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The effect of remyelination blockade on axon survival and damage in experimental autoimmune encephalomyelitis Brown, Douglas Robert 2018

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   THE EFFECT OF REMYELINATION BLOCKADE ON AXON SURVIVAL AND   DAMAGE IN EXPERIMENTAL AUTOIMMUNE ENCEPHALOMYELITIS    by    Douglas Robert Brown   B.Sc., Acadia University, 1987    A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF    MASTER OF SCIENCE   in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Zoology)     THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)   May 2018  © Douglas Robert Brown, 2018 			 ii	The following individuals certify that they have read and recommended to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: 	The Effect of Remyelination Blockade on Axon Survival and Damage in Experimental Autoimmune Encephalomyelitis.  Submitted by Douglas Brown in partial fulfillment of the requirements for the degree of Master of Science in Zoology.  Examining Committee: Supervisor -Professor Wolfram Tetzlaff Supervisory Committee Member- Professor Matthew Ramer Departmental Examiner- Professor Michael Gordon  Additional Supervisory Committee Members: Professor Jacqueline Quandt Professor Tim O’Connor 			 iii	Abstract Multiple sclerosis is the most common cause of neurologic disability in the developed world. A heterogeneous disease of unknown cause that most often presents in mid life, it is characterized by years of relapsing and remitting symptoms that eventually become progressive. The pathology of Multiple Sclerosis is characterized by resolving and non-resolving neurological deficits caused by axonal dysfunction and degeneration, which are mediated by both inflammation and demyelination.   Remyelination is an intrinsic myelin repair mechanism that replaces lost myelin in response to demyelination and mitigates its pathological effects. Experimentally, remyelination has been shown to promote axon survival in inflammatory demyelination contexts, however, it is unknown if blocking remyelination will result in increased axon loss and damage. Determining the importance of remyelination for axon preservation is necessary to determine the efficacy of remyelination therapies. Assessing the effect of blocked remyelination is an important part of this picture.   To determine this we used the rodent model of MS, Experimental Autoimmune Encephalomyelitis (EAE), to initiate demyelination, and blocked remyelination by inducibly deleting the gene Myelin Gene Regulatory Factor (Myrf) using the Cre-lox gene editing system. We then assessed axon survival and damage, myelination state, EAE disease severity and progression, microglial activation, and dorsal column size in the lumbar spinal cord of affected mice.   			 iv	We found that blocked remyelination did not affect axon survival or damage, but delayed EAE disease onset, reduced myelin in the ventral white matter and increase activation of microglia in affected areas. Strictly interpreted, our results suggest that remyelination may not be as important for axon survival as hypothesized. However, non-statistically significant trends in the results (Axon Loss p = 0.11 and Axon damage p = 0.15 in ventral/dorsal white matter combined) suggest that the lack of effect seen here may have been due to limitations and unforeseen problems encountered during these experiments. Unfortunately, these casts some doubt on our findings, but may highlight some previously unknown difficulties and effects such as delayed EAE induction and increased disease severity that may have been unintended consequences of the Myrf knock out, indicating that more investigation is warranted.    			 v	Lay Summary The	conduction	of	signals	along	nerves	allows	us	to	think,	speak,	remember,	breathe	and	move.	Nerves	relay	information	from	one	part	of	the	body	to	another,	similarly	to	 the	 way	 telephone	 lines	 relaying	 signals	 between	 cities.	 Like	 telephone	 wires,	many	nerve	fibers	are	 insulated,	wrapped	in	coating	known	as	myelin.	 If	myelin	 is	removed,	the	axon	like	a	wire,	may	eventually	deteriorate	and	die.			In	 Multiple	 Sclerosis	 the	 body’s	 immune	 system	 attacks	 its	 own	 myelin	 placing	axons	 at	 risk.	 Fortunately,	 an	 internal	 repair	mechanism	 replaces	 lost	myelin	 and	protects	axons.	Understanding	how	important	the	repair	mechanism	is	in	protecting	axons	is	essential.	To	investigate	this	I	gave	mice	a	laboratory	version	of	MS,	blocked	the	repair	mechanism	and	assessed	axon	survival.			I	 found	that	blocking	the	repair	mechanism	did	not	affect	axon	survival,	 indicating	that	it	may	be	not	be	as	important	in	preventing	axon	damage	as	previously	thought.					 vi	Preface Dr. Wolfram Tetzlaff and Dr. Jason Plemel generated the ideas and questions that led to these experiments. The method for genetic knock out of the Myrf gene and the generation of the transgenic mouse line used, was piloted and fine-tuned by Gregory Duncan.  The specific mouse lines, PDGFRα-Cre ERT2, Myrfflfl, and ROSA26-YFP were; obtained from Dr. Dwight Bergles  (John Hopkins University; Baltimore, MD, U.S.A.), Dr. Ben Emery (Oregon Health and Science University; Portland, Or, U.S.A.) and Dr. Ben Barres (Stanford University; Stanford, CA, U.S.A.) and Jackson Laboratories respectively. Mike Lee (technician), Aaron Mouslon (MSc), and Sohrab Manesh (MSc candidate) conducted the analytical blinding for these experiments.   Reagent sourcing, experimental planning, all animal care and experimental procedures, tissue collection and cryoprotection, tissue sectioning and immunostaining, tissue imaging and analysis, for 7 pilot experiments, the main experiment and an experimental extension were conducted by myself. Gregory Duncan and Aaron Moulson assisted in the inoculation of mice in the main experiment, and Gregory Duncan and Peggy Assinck assisted in the perfusion and spinal cord extraction in the main experiment. Dr. Tetzlaff, Gregory Duncan, and Aaron Moulson provided throughout critical feedback on experimental protocol, method, and analysis.  The work conducted for, and presented in this thesis was done with the approval of the University of British Columbia Animal Care Committee (U.B.C, A.C.C) in accordance 			 vii	with the Canadian Council on Animal Care (C.A.C.C.) under protocol A14-0229 - ‘EAE in Transgenic Mice Pilot Main Experiment (Version 2.0.).’ 			viii	Table of Contents  Abstract ......................................................................................................................................... iii	Lay Summary .................................................................................................................................v	Preface .......................................................................................................................................... vii	Table of Contents ...................................................................................................................... viiii	List of Tables .............................................................................................................................. xiii	List of Figures ............................................................................................................................. xiv	List of Abbreviations ............................................................................................................... xviii	Glossary ...................................................................................................................................... xxi	Acknowledgements ................................................................................................................. xxxii	Dedication ............................................................................................................................... xxxiv	Chapter	1:	Introduction ..............................................................................................................1	1.1	 Overview ................................................................................................................................1	1.2	 Multiple Sclerosis ..................................................................................................................2	1.2.1	 Epidemiology .............................................................................................................. 4	1.2.2	 Susceptibility-Modifying Factors ............................................................................... 4	1.2.2.1		Environmental Factors ........................................................................................... 4	1.2.2.1.1	 Geography/Latitude .............................................................................. 4	1.2.2.1.2	 Birth month/season ............................................................................... 5	1.2.2.1.3	 UV Exposure/Vitamin D ....................................................................... 6	1.2.2.2			Genetic Factors ...................................................................................................... 7	1.2.2.3			Infectious Agents ................................................................................................... 8	1.2.2.3.1	 Viral infection ....................................................................................... 8				 ix	1.2.2.3.2	 Bacterial Infection and the Gut Microbiome ........................................ 9	1.2.2.4			Gender ................................................................................................................. 10	1.2.3				Pathology ................................................................................................................... 10	1.2.3.1				Resolving and Progressive Deficits .................................................................... 10	1.2.4				Etiological Theories .................................................................................................. 11	1.3	 Myelin ...................................................................................................................................12	1.3.1	 Structure and Function .............................................................................................. 12	1.3.1.1			Saltatory Conduction ........................................................................................... 14	1.3.1.2			Myelin Plasticity and Remodelling ..................................................................... 14	1.3.1.3			Myelin Support of Axons .................................................................................... 15	1.3.2	 Myelination ............................................................................................................... 17	1.3.2.1			Developmental Myelination ................................................................................ 18	1.3.2.2			Adult Myelination ............................................................................................... 19	1.3.3	 Demyelination/Remyelination .................................................................................. 20	1.3.4	 Factors Affecting Remyelination .............................................................................. 20	1.3.4.1			OPC Differentiation ............................................................................................ 21	1.3.4.2			Neural activity ..................................................................................................... 21	1.3.4.3			Mechanical Signals ............................................................................................. 22	1.3.5	 Remyelination Inhibition and Failure ....................................................................... 22	1.3.6	 Myelin Gene Regulatory Factor (MYRF) ................................................................. 24	1.4	 Mechanisms of Demyelination Induced Axon Degeneration ..........................................25	1.4.1	 Structural Destabilization .......................................................................................... 25	1.4.2	 Glutamate Excitotoxicity .......................................................................................... 26				 x	1.4.3	 Energy deficit ............................................................................................................ 27	1.5	 Animal Models of Demyelination ......................................................................................27	1.5.1	 The Lysolecithin and Cuprizone models .................................................................. 28	1.5.2	 The EAE model ......................................................................................................... 28	1.6	 Research Hypothesis and Aims .........................................................................................30	Chapter 2 Methods and Results .................................................................................................33	2.1	 Experimental Methods .......................................................................................................33	2.1.1	 Mice .......................................................................................................................... 33	2.1.2	 Animal Model (EAE) ................................................................................................ 35	2.1.3	 Experimental Outline ................................................................................................ 36	2.1.4	 Animal Care .............................................................................................................. 40	2.1.5	 Genotyping ................................................................................................................ 40	2.1.6	 Tamoxifen Preparation and Administration .............................................................. 40	2.1.7	 CFA Concentration Adjustment ............................................................................... 40	2.1.8	 MOG 35-55 Emulsion Preparation ........................................................................... 41	2.1.9	 Pertussis Toxin Preparation ...................................................................................... 41	2.1.10	 EAE Induction .......................................................................................................... 41	2.1.11	 Behavioural Analysis ................................................................................................ 41	2.1.12	 Perfusion/Euthanasia/Tissue Harvesting and Cryoprotection .................................. 42	2.1.13	 Tissue Segmentation and Cryostorage ...................................................................... 43	2.1.14	 Cryosectioning .......................................................................................................... 43	2.1.15	 Immunohistochemistry ............................................................................................. 44	2.1.16	 Antibodies ................................................................................................................. 45				 xi	2.1.17	 Imaging ..................................................................................................................... 45	2.1.18	 Histological Analysis and Quantifications ................................................................ 46	2.1.19	 Image Thresholding .................................................................................................. 46	2.1.20	 Axon Counts ............................................................................................................. 47	2.2	 Analytic Methods ................................................................................................................47	2.2.1	 Behavioral Analyses ................................................................................................. 47	2.2.2	 Histological Analyses ............................................................................................... 48	2.2.2.1			% Myelin of Whole Cord White Matter .............................................................. 49	2.2.2.2			% Myelin of Ventral Lip White Matter ............................................................... 49	2.2.2.3			% Myelin of Focal Lesions ................................................................................. 50	2.2.2.4			DC Size ............................................................................................................... 51	2.2.2.5			Microglial Activation of Whole Cord Cross-section (20x) ................................. 52	2.2.2.6			Microglia Activation of Ventral White Matter (63x) .......................................... 53	2.2.2.7			Form Factor Analysis (FFA) of Microglial Ramification (63x) ......................... 54	2.2.2.8			DC and Ventral White Matter NF200+/SMI-312+ Axon Counts (63x) ............. 56	2.2.2.9			% SMI-32 + Axons in the DC and Ventral White Matter (20x) ......................... 57	2.2.2.10			SMI-32+ Axon Counts in the DC and Ventral White Matter (63x) .................. 58	2.3	 Statistical Analyses..............................................................................................................59	2.4	 Results ..................................................................................................................................60	2.4.1	 Behavioural Results: Remyelination blockade causes delayed EAE symptom presentation. .......................................................................................................................... 60	2.4.2	 Histological Results .................................................................................................. 62	2.4.2.1   Myelin: Remyelination blockade causes reduced myelin in the  			 xii	ventral white matter. ......................................................................................................... 62	2.4.2.2				DC Size: Remyelination blockade does not cause a reduction in DC size. ....... 65	2.4.2.3	 	 Microglial Activation: Blocked Remyelination causes increased microglial activation in affected areas. ............................................................................. 67 2.4.2.4				Axon Loss: Blocked Remyelination does not causes increased axon loss in the  DC or the Ventral White matter. ............................................................................ 71 2.4.2.5	 	 	Axon Damage: Blocked Remyelination does not cause increased axon damage in the DC or the Ventral White matter. ............................................................... 75 Chapter 3 Discussion and Conclusions ......................................................................................80	3.1	 Behavioural Analyses .........................................................................................................80	3.2	 Histological Analyses ..........................................................................................................83	3.3	 Limitations ...........................................................................................................................88	3.4	 Conclusions ..........................................................................................................................89 Bibliography .................................................................................................................................91 				xiii	List of Tables Chapter 2 Table 2.1 Primary Antibody definition and usage ........................................................................ 45	     																										xiv	List of Figures 	Chapter 2  Figure 2.1 Graphic representation of the transgenic constructs used, their function and the mechanism of the inducible Cre-lox system ................................................................................. 35 Figure 2.2 Genotypes, groupings, gender distribution, total number of mice inoculated and number of EAE >0 mice ........................................................................................................ 37  Figure 2.3 Experimental Overview .............................................................................................. 39 Figure 2.4 The Approved UBC EAE Scoring Scale, used to score EAE severity ....................... 42 Figure 2.5 Graphic representation of tissue segmentation, cryostat sectioning and immunostaining............................................................................................................................. 