University of Florida Thesis Or Dissertation Formatting Template

AT THE INTERSECTION OF PROTEOSTASIS AND NEURODEGENERATIVE DISEASE: BYSTANDER MISFOLDING AND IMPAIRED PROTEOME INTEGRITY

MICHAEL PACE

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2018

To my wife, friends, family, and everyone who supported me throughout this endeavor, as well as to the scientific process and an appreciation of critical thinking, without which I would not have made it this far.

ACKNOWLEDGMENTS

I wish to thank my mentor, Dr. David Borchelt, for always being available to answer my questions and unravel the scientific minutia of my projects whenever I was unable to do so. I wish to thank my colleagues and collaborators Dr. Guilian Xu, Hilda

Brown, Susan Fromholt, Dr. Jada Lewis, John Howard, Dr. Sruti Rayaprolu, Dr.

Matthew Hamm, Dr. Kevin Strang, Dr. Jacob Ayers, and Keith Crosby. They provided invaluable support in the form of scientific and technical expertise as well as insightful conversation on a daily basis to push my projects forward. I wish to thank the

Interdisciplinary Center for Biotechnology Research (ICBR) at the University of Florida for assistance in processing and analyzing samples during proteomic studies. My committee (consisting of Dr. David Borchelt, Dr. Lucia Notterpek, Dr. Benoit Giasson,

Dr. Ron Mandel and Dr. Timothy Garrett) provided invaluable scientific insight throughout the progression of my degree. Lastly, I wish to acknowledge Drs. Dawn

Bowers and David Vaillancourt, the co-directors of the training grant that I received, for professional development advice and advancing my opportunities to grow and mature as a scientist.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 9

LIST OF OBJECTS ...... 12

LIST OF ABBREVIATIONS ...... 13

ABSTRACT ...... 16

CHAPTER

1 INTRODUCTION ...... 18

Proteostasis Network Composition and Functionality ...... 20 Molecular Chaperones ...... 21 The Ubiquitin-Proteasome System ...... 24 The Autohphagy-Lysosomal System ...... 28 Effects of Pathologic Proteinopathies on Proteostasis ...... 32 Evidence for Compromised Cellular Protein Folding in the Face of Neurodegenerative Proteinopathies ...... 36

2 DIFFERENTIAL INDUCTION OF MUTANT SOD1 MISFOLDING AND AGGREGATION BY TAU AND α-SYNUCLEIN PATHOLOGY ...... 40

Methods ...... 43 Transgenic Mice ...... 43 Breeding Scheme to Generate Mice Co-expressing G85R-SOD1:YFP and Mutant Proteins Associated with Human Proteinopathies ...... 44 Intramuscular Human αSyn Fibril Injections into Hemizygous M83 and Bigenic M83-G85R-SOD1:YFP Transgenic Mice to Seed αSyn Pathology .. 45 Tissue Processing, Immunohistochemistry and Image Microscopy ...... 45 Fluorescence Quantification and Statistical Analysis ...... 47 Preparation of Brain and Spinal Cord Tissues for Immunoblot Analysis ...... 47 Immunoblotting and Western Blot Quantification ...... 49 Results ...... 50 Mutant Tau Induces G85R-SOD1:YFP Inclusion Pathology in the Spinal Cord and Brain Stem ...... 50 Localization of SOD1 Pathology Relative to Tau Pathology ...... 51 Lack of G85R-SOD1:YFP Inclusion Pathology Induction in the rTg4510 Model of Cortical and Hippocampal Tauopathy ...... 52

Paucity of Induced G85R-SOD1:YFP Aggregation in the M83 Model of αSynucleinopathy ...... 53 Discussion ...... 54 Conclusions ...... 61

3 CHANGES IN PROTEOME SOLUBILITY INDICATE WIDESPREAD PROTEOSTATIC DISRUPTION IN MOUSE MODELS OF NEURODEGENERATIVE DISEASE ...... 80

Materials and Methods...... 82 Transgenic Animals ...... 82 Intramuscular Injection of Preformed α-synuclein Fibrils into M83 Transgenic Mice ...... 83 Sequential Protein Detergent Extraction from Mouse Forebrain/Spinal Cord and Preparation of Protein Samples for Proteomics Analysis ...... 84 LC-MS/MS Analysis ...... 85 Calibration, Relative Quantification and Bioinformatics of Proteomics Data ..... 86 Western Blot Validations of LC-MS/MS Data ...... 88 Expression and Purification of Recombinant K18 Tau and Assembly of Recombinant K18 Tau Fibrils ...... 88 N2a Cell Culture and K18-mediated Human Tau Seeding in vitro ...... 89 Results ...... 90 Neurofibrillary Tangle Pathology Perturbs the Solubility of CNS Cytosolic Proteins ...... 90 Validation of LC-MS/MS Data in Tauopathy ...... 94 Differential Effects of Pathological Tau Versus Amyloid-β on Proteome Solubility ...... 97 Analysis of Changes in Proteome Solubility in Mouse Models of Spinal Proteinopathy ...... 98 Identification of Proteins in SDS-insoluble Fractions from N2a Cell Lysates Prepared with Tau Aggregates ...... 101 Bioinformatic Analysis of Proteins that Aberrantly Fractionate as SDS- insoluble Reveals Commonly Affected Protein Classes ...... 103 Discussion ...... 104

4 ASSESSING THE ALLEVIATION OF ABERRANT PROTEOME INSOLUBILITY VIA TRANSIENT INHIBITION OF TRANSLATION WITH CYCLOHEXIMIDE ...... 130

Materials and Methods...... 133 Transgenic Mice ...... 133 Cycloheximide Preparation, Injection, and Harvesting Procedures ...... 133 Sequential Detergent Extraction of Spinal Cord Tissue ...... 134 Liquid Chromatrography Tandem Mass Spectrometry Analysis ...... 135 Bioinformatics, Statistics, and the Calibration/Relative Quantification of Proteomics Data ...... 137 Results ...... 138 Discussion ...... 140

5 DISCUSSION ...... 148

LIST OF REFERENCES ...... 156

BIOGRAPHICAL SKETCH ...... 184

LIST OF TABLES

Table page

2-1 RNAseq expression data for SOD1 in mouse and human tauopathies ...... 79

3-1 Statistical information for different proteinopathy animal groups analyzed via LC-MS/MS ...... 125

3-2 List of the proteins that showed the highest differential of over-representation in SDS-insoluble fractions from the forebrain of 7-month-old rTg4510 mice .... 126

3-3 Overlapping protein identifications between SDS-insoluble fractions from rTg4510 mice and previous proteomic studies of disease-associated pathological features ...... 127

LIST OF FIGURES

Figure page

2-1 Kaplan-Meier survival curves in JNPL3/G85R-SOD1:YFP mice relative to single transgenic JNPL3 control ...... 62

2-2 G85R-SOD1:YFP aggregation into punctate inclusions within the spinal cord of JNPL3/G85R-SOD1:YFP mice ...... 63

2-3 Low power views of G85R-SOD1:YFP pathology in the spinal cord of bigenic JNPL3-G85R-SOD1:YFP mice ...... 64

2-4 Primary pathology burden in the JNPL3 spinal cord relative to those crossed to G85R-SOD1:YFP mice ...... 65

2-5 Solubility of SOD1 in JNPL3/G85R-SOD1:YFP mice ...... 66

2-6 Localization of tau MC1 immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3/G85R-SOD1:YFP mice ...... 67

2-7 Localization of phosphotau immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3/G85R-SOD1:YFP animals ...... 68

2-8 Localization of phosphotau immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3-G85R-SOD1:YFP mice ...... 69

2-9 G85R-SOD1:YFP does not form inclusions in the forebrain of rTg4510/G85R-SOD1:YFP bigenic ...... 70

2-10 Primary pathology burden in the rTg4510 transgenic mouse cortex relative to those crossed to the G85R-SOD1:YFP mouse ...... 71

2-11 Quantification of G85R-SOD1:YFP levels between G85R-SOD1:YFP and rTg4510/G85R-SOD1:YFP mice using direct fluorescence and immunoblot densitometric analysis ...... 72

2-12 Primary pathology burden in the M83 transgenic mouse spinal cord relative to M83/G85R-SOD1:YFP mice ...... 73

2-13 Lack of G85R-SOD1:YFP inclusion pathology in the spinal cord of M83/G85R-SOD1:YFP mice ...... 74

2-14 Kaplan-Meier survival curves for M83/G85R-SOD1:YFP mice relative to single transgenic M83 controls ...... 75

2-15 Solubility of αSyn and SOD1 in M83/G85R-SOD1:YFP mice ...... 76

2-16 G85R-SOD1:YFP expression in spinal cord is 2-fold higher than forebrain in G85R-SOD1:YFP heterozygous mice...... 77

2-17 Hypothetical mechanism of differential effects of tauopathy versus synucleinopathy on G85R-SOD1:YFP secondary aggregation in the spinal cord and cortex ...... 78

3-1 Quantification of changes in protein detection in SDS-insoluble fractions in brains of rTg4510 mice ...... 113

3-2 Two-way clustering of spectral count data from rTg4510 mice ...... 114

3-3 Venn diagram of common proteins identified in APPswe/PS1dE9 (L85) across different analysis timepoints ...... 114

3-4 Immunoblot validations of LC-MS/MS data in rTg4510 mice ...... 115

3-5 Immunoreactivity for Hspa4 protein is not highly co-localized with neurofibrillary tangle pathology of rTg4510 mice ...... 116

3-6 Two-way clustering of spectral count data from SDS-insoluble fractions from rTg4510, rTg21221 and APPswe/PS1dE9 mice ...... 117

3-7 Comparison of spectral count data between rTg4510 and G93A-SOD1 mice .. 118

3-8 Neurodegenerative models of spinal proteinopathy characterized by paralysis also induce impairments in proteome solubility ...... 119

3-9 Two-way clustering of SDS-insoluble spectra for rTg4510, M83, M83 seeded, JNPL3, and G93A SOD1 models ...... 120

3-10 Analysis of cellular protein co-sedimentation with tau aggregates in mouse N2a cell models ...... 121

3-11 Bioinformatic analysis of protein classes that are statistically over- represented in SDS-insoluble fractions of proteinopathy models analyzed via LC-MS/MS ...... 122

3-12 Bioinformatic analysis of protein classes that are statistically over- represented in SDS-insoluble fractions rTg4510 mice ...... 122

3-13 Overlapping protein identifications between SDS-insoluble fractions from Tg4510 mice and previous proteomic studies of disease-associated pathological features ...... 123

3-14 Combined Venn diagram representative of both diagrams from Figure 3-13, encompassing the numbers of overlapping proteins from all types of

methodologies used in previous literature (IP, Detergent-Insoluble, LCM, and Other) ...... 124

4-1 Fold-changes for individual proteins affected in G93A SOD1 mice with and without CHX treatment ...... 145

4-2 Numbers of aberrantly insoluble proteins for individual mice analyzed by LC- MS/MS with or without CHX treatment relative to control animals ...... 146

4-3 Comparison of aberrantly insoluble proteins from mild and end-stage phenotypic G93A SOD1 mice from separate independent studies ...... 147

LIST OF OBJECTS

Object page

3-1 Compiled proteomic data highlighted proteins that lose solubility in mouse models of neurodegenerative proteinopathy (.xlsx file 1.08 MB) ...... 129

3-2 Raw proteomic data from all analyzed mouse models (.xlsx file 428 KB) ...... 129

LIST OF ABBREVIATIONS

Aβ Amyloid-β

AD Alzheimer’s disease

ALDOC Fructose biphosphate aldolase C

ALS Amyotrophic lateral sclerosis

αSyn α-synuclein

ATCC American type culture collection

BCA Bicinchoninic acid

CaMKII Ca^(2+) calmodulin kinase II

CHIP Carboxy-terminal Hsp70-interacting protein

CHX Cycloheximide

CMT1B Charcot-Marie Tooth 1B

CMV Cytomegalovirus

CNS Central Nervous System

DAB 3,3'-diaminobenzidine

DMSO Dimethyl sulfoxide

DOC Deoxycholate

Dox Doxycycline eIF2α Eukaryotic translation initiation factor 2

ENO1 Enolase 1

FTD Frontotemporal dementia

G85R- SOD1 protein with glycine mutated to arginine tagged to yellow SOD1:YFP fluorescent protein

GFP Green fluorescent protein

GSK3β Glycogen synthase kinase 3β

Hsp Heat shock protein

IACUC Institutional Animal Care and Use Committee

IM Intramuscular

LC-MS/MS Liquid chromatography tandem mass spectrometry

MDH1 Malate dehydrogenase 1 (cytoplasmic)

MIF Macrophage migration inhibitory factor

N2a Neuro 2a

NFT Neurofibrillary tangles

NP40 Nonidet P-40

NTg Nontransgenic

PANTHER Protein analysis through evolutionary relationships

PBS Phosphate buffered saline

PBS-S PBS-soluble

PBS-T PBS with 10% tween

PD Parkinson’s disease

PGAM1 Phosphoglycerate mutase 1

PolyQ Polyglutamine

PrP Prion protein

SAINT Significance analysis of interactome

SDS Sodium dodecyl sulfate

SDS-P SDS-pellet (insoluble)

SDS-PAGE Sodium dodecyl sulfate-polyacrylamide gel electrophoresis

SOD1 Superoxide dismutase 1

TDP-43 Tar DNA-binding protein 43 kDa

TEN 10 mM Tris-HCl pH 7.5/1 mM EDTA/100 mM NaCl

TS Temperature-sensitive tTA Tet-transactivator

UCHL1 Ubiquitin carboxyl-terminal hydrolase isozyme 1

UPR Unfolded protein response

UPS Ubiquitin-proteasome system

WT Wild type

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

AT THE INTERSECTION OF PROTEOSTASIS AND NEURODEGENERATIVE DISEASE: BYSTANDER MISFOLDING AND IMPAIRED PROTEOME INTEGRITY

Michael Pace

December 2018

Chair: David Borchelt Major: Medical Sciences

The deposition of pathologic misfolded proteins in neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia and amyotrophic lateral sclerosis is hypothesized to burden protein homeostatic

(proteostatic) machinery, potentially leading to insufficient capacity to maintain the proteome. This hypothesis has been supported by previous work in our laboratory, as evidenced by the perturbation of cytosolic protein solubility in response to amyloid plaques in a mouse model of Alzheimer’s amyloidosis. Additional work in C. elegans demonstrated that the expression of aggregation-prone polyglutamine proteins in muscle wall cells compromised the folding of co-expressed temperature-sensitive proteins, prompting interest in whether the accumulation of a misfolded protein in pathologic features of human neurodegenerative disease burdens cellular proteostatic machinery in a manner that impairs the folding of other cellular proteins. In the current studies, we have made novel discoveries demonstrating the potential and degree of this

“bystander” misfolding that occurs in the presence of a proteinopathy. Mice expressing

G85R-SOD1:YFP, a protein prone to misfold, exhibit robust inclusion pathology when introduced to a background of spinal tau pathology. Interestingly, this did not occur in

the presence of either cortical tau pathology or spinal synucleinopathy, indicating both an anatomical and pathololgic specificity in this bystander misfolding paradigm. We next demonstrated that tau, αSyn, and SOD1 pathologies are capable of disruptiong the solubility of hundreds of CNS proteins via detergent extraction methodologies coupled to LC-MS/MS. Many of these proteins exhibited insolubility irrespective of the initiating proteinopathy. Finally, we generated preliminary evidence that the transient inhibition of translation may be effective in restoring proteostasis, as evidenced by the resoration of proteome solubility with CHX treatment. Overall, our data demonstrate the deleterious effects of a chronic misfolded protein pathology on proteostasis, and these effects appear to be dependent upon both the initiating misfolded protein and the anatomical location of the pathology. Temporarily preventing protein synthesis may alleviate the accumulation of these aberrantly insoluble proteins. Future studies will aim to further elucidate this specificity by understanding chaperone networks that differ across regions of the CNS and by assessing proteasomal and autophagic efficacies in the face of varying neurodegenerative pathologies.

CHAPTER 1 INTRODUCTION

Protein misfolding and the formation of oligomeric and aggregated protein species is a recurring theme in what have been termed protein misfolding diseases

(also known as proteinopathies or protein conformational diseases) [32]. This group of diseases includes, but is not limited to, cystic fibrosis (CF), prion disorders, sickle cell anemia, keratin diseases, Gaucher disease, type 2 diabetes, polyglutamine disorders

(Huntington’s disease, spinocerebellar ataxias, etc.) and many neurodegenerative disorders [32, 109, 185]. Neurodegenerative diseases, of which Alzheimer’s and

Parkinson’s diseases exhibit the highest degree of prevalence worldwide, are characterized by the accumulation of specific misfolded proteins in affected central nervous system (CNS) tissue [32, 64]. Other neurodegenerative disorders that exhibit the accumulation of misfolded proteins include amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration with either tau or TDP-43 pathology (FTLD-tau and

FTLD-U, respectively), spinocerebellar ataxias, Huntington’s disease (HD), progressive supranuclear palsy (PSP), Dementia with Lewy bodies (DLB), corticobasal degeneration

(CBD), Pick’s disease (PiD), multiple system atrophy, and transmissible spongiform encephalopathies (associated with the prion protein) such as Creutzfelt-Jakob disease

[95, 184, 239]. These diseases are often pathologically defined by whichever specific protein misfolds and is the primary constituent of intracellular and/or extracellular aggregates inside affected cells. The primary cause of the protein misfolding cascade leading to aggregate formation in these diseases is poorly understood. While particular genetic changes in protein sequence are known to increase the aggregation propensity of certain proteins [such as huntingtin in Huntington’s disease and superoxide

dismutase 1 (SOD1) in ALS] [39, 201, 220, 224], little is known regarding what initiates deleterious protein misfolding in diseases that occur with no known genetic component, such as sporadic cases of neurodegenerative disorders.

There is still much debate regarding potential gain- versus loss-of-function effects of ubiquitous protein misfolding in neurodegenerative disorders. For example, polyglutamine (polyQ) proteins that accumulate in Huntington’s disease are thought to exhibit gain-of-function toxicity, having been shown to cause deleterious effects on motility in C. elegans [183]. It is also reasonable to assume that any given misfolded protein may not function at full capacity relative to its natively folded form; thus, if misfolding occurred to a sufficient degree, loss-of-function effects could be problematic.

Many other mechanisms of cellular toxicity have been proposed that cause neurodegeneration, including oxidative stress, mitochondrial dysfunction, excitotoxic insult, and synaptic failure (for a review, see [25]). However, one mechanism of cellular dysfunction that has recently gained traction is the deleterious effect of the accumulation of misfolded proteins on the protein homeostasis (proteostasis) network

[14, 24, 50, 67, 119, 152, 161, 182, 199, 254, 272]. This idea has been reinforced by the number of neurodegenerative disorders caused by mutations in genes encoding proteostatic factors, such as proteins involved in autophagy and the ubiquitin- proteasome system. Examples of this include mutations in VCP [228] and UBQLN2 [58,

279] which have been associated with both ALS and frontotemporal dementia. Deficient proteostasis could contribute to proteotoxic effects within the cell and the formation of nonnative protein species [181]. An efficient proteostasis network is especially pertinent in neuronal cells, specifically due to their post-mitotic status and susceptibility to the

accumulation of misfolded proteins over time [50]. Neurons, unlike other cell types, are unable to asymmetrically distribute inclusion bodies during cellular division [214]. Given that a plethora of neurodegenerative disorders are primarily characterized, and often defined, by the presence of aggregates composed of misfolded proteins as well as soluble misfolded oligomeric species, it is not unreasonable to propose that this alone indicates an imbalance within the proteostasis network [14, 50, 181, 290]. The following introduction will encompass the primary components responsible for proteostatic maintenance, their function at the cellular level, and the relationships that are thought to exist between the proteostasis network, neurodegenerative diseases, and the misfolded proteins associated with them.

Proteostasis Network Composition and Functionality

Altogether, the idea of proteostasis refers to a healthy balance of the proteome, especially when a cell is faced with environmental stressors/changes (e.g. thermal, oxidative and hypoxic stress) [248]. The proteostasis network encompasses a wide range of cellular components that perform many functions and processes to manage proteome integrity, including protein synthesis, folding, trafficking, and degradation.

These functions are performed by a variety of cellular factors, but chaperones, the ubiquitin-proteasome system, and autophagy are thought to be primary players that maintain proteostasis in respect to the prevention of misfolded protein accumulation

[109, 152, 252, 290]. Additional cellular mechanisms for proteostasis maintenance include the heat shock response [162, 263], the unfolded protein response within the endoplasmic reticulum (for a review, see [222]), and the active sequestration of misfolded proteins into cellular compartments such as Q-bodies, the insoluble protein deposit (IPOD) and the juxtanuclear quality control compartment (JUNQ) (for a review,

see [238]). In particular, it has been suggested that the formation of proteinaceous inclusions could act as a defense mechanism of affected cells in these disorders, in an attempt to sequester proteotoxic soluble oligomeric proteins into less harmful structures

(analogous to the JUNQ and IPOD compartments) [134, 180, 234, 267]. There is a general consensus that cellular components responsible for proteostasis maintenance have co-evolved and are present at sufficient levels with little redundancy in order to respond to stressors in the most efficient manner [14, 180, 200]. Additionally, it is thought that this network exists in a tightly balanced state, with each component in consistent cross-talk to ensure proper protein folding and degradation [14, 180]. The function of these processes is to maintain a proper balance of protein synthesis/turnover and the efficient degradation of dysfunctional/improperly folded proteins. Thus, it is possible that any significant burden upon this network or impaired functionality of any of its components would lead to inefficient protein folding and degradation. While proteostatic mechanisms are broadly thought to be conserved across multiple evolutionary domains, this review will focus on eukaryotic mechanisms of maintaining the cellular proteome unless otherwise indicated.

Molecular Chaperones

Throughout the synthesis and life cycle of a singular protein, there are multiple checkpoints to ensure it reaches its natively folded state and, thus, full functionality.

Accordingly, there are cellular responses that are designed to remedy inadequacies in proteome integrity. These processes are largely mediated through molecular chaperones, which serve to facilitate protein folding while simultaneously preventing protein aggregation or other unfavorable molecular interactions within a crowded cellular environment [65, 74, 146]. However, other non-chaperone proteins are also

critical for this process. These include transcription factors, signaling proteins/receptors, and regulators of the cell cycle [112]. The folding pathways undergone by any given protein contain many alternative pathways leading to different confirmations, some of which are not conducive to reaching its natively folded state. Such aberrant alternatives include amorphous aggregates, oligomers, and amyloid fibrils, all of which exist at thermodynamically favorable energy states relative to safer alternatives (partially folded states and folding intermediates) [15, 146]. Chaperones function to prevent the formation of these misfolded states, specifically through their affinity to bind hydrophobic segments within a polypeptide, as these regions within a protein are thought to drive protein aggregation [38, 146]. Once the synthesis of a protein is initiated, specific ribosome-associated chaperones [trigger factor (TF) in the case of bacteria and the nascent-chain-associated complex (NAC) for archaea and eukarya] will associate with hydrophobic regions within the nascent polypeptide [108, 146]. This will stabilize the polypeptide during the process of folding. These chaperone types are also referred to as chaperones linked to protein synthesis (CLIPs) [248]. Subsequent stages of protein folding/stabilization occur beyond the context of the ribosome.

Once a protein has been released from the ribosome, chaperones without any association to the ribosome will then interact with the polypeptide further downstream in the folding process, such as various heat shock proteins (Hsps) [146]. Hsps are upregulated by the induction of the heat shock response (HSR), which can be activated by cellular stressors, such as excessive heat [162]. These include, but are not limited to, small Hsps, Hsp40, Hsp90 and Hsp70. The upregulation of these chaperones is mediated by the transcription factor HSF1, which functions primarily by targeting heat-

shock elements within promoter regions of heat shock genes [83, 181]. Hsp70s have fundamental roles in maintaining cytosolic proteostasis (not just in assisting newly synthesized proteins to reach their native state). They function via both an N-terminal

ATP-binding domain (NBD) and C-terminal substrate-binding domain (SBD), both being necessary for proper function of any given Hsp70 [26]. Unfolded polypeptides containing accessible hydrophobic regions will transiently interact with the SBD. The binding of ATP to the NBD leads to decreased affinity for chaperone substrates, hastening the on/off rates of substrate recognition [26, 30]. Conversely, the binding of a substrate to the SBD leads to ATP hydrolysis at the NBD and the subsequent stabilization of the Hsp70-substrate complex. It is this cycle of coordinated binding/release of a substrate that facilitates substrate folding while simultaneously preventing aggregation/misfolding [166]. Despite not having an affinity for the ribosome,

Hsp70s interact with newly synthesized polypeptides in conjunction with TF in bacteria

[255]. They also function as cochaperones with Hsp40s (also referred to as DnaJs) and

Hsp110 nucleotide exchange factors to prevent unfavorable interactions of nascent polypeptide chains with other cellular components [136].

It is important to note that for many proteins, folding into a native functional state happens spontaneously [74]. However, those that take longer to fold or persist in a partially folded state may be transferred to chaperonins [such as GroEL/GroES in bacteria and the tailless complex polypeptide-1 complex (TRiC) in eukaryotes], a cylindrically-shaped class of chaperones that provide an isolated environment for efficient folding [82, 108, 146, 153]. In a similar manner to which proteins are transferred to chaperonins, proteins can also be transferred to ATP-dependent Hsp90-class

chaperones in the case of eukaryotes [251]. This class of chaperones can regulate the conformation of folding polypeptides and also complete the folding process [167, 251,

295]. Overall, chaperones stabilize nascent polypeptides throughout the folding process and prevent unfavorable interactions with other cellular components, leading to the timely and efficient development of fully functional proteins.

The Ubiquitin-Proteasome System

Whether a protein completes its life cycle and maintains functionality or becomes damaged/misfolded at any point, it is important for any given cell to maintain adequate means of protein degradation. This is because misfolded proteins, having hydrophobic regions exposed, are deleterious to protein quality control systems as they begin to accumulate and require additional maintenance. Thus, the primary protein degradation mechanisms used by the cell (the ubiquitin-proteasome and autophagy-lysosomal systems) are critical for ensuring proper proteostatic balance [265]. The integrity of these systems is particularly critical for post-mitotic neurons, which cannot divide in an attempt to reduce a high load of damaged/misfolded proteins [169].

The ubiquitin-proteasome system (UPS) is a heavily conserved, tightly regulated cellular machinery that acts as the primary mechanism for degrading misfolded proteins when chaperones are unable to refold a protein or otherwise assist in it reaching its native state (for reviews, see [41, 252]). While its significance in the scope of protein misfolding in neurodegenerative diseases is acknowledged, it also regularly functions to break down cellular proteins in a routine manner for amino acid recycling [294]. This most often consists of soluble proteins contained within the cytosol and nucleus, in addition to some proteins that are shuttled from the endoplasmic reticulum to the cytosol for degradation [237, 256]. The UPS degrades proteins through the proteolytic activity of

the 26S proteasome, which is composed of a singular 20S core particle and two 19S regulatory particles [169]. The two regulatory particles associate with the ends of the

20S core particle in opposite orientations, forming barrel structure with two “caps” [46,

252]. The 26S proteasome has been characterized in a wide variety of organisms, from prokaryotes to humans [79, 123, 223, 253, 274, 286]. Differential proteasome compositions, proteolytic properties, and interacting proteins have been reported, and vary among different types of tissue [68, 92, 249]. However, for the scope of eukaryotic proteasomes, many consistencies have emerged regarding structure and function. The core particle is made up of four heptameric rings, resulting from the stacking of two inner β-rings and two outer α-rings [252]. Each  ring is composed of seven α or β subunits, of which the β1, 2, and 5 varieties exhibit caspase-, trypsin-, and chymotrypsin-like activities, respectively [252]. The α rings, on the other hand, appear to regulate the entry of protein substrates into the inner catalytically active β rings, which has been suggested by the crystal structure of the core particle [97, 252, 262]. Even higher up on the regulatory chain of proteasomal degradation is the regulatory particle itself (a pair of 19S particles), with each 19S particle composed of six triple ATPase subunits as well as 13 non-ATPase subunits [252]. This regulatory particle is responsible for substrate recognition and unfolding, followed by the translocation of the substrate to the inner core particle for degradation [252].

In order for a protein to be degraded via the UPS, it first must be modified with the addition of multiple ubiquitin moieties to form a polyubiquitin chain that is covalently bonded to the substrate protein. It is worth noting that the addition of ubiquitin as a post- translational modification serves additional roles aside from targeting a protein for

degradation. The addition of ubiquitin moieties to a substrate is important for a range of cellular processes, including transcription, translation, vesicle transport, apoptosis, cell cycle, and DNA damage repair [290]. For the purposes of this review, however, the role that the UPS plays in degrading misolfed proteins is most pertinent regarding pathology of neurodegenerative disorders and will therefore be the primary focus. The process of adding ubiquitin to a substrate occurs in a multi-step, ATP-dependent manner. First, a ubiquitin-activating enzyme (E1) recruits a free ubiquitin moiety, forming a thiol-ester bond between itself and the c-terminal glycine of ubiquitin [277]. This initial activation of ubiquitin is dependent upon the presence of ATP. Next, the newly attached ubiquitin will be transferred to an E2 ubiquitin-conjugating enzyme via its c-terminus. Lastly, an E3 ubiquitin ligase which is specific to, and interacts with, the substrate protein will facilitate the transfer of ubiquitin from the E2 to a lysine residue of the substrate protein [277].

Overall, the specificity of the ubiquitin-associated enzymes increases sequentially, with

E1 enzymes being the least specific and E3s being the most specific. Thus, the resulting ubiquitinated substrate protein is primarily dependent upon the involved E3

[116, 256]. Ubiquitin homeostasis itself is critical for cellular health. In high stress situations, free ubiquitin levels must increase in order to accommodate for adequate substrate polyubiquitin conjugation [78]. This is reinforced by the fact that genes encoding monoubiquitin (Uba) and polyubiquitin (Ubb and Ubc) are induced by cellular stress, emphasizing the significance of ubiquitin homeostatic maintenance [215].

However, too much free ubiquitin is thought to be harmful; thus, balance in ubiquitin homeostasis is maintained by a class enzymes known as deubiquitinating enzymes and their respective inhibitors [147, 252]. The organization of polyubiquitin conjugation onto

a targeted protein is critical for substrate recognition and destination. More specifically, the ubiquitin protein consists of seven lysine residues and a methionine residue at its N- terminus; these are used to nucleate the polyubiquitin chain [208, 277]. The subsequent arrangement and number of ubiquitin molecules attached to a substrate protein determines how it is recognized and processed within the cell (for reviews, see [208,

277]). For the purpose of proteasomal degradation, it is widely agreed upon that lysine-

48 (K48) linked polyubiquitin, attached to the substrate protein via glycine-76 (G76), is sufficient to target the protein for degradation [34]. Furthermore, it is thought that a minimum of four ubiquitin molecules must be present in the aforementioned polyubiquitin chain in order for degradation procession [256].

Once a protein is targeted for degradation by the addition of a K48-linked polyubiquitin chain, it will then be processed and degraded by the enzymatic activity of the proteasome and recycled into amino acids [52, 211]. This begins with the initial reversible binding of the substrate to the 19S regulatory particle in an ATP-independent manner; this depends only on the presence of the polyubiquitin chain and can even occur at temperatures as cold as 4°C [44, 197]. However, a subsequent and stronger association between the substrate and the proteasome is then possible that is based on the ubiquitinated protein’s structure and is ATP-dependent [197]. The brief time in between these two interactions allows for competing ubiquitin-recognition processes to occur, should they be appropriate [44]. It is possible to release a substrate protein from the initial interaction with the 19S regulatory particle through the action of deubiquitinating enzymes [154]. However, upon binding completion of the ubiquitinated substrate to the 19S regulatory particle, structural changes within the 19S complex itself

will occur that facilitate substrate entry into the 20S core particle [44, 165]. Specifically, cryo-electron microscopic methods have revealed a widening of the central ATPase ring that makes up the 19S regulatory particle, allowing for substrate translocation. However, before a substrate can enter the core particle, it first must be deubiquitinated, which occurs through the action of deubiquitination enzymes, three of which are primarily associated with the proteasome: the metalloprotease Rpn11 and the cysteine proteases

Usp14 and Uch37/Uchl5 [23, 245, 264, 289]. Additionally, in order for a substrate to become completely engulfed by core particle of the proteasome, it first must be at least partially unfolded. This unfolding has been shown to occur via the induced linearization of the polypeptide caused by the ATP-dependent translocation through the ATPase central channel of the 19S regulatory particle [143]. Once a substrate has been unfolded and deubiquitinated, it can then enter the core particle through the process of facilitated diffusion [233]. Finally, once a substrate has made its way into the 20S core particle, proteolysis occurs which is mediated by nucleophilic attack via N-terminal threonine residues on the β subunits [113]. If a misfolded protein targeted for proteasomal degradation fails to be processed accordingly, it could be shuttled into a larger, insoluble structure within the cell, destined to be degraded by other cellular mechanisms, such as autophagy.

The Autohphagy-Lysosomal System

The autophagy-lysosomal system, often referred to as the process of macroautophagy or autophagy, is broadly responsible for the degradation of cytoplasmic cellular components, and does this through the formation of a double membraned vesicle around the cellular cargo and subsequent catabolism via lysosomal hydrolases [150, 210]. It can be induced by a variety of cellular stressors, such as

starvation, growth factor inadequacies, and an abundance of misfolded proteins [150].

This process is initiated by the formation of the phagophore and sequentially the autophagosome, which engulfs cellular material marked for degradation [177]. This is followed by the migration of the autophagosome to the lysosome itself and the fusion of the two compartments [177]. The contents of this fused structure are then degraded by lysosomal hydrolases. Autophagy broadly maintains homeostasis in the cell and, aside from degrading damaged/aged cellular components, also functions to recycle bioenergetic components (such as amino acids) during periods of cellular nutrient starvation [150, 176]. In contrast to the proteasome, however, the autophagic process does not require any specificity to ubiquitinated substrates, nor does it display a preference for shorter-lived proteins. Instead, the lysosome (the end-stage step during autophagy) can be viewed as a trash receptacle for the cell, the contents of which can be degraded in either a targeted or nonspecific manner [150].

The original discoveries of the molecular mechanisms of autophagy were made in genetic studies using yeast (Saccharomyces cerevisiae), which identified a plethora of autophagy-related (Atg) genes and their corresponding encoded proteins [148, 257,

260]. While the list of proteins is extensive (for a review, see [178]), they can be divided into different complexes that are essential for autophagosome formation. First, the formation of the Atg1/Unc-51-like kinase (ULK) complex occurs, which contains the only proteins with kinase activity among the Atg proteins [178]. This complex contains yeast

Atg proteins 1, 11, 13, 17, 29 and 31 [or Atg13, focal adhesion kinase family interacting protein of 200 kDa (FIP200), and Atg101 in mammals], and functions to initiate the formation of the pre-autophagosomal structure (PAS) [191, 247]. This structure,

originally discovered in yeast, is localized near the vacuole membrane and is a hot spot for Atg proteins. Importantly, the mammalian target of rapamycin complex 1 (mTORC1) negatively regulates the formation of the Atg1/ULK complex under nutrient-rich conditions [22, 178]. Autophagy induction leads to the dephosphorylation and subsequent activation of the ULK kinases. This feature of the autophagy pathway grants researchers the ability to augment autophagic flux using small molecules that inhibit mTOR, such as rapamycin [22, 213]. Broadly, it is thought that this selective variant of autophagic degradation [sometimes referred to as the cytoplasm-to-vacuole targeting

(CVT) pathway] occurs under low-stress, high nutrient conditions [150]. This is associated with mTOR being maintained in an active state. However, under starvation conditions, mTOR becomes inactivated leading to the induction of autophagy in an effort to provide the cell with basic bioenergetics components as an alternative strategy

[150].

Once autophagy has been initiated, the next step in the autophagosome formation process is the generation of the phosphatidylinositol 3-kinase (PI3K) complex, which yields phosphatidylinositol 3-phosphate (PI3P) in the PAS. This complex, which is critical for initiating the nucleation process in the assembly of the PAS, contains vacuolar protein sorting-associated (VPS) 34, VPS15, and Atg14 [150, 178, 288], and is activated by Atg13 and Atg9. Additionally, in conjunction with Beclin 1 (of which the yeast homolog is Atg6), this complex is responsible for the recruitment/localization of a host of other Atg proteins to the PAS, which are critical for the expansion of the vesicle membrane in this subcellular region [150]. Further expansion and eventual completion of the vesicle around cellular cargo destined for degradation is facilitated by the

Atg5/Atg12 complex in conjunction with Atg16, which are recruited to the PAS in a PI3K complex-dependent manner [150]. The expansion of the vesicle is also assisted by the

Atg8-phosphatidylethanolamine (PE) conjugate [150, 288]. While the Atg5-Atg12-Atg16 complex is thought to coat the vesicle itself as it forms, the Atg8-PE conjugate interacts with each surface of the expanding autophagosome, acting as a structural component during elongation [150, 288]. This is followed by vesicle completion, which is characterized by the fusion of the two ends in a manner independent of soluble N- ethylmaleimide sensitive factor attachment (SNARE) proteins (which are required for other endosomal processes) [209]. Immediately prior to fusion completion, the Atg8-PE conjugate is removed from the vesicle surface through the actions of the Atg4 protease, which is followed by the release of the other Atg complexes (Atg5/Atg12, Atg16) [150,

288].

