Stem-Like Cells and Glial Progenitors in the Adult Mouse Suprachiasmatic Nucleus

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STEM-LIKE CELLS AND GLIAL PROGENITORS IN THE ADULT MOUSE SUPRACHIASMATIC NUCLEUS

Dilshan H. Beligala

A Dissertation

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

December 2019

Committee:

Michael E. Geusz, Advisor

Pascal Bizarro Graduate Faculty Representative

George S. Bullerjahn

Howard C. Cromwell

Paul F. Morris

Dilshan H. Beligala

Michael E. Geusz, Advisor

Reports have described cells with stem-like protein expression in the hypothalamic suprachiasmatic nucleus (SCN), which contains the principal circadian pacemaker of the body.

Additionally, there are oligodendrocyte progenitor cells (OPCs) scattered throughout the SCN and other brain areas with reported abilities to differentiate into neurons and glia. The SCN is a particularly good structure for studying adult neurogenesis because its cellular manipulation has known quantifiable effects on specific parameters of circadian rhythms. The objectives of this study were to characterize stem and progenitor cells in the SCN and to study neurogenesis from

SCN OPCs in vitro. We first performed a meta-analysis to identify the expression of stem cell- related genes in the SCN and then used defined serum-free media for inducing stem and progenitor cell proliferation in SCN explant cultures, identified by immunocytochemistry and confocal microscopy. In the meta-analysis, we analyzed 25 genes associated with stem cell maintenance and increased motility, out of which over 90% were expressed at higher levels in the SCN than in other brain areas. In explant cultures maintained in stem and progenitor cell medium (SPM), cells expressed stem cell proteins: SOX2, nestin, MSI2 and OCT4. Explant cultures had ongoing mitotic activity and extensive cell loss. Despite neuronal loss, tissue remained viable for over 7 weeks in culture, as shown by bioluminescence imaging. The circadian rhythm in SCN gene expression persisted in brain slice cultures in SPM. SCN explants maintained in NeuralX medium supporting OPC proliferation, formed a cell monolayer and a suspended cell culture that included 87% OPCs. These cells were then induced to differentiate into neurons, which were identified by immunocytochemistry and electrical impulses recorded with microelectrode arrays. In differentiating cultures, a subset of OPCs formed iv oligodendrocytes that myelinated nascent neurons. These results provide evidence that the mature SCN has cells with regenerative properties providing plasticity that may enable circadian rhythms to adjust to changing environmental timing cues, seasonal behavioral cycles or aging.

These immature cells can be used to prepare an SCN cell line that may provide a consistent source of rhythmic cells that would enable simpler genetic manipulation of key mammalian clock genes. v

I would like to dedicate this work to my family and my mentors

for being great pillars of support vi ACKNOWLEDGMENTS

On the very outset of this dissertation, I would like to extend my sincere and heartfelt gratitude to all the personages who have helped me in this endeavor. Without their guidance, help and motivation, this would not have been a success.

First and foremost, I would like to pay my gratitude to my advisor, Associate Professor

Michael E. Geusz, for his time and effort spent on continuously leading, advising and encouraging me throughout this research. His passion for challenges has given me inspiration, his vast knowledge has given me guidance and his enthusiasm in research has given me motivation. I truly feel lucky to work under the supervision of such a talented advisor.

I am extremely thankful for my committee members, professors George S. Bullerjahn,

Paul F. Morris, Howard C. Cromwell. and Pascal Bizarro, whose stimulating motivation and valuable ideas were extremely helpful in completing my research successfully. They have been a constant source of knowledge and support throughout the years.

Further, I am indebted to my collaborators Dr. Rae Silver (Columbia University), Dr.

Joseph LeSauter (Columbia University), Dr. Astha Malik (Cincinnati Children’s Hospital), Dr.

Peter Lu (BGSU) and Ms. Lorena Alvarez (BGSU) for their immense contribution towards my research experiments and publications. I would also like to acknowledge the undergraduate students who helped me with data analysis throughout the years: Mr. Hugh J. McQuillen, Ms.

Hayley Ruff, Ms. Erin Tepe, Mr. Ifeanyichukwu Amujiogu, and Ms. Amanda Fairbairn.

In addition, I gratefully acknowledge the support of all the academic and non-academic staff members in the Department of Biological Science, Bowling Green State University, especially Ms. Dorothy Laforce, Ms. Susan Schooner, Ms. Chris Hess and Mr. Steve Queen for their kindness and support in all administration and technical issues. I would also like to thank

Ms. Jenifer Baranski of the BGSU Animal Care Facility for all the help with animal care and Dr.

Marilyn Cayer for her support in confocal imaging. vii Furthermore, I am grateful to all the current and past Geusz lab members: Mr. Arpan De,

Mr. Tyler Birkholz, and Ms. Katarina Coulson. I feel lucky to have the opportunity to work with such friendly lab mates.

Finally, my deepest gratitude goes to my loving parents (Mr. Samarasinghe Beligala &

Ms. Renuka Ranaweera), my brother (Mr. Lakshan Beligala) and my wife (Ms. Gayathri

Beligala) for their support in my studies and for being there with me through thick and thin. I am forever indebted to all that they have done for me. Without their endless support and unconditional love, I wouldn’t have achieved this much. Thank you for being around and for never ending motivations I’ve been getting all this while. viii

TABLE OF CONTENTS

Page

CHAPTER I: INTRODUCTION ...... 1

The Suprachiasmatic Nucleus (SCN) ...... 1

Adult Neural Stem Cells (NSCs) ...... 5

Adult Neurogenesis in the Brain ...... 7

Adult Neurogenesis in Brain Regions other than DG and SVZ ...... 9

Evidence of Cells with Stem Cell or Developmental Properties in the Adult Rodent

SCN ...... 12

CHAPTER II: A META-ANALYSIS CHARACTERIZING STEM-LIKE GENE

EXPRESSION IN THE SUPRACHIASMATIC NUCLEUS AND ITS CIRCADIAN

CLOCK ...... 14

Preface ...... 14

Introduction ...... 14

Materials and Methods …………………………………………………………… .. 18

Databases Queried ...... 18

Procedure for Selecting Candidate Stem Cell-Related Genes ...... 19

Results and Discussion ...... 20

FSS Analysis ...... 20

Evaluating Transcription Factors Expressed at High Levels in the SCN ...... 25

Genes Expressed in the SCN That Serve in Stem Cell-Regulating Pathways 28

Stem Cell-Related Genes Regulating SCN Circadian Rhythm Output or Phase

Shifts through Cell-Cell Coupling ...... 33

Summary of Candidate Stem-Like Gene Activity in Adult Mouse SCN ...... 36 ix

Conclusions ...... 39

CHAPTER III: MUSASHI-2 AND RELATED STEM CELL PROTEINS IN THE MOUSE

SUPRACHIASMATIC NUCLEUS AND THEIR POTENTIAL ROLE IN CIRCADIAN

RHYTHMS………………………...... 40

Preface ...... 40

Introduction ...... 40

Materials and Methods ...... 43

Animals ...... 43

Microdissected SCN Explant Cultures and Immunocytochemistry (ICC) .... 43

Live/Dead Staining ...... 52

Explant Bioluminescence Imaging ...... 52

Bioinformatics Analysis ...... 53

Results ...... 61

Culture in SPM Causes Morphological and Cellular Changes in SCN

Explants ...... 61

SCN Cells Express Multiple Stem Cell-Related Proteins ...... 62

SCN Explant Cultures Express Stem Cell and Progenitor Cell Markers ...... 66

Bioinformatics Indicate Significant MSI2 and RNA-Binding Protein Functions

in SCN ...... 66

Circadian Rhythms Persist in the SCN of Brain Slice Cultures Maintained in

Stem Cell Medium ...... 68

Discussion ...... 72

The SCN Expresses Many Proteins Found in Partially Differentiated Cells . 72 x

Partially Differentiated SCN Cells may Provide Developmental and Adult

Neuroplasticity ...... 75

Elevated Expression of Stem Cell Marker MSI2 in the SCN Suggests

Significant RNA Processing Occurs in Circadian Clock Cells ...... 78

MSI2 may Control SCN Cells by Regulating miRNA ...... 83

Stem-Like Cells Persist in SCN Explant Cultures Made from Mice of Different

Mouse Strains and Across a Wide Age Range ...... 84

Conclusions ...... 85

CHAPTER IV: OLIGODENDROCYTE PROGENITOR CELLS FROM THE ADULT

MOUSE SUPRACHIASMATIC NUCLEUS FORM NEURONS WITH ONGOING

MYELINATION IN VITRO………………………...... 86

Introduction ...... 86

Materials and Methods ...... 87

Animals ...... 87

Microdissected SCN Explant Cultures and Differentiation Studies ...... 88

Immunocytochemistry (ICC) and Confocal Microscopy ...... 88

Microelectrode Array (MEA) Recordings ...... 90

Results ...... 91

OPCs, which are Scattered in the SCN, Migrate from the Explant Edge,

Proliferate, and Form a Monolayer ...... 91

Cells in the Monolayer Express OPC and Proliferation Markers ...... 93

Cells in the Monolayer Have the Potential to Differentiate into Neurons or

Oligodendrocytes Depending on Culture Media ...... 95

Cells of BP-Treated Cultures on MEAs Produce Neural Impulses ...... 104 xi

Discussion ...... 106

Conclusions ...... 108

CHAPTER V: CONCLUSIONS AND FUTURE DIRECTIONS………………………… 109

Summary of Conclusions ...... 109

Limitations ...... 109

Relevance to Medical Fields ...... 111

Future Directions ...... 112

REFERENCES……………………………………………………………………………… 113

APPENDIX A: SUPPLEMENTAL FIGURES…………………………………………… . 144

APPENDIX B: COPYRIGHTS ...... 146

APPENDIX C: LIST OF ABBREVIATIONS ...... 150

APPENDIX D: IACUC APPROVAL ...... 153

xii

LIST OF FIGURES

Figure Page

1 Neuronal circuitry of the SCN ...... 2

2 The cell-autonomous molecular feedback loop generating circadian rhythms in the

SCN ...... 4

3 Cell division and differentiation capacity of NSCs ...... 6

4 Locations of the DG, SVZ, RMS and OB in a sagittal view of the adult mouse

brain ...... 7

5 Expression of SOX2 in the SCN ...... 13

6 Summary of possible interactions between the SCN circadian clock and genes

associated with stem cells and neurogenesis ...... 38

7 SCN explant cultures in stem cell medium ...... 45

8 Stem cell markers provide additional evidence of neural stem cells and progenitor

cells in the SCN and SCN explant cultures ...... 49

9 Cells expressing MSI2 and GFAP in SCN ...... 51

10 Proportions of cells expressing stem cell proteins in the SCN and SCN explant

cultures ...... 64

11 Bioluminescence imaging of SCN brain slices maintained in SPM ...... 70

12 Cells expressing OPC markers identified in the SCN and after they migrate from the

SCN explant edge, proliferate, and form a monolayer ...... 92

13 Cell monolayers seeded from explants in OPM and then expanded express OPC markers

and cell proliferation marker PCNA ...... 94

14 Cells in the monolayer form neuron-like and glial-like cells after treatment with BP and

NLQ, respectively ...... 96 xiii

15 Cells produce markers for neurons and neuroblasts after treatment with BP medium to

induce differentiation ...... 98

16 Some OPCs differentiate into oligodendrocytes in BP medium and appear to provide

myelination to nascent neurons ...... 101

17 Cells produce markers for mature oligodendrocytes and astrocytes when treated with

NLQ medium to induce differentiation ...... 103

18 OPC cultures produce neural impulses after differentiation in BP medium ...... 105

xiv

LIST OF TABLES

Table Page

1 Genes expressed in adult mouse SCN selected from the Fine Structure Search ...... 21

2 SCN-enriched transcription regulator genes identified by Hatori et al., 2014 ...... 26

3 Fold change in gene expression in the SCN relative to contrast areas examined through

Differential Search analysis ...... 29

4 List of antibodies used ...... 47

5 RNA-binding, circadian, and stem cell properties of selected genes expressed in mouse

SCN ...... 54

6 MSI2 knockout (KO), knockdown (KD), and overexpression (OE) studies ...... 80

CHAPTER I: INTRODUCTION

The Suprachiasmatic Nucleus (SCN)

Nearly all living organisms need to alter their metabolism, physiology and behavior to adapt to daily and seasonal environmental changes. In mammals, this task is accomplished by a body-wide system of circadian oscillators present in all major organs. The suprachiasmatic nucleus (SCN) of the hypothalamus (Figure 1A) is the principal circadian pacemaker that functions to sustain and synchronize all the body clocks to each other and to solar time (Hastings et al. 2019).

The SCN, which is mainly made up of small diameter neurons, is located lateral to the third ventricle and superior to the optic chiasm. It is divided into two anatomical subdivisions: a ventrolateral ‘core’ region and a dorsomedial ‘shell’ region (Figure 1A). The core neurons receive and integrate external inputs from three major pathways: the retinohypothalamic tract

(RHT), the geniculohypothalamic tract from the thalamus and projections from the raphe nuclei.

Many of the core neurons express the neuropeptides vasoactive intestinal polypeptide (VIP) or gastrin-releasing peptide (GRP), whereas most of the shell neurons express arginine vasopressin

(AVP) or prokineticin 2 (PK2). The core neurons relay the information received from external inputs to the rest of the SCN and other hypothalamic regions using VIP, GRP or GABA (Figure

1B) (Colwell 2011).

Figure 1: Neuronal circuitry of the SCN. A. The SCN has two anatomical subdivisions as a ventrolateral core region and a dorsomedial shell region. B. The core neurons receive external inputs from three major pathways: the retinohypothalamic tract (RHT), the geniculohypothalamic tract from the thalamus and projections from the raphe nuclei. The core neurons relay the information received from external inputs to the rest of the SCN and other hypothalamic regions using VIP, GRP or GABA. The shell neurons communicate with other hypothalamic regions using AVP, PK2 or GABA. Adapted and modified from: Colwell, Nature

Reviews Neuroscience (Colwell 2011)

In the SCN, generation of circadian rhythms in gene expression is regulated by a cell- autonomous molecular feedback loop (Figure 2). The transcription factors, circadian locomotor output cycles kaput (CLOCK) and brain and muscle ARNT-like protein 1 (BMAL1) constitute the positive arm of this molecular clockwork, whereas the proteins, period (PER) and cryptochrome (CRY), constitute the negative arm (El Cheikh Hussein, Mollard, and Bonnefont

2019). The cycle begins when the CLOCK–BMAL1 protein complexes bind the E-box and activate the transcription of period (Per1, Per2 and Per3) and cryptochrome (Cry1 and Cry2) genes. The PER and CRY protein levels peak in the early night when they translocate back into the nucleus to deactivate the CLOCK–BMAL1 transcriptional activation of their own genes.