44 Figure 2.6 Graphic representation of myelin sampling, % MBP + of whole cord white matter analysis. ............................................................................................................................. 49 Figure 2.7 Graphic representation of myelin sampling, % MBP + area of ventral lip white matter analysis .............................................................................................................................. 50 Figure 2.8 Graphic representation of the identification of focal lesion location, and sampling for % MBP + area focal lesion analysis ........................................................................ 51 Figure 2.9 Graphic representation of DC and Whole cord area calculation and sampling for % area DC analysis ................................................................................................................. 52 Figure 2.10 Graphic representation of sampling for whole cord cross-section % IBA1+ area analysis. ................................................................................................................................. 53 Figure 2.11 Graphic representation of sampling for VWM % IBA1+ area analysis .................... 54 Figure 2.12 Graphic representation of single cell sampling of VWM IBA1 63x images for the FFA analysis ........................................................................................................................... 56 			 xv	 Figure 2.13 Sample images of IBA1 FFA quantification, showing A) activated, B) partially activated, and C) resting microglia ................................................................................. 57 Figure 2.14 Graphic representation of sampling and analysis for DC, VM and VL axon count analysis ................................................................................................................................ 58 Figure 2.15 Graphic representation of sampling and analysis for DC, and VWM for the % SMI-32+ area analysis .................................................................................................................. 59 Figure 2.16 Graphic representation of sampling and analysis for DC, VM and VL SMI-32+ axon count analysis ................................................................................................................ 60 Figure 2.17 Behavioural data results from inoculation ................................................................. 62 Figure 2.18 Behavioural data results from first symptom ............................................................ 63 Figure 2.19 MBP IHC Samples images ........................................................................................ 64 Figure 2.20 Sample images the focal lesion and ventral lip MBP staining in the lumbar spinal cord ..................................................................................................................................... 65 Figure 2.21 Myelin analysis and results ....................................................................................... 66 Figure 2.22 Graphic representation of % DC analysis and results ............................................... 67 Figure 2.23 IBA1 IHC samples images ........................................................................................ 70 Figure 2.24 Graphic representation of microglial sampling areas, example images, and analyses results .............................................................................................................................. 71 Figure 2.25 Sample images, analyses and results histograms of the Form Function analysis .......................................................................................................................................... 72 Figure 2.26 Nf200 and SMI-32 IHC Sample images of whole cord staining ............................... 74 Figure 2.27 Nf200 and SMI-312 IHC Samples images Nf200 and SMI-32 IHC of the ventral white matter ...................................................................................................................... 75 			xvi	Figure 2.28 Graphic representation of the axon count analysis image sampling and results ....... 76 Figure 2.29 SMI-32 IHC Samples images of the ventral white matter ........................................ 78 Figure 2.30 Graphic representation of axon damage count analyses ............................................ 79 Figure 2.31 Graphic representation of axon damage threshold .................................................... 80 	 			xvii	List of Abbreviations ACC –	animal	care	committee 	Adams4 – a disintegrin and metalloproteinase 4 Akt/mTor –	protein	kinase	B/mammalian	target	of	rapamycin AMPAR –	α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor cAMP –	cyclic	adenosine	monophosphate CC1 –	oligodendrocyte	marker CFA –	complete	Freund’s	adjuvant CNP – 2',3'-cyclic nucleotide 3'-phosphohydrolase CNS –	central	nervous	system CONT –	control Cre –	cre-recombinase Cre-lox –	cre–recombinase	coupled	with	LoxP	sites CreERT2 –cre-recombinase	with	an	attached	type	2	estrogen	receptor	 DNA –	deoxyribonucleic	acid DREADDs –	designer	receptor	exclusively	activated	by	designer	drugs	 EAE –	experimental	autoimmune	encephalomyelitis  EBV – Epstein-Barr virus  ECR9 - ecdysone receptor 9 ERK1/2 – extracellular signal–regulated kinases 1 and 2 FFA –	form	factor	analysis GluR4 –	glutamate	receptor	4 			xviii	GPR 17 –	G	protein	coupled	receptor	17 GPR 37 –	G	protein	coupled	receptor	37 GPR 56 –	G	protein	coupled	receptor	56 GWAS –	genome	wide	association	study HDAC –	histone	deacetylases	 HLA –	human	leukocyte	antigen IBA1–	ionized calcium-binding adapter molecule 1 IP –	intraperitoneal KO –	knock	out Krox-20 –	early growth response protein 2 LINGO-1 –	Leucine rich repeat and Immunoglobin-like domain-containing protein 1 MAG –	myelin	associated	glycoprotein	MAPK –	mitogen	activated	protein	kinase MBP –	myelin	basic	protein miRNA-219 –	microRNA	number	219 miRNA-338 –	microRNA	number	338 MOG 33-55 –	myelin	oligodendrocyte	glycoprotein	peptide	33-55 MS –	multiple	sclerosis  MT –	mycobacterium	tuberculosis MYRF – myelin gene regulatory factor (transcription factor)  Myrf –	myelin	gene	regulatory	factor	(gene) Myrf flfl –	floxed	myelin	gene	regulatory	factor NF200 –neurofilament	200 			xix	Nkx2.2 –	NK2	homeobox	protein	2 NO –	nitric	oxide NT3, and NT4/5 OCT-optimum cutting temperature compound OL –	oligodendrocyte Olig1 –	oligodendrocyte	transcription	factor	1	OPC –	oligodendrocyte	progenitor	cell PBS –	phosphate	buffered	saline PDGFRα –	platelet	derived	growth	factor	alpha PLP –	proteolipid	protein	PMD –	Pelizaeus-Merzbachers disease PPMS –	primary	progressive	multiple	sclerosis PSA-NCAM –	polysailylated-neural	cell	adhesion	molecule PtdIns (3,4,5) 3 –	phosphatidylinositol (3,4,5)-trisphosphate PTEN –	phosphatase	and	tensin	homologue Rag 1 –	recombination	activated	gene	1 RRMS –	relapse	and	remitting	multiple	sclerosis	 SJL –	swiss	jim	lambert Sox10 –	sex determining region - related high mobility group-box protein 10 Sox 5 – sex determining region - related high mobility group-box protein 5 SPMS –	secondary	progressive	multiple	sclerosis TAM –	tamoxifen TIFF –	tagged	information	file	format 			 xx	TMEV –	Theiler's	murine	encephalomyelitis	virus TPPP –	tubulin	polymerization-promoting	protein UBC –	University	of	British	Columbia UV –	ultra	violet	light VDR –	vitamin	D	receptor VDRE –	vitamin	D	response	element VGE –	ventral	ganglionic	eminence YY1–	yin	yang	1 ZFP191 –	zinc	finger	protein	191             				xxi	Glossary 1,25-(OH)2D3 or calcitriol, or 1,25-dihydroxyvitamin D3 -the active metabolite of  vitamin D with three hydroxyl groups. 2’-3’ cyclic nucleotide protein - an enzyme that is associated with CNS myelin, thought  to catalyze the phosphodiester hydrolysis of 2’-3’ cyclic nucleotides to 2'-cyclic  nucleotides. 7-dehydrocholesterol - a zoosterol that functions as a cholesterol precursor and is  converted to vitamin D3 in the skin. Action potential -the wave of membrane depolarization that begins in the axon initial  segment and propagates down the axon to its terminus. Its purpose is to trigger the release  of the appropriate neurotransmitter from axon presynaptic terminals. Active EAE induction - the induction of EAE by triggering a myelin based autoimmune  attack using a myelin peptide in CFA coupled with pertussis toxin.  Adaptive immune system - that part of the immune system that provides immunological  protection from specific pathogens. It is designed to attack and remember specific peptide  sequences of pathogenic agents. It is comprised primarily of antigen presenting cells, T-cells,  and B-cells.   Adult myelination- that myelin that has been generated after developmental myelination  has ended. Amoeboid - having the shape resembling an amoeba, generally irregularly spherical  AMPA receptor - an ionotrophic transmembrane receptor for the neurotransmitter  glutamate.  			xxii	Autoimmune - an adaptive immune system attack on an organism’s own cells.  Axon - the long slender extension of a neural cell body that conducts action potentials  away from the cell body. Axon degeneration - the continued regressive die back of axons toward the cell body  following initial transection. Axonal transection - the loss of continuity in the axon from the cell body to the axon  terminal due to loss of normal structural integrity. Axonal transport - the system by which necessary molecules are moved between the cell  body to the axon terminals, generally making uses of energy dependent cellular transport  mechanisms such as kinesins and dyneins. Bipolar morphology - a cellular morphology in which two processes extend from the  cell body, often diametrically opposed.  Cytotoxic CD8+ T-cells - T-cells that express the MHC I recognition complex and  function primarily to proteolytically kill cancers and virally infected self cells Channel rhodopsin - a rhodopsin molecule that functions as a voltage gated ion channel,  they have been used in neuroscientific research to stimulate neural activity with specific  wave lengths of light. Cis-regulatory element - regions on noncoding DNA that regulate the activity of  nearby genes.   Confocal microscopy - an optical imaging technique for increasing optical resolution  and contrast of a micrograph by means of adding an optical pinhole at the confocal plane 			xxiii	to eliminate out of focus light. Cre-recombinase - a tyrosine recombinase enzyme derived from the P1 bacteriophage  that catalyzes recombination at specific DNA sequences known as LoxP sites. Critical period - a maturational stage in the lifespan of an organism during which it is  especially sensitive to particular stimuli.  Cryostat - a device used to microsection tissue at cryogenic temperatures. Cuprizone - a copper chelating chemical compound also known as Bisclohexanone  Oxaldihydrazone. It is used experimental to cause spontaneous demyelination in the  corpus callosum and cerebellum. Delipidation - the disruption of cellular lipid membranes using a ascending series of  ethanol washes for the purpose of better antibody tissue penetration for  immunohistochemistry. Designer receptors exclusively activate by designer drugs - an extension on the receptor activated by a synthetic ligand (RASSL) concept. It allows spatiotemporal control of G  protein signaling in vivo. In neuroscience they have been used to alter neural activity  using a synthetic inert drug like protein.  Differention (cellular) - the process by which less specialized cells become more  specialized. Direct electrode stimulation - using electric current to stimulate neural activity.   DNA binding domain - a protein domain that recognizes and binds specific sequences of   DNA.  Dorsal column - an anatomical area of the dorsal part of the spinal cord that forms a "'V"  			xxiv	pointing from the peripheral medial dorsal cord toward the central canal. It is primarily made up of ascending sensory tracts with a small area of descending motor tract.  Encephalitis - a sudden onset of inflammation in the brain. Epigenetic - factors that affect the temporal and spatial control of gene transcription Excitotoxic –causing neuronal death or damage by overactivation of excitatory  neuroreceptors caused by excess glutamate. Excitotoxic cascade - the effect generated when the glutamate released following neuronal  death generated by an initial pathology causes the death and further release of glutamate from surrounding neurons; causing amplification of the initial pathological event. Exon - a segment of coding DNA that will generate a segment of the initial RNA message. Experimental Autoimmune Encephalomyelitis - an induced autoimmune attack on  CNS myelin, used experimentally as a model of demyelination and MS. Form Factor Analysis - a mathematic determination of the level of cellular ramification  Genome wide association studies - the examination of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a specific trait. GluR4 receptor - one of four types of glutamate receptor that causes fast synaptic  excitatory neurotransmission they are found in post synaptic membranes of neurons and  some glial cells. Glutamate - the predominant excitatory neurotransmitter in the vertebrate nervous system.  Glycosphingolipids - a lipid carbohydrate molecule that contains an amino alcohol  sophingosine involved in membrane organization and protein lipid interactions. Histone deacetylases - are deacetylases that remove acetyl groups from N-acetyl  			xxv	lysine amino acid on histone molecules, allowing the DNA to wrap more tightly around  the histone decreasing the likelihood of transcription. Image J software - image processing software.   In vivo - studies conducted on whole living organisms or cells within a living organism Inflammatory cytokines - signaling molecules generated during an immune response that  serve to increase inflammation and the immune response itself. Innate immune system - that part of the immune system that recognizes specific  pathogenic molecular epitopes and remembers them so that subsequent infections will be met more quickly. Intraperitoneal - into the peritoneum, often used to describe a type of injection. Jagged - a ligand in the Notch signaling pathway that promotes proliferation during  neurodevelopment. Juxtaparanodal region - the region of the axon that borders the inner side of the  paranode opposite the node itself. Kainate - ionotrophic non- NMDA receptors that respond to glutamate and kainate. Knockout group - the group that has the gene functionally deleted. LINGO-1 - a functional component of the NOGO receptor that is involved in neuronal differentiation, and growth as well as the regulation of myelination. LoxP sites - discrete sections of DNA that are binding targets for the enzyme  Cre-recombinase. Lumbar enlargement - the section of the lumber spinal cord where the lower limb  enervation connects with spinal cord resulting in a much larger diameter than the spinal  cord both rostral and caudal of it.  			xxvi	Macrophage - a leukocyte that is part of the innate immune system. It resides in tissues and eliminates pathogens and debris by phagocytosis. Meninges - three membranes that envelope the brain and spinal cord. Microbiome - the genomes of the combined  bacteria, fungi, Achaea, and viruses  that normally inhabit the human body. Microglia - a glial cell specifically found in the CNS. They function the resident  immune cells of the CNS similar to peripheral macrophages. Morphogens - a substance that causes patterned tissue development through graded  differences in its concentration. Mycobacterium Tuberculosis - a pathogenic bacteria that causes the disease tuberculosis. Myelin associated glycoprotein - a cell membrane protein commonly found in CNS myelin.  It functions as an adhesion molecule, and may be necessary for the structural integrity of  myelin. Myelin Gene Regulatory Factor - a transcription factor essential for the initiation of the myelination program in newly differentiated oligodendrocytes. Myelin oligodendrocyte glycoprotein - a cell membrane protein commonly found in  CNS myelin. It functions as an adhesion molecule, and may be necessary for the  structural integrity of myelin. Nerve growth factor - a neurotrophin involved in the regulation of growth, maintenance,  proliferation and survival of target neurons. Neurotrophin 3 and 4/5 - a family of growth factors that induce survival, development,  and growth.  			xxvii	Nodes of Ranvier - the areas on a myelinated axon devoid of myelin containing concentrated clusters of voltage gated ion channels. They are responsible for generating  saltatory conduction.  Nitric oxide - a free radical important in cellular signaling and vasodilation. It is  associated with inflammation in the CNS and the loss of mitochondrial membrane  polarity. Nogo - an inhibitor of neurite out growth in the CNS. Nonreceptor tyrosine kinase Fyn -a member of the protein-tyrosine kinase oncogene  family implicated in cell growth, neuronal and T-cell signaling. Notch - a single pass transmembrane receptor that promotes proliferation during  Neurogenesis. Oligodendrocytes - glial cells of the CNS that generate myelin and form the myelin  sheath. Optimum cutting temperature compound - an embedding compound used in tissue  cryosectioning. Outside-In Theory - the theory of MS etiology that proposes that the initial pathology  first occurs on the outer membrane "outside" of the myelin sheath mediated by an  immune attack on the myelin that causes subsequent "inside" axon pathology. Parabiosis - the surgical fusion of two animals allowing shared circulation  Paraformaldehyde - a tissue fixative that causes cross bridging of proteins preserving  the overall structure of the tissue. Paranodal region - the region of the myelinated axon adjacent to the node of Ranvier  			xxviii	rich in adhesion molecules.   Passive transfer EAE - the initiation of myelin protein targeted autoimmunity induced  by transferring activated T-cell from previously activated EAE animals Pelizaeus-Merzbachers disease - a genetic leukodystrophy that causes abnormalities in  the growth of the myelin sheath causing coordination problems, motor disability, and  decreased intellectual function. Peptide -a short segment of a protein.  Pericytes - cells that wrap around the endothelium of vennules and capillaries, they  regulate capillary blood flow, clearance of cellular debris and the permeability of the  blood brain barrier.  Pertussis toxin - a toxin produced by the bacterium Bordetella pertussis that causes  whooping cough. It is used in neuroscientific research for the induction of EAE.  Phosphatase and tensin homologue - a protein that inhibits molecules of the AKT  signaling pathway. pMN domain - a area of the early neural tube that produces motor neurons and  oligodendrocyte progenitor cells during development. Proinflammatory cells - a subset of immune cells that promote inflammation. PSA-NCAM - a neural adhesion molecule with a postranscriptionally added polysialic  acid that reduced cell adhesion. It is important in learning g and memory. Rag 1 mice - immunologically deficient mice that lack an enzyme necessary for the  generation of immunoglobulin and T- cell receptors.  Ramification - branching or out growth. 			xxix	  Recapitulation hypothesis - an hypothesis of remyelination that proposes that the  mechanisms of remyelination are generally a recapitulation of those that occur during  development. Receptor 1,25-(OH)2D-MARRS - a membrane associated rapid response steroid  receptor for calcitriol that is important for immune function affecting the assembly of the  MHC I molecule.  Remyelination - the process of generating new myelin sheath on sections of  demyelinated axon. Retinal ganglion cells - a type of neuron located near the inner surface of the retina of  the eye. Saltatory Conduction - the conduction of an action potential in a myelinated axon  characterized by jumping from one node to the next. It is faster and more energetically  efficient than non myelinated signal propagation.  Schwann cell - a cell that myelinates axons in the peripheral nervous system. Segmented filamentous bacteria - a bacteria that is a normal part of the gut microbiota  of many animals. It is known to affect the status of the immune system. Serum antibodies - are antibodies found in the serum, which is a component of the blood  left after coagulation.  Single nucleotide polymorphisms - a variation of a single nucleotide in a section of  DNA. They are thought to underlie differences in individual disease susceptibilities  and disease course.  			