Finally, the completed autophagosome is targeted to the vacuole and fuses with it, merging the contents of the two compartments. This fusion occurs in a similar manner as other membrane fusion events, including those of late endosomes, multivesicular bodies, and Golgi (which all use the same mechanisms involving SNARE proteins to achieve fusion) [150, 278]. The next step in autophagy, the degradation of cargo delivered by the autophagosome, is mediated by hydrolases such as cathepsins B, L, and D and the lipase Atg15 [135, 150]. In order to recycle the breakdown products of autophagy for future use, it is thought that particular vacuolar effluxers, such as Atg22,

Avt3, and Avt4, work to shuttle amino acids from the lysosome/vacuole into the cytoplasm [287]. As mentioned previously, this is of particular importance under

conditions of cellular stress and is known to specifically help maintain protein synthesis and cellular viability during nitrogen starvation.

Effects of Pathologic Proteinopathies on Proteostasis

Proteins that are thought to be causative agents of human neurodegenerative diseases, including the microtubule associated protein tau, amyloid-β, α-synuclein, and

SOD1, are all proteins known to misfold and form aggregates in the cases of

Alzheimer’s disease, Parkinson’s disease and familial variants of ALS, respectively [28,

98, 242, 280]. Furthermore, there is evidence that each of these individual proteins, when present in a known pathogenic state, disrupt cellular proteostasis to a certain extent. While the effects upon proteostatic components are thought to be differential and dependent upon the protein in question, it generally accepted that the accumulation of misfolded proteins in the manner of which occurs in human neurodegenerative disorders is sufficient to impair the balance of proteostasis [14, 67, 152, 180].

The microtubule associated protein tau is affected in neurodegenerative disorders termed “tauopathies”, and in the case of disease it is known to misfold, dissociate from microtubules and become hyperphosphorylated to form aggregates (for a review, see [184]). Specific aggregates known to be composed of tau often have specific names, including neurofibrillary tangles (NFTs) in Alzheimer’s disease and Pick bodies in the case of Pick’s disease[93, 203]. An abundance of misfolded tau within affected neurons is thought to place additional stress upon proteostatic network components, such as chaperones, the ubiquitin-proteasome system, and autophagy.

Tau is known to associate with a plethora of chaperones that are engaged in multiple functions, including the facilitation of microtubule binding and its proteolytic turnover [61,

66, 73, 129, 137, 175, 198, 218]. It has therefore been proposed that the accumulation

of misfolded tau, and other proteins that misfold in neurodegenerative diseases, can disrupt the availability of chaperones for other substrates due to the tightly balanced state in which proteostasis exists [200]. Aside from chaperones, an interactome mapping study conducted by Wang and colleagues [272] identified Otub1, a deubiquitinating enzyme, as an interactor with Tau using PS19 mice. Otub1 was found to impact K48-linked tau deubiquitination and impair tau degradation. The accumulation of insoluble tau has also been found to reduce the activity of 26S proteasomes within the brains of rTg4510 tauopathy mice, leading to an accumulation of ubiquitinated proteins and a fluorescent reporter used to assess proteasome function [187]. Lastly, tau is known to be preferentially be degraded through specific molecular pathways, leading to its catabolism either via the proteasome or autophagy [10, 31, 73]. Different mutations in tau have been found to differentially perturb its degradation by multiple autophagic pathways [31]. Thus, pathologic tau variants are thought to be capable of inducing a disruption in cellular proteostasis in a multifaceted manner.

The primary protein known to misfold and aggregate in Parkinson’s disease,

Lewy body variant Alzheimer’s disease, dementia with Lewy bodies, and multiple system atrophy is α-synuclein [9, 70, 84, 240, 242, 261]. Aggregates composed of this protein are also known to deleteriously affect proteostatic network components. Along a similar vein as was discussed in relation to tau, the accumulation of misfolded α- synuclein is thought to overwhelm the capacity of normal levels of molecular chaperones present at any given time. This idea is reinforced by the many studies demonstrating the ability of a wide variety of chaperones to prevent α-synuclein aggregation and remedy its toxicity in a variety of in vitro and in vivo models [3, 47, 54,

72, 76, 164]. Additionally, the relationship between pathogenic variants of α-synuclein and proteasome dysfunction is well established. First, Emmanouilidou and colleagues demonstrated using PC12 cells stably expressing both wild-type and mutant α-synuclein that not only do soluble, oligomeric α-synuclein species associate with the 26S proteasome, but they also increase in abundance following the use of proteasomal inhibitors [75]. Most importantly, the stable expression of α-synuclein in these cells also significantly reduced proteasome activity without influencing proteasome levels/assembly. A similar study revealed using HEK293 cells that α-synuclein protofibrils, but not monomers/dimers, impaired proteasomal function as evidenced by the hindered degradation of polyubiquitinated folded proteins [293]. This study also found that these protofibrils preferably bind to the 26S proteasome relative to the monomers/dimers. Lastly, both monomeric and aggregated species of α-synuclein have been found to bind the S6’ subunit of the 19S cap within the 26S proteasome, which normally functions to regulate substrate entry into the 20S core particle for degradation

[235].

Aside from work done in vitro to assess the interaction between α-synuclein and the proteasome, similar studies have been conducted using mouse models of synucleinopathy relevant to human disease. Data has also been gathered on proteasomal dysfunction in human PD brains. One particular study published in 2006 revealed abnormalities in proteasome function and composition in the hm2α-SYN-39 mouse model of synucleinopathy [212]. This transgenic model expresses a double mutant variant of α-synuclein (A30P/A53T); both mutations are known to be associated with familial PD. The expression of this protein not only decreased levels of activity in

the 20S core particle of the proteasome, but also reduced levels of two different subunits within the 19S regulatory particle, Rpt1 and Rpn2 [35]. These deficits were proportional to the degree of neurodegeneration within the substantia nigra that occurs in this model. Regarding studies conducted in human patients with PD, McNaught and colleagues have published a range of studies characterizing proteasomal abnormalities, including evidence for reduced enzymatic activity, loss of specific subunits, and a thorough review of the relationship between proteasomal dysfunction and relevant genes linked to PD [170–172]. The above studies demonstrate that pathologic α- synuclein is capable of, at least to a certain extent, disrupting proteostasis.

ALS is a devastating disease characterized by the death of motor neurons in the brain and spinal cord that is often fatal due to paralysis. In a subset of familial ALS cases (10-20%), the protein superoxide dismutase 1 (SOD1) becomes mutated, leading to aberrant misfolding and aggregation of the SOD1 protein [6]. While not all mutations have been characterized, all investigated mutants have been shown to promote the formation of detergent-insoluble aggregates of the protein [6, 28, 130, 138, 269]. As is the case with previously discussed proteins that aggregate in the context of neurodegenerative disorders, pathologic SOD1 has been proposed to perturb proteostatic functions within affected neurons. Many of these studies have been conducted using the G93A SOD1 transgenic mouse model, which is widely used to study ALS [101]. Aggregates composed of this mutant SOD1 variant have been found to be polyubiquitinated in a K48-linked manner (indicative as being targeted for degradation by the proteasome), and this ubiquitination correlates with a reduction in levels of the 20S core and 19S regulatory particles that make up the 26S proteasome

within motor neurons [17, 37]. An additional study showed the accumulation of a GFP- tagged mutant ubiquitin (G76V) reporter in G93A SOD1 mice, demonstrating impaired proteasomal degradation relative to control animals [36]. Regarding similar studies in human patients, an analysis of spinal cord tissue obtained at autopsy from both sporadic ALS and control patients revealed both a decrease in the enzymatic activity

(chymotrypsin-, caspase-, and trypsin-like) of the proteasome as well as reduced proteasome expression in motor neurons [132]. This study also highlighted specific changes regarding the proteasome observed in both ventral and dorsal portions of the spinal cord that had previously been reported in SOD1 G93A mice. These changes include a reduction in enzymatic activity of all three subtypes, reduction in β5 subunit levels (a specific subunit with chymotrypsin-like activity), a decrease in 19S5a cap protein levels (a protein responsible for processing ubiquitinated substrates) and a decrease in 20S proteasome levels that is specific to motor neurons as compared to general neuropil [131–133]. Overall, the evidence for proteostatic disruption in the face of pathogenic levels of misfolded tau, α-synuclein, and SOD1 provides the rationale to further investigate the effects that these deleterious effects have on cellular and proteome integrity.

Evidence for Compromised Cellular Protein Folding in the Face of Neurodegenerative Proteinopathies

Additional burden upon proteostasis in the presence of pathological misfolded proteins has given rise to the idea that overall cellular protein folding/degradation might not function at full capacity in the cases of these diseases. Aside from the aforementioned evidence that overall proteostatic efficacy could be hindered during instances of human neurodegenerative disease, there is also evidence for hindered

folding capacities of specific proteins that depend upon a functional proteostasis network. This idea was pioneered in the C. elegans invertebrate model, specifically using transgenesis to express intrinsically metastable, mutant, temperature-sensitive

(TS) proteins in these organisms [90]. These nematode worms were also designed to express, in addition to the TS mutants, a mutant variant of the exon 1 fragment of huntingtin (HTT), which is prone to aggregate [220]. These TS mutant proteins

(paramyosin and dynamin-1) achieve a functional conformation at a permissive temperature of 15°C. However, their function becomes compromised at a restrictive temperature (25°C) [90]. When mutant HTT was introduced at lower temperatures, it placed a burden upon cellular folding systems, preventing the TS mutants from reaching a conformation that yields functionality. In this paradigm, not only did the added stress from mutant HTT impact the stability of the TS mutant proteins, but the same effect occurred in reverse. The presence of TS mutant proteins exacerbated HTT aggregation, supporting the idea that protein folding machinery can be overly burdened by proteins thought to require a high degree of proteostatic maintenance [90]. This study in C. elegans, among others conducted by Gidalevitz and colleagues [91], were the some of the first to describe the effect of “bystander” or “secondary” misfolding of a metastable protein due to the introduction of another protein that is prone to misfold and/or aggregate.

Aside from studies in invertebrate models suggesting that hindered cellular protein folding may be a side effect of an overabundance of any misfolded protein pathology, this idea has been further studied in additional model systems, including human cells and in an animal model that exhibits amyloid plaques (a hallmark of

Alzheimer’s disease). First, in multiple studies using heat shock as an inducer of acute proteostatic stress, it was found that in HEK293, CCF-STTG1 and SH-SY5Y cells a specific subproteome was vulnerable to misfolding, as determined by assessing their solubility in stringent detergents [283, 284]. Multiple proteins were similarly vulnerable across these different cell lines, including ubiquitin, CDK1, FEN1 and MATR3, with

TDP-43 being common between CCF-STTG1 and HEK293 cells. While these studies slightly differ from those done in C. elegans with the use of heat shock to stress proteome stability as opposed to the introduction of an aggregation-prone protein, they are nonetheless informative as heat is a canonically accepted strain upon protein stability [162]. Additionally, this work strengthened the hypothesis that proteostatic stress, no matter the source, can compromise the folding capacities of metastable proteins. These studies in cell culture models also utilized the transient transfection of mutant huntingtin containing 103 polyQ repeats. As expected, the introduction of aggregation-prone huntingtin induced the accumulation of the previously identified vulnerable proteins (CDK1, FEN1, MATR3, Ubiquitin, and TDP-43) in detergent- insoluble fractions, suggestive of their misfolded state [283]. Broadly, these initial cell culture experiments further demonstrate how varying sources of proteostatic stress can lead to the over-representation of a select group of proteins in detergent-insoluble fractions.

The concept of “bystander” or “secondary” misfolded has been extended into a mouse model of Alzheimer’s amyloidosis. These transgenic mice, collectively referred to as APPswe/PS1dE9 or Line 85 (L85) mice, express the Swedish mutation in the amyloid precursor protein and the deletion of exon 9 in the presenilin 1 gene [127]. This

leads to the accumulation of amyloid plaques largely in the cortex and hippocampus beginning at 6 months of age and continues to worsen in severity up to 12 months of age [85]. Through the use of a novel detergent extraction protocol coupled to bottom-up proteomics, it was identified, in a similar manner to the aforementioned cell lines, that a subset of proteins was vulnerable to the loss of solubility in the presence of amyloid plaques [285]. Upon this discovery, it was presumed that these proteins are dependent upon efficient proteostatic capacities within affected cells and amyloid deposition can impose a burden upon proteostasis. The accumulation of these aberrantly insoluble proteins coincided with an increase in K-48-linked polyubiquitin, which is consistent with diminished proteostasis and/or proteasomal function [20]. However, amyloid plaques persist extracellularly in the case of Alzheimer’s disease, so the effects of intracellular misfolded protein inclusions were not determined within the scope of this study. Indeed, pathogenic variants of the amyloid-β protein are known to be degraded by a range of extracellular proteases including insulin-degrading enzyme [77], neprilysin [125], angiotensin-converting enzyme [115] and matrix metalloproteinases [11], and intracellular proteostasis could differentially be affected by inclusions that persist in the cytosol. Thus, further work is needed to determine whether a predominantly cytosolic proteinopathy is capable of inducing similar, or even more severe, insults in proteome solubility, as these proteinopathies are more likely to engage intracellular proteostatic components. The following chapters describe experiments aimed at discovering the degree fo bystander misfolding that occurs in mouse models of neurodegenerative proteinopathies and whether this misfolding can be remedied by altering aspects of cellular proteostasis.

CHAPTER 2 5DIFFERENTIAL INDUCTION OF MUTANT SOD1 MISFOLDING AND AGGREGATION BY TAU AND α-SYNUCLEIN PATHOLOGY

Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS) and

Huntington’s disease are often defined pathologically by the accumulation of misfolded proteins that become aggregated to form intracellular and/or extracellular inclusions [1–

4]. This underlying theme across these diseases has suggested that a similar pathogenic mechanism contributes, at least in part, to the development and/or progression of these disorders. To date, defects in many cellular pathways have been implicated in the pathogenesis of these diseases [5,6]. Some of these suspected pathways are critical in cellular protein quality control such as the ubiquitin-proteasome system (UPS) (reviewed in [7]) and autophagy (reviewed in [8]). Indeed, it has been previously demonstrated that pathological forms of tau (associated with Alzheimer’s disease and various tauopathies) and αSyn (associated with Parkinson’s disease and other synucleinopathies) can hinder the efficacy of the proteasome [9–16]. This finding is further supported by the accumulation of ubiquitin-positive inclusions in the cases of many neurodegenerative disorders [17–19]. Hence, one hypothesis that has gained traction is that protein aggregation in these neurodegenerative disorders is a biomarker of underlying dysfunction in protein quality control systems (reviewed in [20]).

Protein homeostasis (proteostasis) is maintained by a network of factors

(reviewed in [21–23]) that primarily fall into three main components at the cytosolic level: molecular chaperones responsible for folding newly synthesized proteins and refolding misfolded proteins [24], the UPS which is responsible for the degradation of misfolded and inherently short-lived proteins (reviewed in [25,26]), and the autophagy-

lysosomal pathway which is necessary for the removal of large insoluble protein aggregates that cannot otherwise be degraded [27]. The implications of this systemic malfunction in proteostasis could be widespread at the cellular level, and one particular idea that has emerged is the concept of “secondary” protein misfolding, where the accumulation of one misfolded protein imposes a burden on the proteostasis network that leaves other vulnerable proteins with insufficient support to fold correctly [28,29].

Disruption of the proteostasis network could potentially explain the origin of mixed pathologies in human neurodegenerative diseases, which are relatively common [30–

34]. Accordingly, we have previously shown the aggregation of phosphorylated TDP-43 protein as a secondary event to the aggregation of phosphorylated tau in two independent transgenic models [35]. These instances of mixed pathologies could, however, have been a result of cross-seeding, which has been demonstrated for many proteins pathologically associated with neurodegeneration [36–41].

The original concept of secondary misfolding was characterized in the invertebrate C. elegans. In this study, it was found that the expression of an aggregation-prone protein could impair the folding integrity of other proteins, or

“bystander” proteins [28]. Specifically, a fragment of (exon 1) mutant human huntingtin

(HTT) gene containing a polyglutamine (polyQ) expansion was co-expressed with temperature-sensitive (TS) mutant forms of paramyosin and dynamin-1. Both proteins achieve functional conformations at lower temperatures (15°C), but are inactive at 25°C.

Mutant huntingtin exon-1 fragments are very prone to aggregate [42] and, when expressed in the muscle wall of C. elegans concomitantly with these TS mutants, the

TS proteins failed to achieve active conformations at 15°C [28]. This outcome was

thought to be due to the stress placed upon the proteostasis network by mutant huntingtin, overwhelming the system and preventing proteins that are particularly dependent upon the proteostasis network (e.g. TS mutant proteins) from achieving active conformations [28]. Interestingly, the added burden of co-expressed TS mutant proteins exacerbated the aggregation of mutant huntingtin, supporting the argument that the capacity of the cellular protein folding machinery of C. elegans is limited and easily over-burdened.

In the present study, we asked whether the deposition of human tau or αSyn aggregates in the central nervous system (CNS) of mouse models might impose a burden on proteostatic function using a mutant form of SOD1 fused to YFP as a reporter in a paradigm akin to the foregoing C. elegans studies. We have been using a mouse model that expresses the G85R variant of SOD1 fused to YFP as model in studies of prion-like propagation of misfolded SOD1 [43–45]. Hemizygous mice expressing G85R-

SOD1:YFP do not intrinsically develop ALS symptoms or show inclusion pathology, while homozygous G85R-SOD1:YFP mice develop paralysis from six months onward with spinal cords that contain fluorescent inclusions and detergent-insoluble G85R-

SOD1:YFP [46]. Thus, the hemizygous G85R-SOD1:YFP mouse could be viewed as model that is sub-threshold for induction of disease. In such a setting, any perturbation that diminished proteostatic function could then lead to a breach of threshold to induce mutant SOD1 aggregation. Importantly, the YFP tag on the G85R-SOD1 protein allows for simple detection and visualization of aggregation and inclusion formation, and we use this feature as a readout to assess secondary misfolding in mice that develop tau and αSyn pathology. We crossed the G85R-SOD1:YFP mice to three different models

of proteinopathies: 1) a model of spinal tau pathology expressing human P301L tau

(termed JNPL3 [47]), 2) a model of spinal αSyn pathology expressing human A53T

αSyn (termed M83 [48]), and 3) a model of cortical tau pathology expressing human

P301L tau (termed rTg4510 [49,50]). Despite abundant proteinopathy in these models, only bigenic mice from the cross with JNPL3 mice caused robust G85R-SOD1:YFP pathology to develop. Our findings demonstrate complex interactions between pathologically misfolded tau, αSyn and the proteostatic network in triggering the

“secondary aggregation” of our mutant SOD1 reporter.

Methods

Transgenic Mice

To model tauopathy, we utilized both the JNPL3 and rTg4510 mouse models.

Briefly, JNPL3 mice (maintained on the Swiss Webster background from Taconic) express mutant human tau (P301L, 4R0N) under the mouse prion promoter which leads to mutant tau pathology primarily in the spinal cord and brain stem (though other regions are more modestly affected) [158]. rTg4510 mice (maintained on a hybrid

129S6/FVB background) are bigenic mice that express both human tau with the P301L mutation (4R0N) behind by a disrupted minimal CMV promoter and the tet- transactivator (tTA) driven by a Ca2+ calmodulin kinase II (CaMKII) promoter (forebrain- specific). The tTA protein binds to the disrupted promoter to drive mutant tau expression at high levels, primarily within the hippocampus and neocortex [207, 217]. To model α- synucleinopathy, we used the M83 mouse model (maintained on the hybrid C3H/B6 background). This model overexpresses mutant (A53T) human αSyn under the mouse prion promoter [87], and develops αSyn pathology primarily within the spinal cord, brain stem midbrain, hypothalamus, thalamus and periaqueductal gray regions (with other

brain regions also somewhat affected), resulting in a severe motor phenotype and paralysis. This pathology and phenotype occurs between 8-16 months of age in homozygous M83 mice, but later than 21 months in hemizygous M83 mice [87]. Lastly, hemizygous mice (maintained on the FVB background) expressing the G85R mutant of

SOD1 tagged to YFP under the human SOD1 promoter were used for all crossing experiments [268].

All mice were kept in specific pathogen free cages prior to harvesting and histology procedures. All animals were handled and processed according to approved protocols by the University of Florida Institutional Animal Care and Use Committee

(IACUC). All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Breeding Scheme to Generate Mice Co-expressing G85R-SOD1:YFP and Mutant Proteins Associated with Human Proteinopathies

Mice heterozygous for the G85R-SOD1:YFP transgene were bred to mice transgenic for either mutant tau or αSyn. In order to generate JNPL3-G85R-SOD1:YFP animals, we first bred heterozygous JNPL3 mice to heterozygous G85R-SOD1:YFP mice to produce male animals expressing both the JNPL3 tau and SOD1 transgenes.

These were bred to a homozygous JNPL3 female mice to produce offspring that were then bred to generate a large cohort of mice, some of which expressed both mutant tau and our reporter G85R-SOD1:YFP transgene. A subset of these mice were expected to be homozygous for the tau transgene and to develop early onset tauopathy, with a subset of these mice being transgenic for the G85R-SOD1:YFP transgene. To generate mice expressing both mutant αSyn and our G85R-SOD1:YFP reporter,

homozygous M83 mice were bred to mice heterozygous for the G85R-SOD1:YFP transgene. Mice expressing G85R-SOD1:YFP as well as the transgenes associated with the rTg4510 line are triple transgenic animals, which were generated by first crossing mice transgenic for P301L mutant tau to mice transgenic for G85R-SOD1:YFP.

The double transgenic mice generated from this cross were then crossed to mice transgenic for tTA under the CaMKII promoter in order to generate rTg4510 mice

(tau/tTA) expressing G85R-SOD1:YFP.

Intramuscular Human αSyn Fibril Injections into Hemizygous M83 and Bigenic M83-G85R-SOD1:YFP Transgenic Mice to Seed αSyn Pathology

As has been previously described [216], sonicated wild type human αSyn fibrils

(2mg/mL) were injected at a volume of 5 μL into hemizygous M83xG85R-SOD1:YFP mice once they reached 8 weeks of age. Injections were conducted using a Hamilton 10

μL syringe (Reno, NV) along with a 25-gauge needle. The needle was injected ~1 mm deep into the gastrocnemius muscle bilaterally in each animal. Mice were anesthetized with isoflurane during the procedure.

Tissue Processing, Immunohistochemistry and Image Microscopy

Mice were euthanized by isoflurane anesthesia overdose with exsanguination and transcardial perfusion with cold PBS. The harvested brains were bisected sagittally and for a subset of animals, one hemi-brain was frozen on dry ice (stored at -80°C) and the other was drop fixed in 4% paraformaldehyde for 48 hours. For a subset of the animals, both hemi-brains were drop-fixed with one used for cryostat sections (10 µm) to directly visualize fluorescence and the other was embedded in paraffin for sectioning

(5 µm). The harvested spinal cords were divided into 4 equivalent segments. For two of the segments, the spinal column was drop-fixed in 4% paraformaldehyde for 48 hours before embedding in paraffin for sectioning. In a subset of animals, spinal segments were flash frozen on dry ice and then stored at -80°C. For a subset of animals, all 4 segments of spinal column were drop-fixed in 4% paraformaldehyde so that 2 of the segments could be sectioned by cryostat with 2 segments embedded in paraffin for sectioning. All sections were attached to Superfrost Plus microscope slides (Fisher

Scientific, Hampton, NH) for imaging. To prepare paraffin-embedded tissue for histology, sections first were de-paraffinized and rehydrated through immersion in serial dilutions of ethanol. For sections used for direct fluorescence microscopy, the frozen section or rehydrated paraffin section was coverslipped with Vectashield (Vector

Laboratories, Burlingame, CA) mounting medium. Tissue sections used for immunohistochemistry were rinsed in water, followed by antigen retrieval via a 30- minute incubation in a steamer containing citrate buffer (10 mM sodium citrate with

0.05% Tween-20, pH 6.0). The citrate antigen retrieval procedure quenches the fluorescence of the G85R-SOD1:YFP, requiring the use of a primary antibody to

GFP/YFP for visualization. Tissue sections were blocked using a PBS solution containing 3% normal goat serum and 0.1% Triton X-100. Primary antibodies in 3% normal goat serum in PBS-T were incubated overnight at 4 °C. For DAB-mediated immunostaining, endogenous peroxidases were blocked using a solution of 0.3% H2O2 in PBS. An ABC kit (Vector Laboratories, Burlingame, CA) was used with a DAB reagent set (KPL, Gaithersburg, MD) to detect signal. Sections were then counterstained with hematoxylin prior to dehydration in ethanol and coverslipping.

Primary antibodies used included AT8 (1:500, mouse monoclonal, Thermo Fisher,

Waltham, MA), MC1 (1:125, mouse monoclonal, Peter Davies), PHF1 (1:500, mouse monoclonal, Peter Davies), GFP (green fluorescent protein)/YFP (1:200, rabbit polyclonal, Invitrogen, Waltham, MA) and JL-8 GFP/YFP (1:200, mouse monoclonal,

Clontech, Mountain View, CA, USA). Secondary fluorescent antibodies used for immunofluorescence staining included goat anti-rabbit IgG (1:1000, Alexa Fluor 488,

Invitrogen, Waltham, MA) and goat anti-mouse IgG (1:1000, Alexa Fluor 568,

Invitrogen, Waltham, MA). Biotinylated secondary antibodies (Vector Laboratories,

Burlingame, CA) were used for DAB-mediated staining for 30 minutes at room temperature (1:500). Tissue sections were imaged using an Olympus DSU-IX81 spinning disc confocal microscope (Tokyo, Japan) or scanned using the Scanscope FL image scanner (Aperio, Vista, CA).

Fluorescence Quantification and Statistical Analysis

Fluorescence quantification, when necessary, was conducted using ImageJ

(version 1.51g). Statistical analyses were conducted using GraphPad PRISM (version

7.0h, La Jolla, CA).

Preparation of Brain and Spinal Cord Tissues for Immunoblot Analysis

To assess the levels of G85R-SOD1:YFP in the brains of trigenic rTg4510 x

G85R-SOD1:YFP mice, one hemi-forebrain was homogenized in PBS (10% weight/volume) with 1% protease inhibitor cocktail P8340 in DMSO (Sigma Aldrich, St.

Louis, MO). Protein concentrations were measured by the BCA (bicinchoninic) assay

(Fisher Scientific, Hampton, NH) and 20 μg of protein from each brain homogenate was

adjusted to 1 x Laemmli buffer, boiled, loaded onto a 4-20% Tris-glycine gel (Invitrogen,

Waltham, MA) and subjected to SDS-PAGE (120V for 90 minutes). Proteins were then transferred to nitrocellulose membranes overnight at 100 mA.

To generate detergent insoluble fractions from JNPL3/G85R-SOD1:YFP mice,

G85R-SOD1:YFP mice, JNPL3 mice, and nontransgenic control mice, we used a method used to fractionate insoluble SOD1 aggregates that has been previously described [138, 269]. Briefly, spinal cord tissues were dissected from the frozen spinal columns after a brief thaw and homogenized in 1x TEN (10mM Tris-HCl pH 7.5/1 mM

EDTA/100 mM NaCl) at a 10:1 volume to weight ratio. This homogenate was then mixed 1:1 with a second buffer containing 1x TEN with 1% NP40 and 1% protease inhibitor cocktail P8340 (Sigma Aldrich, St. Louis, MO). This mixture was sonicated and centrifuged at >1,000,000g in an airfuge (Beckman Coulter, Brea, CA) for 10 minutes to separate soluble from insoluble protein fractions. The pellet fraction was then washed in a buffer containing 1x TEN with 0.5% NP40, sonicated, and spun down to obtain the final pellet fraction which was resuspended in 30 μL of buffer containing 1x TEN with

0.5% NP40, 0.25% SDS, 0.5% deoxycholate and 1% protease inhibitor cocktail. Protein concentrations in each fraction were measured by BCA (bicinchoninic) assay (Fisher

Scientific, Hampton, NH). 20 µg of protein from each fraction, suspended in 1x Laemmli buffer, was boiled and then electrophoresed into 16% Tris-glycine gels before transfer to nitrocellulose membranes overnight at 100mA. The membranes were then analyzed with antibodies to SOD1 as described below.

To examine the levels of insoluble αSyn and SOD1 in M83/G85R-

SOD1:YFP mice, the protocol used for detergent extraction and sedimentation differed

slightly, following a previously described method [285]. Briefly, the tissue was initially homogenized in PBS containing 1% protease inhibitor cocktail and then centrifuged at

100,000 x g for 30 minutes. The supernatant was collected and saved as the PBS- soluble fraction. The pellet was resuspended in 1x TEN buffer containing 0.5% NP40 by brief sonication and then centrifuged at 100,000 x g (Optima L100K Ultracentrifuge

[Beckman Coulter, Brea, CA] using a 70.1 Ti rotor at 35,000 RPM) for 30 minutes to produce NP-40 soluble and insoluble fractions. The NP-40 insoluble pellet was then resuspended in a volume of TEN with 2% sodium deoxycholate equal to the original homogenization volume by brief sonication. 30 µL of either PBS-soluble or NP40- insoluble protein fractions were mixed with 4 x Laemmli buffer, boiled, and loaded onto a 16% Tris-glycine gel. After transfer to nitrocellulose at 300 mA for 1 hour, the membranes were probed with antibodies to SOD1 and αSyn as described below.

Immunoblotting and Western Blot Quantification

Nitrocellulose membranes were blocked in a 5% powdered milk (Nestle

Carnation, Glendale, CA) solution in PBS-T. The membrane was then incubated in primary antibody in the blocking solution overnight, followed by three 10-minute washes in PBS-T. Primary antibodies included GAPDH (1:5000, Meridian Life Science,

Memphis, TN), Tau13 (1:1000, BioLegend, San Diego, CA), mouse/human SOD1

(1:4000, generated in-house) and human SOD1 (1:2500, generated in-house [27]).

Horseradish peroxidase-conjugated secondary anti-mouse or anti-rabbit antibody

(Vector Laboratories, Burlingame, CA) was used in order to visualize proteins by chemiluminescence using the Pierce ECL Western Blot Substrate Kit (Thermo

Scientific, Waltham, MA). Western blot quantification was conducted using GeneTools by Syngene (in correlation with the GeneSys imager, Daly City, CA).

Results

Mutant Tau Induces G85R-SOD1:YFP Inclusion Pathology in the Spinal Cord and Brain Stem

In order to determine whether tau pathology could induce G85R-SOD1:YFP to aggregate by a proteinopathy, we analyzed the JNPL3 transgenic mice model of spinal tau pathology on the hemizygous G85R-SOD1:YFP background. For this study, only female bigenic JNPL3/G85R-SOD1:YFP mice were analyzed due to the differences in tau transgene expression between males and females that we previously reported in the

JNPL3 mice (specifically that females express mutant tau at much higher levels than their male counterparts) [157]. JNPL3/G85R-SOD1:YFP and JNPL3 transgenic animals were harvested at humane endpoints (ranging from 7 to 15.5 months of age), characterized by paralysis in at least one limb (usually a hind limb). Compared to littermates that were transgenic only for tau, JNPL3/G85R-SOD1:YFP mice showed a statistically significant, but modest acceleration of the paralysis phenotype (Figure 2-1).

We hypothesized that the presence of tau pathology in the JNPL3/G85R-

SOD1:YFP animals could act as a stressor upon cellular proteostasis that could cause bystander aggregation of G85R-SOD1:YFP and the formation of fluorescent inclusions.

In contrast to the soluble and diffuse distribution of G85R-SOD1:YFP seen in hemizygous animals (Figure 2-2 a and b), JNPL3/G85R-SOD1:YFP bigenic mice exhibited robust inclusion pathology in the form of widespread punctate aggregates in the gray matter visible by direct fluorescence (Figure 2-2 c and d). This pathology was

predominantly observed in the spinal cord and brain stem (Figure 2-2, Figure 2-3), the same regions that are subject to heavy tau burden in the JNPL3 model (Figure 2-4, spinal tauopathy shown)[158]. The abundant fluorescent neuropil aggregates with granular/punctate pathology in the cell body was similar in appearance to what has been described for the homozygous G85-SOD1:YFP mice that develop paralysis [268] and for G85R-SOD1:YFP mice induced to develop paralysis by prion-like transmission experiments [7].

To further confirm that G85R-SOD1:YFP in the bigenic tau/SOD1 mice was aggregated, we conducted detergent extraction and sedimentation of spinal cords from these mice to determine changes in protein solubility. In previous study, we have demonstrated that the aggregates formed by mutant SOD1 become aberrantly crosslinked through disulfide oxidation and to visual these aggregates the SDS-PAGE was performed in the absence of reducing agent [138]. As expected from this prior study, soluble G85R-SOD1:YFP was detected in spinal cord extracts from bigenic tau/SOD1 mice and mice expressing G85R-SOD1:YFP alone, but NP40-insoluble, highly crosslinked, G85R-SOD1:YFP was only detected in the tau/SOD1 bigenic mice that showed inclusion pathology (Figure 2-5 a and b). Collectively, these data demonstrate that the G85R-SOD1:YFP protein was induced to misfold and aggregate in the spinal cords of mice with abundant spinal tau pathology.

Localization of SOD1 Pathology Relative to Tau Pathology

We next sought to determine whether the G85R-SOD1:YFP inclusions were simply co-depositing with aggregating tau. To our knowledge, no interaction between these two proteins has been reported, nor has SOD1 pathology been described as a

secondary event to tauopathy. We performed double immunostaining of brain and spinal cord tissues with three well-characterized tau antibodies (MC1, PHF1, or AT8) in conjunction with a primary antibody to YFP to assess tau and SOD1 pathology (Figures

2-6, 2-7 and 2-8). Both end-stage JNPL3 mice and JNPL3/G85R-SOD1:YFP mice had extensive tau pathology (Figure 2-4, Figure 2-6 a and b, Figure 2-7 a and b, and Figure

2-8 a and b). Consistent with our original reports on the pathology of JNPL3 mice, both hyperphosphorylated tau as detected by AT8 and PHF1 immunostaining, and tau of an abnormal conformation as detected by MC1 immunostaining were present [157, 158].

We observed limited co-localization between the tau and SOD1 aggregates in the spinal cord of JNPL3/G85R-SOD1:YFP bigenic animals (Figure 2-6d, Figure 2-7d and Figure

2-8d). Overall, bigenic animals exhibit both robust tau and SOD1 pathology, but with no obvious direct evidence for co-aggregation occurring between the two proteins.

Lack of G85R-SOD1:YFP Inclusion Pathology Induction in the rTg4510 Model of Cortical and Hippocampal Tauopathy

Neither homozygous nor hemizygous G85R-SOD1:YFP mice typically develop inclusion pathology in the forebrain (cortex, hippocampus, striatum) similar to the degree that is seen in the spinal cord [268]. To assess whether cortical/hippocampal tau pathology could also induce secondary aggregation of G85R-SOD1:YFP, we used the rTg4510 model that develops robust cortical tau pathology by 5.5 months of age (Figure

2-9 a and b and Figure 2-10) [207, 217]. The introduction of G85R-SOD1:YFP expression in rTg4510 mice yielded no noticeable motor phenotype and despite very robust tau pathology, there was no clear formation of widespread fluorescent inclusions in rTg4510/G85R-SOD1:YFP mice (Figure 2-9d, cortex shown). In these trigenic mice,

there was a general increase in overall fluorescence intensity throughout the cortex and hippocampus with occasional cells that were intensely fluorescent (Figure 2-9d; for quantification of direct fluorescence see Figure 2-11) as compared to single transgenic

G85R-SOD1:YFP controls (Figure 2-9 c and d). However, we could not attribute the increased fluorescence to increased levels of G85R-SOD1:YFP protein in immunoblot analysis of forebrains in the trigenic mice compared to G85R-SOD1:YFP alone (Figure

2-11) and thus the basis for the heightened fluorescence intensity is unknown. In any case, there was no evidence of fluorescent inclusions as was observed in the

JNPL3/G85R-SOD1:YFP bigenic mice.

Paucity of Induced G85R-SOD1:YFP Aggregation in the M83 Model of αSynucleinopathy

Given our observation of aggregated SOD1:YFP reporter in the JNPL3 model of spinal tauopathy, we next sought to determine whether the effects we observed were specific to tau or could be extended to a different type of spinal proteinopathy. We utilized the M83 model of αSyn-opathy that expresses mutant (A53T) αSyn under the mouse prion promoter [87], which is the same vector that was used to create the JNPL3 tauopathy model. The two models show very similar anatomical pathological burden

(compare Figure 2-4 to Figure 2-12) and both develop paralytic phenotypes. To induce the αSyn pathology, bigenic M83/G85R-SOD1:YFP mice were injected intramuscularly with fibrillized human αSyn protein as previously described [216]. This seeded induction of αSyn pathology produces a predictably accelerated robust spinal pathology that is accompanied by a paralytic motor phenotype (between 3 and 4 months post-IM- injection) compared to uninjected hemizygous M83 mice, which acquire this phenotype later than 21 months of age [87, 216]. Unexpectedly, the spinal cords and brainstems of

paralyzed bigenic M83/G85R-SOD1:YFP lacked any evidence of G85R-SOD1:YFP inclusions (Figure 2-13). There was no significant difference observed in motor phenotype for mice expressing only αSyn versus double transgenic animals expressing both αSyn and G85R-SOD1:YFP (Figure 2-14). The level of αSyn pathology in these bigenic mice was not obviously different from that of M83 littermates that also were IM injected with αSyn fibrils (Figure 2-12). Thus, in stark contrast to tau pathology, we do not observe secondary G85R-SOD1:YFP pathology in the presence of αSyn pathology.