These proteins are degraded following ubiquitylation, opening the capacity for another cycle to begin. Most of the SCN cells contain this feedback loop regulating a rhythmic expression of a number of clock-controlled genes (CCGs) (Hastings et al. 2019; Hastings, Maywood, and

Brancaccio 2018; Colwell 2011). There is also an additional stabilizing loop which modulates the Bmal1 mRNA levels. This loop mainly consists of circadian nuclear receptors REV-ERBs and retinoic acid receptor-related orphan nuclear receptors (RORs), that compete for the

RORs/REV-ERBs-response elements (RREs) in the Bmal1 promoter. These RREs also can regulate the rhythmic expression of CCGs (Cha et al. 2019).

Figure 2: The cell-autonomous molecular feedback loop generating circadian rhythms in the SCN. In the molecular feedback loop (core loop), the CLOCK–BMAL1 protein complexes bind the E-box and activate the transcription of period (Per1, Per2 and Per3) and cryptochrome

(Cry1 and Cry2) genes. The PER and CRY proteins translocate back into the nucleus to deactivate the CLOCK–BMAL1 transcriptional activity. The stabilizing loop mainly consists of circadian nuclear receptors REV-ERBs and RORs and modulates Bmal1 mRNA levels. Both the feedback loop and the stabilizing loop regulate a rhythmic expression of a number of CCGs.

Adapted and modified from: Cha et al., Frontiers in Molecular Neuroscience (Cha et al. 2019)

Adult Neural Stem Cells (NSCs)

NSCs are self-renewing and multipotent cells that can generate neurons and glial cells within the nervous system. It is now well established that NSCs are functional not only during embryonic development, but also in the adult brain of all mammals. The process of generating new functional neurons or glia from adult NSCs and integration of these new cells into existing neural circuits is referred to as adult neurogenesis. Neurogenesis in the adult brain was first described by Joseph Altman (Altman and Das 1965) and it was studied more as a machinery to repair injured brain.

Adult NSCs have the ability to transition between quiescent and active states and when activated, they can undergo either symmetric division or asymmetric division (Figure 3).

Asymmetric division can give rise to an NSC and a progenitor while symmetric division can result in producing two NSCs or two progenitors. Progenitors can be fate restricted or multipotent (Bond, Ming, and Song 2015).

Figure 3: Cell division and differentiation capacity of NSCs. Adult NSCs can divide symmetrically or asymmetrically giving rise to one of the three main cell types of the nervous system: a neuron, an astrocyte or an oligodendrocyte. Adapted and modified from: Bond et al.,

Cell Stem Cell (Bond, Ming, and Song 2015)

Adult Neurogenesis in the Brain

The NSCs that ultimately generate neurons and glial cells are maintained by paracrine and extracellular matrix factors within a “niche” that regulates their symmetrical (self-renewing) and asymmetrical (differentiating) cell divisions (Porlan et al. 2013; Kazanis et al. 2010; De

Filippis and Binda 2012). In the adult mammalian brain, there are two known neurogenic niches, the subventricular zone (SVZ) of the lateral ventricles and the subgranular zone (SGZ) within the dentate gyrus (DG) of the hippocampus (Figure 4).

As differentiating cells are formed, the neural precursors (neuroblasts) migrate away from the niche to join nearby neural circuits, as in the DG, or much further away, as in the SVZ (Gage

2000). Neurons generated in the SVZ, migrate through the rostral migratory stream (RMS) to the olfactory bulb (OB) and become olfactory interneurons (Konefal, Elliot, and Crespi 2013; Braun and Jessberger 2013). These new OB neurons function in odor discrimination and odor-reward association (Obernier and Alvarez-Buylla 2019). In contrast, neurogenesis in the SGZ produces dentate granule cells that are incorporated into nearby neural circuits in the hippocampus.

Figure 4: Locations of the DG, SVZ, RMS and OB in a sagittal view of the adult mouse brain. NSC niches are shown in green and the neuroblast migratory path is shown in red. Adapted from: Braun and

Jessberger, Frontiers in Biology (Braun and Jessberger 2013)

SVZ is the largest NSC niche in the adult brain. There are four main cell types that constitute the SVZ: neuroblasts (Type A cells), SVZ astrocytes (Type B cells), immature

8 precursors (Type C cells) and ependymal cells. NSCs in this region are a special type of SVZ astrocyte, and there are approximately 7000 of these Type B cells per lateral wall of the lateral ventricles. Type B cells produce about 10,000 migrating interneurons (neuroblasts or Type A cells) every day in young adult mice through the generation of transit-amplifying intermediate progenitors (Obernier and Alvarez-Buylla 2019; Doetsch 2003). The renewal and differentiation of SVZ astrocytes are regulated by a variety of signaling molecules coming from multiple and varied sources. These sources include immediate NSC niche, cerebrospinal fluid, choroid plexus and a variety of nearby and distant neuronal sources (Obernier and Alvarez-Buylla 2019).

In the SGZ, NSCs reside in a germinal layer between the DG and the hilus. There are

SGZ astrocytes in hippocampal foci closely associated with blood vessels and they function as the primary precursors of neurons. These SGZ astrocytes differentiate to form granule cells via

Type D cells (Doetsch 2003).

Adult neurogenesis plays an important role contributing to brain plasticity, which helps animals to regulate seasonal cycles in physiology and behavior to cope with variations in the environment (Migaud, Butrille, and Batailler 2015). As a consequence of this and other important functions, adult neurogenesis can cause different disease conditions when altered.

There are several reports describing impaired adult neurogenesis involved in neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and Huntington's disease (Winner and

Winkler 2015). Decreased adult hippocampal neurogenesis has also been shown to cause impaired learning, memory and affective behavior in animal models (Steiner, Tata, and Frisén

2019). Furthermore, there is a possibility that several brain disorders in humans such as age- dependent cognitive decline, major depressive disorders and medial-temporal lobe epilepsy are also caused by dysregulation of adult hippocampal neurogenesis (Toda et al. 2019).

Adult Neurogenesis in Brain Regions other than DG and SVZ

Over the past few decades, there were several reports describing adult neurogenesis in discrete brain regions outside the two main neurogenic niches, SVZ and DG. Neurogenesis has been reported in the neocortex, olfactory bulbs, piriform cortex, amygdala, striatum, substantia nigra, dorsal vagal complex, ependymal cells of the third ventricle, median eminence (tanycytes), choroid plexus, and hypothalamus (Nogueira et al. 2014; Migaud et al. 2010).

The hypothalamus is an important homeostatic structure that regulates various physiological functions including reproduction, food and water intake, thermoregulation and circadian rhythms. Over the past two decades, the hypothalamus has gained more attention among the studies exploring adult neurogenic niches in the brain. Recent evidence of neurogenesis in adult hypothalamus suggests it could alter this structure’s control of homeostatic behaviors. Hypothalamic plasticity in response to neurogenesis is a transformative concept that could provide new research tools to investigate neural control of behavior and regulation of synapses.

There are reports describing newborn neurons in the hypothalamus of various mammals including the mouse, rat, sheep, vole and hamster. Nascent neurons have also been reported in median eminence, arcuate nucleus and ventromedial nucleus of the human hypothalamus

(Maggi, Zasso, and Conti 2015; Migaud, Butrille, and Batailler 2015). The hypothalamus expresses high levels of the proteins nestin and polysialylated neural cell adhesion molecule

(PSA-NCAM), both of which have functions related to neural plasticity (Migaud et al. 2010).

NG2 cells are the most likely candidates for hypothalamic neural stem cells, although

NSCs more closely resembling those of the SVZ and SGZ also reside in adult mouse hypothalamic nuclei, including the SCN. Hence, there are two or more types of stem or progenitor cells that may coexist in the SCN and the hypothalamus. NG2 cells were previously

10 considered to be a population of oligodendrocyte progenitor cells (OPCs), but recent studies show that they also include cells that differentiate into functional neurons and astrocytes

(Belachew et al. 2003). They form close interactions with neurons and receive synaptic input through various neurotransmitters (Hill and Nishiyama 2014; Wenjing Sun and Dietrich 2013;

Larson, Zhang, and Bergles 2016). It has been reported that some of the adult-born functional neurons in the hypothalamus are derived from NG2 glial cells distributed throughout the mediobasal hypothalamus. Neurogenesis in the hypothalamus is also indicated by studies showing constitutive BrdU incorporation into NG2 cells and hypothalamic neurons of adult mouse brain that co-localizes with SOX2 (a transcription factor that is essential of maintaining pluripotency of embryonic stem cells) and DCX (a microtubule-associated protein involved in neuroblast migration during development) (Robins et al. 2013). Also, nestin-positive and DCX- positive cells are present in the human hypothalamus along with cells positive for the cell proliferation marker Ki-67. NG2 cells proliferate and differentiate rapidly in response to stressors or brain injury, but also provide much of the ongoing mitotic activity of the brain (Geha et al. 2010).

The hypothalamic SCN that contains the master circadian clock is a particularly good structure for studying adult neurogenesis because its cellular manipulation has known quantifiable effects on specific parameters of circadian rhythms, most often assayed through locomotor activity (Evans and Gorman 2016). Equally important, the SCN has unusual gene expression patterns suggesting its neuronal phenotypes are mutable and circuitry is more plastic than in other hypothalamic nuclei.

SOX2, SRY (sex determining region Y)-box 2, is a transcription factor with multiple roles during mammalian development. Its expression is generally reduced in the adult brain.

Doublecortin (DCX) is a microtubule associated protein expressed in differentiating and

11 migrating immature neurons. Previous studies have shown that both SOX2 and DCX are expressed in the adult SCN suggesting the presence of stem-like cells (Geoghegan and Carter

2008; Saaltink et al. 2012; Hoefflin and Carter 2014). Three possibilities could explain the presence of stem cell-related proteins such as SOX2 and DCX in the SCN:

(a) Neurogenesis occurs gradually at a moderate rate that might significantly influence the

timing network if the nascent cells are key components. There is currently no

information suggesting that only a few cells can substantially alter the rhythm, and no

neurogenesis within the adult SCN has been convincingly described, although

neurogenesis has been reported in other areas of the adult hypothalamus (Sooyeon Yoo

and Blackshaw 2018). However, studies using BrDU injection into the third ventricle and

other markers described new neurons forming in the mouse hypothalamus (D. A. Lee and

Blackshaw 2012; Nogueira et al. 2014; Robins et al. 2013). The SCN was not

mentioned, but the diffuse BrDU distribution throughout the hypothalamus could include

the rostral SCN (Robins et al. 2013). Similar to neurogenesis in the adult hippocampus,

nascent neurons with heightened excitability could alter SCN rhythms when they join

existing networks (Schreiber and Newman-Tancredi 2014; Migaud et al. 2010).

(b) The SCN has latent neurogenesis abilities that are triggered episodically in response to

infrequent external or internal signals or stressors that lead to adaptive adjustments in

circadian timing. Changing seasonal or reproductive demands on the SCN’s ability to

regulate metabolism and behavior might require this plasticity. For example, trauma,

stress, dietary factors, and the circadian cycle evoke greater adult neurogenesis in the DG

beyond ongoing, basal rates (R. L. Zhang et al. 2007; Gleason et al. 2008; Luo et al. n.d.;

Carlén et al. 2009).

alter adult SCN cell network properties even without resulting in substantial

neurogenesis. Strongly associated with stem cells and neurogenesis are structural changes

of cells enabling the motility observed in the embryonic brain, e.g. RMS, and in the well-

established areas of adult neurogenesis in the SGZ of the hippocampus and the SVZ.

This plasticity includes altered cell-cell adhesions, cytoskeleton, and extracellular matrix.

Similar cell transformations through stem-like states occur in the epithelial-to-

mesenchymal transitions of cancer cells.

Evidence of Cells with Stem Cell or Developmental Properties in the Adult Rodent SCN

The adult rodent SCN shows evidence of cells with stem cell or developmental properties, distinguishing it from neighboring hypothalamic nuclei by its “neotenic”, less mature state. The SCN contains an unusually high number of cells expressing SOX2 (Figure 5) (Lein et al. 2007), DCX, and DCX-like protein, which are involved in neurogenesis (Saaltink et al. 2012).

Also, it has a lower expression of the mature neuron marker NeuN relative to other brain areas, suggesting that many of the neurons are functional but remain in an unusual, less differentiated state (Morin, Hefton, and Studholme 2011). In addition, according to in situ hybridization results in the Allen Brain Atlas, the SCN shows a higher expression of several genes that serve in stem cell maintenance or neurogenesis that are not typically expressed at these levels in other hypothalamic areas. Three striking examples are Neurod2, which regulates neuronal differentiation, Msi2, a commonly used marker for NSCs, and Dlk1, a NOTCH1 ligand secreted from specialized SVZ astrocytes and present on neural stem cells (Morin, Hefton, and Studholme

2011). The expression of most of these genes in the adult SCN has yet to be characterized, which is one of the main purposes of this study.

Figure 5: Expression of SOX2 in the SCN. A sagittal section of the mouse brain from the Allen

Brain Atlas showing the elevated expression of SOX2 in the SCN by in situ hybridization. Image credit: Allen Brain Institute Mouse Brain Atlas (Experiment number: 79677365)

Several reports describe cells with stem-like characteristics in the SCN that could be undergoing differentiation into neurons or glial cells. New neurons introduced into SCN neural circuits could modify circadian timing in response to changes in day length, nutrient availability or seasonal cycles. Although the SCN contains individual circadian clock cells with intrinsic timing abilities, their synaptic and, possibly, paracrine interactions modulate rhythms, making them more stable and setting the phase and period. By identifying and isolating SCN NSCs a cell line could be prepared to provide more consistent and powerful studies of the molecular circadian timing mechanism and the intercellular communication that modulates circadian rhythms in neural activity (Porlan et al. 2013).

CHAPTER II: A META-ANALYSIS CHARACTERIZING STEM-LIKE GENE EXPRESSION

IN THE SUPRACHIASMATIC NUCLEUS AND ITS CIRCADIAN CLOCK

Preface

This chapter was originally published as a research article in BioMed Research

International June 2018 (Beligala, De, and Geusz 2018). The original publication has been altered to meet BGSU’s specifications for formatting a dissertation. This publication identifies stem cell related genes expressed in the SCN.

Introduction

Circadian rhythms that control daily behavior and physiology of mammals are regulated by a timing system in which multiple circadian clocks in the organs and tissues interact with a master clock in the suprachiasmatic nucleus (SCN) of the hypothalamus (Abrahamson and

Moore 2001; Guilding and Piggins 2007; Silver and Kriegsfeld 2014). The SCN is a relatively small brain area positioned just beyond the optic chiasm where it receives signals directly from the retina. These light signals and additional synaptic and hormonal inputs entrain the SCN’s clock so that the circadian system remains synchronized to predictable daily events in the environment.