xxx	STOP codon -a nucleotide triplet in mRNA that signals the termination of translation.  Subarachnoid space - the interval between the arachnoid membrane and the pia mater. Tagged image file format - a computer file storage format for storing raster graphics  images that is popular among graphic artists. Tamoxifen - a medication used to prevent breast cancer, also used on the Cre-ERT2  inducible recombination system to initiate recombination. Telencephalon - the embryonic precursor of the cerebrum. Theiler’s murine encephalomyelitis virus - a single stranded RNA murine cardiovirus  virus used as a mouse model for studying MS. Transcription factor - a protein that controls the rate of gene transcription by binding to  specific DNA sequences and recruiting transcriptional machinery to the site. Transgenic mice -mice having genes from another unrelated organism. Valproic acid - a histone deacetylase agonist also known to increase levels of GABA in  the brain. Vitamin D - a fat soluble steroid responsible for absorption of calcium, magnesium,  phosphate and zinc. It is also implicated in some immunomodulatory mechanisms Vitamin D receptor -an nuclear hormone receptor that acts as a ligand induced transcription factor.  Vitamin D receptor response element - is a DNA sequence found in the promoter region  of vitamin D regulated genes. It allows vitamin D levels to control gene expression. Voltage gated ion channels - a class of transmembrane protein that form ion channels  that are activated by changes the electrical membrane potential near the channel. Yin Yang 1 - a transcription factor belonging to the GLI-Kruppel class of zinc-finger  			xxxi	proteins. It functions as repressor and activator of many proteins. It may be involved in  epigenetic histone modification. Z stack - a series of confocal microscopic images of a single location taken at specific intervals  through the vertical "Z" dimension of the tissue.  			xxxii	Acknowledgements  I acknowledge and thank my graduate supervisor Dr. Wolfram Tetzlaff for providing me with the opportunity to pursue my interest in neuroscientific research, his guidance throughout my project, and most importantly, his patience and support through some particularly difficult years are greatly appreciated.  I wish to thank my graduate committee members, Dr. Jacqueline Quandt, Dr. Timothy      O’Connor and Dr. Matthew Ramer for their critical input.   I would like to extend a special thanks to Dr. John Steeves for his guidance, friendship, and genuine concern for my well being and future.  I extend my gratitude to fellow members of the Tetzlaff laboratory for their scientific insights, personal camaraderie and good humor, including Dr. Oscar Siera, Dr. Brett Hilton, Gregory Duncan, Aaron Moulson, Sohrab Manesh, Dr. Peggy Assinck, Peter Tan, Nicole Janzen, Ward Plunet and Jie Liu.   I would also like to thank ICORD, the Department of Zoology, and U.B.C. staff/faculty for providing an excellent and well-run facility.    			xxxiii	I offer very special thanks, and acknowledge an enormous debt of gratitude, to Tim Mac Aree, whose gift to me was of a magnitude that cannot be expressed in words, and without whom I would not have completed this degree, or anything else.    Lastly, I would like to thank my brother Hilary Brown, who was constant throughout, listening, commiserating, supporting and encouraging me to continue during the moments when the goal appeared too distant to be attainable.   				xxxiv	Dedication  This is thesis is dedicated to my mother Agnes Susan Brown.   			 1	Chapter	1:	Introduction	1.1 Overview Experiments have shown that vertebrate myelin facilitates and regulates rapid action potential conduction (Moore et al., 1978; Morell and Norton, 1980; Kaplan et al., 1997), axon structural integrity and axonal metabolic support (Lappe-Siefke et al., 2003; Nave, 2010; Lee et al., 2012b).  In MS the loss of myelin coupled with the inflammatory environment (Redford et al., 1997; Shrager et al., 1998) can result in the temporary disruption of saltatory conduction (Morell and Norton, 1980; Felts et al., 1997; Sadeghian et al., 2016), breakdown of axonal structure and transport (Morfini et al., 2009), and dysregulation of axonal metabolism (Mahad et al., 2009). If they persist, these conditions can lead to irreversible axonal degeneration (Hohlfeld, 1997). The temporal combination of these pathologies is thought to lead to the permanent and resolving symptoms of MS (Lassmann et al., 2001; Lassmann, 2014; Mahad et al., 2015; Mallucci et al., 2015).  After a demyelinating injury or disease a robust remyelination response is thought to aid in axon survival and symptomatic recovery in relapse and remitting MS (RRMS). Unfortunately, this response wanes and eventually fails with age, exposing axons to chronic demyelination and increasing the likelihood of degeneration. (Compston, 2001). The extent to which remyelination mitigates axonal loss and by extension MS disease severity and progression is not well understood (Sim et al., 2002; Franklin and Ffrench-Constant, 2008; Franklin et al., 2012; Franklin and Goldman, 2015).  Determining this will be important in the development of future MS treatment strategies. 			 2	 Previous studies using the non-immune mediated demyelination protocols of lysolecithin and cuprizone and the same remyelination blocking method employed here, have indicated that remyelination aids in axon survival (Matsushima and Morell, 2001; Kipp et al., 2009). Here, by blocking remyelination and inducing immune-mediated demyelination, I have attempted to increase the clinical relevance of previous experiments and achieve a greater understanding of the effect of remyelination on axonal survival in an inflammatory demyelinating context. An inducible Cre-lox genetic knockout of the gene Myrf (Ben Emery et al., 2009; Bujalka et al., 2013; Li et al., 2013; Duncan et al., 2017) was used to functionally block remyelination, and an inflammatory demyelinating model known as Experimental Autoimmune Encephalomyelitis (EAE) (Stromnes and Goverman, 2006) was used to cause demyelination.  1.2 Multiple Sclerosis  Multiple Sclerosis (MS) is the most common neurodegenerative disease affecting the global population. It is a clinically heterogeneous disease of the central nervous system (CNS) involving both focal and diffuse inflammation, demyelination and varying axon loss (Poser, 1994; Lassmann et al., 2001). Symptoms can manifest over a varied time course, often beginning in middle age and extending into a patient’s seventies (Lassmann et al., 2001). To date, the etiology and exact pathology of MS are only partially understood (Trapp and Nave, 2008; Stys et al., 2012).   MS may present in several different patterns classified by the presentation of symptoms. The most common pattern, affecting nearly 85% of new patients, is RRMS. RRMS has a 			 3	mean onset age of 30 and is defined by sudden loss of varied neurological functions that relapse and remit over time; RRMS attacks can last from weeks to months but eventually remit. Over time RRMS relapses increase in severity and frequency and remit less frequently. Eventually, many RRMS patients may fail to remit and enter a phase known as SPMS, which is characterized by a more severe disease course, lack of remission, reduced inflammation and continued loss of neurological function (Ransohoff et al., 2015).   Primary progressive MS (PPMS) is a third, less common variant characterized by an average clinical onset 10 years later than RRMS, and initial deficits that are consistent with SPMS (Brück et al., 2002; Ransohoff et al., 2015). A fourth pattern, the Marburg variant, is the most severe form of MS. It occurs in a younger patient group and is characterized by a more aggressive and highly inflammatory monophasic initial attack that can result in death within 2 years. Because Marburg’s clinical and imaging presentation is similar to many brain tumors it is often misdiagnosed as such. The fifth variant of MS, known as clinically isolated syndrome (CIS), is the occurrence of a single symptomatic episode that is not followed by a second. Although most CIS patients never have a second attack, some develop RRMS later in life. A sixth, very rare presentation of MS is progressive-relapsing MS (PRMS). PRMS shares the disease course of PPMS with the addition of regular acute attacks of increased intensity (Kremenchutzky, 1999; Stys et al., 2012; Ransohoff et al., 2015). 			 4	1.2.1 Epidemiology Epidemiological studies have found that MS is relatively common in countries of northern latitudes, as well as some countries in the southern hemisphere (Giesser, 2016). The highest incidence in the world is found on the Orkney Islands, where the prevalence is 270 in every 100,000 (Pugliati et al., 2002). The incidence of MS is lower in equatorial populations in both hemispheres, and it is relatively rare in tropical and subtropical regions and most of Asia (Pugliati et al., 2002). MS is two to three times more prevalent in women than in men, and incidences are currently increasing more rapidly in women (Orton et al., 2006; Debouverie et al., 2007; Hirst et al., 2009).  1.2.2 Susceptibility-Modifying Factors Although the exact etiology of MS pathology remains unclear, some risk and susceptibility modifying factors have been identified (Lassmann, 2003; 2005; Witte et al., 2014; Mahad et al., 2015). They can be broadly categorized as those that are generated by the environment and those attributed to genetic factors. 1.2.2.1 Environmental Factors Genetic association studies have found connections between MS susceptibility and several gene mutations that point to a genetic etiology, however the lack of a Mendelian inheritance pattern in twin studies (Hauser and Oksenberg, 2006) suggests that the overall susceptibility is a function of genetic and environmental interactions.  1.2.2.1.1 Geography/Latitude The geographic variation in MS susceptibility has been well documented; MS incidences are higher with increasing distance from the equator and increasing levels of 			 5	socioeconomic development. The highest incidences occur in North America and Europe, at 140 per 100000 (Evans et al., 2013) and 108 per 100000 (Kingwell et al., 2013) respectively. The lowest incidences are found in sub-Saharan Africa and East Asia at 2 per 1000000 (Browne et al., 2014). Although the overall global incidence of MS is increasing, the effect of latitude appears to be diminishing, potentially due to the adoption of westernized lifestyles and diets in developing countries (Manzel et al., 2013).   Studies have determined that geographic susceptibility modification is not immutable. The susceptibility of an individual migrating between regions of differing disease incidences depends on age. Those migrating before approximately 15 years of age were found to acquire the incidence of their destination region; those older than 15 years retained the incidence of their original location (Dean and Elian, 1997). Interestingly, this has not been universally supported; contrary to expectations, a study of young adult UK/Irish immigrants to Australia showed reduced incidences of MS after migration. Thus implying that latitude may be only one of many factors that influence overall susceptibility (Hammond et al., 2000). 1.2.2.1.2 Birth month/season Birth month has also been epidemiologically implicated in MS susceptibility. A study of 40,000 MS patients from Scandinavia found that children born in November had a lower incidence of MS than those born in May (Willer et al., 2005).  This may be because mothers of children born in May in the northern hemisphere will have carried their infants during the period of minimal UV exposure, while those who gave birth in 			 6	November would have carried their infants during the annual period of maximal UV exposure (Willer et al., 2005).  1.2.2.1.3 UV Exposure/Vitamin D Many susceptibility-modifying factors may ultimately arise from differences in UV exposure and related Vitamin D production. UV light-regulated vitamin D production has been linked to latitude (Olsson et al., 2017), season, immune function (Ramagopalan et al., 2009; Munger et al., 2014) and protein transcription (Khanal and Nemere, 2007). Reduced UV exposure results in reduced Vitamin D synthesis which has been correlated with increased MS susceptibility at higher latitudes, although a mechanism is still lacking (Howard et al., 2016).   A study of MS susceptibility in northern Scandinavian populations has supported the involvement of Vitamin D, demonstrating a consistent increase in MS susceptibility with increasing latitude in all countries with the exception of Norway, perhaps because the abundance of Vitamin D-rich oily fish in the Norwegian diet compensates for the effect of reduced UV exposure (Manzel et al., 2013; Simpson and Taylor, 2014). More recently, the function of vitamin D has been further elucidated. In most animals Vitamin D3 is generated when UV light strikes the skin and photochemically converts 7-dehydrocholesterol into vitamin D3 by hydroxylating 7-dehydrocholesterol twice to yield the physiologically active 1,25-(OH)2D3 or calcitriol (Fernandes de Abreu et al., 2011).  Calcitriol can affect cells in two ways: rapidly, by binding to the Vitamin D membrane receptor 1,25-(OH)2D-MARRS, or more slowly and persistently, by binding the Vitamin 			 7	D receptor (VDR). The VDR is a member of the nuclear receptor family and in the brain regulates roughly a thousand genes (Khanal and Nemere, 2007; Pierrot-Deseilligny and Souberbielle, 2013; Munger et al., 2014).   Experiments have shown that single nucleotide polymorphisms in calcitriol-producing enzymes, the VDR or the vitamin D receptor response element (VDRE) genes correlate with increased MS susceptibility (Ramagopalan et al., 2009). Although the mechanism by which calcitriol affects MS susceptibility remains unknown, variation in UV exposure and related calcitriol production may explain other epidemiologically identified susceptibility factors such as geography/latitude (Browne et al., 2014), cultural/socioeconomic (Berg-Hansen and Celius, 2015), and also influence genetic susceptibility (Belbasis et al., 2015; Olsson et al., 2017). 1.2.2.2 Genetic Factors The fact that first-degree relatives of MS patients have a 35x greater likelihood of disease incidence than the general population has suggested a strong genetic contribution to MS susceptibility. Although this implies a heritable component, several factors may confound this conclusion (Ebers et al., 1995). One theory suggests that familial MS clustering is a result of the shared familial environment rather than genetics; however, spouses (Sadovnick et al., 2000), stepsiblings (Dyment et al., 2006), and adoptees (Ebers et al., 1995) share this environment but not the susceptibility, weakening this argument. Additionally, genome-wide association studies (GWAS) have identified 108 genetic variants associated with increased MS incidence (Beecham et al., 2013), the majority of 			 8	which are commonly seen in other autoimmune diseases and are allelic variants of genes that regulate immune function (Cotsapas and Hafler, 2013).  1.2.2.3 Infectious Agents Infectious agents were first suspected of modulating MS susceptibilities when it was discovered that MS prevalence rose in geographic areas of low susceptibility after disease epidemics (Kurtzke and Hyllested, 1979). Infectious diseases that have been correlated with MS include measles (Sibley and Foley, 1965), mumps (Millar et al., 1971), rubella (Horikawa et al., 1973), varicella-zoster (Ross et al., 1965) and the Epstein-Barr virus (EBV) (Sumaya et al., 1980).  1.2.2.3.1 Viral infection Of the infectious agents associated with MS the EBV has the strongest correlation. Serum antibody sampling of MS patients has revealed a 99%-100% incidence of EBV versus a 90% in the general population (Ascherio and Munch, 2000; Pakpoor et al., 2013). EBV, a member of the Herpes family of viruses also known as Human Herpes Virus 4, is responsible for the disease condition known as Infectious Mononucleosis. EBV is one of the most ubiquitous viruses found in the human population and has been associated with other autoimmune diseases. Evidence of its involvement in MS includes shared peptide sequences between EBV and myelin proteins, suggesting possible molecular mimicry (Lang et al., 2002), and the prevalence of EBV reactive CD8+ T-cells in MS patients with active disease (Angelini et al., 2013).    			 9	1.2.2.3.2 Bacterial Infection and the Gut Microbiome  Although not as prominent as viral infections some bacterial infections have also been shown to modulate immune responses and have been implicated in MS susceptibility. The effect of microbiota has been demonstrated by the discovery that in germ-free environments relapsing and remitting EAE cannot be initiated (Berer et al., 2011) and mice with only segmented filamentous bacteria in their guts can develop EAE spontaneously.   Maintaining the normal balance of microbiotic gut content requires an immune tone that is active enough to eliminate pathogenic infections and passive enough to maintain levels of microbiota beneficial to optimal digestive function (Glenn and Mowry, 2016). Most of the bacteria that influence EAE susceptibility are normal constituents of the rodent gut microbiota, suggesting that an imbalance in normal gut flora, rather than an external pathogenic infection, is likely responsible for changes in MS susceptibility. As exposure of the fetus to maternal gut and milk microbiota aids in the initial gut colonization during vaginal birth and breast feeding, abnormal gut colonization dynamics attributed to delivery by cesarean section and bottle feeding have been associated with increased MS susceptibilities(Fernández et al., 2013). Mechanistically, it is thought that a microbiotic imbalance may cause resident bacteria to produce interleukin 17 (IL-17), a proinflammatory cytokine, that can increase inflammation and the likelihood of an autoimmune attack (Lee et al., 2011; Glenn and Mowry, 2016). 			 10	1.2.2.4 Gender	Epidemiological studies have shown that MS has a higher prevalence but lower severity in women. Sex hormones may create differences in immune system responses, the blood brain barrier and the resident CNS immune cells, which may account for the increased susceptibility. Hormonal changes during pregnancy have been linked with improvements in MS symptoms (Saraste et al., 2007) and clinical studies indicate that sex steroid supplementation may be beneficial for MS, possibly due to anti-inflammatory influences on the immune system (Nicot, 2009; Bove and Chitnis, 2013). Currently, many aspects of gender mediated MS susceptibility are being investigated both clinically and experimentally.  1.2.3 Pathology	MS results from a layering of pathological effects that arise from a combination of the inflammatory environment, demyelination,	 remyelination, and axonal degeneration (Lassmann, 2014). The resultant neurological deficits lead to a heterogeneous blend of cognitive, motor and sensory symptoms that define the various forms of MS. These symptoms can be grossly divided into resolving deficits and progressive deficits based on the presence or lack of remission and the related underlying pathology (Barnett and Prineas, 2004; Papadopoulos et al., 2006).  1.2.3.1 Resolving and Progressive Deficits RRMS is characterized by intermittent inflammation that correlates with the appearance and resolution of neurological symptoms mediated by the disruption and recovery of axon signal propagation. These deficits are thought to result from the effects of transient inflammation and demyelination on axon function. The remission of symptoms is 			 11	believed to be due to the recovery of axon function associated with the resolution of inflammation and remyelination of demyelinated axons (McDonald and Sears, 1970; Youl et al., 1991; Moreau et al., 1996; Trapp and Nave, 2008). However, if demyelination and/or inflammation persist chronically, as in SPMS, axons may be stressed beyond the point of recovery and irreversible degeneration can occur. The symptoms generated by axon degeneration are permanent and constitute the progressive neurological deficits of MS (Lublin et al., 2014; Kuhlmann et al., 2016).  