To confirm the pathological findings, we assessed the levels of soluble and insoluble αSyn and 85R-SOD1:YFP in the mice resulting from this cross. For this study, we used a slightly different fractionation protocol (see Methods) that enabled detection both soluble and insoluble αSyn in the fractionated lysates of these mice (Figure 2-15 a and b). By contrast, and in agreement with the histological findings, we could only detect G85R-SOD1:YFP in the soluble fraction from the double transgenic mice (Figure

2-15 c and d). Collectively, these data indicate that despite robust αSyn pathology and aggregation in spinal cord, the G85R-SOD1:YFP protein remains soluble.

Discussion

In the current study, we crossed mouse models of tau and αSyn pathologies to mice that express a mutant form of SOD1 that we hypothesized could be vulnerable to proteostasis stress (in this case, the G85R-SOD1:YFP) to provide a reporter of secondary aggregation. Our study is the first that we are aware of to use a fluorescent reporter (e.g., a protein tagged to YFP) to investigate bystander misfolding in a mammalian system in vivo. We observed robust induction of G85R-SOD1:YFP inclusion pathology throughout the neuropil only when the protein was expressed in the JNPL3 model of spinal tauopathy. Importantly, with this model we demonstrate that G85R-

SOD1:YFP pathology did not significantly co-localize with tau pathology in the spinal cord of JNPL3-G85R-SOD1:YFP animals, providing evidence against simple co- aggregation of the two proteins. Although it is possible that misfolded mutant tau cross- seeded mutant SOD1 aggregation when co-expressed, we have previously reported that we could not cross-seed G85R-SOD1:YFP aggregation by injecting the spinal cords of these mice with spinal homogenates of paralyzed JNPL3 mice containing pathological tau aggregates [5]. Despite robust burdens of neurodegenerative pathology, we did not observe induced aggregation of G85R-SOD1:YFP in crosses to the spinal model of α-synucleinopathy or the cortical model of tauopathy. Our results suggest a model in which there are cell-type differences in the vulnerability of proteins to bystander misfolding, and a degree of specificity in terms of which proteins succumb to bystander misfold in response to the primary protein pathology.

Evidence of secondary protein misfolding in vivo is relatively scarce. Reports in

C. elegans were some of the first described instances of secondary misfolding; these made use of temperature-sensitive mutants of paramyosin, dynamin, and ras that failed to achieve active conformations in the presence of aggregation-prone proteins

(huntingtin and SOD1) [90, 91]. This finding was originally thought to occur because the expression of the aggregation-prone protein overwhelmed the cellular protein folding machinery, thus leaving TS mutant proteins with too little support to fold correctly. We argue that the G85R-SOD1:YFP construct that is expressed at low levels in the transgenic model used here is a reasonable parallel to the study in C. elegans with TS mutant protein. Although we cannot assert that the mutant SOD1 protein is ever completely natively folded, in hemizygous mice the mutant SOD1 protein displays a

diffuse cytoplasmic distribution and these mice do not develop evidence of motor neuron disease or the accompanying pathology (astrogliosis or microglosis [6]).

However it is clear that the G85R-SOD1:YFP protein is vulnerable to the misfolding associated with aggregation, because it can easily be induced to do so by injecting small amounts of tissues containing aggregates of mutant SOD1 [5–7] or by raising the levels of the protein by generating homozygous mice as was described in the original model [268]. We have also previously observed induction of G85R-SOD1:YFP aggregation in bigenic mice generated by crosses to a transgenic G93A SOD1 animal

[6]. Notably, the location and appearance of the fluorescent inclusion pathology we have observed here in bigenic JNPL3/G85R-SOD1:YFP animals is very similar to what we observed in bigenic G93A/G85R-SOD1:YFP mice and G85R-SOD1:YFP mice injected with tissue homogenates containing G93A SOD1 aggregates [6]. Importantly, intraspinal injection of tissue homogenates from paralyzed JNPL3 mice does not induce aggregation of G85R-SOD1:YFP [5]. Thus, in the case of the JNPL3 cross to the G85R-

SOD1:YFP mice, we argue that the induced aggregation of the fusion protein is not likely to be due to direct cross seeding, but to an alternative mechanism.

One of the goals of using the G85R-SOD1:YFP mice as a reporter was to identify which cell types were experiencing proteostatic stress to induce secondary misfolding associated with aggregation. Our analysis of the JNPL3 cross to G85R-SOD1:YFP mice revealed the presence of inclusions in the cell bodies of a subset of large motor neurons. However, most of the inclusions were in the neuropil where it is very difficult to ascertain which cell type contains the inclusion. Additionally, as mentioned above, in the interim between when the studies were first initiated and the present we learned that

some form of misfolded G85R-SOD1:YFP has the potential to propagate throughout the central nervous system [7]. Thus, it is difficult to decisively conclude whether a cell with a fluorescent inclusion was originally under proteostatic stress or if the inclusion was generated by intracellular spread of aggregate-inducing conformers of G85R-

SOD1:YFP originating elsewhere in the CNS [7]. Moreover, the ability of some form of misfolded G85R-SOD1:YFP to mediate cell-to-cell propagation, coupled with the fact that raising expression levels of the protein can induce it to aggregate, makes it very difficult to rule out a scenario in which the presence of tau pathology caused a focal change in expression at some location that created “seeds” of aggregation-prone SOD1 that propagated throughout the spinal axis. Recent transcriptomic studies of mouse models of tauopathy, including the JNPL3 and rTg4510, and transcriptomic studies of human tauopathies (Alzheimer’s Disease [AD] and progressive supranuclear palsy

[PSP]), however, have demonstrated that SOD1 expression is not induced in any of these disease settings (Table 2-1). The transgene construct used to produce the G85R-

SOD1:YFP animals is an engineered fragment of human genomic DNA, which would be expected to be regulated as endogenous SOD1 in humans. Thus, there is little evidence to suspect that the induced misfolding of G85R-SOD1:YFP in the bigenic crosses with

JNPL3 mice is due to an induction of the SOD1 transgene expression. The available data suggest that the more likely scenario is that loss of proteostatic function within the spinal axis of the JNPL3/G85R-SOD1:YFP mice led to the induced misfolding and aggregation of the mutant SOD1 reporter.

Our findings in the crosses of G85R-SOD1:YFP mice to JNPL3 mice were in contrast to findings in crosses with mice that develop cortical tau pathology (rTg4510

mice). These findings also contrast to previous observations of what appears to be

“secondary induction” of cytoplasmic TDP-43 pathology (a protein that has been pathologically associated with both ALS and FTD) in response to tauopathy in both the

JNPL3 and rTg4510 mouse models [2, 43]. In these models, tau pathology usually preceded TDP-43 pathology, suggesting that TDP-43 pathology may largely occur due to the presence of the pathological tau. The lack of G85R-SOD1:YFP inclusion formation in the rTg4510 cross is also remarkable given the fact that SOD1 aggregation is induced by relatively low levels of tau expression in JNPL3 mice (2X endogenous

[158]); whereas, the rTg4510 mice produce much higher levels of mutant tau (13X endogenous [207, 217]). Notably, cortical pathology is generally not seen in mice that express mutant SOD1 including the homozygous G85R-SOD1:YFP mice [268]. The expression level of the G85R-SOD1:YFP protein in forebrain is about 2-fold lower than in spinal cord (Figure 2-16), which could partially explain the lack of induced mutant

SOD1 aggregation in the cross with the rTg4510 mice. However, the rTg4510 mice exhibit profound neurodegenerative changes by 5.5 months of age [217], and it is difficult to accept that the levels of G85R-SOD1:YFP are the sole determinate of whether or not it misfolds and aggregates. Alternatively, it is possible that cortical neurons express unique proteostatic factors that effectively limit the coalescence of misfolded mutant SOD1 into inclusions even in the setting of severe proteostatic distress (see hypothetical model in Figure 2-17). Alternatively, there may be differences in the expression levels of one or more proteostatic factors (chaperones, ubiquitin ligases, etc.) between forebrain and spinal cord, such that spinal cord is more vulnerable (Figure 2-17). One such factor that has previously been identified by

Israelson and colleagues as potentially being responsible for tissue specificity of SOD1 misfolding is macrophage migration inhibitory factor (MIF) [124]. Cells that exhibited MIF localization to the cell bodies were protected from mutant SOD1 aggregation. However, the commercially available antibodies used to study MIF by Israelson in the foregoing study have been discontinued, and antibodies we obtained from other sources did not produce the same staining pattern. Therefore, we were not able to determine the levels or subcellular distribution of MIF in the cortex of the rTg4510 mice might explain our findings. Additionally, it has been shown that spinal motor neurons exhibit a higher threshold for the induction of the protective heat-shock response, specifically regarding a hindered ability in the activation of the transcription factor HSF1 [19]. HSF1 activation leads to the upregulation of the chaperones Hsp70 and Hsp90 which, when induced in mice expressing the G93A mutant SOD1 variant, leads to slower progression of disease

[144]. This naturally lower threshold for the heat-shock response could contribute to a higher propensity for mutant SOD1 aggregation in the spinal cord compared to other regions.

Our results from the cross of M83 mice to G85R-SOD1:YFP mice strongly contrasted to the results from the cross with the JNPL3 model. Despite both the JNPL3 and M83 exhibiting robust spinal cord and brain stem pathology, the impact of tau versus αSyn pathology upon our G85R-SOD1:YFP aggregation was dramatically different. This was especially interesting given recent reports suggesting that αSyn and

SOD1 interact, leading to increased SOD1 oligomerization [114, 149]. We postulate that our findings reveal the differential effects that tau and αSyn have upon proteostasis and the maintenance of protein folding. More specifically, the proteostatic factors

(chaperones, ubiquitin ligases, deubiquitinating enzymes, etc.) that maintain the folding state of tau, αSyn and SOD1 could differ in a manner that leaves mutant SOD1 vulnerable to aggregation in the presence of severe tau pathology, but not in the presence of αSyn pathology (Figure 2-17).

Unfortunately, the chaperone subnetworks that are critical in preventing mutant

SOD1 aggregation or that are engaged by tau and αSyn pathology remain unclear.

Mutant SOD1 has been shown to associate with Hsc70, Hsp70, Hsp27, Hsp25, αB- crystallin and Hsp110 subfamily chaperones [188, 196, 268]. Hsp70 has been shown to bind to the microtubule binding repeats of tau[218], regulating and stabilizing its association with microtubules [66, 129]. Complexes containing the carboxy-terminal

Hsp70-interacting protein (CHIP) and either Hsp70 or Hsp90 have been found to promote tau degradation [60, 137, 198]. The interactions of tau with small Hsps are slightly less clear; however, Hsp27 has been shown to interact with hyperphosphorylated tau in human AD brain tissue [229]. Hsp70/CHIP have also been found to contribute to αSyn maintenance and combat fibril formation [4, 72, 121, 164,

231]. Additionally, the small Hsps (αB-crystallin, Hsp27, Hsp20, HspB8, and HspB2B3) all appear to interact with αSyn (both wild-type and mutant), working to prevent the development of fibrils[29]. Finally, Hsp90 is known to modulate αSyn aggregation, binding to oligomeric species to increase their stability and attenuate toxicity [54, 76].

Deciphering whether there are specific chaperones, or other proteostatic factors, that become engaged in attempting to mitigate misfolded tau in spinal neurons, leaving mutant SOD1 with inadequate access to factors that mitigate its aggregation and will require further study to confirm.

Conclusions

In conclusion, we have used the co-expression of G85R-SOD1:YFP, a protein that is inherently prone to misfolding, to visualize and investigate “secondary misfolding” in settings of tau and αSyn pathology. The induced aggregation of G85R-SOD1:YFP in the presence of robust spinal tauopathy (as seen in the JNPL3 model) is an outcome consistent with bystander aggregation caused by proteostatic stress. Unexpectedly, the presence of either robust tau pathology in cortical neurons or αSyn pathology in the spinal cord, which in both cases causes severe degenerative changes, did not induce

G85R-SOD1:YFP aggregation. One hypothesis that could explain this outcome is that tau and SOD1 have overlapping demands for proteostatic factors that are in limited supply in the spinal axis, such that the presence of the misfolded tau essentially competes for a factor, or factors, that are critical in preventing the aggregation of mutant

SOD1 in spinal cord (Figure 2-17). Further studies will be required to understand the molecular basis for selective induction of G85R-SOD1:YFP aggregation in these models. That being said, the G85R-SOD1:YFP model has nonetheless proved useful in clearly demonstrating that induced misfolding of one protein by another in neurodegenerative conditions is more complex than simple proteostatic failure. The complexity of bystander misfolding in response to proteinopathies could provide a basis for distinctive clinical symptoms associated with these disorders.

Figure 2-1. Kaplan-Meier survival curves in JNPL3/G85R-SOD1:YFP mice relative to single transgenic JNPL3 controls. JNPL3 mice expressing the G85R- SOD1:YFP reporter protein (n=8) that exhibited SOD1 inclusion pathology reached an end-stage phenotype significantly faster than JNPL3 transgenic mice (n=7) (p < 0.05, Mantel-Cox test). The graphed data originated from six bigenic JNPL3/G85R-SOD1:YFP mice and seven tau-only transgenic JNPL3 mice that were littermate controls. All mice were female. Figure 2-1 was generated using GraphPad Prism (version 7.0h).

Figure 2-2. G85R-SOD1:YFP aggregation into punctate inclusions within the spinal cord of JNPL3/G85R-SOD1:YFP mice. Compared to the diffuse distribution of G85R-SOD1:YFP in spinal motor neurons of single transgenic animals (a and b), the fluorescence is organized into large neuropil inclusions with granular/punctate accumulation in the cell bodies of spinal motor neurons of bigenic JNPL3/G85R-SOD1:YFP mice (c and d). Exposure times were kept consistent across images and set to capture images of the inclusions in the bigenic mice at optimal exposure. Nuclei were stained with DAPI (blue). All animals analyzed were female. Representative images (40x magnification) of the ventral horn within the spinal cord are shown for 8 JNPL3-G85R- SOD1:YFP double transgenic mice and 3 G85R-SOD1:YFP single transgenic mice (aged 7 to 15.5 months).

Figure 2-3. Low power views of G85R-SOD1:YFP pathology in the spinal cord of bigenic JNPL3-G85R-SOD1:YFP mice (a). The box marks the position of the image shown in Figure 2-2d. Low power view of fluorescence in mice expressing G85R-SOD1:YFP alone (c). Images shows midsagittal brain section (b). Nuclei were stained with DAPI (blue). The left and right arrows are drawn to magnified regions that are shown in the top left and top right of (b), respectively. Images shown are representative of 8 JNPL3-G85R- SOD1:YFP mice and 3 G85R-SOD1:YFP mice.

Figure 2-4. Primary pathology burden in the JNPL3 spinal cord relative to those crossed to G85R-SOD1:YFP mice. JNPL3 mice (a) and those on the G85R- SOD1:YFP background (b) were stained with the MC1 antibody (misfolded human tau). Lumbar spinal cord sections are shown. Scale bar; 900 μm.

Figure 2-5. Solubility of SOD1 in JNPL3/G85R-SOD1:YFP mice. For these immunoblots, we used a previously described method of detergent extraction and sedimentation (see Methods). To observe aberrant disulfide cross-links that form as mutant SOD1 aggregates, we performed the SDS-PAGE in the absence of reducing agent (a and b). In JNPL3/G85R-SOD1:YFP mice versus G85R-SOD1:YFP mice, soluble G85R-SOD1:YFP exists predominantly in higher molecular weight states in double transgenic mice versus single transgenic controls (a). However, aggregates of G85R- SOD1:YFP were detected in NP40-insoluble fractions only in the bigenic, paralyzed, mice (b). 20 µg protein loaded for all samples. Mouse/human SOD1 was detected using an in-house generated antibody. n=3 per genotype.

Figure 2-6. Localization of tau MC1 immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3/G85R-SOD1:YFP mice. Misfolded human tau recognized by the MC1 antibody (red) appears similar in JNPL3 tau- transgenic versus JNPL3/G85R-SOD1:YFP bigenic animals (a, b). G85R- SOD1:YFP pathology, detected by an YFP antibody (green) (c), does not robustly co-localize with tau pathology in double transgenic animals (d). Nuclei were stained with DAPI (blue). Representative images (60x magnification) are shown within the ventral horn of the spinal cord of 8 JNPL3 and 8 JNPL3/G85R-SOD1:YFP animals. All animals analyzed were female aged 7 to 15.5 months.

Figure 2-7. Localization of phosphotau immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3/G85R-SOD1:YFP animals. Hyperphosphorylated human tau pathology recognized by the PHF1 (Ser396/Ser404; red) antibody appears similar in JNPL3 tau-transgenic versus JNPL3/G85R-SOD1:YFP bigenic mice (a, b). G85R-SOD1:YFP pathology, detected using an YFP antibody (green) (c), does not robustly co-localize with tau pathology in double transgenic animals (d). Nuclei were stained with DAPI (blue). Images are of 60x magnification within the ventral horn of the spinal cord of JNPL3 and JNPL3/G85R-SOD1:YFP mice. The images shown are representative of 8 JNPL3 and 8 JNPL3/G85R-SOD1:YFP female animals aged 7 to 15.5 months.

Figure 2-8. Localization of phosphotau immunoreactivity versus G85R-SOD1:YFP pathology in bigenic JNPL3-G85R-SOD1:YFP mice. Hyperphosphorylated human tau pathology recognized by the AT8 (Ser202/Thr205) antibody appears similar in JNPL3 single transgenic versus JNPL3- 85R-SOD1:YFP bigenic mice (a, b). G85R-SOD1:YFP pathology, detected by an YFP antibody (c), does not robustly co-localize with tau pathology in double transgenic mice (d). Nuclei were stained with DAPI (blue). Images are of 60x magnification within the ventral horn of the spinal cord of JNPL3 and JNPL3- G85R-SOD1:YFP mice.

Figure 2-9. G85R-SOD1:YFP does not form inclusions in the forebrain of rTg4510/G85R-SOD1:YFP bigenic. The severity of neurofibrillary tangle pathology in the hippocampus and cortex (a, cortex shown immunostained with the MC1 antibody, red) in rTg4510 mice is similar to that of rTg4510/G85R-SOD1:YFP bigenic mice (b). Although the intensity of YFP fluorescence in the trigenic P301L/G85R-SOD1:YFP mice was higher than that of mice expressing G85R-SOD1:YFP alone, but there was no evidence of organization into inclusion structures (c and d; see Figure 2-10). There were isolated cells that were hyperfluorescent (d), but the fluorescence in these cells did not appear to be organized into fibrils. All images were taken at 60X magnification of 5 μm paraffin-embedded sections. Nuclei were stained with DAPI (blue). Exposure time and specifications were kept consistent across all images, optimized to the rTg4510/G85R-SOD1:YFP tissue sections. Representative images are shown for 5 rTg4510/G85R- SOD1:YFP mice (1 male, 4 female) and 4 G85R-SOD1:YFP mice (4 males) between 8 and 9 months of age.

Figure 2-10. Primary pathology burden in the rTg4510 transgenic mouse cortex relative to those crossed to the G85R-SOD1:YFP mouse. rTg4510 mice (a) compared to trigenic rTg4510/G85R-SOD1:YFP mice (b) after immunostaining with the MC1 antibody (misfolded human tau). Scale bar; 300 μm.

Figure 2-11. Quantification of G85R-SOD1:YFP levels between G85R-SOD1:YFP and rTg4510/G85R-SOD1:YFP mice using direct fluorescence and immunoblot densitometric analysis. Quantification of fluorescence intensity reveals a significantly more intense YFP fluorescence in rTg4510/G85R-SOD1:YFP mice (abbreviated rTg4510-SOD1) compared to G85R-SOD1:YFP controls (abbreviated SOD1) (n=4) (a). However, immunoblot analysis using an antibody to both mouse and human SOD1 demonstrates no statistical difference between levels of G85R-SOD1:YFP in the two mouse groups (b, c) (n=3 per genotype). Endogenous mouse SOD1 (mSOD1) was used as a loading control, and was detected on the same blot shown. Statistical analysis was conducted using GraphPad Prism (version 7.0h). Error bars show mean ± S.D.; unpaired, two tailed, T-test revealed a significant difference in fluorescence intensity in forebrain by genotype (p < 0.01). n.s.; not significant.

Figure 2-12. Primary pathology burden in the M83 transgenic mouse spinal cord relative to M83/G85R-SOD1:YFP mice. M83 only mice (a) compared to M83/G85R- SOD1:YFP mice (b) after injection with αSyn fibrils to induce αSyn pathology. Sections were stained with the 81A antibody (pSer129 αSyn). Lumbar spinal cord sections are shown. Scale bar; 900 μm.

Figure 2-13. Lack of G85R-SOD1:YFP inclusion pathology in the spinal cord of M83/G85R-SOD1:YFP mice. Mice were IM injected to induce αSyn pathology at 2 months of age and then euthanized at a humane endpoint (both hind limbs paralyzed). Compared to the diffuse distribution of G85R-SOD1:YFP in single transgenic animals (a), M83 mice expressing the G85R-SOD1:YFP reporter protein have a similar distribution of the protein (b), visible by direct fluorescence. Exposure times were kept consistent across images. Nuclei were stained with DAPI (blue). Representative images (60x magnification) of the ventral horn within the spinal cord are shown for 8 M83/G85R-SOD1:YFP double transgenic mice (5 female, 3 male) and 6 G85R-SOD1:YFP single transgenic mice (2 female, 4 male). Mean fluorescence intensity was not statistically significant between M83 mice expressing G85R-SOD1:YFP (abbreviated M83-SOD1) and those expressing G85R-SOD1:YFP alone (abbreviated SOD1) (c). Statistical analysis was conducted using GraphPad Prism (version 7.0h). Error bars show mean ± S.D.; unpaired T-test.

Figure 2-14. Kaplan-Meier survival curves for M83/G85R-SOD1:YFP mice relative to single transgenic M83 controls. All mice were injected intramuscularly with αSyn fibrils to induce pathology. M83 mice expressing the G85R-SOD1:YFP reporter protein that exhibited SOD1 inclusion pathology did not reach an end-stage phenotype significantly faster than M83 transgenic mice. The graphed data originated from 11 bigenic M83/G85R-SOD1:YFP mice (6 female, 5 male) and 15 single transgenic M83 mice (10 male, 5 female) that were littermate controls. Figure 2-14 was generated using GraphPad Prism (version 7.0h).

Figure 2-15. Solubility of αSyn and SOD1 in M83/G85R-SOD1:YFP mice. No changes in soluble versus NP40-insoluble αSyn were observed between M83/G85R- SOD1:YFP versus G85R-SOD1:YFP mice (a and b). For these immunoblots we used a sequential fractionation protocol that produced a PBS-soluble fraction and an NP40-insoluble fractions (see Methods). Here we controlled sample concentration by resuspending the NP40-insoluble fraction in a volume equivalent to the initial PBS soluble fraction. Equivalent amounts of each fraction were analyzed by SDS-PAGE (30 µL per sample). We used antibodies to GAPDH as a loading control in soluble fractions on the same blot (a). Soluble G85R-SOD1:YFP and endogenous mouse SOD1 was detected in both animal groups (c), and insoluble G85R-SOD1:YFP was not detected in either group (d). αSyn was detected using the 94-3A10 antibody (provided by the laboratory of Benoit Giasson [59]), while mouse/human SOD1 was detected using an in-house generated antibody. n=3 per genotype.

Figure 2-16. G85R-SOD1:YFP expression in spinal cord is 2-fold higher than forebrain in G85R-SOD1:YFP heterozygous mice. Forebrain and spinal cord tissue were extracted and 20 μg of protein was used for immunoblot analysis of SOD1 levels, using an antibody specific for human SOD1 (hSOD1) (a). Each lane represents an individual animal (n=3). Graph represents densitometric quantification of hSOD1 levels normalized to GAPDH (b). Statistical analysis was conducted using GraphPad Prism (version 7.0h) Error bars show mean ± S.D.; unpaired T-test. A.U.; arbitrary units.

Figure 2-17. Hypothetical mechanism of differential effects of tauopathy versus synucleinopathy on G85R-SOD1:YFP secondary aggregation in the spinal cord and cortex. In the JNPL3 spinal cord, misfolded tau occupies proteostatic factors (Factor X) that the mutant SOD1 reporter is also dependent upon for folding or degradation. In the cortex of rTg4510 mice, the levels of Factor X could be higher, or other proteostatic factors specific to brain (Factor Y) could be present to prevent the aggregation mutant SOD1. Meanwhile, misfolded αSyn occupies proteostatic factors distinct from those of tau (Factor Z), leaving a sufficient level of Factor X to prevent the aggregation of mutant SOD1.

Table 2-1. RNAseq expression data for SOD1 in mouse and human tauopathies. Transcriptomic data from studies of the rTg4510 and JNPL3 mouse models, and from studies of humans brain tissues from Alzheimer disease (AD) and progressive supranuclear palsy (PSP) cases available in https://www.synapse.org/#!Synapse:syn2580853/wiki/409840. Brain Tissue Donor Fold change q value (adjusted p Group size relative to value) controls 6 mo old rTg450 1.03 0.78 6 vs 6 12 mo old 1.01 0.95 6 vs 6 homozygous JNPL3 Human AD brain 0.97 0.64 Approx 80 vs 80 (temporal cortex) Human PSP brain 1.18 0.12 Approx 80 vs 80 (temporal cortex)

CHAPTER 3 CHANGES IN PROTEOME SOLUBILITY INDICATE WIDESPREAD PROTEOSTATIC DISRUPTION IN MOUSE MODELS OF NEURODEGENERATIVE DISEASE

Neurodegenerative disorders, including Alzheimer’s disease (AD),

Frontotemporal Dementia (FTD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS) are characterized pathologically by the accumulation of misfolded proteins (often referred to as “proteinopathies”) [32, 63, 64, 111, 239, 241].

Considerable evidence supports the idea that the accumulation of misfolded proteins could be deleterious to the proteostasis network [14, 24, 50, 67, 119, 152, 161, 182,

199, 254, 272]. This network includes chaperones, the ubiquitin-proteasome system, and the autophagic system working in unison to maintain protein folding or degrade misfolded/aggregated protein species. Aggregated forms of misfolded tau are degraded in the autophagy-lysosomal system, while the accumulation of misfolded tau in CNS tissues of AD, and other tauopathies, is associated with lower 26S proteasome activity

[105, 140, 187, 250]. Similar reductions in proteostatic activity have been reported in the presence of α-synuclein (αSyn) pathology [51, 71, 75, 293], and in tissues from mouse models that over-express ALS-associated variants of superoxide dismutase 1 (SOD1)

[17, 37, 48, 132, 133, 219]. Accumulations of misfolded protein have also been associated with overburdened chaperone function, leading to impaired folding and maturation other proteins (reviewed in [14, 119]). This idea was originally elaborated in

C. elegans where muscle cells expressing aggregating mutants of huntingtin, or SOD1, failed to correctly fold co-expressed temperature-sensitive metastable proteins [90, 91].

Accordingly, it has become increasingly clear that “mixed” proteinopathies are common in neurodegenerative disease [45, 117, 126, 243, 266]. For example, humans with

tauopathy, as well as transgenic mice that model tauopathy, often have pathologic deposition of TDP-43 and αSyn [43, 117, 159, 163, 291]. Thus, there is evidence that disruptions in proteostatic function could degrade proteome integrity in neurodegenerative disease. To date, however, there is limited understanding of how changes in these proteostatic functions could impact overall proteome folding in the mammalian nervous system.

We have previously shown in a mouse model of Alzheimer’s amyloidosis that, as

Aβ deposition increases, the CNS proteome begins to lose solubility and a fraction of cytosolic proteins become aberrantly detectable in detergent-insoluble fractions [285].

Given that Aβ is largely deposited extracellularly, it was difficult to conclude that our observed outcomes could be explained by misfolded Aβ peptides directly over- burdening cytosolic protein chaperone functions. To assess whether the cytoplasmic, intracellular, accumulation of misfolded proteins, such as tau, might impose a burden on protein folding, we have examined proteome solubility in transgenic mouse models of mutant tau, mutant SOD1, and mutant αSyn proteinopathies. Similar to prior effort in amyloidosis models, we used bottom-up label-free proteomics to identify CNS proteins that lose solubility in detergent-containing buffers as pathology develops. The study design was to identify CNS proteins in control nontransgenic animals that are normally consistently detectable in aqueous fractions and of low abundance, or absent, from the detergent-insoluble fractions. We then assessed whether these proteins aberrantly fractionate into insoluble fractions at a greater frequency in the CNS lysates of our neurodegenerative mouse models. To study the effects of tau pathology on proteome solubility, we utilized the rTg4510 mouse (human tau-P301L), an established model of

conditional tauopathy [207, 217]. We also examined changes in proteome solubility in the JNPL3 model (human tau-P301L) of spinal tau pathology [156], the M83 model

(human αSyn-A53T) of spinal αSyn pathology [87], and the G93A model (human SOD1-

G93A) of spinal SOD1 pathology [101]. In all of these models, we observe >100 proteins that lose solubility in buffers containing SDS as pathology develops. Although some proteins were unique to each model, many were common to all four models, with some additional overlap with Aβ amyloidosis models. Overall, our data are consistent with the hypothesis that the accumulation of misfolded proteins associated with neurodegenerative disease imposes a burden on proteostatic function such that a subpopulation of CNS cytosolic proteins fail to maintain normal soluble conformations.

Materials and Methods

Transgenic Animals

The JNPL3 mouse model of tauopathy (maintained on the Swiss Webster background from Taconic) expresses mutant human tau (P301L, 4R0N) under the mouse prion promoter and develops robust tau pathology in the spinal cord and brain stem with other regions being modestly affected [158]. All of the JNPL3 mice used in this study were female due to an earlier onset of tau pathology and motor dysfunction.

The rTg4510 model of tau pathology (maintained on a hybrid 129S6/FVB background) consists of bigenic mice that contain both human tau (P301L, 4R0N) behind by a minimal promoter disrupted by tetracycline responsive elements, and the tet- transactivator (tTA) driven by a Ca2+ calmodulin kinase II promoter (forebrain-specific); promoting high levels of mutant tau within the hippocampus and neocortex [207]. All of the rTg4510 mice used in this study were female due to the potential for differences in the severity of tau pathology between males and females [13]. The rTg21221 mice

express the wild-type human tau (4R0N) gene under the same promoter systems as that of rTg4510 mice [120]. To model α-synucleinopathy, we used the M83 mouse model (maintained on the hybrid B6/C3 background). This model overexpresses mutant

(A53T) human αSyn under the mouse prion promoter [87], and develops αSyn pathology primarily within the spinal cord, brain stem midbrain, hypothalamus, thalamus and periaqueductal gray regions (other brain regions less affected) resulting in a severe motor phenotype and paralysis. This pathology and phenotype occurs between 8-16 months of age in homozygous M83 mice, but later than 21 months in hemizygous M83 mice [87]. Mice expressing the G93A mutant of human SOD1 have been previously characterized [101]. The mutant gene is expressed under the human SOD1 promoter within a 12 Kb fragment of genomic human DNA. The G93A mice used for the current study were maintained on the FVB background and develop paralysis at about 150 days of age.

Intramuscular Injection of Preformed α-synuclein Fibrils into M83 Transgenic Mice

Intramuscular injections of αSyn fibrils to seed pathology have been previously described [216]. Briefly, wild-type αSyn fibrils were injected bilaterally via needle insertion in the gastrocnemius muscle of heterozygous M83 transgenic mice. Injections were conducted with a 10-μL Hamilton syringe and a 25-gauge needle, which penetrated approximately 1 mm deep into muscle tissue. Mice were eight weeks of age at the time of injections, which were conducted while mice were anesthetized via isoflurane inhalation.

Sequential Protein Detergent Extraction from Mouse Forebrain/Spinal Cord and Preparation of Protein Samples for Proteomics Analysis

The protocol used here is based on changes in protein solubility in buffers containing detergents and was developed in previous studies of proteome solubility in heat-stressed cultured cells and the brains of APPswe/PS1dE9 (Line 85 or L85) mice that model Alzheimer’s amyloidosis [284, 285]. Altered protein solubility in buffers containing either nonionic (e.g. NP40) or ionic detergents (e.g. SDS) is a well-known criterion used to distinguish natively folded proteins from those that are misfolded and/or aggregated [89, 139, 168, 220, 258, 269]. The sequential extraction and sedimentation technique was used to reduce the complexity of samples that were subjected to LC-

MS/MS. Mice were anesthetized with isoflurane, perfused with PBS, followed by the extraction of the forebrain or spinal cord. These tissues were then homogenized in 4 ml

PBS on ice with 1% protease inhibitor cocktail in DMSO (Sigma Aldrich, St. Louis, MO) followed by sequential detergent extraction and ultracentrifugation. The sequence of detergents used was nonidet-P40 (NP40), followed by deoxycholate (DOC), and then sodium dodecyl sulfate (SDS) according to our previously utilized protocol [285]. We ultimately compared PBS-soluble (PBS-S) and SDS-insoluble fractions, the latter of which was resuspended in 300 l of 1x Laemmli buffer, in chromatography tandem mass spectrometry (LC-MS/MS). 30 l of each SDS-insoluble sample or 20 l of each

PBS-soluble sample was loaded into a 4-20% Tris-HCl (Bio-Rad, Hercules, CA) gel and subjected to SDS-PAGE until proteins migrated about 1.5 cm into the gel. The gel was then stained with Coomassie blue and each lane was individually excised from the gel and cut into ~1 mm3 pieces. This was followed by trypsin (Sigma Aldrich, St. Louis, MO) digestion and peptide extraction from the gel by standard protocols (Online Resource 1)

executed by personnel in the University of Florida Interdisciplinary Center for

Biotechnology Research Proteomics and Mass Spectrometry Core (Gainesville, FL).

LC-MS/MS Analysis

The digested peptides from each sample were dried in a speed vac and then resuspended in a 0.1% formic acid in water solvent for liquid chromatography. Each sample was loaded through an Acclaim Pepmap 100 pre-column (20 mm x 75 m; 2

m-C18) and a Pepmap RSLC analytical column (250 mm x 75 m; 2 m-C18) at a

300nl/minute flow rate. The peptides were separated by a linear gradient of solvent A

(0.1% formic acid) to 25% solvent B (0.1% formic acid 80% acetonitrile) for 95 minutes followed by ramping up to 98% solvent B for an additional 25 min. Chromatographic separation of the peptides was performed with an automated Easy-nLC 1000 system

(Thermo Fisher Scientific, Bremen, Germany) that was interfaced with a Hybrid

Quadrupole-Orbitrap Mass Spectrometer system (Thermo Fisher Scientific, Bremen,

Germany).

The MS/MS spectra were extracted by Mascot Distiller (version 2.4). Mascot

(Matrix Science, London, UK; version 2.4.1) and X! Tandem [The GPM, thegpm.org; version CYCLONE (2010.12.01.01)] was used to analyze the samples. We used

Mascot, based upon trypsin digestion, to search the “Mouse UniProt Protein

Knowledgebase (canonical & isoform)” that had been customized by the addition of human protein data related to expressed transgenes of interest (89029 entries). X!

Tandem was utilized to search a reverse concatenated subset of the same database.

Peptides were identified with specifications within Mascot and X! Tandem of a fragment ion mass tolerance of 0.01 Da and a parent ion tolerance of 10.0 PPM.

Carbamidomethyl of cysteine was specified as a fixed modification while variable modifications were included the ammonia-loss of asparagine, gln->pyro-Glu of the n- terminus, deamidated of asparagine and glutamine, oxidation of methionine and ubiquitination of lysine (Gly-Gly).

In order to validate peptide and protein identifications by MS/MS, Scaffold

(version Scaffold_4.7.3, Proteome Software Inc., Portland, OR) was utilized and identifications were accepted only if the peptides surpassed 95% probability with

Scaffold delta-mass correction according to the Peptide Prophet algorithm [141].

Peptide probabilities generated by X! Tandem were designated according the Scaffold

Local FDR algorithm. An identification of a particular protein was accepted if it passed

99% probability and included at least two identified peptides. The Protein Prophet algorithm was used to assign the protein probabilities [189]. If multiple proteins shared significant peptide evidence, they were grouped into clusters. The principles of parsimony served to group proteins that could not be differentiated according to MS/MS analysis alone.

