– 1470. doi:10.1002/mds.27802. Heusinkveld HJ, Westerink RHS. 2012. Organochlorine insecticides lindane and dieldrin and their binary mixture disturb calcium homeostasis in dopaminergic PC12 cells. Environ Sci Technol. 46(3):1842–1848. doi:10.1021/es203303r. Hill-Burns EM, Singh N, Ganguly P, Hamza TH, Montimurro J, Kay DM, Yearout D, Sheehan P, Frodey K, Mclear JA, et al. 2013. A genetic basis for the variable effect of smoking/nicotine on Parkinson’s disease. Pharmacogenomics J. 13(6):530–537. doi:10.1038/tpj.2012.38. Hirsch EC, Alvarez-Fischer D, Andreas H, Oertel WH, Höglinger GU, Roscher R, Vulinovic F, Höllerhage M, Sturn A, Noelker C, et al. 2015. Glucocerebrosidase deficiency and mitochondrial impairment in experimental Parkinson disease. J Neurol Sci. 356(1–2):129–136. doi:10.1016/j.jns.2015.06.030. Hogberg HT, Bressler J, Christian KM, Harris G, Makri G, O’Driscoll C, Pamies D, Smirnova L, Wen Z, Hartung T. 2013. Toward a 3D model of human brain development for studying gene/environment interactions. Stem Cell Res Ther. 4(S1):S4. doi:10.1186/scrt365. Hogberg HT, Smirnova L. 2022. The Future of 3D Brain Cultures in Developmental Neurotoxicity Testing. Frontiers in Toxicology. 4. doi:10.3389/ftox.2022.808620. Hornykiewicz O. 1966. DOPAMINE (3-HYDROXYTYRAMINE) AND BRAIN FUNCTION. Iannitelli AF, Kelberman MA, Lustberg DJ, Korukonda A, McCann KE, Mulvey B, Segal A, Liles LC, Sloan SA, Dougherty JD, et al. 2023. The Neurotoxin DSP-4 Dysregulates the Locus Coeruleus-Norepinephrine System and Recapitulates Molecular and Behavioral Aspects of Prodromal Neurodegenerative Disease. eNeuro. 10(1). doi:10.1523/ENEURO.0483-22.2022. Ikeda T, Nagata K, Honda H, Shono1 T, Narahashi2 T. 1998. Insecticidal Activity of Sikimi Extract and Its Modulation of the Receptor Channel GABA A. Iranzo A, Ramos LA, Novo S. 2021. The Isolated Form of Rapid Eye Movement Sleep Behavior Disorder. Sleep Med Clin. 16(2):335–348. doi:10.1016/j.jsmc.2021.03.002. 74 Jackson-Lewis V, Przedborski S. 2007. Protocol for the MPTP mouse model of Parkinson’s disease. Nat Protoc. 2(1):141–151. doi:10.1038/nprot.2006.342. Jagmag SA, Tripathi N, Shukla SD, Maiti S, Khurana S. 2016. Evaluation of models of Parkinson’s disease. Front Neurosci. 9(JAN). doi:10.3389/fnins.2015.00503. Jensen MB, Bhatia VK, Jao CC, Rasmussen JE, Pedersen SL, Jensen KJ, Langen R, Stamou D. 2011. Membrane Curvature Sensing by Amphipathic Helices. Journal of Biological Chemistry. 286(49):42603–42614. doi:10.1074/jbc.M111.271130. Jiang W, Ju C, Jiang H, Zhang D. 2014. Dairy foods intake and risk of Parkinson’s disease: a dose–response meta-analysis of prospective cohort studies. Eur J Epidemiol. 29(9):613–619. doi:10.1007/s10654-014-9921-4. Jiménez-Sánchez L, Blesa J, Del Rey NL, Monje MHG, Obeso JA, Cavada C. 2020. Serotonergic innervation of the striatum in a nonhuman primate model of Parkinson’s disease. Neuropharmacology. 170. doi:10.1016/j.neuropharm.2019.107806. Jin H, Kanthasamy A, Ghosh A, Yang Y, Anantharam V, Kanthasamy AG. 2011. α- Synuclein Negatively Regulates Protein Kinase Cδ Expression to Suppress Apoptosis in Dopaminergic Neurons by Reducing p300 Histone Acetyltransferase Activity. The Journal of Neuroscience. 31(6):2035–2051. doi:10.1523/JNEUROSCI.5634-10.2011. Jo H, Kim D, Song J, Choi S, Joo E. 2021. Sleep Disturbances and Phenoconversion in Patients with REM Sleep Behavior Disorder. J Clin Med. 10(20):4709. doi:10.3390/jcm10204709. de Jong Geert, H Swaen GM, M Slangen Joseph J, M Slangen J J, de Jong G. 1997. Mortality of workers exposed to dieldrin and aldrin: a retrospective cohort study. Occup Environ Med. 54:702–707. doi:10.1136/oem.54.10.702. Jorgenson JL. 2001. Aldrin and dieldrin: a review of research on their production, environmental deposition and fate, bioaccumulation, toxicology, and epidemiology in the United States. Environ Health Perspect. 109(suppl 1):113–139. doi:10.1289/ehp.01109s1113. Jowaed A, Schmitt I, Kaut O, Wüllner U. 2010. Methylation Regulates Alpha-Synuclein Expression and Is Decreased in Parkinson’s Disease Patients’ Brains. The Journal of Neuroscience. 30(18):6355–6359. doi:10.1523/JNEUROSCI.6119-09.2010. Jucker M, Walker LC. 2013. Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature. 501(7465):45–51. doi:10.1038/nature12481. Jucker M, Walker LC. 2018. Propagation and spread of pathogenic protein assemblies in neurodegenerative diseases. Nat Neurosci. 21(10):1341–1349. doi:10.1038/s41593- 018-0238-6. 75 Kanthasamy AG, Kitazawa M, Kanthasamy A, Anantharam V. 2005. Dieldrin-induced neurotoxicity: Relevance to Parkinson’s disease pathogenesis. Neurotoxicology. 26(4 SPEC. ISS.):701–719. doi:10.1016/j.neuro.2004.07.010. Kappil M, Lambertini L, Chen J. 2015. Environmental Influences on Genomic Imprinting. Curr Environ Health Rep. 2(2):155–162. doi:10.1007/s40572-015-0046-z. Karstaedt P, Kersasidis H, Pincus J, Meloni R, Graham J, Gale K. 1994. Unilateral Destruction of Dopamine Pathways Increases Ipsilateral Striatal Serotonin Turnover in Rats. Exp Neurol. 126(1):25–30. Kidd SK, Schneider JS. 2010. Protection of dopaminergic cells from MPP+-mediated toxicity by histone deacetylase inhibition. Brain Res. 1354:172–178. doi:10.1016/j.brainres.2010.07.041. Kidd SK, Schneider JS. 2011. Protective effects of valproic acid on the nigrostriatal dopamine system in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mouse model of Parkinson’s disease. Neuroscience. 194:189–194. doi:10.1016/j.neuroscience.2011.08.010. Killinger B, Labrie V. 2019. The Appendix in Parkinson’s Disease: From Vestigial Remnant to Vital Organ? J Parkinsons Dis. 9(s2):S345–S358. doi:10.3233/JPD-191703. Killinger BA, Madaj Z, Sikora JW, Rey N, Haas AJ, Vepa Y, Lindqvist D, Chen H, Thomas PM, Brundin P, et al. 2018. The vermiform appendix impacts the risk of developing Parkinson’s disease. Sci Transl Med. 10(465). doi:10.1126/scitranslmed.aar5280. Kim TD, Paik SR, Yang C-H. 2002. Structural and Functional Implications of C-Terminal Regions of α-Synuclein. Biochemistry. 41(46):13782–13790. doi:10.1021/bi026284c. Kitazawa M, Anantharam V, Kanthasamy AG. 2001. Dieldrin-induced oxidative stress and neurochemical changes contribute to apoptopic cell death in dopaminergic cells. Free Radic Biol Med. 31(11):1473–1485. doi:10.1016/S0891-5849(01)00726-2. Kitazawa M, Anantharam V, Kanthasamy AG. 2003. Dieldrin induces apoptosis by promoting caspase-3-dependent proteolytic cleavage of protein kinase Cδ in dopaminergic cells: Relevance to oxidative stress and dopaminergic degeneration. Neuroscience. 119(4):945–964. doi:10.1016/S0306-4522(03)00226-4. Klein C, Westenberger A. 2012. Genetics of Parkinson’s disease. Cold Spring Harb Perspect Med. 2(1). doi:10.1101/cshperspect.a008888. Ko KR, Tam NW, Teixeira AG, Frampton JP. 2020. SH‐SY5Y and LUHMES cells display differential sensitivity to MPP+, tunicamycin, and epoxomicin in 2D and 3D cell culture. Biotechnol Prog. 36(2):e2942. doi:10.1002/btpr.2942. [accessed 2021 Mar 10]. https://onlinelibrary.wiley.com/doi/abs/10.1002/btpr.2942. 76 Kochmanski J, Bernstein AI. 2007. The impact of environmental factors on 5- Hydroxymethylctosine in the Brain. Toxicol Lett. 172:S19–S20. doi:10.1016/j.toxlet.2007.05.075. Kochmanski Joesph, Vanoeveren SE, Bernstein AI. 2019. Developmental Dieldrin Exposure Alters DNA Methylation at Genes Related to Dopaminergic Neuron Development and Parkinson’s Disease in Mouse Midbrain. Toxicol Sci. 169(2):593–607. doi:10.1093/toxsci/kfz069. [accessed 2023 Apr 5]. https://pubmed.ncbi.nlm.nih.gov/30859219/. Kochmanski Joseph, Vanoeveren SE, Patterson JR, Bernstein AI. 2019. Developmental dieldrin exposure alters DNA methylation at genes related to dopaminergic neuron development and Parkinson’s disease in mouse midbrain. Toxicological Sciences. 169(2):593–607. doi:10.1093/toxsci/kfz069. Konovalova EV, Lopacheva OM, Grivennikov IA, Lebedeva OS, Dashinimaev EB, Khaspekov LG, Fedotova EY, Illarioshkin SN. 2015. Mutations in Parkinson’s Disease- Associated PARK2 Gene Are Accompanied by Imbalance in Programmed Cell Death Systems. Acta Naturae. 4(27). Kontopoulos E, Parvin JD, Feany MB. 2006. α-synuclein acts in the nucleus to inhibit histone acetylation and promote neurotoxicity. Hum Mol Genet. 15(20):3012–3023. doi:10.1093/hmg/ddl243. Kordower JH, Olanow CW, Dodiya HB, Chu Y, Beach TG, Adler CH, Halliday GM, Bartus RT. 2013. Disease duration and the integrity of the nigrostriatal system in Parkinson’s disease. Brain. 136(8):2419–2431. doi:10.1093/brain/awt192. Kraft AD, Aschner M, Cory-Slechta DA, Bilbo SD, Caudle WM, Makris SL. 2016. Unmasking silent neurotoxicity following developmental exposure to environmental toxicants. Neurotoxicol Teratol. 55:38–44. doi:10.1016/j.ntt.2016.03.005. Kriaucionis S, Tahiliani M. 2014. Expanding the Epigenetic Landscape: Novel Modifications of Cytosine in Genomic DNA. Cold Spring Harb Perspect Biol. 6(10):a018630–a018630. doi:10.1101/cshperspect.a018630. Krug AK, Gutbier S, Zhao L, Pöltl D, Kullmann C, Ivanova V, Förster S, Jagtap S, Meiser J, Leparc G, et al. 2014. Transcriptional and metabolic adaptation of human neurons to the mitochondrial toxicant MPP +. Cell Death Dis. 5(5):e1222–e1222. doi:10.1038/cddis.2014.166. Lardenoije R, Iatrou A, Kenis G, Kompotis K, Steinbusch HWM, Mastroeni D, Coleman P, Lemere CA, Hof PR, van den Hove DLA, et al. 2015. The epigenetics of aging and neurodegeneration. Prog Neurobiol. 131:21–64. doi:10.1016/j.pneurobio.2015.05.002. http://dx.doi.org/10.1016/j.pneurobio.2015.05.002. 77 Lardenoije R, Pishva E, Lunnon K, van den Hove DL. 2018. Neuroepigenetics of Aging and Age-Related Neurodegenerative Disorders. 1st ed. Elsevier Inc. http://dx.doi.org/10.1016/bs.pmbts.2018.04.008. Larsen KE, Schmitz Y, Troyer MD, Mosharov E, Dietrich P, Quazi AZ, Savalle M, Nemani V, Chaudhry FA, Edwards RH, et al. 2006. α-Synuclein overexpression in PC12 and chromaffin cells impairs catecholamine release by interfering with a late step in exocytosis. Journal of Neuroscience. 26(46):11915–11922. doi:10.1523/JNEUROSCI.3821-06.2006. Lautenschläger J, Stephens AD, Fusco G, Ströhl F, Curry N, Zacharopoulou M, Michel CH, Laine R, Nespovitaya N, Fantham M, et al. 2018. C-terminal calcium binding of α- synuclein modulates synaptic vesicle interaction. Nat Commun. 9(1). doi:10.1038/s41467-018-03111-4. Lauter G, Coschiera A, Yoshihara M, Sugiaman-Trapman D, Ezer S, Sethurathinam S, Katayama S, Kere J, Swoboda P. 2020. Differentiation of ciliated human midbrain- derived LUHMES neurons. J Cell Sci. 133(21). doi:10.1242/jcs.249789. [accessed 2021 Mar 10]. https://jcs.biologists.org/content/133/21/jcs249789. Lawson LJ, Perry VH, Dri P, Gordon S. 1990. Heterogeneity in the distribution and morphology of microglia in the normal adult mouse brain. Neuroscience. 39(1):151–170. doi:10.1016/0306-4522(90)90229-W. Leah T, Vazquez-Villaseñor I, Ferraiuolo L, Wharton S, Mortiboys H. 2021. A Parkinson’s Disease-relevant Mitochondrial and Neuronal Morphology High-throughput Screening Assay in LUHMES Cells. Bio Protoc. 11(1). doi:10.21769/BioProtoc.3881. Lecours C, Bordeleau M, Cantin L, Parent M, Paolo T Di, Tremblay M-È. 2018. Microglial Implication in Parkinson’s Disease: Loss of Beneficial Physiological Roles or Gain of Inflammatory Functions? Front Cell Neurosci. 12. doi:10.3389/fncel.2018.00282. Lee H-J, Choi C, Lee S-J. 2002. Membrane-bound α-Synuclein Has a High Aggregation Propensity and the Ability to Seed the Aggregation of the Cytosolic Form. Journal of Biological Chemistry. 277(1):671–678. doi:10.1074/jbc.M107045200. Lee H-J, Lee S-J. 2002. Characterization of Cytoplasmic α-Synuclein Aggregates. Journal of Biological Chemistry. 277(50):48976–48983. doi:10.1074/jbc.M208192200. Lee TK, Yankee EL. 2022. A review on Parkinson’s disease treatment. Neuroimmunol Neuroinflamm. 8:222. doi:10.20517/2347-8659.2020.58. Leite PEC, Pereira MR, Harris G, Pamies D, Dos Santos LMG, Granjeiro JM, Hogberg HT, Hartung T, Smirnova L. 2019. Suitability of 3D human brain spheroid models to distinguish toxic effects of gold and poly-lactic acid nanoparticles to assess biocompatibility for brain drug delivery. Part Fibre Toxicol. 16(1):1–20. doi:10.1186/s12989-019-0307-3. 78 Liang L, Jiang D. 1991. Effect of 6-hydroxydopamine on cerebral catecholamines, lipid peroxidation and antioxidant enzymes in rats-concerned with pathogenesis of Parkinson’s disease. Chinese Journal of Neurology and Psychiatry. 24(4):223–227. Lill CM. 2016. Genetics of Parkinson’s disease. Mol Cell Probes. 30(6):386–396. doi:10.1016/j.mcp.2016.11.001. Lin H, Tang R, Fan L, Wang E. 2022. Exogenous Tetranectin Alleviates Pre-formed- fibrils-induced Synucleinopathies in SH-SY5Y Cells by Activating the Plasminogen Activation System. Neurochem Res. 47(10):3192–3201. doi:10.1007/s11064-022- 03673-2. Liu J;, Brannen KC;, Grayson DR, Morrow A, Leslie ;, Devaud LL;, Lauder J. 1998. Prenatal Exposure to the Pesticide Dieldrin or the GABAA Receptor. Liu J, Brannen KC, Grayson DR, Morrow AL, Devaud LL, Lauder JM. 1998. Prenatal exposure to the pesticide dieldrin or the GABA(A) receptor antagonist bicuculline differentially alters expression of GABA(A) receptor subunit mRNAs in fetal rat brainstem. Dev Neurosci. 20(1):83–92. doi:10.1159/000017302. Liu J, Morrow AL, Devaud LL, Grayson DR, Lauder JM. 1997. Regulation of GABA(A) receptor subunit mRNA expression by the pesticide dieldrin in embryonic brainstem cultures: A quantitative, competitive reverse transcription-polymerase chain reaction study. J Neurosci Res. 49(5):645–653. doi:10.1002/(SICI)1097- 4547(19970901)49:5<645::AID-JNR15>3.0.CO;2-U. Lohr KM, Chen M, Hoffman CA, McDaniel MJ, Stout KA, Dunn AR, Wang M, Bernstein AI, Miller GW. 2016. Vesicular monoamine transporter 2 (VMAT2) level regulates MPTP vulnerability and clearance of excess dopamine in mouse striatal terminals. Toxicological Sciences. 153(1):79–88. doi:10.1093/toxsci/kfw106. Lopes FM, Bristot IJ, da Motta LL, Parsons RB, Klamt F. 2017. Mimicking Parkinson’s Disease in a Dish: Merits and Pitfalls of the Most Commonly used Dopaminergic In Vitro Models. Neuromolecular Med. 19(2–3):241–255. doi:10.1007/s12017-017-8454-x. Lotharius J, Barg S, Wiekop P, Lundberg C, Raymon HK, Brundin P. 2002. Effect of Mutant α-Synuclein on Dopamine Homeostasis in a New Human Mesencephalic Cell Line. Journal of Biological Chemistry. 277(41):38884–38894. doi:10.1074/jbc.M205518200. Lotharius J, Falsig J, van Beek J, Payne S, Dringen R, Brundin P, Leist M. 2005. Progressive degeneration of human mesencephalic neuron-derived cells triggered by dopamine-dependent oxidative stress is dependent on the mixed-lineage kinase pathway. The Journal of neuroscience. 25(27):6329–42. doi:10.1523/JNEUROSCI.1746-05.2005. Luk K, Song C, O’Brien P, Stieber A, Branch JR, Brunden KR, Trojanowski JQ, Lee VMY. 2009. Exogenous α-synuclein fibrils seed the formation of Lewy body-like 79 intracellular inclusions in cultured cells. Proc Natl Acad Sci U S A. 106(47):20051– 20056. doi:10.1073/pnas.0908005106. Luk KC, Kehm V, Carroll J, Zhang B, O’Brein P, Trojanowski JQ, Lee VM-Y. 2012. Pathological α-Synuclein Transmission Initiates Parkinson-like Neurodegeneration in Non-transgenic Mice. Science (1979). 338(6109):949–953. doi:10.1126/science.1227157. Luthman J, Fredriksson A, Sundström E, Jonsson G, Archer T. 1989. Selective lesion of central dopamine or noradrenaline neuron systems in the neonatal rat: motor behavior and monoamine alterations at adult stage. Behavioural Brain Research. 33(3):267–277. doi:10.1016/S0166-4328(89)80121-4. Maeda T, Kannari K, Shen H, Arai A, Tomiyama M, Matsunaga M, Suda T. 2003. Rapid induction of serotonergic hyperinnervation in the adult rat striatum with extensive dopaminergic denervation. Neurosci Lett. 343(1):17–20. doi:10.1016/S0304- 3940(03)00295-7. Maiti P, Manna J, Dunbar GL, Maiti P, Dunbar GL. 2017. Current understanding of the molecular mechanisms in Parkinson’s disease: Targets for potential treatments. Transl Neurodegener. 6(1). doi:10.1186/s40035-017-0099-z. Maries E, Dass B, Collier TJ, Kordower JH, Steece-Collier K. 2003. The role of α- synuclein in Parkinson’s disease: insights from animal models. Nat Rev Neurosci. 4(9):727–738. doi:10.1038/nrn1199. Marques O, Outeiro TF. 2012. Alpha-synuclein: from secretion to dysfunction and death. Cell Death Dis. 3(7):e350–e350. doi:10.1038/cddis.2012.94. Marques S, Outeiro TF. 2013. Epigenetics in Parkinson’s and Alzheimer’s Diseases. Subcell Biochem. 61:507–525. doi:10.1007/978-94-007-4525-4_22. Marques SCF, Oliveira CR, Pereira CMF, Outeiro TF. 2011. Epigenetics in neurodegeneration: A new layer of complexity. Prog Neuropsychopharmacol Biol Psychiatry. 35(2):348–355. doi:10.1016/j.pnpbp.2010.08.008. http://dx.doi.org/10.1016/j.pnpbp.2010.08.008. Martin GE, Myers RD, Newberg DC. 1976. Catecholamine release by intracerebral perfusion of 6-hydroxydopamine and desipramine. Eur J Pharmacol. 36(2):299–311. doi:10.1016/0014-2999(76)90083-2. Matsuda W, Furuta T, Nakamura KC, Hioki H, Fujiyama F, Arai R, Kaneko T. 2009. Single Nigrostriatal Dopaminergic Neurons Form Widely Spread and Highly Dense Axonal Arborizations in the Neostriatum. The Journal of Neuroscience. 29(2):444–453. doi:10.1523/JNEUROSCI.4029-08.2009. 80 Matsumoto L, Takuma H, Tamaoka A, Kurisaki H, Date H, Tsuji S, Iwata A. 2010. CpG Demethylation Enhances Alpha-Synuclein Expression and Affects the Pathogenesis of Parkinson’s Disease. PLoS One. 5(11):e15522. doi:10.1371/journal.pone.0015522. Di Matteo V, Pierucci M, Esposito E, Crescimanno G, Benigno A, Di Giovanni G. 2008. Serotonin modulation of the basal ganglia circuitry: therapeutic implication for Parkinson’s disease and other motor disorders. Prog Brain Res. 172:423–463. doi:10.1016/S0079-6123(08)00921-7. Mehler-Wex C, Riederer P, Gerlach M. 2006. Dopaminergic Dysbalance in Distinct Basal Ganglia Neurocircuits: Implications for the Pathophysiology of Parkinson´s Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. Neurotox Res. 10:167–179. doi:10.1007/BF03033354. Mehrotra B.D., Moorthy K.S., Ravichandra Reddy S., Desaiah D. 1989. Effects of cyclodiene compounds on calcium pump activity in rat brain and heart. Toxicology. doi:10.1016/0300-483x(89)90075-9. Mehrotra B.D., Ravichandra Reddy S., Desaiah D. 1988. Effect of subchronic dieldrin treatment on calmodulin-regulated ca2+ pump activity in rat brain. J Toxicol Environ Health. 25(4):461–469. doi:10.1080/15287398809531224. Meijer SN, Halsall CJ, Harner T, Peters AJ, Ockenden WA, Johnston AE, Jones KC. 2001. Organochlorine pesticide residues in archived UK soil. Environ Sci Technol. 35(10):1989–95. doi:10.1021/es0000955. Middleton ER, Rhoades E. 2010. Effects of Curvature and Composition on α-Synuclein Binding to Lipid Vesicles. Biophys J. 99(7):2279–2288. doi:10.1016/j.bpj.2010.07.056. Miglis MG, Adler CH, Antelmi E, Arnaldi D, Baldelli L, Boeve BF, Cesari M, Dall’Antonia I, Diederich NJ, Doppler K, et al. 2021. Biomarkers of conversion to α-synucleinopathy in isolated rapid-eye-movement sleep behaviour disorder. Lancet Neurol. 20(8):671– 684. doi:10.1016/S1474-4422(21)00176-9. Miller GW. 2007. Paraquat: The Red Herring of Parkinson’s Disease Research. Toxicological Sciences. 100(1):1–2. doi:10.1093/toxsci/kfm223. Miller GW, Gainetdinov RR, Levey AI, Caron MG. 1999. Dopamine transporters and neuronal injury. Trends Pharmacol Sci. 20(10):424–429. doi:10.1016/S0165- 6147(99)01379-6. Miller GW, Taylor TN, Caudle WM. 2011. VMAT2-deficient mice display nigral and extranigral pathology and motor and nonmotor symptoms of Parkinson’s disease. Parkinsons Dis. 2011. doi:10.4061/2011/124165. Miller SJ. 2018. Astrocyte Heterogeneity in the Adult Central Nervous System. Front Cell Neurosci. 12. doi:10.3389/fncel.2018.00401. 81 Miyazaki I, Asanuma M. 2009. Approaches to Prevent Dopamine Quinone-Induced Neurotoxicity. Neurochem Res. 34(4):698–706. doi:10.1007/s11064-008-9843-1. Molina-Mateo D, Fuenzalida-Uribe N, Hidalgo S, Molina-Fernández C, Abarca J, Zárate R V., Escandón M, Figueroa R, Tevy MF, Campusano JM. 2017. Characterization of a presymptomatic stage in a Drosophila Parkinson’s disease model: Unveiling dopaminergic compensatory mechanisms. Biochim Biophys Acta Mol Basis Dis. 1863(11):2882–2890. doi:10.1016/j.bbadis.2017.07.013. Monti B, Gatta V, Piretti F, Raffaelli SS, Virgili M, Contestabile A. 2010. Valproic Acid is Neuroprotective in the Rotenone Rat Model of Parkinson’s Disease: Involvement of α- Synuclein. Neurotox Res. 17(2):130–141. doi:10.1007/s12640-009-9090-5. Moore LD, Le T, Fan G. 2013. DNA methylation and its basic function. Neuropsychopharmacology. 38(1):23–38. doi:10.1038/npp.2012.112. Moore R, Zigmond M. 1994. Compensatory mechanisms in central neurodegenerative disease. Neurodegener Dis.:355–369. Moretto A, Colosio C. 2011. Biochemical and toxicological evidence of neurological effects of pesticides: The example of Parkinson’s disease. Neurotoxicology. 32(4):383– 391. doi:10.1016/j.neuro.2011.03.004. Mosharov E V., Larsen KE, Kanter E, Phillips KA, Wilson K, Schmitz Y, Krantz DE, Kobayashi K, Edwards RH, Sulzer D. 2009. Interplay between Cytosolic Dopamine, Calcium, and α-Synuclein Causes Selective Death of Substantia Nigra Neurons. Neuron. 62(2):218–229. doi:10.1016/j.neuron.2009.01.033. Mounayar S, Boulet S, Tandé D, Jan C, Pessiglione M, Hirsch EC, Féger J, Savasta M, François C, Tremblay L. 2007. A new model to study compensatory mechanisms in MPTP-treated monkeys exhibiting recovery. Brain. 130(11):2898–2914. doi:10.1093/brain/awm208. Nalls MA, Blauwendraat C, Vallerga CL, Heilbron K, Bandres-Ciga S, Chang D, Tan M, Kia DA, Noyce AJ, Xue A, et al. 2019. Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet Neurol. 18(12):1091–1102. doi:10.1016/S1474-4422(19)30320-5. Narahashi T, Carter DB, Frey J, Ginsburg K, Hamilton BJ, Nagata K, Roy ML, Song J-H, Tatebayashi H. 1995. Sodium channels and GABA, receptor-channel targets of environmental toxicants. Toxicol Lett. 82:239–245. doi:10.1016/0378-4274(95)03482-x. Nemani VM, Lu W, Berge V, Nakamura K, Onoa B, Lee MK, Chaudhry FA, Nicoll RA, Edwards RH. 2010. Increased Expression of α-Synuclein Reduces Neurotransmitter Release by Inhibiting Synaptic Vesicle Reclustering after Endocytosis. Neuron. 65(1):66–79. doi:10.1016/j.neuron.2009.12.023. 82 Nicolai MM, Witt B, Friese S, Michaelis V, Hölz-Armstrong L, Martin M, Ebert F, Schwerdtle T, Bornhorst J. 2022. Mechanistic studies on the adverse effects of manganese overexposure in differentiated LUHMES cells. Food and Chemical Toxicology. 161:112822. doi:10.1016/j.fct.2022.112822. Noyce AJ, Bestwick JP, Silveira‐Moriyama L, Hawkes CH, Giovannoni G, Lees AJ, Schrag A. 2012. Meta‐analysis of early nonmotor features and risk factors for Parkinson disease. Ann Neurol. 72(6):893–901. doi:10.1002/ana.23687. Nuytemans K, Theuns J, Cruts M, Van Broeckhoven C. 2010. Genetic etiology of Parkinson disease associated with mutations in the SNCA, PARK2, PINK1, PARK7, and LRRK2 genes: A mutation update. Hum Mutat. 31(7):763–780. doi:10.1002/humu.21277. Obeso A, Rodriguez-Oroz MC, Rodriguez M, Lanciego L, Artieda J, Gonzalo N, Warren Olanow C, ObesG Maria Rodrfguez-Oroz AC, Artieda lulio, Gonzalo are N. 2000. Pathophysiology of the basal ganglia in Parkinson’s disease. Trends Neurosci.:8–19. doi:10.1016/s1471-1931(00)00028-8. Obeso JA, Rodriguez-Oroz MC, Lanciego JL, Rodriguez Diaz M, Bezard E, Gross CE, Brotchie JM. 2004. How does Parkinson’s disease begin? The role of compensatory mechanisms (multiple letters). Trends Neurosci. 27(3):125–127. doi:10.1016/j.tins.2003.12.006. Oliveira LMAAA, Falomir-Lockhart LJ, Botelho MG, Lin K-HHH, Wales P, Koch JC, Gerhardt E, Taschenberger H, Outeiro TF, Lingor P, et al. 2015. Elevated a-synuclein caused by SNCA gene triplication impairs neuronal differentiation and maturation in Parkinson’s patient-derived induced pluripotent stem cells. Cell Death Dis. 6(11):e1994– e1994. doi:10.1038/cddis.2015.318. Onn S-P, Berger TW, Stricker EM, Zigmond MJ. 1986. Effects of Intraventricular 6- Hydroxydopamine on the Dopaminergic Innervation of Striatum: Histochemical and Neurochemical Analysis. Brain Res. 376:8–19. doi:10.1016/0006-8993(86)90894-2. Outeiro TF, Kontopoulos E, Altmann SM, Kufareva I, Strathearn KE, Amore AM, Volk CB, Maxwell MM, Rochet J-C, McLean PJ, et al. 2007. Sirtuin 2 Inhibitors Rescue α- Synuclein-Mediated Toxicity in Models of Parkinson’s Disease. Science (1979). 317(5837):516–519. doi:10.1126/science.1143780. Pagano G, Niccolini F, Politis M. 2018. The serotonergic system in Parkinson’s patients with dyskinesia: evidence from imaging studies. J Neural Transm. 125(8):1217–1223. doi:10.1007/s00702-017-1823-7. Pang SY-Y, Ho PW-L, Liu H-F, Leung C-T, Li L, Chang EES, Ramsden DB, Ho S-L. 2019. The interplay of aging, genetics and environmental factors in the pathogenesis of Parkinson’s disease. Transl Neurodegener. 8(1):23. doi:10.1186/s40035-019-0165-9. 83 Pantazopoulou M, Brembati V, Kanellidi A, Bousset L, Melki R, Stefanis L. 2021. Distinct alpha‐Synuclein species induced by seeding are selectively cleared by the Lysosome or the Proteasome in neuronally differentiated SH‐SY5Y cells. J Neurochem. 156(6):880– 896. doi:10.1111/jnc.15174. Park SM, Jung HY, Kim TD, Park JH, Yang C-H, Kim J. 2002. Distinct Roles of the N- terminal-binding Domain and the C-terminal-solubilizing Domain of α-Synuclein, a Molecular Chaperone. Journal of Biological Chemistry. 277(32):28512–28520. doi:10.1074/jbc.M111971200. Parker MJ, Weigele PR, Saleh L. 2019. Insights into the Biochemistry, Evolution, and Biotechnological Applications of the Ten-Eleven Translocation (TET) Enzymes. Biochemistry. 58(6):450–467. doi:10.1021/acs.biochem.8b01185. Patterson JR, Duffy MF, Kemp CJ, Howe JW, Collier TJ, Stoll AC, Miller KM, Patel P, Levine N, Moore DJ, et al. 2019. Time course and magnitude of alpha-synuclein inclusion formation and nigrostriatal degeneration in the rat model of synucleinopathy triggered by intrastriatal α-synuclein preformed fibrils. Neurobiol Dis. 130(January). doi:10.1016/j.nbd.2019.104525. Paumier KL, Luk KC, Manfredsson FP, Kanaan NM, Lipton JW, Collier TJ, Steece- Collier K, Kemp CJ, Celano S, Schulz E, et al. 2015. Intrastriatal injection of pre-formed mouse α-synuclein fibrils into rats triggers α-synuclein pathology and bilateral nigrostriatal degeneration. Neurobiol Dis. 82:185–199. doi:10.1016/j.nbd.2015.06.003. Peng XM, Tehranian R, Dietrich P, Stefanis L, Perez RG. 2005. α-synuclein activation of protein phosphatase 2A reduces tyrosine hydroxylase phosphorylation in dopaminergic cells. J Cell Sci. 118(15):3523–3530. doi:10.1242/jcs.02481. Perez RG, Waymire JC, Lin E, Liu JJ, Guo F, Zigmond MJ. 2002. A Role for-Synuclein in the Regulation of Dopamine Biosynthesis. J Neurosci. 22(8):3090–3099. doi:10.1523/JNEUROSCI.22-08-03090.2002. Perfeito R, Lázaro DF, Outeiro TF, Rego AC. 2014. Linking alpha-synuclein phosphorylation to reactive oxygen species formation and mitochondrial dysfunction in SH-SY5Y cells. Molecular and Cellular Neuroscience. 62:51–59. doi:10.1016/j.mcn.2014.08.002. Pollanen MS, Dickson DW, Bergeron C. 1993. Pathology and Biology of the Lewy Body. J Neuropathol Exp Neurol. 52(3):183–191. doi:10.1097/00005072-199305000-00001. Pöltl D, Schildknecht S, Karreman C, Leist M. 2012. Uncoupling of ATP-depletion and cell death in human dopaminergic neurons. Neurotoxicology. 33(4):769–779. doi:10.1016/j.neuro.2011.12.007. Pomps A, Rodrfguez-Farr6 E, Sufiol C. 1993. Inhibition of t- [35S]butylbicyclophosphorothionate binding by convulsant agents in primary cultures of 84 cerebellar neurons. Developmental Brain Research. 73:85–90. doi:10.1016/0165- 3806(93)90049-g. Post MR, Lieberman OJ, Mosharov E V. 2018. Can interactions between α-synuclein, dopamine and calcium explain selective neurodegeneration in Parkinson’s disease? Front Neurosci. 12(MAR). doi:10.3389/fnins.2018.00161. Postuma RB, Berg D. 2016. Advances in markers of prodromal Parkinson disease. Nat Rev Neurol. 12(11):622–634. doi:10.1038/nrneurol.2016.152. Postuma RB, Berg D, Adler CH, Bloem BR, Chan P, Deuschl G, Gasser T, Goetz CG, Halliday G, Joseph L, et al. 2016. The new definition and diagnostic criteria of Parkinson’s disease. Lancet Neurol. 15(6):546–548. doi:10.1016/S1474- 4422(16)00116-2. Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, Obeso J, Marek K, Litvan I, Lang AE, et al. 2015. MDS clinical diagnostic criteria for Parkinson’s disease. Movement Disorders. 30(12):1591–1601. doi:10.1002/mds.26424. Power JHT, Barnes OL, Chegini F. 2017. Lewy Bodies and the Mechanisms of Neuronal Cell Death in Parkinson’s Disease and Dementia with Lewy Bodies. Brain Pathology. 27(1):3–12. doi:10.1111/bpa.12344. Pranke IM, Morello V, Bigay J, Gibson K, Verbavatz J-M, Antonny B, Jackson CL. 2011. α-Synuclein and ALPS motifs are membrane curvature sensors whose contrasting chemistry mediates selective vesicle binding. Journal of Cell Biology. 194(1):89–103. doi:10.1083/jcb.201011118. Priyadarshi A, Khuder S, Schaub E, Shirvastava S. 2000. A meta-analysis of Parkinson’s disease and exposure to pesticides. Neurotoxicology. 21(4):435–440. Priyadarshi A, Khuder SA, Schaub EA, Priyadarshi SS. 2001. Environmental risk factors and parkinson’s disease: A metaanalysis. Environ Res. 86(2):122–127. doi:10.1006/enrs.2001.4264. Puschmann A. 2013. Monogenic Parkinson’s disease and parkinsonism: Clinical phenotypes and frequencies of known mutations. Parkinsonism Relat Disord. 19(4):407–415. doi:10.1016/j.parkreldis.2013.01.020. Raheel K, Deegan G, Di Giulio I, Cash D, Ilic K, Gnoni V, Chaudhuri KR, Drakatos P, Moran R, Rosenzweig I. 2023. Sex differences in alpha-synucleinopathies: a systematic review. Front Neurol. 14. doi:10.3389/fneur.2023.1204104. Rarnsaysb RR, Singers TP. 1986. Energy-dependent Uptake of N-Methyl-4- phenylpyridinium, the Neurotoxic Metabolite of l-Methyl-4-Phenyl-1,2,3,6- tetrahydropyridine, by Mitochondria*. J Biol Chem. 261(17):7585–7587. 85 Rasmussen KD, Helin K. 2016. Role of TET enzymes in DNA methylation, development, and cancer. Genes Dev. 30(7):733–750. doi:10.1101/gad.276568.115. Reed MC, Nijhout HF, Best J. 2013. Computational studies of the role of serotonin in the basal ganglia. Front Integr Neurosci.(MAY). doi:10.3389/fnint.2013.00041. Richardson JR, Caudle WM, Wang M, Dean ED, Pennell KD, Miller GW, Richardson JR, Caudle WM, Wang M, Dean ED, et al. 2006a. Developmental exposure to the pesticide dieldrin alters the dopamine system and increases neurotoxicity in an animal model of Parkinson’s disease. The FASEB Journal. 20(10):1695–1697. doi:10.1096/fj.06-5864fje. Richardson JR, Caudle WM, Wang M, Dean ED, Pennell KD, Miller GW, Richardson JR, Caudle WM, Wang M, Dean ED, et al. 2006b. Developmental exposure to the pesticide dieldrin alters the dopamine system and increases neurotoxicity in an animal model of Parkinson’s disease. The FASEB Journal. 20(10):1695–1697. doi:10.1096/fj.06-5864fje. Richardson JR, Quan Y, Sherer TB, Greenamyre JT, Miller GW. 2005. Paraquat Neurotoxicity is Distinct from that of MPTP and Rotenone. Toxicological Sciences. 88(1):193–201. doi:10.1093/toxsci/kfi304. Riederer P, Lange KW, Kornhuber J, Danielczyk W. Glutamatergic-Dopaminergic Balance in the Brain Its importance in motor disorders and schizophrenia. Rietdijk CD, Perez-Pardo P, Garssen J, van Wezel RJA, Kraneveld AD. 2017. Exploring Braak’s hypothesis of parkinson’s disease. Front Neurol. 8(FEB). doi:10.3389/fneur.2017.00037. Ritz B, Yu F. 2000. Parkinson’s disease mortality and pesticide exposure in California 1984–1994. Int J Epidemiol. 29(3):323–329. doi:10.1093/ije/29.2.323. Rodriguez L, Marano MM, Tandon A. 2018. Import and export of misfolded α-synuclein. Front Neurosci. 12(MAY):1–9. doi:10.3389/fnins.2018.00344. Rodriguez-Farre E, Suñol C. 1995. Disruption of GABA-dependent chloride flux by cyclodienes and hexachlorocyclohexanes in primary cultures of cortical neurons Human IgE mAb View project Effects of organochlorine pesticides on glutamate neurotransmission View project Anna Pomés Indoor Biotechnologies. Article in Journal of Pharmacology and Experimental Therapeutics. Ross A, Xing V, Wang TT, Bureau SC, Link GA, Fortin T, Zhang H, Hayley S, Sun H. 2020a. Alleviating toxic α-Synuclein accumulation by membrane depolarization: Evidence from an in vitro model of Parkinson’s disease. Mol Brain. 13(1):1–11. doi:10.1186/s13041-020-00648-8. Ross A, Xing V, Wang TT, Bureau SC, Link GA, Fortin T, Zhang H, Hayley S, Sun H. 2020b. Alleviating toxic α-Synuclein accumulation by membrane depolarization: 86 evidence from an in vitro model of Parkinson’s disease. Mol Brain. 13(1):108. doi:10.1186/s13041-020-00648-8. Roy S. 2017. Synuclein and dopamine: The Bonnie and Clyde of Parkinson’s disease. Nat Neurosci. 20(11):1514–1515. doi:10.1038/nn.4660. Rozas G, Liste I, Guerra MJ, Labandeira-Garcia JL. 1998. Sprouting of the serotonergic afferents into striatum after selective lesion of the dopaminergic system by MPTP in adult mice. Neurosci Lett. doi:10.1016/s0304-3940(98)00198-0. Rush T, Liu XQ, Hjelmhaug J, Lobner D. 2010. Mechanisms of chlorpyrifos and diazinon induced neurotoxicity in cortical culture. Neuroscience. 166(3):899–906. doi:10.1016/j.neuroscience.2010.01.025. Sala G, Marinig D, Arosio A, Ferrarese C. 2016. Role of Chaperone-Mediated Autophagy Dysfunctions in the Pathogenesis of Parkinson’s Disease. Front Mol Neurosci. 9. doi:10.3389/fnmol.2016.00157. Sanchez-Ramos J, Facca A, Basit A, Song S. 1998. Toxicity of dieldrin for dopaminergic neurons in mesencephalic cultures. Exp Neurol. 150(2):263–271. doi:10.1006/exnr.1997.6770. Sariola H, Saarma M. 2003. Novel functions and signalling pathways for GDNF. J Cell Sci. 116(19):3855–3862. doi:10.1242/jcs.00786. Sassone J, Reale C, Dati G, Regoni M, Pellecchia MT, Garavaglia B. 2021. The Role of VPS35 in the Pathobiology of Parkinson’s Disease. Cell Mol Neurobiol. 41(2):199–227. doi:10.1007/s10571-020-00849-8. Satake W, Nakabayashi Y, Mizuta I, Hirota Y, Ito C, Kubo M, Kawaguchi T, Tsunoda T, Watanabe M, Takeda A, et al. 2009. Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson’s disease. Nat Genet. 41(12):1303–1307. doi:10.1038/ng.485. Schildknecht S, Karreman C, Pöltl D, Efrémova L, Kullmann C, Gutbier S, Krug A, Scholz D, Gerding HR, Leist M. 2013. Generation of genetically-modified human differentiated cells for toxicological tests and the study of neurodegenerative diseases. ALTEX. 30(4):427–444. doi:10.14573/altex.2013.4.427. Schimmöller F, Dı́az E, Mühlbauer B, Pfeffer SR. 1998. Characterization of a 76 kDa endosomal, multispanning membrane protein that is highly conserved throughout evolution. Gene. 216(2):311–318. doi:10.1016/S0378-1119(98)00349-7. Schmidt JT, Rushin A, Boyda J, Souders CL, Martyniuk CJ. 2017. Dieldrin-induced neurotoxicity involves impaired mitochondrial bioenergetics and an endoplasmic reticulum stress response in rat dopaminergic cells. Neurotoxicology. 63:1–12. doi:10.1016/j.neuro.2017.08.007. https://doi.org/10.1016/j.neuro.2017.08.007. 87 Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011a. Rapid, complete and large-scale generation of post-mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011b. Rapid, complete and large-scale generation of post-mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011c. Rapid, complete and large‐scale generation of post‐mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Schootman M. 2012. Predictors of Survival in Patients With Parkinson Disease. Arch Neurol. 69(5):601. doi:10.1001/archneurol.2011.2370. Scott B, Borgman A, Engler H, Johnels B, Aquilonius SM. 2000. Gender differences in Parkinson’s disease symptom profile. Acta Neurol Scand. 102(1):37–43. doi:10.1034/j.1600-0404.2000.102001037.x. Scott D, Roy S. 2012a. α-Synuclein inhibits intersynaptic vesicle mobility and maintains recycling-pool homeostasis. Journal of Neuroscience. 32(30):10129–10135. doi:10.1523/JNEUROSCI.0535-12.2012. Scott D, Roy S. 2012b. α-Synuclein inhibits intersynaptic vesicle mobility and maintains recycling-pool homeostasis. J Neurosci. 32(30):10129–35. doi:10.1523/JNEUROSCI.0535-12.2012. Semchuk KM, Love EJ, Lee RG. 1992. Parkinson’s disease and exposure to agricultural work and pesticide chemicals. Neurology. 42:1328–1335. doi:10.1212/wnl.42.7.1328. Shahmoradian SH, Lewis AJ, Genoud C, Hench J, Moors TE, Navarro PP, Castaño- Díez D, Schweighauser G, Graff-Meyer A, Goldie KN, et al. 2019. Lewy pathology in Parkinson’s disease consists of crowded organelles and lipid membranes. Nat Neurosci. 22(7):1099–1109. doi:10.1038/s41593-019-0423-2. Sharma RP, Winn DS, Low JB. 1977. Toxic, neurochemical and behavioral effects of dieldrin exposure in mallard ducks. Arch Environ Contam Toxicol. 5(1):43–53. doi:10.1007/BF02220889. Sharma SK, Priya S. 2017. Expanding role of molecular chaperones in regulating α- synuclein misfolding; implications in Parkinson’s disease. Cellular and Molecular Life Sciences. 74(4):617–629. doi:10.1007/s00018-016-2340-9. Sharman A, Hirji R, Birmingham JT, Govind CK. 2000. Dopaminergic innervation of the subthalamic nucleus in the normal state, in MPTP-treated monkeys, and in Parkinson’s 88 disease patients. Journal of Comparative Neurology. 425(1):121–129. doi:10.1002/1096-9861(20000911)425:1<121::AID-CNE10>3.0.CO;2-G. Shekhawat J, Gauba K, Gupta S, Choudhury B, Purohit P, Sharma P, Banerjee M. 2021. Ten–eleven translocase: key regulator of the methylation landscape in cancer. J Cancer Res Clin Oncol. 147(7):1869–1879. doi:10.1007/s00432-021-03641-3. Shimohama S, Sawada H, Kitamura Y, Taniguchi T. 2003. Disease model: Parkinson’s disease. Trends Mol Med. 9(8):360–365. doi:10.1016/S1471-4914(03)00117-5. Shipley MM, Mangold CA, Szpara ML. 2016. Differentiation of the SH-SY5Y human neuroblastoma cell line. Journal of Visualized Experiments. 2016(108). doi:10.3791/53193. Shu L, Qin L, Min S, Pan H, Zhong J, Guo J, Sun Q, Yan X, Chen C, Tang B, et al. 2019. Genetic analysis of DNA methylation and hydroxymethylation genes in Parkinson’s disease. Neurobiol Aging. 84:242.e13-242.e16. doi:10.1016/j.neurobiolaging.2019.02.025. Shulman JM, De Jager PL, Feany MB. 2011. Parkinson’s disease: Genetics and pathogenesis. Annual Review of Pathology: Mechanisms of Disease. 6:193–222. doi:10.1146/annurev-pathol-011110-130242. Shulman LM, Bhat V. 2006. Gender disparities in Parkinson’s disease. Expert Rev Neurother. 6(3):407–416. doi:10.1586/14737175.6.3.407. Simola N, Morelli M, Carta A. 2007. MECHANISMS OF NEUROTOXICITY OF 6-OHDA. Simón-Sánchez J, Schulte C, Bras JM, Sharma M, Gibbs JR, Berg D, Paisan-Ruiz C, Lichtner P, Scholz SW, Hernandez DG, et al. 2009. Genome-wide association study reveals genetic risk underlying Parkinson’s disease. Nat Genet. 41(12):1308–1312. doi:10.1038/ng.487. Simonyan K. 2019. Recent advances in understanding the role of the basal ganglia. F1000Res. 8:122. doi:10.12688/f1000research.16524.1. Slotkin TA, Seidler FJ. 2008. Developmental neurotoxicants target neurodifferentiation into the serotonin phenotype: Chlorpyrifos, diazinon, dieldrin and divalent nickel. Toxicol Appl Pharmacol. 