1.2.4 Etiological Theories Historically, the majority of MS researchers have accepted myelin-based autoimmunity as the underlying cause of MS, resulting in an immunomodulatory bias in MS research and treatment. However, the failure of immunomodulation to generate long-term treatments or a cure has prompted some researchers to propose alternate theories. The field is now divided into those who favour the original Outside-In (autoimmune) theory or the more recent Inside-Out (degenerative) concept (Hauser and Oksenberg, 2006; Trapp and Nave, 2008; Stys et al., 2012).  Support for the Outside-In theory includes a tight correlation between inflammation and demyelination, the preponderance of associated susceptibility genes’ being immuno-modulatory in nature and dense adaptive immune cell infiltration in the subarachnoid space and meninges of MS patients (Magliozzi et al., 2010; Howell et al., 2011). Proponents of the Inside-Out model point out that inflammation and/or adaptive immune activation are not present in all stages of MS despite continued myelin and axon degeneration, myelin degeneration appears to begin in the myelin wraps closest to the 			 12	axonal surface (rather than the outside wraps as would be expected in an autoimmune attack) (Rodriguez and Scheithauer, 2009), in the early stages of demyelination the  loss of the myelin associated glycoprotein (MAG) occurs first in the inner wraps of the myelin sheath (Aboul-Enein et al., 2003), and finally that myelin ultra-structural damage has been found in areas with no inflammation, suggesting that demyelination may proceed inflammation (Rodriguez and Scheithauer, 2009). Until further mechanistic research can clarify the etiology of MS the debate will continue.  1.3 Myelin In 1858, Rudolf Virchow, a German physician and medical science pioneer, intuitively predicted the presence of myelin and coined the term before there was any evidence of its existence. Subsequent research has confirmed his insight and further illuminated both the structure and function of myelin (Simons and Nave, 2015a).  1.3.1 Structure and Function Myelin exists in both the central and peripheral nervous systems. Although similar in function and basic structure, their developmental origins, generating cells and fine structure are different (Nave and Werner, 2014). In the CNS, myelin is the product of specialized cells called OLs that increase their plasma membrane enormously, and generate multiple (as many as 50) myelin sheaths or internodes (Morell and Norton, 1980). A single internode is composed of multiple layers of OL plasma membrane that wrap around a discrete length of the axon, spiraling inward toward the axonal surface. On myelinated axons, internodes are arranged sequentially along the longitudinal axis, much like elongated beads on a string. Between each individual internode there are short 			 13	sections of unmyelinated axon known as nodes of Ranvier (Bunge, 1968; Morell and Norton, 1980; Sobottka et al., 2011).   The nodes of Ranvier, or nodes, contain specialized architecture both within the node itself and in the paranodal, and juxtaparanodal areas flanking it. Adhesion proteins in myelin loops on the lateral ends of each myelin internode interact with adjacent axonal surface, anchoring the myelin wraps and defining the architecture of the node and internode. Voltage gated ion channels are clustered in the axon membrane at the nodes and are responsible for metering ion flow, which renews the action potential as it “jumps” from node to node in a form of signal propagation known as saltatory conduction (Duflocq et al., 2008; Black et al., 2012). Myelin facilitates saltatory conduction by aiding in nodal development, increasing axon membrane resistance and decreasing capacitance allowing faster and more energetically efficient signal propagation (Rasband and Peles, 2015).   Although cytoplasm-poor myelin is protein-rich, normal myelin contains several key proteins necessary for its generation and function (Bunge, 1968; Morell and Norton, 1980; Simons and Nave, 2015a). Because generating the vast amounts of plasma membrane and protein needed for myelination is energetically expensive it is not surprising that, unlike other metabolically active membranes, myelin is relatively stable (Aggarwal et al., 2011) Both the lipid and protein constituents have been shown to have extremely long half-lives (Smith and Eng, 1965; Toyama et al., 2013) and myelin as old as 5000 years has been found to have intact ultrastructure (Hess et al., 1998). 				 14	1.3.1.1 Saltatory Conduction  Fast axonal conduction is beneficial for organism survival, imparting a selective survival advantage by increasing the speed of recognition and response to threat and prey (Dubois-Dalcq et al., 2008; Castelfranco and Hartline, 2016). Physiologically, action potential propagation speeds can be increased in two ways: by increasing axon diameter and/or through some form of myelination. Many invertebrates, are amyelinate and achieve fast conduction by selectively enlarging behaviour-specific axons or through a rudimentary form of myelination (Hartline and Colman, 2007). However, in vertebrates, CNS growth is spatially constrained by the evolution of the skull and spinal column, making enlarging axons impractical. The development and refining of myelin provided a spatially efficient means of increasing signal propagation speed and energy efficiency (Zalc and Colman, 2000; Dubois-Dalcq et al., 2008; Castelfranco and Hartline, 2016).  1.3.1.2 Myelin Plasticity and Remodelling Neuroplasticity is the ability of the CNS to adapt both structurally and physiologically to environmental stimuli in order to maximize efficiency and optimize function, and it is necessary for learning and memory (Zatorre et al., 2012). Although maximizing signal conduction speed is important for some neuronal functions, in many higher functions precise signal timing is more important. Neural networks rely heavily on the synchrony or asynchrony of signals to function effectively. Adult myelination and myelin remodelling are thought to aid in overall system plasticity; the addition or removal of myelin internodes, and changes in myelin thickness can alter signal speeds, essentially fine-tuning the network. Changes in the myelination status of a given circuit can either optimize it or, as in the case of pathological demyelination, disrupt it (Chang et al., 2016). 			 15	 Recent work supporting of the involvement of adult myelination and myelin remodelling in system plasticity has shown that: some axons in the cortex are only partially myelinated (Tomassy et al., 2014), many axons  below 0.8 µm in diameter are wholly unmyelinated (Hildebrand et al., 1993), mature oligodendrocytes do not generate new myelin sheaths after a short period following differentiation (Watkins et al., 2008; Czopka et al., 2013), and OPCs are broadly distributed throughout the CNS (Richardson et al., 2011; Zatorre et al., 2012; Wang and Young, 2014; de Hoz and Simons, 2015). These findings suggest that the unmyelinated axon segments may be substrates for OPC mediated myelin plasticity and are supported by a recent study of irregular wheel running in adult mice demonstrating that an increase in OPC proliferation and newly generated OLs was correlated with better wheel performance, which was lost when adult myelination was blocked (McKenzie et al., 2014).  1.3.1.3 Myelin Support of Axons	The neurological functions necessary for cognition, learning and memory (Richardson et al., 2011; Zatorre et al., 2012) and sensation and motor function, utilize significant metabolic resources (Zatorre et al., 2012; Chang et al., 2016). Because some axons are far removed from their cell bodies, normal cellular transport speeds may not be sufficient to meet the metabolic demands. For example, glycolytic enzymes necessary for metabolism would degrade before reaching their targets if delivered from the cell body. This implies that there may be an alternate, more timely, means of achieving the necessary metabolic support (Brady and Lasek, 1981; Yuan et al., 1999)  			 16	The intimate nature of the myelin axonal interface makes OLs and myelin an excellent candidate for local axon support. It has been shown that myelin is critical for the health of some axons, and that loss of myelin can lead to energy deficits resulting in axon degeneration and loss (Brady and Lasek, 1981; Yuan et al., 1999). The reliance of axons on OLs has been demonstrated in both mouse models and humans (Nave and Trapp, 2008). Deletion of important structural myelin proteins 2’-3’ cyclic nucleotide protein (CNP) (Griffiths et al., 1998; Lappe-Siefke et al., 2003), and proteolipid protein (PLP) (Edgar et al., 2004), both experimentally and in Pelizaeus-Merzbachers disease (PMD) (Garbern et al., 2002) has led to axon degeneration.   Determining the viability of remyelination as a therapeutic target for demyelinating diseases such as MS, requires an understanding of the involvement of myelin based axonal support in axon degeneration. Because inflammation and demyelination occur nearly simultaneously in MS, the respective roles of the loss of supporting myelin and inflammation induced energy deficit in axon degeneration are unclear. To clarify this, researchers assessed axon survival following genetically induced demyelination in immunologically deficient Rag 1 mice. The results indicated that axons were lost when demyelinated even in the absence of inflammation suggesting that demyelination alone is sufficient to cause axon degeneration (Pohl et al., 2011). Furthermore, human clinical studies that have shown axonal sparing in areas of remyelination in human MS patients (Kornek et al., 2000).  			 17	Mechanistically it has been suggested that myelin may support axons by shuttling by shuttling lactate produced in astrocytes to the axonal surface via myelinic channels. Studies have shown that OLs express the monocarboxylate transporter 1 (MCT 1), the most abundant lactate transporter in the CNS, at higher levels than other cell types, and that disruption of this transporter results in axon damage and neuronal loss (Lee et al., 2012b; Morrison et al., 2013). 1.3.2 Myelination Myelination is the highly controlled process of generating myelin sheaths, carried out by specialized cells known as OLs. Myelination begins shortly following differentiation of OPCs into OLs and follows a strict pattern. It begins with the extension of OL processes, which, upon contact with axons, begin to flatten into sheets and wrap around it. The wraps’ lateral edges then elongate down the length of the axon and compact, juxtaposing layers of membrane and extruding the majority of the cytoplasm and extracellular fluid. Myelin compaction is considered the final stage of myelination and is a marker of mature myelin (Sherman and Brophy, 2005; Nave and Werner, 2014; Bercury and Macklin, 2015; Rasband and Peles, 2015; Simons and Nave, 2015b; Chang et al., 2016).   Myelination can be divided into two categories based on when it occurs during the life span: developmental myelination (Jessell, 2000) and adult myelination (Franklin and Ffrench-Constant, 2008; Fancy et al., 2011; Chang et al., 2016). Developmental myelination begins in the embryo, following axon extension (Noll and Miller, 1993) and continues until completion of prefrontal myelination in the second decade. Although 			 18	developmental myelination ends here, myelination in general continues throughout life and is termed adult myelination thereafter (Yeung et al., 2014).   Adult myelination can be divided into two sub-categories, de novo myelination, or myelination of previously unmyelinated tracts (Fields, 2008), and remyelination, myelination which occurs after a demyelinating insult, such as disease or injury (Fancy et al., 2011). Most of what is known about myelination has been gleaned from experiments carried out during development: hence, much more is known about developmental myelination than adult myelination. This has led to the recapitulation hypothesis of remyelination (Fancy et al., 2011) which postulates that the mechanisms involved in adult remyelination are a recapitulation of those during development. However, differences between the developmental and the adult milieu may present difficulties in applying developmental findings to adult myelination.  Therefore, a deeper understanding of adult myelination will be necessary before remyelination can be manipulated therapeutically. Such understanding may make it possible to induce remyelination where it has failed, such as in late stage MS, potentially forestalling the conversion of RRMS to SPMS (Franklin and Ffrench-Constant, 2008; Kuhlmann et al., 2008; Fancy et al., 2010; Taveggia et al., 2010). 1.3.2.1 Developmental Myelination Developmental myelination occurs in discrete steps that include oligodendrocyte progenitor cell (OPC) generation, migration, proliferation, terminal differentiation into OLs, and generation of myelin sheaths (Chang et al., 2016). In development, OPC’s originate in the second wave of cellular specification from the pMN domain of the early 			 19	neural tube (Kessaris et al., 2001; 2006). The pMN domain is defined by the cells that it produces, which is determined by a system of cross repressing transcription factors that are generated by the dorso-ventral concentration gradient of the morphogens Bone Morphogenic Protein (BMP) and Sonic Hedge Hog (SHH) (Kessaris et al., 2001).  Following specification, progenitors must migrate to predetermined areas where they will differentiate into OLs. In the spinal cord progenitor cells migrate laterally and dorsally to white matter tracts, differentiate and begin to myelinate axons (Rowitch, 2004). In the telencephalon, the first wave of ventrally derived precursors migrate outward to all areas; however, unlike in the spinal cord, two later waves of more dorsally derived progenitors join the first wave making the final forebrain OPC population a mixture of precursor cells derived from all three areas (Kessaris et al., 2006). 	Many factors are involved in the activation and control of OPC differentiation and subsequent myelination. These include the microRNAs, miRNA-219 and miRNA-338, that initiate differentiation by inhibiting the differentiation repressing transcription factors Sox5/6, Hes5, and PDGFRα (Dugas et al., 2010; Zhao et al., 2010). Other factors involved in OPC differentiation include the transcription factors MYRF, Sox10, Nxk2.2, Olig1, YY1, and Zfp1. Although these and other factors have been identified, how they interact during myelination is still not well understood (Simons and Nave, 2015a). 1.3.2.2 Adult Myelination In contrast to developmental myelination, adult myelination begins with OPCs already in place in the brain parenchyma. OPCs monitor the internal CNS environment for signals of neuronal activity, damage, disease or demyelination and are responsible for both de 			 20	novo myelination and remyelination. When the appropriate signals are received, OPCs migrate toward the source, proliferate, differentiate into OLs (Hughes et al., 2013) and begin the myelination process (Nave and Werner, 2014; Chang et al., 2016).  Adult myelin internodes differs from developmental myelin in that they are generally shorter and thinner (Blakemore, 1974; Stidworthy et al., 2006) and unlike developmental myelin, axon diameter and myelin thickness are not correlated (Franklin and Hinks, 1999). One proposed explanation is that during development, myelin first associates with axons before they have achieved their final diameter. Thus, developmental myelin may thicken during axon growth and maturation, reaching its final diameter before adult myelination can occur (Franklin and Hinks, 1999). 1.3.3 Demyelination/Remyelination  Demyelination of myelinated axons causes the loss of saltatory conduction and metabolic support, and changes axon structure (McDonald and Sears, 1970). Acutely, this results in a loss of axon connectivity and a consequent temporary loss of normal function. Timely remyelination during the acute phase of demyelination can restore normal axon conduction and health. However, delayed or failed remyelination can lead to chronic demyelination and axon degeneration (McDonald and Sears, 1970). In contrast to de novo myelination, remyelination is adult myelination that occurs in response to demyelination or normal OL turnover (Fancy et al., 2011) (Yeung et al., 2014) (Smith et al., 1979).  1.3.4 Factors Affecting Remyelination Like developmental myelination, remyelination is a very complex process involving mechanisms needed to induce and control many cellular processes. These include the 			 21	migration, proliferation, and differentiation, of OPCs and the generation of large amounts of membrane and proteins by OLs. Successful remyelination involves coordinated interaction of the factors that control these processes as well as many cellular pathways and pathway-associated factors (Franklin and Goldman, 2015).  1.3.4.1 	OPC Differentiation  OPC differentiation is controlled by both internal and external cellular factors. Internally, the up-regulation of the transcription factors; Myelin Gene Regulatory Factor (MYRF), Nkx2.2, Olig1, Sox10, YY1, and ZFP191 (He et al., 2007; Flores et al., 2008; Ben Emery et al., 2009; Harrington et al., 2010; Howng et al., 2010; Bujalka et al., 2013; Ishii et al., 2014) promote differentiation. Externally, cell surface receptors influence OPC differentiation; ligand binding of two g-coupled receptors (GPR), GPR 37 and GPR 17 has been shown to negatively regulate OL differentiation (Chen et al., 2009; Hennen et al., 2013).  1.3.4.2 Neural activity  Neural activity has been found to be a key factor in regulating adult de novo myelination. Experimental results in rehabilitation and selective axonal activation have shown that axonal activity correlates with system plasticity (Bliss and Collingridge, 1993) and subsequent myelination. Supporting evidence includes the direct synaptic connection between OPC and axons (Bergles et al., 2000) the positive correlation between  retinal ganglion cell activity and OPC proliferation (Barres and Raff, 1993) and the generation of new myelin (Demerens et al., 1996; Gibson et al., 2014). Experiments using; direct electrode stimulation (Li et al., 2010), chemostimulation through designer receptors exclusively activate by designer drugs (DREADDs) (Lim et al., 2016), light stimulated 			 22	activity through channel rhodopsins (Gibson et al., 2014), random neural firing in vision and or hearing without external stimulus (Wang et al., 2015) and rehabilitation training (McKenzie et al., 2014) have further supported this concept. Promoting neuronal activity as a means of encouraging remyelination after disease or injury is being investigated and may prove useful in treating demyelinating diseases.  1.3.4.3 Mechanical Signals The signals that control myelination are not confined to external secreted receptor-ligand or internal cellular mechanisms. Both OPCs and OLs show sensitivity to environmental mechanical signals. In order to separate the effects of mechanical and secreted receptor ligand signalling, in vitro experiments were conducted using inert substrates rather than neural co-cultures. In the absence of other in vivo signalling factors, it was found that OPC proliferation can be influenced by density cues elicited by the size and density inert nanospheres (Rosenberg et al., 2008). Mechanical signals were also shown to be important in the decision to myelinate; in the absence of other in vivo signals OLs preferentially myelinate inert nanofibers above 0.4 µm in diameter. This agrees with observations that in vivo axons less than 0.4 µm in diameter are rarely myelinated and suggests that mechanical signals derived from the radial curvature of an axon’s outer surface may influence remyelination (Lee et al., 2012a). Interestingly, this effect was lost with the deletion of the nonreceptor tyrosine kinase Fyn (Umemori et al., 1994), suggesting that it may be important in determining the myelination status of some axons.  1.3.5 Remyelination Inhibition and Failure   Remyelination efficiency has been shown to diminish and eventually fail with age (Franklin, 2002; Fancy et al., 2010). As the remyelinating response wanes demyelinated 			 23	axons are exposed to longer periods of energetic stress and become more likely to irreversibly degenerate (Lovas et al., 2000). Many age-related changes in cellular function have been implicated in this process, including reductions in overall OPC numbers (Sim et al., 2002), recruitment (Kiernan et al., 1996) and differentiation efficiency (Kuhlmann et al., 2008; Shen et al., 2008), immune function and epigenetic transcriptional regulation. More recently, OPC differentiation failure has become a focal point in remyelination failure research (Woodruff et al., 2004; Kuhlmann et al., 2008).  