Along with its role in processing light signals and generating circadian rhythms, the SCN has an additional distinctive feature that has not yet been explained. Many of its cells express an unusual number of genes that would be expected in fetal and early postnatal brains but not in mature brain tissue other than the few areas in which elevated ongoing and induced adult neurogenesis occurs. For example, SOX2 is a common cell-specific marker for the stem cell state

(Venere et al. 2012) and is also expressed in the adult SCN (Hoefflin and Carter 2014). Ube3a gene expression colocalizes with SOX2 expression in the adult SCN. When mutated it causes neural developmental disorders and sleep disruption, possibly through its actions on core clock

15 proteins (Jones et al. 2016), which could indicate a role for SOX2 in the adult SCN by association. Doublecortin (DCX) and doublecortin-like (DCL) proteins are usually found in neuroblasts undergoing a final differentiation into neurons and radial glial cells, but their genes are also expressed in the adult SCN (Geoghegan and Carter 2008; Saaltink et al. 2012). Several of these neurogenesis-related genes regulate each other. For example, virus-driven SOX2 expression induces DCX-positive neuroblasts, and induced pluripotent stem cells made from astrocytes show a sequence of differentiation from SOX2 through DCX expression (Niu et al.

2015). Six3 is expressed in developing brain and its loss prevents SCN formation, yet it is also expressed prominently in adult SCN cells (VanDunk, Hunter, and Gray 2011). Furthermore, the

SCN’s unusually low expression of NeuN (Rbfox3) (Geoghegan and Carter 2008), a marker for mature neurons, also suggests that many SCN neurons may not be in a fully differentiated state.

Nevertheless, SCN neurons are adequately mature to generate spontaneous action potentials in robust circadian rhythms (Mohawk and Takahashi 2011).

A puzzling aspect of these stem-like features is that the adult SCN shows conspicuous expression of stem cell marker proteins but lacks obvious neurogenesis (Antle, LeSauter, and

Silver 2005). Because most SCN histological studies have relied on animals maintained under highly regulated laboratory and animal care conditions it is possible that the SCN has a neurogenesis program that is initiated more often in animals experiencing their natural environment and in response to episodic stressors and challenges throughout the lifetime

(Sominsky et al. 2018). Here, we provide evidence that the SCN’s unique stem-like state reflects immature cells that retain a degree of plasticity allowing them to adaptively rearrange neuronal circuitry responsible for modifying the SCN’s circadian rhythms. Several researchers have reported that cell-cell contact, the extracellular matrix, and synaptic plasticity alter the SCN circadian clock’s period and entrainment (Prosser et al. 2003; Iyer, Wang, and Gillette 2014;

Evans and Gorman 2016), and the circadian clock can in turn regulate synaptic strength

(Chaudhury, Wang, and Colwell 2005). We also examine here the possibility of a latent feature of SCN cells to undergo episodic adult neurogenesis when appropriate conditions arise.

The SCN network of circadian clock cells is a heterogeneous population of neurons and glial cells. There has been substantial progress in explaining the intracellular timing mechanism within individual SCN clock cells, but mathematical modeling is needed to understand how the ensemble output of multiple SCN neurons determines the pattern of circadian timing information reaching the rest of the brain and body (Azzi et al. 2017). Several network models of coupled

SCN clock cells include flexibility of neuron interactions and their responses to external demands on the animal (Mirsky et al. 2009; Hafner, Koeppl, and Gonze 2012; Mieda et al. 2015;

Bordyugov et al. 2015). Examining all of the most probable circuit modulators is needed to understand how the collective rhythmic pattern originates within the SCN cell network. Clearly,

GABA neurosecretion is important in forming the ensemble circadian rhythm along with synaptic transmission within and between large populations of neurons producing vasoactive intestinal polypeptide (VIP), arginine vasopressin (AVP), gastrin releasing peptide (GRP), and calretinin (CR) or calbindin (Azzi et al. 2017; Jobst, Robinson, and Allen 2004; Itri and Colwell

2003; Maywood et al. 2006; Hughes et al. 2015). Nevertheless, several other nonneuronal cell types play important but poorly defined roles (Slat, Freeman Jr., and Herzog 2013; Leone et al.

2015). Astrocytes interdigitate between SCN neurons, likely modulating synaptic strength, and display circadian rhythms in expression of the astrocyte marker glial fibrillary acidic protein

(GFAP) (Lindley et al. 2008). Consequently, a much clearer understanding of how the SCN adjusts its circuitry to modulate rhythmic output requires a broader examination looking beyond neurons and encompassing cell interactions of intrinsically rhythmic and nonrhythmic network components (Brancaccio et al. 2014).

The SCN timing signals that essentially schedule appropriate animal behavior relative to local time originate mostly within a population of SCN neurons that are most notable for their arrangement in a dorsomedial “shell” area surrounding a distinct ventrolateral “core” of cells

(Abrahamson and Moore 2001). Although numerous neuropeptides are expressed within the

SCN, the shell is notably dominated by neurons expressing AVP, whereas cells in the core express GRP and conspicuous levels of VIP, which is found in few other brain areas. Substantial evidence supports retinal axons projecting principally to the core, but also to other SCN cells.

VIP receptors of shell neurons respond to core neurons, and shell AVP neurons communicate with VIP neurons as well as each other (Evans and Gorman 2016; Piggins and Cutler 2003).

These connections provide tight coupling of the circadian clocks within cells receiving these timing signals and possibly others more indirectly connected through cell interactions not yet well understood. Furthermore, several studies have supported a plasticity in the phase relationships between the shell and core SCN, particularly while the SCN clock responds to light exposure by either advancing or delaying its phase (Mohawk and Takahashi 2011).

Otherwise, the SCN seems to lack organized arrangements of synapses or cell bodies like those of cortical areas, cerebellum, olfactory bulb, etc. in which cell layers and fiber tracts are understood to convey specific information relevant to each brain substructure. Although clustering of locally interacting SCN neurons of specific phenotypes has been described (Evans and Gorman 2016), any rigidly defined cell connectivity remains elusive, despite patterns of rhythmic neural activity and gene expression indicating information passing between areas

(Evans et al. 2015). Although not conclusive, this apparently looser SCN architecture raises the possibility of cell motility and rearrangement of cell contacts. Several studies have examined

SCN expression of proteins considered important in cell-cell communication other than through neurosecretion (Lee et al. 2015), and the evidence indicates they alter the period of ensemble

SCN rhythms and responses to retinal light signals. Adjustments in SCN cell interactions modify rhythmic behavior and may be needed adaptively to survive changing seasonal conditions or altered food availability.

This study was initiated to provide a more comprehensive assessment of stem cell marker proteins and related cell contact proteins in the mouse SCN based on published reports and databases describing the SCN transcriptome. Cells that are partially differentiated or have undergone dedifferentiation, as cancer cells do prior to metastasis, are known to express a distinct set of proteins indicating loss of endothelial cell connectivity and greater interaction with the extracellular matrix and other cell types. If modifying cell-cell contacts is important for basic

SCN timing functions, then it can be predicted that SCN cells do express a substantial number of the known proteins supporting these connections and their maintenance, including proteins conspicuous in cancer. Results presented here describe several genes of these poorly differentiated cell types that are expressed in the SCN and are promising candidates for additional exploration of circadian network properties.

Materials and Methods

Databases Queried

Descriptions of major functions of mouse genes and their human orthologs were derived primarily from the following databases: GeneCards (http://www.genecards.org/), Gene Ontology

(GO) Consortium (http://www.geneontology.org/) (Ashburner et al. 2000), PANTHER

(http://pantherdb.org/) (Mi, Muruganujan, and Thomas 2013), and Entrez from the National

Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/) (Sayers et al. 2012).

Images showing in situ hybridization (ISH) results in sections of the adult mouse brain were obtained from the Allen Institute Mouse Brain Atlas (ABA) and are available online at http://mouse.brain-map.org/ (Lein et al. 2007).

Procedure for Selecting Candidate Stem Cell-Related Genes

To select for candidate genes with a role in stem cells and related cell-cell interaction the genes listed in the Fine Structure Search (FSS) of the ABA were examined. The FSS provides a curated list of genes expressed at high levels in a user selected brain area and ranks the genes based on their expression level and whether they are predominately expressed in that location when compared with other brain areas. A set of genes producing gene regulators reported to have enriched expression in the mouse adult SCN by Hatori et al., 2014 (Hatori et al. 2014), was also examined. These genes and the SCN FSS genes were evaluated further based on a search of the

PANTHER database, where Complete GO Bioprocess (BP) listings were explored. BP terms relevant to development, differentiation, stem cell maintenance, cell-cell contact, or contact with extracellular matrix related to stem cells were gathered. Any terms relevant to the nervous system were selected first. Some related bioprocesses relevant to these stem cell target areas were not included in the resulting list because of space limitations. The candidate genes selected because of their GO BP attributes were tested further using the Differential Search feature of the

ABA to determine their expression level in the SCN versus several brain areas.

The same genes were also examined in CircaDB and SCNseq online databases. CircaDB provides the expression of mouse and human genes at time intervals throughout the circadian cycle and also enables statistical analyses (http://circadb.hogeneschlab.org/) (Pizarro et al. 2013).

The SCNseq database provides gene expression data over a 24-hour cycle from SCN of mice maintained in cycles of 12 hours of light and 12 hours of dark, thereby including additional light- driven gene expression (http://www.wgpembroke.com/shiny/SCNseq/) (Pembroke et al. 2015).

Finally, the selected candidate genes and additional relevant genes of interest were evaluated through the Differential Search feature of the ABA that provided the fold change in expression between the SCN (target area) and various contrast areas.

Results and Discussion

FSS Analysis

Genes listed in the FSS, which are principally expressed in the SCN and at high levels, were screened for any described role in development, differentiation, stem cell maintenance, cell-cell contact, or contact with extracellular matrix related to stem cells. The list includes obvious intrinsic cell membrane proteins and not only denizens of the extracellular space, but also intracellular cell signaling molecules mediating cell-cell contact information. Of the 47 genes in the FSS, 17 were found to have a role in stem cells or closely related processes (Table

1).

Genes with only a role in chemical or electrical synaptic communication were not included. Nevertheless, the targeted biological processes were well represented in the SCN transcriptome relative to other hypothalamic structures (Table 1). For some of the genes the lack of evidence showing involvement in stem-like properties may be because of few reported studies describing their functions.

Any mentioned role in circadian rhythms was included in Table 1, and the phase of any of the genes reported to display a significant circadian rhythm in expression was included, as shown by the phase of the oscillation’s peak as reported in CircaDB. Furthermore, the phase of the peak expression in mice maintained in a light/dark cycle was included along with an indication of whether the oscillation had a statistically significant fluctuation according to

SCNseq results.

Table 1. Genes expressed in adult mouse SCN selected from the Fine Structure Search Circadian LD Gene symbol and PANTHER GO Biological Process FSS phase in phase Fluctuating name (GO BP Complete) ranking SCN in SCN in LD (hours) (hours) Lhx1 (LIM nervous system development, cell-cell 2 ND1 6 No2 homeobox protein signaling 1) Rorb (RAR- regulation of circadian rhythm, amacrine 6 6 0 Yes related orphan cell differentiation, retina development in receptor beta)3 camera-type eye, negative regulation of osteoblast differentiation

Rora (RAR- regulation of circadian rhythm, regulation 10 (7) 6 Yes related orphan of smoothened signaling pathway, receptor alpha)3 cerebellar Purkinje cell differentiation, negative regulation of fat cell differentiation Flrt3 (fibronectin neuron projection development, synapse 13 8 0 Yes leucine rich organization, fibroblast growth factor transmembrane receptor signaling pathway, axon protein 3) guidance, cell adhesion, response to axon injury, synapse assembly, embryonic morphogenesis, neuron projection extension, cell-cell adhesion via plasma- membrane adhesion molecules, positive regulation of synapse assembly Zic1 (zinc finger nervous system development, regulation 14 (8) 5 No protein of the of smoothened signaling pathway, spinal cerebellum 1) cord development, adult walking

behavior, central nervous system development, cell differentiation Btg1 (B cell positive regulation of myoblast 16 (5) 8 Yes translocation gene differentiation, positive regulation of 1, anti- endothelial cell differentiation proliferative) Spon1 (spondin 1, cell adhesion 19 ND 9 No extracellular matrix protein) Dlk1 (delta-like1 post-embryonic development, negative 21 ND 0 Yes homolog regulation of fat cell differentiation, Drosophila) negative regulation of Notch signaling pathway, osteoblast differentiation Neurod2 regulation of synapse maturation, nervous 22 ND 13 Yes (neurogenic system development, positive regulation differentiation2)4 of neuron differentiation, regulation of neuron differentiation, associative learning, cerebellar cortex development, behavioral fear response, positive regulation of synaptic plasticity, cell differentiation, cellular response to electrical stimulus Igfbp5 (insulin- negative regulation of muscle tissue 24 (10) 6 Yes like growth factor development, negative regulation of binding protein 5) osteoblast differentiation, striated muscle cell differentiation, osteoblast differentiation, negative regulation of cell migration

Thsd7b anatomical structure morphogenesis, 26 ND 22 Yes (thrombospondin, ectoderm development5 type I, domain containing 7B) Msi2 (musashi stem cell development 32 ND 8 No RNA-binding protein 2)6 Nkd1 (naked positive and negative regulation of 34 ND 2 No cuticle 1 homolog canonical Wnt signaling pathway, Drosophila) spermatogenesis, cell differentiation Myt1 (myelin post-embryonic development, nervous 35 ND 20 No transcription factor system development, cell differentiation, 1) endocrine pancreas development Zfhx3 (zinc finger nervous system development, cerebellar 36 1 6 No homeobox 3) Purkinje cell differentiation, embryonic retina morphogenesis in camera-type eye, cell-cell signalling

Cdh13 (cadherin calcium-dependent cell-cell adhesion via 46 10 20 No 13) plasma membrane cell adhesion molecules, endothelial cell migration, positive regulation of cell-matrix adhesion, positive regulation of cell migration Pcsk2 (proprotein nervous system development 49 ND 13 No convertase subtilisin/kexin type 2)

Boldface indicates a gene also present in Table 2. 1Lhx1 expression does shows a rhythm with a 32-hour period in the mouse SCN by JTK analysis (CircaDB). Acceptable circadian periods in this study were 19-30 hours. 2Lhx1 is suppressed by light (Hatori et al. 2014). 3Circadian clock-related or core clock gene. 4Neuronal differentiation marker. 5Only the GO slim annotation was available. 6Stem cell marker. ND = no significant rhythm detected in CircaDB using the JTK test. () = average phase when phases from multiple experiments were reported by CircaDB for circadian rhythms in the SCN.