Calibration, Relative Quantification and Bioinformatics of Proteomics Data

The number of MS/MS spectra identified for a particular protein is presumed to be largely proportional to its abundance in a sample. To determine whether a particular protein identified in SDS-insoluble fractions from CNS tissues of transgene positive mice was over-represented relative to nontransgenic controls, we used two statistical tools to analyze the total unweighted spectrum counts for each protein from the Scaffold data on protein identity (see Table 3-1 for a summary of the number of animals compared by the different statistical approaches). One of the statistical tools we used is the G-test (likelihood ratio test for independence) [192, 204], which can be programmed

into Microsoft Excel. In analyzing data for rTg4510 and APPswe/PS1dE9 mice across ages, we used littermate controls (Table 3-1). In studies of the JNPL3 tau, G93A SOD1,

M83 αSyn mice, we grouped all of the data for nontransgenics together to produce a collective control group of n=6 (Table 3-1). For many proteins, the average number of spectral counts for a given protein was <1 in the nontransgenic littermate control samples. In such cases, the corresponding transgenic sample must have contained at least 5 spectra for the protein analyzed to achieve G-test significance (p< 0.05). In cases in which the average number of spectra for a given protein in controls was ≥1, we identified proteins in the transgenic sample that presented with 3-fold more spectra and used an unpaired t-test, as well as the G-test (at least 5 spectra in the transgenic sample), to establish whether the spectral count numbers were significantly different.

GraphPad Prism (Version 7.0h, La Jolla, CA) was used when t-tests were a statistical method of comparison. In order to identify proteins that were statistically consistent by genotype and age, we used SAINT (Significance Analysis of INTeractome) analysis with a SAINT score threshold of ≥0.9 as the cut off for confidence in over-representation in

SDS-insoluble fractions [40]. The SAINT scoring algorithm factors protein molecular weight in its calculation of statistical probability of over-representation. To identify proteins with the highest possible confidence level as being over-represented in SDS- insoluble fractions from samples from transgene-positive rTg4510 mice, we used the

SAINT scoring system and grouped all nontransgenic littermate controls for all ages together as collective control group (n=34). Bioinformatics analysis was conducted using the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database

(version 12.0, Los Angeles, CA) [173, 174]. SAS JMP pro (version 13) was used to perform cluster analysis and generate heat maps (Cary, NC).

Western Blot Validations of LC-MS/MS Data

30 μL of SDS-insoluble or 5 µL of PBS-soluble protein fractions from each animal were loaded onto a Criterion 4-20% tris-glycine gel (Bio-Rad, Hercules, CA). After overnight transfer to nitrocellulose membrane, the proteins were identified by overnight incubation in primary antibody following standard procedures. Primary antibodies included ubiquitin carboxyl-terminal hydrolase isozyme 1 (UCHL1, 1:1000 Proteintech,

Rosemont, IL), alpha-enolase (ENO1, 1:200, Santacruz Biotechnology, Dallas, TX), fructose biphosphate aldolase C (ALDOC, 1:1000, Encore Biotechnology, Gainesville,

FL), phosphoglycerate mutase 1 (PGAM1, 1:5000, Sigma Aldrich, St. Louis, MO), malate dehydrogenase (cytoplasmic) (MDH1, 1:1000, Abcam, Cambridge, MA) and superoxide dismutase 1 (SOD1, 1:4000, generated in house).

Expression and Purification of Recombinant K18 Tau and Assembly of Recombinant K18 Tau Fibrils

K18 tau fibrils were generated as previously described [246]. Briefly, recombinant

K18 tau protein was generated by utilizing cDNA encoding the human K18 tau fragment, which contains residues Q244-E372 in 2N/4R human tau. K18 tau fragments contained an additional methionine residue at the N-terminus and was cloned into the bacterial expression plasmid pRK172. BL21 (DE3)/RIL Escherichia coli (Agilent

Technologies, Santa Clara, CA) were then used to express the plasmid. Previously utilized protocols [88] were used to purify K18 tau protein. The bicinchoninic acid assay

(BCA; Pierce, Waltham, MA) with bovine serum albumin (BSA) standards were used to determine K18 protein concentration. In order to assemble recombinant K18 tau

proteins (1 mg/ml) into filaments, the protein was incubated at 37°C for at least 48 hours in sterile PBS containing 50 μM heparin [94, 110] with concurrent shaking at 1,050 rpm with an Eppendorf Thermomixer R. The K114 assay was utilized to confirm the formation of fibrillar tau as previously described [49, 276]. The heparin was removed from the protein fibril preparation via centrifugation at 100,000 x g, resuspension of the

K18 fibrils in PBS, and determining resultant protein concentrations using the BCA assay. Water bath sonication was then used in order to break up the fibrils into smaller tau “seeds” [276].

N2a Cell Culture and K18-mediated Human Tau Seeding in vitro

Neuro 2a (N2a) cells were purchased from the American Type Culture Collection

(ATCC) and cultured in media containing an equal amount of Dulbecco’s Modified Eagle

Media (Thermo Fisher Scientific, Hampton, NH, USA) and Opti-MEM Reduced Serum

Medium (Thermo Fisher Scientific). Media was supplemented with 5% fetal bovine serum (Thermo Fisher Scientific) and 1% penicillin-streptomycin (Life Technologies,

Carlsbad, CA, USA). Cell transfections were conducted using Lipofectamine 2000

(Thermo Fisher Scientific) according to the manufacturer’s protocol. The vector expressing 4R/0N human tau P301L has been previously described [246]. Twenty minutes post-transfection, wild-type human K18 tau fibrils were added to the cell media to achieve a 1 μM concentration. Cells were harvested 48 hours post-transfection followed by detergent extraction as previously described [283]. Briefly, cells were initially harvested in PBS with 1% protease inhibitor cocktail (Sigma Aldrich, St. Louis, MO,

USA) followed by sequential homogenization/extraction in different detergents (NP40 and DOC), yielding the DOC-insoluble protein fraction which was resuspended in 1x

Laemmli buffer prepared from a 4x Laemmli buffer stock solution. These samples were analyzed by LC-MS/MS as described above and in Online Resource 1.

Results

Neurofibrillary Tangle Pathology Perturbs the Solubility of CNS Cytosolic Proteins

The rTg4510 model of tau pathology produces robust neurofibrillary tangle pathology that progressively worsens with age [207, 217]. Guided by previous studies of this model, we produced cohorts of mice aged to 2.5, 4.5, 7.0 and 9.5 months before harvesting. Following methods described in Material and Methods (and Online

Resource 1), we produced PBS-soluble and SDS-insoluble fractions from the homogenized forebrains of rTg4510 mice and nontransgenic littermates for proteomics analysis. The proteins we focused on were those that were readily detected in PBS- soluble fractions from the nontransgenic mice (having at least 5 peptide spectra detected in all nontransgenic PBS-soluble fractions analyzed per group). We viewed these proteins as molecules that should normally be highly soluble. We used two separate criteria for distinguishing when these proteins became over-represented in

SDS-insoluble fractions of mutant mice relative to the nontransgenic controls. One criterion required at least a 3-fold difference in the number of peptide spectra in the

SDS-insoluble fraction in transgenic samples relative to the average value for nontransgenic insoluble samples. There were many proteins where the average spectral counts for nontransgenic samples was less than 1 or zero. In these cases, only proteins in which there were at least five peptide spectra for that protein in the transgenic sample met statistical criteria (G-test; p <0.05) for over-representation [118,

192, 236]. In each individual animal analyzed the number of proteins that met criteria for

over-representation in SDS-insoluble fractions increased progressively by age group

(Figure 3-1a; Object 3-1, Sheet 1). Notably, the brains of rTg4510 mice at all ages exhibited significantly higher levels of insoluble tau as compared to nontransgenic mice, with the levels of insoluble tau rising steadily across the 4 age groups (Figure 3-1b).

The rTg4510 mouse expresses mutant human tau-P301L conditionally, using the tet-off system in which the administration of doxycycline suppresses transgene expression. In a paradigm similar to the initial characterization of this model [207, 217], two groups of rTg4510 mice received doxycycline, beginning either at 4.5 or 5.5 months with harvest at 7.0 months of age, or beginning at 5.5 months with harvest at 9.5 months of age.

When we conducted proteomics analyses on rTg4510 mice that received doxycycline, number of proteins meeting criteria for over-representation in SDS-insoluble fractions was reduced in parallel to reduced levels of insoluble tau (Figure 3-1 a and b, shaded area). Overall, these data demonstrate that changes in protein solubility worsen as the level of misfolded tau increases and that suppression of transgene expression attenuates the shifts in proteome solubility.

The proteins identified as losing solubility in the younger rTg4510 animals were also identified in older rTg4510 animals. Of the 148 unique proteins that were identified collectively as over-represented in the SDS-insoluble fractions for the 2.5 month old mice, 128 (86%) were identified in insoluble fractions from the forebrains of 7.0 and 9.5 month old animals; however, for many of these proteins there was considerable animal- to-animal variability in spectral count numbers (Object 3-1, Sheet 1). Therefore, we used two statistical approaches to compare data between mice of different age groups to identify proteins that were consistently over-represented in the SDS-insoluble

fractions. We initially used an approach in which we identified proteins that were over- represented in SDS-insoluble fractions in 7 of 10 7.0 month old rTg4510 mice and all three 9.5 month old rTg4510 mice. By this approach, we identified >200 proteins

(including tau) that met statistical criteria for over-representation, relative to littermate controls (Object 3-1, Sheet 2). Between the mice from the two age groups, there were

169 proteins that were common, with 255 unique proteins identified when both age groups were considered together. To further refine the data, we applied a second statistical analysis, called SAINT scoring [40], that accounts for variability in spectral data between animals and for differences in protein molecular weight in calculating the probability of over-representation in a set of samples. The SAINT system was originally developed for analyzing protein:protein interaction data, and compares spectral count numbers between samples from two different conditions. In our study, the two conditions compared were spectral counts from controls versus transgene positive animals. In this approach, we analyze all of the data collectively, comparing the transgene positive rTg4510 mice to all nontransgenic mice of any age (Table 3-1).

Table 3-1 lists the 30 proteins other than tau with the largest fold-change in spectral counts as complied by SAINT score analysis (see Object 3-1, Sheet 2 for complete protein lists). Under this more stringent analysis, we identified 5 proteins that met a confidence level of 90% (0.9) probability to be over-represented in the SDS-insoluble fractions of forebrains from 2.5 month old rTg4510 mice (Figure 3-1c; Object 3-1, Sheet

3 All 5 of the proteins were also detected in insoluble fractions of 7.0 and 9.5 month old mice (Figure 3-1c). Further, with these more stringent criteria, we observed a high level of overlap in protein identifications as over-represented in SDS-insoluble fractions

among all age groups of rTg4510 mice (Figure 3-1c). In the two oldest age groups (7.0 and 9.5 months), SAINT scoring identified 190 proteins that were common, with 277 unique proteins (aside from tau) identified when both age groups were considered together. Collectively, these data indicate that a nonrandom subpopulation of the murine

CNS proteome is over-represented in SDS-insoluble fractions from the brains of rTg4510 mice with more severe tau pathology.

To further compare changes in protein solubility across all rTg4510 mice that were analyzed, we performed a cluster analysis of SDS-insoluble peptide spectra from all of the mice within our rTg4510 cohort. Based upon this analysis, which groups data sets by similarity, rTg4510 mice that received Dox from 4.5/5.5 months to 7.0 months clustered together with 2.5 and 4.5-month-old rTg4510 mice (Figure 3-2). Only two out of five 9.5-month-old mice that received Dox beginning at 5.5 months clustered with aged rTg4510 mice (7.0 and 9.5 months) that did not receive Dox. This analysis indicates that changes in proteome solubility were partially mitigated by suppressing tau expression in the 4.5-5.5 month age window. Importantly, the effect of Dox on mutant tau expression was not complete as the treated mice still express the human tau-P301L transgene at levels that are 2-fold over endogenous mouse tau [217]. Thus, in mice treated with Dox at 4.5 or 5.5 months of age, the tau pathology still worsens progressively when aged to 9.5 months [217]. Overall, the data strongly indicate that the number of CNS proteins that lose solubility in rTg4510 mice is highly correlated with the severity of tau pathology.

As indicated above, the techniques used here to analyze the rTg4510 mice are very similar to what we have used in the past to examine changes in proteome solubility

in the brains of the APPswe/PS1dE9 model of Alzheimer’s amyloidosis [285]. The technology in mass spectrometry has evolved rapidly in the last few years and we thus conducted a replication study of proteome solubility in the APPswe/PS1dE9 mice so that we could make better comparisons of data between the two models. Our prior study with older mass spectrometry instruments identified 28 proteins in addition to Aβ that were over-represented in SDS-insoluble fractions of 16 months old APPswe/PS1dE9 mice. Importantly, we were able to identify 21 of the same proteins, including Aβ, in the new data sets, which grew to a list of 179 proteins in 20 month old APPswe/PS1dE9 mice (Figure 3-3; Object 3-2, Sheet 1). Between the APPswe/PS1dE9 and rTg4510 models, there were 141 common proteins that could be identified as over-represented in

SDS-insoluble fractions despite the very distinct locations of Aβ and tau pathology

(Figure 3-1d; Onbject 3-1, Sheets 3 and 4). Overall, however, the total number of proteins that show changes in solubility in the brains of rTg4510 mice was much higher than the APPswe/PS1dE9 mice.

Validation of LC-MS/MS Data in Tauopathy

To validate the LC-MS/MS data, we conducted immunoblot confirmations for a subset of proteins identified. We obtained antibodies from commercial sources and confirmed detection of a band of the appropriate size for proteins of interest by immunoblots of PBS-soluble fractions. Importantly, the proteins that we tested spanned a wide range of relative abundance in our samples (estimated by spectral counts). We included in this validation rTg21221 mice expressing wild-type (WT) human tau, which do not exhibit NFT pathology [120]. No proteins consistently lost solubility in this model when analyzed at 9.5 months of age (Object 3-1, Sheet 1). We also included rTg4510 animals at 2.5, 4.5, 7.0, and 9.5 months of age, doxycycline-treated rTg4510 mice, and

nontransgenic control mice. Because the composition and level of proteins in the insoluble fractions was expected to vary considerably by genotype and age, we normalized all fractions by volume. For each tissue sample, we initially generated a 10% weight by volume homogenate in PBS. The final volume of each fraction generated from a given sample was adjusted to be equivalent to the starting volume of the initial PBS homogenate (10% weight by volume). We then loaded an equivalent volume of sample in each lane, meaning that each lane should contain the same volumetric fraction of the original 10% homogenate. Focusing on SDS-insoluble fractions, we conducted immunoblots to ubiquitin carboxyl-terminal hydrolase isozyme 1 (UCHL1), alpha- enolase (ENO1), fructose biphosphate aldolase C (ALDOC), phosphoglycerate mutase

1 (PGAM1) and malate dehydrogenase (cytoplasmic; MDH1) (Figure 3-4a). These proteins were easily detected in PBS-soluble fractions of nontransgenic control mice, indicative of their normally soluble state (Figure 3-4a). In good alignment with the LC-

MS/MS data, we observed an increase in the intensity of the band corresponding to these proteins in samples from 4.5 and 7.0 month old untreated rTg4510 mice. The intensity of the band for each protein was variably lower in Dox-treated mice. Overall, the intensity of the band for each protein tracked well with the LC/MS-MS data at 4.5 and 7.0 months of age (Object 3-1, Sheet 5), but for unknown reasons the intensity of immunoreactivity for these proteins in 9.5 month old rTg410 mice was consistently lower than expected. By 9.5 months of age, we note significant animal-to-animal variability in the spectral count data and that the intensity of immunoreactivity for each protein in

SDS-insoluble fractions does not entirely correlate to spectral count numbers. For example, the spectral count numbers for Eno1 are much higher than that of Uchl1, but

the immunoblot data would suggest that the latter protein should be more abundant

(Object 3-1, Sheet 5). Overall, the immunoblot data provide a measure of validation of the mass spectrometry data.

Because the complexity of the PBS-soluble fractions that were analyzed by LC-

MS/MS was much greater than that of the SDS-insoluble fractions, direct comparisons of protein abundance by spectral counting is difficult. Spectral count numbers for peptides from any given protein can be affected by co-elution with other abundant peptides and the number of spectra for any given peptide can reach a saturation point from sample loading. From an analysis of serially diluted PBS-soluble fractions, we observed that each protein exhibits different saturation points. In the present study, the amount of sample that was loaded for LC-MS/MS of PBS-soluble fractions was biased towards detecting enough spectra from proteins of lesser abundance to provide confidence of protein identification. In this setting, the spectral counts for very abundant proteins were at saturation. Based on the intensity of immunostaining of proteins detected in SDS-insoluble fractions relative to PBS-soluble fractions in immunoblots, we surmised that a relatively small fraction of the total amount of any given protein shows shifts in solubility in the brains of the aged rTg4510 mice. To confirm this assumption, we compared the relative intensity of the immunoreactivity for MDH1 in the PBS-soluble fraction from nontransgenic brains to that of 7.0 month old rTg4510 mice. As expected, the levels of MDH1 in the PBS-soluble fraction of brain lysate from rTg4510 mice were not significantly different from that of brain lysates from age-matched nontransgenic littermates (Figure 3-4 b and c). Immunoblotting for SOD1 was used as a loading control because SOD1 is only detected in PBS-soluble fractions in both nontransgenic and

transgenic mice (Object 3-1, Sheet 1). We conclude that at steady-state, a relatively small fraction of these proteins exhibits altered solubility. Whether these non-natively folded proteins are cleared or whether they may be in equilibrium with a natively folded state is unknown at present.

We next asked whether the proteins detected in SDS-insoluble fractions would potentially be visible as inclusions in tissue from mice with high levels of neurofibrillary tangle pathology and if changes in the distribution of these proteins would change by

Dox treatment. As with validating LC-MS/MS data using immunoblot, obtaining reliable antibodies for histology was also a challenge, particularly with less-studied proteins.

One of the proteins that had a large differential in spectral counts in SDS-insoluble fractions from nontransgenics relative to older rTg4510 mice was Hspa4 (Table 3-2).

We were able to identify an antibody that appeared to be specific for Hspa4 and demonstrated increased immunostaining for this protein in older rTg4510 mice (Figure

3-5). The increased staining for Hspa4 did not appear to overlap with tau reactivity in

NFT structures, suggestive that Hspa4 was not co-depositing with tau in vivo.

Differential Effects of Pathological Tau Versus Amyloid-β on Proteome Solubility

As noted above, there was a somewhat surprising degree of overlap in the identity of proteins that lost solubility in the APPswe/PS1dE9 and rTg4510 models. We used cluster analysis to compare the data from these two models to get a more in-depth assessment of similarity. For comparison, we also included data from analysis of SDS- insoluble proteins in the brains of rTg21221 mice expressing WT human tau. All rTg21221 mice clustered into a distinct subgroup, which was expected given the lack of tau pathology and misfolded tau in this model (Figure 3-6). The data from rTg21221 brain analysis clustered together with younger (2.5 months) rTg4510 samples and one

4.5-month-old rTg4510 sample. The three remaining 4.5-month-old rTg4510 mice were clustered into a separate group, exemplifying the variability in spectral count data from the SDS-insoluble brain fractions of this age group (Figure 3-6). Interestingly, these three mice at this stage of tauopathy were more similar to aged APPswe/PS1dE9 mice than to their older rTg4510 counterparts. As expected, all older rTg4510 mice (both 7- and 9.5-month groups) clustered together aside from one 7.0 month old anmial, reflecting their similarities in the number and identity of proteins that aberrantly fractionate in the SDS-insoluble fraction (Figure 3-6). APPswe/PS1dE9 animals clustered according to age, with older mice (20 months of age) exhibiting more severe proteome insolubility compared to younger mice (9, 12 and 16 months of age) and accurately reflects our previous findings in this model [285]. Older groups of both rTg4510 and APPswe/PS1dE9 mice were more similar to each other regarding their insoluble proteomes compared their younger counterparts. Thus, it appears that as pathological burden increases with age (highest in older mice of these lines) a specific subpopulation of the proteome becomes over-represented in SDS-insoluble fractions from the brains of these mice.

Analysis of Changes in Proteome Solubility in Mouse Models of Spinal Proteinopathy

To further extend our analysis of changes in proteome solubility that occur in neurodegenerative disorders, we analyzed the SDS-insoluble proteomes of mice that model SOD1-linked ALS, spinal tauopathy and spinal α-synucleinopathy (Object 3-2,

Sheet 2), using the same criteria and statistical analyses as described above. The

G93A SOD1 model develops an ALS-like paralytic phenotype accompanied by motor neuron degeneration [101] and the accumulation of aggregated mutant SOD1 that is

insoluble in non-ionic detergent [130, 138, 269, 270]. Our proteomics analysis of G93A

SOD1 mice revealed many cytosolic proteins that aberrantly fractionate as SDS- insoluble in spinal cords of paralyzed G93A mice. Specifically, 177 proteins were identified that exhibited a SAINT score of ≥0.9 based on spectra from 4 independent replicates of G93A SOD1 mice compared to 6 nontransgenic controls (see Object 3-1,

Sheet 3; proteins with greatest differential listed in Sheet 6). Notably, prior studies have demonstrated that mutant SOD1 aggregates in G93A spinal cord are solubilized by

SDS [138]. Neither human nor mouse SOD1 peptides were detected in SDS-insoluble fractions at levels that met statistical significance criteria (Object 3-1, Sheet 3). Thus, in the G93A model, proteins that fractionate in SDS-insoluble fractions are clearly not doing so because of some association with an SDS-insoluble SOD1. By contrast, in rTg4510 mice, tau peptide spectra were easily detected at high frequency in SDS- insoluble fractions (Object 3-1, Sheet 3). In comparing the identities of proteins with abundant peptide spectral counts in the SDS-insoluble fractions of the G93A and rTg4510 mice (based on spectral counts), there were multiple proteins in common

(Figure 3-7 a and b). In the data for Aβ, tau and SOD1 models, there were 91 shared proteins that were over-represented in the SDS-insoluble fractions G93A spinal cords and the brains of APPswe/PS1dE9 and rTg4510 models (Figure 3-7c; Object 3-1, Sheet

7).

To compare the effects of tau and αSyn pathology in the spinal cord on proteome solubility, we utilized the JNPL3 (human tau-P301L [158]) and M83 (human aSyn-A53T,

[87]) mouse models. Both models develop abundant spinal tau or αSyn inclusions, respectively, as well as severe motor dysfunction. We used M83 mice in two separate

paradigms. These included homozygous M83 mice that intrinsically develop αSyn pathology with age [87] and hemizygous M83 mice induced to develop CNS pathology via peripheral intramuscular (IM) injection of pre-formed αSyn fibrils [216]. In mice from all three models that exhibited severe spinal pathology and motor deficits, we identified over 100 proteins that showed 3-fold or greater over-representation in the SDS- insoluble fraction (Figure 3-8a). The harvest age for each model varied according to the age of paralytic impairment, ranging from 13 to 18 months in JNPL3 mice, 12 to 15 months in homozygous M83 mice, 5.4 to 5.8 months in the seeded M83 IM-injected mice (hereafter referred to as M83 seeded), and at 6 months in G93A SOD1 mice. The control mice for these studies, which also varied in age, were grouped as a single control population (n=6; Table 3-1). Individual samples for the JNPL3 mice produced a wide variation in the number of proteins that met criteria (3-fold difference, with minimum of 5 spectral counts in the transgenic sample), ranging from 50 to 233 (134 average; Figure 3-8a). SDS-insoluble fractions from individual spinal cords of aged homozygous M83 mice exhibited a range of 102 to 180 affected proteins (161 average;

Figure 3-8a). Similar results were achieved in heterozygous seeded M83 mice, ranging from 142 to 195 proteins identified (173 average, Figure 3-8a). In comparison, in the

G93A model, the range of proteins meeting criteria was 195 to 223 (210 average;

Figure 3-8a).

To identify proteins in the SDS-insoluble fractions that were common between the models, we used SAINT score analysis (using a score threshold of ≥0.9), which compared data across all models and controls in statistical analyses (individual lists per transgenic model can be found in Object 3-1, Sheet 3). Among these different models,

100

we identified 43 proteins that were commonly identified as over-represented in SDS- insoluble fractions (Object 3-1, Sheet 8). To further define shared features of these models, we used cluster analysis based upon peptide spectra for detergent-insoluble proteins. The proteins identified and the number of peptide spectra for SDS-insoluble fractions from tissues from each model clustered largely by genotype (Figure 3-9).

Additionally, compared to the data from rTg4510 mice, the different models of spinal proteinopathy grouped together, with G93A SOD1 mice being most similar to M83 seeded mice (accelerated pathology model). Meanwhile, JNPL3 mice displayed the greatest degree of variability, having the most similarity to aged homozygous M83 mice.

Overall, the proteomic data from these models clustered first according to pathological localization and second according to genotype. In summary, our data demonstrate changes in the solubility of a subpopulation of CNS proteins and identify 43 proteins that are aberrantly detectable in SDS-insoluble fractions of spinal cord from mice with mutant SOD1, tau, or αSyn pathology.

Identification of Proteins in SDS-insoluble Fractions from N2a Cell Lysates Prepared with Tau Aggregates

To obtain additional evidence that what was observed in our proteomics analysis of transgenic mouse tissues from tau mice was not due to the binding of cellular proteins to pathologic tau aggregates, we utilized an established paradigm of exposing mouse Neuro2a (N2a) cells to human tau aggregates [81, 100]. N2a cells were expected to express many of the same proteins found in CNS tissues. Cells were transfected with vectors to express human mutant P301L tau in conjunction with seeding the cells with pre-formed aggregates of a synthetic tau fragment (K18) [100]. In this paradigm, a subset of cells produce full-length human tau aggregates [100]. We

101

hypothesized that, if proteins identified in SDS-insoluble fractions from the tau mice were simply binding to misfolded tau during the fractionation process, then such proteins should exhibit similar behavior if they are present in the N2a cells. In all of the mouse studies above, the samples underwent sequential extraction starting with PBS, then in buffers containing NP40, DOC, and SDS (see Materials and Methods). In this cell culture model, we simplified the protocol to separate PBS soluble proteins from proteins insoluble in buffered DOC. We had previously determined that high quality LC-

MS/MS data can be obtained from cultured cells with this simplified method [283, 284].

Proteins in which the spectra were at least 3-fold more abundant in DOC-insoluble fractions of cells seeded to induce tau aggregation compared to naïve cells in 2 out of 3 replicates were considered to meet criteria for over-representation. If a protein was absent from the DOC-insoluble protein fractions of naïve cells, then there must have been five peptide spectra present for the protein in the insoluble fractions from the tau seeded condition to meet criteria (G-test p>0.05). As previously described, the data was filtered to focus on proteins that are normally readily detectable in PBS-soluble fractions of naïve cells but aberrantly fractionate into detergent-insoluble fractions in cells exposed to aggregated tau. Of the 20 proteins with the highest number of spectral counts in SDS-insoluble fractions from the brain of rTg4510 mice (see Figure 3-7b), 7 met criteria for detection in insoluble fractions generated from the seeded N2a cells

(having an average spectral count ≥ 5) while 13 were detected only in PBS-soluble fractions (Figire 3-10 a and b). Importantly, only tau and one other protein (Fasn) met criteria for over-representation in the DOC/SDS-insoluble fractions of both N2a cells and rTg4510 mice (Figure 3-10a). As expected, the number of spectral counts for tau in the

102

insoluble fractions from the seeded N2a cells was much higher than any other protein

(Figure 3-10a). The vast majority of these tau spectral counts were derived from the recombinant tau seeds, which comprise the amino acids 244 to 372 of human tau. We identified 16 proteins that met criteria for over-representation in detergent-insoluble fractions in tau seeded N2a cells, 12 of which were unique to this paradigm and not present in either rTg4510 or JNPL3 mice (Figure 3-10 c and d). There were 3 proteins aside from Fasn (Acly, Gls and Tpi1) that were over-represented in the DOC-insoluble fraction of N2a cells that also met criterion for SDS-insoluble fractions from either rTg4510 or JNPL3 mice (Figure 3-10d); however, the spectral counts for these three proteins were relatively low (Object 3-2, Sheet 3). Of the 453 proteins detected only in

PBS-soluble fractions of tau seeded N2a cells, 102 of these proteins were among those that were over-represented in detergent-insoluble fractions of CNS lysates from the rTg4510 and JNPL3 models (Figure 3-10d). Collectively, these data indicate that the proteins identified as over-represented in detergent-insoluble fractions of the tau models are not likely to be associating with misfolded tau aggregates during the fractionation process.

Bioinformatic Analysis of Proteins that Aberrantly Fractionate as SDS-insoluble Reveals Commonly Affected Protein Classes

Our data to this point indicate that the brains of mice with distinct pathological features show common signatures of altered protein solubility. To determine whether particular classes of proteins might be selectively vulnerable, we conducted bioinformatics analyses on all proteins that met statistical criteria across the neurodegenerative proteinopathy models. For this gene ontology analysis, we honed in on protein classes that were significantly over-represented (statistical over-

103

representation test, PANTHER database, see Materials and Methods) in the SDS- insoluble fraction relative to the mouse proteome. This revealed the common occurrence of transferases, oxidoreductases, dehydrogenases, kinases, ligases, chaperonins, chaperones and lyases as aberrantly fractionating into insoluble fractions in the presence of neurodegenerative pathology (Figure 3-11). Many protein classes were present in three or more proteinopathy models, including cytoskeletal proteins, actin family cytoskeletal proteins, non-motor actin binding proteins, aminoacyl-tRNA synthetases and hydrolases. Other affected protein classes were unique to the presence of a particular type and/or location of pathological inclusion, such as anion channels being specific to the M83 seeded model and cysteine proteases/proteases being specific to G93A SOD1 mice. Meanwhile, several protein classes were specifically affected in the presence of cortical tauopathy (Figure 3-12). Overall, the data indicate significant commonality in the identities and classes of proteins that aberrantly fractionate into SDS-insoluble fractions of CNS tissues from neurodegenerative mouse models.

Discussion

In the current study, we have determined the identity of CNS proteins that exhibit changes in detergent solubility in the presence of robust neurodegenerative pathology.

Building on a prior study of mice that model Alzheimer’s amyloidosis, the models examined here included mice that develop tau, αSyn, or SOD1 pathology. In mice that model cortical tau pathology, we demonstrate that the number of proteins that become aberrantly detectable in SDS-insoluble fractions increases as pathology worsens and the levels of insoluble tau increase. To control for possible associations between aggregated tau and cytosolic proteins, we used an N2a cell culture model of seeded tau

104

aggregation. In these seeding experiments, only a fraction of the cells contain tau aggregates and, thus, this paradigm provides a control for potential interactions between tau aggregates and cytosolic proteins during cell lysis and fractionation. Our data suggest that the proteins that were over-represented in SDS-insoluble fractions of rTg4510/JNPL3 mice were not merely binding to and co-sedimenting with tau aggregates during the fractionation process. Cluster analysis of the detergent-insoluble peptide spectra across the different models demonstrated that mice with high levels of amyloidosis (aged APPswe/PS1dE9 model) clustered together with older rTg4510 mice.

141 of the 179 proteins identified as over-represented in insoluble fractions from the brains of APPswe/PS1dE9 mice by SAINT score were also found in insoluble fractions from the brains of rTg4510 mice (277 total proteins by SAINT score). Interestingly, 91 proteins identified in SDS-insoluble fractions of brains from APPswe/PS1dE9 or rTg410 mice were also found in insoluble fractions from spinal cords of G93A SOD1 models.

Additionally, there were 43 proteins that were present in the insoluble fractions from spinal cords of G93A SOD1 mice that were also found in spinal fractions from αSyn and tau models. Importantly, the shifts in proteome solubility in the spinal cords of G93A mice (177 proteins total) occurred despite the fact that misfolded mutant SOD1 was not itself SDS-insoluble [138]. Collectively, these data provide strong arguments against the notion that the cytosolic proteins found in SDS-insoluble fractions of CNS tissues from these mouse models are simply binding to, or otherwise specifically co-aggregating with, a primary pathologic protein.

Proteomic approaches have been used extensively to investigate proteins that may associate with pathological features in neurodegenerative disorders (Table 3-3).

105

One aspect of our study that must be emphasized is that the tissues we have subjected to our detergent extraction protocol were all freshly isolated. When we first began to use our protocol to analyze mice that develop Alzheimer’s amyloidosis, we noticed a remarkable difference in the LC-MS/MS data between freshly prepared and frozen tissue [285]. This aspect of our study must be taken into account when comparing our findings to previous work of human and mouse samples that had been frozen prior to tissue analysis (Table 3-3; one study used tissue embedded in paraffin [69]). We harvest and homogenize fresh tissue in order to avoid changes in solubility that could occur due to freeze/thaw. Nonetheless, despite methodological differences, a subset of the proteins we identified had also been identified in other studies as associated with pathological features or pathological proteins. Multiple studies have used a co- immunoprecipitation paradigm with either Aβ, or tau, on human AD and tauopathy tissues (Table 3-3). Of the collective 352 proteins identified in these studies, 109 overlapped with our data set (Figure 3-13, left panel). One of these co- immunoprecipitation studies, identified over 100 proteins that bind to a synthetic β- structure peptide [193], but our data showed minimal overlap with this data set (only 7 proteins; Table 3-3). Altogether, of the 277 proteins (across all ages) we identified as over-represented in SDS-insoluble fractions of brain lysates from the rTg4510 mice, there were 115 that had been previously identified as binding Tau (Object 3-1, Sheet 9).

Laser capture microdissection another approach that has been used to enrich for proteins adjacent to pathological features in human tissues [69, 160, 273] (Table 3-3).

Of the 296 proteins identified by these approaches, 94 overlap with our data set (Figure

3-13, left panel). Notably, of the 36 proteins identified to be associated with Lewy bodies

106

present in AD brains, 17 were also present in SDS-insoluble protein fractions of rTg4150 mice (Table 3-3) [282]. Collectively, these prior studies identified 143 proteins

(in addition to tau itself) that were associated with pathologic features that we also detected as over-represented in SDS-insoluble fractions from rTg4510 mice (Object 3-1,

Sheet 10). Several studies have identified proteins in tissues from AD and tauopathy patients that were insoluble in detergents or otherwise exhibited altered solubility [8, 12,

96, 102, 226, 281] (Table 3-3), and our study identified many of the same proteins (n =

60; Figure 3-13, right panel). One study of mice expressing tau-P30L transgenes, similar to our JNPL3 mice, identified proteins with shifts in solubility [55], and our study identified 10 of the 28 proteins previously characterized as altered (Table 3-3).

Altogether, of the 277 proteins we identified as over-represented in SDS-insoluble fractions from the brains of 7.0-9.5 month old rTg4510 mice, 121 have not been identified in any previous proteomic study of neurodegenerative pathology (Figure 3-

14).

Previous work in G93A SOD1 mice had looked for detergent-insoluble proteins that may specifically become sequestered into SOD1 aggregates [227]. An analysis of proteins extracted from frozen tissues that were insoluble in NP40 detergent identified mutant SOD1 as the only protein uniquely present in samples derived from the paralyzed G93A mice. Another study in G93A SOD1 mice identified 29 proteins enriched in triton-insoluble fractions of spinal cords from 26 week-old mice [18]; however, only 11 of these 29 proteins overlapped with our own data from this line of mice. Overall, the vast majority of proteins we identify in SDS-insoluble fractions from the spinal cords of G93A SOD1 mice have not been previously recognized as binding

107

aggregated SOD1. Moreover, as noted above, aggregated SOD1 is largely soluble in

SDS and, thus, the insoluble proteins we detected in spinal cords of these mice were not bound to SOD1.

The process by which a subset of cellular proteins become insoluble in SDS in these models requires further study. None of the proteins identified here have been previously described to form inclusions in CNS tissues of the mouse models we examined. While it is difficult to completely exclude interactions between misfolded pathologic proteins (tau, SOD1, αSyn, etc.) and a subset of cytosolic proteins, we also envision a scenario in which proteins form SDS-resistant conglomerates as a result of extended existence in a non-natively folded state. These non-natively folded proteins could persist longer in neural cells in neurodegenerative disease either because there is insufficient chaperone function to fold them or insufficient proteasome/autophagic function to degrade them. In non-native states of folding, hydrophobic regions within these proteins could be exposed, causing them to associate into amorphous aggregates that rapidly coalesce into larger sedimentable aggregates when the tissues are initially homogenized in PBS. Notably, in prior studies of proteostatic stress in cell culture models, we have observed that acute thermal stress causes shifts in protein solubility, but the structures generated are not resistant to SDS [284]. We hypothesize that the proteins we identify as aberrantly insoluble in mouse models of tauopathy, α- synucleinopathy, and SOD1 pathology may exhibit this property due to extended existence in a non-natively folded state. There is well-established precedence for non- natively folded proteins to organize into large aggregates in the presence of detergents from studies of misfolded prion protein (PrP). Misfolded PrPSc that accumulates in the

108

brains of hamsters infected with prion rapidly organizes into large aggregates when membranes isolated in aqueous solutions are exposed to detergents [168]. Notably, the misfolded PrPSc in the brains of infected hamsters often accumulates without organizing into recognizable intracellular inclusions [168]. We hypothesize that a similar type of reorganization of dispersed, misfolded, cellular proteins in the brains of our models could cause these proteins to lose solubility in SDS.