Supporting experiments showed that the parabiotic connection of the circulation of young and old rats reduced the aged-related remyelination delay in the aged rats and restored a younger remyelinating phenotype, implicating a blood-borne factor (Conboy et al., 2005; Ruckh et al., 2012). Age-related changes in immune cell function have also been shown to indirectly affect remyelination. Activated macrophages/microglia in young animals respond rapidly to the presence of cellular debris. However, in aged animals, this response is reduced, resulting in the accumulation of cellular debris which can trigger a heightened pro-inflammatory cytokine release from macrophages and surrounding glial cells. This pro-inflammatory milieu can inhibit OPC differentiation and by extension remyelination (Zhao et al., 2006).  Epigenetic factors have also been implicated in age related remyelination failure. Age-related reductions in HDAC recruitment to the differentiation inhibitors GRP 17 and GPR 37 results in their prolonged expression and delayed OPC differentiation. HDACs deacetylate the GRP 17 and GPR 37 genes blocking their transcription and releasing the 			 24	OPC from differentiation inhibition (Marin-Husstege et al., 2002). Experiments using the HDAC antagonist Valproic acid have reproduced age-related remyelination decline in young animals after chemical demyelination (Shen et al., 2008). Lastly, the OPCs of younger animals migrate and differentiate more quickly in response to trophic cues than their older counterparts, suggesting that aged OPC have an attenuated ability to respond to trophic factors which causes slowed or failed migration that may delay remyelination (Tang et al., 2000; Chari et al., 2003).  Although these factors aid our understanding of age-related remyelination failure, they represent only a small piece of the picture. A more complete understanding will be necessary before it may be possible to prevent remyelination failure and possibly forestall the conversion of RRMS to SPMS. 1.3.6 Myelin Gene Regulatory Factor (MYRF)  The discovery that the transcription factor early growth response protein 2  (EGR2 or Krox20) as both sufficient and necessary for myelin gene transcription in Schwann cells in the peripheral nervous system (Topilko et al., 1994; Nagarajan et al., 2001) led to speculation about the existence of an analogue  in the CNS (Ben Emery et al., 2009). In transcriptome analysis of isolated neuron, astrocytes and OL cultures, a single gene (then named gene model 98, later designated MRF, and, finally Myrf) was expressed only in postmitotic OLs (Cahoy et al., 2008). Biochemical investigation revealed that MYRF, the product of the gene Myrf, is in fact a homotrimeric membrane protein with an N-terminal Ndt80 DNA binding domain that autoproteolytically cleaves upon trimerization, yielding an N-terminal fragment with a nuclear localizing site. This fragment can enter the nucleus 			 25	and bind to many cis-regulatory elements of multiple OL-specific genes, mediating the differentiation of OPC and the initiation of myelination (Bujalka et al., 2013; Li et al., 2013).  MYRF is required for the expression of genes associated with OL maturation (Ben Emery et al., 2009) and necessary for the ongoing expression of myelin proteins and the early OL marker adenomatous polyposis coli (APC). Experiments conditionally ablating MYRF from mature OLs have shown demyelination, inflammation and microglial activation, and axon damage, confirming that ongoing expression of MYRF is necessary for maintenance of mature myelin and OL identity (Koenning et al., 2012). More recently MYRF has been shown to drive remyelination after chemically induced demyelination (Duncan et al., 2017). 1.4 Mechanisms of Demyelination Induced Axon Degeneration   Chronic demyelination can lead to axon degeneration via various pathways such as structural destabilization, excitotoxic insult and energetic deficit.  1.4.1 Structural Destabilization Myelin not only aids in axonal conduction, energetics and trophic support, it also helps to provide structural stability to axons. The loss of axon-stabilizing myelin proteins during demyelination may contribute to axon pathology (Ferguson et al., 1997; Edgar and Nave, 2009; Morfini et al., 2009). Experiments ablating various myelin proteins such as Proteolipid Protein (PLP) (Griffiths et al., 1998), 2’,3’ cyclic nucleotide 3’ phosphodiesterase (CNP) (Rasband et al., 2005), Myelin-associated glycoprotein (MAG) (Fruttiger et al., 1995; Yin et al., 1998), have yielded axon pathology consistent with 			 26	structural break down. Interestingly, studies using a combined ablation of any two myelin proteins resulted in more severe axon pathology, suggesting an additive effect and an overlap in function (Edgar and Nave, 2009). 1.4.2 Glutamate Excitotoxicity Dying neurons release an excess of the excitatory neurotransmitter glutamate in the diseased or injured gray matter commonly seen in MS, stroke (Lee et al., 1999), or traumatic brain injury (Lau and Tymianski, 2010). This can generate a cascade of excitotoxic neuronal death that expands the initial insult. Because they lack synaptic machinery, non-synaptic neuronal structures such as axons, and glial cells, were traditionally thought to be unaffected by excitotoxic insult. Recently, this idea has been revised (Matute et al., 2001; 2002; Lau and Tymianski, 2010). Studies have determined that OLs express the glutamate receptors GluR3 and GluR4 (but not GluR2), AMPA receptors, and all kainate subunits except GluR5 (García-Barcina and Matute, 1996; 1998; Matute et al., 2002). The lack of GluR2 and the high level of AMPA and kainate receptors in OLs may explain their high susceptibility to Ca+ influx (Barres et al., 1990; Kastritsis and McCarthy, 1993) and ischemia (Fern and Möller, 2000; Follett et al., 2000). In vitro experiments in OL monocultures (Yoshioka et al., 1996), and in vivo experiments in the spinal cord dorsal column (Li and Stys, 2000) and the optic nerve (Carlos Matute, 1997) have shown that increased neurotransmitter induced AMPA and kainate signaling causes excitotoxic OL cell death (Sánchez-Gómez and Matute, 1999). Additionally, both in vitro (Tekkök and Goldberg, 2001) and in vivo studies (Pitt et al., 2000) have shown that myelin sheaths also express the GluR4 receptor and are similarly susceptible to pathogenic excitatory Ca+ influx.  			 27	1.4.3 Energy deficit 	The maintenance and regeneration of axon membrane polarity is essential for continued firing of action potentials, and is dependent on an uninterrupted supply of ATP. The energy dependent Na+/K+ ATPase ion pump generates axon membrane polarity by pumping   Na+ ions out of the axon, against the concentration gradient. Short term reductions of axonal ATP can cause failure of the Na+/K+ ATPase pump, preventing repolarization and blocking action potentials propagation (Dutta et al., 2006; Mahad et al., 2009; Sadeghian et al., 2016). If the ATP deficits are prolonged the failure of the Na+/K+ ATPase pump results in accumulation of internal Na+. This, in turn, causes the concentration-dependent Na+/Ca+ exchanger to reverse, moving Ca+ into the axon. Increased internal Ca+ triggers the release of cytochrome C from mitochondria, which activates caspases and the apoptotic cascade. Increased cytochrome C amplifies the initial Ca+ influx by causing the release of large amounts of Ca+ from the endoplasmic reticulum causing a positive degenerative feed back loop (Mattson and Chan, 2003) (Lu et al., 2000; Larsson, 2010). Energy deficits can be generated by oxidative damage to the mitochondrial respiration chain caused by the accumulation of reactive oxygen species (ROS) and nitric oxide (NO) (Li and Stys, 2000; Matute et al., 2002) which can occur as a by product of  excitotoxic cell death or release by  CNS resident immune cells and astrocytes (Sadeghian et al., 2016).  1.5 Animal Models of Demyelination In the last 20-30 years several animal models of demyelination have been developed to aid in investigating MS pathology (Denic et al., 2011). They can be roughly categorized into three groups; autoimmune mediated models such as experimental autoimmune 			 28	encephalomyelitis (EAE) (Krishnamoorthy and Wekerle, 2009; Hart et al., 2011; Behan and Chaudhuri, 2014), virally induced models such as Theiler’s murine encephalomyelitis virus (TMEV) (Denic et al., 2011), and toxin induced models, such as cuprizone or lysolecithin (Denic et al., 2011; Procaccini et al., 2015).  Although all of these models result in demyelination, the mechanisms and areas affected vary (Denic et al., 2011; Procaccini et al., 2015).  1.5.1 The Lysolecithin and Cuprizone models The lysolecithin (LPC) demyelination model involves the injection of LPC into CNS white matter tracts. It causes focal demyelination in the area of injection and has been used to study the effects of demyelination in a relatively noninflammatory context (Matsushima and Morell, 2001) (Hall, 1972; Blakemore, 1976; Denic et al., 2011). The cuprizone (bis–cyclohexanone-oxaldihydrazone) model is a widely used animal model for studying MS-related myelin pathology. The addition of cuprizone, a copper chelator, to rodent diets leads to reproducible toxic demyelination of the corpus callosum and the cerebellum within 6 weeks (Pfeifenbring et al., 2015).  1.5.2 The EAE model 	The EAE active induction protocol has remained largely unchanged since its discovery in the 1940s. Initially, spinal cord tissue homogenates were emulsified in a mixture of mineral oil and heat-killed mycobacterium tuberculosis known as complete Freund’s adjuvant (CFA). Today specific myelin peptides are now used in place of spinal cord homogenates, increasing the specificity of the induced autoimmune reaction; in some protocols pertussis toxin has been added to aid in opening the blood brain-barrier and boost immune reactivity (Baxter, 2007). 			 29	 Although there is variation, the first pathological symptoms of many EAE protocols appear between 10 and 14 days post inoculation. EAE symptoms initially present caudally and move rostrally as the disease progresses, correlating with increased inflammation and symptom severity. In many mice the first indication of disease development is a limp tail; as EAE progresses this can be followed by complete tail paralysis, hind limb paresis and then complete hind limb paralyses; in very severe cases paralysis may progress rostrally into the forelimbs. The exact disease course of any EAE protocol depends on the combination of mouse strain, gender and the peptide used (Lindsey, 1996; Papenfuss et al., 2004; Jones et al., 2008; Bittner et al., 2014; Rahn et al., 2014). Many factors can influence the outcome of EAE experiments including the time of year, the cleanliness of the facility, or the source of the reagents used (Papenfuss et al., 2004; Stromnes and Goverman, 2006).   EAE is the predominant experimental animal model for MS and a valuable research tool (Krishnamoorthy and Wekerle, 2009; Hart et al., 2011), however,  although EAE reproduces many of the pathological elements of MS, it is not an experimental replication. In fact, the discrepancies between EAE and MS are large enough that some researchers argue that EAE does not model MS at all, and may be incorrectly biasing the research community in an immunological direction (Behan and Chaudhuri, 2014).    			 30	1.6 Research Hypothesis and Aims  Hypotheses   • Myrf ICKO mice will have significantly higher EAE disease severity, and earlier disease onset than the wildtype control group.  • Myrf ICKO will prevent remyelination and cause a reduction of myelin in EAE affected areas of the lumbar spinal cord.   • Myrf ICKO will cause Dorsal Column shrinkage.   • Myrf ICKO will cause an increase in the level of microglial activation in EAE affected mice.   • Myrf ICKO will causes increased axon loss in EAE affected areas of the lumbar spinal cord.   • Myrf ICKO will causes increased axon damage in EAE affected areas of the lumbar spinal cord.      			 31	Aim 1  Develop a working model of EAE in the transgenic mice described in Chapter 2; assess behaviour, using the approved EAE rating scale, (also described in Chapter 2) for EAE disease severity on onset.  Aim 2 Using tissue collected from Aim 1, assess the efficacy of MYRF ICKO induced remyelination block by histologically quantifying the amount of myelin using confocal microscopic imaging of immunohistochemical staining for myelin basic protein (MBP) in specific white matter tracts.  Aim 3 Using tissue collected from Aim 1, assess for axon loss induced white matter tract shrinkage between KO EAE >0 and Control EAE >0 groups by histologically quantifying differences in DC size using confocal microscopic imaging of immunohistochemical staining for myelin basic protein (MBP).  Aim 4 Using tissue collected from Aim 1, assess for remyelination block induced differences in microglial activation between KO EAE >0 and Control EAE >0 groups by histologically quantifying microglial activation state using confocal microscopic imaging of immunohistochemical staining for ionized calcium binding adapter protein 1 (IBA1).      			 32	Aim 5 Using tissue collected from Aim 1, assess for remyelination block induced differences in axon loss by histologically quantifying axons in KO EAE >0 and Control EAE >0 groups using confocal microscopic imaging of immunohistochemical staining for neurofilaments (NF200/SMI-312). Aim 6 Using tissue collected from Aim 1, assess for remyelination block induced differences in axon damage by histologically quantifying damaged axons using confocal microscopic imaging of immunohistochemical staining for non-phosphorylated neurofilaments (SMI-32).  																							 			 33	2 Chapter 2 Methods and Results  	2.1 Experimental Methods   In this section I will describe the methods used in these experiments, including the generation of transgenic mice, animal model used, the experimental outline, animal care, preparation of reagents, EAE induction, collection and processing of tissue, staining and imaging, and all analyses.  2.1.1 Mice For the main experimental group triple transgenic mice were generated by cross-breeding three transgenic lines: Myrf flfl (Ben Emery et al., 2009), PDGFRα CreERT2 (Rivers et al., 2008), and ROSA26 YFP (Jax stock # 006148) (Srinivas et al., 2001). The first construct, Myrf flfl, has LoxP sites inserted flanking exon 8 of the Myrf gene. When exposed to Cre-recombinase (Cre) this construct removes exon 8 from Myrf (Cre) resulting in a nonfunctional MYFR protein. (Ben Emery et al., 2009). Cre is a bacterial nuclease that recombines DNA at specific locations marked by LoxP sites and has been adapted for experimental in vivo DNA manipulation (Nagy, 2000; Van Duyne, 2015) (Fig. 2.1).  The second construct, PDGFRα CreERT2, is a Cre-recombinase cassette with an attached estrogen receptor (ERT2) coupled with a promoter sequence for platelet derived growth factor alpha (PDGFRα). This construct serves two purposes: it provides cell type specificity, and the inducibility of the genetic knockout. The PDGFRα promoter sequence, confines the expression of CreERT2 to cell types that express this receptor (mainly OPCs in the CNS), the addition of the ERT2 to the Cre construct allows temporal 			 34	control of Cre function by preventing the Cre from entering the nucleus until Tamoxifen (TAM) is injected (Nishiyama et al., 1996; Wilson et al., 2006; Rivers et al., 2008). In this way Cre can be expressed during development without the embryonic/early developmental lethality that would occur if it were constitutively active (Indra et al., 1999; Ghosh and Van Duyne, 2002; Ruzankina et al., 2007). When TAM is injected, it binds CreERT2 complex, releasing HSP 90 and allowing the CreERT2 complex it to translocate to the nucleus. There it dissociates from the ERT2 and acts upon the LoxP sites of the other constructs. In this way, the injection of TAM controls the temporal activation of Cre and the subsequent deletion of exon 8 in the Myrf flfl construct and the STOP codon in Rosa26R-YFP (Ghosh and Van Duyne, 2002)(Fig. 2.1).  The third construct, Rosa26R-YFP, is a yellow fluorescent protein containing a floxed STOP codon and the promoter sequence for the ubiquitously expressed housekeeping gene Rosa-26. When coupled with the CreERT2 this construct will inducibly produce yellow fluorescent protein (YFP) in the cytoplasm of cells expressing Cre. It can serve two purposes, the fate mapping of Cre producing cells and the estimation of the recombination efficiency of the PDGFRα CreERT2 construct. This construct resembles the Myrf flfl   construct except that the LoxP sites flank a stop codon. The stop codon’s removal results in transcription of the YFP and initiates fluorophore production (Srinivas et al., 2001; Tatsumi et al., 2008) (Fig.2.1).  			 35	 Figure 2.1 Graphic representation of the transgenic constructs used, their function and the mechanism of the inducible Cre-lox system. A) the PDGFRαCreERT2 construct, B) the administration of Tamoxifen and its effect, C) Cre enters the nucleus and acts upon the LoxP sites of the Myrf FLFL and ROSA26YFP constructs, D) the Myrf FLFL construct, E) the ROSA26YFP construct, F) Exon 8 has been deleted from Myrf, G) STOP codon has been removed form YFP construct.  2.1.2 Animal Model (EAE) EAE may be induced in two ways: active induction and passive transfer. Inoculation of animals with a combination of myelin peptide and Complete Freund’s Adjuvant (CFA) coupled with separate injections of pertussis toxin is known as active induction. Alternately, the injection of myelin primed autoreactive T-cells from an animal that has PDGFrα	 Cre	 ER	Cre	ER	TAM	Myrf	exon	8	STOP	 YFP	Exon	7	 Exon	9	HSP	90	Exon	7	 Exon	9	YFP	YFP	Cre	ER	TAM	lox-p	lox-p	lox-p	lox-p	Cytoplasm		Nucleus			PDGFrα	Construct		Myrf	FLFL	Construct		ROSA	26	ROSA	26YFP	Construct	Myrf	Exon	8	deleted	YFP	STOP	codon	removed	A	D	C	B	E	F	IP	InjecNon	G				 36	previously been actively induced, into a naive animal is known as passive transfer EAE (Stromnes and Goverman, 2006; Baxter, 2007).   In these experiments I use an active induction model of EAE, in which a myelin peptide, Myelin Oligodendrocyte Glycoprotein (MOG) segment 35-55, emulsified in CFA and diluted pertussis toxin are injected into the triple transgenic mice described above (Bittner et al., 2014). 2.1.3 Experimental Outline  For these experiments two groups of mice were generated based on genotype. Both groups were made up of males and females aged between 8 and 12 weeks. Mice with the triple transgenic genotype PRGDRα-CreERT2+; Myrf flfl+; Rosa26R-YFP + or -, were categorized as the knockout group (KO) and PRGDRα-CreERT2 -; Myrf flfl + or -; Rosa26R-YFP + or -, were categorized as the control group (CONT). Initially, 48 mice of these genotypes were assigned to this experiment and designated the cytoplasmic group (Fig. 2.2).  			 37	 Figure 2.2 Genotypes, groupings, gender distribution, total number of mice inoculated and number of EAE >0 mice, A) the main experimental ICKO and Control groups using a cytoplasmic reporter, B) Additional main experimental ICKO and Control groups using a membrane reporter, C) the supplemental experimental ICKO and Control groups using a cytoplasmic reporter.   An additional 12 mice, the membrane group, that had a membrane tethered fluorescent reporter Rosa26-mGFP (JAX Stock# 007576) substituted for the cytoplasmic Rosa26R- YFP was added to the initial 47, yielding a total of 59 experimental mice (Fig. 2.2). The membrane group was added because the membrane tethered reporter allows the visualization of myelin wraps and oligodendrocyte processes that cannot be visualized Main	Experimental	Groups	PRGDRα-CreERT2+	;	Myrf	flfl+	;	Rosa26R-YFP	+	or	-		PRGDRα-CreERT2–	;	Myrf	flfl	+	or	–	;	Rosa26R-YFP	+	or	-		Control	Group	KO	Group	12	female		7	male	19	total	3	EAE	>0	12	female		16	male		28	total	3	EAE	>0	47	PRGDRα-CreERT2+	;	Myrf	flfl+	;	Rosa26R-mGFP	+	PRGDRα-CreERT2–	;	Myrf	flfl	+	or	–	;	Rosa26R-mGFP	+or-		Control	Group	KO	Group	3	female		1	male	4	total	0	EAE	>0	3	female		5	male		8	total	0	EAE	>0	12	PRGDRα-CreERT2+	;	Myrf	flfl+	;	Rosa26R-YFP	+	or	-		PRGDRα-CreERT2–	;	Myrf	flfl	+	or	–	;	Rosa26R-YFP	+	or	-		Control	Group	KO	Group	2	female		1	male	3	total	3	EAE	>0	5	female		4	male		9	total	2	EAE	>0	12	Supplementary	Experimental	Groups	Cytoplasmic	YFP	 Membrane	YFP	6	 0	5	A	 B	C				 38	with a cytoplasmic reporter. Unfortunately, this entire secondary cohort failed to develop EAE and was excluded from final analysis. The most plausible explanation for this failure was a strain peptide mismatch. Because the Rosa26-mGFP construct is built in a different strain of mouse than the Rosa26-YFP construct, attempting to induce EAE with the MOG-35-55 protocol may have been futile.   