Evaluating Transcription Factors Expressed at High Levels in the SCN

As an additional evaluation of the stem-like properties of the SCN we examined the gene expression results of Hatori et al. (2014), who identified 13 transcription regulator genes that have elevated expression in the SCN (Hatori et al. 2014). Interestingly, nine of these enriched genes are involved in stem cells or development according to gene annotations in PANTHER

(Table 2), and only two of the 13 genes did not show a relevant gene association—Gatad2b

(GATA zinc finger domain containing 2B) and Hsf2 (heat shock factor 2). As in Table 1, any gene showing significant circadian rhythms was indicated by the phase of the rhythm’s peak, and the peak expression in mice maintained in a light/dark cycle was included along with indication of any significant amplitude

Table 2. SCN-enriched transcription regulator genes identified by Hatori et al., 2014 (Hatori et al. 2014) Circadian LD Gene symbol and PANTHER GO Biological Process Fluctuating name phase phase (GO BP Complete) in LD (hours) (hours) Dlx2 (distal-less cerebral cortex GABAergic interneuron ND 8 No homeobox 2) differentiation and fate commitment, negative regulation of Notch signaling pathway

Dlx6 (distal-less inner ear morphogenesis, epithelial cell ND 8 Yes homeobox 6) differentiation, positive regulation of epithelial cell proliferation

Foxd1 (forkhead box axon guidance, positive regulation of kidney ND 6 No D1) development, positive regulation of bone morphogenetic protein signaling

Lhx1 (LIM nervous system development, cerebellar Purkinje ND 6 No homeobox protein 1) cell differentiation, cell-cell signaling, embryonic retina morphogenesis in camera-type eye

Nr2f2 (nuclear neuron migration, forebrain development, 10 6 Yes receptor subfamily 2, anterior/posterior pattern specification group F, member 2)

Rora (RAR-related cerebellar granule cell precursor proliferation, (7) 6 Yes orphan receptor cerebellar Purkinje cell differentiation, circadian alpha) regulation of gene expression, cellular response to tumor necrosis factor, regulation of smoothened signaling pathway, negative regulation of fat cell

differentiation, muscle cell differentiation, T-helper 17 cell differentiation

Rorb (RAR-related amacrine cell differentiation, retina development in 6 0 Yes orphan receptor camera-type eye, regulation of circadian rhythm beta)

Six3 (sine oculis- negative regulation of neuron differentiation, ND 6 Yes related homeobox 3) circadian behavior, neuroblast differentiation and migration, negative regulation of Wnt signaling pathway

Sox1 (SRY (sex neuron migration, forebrain neuron differentiation, ND 6 Yes determining region nervous system, development Y)-box 1) 3

Sox11 (SRY (sex positive regulation of neuron differentiation, glial (15.5) 6 No determining region cell development, positive regulation of Y)-box 11) neurogenesis, positive regulation of hippo signaling, positive regulation of stem cell proliferation

Tle4 (transducin-like Wnt signaling pathway ND 2 Yes enhancer of split 4) Boldface indicates genes also listed in Table 1. Circadian phases are from CircaDB. ND = no significant rhythm detected in CircaDB using the JTK test. () = average phase when phases from more than one experiment were reported for a rhythm in the SCN. Acceptable circadian periods were between 19-30 hours. Phases in light/dark cycle (LD) and significance of daily fluctuations are from SCNseq.

Because it was not a focus of this study, BP annotations for gene regulation were not typically included. Some of the genes (Dlx2, Lhx1, Nr2f2, Rora, Six3, Sox1, Sox11) have a large number of BP annotations for stem cell processes including differentiation and stem cell maintenance outside the nervous system, which were not listed here. Some of the reports of stem-like properties include artificial manipulations outside embryonic or fetal development such as the ability of Foxd1 to reprogram induced pluripotent stem cells (Koga et al. 2014).

Genes Expressed in the SCN That Serve in Stem Cell-Regulating Pathways

Table 3 provides additional evidence that the genes in Tables 1 and 2 are expressed at higher levels in the SCN relative to other brain areas and so are likely to have a function relevant to SCN properties including the circadian clock. Genes in Tables 1 and 2 were explored further through the Differential Search feature of the ABA with the SCN serving as the target structure and various other brain areas serving as the contrast structure. The fold expression shown is the target gene expression divided by the contrast structure expression. If expression was considered by the routine to be absent in either structure, no value was returned. Such was the case for Lhx1, which was expressed almost entirely in the SCN. Only coronal data were included to avoid comparisons across different SCN subregions. Many of the genes in Table 2 that were not in

Table 1 did not generate a result because they either were missing from the ABA (Sox1) or were not included in experiments using coronal sections (Dlx6, Foxd1, Nr2f2, Six3, Sox1, Sox11) or were otherwise unavailable (Dlx2).

Table 3. Fold change in gene expression in the SCN relative to contrast areas examined through Differential Search analysis

Gene Fold change in the SCN compared to contrast region symbol SO LPO PVH PVHd ARH DG Btg1 9.097 4.689 1.579 4.099 0.339 0.231 3.554- 1.585- 2.704 1.033- 1.291- 2.509- Cdh13 6.873 2.852 3.584 23.019 4.947 Dlk1 4.535 4.479 1.628 1.32 1.067 123.262 Flrt3 25.477 2.969 14.839 5.19 3.383 0.721

Igfbp5 10.391 7.541 3.416 2.868 2.321 1.34

Lhx1 NE NE NE NE NE NE

Msi2 5.175 2.019 2.333 10.993 2.456 3.7

Myt1 3.055 2.825 1.323 1.08 1.062 0.944

Neurod2 3.517 4.373 2.807 NA 3.845 0.855

Nkd1 1.964 5.242 0.88 0.7 2.079 2.685

Nr2f2 2.292 4.411 NE 4.844 1.476 2.362

Pcsk2 3.872 NE 0.941 1.028 1.506 0.944

Rora 16.865- 22.593- 3.44- 1.919- 16.377- 8.694- 29.842 22.99 9.991 6.545 18.926 11.126 Rorb 35.538 19.534 8.161 18.822 9.207 32.208

Spon1 1.629 1.865 1.562 1.076 0.82 0.612

Thsd7b 4.586 0.755 0.566 NE 4.101 1.595

Tle4 40.204 13.117 NE 20.09 3.658 0.915

Zfhx3 5.525 3.685 2.379 1.803 1.659 9.041

Zic1 2.47 1.839 0.639 NE 29.025 2.416

% of genes with 100 94.7 78.9 94.4 89.5 63.2 higher SCN expression Bold indicates where the contrast area had higher expression. The range of fold change is shown when more than one experiment was available for comparison. The maximum number of experiments per gene was three or less. NE: no significant expression in the contrast area. NA: target area expression was not available. SO: supraoptic nucleus, LPO: lateral preoptic area, PVH: paraventricular hypothalamic nucleus, PVHd: PVH descending division, ARH: arcuate nucleus of the hypothalamus, DG: dentate gyrus.

It was clear from the Differential Search results that the candidate genes are expressed at higher levels in the SCN than the hypothalamic nuclei examined. As listed in Table 3, large percentages of the candidate genes were expressed in the SCN relative to the contrast areas. Both the paraventricular hypothalamic nucleus (PVH), which receives SCN neuronal projections, and the PVH descending division (PVHd) showed far lower expression of nearly all of the candidate genes. Expression of nearly all of these genes was greater in the SCN than the arcuate nucleus of the hypothalamus (ARH), a structure with reported adult neurogenic abilities (Sominsky et al.

2018; Yoo and Blackshaw 2018). The percentage of genes expressed at a higher level in the SCN declined when it was compared with the dentate gyrus (DG, 63%), which was not surprising considering the large number of stem cell-related genes expressed in this well-established site for rodent adult neurogenesis. Nevertheless, the replicate experiments provided in the ABA for some of the candidate genes in Table 3 showed a large range of fold change indicating that this approach is effective for comparing two structures but is at best semiquantitative.

Interestingly, all but five of the genes in Table 3 (Dlk1, Lhx1, Pcsk2, Rora, Rorb) were visibly expressed in the rostral migratory stream structure that delivers neuroblasts to the olfactory bulb where they differentiate into interneurons (Sun, Kim, and Moon 2010). This observation provides additional evidence that many of the candidate genes serve a function related to neurogenesis. It is possible that the mobile or altered cell interaction properties of neuroblasts are maintained in SCN cells by these and related genes, whether or not they fully differentiate into mature neurons.

Tables 1 and 2 also provide evidence that stem cell-regulating pathways are involved in maintaining SCN stemness. For example, Nkd1, Six3, and Tle4 expression serves in Wnt signaling. Interestingly, stem cell replication in the mouse intestine is controlled by circadian rhythms in WNT secretion from Paneth cells (Matsu-Ura et al. 2016). The gene annotations also

32 showed that expression of Dlk1 and Zic1, which along with Rora regulate smoothened homolog

(Smo), is linked to hedgehog pathways (Aruga 2004). The ABA reveals moderate expression of

Sonic hedgehog (Shh), Indian hedgehog (Ihh), and Desert hedgehog (Dhh) in the SCN based on visual inspection of ISH in brain sections.

Genes coding for Notch proteins were expressed weakly in the SCN according to the intensity of ISH signals in the ABA. Nevertheless, there was evidence for noncanonical Notch expression. For example, Dner (Delta/Notch-like EGF repeat containing) is highly expressed in the SCN, suggesting that it may have a role in processes relevant to the SCN such as responses to photic sensory signals or production and modulation of circadian rhythms. Dner is expressed at relatively lower levels in some but not all neighboring brain areas. A Differential Search in the

ABA found 17.75, 0.824, and 0.577-fold expression in the SCN when compared with the SO,

LPO, and PVH, respectively. It was expressed only 0.702-fold in the SCN relative to the DG.

Similarly, strawberry notch homolog 1 (Sbno1) was expressed moderately in the SCN. A

Differential Search found that Sbno1 is expressed at higher levels in the SCN than the PVH and

SO (2.495- and 7.166-fold, respectively) and only 0.288-fold when compared with the DG, most likely because of its possible role in DG neurogenesis. Members of a gene family expressing important regulators of Notch signaling (Adam10, 11, 15, and 23) showed moderately high expression in the SCN and other hypothalamic nuclei following visual inspection. Thus, many of the components related to the Delta/Notch signaling pathway are induced in the SCN. Additional studies should determine which of these genes act together in a functional pathway to regulate stem-like cells and possibly suppress differentiation.

Additional genes in the FSS list that should be examined for possible roles in altering

SCN cell interactions are Epha6 (Eph receptor A6) and Blcap (bladder cancer associated protein). EPHA6 protein maintains communication between adjacent cells, and Epha6 expression

33 is under circadian control in the SCN according to CircaDB. Blcap counters cell proliferation by increasing apoptosis. These two genes along with Zfhx3 and several others in the FSS are also involved in cancer cell activity (Mao et al. 2018) and others, such as Btg1 and Dlk1 control cell division, a process more relevant to a tumor than a neural structure not currently considered a site of cell renewal.

Why there is a pattern of gene expression in the SCN that overlaps genes expressed in stem cells and cancer cells remains unclear other than the generally undifferentiated state of cancer cells and cancer stem cells, in particular (Batlle and Clevers 2017). To dissect this pattern more finely, studies could differentiate between stem-like properties of the SCN that are more closely associated with cancer stem cells and those of noncancerous embryonic or adult stem cells. Similarly, selecting genes showing preferred expression in gliomas rather than glial cells could further define the pool of stem-like genes expressed in the SCN. The resulting set of potentially interacting genes might reveal what functions this population serves.

Stem Cell-Related Genes Regulating SCN Circadian Rhythm Output or Phase Shifts through

Cell-Cell Coupling

It is well established that manipulation of genes expressing core proteins of the circadian clock timing mechanism or genes that regulate these proteins can alter or even eliminate the circadian rhythm’s period within the SCN (Wegner et al. 2017). Substantial research has shown that circadian clocks of organisms depend on individual cells endowed with these intrinsic circadian timing abilities. It is commonly stated that circadian clocks are present within nearly all cells of the body, but some cells and tissues lack an ability to sustain normal circadian rhythm generation without close proximity to other cells (Noguchi, Wang, and Welsh 2013) or intermittent synchronizing timing signals from more robust and sustained clocks such as the one in the SCN (Harmar 2003). Many cell lines, for example, will show their abilities to express a

34 circadian rhythm after synchronization of their circadian oscillators with agents that induce cell signaling pathways and gene expression such as dexamethasone, forskolin, or a “serum shock” in which a high level of serum is delivered transiently to cells previously deprived of serum

(Balsalobre, Damiola, and Schibler 1998; Balsalobre, Marcacci, and Schibler 2000; Sharma,

Anderson, and Geusz 2014). These “resetting” methods bring the individual circadian clocks, which presumably are within nearly all the culture’s cells, to a common phase of the cycle. This synchronization activates genes serving within the central circadian timing mechanism and is much like the ability of strong photic stimuli to reset circadian clocks within animals or animal populations to a common circadian phase.

Circadian rhythms have been recorded in cell lines without using resetting procedures, which suggests there is either spontaneous synchronization through intercellular communication or an unintended delivery of a timing signal (Zeitgeber) such as the stimulation imposed by culture medium exchange (Sharma, Anderson, and Geusz 2014; Welsh et al. 2004). Circadian rhythms recorded in cell cultures, tumor spheroid cultures, and tissue explant cultures in the absence of a specific synchronizing treatment suggest that cell-cell communication can bring circadian clocks within cells of a culture into a common phase and maintain them in a coherent rhythm (Mohawk and Takahashi 2011; Jobst, Robinson, and Allen 2004).

The SCN in brain slices maintained as explant cultures expresses many cycles of circadian activity without need for a synchronizing agent, providing further evidence of the tight coupling between its cellular clocks. Nevertheless, that coupling can be weakened, resulting in a reduced rhythm amplitude and loss of circadian behavioral activity rhythms controlled by the

SCN. This influence on cell-cell coupling was reported by knocking out the Lhx1 gene in mice, which appears to regulate cell interactions through VIP and possible SCN cell interactions with the extracellular matrix (Hatori et al. 2014; Bedont et al. 2014). Lhx1 expression in the SCN is

35 also suppressed by retinal light exposure (Hatori et al. 2014). Lhx1 has emerged as an important potential regulator of cell coupling within the SCN with effects on period and phase shifts.

Evidence provided here suggests that it is among a group of genes that function in maintaining the stem-like state of cells and associated alterations in cell shape and motility.

Stem cells and migrating cancer cells show altered cell-cell interactions because of a switch in their gene expression patterns, producing distinct morphological alterations including the epithelial-to-mesenchymal transition (EMT) of migrating or metastatic cancer cells (Batlle and Clevers 2017; Shibue and Weinberg 2017). Proteins that serve in cell-cell interactions also modify the SCN’s rhythmic output, supporting the idea that the stem cell-like state of SCN cells functions in providing plasticity of circadian timing. In addition to Lhx1, Zfhx3 expression is reported to regulate coupling between SCN neurons (Parsons et al. 2015). Lhx1 serves in SCN development and when it is knocked out in the SCN the rhythmic output is disrupted, circadian locomotor activity is diminished, and peptidergic neurons (VIP, AVP) that provide rhythmic output are fewer (Hatori et al. 2014; Bedont et al. 2014; Costello et al. 2015). When the transcription factor ZFHX3, which functions in neurulation and neuronal terminal differentiation, is knocked out in the adult SCN the wheel-running rhythm in constant darkness is shortened by over an hour or becomes completely arrhythmic (Wilcox et al. 2017).