There have been multiple studies that have documented changes in proteasome function in tissues from mouse models of neurodegenerative disease as well as human tissues [37, 71, 75, 131–133, 140, 187, 219, 250, 293]. Diminished proteasome or autophagic function could cause non-natively folded proteins to persist longer than normal. Similarly, there is ample evidence that insufficient chaperone function could play a role in causing proteins to lose solubility. Reports have described associations between tau many different chaperones that are engaged in multiple functions, including the facilitation of microtubule binding and its proteolytic turnover [61, 66, 73, 129, 137,

175, 198, 218]. Tau also associates with other proteostatic factors, including the E3 ligases CHIP, TRAF6, and Axotrophin/MARCH7 [10, 80, 198, 230]. Both the ubiquitin/proteasome and autophagic systems contribute to tau degradation [10, 56, 62,

73, 105, 106, 155, 198, 275] It has also recently been discovered that a deubiquinating enzyme, OTUB1, regulates the ubiquitination state of tau [272]. As previously mentioned, proteasomal impairment has been linked to tauopathy in a wide range of settings [56, 106, 140, 155, 187, 250]. Based upon the extensive degree of proteostatic elements and processes involved in tau homeostasis, it is reasonable to propose that when pathological tau accumulates to the degree that is seen in rTg4510 mice, the

109

balance of cellular proteostasis may be compromised, leading to insufficient capacity to maintain other cellular proteins.

One of the aspects of the rTg4510 model that is particularly useful is that the expression of mutant tau is driven by promoter elements that can be regulated by treating the mice with analogs of tetracycline such as doxycycline [207]. Tau suppression was effective in improving proteome solubility when animals were harvested 2.5 or 1.5 months after initiating treatment at 4.5 or 5.5 months of age, respectively, but much less effective when the mice were aged longer (with doxycycline administered at 5.5 months of age and harvested at 9.5 months). Previous work in the rTg4510 model has characterized the effects that tau reduction has on NFT pathology, tau solubility, and cognitive performance [217]. Suppression of tau expression at 4.5 or

5.5 months of age has a limited effect on the evolution of tau pathology due to the baseline expression of the mutant tau gene (estimated to be 2-fold over endogenous in the presence of doxycycline) [217]. Our mass spectrometry data, however, show that the levels of SDS-insoluble tau are lower in mice treated with doxycycline. In prior studies of rTg4510 mice, doxycycline to suppression of mutant tau at 5.5 months of age led to statistically significant improvements (but not a full recovery) in cognitive performance when tested at either 7.0 or 9.5 months of age [217]. We observed that far fewer proteins were identified as over-represented in SDS-insoluble brain fractions from mice treated with doxycycline at 5.5 months and harvested at 7.0 months or 9.5 months.

The alignment of these data suggests that changes in proteome solubility could contribute to cognitive dysfunction and neuronal death. Notably, significant losses in hippocampal neurons are first evident in rTg4510 mice at 5.5 months age, which is

110

beyond the age that we first observe changes in proteome solubility (4.5 months; see

Figure 3-1a).

The present work, coupled with a prior effort using mice that model Alzheimer’s amyloidosis, demonstrates that one of the common signatures of disease in mouse models of neurodegenerative proteinopathy is a loss in proteome integrity. In each of the models we examined, we identified >100 proteins that aberrantly fractionated into detergent-insoluble fractions. This study focused on proteins that were consistently detected in PBS-soluble fractions with minimal tendency to spontaneously lose solubility with age (Object 3-1, Sheet 1). A large body of literature has described changes in protein quality control networks in neurodegenerative disease including changes in the function of chaperones, the ubiquitin-proteasome system, and the autophagy-lysosomal pathway. How these changes impact cellular function has largely been uncharacterized.

Here, we identify the cellular proteins and specific protein classes that are most impacted by the disruptive features of misfolded Aβ, tau, αSyn, and SOD1. Although each proteinopathy exhibits some unique signatures of altered cellular proteome solubility dysfunction, we identified a core of vulnerable proteins that were consistently detected in SDS-insoluble fractions at much higher frequency in the transgenic animal models analyzed here. For any given cellular protein, the portion that aberrantly fractionated as SDS-insoluble was relatively modest and this limited alteration in solubility seems unlikely to be sufficient to cause loss of function of any particular protein that we identified. However, it is possible that our method does not fully account for changes in proteome folding because some, or most, of the non-natively folded proteins in the CNS of these models might not coalesce into detergent-resistant

111

aggregates. In conclusion, our study provides the first systematic comparison of proteome solubility across different models of neurodegenerative disease and reveals the identity of proteins that consistently show aberrant fractionation into SDS-insoluble fractions and, thus, could be useful molecular biomarkers of proteostatic disruption.

112

Figure 3-1. Quantification of changes in protein detection in SDS-insoluble fractions in brains of rTg4510 mice. (a) Numbers of proteins that meet criteria for over- representation in SDS-insoluble fractions in rTg4510 mice at different stages of tauopathy, both with (shaded area) and without tau suppression via doxycycline. Data are presented as mean ± SD. *, p < 0.05; **, p < 0.01; ***, p<0.0001. Proteins were accepted if they achieved (i) at least a 3-fold increase in SDS-insoluble peptide spectra from nontransgenic to transgenic counterparts, (ii) when nontransgenic SDS-insoluble fractions yielded an average of <1 spectra for any given protein, the transgenic SDS-insoluble fraction contained at least 5 peptide spectra identified, and (iii) each individual protein in a given animal achieved G-test significance (p < 0.05). For doxycycline (DOX) treatment, the number shown within parentheses indicates the age (in months) at which the mice received doxycycline to suppress tau expression. Orange symbols were animals treated with DOX beginning at 4.5 months and the black symbols were animals that were treated with DOX beginning at 5.5 months of age, with all harvested at 7.0 months of age. n.s.; not significant. (b) Numbers of SDS-insoluble tau spectra corresponding to each animal analyzed. (a-b) Each data point symbol represents an individual animal with each symbol corresponding to the same animal analyzed in panel (a). (c) Venn diagram of the affected proteins that reach SAINT score threshold (≥0.9) in each individual age group of rTg4510 mice (Object 3-1, Sheet 3). (d) Venn diagram of the overlap between rTg4510 and APPswe/PS1dE9 mice based upon LC-MS/MS analysis of SDS-insoluble proteins. The protein list was compiled based upon the lists of proteins generated in Object 3-1, Sheet 3.

113

Figure 3-2. Two-way clustering of spectral count data from rTg4510 mice. Clustering is based upon detergent-insoluble peptide spectra for 206 total proteins identified as affected in rTg4510 mice of any age (with and without DOX treatment). Red is indicative of the highest number of peptide spectra for a given protein relative to nontransgenic control mice, while blue is indicative of an absence of the peptide in SDS-insoluble fractions, or absence of a difference between transgenic and nontransgenic samples. Figure 3-2 was generated using JMP Pro Statistical Discovery from SAS (version 13.0, Cary, NC, USA).

Figure 3-3. Venn diagram of common proteins identified in APPswe/PS1dE9 (L85) across different analysis timepoints. Newly analyzed L85 mice were compared to previously analyzed animals.

114

Figure 3-4. Immunoblot validations of LC-MS/MS data in rTg4510 mice. (a) SDS- insoluble fractions were analyzed for rTg4510, nontransgenic littermate, and rTg21221 (wild-type) tau-expressing control mice and probed with antibodies for MDH1, PGAM1, ALDOC, UCHL1 and ENO1. 30 μL of the SDS-insoluble fractions (of the total ~300 μL volume) from the forebrains of rTg4510 or nontransgenic mice were separated on a 4-20% tris-glycine gel. DOX treated animals received the drug at 4.5 months of age (7.0 month group) or 5.5 months of age (9.5 month group). The spectral count data from the proteins analyzed by immunoblotting are provided in Object 3-1, Sheet 5. (b) MDH1 immunoblot of PBS-soluble fractions of 7-month-old rTg4150 mice and nontransgenic controls. 5 µg of protein were loaded per well. Immunoblotting for SOD1 served as a loading control. All lanes in which samples were loaded are shown in each blot, with the blot cropped to include the relevant weight marker for each protein detected. (c) Quantification of MDH1 signal; data are presented as mean ± SD; n.s., not significant; A.U., arbitrary units.

115

Figure 3-5. Immunoreactivity for Hspa4 protein is not highly co-localized with neurofibrillary tangle pathology of rTg4510 mice. Nontransgenic mice (a & b) exhibit minimal positive staining of Hspa4 puncta (green). rTg4510 (c & d) exhibit dramatic increases in Hspa4 puncta (green) that do not directly co- localize with neurofibrillary tangles (stained using the MC1 antibody to misfolded human tau, red). rTg4510 mice that received doxycycline to suppress mutant tau expression from 4.5 – 7.0 months of age (e & f) exhibited reduced Hspa4 immunostaining compared to rTg4510 mice that did not receive doxycycline. The graph shows the number of spectral counts for Hspa4 in SDS-insoluble fractions from the forebrains of NTg, 7-month-old rTg4510 mice, and 7-month-old rTg4510 that began DOX treatment at 4.5 months of age (g).

116

Figure 3-6. Two-way clustering of spectral count data from SDS-insoluble fractions from rTg4510, rTg21221 and APPswe/PS1dE9 mice. Clustering is based upon detergent-insoluble peptide spectra for 222 total proteins identified as affected in either rTg4510, rTg21221 or APPswe/PS1dE9 Line 85 (L85) mice. Red is indicative of the highest number of peptide spectra for a given protein relative to nontransgenic control mice, while blue is indicative of absence of the peptide in SDS-insoluble fractions, or absence of a difference between transgenic and nontransgenic samples. Figure 3-6 was generated using JMP Pro Statistical Discovery from SAS (version 13.0, Cary, NC, USA).

117

Figure 3-7. Comparison of spectral count data between rTg4510 and G93A-SOD1 mice. (a-b) Average spectral counts of the 20 most affected proteins in either paralyzed G93A mice (a) or 7-month rTg4510 (b) mice relative to either mutant SOD1 or tau, demonstrating low levels of mutant SOD1 in the SDS- insoluble fractions of spinal cord from G93A SOD1 mice. The small black arrow marks the position for tau and SOD1 in each graph. (c) Venn diagram of the overlap between rTg4510, APPswe/PS1dE9 (L85), and G93A SOD1 mice based upon LC-MS/MS analysis of SDS-insoluble proteins. There were 91 proteins that were identified as enriched in SDS-insoluble fractions in G93A spinal cord by SAINT score analysis that were common between the three models.

118

Figure 3-8. Neurodegenerative models of spinal proteinopathy characterized by paralysis also induce impairments in proteome solubility. (a) Numbers of proteins that abnormally shift to an insoluble state in JNPL3 (n = 7), homozygous M83 (n = 5), hemizygous M83 seeded (n = 4) and G93A SOD1 (n = 4). Graph displays the number of proteins in each model that were identified as over-represented in SDS-insoluble fractions of the transgenic animal relative to nontransgenic control mice. JNPL3 (all female), homozygous M83 (3 female, 2 male), hemizygous M83 seeded (2 male, 2 female) and G93A SOD1 (2 male, 2 female) mice were analyzed at end-stage phenotype (one or more limbs exhibiting paresis). Figure 3-8a was generated using GraphPad Prism (version 7.0h). Significance was assessed by unpaired, two tailed T-test *, p < 0.01; **, p < 0.005. Data are presented as mean ± SD. (b) Venn diagram of the proteins that met criteria by SAINT score (0.9 threshold) as over-represented in SDS-insoluble fractions among all spinal models.

119

Figure 3-9. Two-way clustering of SDS-insoluble spectra for rTg4510, M83, M83 seeded, JNPL3, and G93A SOD1 models. Clustering is based upon detergent-insoluble peptide spectra for 310 total proteins identified as affected in any spinal proteinopathy model. Red is indicative of the highest number of peptide spectra for a given protein relative to nontransgenic control mice, while blue is indicative of an absence of the peptide in SDS-insoluble fractions, or absence of a difference between transgenic and nontransgenic samples. Figure 3-9 was generated using JMP Pro Statistical Discovery from SAS (version 13.0, Cary, NC, USA).

120

Figure 3-10. Analysis of cellular protein co-sedimentation with tau aggregates in mouse N2a cell models. (a) Average DOC-insoluble spectral counts in the seeded N2a cells for a subset of proteins that were identified as aberrantly fractionating to SDS-insoluble fractions from the brains of rTg4510 mice. (b) Average PBS-soluble spectral counts for the same proteins displayed in panel (a), indicating the level of detectability of the proteins in PBS-soluble fractions. (c) Spectral count data for the small number of proteins that meet criteria for over-representation in DOC-insoluble fractions from N2a cells seeded for tau aggregation. Proteins were accepted if they (i) achieved at least a 3-fold increase in DOC-insoluble spectra from untransfected to tau seeded cells for at least 2 out of 3 experimental replicates and (ii) during instances where untransfected cells yielded 0 peptides for any given proteins, the tau seeded condition yielded a significant G-test (p < 0.05). (d) Venn Diagram comparing DOC-insoluble and PBS-soluble proteins from the N2a cells with the proteins identified as over-represented in SDS-insoluble fractions from either brain or spinal cord of rTg4510 and JNPL3 mice, respectively.

121

Figure 3-11. Bioinformatic analysis of protein classes that are statistically over- represented in SDS-insoluble fractions of proteinopathy models analyzed via LC-MS/MS. Statistical over-representation tests (p < 0.05) with Bonferroni correction for multiple testing were conducted using the PANTHER (Protein ANalysis THrough Evolutionary Relationships) database (version 12.0). The graph was generated using Microsoft Excel (version 16.0). The protein list was compiled based upon the lists of proteins generated in Object 3-1, Sheet 3.

Figure 3-12. Bioinformatic analysis of protein classes that are statistically over- represented in SDS-insoluble fractions rTg4510 mice. Pie chart of protein classes uniquely affected in rTg4510 mice. The protein list was compiled based upon the lists of proteins generated in Object 3-1, Sheet 3.

122

Figure 3-13. Overlapping protein identifications between SDS-insoluble fractions from Tg4510 mice and previous proteomic studies of disease-associated pathological features. Venn diagram demonstrating the number of proteins identified from previous studies listed in Table 3-3. These prior studies used various techniques including laser capture microdissections of amyloid plaques and tau tangles (LCM), affinity capture with antibodies to tau, Aβ-42, or synthetic β-structure proteins (IP), isolation of detergent-insoluble proteins from transgenic mouse and human disease tissue (Detergent-Insoluble), and density gradient (Other) methodologies.

123

Figure 3-14. Combined Venn diagram representative of both diagrams from Figure 3- 13, encompassing the numbers of overlapping proteins from all types of methodologies used in previous literature (IP, Detergent-Insoluble, LCM, and Other).

124

Table 3-1. Statistical information for different proteinopathy animal groups analyzed via LC-MS/MS Animal Group Statistical Approach N (experimental) N (control) rTg4510 2.5 mo. Fold-change/G-test 6 7 rTg4510 2.5 mo. SAINT Analysis 6 34 rTg4510 4.5 mo. Fold-change/G-test 4 4 rTg4510 4.5 mo. SAINT Analysis 4 34 rTg4510 7.0 mo. Fold-change/G-test 10 5 rTg4510 7.0 mo. SAINT Analysis 10 34 rTg4510 9.5 mo. Fold-change/G-test 3 7 rTg4510 9.5 mo. SAINT Analysis 3 34 rTg4510 7.0 mo. Fold-change/G-test 4 3 DOX rTg4510 7.0 mo. SAINT Analysis 4 34 DOX rTg4510 9.5 mo. Fold-change/G-test 5 5 DOX rTg4510 9.5 mo. SAINT Analysis 5 34 DOX APPswe/PS1dE9 Fold-change/G-test 3 3 APPswe/PS1dE9 SAINT Analysis 3 3 JNPL3 Fold-change/G-test 7 6 JNPL3 SAINT Analysis 7 6 G93A SOD1 Fold-change/G-test 4 6 G93A SOD1 SAINT Analysis 4 6 M83 Aged Fold-change/G-test 6 6 M83 Aged SAINT Analysis 6 6 M83 Seeded Fold-change/G-test 4 6 M83 Seeded SAINT Analysis 4 6

125

Table 3-2. List of the proteins that showed the highest differential of over-representation in SDS-insoluble fractions from the forebrain of 7-month-old rTg4510 mice. Spectral counts for each protein were averaged from data from 10 individual rTg4510 animals versus 34 nontransgenic controls. All spectral count comparisons in this table exhibited a SAINT score of ≥0.9 (n=10) for over-representation in SDS-insoluble fractions. nTg = nontransgenic, Tg = transgenic, PBS-S = PBS soluble. Gene Symbol Protein Accession Number MW Average Spectral Counts kDa SDS-insoluble PBS-S Ctrl rTg4510 nTg Pgk1 Phosphoglycerate kinase 1 PGK1_MOUSE 45 4.47 58.2 96.8 Pkm Pyruvate kinase KPYM_MOUSE 58 3.74 49.8 164 Uba1 Ubiquitin-activating enzyme E1 B9EHN0_MOUSE 118 3.44 47.7 103.3 Fasn Fatty acid synthase FAS_MOUSE 272 1.79 37.6 40.5 Ldhb L-lactate dehydrogenase B chain LDHB_MOUSE 37 3.91 36.4 89 Gpi Glucose-6-phosphate isomerase G6PI_MOUSE 63 3.26 35.7 107 Crmp1 Dihydropyrimidinase-related protein 1 Q6P1J1_MOUSE 62 4.41 33.7 72 Rap1gds1 RAP1 GTPase-GDP dissociation stimulator 1 Q3TU36_MOUSE 66 1.62 32.7 52.5 Cand1 Cullin-associated NEDD8-dissociated protein 1 CAND1_MOUSE 136 3.74 31 59.3 Pfkl ATP-dependent 6-phosphofructokinase, liver type PFKAL_MOUSE 85 2.03 27.9 25 Gdi1 Rab GDP dissociation inhibitor alpha GDIA_MOUSE 51 3.47 27.6 84.8 Synj1 Synaptojanin-1 D3Z656_MOUSE 176 3.62 26.6 54.3 Vcp Transitional endoplasmic reticulum ATPase TERA_MOUSE 89 0.74 26.6 56.3 Tkt Transketolase TKT_MOUSE 68 0.85 25.8 58 Mdh1 Malate dehydrogenase, cytoplasmic MDHC_MOUSE 37 3.85 25.4 56 Fscn1 Fascin FSCN1_MOUSE 55 2.38 24.9 30.8 Ldha L-lactate dehydrogenase A chain Q3UDU4_MOUSE 36 1.03 23.2 61.3 Prkca Protein kinase C Q4VA93_MOUSE 77 2.74 23.2 12.5 Eef2 Elongation factor 2 EF2_MOUSE 95 2.09 21.8 72.3 Gstp1 Glutathione S-transferase P 1 GSTP1_MOUSE 24 2.56 21.2 35.5 Glul Glutamine synthetase GLNA_MOUSE 42 3.65 21.1 50 Idh3b Isocitrate dehydrogenase [NAD] subunit, mitochondrial Q91VA7_MOUSE 42 2.94 21.1 24 Pgam1 Phosphoglycerate mutase 1 PGAM1_MOUSE 29 2.09 20.8 73.3 Vps35 Vacuolar protein sorting 35 Q3TRJ1_MOUSE 92 2.18 20.8 36 Qdpr Dihydropteridine reductase DHPR_MOUSE 26 1.00 20.7 16.8 Cs Citrate synthase, mitochondrial CISY_MOUSE 52 4.15 20.6 35.8 Ppia Peptidyl-prolyl cis-trans isomerase A PPIA_MOUSE 18 4.76 20.3 54.3 Gdi2 Rab GDP dissociation inhibitor beta Q3UC72_MOUSE 57 3.09 19.7 53.75 Hspa4 Heat shock 70 kDa protein 4 Q571M2_MOUSE 94 0.56 19.6 52.5 Aldoc Fructose-bisphosphate aldolase C ALDOC_MOUSE 39 2.53 19.3 96

126

Table 3-3. Table S13 Overlapping protein identifications between SDS-insoluble fractions from rTg4510 mice and previous proteomic studies of disease-associated pathological features. For complete lists of overlapping proteins from the first two rows of the table, see Object 3-1, Sheets 8-11. AD; Alzheimer’s disease, NFTs; neurofibrillary tangles, DOC; deoxycholate, SDS; sodium dodecyl sulfate, FTLD; frontotemporal lobar degeneration, IP; immunoprecipitation. Study Method of enrichment Overlapping protein identifications # # Proteins Reference Proteins overlapping identified with our findings P301S Tau co-IP Object 3-1, Sheet 11 205 97 [272] Mouse (PS19 model) Brain AD Laser capture Object 3-1, Sheet 11 277 91 [69] hippocampus/ microdissection entorhinal cortex Aβ plaques P301L 40mM tris-insoluble DPYSL2, DPYSL3, GSTM1, GSTP1, MDH1, PRDX6, 28 10 [55] Transgenic TPI1, STIP1, NAPG, ABAT Mice (mThy1.2 promoter) AD plaques Laser capture HSP90AB1, CORO1A, PFKP, YWHAB, YWHAE, 26 9 [160] microdissection ATP6V1E1, UBA1, MAPT, ATP6V1B2 AD Lewy Density gradient UCHL1, OTUB1, PSMD2, VPS35, ATP6V1A, ACO2, 36 17 [282] bodies GPI, ATIC, DPYSL2, HSP90AB1, WDR1, CBR1, PRDX5, PRKCB, DCTN1, UBA52, UBA1, GAPDH AD NFTs Laser capture CFL1, MAPT, TUBB1, ALDOC, MDH2, GPI, ALDOA, 55 25 [273] microdissection PKM, LDHB, GAPDH, MDH1, PGK1, CA2, ENO1, ATP6V1A, STXBP1, ANXA5, MAPK1, PRDX2, UCHL1, PPIA, PRDX1, PRDX6, DPYSL2, UBA52 AD Cortex Triton/sarkosyl-insoluble MAPT 11 1 [96] AD Cortex Triton/sarkosyl-insoluble CFL1, GAPDH, RTN1, DSTN, TUBB1 15 5 [281] β-structure Affinity Chromatography CAND1, KIF5B, AP1G1, ARHGDIA, EIF4A1, HSPH1, 105 7 [193] binding WARS

127

Table 3-3. Continued Study Method of enrichment Overlapping protein identifications # Proteins # Proteins Reference identified overlapping with our findings AD Cortex Sarkosyl-insoluble Total Insoluble: MAPT, CCT8, ACTR1B, ABAT, 176 10 [102] PAFAH1B1, FH, DIRAS2, IDH3G, UBE2V2, CNRIP1 Insoluble Aβ correlation: ANXA5, ATP1B1, CNRIP1 56 3 Insoluble Tau correlation: ADH5, TKT, SYNJ1, FH, 87 17 LTA4H, ALDOC, PRKAR2A, ASS1, PGK1, PSAT1, TPI1, STX1B, RAN, ANXA5, ALDOA, LANCL1, NAPA AD Cortex Sarkosyl-Insoluble SYNJ1, FH, ABAT, MAPT 36 4 [12] FTLD cortex Triton/sarkosyl-insoluble SILAC: PSAT1, GPI, TKT, UBA1, TPI1, CFL1, DCTN1, 21 12 [226] (TDP-43 FASN, MAPK1, IDH3A, IDH3B, ARHGDIA positive, Tau- Label-Free: PPIA, STXBP1, DPYSL2, UCHL1, PRDX5, 18 7 [226] negative) CBR1, PGAM1 AD Purified sarkosyl-insoluble Total sarkosyl-insoluble: YWHAB, YWHAE, NAPB, 38 13 [8] hippocampus aggregates;Aβ42 co-IP; Tau CBR1, EEF2, GSTM5, HSP90AA1, HSP90AB1, MAPT, co-IP PPIA, PGAM1, UBA1, UCHL1 Aβ42 co-IP: YWHAB, YWHAE, ENO1, CBR1, DPYSL2, 84 22 3, 4, 5, DCTN1, DYNC1LI1, EEF2, GSTM5, HSPA12A, HSP90AA1, HSP90AB1, PPIA, PRDX1, PGAM1, STX1B, PFKP, UBA1, UCHL1 Tau co-IP: YWHAB, YWHAE, CBR1, DPYSL2, 3, 4, 5, 80 19 DYNC1LI1, EEF2, HSPA12A, HSP90AA1, HSP90AB1, MAPT, PPIA, PGAM1, STX1B, PFKP, UBA1, UCHL1

128

Object 3-1. Compiled proteomic data highlighted proteins that lose solubility in mouse models of neurodegenerative proteinopathy (.xlsx file 1.08 MB)

Object 3-2. Raw proteomic data from all analyzed mouse models (.xlsx file 428 KB)

129

CHAPTER 4 ASSESSING THE ALLEVIATION OF ABERRANT PROTEOME INSOLUBILITY VIA TRANSIENT INHIBITION OF TRANSLATION WITH CYCLOHEXIMIDE

The accumulation of misfolded proteins within the central nervous system is the hallmark of many different neurodegenerative diseases including AD, PD, Huntington’s disease, FTD, ALS and diseases characterized by the misfolding of the prion protein such as Creutzfelt-Jakob disease [32, 64, 239]. It has been demonstrated, in the context of many proteins implicated in neurodegeneration, that the persistence of misfolded protein pathology within a cell can negatively affect different aspects of protein homeostasis (proteostasis) [35, 57, 71, 131–133, 140, 142, 170, 171, 187, 235, 293].

This has most often been shown within the scope of impaired proteasomal function, which has been observed in the presence of tau, α-synuclein, superoxide dismutase 1

(SOD1) and huntingtin, which have broader implications in AD, PD and Huntington’s disease.

Proteostatic networks are thought to be heavily conserved and tightly regulated, bearing minimal capacity to adjust in the face additional stressors [181, 200]. This inability to pivot in response to a decline in proteostatic maintenance that has been associated with age is thought to contribute, at least in part, to the accumulation of misfolded proteins seen neurodegenerative diseases such as AD [14, 151, 254].

Multiple approaches have been used in an effort to restore proteostatic efficiency and balance, including inhibors of chaperone networks (such as HSP90) and inducers of autophagy (such as rapamycin) [21, 202]. One particular strategy that has only minimally been explored is through the reduction of protein synthesis, which could be pursued in an effort to “reset” cellular proteostasis to allow for protein quality control networks to degrade aggregated proteins. Historically, individuals who survive particular

130

types of cancer and subsequent cancer treatment have reduced risk for developing

Alzheimer’s disease [186]. Interestingly, chemotherapy drugs are often inhibitors of protein synthesis, which many of these patients will have received as a part of standard treatment regimens [33]. It is entirely possible that these cancer patients received treatments that lowered proteostatic burdens at critical timepoints in what would have been the development of early AD pathology, leading to the ability of neurons to clear potentially aggregation prone proteins (such as tau and amyloid-β) and prevent pathology from spreading.

Impaired proteostatic capacity within an affected cell has been hypothesized to impair the folding and maintenance of other vulnerable proteins that are particularly dependent upon a highly functioning proteostasis network. This has been exemplified in multiple cases, including the induction of mutant SOD1 misfolding in a mouse model of tauopathy and the impaired function and folding of temperature-sensitive mutant proteins when either co-expressed with mutant huntingtin or exposed to heat-shock in the C. elegans model [90, 91, 195]. This concept has been further explored through the use bottom-up proteomics experiments to identify proteins that become aberrantly insoluble in the presence of a proteostatic stress (caused by heat-shock or a neurodegenerative proteinopathy), as proteins that are insoluble in stringent detergents are known persist in midfolded states [89, 130, 139, 168, 220, 269]. First, introducing both human neuroblastoma and glioma cell lines to transient stress via heat-shock has been shown to induce the aberrant insolubility of 58 proteins, 10 of which were common between the two cell lines [284]. In a separate study, hundreds of proteins were found to exhibit this abnormal insolubility within the CNS of mice that express mutant variants of

131

the amyloid precursor protein and presenilin 1 (leading to the formation of amyloid plaques) [127, 285], tau, α-synuclein and SOD1 [194]. This work revealed that not only did hundreds of proteins lose solubility in these mice, but also that many proteins were commonly affected no matter the initiating proteinoapthy, further suggesting that broad proteostatic burden occurs in the face of a primary protein misfolding pathology. A study conducted using cycloheximide, a potent inhibitor of protein synthesis [292], revealed that newly synthesized variants of these suspect proteins appear to be particularly vulnerable to misfolding under conditions of proteostatic stress [283]. Despite these recurring evidences of burdened proteostasis leading to detriments in the folding capacities of proteins, it has yet to be determined whether this phenomenon occurs transiently or chronically as pathology worsens.

In the current study, we aimed to assess whether the transient inhibition of protein synthesis would be sufficient to alleviate the aberrant insolubility of proteins observed to exhibit this quality in the presence of a neurodegenerative proteinopathy.

We demonstrated previously that G93A SOD1 mice (expressing SOD1 with glycine mutated to alanine at the 93rd amino acid position) are plagued with hundreds of proteins that aberrantly shift into the insoluble fraction [194]. Using cycloheximide in these mice over an extended dosage period of our own design, we sought to prevent the synthesis of new proteins by as much as 95% over a period of 6 hours in G93A

SOD1 mice [205]. If the subpopulation of the proteome that is vulnerable to proteostatic stress consists mostly of newly synthesized proteins, then the degree of translation inhibition induced by cycloheximide could be sufficient to “reset” proteostasis in these mice. Indeed, newly synthesized protein variants have hydrophobic regions exposed

132

which, without the proper maintenance, could initiate a misfolding cascade in an environment of insufficient proteostasis [15]. Our findings reveal a preliminary, yet promising, effect of transient translation inhibition in the restoration of proteostasis and resolving losses in proteome solubility.

Materials and Methods

Transgenic Mice

G93A SOD1 mice that express the mutant variant SOD1 protein associated with familial ALS have been previously characterized [101]. Expressed under the human

SOD1 promoter, the mutant transgene is expressed within a 12 Kb fragment of genomic human DNA. These mice and nontransgenic (NTg) littermate controls were maintained on the FVB background. Normally, the G93A SOD1 line develops paralysis at about 150 days of age. For the current study we harvested mice at a mild phenotype, a time at which motor dysfunction is beginning to become apparent in these animals. This occurred at ages ranging from 93 to 117 days. We chose this phenotypic time point in order to reduce any complicating factors that could arise with the combination of cycloheximide use in the mice, as this compound is known to have a certain degree of toxicity in mammals [86, 292].

Cycloheximide Preparation, Injection, and Harvesting Procedures

Cycloheximide (CHX, Sigma Aldrich, St. Louis, MO) was solubilized in water at a concentration of two mg/ml 24 hours prior to injection and stored at 4°C. The solubilized drug was administered via intraperitoneal injection using a one mL syringe (BD

Biosciences, Franklin Lakes, NJ). G93A SOD1 or NTg littermate control animals were given three treatments of cycloheximide over a six-hour period, with each dose separated by a two hour time block. The first dose was 120 mg/kg, followed by two 75

133

mg/kg dosages. At the end of the six-hour dosing period, animals were perfused with cold (4°C) PBS followed by the extraction of spinal cord tissue, which was placed on ice.

Sequential Detergent Extraction of Spinal Cord Tissue

We have previously determined in our laboratory that a subset of proteins lose solubility in the APPswe/PS1dE9 mouse model of Alzheimer’s amyloidosis (also referred to as Line 85, or L85) [284, 285]. In order to assess this, we developed a sequential detergent extraction and sedimentation protocol in conjunction with liquid chromatography tandem mass spectrometry (LC-MS/MS) that served to identify specific proteins that become abnormally insoluble in stringent detergent. The acquired insolubility in detergents, whether they be nonionic [e.g. nonidet P-40 (NP-40)] or ionic

[e.g. sodium dodecyl sulfate (SDS)] is an established criterion utilized to separate proteins that are misfolded and/or aggregated from those that exist in a natively folded state [89, 139, 168, 220, 258, 269]. We applied the same technique here in G93A SOD1 mice following either CHX injection or vehicle control. The primary purpose for our sequential detergent extraction methodology is to generate protein fractions of an ideal complexity for analysis via LC-MS/MS. G93A SOD1 mice under the influence of isoflurane were perfused with PBS followed by the extraction of spinal cord tissue which was placed on ice immediately afterward. The tissue was then homogenized in 4 mL

PBS along with 1% protease inhibitor cocktail in DMSO (Sigma Aldrich, St. Louis, MO).

This was followed by homogenization in sequentially more stringent detergents [NP-40, deoxycholate (DOC) and SDS] in order to separate each protein fraction based upon the solubility in the aforementioned detergents. Protein fractions that were insoluble in

SDS (SDS-P) and soluble in PBS (PBS-S) were chosen to analyze by mass

134

spectrometry, based upon their previously established ideal complexity [285]. SDS-P fractions were resuspended in 300 μL 1x Laemmli buffer after their isolation. Preparing each sample for proteomics analysis was initiated by loading 20 μL of each PBS-S fraction and 30 μL of SDS-P fraction into a 4-20% Tris-HCl (Bio-Rad, Hercules, CA) gel.

The proteins were then separated via SDS-PAGE at 125 volts for 15 minutes. The gel was then stained with Coomassie blue followed by each lane being cut into ~1 mm3 fragments. Proteins were then subject to in-gel trypsin (Sigma Aldrich, St. Louis, MO) digestion and peptides extracted from the gel per protocol from the University of Florida

Interdisciplinary Center for Biotechnology Research Proteomics and Mass Spectrometry

Core (ICBR, Gainesville, FL). Finally, the digested peptides were dried using a speed vacuum.

Liquid Chromatrography Tandem Mass Spectrometry Analysis

To prepare the peptides resulting from the in-gel trypsin digestion for liquid chromatography, each sample was resuspended in 0.1% formic acid in water. This was followed by running each sample through an Acclaim Pepmap 100 pre-column (20 mm x 75 μm; 2 μm-C18) and a Pepmap RSLC analytical column (250 mm x 75 μm; 2 μm-

C18) at a flow rate of 300 nl/minute. The prepared peptides were then separated using a linear gradient of solvent A (0.1% formic acid) to 25% solvent B (0.1% formic acid

80% acetonitrile). This was conducted for 95 minutes and then elevated to 98% solvent

B for 25 more minutes. A hybrid quadrupole Orbitrap (Q Exactive Plus) MS system

(Thermo Fisher Scientific, Bremen, Germany) was used with high energy collision dissociation (HCD) for MS and MS/MS cycles. An automated Easy-nLC 1000 system

(Thermo Fisher Scientific, Bremen, Germany) was interfaced with the MS system in order to conduct a 120 minute gradient for chromatography separation.

135

Mascot Distiller (version 2.4) was used to extract MS/MS spectra followed by sample analysis suing X! Tandem [The GPM, thegpm.org; version CYCLONE

(2010.12.01.01)]. The “Mouse Uniprot Protein Knowledgebase (canonical & isoform)” with supplemented human proteins of interest based upon transgenes expressed in our mouse models (89029 entries) was searched based upon the trypsin digestion to identify proteins from peptide spectra. X! Tandem was then used to look through a reverse concatenated section of the customized Mouse Uniprot database.

Specifications within X! Tandem and Mascot were set to a fragment ion mass tolerance of 0.01 Da and parent ion tolerance set to 10.0 PPM. Carbamidomethylated cysteine was input as a fixed modification. Other variable modifications included glutamine→pyroglutamate at the N-terminus, deaminated glutamate and asparagine, the oxidation of methionine, the loss of ammonia on asparagine, and the ubiquitination of lysine (Gly-Gly).

MS/MS-based protein and peptide identifications were confirmed using Scaffold

(version Scaffold_4.7.3, Proteome Software Inc., Portland, OR). Peptide identifications were only established if they surpassed a 95% probability according to the Peptide

Prophet algorithm with Scaffold delta-mass correction [141]. X! Tandem was used to generate the peptide identification probabilities, which were assigned using the Scaffold

Local FDR algorithm. The threshold for accepting a particular protein resided at 99% probability and included at least two identified peptides. The protein probabilities themselves were designated according to the Protein Prophet algorithm [189]. During instances in which more than one protein was supported by significant peptide evidence, these proteins were arranged into clusters. When a group of proteins could

136

not be distinguished according to MS/MS data, they were grouped according to the principles of parsimony.

Bioinformatics, Statistics, and the Calibration/Relative Quantification of Proteomics Data

Quantifying and comparing the different protein fractions between animals was conducted using the unweighted spectrum counts for each protein generated by

Scaffold. These spectral counts were then compared for transgenic versus nontransgenic mice, with separate comparisons made for mice that received CHX versus those that did not. This strategy of using unweighted spectrum counts from one sample to the next to determine differences between them has been previously described [204]. The primary principle behind this is that the number of MS/MS spectra generated per protein is indicative of the relative abundance of said protein. These relative abundances can then be compared for a given protein (or thousands of identified proteins) to assess if a difference occurs between two or more groups. A protein was considered significantly changed if there was greater than a 2-fold increase in spectral count in transgenic G93A SOD1 mice compared to age-matched nontransgenic controls. During instances in which the number of spectra for a given protein was zero for control samples, G-test (likelihood ratio test for independence) analysis using Microsoft Excel (v16.0, Redmond, WA) was used to determine if the differences in spectral counts between groups was statistically significant [192, 204].

When comparing the total numbers of proteins meeting the above criteria for multiple animals across different age groups, unpaired t-tests (conducted using GraphPad

Prism, version 7.0h, La Jolla, CA) were used to determine if one group was statistically different from another. An alternative method to distinguish proteins that were

137

significantly altered between animal groups, we utilized the SAINT (Significance

Analysis of INTeractome) analysis tool [40]. While originally designed to assess confidence in protein-protein interactions with a bait-prey paradigm using label-free spectral count data, we have repurposed SAINT analysis to assess confidence in the significance of the presence of a particular protein (prey) in the SDS-insoluble fractions of G93A SOD1 mice (bait). We used an initial SAINT score threshold of ≥0.5 (50% confidence) to screen for candidate proteins that may have been reduced with CHX treatment, followed by further analyses of fold-change differences between groups based upon peptide spectra [40]. The SAINT score algorithm factors protein molecular weight in its calculation of statistical probability of over-representation.