233(2):211–219. doi:10.1016/j.taap.2008.08.020. Slotkin TA, Seidler FJ. 2009. Oxidative and excitatory mechanisms of developmental neurotoxicity: Transcriptional profiles for chlorpyrifos, diazinon, dieldrin, and divalent nickel in PC12 Cells. Environ Health Perspect. 117(4):587–596. doi:10.1289/ehp.0800251. Smallwood SA, Kelsey G. 2012. De novo DNA methylation: A germ cell perspective. Trends in Genetics. 28(1):33–42. doi:10.1016/j.tig.2011.09.004. http://dx.doi.org/10.1016/j.tig.2011.09.004. 89 Smirnova L., Harris G, Delp J, Valadares M, Pamies D, Hogberg HT, Waldmann T, Leist M, Hartung T. 2016. A LUHMES 3D dopaminergic neuronal model for neurotoxicity testing allowing long-term exposure and cellular resilience analysis. Arch Toxicol. 90(11):2725–2743. doi:10.1007/s00204-015-1637-z. Smirnova L, Harris G, Delp J, Valadares M, Pamies D, Hogberg HT, Waldmann T, Leist M, Hartung T. 2016. A LUHMES 3D dopaminergic neuronal model for neurotoxicity testing allowing long-term exposure and cellular resilience analysis. Arch Toxicol. 90(11):2725–2743. doi:10.1007/s00204-015-1637-z. Smith Y, Villalba RM, Raju D V. 2009. Striatal spine plasticity in Parkinson’s disease: pathological or not? Parkinsonism Relat Disord. 15(SUPPL. 3). doi:10.1016/S1353- 8020(09)70805-3. Snyder. GL, Keller R, igmond M. 1990. Dopamine efflux from striatal slices after intracerebral 6-hydroxydopamine: Evidence for compensatory hyperactivity of residual terminals. Pharmacology and Experimental Therapeutics. 253:867–876. Song C, Kanthasamy A, Anantharam V, Sun F, Kanthasamy AG. 2010. Environmental Neurotoxic Pesticide Increases Histone Acetylation to Promote Apoptosis in Dopaminergic Neuronal Cells: Relevance to Epigenetic Mechanisms of Neurodegeneration. Mol Pharmacol. 77(4):621–632. doi:10.1124/mol.109.062174. Spillantini MG, Crowther RA, Jakes R, Hasegawa M, Goedert M. 1998. α-Synuclein in filamentous inclusions of Lewy bodies from Parkinson’s disease and dementia with Lewy bodies. Proceedings of the National Academy of Sciences. 95(11):6469–6473. doi:10.1073/pnas.95.11.6469. Spillantini MG, Schmidt ML, Lee VM-Y, Trojanowski JQ, Jakes R, Goedert M. 1997. α- Synuclein in Lewy bodies. Nature. 388(6645):839–840. doi:10.1038/42166. Steece-Collier K, Maries E, Kordower JH. 2002. Etiology of Parkinson’s disease: Genetics and environment revisited. Proc Natl Acad Sci U S A. 99(22):13972–13974. doi:10.1073/pnas.242594999. Steenland K, Hein MJ, Cassinelli RT, Prince MM, Nilsen NB, Whelan EA, Waters MA, Ruder AM, Schnorr TM. 2006. Polychlorinated biphenyls and neurodegenerative disease mortality in an occupational cohort. Epidemiology. 17(1):8–13. doi:10.1097/01.ede.0000190707.51536.2b. Subramanian I, Mathur S, Oosterbaan A, Flanagan R, Keener AM, Moro E. 2022. Unmet Needs of Women Living with Parkinson’s Disease: Gaps and Controversies. Movement Disorders. 37(3):444–455. doi:10.1002/mds.28921. Sulzer D. 2007. Multiple hit hypotheses for dopamine neuron loss in Parkinson’s disease. Trends Neurosci. 30(5):244–250. doi:10.1016/j.tins.2007.03.009. 90 Sun F, Anantharam V, Latchoumycandane C, Kanthasamy A, Kanthasamy AG. 2005. Dieldrin induces ubiquitin-proteasome dysfunction in α-synuclein overexpressing dopaminergic neuronal cells and enhances susceptibility to apoptotic cell death. Journal of Pharmacology and Experimental Therapeutics. 315(1):69–79. doi:10.1124/jpet.105.084632. Sun J, Kouranova E, Cui X, Mach RH, Xu J. 2013. Regulation of dopamine presynaptic markers and receptors in the striatum of DJ-1 and pink1 knockout rats. Neurosci Lett. 557(PB):123–128. doi:10.1016/j.neulet.2013.10.034. Tahiliani M, Koh KP, Shen Y, Pastor WA, Bandukwala H, Brudno Y, Agarwal S, Iyer LM, Liu DR, Aravind L, et al. 2009. Conversion of 5-Methylcytosine to 5- Hydroxymethylcytosine in Mammalian DNA by MLL Partner TET1. Science (1979). 324(5929):930–935. doi:10.1126/science.1170116. Talebi S, Ghoreishy SM, Jayedi A, Travica N, Mohammadi H. 2022. Dietary Antioxidants and Risk of Parkinson’s Disease: A Systematic Review and Dose–Response Meta- analysis of Observational Studies. Advances in Nutrition. 13(5):1493–1504. doi:10.1093/advances/nmac001. Tanner CM, Aston DA. 2000. Epidemiology of Parkinson’s disease and akinetic syndromes. Curr Opin Neurol. 13:427–430. doi:10.1097/00019052-200008000-00010. Tanner CM, Kame F, Ross GW, Hoppin JA, Goldman SM, Korell M, Marras C, Bhudhikanok GS, Kasten M, Chade AR, et al. 2011. Rotenone, paraquat, and Parkinson’s disease. Environ Health Perspect. 119(6):866–872. doi:10.1289/ehp.1002839. Tanner CM, Langston JW. 1990. Do environmental toxins cause Parkinson’s disease? A critical review. Neurology. 40(10):17–30. Tehranian R, Montoya SE, Van Laar AD, Hastings TG, Perez RG. 2006. Alpha-synuclein inhibits aromatic amino acid decarboxylase activity in dopaminergic cells. J Neurochem. 99(4):1188–1196. doi:10.1111/j.1471-4159.2006.04146.x. Tong Z Bin, Hogberg H, Kuo D, Sakamuru S, Xia M, Smirnova L, Hartung T, Gerhold D. 2017. Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening. Journal of Applied Toxicology. 37(2):167–180. doi:10.1002/jat.3334. Tong Z-B, Braisted J, Chu P-H, Gerhold D. 2020. The MT1G Gene in LUHMES Neurons Is a Sensitive Biomarker of Neurotoxicity. Neurotox Res. 38(4):967–978. doi:10.1007/s12640-020-00272-3. Tong Z-B, Kim H, El Touny L, Simeonov A, Gerhold D. 2022. LUHMES Dopaminergic Neurons Are Uniquely Susceptible to Ferroptosis. Neurotox Res. 40(5):1526–1536. doi:10.1007/s12640-022-00538-y. 91 Tsalenchuk M, Gentleman SM, Marzi SJ. 2023. Linking environmental risk factors with epigenetic mechanisms in Parkinson’s disease. NPJ Parkinsons Dis. 9(1):123. doi:10.1038/s41531-023-00568-z. Tüshaus J, Kataka ES, Zaucha J, Frishman D, Müller SA, Lichtenthaler SF. 2020. Neuronal Differentiation of LUHMES Cells Induces Substantial Changes of the Proteome. Proteomics.:2000174. doi:10.1002/pmic.202000174. Valdinocci D, Radford RAW, Siow SM, Chung RS, Pountney DL. 2017. Potential modes of intercellular α-synuclein transmission. Int J Mol Sci. 18(2). doi:10.3390/ijms18020469. Vale C, Fonfría E, Bujons J, Messeguer A, Rodríguez-Farré E, Suñol C. 2003. The organochlorine pesticides γ-hexachlorocyclohexane (Lindane), α-endosulfan and dieldrin differentially interact with GABAA and glycine-gated chloride channels in primary cultures of cerebellar granule cells. Neuroscience. 117(2):397–403. doi:10.1016/S0306-4522(02)00875-8. Vanderperre B, Muraleedharan A, Dorion MF, Larroquette F, Del Cid Pellitero E, Rajakulendran N, Chen CXQ, Lariviere R, Michaud-Tardif C, Chidiac R, et al. 2023. A genome-wide CRISPR/Cas9 screen identifies genes that regulate the cellular uptake of α-synuclein fibrils by modulating heparan sulfate proteoglycans. BioRxiv. doi:10.1101/2023.09.29.560170. https://doi.org/10.1101/2023.09.29.560170. Varastet M, Riche D, Maziere M, Hantraye P. 1994. CHRONIC MPTP TREATMENT REPRODUCES IN BABOONS THE DIFFERENTIAL VULNERABILITY OF MESENCEPHALIC DOPAMINERGIC NEURONS OBSERVED IN PARKINSON’S DISEASE. Neuroscience. 63(I):47–56. doi:10.1016/0306-4522(94)90006-x. Vargas KJ, Makani S, Davis T, Westphal CH, Castillo PE, Chandra SS. 2014. Synucleins regulate the kinetics of synaptic vesicle endocytosis. Journal of Neuroscience. 34(28):9364–9376. doi:10.1523/JNEUROSCI.4787-13.2014. Venda LL, Cragg SJ, Buchman VL, Wade-Martins R. 2010. α-Synuclein and dopamine at the crossroads of Parkinson’s disease. Trends Neurosci. 33(12):559–568. doi:10.1016/j.tins.2010.09.004. Villalba RM, Mathai A, Smith Y. 2015. Morphological changes of glutamatergic synapses in animal models of Parkinson’s disease. Front Neuroanat. 9(September). doi:10.3389/fnana.2015.00117. Villalba RM, Smith Y. 2018. Loss and remodeling of striatal dendritic spines in Parkinson’s disease: from homeostasis to maladaptive plasticity? J Neural Transm. 125(3):431–447. doi:10.1007/s00702-017-1735-6. Volpicelli-Daley LA, Luk KC, Lee VMY. 2014. Addition of exogenous α-synuclein preformed fibrils to primary neuronal cultures to seed recruitment of endogenous α- synuclein to Lewy body and Lewy neurite-like aggregates. Nat Protoc. 9(9):2135–2146. doi:10.1038/nprot.2014.143. 92 Volpicelli-Daley LA, Luk KC, Patel TP, Tanik SA, Riddle DM, Stieber A, Meaney DF, Trojanowski JQ, Lee VMY. 2011. Exogenous α-Synuclein Fibrils Induce Lewy Body Pathology Leading to Synaptic Dysfunction and Neuron Death. Neuron. 72(1):57–71. doi:10.1016/j.neuron.2011.08.033. http://dx.doi.org/10.1016/j.neuron.2011.08.033. Wadman M. 2016. Rogue protein’s partners offer hope in Parkinson’s disease. Science (1979). 354(6315):956–956. doi:10.1126/science.354.6315.956. Wagner SR, Greene FE. 1978. Dieldrin-induced alterations in biogenic amine content of rat brain. Toxicol Appl Pharmacol. 43(1):45–55. doi:10.1016/S0041-008X(78)80031-3. Wakabayashi K, Tanji K, Mori F, Takahashi H. 2007a. The Lewy body in Parkinson’s disease: Molecules implicated in the formation and degradation of α-synuclein aggregates. Neuropathology. 27(5):494–506. doi:10.1111/j.1440-1789.2007.00803.x. Wakabayashi K, Tanji K, Mori F, Takahashi H. 2007b. The Lewy body in Parkinson’s disease: Molecules implicated in the formation and degradation of α‐synuclein aggregates. Neuropathology. 27(5):494–506. doi:10.1111/j.1440-1789.2007.00803.x. Wang J, Wang F, Mai D, Qu S. 2020. Molecular Mechanisms of Glutamate Toxicity in Parkinson’s Disease. Front Neurosci. 14. doi:10.3389/fnins.2020.585584. Wang L, Das U, Scott DA, Tang Y, McLean PJ, Roy S. 2014. α-Synuclein multimers cluster synaptic vesicles and attenuate recycling. Current Biology. 24(19):2319–2326. doi:10.1016/j.cub.2014.08.027. Weisskopf M, Knekt P, O’Reilly E, Lyytinen J, Reunanen A, Laden F, Altshul L, Ascherio A. 2010. Persistent organochlorine pesticides in serum and risk of Parkinson disease. Neurology. 74(13):1055–1061. doi:10.1212/WNL.0b013e3181d76a93. http://www.embase.com/search/results?subaction=viewrecord&from=export&id=L35854 8467%5Cnhttp://dx.doi.org/10.1212/WNL.0b013e3181d76a93. Wile DJ, Agarwal PA, Schulzer M, Mak E, Dinelle K, Shahinfard E, Vafai N, Hasegawa K, Zhang J, McKenzie J, et al. 2017. Serotonin and dopamine transporter PET changes in the premotor phase of LRRK2 parkinsonism: cross-sectional studies. Lancet Neurol. 16(5):351–359. doi:10.1016/S1474-4422(17)30056-X. Williams ET, Chen X, Moore DJ. 2017. VPS35, the Retromer Complex and Parkinson’s Disease. J Parkinsons Dis. 7(2):219–233. doi:10.3233/JPD-161020. Willis AW, Roberts E, Beck JC, Fiske B, Ross W, Savica R, Van Den Eeden SK, Tanner CM, Marras C, Alcalay R, et al. 2022. Incidence of Parkinson disease in North America. NPJ Parkinsons Dis. 8(1). doi:10.1038/s41531-022-00410-y. Wirdefeldt K, Adami HO, Cole P, Trichopoulos D, Mandel J. 2011. Epidemiology and etiology of Parkinson’s disease: A review of the evidence. Eur J Epidemiol. 26(SUPPL. 1). doi:10.1007/s10654-011-9581-6. 93 Wong D, Dorovini-Zis K, Vincent SR. 2004. Cytokines, nitric oxide, and cGMP modulate the permeability of an in vitro model of the human blood–brain barrier. Exp Neurol. 190(2):446–455. doi:10.1016/j.expneurol.2004.08.008. Wong YC, Luk K, Purtell K, Burke Nanni S, Stoessl AJ, Trudeau LE, Yue Z, Krainc D, Oertel W, Obeso JA, et al. 2019. Neuronal vulnerability in Parkinson disease: Should the focus be on axons and synaptic terminals? Movement Disorders. 34(10):1406– 1422. doi:10.1002/mds.27823. Wu T, Wang J, Wang C, Hallett M, Zang Y, Wu X, Chan P. 2012. Basal ganglia circuits changes in Parkinson’s disease patients. Neurosci Lett. 524(1):55–59. doi:10.1016/j.neulet.2012.07.012. Xicoy H, Wieringa B, Martens GJM. 2017. The SH-SY5Y cell line in Parkinson’s disease research: a systematic review. Mol Neurodegener. 12(1):1–11. doi:10.1186/s13024-017- 0149-0. http://dx.doi.org/10.1186/s13024-017-0149-0. Xu J, Wu X-S, Sheng J, Zhang Z, Yue H-Y, Sun L, Sgobio C, Lin X, Peng S, Jin Y, et al. 2016. α-Synuclein Mutation Inhibits Endocytosis at Mammalian Central Nerve Terminals. The Journal of Neuroscience. 36(16):4408–4414. doi:10.1523/JNEUROSCI.3627-15.2016. Yamaguchi A, Ishikawa K ichi, Inoshita T, Shiba-Fukushima K, Saiki S, Hatano T, Mori A, Oji Y, Okuzumi A, Li Y, et al. 2020. Identifying Therapeutic Agents for Amelioration of Mitochondrial Clearance Disorder in Neurons of Familial Parkinson Disease. Stem Cell Reports. 14(6):1060–1075. doi:10.1016/j.stemcr.2020.04.011. https://doi.org/10.1016/j.stemcr.2020.04.011. Yang F, Trolle Lagerros Y, Bellocco R, Adami H-O, Fang F, Pedersen NL, Wirdefeldt K. 2015. Physical activity and risk of Parkinson’s disease in the Swedish National March Cohort. Brain. 138(2):269–275. doi:10.1093/brain/awu323. Yavich L, Tanila H, Vepsäläinen S, Jäkälä P. 2004a. Role of α-synuclein in presynaptic dopamine recruitment. J Neurosci. 24(49):11165–11170. doi:10.1523/JNEUROSCI.2559-04.2004. Yavich L, Tanila H, Vepsäläinen S, Jäkälä P. 2004b. Role of α-synuclein in presynaptic dopamine recruitment. Journal of Neuroscience. 24(49):11165–11170. doi:10.1523/JNEUROSCI.2559-04.2004. Zaman V, Shields DC, Shams R, Drasites KP, Matzelle D, Haque A, Banik NL. 2021. Cellular and molecular pathophysiology in the progression of Parkinson’s disease. Metab Brain Dis. 36(5):815–827. doi:10.1007/s11011-021-00689-5. Zhang H, Iranzo A, Högl B, Arnulf I, Ferini‐Strambi L, Manni R, Miyamoto T, Oertel WH, Dauvilliers Y, Ju Y, et al. 2022. Risk Factors for Phenoconversion in Rapid Eye Movement Sleep Behavior Disorder. Ann Neurol. 91(3):404–416. doi:10.1002/ana.26298. 94 Zhang WQ, Tilson HA, Nanry KP, Hudson PM, Hong JS, Stachowiak MK. 1988. Increased dopamine release from striata of rats after unilateral nigrostriatal bundle damage. Brain Res. 461:335–342. doi:10.1016/0006-8993(88)90264-8. Zhang X, Yin M, Zhang M. 2014. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. Zhang XM, Yin M, Zhang MH. 2014a. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. Zhang XM, Yin M, Zhang MH. 2014b. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. Zhao X, Salgado VL, Yeh JZ, Narahashi T. 2003. Differential actions of fipronil and dieldrin insecticides on GABA-gated chloride channels in cockroach neurons. Journal of Pharmacology and Experimental Therapeutics. 306(3):914–924. doi:10.1124/jpet.103.051839. Zhou FC, Bledsoe S, Murphy J. 1991. Serotonergic sprouting is induced by dopamine- lesion in substantia nigra of adult rat brain. Brain Res. doi:10.1016/0006- 8993(91)90553-8. Zigmond M. 1997. Do Compensatory Processes Underlie the Preclinical Phase of Neurodegenerative Disease? Insights from an Animal Model of Parkinsonism. Neurobiol Dis. 4(3–4):247–253. doi:10.1006/nbdi.1997.0157. Zigmond M, Abercrombie E, Berger T, Grace A, Stricker E. 1993. Compensatory responses to partial loss of dopaminergic neurons: Studies with 6-hydroxydopamine. Current Concepts in Parkinson’s Disease Research.:99–140. doi:10.1007/BF03159728. Zigmond M, Acheson AL, Stachowiak MK, Strickerm EM. 1984. Neurochemical Compensation After Nigrostriatal Bundle Injury in an Animal Model of Preclinical Parkinsonism. Arch Neurol. 41(8):856–861. doi:10.1001/archneur.1984.04050190062015. Zigmond M, Castro S, Keefe K, Abercrombie E, Sved A. 1998. Role of excitatory amino acids in the regulation of dopamine synthesis and release in the neostriatum. Amino Acids. 14(1–3):57–62. doi:10.1007/BF01345243. Zigmond MJ. 1994. Chemical transmission in the brain: homeostatic regulation and its functional implications Homeostasis of neuronal function. Prog Brain Res. 100:115–122. doi:10.1016/s0079-6123(08)60776-1. Zimprich A, Biskup S, Leitner P, Lichtner P, Farrer M, Lincoln S, Kachergus J, Hulihan M, Uitti RJ, Calne DB, et al. 2004. Mutations in LRRK2 cause autosomal-dominant 95 parkinsonism with pleomorphic pathology. Neuron. 44(4):601–7. doi:10.1016/j.neuron.2004.11.005. Zolfaghari S, Lewandowski N, Pelletier A, Naeimi SA, Gagnon J-F, Brillon-Corbeil M, Montplaisir JY, Postuma RB. 2022. Cardiovascular Risk Factors and Phenoconversion to Neurodegenerative Synucleinopathies in Idiopathic REM Sleep Behavior Disorder. J Parkinsons Dis. 12(3):927–933. doi:10.3233/JPD-212984. 96 Chapter 2: Developmental exposure to the Parkinson’s disease-associated organochlorine pesticide dieldrin alters dopamine neurotransmission in α- synuclein pre-formed fibril (PFF)-injected mice 97 Sierra L. Boyd1, Nathan C. Kuhn1, Joseph R. Patterson1, Anna C. Stoll1, Sydney A. Zimmerman2, Mason R. Kolanowski2, Joseph J. Neubecker2, Kelvin C. Luk3, Eric S. Ramsson2, Caryl E. Sortwell1, Alison I. Bernstein,1,4,5,* 1Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI 2Biomedical Sciences Department, Grand Valley State University, Allendale, MI 3Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 4Department of Pharmacology and Toxicology, School of Pharmacy, Rutgers University, Piscataway, NJ 5Environmental and Occupational Health Sciences Institute, Rutgers University, Piscataway, NJ *Corresponding author: bernstein.alison@rutgers.edu; 170 Frelinghuysen Rd, Piscataway, NJ 08854 ORCID IDs Sierra L. Boyd: 0000-0003-1039-9484 Joseph R. Patterson: 0000-0003-0926-7396 Anna C. Stoll: 0000-0001-7135-121X Sydney A. Zimmerman: 0009-0003-7419-0329 Mason R. Kolanowski: 0009-0006-3101-9574 Joseph J. Neubecker: 0009-0005-5044-0623 Kelvin C. Luk: 0000-0002-6591-6269 Eric S. Ramsson: 0000-0001-7187-7684 Caryl E. Sortwell: 0000-0003-2571-6753 Alison I. Bernstein: https://orcid.org/0000-0002-5589-4318 Keywords: Parkinson Disease, alpha-Synuclein, Pesticides, Dieldrin, Dopamine, Developmental Neurotoxicity Running head: Dieldrin alters dopamine transmission in the α-syn PFF model 98 This chapter was previously published in Toxicology Sciences and is included here under the terms of the Creative Commons Attribution-Non Commercial License (CC: BY-NC 4.0 DEED), which permits non-commercial re-use, distribution, and reproduction (Boyd et al. 2023). 99 Abstract Parkinson’s disease (PD) is the fastest-growing neurological disease worldwide, with increases outpacing aging and occurring most rapidly in recently industrialized areas, suggesting a role of environmental factors. Epidemiological, post-mortem and mechanistic studies suggest that persistent organic pollutants, including the organochlorine pesticide dieldrin, increase PD risk. In mice, developmental dieldrin exposure causes male-specific exacerbation of neuronal susceptibility to MPTP and synucleinopathy. Specifically, in the α-synuclein (α-syn) pre-formed fibril (PFF) model, exposure leads to increased deficits in striatal dopamine (DA) turnover and motor deficits on the challenging beam. Here, we hypothesized that alterations in DA handling contribute to the observed changes and assessed vesicular monoamine transporter 2 (VMAT2) function and DA release in this dieldrin/PFF two-hit model. Female C57BL/6 mice were exposed to 0.3 mg/kg dieldrin or vehicle every 3 days by feeding, starting at 8 weeks of age, and continuing throughout breeding, gestation, and lactation. Male offspring from independent litters underwent unilateral, intrastriatal injections of α-syn PFFs at 12 weeks of age and vesicular 3H-DA uptake assays and fast-scan cyclic voltammetry (FSCV) were performed 4 months post-PFF injection. Dieldrin induced an increase in DA release in striatal slices in PFF-injected animals, but no change in VMAT2 activity. These results suggest that developmental dieldrin exposure increases a compensatory response to synucleinopathy-triggered striatal DA loss. These findings are consistent with silent neurotoxicity, where developmental exposure to dieldrin primes the nigrostriatal striatal system to have an exacerbated response to 100 synucleinopathy in the absence of observable changes in typical markers of nigrostriatal dysfunction and degeneration. Introduction Parkinson’s disease (PD) is a multi-system disorder pathologically defined by the degeneration of dopaminergic neurons in the nigrostriatal pathway and the formation of α-synuclein (α-syn)-containing Lewy bodies. PD is the most common movement disorder, the second most common neurogenerative disease, and one of the fastest- growing neurological diseases (de Lau and Breteler 2006). From 1990 to 2016, the prevalence of PD has more than doubled globally (Ray Dorsey et al. 2018). In addition, a recent study suggests that PD incidence in the US is 50% higher than previously estimated, with 90,000 diagnoses per year (Willis et al. 2022). Of relevance to this work, the authors reported PD incidence rates higher in certain geographic areas including the “Rust Belt,” a region with a history of heavy industrial manufacturing. This is consistent with epidemiological research that shows an association between increased risk of PD and environmental factors associated with industrialization, including heavy metals, solvents, and pesticide exposures (Semchuk et al. 1992; Tanner and Aston 2000; Ascherio et al. 2006; Brown et al. 2006; de Lau and Breteler 2006; Steenland et al. 2006; Hatcher et al. 2008; Cicchetti et al. 2009; Elbaz et al. 2009; Moretto and Colosio 2011; Tanner et al. 2011; Wirdefeldt et al. 2011; Freire and Koifman 2012; Fleming 2017; Ray Dorsey et al. 2018; De Miranda et al. 2022). Multiple epidemiological studies have found elevated levels of organochlorines in general in the serum and brain of PD subjects (Corrigan et al. 1998; Corrigan et al. 2000; Steenland et al. 2006; Elbaz et al. 2009; Freire and Koifman 2012). Of relevance here, one study reported a specific association between dieldrin levels and PD risk with an odds ratio of 1.95 per 101 interquartile range in non-smokers, while other organochlorines did not show an association (Weisskopf et al. 2010). In addition, when combined with post-mortem analysis and mechanistic studies, a potential role for dieldrin in PD emerges (Tanner and Langston 1990; Semchuk et al. 1991; Semchuk et al. 1992; Fleming et al. 1994; Corrigan et al. 1998; Le Couteur et al. 1999; Corrigan et al. 2000; Priyadarshi et al. 2000; Ritz and Yu 2000; Tanner and Aston 2000; Priyadarshi et al. 2001; Kanthasamy et al. 2005; Ascherio et al. 2006; Brown et al. 2006; Steenland et al. 2006; Hatcher et al. 2007; Elbaz et al. 2009; Weisskopf et al. 2010; Moretto and Colosio 2011; Tanner et al. 2011; Wirdefeldt et al. 2011; Caudle et al. 2012; Freire and Koifman 2012). Because dieldrin was phased out in the 1970s and 1980s, the potential for new, acute exposure to dieldrin is low. However, the health effects of past exposures will continue for decades as the population currently diagnosed with PD and those that will develop PD in the next 20-30 years were likely exposed to dieldrin before its phase-out during critical neurodevelopmental periods (de Jong et al. 1997; Jorgenson 2001; Meijer et al. 2001; Kanthasamy et al. 2005). Furthermore, well-established models of dieldrin exposure have demonstrated that dieldrin induces oxidative stress, is selectively toxic to dopaminergic cells, disrupts striatal dopamine (DA) activity, and may promote α-syn aggregation (Sanchez-Ramos et al. 1998; Chun et al. 2001; Kitazawa et al. 2001; Kitazawa et al. 2003; Kanthasamy et al. 2005; Richardson et al. 2006; Hatcher et al. 2007; Moretto and Colosio 2011). Thus, dieldrin serves as an important representative PD-related toxicant that has well-characterized animal exposure paradigms and provides a roadmap for understanding how environmental exposures confer PD risk (Kochmanski et al. 2019; Gezer et al. 2020) 102 Here, we utilize a mouse developmental dieldrin exposure model where exposure induces sex-specific stable alterations in the DA system that increase susceptibility to subsequent exposure to both α-synuclein (α-syn) pre-formed fibril (PFF)-induced synucleinopathy and MPTP in male, but not female, offspring, suggesting that this model is broadly applicable to investigating how this exposure affects PD risk and neuronal susceptibility (Richardson et al. 2006; Luk et al. 2012a; Luk et al. 2012b; Kochmanski et al. 2019; Gezer et al. 2020) In this model, dams are fed dieldrin (0.3 mg/kg, every 3 days) throughout mating, gestation, and lactation and F1 pups are assessed for toxicity in PD models at 12 weeks of age (Richardson et al. 2006; Kochmanski et al. 2019; Gezer et al. 2020). This dose was chosen based on a previous dose-response study and our results in the two-hit dieldrin/PFF model (Richardson et al. 2006; Kochmanski et al. 2019; Gezer et al. 2020). Mice were exposed through oral ingestion by the dam because the most likely route of exposure to dieldrin in humans is through ingestion of contaminated foods (ATSDR 2022). In this two-hit model, we previously reported a male-specific dieldrin-associated exacerbation of synucleinopathy- induced increases in DA turnover at 6 months, but not at 2 months, as well as an exacerbation of motor deficits on challenging beam at 6 months (Gezer et al. 2020). We also reported no dieldrin effect on the number of α-syn aggregates 1 and 2 months after PFF injection or the reductions in total striatal dopamine by HPLC at 2 and 6 months post-PFF injection. We also demonstrated that synucleinopathy-induced loss of DA neurons by TH and NeuN counts in the SN at 6 months is not exacerbated by dieldrin exposure (Figure 6). While we are unaware of specific epidemiological evidence of sex differences for the dieldrin-related increase in PD risk, this sex specificity of our 103 observed phenotype is consistent with known sex differences in dopaminergic vulnerability to parkinsonian toxicants and our previously reported sex-specific epigenetic effects of developmental dieldrin exposure (Baldereschi et al. 2000; Elbaz et al. 2002; van den Eeden et al. 2003; Wooten et al. 2004; Haaxma et al. 2007; Taylor et al. 2007; Alves et al. 2009; Weisskopf et al. 2010; Gillies et al. 2014; Georgiev et al. 2017; Kochmanski et al. 2019; De Miranda et al. 2019; Adamson et al. 2022). Based on the observed exacerbation in PFF-induced increases in striatal DA turnover by dieldrin, we hypothesized here that dieldrin-induced alterations in DA packaging and synaptic vesicle function contribute to the exacerbated toxicity in PFF-injected animals. Proper packaging of DA into synaptic vesicles is critical for DA neurotransmission and neuronal health. (Alter et al. 2013). Because cytosolic DA is metabolized to DOPAC and HVA and broken down into toxic products, disruption of DA handling and packaging can increase cytosolic DA and lead to oxidative stress and acceleration of the toxic interplay between dysregulated α-syn and DA (Graham et al. 1978; Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Zigmond et al. 1993; Ben-Scachar et al. 1995; Hastings et al. 1996; Bezard and Gross 1997; Zigmond 1997; Uhl 1998; Zigmond et al. 1998; Gainetdinov et al. 1999; Caudle et al. 2007; Guillot et al. 2008; Taylor et al. 2009; Miller et al. 2011; Alter et al. 2013; Meiser et al. 2013; Lohr et al. 2014; Molina-Mateo et al. 2017; Mor et al. 2017; Iannitelli et al. 2023). To test this, we assessed VMAT2 function by vesicular uptake assay and DA release and uptake by fast-scan cyclic voltammetry (FSCV) in the dieldrin/PFF two-hit model 4 months post- PFF injection in male F1 offspring developmentally exposed to dieldrin. Testing at 4 months allowed us to capture changes in the striatal synapse prior to significant 104 nigrostriatal degeneration. Assessing these endpoints at 6 months when degeneration of striatal terminals and nigral cell bodies is already pronounced would test mainly the effects of degeneration, rather than the functional changes that precede it. 105 Methods Animals Figure 2.1. Experimental design including dosing schedule, weaning strategy, cage and group assignments. A) Timeline of dieldrin-PFF two-hit model: At 8 weeks of age, female C57BL/6 mice dieldrin exposure began via oral administration of 0.3mg/kg dissolved in corn oil and injected into peanut butter pellets. At 12 weeks of age, mating began, and exposure continued through weaning of pups. F1 pups were weaned 3 weeks after birth and separated by litter and sex (2-4 animals per cage). At 3 months of age, male pups underwent intrastriatal injections of PFFs and were individually housed after surgery. B) Cage, group assignments, and group numbers: Male F1 offspring (F1) that underwent intrastriatal PFF-injections were assigned to endpoints such that every animal for each endpoint came from an independent litter. The Fourth F1 litter is an example of a litter excluded from endpoint assignments due to individual housing. Made in BioRender. 106 Male (11 weeks old) and female (7 weeks old) C57BL/6 mice were purchased from Jackson Laboratory (Bar Harbor, Maine). Animal husbandry and colony maintenance was completed as previously described (Kochmanski et al. 2019; Gezer et al. 2020). All procedures were conducted in accordance with the National Institutes of Health Guide for Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee at Michigan State University. Dieldrin exposure paradigm Dosing was carried out as previously described (Kochmanski et al. 2019; Gezer et al. 2020). Adult C57BL/6 (8-week-old) female animals were treated throughout breeding, gestation, and lactation (Figure 2.1A). Mice were administered 0.3 mg/kg dieldrin (ChemService, CAS# 60-57-1) dissolved in corn oil vehicle and mixed with peanut butter pellets every 3 days (Gonzales et al. 2014; Kochmanski et al. 2019; Gezer et al. 2020). This dose was chosen based on a previous dose-response study and our results in the two-hit dieldrin/PFF model (Richardson et al. 2006; Kochmanski et al. 2019; Gezer et al. 2020). Mice were exposed through oral ingestion by the dam because the most likely route of exposure to dieldrin in humans was through ingestion of contaminated foods and ingestion of the resulting contaminated breast milk (ATSDR) 2022). Control mice received an equivalent amount of corn oil vehicle in peanut butter. Four weeks into female exposure, unexposed C57BL/6 males (8–12 weeks old) were introduced for breeding. Offspring were weaned at 3 weeks of age and separated by litter and by sex, with 2-4 animals per cage (Figure 2.1B). At 12 weeks of age, male offspring from independent litters were selected for PFF or monomer injection. This time point was chosen based on previous results demonstrating increased neuronal 107 susceptibility to this age (Richardson et al. 2006; Gezer et al. 2020). This developmental dieldrin dosing paradigm has been previously used in our lab to study the role of epigenetics and its effects on synucleinopathy-induced toxicity (Kochmanski et al. 2019; Gezer et al. 2020). Preparation of α-synuclein PFFs and fibril size verification Recombinant mouse α-syn monomers and PFFs were provided by the Luk lab, stored at -80 °C, and prepared as previously described (Luk et al. 2012a; Patterson et al. 2019). Over 500 fibrils were measured to determine the average fibril length of 45.06nm +/- 14.7nm (Figure 2.2). Fibril length was assessed before and after surgeries to ensure Figure 2.2. Verification of α-synuclein PFF size. A) PFF length distribution determined via TEM. Each point represents a measured fibril length, the error bars denote standard deviation. B) Representative TEM image of sonicated fibrils. C) Frequency distribution of PFF lengths post-sonication. that fibrils did not re-aggregate over the duration of the surgeries. All measurements were performed with ImageJ (Schneider et al. 2012). Intrastriatal injection of α-syn PFFs At 12 weeks of age, animals received unilateral intrastriatal PFF injections according to their cage and group assignment (Figure 2.1B). Surgeries were performed as previously 108 described (Luk et al. 2012a; Gezer et al. 2020). Mice received a total of 5 µg of PFFs (2.5 µL injection of 2 µg/µL PFFs) and received a single intrastriatal injection (anterior- posterior (AP) +0.2, medial-lateral (ML) +2.0, dorsal-ventral (DV) -2.6) with a flow rate of 0.5 μl/ml. post-surgery, mice received 1mg/kg of sustained-release buprenorphine by subcutaneous injection and were monitored closely until they recovered from anesthesia. In the three days following recovery, animals were monitored daily for adverse outcomes. A small subset of animals (n=2 for FSCV and n=4 for uptake) received α-syn monomer injections as a negative control to ensure that there were no effects of surgery itself. Animals were singly housed following surgeries for the duration of the experiment, consistent with our previous study (Gezer et al. 2020). Vesicular 3H-dopamine uptake Animals were killed by cervical dislocation and hemisected. Half of the brain from each group was homogenized for each statistical n, and vesicular DA uptake was performed as previously described (Staal et al. 2000; Caudle et al. 2007; Bernstein et al. 2012; Lohr et al. 2014). Data was normalized to protein level determined by BCA assay and expressed as pmol DA/mg protein/minute. Fast-scan cyclic voltammetry Animals were killed by cervical dislocation and brains were sectioned in oxygenated, 4°C artificial cerebrospinal fluid (aCSF) at 300 µm thick using a vibratome (Campden Instruments 5100mz-Plus) (Ferris et al. 2014). FSCV was carried out in the lateral, dorsal striatal sections as previously described (Yorgason et al. 2011; Ferris et al. 2014; Lohr et al. 2014; Ramsson et al. 2015; Ramsson 2016; Everett et al. 2022). 109 Carbon fiber glass microelectrodes were constructed using a vacuum to pull carbon fiber through a glass capillary tube, pulled using a horizontal electrode puller, broken, and sealed with paraffin (Ramsson et al. 2015). Microelectrodes were cycled for at least 15 minutes before recording at a frequency of 60Hz, then cycled at 10Hz until stable (Takmakov et al. 2010; Ramsson et al. 2015; Ramsson 2016; Davis et al. 2020). Carbon fiber microelectrodes were calibrated using a pipette-based calibration system by adding a dilute stock DA solution to a buffer and measuring the oxidation and/or reduction (Ramsson 2016). All cycling and recordings occurred with a triangle waveform (-0.4 to 1.3V to -0.4V; 400V/s 10Hz) (Lohr et al. 2014; Ramsson et al. 2015; Kang et al. 2021; Everett et al. 2022). Dopamine release was elicited with a bipolar twisted electrode (PlasticsOne) and a 350 µA, 4 ms monophasic optically isolated stimulus pulse (Neurolog NL800). Data was collected and analyzed using Demon Voltammetry and Analysis Software (Wake Forest Innovations) (Yorgason et al. 2011). A five- recording survey of two different dorsal striatal release sites per hemisphere in 2 different slices was taken for each animal with a 5-min rest interval between each stimulation (Lohr et al. 2014; Everett et al. 2022). Peak Dopamine, upward velocity (DA release), downward velocity (uptake; a Vmax estimate for DAT uptake), and tau (uptake; a Km estimate for DAT uptake) were calculated for each recording (Figure 5A) (Everett et al. 2022). Ipsilateral values were normalized to contralateral values to account for animal-to-animal variability. Immunohistochemistry The rostral remainder of the brains used for FSCV were immersion fixed in 4% paraformaldehyde for 24 hours and placed into 30% sucrose in PBS at 4°C for 110 immunohistochemistry. Fixed brains were frozen on a sliding microtome and sliced at 40 μm coronally. Free-floating sections were stored in cryoprotectant (30% sucrose, 30% ethylene glycol, 0.05 M PBS) at −20 °C. A 1:6 series of the entire rostral portion of the brain was used for staining and two nigral sections per animal were selected for imaging and quantification. Nonspecific staining was blocked with 10% normal goat serum, and sections were then incubated overnight in appropriate primary antibodies in TBS with 1% NGS/0.25% Triton X-100 followed by appropriate secondary antibodies for 2 hours (Table 2.1). Slides were cover-slipped with VECTASHIELD Vibrance Antifade Mounting Medium (VectaLabs) with DAPI and imaged on a Zeiss AxioScan 7 Digital Slide Scanning Microscope. Analysis of pSyn counts for immunohistochemistry was completed using the object colocalization module in the HALO Image Analysis Platform (Indica Labs). The SNpc was manually traced as the region of interest based on TH staining and pSyn-positive objects within this region were identified on two sections per animal from the same level. Table 2.1. Antibodies Used for Immunohistochemistry Data Analysis and Statistics Statistical analysis and graphing were performed using GraphPad Prism 9. Vehicle- exposed animals injected with PFFs (Vehicle/PFF) and dieldrin-exposed animals 111 injected with PFFs (Dieldrin/PFF) were compared with two-tailed, unpaired t-tests. All data are shown as mean +/- SD and the cutoff for statistical significance was p<0.05. Monomer-injected animals (Vehicle/Monomer, Dieldrin/Monomer) were used as controls to ensure there were no effects of surgery on its own, but these were not included in the statistical analysis, consistent with our preregistration and power analysis (Bernstein and Boyd 2022). Results Confirmation of PFF-induced seeding of pSyn-positive aggregates To confirm PFF-induced seeding, nigral slices were stained for TH and phosphorylated- synuclein (pSyn) from the remaining tissue of brains used for FSCV. We were unable to confirm seeding in animals used for uptake since the entire brain was used for that assay. We confirmed seeding in all animals used for FSCV and counted the number of pSyn-positive objects. At 4 months post-injection, as expected, we observed pSyn positive inclusions ipsilateral, but not contralateral, SN, in both dieldrin and vehicle/PFF groups (Figure 2.3A-B). Consistent with previous results, dieldrin did not affect the number of pSyn-positive inclusions (Figure 2.3C)(Gezer et al. 2020). 