One example of a gene family that is altered substantially during EMT is the cadherins, and interestingly Cdh13 (cadherin 13) is listed in the FSS because of its high expression in the

SCN. Another Table 1 gene that invites further scrutiny for its possible role in SCN rhythm modification is Flrt3 (fibronectin leucine rich transmembrane protein 3), which has many roles in cell-cell contact control and synapse plasticity. This gene should be examined further because of the SCN’s major glutamatergic retinal afferents and the role of FLRT3 in altering glutamate synapse development (O’Sullivan et al. 2012). One question is whether FLRT3 maintains or

36 modifies SCN afferents in the adult. Evidence indicates that interfering with the polysialylated derivative of neural cell adhesion molecule (NCAM), which alters cell-cell contacts and glutamatergic synapses, prevents retinal light signals and other synchronizing stimuli from shifting the phase of the SCN clock (Prosser et al. 2003).

Summary of Candidate Stem-Like Gene Activity in Adult Mouse SCN

One additional question is whether some of the candidate stem cell genes are expressed in the same cells, where their products may interact. We observed in the ABA that the candidate genes were expressed in cells with different morphologies and distributions in the SCN, ranging from rounded neuron-like cells to much smaller cells and cells resembling astrocytes.

Nevertheless, the candidate genes could serve in coupling between cell types within networks that include the established interactions through VIP and AVP, providing additional modifications of SCN rhythms and phase shifts in response to light.

Potentially, the in situ gene expression data examined in Tables 1 and 3 included light- induced expression as well. We can presume that the mice used for the ABA were euthanized during exposure to visible light, and probably this was during the animal’s daytime. Therefore, it should be considered that all of the expression values shown in the tables could represent, to a variable extent, the light-induced state of the genes. In Tables 1 and 2, we included an estimate of the responsiveness of the candidate genes to light from data in SCNseq. A more thorough examination of light-dependent responses of the genes in Table 2 can be found in Hatori et al.,

2014 (Hatori et al. 2014).

The phases of gene expression in Table 1 that were significantly rhythmic in the SCN of mice maintained in darkness are presented in Figure 6. Significant clustering of phases was detected by Rayleigh test (Z=4.22, p=0.011) and Rao test (U=177, p< 0.05). Six of the genes in

Table 1 have highest expression near the time of maximal expression of core clock genes Rora

37 and Rorb (6:00-7:00), suggesting that they are under similar circadian control. Lhx1 also shows maximal expression at 6:00 and has an estimated 32-hour period, just outside the circadian range considered here. Because Rora and Rorb are induced by BMAL1 and CLOCK it is likely that many of the other candidate stem cell genes are regulated through this same transcription factor complex or indirectly by this clock output pathway. It is also possible that the SCN’s circadian rhythm in intracellular Ca2+ levels or the elevated neuronal firing rate preceding this phase induces expression of some of these genes. Whatever function the stem-like state of the SCN provides may be explored best by addressing why these clock-controlled genes are most active during this portion of the cycle. It has been suggested that SCN cells of mice and perhaps other night-active animals reorganize their connections during the night and that gene expression during the day is in preparation for the circuit plasticity that follows (Hatori et al. 2014). This possibility might explain the phase of candidate gene expression maxima during the day.

Figure 6: Sumary of possible interactions between the SCN circadian clock and genes associated with stem cells and neurogenesis. Left: Circadian phases of SCN stem cell related genes. Phases of maximal expression of rhythmic genes from Tables 1 and 2 are shown

(arrowheads). Significant clustering was around 7:59 as shown by the mean phase vector

(arrow). The time indicated is relative to the prior light/dark cycle of the animals in which hour zero equals the time when light onset would have occurred and dusk would have been at hour 12.

Right: Theoretical functions of stem-like genes in the SCN. Entraining light signals act on circadian clocks within cells of the SCN cell network and also induce stem cell-related genes.

Stem cell properties include altered cell interactions, providing a plastitcity in cell networks that ultimately changes the generated circadian rhythm. Neurogenesis in the adult SCN remains a possibly but requires additional supportive evidence.

Conclusions

These results indicate that many genes expressed most prominently in the SCN are ones known or suspected to serve in maintenance of stem cell states and stages of neurogenesis and neural circuit formation. These processes include control of stem cell and progenitor cell proliferation and differentiation as well as later events including axon lengthening and synapse formation of maturing neurons. Furthermore, 10 of these 25 candidate genes are under circadian clock control and most are expressed in the SCN at highest levels during mid-to-late daytime. In fact, two of the genes are known components of the core circadian clock mechanism that also serve in development. Of the genes controlling the status of stem cells, expression data indicate that Wnt and noncanonical Notch pathways are likely to have important roles in the SCN. One possibility is that SCN cells upregulate proteins providing increased plasticity in their neural circuits by inducing gene regulatory pathways of stem cells. This adaptive flexibility may be required to allow the circadian clock to match timing system functions to changing environmental variables delivered in part to the SCN by retinal signals.

CHAPTER III: MUSASHI-2 AND RELATED STEM CELL PROTEINS IN THE MOUSE

SUPRACHIASMATIC NUCLEUS AND THEIR POTENTIAL ROLE IN CIRCADIAN

RHYTHMS

Preface

This chapter was originally published as a research article in International Journal of

Developmental Neuroscience May 2019 (Beligala et al. 2019). The original publication has been altered to meet BGSU’s specifications for formatting a dissertation. This publication identifies musashi-2 and related stem cell proteins expressed in the SCN.

Introduction

A fundamental question in brain development is what determines when individual brain regions lose their embryonic properties and mature. Cells with the characteristics of neural stem cells (NSCs) have been identified within the adult suprachiasmatic nucleus (SCN), a hypothalamic area containing a master circadian clock in many species, suggesting that this structure has characteristics of immature brain (Geoghegan and Carter 2008). For example, Six3 genes show distinct expression in the SCN during early development, which persists in the adult

(VanDunk, Hunter, and Gray 2011). A role for these apparently immature cells in neurogenesis or the SCN’s circadian rhythms remains unknown. Evidence suggests a low rate of neurogenesis persists in the adult hypothalamus (Migaud, Butrille, and Batailler 2015), while higher rates occur in the subventricular zone (SVZ) of the lateral ventricles and the hippocampal dentate gyrus (DG) of adult rodents (Yoo and Blackshaw 2018). Recent studies also provide evidence that neurons serving in timing of ovulation are produced in pubertal and adult rat SCN and that adult neurogenesis in the SCN is important for female reproductive state (Mohr, DonCarlos, and

Sisk 2017).

One possible function for the immature cell phenotypes of the SCN is that they may enable episodic neurogenesis providing SCN neural circuits a plasticity needed to modify circadian properties such as period, phase, or amplitude of rhythms. These alterations could compensate for events such as reproductive maturation, pregnancy, seasonal metabolic changes or other significant influences on circadian control of physiology and behavior. The SCN’s unique role in regulating a wide range of behaviors and cellular processes, including sleep and daily metabolic cycles, and its adjustment to local time and seasonal conditions also suggest that it may rely on greater flexibility in its neural circuits compared to other hypothalamic areas of adult mammals (Migaud, Butrille, and Batailler 2015). The stem-like characteristics of SCN neurons and glia might also reflect a plasticity in cell interactions independent of complete neurogenesis because stem cells have mesenchymal cell properties including altered cell-cell contacts, morphological flexibility, and increased motility that could alter neural circuits (Zhao et al. 2016).

Evidence of the adult SCN’s partially undifferentiated state includes cells expressing

SOX2, an important regulatory protein in embryonic and adult neural stem cells (Hoefflin and

Carter 2014; Pellegrino et al. 2018), and doublecortin (DCX), a marker for immature cells such as neuroblasts committed to further differentiation into neurons (Walker et al. 2007; Geoghegan and Carter 2008). DCX-expressing cells were described in the SCN’s core region and colocalized with neurons expressing vasoactive intestinal polypeptide (VIP) or gastrin-releasing peptide (GRP) (Geoghegan and Carter 2008). Also, the SCN has unusually low levels of NeuN

(neuronal nuclei), a protein expressed in mature neurons, again revealing an immature feature possibly providing neuroplasticity (Geoghegan and Carter 2008). Finally, doublecortin-like protein is expressed in the SCN along with DCX and has been implicated in neural plasticity

(Saaltink et al. 2012). Proteins expressed during adult neurogenesis are well characterized in the

42 mouse DG and SVZ, where NSCs replicate and differentiate into early progenitor cells that differentiate further into cells committed to becoming interneurons, astrocytes, or oligodendrocytes (Ming and Song 2011). Stages of cell differentiation during adult neurogenesis are distinguished by their unique protein expression patterns (von Bohlen und Halbach 2007).

Immunocytochemistry was used in the present study to test for these and other protein markers of stem cells in microdissected SCN explants prepared from juvenile and adult mice. A stem and progenitor cell culture medium (SPM) was used that maintains stem-like properties while suppressing differentiation and promoting NSC growth. We examined whether SCN stem- like cells survive and proliferate under these conditions. This physiological property of stem-like cells was combined with immunostaining results characterizing the surviving cells.

Immunostained brain sections and SCN explants revealed stem cell markers OCT4, nestin, and

RNA-binding protein MSI2 in mouse SCN. The results indicated a latent SCN ability that may be activated in response to physiological challenges or individual life events.

We also addressed whether SCN circadian rhythms persist in SPM. Previously, circadian rhythms appeared lacking in NSCs of neurosphere cultures prepared from adult mouse SVZ and

DG until they were induced to differentiate (Malik, Jamasbi, et al. 2015; Malik, Kondratov, et al.

2015). We report that this minimal culture medium not only supported cell survival and proliferation but also permitted neurons or glial cells to express circadian rhythms that persisted with distinct modulation. In addition, a bioinformatics study centered on MSI2, which is highly expressed in the SCN (Beligala, De, and Geusz 2018), supported the view that immature properties of SCN neurons allow a coordinated flexibility in its neural circuits, possibly facilitating adaptive circadian rhythm adjustments.

Materials and Methods

Animals

Mice were bred and maintained in cycles of 12 h light and 12 h dark to entrain their circadian system. Food and water were provided ad libitum. Males and females of three mouse strains were used to evaluate how broadly stem-like cells occur in the SCN: C57BL/6 (B6), C3H, and HRS. Some B6 and HRS mice contained the Per1::luc transgene, and some C3H mice contained a fos::luc transgene. Only bioluminescence from Per1::luc tissue was used in this study. B6 is an inbred line that is useful making genetic comparisons between studies. C3H is an outbred line that has typical serum melatonin levels, unlike B6 in which this is highly suppressed. HRS are a hairless, albino mice from a very different genetic background, the Swiss

Webster line.

Animals were 3–33 weeks old at the time of tissue harvesting, except where noted.

Animal procedures were approved by the BGSU Institutional Animal Care and Use Committee and met National Institutes of Health guidelines.

Microdissected SCN Explant Cultures and Immunocytochemistry (ICC)

For immunocytochemistry (ICC) of SCN immediately after sectioning, 150 μm-thick coronal sections were made from ice-chilled brains removed after isoflurane anesthesia and decapita. For SCN explant cultures, surgical reductions of each SCN in 300-μm coronal brain sections were made with three scalpel cuts to remove the ependymal cell layer and optic chiasm tissue as shown in Figure 7A. Explants were placed in glass-bottom culture dishes (Mattek) or plastic culture dishes, containing SPM, which consisted of Dulbecco's Modified Eagle Medium

(DMEM) with 10 ng/ml fibroblast growth factor-2 (FGF-2, Invitrogen), 20 ng/ml epidermal growth factor (EGF, Invitrogen) and 100 U/ml penicillin and 100 μg/ml streptomycin. SPM lacks

44 many of the growth factors and other differentiation-inducing agents of standard serum-based cultures or medium used with various serum supplements to maintain neuron survival in vitro.

Figure 7: SCN explant cultures in stem cell medium. Explants in SPM culture show tissue reorganization and cell movement. A: Where scalpel cuts were made in 300-μm-thick brain slices of the SCN region to remove the ependymal cells of the third ventricle (3 V) and the optic chiasm (OC). B: Explant at the start of culture. C: Same explant after 8 days in culture. Explant was made from a HRS mouse that was 64 weeks old. Scale bar = 50 μm. D: Cross-sectional area occupied by explants providing a measure of tissue reorganization in SPM. Shown are average areas (±SEM) for explants in four experiments (25 explants). Mean explant area increased significantly between days 1 and 6 (T test, t = 5.641, p = 0.011, n = 4 experiments). E:

Bioluminescence imaging of explants expressing luciferase under control by the Per1 gene promoter. Bottom: Corresponding brightfield image. Explants were in culture for 52 days and were made from a 38 week-old B6 (Per1::luc) mouse. F: Loss of neurons in SCN explants with time in culture in SPM while circadian clock gene expression persists. Explant has significantly fewer VIP-positive cells (p < 0.001) after 8 days in culture.

Bright field microscope images were captured at 2-day intervals with a 4X lens and a megapixel Kodak digital color camera. For immunofluorescence imaging, explants in culture for

11–32 days (average of 16 days) were fixed in 100% methanol for 10 min or 4% formalin in phosphate-buffered saline for 1 h at room temperature (RT) and standard ICC was performed.

Indirect immunofluorescence staining with confocal microscopy was used to identify stem-like cells, neurons, astrocytes, and proliferating cells. Samples were rinsed after overnight incubation at 4 °C with primary antibodies and were then incubated for 2 h with appropriate Alexa Fluor

488 and Alexa Fluor 568-conjugated secondary antibody (Life Technologies) at room temperature on a shaker. Confocal microscopy was performed as described in our previous study of neurosphere cultures (Malik, Jamasbi, et al. 2015; Malik, Kondratov, et al. 2015). ICC was also performed using mice after transcardial perfusion with formaldehyde 2 h after lights on.

Cryostat sections were incubated with mouse anti-GFAP (glial fibrillary acidic protein) and rabbit anti-MSl2 antibodies and stained with Cy2 anti mouse and Cy3 anti-rabbit (Table 4).