Results

CHX treatment demonstrates preliminary potential to reset proteostasis in the presence of SOD1 spinal cord pathology. To address the question of whether the transient inhibition of translation would be sufficient to allow turnover of aberrantly insoluble proteins that accumulate in the presence of a proteinopathy, we utilized the small molecule CHX. CHX is a common laboratory reagent used to inhibit eukaryotic protein synthesis and is capable of preventing up to 95% of new protein synthesis via blocking the elongation phase of translation through its interaction with the 60S ribosome subunit [205]. The mechanism by which CHX inhibits translation has not been fully elucidated, but it is understood to prevent eukayotic translation elongation factor 2

(EEF2)-mediated translocation [221]. We have previously used CHX to successfully test this this idea in cell culture [283], and thus sought to extend it in vivo.

Previous results in G93A SOD1 mice from our laboratory demonstrated that, once an end-stage phenotype has been reached, >100 proteins consistently loss

138

solubility in the presence of SOD1 spinal pathology [194]. Due to the potential toxic effects of CHX administration, we chose to use G93A SOD1 animals at a mild phenotypic stage (beginning to show signs of motor dysfunction/paralysis) as opposed to end-stage. The injection paradigm consisted of three subsequent doses (120 mg/kg,

75 mg/kg, 75 mg/kg) separated over 6 hours with 2 hours separating each dose.

Following the last dose, mice were harvested followed by our previously described detergent extraction procedure to isolate SDS-insoluble protein fractions. Mice were separated into 4 groups (n=3-4 per group): G93A SOD1 + vehicle (positive control),

G93A SOD1 + CHX (experimental group), NTg + vehicle (baseline comparison for

G93A SOD1 group) and NTg + CHX (baseline comparison for G93A + CHX group). We lastly used both fold-change/G-test and SAINT score criteria for isolating affected proteins in these mice.

During our first pass of analyzing the SDS-insoluble proteomes of G93A SOD1 mice treated with CHX, we isolated proteins that exhibited a SAINT score threshold of ≥

0.5 across both groups of mice (G93A SOD1 + vehicle and G93A SOD1 + CHX), as we were uncertain as to how dramatic of an effect would be observed with CHX treatment.

Upon conducting this analysis, a large majority of proteins (51 out of 56) that fit this criterion had larger increases in fold-change between the nontransgenic and G93A

SOD1 + vehicle groups compared to the G93A SOD1 + CHX group, indicating at least a mild reduction in SDS-insoluble proteins in mice that received cycloheximide (Figure 4-1 a and b).

Our next strategy for analyzing this data was to assess the number of proteins that exhibited aberrant insolubility in SDS in either G93A SOD1 or G93A SOD1 + CHX

139

groups at the level of the individual animal. When all animals were considered, there was no significant difference detected in the number of proteins that became aberrantly insoluble with or without CHX treatment in G93A SOD1 mice (Figure 4-2a). However, the average number of aberrantly insoluble proteins in the CHX treatment group was less than half of that of the untreated group (18.75 to 47.75, n=4 per group). When removing what could be considered outlier animals from the two groups (those that did not appear to exhibit any degree of a loss of proteome solubility), we also observed no significant difference between groups (Figure 4-2b). The average numbers of affected proteins when comparing these reduced groups of mice were 62 and 37.5 for the G93A

SOD1 (n=3) and G93A SOD1 + CHX (n=2) groups, respectively. Thus, while increases in the numbers of animals analyzed will be needed to gain conclusions with a higher level of confidence, we believe that CHX treatment to transiently halt protein synthesis in mice plagued by a proteinopathy may be sufficient for restoring proteome solubility.

Finally, we compared the lists of proteins affected in our positive control mice exhibiting a mild phenotype to those analyzed in previous studies that exhibited a severe end-stage phenotype [194]. The majority (43 of 58) of proteins that reached a

SAINT score of ≥0.5 in the mice analyzed in this study were also identified in previous analyses of G93A SOD1 mice (Figure 4-3). Thus, even at mild versus severe phenotypes, the proteins that lose solubility in G93A SOD1 mice appear to be relatively consistent.

Discussion

In the current study, we attempted to reverse the accumulation of abnormally detergent-insoluble proteins that occurs in the presence of a neurodegenerative proteinopathy. Specifically, we attempted this strategy in the G93A SOD1 mouse, an

140

established transgenic model frequently utilized in the study of ALS and motor neuron disease [101]. Previously, we identified 100+ proteins that consistently lose solubility in end-stage (paralysis leading to the inability to acquire sufficient nutrition) G93A SOD1 mice relative to nontransgenic littermate control animals [194]. Transient (continual dosing over a 6-hour period) inhibition of translation resulted in a mild, non-statistically significant decrease in the number of aberrantly insoluble proteins in G93A SOD1 mice when CHX was administered at the onset of a mild phenotype. While our results trended in the direction we were anticipating regarding a reversal of aberrant proteome insolubility, the size of the groups analyzed will need to be increased in order to achieve statistical significance, if such an effect exists. Importantly, both independent studies up to this point that assessed SDS-insoluble proteins in G93A SOD1 mice identified similar lists of affected proteins, reinforcing the accuracy and repeatability of both the methodology used (bottom-up, label-free shotgun proteomics) and the insoluble protein content in the presence of a specific proteinopathy (in this case, SOD1 inclusion pathology). However, the list of affected proteins was significantly shorter in animals that exhibited a mild phenotype relative to severe; additionally, the SAINT score threshold had to be shifted in order to compare lists of proteins between the two phenotypes. This demonstrates that a higher degree of motor dysfunction, which is caused by motor neuron death in these mice, is correlated with a greater degree of proteome solubility dysfunction.

Previous literature regarding the relationship between translation rates and neuroprotection in the context of neurodegeneration highlights a variety of promising, yet often conflicting, findings. A generous portion of this research is regarding the

141

unfolded protein response (UPR, for a review in the context of neurodegenerative disorders see [122]), a highly conserved and integral protein quality control mechanism activated in response to stress within the endoplasmic reticulum (ER). An example of such stress is the accumulation of misfolded proteins, which is a hallmark many neurodegenerative disorders [239]. Within the UPR pathway, phosphorylation of the α subunit of eukaryotic translation initiation factor 2 (eIF2α) as a downstream effect of

PERK phosphorylation leads to a decrease in protein synthesis in an effort to “reset” cellular protein quality control [107]. Two small molecules, Guanabenz and Sephin 1, are capable of extending this translation repression by suppressing the activity of

PPP1R15A, a regulatory subunit of an eIF2α phosphatase [53, 259]. These two small molecules have been tested in models of protein misfolding diseases, including a mouse model of Charcot-Marie-Tooth 1B (CMT1B) and the G93A SOD1 mouse used in the current study [53, 128, 271]. When administered Sephin1 at concentrations of

1mg/kg, motor symptoms exhibited in these mice were completely prevented, and prevented the accumulation of insoluble SOD1 in the G93A model [53]. Hence, it appears that there is an existing rationale for using transient inhibition of protein synthesis to prevent toxicity in protein misfolding diseases.

Yet, these aforementioned successes are muddied by the effects of modulating the UPR pathway in other protein misfolding models. The PERK pathway of the UPR

(that which involves the phosphorylation of eIF2α leading to translation suppression) is chronically overactive in mouse models of prion disease and tauopathy [1, 179].

Furthermore, a wide variety of therapeutic approaches (GSK2606414, ISRIB,

Trazodone and DMB) that suppress the PERK pathway have actually been found to be

142

beneficial within the context of toxicity mediated by misfolded TDP-43, tau and prion protein by either reverting eIF2α phosphorylation directly or indirectly restoring protein synthesis [103, 104, 122, 145, 206, 225, 232]. Thus, the effects of eIF2α phosphorylation within the PERK pathway and downstream translation inhibition appear to be either helpful or deleterious, depending upon the misfolded protein in question.

This could be due to whether the disease-associated protein in question is capable of escaping translation repression during times of ER stress, or through a completely different mechanism altogether that is unrelated to rates of translation. For example, the

PERK inhibitor GSK2606414 led to reduced levels of disease-associated tau in the rTg4510 model, despite the restoration of protein synthesis achieved in this paradigm

[206]. Hence, reductions in tau occurred in an environment of translation restoration, not repression. Changes such as these could have occurred via an alternative mechanism, such as the relationship between the activation of eIF2α kinases and that of Glycogen

Synthase Kinase 3β (GSK3β), a known regulator of tau phosphorylation [190]. More work is necessary in order to further elucidate the effects of altering the PERK pathway in the UPR in the context of different disease-associated misfolded proteins.

The potential of treating deficits in proteostasis by transient reductions in protein synthesis remains promising. While the adverse affects of cycloheximide usage reported in mice (deficits in memory) cannot be ignored, these effects were temporary and occurred at relatively high dosages [16, 205, 244]. Intermediate dosages could be achievable that are effective in remedying proteostatic stress that do not cause these negative side effects. The translational aspects of this treatment are yet to be determined. However, a good starting point could be the usage of known

143

chemotherapeutic agents that hinder translation (e.g. bactobolin, septacidin and acvicin) at low doses in order to achieve the desired effect.

The current study was subject to various limitations, the most obvious of which lie in reduced sample sizes and the lack of a robust positive control condition. Prior to initiating this study, we conducted similar proteomic analyses in end-stage G93A SOD1 mice [194]. These mice were burdened by ~150 proteins that became aberrantly insoluble in detergent, which we sought to remedy in this experiment using CHX.

However, due to the potential toxicity of CHX administration, we elected to use animals exhibiting a mild phenotype, in in the hopes of not further exacerbating animal discomfort while still achieving a sufficient degree of detectable insoluble protein. Our results, however, revealed that G93A SOD1 mice exhibiting a mild motor dysfunction phenotype do not have the same degree of aberrantly insoluble proteins as end-stage animals. While this is insightful, as it allows for further elucidation of the degree to which aberrantly insoluble proteins are associated with greater degrees of neurodegeneration and the motor phenotype exhibited in G93A SOD1 mice, this made the assessment of improvements in proteome solubility in mice treated with CHX more difficult to detect.

Additionally, in each group (experimental and positive control) of mice there was at least one G93A SOD1 animal which was minimally affected by the accumulation of insoluble proteins, further reducing the number of animals that could reliably be compared regarding CHX treatment. This led insufficient numbers of animals analyzed in order to assess for statistical significance. To remedy these issues, future studies are planned in which a similar experiment will be conducted in the rTg4510 model of tauopathy. Not only does this model exhibit a more exaggerated insoluble proteome in the face of a

144

proteinopathy [194], but the rTg4510 model is not affected by a paralysis phenotype, which allows us to administer the CHX at an age in which we are confident that untreated animals will be reliable positive controls. The number of animals analyzed will also be increased, to bolster statistical power.

Overall, the data gathered in this study provide a preliminary, yet inconclusive, rationale for transiently halting protein synthesis to allow for stabilization of proteostasis in cells burdened by proteinopathies. While a range of FDA-approved drugs currently exist that work via this mechanism of action for the treatment of other diseases, much more work is needed in order to fully understand how varying degrees of protein synthesis inhibition may be therapeutically useful for counteracting detriments in proteostasis and protein misfolding.

Figure 4-1. Fold-changes for individual proteins affected in G93A SOD1 mice with and without CHX treatment. (a) Fold-changes presented as a scatter plot with each individual point representing a single protein for either condition [untreated G93A mice (Fold G93A) or CHX treated G93A SOD1 mice (Fold CHX)]. (b) Fold-changes presented as a range of values by group. A fold- change is representative of the degree to which an individual protein’s spectral count increased in transgenic relative to nontransgenic littermate control mice.

145

Figure 4-2. Numbers of aberrantly insoluble proteins for individual mice analyzed by LC- MS/MS with or without CHX treatment relative to control animals. (a) Scatter plot containing all animals analyzed with or without cycloheximide treatment. Each point represents an individual mouse. (b) Scatter plot with the removal of outlier animals that did not appear to exhibit the aberrant insolubility of proteins that occurs in the presence of SOD1 pathology.

146

Figure 4-3. Comparison of aberrantly insoluble proteins from mild and end-stage phenotypic G93A SOD1 mice from separate independent studies. Proteins from mildly phenotypic animals were considered affected if they breached a SAINT score threshold of ≥0.5, whereas end-stage phenotypic animal proteins must have reached a score of ≥0.9. This was to increase the visibility of mildly affected proteins in the former group so that a useful comparison could be made between the two groups.

147

CHAPTER 5 DISCUSSION

Accomplishments made in these studies have served to further the understanding of how the accumulation of misfolded proteins negatively impacts the stability of the proteome, and more broadly, cellular proteostasis. Protein conformation abnormalities are a pathological hallmark of many different types of diseases, including neurodegenerative disorders (Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, spinocerebellar ataxias, Huntington’s disease, prion disease, etc.), Down’s syndrome and type 2 diabetes [32, 185, 239]. With increased incidences of mixed pathologies being observed in many of these disorders, it is now more important than ever to understand how a global disruption in proteostasis might contribute the accumulation of misfolded proteins, especially in the context of a primary misfolded protein (e.g. amyloid-β in Alzheimer’s disease) leading to the misfolding of other proteins (tau, TDP-43, α-synuclein, etc.) [99, 126, 266]. Proteoxic aggregates composed of misfolded proteins are thought to contribute to the etiology of neurodegeneration, but mechanisms by which this occurs is are not yet clear. These studies are well justified, as the further elucidation of how different proteinopathies that define varying diseases impact proteostasis will help define the molecular underpinnings of these disorders and other proteins that may contribute to disease etiology.

The first research objective accomplished as a part of these studies was the direct observance of a primary proteinopathy (tau) leading to the misfolding and aggregation of a secondary protein known to be metastable and vulnerable to misfold: the G85R mutant of superoxide dismutase 1 (SOD1) tagged to yellow fluorescent

148

protein (YFP; abbreviated G85R-SOD1:YFP) [268]. While this type of event had been previously shown in the C. elegans model using temperature-sensitive mutant proteins

[90, 91], we were the first to demonstrate this paradigm in a mammalian model using a fluorescent reporter [195]. This finding is particularly relevant as it further strengthens the likelihood that such an event could occur in the human brain, and may, at least in part, contribute to the mechanism by which visible inclusions of different protein species occur in these diseases. Interestingly, this study also revealed a specificity by tau which is capable of stressing proteostasis, as evidenced by the differential aggregation of

SOD1 by pathological tau versus α-synuclein in the mouse spinal cord under the same promoter systems. Given previous evidence suggesting that pathological tau is not merely seeding the aggregation of G85R-SOD1:YFP [5], these results lend to a conceptual framework in which the proteins that misfold in disease are differentially engaging with proteostasis network components, leading to varying specificities in regards to which proteins are subject to impaired proteostatic maintenance downstream of an initiating proteinopathy. However, due to the incomplete understanding of the varying subchaperome networks that maintain the folding state of proteins affected in neurodegenerative disease, it is difficult to ascertain, without future studies, which factors may primarily be at play here. Nonetheless, these experiments provide rationale for the use of the G85R-SOD1:YFP model as a potential reporter of proteostatic stress and dysfunction.

The second research objective accomplished in these studies was a complex and massive undertaking. Using label-free proteomics coupled to detergent extraction techniques, the SDS-insoluble proteomes of varying mouse models of

149

neurodegenerative disease (exhibiting SOD1, α-synuclein, and tau pathologies) were isolated and characterized relative to nontransgenic control mice [194]. With a previous study from our laboratory identifying a subset proteins that lose solubility in the presence of amyloid plaques [285], we sought to determine whether this subproteome is commonly vulnerable in the presence of other proteinopathies, particularly those that exist inside the cell (as opposed to extracellularly, as is the case for amyloid pathology).

These efforts not only confirmed our previous analyses on mice that model Alzheimer’s amyloidosis, but also revealed the aberrant insolubilities of hundreds of proteins, many of which were commonly affected in the presence of any given proteinopathy [194].

These results further demonstrated that any initiating cascade of misfolded proteins is capable of disrupting proteostasis, as evidenced by perturbed proteome solubility.

Additionally, it suggests that the stabilities of specific subproteomes are vulnerable to different types of initiating proteinopathies, whether this be tau, amyloid-β, SOD1, α- synuclein, or other commonly misfolded proteins in neurodegenerative disease. We compared the protein lists we generated with previously identified detergent-insoluble proteins that have been identified in the presence of pathology relevant to neurodegenerative disease [8, 12, 55, 69, 96, 102, 160, 193, 226, 273, 281, 282]. There was a moderate degree of overlap between the proteins we discovered and those identified in previous studies [194], but we also identified many novel proteins that had never been associated with neurodegenerative pathology. Most of the proteins identified in this study were cytosolic and highly abundant. Interestingly, a thorough investigation on the relationship between protein abundance and propensity to aggregate was conducted that drew from a plethora of previous analyses on human and C. elegans

150

samples [42]. This study reported that, overall, the aggregation propensities of proteins are higher for those that exist at high concentrations relative to their solubilities (also referred to as “supersaturated”). Thus, it is entirely possible that the proteins we discovered as vulnerable to proteostatic insult became insoluble, at least in part, due to their high concentration. The amount of any given protein identified in our proteomic studies that loss solubility was partial; thus, we doubt that any significant loss of function is occurring, even for the most severely affected proteins. However, we may have identified an extensive list of candidate proteins that may act as biomarkers for proteostatis stress. These proteins that accumulate as a result of proteostatic inadequacies in neurodegeneration may serve as an ever-present irritant to cellular health throughout disease progression [194].

The last collection of work performed for these studies tested the idea that the proteins identified in the aforementioned proteomic studies existed in a transient state in regard to their insolubility, with frequent turnover by cellular protein degradation mechanisms (proteasome, autophagy, etc.). In order to test this, we administered cycloheximide (CHX), a potent inhibitor of protein synthesis, to G93A SOD1 mice at a mild phenotypic stage (exhibiting early signs of motor dysfunction). We had previously established that the SOD1 pathology characterized in these animals leads to the abnormal accumulation of approximately 150 proteins in the detergent-insoluble fraction when animals are harvested at an end-stage phenotype (paralysis in one or more limbs)

[194]. Our primary hypothesis for this experiment was that, if the aberrantly insoluble proteins we observed in our proteinopathy models existed transiently with frequent turnover, then by temporarily inhibiting translation (by rates up to 95%) [205] we could

151

potentially reset proteostasis at the cellular level and allow protein quality control mechanisms to restore proteome solubility. While significant differences in the levels of insoluble proteins were not obtained between treated (CHX) and untreated (positive control) conditions, there was a trend towards a positive effect of CHX on the restoring proteome solubility. However, these experiments did reveal limitations in the study design and clear modifications that can be made to strengthen potential results. First,

G93A SOD1 mice burdened by a moderate motor dysfunction phenotype were not as robust of a positive control condition as we had anticipated. This made it difficult to assess the degree to which CHX was effective in restoring proteostasis. Additionally, there was one G93A SOD1 untreated animal in the positive control group and two within the CHX treated group that did not exhibit any degree of aberrant proteome insolubility.

The removal of these mice as potential outliers reduced the power of these experiments, making it more difficult to draw conclusions with any degree of confidence.

Despite the minimal number of mice that was suitable for analysis in this study, these results demonstrate preliminary potential for the transient inhibition of translation to combat proteostatic dysfunction.

The current experiments provide the rationale for future studies in order to further understand the relationship between impaired proteostasis and neurodegenerative diseases. Our first study involving the use of a mutant SOD1 YFP-tagged reporter of proteostasis led to many different questions about this phenomenon, specifically regarding both the cell- and tissue-specific effects on the bystander misfolding of G85R-

SOD1:YFP in the presence of tauopathy. As this effect did not appear to occur due to the cross-seeding of the two proteins [195], and differential induction of aggregation

152

occurred based upon the initiating proteinopathy and anatomical location within the

CNS, we believe that further elucidation of subchamperome networks expressed in both cortical and spinal neurons would be useful. Quantitative proteomics in nontransgenic mice including interactome studies on disease-relevant proteins could provide a further understanding of the relevant chaperones at play that regulate the stability of the pathologic proteins studied in these experiments. Additionally, it would be interesting to conduct timecourse experiments assessing when SOD1 pathology develops relative to tauopathy. The occurrence of SOD1 aggregation prior to, simultaneously with, or after the development of tau pathology could help in understanding the degree to which proteostasis is burdened in relation to the development of proteinaceous inclusions.

The comprehensive assessment that we have put together of proteins that become over-represented in detergent-insoluble fractions by the presence of many different neurodegenerative proteinopathies should be further expanded to more disease-relevant instances, including that of TDP-43 pathology and other protein misfolding diseases such as CMT1B and prion disease. This would further elucidate the deleterious effect on protein folding that persists in these types of disorders.

Additionally, a plethora of limitations exist in the nature of the proteomics experiments that we conducted in order to draw these conclusions on changes in proteome solubility.

First, we repeatedly dealt with the supersaturation of particularly abundant proteins, a problem that primarily presented itself when analyzing PBS-soluble fractions of CNS tissues from these mice. This made it difficult to assess ratios of abundance between proteins that were abberantly present in the SDS-insoluble fraction and their levels in corresponding soluble fractions. Conducting these experiments using stable isotopic

153

labeling of proteins may prove advantageous here, specifically for measuring differences between abundances of proteins in soluble fractions. However, we believe that the spectral counting strategy we implemented was sufficient to asses for dramatic differences in protein abundance between SDS-insoluble samples. Further validation analysis of these experiments could include the use of quantitative dot blotting, a methodogy that is now accepted for determining both absolute and relative protein quantifications in any given sample (assuming quality antibodies could be acquired). It would also be useful to assess for post-translational modifications in the proteins we have identified in this study, specifically for different arrangements of polyubiquitin chains, to provide further evidence that protein homeostasis and possibily even ubiquitin homeostasis is negatively altered in these mice.

Lastly, potential solutions exist to the limitations discovered in our experiments with CHX in G93A SOD1 mice. Further experiments using rTg4510 as opposed to

G93A SOD1 mice would be beneficial in the further elucidation of the benefits of transient protein synthesis inhibition on proteome solubility. The rTg4510 model represents a more reliable and robust positive control option for these experiemnts, as we have previously established that >200 proteins lose solubility predictably at specific ages [194]. These mice also do not exhibit a paralysis phenotype, allowing for the administration of CHX at a timepoint in which we know aberrant protein solubility runs rampant. Additinally, it became clear that increasing the number of animals per group in these studies would be useful, to account for any variability in administration of CHX or for unforeseen instances where positive control (untreated) mice do not develop widespread proteome insolubility. Overall, these experiments would help to better

154

understand the phenomena recorded in this dissertation and push forward our understanding of the relationship between proteostatic elements of the cell and pathologies associated with protein misfolding disorders.

Broadly, the experiments described in this dissertation helped to achieve a better understanding of the interrelationship between proteostasis and the misfolded pathologies that characterize neurodegenerative disease. We clearly demonstrated that one misfolded protein pathology can induce the misfolding and aggregation of another protein that is prone to misfold. This concept was then further exhibited through the discovery of hundreds of proteins that appear to be vulnerable to proteostatic insult.

While brief inhibition of protein translation may be sufficient to remedy the observed losses in proteome solubility, further work is required to confirm this phenomenon.

These experiments provide the rationale for further study of how differing cellular systems that maintain proteostasis may be impaired in the context of neurodegenerative pathologies. It will also be enlightening to further define the types of chaperones expressed in different anatomical regions of the CNS, as well as their client substrates.

This could help to unravel the differential maintenance of proteins associated with disease and explain why certain proteins are vulnerable to misfold under certain conditions. A better understanding of the minutia of how proteostasis is hindered in neurodegeneration will provide insight into the potential clinical applications of harnessing this system.

155

LIST OF REFERENCES

1. Abisambra JF, Jinwal UK, Blair LJ, O’Leary JC, Li Q, Brady S, Wang L, Guidi CE, Zhang B, Nordhues BA, Cockman M, Suntharalingham A, Li P, Jin Y, Atkins CA, Dickey CA (2013) Tau Accumulation Activates the Unfolded Protein Response by Impairing Endoplasmic Reticulum-Associated Degradation. J Neurosci 33:9498– 9507. doi: 10.1523/JNEUROSCI.5397-12.2013

2. Arai T, Hasegawa M, Akiyama H, Ikeda K, Nonaka T, Mori H, Mann D, Tsuchiya K, Yoshida M, Hashizume Y, Oda T (2006) TDP-43 is a component of ubiquitin- positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun 351:602–611. doi: 10.1016/j.bbrc.2006.10.093

3. Auluck PK, Bonini NM (2002) Pharmacological prevention of Parkinson disease in Drosophila. Nat Med 8:1185–1186. doi: 10.1038/nm1102-1185

4. Auluck PK, Edwin Chan HY, Trojanowski JQ, Lee VM-Y, Bonini NM (2002) Chaperone Suppression of α-Synuclein Toxicity in a Drosophila Model for Parkinson’s Disease. Science (80- ) 295:865–868. doi: 10.1126/science.1067389

5. Ayers JI, Diamond J, Sari A, Fromholt S, Galaleldeen A, Ostrow LW, Glass JD, Hart PJ, Borchelt DR (2016) Distinct conformers of transmissible misfolded SOD1 distinguish human SOD1-FALS from other forms of familial and sporadic ALS. Acta Neuropathol 132:827–840. doi: 10.1007/s00401-016-1623-4

6. Ayers JI, Fromholt S, Koch M, DeBosier A, McMahon B, Xu G, Borchelt DR (2014) Experimental transmissibility of mutant SOD1 motor neuron disease. Acta Neuropathol 128:791–803. doi: 10.1007/s00401-014-1342-7

7. Ayers JI, Fromholt SE, O’Neal VM, Diamond JH, Borchelt DR (2016) Prion-like propagation of mutant SOD1 misfolding and motor neuron disease spread along neuroanatomical pathways. Acta Neuropathol 131:103–114. doi: 10.1007/s00401- 015-1514-0

8. Ayyadevara S, Balasubramaniam M, Parcon PA, Barger SW, Griffin WST, Alla R, Tackett AJ, Mackintosh SG, Petricoin E, Zhou W, Shmookler Reis RJ (2016) Proteins that mediate protein aggregation and cytotoxicity distinguish Alzheimer’s hippocampus from normal controls. Aging Cell 15:924–939. doi: 10.1111/acel.12501

9. Baba M, Nakajo S, Tu PH, Tomita T, Nakaya K, Lee VM, Trojanowski JQ, Iwatsubo T (1998) Aggregation of alpha-synuclein in Lewy bodies of sporadic Parkinson’s disease and dementia with Lewy bodies. Am J Pathol 152:879–84. doi: 10.1086/281267

156

10. Babu JR, Geetha T, Wooten MW (2005) Sequestosome 1/p62 shuttles polyubiquitinated tau for proteasomal degradation. J Neurochem 94:192–203. doi: 10.1111/j.1471-4159.2005.03181.x

11. Backstrom JR, Lim GP, Cullen MJ, Tokes ZA, Tökés Z a (1996) Matrix metalloproteinase-9 (MMP-9) is synthesized in neurons of the human hippocampus and is capable of degrading the amyloid-beta peptide (1-40). J Neurosci 16:7910–9. doi: 10.1371/journal.pone.0031039

12. Bai B, Hales CM, Chen P, Gozal Y, Dammer EB, Fritz JJ (2013) U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease. Proc Natl Acad Sci U S A 110:16562–16567. doi: 10.1073/pnas.1310249110/- /DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1310249110

13. Bailey RM, Covy JP, Melrose HL, Rousseau L, Watkinson R, Knight J, Miles S, Farrer MJ, Dickson DW, Giasson BI, Lewis J (2013) LRRK2 phosphorylates novel tau epitopes and promotes tauopathy. Acta Neuropathol 126:809–827. doi: 10.1007/s00401-013-1188-4

14. Balch WE, Morimoto RI, Dillin A, Kelly, Jeffery W (2008) Adapting Proteostasis for Disease Intervention. Science (80- ) 319:916–919. doi: 10.1126/science.1141448

15. Balchin D, Hayer-Hartl M, Hartl FU (2016) In vivo aspects of protein folding and quality control. Science (80- ) 353:aac4354. doi: 10.1126/science.aac4354

16. Barondes SH, Cohen HD (1967) Comparative effects of cycloheximide and puromycin on cerebral protein synthesis and consolidation of memory in mice

17. Basso M, Massignan T, Samengo G, Cheroni C, De Biasi S, Salmona M, Bendotti C, Bonetto V (2006) Insoluble mutant SOD1 is partly oligoubiquitinated in amyotrophic lateral sclerosis mice. J Biol Chem 281:33325–33335. doi: 10.1074/jbc.M603489200

18. Basso M, Samengo G, Nardo G, Massignan T, D’Alessandro G, Tartari S, Cantoni L, Marino M, Cheroni C, de Biasi S, Giordana MT, Strong MJ, Estevez AG, Salmona M, Bendotti C, Bonetto V (2009) Characterization of detergent- insoluble proteins in ALS indicates a causal link between nitrative stress and aggregation in pathogenesis. PLoS One 4. doi: 10.1371/journal.pone.0008130

19. Batulan Z, Shinder G a, Minotti S, He BP, Doroudchi MM, Nalbantoglu J, Strong MJ, Durham HD (2003) High threshold for induction of the stress response in motor neurons is associated with failure to activate HSF1. J Neurosci 23:5789– 5798. doi: 23/13/5789 [pii]

20. Bence NF, Sampat RM, Kopito RR (2001) Impairment of the Ubiquitin- Proteasome System by Protein Aggregation. Science (80- ) 292:1552–1555. doi: 10.1126/science.292.5521.1552

157

21. Berger Z, Ravikumar B, Menzies FM, Oroz LG, Underwood BR, Pangalos MN, Schmitt I, Wullner U, Evert BO, O’Kane CJ, Rubinsztein DC (2006) Rapamycin alleviates toxicity of different aggregate-prone proteins. Hum Mol Genet 15:433– 442. doi: 10.1093/hmg/ddi458

22. Blommaart EFC, Luiken JJFP, Blommaart PJE, Van Woerkom GM, Meijer AJ (1995) Phosphorylation of ribosomal protein S6 is inhibitory for autophagy in isolated rat hepatocytes. J Biol Chem 270:2320–2326. doi: 10.1074/jbc.270.5.2320

23. Borodovsky A, Kessler BM, Casagrande R, Overkleeft HS, Wilkinson KD, Ploegh HL (2001) A novel active site-directed probe specific for deubiquitylating enzymes reveals proteasome association of USP14. EMBO J 20:5187–5196. doi: 10.1093/emboj/20.18.5187

24. Bosco DA, LaVoie MJ, Petsko GA, Ringe D (2011) Proteostasis and Movement Disorders: Parkinson’s Disease and Amyotrophic Lateral Sclerosis. Cold Spring Harb Perspect Biol 3:1–24. doi: 10.1101/cshperspect.a007500

25. Bossy-Wetzel E, Schwarzenbacher R, Lipton S a (2004) Molecular pathways to neurodegeneration. Nat Med 10 Suppl:S2–S9. doi: 10.1038/nm1067

26. Broadley SA, Hartl FU (2009) The role of molecular chaperones in human misfolding diseases. FEBS Lett. 583:2647–2653

27. Bruijn LI, Becher MW, Lee MK, Anderson KL, Jenkins NA, Copeland NG, Sisodia SS, Rothstein JD, Borchelt DR, Price DL, Cleveland DW (1997) ALS-linked SOD1 mutant G85R mediates damage to astrocytes and promotes rapidly progressive disease with SOD1-containing inclusions. Neuron 18:327–338. doi: 10.1016/S0896-6273(00)80272-X

28. Bruijn LI, Houseweart MK, Kato S, Anderson KL, Anderson SD, Ohama E, Reaume AG, Scott RW, Cleveland DW (1998) Aggregation and motor neuron toxicity of an ALS-linked SOD1 mutant independent from wild-type SOD1. Science (80- ) 281:1851–1854. doi: 10.1126/science.281.5384.1851

29. Bruinsma IB, Bruggink KA, Kinast K, Versleijen AAM, Segers-Nolten IMJ, Subramaniam V, Bea Kuiperij H, Boelens W, de Waal RMW, Verbeek MM (2011) Inhibition of α-synuclein aggregation by small heat shock proteins. Proteins Struct Funct Bioinforma 79:2956–2967. doi: 10.1002/prot.23152

30. Bukau B, Weissman J, Horwich A (2006) Molecular Chaperones and Protein Quality Control. Cell 125:443–451

31. Caballero B, Wang Y, Diaz A, Tasset I, Juste YR, Mandelkow E-M, Mandelkow E, Cuervo AM (2017) Interplay of pathogenic forms of human tau with different autophagic pathways. Aging Cell 1–17. doi: 10.1111/acel.12692

158

32. Carrell RW, Lomas DA (1997) Conformational disease. Lancet 350:134–138. doi: 10.1016/S0140-6736(97)02073-4

33. Chan J, Khan SN, Harvey I, Merrick W, Pelletier J (2004) Eukaryotic protein synthesis inhibitors identified by comparison of cytotoxicity profiles. RNA 10:528– 543. doi: 10.1261/rna.5200204

34. Chau V, Tobias JW, Bachmair A, Marriott D, Ecker DJ, Gonda DK, Varshavsky A (1989) A multiubiquitin chain is confined to specific lysine in a targeted short-lived protein. Science (80- ) 243:1576–83. doi: 10.1126/science.2538923

35. Chen L, Thiruchelvam MJ, Madura K, Richfield EK (2006) Proteasome dysfunction in aged human α-synuclein transgenic mice. Neurobiol Dis 23:120– 126. doi: 10.1016/j.nbd.2006.02.004

36. Cheroni C, Marino M, Tortarolo M, Veglianese P, De Biasi S, Fontana E, Zuccarello LV, Maynard CJ, Dantuma NP, Bendotti C (2009) Functional alterations of the ubiquitin-proteasome system in motor neurons of a mouse model of familial amyotrophic lateral sclerosis. Hum Mol Genet 18:82–96. doi: 10.1093/hmg/ddn319

37. Cheroni C, Peviani M, Cascio P, DeBiasi S, Monti C, Bendotti C (2005) Accumulation of human SOD1 and ubiquitinated deposits in the spinal cord of SOD1G93A mice during motor neuron disease progression correlates with a decrease of proteasome. Neurobiol Dis 18:509–522. doi: 10.1016/j.nbd.2004.12.007

38. Chiti F, Dobson CM (2006) Protein Misfolding, Functional Amyloid, and Human Disease. Annu Rev Biochem 75:333–66. doi: 10.1146/

39. Chiti F, Stefani M, Taddei N, Ramponi G, Dobson CM (2003) Rationalization of the effects of mutations on peptide and protein aggregation rates. Nature 424:805–8. doi: 10.1038/nature01891

40. Choi H, Larsen B, Lin Z-Y, Breitkreutz A, Mellacheruvu D, Fermin D, Qin ZS, Tyers M, Gingras A-C, Nesvizhskii AI (2011) SAINT: probabilistic scoring of affinity purification-mass spectrometry data. Nat Methods 8:70–3. doi: 10.1038/nmeth.1541

41. Ciechanover A (1994) The ubiquitin-proteasome proteolytic pathway. Cell 79:13– 21

42. Ciryam P, Tartaglia G, Morimoto RI, Dobson CM, Vendruscolo M (2013) Widespread Aggregation and Neurodegenerative Diseases Are Associated with Supersaturated Proteins. Cell Rep 5:781–790. doi: 10.1016/j.celrep.2013.09.043

159

43. Clippinger AK, D’Alton S, Lin WL, Gendron TF, Howard J, Borchelt DR, Cannon A, Carlomagno Y, Chakrabarty P, Cook C, Golde TE, Levites Y, Ranum L, Schultheis PJ, Xu G, Petrucelli L, Sahara N, Dickson DW, Giasson B, Lewis J (2013) Robust cytoplasmic accumulation of phosphorylated TDP-43 in transgenic models of tauopathy. Acta Neuropathol 126:39–50. doi: 10.1007/s00401-013- 1123-8

44. Collins GA, Goldberg AL (2017) The Logic of the 26S Proteasome. Cell 169:792– 806

45. Colom-Cadena M, Gelpi E, Charif S, Belbin O, Blesa R, Marti MJ, Clarimon J, Lleo A (2013) Confluence of alpha-synuclein, tau, and beta-amyloid pathologies in dementia with Lewy bodies. J Neuropathol Exp Neurol 72:1203–1212. doi: 10.1097/NEN.0000000000000018

46. Coux O, Tanaka K, Goldberg AL (1996) Structure and Functions of the 20S and 26S Proteasomes. Annu Rev Biochem 65:801–847. doi: 10.1146/annurev.bi.65.070196.004101

47. Cox D, Whiten DR, Brown JWP, Horrocks MH, Gil RS, Dobson CM, Klenerman D, Van Oijen AM, Ecroyd H (2018) The small heat shock protein Hsp27 binds α- synuclein fibrils, preventing elongation and cytotoxicity. J Biol Chem 293:4486– 4497. doi: 10.1074/jbc.M117.813865