112 Figure 2.3. Confirmation of PFF-induced seeding in FSCV animals. A) Representative images from nigral tissue sections stained with TH (green) and pSyn (red) from a vehicle/PFF (A) and dieldrin/ PFF (B) animals 4 months post-PFF injection. C) pSyn counts in the SNpc show no effect of dieldrin on pSyn-positive objects in the SNpc ipsilateral to the PFF injection (p=0.2441). D) As expected, there were no pSyn- positive objects contralateral to the injection in either group of animals. All data are shown as mean +/- SD. Developmental dieldrin exposure increases DA release in PFF-injected animals FSCV was performed in striatal slices to determine if developmental dieldrin exposure affects evoked DA release or uptake in PFF-injected animals 4 months after PFF injection (Figure 2.5A-D). There was a significant increase in both peak DA concentration and upward velocity, a measure of DA release, in the dieldrin/PFF group compared to the vehicle/PFF group (p=0.0394 and p=0.0434, respectively) (Figure 2.5E, F). However, there was no significant difference in DAT uptake as measured by 113 tau or downward velocity, which are measures of DAT Km and Vmax (p=0.6435 and 0.5303 respectively) (Figure 2.5G, H). Calculated values are shown in Table 2. We verified that there was no difference in any metric on the contralateral side to confirm that dieldrin alone did not affect DA release or uptake (Supplemental Figure 2A-D). We also compared ipsilateral to contralateral metrics in the vehicle/PFF group and observed no significant effect of PFFs alone (Supplemental Figure 2E-H). Monomer-injected animals in both the vehicle and dieldrin-exposed groups showed similar outcomes on all FSCV metrics. Table 2.2. FSCV values (ipsilateral/contralateral) for vehicle/PFF and dieldrin/PFF groups (mean ± standard deviation) Developmental dieldrin exposure does not alter VMAT2 uptake velocity in PFF- injected animals 114 Figure 2.4. Dieldrin does not affect VMAT2 uptake velocity in PFF-injected male F1 offspring. There was no difference in uptake velocity ipsilateral to injection site 4 months post-PFF injection (p= 0.4524). All data shown as mean +/- SD. To determine if dieldrin exposure alters VMAT2 function in PFF-injected animals, uptake assays were performed at 4 months post-PFF injection. Somewhat surprisingly, there was no difference in VMAT2-mediated uptake velocity between the vehicle/PFF and the dieldrin/PFF groups ipsilateral to the injection site (Figure 2.4). As expected, there was no difference in uptake contralateral to the injection site, showing that dieldrin alone did not affect uptake velocity (Supplemental Figure 1A). In addition, uptake was equivalent between the ipsilateral and contralateral sides within the vehicle/PFF group, demonstrating no significant effect of PFFs alone (Supplemental Figure 1B). Observed uptake velocity was consistent with previously published values for VMAT2 uptake velocity in WT C57BL/6 mice (Lohr et al. 2014). Vehicle and dieldrin-exposed animals injected with monomer showed similar VMAT2 uptake velocity in the hemisphere ipsilateral to the injection (vehicle/monomer: 7.020 ± 2.224 pmol/mg/min, n = 4; dieldrin/monomer: 5.460 ± 1.678 pmol/mg/min, n = 4). 115 Figure 2.5. Dieldrin/PFFs increase peak dopamine and upward velocity in striatal tissues measured using FSCV. 4-months post-PFF injection, animals were killed and FSCV was performed in dorsal striatum. A) Example dopamine versus time graph showing each quantified metric. B) Representative dopamine versus time graph for the groups vehicle/PFF (black) and dieldrin/PFF (red). C,D) Representative dopamine concentration vs time plot for (C) vehicle/PFF and (D) dieldrin/PFF following stimulation at t=5 secs. E-H) FSCV metrics represented as ipsilateral values normalized to contralateral values. E) Quantification of peak dopamine showed a significant dieldrin- related increase (p= 0.0394). F) Quantification of upward velocity showed a significant dieldrin-related increase (p= 0.0434). G) Quantification of downward velocity showed no significant effect of dieldrin (p= 0.5303). H) Quantification of tau showed no significant effect of dieldrin (p= 0.6435). Each individual data point represents a sum of 20 recordings per animal. All data shown as mean +/- SD. Discussion A model of environmental risk and silent neurotoxicity in PD Based on the results reported here, we expand our model for how developmental dieldrin exposure leads to increased susceptibility to synucleinopathy-induced deficits in motor behavior (Richardson et al. 2006; Kochmanski et al. 2019; Gezer et al. 2020). In this model, exposure to dieldrin occurs during prenatal and postnatal development. The half-life of dieldrin in mouse brain is less than a week, so no detectable dieldrin remains in the brain of F1 offspring a few weeks after weaning (World Health Organization. et al. 1989; Richardson et al. 2006; Hatcher et al. 2007). When dieldrin is present in the 116 developing brain, it is thought to act on developing DA neurons by inhibiting GABAA receptor-mediated chloride flux, resulting in increased neuronal activity (Narahashi et al. 1995; Narahashi 1996; Liu et al. 1997; Lauder et al. 1998; Paladini and Tepper 1999; Okada et al. 2004). Based on previous results, we propose that this net increase in neuronal activity modifies the dopamine system through persistent sex-specific changes in epigenetic mechanisms, leading to the dysregulation of genes important for dopamine neuron development and maintenance in the substantia nigra and for the neuroinflammatory system in the striatum (Kochmanski et al. 2019; Gezer et al. 2020). These changes alter the response of the nigrostriatal system to future insults via persistent alterations in striatal dopamine synapses that manifest as an early increase in compensatory mechanisms triggered by synucleinopathy-induced striatal DA loss in adult male mice (Figure 4) (Gezer et al. 2020). Our results are also consistent with the idea of silent neurotoxicity, where the effects of early life exposures are unmasked by challenges later in life, the cumulative effects of exposures over the lifespan, or the effects of aging (Cory-Slechta et al. 2005; Kraft et al. 2016). In such a paradigm, developmental exposure to dieldrin primes the nigrostriatal striatal system in male offspring to have an exacerbated response to synucleinopathy induced by α-syn PFFs in the absence of observable changes in typical markers of nigrostriatal dysfunction and degeneration. In support of this, our previous studies identified persistent epigenetic and transcriptomic changes in genes related to DAergic differentiation and maintenance in the midbrain and altered expression of neuroinflammatory genes in the striatum at 12 weeks of age following developmental dieldrin exposure (Kochmanski et al. 2019; Gezer et al. 2020). In a parallel study, we 117 are also tracking the longitudinal patterns of dieldrin-induced epigenetic changes across the timeline of this entire two-hit model from birth to 9 months of age to determine if dieldrin alters the trajectory of epigenetic changes across the lifespan. Taken together, these results suggest that exploring dieldrin-induced changes that produce this high susceptibility state is critical to advancing our understanding of how exposures contribute to increased risk of PD and underscores the need to study PD- related exposures across the lifespan, particularly during sensitive periods of neurodevelopment. Figure 2.6: Overview of developmental dieldrin/PFF two-hit model. Made in BioRender. Developmental dieldrin exposure alters the dopaminergic response to synucleinopathy-triggered dopamine deficits Here, we demonstrate that developmental dieldrin exposure alters response to synucleinopathy and enhances DA release in PFF-injected male animals 4 months after PFF-injection (Figure 2.5,Figure 2.4). These results are consistent with our previous observation of an exacerbated increase in DA turnover at 6 months, summarized in Figure 2.7 (Gezer et al. 2020). If more DA is released at this 4 month, but DAT and VMAT2 uptake velocities are unchanged, this could lead to the increased DA turnover 118 observed at 6-month post-PFF injection (Alter et al. 2013). Importantly, our current data was collected 4 months post PFF injection while our previous data showed increase striatal DA turnover at 6 months, suggesting that this enhanced DA release precedes effects on DA turnover and motor behavior (Gezer et al. 2020). Of note, in our previous study, we reported that pSyn aggregation at 1 and 2 months, the loss of total striatal DA and its metabolites, DOPAC and HVA, at 2 and 6 months post-PFF injection and loss of nigral DA neurons at 6 months were not affected by dieldrin exposure (Gezer et al. 2020) (Figure 6). Taken together, despite similar levels of synucleinopathy-induced pathology and total tissue DA levels in dieldrin and vehicle exposed animals, dieldrin exposed animals display an increase in evoked DA release at 4 months post-PFF injection. While FSCV has been utilized in α-syn knockout and α-syn overexpressing models, to our knowledge, this is the first study to perform FSCV in either the dieldrin or α-syn PFF mouse model with intrastriatal injection (Yavich et al. 2004; Threlfell et al. 2021; Somayaji et al.). A previous paper performed FSCV in the mouse α-syn PFF model via intranigral injections at 2- and 5 months of age and reported decreased DA release in older animals only at 1- and 2 months post-injection (Sun et al. 2021). These and other studies in different α-syn models indicate a critical role for a-syn in DA release, synaptic vesicle fusion, vesicle trafficking, and regulation of synaptic vesicle pool size (Abeliovich et al. 2000; Murphy et al. 2000; Volles et al. 2001; Bellani et al. 2010; Cheng et al. 2011; Xilouri et al. 2013; Ingelsson 2016; Dagra et al. 2021). Given that we did not observe any effect of dieldrin or PFF alone on DA release, dieldrin exposure appears to cause changes in the synaptic terminal that prime the nigrostriatal system for an exacerbated 119 response to synucleinopathy and striatal DA loss, resulting in early enhanced DA release and an eventual increase DA turnover (Supplementary Figure 2)(Kochmanski et al. 2019; Gezer et al. 2020). Early nigrostriatal compensatory changes are well- documented in human PD, multiple animal models of DA deficits, and more recently in a model of other monoaminergic (norepinephrine) loss (Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Zigmond et al. 1993; Zigmond 1994; Bezard and Gross 1997; Zigmond 1997; Zigmond et al. 1998; Molina-Mateo et al. 2017; Iannitelli et al. 2023). Together, this suggests that dieldrin induces changes in the synaptic terminal that increase the compensatory response to early synucleinopathy- induced striatal DA loss that contributes to greater long-term increases in DA turnover due to increases in cytosolic DA, the resulting oxidative stress, and acceleration of the toxic interplay between dysregulated α-syn and DA (Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Zigmond et al. 1993; Bezard and Gross 1997; Zigmond 1997; Zigmond et al. 1998; Molina-Mateo et al. 2017; Iannitelli et al. 2023). Such a relationship between DA and α-syn is well-established and interfering with either can lead to a cycle of neurotoxicity where DA and α-syn interact and exacerbate the toxic effects of one another (Perez et al. 2002; Yavich et al. 2004; Peng et al. 2005; Tehranian et al. 2006; Nemani et al. 2010; Venda et al. 2010; Roy 2017). 120 Developmental dieldrin exposure does not affect DAT- or VMAT2-mediated uptake in PFF-injected animals We expected to see a relative increase in DAT function compared to VMAT2 function 4 months after PFF injection that was greater in animals developmentally exposed to dieldrin would lead to increased cytosolic DA and DA turnover and explain the dieldrin- induced exacerbation of synucleinopathy-induced changes in DA turnover (Richardson et al. 2006; Gezer et al. 2020). However, we did not observe any dieldrin related effect on VMAT2 uptake in PFF-injected animals (Figure 5). It is possible that there is an effect on VMAT2 uptake velocity in the intact system that was not observed here due to methodology. Specifically, isolating synaptic vesicles for this assay removes them from their biological context and measures persistent changes in function (Caudle et al. 2007; Lohr et al. 2014; Lohr et al. 2015; Lohr et al. 2016). In addition, this assay Figure 2.7: Summary of observed changes in the dieldrin PFF two hit model. Timelines show representative changes synuclein pathology, microglial activation, striatal loss, and nigral degeneration in the PFF model based on published literature, shown as the percent change in these markers compared to a saline/monomer injected mouse. Grey boxes indicate previous results from our lab in the dieldrin PFF two hit model. Blue boxes indicate FSCV and uptake results reported here at 4 months post- PFF injection. Blue and grey squares represent results from vehicle:PFF and dieldrin:PFF animals, respectively. 121 involves homogenizing the entire hemisphere of the brain, so effects may be diluted by DAergic vesicles from areas of the brain not affected in our PFF model, including unaffected terminals within the striatum. Thus, this assay may not have the sensitivity to detect a small change in this small subpopulation of terminals. Unfortunately, technical limitations preclude us from performing this assay on unilateral striata from the mouse brain. It is also possible to increase the relative levels of DAT to the VMAT2 function by affecting DAT function without alerting VMAT2 function. Multiple prior studies show that both dieldrin and PFFs can impact DAT expression and function (Richardson et al. 2006; Hatcher et al. 2007; Luk et al. 2012a; Sossi et al. 2022). Specifically, developmental dieldrin exposure was previously reported to lead to increases in striatal DAT levels at 12 weeks of age and changes in the DAT/VMAT2 ratio, but we did not observe the same effect in our previous study (Richardson et al. 2006; Gezer et al. 2020). In the mouse PFF model, striatal DAT protein expression at 6 months post-PFF injection in C57BL/6 mice was observed, but not at 1- and 3 months (Luk et al. 2012a). Thus, it is possible that dieldrin-induced increases in striatal DAT function lead to a less severe loss of DAT following PFF-induced synucleinopathy and a relative increase of DAT to VMAT2 function. However, we observed no change in DAT uptake in this study as measured by Tau and downward velocity, measures of DAT Km and Vmax, from FSCV data (Figure 2.5). Thus, it is possible that if more DA is released, but neither DAT- nor VMAT2-mediated uptake velocity is changed, the observed increase in turnover is due to both intracellular breakdown and extracellular metabolism of DA. Despite these caveats regarding VMAT2 and DAT uptake, this new data is consistent with our previous 122 results in this two-hit model showing no increase in α-syn pathology but an enhanced response to synucleinopathy in dieldrin-exposed F1 male offspring (Gezer et al. 2020). Synucleinopathy alone does not affect DA release 4 months after PFF injection Contrary to our hypothesis, we did not observe a synucleinopathy-induced decrease in DA release despite ~45% loss of total striatal DA levels 2 months post-PFF (Luk et al. 2012a; Gezer et al. 2020). This discrepancy is likely due to methodological differences and the underlying biology of DA neurons. HPLC measures total tissue DA levels from tissue punches, while FSCV measures extracellular DA only from the area immediately surrounding the electrode. Biologically, while there is a significant loss of total tissue DA at 2 months post-PFF injection, reductions in DA release at these synapses may be delayed relative to this loss. Most striatal DA synapses are silent, and the majority of synaptic vesicles are located within the reserve pool rather than the readily releasable pool (Goldstein 2012; Goldstein 2013; Trudeau et al. 2014; Sulzer et al. 2016; Goldstein 2021). Additionally, within the striatum of PFF-injected animals, we expect only a third to a half of terminals to be affected. Together, this leaves a pool of both surviving neurons and vesicles within affected neurons to maintain DA release. Consistent with this, we previously observed only mild PFF-associated effects on motor behavior at 4 months post-PFF injection, suggesting that DA release is maintained even with a 45% loss of total striatal DA at 2 months post-PFF (Gezer et al. 2020). In line with this, it is generally accepted that DA-related symptoms in human PD do not present until at least 30% of dopaminergic neurons in the nigrostriatal pathway are lost, suggesting that remaining neurons release sufficient quantities of DA despite the loss of total DA (Cheng et al. 2010). 123 Data Availability This study was preregistered with Open Science Framework at https://doi.org/10.17605/osf.io/qv4ya (Bernstein and Boyd 2022). All data acquired and analyzed for this study are available in the Dryad Data Repository https://doi.org/10.5061/dryad.qz612jmmq (Bernstein and Boyd 2023). CRediT Author Statement Sierra L. Boyd: Investigation, Software, Formal Analysis, Writing – Original Draft, Writing – Review & Editing, Visualization, Project Administration; Nathan C. Kuhn: Methodology, Investigation, Project Administration; Joseph R. Patterson: Investigation, Validation, Writing – Review & Editing; Anna C. Stoll: Investigation; Sydney A. Zimmerman: Investigation; Mason R. Kolanowski: Investigation; Joseph J. Neubecker: Investigation; Kelvin C. Luk: Resources; Eric S. Ramsson: Conceptualization, Investigation, Supervision, Writing – Review & Editing; Caryl E. Sortwell: Conceptualization, Investigation, Supervision, Writing – Review & Editing; Alison I. Bernstein: Conceptualization, Supervision, Data Curation, Writing – Review & Editing, Funding Acquisition Funding: This work was supported by the National Institutes of Health R01ES031237. Conflicts of Interest Statement: All authors declare that they have no conflicts of interest. 124 TABLES AND FIGURES Figure S2.1. Developmental dieldrin exposure or PFF injection alone do not affect VMAT2-mediated vesicular uptake. A) There was no effect of dieldrin on VMAT2-mediated uptake on the non-injected contralateral side (p=0.5972). B) There was no effect of PFF on uptake from comparing ipsilateral to contralateral in vehicle/PFF animals (p=0.0871). Each data point represents an individual animal. All data shown as mean +/- SD. 125 Figure S2.2. Developmental dieldrin exposure or PFF injection alone do not affect FSCV metrics. A-D) There was no dieldrin-related effect on the contralateral side on peak dopamine, upward velocity, downward velocity, or tau between vehicle/PFF versus dieldrin/PFF, indicating that dieldrin alone has no effect on FSCV metrics at this time point (p=0.2033, 0.2189, 0.5133, and 0.5736, respectively). E-H) There was no PFF-related effect on peak dopamine, upward velocity, downward velocity, or tau between the contralateral versus ipsilateral striata, indicating that PFF injection alone has no effect on FSCV metrics at this point (p=0.6708, 0.6562, 0.2395, and 0.8440 respectively). Each individual data point represents a sum of 20 recordings per animal. All data shown as mean +/- SD. 126 Table S2.1. FSCV values (ipsilateral/contralateral) for each individual animal in vehicle/monomer and dieldrin/monomer groups 127 REFERENCES Abeliovich A, Schmitz Y, Fariñ I, Choi-Lundberg D, Ho W-H, Castillo PE, Shinsky N, Manuel J, Verdugo G, Armanini M, et al. 2000. Mice Lacking a-Synuclein Display Functional Deficits in the Nigrostriatal Dopamine System. Neuron. 25:239–252. doi:10.1016/s0896-6273(00)80886-7. Adamson A, Buck SA, Freyberg Z, De Miranda BR. 2022. Sex Differences in Dopaminergic Vulnerability to Environmental Toxicants — Implications for Parkinson’s Disease. Curr Environ Health Rep. 9(4):563–573. doi:10.1007/s40572-022-00380-6. Agency for Toxic Substances and Disease Registry (ATSDR). 2022. Toxicological Profile for Aldrin and Dieldrin. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. Alter SP, Lenzi GM, Bernstein AI, Miller GW. 2013. Vesicular integrity in parkinson’s disease. Curr Neurol Neurosci Rep. 13(7). doi:10.1007/s11910-013-0362-3. Alves G, Müller B, Herlofson K, HogenEsch I, Telstad W, Aarsland D, Tysnes OB, Larsen JP. 2009. Incidence of Parkinson’s disease in Norway: The Norwegian ParkWest study. J Neurol Neurosurg Psychiatry. 80(8):851–857. doi:10.1136/jnnp.2008.168211. Ascherio A, Chen H, Weisskopf MG, O’Reilly E, McCullough ML, Calle EE, Schwarzschild MA, Thun MJ. 2006. Pesticide exposure and risk for Parkinson’s disease. Ann Neurol. 60(2):197–203. doi:10.1002/ana.20904. Baldereschi M, Carlo A Di, Vanni P, Grigoletto F. 2000. Parkinson’s disease and parkinsonism in a longitudinal study. Neurology. 55(9):1358–1363. doi:10.1212/wnl.55.9.1358. Bellani S, Sousa VL, Ronzitti G, Valtorta F, Meldolesi J, Chieregatti E. 2010. The regulation of synaptic function by α-synuclein. Commun Integr Biol. 3(2):106–109. doi:10.4161/cib.3.2.10964. Ben-Scachar D, Zuk R, Glinka Y. 1995. Dopamine Neurotoxicity: Inhibition of Mitochondrial Respiration. J Neurochem. 64(2):718–723. doi:10.1046/j.1471- 4159.1995.64020718.x. Bernstein AI, Boyd S. 2022 Feb 22. Striatal synaptic function in the dieldrin-PFF two-hit model. Open Science Framework. doi:10.17605/OSF.IO/QV4YA. Bernstein AI, Boyd SL. 2023. Data for: Parkinson’s disease-associated organochlorine pesticide dieldrin alters dopamine neurotransmission in α-synuclein pre-formed fibril (PFF)-injected mice. Dray Data. https://doi.org/10.5061/dryad.qz612jmmq. Bernstein AI, Stout KA, Miller GW. 2012. A fluorescent-based assay for live cell, spatially resolved assessment of vesicular monoamine transporter 2-mediated neurotransmitter transport. J Neurosci Methods. 209(2):357–366. doi:10.1016/j.jneumeth.2012.06.002. 128 Bezard E, Gross CE. 1997. Compensatory mechanisms in experimental and human Parkinsonism: Towards a Dynamic Approach. Prog Neurobiol. 55(2):93–116. doi:10.1016/s0301-0082(98)00006-9. Brown TP, Rumsby PC, Capleton AC, Rushton L, Levy LS. 2006. Pesticides and Parkinson’s disease - Is there a link? Environ Health Perspect. 114(2):156–164. doi:10.1289/ehp.8095. Caudle WM, Guillot TS, Lazo CR, Miller GW. 2012. Industrial toxicants and Parkinson’s disease. Neurotoxicology. 33(2):178–188. doi:10.1016/j.neuro.2012.01.010. Caudle WM, Richardson JR, Wang MZ, Taylor TN, Guillot TS, McCormack AL, Colebrooke RE, Di Monte DA, Emson PC, Miller GW. 2007. Reduced vesicular storage of dopamine causes progressive nigrostriatal neurodegeneration. J Neurosci. 27(30):8138–8148. doi:10.1523/JNEUROSCI.0319-07.2007. Cheng F, Vivacqua G, Yu S. 2011. The role of alpha-synuclein in neurotransmission and synaptic plasticity. J Chem Neuroanat. 42(4):242–248. doi:10.1016/j.jchemneu.2010.12.001. Cheng HC, Ulane CM, Burke RE. 2010. Clinical progression in Parkinson disease and the neurobiology of axons. Ann Neurol. 67(6):715–725. doi:10.1002/ana.21995. Chun HS, Gibson GE, DeGiorgio LA, Zhang H, Kidd VJ, Son JH. 2001. Dopaminergic cell death induced by MPP(+), oxidant and specific neurotoxicants shares the common molecular mechanism. J Neurochem. 76(4):1010–21. Cicchetti F, Drouin-Ouellet J, Gross RE. 2009. Environmental toxins and Parkinson’s disease: what have we learned from pesticide-induced animal models? Trends Pharmacol Sci. 30(9):475–483. doi:10.1016/j.tips.2009.06.005. Corrigan FM, Lochgilphead CL, Shore RF, Daniel SE, Mann D. 2000. Organochlorine insecticides in substantia nigra in parkinson’s disease. J Toxicol Environ Health A. 59(4):229–234. doi:10.1080/009841000156907. Corrigan FM, Murray L, Wyatt CL, Shore RF. 1998. Diorthosubstituted Polychlorinated Biphenyls in Caudate Nucleus in Parkinson’s Disease. Exp Neurol. 150(2):339–342. doi:10.1006/exnr.1998.6776. Cory-Slechta DA, Thiruchelvam M, Richfield EK, Barlow BK, Brooks AI. 2005. Developmental pesticide exposures and the Parkinson’s disease phenotype. Birth Defects Res A Clin Mol Teratol. 73(3):136–139. doi:10.1002/bdra.20118. Le Couteur D, McLean A, Taylor M, Woodham B, Board P. 1999. Pesticides and Parkinson’s disease. Biomed Pharmacother. 53(3):122–130. doi:10.1016/S0753- 3322(99)80077-8. 129 Dagra A, Miller DR, Lin M, Gopinath A, Shaerzadeh F, Harris S, Sorrentino ZA, Støier JF, Velasco S, Azar J, et al. 2021. α-Synuclein-induced dysregulation of neuronal activity contributes to murine dopamine neuron vulnerability. NPJ Parkinsons Dis. 7(1). doi:10.1038/s41531-021-00210-w. Davis SE, Korich AL, Ramsson ES. 2020. Enhancement of fast scan cyclic voltammetry detection of dopamine with tryptophan-modified electrodes. PLoS One. 15(7). doi:10.1371/journal.pone.0235407. Dorsey R, Elbaz A, Nichols E, Abd-Allah F, Abdelalim A, Adsuar JC, Ansha MG, Brayne C, Choi JYJ, Collado-Mateo D, et al. 2018. Global, regional, and national burden of Parkinson’s disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 17(11):939–953. doi:10.1016/S1474- 4422(18)30295-3. van den Eeden SK, Tanner CM, Bernstein AL, Fross RD, Leimpeter A, Bloch DA, Nelson LM. 2003. Incidence of Parkinson’s disease: Variation by age, gender, and race/ethnicity. Am J Epidemiol. 157(11):1015–1022. doi:10.1093/aje/kwg068. Elbaz A, Bower JH, Maraganore DM, Mcdonnell SK, Peterson BJ, Ahlskog JE, Schaid DJ, Rocca WA. 2002. Risk tables for parkinsonism and Parkinson’s disease. J Clin Epidemiol. 55:25–31. doi:10.1016/s0895-4356(01)00425-5. Elbaz A, Clavel J, Rathouz PJ, Moisan F, Galanaud JP, Delemotte B, Alpérovitch A, Tzourio C. 2009. Professional exposure to pesticides and Parkinson disease. Ann Neurol. 66(4):494–504. doi:10.1002/ana.21717. Everett AC, Graul BE, Ronström JW, Robinson JK, Watts DB, España RA, Siciliano CA, Yorgason JT. 2022. Effectiveness and Relationship between Biased and Unbiased Measures of Dopamine Release and Clearance. ACS Chem Neurosci. doi:10.1021/acschemneuro.2c00033. Ferris MJ, España RA, Locke JL, Konstantopoulos JK, Rose JH, Chen R, Jones SR. 2014. Dopamine transporters govern diurnal variation in extracellular dopamine tone. Proc Natl Acad Sci U S A. 111(26). doi:10.1073/pnas.1407935111. Fleming L, Mann JB, Bean J, Briggle T, Sanchez-Ramos JR. 1994. Parkinson’s disease and brain levels of organochlorine pesticides. Ann Neurol. 36(1):100–3. doi:10.1002/ana.410360119. Fleming SM. 2017. Mechanisms of Gene-Environment Interactions in Parkinson’s Disease. Curr Environ Health Rep. 4(2):192–199. doi:10.1007/s40572-017-0143-2. Freire C, Koifman S. 2012. Pesticide exposure and Parkinson’s disease: Epidemiological evidence of association. Neurotoxicology. 33(5):947–971. doi:10.1016/j.neuro.2012.05.011. 130 Gainetdinov R R, Levey A I, Caron M G, Miller GW, Gainetdinov Raul R, Levey Allan I, Caron Marc G. 1999. Dopamine transporters and neuronal injury. Trends Pharmacol Sci. 20(10):424–429. doi:10.1016/s0165-6147(99)01379-6. Georgiev D, Hamberg K, Hariz M, Forsgen L, Hariz G. 2017. Gender differences in Parkinson’s disease: A clinical perspective . Acta Neurol Scand. 136(6):570–584. doi:10.1111/ane.12796. Gezer AO, Kochmanski J, VanOeveren SE, Cole-Strauss A, Kemp CJ, Patterson JR, Miller KM, Kuhn NC, Herman DE, McIntire A, et al. 2020. Developmental exposure to the organochlorine pesticide dieldrin causes male-specific exacerbation of α-synuclein- preformed fibril-induced toxicity and motor deficits. Neurobiol Dis. 141(February):104947. doi:10.1016/j.nbd.2020.104947. Gillies GE, Pienaar IS, Vohra S, Qamhawi Z. 2014. Sex differences in Parkinson’s disease. Front Neuroendocrinol. 35(3):370–384. doi:10.1016/j.yfrne.2014.02.002. Goldstein DS. 2012. Stress, allostatic load, catecholamines, and other neurotransmitters in neurodegenerative diseases. Cell Mol Neurobiol. 32(5):661–666. doi:10.1007/s10571-011-9780-4. Goldstein DS. 2013. Biomarkers, mechanisms, and potential prevention of catecholamine neuron loss in parkinson disease. Adv Pharmacol. 68:235–272. doi:10.1016/B978-0-12-411512-5.00012-9. Goldstein DS. 2021. The catecholaldehyde hypothesis for the pathogenesis of catecholaminergic neurodegeneration: What we know and what we do not know. Int J Mol Sci. 22(11). doi:10.3390/ijms22115999. Gonzales C, Zaleska MM, Riddell DR, Atchison KP, Robshaw A, Zhou H, Sukoff Rizzo SJ. 2014. Alternative method of oral administration by peanut butter pellet formulation results in target engagement of BACE1 and attenuation of gavage-induced stress responses in mice. Pharmacol Biochem Behav. 126:28–35. doi:10.1016/j.pbb.2014.08.010. Graham D, Tiffany S, Bell W, Gutknecht W. 1978. Autoxidation versus Covalent Binding of Quinones as the Mechanism of Toxicity of Dopamine, 6-Hydroxydopamine, and Related Compounds toward C1300 Neuroblastoma Cells in Vitro. Mol Pharmacol. 14(4):644–653. Guillot TS, Shepherd KR, Richardson JR, Wang MZ, Li Y, Emson PC, Miller GW. 2008. Reduced vesicular storage of dopamine exacerbates methamphetamine-induced neurodegeneration and astrogliosis. J Neurochem. 106(5):2205–2217. doi:10.1111/j.1471-4159.2008.05568.x. Haaxma CA, Bloem BR, Borm GF, Oyen WJG, Leenders KL, Eshuis S, Booij J, Dluzen DE, Horstink MWIM. 2007. Gender differences in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 78(8):819–824. doi:10.1136/jnnp.2006.103788. 131 Hastings TG, Lewist DA, Zigmond M. 1996. Role of oxidation in the neurotoxic effects of intrastriatal dopamine injections. Neurobiology. 93:1956–1961. doi:10.1073/pnas.93.5.1956. Hatcher JM, Pennell KD, Miller GW. 2008. Parkinson’s disease and pesticides: a toxicological perspective. Trends Pharmacol Sci. 29(6):322–329. doi:10.1016/j.tips.2008.03.007. Hatcher JM, Richardson JR, Guillot TS, McCormack AL, Di Monte DA, Jones DP, Pennell KD, Miller GW. 2007. Dieldrin exposure induces oxidative damage in the mouse nigrostriatal dopamine system. Exp Neurol. 204(2):619–630. doi:10.1016/j.expneurol.2006.12.020. Iannitelli AF, Kelberman MA, Lustberg DJ, Korukonda A, McCann KE, Mulvey B, Segal A, Liles LC, Sloan SA, Dougherty JD, et al. 2023. The Neurotoxin DSP-4 Dysregulates the Locus Coeruleus-Norepinephrine System and Recapitulates Molecular and Behavioral Aspects of Prodromal Neurodegenerative Disease. eNeuro. 10(1). doi:10.1523/ENEURO.0483-22.2022. Ingelsson M. 2016. Alpha-synuclein oligomers-neurotoxic molecules in Parkinson’s disease and other lewy body disorders. Front Neurosci. 10(SEP):1–10. doi:10.3389/fnins.2016.00408. de Jong Geert, H Swaen GM, M Slangen Joseph J, M Slangen J J, de Jong G. 1997. Mortality of workers exposed to dieldrin and aldrin: a retrospective cohort study. Occup Environ Med. 54:702–707. doi:10.1136/oem.54.10.702. Jorgenson JL. 2001. Aldrin and dieldrin: a review of research on their production, environmental deposition and fate, bioaccumulation, toxicology, and epidemiology in the United States. Environ Health Perspect. 109 (suppl 1):113–139. doi:10.1289/ehp.01109s1113. Kang Y, Goyal A, Hwang S, Park C, Cho HU, Shin H, Park J, Bennet KE, Lee KH, Oh Y, et al. 2021. Enhanced Dopamine Sensitivity Using Steered Fast-Scan Cyclic Voltammetry. ACS Omega. 6(49):33599–33606. doi:10.1021/acsomega.1c04475. Kanthasamy AG, Kitazawa M, Kanthasamy A, Anantharam V. 2005. Dieldrin-induced neurotoxicity: Relevance to Parkinson’s disease pathogenesis. Neurotoxicology. 26(4 SPEC. ISS.):701–719. doi:10.1016/j.neuro.2004.07.010. Kitazawa M, Anantharam V, Kanthasamy AG. 2001. Dieldrin-induced oxidative stress and neurochemical changes contribute to apoptopic cell death in dopaminergic cells. Free Radic Biol Med. 31(11):1473–1485. doi:10.1016/S0891-5849(01)00726-2. Kitazawa M, Anantharam V, Kanthasamy AG. 2003. Dieldrin induces apoptosis by promoting caspase-3-dependent proteolytic cleavage of protein kinase Cδ in dopaminergic cells: Relevance to oxidative stress and dopaminergic degeneration. Neuroscience. 119(4):945–964. doi:10.1016/S0306-4522(03)00226-4. 132 Kochmanski J, Vanoeveren SE, Bernstein AI. 2019. Developmental Dieldrin Exposure Alters DNA Methylation at Genes Related to Dopaminergic Neuron Development and Parkinson’s Disease in Mouse Midbrain. Toxicol Sci. 169(2):593–607. doi:10.1093/toxsci/kfz069. Kraft AD, Aschner M, Cory-Slechta DA, Bilbo SD, Caudle WM, Makris SL. 2016. Unmasking silent neurotoxicity following developmental exposure to environmental toxicants. Neurotoxicol Teratol. 55:38–44. doi:10.1016/j.ntt.2016.03.005. de Lau LM, Breteler MM. 2006. Epidemiology of Parkinson’s Disease. Lancet Neurol. 5(6):525–535. doi:10.1016/S1474-4422(06)70471-9. Lauder J, Jiu J, Devaud L, Morrow A. 1998. GABA as a trophic factor for developing monoamine neurons. Perspect Dev Neurobiol. 5(2–3):247–259. Liu J, Morrow AL, Devaud L, Grayson DR, Lauder JM. 1997. GABA A Receptors Mediate Trophic Effects of GABA on Embryonic Brainstem Monoamine Neurons In Vitro. J Neurosci. 17(7):2420–2428. doi:10.1523/JNEUROSCI.17-07-02420.1997. Lohr KM, Bernstein AI, Stout KA, Dunn AR, Lazo CR, Alter SP, Wang M, Li Y, Fan X, Hess EJ, et al. 2014. Increased vesicular monoamine transporter enhances dopamine release and opposes Parkinson disease-related neurodegeneration in vivo. Proc Natl Acad Sci U S A. 111(27):9977–9982. doi:10.1073/pnas.1402134111. Lohr KM, Chen M, Hoffman CA, McDaniel MJ, Stout KA, Dunn AR, Wang M, Bernstein AI, Miller GW. 2016. Vesicular monoamine transporter 2 (VMAT2) level regulates MPTP vulnerability and clearance of excess dopamine in mouse striatal terminals. Toxicological Sciences. 153(1):79–88. doi:10.1093/toxsci/kfw106. Lohr KM, Stout KA, Dunn AR, Wang M, Salahpour A, Guillot TS, Miller GW. 2015. Increased Vesicular Monoamine Transporter 2 (VMAT2; Slc18a2) Protects against Methamphetamine Toxicity. ACS Chem Neurosci. 6(5):790–799. doi:10.1021/acschemneuro.5b00010. Luk KC, Kehm V, Carroll J, Zhang B, O’Brein P, Trojanowski JQ, Lee VM-Y. 2012. Pathological α-Synuclein Transmission Initiates Parkinson-like Neurodegeneration in Non-transgenic Mice. Science. 338(6109):949–953. doi:10.1126/science.1227157. Luk KC, Kehm VM, Zhang B, O’Brien P, Trojanowski JQ, Lee VMY. 2012. Intracerebral inoculation of pathological α-synuclein initiates a rapidly progressive neurodegenerative α-synucleinopathy in mice. J Exp Med. 209(5):975–988. doi:10.1084/jem.20112457. Meijer SN, Halsall CJ, Harner T, Peters AJ, Ockenden WA, Johnston AE, Jones KC. 2001. Organochlorine pesticide residues in archived UK soil. Environ Sci Technol. 35(10):1989–95. doi:10.1021/es0000955. Meiser J, Weindl D, Hiller K. 2013. Complexity of dopamine metabolism. Cell Communication and Signaling. 11(1):1–18. doi:10.1186/1478-811X-11-34. 133 Miller GW, Taylor TN, Caudle WM. 2011. VMAT2-deficient mice display nigral and extranigral pathology and motor and nonmotor symptoms of Parkinson’s disease. Parkinsons Dis. 2011. doi:10.4061/2011/124165. De Miranda BR, Fazzari M, Rocha EM, Castro S, Greenamyre JT. 2019. Sex Differences in Rotenone Sensitivity Reflect the Male-to-Female Ratio in Human Parkinson’s Disease Incidence. Toxicological Sciences. 170(1):133–143. doi:10.1093/toxsci/kfz082. De Miranda BR, Goldman SM, Miller GW, Greenamyre JT, Dorsey ER. 2022. Preventing Parkinson’s Disease: An Environmental Agenda. J Parkinsons Dis. 12(1):45–68. doi:10.3233/JPD-212922. Molina-Mateo D, Fuenzalida-Uribe N, Hidalgo S, Molina-Fernández C, Abarca J, Zárate R V., Escandón M, Figueroa R, Tevy MF, Campusano JM. 2017. Characterization of a presymptomatic stage in a Drosophila Parkinson’s disease model: Unveiling dopaminergic compensatory mechanisms. Biochim Biophys Acta Mol Basis Dis. 1863(11):2882–2890. doi:10.1016/j.bbadis.2017.07.013. Mor DE, Tsika E, Mazzulli JR, Gould NS, Kim H, Daniels MJ, Doshi S, Gupta P, Grossman JL, Tan VX, et al. 2017. Dopamine induces soluble α-synuclein oligomers and nigrostriatal degeneration. Nat Neurosci. 20(11):1560–1568. doi:10.1038/nn.4641. Moretto A, Colosio C. 2011. Biochemical and toxicological evidence of neurological effects of pesticides: The example of Parkinson’s disease. Neurotoxicology. 32(4):383– 391. doi:10.1016/j.neuro.2011.03.004. Murphy DD, Rueter SM, Trojanowski JQ, M-Y Lee V. 2000. Synucleins Are Developmentally Expressed, and-Synuclein Regulates the Size of the Presynaptic Vesicular Pool in Primary Hippocampal Neurons. J Neurosci. 2000 May 1;20(9):3214- 20. doi: 10.1523/JNEUROSCI.20-09-03214.2000. Narahashi T. 1996. Neuronal Ion Channels as the Target Sites of Insecticides. Pharmacol Toxicol. 79(1):1–14. doi:10.1111/j.1600-0773.1996.tb00234.x. Narahashi T, Carter D, Frey J, Ginsburg K, Hamilton B, Nagata K, Roy M, Song J, Tatebayashi H. 1995. Sodium channels and GABAA receptor-channel complex as targets of environmental toxicants. Toxicol Lett. 82:239–245. doi:10.1016/0378- 4274(95)03482-x. Nemani VM, Lu W, Berge V, Nakamura K, Onoa B, Lee MK, Chaudhry FA, Nicoll RA, Edwards RH. 2010. Increased Expression of α-Synuclein Reduces Neurotransmitter Release by Inhibiting Synaptic Vesicle Reclustering after Endocytosis. Neuron. 65(1):66–79. doi:10.1016/j.neuron.2009.12.023. Okada H, Mtsushita N, Kobayashi Kenta, Kobayashi Kazuto. 2004. Identification of GABAA receptor subunit variants in midbrain dopaminergic neurons. J Neurochem. 89(1):7–14. doi:10.1111/j.1471-4159.2004.02271.x. 134 Onn S-P, Berger TW, Stricker EM, Zigmond MJ. 1986. Effects of Intraventricular 6- Hydroxydopamine on the Dopaminergic Innervation of Striatum: Histochemical and Neurochemical Analysis. Brain Res. 376:8–19. doi:10.1016/0006-8993(86)90894-2. Paladini C, Tepper J. 1999. GABA(A) and GABA(B) antagonists differentially affect the firing pattern of substantia nigra dopaminergic neurons in vivo. Synpase. 32(3):165– 176. doi:10.1002/(SICI)1098-2396(19990601)32:3<165::AID-SYN3>3.0.CO;2-N. Patterson JR, Polinski NK, Duffy MF, Kemp CJ, Luk KC, Volpicelli-Daley LA, Kanaan NM, Sortwell CE. 2019. Generation of alpha-synuclein preformed fibrils from monomers and use in vivo. JoVE. 2019(148):1–10. doi:10.3791/59758. Peng XM, Tehranian R, Dietrich P, Stefanis L, Perez RG. 2005. α-synuclein activation of protein phosphatase 2A reduces tyrosine hydroxylase phosphorylation in dopaminergic cells. J Cell Sci. 118(15):3523–3530. doi:10.1242/jcs.02481. Perez RG, Waymire JC, Lin E, Liu JJ, Guo F, Zigmond MJ. 2002. A Role for-Synuclein in the Regulation of Dopamine Biosynthesis. J Neurosci. 22(8):3090–3099. doi:10.1523/JNEUROSCI.22-08-03090.2002. Priyadarshi A, Khuder S, Schaub E, Shirvastava S. 2000. A meta-analysis of Parkinson’s disease and exposure to pesticides. Neurotoxicology. 21(4):435–440. Priyadarshi A, Khuder SA, Schaub EA, Priyadarshi SS. 2001. Environmental risk factors and parkinson’s disease: A metaanalysis. Environ Res. 86(2):122–127. doi:10.1006/enrs.2001.4264. Ramsson ES. 2016. A pipette-based calibration system for fast-scan cyclic voltammetry with fast response times. Biotechniques. 61(5):269–271. doi:10.2144/000114476. Ramsson ES, Cholger D, Dionise A, Poirier N, Andrus A, Curtiss R. 2015. Characterization of fast-scan cyclic voltammetric electrodes using paraffin as an effective sealant with in vitro and in vivo applications. PLoS One. 10(10):1–15. doi:10.1371/journal.pone.0141340. Richardson JR, Caudle WM, Wang M, Dean ED, Pennell KD, Miller GW, Richardson JR, Caudle WM, Wang M, Dean ED, et al. 2006. Developmental exposure to the pesticide dieldrin alters the dopamine system and increases neurotoxicity in an animal model of Parkinson’s disease. The FASEB Journal. 20(10):1695–1697. doi:10.1096/fj.06-5864fje. Ritz B, Yu F. 2000. Parkinson’s disease mortality and pesticide exposure in California 1984–1994. Int J Epidemiol. 29(3):323–329. doi:10.1093/ije/29.2.323. Roy S. 2017. Synuclein and dopamine: The Bonnie and Clyde of Parkinson’s disease. Nat Neurosci. 20(11):1514–1515. doi:10.1038/nn.4660. 135 Sanchez-Ramos J, Facca A, Basit A, Song S. 1998. Toxicity of dieldrin for dopaminergic neurons in mesencephalic cultures. Exp Neurol. 150(2):263–271. doi:10.1006/exnr.1997.6770. Schneider CA, Rasband WS, Eliceiri KW. 2012. NIH Image to ImageJ: 25 years of Image Analysis HHS Public Access. Nat Methods. 9(7):671–675. doi:10.1038/nmeth.2089. Semchuk KM, Love EJ, Lee RG. 1992. Parkinson’s disease and exposure to agricultural work and pesticide chemicals. Neurology. 