Table 4. List of antibodies used Product name Target Catalog Supplier Working Monoclonal/ number concentr polyclonal ation mouse anti-GFAP GFAP 3670 Cell Signaling 1:1000 Monoclonal Technology mouse anti-GFAP GFAP sc-33673 Santa Cruz 1:500 Monoclonal Biotechnology

Mouse anti-GFAP GFAP sc-33673 Santa Cruz 1:1000 Monoclonal Biotechnology rabbit anti-MSI2 Musashi2 PA5-21145 Invitrogen 1:200 Polyclonal rabbit anti-MSI2 Musashi2 10770-1-AP Proteintech 1:250 Polyclonal chicken anti- nestin NES Aves Labs 1:1000 Polyclonal nestin chicken anti- NeuN NUN Aves Labs 1:1000 Polyclonal NeuN mouse anti-NG2 NG2 sc-53389 Santa Cruz 1:200 Monoclonal (neural/glial Biotechnology antigen 2) rabbit anti-Oct-4 Oct-4 A7920 Abclonal 1:500 Polyclonal mouse anti-PCNA PCNA sc-25280 Santa Cruz 1:500 Monoclonal Biotechnology rabbit anti-SOX2 SOX2 48-1400 Life 1:500 Polyclonal Technologies mouse anti- vimentin sc-373717 Santa Cruz 1:500 Monoclonal vimentin Biotechnology rabbit anti-VIP VIP A1804 Neo Scientific 1:100 Polyclonal rabbit anti-VIP VIP A1804 Abclonal 1:500 Polyclonal

Confocal microscopy was performed as described previously (Malik, Jamasbi, et al.

2015), Briefly, cells were imaged with a DMI3000B inverted microscope (Leica Microsystems,

Buffalo Grove, IL, USA) equipped with a Spectra X LED light engine (Lumencore, Beaverton,

OR, USA), X-Light spinning-disk confocal unit (CrestOptics, Rome, Italy), and a Rolera

Thunder cooled−CCD camera (Photometrics) with Metamorph software controlling image acquisition and data analysis (Molecular Devices, Sunnyvale, CA, USA). Confocal images were collected in a Z-series with 10X and 20X objectives while using standard DAPI, fluorescein, and rhodamine filter wavelengths. The distribution of cell types was then determined and cell counts were obtained using Metamorph Multi-Wavelength Cell Scoring Application Module after background intensity was subtracted based on the highest intensity measurements from controls in which primary antibody was omitted. Cells having a brightness within the top 75% of the intensity range were counted as positive. For Figure 8E, 50 μm sagittal sections containing the

SCN were photographed with a Nikon Eclipse E800 microscope equipped with a cooled CCD camera (Retiga Exi; Q-Imaging), using Q-capture software. For Figure 9, the same section was observed under a Zeiss Axiovert 200 MOT fluorescence microscope (63× objective) with a Zeiss

LSM 510 laser scanning confocal attachment (Carl Zeiss). The sections was excited with argon- krypton, argon, and helium-neon lasers using the excitation wavelengths of 488 nm for Cy2,

543 nm for Cy3, and 633 nm for Cy5. Each laser was excited sequentially to avoid cross talk between the three wavelengths.

Figure 8: Stem cell markers provide additional evidence of neural stem cells and progenitor cells in the SCN and SCN explant cultures. Immunocytochemistry of brain slices containing SCN and surrounding hypothalamus fixed immediately after sectioning show A:

SOX2, B: Nestin, C: OCT4, and D: MSI2 expression (green) along with GFAP + cells (red).

Arrows: colocalization with GFAP (yellow). Clusters of SOX2+/GFAP + and nestin+/GFAP + cells resembling stem cells (yellow) are near the explant core. SCN outline indicates the region used for cell counting. Asterisk: location of neighboring hypothalamic regions dorsal or lateral to SCN for comparison. Arrowhead: blood capillaries positive for nestin.

Scale bar = 100 μm. E: Ex-vivo coronal sections show that MSI2 expression (green) is distributed throughout the SCN along with GFAP expression (red). (Rectangle: region expanded in Figure

9) F: MSI2 expression (green) in SCN explant cultures does not colocalize with neuroglial cells expressing NG2 (red). SCN explant cultures contain cells expressing G: SOX2 (green), H: nestin

(green), and I: OCT4 along with GFAP + cells (red). Arrows: colocalization with GFAP. J:

SOX2 (green) and additional stem cell marker vimentin (red) show colocalization in SCN explants. K: Cell division occurs throughout SCN explants (PCNA+, red), which includes

SOX2+ cells primarily near the edge (yellow). Some SOX2+ cells appear to be quiescent

(green). L: Cell death is mostly near the center of SCN explants (red: propidium iodide; blue:

Hoechst-stained cell nuclei). M: In the same explant, it is clear that mostly neurons (NeuN+) are undergoing cell death (orange and yellow), and few neurons survive (green). Scale bars: 100 μm in A–E and I–K, but 50 μm elsewhere.

Figure 9: Cells expressing MSI2 and GFAP in SCN. The photomicrograph presents a high magnification view of the inset in Figure 8E showing fine details of fibrous astrocytes expressing

MSI2 (green) and GFAP (red) in sections of fixative-perfused mouse brain. Neighboring GFAP- negative cells also express MSI2 and are in close proximity to astrocyte processes. Confocal image is a 1-μm Z-axis optical section. Scale bar: 10 μm.

Live/Dead Staining

Cultures were incubated in 0.02 mg/ml propidium iodide (PI) in PBS for 5 min at 37 °C.

PI was then washed out using PBST (0.1% Triton in PBS), and cells were fixed using 100% methanol for 10 min at RT. Explants were washed with PBS, and cell nuclei were stained using

Hoechst 334 before confocal fluorescence imaging, as described previously (Malik, Kondratov, et al. 2015).

Explant Bioluminescence Imaging

Culture dishes containing surgically reduced SCN explants in serum-containing medium

(SM) consisting of DMEM and 10% FBS were covered with a temperature-controlled optical window, sealed with silicone grease, and maintained at 37 °C (Cell MicroControls, Norfolk,

VA). Luciferin, potassium salt (0.5 mM), was added to explants before imaging with a back- thinned, back-illuminated CCD camera (CH360, Photometrics, Tucson, AZ) or Retiga LUMO cooled CCD camera (QImaging). These long-term brain slice cultures were imaged with 60-min exposures. Bioluminescence imaging (BLI) of explants was performed with 2 × 2 binning and

30-min exposures. Images were analyzed using V++ (Photometrics) and ImageJ (NIH) software.

BLI was also performed with standard brain slice explant cultures of the SCN maintained in SPM for only 8–10 h and then maintained in a modified SPM during BLI. For BLI, bicarbonate was reduced to 4 mM for use in room air, and 10 mM HEPES buffer was used to maintain pH at 7.2. Pen/strep was added and no phenol red was used, as with cultures in 5%

CO2.

Coronal brain sections, 300 μm-thick, were prepared from male mice 38–123 days old using the same procedure as explant cultures but, because of their larger size, were placed on

Millipore cell culture inserts with a thin film of medium (1 ml total) covering the tissue in a

35 mm plastic cell culture dish, as described previously (Hiler et al. 2008).

Bioinformatics Analysis

The most likely MSI2 targets were derived from published high-throughput crosslinking immunoprecipitation (CLIP) and gene expression data generated after knockout (KO), knockdown (KD) or overexpression (OE) of Msi2 in mice or various cell types (Wu et al. 2010;

Park et al. 2014; Wang et al. 2015; Bennett et al. 2016; Rentas et al. 2016; Kharas and Lengner

2017). Data from in situ hybridization (ISH) experiments using sections from adult mouse brain were obtained from the Allen Institute Mouse Brain Atlas (ABA) and are available online at http://mouse.brain-map.org (Lein et al. 2007). To generate Table 5, the Fine Structure Search

(FSS) tool for the ABA was used that provided a curated list of the 46 most significantly expressed SCN genes according to ISH intensity and degree of selective expression in the SCN.

FSS genes were added to Table 5 if one or more of these criteria were met: (1) The gene’s RNA is a likely target of MSI2 regulation, negative or positive, based on CLIP or gene expression studies; (2) The gene product is reported to bind to or otherwise interact directly with MSI2; or

(3) has high SCN expression (z-score >1) based on ISH ABA reported results (i.e., the signal is more than one standard deviation from the mean of all observed SCN gene expression).

Table 5. RNA-binding, circadian, and stem cell properties of selected genes expressed in mouse SCN SCN Relative MSI2- Present circadian Contains expression Selected gene ontology Gene binding or in SCN rhythm RBM level (GO Biological Process) control FSS period (Z score) (hrs)

Blcap (Bladder cancer- (Bennett et GO:0030262 apoptotic nuclear - 3.000 + 20.0-24.0 associated al. 2016) changes protein), 71016617 Celf3 (CUGBP, GO:0007283 spermatogenesis Elav-like GO:0000381 regulation of + - 1.994 + 24.0 family member alternative mRNA splicing, via 3), spliceosome 74641324 Celf4 GO:0090394 negative regulation (CUGBP, of excitatory postsynaptic potential Elav-like + - 1.154 - 24.0 GO:1902866 regulation of retina family member development in camera-type eye 4), 73592527 Celf6 (CUGBP, GO:0001505 regulation of Elav-like + - 1.676 - neurotransmitter levels ND family member GO:0071625 vocalization behavior 6), 71358616 Cirbp (cold inducible RNA (Park et al. GO:0045727 positive regulation of binding 2014; + <1 - translation GO:0030308 negative (24.0)1 protein), Rentas et al. regulation of cell growth 69548958 2016) sagittal

Dclk1 (doublecortin- GO:0048813 dendrite like kinase 1, morphogenesis GO:0021952 - - <1 - 24.0 Dcl), central nervous system projection 69169654 neuron axonogenesis sagittal Dcx GO:0001764 neuron migration (doublecortin), GO:0021952 central nervous - - <1 - 24.0 70946414 system projection neuron sagittal axonogenesis Dlk1 (delta- GO:0030154 cell differentiation like 1 - - <1 + GO:0045746 negative regulation ND homolog), of Notch signaling pathway 71587885 GO:0021892 cerebral cortex Dlx1 (distal- GABAergic interneuron less homeobox - - <1 + differentiation GO:0045746 24.0 1), 72008490 negative regulation of Notch and 348 signaling pathway Dner (delta/notch- GO:0010001 glial cell like EGF- - - <1 - differentiation GO:0005112 Notch ND related binding receptor), 1699 Elav1 GO:2000036 regulation of stem (embryonic (Rentas et cell population maintenance lethal, + <1 - 24.0 al. 2016)2 GO:0045727 positive regulation of abnormal translation vision 1), None Flrt3 (fibronectin GO:0051965 positive regulation of leucine rich (Bennett et synapse assembly GO:0098742 - 3.08 + 24.0 transmembrane al. 2016) cell-cell adhesion via plasma- protein 3), membrane adhesion molecules 73931404

Gfap (glial GO:0010977 negative regulation fibrillary acidic of neuron projection development protein), - - 2.4321 - ND3 GO:0045109 intermediate filament 79591671 and organization 1357 Msi1 (musashi RNA-binding GO:0003727 single-stranded RNA protein 1), + - <1 - binding GO:0008266 poly(U) ND 74509595 RNA binding sagittal Msi2 (musashi GO:0048864 stem cell RNA-binding (Rentas et + 2.117 + development GO:0008266 poly(U) ND protein 2), al. 2016) RNA binding 73616034 GO:0007399 nervous system Nes (nestin), - - 1.501 - development GO:0048858 cell ND 1387 projection morphogenesis GO:0050768 negative regulation Notch1, (Park et al. of neurogenesis GO:0010718 70593326 - <1 - ND 2014) positive regulation of epithelial to sagittal mesenchymal transition Notch2, GO:0001709 cell fate 69837872 (Bennett et - <1 - determination GO:0007219 Notch ND sagittal al. 2016) signaling pathway

Ntpcr (nucleoside- GO:0005524 ATP binding4 triphsphatase, (Rentas et GO:0098519 nucleotide - 2.113 + ND cancer- al. 2016) phosphatase activity, acting on free related), nucleotides4 75773704 GO:0050769 positive regulation of Numb, (Rentas et neurogenesis GO:0045746 69095946 - <1 - ND al. 2016) negative regulation of Notch sagittal signaling pathway

GO:1905064 negative regulation Pdcd4 of vascular smooth muscle cell (programmed (Rentas et differentiation GO:0060940 - 1.533 + 28 cell death 4), al. 2016) epithelial to mesenchymal 73931413 transition involved in cardiac fibroblast development Pou2f1 (POU GO:0030910 olfactory placode domain, class (Rentas et formation GO:0045944 positive 2, transcription - 1.752 - ND al. 2016) regulation of transcription by RNA factor 1) polymerase II (OCT1), 1563 Pou5f1 (POU domain, class GO:0019827 stem cell population 5, transcription - - <1 - maintenance GO:0035198 ND factor 1, OCT miRNA binding 4), 71325348 sagittal GO:0048813 dendrite Rbfox2, morphogenesis (Rentas et 71325402 + <1 - GO:0000381 regulation of 24 al. 2016) sagittal alternative mRNA splicing, via spliceosome GO:0007399 nervous system Rbfox3 development GO:0000381 + - ND5 - ND6 (NeuN), None regulation of alternative mRNA splicing, via spliceosome Rbm4 (RNA GO:0097167 circadian regulation Binding Motif (Rentas et of translation GO:0043153 + 1.534 - ND7 Protein 4; al. 2016) entrainment of circadian clock by Lark1), 888 photoperiod Rgs16 GO:0007186 G-protein coupled (regulator of (Rentas et receptor signaling pathway G-protein - <1 + 24.0-28.0 al. 2016) GO:0043547 positive regulation of signaling), GTPase activity 1567

Rnpc3 (RNA binding region GO:0032502 developmental (RNP1, RRM) + - <1 - process GO:0000398 mRNA ND containing 3), splicing, via spliceosome 583856 sagittal Rorb (RAR- related GO:0042752 regulation of (Rentas et orphanreceptor - - + circadian rhythm GO:0042462 eye 24.0 al. 2016) beta), 2539 and photoreceptor cell development 79556597 Rps6ka2 (ribosomal GO:0002035 brain renin- protein S6 (Rentas et - <1 + angiotensin system GO:0007507 ND kinase, al. 2016) heart development polypeptide 2), 70301276 GO:0007417 central nervous Shh (sonic (X. Ma et al. system development GO:0030178 hedgehog), - 8.543 - ND 2017) negative regulation of Wnt 1418 signaling pathway Slc5a3 (solute carrier family 5 GO:0007422 peripheral nervous (inositol (Bennett et system development GO:0045746 - 3.356 + 24.0 transporters), al. 2016) negative regulation of Notch member 3), signaling pathway 976 Sox2 (SRY- GO:0045747 positive regulation of box containing Coexpressed - 5.289 + Notch signaling pathway ND gene 2), with Msi28 GO:0035198 miRNA binding 77280331 Ssb (Sjogren (Bennett et GO:1990825 sequence-specific syndrome al. 2016; mRNA binding GO:0071045 + <1 - ND antigen B, La), Rentas et al. nuclear histone mRNA catabolic 75081397 2016) process

Syncrip (synaptotagmin binding, (Bennett et cytoplasmic al. 2016; GO:0008143 poly(A) binding RNA + Rentas et al. <1 - GO:0017148 negative regulation ND interacting 2016; Wang of translation protein, et al. 2015) hnRNP Q), 1391 Trp53i11 (transformation (Bennett et related protein al. 2016; GO:0016021 integral component - 3.696 + ND 53 inducible Rentas et al. of membrane4 protein 11), 2016) 73521826 Vim GO:0014002 astrocyte (vimentin), development GO:0010977 - - 1.921 - ND 1309 and negative regulation of neuron 79907904 projection development Wnt2b (wingless- (Kharas and GO:0030182 neuron related MMTV - Lengner 5.444 - differentiation GO:0045165 cell ND integration site 2017) fate commitment 2B), 1589 GO:0030182 neuron (Kharas and differentiation GO:0071425 Wnt10b, 2725 - Lengner 4.382 - ND hematopoietic stem cell 2017) proliferation Zfhx3 (zinc GO:0032922 circadian regulation finger (Rentas et of gene expression GO:0045662 - 4.875 + ND9 homeobox 3), al. 2016) negative regulation of myoblast 74641308 differentiation

Gene: names followed by the Allen Mouse Brain Atlas experiment number for coronal sections, except where indicated. Boldfaced genes indicate where protein expression was confirmed in brain sections or tissue explants during the current study. Contains RBM:

RRM domain present in protein. MSI2-binding or controlled: based on published studies. Relative expression level: number of standard deviations above the average expression of genes in SCN, from ISH data in the Allen Institute Mouse Brain Atlas and Brain

Explorer. Present in SCN FSS: from Fine Structure Search of SCN by Allen Institute using Mouse Brain Atlas. Selected gene ontology: from MGI database. SCN circadian rhythm: CircaDB JTK analysis with p<0.05, default settings; ND = not detected.