Both KO and CONT groups were injected with TAM and inoculated with MOG 35-55/CFA and pertussis toxin as per protocol. They were monitored for 28 days after inoculation and perfused. Tissue was collected, processed and analyzed according to the methods below. Unfortunately, only 6 mice of the initial 60 developed EAE. However, because the initial results of this small cohort indicated a potential trend, a supplementary experimental group of 12 mice was added in an effort to boost the number of EAE >0 mice (Fig 2.2).   All experimental procedures and analyses of this additional cohort were conducted exactly as in the original, with one exception: animals that did not demonstrate EAE behavioural symptoms at 28 days were not perfused with their affected litter-mates, but housed for an additional 20 days. In this experiment, 3 mice developed symptomatic EAE during the first 28 days and were perfused, and in the following 20 days an additional 2 mice developed EAE and were also perfused, for a total of 5 additional mice. These were added to the original 6 yielding a total of 11 symptomatic EAE mice (EAE >0).   			 39	The 11 mice were separated into the following groups for histological analysis; KO EAE >0 (mice with Myrf ICKO that developed visible EAE), Control EAE >0 (mice with functional Myrf that developed visible EAE), KO EAE 0 (mice with Myrf ICKO that did not develop visible EAE), Control EAE 0 (mice with functional Myrf that did not develop visible EAE), KO EAE 0 FL (mice with Myrf KO that did not develop visible EAE but showed histological evidence of lesion formation), and Control EAE 0 FL (mice with functional Myrf that did not develop visible EAE but showed histological evidence of lesion formation). The experimental outline and final histological groupings can be seen in the below (Fig.2.3).   A	 B	C	MOG35-55/CFA	SUB	CUE	[1mg/ml]								[5mg/ml	MBT]	Pertussis	Toxin	IP	[2500	ng/ml]		Main	Cohort			Aug	1,2015		59	mice		7	mice	develop	EAE	1	excluded		3	KO	3	Control	+11	EAE	0	&	EAE	0FL		Supplementary	Cohort		Oct	2,2016			12	mice		5	mice	develop	EAE		3	KO	2	Control		Group	colors	and	numbers		used	in	all	analyses				 40	Figure 2.3 Experimental Overview, A) reagent injection location and concentrations, B) experimental timeline, C) mouse groupings, number of mice and colour coding used in all analyses.   2.1.4 Animal Care  Triple transgenic mice, described above, aged between 8 and 12 weeks were housed, monitored and treated in accordance with the UBC Animal Care Committee (ACC) regulations. All animals were monitored for lesions, weight loss, EAE symptoms and overall health. Animal health and humane end points and EAE disease course were assessed using approved UBC ACC health monitoring sheets and EAE rating scale respectively. 2.1.5 Genotyping Genotyping was performed using PCR and primers specific to the genes in question and was carried out prior to the start and at the completion of the experiment. 2.1.6 Tamoxifen Preparation and Administration Tamoxifen (Sigma, T5648) was prepared in advance by it dissolving in corn oil (Sigma, C8267) and was administered by IP injection at a concentration of 100mg/kg for 5 consecutive days. Following the injections, 9 days were allowed for Tamoxifen to clear prior to initiation of EAE inoculation.  2.1.7 CFA Concentration Adjustment  CFA (Sigma) is a mixture of Mycobacterium Tuberculosis (MT) and mineral oil and can only be purchased in the concentrations of 1mg MT/ml mineral oil. Because it was suggested during pilot experiments that increasing the MT concentration from 1mg/ml to 			 41	5mg/ml might result in more reliable EAE induction, I manually adjusted the MT concentration of the CFA to 5mg/ml by adding 4 mg of heat-killed MT (List biological) to each ml of 1mg/ml CFA.  2.1.8 MOG 35-55 Emulsion Preparation Lyophilized MOG 35-55 (Genscript) was rehydrated in 1ml of distilled water to a concentration of 2 mg/ml. This was the added to an equal volume of CFA and emulsified. The final concentration of MOG 35-55/CFA emulsion was 1mg/ml. This was loaded into 1 ml syringes for subcutaneous injection (Stromnes and Goverman, 2006).   2.1.9 Pertussis Toxin Preparation Lyophilized pertussis toxin (List Biological) was reconstituted with distilled water. The reconstitute was then further diluted to a concentration of 2500 ng/ml then loaded into 1ml syringes for IP injection (Stromnes and Goverman, 2006).   2.1.10 EAE Induction Mice were shaved dorsally from the base of the tail to the middle of the back rostrally. Subcutaneous (SC) injections of MOG35-55/CFA emulsion were performed on day 0 and day 7. Each mouse received 4 subcutaneous (SC) injections of 0.05 ml at separate locations on the rump, yielding a total of 0.2 ml per mouse. Injections sites were arranged rostro-caudally, two on either side of the dorsal midline. A single IP injection 0.1ml of pertussis toxin was administered at a concentration of 2500 ng/ml on day 0 and day 2.   2.1.11 Behavioural Analysis   Animals were assessed for EAE symptoms daily, from inoculation until the end of the experimental period. Mice were removed from the cage and placed on a flat open surface 			 42	and assessed for locomotion and overall health using an approved UBC ACC EAE rating scale (Fig. 2.4). The daily assessments were recorded and used in behavioural analysis to determine EAE onset, duration, and severity.     Figure 2.4 The Approved UBC EAE Scoring Scale, used to score EAE severity. 2.1.12 Perfusion/Euthanasia/Tissue Harvesting and Cryoprotection  All experimental animals were either perfused with 4% paraformaldehyde, or euthanized according to UBC ACC protocol. Perfused animals were deeply anesthetized and transcardially perfused with 15ml of 1x phosphate buffered saline (PBS) (Fisher Scientific) to clear blood from vessels followed by 40ml of fresh, cold, 4% Paraformaldehyde (PF) solution (Fisher Scientific) to fix the tissue. Full length spinal UBC	ACC	approved	EAE	Ra/ng	Scale					 43	cords were harvested and placed in 4% PF for 8 hours then cryoprotected by transferring them into ascending concentrations of sucrose solution (12%, 18% and 24%) for 24 hours each.  2.1.13 Tissue Segmentation and Cryostorage After the last stage of sucrose cryoprotection, the tissue was removed from solution, blotted to remove excess sucrose, and segmented. Complete spinal cords were divided into three sections. The lumbar segment was identified as extending from 2mm rostral of the widest part of the lumbar enlargement to the caudal end of the spinal cord. The cervical section was defined as extending 1 cm caudally from the rostral most end of the cervical cord, and the thoracic section was the remainder between the cervical and lumbar segments (Fig.2.5). The tissue segments were then embedded in optimum cutting temperature compound (OCT) filled moulds, rapidly frozen on dry ice and stored at         -80°C.   2.1.14 Cryosectioning Lumbar sections of frozen spinal cords were removed from -80° C and allowed to warm to -15° C for sectioning. The spinal cords were sectioned transversely on a cryostat (HM-525, Thermo Scientific) at a thickness of 20 µm. Sections were collected on Super Frost Plus slides (Fisher Scientific) and thaw-mounted. Ten sections of tissue were placed on each slide and slides were arranged into sets of ten and stored at -80° C (Fig.2.5).   			 44	 Figure 2.5 Graphic representation of tissue segmentation, cryostat sectioning and immunostaining. 2.1.15 Immunohistochemistry Slides were removed from -80° C and thawed at room temperature for 2 hours. They were rehydrated in PBS and delipidated for better antibody penetration using ascending and then descending concentrations (50%, 75%, 90%, 95% and 100%) of ethanol washes. Following delipidation, 10% Normal Donkey Serum and 0.1% Triton in PBS was applied to the slides for 30 min to block for nonspecific protein-antibody binding. The blocker was washed off and primary antibodies were applied and left to incubate overnight at room temperature in a humidity-controlled chamber.  The following morning, slides were removed from the chamber, washed with PBS three times and the appropriate Alexa Sec$oning	and	Staining	2mm	1cm	Widest	part	of	lumbar	enlargement	Cervical	Thoracic	Lumbar	20	um	1-101-10!11-20!21-30!SECTION !SECTION !SECTION !IMMUNO	1		CD3	IBA1	MBP	Nf200/SMI-312			IMMUNO	2	SMI-32	βAPP	MBP	βIII	tubulin	intact	Unstained				 45	Floura or Dylight secondary antibodies were applied (Jackson Immunoresearch laboratories Inc). Secondary antibodies were then washed off and coverslips were applied; finished slides were refrigerated at 4° C.  2.1.16  Primary Antibodies  The	antibodies	used	in	the	histological	quantifications	of	these	analyses	are	defined	in	Table	2.1.	 Table 2.1 Antibody definition and usage. 2.1.17 Imaging All images were taken on a Zeiss Axio-observer M1 inverted confocal microscope equipped with a Yokugawa spinning disc, controlled by Zeiss Zen blue software.  Whole IBA1 Host-Rabbit Source-Wako Ratio-1:2000  -ionized calcium binding adapter molecule 1or Allograft Inflammatory Factor 1, is upregulated in microglia in response to inflammatory cues, particularly IL-17. In the CNS, antibodies against IBA1 mark microglia; the amount of staining is positively correlated with the inflammatory activation state of the cell.  MBP  Host-Chicken Source-Aves Ratio-1:200  -myelin basic protein, a major protein constituent of myelin. MBP antibodies are used to quantify the amount of myelin.  SMI-312 Host-Mouse Source-Covance Ratio-1:1000  -a mixture of monoclonal antibodies that react against complex networks of axons. It is directed against phosphorylated axonal epitopes on neurofilaments M and H and marks medium and large caliber axons. It is used here to quantify the number of axons.  NF-200 Host-Mouse Source-Sigma Ratio-1:500  - a member of the intermediate filament family, antibodies against NF200 mark large caliber myelinated axons. It is used here in conjunction with SMI312 to quantify the number of axons.  SMI-32 Host-Mouse Source-Bio Legend Ratio-1:1000  - a nonphosphorylated H neurofilament. SMI-32 recognizes the non-phosphorylated neurofilament H proteins that are correlated with axon damage. It is used here to quantify the number of damaged large caliber axons.  			 46	spinal cord cross sections were imaged with a 20x objective lens and the dorsal column (DC), and ventral white matter (VWM) tracts were imaged with the 63x objective yielding a total magnification of 200x and 630x respectively. All images were taken as Z stacks of the full tissue depth; individual stack images were spaced at 1µm intervals vertically. 63x immunoflourescent images were taken of MBP, IBA1, SMI-32, and NF200/SMI-312 and 20x objective images of were taken of all animals for MBP, IBA1 and SMI-32. 2.1.18 Histological Analysis and Quantifications Behavioural scores and all histological quantifications were performed under blinded conditions. Quantifications of images taken were conducted in three manners: image thresholding using Image J processing software to assess % area fluorescence, manual axon counts using Zeiss Zen Blue analysis software, and Form Factor Analysis (FFA) of microglial cells. 2.1.19  Image Thresholding To generate image threshold data, Zeiss CZI images were set to best-fit intensity levels, converted to a maximum intensity projection in tagged image file format (TIFF) and exported from Zeiss Zen Blue software. TIFF files were then opened in Image J (NIH) converted to 8bit format, cropped for the area of interest and thresholded. The determination of representative threshold levels was performed based on visual assessment of cell and tissue morphology. The area occupied by thresholded pixels was calculated by applying a pixel to distance correction factor, determined by Zen Blue software, and the % area of pixel occupancy was determined. This method was used for all 20x and some 63x objective lens images. 			 47	2.1.20 Axon Counts Axon counts were conducted using images taken with 63x objective lens and Zen blue image processing software. A 76um x 76um counting frame was superimposed over 63x images of specific white matter tracts. Within the frame axons were manually counted using the full depth of the image Z stack. Axons were considered within the frame and counted if they were either wholly within the frame boundaries or if their perimeter touched the top and right side of the counting frame. They were excluded from the count if they were wholly outside the counting frame or if their perimeter touched the left or bottom counting frame boundary.  2.2 Analytic Methods The specific analysis conducted include; EAE behaviour, % myelin of whole cord white matter only (20x), % myelin in VWM (63x), % myelin in focal lesion areas (63x), % DC of total area cord cross section (20x), % microglial activation of whole cord white matter only (20x), % microglial activation of VWM (63x), microglial ramification analysis using FFA (63x), DC and VWM axon counts (63x), DC and VWM damaged axon counts (63x). 2.2.1 Behavioral Analyses 	The EAE behavioral data collected were analyzed in four ways: EAE severity from the day of inoculation, EAE severity from day of first symptom, average group EAE severity based on days symptomatic and average group time from EAE inoculation until the presentation of the first symptom. In the first analysis, EAE Average Scores Day Post Inoculation (Fig. 2.16 B), group data were averaged for EAE >0 mice from inoculation 			 48	until completion regardless of the timing of symptom onset. However, because the EAE generated here was more variable than usual, three additional analyses were conducted.   The second analysis, EAE Average Scores Day Post First Symptom (Fig. 2.17 C), was conducted in order to make more meaningful comparisons of EAE severity data, EAE >0 group data were organized and averaged so that the first symptomatic day of each mouse was considered day 1; this allows comparison of the severities of attacks that begin on differing days. The third analysis, Average EAE Score per Day Symptomatic (Fig. 2.17D), was conducted by averaging the daily scores of each mouse for symptomatic days only, generating group average severities on a per day symptomatic basis. This approach allows for average severity data grouping of animals with different numbers of symptomatic days and generates a group average severity per day symptomatic. The fourth analysis, Average Days from Inoculation to EAE Onset (Fig. 2.17E), was conducted because of differences observed in the appearance of the first EAE symptom between groups. To generate a group average number of days from inoculation to first symptom, the number of days between EAE inoculations was recorded and averaged per group, the group averages were then analyzed statistically. 2.2.2 Histological Analyses 	In order to determine the efficacy of Myrf ICKO in blocking remyelination, I quantified the amount of myelin in three areas of lumbar sections of KO EAE >0 and Control EAE >0 mice using confocal imagery and MBP immunohistochemical staining. If Myrf ICKO did effectively block remyelination, less myelin should be quantified in KO EAE >0 mice than their control counterparts. 				 49	2.2.2.1 % Myelin of Whole Cord White Matter  Whole spinal cord crossection images were taken of MBP staining of tissue sections of the rostral area of the lumbar spinal cord. The images were cropped to isolate the white matter of the whole cord cross section and processed as per Image Thresholding above. These data were averaged per group and analyzed statistically (Fig. 2.6).  Figure 2.6 Graphic representation of myelin sampling, % MBP +  of whole cord white matter analysis. 2.2.2.2 % Myelin of Ventral Lip White Matter 	Because the results of the % Myelin of Whole Cord White Matter analysis suggested that the inclusion of a large amount of unaffected white matter tracts might have affected the results, an analysis of the ventral white matter only was conducted. The ventral lip white Myelin	Sampling		Lumbar	spinal	cord	Image	J	threshold	Image	J	%	IBA1of	whole	cord		white	ma?er	20x	MBP				 50	matter was imaged for MBP fluorescence using a 63x objective lens. The images were then processed and quantified for % MBP staining of sampled area as per Image Thresholding. These data were averaged per group and analyzed statistically (Fig. 2.7).   Figure 2.7 Graphic representation of myelin sampling, % MBP + area of ventral lip white matter analysis.  2.2.2.3 % Myelin of Focal Lesions 	To further parse the differences in remyelination between KO and control groups, myelin was analyzed in ventral areas of focal lesions. Focal lesions were identified as areas that showed both concentrated microglial activation and loss of MBP staining. These areas were located in the perimeningeal white matter of either the ventral lip or the ventrolateral corners near the point of ventral root exit. Four 63x objective confocal Myelin	(MBP)	ventral	Lip	sampling	(63x)		Lumbar	spinal	cord	Image	J	%	MBP+	of	sampled	area	63x	MBP				 51	images measuring 1540 µm x 1540 µm were taken, processed and analyzed for % MBP staining of the sampled area as per Image Thresholding. These data were averaged per group and analyzed statistically (Fig. 2.8).   Figure 2.8 Graphic representation of the identification of focal lesion location, and sampling for % MBP + area focal lesion analysis. 2.2.2.4 DC Size   To assess the differences in the relative size of the DC between the KO EAE >0 and Control EAE >0 groups, 20x MBP whole cord crossection lumbar spinal cord images were processed as per Image Thresholding above. Image J software was used to outline both the DC and the whole cord circumference and calculate the area of each. The area of the DC was divided by the area of the whole spinal cord and multiplied by 100 to achieve Lumbar	spinal	cord	Myelin	MBP	63x	Focal	Lesion		Sampling	Image	J	%	Myelin	of	focal	lesion	area	MBP	IBA1	63x		MBP				 52	the % DC area of whole cord area. These data were averaged per group and compared statistically (Fig. 2.9).    Figure 2.9 Graphic representation of DC and Whole cord area calculation and sampling for % area DC analysis. 	2.2.2.5 Microglial Activation of Whole Cord Cross-section (20x) 	To determine the % of microglial activation, sections were stained for IBA1, a well-characterized microglial marker that is up regulated after injury or disease (Ito et al., 1998) and is correlated with increased microglial activation (Ito et al., 1998). Whole cord cross section confocal images of IBA1 staining were taken using a 20x objective lens. %	Dorsal	Column	Area	Sampling	Method	Lumbar	spinal	cord	mm2	 mm2	 100	 %	DC	area	of	Cord			X	sec?onal	area	Image	J	DC	and	Whole	Cord		Area	mm	2	MBP		20x				 53	The images were processed, exported and analyzed as per Image Thresholding. The data generated were averaged per group and analyzed statistically (Fig. 2.10).   Figure 2.10 Graphic representation of sampling for whole cord cross-section % IBA1+ area analysis.  2.2.2.6 Microglia Activation of Ventral White Matter (63x) 	Because it was found in the myelin analysis that whole cord sampling can affect local results, a quantification of microglial activation in the ventral white matter only was conducted. The ventral white matter was imaged for IBA1 fluorescence using a 63x objective lens. The images were processed, exported and analyzed as per Image Microglial	20x	Sampling	Method	Lumbar	spinal	cord	Image	J	%	IBA1of	whole	cord	20x	IBA1				 54	Thresholding. The data generated were averaged per group and analyzed statistically (Fig. 2.11). 	 Figure 2.11 Graphic representation of sampling for VWM % IBA1+ area analysis  2.2.2.7 Form Factor Analysis (FFA) of Microglial Ramification (63x) 	FFA is one means of assessing cellular ramification. FFA is a mathematical method that applies a numerical value to cellular ramification state (Wilms et al., 1997; Karperien and Ahammer, 2013a). Briefly, four representative microglial cells were chosen per animal from the processed 63x objective IBA1 images used in the IBA1 VWM analysis. Cells chosen for analysis must be visually separate cells with minimal process overlap and clearly distinguishable from other cells. The outline of selected cells was traced using Microglial	63x	sampling	method	Lumbar	spinal	cord	Image	J	%	IBA1of	sampled	area	63x	IBA1				 55	Image J software and the area and perimeter were calculated. The results were entered into the formula FF = 4π x area /perimeter2 (Fig. 2.12). Higher FFA values indicate that a cell has a more circular (amoeboid) morphology and a higher level of activation; lower FFA numbers indicate a higher degree of ramification and a lower level of activation (Fig. 2.13). The data generated were grouped, averaged and analyzed statistically.   