42:1328–1335. doi:10.1212/wnl.42.7.1328. Semchuk KM, Love EJ, Lee RG. 1991. Parkinson’s Disease and Exposure to Rural Environmental Factors: A Population Based Case-Control Study. Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques. 18(3):279–286. doi:10.1017/S0317167100031826. Snyder. GL, Keller R, igmond M. 1990. Dopamine efflux from striatal slices after intracerebral 6-hydroxydopamine: Evidence for compensatory hyperactivity of residual terminals. Pharmacology and Experimental Therapeutics. 253:867–876. Somayaji M, Cataldi S, Choi J, Edwards RH, Mosharov E V, Sulzer D. 2020. A dual role for α-synuclein in facilitation and depression of dopamine release from substantia nigra neurons in vivo. doi:10.1073/pnas.2013652117. Sossi V, Patterson JR, McCormick S, Kemp CJ, Miller KM, Stoll AC, Kuhn N, Kubik M, Kochmanski J, Luk KC, et al. 2022. Dopaminergic Positron Emission Tomography Imaging in the Alpha-Synuclein Preformed Fibril Model Reveals Similarities to Early Parkinson’s Disease. Movement Disorders. 37(8):1739–1748. doi:10.1002/mds.29051. Staal RGW, Hogan KA, Liang CL, German DC, Sonsalla PK. 2000. In vitro studies of striatal vesicles containing the vesicular monoamine transporter (VMAT2): Rat versus mouse differences in sequestration of 1- methyl-4-phenylpyridinium. J Pharmacol Exp Ther. 293(2):329–335. Steenland K, Hein MJ, Cassinelli RT, Prince MM, Nilsen NB, Whelan EA, Waters MA, Ruder AM, Schnorr TM. 2006. Polychlorinated biphenyls and neurodegenerative disease mortality in an occupational cohort. Epidemiology. 17(1):8–13. doi:10.1097/01.ede.0000190707.51536.2b. Sun F, Salinas, AG, Filser S, Blumenstock S, Medina-Luque J, Herms, J, Sgobio C. 2021. Impact of α-synuclein spreading on the nigrostriatal dopaminergic pathway depends on the onset of the pathology. Brain Pathology. 32(2):e13036. doi:10.1111/bpa.13036. Sulzer D, Cragg SJ, Rice ME. 2016. Striatal dopamine neurotransmission: Regulation of release and uptake. Basal Ganglia. 6(3):123–148. doi:10.1016/j.baga.2016.02.001. 136 Takmakov P, Zachek MK, Keithley RB, Walsh PL, Donley C, McCarty GS, Wightman RM. 2010. Carbon microelectrodes with a renewable Surface. Anal Chem. 82(5):2020– 2028. doi:10.1021/ac902753x. Tanner CM, Aston DA. 2000. Epidemiology of Parkinson’s disease and akinetic syndromes. Curr Opin Neurol. 13:427–430. doi:10.1097/00019052-200008000-00010. Tanner CM, Kame F, Ross GW, Hoppin JA, Goldman SM, Korell M, Marras C, Bhudhikanok GS, Kasten M, Chade AR, et al. 2011. Rotenone, paraquat, and Parkinson’s disease. Environ Health Perspect. 119(6):866–872. doi:10.1289/ehp.1002839. Tanner CM, Langston JW. 1990. Do environmental toxins cause Parkinson’s disease? A critical review. Neurology. 40(10):17–30. Taylor KSM, Cook JA, Counsell CE. 2007. Heterogeneity in male to female risk for Parkinson’s disease [1]. J Neurol Neurosurg Psychiatry. 78(8):905–906. doi:10.1136/jnnp.2006.104695. Taylor TN, Caudle WM, Shepherd KR, Noorian AR, Jackson CR, Iuvone PM, Weinshenker D, Greene JG, Miller GW. 2009. Nonmotor symptoms of Parkinson’s disease revealed in an animal model with reduced monoamine storage capacity. J Neurosci. 29(25):8103–8113. doi:10.1523/JNEUROSCI.1495-09.2009. Tehranian R, Montoya SE, Van Laar AD, Hastings TG, Perez RG. 2006. Alpha-synuclein inhibits aromatic amino acid decarboxylase activity in dopaminergic cells. J Neurochem. 99(4):1188–1196. doi:10.1111/j.1471-4159.2006.04146.x. Threlfell S, Mohammadi AS, Ryan BJ, Connor-Robson N, Platt NJ, Anand R, Serres F, Sharp T, Bengoa-Vergniory N, Wade-Martins R, et al. 2021. Striatal Dopamine Transporter Function Is Facilitated by Converging Biology of α-Synuclein and Cholesterol. Front Cell Neurosci. 15. doi:10.3389/fncel.2021.658244. Trudeau LE, Hnasko TS, Wallén-Mackenzie Å, Morales M, Rayport S, Sulzer D. 2014. The multilingual nature of dopamine neurons. In: Progress in Brain Research. Vol. 211. Elsevier B.V. p. 141–164. Uhl GR. 1998. Hypothesis: the role of dopaminergic transporters inselective vulnerability of cells in Parkinson’s disease. Ann Neurol. 43:555–560. doi:10.1002/ana.410430503. Venda LL, Cragg SJ, Buchman VL, Wade-Martins R. 2010. α-Synuclein and dopamine at the crossroads of Parkinson’s disease. Trends Neurosci. 33(12):559–568. doi:10.1016/j.tins.2010.09.004. Volles MJ, Lee SJ, Rochet JC, Shtilerman MD, Ding TT, Kessler JC, Lansbury PT. 2001. Vesicle permeabilization by protofibrillar α-synuclein: Implications for the pathogenesis and treatment of Parkinson’s disease. Biochemistry. 40(26):7812–7819. doi:10.1021/bi0102398. 137 Weisskopf M, Knekt P, O’Reilly E, Lyytinen J, Reunanen A, Laden F, Altshul L, Ascherio A. 2010. Persistent organochlorine pesticides in serum and risk of Parkinson disease. Neurology. 74(13):1055–1061. doi: 10.1212/WNL.0b013e3181d76a93. Willis AW, Roberts E, Beck JC, Fiske B, Ross W, Savica R, van den Eeden SK, Tanner CM, Marras C, Alcalay R, et al. 2022. Incidence of Parkinson disease in North America. NPJ Parkinsons Dis. 8(1). doi:10.1038/s41531-022-00410-y. Wirdefeldt K, Adami HO, Cole P, Trichopoulos D, Mandel J. 2011. Epidemiology and etiology of Parkinson’s disease: A review of the evidence. Eur J Epidemiol. 26(SUPPL. 1). doi:10.1007/s10654-011-9581-6. Wooten GF, Currie LJ, Bovbjerg VE, Lee JK, Patrie J. 2004. Are men at greater risk for Parkinson’s disease than women? J Neurol Neurosurg Psychiatry. 75(4):637–639. doi:10.1136/jnnp.2003.020982. World Health Organization & International Programme on Chemical Safety. 1989. Aldrin and dieldrin: health and safety guide. World Health Organization. https://apps.who.int/iris/handle/10665/39358 Xilouri M, Brekk OR, Stefanis L. 2013. α-Synuclein and protein degradation systems: a reciprocal relationship. Mol Neurobiol. 47(2):537–551. doi:10.1007/s12035-012-8341-2. Yavich L, Tanila H, Vepsäläinen S, Jäkälä P. 2004. Role of α-synuclein in presynaptic dopamine recruitment. J Neurosci. 24(49):11165–11170. doi:10.1523/JNEUROSCI.2559-04.2004. Yorgason JT, España RA, Jones SR. 2011. Demon Voltammetry and Analysis software: Analysis of cocaine-induced alterations in dopamine signaling using multiple kinetic measures. J Neurosci Methods. 202(2):158–164. doi:10.1016/j.jneumeth.2011.03.001. Zhang WQ, Tilson HA, Nanry KP, Hudson PM, Hong JS, Stachowiak MK. 1988. Increased dopamine release from striata of rats after unilateral nigrostriatal bundle damage. Brain Res. 461:335–342. doi:10.1016/0006-8993(88)90264-8. Zigmond M, Abercrombie E, Berger T, Grace A, Stricker E. 1993. Compensatory responses to partial loss of dopaminergic neurons: Studies with 6-hydroxydopamine. Current Concepts in Parkinson’s Disease Research.:99–140. doi:10.1007/BF03159728. Zigmond M, Castro S, Keefe K, Abercrombie E, Sved A. 1998. Role of excitatory amino acids in the regulation of dopamine synthesis and release in the neostriatum. Amino Acids. 14(1–3):57–62. doi:10.1007/BF01345243. Zigmond M. 1994. Chemical transmission in the brain: homeostatic regulation and its functional implications Homeostasis of neuronal function. Prog Brain Res. 100:115–122. doi:10.1016/s0079-6123(08)60776-1. 138 Zigmond M. 1997. Do Compensatory Processes Underlie the Preclinical Phase of Neurodegenerative Disease? Insights from an Animal Model of Parkinsonism. Neurobiol Dis. 4(3–4):247–253. doi:10.1006/nbdi.1997.0157. Zigmond M, Acheson AL, Stachowiak MK, Strickerm EM. 1984. Neurochemical Compensation After Nigrostriatal Bundle Injury in an Animal Model of Preclinical Parkinsonism. Arch Neurol. 41(8):856–861. doi:10.1001/archneur.1984.04050190062015. 139 Chapter 3: α-synuclein preformed fibrils do not seed aggregation or induce toxicity in LUHMES or SH-SY5Y 3D neurospheres 140 Abstract Recently, 3D neurosphere models have emerged as an important new approach methodology (NAM) for neurotoxicity testing, disease modeling, and drug screening because these show improved differentiation and survival compared to many 2D adherent systems. Here, we aimed to use α-synuclein (α-syn) preformed fibrils (PFFs) in Lund Human Mesencephalic (LUHMES) and SH-SY5Y 3D neurospheres to model synucleinopathy-induced toxicity in vitro and assess if neurotoxicants or specific target genes alter this toxicity. Previously, α-syn PFFs were used to induce synucleinopathy in vivo in mice and rats, as well as in in vitro models including rodent primary neurons and adherent human SH-SY5Y cells, as Parkinson's disease models. However, this model has not yet been adapted for use in 3D in vitro models. We confirmed that after differentiation, both SH-SY5Y and LUHMES neurospheres express the DAergic and neuronal markers tyrosine hydroxylase (TH), vesicular monoamine transporter 2 (VMAT2), and α-syn, but only LUHMES neurospheres express dopamine transporter (DAT) at measurable levels. Consistent with this, LUHMES, but not SH-SY5Y, neurospheres were susceptible to (MPP+) toxicity assessed by ATP and neurite outgrowth assays, as DAT is required for methyl-4-phenylpyridinium (MPP+) uptake into cells. While treatment of both LUHMES and SH-SY5Y neurospheres with human α-syn PFFs at concentrations ranging from 0.5 μg/ml to 2 μg/ml led to a concentration- dependent increase in detergent-insoluble α-syn, no toxicity was observed. Uptake of PFFs into cells requires specific proteins at the synaptic terminals, thus, we suspect that these neurospheres do not have well-developed synapses and lack the machinery to take up PFFs and seed aggregation of endogenous α-syn and/or that levels of α-syn in 141 neurites is too low to allow efficient seeding. Our observation of concentration- dependent increases in detergent-insoluble α-syn may be due to the accumulation of PFF aggregates on the cell surface. Together, our data shows that α-syn PFFs do not seed aggregation of endogenous α-syn or induce toxicity in LUHMES and SH-SY5Y neurospheres. Introduction While animal models traditionally provide the most physiologically relevant system to model disease, in vivo experiments have several limitations. They can be time- consuming, expensive, and resource-intensive, require large numbers of animals, have high variability, and lack translation from animal models to humans (Bal-Price 2018). New approach methodologies (NAMs) are methods designed to replace animal testing in assessing chemical or drug toxicity and offer advantages for neurotoxicity testing, disease modeling, and drug screening (Hogberg et al. 2013; Anderson et al. 2021). Multiple NAMs were developed to screen chemicals for developmental neurotoxicity (DNT) and additional methods in this area are needed as an efficient and translatable approach to assess DNT (Bal-Price 2018). The ability to use cells of human origin is a major advantage of NAMs and may be more translatable in modeling human disease and toxicity than in vivo rodent models. More than 90% of compounds in clinical trials for drug development fail because of effects that were not observed during in vivo testing, partly due to species differences (Hogberg et al. 2013). Human-derived cells can be used for in vitro NAMs at increasing levels of complexity, ranging from adherent cells to organoids. Here, we utilized 3D neurospheres derived from Lund Human Mesencephalic (LUHMES) cells and SH-SY5Y cells because of the well-documented protocols for differentiation into DAergic-like cells. 142 LUHMES cells are derived from 8-week-old female human embryonic mesencephalic, can be differentiated into morphologically and biochemically mature dopamine-like neurons, and are increasingly used for in vitro research (Lotharius et al. 2002; Lotharius et al. 2005; Scholz et al. 2011a; Pöltl et al. 2012; Schildknecht et al. 2013; Krug et al. 2014; X.M. Zhang et al. 2014a; Efremova et al. 2015; Hirsch et al. 2015; Oliveira et al. 2015; L. Smirnova et al. 2016; Tong et al. 2017a). 3D LUHMES neurospheres were developed as a high-throughput toxicity screening platform to take advantage of the fact that 3D cell models show better differentiation and survival than 2D LUHMES cultures (L Smirnova et al. 2016; Harris et al. 2017a; Tong et al. 2017a) After differentiation into 3D neurospheres, these cells express TH, DAT, VMAT2 and α-syn (Scholz et al. 2011b; L. Smirnova et al. 2016; Harris et al. 2017b; Lauter et al. 2020; Tüshaus et al. 2020). This cell model is well established and demonstrates robust performance in high-throughput neurotoxicity studies, including studies of rotenone, another neurotoxicant relevant to PD (Scholz et al. 2011c; Scholz et al. 2011b; X. Zhang et al. 2014; X.M. Zhang et al. 2014b; L. Smirnova et al. 2016; Harris et al. 2017b; Harris et al. 2018; Leite et al. 2019; Ko et al. 2020; Tong et al. 2020; Tüshaus et al. 2020; Yamaguchi et al. 2020; Leah et al. 2021; Nicolai et al. 2022; Tong et al. 2022; Ali et al. 2023; Capinha et al. 2023). SH-SY5Y cells are a sub-cell line of SK-N-SH cells, which are derived from a neuroblastoma from a 4-year-old female (Xicoy et al., 2017). Early characterization of SH-SY5Y cells showed that the cells may have a catecholaminergic phenotype displaying enzymatic activity for both dopamine (DA) and norepinephrine such as tyrosine hydroxylase (TH), dopamine-β-hydroxylase, acetylcholinesterase, and choline acetyltransferase (Xicoy et al. 2017) Shipley et al. has developed methods to induce 143 differentiation in SH-SY5Y cells with retinoic acid and specific growth factors to form a DAergic-like phenotype (Shipley et al. 2016). Previous work has reported growing SH- SY5Y on protein scaffolds and for shorter durations of time, which likely alter the differentiation trajectory of the neurospheres (Song et al. 2012; Innala et al. 2014; Wang et al. 2014; Ito et al. 2017; Marrazzo et al. 2019; Bastiaens et al. 2020; Limboonreung et al. 2020; Lin et al. 2020; Fiore et al. 2022; Welch and Tsai 2022). However, to our knowledge 3D SH-SY5Y neurospheres have not been previously formed in suspension like the LUHMES cell protocol utilized here. Therefore, we have adapted existing differentiation methods to culturing SH-SY5Y neurospheres in suspension and characterized the DAergic-like phenotype for our model of SH-SY5Y neurospheres. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a canonical DAergic toxicant used for in vivo PD research due to its ability to induce robust and specific DAergic degeneration (Crossman et al. 1987; Janson et al. 1992; Bezard et al. 1997; Freyaldenhoven et al. 1997; Grünblatt et al. 2000; Mandavilli et al. 2000; Speciale 2002; Meissner et al. 2003; Schildknecht et al. 2017; Huang et al. 2018). In vivo, MPTP is taken up into astrocytes and metabolized by MAO to form the active metabolite, 1- methyl-4-phenylpyridinium (MPP+), which then enters DAergic neurons via DAT. Inside neurons, MPP+ is a potent inhibitor of complex 1 of the electron transport chain. For in vitro models, the active metabolite, MPP+ is often used because neuronal cultures lacking astrocytes are unable to convert MPTP to MPP+ (Richardson et al. 2007; Jagmag et al. 2016). The MPP+ model of DAergic degeneration was well established and utilized in a wide range of cell lines and primary neuronal cultures from mice and rats (Song et al. 2012; 144 Geng et al. 2017; Ito et al. 2017; Ko et al. 2020; Limboonreung et al. 2020; Beliakov et al. 2023a; Beliakov et al. 2023b). Treating 2D adherent or 3D LUHMES neurospheres with MPP+ results in a concentration-dependent decrease in cell viability and mitochondrial membrane potential (L. Smirnova et al. 2016; Tong et al. 2017b; Ko et al. 2020; Beliakov et al. 2023a). A large number of papers report using the MPP+ model in SH-SY5Y cells grown in a variety of conditions, with varying levels of toxicity dependent on growth and differentiation conditions (Nicotra and Parvez 2002; Song et al. 2012; Wang et al. 2014; Ito et al. 2017; Ko et al. 2020; Limboonreung et al. 2020; Ioghen et al. 2023). The MPTP/MPP+ model is well-established and frequently used in PD research. While it does not replicate all aspects of the disease, it remains a useful tool for studying the susceptibility of DAergic neurons. Despite this, it remains a useful tool for studying the susceptibility of DAergic neurons. To model Lewy-like aggregation and the protracted course of DAergic degeneration, the α-syn PFF model was established in vivo and successfully recapitulated in iPSCs and primary rodent neurons (Luk et al. 2009; Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014; Gao et al. 2019a; Ross et al. 2020a). In this model, PFFs produced from recombinant α-syn template endogenous α-syn form protease-resistant, detergent- insoluble, ubiquitinated, and hyperphosphorylated inclusions and eventually lead to cell death (Luk et al., 2009; Volpicelli-Daley et al., 2011, 2014). Many aspects of the in vivo model can be recapitulated in vitro, including the formation of phosphorylated inclusions, mitochondrial dysfunction, oxidative stress, deficits in neuronal excitability, increased autophagy, loss of synaptic markers, and eventual degeneration of neurons (Luk et al. 2009; Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014; Ross et al. 145 2020a). Initial work in primary hippocampal neurons, chosen because of their high levels of α-syn, showed that phosphorylated inclusions are present 4 days after application of PFFs and compact puncta form by 7 days. By 14 days post-treatment, 20- 30% of treated primary hippocampal neurons degenerate, showing mitochondrial oxidant stress, deficits in neuronal excitability, increased autophagy, and loss of synaptic markers (Volpicelli-Daley et al. 2011; Volpicelli-Daley et al. 2014). Some work has extended the PFF model in 2D SH-SY5Y cells to study aggregate clearance pathways and mitochondrial dysfunction associated with PFF-induced aggregation (Perfeito et al. 2014; Choi et al. 2018; Gao et al. 2019b; Ross et al. 2020b; Pantazopoulou et al. 2021; Feng et al. 2022; Lin et al. 2022). While the α-syn PFF model has successfully been used in multiple in vitro systems, it has not yet been used in LUHMES cells or any 3D neurosphere model. Therefore, in this study, we aimed to adapt the PFF model to 3D LUHMES and SH-SY5Y neurospheres to take advantage of advances in the development of NAMs. Here, we demonstrate that LUHMES, but not SH-SY5Y neurospheres are susceptible to MPP+- induced cell loss as measured by ATP and neurite outgrowth assays, consistent with the observed lack of DAT expression in SH-SY5Y neurospheres. We also show a concentration-dependent PFF-induced increase in detergent-insoluble α-syn in both LUHMES and SH-SY5Y neurosphere cultures, but no effect on cell viability. Based on these findings, we suspect that the synapses in these neurospheres may not form the proper synaptic connections and/or do not have enough endogenous levels of α-syn to template α-syn PFFs to form aggregates. Overall, our data show that neither LUHMES 146 nor SH-SY5Y neurospheres are not susceptible to α-syn PFF-induced aggregation or toxicity. Figure 3.1. Differentiation timeline for LUHMES and SH-SY5Y cells. A) Timeline for LUHMES experiments. On day 0, spheroid formation and media are replaced from proliferation to differentiation media. MPP+ treatment is added on day 14, ATP assay on day 16, and neurite outgrowth assays on day 17. α-syn PFFs are added on Day 8, ATP assays on day 16, and samples to confirm PFF seeding via western blots are collected on days 10, 16, and 18. B) Timeline for SH-SY5Y cells. On day 0, basic growth media is replaced for differentiation media 1. On Day 8, differentiation media 1 is exchanged for differentiation media 2 when spheroid formation begins. On day 11, differentiation media 2 is replaced with differentiation media 3. α-syn PFFs are added on Day 9, ATP assays on day 17, and samples to confirm PFF seeding via western blots are collected on days 11, 17, and 19. For both LUHMES and SH-SY5Y, samples were collected throughout the differentiation time course for DAergic characterization using ddPCR, immunocytochemistry, and western blots. Made in BioRender. 147 Methods LUHMES Cell Culture LUHMES cells (ATCC CRL-2927, RRID: CVCL_B056) were grown as previously described with modifications to the differentiation media supplements. (L. Smirnova et al. 2016; Harris et al. 2017b; Tong et al. 2017b; Harris et al. 2018; Leite et al. 2019) For proliferation, cells were grown in flasks coated with 50 μg/ml Poly-L-ornithine and 1 μg/ml Fibronectin. Proliferation Media was completely exchanged every other day, and cells were passaged every 3-4 days (Table 1). For differentiation, cells were trypsinized with TrypLE Express (Gibco) and seeded at 2.25 x 106 cells/ml in cell-repellent 6-well plates (Corning) in 2 ml/well Differentiation Media and this was designated Differentiation Day 0 (Harischandra et al., 2020) (Table 2). The 6-well plates were placed on an orbital shaker at 90 rpm in an incubator (37°, 5% CO2) for the remainder of the experiment. Two days after seeding the 6-well plates (Differentiation Day 2), 1 ml of media was exchanged for 1 ml of Differentiation Media with 20 nM Taxol (Sigma-Aldrich) to inhibit proliferation. Two days after Taxol treatment (Differentiation Day 4), 1.8 ml of media was removed from each well and replaced with 2 ml of differentiation media to wash out Taxol. After the Taxol washout, half media changes were completed every other day for the remainder of the experiment as previously described (L. Smirnova et al. 2016; Harris et al. 2017b; Tong et al. 2017b; Harris et al. 2018; Leite et al. 2019) 148 Table 3.1. LUHMES Proliferation Media Table 3.2. LUHMES Differentiation Media 149 SH-SY5Y Cell Culture Table 3.3. SH-SY5Y Basic Growth Media Table 3.4. SH-SY5Y Differentiation Media 1 150 Table 3.5. SH-SY5Y Differentiation Media 2 Table 3.6. SH-SY5Y Differentiation Media 3 151 SH-SY5Y cells (ATCC CRL-2266, RRID: CVCL_0019) were grown in uncoated flasks while proliferating in Basic Growth Media as previously described (Shipley et al. 2016) (Table 3). Once the cells were 80% confluent, the media was completely exchanged to Differentiation Media 1 Differentiation Day 0 (Table 4). On Differentiation Day 8, the cells were trypsinized using Trypsin-EDTA 0.05% (Gibco) and plated in 6-well at 2.50 x106 cells/ml in cell-repellent 6-well plates (Corning) at 2 ml/well in Differentiation Media 1 (Table 4). The 6-well plates were placed on an orbital shaker at 90 rpm in an incubator (37°, 5% CO2) for the remainder of the experiment. One day after seeding, the 6-well plates (Differentiation Day 9), and 2 ml of Differentiation Media 2 were added to the wells (Table 5). On Differentiation Day 10, 3 ml of media was removed and replaced with 1 ml of Differentiation Media 2 (Table 2). On Differentiation Day 14, 1 ml of media was exchanged for 1 ml of Differentiation Media 3 (Table 5). Half of the media was exchanged with Differentiation Media 3 every two days for the remainder of the experiment. MPP+ Treatment MPP+ was resuspended in PBS at a stock concentration of 10 mM in PBS. On the day of treatment, MPP+ was diluted in media to make 2x the final concentration, and 1 ml of media was removed from each well of the 6-well plate and replaced with 1 ml of 2x media with MPP+. Each well was treated with concentrations ranging from 0.001 - 200 µM of MPP+. At 48 hours post-treatment, 8 spheroids from each 6-well were transferred to Matrigel-coated plates (1 spheroid per well) for neurite outgrowth assays and the remaining spheroids in each MPP+ treated well were used for ATP assays. 152 Preparation of α-synuclein PFFs and fibril size verification Recombinant human α-syn PFFs were provided by the Luk lab, stored at -80°C, and prepared via a Q500 Sonicator with a cup-horn assembly and chiller (Qsonica) as previously described (Luk et al. 2012; Volpicelli-Daley et al. 2014; Patterson et al. 2019). To determine the average fibril length, transmission electron microscopy (TEM) was completed as previously described (Patterson et al. 2019). To briefly describe this process, PFF samples were prepared on Formvar/carbon-coated copper grids (EMSDIASUM, FCF300-Cu). Grids were imaged with a JEOL JEM-1400+ TEM. TEM images were analyzed for fibril length in ImageJ (Schneider et al. 2012). 500 fibrils were measured to determine the average fibril length of 38.94 nm +/- 11.65 nm. Figure 3.2. Verification of α-synuclein PFF size. A) PFF length distribution determined via TEM. Each point represents a measured fibril length, the error bars denote standard deviation. B) Representative TEM image of sonicated fibrils. C) Frequency distribution of PFF lengths post-sonication. 153 PFF Treatment Human α-syn PFFs (0.5 μg/ml to 2.0 μg/ml) diluted in PBS were added to 1 ml of media and added to neurosphere cultures on Differentiation Day 8 for LUHMES and SH-SY5Y. 48-hour post-treatment, 1 ml of media was removed and replaced with fresh media. Half media changes were conducted every 48 hours. RNA Isolation, Reverse Transcription, and droplet digital PCR All spheroids from one well of a 6-well plate were collected using a wide bore pipette tip at indicated time points, spun at 500xg for 5 minutes, the media was aspirated. To rinse, cell pellets were resuspended in PBS and spun again at 500xg for 5 minutes. The PBS was aspirated, and the rinsed cells were frozen as pellets stored at -80°C until RNA extraction (Figure 1). RNA was isolated from frozen cell pellets resuspended in QIAzol (Qiagen) using a Quick-RNA MiniPrep Kit as directed (Zymo Research). RNA integrity and concentration were measured via NanoDrop UV-Vis spectrophotometer (ThermoScientific). For quality control, 260/280 absorbance ratios for all samples were in the 1.8-2.2 range. Purified RNA was loaded in equal amounts of 1,000 ng and reverse transcribed via iScript MasterMix (BioRad) to form cDNA. cDNA was diluted 1:10 for a final RNA amount of 100ng and analyzed via droplet digital PCR to assess expression of TH (Hs00165941_m1), SLC6A3 (Hs00997374_m1), SLC18A2 (Hs00996835_m1), SNCAIP (H200914722_m1), and MK167 (HS04260396_m1) using ddPCR Mastermix (BioRad) and TaqMan Gene Expression Assays (ThermoFisher). Samples were partitioned with a BioRad QX200 droplet generator and amplified and analyzed using a BioRad QX200 154 droplet reader. All TaqMan assays were completed with at least 3 biological replicates from independent experiments. Sequential protein expression for insoluble α-synuclein western blotting To confirm insoluble α-synuclein in PFF-treated neurospheres, spheroids from each well of the 6-well plate were collected, processed, and frozen as stated for RNA extraction at 2, 5, and 10 days post-treatment. Cell pellets were thawed on ice and resuspended with 1% Triton in Tris Buffered Saline (TBS) and protease inhibitors, then sonicated for 2 pulses, 30% amplitude with a probe sonicator. Lysates were spun at 100,000xg at 4°C for 30 minutes. The supernatant was collected as the soluble fraction. The pellet was sonicated in 2% sodium dodecyl sulfate (SDS) in TBS and collected as the insoluble fraction. Protein levels for the soluble and insoluble fractions were quantified by BCA protein assay (Volpicelli-Daley et al. 2014). Immunocytochemistry Neurospheres were transferred to Netwell inserts and fixed with 4% PFA for 30 minutes. Non-specific staining was blocked with 5% normal goat serum (NGS), 1% bovine serum albumin, and 0.1% Triton for 1 hour. Fixed neurospheres were incubated overnight in the appropriate primary antibodies in TBS with 1% NGS/0.1% Triton X-100 followed by appropriate secondary antibodies for 2 hours. Spheroids were stained with DAPI for 10 minutes following secondary incubation. Slides were cover-slipped with VECTASHIELD Vibrance Antifade Mounting Medium (VectaLabs). Stained neurospheres were imaged on a Lionheart Fx Automated Microscope (BioTek). 155 Table 3.7. Antibodies used for Immunohistochemistry Collection of cell lysates and western blotting Cell pellets were resuspended in RIPA buffer with protease inhibitors and homogenized with a pestle. Lysates were spun at 1,000 xg for 5 minutes, and the supernatant was collected as the lysate for western blotting. 18 μg of protein for soluble and insoluble α-syn western blots were loaded onto AnyKD Criterion midi gel (BioRad) gels. 20 μg of protein for lysates for TH, DAT, and VMAT2 were loaded onto Novex 10% Bis-Tris gels (Invitrogen). Proteins were electrophoretically transferred to nitrocellulose membranes (BioRad). For α-syn blots only, membranes were fixed in 0.4% paraformaldehyde for 30 minutes immediately after transfer. Membranes were stained with Revert 700 Total-Protein Stain (LI-COR) for 5 minutes and imaged with a LI-COR Odyssey CLx. Membranes were blocked with Odyssey blocking Buffer (LI-COR), and incubated in either α-syn (Invitrogen), Tyrosine hydroxylase (Millipore), DAT (Sigma), or VMAT2 primary antibodies overnight at 4°C. After washing, membranes were incubated in goat anti-Rb 800CW (LI-COR) for 2 hours and imaged with a LI-COR Odyssey CLx. 156 Table 3.8. Antibodies used for Western Blotting ATP Assays For ATP assays, 1 ml of media from each well of the 6-well neurosphere plate was removed and replaced with 1 ml of Cell Titer-Glo 3D reagent (Promega). Neurospheres were lysed by shaking the plates at 700 rpm for 20 minutes at room temperature in a Thermomixer (Eppendorf). To avoid cellular debris, the supernatant was transferred to a white 96-well assay plate in triplicate (Corning). ATP standards were diluted in media and pipetted in triplicate in the white 96-well assay plate. The plate was incubated for 10 minutes in the dark and luminescence was read using a Synergy H1 plate reader at an integration time of 1.5 seconds and a reading height of 7.00 mm (BioTek). Blanks were subtracted and samples were calibrated to the ATP standard to calculate ATP concentration (µM). All ATP cytotoxicity assays were completed with at least 3 biological replicates from independent experiments, with 4 technical replicates per experiment. Neurite Outgrowth Assays 48 hours before neurite analysis, black 96-well optical bottom plates (Corning) were coated with growth factor reduced Matrigel® Growth Factor Reduced (GFR) Basement Membrane Matrix (Corning) diluted 1:24 in DMEM/F12 and placed in an incubator to polymerize overnight. Following polymerization, Matrigel was aspirated and replaced 157 with either LUHMES Differentiation Media made with phenol-free DMEM/F12 (Gibco) or SH-SY5Y Differentiation Media 3 made with phenol-free Neurobasal (Gibco). Individual spheroids were transferred to single wells in the Matrigel-coated plate. 24 hours after plating, neurites were stained with a neurite outgrowth staining kit (ThermoFisher) for 30 minutes as directed. At the end of incubation, half of the solution was replaced with a 3x Background Suppression Dye. Neurospheres were imaged with a Lionheart Fx Automated Microscope at 4x using a GFP filter cube (BioTek). Images were then analyzed in Gen5 software. Briefly, a primary mask around the spheroid body is generated by thresholding and a secondary mask is generated by thresholding without a ring around the spheroid body (Figure 3). The ratio of the areas of the secondary mask to the primary mask provides a measure of neurite outgrowth. Each well was manually checked for the following exclusion criteria: wells containing multiple spheroids, spheroids touching the edge of the well, or spheroid or neurites no longer attached to the plate. For each treatment condition, 8 neurospheres were individually transferred to a 96-well plate to ensure at least 4 technical replicates per concentration were included after the exclusion, and 3 biological replicates were used from independent experiments for all neurite outgrowth assays. Figure 3.3. Representative neurite outgrowth analysis. Scale bar represents 1000 µM. 158 Statistical analysis Independent, biological replicates are defined as cells from separate independent thaws and differentiation of LUHMES cells. At least three biological replicates were used for every endpoint. Technical replicates were defined as follows for each outcome measure. After lysis for the ATP assay, the lysate is pipetted in triplicate into the white 96-well assay plate for 3 technical replicates for every biological replicate. For the neurite outgrowth assay, 8 neurospheres were transferred from each well (concentration of MPP+) of the 6-well plate to a Matrigel-coated 96-well plate. After the exclusion mentioned in the above section, at least 4 neurospheres per concentration were used as technical replicates for every biological replicate. For both assays, technical replicates were averaged and normalized to untreated control. Normalized data for all independent biological replicates was then averaged. Nonlinear regression curve fitting was used in GraphPad Prism. 159 Results Figure 3.4. LUHMES neurospheres express DAergic markers after differentiation. A) mRNA expression for TH, DAT, VMAT2, α-synuclein, and Ki67 at days Differentiation Days 0, 5, 8, 13, 16, and 19 B) Representative Immunocytochemistry for DAPI (blue), TH (green) and merge images of neurospheres at differentiation days 14 (top) and 19 (bottom) C) Representative Immunocytochemistry for DAPI (blue), α-synuclein (green), and merge images at days 14 (top) and 19 (bottom). D) Representative western blots for TH, DAT, and VMAT2 at Differentiation days 0, 10, 15, and 18. C) Representative western blots for TH, DAT and VMAT2 at Differentiation Day12. Graphs show mean ± SD for 3 independent experiments. 160 Figure 3.5. SH-SY5Y neurospheres express some DAergic markers after differentiation. A) mRNA expression for TH, DAT, VMAT2, α-synuclein, and Ki67 at days Differentiation Day 0, 5, 8, 13, 16, and 19 B) Representative Immunocytochemistry for DAPI (blue), TH (green) and merge images of neurospheres at Differentiation Day 14 and 19 (top) C) Representative Immunocytochemistry for DAPI (blue), α-synuclein (green), and merge images at days 14 (top) and 19 (bottom). Graphs show mean ± SD for 3 independent experiments. 161 Confirmation of DAergic differentiation in LUHMES neurospheres To confirm that differentiated LUHMES neurospheres develop a DAergic-like phenotype, we assessed mRNA and protein levels of DAergic markers (TH, DAT, and VMAT2), α- syn, and the proliferation marker Ki67. Neurospheres were collected throughout the differentiation time course for ddPCR analysis of mRNA levels. LUHMES neurospheres had detectable levels of TH, DAT, and VMAT2, during differentiation (Figure 4A). Following Taxol treatment, Ki67 mRNA levels were non-detectable in LUHMES neurospheres (Figure 4A). Raw values for ddPCR are shown in table 9. To confirm protein expression of DAergic markers, LUHMES neurospheres were stained for α-syn and TH at Differentiation Day 14 and 19, and expression of both proteins was confirmed (Figure 4B). Expression of TH, DAT, and VMAT2 protein was confirmed at Differentiation Day 12 by western blot (Figure 4C). Table 3.9. ddPCR values for LUHMES Cells (Average Copies per 20µl) 162 Confirmation of DAergic Differentiation in SH-SY5Y Neurospheres To confirm that differentiated SH-SY5Y neurospheres develop a DAergic-like phenotype, we also assessed these cells for mRNA and protein expression of the same markers. SH-SY5Y neurospheres showed detectable mRNA expression for TH, VMAT2, and α-syn throughout differentiation (Figure 5A). However, there were no detectable levels of DAT at any timepoint in SH-SY5Y cells (Figure 5A). SH-SY5Y neurospheres express the proliferation marker of Ki67 throughout differentiation (Figure 5A). Raw values for ddPCR is shown in table 10. Protein expression for TH and α-syn was verified with immunocytochemistry at Differentiation Days 14 and 19 (Figure 5B). Table 3.10. ddPCR Values for SH-SY5Y Cells (Average Copies per 20µl) MPP+ induces toxicity in LUHMES, but not SH-SY5Y, neurospheres LUHMES neurospheres were treated with various concentrations of MPP+, the active metabolite of MPTP at Differentiation Day 13, a timepoint where DAT is expressed. Toxicity was measured with ATP assays 48 hours post MPP+ treatment, showing a concentration-dependent decrease in ATP content in LUHMES neurospheres (IC50=17.08μM) (Figure 6A). MPP+-induced toxicity was also measured in neurite 163 outgrowth assays, which showed a concentration-dependent decrease in normalized neurite outgrowth (IC50=54.90μM) (Figure 6B-C). Consistent with a lack of DAT expression, SH-SY5Y neurospheres were not susceptible to MPP+ treatment across the same concentrations applied to LUHMES cells or up to 1 mM MPP+ (data not shown). Figure 3.6. MPP+ concentration-response curves generated from ATP and neurite outgrowth assays in LUHMES neurospheres. (A) and neurite outgrowth assays (B- C) confirm expected susceptibility of 3D LUHMES neurospheres to MPP+. A) ATP assay. B) Neurite outgrowth assay C) Representative neurite outgrowth images in MPP+ treated LUHMES neurospheres. Graphs show mean ± SD for 3 independent experiments. Increase in detergent-insoluble α-syn after application of α-syn PFFs Next, α-syn PFFs were added to neurospheres at Differentiation Day 9. This time point was selected because the cells express α-syn and expression of endogenous α-syn protein is required for PFF-induced seeding. Samples were collected at three-time 164 points post-PFF treatment and analyzed for Triton-soluble and insoluble α-syn. One of the features of α-syn aggregates is that they are insoluble in Triton X-100 detergent. As expected, there was a concentration-dependent increase in Triton-insoluble α-syn protein in both LUHMES and SH-SY5Y neurospheres at each timepoint post-treatment (2, 5, and 10 days) (Figure 7). However, it appears that there is a decrease in Triton- soluble α-syn was also detected in all samples. Figure 3.7. α-synuclein PFF treatment induces a concentration-dependent increase in Triton-insoluble α-synuclein in both LUHMES and SH-SY5Y neurospheres. Representative western blots for Triton soluble and insoluble α- synuclein Differentiation Days 10, 15, and 18 (2,7, and 10 days post-PFF treatment respectively) in A) LUHMES and B) SH-SY5Y neurospheres. Assessment of α-Synuclein PFF-induced toxicity To determine if α-syn PFF treatment is toxic in 3D LUHMES and SH-SY5Y neurospheres, we collected samples for ATP assays at Differentiation Day 18 (20 days after treatment). However, there were no significant effects of α-syn PFFs on ATP concentrations in either cell line at concentrations that induced Triton-insoluble α-syn formation in either LUHMES or SH-SY5Y neurospheres (Figure 8). 