48. Crippa V, Sau D, Rusmini P, Boncoraglio A, Onesto E, Bolzoni E, Galbiati M, Fontana E, Marino M, Carra S, Bendotti C, de Biasi S, Poletti A (2010) The small heat shock protein B8 (HspB8) promotes autophagic removal of misfolded proteins involved in amyotrophic lateral sclerosis (ALS). Hum Mol Genet 19:3440– 3456. doi: 10.1093/hmg/ddq257

49. Crystal AS, Giasson BI, Crowe A, Kung MP, Zhuang ZP, Trojanowski JQ, Lee VMY (2003) A comparison of amyloid fibrillogenesis using the novel fluorescent compound K114. J Neurochem 86:1359–1368. doi: 10.1046/j.1471- 4159.2003.01949.x

50. Cuanalo-Contreras K, Mukherjee A, Soto C (2013) Role of protein misfolding and proteostasis deficiency in protein misfolding diseases and aging. Int J Cell Biol 2013. doi: 10.1155/2013/638083

51. Cuervo AM, Stefanis L, Fredenburg R, Lansbury PT, Sulzer D (2004) Impaired Degradation of Mutant -Synuclein by Chaperone-Mediated Autophagy. Science (80- ) 305:1292–1295. doi: 10.1126/science.1101738

52. Dantuma NP, Bott LC (2014) The ubiquitin-proteasome system in neurodegenerative diseases: precipitating factor, yet part of the solution. Front Mol Neurosci 7:70. doi: 10.3389/fnmol.2014.00070

160

53. Das I, Krzyzosiak A, Schneider K, Wrabetz L, D’Antonio M, Barry N, Sigurdardottir A, Bertolotti A (2015) Preventing proteostasis diseases by selective inhibition of a phosphatase regulatory subunit. Science (80- ) 348:239–242. doi: 10.1126/science.aaa4484

54. Daturpalli S, Waudby CA, Meehan S, Jackson SE (2013) Hsp90 inhibits α- synuclein aggregation by interacting with soluble oligomers. J Mol Biol 425:4614– 4628. doi: 10.1016/j.jmb.2013.08.006

55. David DC, Hauptmann S, Scherping I, Schuessel K, Keil U, Rizzu P, Ravid R, Dröse S, Brandt U, Müller WE, Eckert A, Götz J (2005) Proteomic and functional analyses reveal a mitochondrial dysfunction in P301L tau transgenic mice. J Biol Chem 280:23802–23814. doi: 10.1074/jbc.M500356200

56. David DC, Layfield R, Serpell L, Narain Y, Goedert M, Spillantini MG (2002) Proteasomal degradation of tau protein. J Neurochem 83:176–185. doi: 10.1046/j.1471-4159.2002.01137.x

57. Deger JM, Gerson JE, Kayed R (2015) The interrelationship of proteasome impairment and oligomeric intermediates in neurodegeneration. Aging Cell 14:715–724. doi: 10.1111/acel.12359

58. Deng HX, Chen W, Hong ST, Boycott KM, Gorrie GH, Siddique N, Yang Y, Fecto F, Shi Y, Zhai H, Jiang H, Hirano M, Rampersaud E, Jansen GH, Donkervoort S, Bigio EH, Brooks BR, Ajroud K, Sufit RL, Haines JL, Mugnaini E, Pericak-Vance MA, Siddique T (2011) Mutations in UBQLN2 cause dominant X-linked juvenile and adult-onset ALS and ALS/dementia. Nature 477:211–215. doi: 10.1038/nature10353

59. Dhillon JKS, Riffe C, Moore BD, Ran Y, Chakrabarty P, Golde TE, Giasson BI (2017) A novel panel of α-synuclein antibodies reveal distinctive staining profiles in synucleinopathies. PLoS One 12. doi: 10.1371/journal.pone.0184731

60. Dickey CA, Kamal A, Lundgren K, Klosak N, Bailey RM, Dunmore J, Ash P, Shoraka S, Zlatkovic J, Eckman CB, Patterson C, Dickson DW, Nahman NS, Hutton M, Burrows F, Petrucelli L (2007) The high-affinity HSP90-CHIP complex recognizes and selectively degrades phosphorylated tau client proteins. J Clin Invest 117:648–658. doi: 10.1172/JCI29715

61. Dickey CA, Koren J, Zhang Y-J, Xu Y-F, Jinwal UK, Birnbaum MJ, Monks B, Sun M, Cheng JQ, Patterson C, Bailey RM, Dunmore J, Soresh S, Leon C, Morgan D, Petrucelli L (2008) Akt and CHIP coregulate tau degradation through coordinated interactions. Proc Natl Acad Sci U S A 105:3622–7. doi: 10.1073/pnas.0709180105

161

62. Dickey CA, Yue M, Lin W-L, Dickson DW, Dunmore JH, Lee WC, Zehr C, West G, Cao S, Clark AMK, Caldwell GA, Caldwell KA, Eckman C, Patterson C, Hutton M, Petrucelli L (2006) Deletion of the Ubiquitin Ligase CHIP Leads to the Accumulation, But Not the Aggregation, of Both Endogenous Phospho- and Caspase-3-Cleaved Tau Species. J Neurosci 26:6985–6996. doi: 10.1523/JNEUROSCI.0746-06.2006

63. Dickson DW, Bergeron C, Chin SS, Duyckaerts C, Horoupian D, Ikeda K, Jellinger K, Lantos PL, Lippa CF, Mirra SS, Tabaton M, Vonsattel JP, Wakabayashi K, Litvan I (2002) Office of rare diseases neuropathologic criteria for corticobasal degeneration. J Neuropathol Exp Neurol 61:935–946. doi: 10.1093/jnen/61.11.935

64. Dobson CM (1999) Protein misfolding, evolution and disease. Trends Biochem Sci 24:329–332. doi: 10.1016/S0968-0004(99)01445-0

65. Dobson CM, Sali A, Karplus M (1998) Protein folding: A perspective from theory and experiment. Angew Chemie - Int Ed 37:868–893. doi: 10.1002/(SICI)1521- 3773(19980420)37:7<868::AID-ANIE868>3.0.CO;2-H

66. Dou F, Netzer WJ, Tanemura K, Li F, Hartl FU, Takashima A, Gouras GK, Greengard P, Xu H (2003) Chaperones increase association of tau protein with microtubules. Proc Natl Acad Sci U S A 100:721–6. doi: 10.1073/pnas.242720499

67. Douglas PM, Dillin A (2010) Protein homeostasis and aging in neurodegeneration. J Cell Biol 190:719–729. doi: 10.1083/jcb.201005144

68. Drews, Wildgruber, Zong, Sukop, Nissum, Weber, Gomes, Ping (2007) Mammalian Proteasome Subpopulations with Distinct Molecular Compositions and Proteolytic Activities. Mol Cell Proteomics 6:2021–2031. doi: 10.1074/mcp.M700187-MCP200

69. Drummond E, Nayak S, Faustin A, Pires G, Hickman RA, Askenazi M, Cohen M, Haldiman T, Kim C, Han X, Shao Y, Safar JG, Ueberheide B, Wisniewski T (2017) Proteomic differences in amyloid plaques in rapidly progressive and sporadic Alzheimer’s disease. Acta Neuropathol 133:933–954. doi: 10.1007/s00401-017- 1691-0

70. Duda JE, Giasson BI, Gur TL, Montine TJ, Robertson D, Biaggioni I, Hurtig HI, Stern MB, Gollomp SM, Grossman M, Lee VMY, Trojanowski JQ (2000) Immunohistochemical and biochemical studies demonstrate a distinct profile of α- Synuclein permutations in multiple system atrophy. J Neuropathol Exp Neurol 59:830–841. doi: 10.1093/jnen/59.9.830

71. Dyllick-Brenzinger M, D’Souza CA, Dahlmann B, Kloetzel P-M, Tandon A (2010) Reciprocal Effects of α-Synuclein Overexpression and Proteasome Inhibition in Neuronal Cells and Tissue. Neurotox Res 17:215–227. doi: 10.1007/s12640-009- 9094-1

162

72. Ebrahimi-Fakhari D, Saidi L-J, Wahlster L (2013) Molecular chaperones and protein folding as therapeutic targets in Parkinson’s disease and other synucleinopathies. Acta Neuropathol Commun 1:79. doi: 10.1186/2051-5960-1-79

73. Elliott E, Tsvetkov P, Ginzburg I (2007) BAG-1 associates with Hsc70Tau complex and regulates the proteasomal degradation of Tau protein. J Biol Chem 282:37276–37284. doi: 10.1074/jbc.M706379200

74. Ellis RJ, Minton AP (2006) Protein aggregation in crowded environments. Biol. Chem. 387:485

75. Emmanouilidou E, Stefanis L, Vekrellis K (2010) Cell-produced α-synuclein oligomers are targeted to, and impair, the 26S proteasome. Neurobiol Aging 31:953–968. doi: 10.1016/j.neurobiolaging.2008.07.008

76. Falsone SF, Kungl AJ, Rek A, Cappai R, Zangger K (2009) The molecular chaperone Hsp90 modulates intermediate steps of amyloid assembly of the Parkinson-related protein α-synuclein. J Biol Chem 284:31190–31199. doi: 10.1074/jbc.M109.057240

77. Farris W, Mansourian S, Chang Y, Lindsley L, Eckman EA, Frosch MP, Eckman CB, Tanzi RE, Selkoe DJ, Guenette S (2003) Insulin-degrading enzyme regulates the levels of insulin, amyloid beta-protein, and the beta-amyloid precursor protein intracellular domain in vivo. Proc Natl Acad Sci U S A 100:4162–7. doi: 10.1073/pnas.0230450100

78. Finley D, Özkaynak E, Varshavsky A (1987) The yeast polyubiquitin gene is essential for resistance to high temperatures, starvation, and other stresses. Cell 48:1035–1046. doi: 10.1016/0092-8674(87)90711-2

79. Fischer M, Hilt W, Richter-Ruoff B, Gonen H, Ciechanover A, Wolf DH (1994) The 26S proteasome of the yeast Saccharomyces cerevisiae. FEBS Lett 355:69–75. doi: 0014-5793(94)01177-X [pii]

80. Flach K, Ramminger E, Hilbrich I, Arsalan-Werner A, Albrecht F, Herrmann L, Goedert M, Arendt T, Holzer M (2014) Axotrophin/MARCH7 acts as an E3 ubiquitin ligase and ubiquitinates tau protein in vitro impairing microtubule binding. Biochim Biophys Acta - Mol Basis Dis 1842:1527–1538. doi: 10.1016/j.bbadis.2014.05.029

81. Frost B, Jacks RL, Diamond MI (2009) Propagation of Tau misfolding from the outside to the inside of a cell. J Biol Chem 284:12845–12852. doi: 10.1074/jbc.M808759200

82. Frydman J, Nimmesgern E, Ohtsuka K, Hartl FU (1994) Folding of nascent polypeptide chains in a high molecular mass assembly with molecular chaperones. Nature 370:111–117. doi: 10.1038/370111a0

163

83. Fujikake N, Nagai Y, Popiel HA, Okamoto Y, Yamaguchi M, Toda T (2008) Heat shock transcription factor 1-activating compounds suppress polyglutamine- induced neurodegeneration through induction of multiple molecular chaperones. J Biol Chem 283:26188–26197. doi: 10.1074/jbc.M710521200

84. Galvin JE, Giasson B, Hurtig HI, Lee VMY, Trojanowski JQ (2000) Neurodegeneration with brain iron accumulation, type 1 is characterized by α-, β-, and γ-synuclein neuropathology. Am J Pathol 157:361–368. doi: 10.1016/S0002- 9440(10)64548-8

85. Garcia-Alloza M, Robbins EM, Zhang-Nunes SX, Purcell SM, Betensky RA, Raju S, Prada C, Greenberg SM, Bacskai BJ, Frosch MP (2006) Characterization of amyloid deposition in the APPswe/PS1dE9 mouse model of Alzheimer disease. Neurobiol Dis 24:516–524. doi: 10.1016/j.nbd.2006.08.017

86. Geller A, Robustelli F, Barondes SH, Cohen HD, Jarvik ME (1969) Impaired performance by post-trial injections of cycloheximide in a passive avoidance task. Psychopharmacologia 14:371–376. doi: 10.1007/BF00403577

87. Giasson BI, Duda JE, Quinn SM, Zhang B, Trojanowski JQ, Lee VMY (2002) Neuronal α-synucleinopathy with severe movement disorder in mice expressing A53T human α-synuclein. Neuron 34:521–533. doi: 10.1016/S0896- 6273(02)00682-7

88. 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 (80- ) 300:636–640. doi: 10.1126/science.1082324

89. Giasson BI, Uryu K, Trojanowski JQ, Lee VMY (1999) Mutant and wild type human α-synucleins assemble into elongated filaments with distinct morphologies in vitro. J Biol Chem 274:7619–7622. doi: 10.1074/jbc.274.12.7619

90. Gidalevitz T, Ben-Zvi A, Ho KH, Brignull HR, Morimoto RI (2006) Progressive disruption of cellular protein folding in models of polyglutamine diseases. Science (80- ) 311:1471–1474. doi: 10.1126/science.1124514

91. Gidalevitz T, Krupinski T, Garcia S, Morimoto RI (2009) Destabilizing protein polymorphisms in the genetic background direct phenotypic expression of mutant SOD1 toxicity. PLoS Genet 5. doi: 10.1371/journal.pgen.1000399

92. Glickman MH, Raveh D (2005) Proteasome plasticity. FEBS Lett 579:3214–3223. doi: 10.1016/j.febslet.2005.04.048

93. Goedert M (1996) Tau protein and the neurofibrillary pathology of Alzheimer’s disease. Ann N Y Acad Sci 777:121–31. doi: 10.1111/j.1749-6632.1996.tb34410.x

164

94. Goedert M, Jakes R, Spillantini MG, Hasegawa M, Smith MJ, Crowther RA (1996) Assembly of microtubule-associated protein tau into Alzheimer-like filaments induced by sulphated glycosaminoglycans. Nature 383:550–553. doi: 10.1038/383550a0

95. Golde TE, Borchelt DR, Giasson BI, Lewis J (2013) Thinking laterally about neurodegenerative proteinopathies. J Clin Invest 123:1847–1855. doi: 10.1172/JCI66029

96. Gozal YM, Duong DM, Gearing M, Cheng D, Hanfelt JJ, Funderburk C, Peng J, Lah JJ, Levey AI (2009) Proteomics Analysis Reveals Novel Components in the Detergent-Insoluble Subproteome in Alzheimer ’ s Disease research articles. J Proteome Res 8:5069–5079

97. Groll M, Ditzel L, Löwe J, Stock D, Bochtler M, Bartunik HD, Huber R (1997) Structure of 20S proteasome from yeast at 2.4 Å resolution. Nature 386:463–471. doi: 10.1038/386463a0

98. Grundke-Iqbal I, Iqbal K, Tung Y-C, Quinlan M, Wisniewski H, Binder L (1987) Abnormal phosphorylation of the microtubule-associated protein t (tau) in Alzheimer cytoskeletal pathology. Alzheimer Dis Assoc Disord 1:202. doi: 10.1097/00002093-198701030-00020

99. Guerrero-Muñoz MJ, Castillo-Carranza DL, Krishnamurthy S, Paulucci- Holthauzen AA, Sengupta U, Lasagna-Reeves CA, Ahmad Y, Jackson GR, Kayed R (2014) Amyloid-β oligomers as a template for secondary amyloidosis in Alzheimer’s disease. Neurobiol Dis 71:14–23. doi: 10.1016/j.nbd.2014.08.008

100. Guo JL, Lee VMY (2011) Seeding of normal tau by pathological tau conformers drives pathogenesis of Alzheimer-like tangles. J Biol Chem 286:15317–15331. doi: 10.1074/jbc.M110.209296

101. Gurney ME, Pu H, Chiu AY, Dal Canto MC, Polchow CY, Alexander DD, Caliendo J, Hentati A, Kwon YW, Deng H-X, Chen W, Zhai P, Sufit RL, Siddique T (1994) Motor neuron degeneration in mice that express a human Cu,Zn superoxide dismutase mutation. Science (80- ) 264:1772–1775. doi: 10.1126/science.8209258

102. Hales CM, Dammer EB, Deng Q, Duong DM, Gearing M, Troncoso JC, Thambisetty M, Lah JJ, Shulman JM, Levey AI, Seyfried NT (2016) Changes in the detergent-insoluble brain proteome linked to amyloid and tau in Alzheimer’s Disease progression. Proteomics 1–27. doi: 10.1002/pmic.201600057

103. Halliday M, Radford H, Sekine Y, Moreno J, Verity N, Le Quesne J, Ortori CA, Barrett DA, Fromont C, Fischer PM, Harding HP, Ron D, Mallucci GR (2015) Partial restoration of protein synthesis rates by the small molecule ISRIB prevents neurodegeneration without pancreatic toxicity. Cell Death Dis 6:e1672-9. doi: 10.1038/cddis.2015.49

165

104. Halliday M, Radford H, Zents KAM, Molloy C, Moreno JA, Verity NC, Smith E, Ortori CA, Barrett DA, Bushell M, Mallucci GR (2017) Repurposed drugs targeting eIF2α-P-mediated translational repression prevent neurodegeneration in mice. Brain 1–16. doi: 10.1093/brain/awx074

105. Hamano T, Gendron TF, Causevic E, Yen SH, Lin WL, Isidoro C, Deture M, Ko LW (2008) Autophagic-lysosomal perturbation enhances tau aggregation in transfectants with induced wild-type tau expression. Eur J Neurosci 27:1119– 1130. doi: 10.1111/j.1460-9568.2008.06084.x

106. Han DH, Na H-K, Choi WH, Lee JH, Kim YK, Won C, Lee S-H, Kim KP, Kuret J, Min D-H, Lee MJ (2014) Direct cellular delivery of human proteasomes to delay tau aggregation. Nat Commun 5:5633. doi: 10.1038/ncomms6633

107. Harding HP, Zhang Y, Bertolotti A, Zeng H, Ron D (2000) Perk is essential for translational regulation and cell survival during the unfolded protein response. Mol Cell 5:897–904. doi: 10.1016/S1097-2765(00)80330-5

108. Hartl FU, Hayer-Hartl M (2002) Molecular Chaperones in the Cytosol: from Nascent Chain to Folded Protein. Science (80- ) 295:1852–1858. doi: 10.1126/science.1068408

109. Hartl UU, Bracher A, Hayer-Hartl M (2011) Molecular chaperones in protein folding and proteostasis. Nature 475:324–332. doi: 10.1016/S0959- 440X(96)80093-5

110. Hasegawa M, Crowther RA, Jakes R, Goedert M (1997) Alzheimer-like changes in microtubule-associated protein tau induced by sulfated glycosaminoglycans. Inhibition of microtubule binding stimulation of phosphorylation filament assembly depend on the degree of sulfation. J Biol Chem 272:33118–33124. doi: 10.1074/jbc.272.52.33118

111. Hauw JJ, Daniel SE, Dickson D, Horoupian DS, Jellinger K, Lantos PL, McKee A, Tabaton M, Litvan I (1994) Preliminary NINDS neuropathologic criteria for Steele- Richardson-Olszewski syndrome (progressive supranuclear palsy). Neurology 44:2015–9

112. Hayashida N, Fujimoto M, Tan K, Prakasam R, Shinkawa T, Li L, Ichikawa H, Takii R, Nakai A (2010) Heat shock factor 1 ameliorates proteotoxicity in cooperation with the transcription factor NFAT. EMBO J 29:3459–3469. doi: 10.1038/emboj.2010.225

113. Heinemeyer W, Fischer M, Krimmer T, Stachon U, Wolf DH (1997) The active sites of the eukaryotic 20 S proteasome and their involvement in subunit precursor processing. J Biol Chem 272:25200–25209. doi: 10.1074/jbc.272.40.25200

166

114. Helferich AM, Ruf WP, Grozdanov V, Freischmidt A, Feiler MS, Zondler L, Ludolph AC, McLean PJ, Weishaupt JH, Danzer KM (2015) α-synuclein interacts with SOD1 and promotes its oligomerization. Mol Neurodegener 10:66. doi: 10.1186/s13024-015-0062-3

115. Hemming ML, Selkoe DJ (2005) Amyloid β-protein is degraded by cellular angiotensin-converting enzyme (ACE) and elevated by an ACE inhibitor. J Biol Chem 280:37644–37650. doi: 10.1074/jbc.M508460200

116. Hershko A, Ciechanover A (1998) The ubiquitin system. Annu Rev Biochem 67:425–79

117. Higashi S, Iseki E, Yamamoto R, Minegishi M, Hino H, Fujisawa K, Togo T, Katsuse O, Uchikado H, Furukawa Y, Kosaka K, Arai H (2007) Concurrence of TDP-43, tau and alpha-synuclein pathology in brains of Alzheimer’s disease and dementia with Lewy bodies. Brain Res 1184:284–94. doi: 10.1016/j.brainres.2007.09.048

118. Higgs RE, Knierman MD, Freeman AB, Gelbert LM, Patil ST, Hale JE (2007) Estimating the statistical significance of peptide identifications from shotgun proteomics experiments. J Proteome Res 6:1758–1767. doi: 10.1021/pr0605320

119. Hipp MS, Park SH, Hartl UU (2014) Proteostasis impairment in protein-misfolding and -aggregation diseases. Trends Cell Biol 24:506–514. doi: 10.1016/j.tcb.2014.05.003

120. Hoover BR, Reed MN, Su J, Penrod RD, Kotilinek LA, Grant MK, Pitstick R, Carlson GA, Lanier LM, Yuan LL, Ashe KH, Liao D (2010) Tau Mislocalization to Dendritic Spines Mediates Synaptic Dysfunction Independently of Neurodegeneration. Neuron 68:1067–1081. doi: 10.1016/j.neuron.2010.11.030

121. Huang C, Cheng H, Hao S, Zhou H, Zhang X, Gao J, Sun QH, Hu H, Wang C chen (2006) Heat Shock Protein 70 Inhibits α-Synuclein Fibril Formation via Interactions with Diverse Intermediates. J Mol Biol 364:323–336. doi: 10.1016/j.jmb.2006.08.062

122. Hughes D, Mallucci GR (2018) The unfolded protein response in neurodegenerative disorders - therapeutic modulation of the PERK pathway. FEBS J 1–14. doi: 10.1111/febs.14422

123. Humbard MA, Maupin-Furlow JA (2013) Prokaryotic proteasomes: Nanocompartments of degradation. J Mol Microbiol Biotechnol 23:321–334. doi: 10.1159/000351348

167

124. Israelson A, Ditsworth D, Sun S, Song SW, Liang J, Hruska-Plochan M, McAlonis- Downes M, Abu-Hamad S, Zoltsman G, Shani T, Maldonado M, Bui A, Navarro M, Zhou H, Marsala M, Kaspar BK, DaCruz S, Cleveland DW (2015) Macrophage migration inhibitory factor as a chaperone inhibiting accumulation of misfolded SOD1. Neuron 86:218–232. doi: 10.1016/j.neuron.2015.02.034

125. Iwata N, Tsubuki S, Takaki Y, Watanabe K, Sekiguchi M, Hosoki E, Kawashima- Morishima M, Lee HJ, Hama E, Sekine-Aizawa Y, Saido TC (2000) Identification of the major Aβ1-42-degrading catabolic pathway in brain parenchyma: Suppression leads to biochemical and pathological deposition. Nat Med 6:143– 150. doi: 10.1038/72237

126. James BD, Wilson RS, Boyle PA, Trojanowski JQ, Bennett DA, Schneider JA (2016) TDP-43 stage, mixed pathologies, and clinical Alzheimer’s-type dementia. BRAIN 139:2983–2993. doi: 10.1093/brain/aww224

127. Jankowsky JL, Fadale DJ, Anderson J, Xu GM, Gonzales V, Jenkins NA, Copeland NG, Lee MK, Younkin LH, Wagner SL, Younkin SG, Borchelt DR (2004) Mutant presenilins specifically elevate the levels of the 42 residue beta- amyloid peptide in vivo: evidence for augmentation of a 42-specific gamma secretase. Hum Mol Genet 13:159–70. doi: 10.1093/hmg/ddh019

128. Jiang HQ, Ren M, Jiang HZ, Wang J, Zhang J, Yin X, Wang SY, Qi Y, Wang XD, Feng HL (2014) Guanabenz delays the onset of disease symptoms, extends lifespan, improves motor performance and attenuates motor neuron loss in the SOD1 G93A mouse model of amyotrophic lateral sclerosis. Neuroscience 277:132–138. doi: 10.1016/j.neuroscience.2014.03.047

129. Jinwal UK, O’Leary JC, Borysov SI, Jones JR, Li Q, Koren J, Abisambra JF, Vestal GD, Lawson LY, Johnson AG, Blair LJ, Jin Y, Miyata Y, Gestwicki JE, Dickey CA (2010) Hsc70 rapidly engages tau after microtubule destabilization. J Biol Chem 285:16798–16805. doi: 10.1074/jbc.M110.113753

130. Johnston JA, Dalton MJ, Gurney ME, Kopito RR (2000) Formation of high molecular weight complexes of mutant Cu, Zn-superoxide dismutase in a mouse model for familial amyotrophic lateral sclerosis. Proc Natl Acad Sci U S A 97:12571–6. doi: 10.1073/pnas.220417997

131. Kabashi E, Agar JN, Hong Y, Taylor DM, Minotti S, Figlewicz DA, Durham HD (2008) Proteasomes remain intact, but show early focal alteration in their composition in a mouse model of amyotrophic lateral sclerosis. J Neurochem 105:2353–2366. doi: 10.1111/j.1471-4159.2008.05317.x

132. Kabashi E, Agar JN, Strong MJ, Durham HD (2012) Impaired proteasome function in sporadic amyotrophic lateral sclerosis. Amyotroph Lateral Scler 13:367–371. doi: 10.3109/17482968.2012.686511

168

133. Kabashi E, Agar JN, Taylor DM, Minotti S, Durham HD (2004) Focal dysfunction of the proteasome: A pathogenic factor in a mouse model of amyotrophic lateral sclerosis. J Neurochem 89:1325–1335. doi: 10.1111/j.1471-4159.2004.02453.x

134. Kaganovich D, Kopito R, Frydman J (2008) Misfolded proteins partition between two distinct quality control compartments. Nature 454:1088–1095. doi: 10.1038/nature07195

135. Kaminskyy V, Zhivotovsky B (2012) Proteases in autophagy. Biochim. Biophys. Acta - Proteins Proteomics 1824:44–50

136. Kampinga HH, Craig EA (2010) The HSP70 chaperone machinery: J proteins as drivers of functional specificity. Nat Rev Mol Cell Biol 11:579–592. doi: 10.1038/nrm2941

137. Karagö GE, Duarte AMS, Akoury E, Ippel H, Biernat J, Moran Luengo T, Radli M, Didenko T, Nordhues BA, Veprintsev DB, Dickey CA, Mandelkow E, Zweckstetter M, Boelens R, Madl T, Rudiger SGD (2014) Hsp90-tau complex reveals molecular basis for specificity in chaperone action. Cell 156:963–974. doi: 10.1016/j.cell.2014.01.037

138. Karch CM, Prudencio M, Winkler DD, Hart PJ, Borchelt DR (2009) Role of mutant SOD1 disulfide oxidation and aggregation in the pathogenesis of familial ALS. Proc Natl Acad Sci U S A 106:7774–9. doi: 10.1073/pnas.0902505106

139. Kawarabayashi T, Younkin L (2001) Age-dependent changes in brain, CSF, and plasma amyloid β protein in the Tg2576 transgenic mouse model of Alzheimer’s disease. J Neurosci 21:372–381

140. Keck S, Nitsch R, Grune T, Ullrich O (2003) Proteasome inhibition by paired helical filament-tau in brains of patients with Alzheimer’s disease. J Neurochem 85:115–122. doi: 10.1046/j.1471-4159.2003.01642.x

141. Keller A, Nesvizhskii AI, Kolker E, Aebersold R (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74:5383–5392. doi: 10.1021/ac025747h

142. Keller JN, Hanni KB, Markesbery WR (2000) Impaired proteasome function in Alzheimer’s disease. J Neurochem 75:436–439. doi: 10.1046/j.1471- 4159.2000.0750436.x

143. Kenniston JA, Baker TA, Fernandez JM, Sauer RT (2003) Linkage between ATP consumption and mechanical unfolding during the protein processing reactions of an AAA+degradation machine. Cell 114:511–520. doi: 10.1016/S0092- 8674(03)00612-3

169

144. Kieran D, Kalmar B, Dick JRT, Riddoch-Contreras J, Burnstock G, Greensmith L (2004) Treatment with arimoclomol, a coinducer of heat shock proteins, delays disease progression in ALS mice. Nat Med 10:402–405. doi: 10.1038/nm1021

145. Kim HJ, Raphael AR, Ladow ES, Mcgurk L, Weber RA, Trojanowski JQ, Lee VMY, Finkbeiner S, Gitler AD, Bonini NM (2014) Therapeutic modulation of eIF2α phosphorylation rescues TDP-43 toxicity in amyotrophic lateral sclerosis disease models. Nat Genet 46:152–160. doi: 10.1038/ng.2853

146. Kim YE, Hipp MS, Bracher A, Hayer-Hartl M, Hartl FU (2013) Molecular Chaperone Functions in Protein Folding and Proteostasis. Annu Rev Biochem 82:323–355. doi: 10.1146/annurev-biochem-060208-092442

147. Kimura Y, Yashiroda H, Kudo T, Koitabashi S, Murata S, Kakizuka A, Tanaka K (2009) An Inhibitor of a Deubiquitinating Enzyme Regulates Ubiquitin Homeostasis. Cell 137:549–559. doi: 10.1016/j.cell.2009.02.028

148. Klionsky DJ, Cregg JM, Dunn WA, Emr SD, Sakai Y, Sandoval I V., Sibirny A, Subramani S, Thumm M, Veenhuis M, Ohsumi Y (2003) A unified nomenclature for yeast autophagy-related genes. Dev. Cell 5:539–545

149. Koch Y, Helferich AM, Steinacker P, Oeckl P, Walther P, Weishaupt JH, Danzer KM, Otto M (2016) Aggregated α-Synuclein Increases SOD1 Oligomerization in a Mouse Model of Amyotrophic Lateral Sclerosis. Am J Pathol 186:2152–2161. doi: 10.1016/j.ajpath.2016.04.008

150. Kundu M, Thompson CB (2008) Autophagy: basic principles and relevance to disease. Annu Rev Pathol 3:427–455. doi: 10.1146/annurev.pathmechdis.2.010506.091842

151. Labbadia J, Morimoto RI (2014) Proteostasis and longevity: when does aging really begin? F1000Prime Rep 6:7. doi: 10.12703/P6-7

152. Labbadia J, Morimoto RI (2015) The Biology of Proteostasis in Aging and Disease. Annu Rev Biochem 1–30. doi: 10.1146/annurev-biochem-060614- 033955

153. Langer T, Lu C, Echols H, Flanagan J, Hayer MK, Hartl FU (1992) Successive action of DnaK, DnaJ and GroEL along the pathway of chaperone-mediated protein folding. Nature 356:683–689. doi: 10.1038/356683a0

154. Lee BH, Lu Y, Prado MA, Shi Y, Tian G, Sun S, Elsasser S, Gygi SP, King RW, Finley D (2016) USP14 deubiquitinates proteasome-bound substrates that are ubiquitinated at multiple sites. Nature 532:398–401. doi: 10.1038/nature17433

155. Lee MJ, Lee JH, Rubinsztein DC (2013) Tau degradation: The ubiquitin- proteasome system versus the autophagy-lysosome system. Prog. Neurobiol. 105:49–59

170

156. Lewis J, Dickson DW, Lin W-L, Chisholm L, Corral A, Jones G, Yen S, Sahara N, Skipper L, Yager D, Eckman C, Hardy J, Hutton M (2001) Enhanced Neuro brillary Degeneration in Transgenic Mice Expressing Mutant Tau and APP. Science (80- ) 293:1487–1491. doi: 10.1126/science.1058189

157. Lewis J, Dickson DW, Lin WL, Chisholm L, Corral A, Jones G, Yen SH, Sahara N, Skipper L, Yager D, Eckman C, Hardy J, Hutton M, McGowan E (2001) Enhanced neurofibrillary degeneration in transgenic mice expressing mutant tau and APP. Science 293:1487–91. doi: 10.1126/science.1058189

158. Lewis J, McGowan E, Rockwood J, Melrose H, Nacharaju P, Van Slegtenhorst M, Gwinn-Hardy K, Paul Murphy M, Baker M, Yu X, Duff K, Hardy J, Corral A, Lin WL, Yen SH, Dickson DW, Davies P, Hutton M (2000) Neurofibrillary tangles, amyotrophy and progressive motor disturbance in mice expressing mutant (P301L) tau protein. Nat Genet 25:402–405. doi: 10.1038/79109

159. Liang TW, Forman MS, Duda JE, McCluskey L, Trojanowski JQ, Siderowf A (2005) Multiple pathologies in a patient with a progressive neurodegenerative syndrome. J Neurol Neurosurg Psychiatry 76:252–255. doi: DOI 10.1136/jnnp.2004.039479

160. Liao L, Cheng D, Wang J, Duong DM, Losik TG, Gearing M, Rees HD, Lah JJ, Levey AI, Peng J (2004) Proteomic characterization of postmortem amyloid plaques isolated by laser capture microdissection. J Biol Chem 279:37061– 37068. doi: 10.1074/jbc.M403672200

161. Lindberg I, Shorter J, Wiseman RL, Chiti F, Dickey C a, McLean PJ (2015) Chaperones in Neurodegeneration. J Neurosci 35:13853–9. doi: 10.1523/JNEUROSCI.2600-15.2015

162. Lindquist S (1986) The Heat-Shock Response. Annu Rev Biochem 55:1151– 1191. doi: 10.1146/annurev.bi.55.070186.005443

163. Love S, Saitoh T, Quijada S, Cole GM, Terry RD (1988) Alz-50, ubiquitin and tau immunoreactivity of neurofibrillary tangles, Pick bodies and Lewy bodies. J Neuropathol Exp Neurol 47:393–405

164. Luk KC, Mills IP, Trojanowski JQ, Lee VMY (2008) Interactions between Hsp70 and the Hydrophobic Core of α-Synuclein Inhibit Fibril Assembly. Biochemistry 47:12614–12625

165. Matyskiela ME, Lander GC, Martin A (2013) Conformational switching of the 26S proteasome enables substrate degradation. Nat Struct Mol Biol 20:781–788. doi: 10.1038/nsmb.2616

166. Mayer MP, Bukau B (2005) Hsp70 chaperones: Cellular functions and molecular mechanism. Cell Mol Life Sci 62:670–684. doi: 10.1007/s00018-004-4464-6

171

167. McClellan AJ, Xia Y, Deutschbauer AM, Davis RW, Gerstein M, Frydman J (2007) Diverse Cellular Functions of the Hsp90 Molecular Chaperone Uncovered Using Systems Approaches. Cell 131:121–135. doi: 10.1016/j.cell.2007.07.036

168. McKinley MP, Meyer RK, Kenaga L, Rahbar F, Cotter R, Serban A, Prusiner SB (1991) Scrapie prion rod formation in vitro requires both detergent extraction and limited proteolysis. J Virol 65:1340–51

169. McKinnon C, Tabrizi SJ (2014) The Ubiquitin-Proteasome System in Neurodegeneration. Antioxid Redox Signal 21:2302–2321. doi: 10.1089/ars.2013.5802

170. McNaught KS., Belizaire R, Jenner P, Olanow CW, Isacson O (2002) Selective loss of 20S proteasome α-subunits in the substantia nigra pars compacta in Parkinson’s disease. Neurosci Lett 326:155–158. doi: 10.1016/S0304- 3940(02)00296-3

171. McNaught KSP, Jenner P (2001) Proteasomal function is impaired in substantia nigra in Parkinson’s disease. Neurosci Lett 297:191–194. doi: 10.1016/S0304- 3940(00)01701-8

172. McNaught KSP, Olanow CW, Schapira, Jenner, Isacson, Hunot, Tatton, Beal (2003) Proteolytic stress: A unifying concept for the etiopathogenesis of Parkinson’s disease. Ann Neurol 53:73–86. doi: 10.1002/ana.10512

173. Mi H, Huang X, Muruganujan A, Tang H, Mills C, Kang D, Thomas PD (2017) PANTHER version 11: Expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res 45:D183–D189. doi: 10.1093/nar/gkw1138

174. Mi H, Muruganujan A, Casagrande JT, Thomas PD (2013) Large-scale gene function analysis with the PANTHER classification system. Nat Protoc 8:1551– 1566. doi: 10.1038/nprot.2013.092

175. Miyata Y, Koren J, Kiray J, Dickey CA, Gestwicki JE (2011) Molecular chaperones and regulation of tau quality control: strategies for drug discovery in tauopathies. Future Med Chem 3:1523–1537. doi: 10.4155/fmc.11.88

176. Mizushima N, Komatsu M (2011) Autophagy: Renovation of cells and tissues. Cell 147:728–741

177. Mizushima N, Ohsumi Y, Yoshimori T (2002) Autophagosome Formation in Mammalian Cells. Cell Struct Funct 27:421–429. doi: 10.1247/csf.27.421