Figure 2.12 Graphic representation of single cell sampling of VWM IBA1 63x images for the FFA analysis.  Microglial	Ramifica-on	Sampling	Method	Lumbar	spinal	cord	4x	Image	J	Area	μm2	and	Perimeter	μm	63x	IBA1				 56	 Figure 2.13 Sample images of IBA1 FFA quantification, showing A) activated, B) partially activated, and C) resting microglia. 2.2.2.8 DC and Ventral White Matter NF200+/SMI-312+ Axon Counts (63x) 	To assess the effect of blocked remyelination on axon survival, slides from the lumbar spinal cord were co-stained with antibodies against NF200 and SMI-312. These antibodies stain L and M neurofilament subunits present in medium and large caliber axons. Confocal images using a 63x objective lens were taken of four areas within the DC, and 3 areas in both the ventromedial (VM) and ventrolateral (VL) white matter. The images were processed and quantified as per Axon Counts above. The data generated were grouped, averaged and analyzed (Fig 2.14).   Examples	of	FFA	Quan1fica1on	KO	EAE	>	0	 Control	EAE	>0	EAE	0	Ac1vated/Amoeboid	Nonac1vated/Ramified		Par1ally	Ac1vated	A	 B	C				 57	  Figure 2.14 Graphic representation of sampling and analysis for DC, VM and VL axon count analysis.   2.2.2.9 % SMI-32 + Axons in the DC and Ventral White Matter (20x)  	To assess the effect of blocked remyelination on axon damage, slides from the lumbar spinal cord were stained with antibodies against nonphosphorylated neurofilament (SMI-32). SMI-32 antibodies stain for non-phosphorylated neurofilaments that indicate axon damage (Petzold, 2005; Petzold et al., 2008). 20x confocal images were taken of whole cord crossection of the lumbar spinal cord. The images were cropped for the DC and VWM, processed, exported and analyzed as per Image Thresholding. The data generated were grouped, averaged and analyzed (Fig 2.15). 63x	Axon	sampling	method	Lumbar	spinal	cord	Nf	200/SMI312	Nf200+	Axons/mm2		ventral	root	Zen	Blue	CounFng	SoGware	63x				 58	  Figure 2.15 Graphic representation of sampling and analysis for DC, and VWM for the % SMI-32+ area analysis. 2.2.2.10 SMI-32+ Axon Counts in the DC and Ventral White Matter (63x) 	In order to achieve higher fidelity in axon damage quantification, and to match the methods used in the axon analysis further quantification was conducted. 63x objective confocal images of SMI-32 staining in four commonly affected areas within the DC and the ventromedial (VM) and ventrolateral (VL) white matter were taken. The images were processed and quantified as per Axon Counts. The data generated were grouped, averaged and analyzed statistically (Fig. 2.16).  Areas	were	outlined	in	Image	J	and	thresholded	for	SMI	32,	both	DC	and	VM	areas	were	assessed.	This	was	done	to	ge	an	accurate	assessment	of	white	maAer	damage	without	unwanted	background	from	grey	maAer	neuronal	staining.	Lumbar	spinal	cord	SMI	32	20x	Threshold	Sampling	Method	Image	J	%	SMI	+	area	of	sample	area	20x	SMI32				 59	 Figure 2.16 Graphic representation of sampling and analysis for DC, VM and VL SMI-32+ axon count analysis.   2.3 Statistical Analyses All data analyzed for these experiments were checked for normality and statistical significance using GraphPad Prism version 6.0c analytic software. Data samples were checked for normality using the D'Agostino & Pearson omnibus normality test, Shapiro-Wilk normality test, and the Kolmogorov-Smirnov (KS) normality test. If normality was achieved, result significance was tested using an unpaired t test. If normality was not achieved a Mann-Whitney test was applied. The significance threshold was set at 0.05 for all analyses and is indicated by an asterisk on graphs. SMI	32	63x	sampling	method	Lumbar	spinal	cord	SMI-32+	Axons/mm2		Zen	Blue	CounBng	SoCware	63x	SMI32	ventral	root				 60	2.4 Results 	The purpose of these experiments was to investigate the effect of blocked remyelination on axon survival in the EAE model of inflammatory demyelination. To do this I have incorporated one behavioural study, and four histological studies. Each study is comprised of multiple analyses, most of which were conducted using different images, sampling areas and techniques.  2.4.1 Behavioural Results: Remyelination blockade causes delayed EAE symptom presentation. Axons rely on myelin for support, and the chronic loss of myelin can result in axonal degeneration and neuronal death (Nave, 2010; Pohl et al., 2011). In the absence of remyelination, due to the functional deletion of MYRF, affected axons will be chronically demyelinated and more prone to degeneration. Because inflammation and axon demyelination both contribute to the neurological deficits of EAE and MS (Krishnamoorthy and Wekerle, 2009) it is important to understand the contribution of each one to axon degeneration and neurological dysfunction. To assess this we used EAE to generate inflammatory demyelination in both experimental and control groups, blocked remyelination in the experimental group and assessed EAE severity using a standard EAE assessment protocol.   Four analyses of behavioral data were conducted: EAE disease severity from inoculation (Fig. 2.17), EAE disease severity from first symptom presentation, the average EAE severity per day symptomatic and the average number of days from EAE inoculation to first symptom presentation (Fig. 2.18).   			 61	 Because of variability in EAE induction (Fig. 2.17, A)), statistical analyses were only conducted on the average severity per day symptomatic and the days from inoculation to first symptom analyses. The results indicated that remyelination-blocked mice had a statistically significant longer period from inoculation to first symptom (p = 0.02). The results of the analysis of average severity per day symptomatic were not significant  (p = 0.11) (Fig. 2.18).    Figure 2.17 Behavioural data results days post inoculation, A) Individual EAE scores for all EAE> 0 mice from inoculation, B) Daily group average EAE scores from inoculation to perfusion for EAE >0 KO and EAE >0 CONT groups.  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 4201234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE ScoreKO EAE >0Control EAE >0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 4201234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE ScoreF KO 1011F KO 1033M KO 2137M KO 2036M KO 2038F KO 1046M Cont 2026M Cont 2023F Cont 1112M Cont 2033M Cont 2037A	C	B				 62	  Figure 2.18 Behavioral data results from first symptom, A) EAE scores grouped from first symptomatic day for KO EAE >0 mice, B) EAE scores grouped from first symptomatic day for Control EAE >0 mice, C) group averages EAE scores from first symptom until perfusion for EAE >0 KO and EAE >0 Control groups, D) Group average EAE scores based on individual average score per day symptomatic, E) the average number of days from inoculation to presentation of the first symptom for the EAE >0 KO and EAE >0 CONT groups. 2.4.2 Histological Results 2.4.2.1 Myelin: Remyelination blockade causes reduced myelin in the ventral white matter.    Myrf ICKO results in functional deletion of the transcription factor MYRF effectively blocking remyelination (Ben Emery et al., 2009; Emery, 2010). To assess the effect of 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1601234 KO EAE Scores from First SymptomDays Post  First SymptomEAE ScoreF KO 1011F KO 1033M KO 2137M KO 2036M KO 2038F KO 1046KO EAE>0 Control EAE>0010203040Average Days fromInoculation to EAE Onset Days Post Inoculation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1701234EAE average Scores Days Post First SymptomDays Post  First SymptomEAE ScoreKO EAE>0   Control EAE >0 KO EAE>0 Control EAE>00123Average  EAE  Score/ Day SymptomaticEAE ScoreA	 B	C	 D	*	1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1701234Control EAE Scores from First SymptomDays Post  First SymptomEAE ScoreM Cont 2026M Cont 2023F Cont 1112M Cont 2033M Cont 2037E				 63	Myrf ICKO on remyelination three histological analyses were conducted. Using MBP immunohistochemical (IHC) staining, the amount of myelin was quantified in the white matter of the entire spinal cord cross-section (Fig. 2.19), the ventral lip, and areas of focal lesion (Fig. 2.20). The results indicated that there was significantly less myelin in the ventral lip white matter of the KO EAE >0 group (p= 0.018). The results of whole cord white matter and focal lesion analyses did not reach statistical significance (p= 0.21 and p= 0.076 respectively) (Fig. 2.21).    Figure 2.19 MBP IHC Samples images. A) and B) 20 x sample images and whole cord white matter MBP staining in the lumbar spinal cord of KO EAE >0 and Control EAE >0 respectively, C) and D) 20 x sample images of the whole cord white matter MBP staining in the lumbar spinal cord of KO EAE 0 and Control EAE 0 respectively. Animal	1011	KO	EAE	>0		Animal	2026	Control	EAE	>0	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score1011Animal	1013	KO	EAE	0		Animal	1031	Control	EAE	0	Whole	Cord	20x	MBP	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026A	C	 D	B				 64	   Figure 2.20 Sample images the focal lesion and ventral lip MBP staining in the lumbar spinal cord, A) and B) focal lesion example images of KO EAE >0 and Control EAE >0 mice respectively, C) and D) ventral lip example images of KO EAE >0 and Control EAE >0 mice respectively. Animal	1011	KO	EAE	>0	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score10110 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026	Animal	2026	Control	EAE	>0	63x	Focal	lesion	MBP	63x	Ventral	Lip	MBP	A B	C	 D				 65	 Figure 2.21 Myelin analysis and results, A) Graphic representation of the sampling areas for the three analyses conducted, blue represents whole cord white matter, red represents the ventral lip white matter, and green represents the focal lesion white matter B) % MBP+ area of whole cord white matter cross sections data grouped as per Fig. 2.3, C) histograms of the results of the whole cord white matter, D) ventral lip, and E) focal lesion analyses, comparing the KO EAE >0 group to the Control EAE >0 group. 2.4.2.2 DC Size: Remyelination blockade does not cause a reduction in DC size. 	Cortical shrinkage is a symptom of late stage MS generally attributed to the loss neurons and axons (Minagar et al., 2004). To assess the effect of blocked remyelination mediated axon degeneration on white matter tract size; the relative size of the DC was assessed and analyzed. The DC was chosen for this analysis because it is easily anatomically KO EAE >0 Control EAE >0 KO EAE 0Control EAE 0KO EAE  0 FLControl EAE 0 FL 020406080% Myelin Whole Cord White matter X section % MBP+ Area of Total Cord White matter X Section  KO EAE >0 Control EAE >0 010203040% MBP+ Area of Ventral Lip% MBP+ Area KO EAE >0 Control EAE >0 3040506070% Myelin Whole Cord White matterX section KO vs Cont% MBP + Area KO EAE>0 Control EAE>0010203040% MBP+ Area of Focal LesionKO vs Control% MBP+ Area A	 B	C	 E	D	*	P=0.076				 66	identified, well defined, and commonly affected by EAE. Three analyses of relative DC size were conducted; EAE >0 mice were compared with EAE 0 mice regardless of genotype to assess the effect of inflammation alone (Fig. 2.20 C), Myrf ICKO KO mice were compared with Control mice regardless of EAE status to assess for potential non-remyelination based effects caused by mouse genetics (Fig. 2.20 D), and KO EAE >0 mice were compared with Control EAE >0 mice to assess the effect blocked remyelination (Fig. 2.20 E). The results indicated that there were no statistically significant differences in any of the analyses (p = 0.38 Fig. 2.22 D), and p = 0.44 Fig. 2.22 E)): however the EAE >0 vs EAE 0 analysis was very close to significance (p = 0.057) (Fig. 2.22).       EAE>0 EAE 0 02468% DC of Total Cord Area EAE>0 vs EAE 0% DC of Total Cord AreaKO CONT012345678% DC of Total Cord Area% DC of Total Cord Area KO vs CONTKO EAE>0ControlEAE >0 02468% DC of Total Cord Area EAE >0 KO vs Cont% DC of Total Cord AreaKO EAE >0Control EAE >0KO EAE 0Control EAE 0KO EAE 0 FLControl EAE 0 FL 02468%  X Sectional Area % Area of DC of Total Cord AreaA																							Area	of	DC													Total	Crossec/on	area		%	DC	Area=	 x100	B	C	 D	 E	P=	0.057				 67	Figure 2.22 Graphic representation of % DC analysis and results, A) Graphic representation of the sampled areas and method of calculation, B) quantification of the % area of DC of the total area of the spinal cord cross section, grouped as per Fig. 2.3,  C) the results of the EAE>0 vs EAE 0 analysis, D) the results of the Myrf ICKO vs Control group analysis (regardless of EAE status), and D) the results of the KO EAE >0 group compared and the Control EAE >0 group analysis.  2.4.2.3 Microglial Activation: Blocked Remyelination causes increased microglial activation in affected areas.  	Microglial activation is a fundamental aspect of EAE induced inflammatory demyelination (David and Kroner, 2011) and has been shown to increase with Myrf ICKO in mature OLs (Koenning et al., 2012). Because differences in microglial activation can affect axon damage and the severity and duration of EAE disease course, two threshold analyses of IBA1 staining were conducted. To assess Myrf ICKO mediated differences in microglial activation; IBA1 staining was quantified in the whole spinal cord cross-section (Fig. 2.23) and the ventral white matter (Fig. 2.24, A)).   Because threshold analyses cannot distinguish between microglial proliferation and activation, an additional microglial ramification analysis (FFA) (Wilms et al., 1997) was conducted to measure the activation level of individual cells. In their resting, non-activated, state microglial morphology is highly ramified, characterized by a small cell body and many very long, thin, branched processes. As they become activated the cell body enlarges and the processes become shorter and thicker.  In their most activated state 			 68	microglial cells have an amoeboid morphology and closely resemble peripheral macrophages (Karperien and Ahammer, 2013b) (Fig. 2.13).  The assessment of individual cellular ramification state by FFA can be used to determine cellular ramification and by extension microglial activation independent of proliferation. FFA calculations are described in Form Factor analysis in section 2.2.2.3.3.   The results of both threshold analyses indicated no statistically significant differences in IBA1 staining levels between groups (Fig 2.24) in the whole cord cross section (p = 0.34) or the ventral white matter analyses (p = 0.40):  however the FFA indicated that microglia in inflamed white matter areas of KO EAE >0 were significantly more amoeboid than in the Control EAE >0 group (p = 0.03) indicating increased microglial activation (Fig. 2.25).  			 69	  Figure 2.23 IBA1 IHC samples images. 20 x sample images of the whole cord IBA1 staining in the lumbar spinal cord of A) KO EAE >0 B) Control EAE >0, C) KO EAE 0 and E) Control EAE 0 mice.   B	D	C	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score10110 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026Animal	1011	KO	EAE	>0	Animal	2026	KO	EAE	>0	Animal	1013	KO	EAE	0		Animal	1031	Control	EAE	0	Whole	Cord	20x	IBA1	A				 70	 Figure 2.24 Graphic representation of microglial sampling areas, example images, and analyses results: A) sample images of ventral white matter and graphic representation of areas analyzed (green represents the whole cord cross section sampling and red represents the ventral white matter sampling area) and correlated histograms, B) and D) results histograms of % IBA1+ area of the whole cord cross-section and ventral white matter grouped as per Fig 2.2, C) and E) results histograms of the % IBA1+ area of the whole cord cross section and the ventral white matter analyses between KO EAE >0 and Control EAE >0 groups. KO EAE>0 Control EAE>0KO EAE 0 Control EAE 0  KO EAE 0 FLControl EAE 0 FL 0510152025% IBA1+ area of Ventral White Matter% IBA1 + areaKO EAE>0 Control EAE>00510152025% IBA1+ area of Ventral White Matter% IBA1 + areaKO EAE>0 Control EAE>0KO EAE 0 Control EAE 0KO EAE 0 FLControl EAE 0 FL 0510152025%IBA 1 + Area of Whole Cord X Section% IBA1 + areaKO EAE>0 Control EAE>00510152025% IBA1+  area of Whole Cord X section % IBA1  areaA	B	Ventral	White	Ma-er	C	 E	D	Whole		cord	Ventral	White	Ma-er		KO	EAE>0	Ventral	White	Ma-er	Control		EAE>0	63x	 63x				 71	 Figure 2.25 Sample images, analyses and results histograms of the Form Function analysis. A) 63x sample images of resting, moderately activated and highly activated microglia from left to right, B) results of FFA grouped as per Fig. 2.3 and C) results of FFA between the KO EAE >0 and Control EAE >0 groups. 2.4.2.4 Axon Loss: Blocked Remyelination does not causes increased axon loss in the DC or the Ventral White matter.  	Inflammation and demyelination induced axon degeneration is responsible for the nonresolving neurological deficits of MS and EAE (Redford et al., 1997; Shrager et al., 1998; Sadeghian et al., 2016). Timely remyelination of demyelinated axons reduces both the duration of axonal exposure to metabolic stress and the likelihood of degeneration. KO EAE >0Control EAE >0 KO EAE 0Control EAE 0KO EAE 0 FLControlEAE 0 FL0.00.20.40.6Form Factor analysis of Microglial Ramification FF (4πarea/perimeter2)KO EAE>0 Control EAE>0 0.00.20.40.6Form Factor analysis of Microglial RamificationKO vs Control FF (4π x area / perimeter2 )													4π							x					Area											Perimeter			Perimeter		Increasing	Form	Factor	FFA	=	FFA	*	A																4π				x					Area																													Perimeter2												FF	=	B	 C	*				 72	When remyelination is blocked, acute demyelination that would normally only endure transiently, until remyelination occurs, becomes chronic (Ben Emery et al., 2009; Duncan et al., 2017). Chronically demyelinated axons are exposed to energetic deficits for longer periods of time increasing the likelihood of degeneration (Lovas et al., 2000). To assess the effect of blocked remyelination on axon survival, sections of the lumbar spinal cord were quantified in three areas of white matter commonly affected by EAE, the DC, and the VM and VL white matter. To assess tract or axon diameter-specific effects, the data generated were analyzed in three ways: the DC only, the VM and VL together, and the DC, VM and VL combined. Axons were co-stained with antibodies against Nf200 and SMI-312, imaged and counted (Fig. 2.27). The results failed to show any statistically significant differences between the KO EAE >0 and Control EAE >0 groups in any of the areas analyzed (Fig. 2.28, C) p = 0.11, D) p = 0.19 and E) p = 0.15). Sample images of whole cord Nf200/SMI-32 staining in the EAE >0 mice compared with the EAE 0 groups are shown in Fig 2.26. 			 73	  Figure 2.26 Nf200 and SMI-32 IHC Sample images of whole cord staining. A) KO EAE >0, B) Control EAE >0, C) KO EAE 0 and, D) Control EAE 0. Whole	Cord	20x	Nf200/SMI	312		Animal	1011	KO	EAE	>0	Animal	2026	KO	EAE	>0	Animal	1031	Control	EAE	0	Animal	1013	KO	EAE	0		A	 B	C	 D	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score10110 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026			 74	 Figure 2.27 Nf200 and SMI-312 IHC Samples images. Sample 63x images of the ventral white matter Nf200 and SMI-312 staining in the lumbar spinal cord of, A) KO EAE >0, B) Control EAE >0, C) KO EAE 0 and E) Control EAE 0 mice.   Animal	1011	KO	EAE	>0	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score1011Animal	1013	KO	EAE	0			Animal	1031	Control	EAE	0	Ventral		White	Ma8er	63x	Nf200/SMI	312		A	 B	C	 D	Animal	2026	KO	EAE	>0	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026			 75	  Figure 2.28 Graphic representation of the axon count analysis image sampling and results: A) Graphic representation of the sampling areas, B) combined ventral and DC data grouped as per Fig 2.2, C) D) and E) the results of the KO EAE >0 versus Control EAE >0 group axons count analyses in the DC, VM and VL, the VL and VM only, and the DC only, respectively. 2.4.2.5 Axon Damage: Blocked Remyelination does not cause increased axon damage in the DC or the Ventral White matter.  