165 Figure 3.8. α-synuclein PFF treatment does not induce toxicity in LUHMES or SH- SY5Y neurospheres. ATP concentration at Differentiation Day 18 (10 days post-PFF treatment) in A) LUHMES and B) SH-SY5Y neurospheres. Data is shown as percent of control. Graphs show mean ± SD for 3 independent experiments. Discussion α-synuclein-PFFs may increase detergent insoluble α-synuclein but do not induce toxicity The goal of this project was to adapt the α-syn PFF model to 3D DAergic neurospheres. However, while we observed an initial increase in detergent-insoluble α-syn, seeding does not appear to have occurred and there is no toxicity associated with PFF treatment in either LUHMES and SH-SY5Y neurospheres (Figures 7 and 8). In this model, we did not observe any effects of PFFs on ATP concentration in either cell line at concentrations where we saw insoluble α-syn (Figure 7). We suspect that this is because α-syn PFFs did not seed the formation of aggregates of endogenous α-syn intracellularly for multiple possible reasons. First, we may be detecting insoluble α-syn binding to the membrane of cells rather than internalized aggregates. Second, PFFs may be internalized, but levels of endogenous α-syn in neurites are too low to allow efficient seeding; the expression level of endogenous α-syn is known to be a critical factor for successful seeding. To model synucleinopathy in these cells, future studies could potentially utilize cells 166 overexpressing α-syn. However, the supraphysiological α-syn in overexpression levels has the potential to result in non-PD related pathophysiological effects, potentially reducing the translatability of this model (Duffy et al. 2018). Third, because PFF uptake into cells requires specific proteins at the synaptic terminals, these neurospheres may not have well-developed synapses and lack the machinery to take up PFFs to seed aggregation of endogenous α-syn. Unfortunately, while it is possible to assess if the PFFs were properly internalized in the neurospheres using fluorescently tagged PFFs to visualize and confirm PFF uptake, this is technically beyond the scope of this project (Karpowicz et al. 2017; Valdinocci et al. 2017). To maintain host compatibility, another critical component of successful seeding by PFFs, we used human PFFs in human cells, which also makes it difficult to differentiate endogenous from exogenous α-syn (Luk et al. 2016). The use of PFFs generated from another species could enable the differentiation of endogenous from exogenous α-syn, but seeding efficiency would have likely been greatly reduced. Together, our data suggests that adapting the α-syn PFF model to 3D LUHMES or SH-SY5Y neurospheres faces significant technical challenges and may require additional manipulations that would also reduce its translational potential. 3D LUHMES neurospheres as a model for assessing DAergic toxicity Here, we used protocols adapted from previous work to enhance the differentiation of LUHMES neurospheres. We replicated and extended the characterization of the DAergic-like phenotype in 3D LUHMES neurospheres by measuring RNA and protein expression of key DAergic markers (TH, DAT, and VMAT2) up to Differentiation Day 19 (Shipley et al. 2016; L. Smirnova et al. 2016; Harris et al. 2017b; Harischandra et al. 167 2020)(Figure 4). Previous work did not characterize the DAergic phenotype of 3D LUHMES in longer-term cultures such as day 19, which is essential when using long- term models such as the PFF model. In LUHMES neurospheres, TH and DAT RNA levels peak early in differentiation and decrease over time. However, western blot analysis shows that TH and DAT protein levels are still detectable at Differentiation Day 12 and ICC shows TH expression at Differentiation Day 19 (Figure 4C). In addition, the susceptibility of these cells to MPP+ at Differentiation Day 13 confirms that DAT protein is expressed at this time point (Figure 6). This discrepancy between RNA and protein levels is consistent with the established feedback loops between DA levels and expression of TH and DAT through mechanisms including D2 autoreceptors activation and feedback inhibition by DA itself (Sulzer et al. 2010; Daubner et al. 2011; Chen et al. 2020). As expected, Ki67 RNA levels were undetectable after Taxol treatment indicating that these neurospheres are no longer proliferating, consistent with a mature neuronal phenotype. Expanding on previous characterizations, we demonstrated that these cells also express α-syn RNA and protein, further supporting their utility in studying mechanisms relevant to PD (Figure 4). Together, this data adds to the growing body of evidence supporting the use of 3D LUHMES neurospheres for studies of DAergic toxicity. The relevance of SH-SY5Y cells is highly dependent on growth and differentiation conditions In contrast to the LUHMES cells, 3D SH-SY5Y neurospheres differentiated in suspension do not express DAT and are not susceptible to the DAergic toxicant MPP+ (Figure 5A). They are also not post-mitotic and continue to divide, as demonstrated by 168 sustained Ki67 expression and increasing size from Differentiation Day 14 to 19 (Figure 5A). Other groups have reported inconsistent expression of DAT in SH-SY5Y cells (Presgraves et al. 2004; Song et al. 2012; Wang et al. 2014; Geng et al. 2017; Ito et al. 2017; Ko et al. 2020; Limboonreung et al. 2020) (Figure 5). Together, this suggests that 3D SH-SY5Y neurospheres differentiated with this protocol may not be a useful model of DA neurons. Consistent with DAT expression in LUHMES cells but not SH-SY5Y cells, we showed that LUHMES, but not SH-SY5Y neurospheres, are susceptible to MPP+-induced toxicity (Figure 5). Because DAT is required for MPP+ entry, and our SH-SY5Y neurospheres do not express DAT mRNA at any time point with this differentiation protocol, it is likely that MPP+ is not taken up into these cells (Figure 5). Other groups have demonstrated MPP+ toxicity in SH-SY5Y cells using different differentiation and growth conditions with MPP+ concentrations ranging from 2mM to 5mM. Adherent SH- SY5Y cells grown in 2D are susceptible to MPP+ using assays for mitochondrial function, apoptosis, and ATP concentration (Presgraves et al. 2004; Song et al. 2012; Wang et al. 2014; Geng et al. 2017; Limboonreung et al. 2020). 3D SH-SY5Y neurospheres grown in Matrigel rather than in suspension have also been shown to be susceptible to high concentrations of MPP+, although the media and differentiation conditions used were different than the conditions used here (Ko et al. 2020). In addition, DAT expression appears to be variable between differentiation protocols, 2D vs 3D models, and research groups which likely contributes to the inconsistencies in susceptibility to MPP+ (Presgraves et al. 2004; Song et al. 2012; Wang et al. 2014; Geng et al. 2017; Ito et al. 2017; Ko et al. 2020; Limboonreung et al. 2020) 169 Here, we used a stepwise decrease in FBS, and additional media supplements intended to improve the differentiation of SH-SY5Y cells (Neurobasal growth media, B27 supplement, and cAMP). Lastly, the differentiation protocol reported here for SH-SY5Y neurospheres includes an 18-day retinoic acid differentiation protocol rather than a 9- day retinoic acid protocol used in the Ko et al. paper. Overall, our methods for SH-SY5Y neurospheres involve a more complex differentiation and spheroid formation protocol. Using this SH-SY5Y protocol there is an increase in TH expression, which is a crucial marker for a DAergic phenotype. Previous work was unable to detect any TH using their model of differentiation, suggesting that the cell population was not DAergic (Ko et al. 2020). However, while we did detect TH in these cells, we did not detect another key DAergic marker, DAT, at any time point (Figure 5). In addition, these cells continue to proliferate, as indicated by sustained levels of Ki67 at all time points. Together, this indicates that using this protocol, differentiated SH-SY5Y cells are not mature post- mitotic, DAergic-like neurons. Therefore, the differentiation and spheroid formation protocol reported here only incrementally enhanced the DAergic-like differentiation of SH-SY5Y cells and allowed us to form neurospheres grown in suspension. We were unable to demonstrate MPP+- induced toxicity in our model of SH-SY5Y neurospheres, although we did not test extremely high concentrations of MPP+. Many groups use SH-SY5Y cells to study Parkinson’s disease and related neurodegeneration, however, the LUHMES neurosphere model is better at recapitulating a DAergic phenotype and is also susceptible to the DAergic-toxicant, MPP+ at physiologically relevant concentrations. Therefore, the SH-SY5Y neurosphere model is not suitable for modeling PD-like 170 degeneration or related toxicity due to the lack of DAergic phenotype (lacking DAT expression and high Ki67 proliferation markers) and because of its resistance to MPP+. We also demonstrate here, that neither LUHMES nor SH-SY5Y neurospheres are susceptible to PFF-induced toxicity. 171 TABLES AND FIGURES Figure S3.1. Full western blots and total protein staining for Figure 4. A) Full representative blots for and B) Representative Revert stain. 172 Figure S3.2. Full western blots and total protein staining for Figure 7. Full representative blots for A) LUHMES and B) SH-SY5Y Representative Revert stain for A) LUHMES neurospheres treated with PFFs and B) SH-SY5Y neurospheres treated with PFFs. 173 REFERENCES Ali N, Sane MS, Tang H, Compher J, McLaughlin Q, Jones CD, Maffi SK. 2023. 6- hydroxydopamine affects multiple pathways to induce cytotoxicity in differentiated LUHMES dopaminergic neurons. Neurochem Int. 170:105608. doi:10.1016/j.neuint.2023.105608. Anderson WA, Bosak A, Hogberg HT, Hartung T, Moore MJ. 2021. Advances in 3D neuronal microphysiological systems: towards a functional nervous system on a chip. In Vitro Cell Dev Biol Anim. 57(2):191–206. doi:10.1007/s11626-020-00532-8. Bal-Price A. 2018. Recommendation on test readiness criteria for new approach methods in toxicology: Exemplified for developmental neurotoxicity. ALTEX.:306–352. doi:10.14573/altex.1712081. Bastiaens A, Sabahi-Kaviani R, Luttge R. 2020. Nanogrooves for 2D and 3D Microenvironments of SH-SY5Y Cultures in Brain-on-Chip Technology. Front Neurosci. 14. doi:10.3389/fnins.2020.00666. Beliakov S V., Blokhin V, Surkov SA, Ugrumov M V. 2023a. LUHMES Cells: Phenotype Refinement and Development of an MPP+-Based Test System for Screening Antiparkinsonian Drugs. Int J Mol Sci. 24(1):733. doi:10.3390/ijms24010733. Beliakov S V., Blokhin V, Surkov SA, Ugrumov M V. 2023b. LUHMES Cells: Phenotype Refinement and Development of an MPP+-Based Test System for Screening Antiparkinsonian Drugs. Int J Mol Sci. 24(1):733. doi:10.3390/ijms24010733. Bezard E, Dovero S, Bioulac B, Gross CE. 1997. Kinetics of nigral degeneration in a chronic model of MPTP-treated mice. Neurosci Lett. 234(1):47–50. doi:10.1016/S0304- 3940(97)00663-0. Capinha L, Zhang Y, Holzer A-K, Ückert A-K, Zana M, Carta G, Murphy C, Baldovini J, Mazidi Z, Grillari J, et al. 2023. Transcriptomic-based evaluation of trichloroethylene glutathione and cysteine conjugates demonstrate phenotype-dependent stress responses in a panel of human in vitro models. Arch Toxicol. 97(2):523–545. doi:10.1007/s00204-022-03436-6. Chen R, Ferris MJ, Wang S. 2020. Dopamine D2 autoreceptor interactome: Targeting the receptor complex as a strategy for treatment of substance use disorder. Pharmacol Ther. 213:107583. doi:10.1016/j.pharmthera.2020.107583. Choi M-G, Kim MJ, Kim D-G, Yu R, Jang Y-N, Oh W-J. 2018. Sequestration of synaptic proteins by alpha-synuclein aggregates leading to neurotoxicity is inhibited by small peptide. PLoS One. 13(4):e0195339. doi:10.1371/journal.pone.0195339. Crossman AR, Clarke CE, Boyce S, Robertson RG, Sambrook MA. 1987. MPTP- Induced Parkinsonism in the Monkey: Neurochemical Pathology, Complications of Treatment and Pathophysiological Mechanisms. Canadian Journal of Neurological 174 Sciences / Journal Canadien des Sciences Neurologiques. 14(S3):428–435. doi:10.1017/S0317167100037859. Daubner SC, Le T, Wang S. 2011. Tyrosine hydroxylase and regulation of dopamine synthesis. Arch Biochem Biophys. 508(1):1–12. doi:10.1016/j.abb.2010.12.017. Duffy MF, Collier TJ, Patterson JR, Kemp CJ, Fischer DL, Stoll AC, Sortwell CE. 2018. Quality over quantity: Advantages of using alpha-synuclein preformed fibril triggered synucleinopathy to model idiopathic Parkinson’s disease. Front Neurosci. 12(SEP):1– 10. doi:10.3389/fnins.2018.00621. Efremova L, Schildknecht S, Adam M, Pape R, Gutbier S, Hanf B, Bürkle A, Leist M. 2015. Prevention of the degeneration of human dopaminergic neurons in an astrocyte co-culture system allowing endogenous drug metabolism. Br J Pharmacol. 172(16):4119–4132. doi:10.1111/bph.13193. Feng C, Flores M, Dhoj C, Garcia A, Belleca S, Abbas DA, Parres-Gold J, Anguiano A, Porter E, Wang Y. 2022. Observation of α-Synuclein Preformed Fibrils Interacting with SH-SY5Y Neuroblastoma Cell Membranes Using Scanning Ion Conductance Microscopy. ACS Chem Neurosci. 13(24):3547–3553. doi:10.1021/acschemneuro.2c00478. Fiore NJ, Tamer-Mahoney JD, Beheshti A, Nieland TJF, Kaplan DL. 2022. 3D biocomposite culture enhances differentiation of dopamine-like neurons from SH-SY5Y cells: A model for studying Parkinson’s disease phenotypes. Biomaterials. 290:121858. doi:10.1016/j.biomaterials.2022.121858. Freyaldenhoven TE, Ali SF, Schmued LC. 1997. Systemic administration of MPTP induces thalamic neuronal degeneration in mice. Brain Res. 759(1):9–17. doi:10.1016/S0006-8993(97)00045-0. Gao J, Perera G, Bhadbhade M, Halliday GM, Dzamko N. 2019a. Autophagy activation promotes clearance of α-synuclein inclusions in fibril-seeded human neural cells. Journal of Biological Chemistry. 294(39):14241–14256. doi:10.1074/jbc.RA119.008733. Gao J, Perera G, Bhadbhade M, Halliday GM, Dzamko N. 2019b. Autophagy activation promotes clearance of α-synuclein inclusions in fibril-seeded human neural cells. Journal of Biological Chemistry. 294(39):14241–14256. doi:10.1074/jbc.RA119.008733. Geng L, Liu W, Chen Y. 2017. miR-124-3p attenuates MPP+-induced neuronal injury by targeting STAT3 in SH-SY5Y cells. Exp Biol Med. 242(18):1757–1764. doi:10.1177/1535370217734492. Grünblatt E, Mandel S, Youdim MBH. 2000. MPTP and 6-hydroxydopamine-induced neurodegeneration as models for Parkinson’s disease: neuroprotective strategies. J Neurol. 247(S2):II95–II102. doi:10.1007/PL00022909. 175 Harischandra DS, Rokad D, Ghaisas S, Verma S, Robertson A, Jin H, Anantharam V, Kanthasamy A, Kanthasamy AG. 2020. Enhanced differentiation of human dopaminergic neuronal cell model for preclinical translational research in Parkinson’s disease. Biochim Biophys Acta Mol Basis Dis. 1866(4):165533. doi:10.1016/j.bbadis.2019.165533. https://doi.org/10.1016/j.bbadis.2019.165533. Harris G, Eschment M, Orozco SP, McCaffery JM, Maclennan R, Severin D, Leist M, Kleensang A, Pamies D, Maertens A, et al. 2018. Toxicity, recovery, and resilience in a 3D dopaminergic neuronal in vitro model exposed to rotenone. Arch Toxicol. 92(8):2587–2606. doi:10.1007/s00204-018-2250-8. http://dx.doi.org/10.1007/s00204- 018-2250-8. Harris G, Hogberg H, Hartung T, Smirnova L. 2017a. 3D Differentiation of LUHMES Cell Line to Study Recovery and Delayed Neurotoxic Effects. Curr Protoc Toxicol. 73:11.23.1-11.23.28. doi:10.1002/cptx.29. Harris G, Hogberg H, Hartung T, Smirnova L. 2017b. 3D differentiation of LUHMES cell line to study recovery and delayed neurotoxic effects. Curr Protoc Toxicol. 2017(August):1–28. doi:10.1002/cptx.29. Hirsch EC, Alvarez-Fischer D, Andreas H, Oertel WH, Höglinger GU, Roscher R, Vulinovic F, Höllerhage M, Sturn A, Noelker C, et al. 2015. Glucocerebrosidase deficiency and mitochondrial impairment in experimental Parkinson disease. J Neurol Sci. 356(1–2):129–136. doi:10.1016/j.jns.2015.06.030. Hogberg HT, Bressler J, Christian KM, Harris G, Makri G, O’Driscoll C, Pamies D, Smirnova L, Wen Z, Hartung T. 2013. Toward a 3D model of human brain development for studying gene/environment interactions. Stem Cell Res Ther. 4(S1):S4. doi:10.1186/scrt365. Huang D, Wang Z, Tong J, Wang M, Wang J, Xu J, Bai X, Li H, Huang Y, Wu Y, et al. 2018. Long-term Changes in the Nigrostriatal Pathway in the MPTP Mouse Model of Parkinson’s Disease. Neuroscience. 369:303–313. doi:10.1016/j.neuroscience.2017.11.041. Innala M, Riebe I, Kuzmenko V, Sundberg J, Gatenholm P, Hanse E, Johannesson S. 2014. 3D Culturing and differentiation of SH-SY5Y neuroblastoma cells on bacterial nanocellulose scaffolds. Artif Cells Nanomed Biotechnol. 42(5):302–308. doi:10.3109/21691401.2013.821410. Ioghen OC, Ceafalan LC, Popescu BO. 2023. SH-SY5Y Cell Line In Vitro Models for Parkinson Disease Research—Old Practice for New Trends. J Integr Neurosci. 22(1):20. doi:10.31083/j.jin2201020. Ito K, Eguchi Y, Imagawa Y, Akai S, Mochizuki H, Tsujimoto Y. 2017. MPP+ induces necrostatin-1- and ferrostatin-1-sensitive necrotic death of neuronal SH-SY5Y cells. Cell Death Discov. 3(1):17013. doi:10.1038/cddiscovery.2017.13. 176 Jagmag SA, Tripathi N, Shukla SD, Maiti S, Khurana S. 2016. Evaluation of models of Parkinson’s disease. Front Neurosci. 9(JAN). doi:10.3389/fnins.2015.00503. Janson AM, Fuxe K, Goldstein M. 1992. Differential effects of acute and chronic nicotine treatment on MPTP-(1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) induced degeneration of nigrostriatal dopamine neurons in the black mouse. Clin Investig. 70– 70(3–4). doi:10.1007/BF00184656. Karpowicz RJ, Haney CM, Mihaila TS, Sandler RM, Petersson EJ, Lee VM-Y. 2017. Selective imaging of internalized proteopathic α-synuclein seeds in primary neurons reveals mechanistic insight into transmission of synucleinopathies. Journal of Biological Chemistry. 292(32):13482–13497. doi:10.1074/jbc.M117.780296. Ko KR, Tam NW, Teixeira AG, Frampton JP. 2020. SH‐SY5Y and LUHMES cells display differential sensitivity to MPP+, tunicamycin, and epoxomicin in 2D and 3D cell culture. Biotechnol Prog. 36(2):e2942. doi:10.1002/btpr.2942. [accessed 2021 Mar 10]. https://onlinelibrary.wiley.com/doi/abs/10.1002/btpr.2942. Krug AK, Gutbier S, Zhao L, Pöltl D, Kullmann C, Ivanova V, Förster S, Jagtap S, Meiser J, Leparc G, et al. 2014. Transcriptional and metabolic adaptation of human neurons to the mitochondrial toxicant MPP +. Cell Death Dis. 5(5):e1222–e1222. doi:10.1038/cddis.2014.166. Lauter G, Coschiera A, Yoshihara M, Sugiaman-Trapman D, Ezer S, Sethurathinam S, Katayama S, Kere J, Swoboda P. 2020. Differentiation of ciliated human midbrain- derived LUHMES neurons. J Cell Sci. 133(21). doi:10.1242/jcs.249789. [accessed 2021 Mar 10]. https://jcs.biologists.org/content/133/21/jcs249789. Leah T, Vazquez-Villaseñor I, Ferraiuolo L, Wharton S, Mortiboys H. 2021. A Parkinson’s Disease-relevant Mitochondrial and Neuronal Morphology High-throughput Screening Assay in LUHMES Cells. Bio Protoc. 11(1). doi:10.21769/BioProtoc.3881. Leite PEC, Pereira MR, Harris G, Pamies D, Dos Santos LMG, Granjeiro JM, Hogberg HT, Hartung T, Smirnova L. 2019. Suitability of 3D human brain spheroid models to distinguish toxic effects of gold and poly-lactic acid nanoparticles to assess biocompatibility for brain drug delivery. Part Fibre Toxicol. 16(1):1–20. doi:10.1186/s12989-019-0307-3. Limboonreung T, Tuchinda P, Chongthammakun S. 2020. Chrysoeriol mediates mitochondrial protection via PI3K/Akt pathway in MPP+ treated SH-SY5Y cells. Neurosci Lett. 714:134545. doi:10.1016/j.neulet.2019.134545. Lin C-H, Nicol CJB, Cheng Y-C, Yen C, Wang Y-S, Chiang M-C. 2020. Neuroprotective effects of resveratrol against oxygen glucose deprivation induced mitochondrial dysfunction by activation of AMPK in SH-SY5Y cells with 3D gelatin scaffold. Brain Res. 1726:146492. doi:10.1016/j.brainres.2019.146492. 177 Lin H, Tang R, Fan L, Wang E. 2022. Exogenous Tetranectin Alleviates Pre-formed- fibrils-induced Synucleinopathies in SH-SY5Y Cells by Activating the Plasminogen Activation System. Neurochem Res. 47(10):3192–3201. doi:10.1007/s11064-022- 03673-2. Lotharius J, Barg S, Wiekop P, Lundberg C, Raymon HK, Brundin P. 2002. Effect of Mutant α-Synuclein on Dopamine Homeostasis in a New Human Mesencephalic Cell Line. Journal of Biological Chemistry. 277(41):38884–38894. doi:10.1074/jbc.M205518200. Lotharius J, Falsig J, van Beek J, Payne S, Dringen R, Brundin P, Leist M. 2005. Progressive degeneration of human mesencephalic neuron-derived cells triggered by dopamine-dependent oxidative stress is dependent on the mixed-lineage kinase pathway. The Journal of neuroscience. 25(27):6329–42. doi:10.1523/JNEUROSCI.1746-05.2005. Luk K, Covell DJ, Kehm VM, Zhang B, Song IY, Byrne MD, Pitkin RM, Decker SC, Trojanowski JQ, Lee VMY. 2016. Molecular and Biological Compatibility with Host Alpha-Synuclein Influences Fibril Pathogenicity. Cell Rep. 16(12):3373–3387. doi:10.1016/j.celrep.2016.08.053. http://dx.doi.org/10.1016/j.celrep.2016.08.053. Luk K, Song C, O’Brien P, Stieber A, Branch JR, Brunden KR, Trojanowski JQ, Lee VMY. 2009. Exogenous α-synuclein fibrils seed the formation of Lewy body-like intracellular inclusions in cultured cells. Proc Natl Acad Sci U S A. 106(47):20051– 20056. doi:10.1073/pnas.0908005106. Luk KC, Kehm V, Carroll J, Zhang B, O’Brein P, Trojanowski JQ, Lee VM-Y. 2012. Pathological α-Synuclein Transmission Initiates Parkinson-like Neurodegeneration in Non-transgenic Mice. Science (1979). 338(6109):949–953. doi:10.1126/science.1227157. Mandavilli BS, Ali SF, Van Houten B. 2000. DNA damage in brain mitochondria caused by aging and MPTP treatment. Brain Res. 885(1):45–52. doi:10.1016/S0006- 8993(00)02926-7. Marrazzo P, Angeloni C, Hrelia S. 2019. Combined treatment with three natural antioxidants enhances neuroprotection in a SH-SY5Y 3D culture model. Antioxidants. 8(10). doi:10.3390/antiox8100420. Meissner W, Prunier C, Guilloteau D, Chalon S, Gross CE, Bezard E. 2003. Time- Course of Nigrostriatal Degeneration in a Progressive MPTP-Lesioned Macaque Model of Parkinson’s Disease. Mol Neurobiol. 28(3):209–218. doi:10.1385/MN:28:3:209. Nicolai MM, Witt B, Friese S, Michaelis V, Hölz-Armstrong L, Martin M, Ebert F, Schwerdtle T, Bornhorst J. 2022. Mechanistic studies on the adverse effects of manganese overexposure in differentiated LUHMES cells. Food and Chemical Toxicology. 161:112822. doi:10.1016/j.fct.2022.112822. 178 Nicotra A, Parvez SH. 2002. Apoptotic molecules and MPTP-induced cell death. Neurotoxicol Teratol. 24(5):599–605. doi:10.1016/S0892-0362(02)00213-1. Oliveira LMAAA, Falomir-Lockhart LJ, Botelho MG, Lin K-HHH, Wales P, Koch JC, Gerhardt E, Taschenberger H, Outeiro TF, Lingor P, et al. 2015. Elevated a-synuclein caused by SNCA gene triplication impairs neuronal differentiation and maturation in Parkinson’s patient-derived induced pluripotent stem cells. Cell Death Dis. 6(11):e1994– e1994. doi:10.1038/cddis.2015.318. Pantazopoulou M, Brembati V, Kanellidi A, Bousset L, Melki R, Stefanis L. 2021. Distinct alpha‐Synuclein species induced by seeding are selectively cleared by the Lysosome or the Proteasome in neuronally differentiated SH‐SY5Y cells. J Neurochem. 156(6):880– 896. doi:10.1111/jnc.15174. Patterson JR, Polinski NK, Duffy MF, Kemp CJ, Luk KC, Volpicelli-Daley LA, Kanaan NM, Sortwell CE. 2019. Generation of alpha-synuclein preformed fibrils from monomers and use in vivo. JoVE. 2019(148):1–10. doi:10.3791/59758. Perfeito R, Lázaro DF, Outeiro TF, Rego AC. 2014. Linking alpha-synuclein phosphorylation to reactive oxygen species formation and mitochondrial dysfunction in SH-SY5Y cells. Molecular and Cellular Neuroscience. 62:51–59. doi:10.1016/j.mcn.2014.08.002. Pöltl D, Schildknecht S, Karreman C, Leist M. 2012. Uncoupling of ATP-depletion and cell death in human dopaminergic neurons. Neurotoxicology. 33(4):769–779. doi:10.1016/j.neuro.2011.12.007. Presgraves SP, Ahmed T, Borwege S, Joyce JN. 2004. Terminally differentiated SH- SY5Y cells provide a model system for studying neuroprotective effects of dopamine agonists. Neurotox Res. 5(8):579–98. doi:10.1007/BF03033178. Richardson JR, Caudle WM, Guillot TS, Watson JL, Nakamaru-Ogiso E, Seo BB, Sherer TB, Greenamyre JT, Yagi T, Matsuno-Yagi A, et al. 2007. Obligatory Role for Complex I Inhibition in the Dopaminergic Neurotoxicity of 1-Methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP). Toxicological Sciences. 95(1):196–204. doi:10.1093/toxsci/kfl133. Ross A, Xing V, Wang TT, Bureau SC, Link GA, Fortin T, Zhang H, Hayley S, Sun H. 2020a. Alleviating toxic α-Synuclein accumulation by membrane depolarization: Evidence from an in vitro model of Parkinson’s disease. Mol Brain. 13(1):1–11. doi:10.1186/s13041-020-00648-8. Ross A, Xing V, Wang TT, Bureau SC, Link GA, Fortin T, Zhang H, Hayley S, Sun H. 2020b. Alleviating toxic α-Synuclein accumulation by membrane depolarization: evidence from an in vitro model of Parkinson’s disease. Mol Brain. 13(1):108. doi:10.1186/s13041-020-00648-8. 179 Schildknecht S, Karreman C, Pöltl D, Efrémova L, Kullmann C, Gutbier S, Krug A, Scholz D, Gerding HR, Leist M. 2013. Generation of genetically-modified human differentiated cells for toxicological tests and the study of neurodegenerative diseases. ALTEX. 30(4):427–444. doi:10.14573/altex.2013.4.427. Schildknecht S, Di Monte DA, Pape R, Tieu K, Leist M. 2017. Tipping Points and Endogenous Determinants of Nigrostriatal Degeneration by MPTP. Trends Pharmacol Sci. 38(6):541–555. doi:10.1016/j.tips.2017.03.010. Schneider CA, Rasband WS, Eliceiri KW. 2012. NIH Image to ImageJ: 25 years of Image Analysis HHS Public Access. Nat Methods. 9(7):671–675. doi:10.1038/nmeth.2089. Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011a. Rapid, complete and large-scale generation of post-mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011b. Rapid, complete and large-scale generation of post-mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Scholz D, Pöltl D, Genewsky A, Weng M, Waldmann T, Schildknecht S, Leist M. 2011c. Rapid, complete and large‐scale generation of post‐mitotic neurons from the human LUHMES cell line. J Neurochem. 119(5):957–971. doi:10.1111/j.1471- 4159.2011.07255.x. Shipley MM, Mangold CA, Szpara ML. 2016. Differentiation of the SH-SY5Y human neuroblastoma cell line. Journal of Visualized Experiments. 2016(108). doi:10.3791/53193. Smirnova L., Harris G, Delp J, Valadares M, Pamies D, Hogberg HT, Waldmann T, Leist M, Hartung T. 2016. A LUHMES 3D dopaminergic neuronal model for neurotoxicity testing allowing long-term exposure and cellular resilience analysis. Arch Toxicol. 90(11):2725–2743. doi:10.1007/s00204-015-1637-z. Smirnova L, Harris G, Delp J, Valadares M, Pamies D, Hogberg HT, Waldmann T, Leist M, Hartung T. 2016. A LUHMES 3D dopaminergic neuronal model for neurotoxicity testing allowing long-term exposure and cellular resilience analysis. Arch Toxicol. 90(11):2725–2743. doi:10.1007/s00204-015-1637-z. Song J-X, Shaw P-C, Wong N-S, Sze C-W, Yao X-S, Tang C-W, Tong Y, Zhang Y-B. 2012. Chrysotoxine, a novel bibenzyl compound selectively antagonizes MPP+, but not rotenone, neurotoxicity in dopaminergic SH-SY5Y cells. Neurosci Lett. 521(1):76–81. doi:10.1016/j.neulet.2012.05.063. 180 Speciale SG. 2002. MPTP. Neurotoxicol Teratol. 24(5):607–620. doi:10.1016/S0892- 0362(02)00222-2. Sulzer D, Zhang H, Benoit-Marand M, Gonon F. 2010. Regulation of Extracellular Dopamine: Release and Reuptake. In: Handbook of Behavioral Neuroscience. Vol. 20. Elsevier B.V. p. 297–319. Tong Z Bin, Hogberg H, Kuo D, Sakamuru S, Xia M, Smirnova L, Hartung T, Gerhold D. 2017a. Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening. Journal of Applied Toxicology. 37(2):167–180. doi:10.1002/jat.3334. Tong Z Bin, Hogberg H, Kuo D, Sakamuru S, Xia M, Smirnova L, Hartung T, Gerhold D. 2017b. Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening. Journal of Applied Toxicology. 37(2):167–180. doi:10.1002/jat.3334. Tong Z-B, Braisted J, Chu P-H, Gerhold D. 2020. The MT1G Gene in LUHMES Neurons Is a Sensitive Biomarker of Neurotoxicity. Neurotox Res. 38(4):967–978. doi:10.1007/s12640-020-00272-3. Tong Z-B, Kim H, El Touny L, Simeonov A, Gerhold D. 2022. LUHMES Dopaminergic Neurons Are Uniquely Susceptible to Ferroptosis. Neurotox Res. 40(5):1526–1536. doi:10.1007/s12640-022-00538-y. Tüshaus J, Kataka ES, Zaucha J, Frishman D, Müller SA, Lichtenthaler SF. 2020. Neuronal Differentiation of LUHMES Cells Induces Substantial Changes of the Proteome. Proteomics.:2000174. doi:10.1002/pmic.202000174. Valdinocci D, Radford RAW, Siow SM, Chung RS, Pountney DL. 2017. Potential modes of intercellular α-synuclein transmission. Int J Mol Sci. 18(2). doi:10.3390/ijms18020469. Volpicelli-Daley LA, Luk KC, Lee VMY. 2014. Addition of exogenous α-synuclein preformed fibrils to primary neuronal cultures to seed recruitment of endogenous α- synuclein to Lewy body and Lewy neurite-like aggregates. Nat Protoc. 9(9):2135–2146. doi:10.1038/nprot.2014.143. Volpicelli-Daley LA, Luk KC, Patel TP, Tanik SA, Riddle DM, Stieber A, Meaney DF, Trojanowski JQ, Lee VMY. 2011. Exogenous α-Synuclein Fibrils Induce Lewy Body Pathology Leading to Synaptic Dysfunction and Neuron Death. Neuron. 72(1):57–71. doi:10.1016/j.neuron.2011.08.033. http://dx.doi.org/10.1016/j.neuron.2011.08.033. Wang Y, Gao J, Miao Y, Cui Q, Zhao W, Zhang J, Wang H. 2014. Pinocembrin Protects SH-SY5Y Cells Against MPP+-Induced Neurotoxicity Through the Mitochondrial Apoptotic Pathway. Journal of Molecular Neuroscience. 53(4):537–545. doi:10.1007/s12031-013-0219-x. 181 Welch G, Tsai L. 2022. Mechanisms of DNA damage‐mediated neurotoxicity in neurodegenerative disease. EMBO Rep. 23(6). doi:10.15252/embr.202154217. Xicoy H, Wieringa B, Martens GJM. 2017. The SH-SY5Y cell line in Parkinson’s disease research: a systematic review. Mol Neurodegener. 12(1):1–11. doi:10.1186/s13024-017- 0149-0. http://dx.doi.org/10.1186/s13024-017-0149-0. Yamaguchi A, Ishikawa K ichi, Inoshita T, Shiba-Fukushima K, Saiki S, Hatano T, Mori A, Oji Y, Okuzumi A, Li Y, et al. 2020. Identifying Therapeutic Agents for Amelioration of Mitochondrial Clearance Disorder in Neurons of Familial Parkinson Disease. Stem Cell Reports. 14(6):1060–1075. doi:10.1016/j.stemcr.2020.04.011. https://doi.org/10.1016/j.stemcr.2020.04.011. Zhang X, Yin M, Zhang M. 2014. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. Zhang XM, Yin M, Zhang MH. 2014a. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. Zhang XM, Yin M, Zhang MH. 2014b. Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacol Sin. 35(7):945–956. doi:10.1038/aps.2014.36. 182 Chapter 4: EPHB2 and NR4A2 regulate dopaminergic differentiation and markers of dopaminergic vulnerability in neurospheres, but not MPP+-induced toxicity 183 Abstract Multiple lines of evidence show an association between exposure to persistent organic pollutants (POPs) and an increased risk of Parkinson’s disease (PD). Dieldrin, an organochlorine pesticide, is a specific POP that is associated with an increased risk of PD in both epidemiological and mechanistic studies. In a series of previous studies, we and others demonstrated that developmental exposure to dieldrin in mice leads to a male-specific increase in susceptibility in both the MPTP and α-synuclein pre-formed fibril models. Because epigenetic marks are sensitive to the environment, established during cellular differentiation, and regulate gene expression throughout the lifespan, we characterized DNA modifications induced by developmental dieldrin exposure. We identified sex-specific changes in DNA modifications in genes related to dopaminergic (DAergic) neuron development, suggesting that this exposure establishes a poised epigenetic state early in life that may mediate the observed changes in susceptibility later in life. To model this in vitro, we utilized a 3D Lund human mesencephalic (LUHMES) neurosphere model, where we overexpress or knockdown differentially modified target genes prior to differentiation and assess susceptibility to 1-methyl-4- phenylpyridinium (MPP+), a DAergic toxicant. Here, we focus on two candidate genes that are differentially modified by developmental dieldrin exposure: nuclear receptor subfamily group A member 2 (Nr4a2), a transcription factor critical for DAergic development, and ephrin receptor B2 (Ephb2), a receptor tyrosine kinase involved in axonal guidance and survival. We show that altered NR4A2 and EPHB2 expression disrupts the DAergic phenotype of 3D LUHMES neurospheres and alters the ratio of the dopamine transporter (DAT) to the vesicular monoamine transporter 2 (VMAT2), a 184 marker of DAergic susceptibility to toxicity. However, there were no observed effects of these candidate genes on MPP+-induced toxicity. Therefore, we have modeled developmental dieldrin-induced differentially modified candidate genes and showed that modified expression of NR4A2 and EPHB2 affects DAergic differentiation. Although there were no overt effects on MPP+-induced toxicity, these subtle changes may contribute to DAergic dysfunction and the many factors involved in parkinsonian toxicity. Introduction Epidemiological studies show an association between exposure to persistent organic pollutants and an increased risk of Parkinson’s disease (PD) (Ascherio et al., 2006; Brown et al., 2006; Caudle et al., 2012; Elbaz et al., 2009; Freire & Koifman, 2012; Le Couteur et al., 1999; Priyadarshi et al., 2000; Ritz & Yu, 2000; Semchuk et al., 1992; Steenland et al., 2006; Tanner & Aston, 2000; Tanner & Langston, 1990; Wirdefeldt et al., 2011). When combined with postmortem analysis and mechanistic studies, a role for specific compounds in PD emerges. One such compound is dieldrin, an organochlorine (OC) pesticide that is associated with an increased risk of PD in both epidemiological and mechanistic studies (Corrigan et al., 1998, 2000; Fleming et al., 1994; Hatcher et al., 2007; Kanthasamy et al., 2005; Moretto & Colosio, 2011; Weisskopf et al., 2010). Because dieldrin was phased out in the 1970s and 1980s, the potential for new, acute exposure to dieldrin is low. However, the health effects of past exposures will continue for decades as the population currently diagnosed with PD and those that will develop PD in the next 20-30 years were likely exposed to dieldrin before its phase-out (de Jong et al., 1997; Jorgenson, 2001; Kanthasamy et al., 2005; Meijer et al., 2001). Furthermore, well-established models of dieldrin exposure have demonstrated that dieldrin induces oxidative stress, is selectively toxic to dopaminergic (DAergic) cells, 185 disrupts striatal dopamine (DA) activity, and may promote α-syn aggregation (Chun et al., 2001; Hatcher et al., 2007; Kanthasamy et al., 2005; Kitazawa et al., 2001, 2003; Moretto & Colosio, 2011; Richardson et al., 2006; Sanchez-Ramos et al., 1998). The epigenome is a potential mediator of the relationship between exposures, genes, and disease. Multiple studies suggest that exposure to OCs and dieldrin can induce epigenetic changes. Organochlorines are associated with hypomethylation of repetitive DNA elements in blood from Greenlandic Inuit (Rusiecki et al., 2008). In mice, dieldrin induces histone hyperacetylation in the striatum and substanita nigra (SN) of mice treated for 30 days (Song et al., 2010). We also recently found that developmental dieldrin exposure establishes a sex-specific poised epigenetic state early in life that may mediate observed changes in susceptibility to neurotoxicity in the parkinsonian models, MPTP and α-synuclein (α-syn) pre-formed fibrils (PFF), in adult animals (Gezer et al., 2020; Kochmanski et al., 2019; Richardson et al., 2006) Thus, dynamic environmental exposures to these compounds may induce fixed changes in the epigenome, creating a poised epigenetic state in which developmental exposures program a modified response to later-life challenges. As PD prevalence grows, it is critical to define how environmental exposures affect the epigenetic mechanisms involved in disease susceptibility and etiology (Dorsey et al., 2007). The mechanism by which these epigenetic changes may alter PD risk remains unknown. This is a common knowledge gap in neuroepigenetic studies; as a field, we can identify epigenetic changes associated with disease but linking these changes with functional outcomes and altered susceptibility remains a challenge. Here, we modified the expression of two candidate genes in proliferating Lund human mesencephalic 186 (LUHMES) cells before induction of differentiation to DAergic-like neurons. After differentiation, a second hit with 1-methyl-4-phenylpyridinium (MPP+), a DAergic toxicant and the active metabolite of MPTP, was used to parallel the in vivo two-hit models to assess whether each candidate gene mediates neuronal susceptibility. LUHMES cells can be differentiated into morphologically and biochemically mature dopamine-like neurons and are increasingly used for in vitro research (Efremova et al., 2015; Krug et al., 2014; Lotharius et al., 2002, 2005; Noelker et al., 2015; Oliveira et al., 2015; Pöltl et al., 2012; Schildknecht et al., 2013; Scholz et al., 2011; Tong et al., 2017; X. M. Zhang et al., 2014). 