1Average of two experiments. 2ELAVL1 binds RNA along with MSI2 and is upregulated by MSI2 KO (Park et al. 2014). 3SCN astrocytes show daily rhythms in GFAP cell localization (Lindley et al. 2008). 4Only available GO is from IEA (Inferred from

Electronic Annotation). 5Not detected in ABA; published results show low expression in SCN cells. 6 E-box in Rbfox3 gene promoter could provide circadian clock control. 7LARK protein levels show circadian rhythm modulation (Kojima et al. 2007). 8(Cox et al.

2013) 9Long (32-hr) period detected. MSI-2-binding results were derived from several studies of MSI2 KO, KD or overexpression

(Wu et al. 2010; Park et al. 2014; Wang et al. 2015; Bennett et al. 2016; Rentas et al. 2016; Kharas and Lengner 2017).

Additional genes were included in Table 5 if (1) the gene product is in the RBM family of RNA-binding proteins along with MSI2; (2) was examined in this study through ICC; or (3) is an additional gene discussed in this report in relation to stem cells or cell-cell contact. The estimated period of any circadian rhythm in gene expression described in the SCN was added if it was available in the CircaDB database of microarray results. For each gene, up to two GO codes were selected, if available, based on biological functions in this order: (1) neuronal or glial activity including circadian rhythm functions; (2) stem cells or developmental processes; (3)

RNA binding; and (4) other processes closely related to developmental processes such as cell division, cell-cell contact or apoptosis.

Gene Ontology (GO) designations were obtained from the Mouse Genome Informatics

(MGI) database at http://www.informatics.jax.org/batch/summary. For high stringency, only

Experimental, Computational Analysis, and Curator Statement Evidence Codes were used in

Table 5, except in one case when these were not available and the Inferred from Electronic

Annotation (IEA) Evidence Code was used instead. Estimates of circadian rhythms in gene expression in the mouse SCN were obtained from the database CircaDB using default search criteria, which is available at http://circadb.hogeneschlab.org (Pizarro et al. 2013).

Results

Culture in SPM Causes Morphological and Cellular Changes in SCN Explants

Explants were prepared from brain slices that were surgically-reduced by microdissection to remove the optic chiasm and ependymal cells along with the ventricular zone as shown in

Figure 7A, thereby eliminating these possible sources of stem-like cells from outside the SCN.

During culture in SPM, explants showed distinctive changes in morphology and tissue rearrangement including a transient, 29.1% increase in cross-sectional area (Figure 7B-D) as cells were proliferating or dying. Although the explants were maintained in a medium that does

62 not favor growth and survival of differentiated cells, cultures remained viable, as shown by bioluminescence imaging of explants prepared from SCN of Per1::luc transgenic mice after 52 days in culture (Figure 7E). The explants showed a loss of neurons expressing VIP, which comprise a major cell population in the SCN (Figure 7F, Supplemental Figure 1).

SCN Cells Express Multiple Stem Cell-Related Proteins

ICC provided additional evidence of stem-like cells in the SCN by applying antibodies directed against SOX2, nestin, OCT4, MSI2, and GFAP in brain sections that were formalin- fixed immediately after sectioning (Figure 8A-D, Figure 9). This approach is similar to ICC methods used to characterize cell types in SCN slice cultures (Iwai and Takeda 2007) and it shows the state of cells in explant cultures before circadian rhythms are measured, which is described below. GFAP ICC was used to identify putative stem cells, astrocytes and, more effectively, reactive astrocytes (Sofroniew and Vinters 2010), which are considered to have neurogenesis capabilities in cerebral cortex (Robel, Berninger, and Gotz 2011; Magnusson et al.

2014; Michelucci et al. 2016).

In all brain sections examined, GFAP was more commonly expressed in cells containing

SOX2, Nestin, OCT4 or MSI2 than in cells that did not express these stem cell-related proteins

(Figure 10A-D). SOX2 was expressed about equally in GFAP-negative and positive cells (Figure

10A), consistent with reports of its expression in both SCN neurons and glia (Hoefflin and Carter

2014). The brain sections were prepared immediately after dissection and chilled on ice before fixarion so that immunostaining could be compared directly with results from the SCN explant cultures, as shown by Liu et al., 2018 (D. Liu et al. 2018). However, MSI2 was examined in both non-perfused sections and ones made from formalin-perfused brains as shown in 50 um sections of SCN (Figure 8E, Figure 9). MSI2 staining intensity was elevated in the SCN relative to surrounding hypothalamic tissue and was expressed throughout the shell and core SCN

63 subregions. Confocal microscopy indicated that most, if not all, GFAP-immunoreactive cells contain MSl2 and are widely distributed between other cell types (Figure 9).

Figure 10: Proportions of cells expressing stem cell proteins in the SCN and SCN explant cultures. Percentages are relative to total cells identified by Hoechst-stained nuclei in one confocal section. Percentages of cells expressing stem cell markers; SOX2 (a), Nestin (b), OCT4

SCNs). Percentages of cells expressing stem cell markers; MSI2 (e) SOX2 (f), Nestin (g) and

OCT4 (h) in the SCN explant cultures (average of 5 locations in one explant). Percentages of cells expressing a mesenchymal cell marker vimentin with SOX2 (i), a cell proliferation marker

PCNA with SOX2 (j) and an apoptotic nuclear stain PI with a neuronal marker NeuN (k) in SCN explant cultures (average of 5 locations in one explant).

SCN Explant Cultures Express Stem Cell and Progenitor Cell Markers

As in brain slices, SOX2, nestin, and OCT4 were co-expressed with GFAP in SCN explant cultures after 1–4 weeks in SPM (Figure 8G-I). The percentage of GFAP-positive cells was significantly higher in explants than in brain slices (20.9% ±9.62 SD, n = 3 explants versus

9.31% ±3.35, n = 4 slices, p = 0.035, t-test). Cell counts within five regions were averaged for each slice or explant. This result suggests that reactive astrocytes (potential stem-like cells) were induced or proliferated in SCN explants.

SOX2 in explant cultures was also co-expressed with vimentin (Figure 8J), a marker for cells that have undergone epithelial-to-mesenchymal transition (EMT) through a dedifferention process that generates stem-like cells (Nie et al. 2009). MSI2 was observed in explant cultures and did not show expression in neuroglial cells, another cell type that survived in SPM (Figure

8F).

Cells proliferating or undergoing cell death were quantified in explant cultures by PCNA

ICC (Figure 8K) and PI staining (Figure 8L), respectively. Nearly all SOX2-positive cells in explants were undergoing mitosis according to PCNA staining (88%, Figure 8J). PI was applied prior to fixation to identify cells with compromised cell membranes. About 74% of PI-labeled cells expressed NeuN, and all NeuN-positive cells examined were PI stained (Figure 8L, M), further confirming a major loss of neurons in SPM. The percentages of cells positive for nestin,

OCT4, and MSI2 were lower in explants than in brain slices, possibly because most of these cells were GFAP-negative in brain slices (Figure 10B-D) and therefore likely included neurons that did not survive in explant cultures.

Bioinformatics Indicate Significant MSI2 and RNA-Binding Protein Functions in SCN

The extensive MSI2 expression in the SCN detected by ICC encouraged further examination of this RNA-binding protein that suppresses differentiation of stem cells and is

67 expressed in the DG and SVZ (Sakakibara et al. 2001). The MSI2 expression pattern, which was distributed across the SCN in brain sections, agreed with the Msi2 gene expression pattern in the

ABA based on ISH in coronal and sagittal sections. This feature suggests it may have an important function in multiple SCN activities including circadian rhythm generation, entrainment of the clock to retinal input, and distribution of rhythmic timing signals. The gene ontology (GO) bioprocess (BP) annotation in PANTHER indicates MSI2 regulates RNA metabolic processes and serves in stem cell development. The other member of the Musashi gene family, Msi1, is not highly expressed in the SCN (Table 5). Two of the FSS genes that are MSI2 targets (Table 5) are not well understood (Blcap and Ntpcr), but are expressed abnormally in cancer cells (Pasdziernik et al. 2009; Gromova et al. 2017), which tend to be poorly differentiated.

MSI2 is categorized within the RNA binding motif containing (RBM) family of genes that expresses proteins containing the RNA recognition motif (RRM) (Birney, Kumar, and

Krainer 1993) according to the HUGO Gene Nomenclature Committee at the European

Bioinformatics Institute, https://www.genenames.org/cgi-bin/genefamilies/set/725. We examined the ABA for additional members of the RBM family that are highly expressed in the SCN

(considered here as a Z-score greater than 1), and we identified additional gene candidates for future studies of RNA-binding activity in the circadian clock. Most notable is Celf3, which is expressed at higher levels in the SCN than in most other brain areas and, like MSI2, was included in the SCN FSS. Along with the Celf gene family, other RBM-containing proteins expressed in the SCN are from the Elavl, Rbm, and Rbfox families which are expressed at moderate levels (Table 5). The RNA-binding protein ELAVL1 (HuR) binds to and stimulates

MSI2 activity. Inhibiting Rbm4 message coding for Lark protein impacts circadian rhythms

(Kojima et al. 2007), and Rbfox3 codes for the NeuN marker protein of mature neurons that is expressed at unexpectedly low levels in much of the SCN, as mentioned previously.

Circadian Rhythms Persist in the SCN of Brain Slice Cultures Maintained in Stem Cell

Medium

The circadian clock within the SCN could regulate the differentiation and maturation of the developing or adult SCN, as indicated for neurosphere cultures made from mouse SVZ and

DG (Malik, Jamasbi, et al. 2015; Malik, Kondratov, et al. 2015). Because epidermal stem cells show control by intrinsic circadian clocks (Janich et al. 2011), stem-like cells within the SCN may be capable of generating circadian rhythms. Experiments to explore this possibility would be enhanced if the SCN cells survive and the clock continues to function in a medium such as

SPM that supports stem cells. It was also important to screen for any effects of this atypical culture condition on the SCN’s circadian properties because the SCN explant cultures displayed altered morphology and differential cell survival in SPM. The question addressed was whether circadian clock cells continue to express a rhythm despite the presence of additional growth factors that are known to activate MAP kinase pathways or other SCN inputs that serve in synchronizing the clock to external 24-hour cycles.

BLI of three SCN brain slice cultures showed that circadian expression of the Per1 gene can persist in SPM (Figure 11A&B), although the rhythm was severely disrupted in one culture

(Figure 11C). Period estimates for the two oldest animals were both 23 h based on peak-to-peak intervals, (Figure 11A&B). In the SCN of the oldest animal, the circadian rhythm reached a maximum near the middle of the light phase (Figure 11A), which is in agreement with earlier studies of Per2 gene expression (Nakamura et al. 2005). The previously described phase difference between ventral and dorsal SCN was also observed (Figure 11B). However, the phase of the first peak in the rhythm from this animal’s SCN was later than expected, when compared with the previous light/dark cycle, and there was an unexpected small, early peak in the signal during the first cycle of the right SCN (Figure 11B). Both of these departures in the young SCN

69 from the normal rhythm observed in the older SCN suggested that SPM disrupts but does not eliminate circadian rhythms. Much greater disruption was observed in the SCN from the youngest mouse (Figure 11C). The SCN cultures also showed unexpected Per1 expression in areas ventrolateral (Figure 11B) and dorsal (Figure 11B&C) to the SCN. All three mice were males in the same litter of the inbred B6 strain, which minimized variability.

Figure 11: Bioluminescence imaging of SCN brain slices maintained in SPM. A: SCN brain slice prepared from a 123-day-old Per1::luc transgenic mouse. Left: Circadian bioluminescence rhythm measured from the entire left SCN signal. Right: Bioluminescence image captured 12 h after imaging began showing signal originating almost entirely from the paired SCN. The circadian rhythms and expression pattern were typical of previously described SCN brain slices in normal culture medium. L SCN: left SCN. 3 V: third ventricle. OC: optic chiasm. The timing

71 of the prior light/dark cycle is shown below. ADUs: analog-to-digital units of the sensor after background subtraction. B: SCN brain slice from a 49-day-old Per1::luc mouse. Left: Circadian expression in the SCN persisted in the left SCN with the dorsal SCN (L dSCN) slightly preceding the ventral SCN (L vSCN), as described previously in SCN imaged under normal culture conditions. A circadian rhythm was also detected near the lateral edge of the left ventral

SCN (L lvSCN). The periventricular nucleus (L PeVN) showed unusually high and sustained expression. Right: A circadian rhythm was also present in the right SCN, although the pattern included a smaller peak occurring 12 h earlier than the maximum. Arrows indicate centers of each region-of-interest (ROI). Bioluminescence signals shown were normalized to the maximum in each ROI to facilitate phase comparisons. C: SCN brain slice from 38-day-old Per1::luc mouse. Rhythms in both SCN were disrupted within the first cycle in vitro. Left: Signals recorded from ROIs in the left (L) and right (R) dorsal SCN (dSCN) and ventral SCN (vSCN) as indicated by arrows shown at right. Expression in other areas increased over time, particularly in spots lateral to the third ventricle (3 V). Left dorsal areas (LD1, LD2) and right dorsal areas

(RD1, RD2. RD3) showed increased expression late during the recording and were not rhythmic.