178. Mizushima N, Yoshimori T, Ohsumi Y (2011) The Role of Atg Proteins in Autophagosome Formation. Annu Rev Cell Dev Biol 27:107–132. doi: 10.1146/annurev-cellbio-092910-154005

172

179. Moreno JA, Radford H, Peretti D, Steinert JR, Verity N, Martin MG, Halliday M, Morgan J, Dinsdale D, Ortori CA, Barrett DA, Tsaytler P, Bertolotti A, Willis AE, Bushell M, Mallucci GR (2012) Sustained translational repression by eIF2α-P mediates prion neurodegeneration. Nature 485:507–511. doi: 10.1038/nature11058

180. Morimoto RI (2006) Stress , Aging , and Neurodegenerative Disease. N Engl J Med 355:2254–2255

181. Morimoto RI (2008) Proteotoxic stress and inducible chaperone networks in neurodegenerative disease and aging. Genes Dev 22:1427–1438. doi: 10.1101/gad.1657108

182. Morimoto RI, Cuervo AM (2014) Proteostasis and the aging proteome in health and disease. Journals Gerontol - Ser A Biol Sci Med Sci 69:S33–S38. doi: 10.1093/gerona/glu049

183. Morley JF, Brignull HR, Weyers JJ, Morimoto RI (2002) The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans. Proc Natl Acad Sci U S A 99:10417–22. doi: 10.1073/pnas.152161099

184. Morris M, Maeda S, Vossel K, Mucke L (2011) The Many Faces of Tau. Neuron 70:410–426

185. Mukherjee A, Morales-Scheihing D, Butler PC, Soto C (2015) Type 2 diabetes as a protein misfolding disease. Trends Mol Med 21:439–449. doi: 10.1016/j.molmed.2015.04.005

186. Musicco M, Adorni F, Di Santo S, Prinelli F, Pettenati C, Caltagirone C, Palmer K, Russo A (2013) Inverse occurrence of cancer and Alzheimer disease: a population-based incidence study. Neurology 81:322–8. doi: 10.1212/WNL.0b013e31829c5ec1

187. Myeku N, Clelland CL, Emrani S, Kukushkin N V, Yu WH, Goldberg AL, Duff KE (2015) Tau-driven 26S proteasome impairment and cognitive dysfunction can be prevented early in disease by activating cAMP-PKA signaling. Nat Med 6:1–11. doi: 10.1038/nm.4011

188. Nagy M, Fenton WA, Li D, Furtak K, Horwich AL (2016) Extended survival of misfolded G85R SOD1-linked ALS mice by transgenic expression of chaperone Hsp110. Proc Natl Acad Sci 113:1–5. doi: 10.1073/pnas.1604885113

189. Nesvizhskii AI, Keller A, Kolker E, Aebersold R (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem 75:4646–4658. doi: 10.1021/ac0341261

173

190. Nijholt DAT, Nölle A, van Haastert ES, Edelijn H, Toonen RF, Hoozemans JJM, Scheper W (2013) Unfolded protein response activates glycogen synthase kinase-3 via selective lysosomal degradation. Neurobiol Aging 34:1759–1771. doi: 10.1016/j.neurobiolaging.2013.01.008

191. Noda NN, Inagaki F (2015) Mechanisms of Autophagy. Annu Rev Biophys 44:101–122. doi: 10.1146/annurev-biophys-060414-034248

192. Old WM (2005) Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics. Mol Cell Proteomics 4:1487–1502. doi: 10.1074/mcp.M500084-MCP200

193. Olzscha H, Schermann SM, Woerner AC, Pinkert S, Hecht MH, Tartaglia GG, Vendruscolo M, Hayer-Hartl M, Hartl FU, Vabulas RM (2011) Amyloid-like aggregates sequester numerous metastable proteins with essential cellular functions. Cell 144:67–78. doi: 10.1016/j.cell.2010.11.050

194. Pace MC, Xu G, Fromholt S, Howard J, Crosby K, Benoit ·, Giasson I, Lewis J, Borchelt DR (2018) Changes in proteome solubility indicate widespread proteostatic disruption in mouse models of neurodegenerative disease. Acta Neuropathol. doi: 10.1007/s00401-018-1895-y

195. Pace MC, Xu G, Fromholt S, Howard J, Giasson BI, Lewis J, Borchelt DR (2018) Differential induction of mutant SOD1 misfolding and aggregation by tau and α- synuclein pathology. Mol Neurodegener 13:1–15. doi: 10.1186/s13024-018-0253- 9

196. Parakh S, Atkin JD (2016) Protein folding alterations in amyotrophic lateral sclerosis. Brain Res 1648:633–649. doi: 10.1016/j.brainres.2016.04.010

197. Peth A, Uchiki T, Goldberg AL (2010) ATP-Dependent steps in the binding of ubiquitin conjugates to the 26s proteasome that commit to degradation. Mol Cell 40:671–681. doi: 10.1016/j.molcel.2010.11.002

198. Petrucelli L, Dickson D, Kehoe K, Taylor J, Snyder H, Grover A, De Lucia M, McGowan E, Lewis J, Prihar G, Kim J, Dillmann WH, Browne SE, Hall A, Voellmy R, Tsuboi Y, Dawson TM, Wolozin B, Hardy J, Hutton M (2004) CHIP and Hsp70 regulate tau ubiquitination, degradation and aggregation. Hum Mol Genet 13:703– 714. doi: 10.1093/hmg/ddh083

199. Piras A, Collin L, Grüninger F, Graff C, Rönnbäck A (2016) Autophagic and lysosomal defects in human tauopathies: analysis of post-mortem brain from patients with familial Alzheimer disease, corticobasal degeneration and progressive supranuclear palsy. Acta Neuropathol Commun 4:22. doi: 10.1186/s40478-016-0292-9

174

200. Powers ET, Balch WE (2013) Diversity in the origins of proteostasis networks-a driver for protein function in evolution. Nat. Rev. Mol. Cell Biol. 14:237–248

201. Pratt AJ, Shin DS, Merz GE, Rambo RP, Lancaster WA, Dyer KN, Borbat PP, Poole FL, Adams MWW, Freed JH, Crane BR, Tainer JA, Getzoff ED (2014) Aggregation propensities of superoxide dismutase G93 hotspot mutants mirror ALS clinical phenotypes. Proc Natl Acad Sci U S A 111:E4568-76. doi: 10.1073/pnas.1308531111

202. Pratt WB, Gestwicki JE, Osawa Y, Lieberman AP (2015) Targeting Hsp90/Hsp70- Based Protein Quality Control for Treatment of Adult Onset Neurodegenerative Diseases. Annu Rev Pharmacol Toxicol 55:353–371. doi: 10.1146/annurev- pharmtox-010814-124332

203. Probst A, Tolnay M, Langui D, Goedert M, Spillantini MG (1996) Pick’s disease: Hyperphosphorylated tau protein segregates to the somatoaxonal compartment. Acta Neuropathol 92:588–596. doi: 10.1007/s004010050565

204. Prokai L, Stevens SM, Rauniyar N, Nguyen V (2009) Rapid label-free identification of estrogen-induced differential protein expression in vivo from mouse brain and uterine tissue. J Proteome Res 8:3862–3871. doi: 10.1021/pr900083v

205. Quinton EE, Kramarcy NR (1977) Memory impairment correlates closely with cycloheximide dose and degree of inhibition of protein synthesis. Brain Res 131:184–190. doi: 10.1016/0006-8993(77)90041-5

206. Radford H, Moreno JA, Verity N, Halliday M, Mallucci GR (2015) PERK inhibition prevents tau-mediated neurodegeneration in a mouse model of frontotemporal dementia. Acta Neuropathol 130:633–642. doi: 10.1007/s00401-015-1487-z

207. Ramsden M, Kotilinek L, Forster C, Paulson J, McGowan E, SantaCruz K, Guimaraes A, Yue M, Lewis J, Carlson G, Hutton M, Ashe KH (2005) Age- dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L). J Neurosci 25:10637–10647. doi: 10.1523/JNEUROSCI.3279-05.2005

208. Ravid T, Hochstrasser M (2008) Diversity of degradation signals in the ubiquitin- proteasome system. Nat. Rev. Mol. Cell Biol. 9:679–689

209. Reggiori F (2006) Membrane Origin for Autophagy. Curr Top Dev Biol 74:1–30. doi: 10.1016/S0070-2153(06)74001-7

210. Reggiori F, Klionsky DJ (2005) Autophagosomes: Biogenesis from scratch? Curr. Opin. Cell Biol. 17:415–422

175

211. Reits E, Griekspoor A, Neijssen J, Groothuis T, Jalink K, Van Veelen P, Janssen H, Calafat J, Drijfhout JW, Neefjes J (2003) Peptide Diffusion, Protection, and Degradation in Nuclear and Cytoplasmic Compartments before Antigen Presentation by MHC Class I. Immunity 18:97–108. doi: 10.1016/S1074- 7613(02)00511-3

212. Richfield EK, Thiruchelvam MJ, Cory-Slechta DA, Wuertzer C, Gainetdinov RR, Caron MG, Di Monte DA, Federoff HJ (2002) Behavioral and neurochemical effects of wild-type and mutated human α-synuclein in transgenic mice. Exp Neurol 175:35–48. doi: 10.1006/exnr.2002.7882

213. Rubinsztein DC, Nixon RA (2010) Rapamycin induces autophagic flux in neurons. Proc Natl Acad Sci 107:E181–E181. doi: 10.1073/pnas.1014633107

214. Rujano MA, Bosveld F, Salomons FA, Dijk F, Van Waarde MAWH, Van Der Want JJL, De Vos RAI, Brunt ER, Sibon OCM, Kampinga HH (2006) Polarised asymmetric inheritance of accumulated protein damage in higher eukaryotes. PLoS Biol 4:2325–2335. doi: 10.1371/journal.pbio.0040417

215. Ryu K-Y, Sinnar SA, Reinholdt LG, Vaccari S, Hall S, Garcia MA, Zaitseva TS, Bouley DM, Boekelheide K, Handel MA, Conti M, Kopito RR (2008) The Mouse Polyubiquitin Gene Ubb Is Essential for Meiotic Progression. Mol Cell Biol 28:1136–1146. doi: 10.1128/MCB.01566-07

216. Sacino AN, Brooks M, Thomas MA, McKinney AB, Lee S, Regenhardt RW, McGarvey NH, Ayers JI, Notterpek L, Borchelt DR, Golde TE, Giasson BI (2014) Intramuscular injection of α-synuclein induces CNS α-synuclein pathology and a rapid-onset motor phenotype in transgenic mice. Proc Natl Acad Sci U S A 111:1– 6. doi: 10.1073/pnas.1321785111

217. SantaCruz K, Lewis J, Spires-Jones TL, Paulson J, Kotilinek L, Ingelsson M, Guimaraes A, DeTure M, Ramsden M, McGowan E, Forster C, Yue M, Orne J, Janus C, Mariash A, Kuskowski M, Hyman B, Hutton M, Ashe KH (2005) Tau Suppression in a Neurodegenerative Mouse Model Improves Memory Function. Science (80- ) 309:476–481. doi: 10.1126/science.1113694

218. Sarkar M, Kuret J, Lee G (2008) Two motifs within the tau microtubule-binding domain mediate its association with the hsc70 molecular chaperone. J Neurosci Res 86:2763–2773. doi: 10.1002/jnr.21721

219. Sau D, De Biasi S, Vitellaro-Zuccarello L, Riso P, Guarnieri S, Porrini M, Simeoni S, Crippa V, Onesto E, Palazzolo I, Rusmini P, Bolzoni E, Bendotti C, Poletti A (2007) Mutation of SOD1 in ALS: A gain of a loss of function. Hum Mol Genet 16:1604–1618. doi: 10.1093/hmg/ddm110

176

220. Scherzinger E, Sittler A, Schweiger K, Heiser V, Lurz R, Hasenbank R, Bates GP, Lehrach H, Wanker EE (1999) Self-assembly of polyglutamine-containing huntingtin fragments into amyloid-like fibrils: implications for Huntington’s disease pathology. Proc Natl Acad Sci U S A 96:4604–9. doi: 10.1073/pnas.96.8.4604

221. Schneider-Poetsch T, Ju J, Eyler DE, Dang Y, Bhat S, Merrick WC, Green R, Shen B, Liu JO (2010) Inhibition of eukaryotic translation elongation by cycloheximide and lactimidomycin. Nat Chem Biol 6:209–217. doi: 10.1038/nchembio.304

222. Schröder M, Kaufman RJ (2005) ER stress and the unfolded protein response. Mutat Res 569:29–63. doi: 10.1016/j.mrfmmm.2004.06.056

223. Schweitzer A, Aufderheide A, Rudack T, Beck F, Pfeifer G, Plitzko JM, Sakata E, Schulten K, Förster F, Baumeister W (2016) Structure of the human 26S proteasome at a resolution of 3.9 Å. Proc Natl Acad Sci 113:7816–7821. doi: 10.1073/pnas.1608050113

224. Sekijima Y, Wiseman RL, Matteson J, Hammarström P, Miller SR, Sawkar AR, Balch WE, Kelly JW (2005) The biological and chemical basis for tissue-selective amyloid disease. Cell 121:73–85. doi: 10.1016/j.cell.2005.01.018

225. Sekine Y, Zyryanova A, Crespillo-Casado A, Fischer PM, Harding HP, Ron D (2015) Mutations in a translation initiation factor identify the target of a memory- enhancing compound. Science (80- ) 348:1027–1030. doi: 10.1126/science.aaa6986

226. Seyfried NT, Gozal YM, Donovan LE, Herskowitz JH, Dammer EB, Xia Q, Ku L, Chang J, Duong DM, Rees HD, Cooper DS, Glass JD, Gearing M, Tansey MG, Lah JJ, Feng Y, Levey AI, Peng J (2012) Quantitative analysis of the detergent- insoluble brain proteome in frontotemporal lobar degeneration using SILAC internal standards. J Proteome Res 11:2721–2738. doi: 10.1021/pr2010814

227. Shaw BF, Lelie HL, Durazo A, Nersissian AM, Xu G, Chan PK, Gralla EB, Tiwari A, Hayward LJ, Borchelt DR, Valentine JS, Whitelegge JP (2008) Detergent- insoluble aggregates associated with amyotrophic lateral sclerosis in transgenic mice contain primarily full-length, unmodified superoxide dismutase-1. J Biol Chem 283:8340–8350. doi: 10.1074/jbc.M707751200

228. Shaw CE (2010) Capturing VCP: Another Molecular Piece in the ALS Jigsaw Puzzle. Neuron 68:812–814

229. Shimura H, Miura-Shimura Y, Kosik KS (2004) Binding of Tau to Heat Shock Protein 27 Leads to Decreased Concentration of Hyperphosphorylated Tau and Enhanced Cell Survival. J Biol Chem 279:17957–17962. doi: 10.1074/jbc.M400351200

177

230. Shimura H, Schwartz D, Gygi SP, Kosik KS (2004) CHIP-Hsc70 Complex Ubiquitinates Phosphorylated Tau and Enhances Cell Survival. J Biol Chem 279:4869–4876. doi: 10.1074/jbc.M305838200

231. Shin Y, Klucken J, Patterson C, Hyman BT, McLean PJ (2005) The Co-chaperone carboxyl terminus of Hsp70-interacting protein (CHIP) mediates α-synuclein degradation decisions between proteasomal and lysosomal pathways. J Biol Chem 280:23727–23734. doi: 10.1074/jbc.M503326200

232. Sidrauski C, McGeachy AM, Ingolia NT, Walter P (2015) The small molecule ISRIB reverses the effects of eIF2α phosphorylation on translation and stress granule assembly. Elife 2015:1–16. doi: 10.7554/eLife.05033

233. Smith DM, Benaroudj N, Goldberg A (2006) Proteasomes and their associated ATPases: A destructive combination. J. Struct. Biol. 156:72–83

234. Smith HL, Li W, Cheetham ME (2015) Molecular chaperones and neuronal proteostasis. Semin Cell Dev Biol 40:142–152. doi: 10.1016/j.semcdb.2015.03.003

235. Snyder H, Mensah K, Theisler C, Lee J, Matouschek A, Wolozin B (2003) Aggregated and monomeric α-synuclein bind to the S6’ proteasomal protein and inhibit proteasomal function. J Biol Chem 278:11753–11759. doi: 10.1074/jbc.M208641200

236. Sokal RR, Rohlf JF (1995) Biometry, the principles and practice of statistics in biological research. W.H. Freeman

237. Sommer T, Wolf DH (1997) Endoplasmic reticulum degradation: reverse protein flow of no return. FASEB J 11:1227–1233. doi: 0892-6638/97/0011-1227

238. Sontag EM, Vonk WIM, Frydman J (2014) Sorting out the trash: The spatial nature of eukaryotic protein quality control. Curr. Opin. Cell Biol. 26:139–146

239. Soto C (2003) Unfolding the role of protein misfolding in neurodegenerative diseases. Nat Rev Neurosci 4:49–60. doi: 10.1038/nrn1007

240. Spillantini MG, Crowther RA, Jakes R, Hasegawa M, Goedert M (1998) alpha- Synuclein in filamentous inclusions of Lewy bodies from Parkinson’s disease and dementia with lewy bodies. Proc Natl Acad Sci U S A 95:6469–73. doi: 10.1073/pnas.95.11.6469

241. Spillantini MG, Goedert M, Crowther RA, Murrell JR, Farlow MR, Ghetti B (1997) Familial multiple system tauopathy with presenile dementia: a disease with abundant neuronal and glial tau filaments. Proc Natl Acad Sci U S A 94:4113–8. doi: 10.1073/pnas.94.8.4113

178

242. Spillantini MG, Schmidt ML, Lee VM-Y, Trojanowski JQ, Jakes R, Goedert M (1997) α-Synuclein in Lewy bodies. Nature 388:839–840. doi: 10.1038/42166

243. Spires-Jones TL, Attems J, Thal DR (2017) Interactions of pathological proteins in neurodegenerative diseases. Acta Neuropathol 1–19. doi: 10.1007/s00401-017- 1709-7

244. Squire LR, Barondes SH (1972) Variable decay of memory and its recovery in cycloheximide-treated mice. Proc Natl Acad Sci U S A 69:1416–20. doi: 10.1073/pnas.69.6.1416

245. Stone M, Hartmann-Petersen R, Seeger M, Bech-Otschir D, Wallace M, Gordon C (2004) Uch2/Uch37 is the major deubiquitinating enzyme associated with the 26 S proteasome in fission yeast. J Mol Biol 344:697–706. doi: 10.1016/j.jmb.2004.09.057

246. Strang KH, Croft CL, Sorrentino ZA, Chakrabarty P, Golde TE, Giasson BI (2017) Distinct differences in prion-like seeding and aggregation between tau protein variants provide mechanistic insights into tauopathies. J Biol Chem jbc.M117.815357. doi: 10.1074/jbc.M117.815357

247. Suzuki K, Kirisako T, Kamada Y, Mizushima N, Noda T, Ohsumi Y (2001) The pre-autophagosomal structure organized by concerted functions of APG genes is essential for autophagosome formation. EMBO J 20:5971–5981. doi: 10.1093/emboj/20.21.5971

248. Sweeney P, Park H, Baumann M, Dunlop J, Frydman J, Kopito R, McCampbell A, Leblanc G, Venkateswaran A, Nurmi A, Hodgson R (2017) Protein misfolding in neurodegenerative diseases: implications and strategies. Transl Neurodegener 6:1–13. doi: 10.1186/s40035-017-0077-5

249. Tai H-C (2010) Characterization of the brain 26S proteasome and its interacting proteins. Front Mol Neurosci 3:1–19. doi: 10.3389/fnmol.2010.00012

250. Tai HC, Serrano-Pozo A, Hashimoto T, Frosch MP, Spires-Jones TL, Hyman BT (2012) The synaptic accumulation of hyperphosphorylated tau oligomers in alzheimer disease is associated with dysfunction of the ubiquitin-proteasome system. Am J Pathol 181:1426–1435. doi: 10.1016/j.ajpath.2012.06.033

251. Taipale M, Jarosz DF, Lindquist S (2010) HSP90 at the hub of protein homeostasis: emerging mechanistic insights. Nat Rev Mol Cell Biol 11:515–28. doi: 10.1038/nrm2918

252. Tanaka K, Matsuda N (2014) Proteostasis and neurodegeneration: The roles of proteasomal degradation and autophagy. Biochim. Biophys. Acta - Mol. Cell Res. 1843:197–204

179

253. Tanakas K, Yoshimura T, Ichihara A, Kameyama K, Takagi T, Waxman L, Goldberg AL (1986) A High Molecular Weight Protease in the Cytosol of Rat Liver. J Biol Chem 261:15204–15207

254. Taylor RC, Dillin A (2011) Aging as an event of proteostasis collapse. Cold Spring Harb Perspect Biol 3:1–17. doi: 10.1101/cshperspect.a004440

255. Teter SA, Houry WA, Ang D, Tradler T, Rockabrand D, Fischer G, Blum P, Georgopoulos C, Hartl FU (1999) Polypeptide flux through bacterial Hsp70: DnaK cooperates with trigger factor in chaperoning nascent chains. Cell 97:755–765. doi: 10.1016/S0092-8674(00)80787-4

256. Thrower JS, Hoffman L, Rechsteiner M, Pickart CM (2000) Recognition of the polyubiquitin proteolytic signal. EMBO J 19:94–102. doi: 10.1093/emboj/19.1.94

257. Thumm M, Egner R, Koch B, Schlumpberger M, Straub M, Veenhuis M, Wolf DH (1994) Isolation of autophagocytosis mutants of Saccharomyces cerevisiae. FEBS Lett 349:275–280. doi: 10.1016/0014-5793(94)00672-5

258. Trojanowski JQ, Wang J, Lee VM (1999) Purification of Paired Helical Filament Tau and Normal Tau from Human Brain Tissue. Methods Enzymol 309:81–89

259. Tsaytler P, Harding HP, Ron D, Bertolotti A (2011) Selective Inhibition of a Regulatory Subunit of Protein Phosphatase 1 Restores Proteostasis. Science (80- ) 332:91–94. doi: 10.1126/science.1201396

260. Tsukada M, Ohsumi Y (1993) Isofation and characterization of autophagy- defective mutants of Saccharomyces cerevisiae. FEBS Lett 333:169–174. doi: 10.1016/0014-5793(93)80398-E

261. Tu PH, Galvin JE, Baba M, Giasson B, Tomita T, Leight S, Nakajo S, Iwatsubo T, Trojanowski JQ, Lee VMY (1998) Glial cytoplasmic inclusions in white matter oligodendrocytes of multiple system atrophy brains contain insoluble α-synuclein. Ann Neurol 44:415–422. doi: 10.1002/ana.410440324

262. Unno M, Mizushima T, Morimoto Y, Tomisugi Y, Tanaka K, Yasuoka N, Tsukihara T (2002) The structure of the mammalian 20S proteasome at 2.75 Å resolution. Structure 10:609–618. doi: 10.1016/S0969-2126(02)00748-7

263. Vabulas RM, Raychaudhuri S, Hayer-hartl M, Hartl FU (2010) Heat Shock Response. Cold Spring Harb Perspect Biol 2:a004390:1–18. doi: 10.1101/cshperspect.a004390

264. Verma R, Aravind L, Oania R, McDonald WH, Yates JR 3rd, Koonin E V., Deshaies RJ (2002) Role of Rpn11 Metalloprotease in Deubiquitination and Degradation by the 26S Proteasome. Science (80- ) 298:611–615. doi: 10.1126/science.1075898

180

265. Vilchez D, Saez I, Dillin A (2014) The role of protein clearance mechanisms in organismal ageing and age-related diseases. Nat Commun 5:5659. doi: 10.1038/ncomms6659

266. Walker L, Kirsty ·, Mcaleese E, Thomas AJ, Johnson M, Martin‑ruiz C, Parker C, Colloby SJ, Jellinger K, Attems J (2015) Neuropathologically mixed Alzheimer’s and Lewy body disease: burden of pathological protein aggregates differs between clinical phenotypes. Acta Neuropathol 129:729–748. doi: 10.1007/s00401-015-1406-3

267. Walther DM, Kasturi P, Zheng M, Pinkert S, Vecchi G, Ciryam P, Morimoto RI, Dobson CM, Vendruscolo M, Mann M, Hartl FU (2015) Widespread proteome remodeling and aggregation in aging C. elegans. Cell 161:919–932. doi: 10.1016/j.cell.2015.03.032

268. Wang J, Farr GW, Zeiss CJ, Rodriguez-Gil DJ, Wilson JH, Furtak K, Rutkowski DT, Kaufman RJ, Ruse CI, Yates JR 3rd, Perrin S, Feany MB, Horwich AL (2009) Progressive aggregation despite chaperone associations of a mutant SOD1-YFP in transgenic mice that develop ALS. Proc Natl Acad Sci U S A 106:1392–1397. doi: 10.1073/pnas.0813045106

269. Wang J, Slunt H, Gonzales V, Fromholt D, Coonfield M, Copeland NG, Jenkins NA, Borchelt DR (2003) Copper-binding-site-null SOD1 causes ALS in transgenic mice: aggregates of non-native SOD1 delineate a common feature. Hum Mol Genet 12:2753–64. doi: 10.1093/hmg/ddg312

270. Wang J, Xu G, Gonzales V, Coonfield M, Fromholt D, Copeland NG, Jenkins NA, Borchelt DR (2002) Fibrillar Inclusions and Motor Neuron Degeneration in Transgenic Mice Expressing Superoxide Dismutase 1 with a Disrupted Copper- Binding Site. Neurobiol Dis 10:128–138. doi: 10.1006/nbdi.2002.0498

271. Wang L, Popko B, Tixier E, Roos RP (2014) Guanabenz, which enhances the unfolded protein response, ameliorates mutant SOD1-induced amyotrophic lateral sclerosis. Neurobiol Dis 71:317–324. doi: 10.1016/j.nbd.2014.08.010

272. Wang P, Joberty G, Buist A, Vanoosthuyse A, Stancu I-C, Vasconcelos B, Pierrot N, Faelth-Savitski M, Kienlen-Campard P, Octave J-N, Bantscheff M, Drewes G, Moechars D, Dewachter I (2017) Tau interactome mapping based identification of Otub1 as Tau deubiquitinase involved in accumulation of pathological Tau forms in vitro and in vivo. Acta Neuropathol 133:731–749. doi: 10.1007/s00401-016- 1663-9

273. Wang Q, Woltjer RL, Cimino PJ, Pan C, Montine KS, Zhang J, Montine TJ (2005) Proteomic analysis of neurofibrillary tangles in Alzheimer disease identifies GAPDH as a detergent-insoluble paired helical filament tau binding protein. FASEB J 19:869–871. doi: 10.1096/fj.04-3210fje

181

274. Wang X, Chen CF, Baker PR, Chen PL, Kaiser P, Huang L (2007) Mass spectrometric characterization of the affinity-purified human 26S proteasome complex. Biochemistry 46:3553–3565. doi: 10.1021/bi061994u

275. Wang Y, Martinez-Vicente M, Krüger U, Kaushik S, Wong E, Mandelkow E-M, Cuervo AM, Mandelkow E (2010) Synergy and antagonism of macroautophagy and chaperone-mediated autophagy in a cell model of pathological tau aggregation. Autophagy 6:182–3

276. Waxman EA, Giasson BI (2011) Induction of Intracellular Tau Aggregation Is Promoted by α-Synuclein Seeds and Provides Novel Insights into the Hyperphosphorylation of Tau. J Neurosci 31:7604–7618. doi: 10.1523/JNEUROSCI.0297-11.2011

277. Weissman AM (2001) Themes and variations on ubiquitylation. Nat. Rev. Mol. Cell Biol. 2:169–178

278. Wickner W (2002) Yeast vacuoles and membrane fusion pathways. EMBO J 21:1241–1247

279. Williams KL, Warraich ST, Yang S, Solski JA, Fernando R, Rouleau GA, Nicholson GA, Blair IP (2012) UBQLN2/ubiquilin 2 mutation and pathology in familial amyotrophic lateral sclerosis. Neurobiol Aging 33:2527.e3-2527.e10. doi: 10.1016/j.neurobiolaging.2012.05.008

280. Wischik CM, Novak M, Th0gersen HC, Edwards PC, Runswick MJ, Jakes R, Walker JE, Milstein C, Rotht M, Klug A (1988) Isolation of a fragment of tau derived from the core of the paired helical filament of Alzheimer disease (molecular pathology/neurodegenerative disease/neurofibrillary tangles). Med Sci 85:4506–4510

281. Woltjer RL, Cimino PJ, Boutte AM, Schantz AM, Montine KS, Larson EB, Bird T, Quinn JF, Zhang J, Montine TJ (2005) Proteomic determination of widespread detergent insolubility, including A but not tau, early in the pathogenesis of Alzheimer’s disease. FASEB J 22:1–23. doi: 10.1096/fj.05-4263fje

282. Xia Q, Liao L, Cheng D, Duong DM, Gearing M, Lah JJ, Levey AI, Peng J (2008) Proteomic identification of novel proteins associated with Lewy bodies. Front Biosci 13:3850–6. doi: 10.2741/2973

283. Xu G, Pattamatta A, Hildago R, Pace MC, Brown H, Borchelt DR (2016) Vulnerability of newly synthesized proteins to proteostasis stress. J Cell Sci 129:1892–901. doi: 10.1242/jcs.176479

284. Xu G, Stevens SM, Kobiessy F, Brown H, McClung S, Gold MS, Borchelt DR (2012) Identification of Proteins Sensitive to Thermal Stress in Human Neuroblastoma and Glioma Cell Lines. PLoS One 7:1–13. doi: 10.1371/journal.pone.0049021

182

285. Xu G, Stevens SM, Moore BD, McClung S, Borchelt DR (2013) Cytosolic proteins lose solubility as amyloid deposits in a transgenic mouse model of alzheimer-type amyloidosis. Hum Mol Genet 22:2765–2774. doi: 10.1093/hmg/ddt121

286. Yanagawa Y, Ohhashi A, Murakami Y, Saeki Y, Yokosawa H, Tanaka K, Hashimoto J, Sato T, Nakagawa H (1999) Purification and characterization of the 26S proteasome from cultured rice (Oryza sativa) cells. Plant Sci 149:33–41. doi: 10.1016/S0168-9452(99)00140-5

287. Yang Z, Huang J, Geng J, Nair U, Klionsky DJ (2006) Atg22 Recycles Amino Acids to Link the Degradative and Recycling Functions of Autophagy. Mol Biol Cell 17:5094–5104. doi: 10.1091/mbc.E06-06-0479

288. Yang Z, Klionsky DJ (2009) An overview of the molecular mechanism of autophagy. Curr. Top. Microbiol. Immunol. 335:1–32

289. Yao T, Cohen RE (2002) A cryptic protease couples deubiquitination and degradation by the proteasome. Nature 419:403–407. doi: 10.1038/nature01071

290. Yerbury JJ, Ooi L, Dillin A, Saunders DN, Hatters DM, Beart PM, Cashman NR, Wilson MR, Ecroyd H (2016) Walking the tightrope: Proteostasis and neurodegenerative disease. J Neurochem 137:489–505. doi: 10.1111/jnc.13575

291. Yokota O, Davidson Y, Bigio EH, Ishizu H, Terada S, Arai T, Hasegawa M, Akiyama H, Sikkink S, Pickering-Brown S, Mann DMA (2010) Phosphorylated TDP-43 pathology and hippocampal sclerosis in progressive supranuclear palsy. Acta Neuropathol 120:55–66. doi: 10.1007/s00401-010-0702-1

292. Young CW, Robinson PF, Sacktor B (1963) Inhibition of the synthesis of protein in intact animals by acetoxycycloheximide and a metabolic derangement concomitant with this blockade. Biochem Pharmacol 12:855–865. doi: 10.1016/0006-2952(63)90116-3

293. Zhang NY, Tang Z, Liu CW (2008) α-synuclein protofibrils inhibit 26 S proteasome-mediated protein degradation: Understanding the cytotoxicity of protein protofibrils in neurodegenerative disease pathogenesis. J Biol Chem 283:20288–20298. doi: 10.1074/jbc.M710560200

294. Zhao J, Zhai B, Gygi SP, Goldberg AL (2015) mTOR inhibition activates overall protein degradation by the ubiquitin proteasome system as well as by autophagy. Proc Natl Acad Sci 112:15790–15797. doi: 10.1073/pnas.1521919112

295. Zhao R, Houry WA (2007) Molecular interaction network of the Hsp90 chaperone system. Adv. Exp. Med. Biol. 594:27–36

183

BIOGRAPHICAL SKETCH

Michael obtained his dual Bachelor of Science degree in neuroscience and biology from Indiana University in August of 2013. After working for one year in a laboratory studying Alzheimer’s disease at Indiana University, he then went on to pursue graduate studies at the University of Florida, beginning in August of 2014. He graduated with his Doctor of Philosophy in medical sciences with a concentration in neuroscience from the University of Florida in December of 2018.

Michael’s primary areas of professional interest lie in scientific writing and communication, improving the feasibility and outcomes of clinical trials, and maintaining up-to-date exptertise of new research developments in critical therapeutic areas, including neurology and oncology. His training began with his undergraduate research endeavors in the laboratory of Dr. Joseph Farley at Indiana University. While working for

Dr. Farley, he utilized electrophysiological techniques to elucidate the potential mechanism of the neurotoxicity of the amyloid beta (Aβ, more specifically Aβ 1-42) peptide that is known to aggregate in the pathogenesis of Alzheimer’s disease. This research led to the co-authorship of a Society for Neuroscience abstract, as well as a poster presentation at an Indiana University Psychological & Brain Sciences poster session. He then went on to pursue graduate research at the University of Florida.

During this time, he has focused on using proteomic, histological and biochemical approaches to study protein homeostasis in the context of neurodegenerative disease pathology in the laboratory of Dr. David Borchelt. Dr. Borchelt’s expertise in protein misfolding, protein biochemistry and neurodegenerative disease pathology has been invaluable in assisting Michael to conduct novel and innovative research in this field.

184

The Center for Translational Research in Neurodegenerative Disease at the University of Florida has provided a collaborative and innovative atmosphere that has helped further Michael’s education as an independent scientist. Throughout his graduate studies, Michael acquired expertise in new techniques as well as improved performance in other professional skills (e.g. public speaking, networking, and the critical analysis of biomedical research and literature). As a result of this, he was awarded a T32 training grant in Movement Disorders from Drs. David Vaillancourt and Dawn Bowers, which has further fosterd his professional development. Michael graduated with his PhD in

December of 2018, and has accepted a position as a feasibility research fellow at

Novella Clinical, a contract research organization. In this role, Michael will conduct feasibility research that will facilitate clinical trial success.

Michael has made many contributions to science throughout his career. During his time in the laboratory of Dr. Joseph Farley at Indiana University he pursued a project designed to elucidate the mechanism by which amyloid-β (Aβ) 1-42 causes neurotoxic effects on neurons in the brains of AD patients. The group’s hypothesis was that Aβ causes a disruption in calcium homeostasis and synaptic transmission prior to cell death through the suppression of the Kv1.1 potassium channel. The laboratory group Michael was involved in found, using two-electrode voltage clamp electrophysiology, that Aβ suppresses the activity of the Kv1.1 channel by as much as 50%, leading to further downstream intracellular cascades causing hyperexcitability and increased intracellular calcium levels. His role in this project was to conduct electrophysiology experiments as well as analyze the acquired data. This work is still progressing in the Farley laboratory, including transitions into single-channel electrophysiology work, and could lead to a

185

search for a therapeutic treatment to attenuate decreased Kv1.1 function when exposed to Aβ in Alzheimer’s disease.

Michael’s research as a graduate student has focused on protein misfolding in neurodegenerative diseases. More specifically, he assessed how the proteostasis network, which functions as a quality control system for proteins within cells, may be compromised in the context of disease. His central hypothesis was that primary protein aggregation pathologies, such as tau in Alzheimer’s disease or α-synuclein in

Parkinson’s disease, place a significant burden upon the proteostasis network which may compromise the folding of other bystander proteins. This, he believes, is what leads to the widespread instances of neurodegenerative disorders characterized by the misfolding of multiple protein species, leading to what are referred to as “mixed” proteinopathies. He has demonstrated this paradigm in multiple mouse models of neurodegenerative proteinopathies using both histological and shotgun proteomic approaches. This work has led to 4 total publications, 2 of which he served as first author.

During Michael’s first year as a graduate student at the University of Florida, he spent 6 weeks rotating in the laboratory of Dr. Marcelo Febo. During this he focused on unraveling the mechanism by which methylenedioxypyrovalerone (MDPV), a main constituent of “bath salt” drugs, causes psychostimulatory effects. “Bath salt” drugs are highly abused and addictive synthetic mixtures of various cathinones that are becoming more prevalent in drug markets. His role in this project was to determine if blocking dopamine receptors would prevent impaired functional connectivity in the brain that is

186

with the use of bath salt drugs. Interestingly, blocking D1/D2 receptors via the dopamine receptor antagonist α-flupenthixol did not alleviate the impaired functional connectivity, suggesting that MDPV acts through a neurotransmitter other than dopamine. This is significant given dopamine’s imperative role in the brain’s reward system and the rewarding effects of using “bath salt” drugs. This finding could change the approach of addiction research on “bath salt” drugs and led to a middle author publication.

187