3D LUHMES neurospheres were developed as a high- throughput toxicity screening platform to take advantage of the fact that 3D cell models show better differentiation and survival (Harris et al., 2017; Smirnova et al., 2016; Tong et al., 2017). In addition, LUHMES cells have well-established use and display robust performance in high-throughput neurotoxicity studies, including studies of rotenone, another PD-related neurotoxicant (Beliakov et al., 2023; Harris et al., 2018; Hogberg & Smirnova, 2022; Nicolai et al., 2022; Tong et al., 2017). To select candidate genes, we filtered the 288 genes with female-specific differential modifications and 83 genes with male-specific differential modifications for genes with confirmed expression in 1) neurons (Brain RNA-Seq database) to match our neuronal cell model, 2) midbrain based on our previous RNA-Seq data, and 3) undifferentiated 3D LUHMES cells cultures to ensure we can modify these genes in our model, 180 genes remained (Kochmanski et al., 2019; Pierce et al., 2018; Y. Zhang et al., 2014). We then considered a priori knowledge of the genes, whether genes showed differential expression in our previous RNA-Seq data, network analysis of these 180 genes in 187 StringDB, and the function of the genes in those networks (Szklarczyk et al., 2015, 2017). Based on these additional criteria, we selected a set of candidate genes. Here, we report results for nuclear receptor subfamily 4 group A member 2 (NR4A2) and Ephrin Receptor B2 (EPHB2). NR4A2 encodes the nuclear receptor related-1 (Nurr1) protein, a transcription factor critical for DAergic neuron maintenance and development that may contribute to the pathogenesis of PD (Decressac et al., 2013; Dong et al., 2016; Luo, 2012; Smits et al., 2003). Both clinical and experimental data demonstrate that dysregulation of Nurr1 function leads to DA neuron dysfunction (Decressac et al., 2013). In addition, compounds that activate Nurr1 protein and Nr4a2 gene therapy can enhance DA neurotransmission and protect DA neurons from toxicant and microglia-mediated neuroinflammation (Dong et al., 2016). Data in rat midbrain, human midbrain, and the human neuroblastoma cell line, SK-N-AS, demonstrate that there are multiple Nurr1 splice variants expressed in these cells and these isoforms have variable ability to activate transcription of target genes including DAT and TH, suggesting that regulation of isoform-specific expression could be a critical regulatory mechanism in DA neurons (Michelhaugh et al., 2005). In our developmental dieldrin exposure study, we identified a female specific-hypermethylated site within an intron Nr4a2, making epigenetic regulation of Nr4a2 isoform by environmental toxicants, a novel potential mechanism by which developmental exposure to dieldrin may alter PD susceptibility (Kochmanski et al., 2019). EPHB2 encodes Ephrin type-B receptor 2 (Ephb2), a receptor tyrosine kinase that binds the receptor-binding domain of ephrin-B ligands; these proteins communicate across 188 extracellular space allowing for cell-cell bidirectional signaling (Martínez & Soriano, 2005). Ephrins and the Eph receptors show dynamic expression patterns in the developing central nervous system (CNS) and are expressed in most adult CNS cell types (Yang et al., 2018). The EPHB2 signaling pathway is involved in many developmental processes in the CNS, including migration of neural progenitors to the dentate gyrus, regulation of axon guidance, dendritic spine formation, glutamatergic synaptogenesis, and long-term potentiation (Catchpole & Henkemeyer, 2011; Flanagan & Vanderhaeghen, 1998; Henderson et al., 2001; Kayser et al., 2006; Takasu et al., 2002). We observed female-specific intronic DMC in Ephb2 and increased expression of a protein-coding transcript (Kochmanski et al., 2019). In our String network analysis, Ephb2 appears in a highly connected Rho GTPase network, with specific genes showing differential methylation in our developmental dieldrin exposure model. While previous results demonstrate an association between EPHB2 and Alzheimer’s disease, little work has investigated whether EPHB2 plays a role in PD (Cissé et al., 2011; Simón et al., 2009). In these experiments, we overexpressed and knocked down each candidate gene and assessed effects on the expression of key DAergic markers in differentiated LUHMES cells including tyrosine hydroxylase (TH), the dopamine transporter (DAT), and the vesicular monoamine transporter 2 (VMAT2). The effects of candidate gene modification on DAergic toxicity to MPP+ were also assessed. Here, we showed that NR4A2 and EPHB2 gene modifications during proliferation affected DA markers after differentiation, and EPHB2 knockdown significantly altered the ratio of DAT:VMAT2, which is a key 189 indicator of DAergic susceptibility to toxicity. However, there was no effect of NR4A2 or EPHB2 gene modification on MPP+-induced toxicity in a 3D LUHMES model. Methods Figure 4.1. Experimental design for the current study. B) Timeline of lentivirus- mediated gene modification and MPP+ two-hit experiments. During proliferation (D-7), LUHMES cells are transduced with a lentivirus to knockdown or overexpress target genes. Transduced cells are expanded in 2D for one week. At D0, cells are trypsinized and seeded into 6-well plates to begin spheroid formation and dopaminergic differentiation. At D0, samples are collected to verify knockdown or overexpression. At Differentiation Day 12, each well of neurospheres are treated with a different concentration of MPP+ and samples are also collected to determine the dopaminergic differentiation of the neurospheres. 48-hours post-MPP+ treatment, 8 neurospheres for each concentration of MPP+ are transferred to a Matrigel-coated plate and ATP assays are completed the remaining spheroids in the MPP+-treated 6-well plate. On Differentiation Day 15, spheroids on growing the Matrigel-coated plate are live-stained and imaged. Made in BioRender. Animals Male (11 weeks old) and female (7 weeks old) C57BL/6 mice were purchased from Jackson Laboratory (Bar Harbor, Maine). Animal husbandry and colony maintenance was completed as previously described (Kochmanski et al. 2019; Gezer et al. 2020). All procedures were conducted in accordance with the National Institutes of Health Guide for Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee at Michigan State University. Adult female mice (8 weeks old) were 190 bred, and offspring were euthanized at 3 months of age. Animals were euthanized by pentobarbital overdose and intracardially perfused with 0.9% cold saline followed by cold 4% paraformaldehyde perfusions for 30 minutes. Brains were extracted, post-fixed in 4% paraformaldehyde for 48 hours, and placed in 30% sucrose. RNAscope with co-immunofluorescence Mouse nigral sections were cut at 40 µm on a freezing stage sliding knife microtome and stored in cryoprotectant solution at -20°C. Sections were washed in TBS-Triton-X (TBS-Tx) several times, incubated in 0.3% hydrogen peroxide for 1 hour mounted on a Histobond+ adhesion slide (VWR), and dried on a slide warmer. Slides were washed in TBS-X several times and incubated at 60°C overnight. Slides were incubated in antigen retrieval buffer (ACD Biosciences) for 10 minutes, rinsed, and incubated in protease III solution (ACD BioSciences) for 30 minutes and washed with water. Slides were then incubated with an RNA scope probe (Mm-NR4A2-C1: ACD BioSciences) diluted 1:50 for 2 hours at 40°C. Two washes were performed using wash buffer (ACD BioSciences) and then incubated with amplification solution 1 for 30 minutes, washed, incubated in amplification solution 2 for 15 minutes, washed, incubated in amplification solution 3 for 30 minutes, washed, and incubated in amplification solution 4 Alt B-Fluorophore Atto 550 (ACD BioSciences) for 15 minutes. For co-immunofluorescence, slides were rinsed, blocked in 10% normal goat serum in TBS-Tx for 1 hour, and incubated in primary antibodies (TH and NeuN) diluted in 1% NGS in TBS-Tx overnight at room temperature (Table 1). Slides were washed and incubated in secondary antibodies diluted in 1% TBS-Tx for 2 hours, washed, and coverslip with VectaShield Vibrance (VectaLabs). Slides were imaged on an Axioscan 7 (Zeiss). 191 Table 4.1. Assays and Antibodies used for Fluorescent RNAscope LUHMES Cell Culture LUHMES cells (ATCC CRL-2927, RRID: CVCL_B056) were grown as previously described with modifications to the differentiation media supplements. (Harris et al., 2017, 2018; Leite et al., 2019; Smirnova et al., 2016; Tong et al., 2017) For proliferation, cells were grown in 6-well plates or flasks coated with 50 μg/ml poly-L-ornithine and 1 μg/ml fibronectin. Proliferation Media was completely exchanged every other day, and cells were passaged every 3-4 days (Table 1). For differentiation, cells were trypsinized with TrypLE Express (Gibco) and seeded at 2.25 x 106 cells/ml in cell-repellent 6-well plates (Corning) in 2 ml/well Differentiation Media and this was designated Differentiation Day 0 (Harischandra et al., 2020) (Table 2). The 6-well plates were placed on an orbital shaker at 90 rpm in an incubator (37°, 5% CO2) for the remainder of the experiment. Two days after seeding the 6-well plates (Differentiation Day 2), 1 ml of media was exchanged for 1 ml of Differentiation Media with 20 nM paclitaxel (Sigma-Aldrich) to inhibit proliferation. Two days after paclitaxel treatment (Differentiation Day 4), 1.8 ml of media was removed from each well and 192 replaced with 2 ml of differentiation media to wash out paclitaxel. After the paclitaxel washout, half media changes were completed every other day for the remainder of the experiment as previously described (Harris et al., 2017, 2018; Leite et al., 2019; Smirnova et al., 2016; Tong et al., 2017). Table 4.2. LUHMES Proliferation Media 193 Table 4.3. LUHMES Differentiation Media Lentivirus Production siRNAs targeting EPHB2 (GCCCAAGTTCGGCCAAATTGT) and NR4A2 (CTCCAGAGTTTGTCAAGTTTA) were designed using algorithms as previously described (Benskey et al., 2015; Toro Cabrera & Mueller, 2016). Scrambled control siRNAs containing the same nucleotide composition as target siRNAs in random order were also produced, scrambled EPHB2 (ATTAGTCGCTAAGTCAGGACC) and scrambled NR4A2 (GATATTACCGATATTGTCGCT). siRNAs oligonucleotides were cloned into an shRNA backbone downstream of the H1 promoter and the knockdown 194 efficiency of each respective shRNA was tested using a dual luciferase assay (Promega Dual-Luciferase Reporter Assay System) (Benskey et al., 2015). Following screening, the shRNAs that produced the highest degree of knockdown, and corresponding scrambled control shRNAs, were subcloned into a lentiviral genome that also contained a blue florescent protein (BFP) reporter gene. For overexpression studies, human EPHB2 and NR4A2 cDNA were cloned into a lentiviral genome under the control of the control of chicken β-actin (CBA) promoter. Overexpression vectors contained an NE tag on the N-terminus (Shu Leong Ho Labs). The control condition for the overexpression was untreated cells. Lentiviruses were packaged through the co-transfection of human embryonic kidney 293T (HEK293T) cells with a pHEF VSV-G pseudotyping envelop vector (Addgene #22501), a pNHP packaging vector (Addgene #22500), and the lentiviral genome containing the respective shRNAs, or cDNAs (Coleman et al., 2003). Briefly, HEK293T cells were grown to 70% confluency in 3x150mm culture dishes in 293T (ATCC CRL- 3216) medium containing 5% FBS, penicillin/streptomycin in DMEM base media. Polyethyleneimine (PEI) was used to transfect HEK293T cells with the above plasmids and cells were at 37°C and 5% CO2. 48 hours post-transduction, all media was aspirated and replaced with 26ml of viral media containing 2% FBS, Penicillin/streptomycin using DMEM base media. 24 hours after the media change, producer cell media was harvested and an additional 26ml of viral media was added to the 293T cells. Harvested media was concentrated by first removing cellular debris via a 675 xg 5-minute centrifugation spin and filtering the supernatant via a 0.45 µm filter to clarify the media. Media was added to 3,35ml ultracentrifugation tubes and underlaid 195 with 2ml of a 20% sucrose solution and centrifuged at 82,700 x g for 2 hr at 4°C. The pellets were collected in 500µl of PBS. 24 hours later, producer media was again collected, harvested, clarified, and concentrated as stated above, and the pellet was resuspended and combined with the same 500µl lentivirus containing PBS solution from the previous day. Lentiviruses were mixed well, aliquoted, and stored at -80°C (Coleman et al., 2003; Combs et al., 2021). Lenti X P24 Rapid Titration Elisa Kit (TaKaRa bio) was used according to the manufacturer’s protocol to determine lentiviral physical titers. Lentivirus Transduction in LUHMES Cells LUHMES cells were seeded in poly-L-ornithine and fibronectin-coated 6-well plates at a density of 300,000 cells/well in 2 ml of proliferation media. 24 hours after seeding, media was removed from wells and replaced with 1.5ml of proliferation media. After, lentivirus was diluted in PBS and added to each well at a concentration of 1.0 pg of P24 (determined by Lenti X P24 Rapid Titration Elisa) was added to the cells by evenly distributing throughout the well. 24 hours later, an additional 0.5ml of media was added to each well. 24 hours later the cells were trypsinzed and passaged to a poly-L-ornithine and fibronectin T25 flask and expanded. MPP+ Treatment MPP+ was resuspended in PBS at a stock concentration of 10 mM. On the day of treatment, MPP+ was diluted in media to make 2x the final concentration, and 1 ml of media was removed from each well of the 6-well plate and replaced with 1 ml of 2x media with MPP+. Each well was treated with concentrations of 20 µM (ATP viability assays) or 50 µM (neurite outgrowth assays), equivalent to the previously calculated 196 IC50 for these assays in these cells (Chapter 3). At 48 hours post-treatment, 8 spheroids from each 6-well were transferred to Matrigel-coated 96-well plates for neurite outgrowth assays and the remaining spheroids in each MPP+ treated well were used for ATP assays. Collection of cell lysates and western blotting To confirm DA marker protein expression (TH, DAT, VMAT2) and confirm candidate protein expression (NR4A2 or EPHB2), spheroids from 1-well of the 6-well plate were pooled, collected, processed, and frozen as stated above at Differentiation Day 12. Cell pellets were resuspended in RIPA buffer with protease inhibitors, lysates were spun at 1,000 xg for 5 minutes, and the supernatant was collected as the lysate for western blotting. For TH, DAT, VMAT2, EPHB2, and NR4A2 (overexpression blots only) western blots, 20 µg of protein was loaded onto Novex 10% Bis-Tris gels (Invitrogen) and co-blotted with a standard curve of protein ranging from 5 µg-30 µg. For NR4A2 blots confirming NR4A2 knockdown only, 35 µg of protein was loaded onto Novex 10% Bis-Tris gels (Invitrogen) and co-blotted with a standard curve of protein ranging from 7.5µg-45µg. For TH, the bands quantified are ~50-62kDa, DAT is ~70kDa, VMAT2 is ~56kDa, NR4A2 is ~72kDa, and EPHB2 is ~130kDa. Proteins were electrophoretically transferred to nitrocellulose membranes (BioRad). Membranes were stained with Revert 700 Total-Protein Stain (LI-COR) for 5 minutes and imaged with a LI-COR Odyssey CLx. Membranes were blocked with Odyssey blocking Buffer (LI-COR), and incubated in either NR4A2 (Invitrogen), EPHB2 (Invitrogen) TH (Millipore), DAT (Sigma), or VMAT2 primary antibodies overnight at 4°C. 197 After washing, membranes were incubated in goat anti-Rabbit 800CW (LI-COR) or goat-anti-Mouse IgG1 (for EPHB2 only) for 1 hour and imaged with a LI-COR Odyssey CLx. Bands of interest were normalized to total protein revert stain and the standard curve was included in each blot. Table 4.4. Antibodies used for Western Blotting ATP Assays The baseline effects of overexpressing and knocking down expression of NR4A2 or EPHB2 on cell viability (ATP assay) of LUHMES cells was assessed in the absence of MPP+, while the impact of these gene changes on viability was assessed after exposure to 20 µM MPP+. The 20 µM MPP+ dose was based on previous data in our lab (Chapter 3, Figure 6) where we identified that the IC50 value for MPP+ exposure in spheroids for ATP assays was near 20 µM MPP+ (i.e 17.08 µM MPP+). 198 For ATP assays, 1 ml of media from each well of the 6-well neurosphere plate was removed and replaced with 1 ml of Cell Titer-Glo 3D reagent (Promega). Neurospheres were lysed by shaking the plates at 700 rpm for 20 minutes at room temperature in a Thermomixer (Eppendorf). To avoid cellular debris, the supernatant was transferred to a white 96-well assay plate in triplicate (Corning). ATP standards were diluted in media and pipetted in triplicate in the white 96-well assay plate. The plate was incubated for 10 minutes in the dark and luminescence was read using a Synergy H1 plate reader at an integration time of 1.5 seconds and a reading height of 7.00 mm (BioTek). Blanks were subtracted and samples were calibrated to the ATP standard to calculate ATP concentration (µM). All ATP cytotoxicity assays were completed with at least 3 biological replicates from independent experiments, with 4 technical replicates per experiment. Neurite Outgrowth Assays The baseline effects of overexpressing and knocking down expression of NR4A2 or EPHB2 on neurite outgrowth of LUHMES cells were assessed in the absence of MPP+, while the impact of these gene changes on viability was assessed after exposure to 50 µM MPP+. The 50 µM MPP+ dose was based on previous data in our lab where we Figure 4.2. Representative neurite outgrowth analysis. Scale bar represents 1000 µM. 199 identified that the IC50 value for MPP+ exposure in spheroids for neurite outgrowth assays was near 50 µM MPP+ (i.e 54.90 µM MPP+). 48 hours before neurite analysis, black 96-well optical bottom plates (Corning) were coated with growth factor reduced Matrigel® Growth Factor Reduced (GFR) Basement Membrane Matrix (Corning) diluted 1:24 in DMEM/F12 and placed in an incubator to polymerize overnight. Following polymerization, Matrigel was aspirated and replaced with LUHMES Differentiation Media made with phenol-free DMEM/F12 (Gibco). Individual spheroids were transferred to single wells in the Matrigel-coated plate. 24 hours after plating, neurites were stained with a Neurite Outgrowth Staining Kit (ThermoFisher) for 30 minutes as directed. At the end of incubation, half of the solution was replaced with a 3x Background Suppression Dye. Neurospheres were imaged with a Lionheart Fx Automated Microscope at 4x using a GFP filter cube (BioTek). Images were then analyzed in Gen5 software. Briefly, a primary mask around the spheroid body is generated by thresholding and a secondary mask is generated by thresholding within a ring around the spheroid body. The ratio of the areas of the secondary mask to the primary mask provides a measure of neurite outgrowth (Figure 2). Each well was manually checked for the following exclusion criteria: wells containing multiple spheroids, spheroids touching the edge of the well, or spheroid or neurites no longer attached to the plate. Images were exported from Gen5 and figures were generated in Adobe Illustrator. Statistical analysis Independent experiments are cells from separate differentiations. After lysis for the ATP assay, the lysate is pipetted in triplicate in the white 96-well assay plate which 200 comprises 3 technical replicates for every independent replicate. For the Neurite outgrowth assay, 8 neurospheres were transferred from each well (concentration of MPP+) of the 6-well plate to a Matrigel-coated 96-well plate. For western blot analysis, at least 3 biological replicates were used for every analysis. For all statistics reported here, a paired two-tailed T-test was used with a p-value cutoff of 0.05 using GraphPad Prism 9. Results Confirmation of NR4A2 expression in dopaminergic nigrostriatal neurons To confirm that our candidate genes are expressed in DAergic nigrostriatal neurons, RNAscope for NR4A2 was performed with co-immunofluorescence for tyrosine hydroxylase (TH) and neuronal nuclei (NeuN) in 3-month-old mouse nigral tissue of male mice. Here, we show that NR4A2 mRNA is expressed in TH-immunoreactive, NeuN-immunoreactive neurons of the substantia nigra (SN). However, we determined that EPHB2 transcripts-per-million from RNA sequencing in the midbrain was 3.0 TPM is Figure 4.3. Confirmation of NR4A2 RNA expression in dopaminergic nigrostriatal neurons. A) Substantia nigra indicating location of images in panel B. Scale bar represents 550µm. B) Higher magnification showing TH in green, NeuN in blue, NR4A2 RNA scope in Red, and merged images. Scale bar represents 10µm. 201 below the limit of detection for RNAscope (Allen Brain Atlas). Therefore, EPHB2 mRNA via RNAscope was undetectable. Confirmation of NR4A2 overexpression To confirm NR4A2 overexpression, lysates were collected at Differentiation Day 12 and western blots were run and probed for Nr4a2 protein. Here, we show an approximately 3-fold increase in Nr4a2 protein in transduced LUHMES neurospheres after differentiation (p=0.0173) (Figure 4). Figure 4.4. Confirmation of NR4A2 Overexpression. A) Representative western blot for Nr4a2. B) Quantification of 3 biological replicates show a signficant decrease in protein (p=0.0173) (n=3 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. NR4A2 overexpression during proliferation decreases the expression of dopaminergic phenotype markers in differentiated 3D LUHMES neurospheres On Differentiation Day 12, lysates were collected and western blots were run and probed for DAergic phenotype markers including TH, DAT, and VMAT2. Western bot analysis shows that NR4A2 overexpression during proliferation modifies the expression of DAergic markers in differentiated neurospheres. Here, we show an approximate 40% decrease in TH expression (p=0.0240) (Figure 5A, B). DAT expression was not significantly affected (p=0.2137), while VMAT2 protein was decreased by approximately 202 27% compared to control (p=0.0247) (Figure 5A, C-D). The ratio of DAT:VMAT2 was not significantly affected by NR4A2 overexpression (p=0.5847) (Figure 5E). Figure 4.5. NR4A2 overexpression affects the dopaminergic differentiaon of LUHMES neurospheres. A) Representative blots for TH, DAT, VMAT2 protein. B) TH protein is signficantly decreased in NR4A2 overexpressing neurospheres (p= 0.0240). C) DAT expression is not affected by NR4A2 overexpression (p= 0.2137). D) VMAT2 expression is significantly decreased (p=0.0247). The ratio of DAT:VMAT2 is not significantly affected (p= 0.5847) (n=3 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. NR4A2 overexpression does not affect MPP+-induced toxicity To determine if NR4A2 overexpression affects the health of the cells at baseline, ATP and neurite outgrowth assays were completed on control and overexpressing neurospheres. At baseline, ATP concentration was not affected by NR4A2 overexpression (p= 0.2951). Neurite outgrowth was also not affected by NR4A2 203 Figure 4.6. NR4A2 overexpression does not affect baseline ATP and neurite outgrowth assays nor MPP+-induced toxicity. A) ATP concentration (µM) is not affected in NR4A2 overexpressing neurospheres (p= 0.2951). B) Relative neurite outgrowth is not affected in NR4A2 overexpressing neurospheres compared to control neurospheres (p= 0.2964). C) Representative neurite outgrowth image of control (left) and NR4A2 overexpressing neurospheres (right) at baseline D) ATP concentration (µM) is not affected in NR4A2 overexpressing neurospheres treated with 20 µM MPP+ (p= 0.5963). E) Relative neurite outgrowth is not affected in NR4A2 overexpressing neurospheres (p= 0.3216). F) Representative neurite outgrowth image of control (left) and NR4A2 overexpressing (right) neurospheres treated with 50 µM. (n=3 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. Scale bar represents 1000µm. 204 overexpression (p= 0.2964) (Figure 6A-C). As a second hit, MPP+ concentrations of either 20 µM or 50 µM were added to neurospheres based on previously determined IC50 values for ATP and neurite outgrowth assays, respectively. NR4A2 overexpression did not affect MPP+ (20 µM)-induced decreases in ATP concentration (p=0.5963) (Figure 6D). NR4A2 overexpression did not affect MPP+ (50 µM)-induced decreases in neurite outgrowth (Figure 6E-F). Confirmation of NR4A2 knockdown On Differentiation Day 12, lysates were collected, and western blots were run and probed for Nr4A2 protein. Western blot analysis showed an approximately 45% decrease in Nr4a2 protein in NR4A2 knockdown neurospheres (p= 0.0165) (Figure 7). Figure 4.7. Confirmation of NR4A2 Knockdown. A) Representative western blot for Nr4a2. B) Quantification of 4 biological replicates show a significant decrease in Nr4a2 (p=0.0165). (n=4 and each replicate are indicated by a different symbol; paired two- tailed t-test). Data shown as mean +/- SD. NR4A2 knockdown during proliferation increases the expression of dopaminergic phenotype markers in differentiated 3D LUHMES neurospheres Lysates were collected at Differentiation Day 12 and run on western blots probing for DAergic phenotype markers (TH, DAT, and VMAT2) to determine if knockdown affects DAergic differentiation. NR4A2 knockdown neurospheres showed a 36% increase in TH expression following differentiation (p= 0.0304). DAT expression was significantly 205 decreased by 9% compared to control (p= 0.0032), and there was an approximate 40% increase in VMAT2 protein expression (p= 0.0225). The ratio of DAT: VMAT2 was not significantly affected in NR4A2 knockdown neurospheres (p= 0.1815) (Figure 8). NR4A2 knockdown does not affect MPP+-induced toxicity Figure 4.8. NR4A2 Knockdown affects the dopaminergic differentiation of LUHMES neurospheres. A) Representative blots for TH, DAT, VMAT2 protein. B) TH protein is signficantly increased in NR4A2 knockdown compared to scrambled neurospheres (p=0.0304). C) DAT expression is signficantly decreased (p=0.0032). D) VMAT2 expression is significantly increased compared to scrambled (p=0.0225). The ratio of DAT:VMAT2 is not significantly affected by NR4A2 knockdown neurospheres (p= 0.1815). (n=4 and each replicate are indicated by a different symbol; paired two- tailed t-test). Data shown as mean +/- SD. To test if NR4A2 knockdown affects baseline cell health, ATP and neurite outgrowth assays were completed on scramble and knockdown neurospheres. ATP concentration (µM) was significantly decreased in NR4A2 knockdown neurospheres compared to scrambled shRNA controls (p= 0.0320) (Figure 9A). However, relative neurite outgrowth is not affected by NR4A2 knockdown at baseline (p= 0.5771) (Figure 9B-C). As a 206 second hit, MPP+ concentrations of either 20 µM or 50 µM were added to neurospheres based on previous IC50 values for ATP and neurite outgrowth assays respectively. NR4A2 knockdown did not affect MPP+ (20µM)-induced decreases in ATP concentration (p=0.2301) (Figure 9D). NR4A2 knockdown also did not affect MPP+(50µM)-induced decreases in relative neurite outgrowth in neurospheres (p= 0.0898 respectively) (Figure 9E-F). 207 Figure 4.9. NR4A2 knockdown reduces baseline ATP, but not relative neurite outgrowth or MPP+-induced toxicity. A) ATP concentration (µM) is signficantly decreased in NR4A2 knockdown neurospheres compared to sham treated (p= 0.0320). B) Relative neurite outgrowth is not affected in NR4A2 knockdown neurospheres compared to scrambled neurospheres (p= 0.5771). C) Representative neurite outgrowth image of scrambled (left) and NR4A2 knockdown neurospheres (right) at baseline D) ATP concentration (µM) is not affected in NR4A2 knockdown neurospheres treated with 20 µM MPP+ (p= 0.2301). E) Relative neurite outgrowth is not affected in NR4A2 knockdown neurospheres (p= 0.0898). F) Representative neurite outgrowth image of scrambled (left) and NR4A2 knockdown (right) neurospheres treated with 50 µM. (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. Scale bar represents 1000µm. 208 Confirmation of EPHB2 overexpression To determine the relative knockdown in Ephb2 protein, western blots were run and probed for Ephb2 using lysates collected at Differentiation Day 12. Western blot quantification shows that differentiated neurospheres transduced with EPHB2 lentivirus results in ~128% increase in Ephb2 protein (p =0.0053) (Figure 10). Figure 4.10. Confirmation of EPHB2 Overexpression. A) Representative western blot for Ephb2. B) Quantification of 4 biological replicates show a significant increase in Ephb2 (p= 0.0053). (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. EPHB2 overexpression during proliferation modifies the expression of dopaminergic phenotype markers in differentiated 3D LUHMES neurospheres On Differentiation Day 12, lysates were collected and western blots were run and probed for DAergic phenotype markers including TH, DAT, and VMAT2. EPHB2 overexpression results in a significant decrease in TH protein by ~7% (p= 0.0043). Similarly, DAT expression was not significantly increased compared to control (p= 0.0578). VMAT2 protein was increased by 25% (p= 0.0135). The ratio of DAT:VMAT2 was not significantly affected in EPHB2 overexpressing neurospheres (p= 0.0604) (Figure 11). 209 Figure 4.11. EPHB2 Overexpression affects the dopaminergic differentiaon of LUHMES neurospheres. A) Representative blots for TH, DAT, VMAT2 protein. B) TH protein is signficantly decreased in EPHB2 overexpressing neurospheres compared to control (p= 0. 0043). C) DAT expression was not significantly affected (p= 0.0578). D) VMAT2 expression is significantly increased compared to scrambled (p= 0.0135). The ratio of DAT: VMAT2 is signficantly reduced in EPHB2 overexpressing neurospheres (p= 0.0604). (n=4 and each replicate are indicated by a different symbol; paired two- tailed t-test). Data shown as mean +/- SD. EPHB2 overexpression does not affect MPP+-induced toxicity ATP and neurite outgrowth assays were completed on control and EPHB2 overexpressed neurospheres to determine the effect of EPHB2 on cell health. At baseline, ATP concentration (µM) and relative neurite outgrowth are not affected by EPHB2 overexpression (p= 0.8367 and p= 0.4476, respectively) (Figure 12A-C). To determine if EPHB2 overexpression modifies the response to MPP+-induced toxicity, cells were treated with 20µM of MPP+ for ATP assays or 50µM MPP+ for neurite outgrowth assays. EPHB2 overexpression did not affect MPP+-induced decreases in ATP concentration (p= 0.3910) (Figure 12D). EPHB2 overexpression also did not affect 210 MPP+-induced decreases in relative neurite outgrowth in neurospheres (p= 0.5146) (Figure 12E-F). Figure 4.12. EPHB2 overexpression does not affect baseline ATP and relative neurite outgrowth nor MPP+-induced toxicity. A) ATP concentration (µM) is not affected by EPHB2 overexpression compared to control neurospheres (p=0.8367). B) Relative neurite outgrowth is not affected in EPHB2 overexpression neurospheres compared to control (p= 0.4476). C) Representative neurite outgrowth image of control (left) and EPHB2 overexpression neurospheres (right) at baseline D) ATP concentration (µM) is not affected in EPHB2 overexpression neurospheres treated with 20 µM MPP+ (p= 0.3910). E) Relative neurite outgrowth is not affected in EPHB2 overexpression neurospheres (p= 0.5146). F) Representative neurite outgrowth image of control (left) and EPHB2 overexpression (right) neurospheres treated with 50 µM. (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. Scale bar represents 1000µm. 211 Confirmation of EPHB2 knockdown Lysates were collected, run on western blots, and probed for Ephb2 protein on Differentiation Day 12 to confirm EPHB2 knockdown. Western blot quantification shows that differentiated neurospheres transduced with an EPHB2 shRNA lentivirus result in an approximate 56% decrease in EPHB2 protein (p= 0.0164) (Figure 13). Figure 4.13. Cofirmation of EPHB2 Knockdown. A) Representative western blot for EPHB2. B) Quantification of 4 biological replicates show a significant increase in EPHB2 (p= 0.0164) (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. EPHB2 knockdown during proliferation modifies the expression of dopaminergic phenotype markers in differentiated 3D LUHMES neurospheres Western blots were run and probed for the DAergic phenotype markers (TH, DAT, VMAT2) using lysates collected at Differentiation Day 12 to determine if EPHB2 knockdown affects DAergic differentiation. EPHB2 knockdown resulted in a ~34% increase in TH protein in differentiated neurospheres compared to scramble transduced (p= 0.0099). There was also a 33% decrease in DAT protein (p=0.0199). VMAT2 protein expression was significantly reduced by 48% (p= 0.0061). The ratio of DAT:VMAT2 was significantly increased compared to scramble-transduced neurospheres (p=0.0152) (Figure 14). 212 EPHB2 knockdown does not affect MPP+-induced toxicity Figure 4.14. EPHB2 knockdown affects the dopaminergic differentiaon of LUHMES neurospheres. A) Representative blots for TH, DAT, VMAT2 protein. B) TH protein is signficantly increased in EPHB2 knockdown compared to scrambled (p= 0.0099). C) DAT expression is signficantly decreased (p= 0.0199). D) VMAT2 expression is significantly decreased compared to scrambled (p= 0.0061). The ratio of DAT:VMAT2 is signficantly increased (p= 0.0152). (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. To determine if EPHB2 knockdown affects the baseline health of the cells, ATP and neurite outgrowth assays were completed on scrambled control and knockdown neurospheres. At baseline, ATP concentration (µM) and relative neurite outgrowth are not affected by EPHB2 knockdown (p= 0.4586 and p=0.9556, respectively) (Figure 15A- C). To determine if EPHB2 knockdown affects toxicity induced by MPP+, neurospheres were treated with 20µM MPP+ for ATP assays or 50µM MPP+ for neurite outgrowth assays. EPHB2 knockdown did not affect MPP+-induced decreases in ATP concentration (p= 0.7575) (Figure 15D). MPP+-induced decreases in relative neurite 213 outgrowth were not affected by EPHB2 knockdown in neurospheres (p= 0.9002)) (Figure 15E-F). 214 Figure 4.15. EPHB2 knockdown does not affect baseline ATP or relative neurite outgrowth nor MPP+-induced toxicity. A) ATP concentration (µM) is not affected by EPHB2 knockdown compared to scrambled neurospheres (p= 0.4586). B) Relative neurite outgrowth is not affected in EPHB2 knockdown neurospheres compared to scrambled (p= 0.9556). C) Representative neurite outgrowth image of scrambled (left) and EPHB2 knockdown neurospheres (right) at baseline D) ATP concentration (µM) is not affected in EPHB2 knockdown neurospheres treated with 20 µM MPP+ (p= 0.7575). E) Relative neurite outgrowth is not affected in EPHB2 knockdown neurospheres (p= 0.9002). F) Representative neurite outgrowth image of scrambled (left) and EPHB2 knockdown (right) neurospheres treated with 50 µM. (n=4 and each replicate are indicated by a different symbol; paired two-tailed t-test). Data shown as mean +/- SD. Scale bar represents 1000µm. 215 Table 4.5. Summary of Modified NR4A2 Expression on Differentiated LUHMES Neurospheres Table 4.6. Summary of Modified EPHB2 Expression on Differentiated LUHMES Neurospheres Discussion NR4A2 modification during a developmental phase modifies the expression of dopaminergic markers following differentiation Here, we show that NR4A2 modifies the expression of DAergic proteins TH, DAT, and VMAT2 (Figures 5 and 8). The role of NR4A2 (Nurr1 protein) in DAergic regulation and development has been well-studied. In adult rat-derived neuronal precursor cells, Nurr1 overexpression increases TH but does not affect other DAergic proteins including the D2-like receptors (D2R), VMAT2, and aromatic l-amino acid decarboxylase (AADC) (Sakurada et al., 1999). In human DAergic, MN9D cells, Nurr1 overexpression 216 increases DA content, AADC, and VMAT2 levels 24 hours after induced overexpression (Hermanson, 2003). In line with this, TH expression is significantly upregulated immediately after Nurr1 transduction in adult rat hippocampal progenitor cells (Sakurada et al., 1999). During early stages of neurodevelopment in Nurr1 knockout mice VMAT2, AADC, and TH expression is significantly downregulated at Embryonic day 13.5. Since Nurr1 knockout is lethal soon after birth, levels during adulthood have not been investigated in this model, but Nurr1 deficient heterozygous mice at birth show a decrease in DA in the midbrain and striatum, but no changes in the number of midbrain DA neurons (Zetterström et al., 1997). In contrast, Le et al. did not observe any differences in striatal DA in adult Nurr1 heterozygous mice (Le et al., 1999, 2003). These models show that NR4A2 regulates DAergic protein expression, but Nurr1 activity is highly dependent on timing and phase of development in DAergic neurons. It is important to note that lasting changes in gene expression can induce compensatory mechanisms to tune the effects of DAergic protein expression during neurodevelopment. A feedback loop involving DA activation of DA presynaptic autoreceptors which are known to reduce phosphorylation of TH leading to decreased DA synthesis, packaging, and release (Chen et al., 2020; Daubner et al., 2011; Ford, 2014; Sulzer et al., 2016). Nurr1-mediated effects on DAergic markers and DA levels seem to be variable over time and these differences may be explained by compensatory mechanisms (Moore & Zigmond, 1994; Zigmond et al., 1998). Nurr1 protein was shown to bind the NGFI-B response element site on the TH promoter directly regulating TH activity (Kim et al., 2003). However, a more recent study shows that Nurr1 represses TH promoter activity 217 in human neural stem cells (hNSC), but transactivates the TH promoter in differentiated SH-SY5Y cells (Kim et al., 2013). This suggests that potentially Nurr1 undergoes a functional switch from a transcriptional repressor to an activator during DAergic development (Kim et al., 2013). Here, we show that sustained NR4A2 overexpression during the differentiation phase decreases TH and VMAT2 expression once cells are fully differentiated. In contrast, NR4A2 knockdown results in increased TH, DAT, and VMAT2 protein. Our NR4A2- mediated effects on these DAergic proteins are in line with previous work showing that Nurr1 protein targets TH, DAT, VMAT2, and AADC, crucial DAergic genes (Bannon et al., 2002; Decressac et al., 2013; Hermanson, 2003; Jankovic et al., 2005; Jin et al., 2006; Kim et al., 2003; Kim et al., 2006; Kim et al., 2013; Luo, 2012; Michelhaugh et al., 2005; Rodríguez-Traver et al., 2016; Sakurada et al., 1999; Smits et al., 2003). It is likely that NR4A2 modification before the differentiation phases causes persistent changes in the DAergic development of neurospheres and may involve compensatory or negative feedback regulation of these markers. For example, NR4A2 overexpression may induce an early upregulation of TH resulting in increases in DA that trigger the negative feedback loop, leading to a later reduction in TH. As mentioned above Nurr1 can undergo a functional switch to either activate or repress DAergic gene expression during neurodevelopment to finely control differentiation. It is also possible that in our model, we have mirrored the NR4A2-mediated repression of TH expression that others noted (Kim et al., 2013). In our previous in vivo study, developmental dieldrin exposure resulted in a female-specific hypermethylation of a CpG in Nr4a2, and we expected that overexpression of this gene would be protective against toxicity by maintaining 218 dopaminergic phenotype and integrity (Kochmanski et al., 2019). Here, we show that NR4A2 overexpression decreases the DAergic phenotype of these cells after differentiation, while NR4A2 knockdown increases the DAergic phenotype in fully differentiated LUHMES cells. EPHB2 expression modifies dopaminergic differentiation during neurodevelopmental phases We show EPHB2 modifies the expression of DAergic proteins, TH, DAT, and VMAT2 (Figures 9 and 12). The role of EPHB2 in the development of DAergic neurons has not yet been investigated. However, some work shows that the Ephrin (Eph) family receptors play an important role in orchestrating the topographic connections of DAergic neurons of the nigrostriatal and mesolimbic pathways during development (Xiao et al., 2006; Yue et al., 1999). The Eph family receptors are located throughout the CNS and are thought to play a role in axonal guidance, neurite outgrowth, and synaptic plasticity (Blits-Huizinga et al., 2004). Ephb1 is primarily found in the midbrain, with the highest concentrations found in the SN and the ventral tegmental area (VTA), whereas Ephb2 is expressed greatest in the striatum (Passante et al., 2008; Xiao et al., 2006; Yue et al., 1999). On embryonic day 18, Ephb2 is expressed in the nucleus accumbens (NAc) and the striatum in mice. After birth (postnatal day 1-7), Ephb2 expression increases in the NAc and striatum. In adulthood, Ephb2 expression decreases in the NAc and the striatum indicating a potential role of Ephb2 in DAergic development in controlling SN innervation (Passante et al., 2008; Xiao et al., 2006; Yue et al., 1999). Given that