The accumulation of non-phosphorylated neurofilament in axons has been shown to be a reliable indicator of axon damage and impending degeneration (Petzold, 2005; Petzold et al., 2008). In the transition between acute and chronic demyelination axons are exposed KO EAE>0 Control EAE>00200004000060000Nf200/SMI-32 + Axons/mm2 DC onlyNf200/SMI-32+ Axons /mm2KO EAE>0 Control EAE>001000020000300004000050000Nf200/SMI-312+ Axons/mm2 All VentralNf200/SMI-312+ Axons /mm2KO EAE>0 Control EAE>0010000200003000040000Nf200/SMI-312+ Axons/mm2DC,VM & VL Nf200/SMI-312 +Axons /mm2A	KO EAE>0 Control EAE>0KO EAE 0Control EAE 0KO EAE 0 FLControl EAE 0 FL 020000400006000080000Nf200/SMI-312 + Axons/mm2 DC,VM & VLNf200/SMI-312+ Axons /mm2C	B	D	 E	P=0.15	P=0.19	P=0.11				 76	to increasing periods of metabolic stress (Lovas et al., 2000; Irvine and Blakemore, 2008). Timely remyelination can reduce the duration of axon stress, potentially protecting axons from degeneration (Irvine and Blakemore, 2008; Duncan et al., 2009). When remyelination is blocked, all demyelination becomes chronic, exposing more axons to prolonged metabolic stress increasing the likelihood of damage. To assess the affect of blocked remyelination on axon damage, images of SMI-32 IHC staining  (Fig. 2.29) were analyzed in two ways: SMI-32+ axon counts (Fig 2.30) and SMI-32+ area thresholding (Fig. 2.31). Each analysis was divided into sub-analyses that assessed the dorsal white matter only, the ventral white matter only and the dorsal and ventral white matter combined. The results indicated that there were no statistically significant differences in axon damage between EAE >0 KO mice and EAE >0 Control mice in any of the analyses (Fig. 2.30 C) p = 0.15, D) p = 0.42, E) p = 0.06) and (Fig. 2.31 C) p = 0.19, D) p =0.15, E) p = 0.29). 				 77	   Figure 2.29 SMI-32 IHC Samples images. Sample 20x images of the ventral white matter SMI-32 staining in the lumbar spinal cord of, A) KO EAE >0 B) Control EAE >0, C) KO EAE 0 and E) Control EAE 0 mice. Animal	1033	KO	EAE>0		Animal	2026	Control	EAE>0		Animal	1013	SMI-32		KO	EAE	0		Animal	1031	SMI-32		Control	EAE	0		63x	 63x	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score1011Ventral		White	Ma>er	20x	SMI-32	0 10 20 30 4001234EAE Disease Progression and Severity from InnoculationDays Post InnoculationEAE Score2026			 78	 Figure 2.30 Graphic representation of axon damage count analyses: A) Graphic representation of the sampling areas B) quantification of the SMI-32+ axons /mm2 in the combined sampled areas grouped as per Fig. 2.3, C-E) results histograms of SMI-32+ axons /mm2 between the KO EAE >0 and Control EAE >0 groups in the DC, VM and VL, VL and VM only, and the DC only, respectively.  KO EAE>0 Control EAE>0KO EAE 0 Control EAE 0KO EAE 0 FLControl EAE 0 FL 050001000015000SMI-32 + Axons/mm2 DC,VM & VLSMI 32+ Axons/mm2 KO EAE>0 Control EAE>00100002000030000SMI-32 + Axons/mm2 DC OnlySMI 32+ Axons/mm2 KO EAE>0 Control EAE>00200040006000800010000SMI-32 + Axons/mm2 All VentralSMI 32+ Axons/mm2 KO EAE>0 Control EAE>0050001000015000SMI-32 + Axons/mm2 DC,VM & VLSMI 32+ Axons/mm2 A	E	D	C	B				 79	 Figure	 2.31	 Graphic representation of axon damage threshold analysis: A) Graphic representation of the sampling areas B) quantification of the % SMI-32+ area grouped as per Fig. 2.3, C-E) results histograms of % SMI-32+ area between the KO EAE >0 and Control EAE >0 groups in the DC, VM and VL, VL and VM only, and the DC only, respectively.  		KO EAE>0 Control EAE>0KO EAE0  Control EAE 0KO EAE 0 FLControl EAE 0 FL 051015% SMI-32+ Area Ventral White Matter and DC Avg.% SMI-32 + AreaKO EAE>0 Control EAE>005101520% SMI-32 + Area DC% SMI-32+ AreaKO EAE>0 Control EAE>0051015% SMI-32+ Area Ventral White Matter%SMI-32 + AreaKO EAE>0 Control EAE>0051015% SMI-32+ Area Ventral White Matter and DC Avg. % SMI-32 + AreaA	B	C	 D	 E				 80	3 Chapter 3 Discussion and Conclusions As irreversible axon degeneration mediated by diffuse inflammation and energetic stress cause the progressive deficits of MS, therapies that can reduce axon degeneration are important for future treatments of MS (Cole et al., 2017; Motavaf et al., 2017). Remyelination is thought to protect axons from degeneration in an inflammatory MS context: however its’ exact contribution remains unknown (Franklin and Ffrench-Constant, 2008; Franklin and Goldman, 2015). To assess this, I used an active induction model of EAE that approximates the inflammatory demyelinating context of MS and coupled it with a transgenic deletion of the transcription factor MYRF to prevent remyelination. The results of multiple analyses indicate that blocked remyelination caused a delay in EAE symptom onset, a reduction of myelin in the ventral white matter tracts, and increased microglial activation within in inflamed areas, but did not influence axon loss or damage in the dorsal columns or ventral white matter of affected EAE mice, or DC tract size.  3.1 Behavioural Analyses  Of the two behavioural analyses conducted, only the Average Days from Inoculation to First Symptom produced a statistically significant result, indicating that blocked remyelination delayed symptom onset. The first behavioural symptoms of EAE occur when the cumulative effects of inflammatory conduction block and axon degeneration are sufficient to affect motor and sensory function. Because inflammation in EAE begins before the appearance of the first symptom (Sadeghian et al., 2016) and is responsible for both inflammatory conduction block and demyelination, it is likely that differences in 			 81	EAE symptom onset times are mediated by varied inflammation rather than increased susceptibility to degeneration due to blocked remyelination.   It is possible that differences in antigen load between the groups may affect inflammation in the early stages of EAE. It has been shown that in Myrf ICKO OPCs differentiate into OLs but under go apoptosis prior to generating myelin proteins. In the active EAE lesions of normal remyelinating mice OPCs are recruited to the site of demyelination, differentiate and begin to produce myelin proteins (Yeung et al., 2014) which then become are additional substrate for T and B cells present in lesions. The resultant necrotic cell death and increase in extracellular myelin protein debris (Krishnamoorthy and Wekerle, 2009; Murphy, 2011) increases the overall antigen load in the inflamed area. The amount of antigen present directly affects the microglial proliferation, activation, and production of pro-inflammatory cytokines (Jack et al., 2005; Hanisch and Kettenmann, 2007). Therefore, higher levels of antigen may cause increased overall inflammatory tone and associated autoimmune attack. This, in turn, may cause an increase in NO and other ROS that mediate inflammatory conduction block and demyelination, increasing cumulative axon dysfunction, mediating the timing of first symptom onset.   In Myrf ICKO mice OLs undergo apoptosis before generating myelin proteins (Ben Emery et al., 2009). It is possible that both the apoptotic packaging of cellular debris and the reduction in overall myelin protein antigen load may reduce extracellular debris, damage signaling and overall antigen load and delay first symptom onset.  			 82	 In the EAE severity data from inoculation (Fig 2.16 B) we see higher average daily EAE scores later in the disease progression. Although the late symptom onset of the KO EAE >0 group may be partially responsible for the shift in peak EAE severity of this group to a later time point, it does not explain its overall higher severity observed in the EAE from first symptom analysis (Fig. 2.17 C) or the increased severity in the Average severity per day symptomatic analysis (Fig. 2.17 D). Increases in axon degeneration that occur as a result of blocked remyelination in late stage EAE may be one possible explanation for this. In short, it maybe that as EAE progresses and more axons are demyelinated the effect of blocked remyelination may become more pronounced. In normal remyelinating mice, demyelinated axons are restored to normal function by remyelination. This may have the effect of decreasing the overall deficit load by offsetting the effect of new demyelination and result in less severe overall dysfunction and lower EAE scores. In remyelination-blocked mice, demyelinated axons are not restored to normal function and the dysfunction of new demyelination is not offset by recovery, potentially increasing EAE severity. Moreover, in later stages of EAE, chronically demyelinated axons may continue to degenerate after inflammation has subsided, this may prolong neurological dysfunction and reduce post-attack recovery.   In summary, it is possible that Myrf ICKO induced changes in the inflammatory environment, both acutely and chronically, that may cumulatively explain delayed EAE symptomatic onset (Fig 2.16 B) and increased EAE severity (Fig 2.17 C). It would be possible to test for this by assessing inflammatory differences in the first week following 			 83	inoculation by, immunostaining for differences in the amount of myelin proteins (such as PLP and MOG), the microglial marker IBA1 and the T-cell marker CD-3, and western blotting for the inflammatory cytokine Il-17.   Similarly, assessing for the same inflammatory markers mentioned above, coupled with the axon damage (SMI-32) and degeneration (Caspase-6) markers in membrane reporter Myrf ICKO EAE mice, at 21 and 28 days post inoculation, would allow the quantification of the inflammatory state and axon damage and apoptosis associated with remyelination block during the peak of EAE. This approach may help to determine if differences in axonal degeneration alter the inflammatory state in the later stages of EAE progression.  3.2 	Histological Analyses In these experiments a series of histological analyses were performed to determine the effect of Myrf ICKO on, remyelination, DC size, microglial activation and axon damage and survival. The results of the myelin analyses indicated that affected Myrf ICKO mice had significantly less myelin than Control EAE >0 mice in the affected ventral white matter suggesting that Myrf ICKO did reduce remyelination as seen in other experiments (Duncan et al., 2017). Two other analyses of myelin in whole cord white matter (p = 0.21) and focal lesions (p = 0.08) did not yield significant differences between groups. This inconsistency may be due to differences in the sampling methods used. The inclusion of unaffected areas of white matter in the Whole Cord White matter analysis and the small sample area in the Focal Lesion analysis may have reduce differences between groups. This suggests that threshold based sampling must be conducted in an 			 84	affected area large enough to exclude local variation but focal enough to eliminate the inclusion of unaffected areas.    The results of the analysis for DC size yielded no significant differences in the three analyses conducted. However, although not statistically significant, there appeared to be a trend toward larger DC areas (p = 0.057) (Fig. 20 C) in EAE >0 mice. This may be due to on going microglial activation and proliferation during our relatively acute sample time frame. It is possible that, the infiltration and proliferation of activated immune cells may have enlarged the DC in the EAE >0 group, masking any tract reduction due to axon loss. An interesting follow-up to this study would be a repetition of the current experiment and analyses over a much longer, chronic, time frame. Beyond the acute window, the initial inflammation and microglia activation/proliferation may subside exposing the hypothesized DC shrinkage. Interestingly, this approach may also serve as a model for the overall loss of brain volume seen in late stages of MS when remyelination has failed and inflammation subsided (Minagar et al., 2004).   To assess the effects of blocked remyelination on inflammation, three analyses of microglial activation were conducted. The results were inconsistent: two analyses failed to reach significance and one was successful. Both thresholding analyses yielded no significant differences while the ramification analysis (FFA) indicated greater microglial activation in Myrf ICKO mice. The simplest explanation for this may be that inflammatory attacks in EAE occur somewhat randomly and can vary in severity; therefore, a given sampled area can be either increasing in inflammatory tone or resolving 			 85	depending on the inflammatory state of the specific area sampled and the overall EAE disease progression (Lassmann and Wisniewski, 1979; Kornek et al., 2000; Lassmann et al., 2001). Additionally, differences in the specific sampling methods used could result in inconsistencies; samples of larger areas (Whole Cord White Matter and Ventral White Matter analyses) may be affected by the inclusion of areas of non-inflamed tissue and sampling on a smaller scale, and individual cell sampling  (Form Factor Analysis) may be affected by small sample size and local variation.   Interestingly, there was a trend, although not statistically significant, toward higher average microglial activation in Myrf ICKO mice in all three analyses. This suggests that Myrf ICKO may have had a proinflammatory effect on innate immune activity. Increased innate immune cell activation has been reported in an experiment ablating Myrf from OLs under the PLP promoter (Koenning et al., 2012). Although I have cited reduced inflammation as a potential cause of delayed first symptom presentation in the discussion of the behavioral results, Myrf ICKO may have had the opposite effect in later stages of disease progression. As EAE becomes chronic, acute axon dysfunction is exchanged for chronic axon degeneration resulting in a progressive increase in axon debris and damage signaling later in EAE disease progression. Because the axons of Myrf ICKO mice remain demyelinated they are more susceptible to degeneration, particularly in the later stages of EAE, this may result in the greater accumulation of axon debris causing increased damage signalling, inflammation, microglial activation and autoimmune demyelination, potentially explaining the increased EAE severity seen in Fig. 2.17B) and Fig. 2.18 C) and D).  			 86	 Alternately, because Myrf ICKO mice had a delayed EAE first symptom presentation it is possible that the delayed mice were still in early stages of EAE, characterized by increasing inflammation, when tissue was samples, while their control counter parts, with normal onset, were resolving at the same time. Therefore, although it may appear as though Myrf ICKO mediated increased inflammation, it is possible that the higher average activation was an artifact of delayed EAE onset.   The results of the Axon Loss analysis indicated no significant differences in axon quantification between groups, suggesting that remyelination blockade did not affect axon survival in inflammatory demyelination. One explanation for this unexpected finding may be that, axon degeneration occurs incrementally from early inflammation until its resolution. Mice with later onset (KO EAE >0) may have lost fewer axons compared to mice with normal EAE onset (Control EAE >0) on the same day post inoculation. Additionally, variation in the progression of inflammation from lesion to lesion can also result in varied axon survival within different areas of the same spinal cord section. This may have influenced the results of the quantifications reducing the likelihood of achieving significance.   Although significant differences where not found, the fact that Myrf ICKO mice had a lower average number of axons in all three analyses suggests an affect may have been present but obscured by the issues cited above. Statistical analysis of the Nf200/SMI-			 87	312+ axon counts in the DC, VM and VL, and the combined DC, VM, VL resulted in p-values of 0.15, 0.19 and 0.11 respectively.    To assess axon damage three analyses were conducted on each of two quantifications. Contrary to expectation, the results indicated no significant differences in any of the 6 analyses. Although significant differences where not found, the fact that Myrf ICKO mice had a higher average number of damaged axons in all but one analysis suggests an affect may be present. Statistical analysis of the SMI-32+ axon count in the DC generated a p-value of 0.063, just outside significance. Here again, it is likely that differences in EAE onset may have influenced the data gathered. Because axon damage occurs progressively it is possible that later onset animals (predominantly Myrf ICKO) may not have reached peak axon damage at the time of tissue sampling resulting in artificially low measurements, similar to the mechanism proposed for the axon loss quantification.   Additionally, demyelinated axons in remyelination-blocked mice with normal EAE onset may proceed through the damage stage and begin to degenerate more quickly than remyelination capable mice. This may result in a shorter window to catch axon damage and result in a lower quantification of damaged axons than expected. Taken together, delayed EAE onset and the effects of Myrf ICKO on axon damage progress may have affected the quantification enough to reduce group differences below statistical significance. A potential solution for future experiments may be to take tissue samples from mice based on the number of days post first symptom rather than post inoculation and to measure axon damage acutely, during the initial stages of remyelination before 			 88	more rapid axon degeneration and reduced duration of damage marker expression can affect the quantification. 3.3 Limitations 	The most serious limitation encountered during these experiments was the inability to reliably induce consistent EAE. In the main experiment only 7 of the 59 mice developed EAE, with widely variable onset times yielding a small sample size and differences in EAE disease state between mice at the time of perfusion (Fig. 2.17 A)). One of the many factors that can influence EAE induction is the combination of peptide and mouse strain. In these experiments the genetic construct PDGFRα CreERT2 was generated on two background strains, C57BL/6 and SJL, the other two constructs were based wholly on the C57BL/6 strain. Reliable EAE induction requires the pairing of mouse strain with a specific peptide sequence. Because the induction method used here (MOG 35-55) is specific for the C57BL/6 strain (Papenfuss et al., 2004; Stromnes and Goverman, 2006) the inclusion of the SLJ strain in the these mice may have affected the EAE induction efficiency.  Secondly, the dearth of EAE >0 mice generated in the main experimental group caused an additional limitation by affecting the type of statistical analysis available for use. The original numbers of mice (3 KO and 3 Control) was so small parametric data distribution could not be assessed, excluding the use of parametric statistical testing. To address this shortfall a supplementary experimental group that yielded a further 5 EAE >0 mice (3 KO and 2 Control) was added. When these supplementary data were combined with the main group data, parametric data distribution was achieved using the Kolmogorov-			 89	Smirnov Goodness-of-Fit Test (KS normality test). However, because the animals of this combined grouping were run in separate experiments it is possible that outside confounding factors may have been introduced potentially differentially affecting the experiments. 3.4 Conclusions In interpreting these results, I concluded that: blocked remyelination does not affect EAE severity but does delay EAE on set time, reduces myelin in demyelinated areas, and increased microglial activation in inflamed areas. Furthermore, blocked remyelination does not affect the size of the DC, axon loss or damage. However, due to the limitations of these experiments I believe that further investigation is necessary before stronger claims may be made. Perhaps a recapitulation of the experiment using the transgenic constructs generated on an entirely C57BL/6 strains (now available), and the experimental modifications suggested in the behavioural and histological discussion sections may eliminate may of the problems encountered here and generate more significant results.   However, if these results are considered outside a strictly statistically significant interpretation, the p-values and overall consistency indicate that there may have been an effect that was obscured by the limitations of the experiments. This suggests that remyelination blockade may have had a greater impact on microglial activation, axon survival and damage and EAE disease severity than the results indicate. 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