the highest expression of Ephb2 occurs during embryonic development and immediately after birth, it is not surprising that we were unable to detect Ephb2 mRNA via RNAscope 219 in 3-month-old mouse nigral tissue even though it was previously detected by more sensitive measures in midbrain dissections via RNAseq in 3-month mice (Kochmanski et al., 2019). To test the effect of ephrin-B2 on nigral DAergic neurons, Yue et al. co-cultured embryonic day 18 VTA or nigral neurons on a monolayer of control NIH-3T3 cells or a monolayer of cells from a stable ephrin-B2-expressing NIH-3T3 cell line (Yue et al., 1999). In nigral DAergic and ephrin-B2 expressing co-cultures, there was an approximate 50% decrease in TH-immunoreactive neurons and a reduction in average neuritic length. However, there was not a loss of TH-immunoreactive neurons or average neuritic length in VTA DAergic and ephrin-B2 expressing co-cultures. These effects on TH immunoreactive neuron loss and reductions in neurite outgrowth were moderately rescued by treatment with an EPHB2 antagonist. This suggests that ephrin- B2 signaling may function to selectively inhibit nigral DAergic neuron growth to guide DAergic development in the SN (Yue et al., 1999). Since EPHB2 is highly expressed in DAergic neurons during development and plays an essential role in guiding DAergic innervation, it is not surprising that altering the expression of EPHB2 during the LUHMES proliferation phase affects the DAergic differentiation of LUHMES neurospheres. Specifically, we observed a reduction in TH, but an increase in VMAT2 and no change in DAT when EPHB2 is overexpressed (Figure 11). On the other hand, we observed an increase in TH, but a reduction in DAT and VMAT2 in EPHB2 knockdown neurospheres (Figure 14). Our observed changes in TH expression align with previous research indicating that EPHB2 during development 220 selectively inhibits nigral DAergic neuron growth to maintain proper SN development and interactions. NR4A2 and EPHB2 regulate markers of DAergic susceptibility to toxicity but do not affect effect overt MPP+-induced degeneration We hypothesized that NR4A2 overexpression would be protective against MPP+- induced toxicity. Although there were no significant changes in the expression of the Nr4a2 protein-coding transcript in female animals, there was a slight increase in expression and observed female-specific hypermethylation. Since the phenotype associated with dieldrin-induced exacerbation of PFF is specific to male mice, and because of the known functions of Nr4a2 in DAergic neuron development we expected NR4A2 to protect against DAergic toxicity. Contrary to this hypothesis, we show here that NR4A2 knockdown upregulates DAergic markers and maintains a lower DAT: VMAT2 ratio (Kochmanski et al., 2019). The ratio of DAT:VMAT2 is an indicator of DAergic susceptibility to toxicity. With a lower ratio of DAT:VMAT2 less DA is taken up via DAT and more is sequestered by VMAT2 resulting in less overall cytosolic DA, which is prone to autoxidation and the forming toxic intermediates (Miller et al., 1999). NR4A2 knockdown did not affect the ratio of DAT:VMAT2, and there were no effects of modified NR4A2 expression on MPP+-induced toxicity were observed here (Figures 6 and 9). It was expected that EPHB2 overexpression would serve as a protective gene mitigating the effects of MPP+ because of its hypermethylation and increased expression in developmental dieldrin-exposed female mice and its functions in axonal guidance and neurite outgrowth. The ratio of DAT:VMAT2 is decreased with EPHB2 overexpression, while EPHB2 knockdown increases the ratio of DAT:VMAT2 (Figures 11 and 14). The 221 ratio of DAT:VMAT2 was previously used as an indicator of increased susceptibility to DAergic toxicity (Miller et al., 1999). However, we did not observe any effects of EPHB2 on MPP+-induced toxicity (Figures 12 and 15). Alterations of the developmental dieldrin-induced differentially modified candidate genes during proliferation, NR4A2, and EPHB2 affect the DAergic phenotype of neurospheres following differentiation. This work is based on the hypothesis that these changes in DAergic gene expression modify susceptibility later in life. However, we were unable to recapitulate toxicity to the second hit of MPP+ in this in vitro system. Since NR4A2 and EPHB2 are two of hundreds of genes differentially modified by dieldrin exposure, likely, these genes are not the sole mediators of exacerbated parkinsonian toxicity and may have only small effects on toxicity on their own that are not apparent in this simplified model (Kochmanski et al., 2019). Modifying one candidate gene may have small effects on susceptibility to toxicity, which may require more sensitive endpoint measures to detect. For example, other groups working towards improving new approach methodologies for neurotoxicity screening show that the most sensitive endpoint for measuring neurotoxicity is electrophysiological endpoints including measures of network connectivity (Carstens et al., 2022). Although there were no observed changes in MPP+-induced toxicity in LUHMES neurospheres, it is still possible that altered expression of EPHB2 and NR4A2 could affect disease susceptibility in vivo. The 3D LUHMES neurosphere model was used as opposed to more complex models because we were specifically interested in the role of these candidate genes in DAergic neurons. However, due to the simplicity of the neurosphere model, we might not observe the same effects that we would in vivo. 222 Additionally, concentrations of MPP+ were selected based on previous IC50 values for ATP and neurite outgrowth assays. However, the levels of toxicity at these doses were higher here than previously observed, with greater effects observed at these doses, particularly for the neurite outgrowth assays. In previous work (Chapter 3, Figure 6) the average relative neurite outgrowth value was near 2.0 in untreated control cells. However, in this set of experiments, untreated control cells showed an average relative neurite outgrowth value between 0.5 and 1.0 (Figures 6B, 9B,12B, and 15B). In previous experiments reported in Chapter 3, values in this range were consistent with neurite outgrowth observed at 20 µM MPP+. Here, cells treated with 20 µM MPP+ had almost no neurites, which is more consistent with our highest MPP+ concentrations used in Chapter 3. Therefore, untreated and unmodified cells in these experiments started with far less developed neurites compared to previous work, limiting our ability to detect differences (Chapter 3, Figure 6). This is likely due to the additional passaging and manipulation steps required for viral transduction and cell expansion during the proliferation phase of these cells, indicating that the passage number and handling of LUHMES cells are extremely important and can cause variation in the cellular response. To perform the ATP and neurite outgrowth assays in the future, individual neurospheres should be treated with MPP+ rather than an entire well for a 6-well plate to reduce the amount of passaging needed to expand the transduced cells. Another approach would be to complete these experiments in a 2D format instead. Here, we show that developmental dieldrin-induced differentially modified genes NR4A2 and EPHB2 regulate the expression of DAergic markers in a 3D LUHMES neurosphere model. These changes in the DAergic phenotype of cells result in an altered 223 DAT:VMAT2 ratio, an indicator of susceptibility to DA degeneration, but did affect MPP+ toxicity in this model. Since environmental factors such as dieldrin exposure play a significant role in PD, and developmental periods are specifically vulnerable to such factors, we must continue to study and identify the link between developmental exposures and disease development later in life. 224 TABLES AND FIGURES Figure S4.1. Confirmation of NR4A2 overexpression full blot and total protein stain. 225 Figure S4.2. Full blots and total protein stains for NR4A2 overexpression experiments. A) TH B) DAT C) VMAT2. 226 Figure S4.3. Confirmation of NR4A2 knockdown full blot and total protein stain. 227 Figure S4.4. Full blots and total protein stains for NR4A2 knockdown experiments. A) TH B) DAT C) VMAT2. 228 Figure S4.5. Confirmation of EPHB2 overexpression full blot and total protein stain. 229 Figure S4.6. Full blots and total protein stains for EPHB2 overexpression experiments. A) TH B) DAT C) VMAT2. 230 Figure S4.7. Confirmation of EPHB2 knockdown full blot and total protein stain. 231 Figure S4.8. Full blots and total protein stains for EPHB2 knockdown experiments. A) TH B) DAT C) VMAT2. 232 REFERENCES Ascherio, A., Chen, H., Weisskopf, M. G., O’Reilly, E., McCullough, M. L., Calle, E. E., Schwarzschild, M. A., & Thun, M. J. (2006). Pesticide exposure and risk for Parkinson’s disease. Annals of Neurology, 60(2), 197–203. https://doi.org/10.1002/ana.20904 Bannon, M. J., Pruetz, B., Manning-Bog, A. B., Whitty, C. J., Michelhaugh, S. K., Sacchetti, P., Granneman, J. G., Mash, D. C., & Schmidt, C. J. (2002). Decreased expression of the transcription factor NURR1 in dopamine neurons of cocaine abusers. Proceedings of the National Academy of Sciences, 99(9), 6382–6385. https://doi.org/10.1073/pnas.092654299 Beliakov, S. V., Blokhin, V., Surkov, S. A., & Ugrumov, M. V. (2023). LUHMES Cells: Phenotype Refinement and Development of an MPP+-Based Test System for Screening Antiparkinsonian Drugs. International Journal of Molecular Sciences, 24(1), 733. https://doi.org/10.3390/ijms24010733 Benskey, M. J., Manfredsson, F. P., Lookingland, K. J., & Goudreau, J. L. (2015). The role of parkin in the differential susceptibility of tuberoinfundibular and nigrostriatal dopamine neurons to acute toxicant exposure. Neurotoxicology, 46, 1–11. https://doi.org/10.1016/j.neuro.2014.11.004 Blits-Huizinga, C. T., Nelersa, C. M., Malhotra, A., & Liebl, D. J. (2004). Ephrins and their receptors: Binding versus biology. IUBMB Life, 56(5), 257–265. https://doi.org/10.1080/15216540412331270076 Brown, T. P., Rumsby, P. C., Capleton, A. C., Rushton, L., & Levy, L. S. (2006). Pesticides and Parkinson’s disease - Is there a link? In Environmental Health Perspectives (Vol. 114, Issue 2, pp. 156–164). https://doi.org/10.1289/ehp.8095 Carstens, K. E., Carpenter, A. F., Martin, M. M., Harrill, J. A., Shafer, T. J., & Paul Friedman, K. (2022). Integrating Data from in Vitro New Approach Methodologies for Developmental Neurotoxicity. Toxicological Sciences, 187(1), 62–79. https://doi.org/10.1093/toxsci/kfac018 Catchpole, T., & Henkemeyer, M. (2011). EphB2 tyrosine kinase-dependent forward signaling in migration of neuronal progenitors that populate and form a distinct region of the dentate niche. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 31(32), 11472–11483. https://doi.org/10.1523/JNEUROSCI.6349- 10.2011 Caudle, W. M., Guillot, T. S., Lazo, C. R., & Miller, G. W. (2012). Industrial toxicants and Parkinson’s disease. NeuroToxicology, 33(2), 178–188. https://doi.org/10.1016/j.neuro.2012.01.010 Chen, R., Ferris, M. J., & Wang, S. (2020). Dopamine D2 autoreceptor interactome: Targeting the receptor complex as a strategy for treatment of substance use disorder. 233 Pharmacology & Therapeutics, 213, 107583. https://doi.org/10.1016/j.pharmthera.2020.107583 Chun, H. S., Gibson, G. E., DeGiorgio, L. A., Zhang, H., Kidd, V. J., & Son, J. H. (2001). Dopaminergic cell death induced by MPP(+), oxidant and specific neurotoxicants shares the common molecular mechanism. Journal of Neurochemistry, 76(4), 1010–1021. https://doi.org/10.1046/j.1471-4159.2001.00096.x Cissé, M., Halabisky, B., Harris, J., Devidze, N., Dubal, D. B., Sun, B., Orr, A., Lotz, G., Kim, D. H., Hamto, P., Ho, K., Yu, G. Q., & Mucke, L. (2011). Reversing EphB2 depletion rescues cognitive functions in Alzheimer model. Nature, 469(7328), 47–52. https://doi.org/10.1038/nature09635 Coleman, J. E., Huentelman, M. J., Kasparov, S., Metcalfe, B. L., Paton, J. F. R., Katovich, M. J., Semple-Rowland, S. L., & Raizada, M. K. (2003). Efficient large-scale production and concentration of HIV-1-based lentiviral vectors for use in vivo. Physiological Genomics, 12(3), 221–228. https://doi.org/10.1152/physiolgenomics.00135.2002 Combs, B., Christensen, K. R., Richards, C., Kneynsberg, A., Mueller, R. L., Morris, S. L., Morfini, G. A., Brady, S. T., & Kanaan, N. M. (2021). Frontotemporal Lobar Dementia Mutant Tau Impairs Axonal Transport through a Protein Phosphatase 1γ-Dependent Mechanism. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 41(45), 9431–9451. https://doi.org/10.1523/JNEUROSCI.1914-20.2021 Corrigan, F. M., Lochgilphead, C. L., Shore, R. F., Daniel, S. E., & Mann, D. (2000). Organochlorine insecticides in substantia nigra in parkinson’s disease. Journal of Toxicology and Environmental Health - Part A, 59(4), 229–234. https://doi.org/10.1080/009841000156907 Corrigan, F. M., Murray, L., Wyatt, C. L., & Shore, R. F. (1998). Diorthosubstituted Polychlorinated Biphenyls in Caudate Nucleus in Parkinson’s Disease. Experimental Neurology, 150(2), 339–342. https://doi.org/10.1006/exnr.1998.6776 Daubner, S. C., Le, T., & Wang, S. (2011). Tyrosine hydroxylase and regulation of dopamine synthesis. Archives of Biochemistry and Biophysics, 508(1), 1–12. https://doi.org/10.1016/j.abb.2010.12.017 de Jong, G., H Swaen, G. M., M Slangen, J. J., M Slangen, J. J., & de Jong, G. (1997). Mortality of workers exposed to dieldrin and aldrin: a retrospective cohort study. Occupational and Environmental Medicine, 54, 702–707. https://doi.org/10.1136/oem.54.10.702 Decressac, M., Volakakis, N., Björklund, A., & Perlmann, T. (2013). NURR1 in Parkinson disease--from pathogenesis to therapeutic potential. Nature Reviews. Neurology, 9(11), 629–636. https://doi.org/10.1038/nrneurol.2013.209 234 Dong, J., Li, S., Mo, J. L., Cai, H. Bin, & Le, W. D. (2016). Nurr1-Based Therapies for Parkinson’s Disease. CNS Neuroscience and Therapeutics, 22(5), 351–359. https://doi.org/10.1111/cns.12536 Dorsey, E. R., Constantinescu, ; R, Thompson, ; J P, Biglan, ; K M, Holloway, ; R G, Kieburtz, ; K, Marshall, F. J., Ravina, ; B M, Schifitto, ; G, Siderowf, ; A, & Tanner, C. M. (2007). Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. www.neurology.org Efremova, L., Schildknecht, S., Adam, M., Pape, R., Gutbier, S., Hanf, B., Bürkle, A., & Leist, M. (2015). Prevention of the degeneration of human dopaminergic neurons in an astrocyte co-culture system allowing endogenous drug metabolism. British Journal of Pharmacology, 172(16), 4119–4132. https://doi.org/10.1111/bph.13193 Elbaz, A., Clavel, J., Rathouz, P. J., Moisan, F., Galanaud, J. P., Delemotte, B., Alpérovitch, A., & Tzourio, C. (2009). Professional exposure to pesticides and Parkinson disease. Annals of Neurology, 66(4), 494–504. https://doi.org/10.1002/ana.21717 Flanagan, J. G., & Vanderhaeghen, P. (1998). The ephrins and Eph receptors in neural development. Annual Review of Neuroscience, 21, 309–345. https://doi.org/10.1146/annurev.neuro.21.1.309 Fleming, L., Mann, J. B., Bean, J., Briggle, T., & Sanchez-Ramos, J. R. (1994). Parkinson’s disease and brain levels of organochlorine pesticides. Annals of Neurology, 36(1), 100–103. https://doi.org/10.1002/ana.410360119 Ford, C. P. (2014). The role of D2-autoreceptors in regulating dopamine neuron activity and transmission. Neuroscience, 282, 13–22. https://doi.org/10.1016/j.neuroscience.2014.01.025 Freire, C., & Koifman, S. (2012). Pesticide exposure and Parkinson’s disease: Epidemiological evidence of association. In NeuroToxicology (Vol. 33, Issue 5, pp. 947– 971). https://doi.org/10.1016/j.neuro.2012.05.011 Gezer, A. O., Kochmanski, J., VanOeveren, S. E., Cole-Strauss, A., Kemp, C. J., Patterson, J. R., Miller, K. M., Kuhn, N. C., Herman, D. E., McIntire, A., Lipton, J. W., Luk, K. C., Fleming, S. M., Sortwell, C. E., & Bernstein, A. I. (2020). Developmental exposure to the organochlorine pesticide dieldrin causes male-specific exacerbation of α-synuclein-preformed fibril-induced toxicity and motor deficits. Neurobiology of Disease, 141(February), 104947. https://doi.org/10.1016/j.nbd.2020.104947 Harischandra, D. S., Rokad, D., Ghaisas, S., Verma, S., Robertson, A., Jin, H., Anantharam, V., Kanthasamy, A., & Kanthasamy, A. G. (2020). Enhanced differentiation of human dopaminergic neuronal cell model for preclinical translational research in Parkinson’s disease. Biochimica et Biophysica Acta - Molecular Basis of Disease, 1866(4), 165533. https://doi.org/10.1016/j.bbadis.2019.165533 235 Harris, G., Eschment, M., Orozco, S. P., McCaffery, J. M., Maclennan, R., Severin, D., Leist, M., Kleensang, A., Pamies, D., Maertens, A., Hogberg, H. T., Freeman, D., Kirkwood, A., Hartung, T., & Smirnova, L. (2018). Toxicity, recovery, and resilience in a 3D dopaminergic neuronal in vitro model exposed to rotenone. Archives of Toxicology, 92(8), 2587–2606. https://doi.org/10.1007/s00204-018-2250-8 Harris, G., Hogberg, H., Hartung, T., & Smirnova, L. (2017). 3D differentiation of LUHMES cell line to study recovery and delayed neurotoxic effects. Current Protocols in Toxicology, 2017(August), 1–28. https://doi.org/10.1002/cptx.29 Hatcher, J. M., Richardson, J. R., Guillot, T. S., McCormack, A. L., Di Monte, D. A., Jones, D. P., Pennell, K. D., & Miller, G. W. (2007). Dieldrin exposure induces oxidative damage in the mouse nigrostriatal dopamine system. Experimental Neurology, 204(2), 619–630. https://doi.org/10.1016/j.expneurol.2006.12.020 Henderson, J. T., Georgiou, J., Jia, Z., Robertson, J., Elowe, S., & Roder, J. C. (2001). The Receptor Tyrosine Kinase EphB2 Regulates NMDA-Dependent Synaptic Function cell surface (Holland et al. In Neuron (Vol. 32). Hermanson, E. (2003). Nurr1 regulates dopamine synthesis and storage in MN9D dopamine cells. Experimental Cell Research, 288(2), 324–334. https://doi.org/10.1016/S0014-4827(03)00216-7 Hogberg, H. T., & Smirnova, L. (2022). The Future of 3D Brain Cultures in Developmental Neurotoxicity Testing. Frontiers in Toxicology, 4. https://doi.org/10.3389/ftox.2022.808620 Jankovic, J., Chen, S., & Le, W. D. (2005). The role of Nurr1 in the development of dopaminergic neurons and Parkinson’s disease. Progress in Neurobiology, 77(1–2), 128–138. https://doi.org/10.1016/j.pneurobio.2005.09.001 Jin, H., Romano, G., Marshall, C., Donaldson, A. E., Suon, S., & Iacovitti, L. (2006). Tyrosine hydroxylase gene regulation in human neuronal progenitor cells does not depend on Nurr1 as in the murine and rat systems. Journal of Cellular Physiology, 207(1), 49–57. https://doi.org/10.1002/jcp.20534 Jorgenson, J. L. (2001). Aldrin and dieldrin: a review of research on their production, environmental deposition and fate, bioaccumulation, toxicology, and epidemiology in the United States. Environmental Health Perspectives, 109(suppl 1), 113–139. https://doi.org/10.1289/ehp.01109s1113 Kanthasamy, A. G., Kitazawa, M., Kanthasamy, A., & Anantharam, V. (2005). Dieldrin- induced neurotoxicity: Relevance to Parkinson’s disease pathogenesis. NeuroToxicology, 26(4 SPEC. ISS.), 701–719. https://doi.org/10.1016/j.neuro.2004.07.010 Kayser, M. S., McClelland, A. C., Hughes, E. G., & Dalva, M. B. (2006). Intracellular and trans-synaptic regulation of glutamatergic synaptogenesis by EphB receptors. The 236 Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 26(47), 12152–12164. https://doi.org/10.1523/JNEUROSCI.3072-06.2006 Kim, J., Koh, H. C., Lee, J., Chang, M., Kim, Y., Chung, H., Son, H., Lee, Y., Studer, L., McKay, R., & Lee, S. (2003). Dopaminergic neuronal differentiation from rat embryonic neural precursors by Nurr1 overexpression. Journal of Neurochemistry, 85(6), 1443– 1454. https://doi.org/10.1046/j.1471-4159.2003.01780.x Kim, S. Y., Choi, K. C., Chang, M. S., Kim, M. H., Kim, S. Y., Na, Y.-S., Lee, J. E., Jin, B. K., Lee, B.-H., & Baik, J.-H. (2006). The Dopamine D 2 Receptor Regulates the Development of Dopaminergic Neurons via Extracellular Signal-Regulated Kinase and Nurr1 Activation. The Journal of Neuroscience, 26(17), 4567–4576. https://doi.org/10.1523/JNEUROSCI.5236-05.2006 Kim, T. E., Seo, J. S., Yang, J. W., Kim, M. W., Kausar, R., Joe, E., Kim, B. Y., & Lee, M. A. (2013). Nurr1 Represses Tyrosine Hydroxylase Expression via SIRT1 in Human Neural Stem Cells. PLoS ONE, 8(8), e71469. https://doi.org/10.1371/journal.pone.0071469 Kitazawa, M., Anantharam, V., & Kanthasamy, A. G. (2001). Dieldrin-induced oxidative stress and neurochemical changes contribute to apoptopic cell death in dopaminergic cells. Free Radical Biology and Medicine, 31(11), 1473–1485. https://doi.org/10.1016/S0891-5849(01)00726-2 Kitazawa, M., Anantharam, V., & Kanthasamy, A. G. (2003). Dieldrin induces apoptosis by promoting caspase-3-dependent proteolytic cleavage of protein kinase Cδ in dopaminergic cells: Relevance to oxidative stress and dopaminergic degeneration. Neuroscience, 119(4), 945–964. https://doi.org/10.1016/S0306-4522(03)00226-4 Kochmanski, J., Vanoeveren, S. E., & Bernstein, A. I. (2019). Developmental Dieldrin Exposure Alters DNA Methylation at Genes Related to Dopaminergic Neuron Development and Parkinson’s Disease in Mouse Midbrain. Toxicol Sci., 169(2), 593– 607. https://doi.org/10.1093/toxsci/kfz069 Krug, A. K., Gutbier, S., Zhao, L., Pöltl, D., Kullmann, C., Ivanova, V., Förster, S., Jagtap, S., Meiser, J., Leparc, G., Schildknecht, S., Adam, M., Hiller, K., Farhan, H., Brunner, T., Hartung, T., Sachinidis, A., & Leist, M. (2014). Transcriptional and metabolic adaptation of human neurons to the mitochondrial toxicant MPP(+). Cell Death & Disease, 5(5), e1222. https://doi.org/10.1038/cddis.2014.166 Le Couteur, D., McLean, A., Taylor, M., Woodham, B., & Board, P. (1999). Pesticides and Parkinson’s disease. Biomed Pharmacother., 53(3), 122–130. https://doi.org/10.1016/S0753-3322(99)80077-8 Le, W., Conneely, O. M., Zou, L., He, Y., Saucedo-Cardenas, O., Jankovic, J., Mosier, D. R., & Appel, S. H. (1999). Selective Agenesis of Mesencephalic Dopaminergic Neurons in Nurr1-Deficient Mice. Experimental Neurology, 159(2), 451–458. https://doi.org/10.1006/exnr.1999.7191 237 Le, W., Xu, P., Jankovic, J., Jiang, H., Appel, S. H., Smith, R. G., & Vassilatis, D. K. (2003). Mutations in NR4A2 associated with familial Parkinson disease. Nature Genetics, 33(1), 85–89. https://doi.org/10.1038/ng1066 Leite, P. E. C., Pereira, M. R., Harris, G., Pamies, D., Dos Santos, L. M. G., Granjeiro, J. M., Hogberg, H. T., Hartung, T., & Smirnova, L. (2019). Suitability of 3D human brain spheroid models to distinguish toxic effects of gold and poly-lactic acid nanoparticles to assess biocompatibility for brain drug delivery. Particle and Fibre Toxicology, 16(1), 1– 20. https://doi.org/10.1186/s12989-019-0307-3 Lotharius, J., Barg, S., Wiekop, P., Lundberg, C., Raymon, H. K., & Brundin, P. (2002). Effect of mutant alpha-synuclein on dopamine homeostasis in a new human mesencephalic cell line. The Journal of Biological Chemistry, 277(41), 38884–38894. https://doi.org/10.1074/jbc.M205518200 Lotharius, J., Falsig, J., Van Beek, J., Payne, S., Dringen, R., Brundin, P., & Leist, M. (2005). Progressive degeneration of human mesencephalic neuron-derived cells triggered by dopamine-dependent oxidative stress is dependent on the mixed-lineage kinase pathway. Journal of Neuroscience, 25(27), 6329–6342. https://doi.org/10.1523/JNEUROSCI.1746-05.2005 Luo, Y. (2012). The function and mechanisms of Nurr1 action in midbrain dopaminergic neurons, from development and maintenance to survival. International Review of Neurobiology, 102, 1–22. https://doi.org/10.1016/B978-0-12-386986-9.00001-6 Martínez, A., & Soriano, E. (2005). Functions of ephrin/Eph interactions in the development of the nervous system: emphasis on the hippocampal system. Brain Research. Brain Research Reviews, 49(2), 211–226. https://doi.org/10.1016/j.brainresrev.2005.02.001 Meijer, S. N., Halsall, C. J., Harner, T., Peters, A. J., Ockenden, W. A., Johnston, A. E., & Jones, K. C. (2001). Organochlorine pesticide residues in archived UK soil. Environmental Science & Technology, 35(10), 1989–1995. https://doi.org/10.1021/es0000955 Michelhaugh, S. K., Vaitkevicius, H., Wang, J., Bouhamdan, M., Krieg, A. R., Walker, J. L., Mendiratta, V., & Bannon, M. J. (2005). Dopamine neurons express multiple isoforms of the nuclear receptor nurr1 with diminished transcriptional activity. Journal of Neurochemistry, 95(5), 1342–1350. https://doi.org/10.1111/j.1471-4159.2005.03458.x Miller, G. W., Gainetdinov, R. R., Levey, A. I., & Caron, M. G. (1999). Dopamine transporters and neuronal injury. Trends in Pharmacological Sciences, 20(10), 424–429. https://doi.org/10.1016/S0165-6147(99)01379-6 Moore, R., & Zigmond, M. (1994). Compensatory mechanisms in central neurodegenerative disease. Neurodegenerative Diseases, 355–369. 238 Moretto, A., & Colosio, C. (2011). Biochemical and toxicological evidence of neurological effects of pesticides: The example of Parkinson’s disease. In NeuroToxicology (Vol. 32, Issue 4, pp. 383–391). https://doi.org/10.1016/j.neuro.2011.03.004 Nicolai, M. M., Witt, B., Friese, S., Michaelis, V., Hölz-Armstrong, L., Martin, M., Ebert, F., Schwerdtle, T., & Bornhorst, J. (2022). Mechanistic studies on the adverse effects of manganese overexposure in differentiated LUHMES cells. Food and Chemical Toxicology, 161, 112822. https://doi.org/10.1016/j.fct.2022.112822 Noelker, C., Lu, L., Höllerhage, M., Vulinovic, F., Sturn, A., Roscher, R., Höglinger, G. U., Hirsch, E. C., Oertel, W. H., Alvarez-Fischer, D., & Andreas, H. (2015). Glucocerebrosidase deficiency and mitochondrial impairment in experimental Parkinson disease. Journal of the Neurological Sciences, 356(1–2), 129–136. https://doi.org/10.1016/j.jns.2015.06.030 Oliveira, L. M. A., Falomir-Lockhart, L. J., Botelho, M. G., Lin, K.-H., Wales, P., Koch, J. C., Gerhardt, E., Taschenberger, H., Outeiro, T. F., Lingor, P., Schüle, B., Arndt-Jovin, D. J., & Jovin, T. M. (2015). Elevated α-synuclein caused by SNCA gene triplication impairs neuronal differentiation and maturation in Parkinson’s patient-derived induced pluripotent stem cells. Cell Death & Disease, 6(11), e1994. https://doi.org/10.1038/cddis.2015.318 Passante, L., Gaspard, N., Degraeve, M., Frisén, J., Kullander, K., De Maertelaer, V., & Vanderhaeghen, P. (2008). Temporal regulation of ephrin/Eph signalling is required for the spatial patterning of the mammalian striatum. Development, 135(19), 3281–3290. https://doi.org/10.1242/dev.024778 Pierce, S. E., Tyson, T., Booms, A., Prahl, J., & Coetzee, G. A. (2018). Parkinson’s disease genetic risk in a midbrain neuronal cell line. Neurobiology of Disease, 114, 53– 64. https://doi.org/10.1016/j.nbd.2018.02.007 Pöltl, D., Schildknecht, S., Karreman, C., & Leist, M. (2012). Uncoupling of ATP- depletion and cell death in human dopaminergic neurons. Neurotoxicology, 33(4), 769– 779. https://doi.org/10.1016/j.neuro.2011.12.007 Priyadarshi, A., Khuder, S., Schaub, E., & Shirvastava, S. (2000). A meta-analysis of Parkinson’s disease and exposure to pesticides. Neurotoxicology, 21(4), 435–440. Richardson, J. R., Caudle, W. M., Wang, M., Dean, E. D., Pennell, K. D., Miller, G. W., Richardson, J. R., Caudle, W. M., Wang, M., Dean, E. D., Pennell, K. D., & Miller, G. W. (2006). Developmental exposure to the pesticide dieldrin alters the dopamine system and increases neurotoxicity in an animal model of Parkinson’s disease. The FASEB Journal, 20(10), 1695–1697. https://doi.org/10.1096/fj.06-5864fje Ritz, B., & Yu, F. (2000). Parkinson’s disease mortality and pesticide exposure in California 1984–1994. Int. J. Epidemiol., 29(3), 323–329. https://doi.org/10.1093/ije/29.2.323 239 Rodríguez-Traver, E., Solís, O., Díaz-Guerra, E., Ortiz, Ó., Vergaño-Vera, E., Méndez- Gómez, H. R., García-Sanz, P., Moratalla, R., & Vicario-Abejón, C. (2016). Role of Nurr1 in the Generation and Differentiation of Dopaminergic Neurons from Stem Cells. Neurotoxicity Research, 30(1), 14–31. https://doi.org/10.1007/s12640-015-9586-0 Rusiecki, J. A., Baccarelli, A., Bollati, V., Tarantini, L., Moore, L. E., & Bonefeld- Jorgensen, E. C. (2008). Global DNA hypomethylation is associated with high serum- persistent organic pollutants in Greenlandic Inuit. Environmental Health Perspectives, 116(11), 1547–1552. https://doi.org/10.1289/ehp.11338 Sakurada, K., Ohshima-Sakurada, M., Palmer, T. D., & Gage, F. H. (1999). Nurr1, an orphan nuclear receptor, is a transcriptional activator of endogenous tyrosine hydroxylase in neural progenitor cells derived from the adult brain. Development, 126(18), 4017–4026. https://doi.org/10.1242/dev.126.18.4017 Sanchez-Ramos, J., Facca, A., Basit, A., & Song, S. (1998). Toxicity of dieldrin for dopaminergic neurons in mesencephalic cultures. Experimental Neurology, 150(2), 263–271. https://doi.org/10.1006/exnr.1997.6770 Schildknecht, S., Karreman, C., Pöltl, D., Efrémova, L., Kullmann, C., Gutbier, S., Krug, A., Scholz, D., Gerding, H. R., & Leist, M. (2013). Generation of genetically-modified human differentiated cells for toxicological tests and the study of neurodegenerative diseases. ALTEX, 30(4), 427–444. https://doi.org/10.14573/altex.2013.4.427 Scholz, D., Pöltl, D., Genewsky, A., Weng, M., Waldmann, T., Schildknecht, S., & Leist, M. (2011). Rapid, complete and large-scale generation of post-mitotic neurons from the human LUHMES cell line. Journal of Neurochemistry, 119(5), 957–971. https://doi.org/10.1111/j.1471-4159.2011.07255.x Semchuk, K. M., Love, E. J., & Lee, R. G. (1992). Parkinson’s disease and exposure to agricultural work and pesticide chemicals. Neurology, 42, 1328–1335. https://doi.org/10.1212/wnl.42.7.1328 Simón, A. M., de Maturana, R. L., Ricobaraza, A., Escribano, L., Schiapparelli, L., Cuadrado-Tejedor, M., Pérez-Mediavilla, A., Avila, J., Del Río, J., & Frechilla, D. (2009). Early changes in hippocampal Eph receptors precede the onset of memory decline in mouse models of Alzheimer’s disease. Journal of Alzheimer’s Disease : JAD, 17(4), 773–786. https://doi.org/10.3233/JAD-2009-1096 Smirnova, L., Harris, G., Delp, J., Valadares, M., Pamies, D., Hogberg, H. T., Waldmann, T., Leist, M., & Hartung, T. (2016). A LUHMES 3D dopaminergic neuronal model for neurotoxicity testing allowing long-term exposure and cellular resilience analysis. Archives of Toxicology, 90(11), 2725–2743. https://doi.org/10.1007/s00204- 015-1637-z Smits, S. M., Ponnio, T., Conneely, O. M., Burbach, J. P. H., & Smidt, M. P. (2003). Involvement of Nurr1 in specifying the neurotransmitter identity of ventral midbrain 240 dopaminergic neurons. The European Journal of Neuroscience, 18(7), 1731–1738. https://doi.org/10.1046/j.1460-9568.2003.02885.x Song, C., Kanthasamy, A., Anantharam, V., Sun, F., & Kanthasamy, A. G. (2010). Environmental neurotoxic pesticide increases histone acetylation to promote apoptosis in dopaminergic neuronal cells: relevance to epigenetic mechanisms of neurodegeneration. Molecular Pharmacology, 77(4), 621–632. https://doi.org/10.1124/mol.109.062174 Steenland, K., Hein, M. J., Cassinelli, R. T., Prince, M. M., Nilsen, N. B., Whelan, E. A., Waters, M. A., Ruder, A. M., & Schnorr, T. M. (2006). Polychlorinated biphenyls and neurodegenerative disease mortality in an occupational cohort. Epidemiology, 17(1), 8– 13. https://doi.org/10.1097/01.ede.0000190707.51536.2b Sulzer, D., Cragg, S. J., & Rice, M. E. (2016). Striatal dopamine neurotransmission: Regulation of release and uptake. In Basal Ganglia (Vol. 6, Issue 3, pp. 123–148). Elsevier GmbH. https://doi.org/10.1016/j.baga.2016.02.001 Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., Kuhn, M., Bork, P., Jensen, L. J., & von Mering, C. (2015). STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Research, 43(Database issue), D447-52. https://doi.org/10.1093/nar/gku1003 Szklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N. T., Roth, A., Bork, P., Jensen, L. J., & von Mering, C. (2017). The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Research, 45(D1), D362–D368. https://doi.org/10.1093/nar/gkw937 Takasu, M. A., Dalva, M. B., Zigmond, R. E., & Greenberg, M. E. (2002). Modulation of NMDA receptor-dependent calcium influx and gene expression through EphB receptors. Science (New York, N.Y.), 295(5554), 491–495. https://doi.org/10.1126/science.1065983 Tanner, C. M., & Aston, D. A. (2000). Epidemiology of Parkinson’s disease and akinetic syndromes. Current Opinion in Neurology, 13, 427–430. https://doi.org/10.1097/00019052-200008000-00010 Tanner, C. M., & Langston, J. W. (1990). Do environmental toxins cause Parkinson’s disease? A critical review. Neurology, 40(10), 17–30. Tong, Z. Bin, Hogberg, H., Kuo, D., Sakamuru, S., Xia, M., Smirnova, L., Hartung, T., & Gerhold, D. (2017). Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening. Journal of Applied Toxicology, 37(2), 167–180. https://doi.org/10.1002/jat.3334 241 Toro Cabrera, G., & Mueller, C. (2016). Design of shRNA and miRNA for Delivery to the CNS. Methods in Molecular Biology (Clifton, N.J.), 1382, 67–80. https://doi.org/10.1007/978-1-4939-3271-9_5 Weisskopf, M., Knekt, P., O’Reilly, E., Lyytinen, J., Reunanen, A., Laden, F., Altshul, L., & Ascherio, A. (2010). Persistent organochlorine pesticides in serum and risk of Parkinson disease. Neurology, 74(13), 1055–1061. https://doi.org/10.1212/WNL.0b013e3181d76a93 Wirdefeldt, K., Adami, H. O., Cole, P., Trichopoulos, D., & Mandel, J. (2011). Epidemiology and etiology of Parkinson’s disease: A review of the evidence. In European Journal of Epidemiology (Vol. 26, Issue SUPPL. 1). https://doi.org/10.1007/s10654-011-9581-6 Xiao, D., Miller, G. M., Jassen, A., Westmoreland, S. V., Pauley, D., & Madras, B. K. (2006). Ephrin/Eph receptor expression in brain of adult nonhuman primates: Implications for neuroadaptation. Brain Research, 1067(1), 67–77. https://doi.org/10.1016/j.brainres.2005.10.073 Yang, J. S., Wei, H. X., Chen, P. P., & Wu, G. (2018). Roles of Eph/ephrin bidirectional signaling in central nervous system injury and recovery (Review). Experimental and Therapeutic Medicine, 15(3), 2219–2227. https://doi.org/10.3892/etm.2018.5702 Yue, Y., Widmer, D. A. J., Halladay, A. K., Cerretti, D. P., Wagner, G. C., Dreyer, J.-L., & Zhou, R. (1999). Specification of Distinct Dopaminergic Neural Pathways: Roles of the Eph Family Receptor EphB1 and Ligand Ephrin-B2. The Journal of Neuroscience, 19(6), 2090–2101. https://doi.org/10.1523/JNEUROSCI.19-06-02090.1999 Zetterström, R. H., Solomin, L., Jansson, L., Hoffer, B. J., Olson, L., & Perlmann, T. (1997). Dopamine Neuron Agenesis in Nurr1-Deficient Mice. Science, 276(5310), 248– 250. https://doi.org/10.1126/science.276.5310.248 Zhang, X. M., Yin, M., & Zhang, M. H. (2014). Cell-based assays for Parkinson’s disease using differentiated human LUHMES cells. Acta Pharmacologica Sinica, 35(7), 945–956. https://doi.org/10.1038/aps.2014.36 Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O’Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., Deng, S., Liddelow, S. A., Zhang, C., Daneman, R., Maniatis, T., Barres, B. A., & Wu, J. Q. (2014). An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 34(36), 11929–11947. https://doi.org/10.1523/JNEUROSCI.1860- 14.2014 Zigmond, M., Castro, S., Keefe, K., Abercrombie, E., & Sved, A. (1998). Role of excitatory amino acids in the regulation of dopamine synthesis and release in the neostriatum. Amino Acids, 14(1–3), 57–62. https://doi.org/10.1007/BF01345243 242 Chapter 5: Conclusions 243 Overview Epidemiological studies have consistently shown an association between increased risk of Parkinson’s disease (PD) and exposure to environmental factors, such as heavy metals, solvents, and pesticide exposures, including the organochlorine pesticide dieldrin (Brown et al., 2006; Cicchetti et al., 2009; Corrigan et al., 1998, 2000; de Lau & Breteler, 2006; De Miranda et al., 2022; Dorsey et al., 2018; Elbaz et al., 2009; S. M. Fleming, 2017; Freire & Koifman, 2012; Hatcher et al., 2008; Moretto & Colosio, 2011; Semchuk et al., 1992a; Steenland et al., 2006; Tanner et al., 2011; Tanner & Aston, 2000). Additional research in post-mortem, animal models, and in vitro systems shows a link between dieldrin exposure and increased susceptibility of DAergic (DAergic) neurons (Ascherio et al., 2006; Brown et al., 2006; Caudle et al., 2012; Elbaz et al., 2009; L. Fleming et al., 1994; Freire & Koifman, 2012; Gezer et al., 2020; Hatcher et al., 2007; Kanthasamy et al., 2005; Le Couteur et al., 1999; Moretto & Colosio, 2011; Priyadarshi et al., 2000, 2001; Richardson et al., 2006; Ritz & Yu, 2000; Semchuk et al., 1992b, 1992a; Steenland et al., 2006; Tanner et al., 2011; Tanner & Aston, 2000; Tanner & Langston, 1990; Weisskopf et al., 2010; Wirdefeldt et al., 2011). Despite this body of work, specific mechanisms underlying this association are not well understood. Previous work in mice has established two-hit models demonstrating that developmental exposure to dieldrin induces alterations in developing DAergic neurons and a male-specific increase in susceptibility in PD models, including the DAergic toxicant, MPTP, and the α-synuclein (α-syn) pre-formed fibril (PFF) model (Gezer et al., 2020; Richardson et al., 2006). We have demonstrated that this exposure causes persistent sex-specific changes in epigenetic mechanisms, and dysregulation of genes 244 important for dopamine neuron development and maintenance in the substantia nigra and for the neuroinflammatory system in the striatum (Kochmanski et al. 2019; Gezer et al. 2020). These early changes may prime the synapse for heightened sensitivity later in life. This idea can be described by the term silent neurotoxicity, where the effects of early life exposures are unmasked by challenges later in life, the cumulative effects of exposures over the lifespan, or the effects of aging (Cory-Slechta et al. 2005; Kraft et al. 2016). In this study, we expand on existing data using our previously established in vivo developmental dieldrin/PFF two-hit exposure model (Chapter 2) and an in vitro 3D neurosphere model (Chapters 3 and 4) to elucidate mechanisms by which developmental dieldrin exposure results in exacerbated toxicity later in life. Developmental dieldrin exposure primes the nigrostriatal system for an exacerbated response to synucleinopathy The results reported in Chapter 2 show that there are functional differences in dopamine neurotransmission at nigrostriatal synapses in male mice developmentally exposed to dieldrin after PFF injection. Specifically, our results demonstrate that there is increased striatal dopamine (DA) release in response to PFF-induced striatal DA loss in dieldrin- exposed mice 4 months after PFF injection (Figure 2.6). In previous work, there was a dieldrin-associated exacerbation of PFF-induced deficits in motor behavior and an increase in striatal DA turnover at 6 months post-injection, but no change in the degree of nigral α-syn pathology (1 and 2 months), degeneration of nigral DA neurons (6 months), or loss of striatal DA (2 and 6 months) (Gezer et al., 2020; Luk et al., 2012). In this study, we did not observe any effect of dieldrin or PFF alone on DA release (Figure 245 2.4). Taken together, dieldrin exposure appears to cause changes in the striatal synaptic terminals that prime the nigrostriatal system for an exacerbated response to synucleinopathy. This effect is associated with striatal DA loss, early enhanced DA release, and greater long-term increases in DA turnover and cytosolic DA. These lead to increased oxidative stress, and acceleration of the toxic interplay between dysregulated α-syn and DA (Gezer et al., 2020; Luk et al., 2012). Although there is a reduction in total DA content by 2 months post-PFF injection, here we showed dieldrin-induced increases in striatal evoked DA release upon stimulation using FSCV in PFF-injected mice at 4 months post-PFF injection (Chapter 2). This increase in evoked DA release, despite loss in total striatal DA connect, is consistent with an extensive body of literature on compensatory mechanisms that occur early in human PD, multiple animal models of DA deficits, and most recently in a model of depletion of a related monoamine, norepinephrine (Zigmond et al. 1984; Onn et al. 1986; Zhang et al. 1988; Snyder. GL et al. 1990; Zigmond et al. 1993; Zigmond 1994; Bezard and Gross 1997; Zigmond 1997; Zigmond et al. 1998; Molina-Mateo et al. 2017; Iannitelli et al. 2023).This new work provides further support for the hypothesis that developmental dieldrin exposure induces changes in the nigrostriatal striatal DAergic system that primes it to have an exacerbated response to synucleinopathy induced by α-syn PFFs in male offspring, despite the absence of observable changes in typical markers of nigrostriatal dysfunction and degeneration (Figure 5.1). Taken together, these results highlight the importance of exploring dieldrin-induced changes that produce this high susceptibility state in advancing our understanding of how exposures contribute to increased risk of PD. 246 Based on our results, future studies should explore the following questions: • What specific compensatory mechanisms underlie the increase in dopamine in developmental dieldrin-exposed PFF-injected animals? Figure 5.1. Developmental dieldrin exposure induces early synaptic changes later exacerbating PFF-induced toxicity and motor deficits. Made in BioRender. o Are glutamatergic and serotonergic signaling altered in dieldrin-exposed animals? Studies of DA degeneration show that glutamatergic and serotonergic innervation on striatal neurons is upregulated (Slotkin & Seidler, 2009). Glutamatergic receptors including NMDA receptors negatively regulate DA synthesis and release in the SN (Bustos et al., 2004; Moore & Zigmond, 1994; Zigmond, 1994). Dieldrin exposure in vitro was shown to increase NMDA and AMPA subunit expression. Since NMDA and AMPA receptors mediate glutamatergic signaling and are involved in the process of excitotoxicity, it may be important to determine if these 247 glutamatergic signaling pathways underly the exacerbation of dieldrin- induced increases in DA release in PFF injected animals (Dong et al., 2009). o Is calcium homeostasis affected by dieldrin? Since calcium homeostasis is an important regulator in neurotransmitter release (Ambrosi et al., 2014; Dong et al., 2009; Post et al., 2018). Dieldrin exposure can alter Ca2+ signaling by regulating expression of Ca2+ ATPase activity resulting in impaired Ca2+ metabolism and signaling (Mehrotra et al., 1988, 1989). Ca2+ regulation is important in preventing excitotoxicity and downstream effects including activation of apoptotic factors, cytochrome C production, reactive oxygen species formation, and effects on the mitochondria (Ambrosi et al., 2014; Post et al., 2018). In PD, voltage-gated L-type Ca2+ channels (Cav) are affected. Specifically, Cav1 channel is reduced and Cav1.3 is increased in surviving neurons. This increase in Cav1.3 expression is thought to play an important role in facilitating excitotoxicity and related degeneration in PD (Post et al., 2018). • Are there alterations in synaptic vesicle pools and trafficking in developmental dieldrin-exposed PFF-injected animals? Studies in different α-syn models indicate a critical role for a-syn in DA release, synaptic vesicle fusion, vesicle trafficking, and regulation of synaptic vesicle pool size (Abeliovich et al., 2000; Bellani et al., 2010; Cheng et al., 2011; Dagra et al., 2021; Ingelsson, 2016; Murphy et al., 2000; Volles et al., 2001; Xilouri et al., 2013). It is also known that most striatal DA synapses are silent, and the majority of synaptic vesicles are 248 located within the reserve pool rather than the readily releasable pool as discussed in Chapter 2 (Goldstein, 2012, 2013, 2021; Sulzer et al., 2016; Trudeau et al., 2014). Additionally, within the striatum of PFF-injected animals, we expect that only one-third to one-half of DA terminals are affected. Together, this leaves a pool of both surviving neurons and vesicles within affected neurons to maintain DA release. Therefore, there may be decreases in the reserve pool of synaptic vesicles or changes in vesicular trafficking dynamics that we were unable to capture in previous experiments. Failure to recapitulate the dieldrin/PFF two-hit model using in vitro 3D neurospheres model Methods for studying developmental neurotoxicity (DNT) in vitro remain limited making it difficult to screen potential toxicants or investigate mechanisms of action involved in DNT. Therefore, the overall goal of the work reported in Chapters 3 and 4 of this dissertation was to develop an in vitro two-hit system to parallel our in vivo model. The purpose of Chapter 3 was to adapt the α-syn-PFF model to 3D neurospheres. Although we were able to replicate previous work and induce a DAergic-like phenotype in neurospheres formed using the human cell lines, LUHMES, the enhanced differentiation and spheroid formation protocol implemented for SH-SY5Y neurospheres did induce a DAergic-like phenotype. While this protocol increased TH expression in these cells, differentiated SH-SY5Y cells were not post-mitotic and did not express detectable levels of DAT, limiting their utility for our studies. We also confirmed that LUHMES neurospheres are susceptible to MPP+, but SH-SH5Y neurospheres differentiated with this method do not express DAT and are not susceptible to MPP+. Finally, we were 249 unable to adapt the α-syn PFF model in either LUHMES or SH-SY5Y neurospheres. We observed a concentration-dependent increase in detergent-insoluble α-synuclein after PFF application, but no toxicity was observed (Figure 3.6). Based on these results, in Chapter 4, we aimed to recapitulate the two-hit system in vitro system using the MPP+ model in LUHMES neurospheres to study the role of specific genes of interest in PD- related DAergic toxicity. Linking the role of developmental dieldrin-induced differentially modified candidate genes and the exacerbation of Parkinsonian toxicity Developmental dieldrin exposure induces a poised epigenetic state early in life that mediates susceptibility to Parkinsonian toxicity in adulthood. Previous work has identified that developmental dieldrin exposure induces sex-specific differential methylation and protein-coding transcript expression in the mouse midbrain (Kochmanski et al., 2019). Specifically, 288 genes with female-specific differential methylation and 83 genes with male-specific differential methylation were identified. The list of genes was filtered based on confirmation of expression in neurons from the Brain RNAseq database, midbrain expression based on midbrain RNAseq data from Kochmanski et al., and expression in undifferentiated LUHMES cells from Pierce et al. (Kochmanski et al., 2019; Pierce et al., 2018; Zhang et al., 2016). Further selection was based on differential expression in our previous developmental dieldrin exposure study, network analysis via StringDB, and prior knowledge of gene function (Kochmanski et al., 2019). Based on these criteria, the nuclear receptor-related -1 (NR4A2) and the ephrin receptor B2 (EPHB2) were selected as candidate genes of interest for follow-up studies. 250 Figure 5.2 Environmental factors modify the epigenome, leading to changes in the regulation of gene expression and altered susceptibility to future insults. Made in BioRender. In this project, the differential expression of these candidate genes during development was modeled by modifying the expression of candidate genes in proliferating LUHMES cells before induction of DAergic differentiation. After differentiation, a second hit with 1- methyl-4-phenylpyridinium (MPP+), a DAergic toxicant and the active metabolite of MPTP, was used to parallel the in vivo two-hit models to assess whether each candidate gene mediates neuronal susceptibility to PD-related toxicity (Figure 5.2). NR4A2 NR4A2 encodes the nuclear receptor related-1 (NURR1) protein, a transcription factor critical for DAergic neuron maintenance and development (Decressac et al., 2013; J. Dong et al., 2016; Luo, 2012; Smits et al., 2003). Both clinical and experimental data demonstrate that dysregulation of Nurr1 function leads to DA neuron dysfunction and 251 that may contribute to the pathogenesis of PD (Decressac et al., 2013). In addition, compounds that activate Nurr1 protein and Nr4a2 gene therapy in preclinical rodent models can enhance DA neurotransmission and protect DA neurons from toxicant and microglia-mediated neuroinflammation (J. Dong et al., 2016). Data in rat midbrain, human midbrain, and the human neuroblastoma cell line, SK-N-AS, demonstrate that there are multiple Nurr1 splice variants expressed in these cells. These isoforms have variable ability to activate transcription of target genes including DAT and TH, suggesting that regulation of isoform-specific expression could be a critical regulatory mechanism in DA neurons (Michelhaugh et al., 2005). In our developmental dieldrin exposure study, we identified a female specific-hypermethylated site within an intron Nr4a2. This result makes epigenetic regulation of Nr4a2 by environmental toxicants potentially through differential isoform expression, a novel potential mechanism by which developmental exposure to dieldrin may alter PD susceptibility (Kochmanski et al., 2019). Since Nr4a2 there was a slight increase in expression of the protein-coding transcript in female animals, and the phenotype associated with dieldrin-induced exacerbation of PFF is specific to male mice, we expected that NR4A2 would be protective against toxicity. While we did not detect changes in expression in these changes, our data suggests there may be small transcript level changes that we were unable to detect and did not model here. Nevertheless, if there is an actual increase in expression in females, we would expect that knockdown of NR4A2 would increase susceptibility and overexpression would result in no change or a decrease in susceptibility to PD-related toxicity. 252 Modifying the expression of the candidate gene, NR4A2 during proliferation, affects the expression of DA markers after differentiation of neurospheres. It appears that NR4A2 knockdown upregulates DAergic markers and maintains a lower DAT: VMAT2 ratio (Kochmanski et al., 2019). Previous work has shown that this ratio of DAT:VMAT2 is an indicator of a neuron’s sensitivity to DAergic toxicity. A higher ratio would indicate an upregulation of DAT which would allow more DA uptake, but a lower expression of VMAT2 would result in less DA sequestering into synaptic vesicles resulting in increased cytosolic DA. Cytoslic DA is prone to autoxidation and enzymatic degradation forming toxic metabolites which can result in dopaminergic degeneration (Miller et al., 1999). NR4A2 knockdown maintained a reduced ratio of DAT:VMAT2 suggesting that we would see decreased susceptibility to DAergic toxicity. The DAT:VMAT2 ratio in NR4A2 overexpressing neurospheres was not significantly affected. However, neither modification of NR4A2 expression affected MPP+-induced toxicity. Therefore, altered NR4A2 expression during a differentiation modeled in vitro, alters the differentiation of DAergic neurons, and knocking down NR4A2 resulting in a decrease in a marker of susceptibility to toxicity as indicated by the ratio of DAT:VMAT2. Limitations and future directions are discussed below in conjunction with EPHB2 findings. EPHB2 EPHB2 encodes Ephrin type-B receptor 2 (EPHB2), a receptor tyrosine kinase that binds the receptor-binding domain of ephrin-B ligands; these proteins communicate across extracellular space allowing for cell-cell bidirectional signaling (Martínez & Soriano, 2005). Ephrins and the Eph receptors show dynamic expression patterns in the developing central nervous system (CNS) and are expressed in most adult CNS cell 253 types (Yang et al., 2018). The EPHB2 signaling pathway is involved in many developmental processes in the CNS, including migration of neural progenitors to the dentate gyrus, regulation of axon guidance, dendritic spine formation, glutamatergic synaptogenesis, and long-term potentiation (Catchpole & Henkemeyer, 2011; Flanagan & Vanderhaeghen, 1998; Henderson et al., 2001; Kayser et al., 2006; Takasu et al., 2002). We observed female-specific hypermethylation of Ephb2 and increased expression of a protein-coding transcript (Kochmanski et al., 2019). The phenotype and toxicity associated with dieldrin-induced exacerbation of PFFs was specific to male mice only, and because of the known reduced risk of PD in females, we expected that EPHB2 expression would serve as a protective gene against PD-related toxicity. Alterations of EPHB2 also modify the expression of DA markers and the indicator of DAergic vulnerability, the ratio of DAT: VMAT2 in neurospheres. EPHB2 overexpression significantly reduced TH and DAT expression, but increased VMAT2 resulting in a decreased ratio of DAT: VMAT2 which is thought to be a protective marker against DAergic toxicity (Miller et al., 1999). On the other hand, EPHB2 knockdown increased TH, but a reduction in DAT, VMAT2 levels, and an overall increase in DAT:VMAT2. Therefore, EPHB2 expression plays an important role in regulating DAergic differentiation. The previously observed-developmental-dieldrin-induced hypermethylation and increased expression of Ephb2 in female mice may serve as a protective factor by regulating DAergic development and maintaining a lower DAT: VMAT2 ratio. However, there were no observed alterations in MPP+-induced toxicity. 254 Alterations of the developmental dieldrin-induced differentially modified candidate genes during proliferation, NR4A2, and EPHB2 affect the DAergic phenotype and the ratio of DAT:VMAT2 of neurospheres following differentiation. This work is based on the hypothesis that these changes in DAergic gene expression modify susceptibility later in life. Although we showed observed changes in an established marker of susceptibility to DAergic toxicity (DAT:VMAT2), we were unable to recapitulate toxicity to the second hit of MPP+ in this in vitro system. Since NR4A2 and EPHB2 are two of hundreds of genes differentially modified by dieldrin exposure, likely, these genes are not the sole mediators of exacerbated Parkinsonian toxicity and may have only small effects on toxicity on their own that are not apparent in this simplified model (Kochmanski et al., 2019). Since MPP+ produces robust and rapid DAergic degeneration, it is possible that this model is too potent to observe the effects of these candidate genes on mitigating or exacerbating toxicity to MPP+. The gene modifications that were observed in vivo were sex-specific, and only male mice were susceptible to developmental dieldrin-induced exacerbations to PFFs while female mice did not show any changes in susceptibility indicating a potential role of sex-specific mechanisms (Gezer et al., 2020; Kochmanski et al., 2019). Specifically, the previous study showed that developmental dieldrin-induced sex-specific modifications of the expression of protein-coding transcripts for Ephb2 were transcript-specific, and there were no significant changes in Nr4a2 protein-coding transcript expression (Kochmanski et al., 2019). Since LUHMES cells are genetically female, we may not have been able to model this effect, depending on the sex-specific mechanism. However, there is not a comparable cell system derived from genetically males. In the previous study, there 255 were observed differential methylation patterns on these candidate genes in vivo. However, here we modified the expression of the full length of these genes as a proxy for the changes observed in vivo. Based on these findings, future projects should address the following: • What are the effects of modifying these genes in vivo? The ratio of DAT to VMAT2 is an indicator of susceptibility to DAergic toxicity. This ratio was used as a predictor of susceptibility in in vivo models using MPTP (Miller et al., 1999). However, the implications of this ratio have not yet been extended to in vitro models. Although we observed significant changes in the ratio of DAT: VMAT2 with NR4A2 and EPHB2 expression modification, there was no observed effect on MPP+-induced toxicity. Therefore, this ratio may only serve as a predictor of vulnerability in more complex models that include other cell populations. Therefore, these modifications to candidate genes should be extended to more complex models to recapitulate the effects observed in vivo. o In addition to the DAT: VMAT2 ratio, these gene modifications altered the DAergic phenotype in differentiated LUHMES cells. The effects of these gene modifications on DA release and DA mishandling should be followed up on in vivo. • Are more functional measures like network activity, firing rate, and measures of synchrony more sensitive to measuring the effects of differential gene modification on disease susceptibility? In new approach methodologies, a battery of assays is often used to screen for toxicity. In a high-throughput screen of compounds on neurodevelopmental toxicity, it was found that network activity 256 was the most sensitive assay in 2D adherent in vitro models in comparison to assays that we have used here like neurite outgrowth and ATP assays (Carstens et al., 2022). Therefore, more sensitive measures in neuronal functioning should be used to address other ways in which these genes may mediate toxic responses rather than hypothesizing that these genes affect overt toxicity to MPP+. o Does modifying NR4A2 and EPHB2 alter other functions involving the mitochondria? DAergic neurons are particularly sensitive to mitochondrial damage, and oxidative stress, and have low antioxidant capacity which can result in DAergic dysfunction (Haddad & Nakamura, 2015). Oxidative stress and DAergic dysfunction precede DAergic degeneration. Therefore, it is possible that these developmental dieldrin-induced differentially modified genes play a role in these early mitochondria alterations and DAergic dysfunction, but do not overtly affect ATP and neurite loss. Concluding Remarks Overall, this project has expanded our understanding of the link between developmental dieldrin exposure and PD risk. Consistent with previous literature, this work has demonstrated that developmental dieldrin exposure results in alterations in the dopamine system which contributes to an exacerbated susceptibility to PD. Furthermore, work was completed to optimize and develop methods to screen candidate genes or other toxicants in PD-related toxicity using a DAergic-like neurosphere model. Using this model, two candidate genes with developmental dieldrin exposure-induced modifications were screened for their effects on PD-like toxicity. 257 Using this model, it was demonstrated that altering these genes during differentiation alters the DAergic phenotype and markers of DAergic mishandling (Figure 5.3). In conclusion, this work has investigated the hypothesis that developmental exposures lead to persistent epigenetic changes in the regulation of gene expression that can result in alterations in DAergic function and increased disease susceptibility later in life. Since environmental factors play a significant role in PD, and developmental periods are specifically vulnerable to such factors, we must continue to study and identify the link between developmental exposures and disease development later in life. Figure 5.3. A model of developmental dieldrin exposure and exacerbated vulnerability to Parkinson’s disease. Developmental exposures to dieldrin can alter developing dopaminergic neurons which can result in associated changes in gene modifications which induces alteration in stiratal synapse function. With a second hit such as PFFs, this dopaminergic dysfunction is further exacerbated and unmasked resulting in detectable motor deficits. Made in BioRender. 258 REFERENCES Abeliovich, A., Schmitz, Y., Fariñ, I., Choi-Lundberg, D., Ho, W.-H., Castillo, P. E., Shinsky, N., Manuel, J., Verdugo, G., Armanini, M., Ryan, A., Hynes, M., & Phillips, H. (2000). Mice Lacking a-Synuclein Display Functional Deficits in the Nigrostriatal Dopamine System. Neuron, 25, 239–252. https://doi.org/10.1016/s0896- 6273(00)80886-7. Ambrosi, G., Cerri, S., & Blandini, F. (2014). A further update on the role of excitotoxicity in the pathogenesis of Parkinson’s disease. Journal of Neural Transmission, 121(8), 849–859. https://doi.org/10.1007/s00702-013-1149-z Ascherio, A., Chen, H., Weisskopf, M. G., O’Reilly, E., McCullough, M. L., Calle, E. E., Schwarzschild, M. A., & Thun, M. J. (2006). Pesticide exposure and risk for Parkinson’s disease. Annals of Neurology, 60(2), 197–203. https://doi.org/10.1002/ana.20904 Bellani, S., Sousa, V. L., Ronzitti, G., Valtorta, F., Meldolesi, J., & Chieregatti, E. (2010). The regulation of synaptic function by α-synuclein. Communicative and Integrative Biology, 3(2), 106–109. https://doi.org/10.4161/cib.3.2.10964 Brown, T. P., Rumsby, P. C., Capleton, A. C., Rushton, L., & Levy, L. S. (2006). Pesticides and Parkinson’s disease - Is there a link? In Environmental Health Perspectives (Vol. 114, Issue 2, pp. 156–164). https://doi.org/10.1289/ehp.8095 Bustos, G., Abarca, J., Campusano, J., Bustos, V., Noriega, V., & Aliaga, E. (2004). Functional interactions between somatodendritic dopamine release, glutamate receptors and brain-derived neurotrophic factor expression in mesencephalic structures of the brain. Brain Research Reviews, 47(1–3), 126–144. https://doi.org/10.1016/j.brainresrev.2004.05.002 Carstens, K. E., Carpenter, A. F., Martin, M. M., Harrill, J. A., Shafer, T. J., & Paul Friedman, K. (2022). Integrating Data from in Vitro New Approach Methodologies for Developmental Neurotoxicity. Toxicological Sciences, 187(1), 62–79. https://doi.org/10.1093/toxsci/kfac018 Catchpole, T., & Henkemeyer, M. (2011). EphB2 tyrosine kinase-dependent forward signaling in migration of neuronal progenitors that populate and form a distinct region of the dentate niche. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 31(32), 11472–11483. https://doi.org/10.1523/JNEUROSCI.6349- 10.2011 Caudle, W. M., Guillot, T. S., Lazo, C. R., & Miller, G. W. (2012). Industrial toxicants and Parkinson’s disease. NeuroToxicology, 33(2), 178–188. https://doi.org/10.1016/j.neuro.2012.01.010 Cheng, F., Vivacqua, G., & Yu, S. (2011). The role of alpha-synuclein in neurotransmission and synaptic plasticity. Journal of Chemical Neuroanatomy, 42(4), 242–248. https://doi.org/10.1016/j.jchemneu.2010.12.001 259 Cicchetti, F., Drouin-Ouellet, J., & Gross, R. E. (2009). Environmental toxins and Parkinson’s disease: what have we learned from pesticide-induced animal models? In Trends in Pharmacological Sciences (Vol. 30, Issue 9, pp. 475–483). https://doi.org/10.1016/j.tips.2009.06.005 Corrigan, F. M., Lochgilphead, C. L., Shore, R. F., Daniel, S. E., & Mann, D. (2000). Organochlorine insecticides in substantia nigra in parkinson’s disease. Journal of Toxicology and Environmental Health - Part A, 59(4), 229–234. https://doi.org/10.1080/009841000156907 Corrigan, F. M., Murray, L., Wyatt, C. L., & Shore, R. F. (1998). Diorthosubstituted Polychlorinated Biphenyls in Caudate Nucleus in Parkinson’s Disease. Experimental Neurology, 150(2), 339–342. https://doi.org/10.1006/exnr.1998.6776 Dagra, A., Miller, D. R., Lin, M., Gopinath, A., Shaerzadeh, F., Harris, S., Sorrentino, Z. A., Støier, J. F., Velasco, S., Azar, J., Alonge, A. R., Lebowitz, J. J., Ulm, B., Bu, M., Hansen, C. A., Urs, N., Giasson, B. I., & Khoshbouei, H. (2021). α-Synuclein-induced dysregulation of neuronal activity contributes to murine dopamine neuron vulnerability. Npj Parkinson’s Disease, 7(1). https://doi.org/10.1038/s41531-021-00210-w de Lau, L. M., & Breteler, M. M. B. (2006). Epidemiology of Parkinson’s disease. Lancet Neurol, 5(6), 525–535. https://doi.org/10.1016/S1474-4422(06)70471-9 De Miranda, B. R., Goldman, S. M., Miller, G. W., Greenamyre, J. T., & Dorsey, E. R. (2022). Preventing Parkinson’s Disease: An Environmental Agenda. Journal of Parkinson’s Disease, 12(1), 45–68. https://doi.org/10.3233/JPD-212922 Decressac, M., Volakakis, N., Björklund, A., & Perlmann, T. (2013). NURR1 in Parkinson disease--from pathogenesis to therapeutic potential. Nature Reviews. Neurology, 9(11), 629–636. https://doi.org/10.1038/nrneurol.2013.209 Dong, J., Li, S., Mo, J. L., Cai, H. Bin, & Le, W. D. (2016). Nurr1-Based Therapies for Parkinson’s Disease. CNS Neuroscience and Therapeutics, 22(5), 351–359. https://doi.org/10.1111/cns.12536 Dong, X. X., Wang, Y., & Qin, Z. H. (2009). Molecular mechanisms of excitotoxicity and their relevance to pathogenesis of neurodegenerative diseases. In Acta Pharmacologica Sinica (Vol. 30, Issue 4, pp. 379–387). https://doi.org/10.1038/aps.2009.24 Dorsey, E. R., Sherer, T., Okun, M. S., & Bloemd, B. R. (2018). The emerging evidence of the Parkinson pandemic. In Journal of Parkinson’s Disease (Vol. 8, Issue s1, pp. S3– S8). IOS Press. https://doi.org/10.3233/JPD-181474 Elbaz, A., Clavel, J., Rathouz, P. J., Moisan, F., Galanaud, J. P., Delemotte, B., Alpérovitch, A., & Tzourio, C. (2009). Professional exposure to pesticides and Parkinson disease. Annals of Neurology, 66(4), 494–504. https://doi.org/10.1002/ana.21717 260 Flanagan, J. G., & Vanderhaeghen, P. (1998). The ephrins and Eph receptors in neural development. Annual Review of Neuroscience, 21, 309–345. https://doi.org/10.1146/annurev.neuro.21.1.309 Fleming, L., Mann, J. B., Bean, J., Briggle, T., & Sanchez-Ramos, J. R. (1994). Parkinson’s disease and brain levels of organochlorine pesticides. Annals of Neurology, 36(1), 100–103. https://doi.org/10.1002/ana.410360119 Fleming, S. M. (2017). Mechanisms of Gene-Environment Interactions in Parkinson’s Disease. In Current environmental health reports (Vol. 4, Issue 2, pp. 192–199). Springer. https://doi.org/10.1007/s40572-017-0143-2 Freire, C., & Koifman, S. (2012). Pesticide exposure and Parkinson’s disease: Epidemiological evidence of association. NeuroToxicology, 33(5), 947–971. https://doi.org/10.1016/j.neuro.2012.05.011 Gezer, A. O., Kochmanski, J., VanOeveren, S. E., Cole-Strauss, A., Kemp, C. J., Patterson, J. R., Miller, K. M., Kuhn, N. C., Herman, D. E., McIntire, A., Lipton, J. W., Luk, K. C., Fleming, S. M., Sortwell, C. E., & Bernstein, A. I. (2020). Developmental exposure to the organochlorine pesticide dieldrin causes male-specific exacerbation of α-synuclein-preformed fibril-induced toxicity and motor deficits. Neurobiology of Disease, 141(February), 104947. https://doi.org/10.1016/j.nbd.2020.104947 Goldstein, D. S. (2012). Stress, allostatic load, catecholamines, and other neurotransmitters in neurodegenerative diseases. In Cellular and Molecular Neurobiology (Vol. 32, Issue 5, pp. 661–666). https://doi.org/10.1007/s10571-011-9780- 4 Goldstein, D. S. (2013). Biomarkers, mechanisms, and potential prevention of catecholamine neuron loss in parkinson disease. Advances in Pharmacology, 68, 235– 272. https://doi.org/10.1016/B978-0-12-411512-5.00012-9 Goldstein, D. S. (2021). The catecholaldehyde hypothesis for the pathogenesis of catecholaminergic neurodegeneration: What we know and what we do not know. In International Journal of Molecular Sciences (Vol. 22, Issue 11). MDPI. https://doi.org/10.3390/ijms22115999 Haddad, D., & Nakamura, K. (2015). Understanding the susceptibility of dopamine neurons to mitochondrial stressors in Parkinson’s disease. FEBS Letters, 589(24PartA), 3702–3713. https://doi.org/10.1016/j.febslet.2015.10.021 Hatcher, J. M., Pennell, K. D., & Miller, G. W. (2008). Parkinson’s disease and pesticides: a toxicological perspective. In Trends in Pharmacological Sciences (Vol. 29, Issue 6, pp. 322–329). https://doi.org/10.1016/j.tips.2008.03.007 Hatcher, J. M., Richardson, J. R., Guillot, T. S., McCormack, A. L., Di Monte, D. A., Jones, D. P., Pennell, K. D., & Miller, G. W. (2007). Dieldrin exposure induces oxidative 261 damage in the mouse nigrostriatal dopamine system. Experimental Neurology, 204(2), 619–630. https://doi.org/10.1016/j.expneurol.2006.12.020 Henderson, J. T., Georgiou, J., Jia, Z., Robertson, J., Elowe, S., & Roder, J. C. (2001). The Receptor Tyrosine Kinase EphB2 Regulates NMDA-Dependent Synaptic Function cell surface (Holland et al. In Neuron (Vol. 32). Ingelsson, M. (2016). Alpha-synuclein oligomers-neurotoxic molecules in Parkinson’s disease and other lewy body disorders. Frontiers in Neuroscience, 10(SEP), 1–10. https://doi.org/10.3389/fnins.2016.00408 Kanthasamy, A. G., Kitazawa, M., Kanthasamy, A., & Anantharam, V. (2005). Dieldrin- induced neurotoxicity: Relevance to Parkinson’s disease pathogenesis. NeuroToxicology, 26(4 SPEC. ISS.), 701–719. https://doi.org/10.1016/j.neuro.2004.07.010 Kayser, M. S., McClelland, A. C., Hughes, E. G., & Dalva, M. B. (2006). Intracellular and trans-synaptic regulation of glutamatergic synaptogenesis by EphB receptors. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 26(47), 12152–12164. https://doi.org/10.1523/JNEUROSCI.3072-06.2006 Kochmanski, J., Vanoeveren, S. E., & Bernstein, A. I. (2019). Developmental Dieldrin Exposure Alters DNA Methylation at Genes Related to Dopaminergic Neuron Development and Parkinson’s Disease in Mouse Midbrain. Toxicol Sci., 169(2), 593– 607. https://doi.org/10.1093/toxsci/kfz069 Le Couteur, D., McLean, A., Taylor, M., Woodham, B., & Board, P. (1999). Pesticides and Parkinson’s disease. Biomed Pharmacother., 53(3), 122–130. https://doi.org/10.1016/S0753-3322(99)80077-8 Luk, KC., Kehm, V., Carroll, J., Zhang, B., O’Brein, P., Trojanowski, J. Q., & Lee, V. M.- Y. (2012). Pathological α-Synuclein Transmission Initiates Parkinson-like Neurodegeneration in Non-transgenic Mice. Science, 338(6109), 949–953. https://doi.org/10.1126/science.1227157 Luo, Y. (2012). The function and mechanisms of Nurr1 action in midbrain dopaminergic neurons, from development and maintenance to survival. International Review of Neurobiology, 102, 1–22. https://doi.org/10.1016/B978-0-12-386986-9.00001-6 Martínez, A., & Soriano, E. (2005). Functions of ephrin/Eph interactions in the development of the nervous system: emphasis on the hippocampal system. Brain Research. Brain Research Reviews, 49(2), 211–226. https://doi.org/10.1016/j.brainresrev.2005.02.001 Mehrotra B.D., Moorthy K.S., Ravichandra Reddy S., & Desaiah D. (1989). Effects of cyclodiene compounds on calcium pump activity in rat brain and heart. Toxicology. https://doi.org/10.1016/0300-483x(89)90075-9 262 Mehrotra B.D., Ravichandra Reddy S., & Desaiah D. (1988). Effect of subchronic dieldrin treatment on calmodulin-regulated ca2+ pump activity in rat brain. Journal of Toxicology and Environmental Health, 25(4), 461–469. https://doi.org/10.1080/15287398809531224 Michelhaugh, S. K., Vaitkevicius, H., Wang, J., Bouhamdan, M., Krieg, A. R., Walker, J. L., Mendiratta, V., & Bannon, M. J. (2005). Dopamine neurons express multiple isoforms of the nuclear receptor nurr1 with diminished transcriptional activity. Journal of Neurochemistry, 95(5), 1342–1350. https://doi.org/10.1111/j.1471-4159.2005.03458.x Miller, G. W., Gainetdinov, R. R., Levey, A. I., & Caron, M. G. (1999). Dopamine transporters and neuronal injury. Trends in Pharmacological Sciences, 20(10), 424–429. https://doi.org/10.1016/S0165-6147(99)01379-6 Moore, R., & Zigmond, M. (1994). Compensatory mechanisms in central neurodegenerative disease. Neurodegenerative Diseases, 355–369. Moretto, A., & Colosio, C. (2011). Biochemical and toxicological evidence of neurological effects of pesticides: The example of Parkinson’s disease. In NeuroToxicology (Vol. 32, Issue 4, pp. 383–391). https://doi.org/10.1016/j.neuro.2011.03.004 Murphy, D. D., Rueter, S. M., Trojanowski, J. Q., & M-Y Lee, V. (2000). Synucleins Are Developmentally Expressed, and-Synuclein Regulates the Size of the Presynaptic Vesicular Pool in Primary Hippocampal Neurons. Pierce, S. E., Tyson, T., Booms, A., Prahl, J., & Coetzee, G. A. (2018). Parkinson’s disease genetic risk in a midbrain neuronal cell line. Neurobiology of Disease, 114, 53– 64. https://doi.org/10.1016/j.nbd.2018.02.007 Post, M. R., Lieberman, O. J., & Mosharov, E. V. (2018). Can interactions between α- synuclein, dopamine and calcium explain selective neurodegeneration in Parkinson’s disease? In Frontiers in Neuroscience (Vol. 12, Issue MAR). Frontiers Media S.A. https://doi.org/10.3389/fnins.2018.00161 Priyadarshi, A., Khuder, S. A., Schaub, E. A., & Priyadarshi, S. S. (2001). Environmental risk factors and parkinson’s disease: A metaanalysis. Environmental Research, 86(2), 122–127. https://doi.org/10.1006/enrs.2001.4264 Priyadarshi, A., Khuder, S., Schaub, E., & Shirvastava, S. (2000). A meta-analysis of Parkinson’s disease and exposure to pesticides. Neurotoxicology, 21(4), 435–440. Richardson, J. R., Caudle, W. M., Wang, M., Dean, E. D., Pennell, K. D., Miller, G. W., Richardson, J. R., Caudle, W. M., Wang, M., Dean, E. D., Pennell, K. D., & Miller, G. W. (2006). Developmental exposure to the pesticide dieldrin alters the dopamine system and increases neurotoxicity in an animal model of Parkinson’s disease. The FASEB Journal, 20(10), 1695–1697. https://doi.org/10.1096/fj.06-5864fje 263 Ritz, B., & Yu, F. (2000). Parkinson’s disease mortality and pesticide exposure in California 1984–1994. Int. J. Epidemiol., 29(3), 323–329. https://doi.org/10.1093/ije/29.2.323 Semchuk, K. M., Love, E. J., & Lee, R. G. (1992a). Parkinson’s disease and exposure to agricultural work and pesticide chemicals. Neurology, 42, 1328–1335. https://doi.org/10.1212/wnl.42.7.1328 Semchuk, K. M., Love, E. J., & Lee, R. G. (1992b). Parkinson’s disease and exposure to agricultural work and pesticide chemicals. Slotkin, T. A., & Seidler, F. J. (2009). Oxidative and excitatory mechanisms of developmental neurotoxicity: Transcriptional profiles for chlorpyrifos, diazinon, dieldrin, and divalent nickel in PC12 Cells. Environmental Health Perspectives, 117(4), 587–596. https://doi.org/10.1289/ehp.0800251 Smits, S. M., Ponnio, T., Conneely, O. M., Burbach, J. P. H., & Smidt, M. P. (2003). Involvement of Nurr1 in specifying the neurotransmitter identity of ventral midbrain dopaminergic neurons. The European Journal of Neuroscience, 18(7), 1731–1738. https://doi.org/10.1046/j.1460-9568.2003.02885.x Steenland, K., Hein, M. J., Cassinelli, R. T., Prince, M. M., Nilsen, N. B., Whelan, E. A., Waters, M. A., Ruder, A. M., & Schnorr, T. M. (2006). Polychlorinated biphenyls and neurodegenerative disease mortality in an occupational cohort. Epidemiology, 17(1), 8– 13. https://doi.org/10.1097/01.ede.0000190707.51536.2b Sulzer, D., Cragg, S. J., & Rice, M. E. (2016). Striatal dopamine neurotransmission: Regulation of release and uptake. In Basal Ganglia (Vol. 6, Issue 3, pp. 123–148). Elsevier GmbH. https://doi.org/10.1016/j.baga.2016.02.001 Takasu, M. A., Dalva, M. B., Zigmond, R. E., & Greenberg, M. E. (2002). Modulation of NMDA receptor-dependent calcium influx and gene expression through EphB receptors. Science (New York, N.Y.), 295(5554), 491–495. https://doi.org/10.1126/science.1065983 Tanner, C. M., & Aston, D. A. (2000). Epidemiology of Parkinson’s disease and akinetic syndromes. Current Opinion in Neurology, 13, 427–430. https://doi.org/10.1097/00019052-200008000-00010 Tanner, C. M., Kame, F., Ross, G. W., Hoppin, J. A., Goldman, S. M., Korell, M., Marras, C., Bhudhikanok, G. S., Kasten, M., Chade, A. R., Comyns, K., Richards, M. B., Meng, C., Priestley, B., Fernandez, H. H., Cambi, F., Umbach, D. M., Blair, A., Sandler, D. P., & Langston, J. W. (2011). Rotenone, paraquat, and Parkinson’s disease. Environmental Health Perspectives, 119(6), 866–872. https://doi.org/10.1289/ehp.1002839 Tanner, C. M., & Langston, J. W. (1990). Do environmental toxins cause Parkinson’s disease? A critical review. Neurology, 40(10), 17–30. 264 Trudeau, L. E., Hnasko, T. S., Wallén-Mackenzie, Å., Morales, M., Rayport, S., & Sulzer, D. (2014). The multilingual nature of dopamine neurons. In Progress in Brain Research (Vol. 211, pp. 141–164). Elsevier B.V. https://doi.org/10.1016/B978-0-444-63425- 2.00006-4 Volles, M. J., Lee, S. J., Rochet, J. C., Shtilerman, M. D., Ding, T. T., Kessler, J. C., & Lansbury, P. T. (2001). Vesicle permeabilization by protofibrillar α-synuclein: Implications for the pathogenesis and treatment of Parkinson’s disease. Biochemistry, 40(26), 7812– 7819. https://doi.org/10.1021/bi0102398 Weisskopf, M., Knekt, P., O’Reilly, E., Lyytinen, J., Reunanen, A., Laden, F., Altshul, L., & Ascherio, A. (2010). Persistent organochlorine pesticides in serum and risk of Parkinson disease. Neurology, 74(13), 1055–1061. https://doi.org/10.1212/WNL.0b013e3181d76a93 Wirdefeldt, K., Adami, H. O., Cole, P., Trichopoulos, D., & Mandel, J. (2011). Epidemiology and etiology of Parkinson’s disease: A review of the evidence. In European Journal of Epidemiology (Vol. 26, Issue SUPPL. 1). https://doi.org/10.1007/s10654-011-9581-6 Xilouri, M., Brekk, O. R., & Stefanis, L. (2013). α-Synuclein and protein degradation systems: a reciprocal relationship. Molecular Neurobiology, 47(2), 537–551. https://doi.org/10.1007/s12035-012-8341-2 Yang, J. S., Wei, H. X., Chen, P. P., & Wu, G. (2018). Roles of Eph/ephrin bidirectional signaling in central nervous system injury and recovery (Review). Experimental and Therapeutic Medicine, 15(3), 2219–2227. https://doi.org/10.3892/etm.2018.5702 Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., Duncan, J. A., Cheshier, S. H., Shuer, L. M., Chang, E. F., Grant, G. A., Gephart, M. G. H., & Barres, B. A. (2016). Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse. Neuron, 89(1), 37–53. https://doi.org/10.1016/j.neuron.2015.11.013 Zigmond, M. J. (1994). Chemical transmission in the brain: homeostatic regulation and its functional implications Homeostasis of neuronal function. Progress in Brain Research, 100, 115–122. https://doi.org/10.1016/s0079-6123(08)60776-1 265