Discussion

The SCN Expresses Many Proteins Found in Partially Differentiated Cells

The current results confirmed and extended previous descriptions of apparent partial cell differentiation in the SCN through phenotyping of SCN cells by ICC and cell survival and proliferation assays in SPM. These additional stem cell-like properties include expression of

MSI2, nestin, OCT4, and vimentin in brain slices and explant cultures. Nestin, OCT4, and SOX2 colocalized with another stem cell marker protein, GFAP, that is also a marker of reactive astrocytes (Robel, Berninger, and Gotz 2011), suggesting a range of stem-like cell types survived in culture. Close examination of MSI2 expression showed that it was expressed in GFAP- positive cells resembling astrocytes and in numerous adjacent cells lacking GFAP including neurons. Earlier reports showed expression of SOX2, DCX, and DCX-like proteins in SCN neurons and unusually low expression of mature neuronal marker NeuN (Walker et al. 2007;

Geoghegan and Carter 2008; Hoefflin and Carter 2014; Saaltink et al. 2012). SCN cells expressing SOX2 with GFAP are most similar to the neurogenic stem cells of the DG and SVZ, whereas SOX2-positive cells lacking GFAP resemble progenitor cells (Ming and Song 2011).

Our results with explant cultures showed colocalization of SOX2 and PCNA, indicating

SOX2-positive cells proliferated, while neurons were lost through cell death. Additional evidence that the explants remained viable in SPM was provided by luciferase bioluminescence persisting for at least seven weeks. Removal of the ependymal cells and the optic chiasm of SCN explants before culture indicates presence of resident stem-like cells in the SCN rather than their origination in adjacent structures followed by migration into the SCN. SOX2 was also co- expressed with the intermediate filament vimentin found in stem cells (Nie et al. 2009). Survival and proliferation of stem cells in tumors and normal tissues is favored by low-oxygen conditions activating hypoxia-inducible factor-1 (HIF-1) (Bar et al. 2010). Similarly, the SCN explants in

73 our study were treated like neurosphere cultures (Malik, Jamasbi, et al. 2015) and maintained in standard culture dishes that favored stem-like cell growth but not neuron survival. In contrast, typical bioluminescence imaging experiments of SCN explant cultures lasting several days usually rely on conditions favoring oxygen exchange through a porous membrane support that holds the neural tissue in a thin film of medium. This interface culture method was employed here when imaging brain slices of Per1::luc mice containing the SCN to evaluate circadian rhythms. The circadian rhythm of bioluminescence persisted in two of the three cultures maintained in SPM but with a shifted phase and atypical Per1 expression dorsal to the SCN. The

Per1::luc transgene expression observed within and outside the SCN indicates Per1 is not silenced by this culture medium and could have a function in the stem-like cells independent of its role in the circadian clock’s timing mechanism, particularly in areas that do not appear to be rhythmic.

It is still not completely understood whether circadian rhythms persist in most adult

(mesenchymal), embryonic, or induced pluripotent stem cells (Morse et al. 2003; Kimiwada et al. 2009; Yagita et al. 2010; Malik, Jamasbi, et al. 2015). Circadian rhythms regulate stem cells of the epidermis (Janich et al. 2011), but appear to be lacking in NSCs of neurosphere cultures prepared from adult mouse SVZ and DG until the cells are induced to differentiate (Malik,

Jamasbi, et al. 2015; Malik, Kondratov, et al. 2015). The current results show that this stem cell culture medium can support circadian rhythms. It could be a useful environment for testing which conditions are permissive for the circadian clock and whether individual neural stem cells or progenitors also generate rhythms. It is noteworthy that SCN circadian rhythms were observed despite the absence of the serum supplement B27 that is typically used to maintain neuron survival in circadian studies of brain slice cultures. Nevertheless, the results also show the limitations imposed on measuring circadian rhythms in cell or tissue explant cultures maintained

74 in SPM. The observed disruptions in rhythms may be explained as a disturbance in the phase or coupling between the circadian pacemakers within the SCN cell population, while circadian rhythms may persist in individual cells. It is likely that there was a shift in the bioluminescence signal over time in SPM towards origination in other rhythmic cell types such as astrocytes, thereby distorting the rhythmic pattern recorded. Astrocytes could have survived in the SCN explants because of EGF in the SPM that may have stimulated astrocytes through their heparin- binding epidermal growth factor receptors (HBEGFR) that are part of the EGF receptor family.

HBEGF has been used in a serum-free culture method for cortical astrocytes that, reportedly, maintains a gene expression pattern more like that of resident reactive astrocytes of the brain than astrocytes maintained in serum-based medium (Foo et al. 2011).

EGFR expression was shown previously to be scattered throughout the SCN and also concentrated dorsal to the SCN in the hypothalamic subparaventricular region where SCN neurons project (Ma et al. 1994; Kramer et al. 2001; Snodgrass-Belt, Gilbert, and Davis 2005). It was concluded that this pathway regulates the animal’s circadian locomotor rhythms, and EGF signaling suppression reversibly blocks locomotor activity. Evidence indicates that, rather than

EGF, this timing signal is mediated through TGF-alpha binding to EGFR (Kramer et al. 2001), thereby activating downstream mitogen-activated kinase pathways in the SCN (Hao and

Schwaber 2006). Both neurons and astrocytes of the hypothalamus express EGFR. EGFR expression in the hypothalamic arcuate nucleus undergoes dynamic changes at the time of first proestrus in primates (Ma et al. 1994), an alteration that might also occur in the SCN to modify expressed circadian rhythms. In contrast, very little is known about the role of FGF-2 (the other

SPM growth factor) in adult hypothalamic cells or the circadian clock.

Partially Differentiated SCN Cells may Provide Developmental and Adult Neuroplasticity

SCN cells described in the current study showing nestin and GFAP co-expression resemble stem cells that undergo neurogenesis in the DG or SVZ (von Bohlen und Halbach

2007). These cells may be a type of astrocyte that is proposed to regulate neurogenesis through

Notch signaling (Lebkuechner et al. 2015). In this model, based on single-cell phenotyping, astrocytes expressing SOX2 and cytoskeletal proteins GFAP, vimentin, and nestin control Notch signaling pathways that suppress differentiation. It is possible that the overlapping pattern of

SOX2, GFAP, vimentin, and nestin expression we observed in SCN brain sections or explant cultures indicates astrocytes maintaining the SCN’s stem-like state through this mechanism.

Interestingly, loss of Notch signaling enables neurogenesis from astrocytes of the striatum

(Magnusson et al. 2014). Furthermore, Notch signaling through glial cells has been implicated in regulating memory impairments from sleep loss in Drosophila (Miller et al. 2009). Note, however, that a previous immunochemical study of perfused tissue did not see co-expression of

SOX2 with nestin or vimentin in mouse SCN (Pellegrino et al. 2018), whereas we observed about 5% of cells in explant cultures co-expressing SOX2 and vimentin.

The SCN’s stem cell properties may enable its cell network of circadian oscillators to adaptively adjust rhythmic timing signals leaving the SCN. Clearly, GABA neurosecretion is important in forming the ensemble circadian rhythm along with synaptic transmission within and between large populations of neurons producing VIP, arginine vasopressin (AVP), GRP, and calretinin (CR) or calbindin (Moore and Silver 1998; Jobst, Robinson, and Allen 2004; Antle and

Silver 2005; Azzi et al. 2017). The substantial success with restoring circadian rhythms in SCN- ablated adult animals through embryonic SCN transplants may have been aided by a plasticity within the neural circuitry of the circadian timing system (Lehman et al. 1987; Silver et al.

1990). It is noteworthy that similar early transplantation studies using other brain regions were

76 less successful at providing major recovery in animal models of Parkinson’s disease (Bjorklund and Lindvall 2017). The apparent lack of complete development of some SCN cells may enable them to further differentiate and grow adaptively in new microenvironments following various stressors like those impacting neural transplants. Transplant studies revealed SCN flexibility in how it conveys circadian signals in that synaptic or humoral signaling suffice (Silver et al. 1990).

Some of the apparent plasticity in SCN organization may have evolved because the SCN is a sensory structure receiving retinal input and uniquely engaged in providing precise daily timing to multiple behavioral and physiological processes. It provides sleep and metabolic regulation that can be impacted by shifting seasonal dawn and dusk and ongoing postnatal development. Critical in its production of accurate timing signals for the body is a prominent fiber tract from the optic nerve conveying photic information through direct excitatory glutamatergic synapses, making the SCN an important sensory area of the brain (Lokshin,

LeSauter, and Silver 2015).

The stem-like cells described in the SCN resemble, to some extent, stem cells reported in the arcuate nucleus that have been suggested as serving in neuroplasticity needed for arcuate- dependent behavioral and physiological functions (McNay et al. 2012). Possible factors selecting for SCN neural plasticity provided by partially differentiated cells includes transitions through life stages (e.g., sexual maturation, pregnancy or aging) and their differing metabolic demands on the organism. Because of the pivotal role of the SCN in many brain functions the stem-like cells may provide a plasticity in SCN circuitry to correct for external forces, such as responses to food scarcity or abundance associated with seasons and their differing day length and light intensity.

The SCN progenitor-like cells and cells resembling neuroblasts may complete their differentiation and form synapses that alter neural circuits responsible for adjusting key

77 properties of circadian rhythms resulting from the SCN’s coupled circadian oscillators (Herzog et al. 2004; Sun et al. 2017). These features of the clock include the period of the oscillation and its phase relative to the external cycle of light and darkness. As stem cells differentiate, cell junctions and direct communication between cells typically increase, e.g., through increased E- cadherin versus N-cadherin expression. Evidence indicates that changes in cell-cell communication occur rhythmically in the SCN (Prosser et al. 2003) and also alter the circadian period, which could represent an adaptive neural plasticity along with chemical synapse modifications (Azzi et al. 2017).

The importance of cell connectivity in SCN functions was also revealed in two recent meta-analyses of genes expressed preferentially in mouse SCN (Zhao et al. 2016; Brown et al.

2017). Interestingly, we examined the 20 most SCN-enriched genes reported by the first of these studies and found that nine have stem cell or developmental GO Biological Process designations:

Ahl1, Calcr, Cckar, Chodl, Gpld1, Hap1, Ngb, Scn9a, and Zcchc12. In the second study a statistical method was used that minimizes effects from variance in gene expression on measures of gene importance in the SCN, and mouse RNA was collected at different times of day in the studies they included. The authors mention that these two factors combined to reduce representation of some rhythmic genes (Brown et al. 2017). Similarly, reliance on FSS data in our study may have also minimized inclusion of important SCN genes because these mice were sampled just after light onset, between 7 and 9 A M (Allen Brain Institute, personal communication), possibly selecting against rhythmic genes maximally expressed many hours later. Additionally, the ABA study was derived from only male adult mice. Nevertheless, Brown et al., who included data from adult females and multiple phases (Brown et al. 2017), did confirm the importance of two additional homeobox genes, Six3 and Six6, and four FSS genes

78 expressed in the SCN (Avp, Lhx1, Rgs16, and Vipr2) in agreement with Beligala et al., 2018

(Beligala, De, and Geusz 2018; Zhao et al. 2016).

Elevated Expression of Stem Cell Marker MSI2 in the SCN Suggests Significant RNA

Processing Occurs in Circadian Clock Cells

Results provided here indicate MSI2 regulates 12 of the 46 genes in the FSS, including itself, providing evidence that it is a broad regulator of established as well as potentially important SCN gene products (Blcap, Flrt3, Msi2, Ntpcr, Pdcd4, Rgs16, Rorb, Rps6ka2, Slc5a3,

Sox2, Trp53i11, Zfhx3). Many of these target genes have yet to be characterized in relation to the circadian clock. Recent reviews describe several RNA processing events regulated by and serving in circadian clocks throughout the body (Green 2018; Torres et al. 2018). MSI2 is a master RNA-binding protein and posttranscriptional regulator that primarily controls mRNA stability and translation (A E Kudinov et al. 2017). It maintains the undifferentiated state of stem cells and cancer cells, serves in tissue regeneration, and is controlled through Notch pathways of stem cells (Takahashi et al. 2013; Kharas and Lengner 2017). Although MSI2 and its isoform

MSI1 are more commonly found in neoplastic cells (Kudinov et al. 2017), MSI2 is expressed throughout the SCN, as shown in the current study, within neurons and GFAP-positive astrocytes of SCN explant tissue before and after culture and in brain sections from perfused mice. This pattern confirms the elevated Msi2 RNA levels detected in SCN through ISH patterns depicted in the ABA and the inclusion of Msi2 in the SCN FSS (Zhao et al. 2016). MSI1 and MSI2 expression have been identified previously in reactive astrocytes and sites of adult neurogenesis in mouse brain (Sakakibara et al. 2001).

In summary of results in Table 5, highly likely MSI2 targets in the SCN include several of the core clock genes, about a fourth of FSS genes, 7 of 11 stem-like FSS genes, and 15 of the

29 stem cell genes examined. Interestingly, we did not find evidence of MSI2 targeting GFAP,

79 nestin, or vimentin, suggesting that they may function upstream of MSI2. This result agrees with proposed astrocyte regulation of the stem-like state through Notch signaling (Lebkuechner et al.

2015), as mentioned above, while Notch genes may also be under MSI2 control (Table 5).

Although Notch was not highly expressed in the SCN, stem cell-regulators Wnt and Shh that interact with Notch pathways were (Table 5). Also, the GO Biological Processes of SCN FSS members Dlk1 and Slc35c1 include negative regulation of Notch signaling pathway.

The mRNA altered by Msi2 KO, KD, and OE has been described in several tissues: skin

(Bennett et al. 2016; Ma et al. 2017), intestinal epithelium (Wang et al. 2015), hematopoietic stem cells (Park et al. 2014; Rentas et al. 2016; Kharas and Lengner 2017). As summarized in

Table 6, these studies describe MSI2 effects on cell differentiation, migration, and cell-cell interactions that may be relevant to any neurogenesis or circuit remodeling in the SCN. Cell-cell interactions are modified when cells dedifferentiate during EMT into a more stem-like state, typically producing more motile cells (Shibue and Weinberg 2017). In the SCN, these physically altered cells may generate new neurites or undergo synaptic plasticity under the control of RNA- binding proteins (Sephton and Yu 2015).

Table 6. MSI2 knockout (KO), knockdown (KD), and overexpression (OE) studies

Target tissue Reference Major cellular Major targets and methods effects Intestinal (Wang et al. KO: reduced Pathways serving ribosomes, epithelium, 2015) intestinal epithelial stem cells, metabolism, cell-cell colorectal cell proliferation communication, and cancer cell lines KD: reduced neurodegenerative diseases – CLIP-Seq; colorectal cancer cell qRT-PCR proliferation OE: increased intestinal epithelial proliferation HSC, leukemia (Park et al. KO: increased TGFβ receptors; Numb; RNA cell line – HITS- 2014) differentiation into metabolism and HSC self- CLIP; RNA-Seq progenitor cells; renewal signaling pathways smaller quiescent cell population HSC – HITS- (Rentas et al. KD: decreased cell AHR signaling; TGFβ receptors; CLIP; RNA-seq 2016) number PER1, PER2, NR1D2, and OE: increased HSC ARNTL2 self-renewal HSC, human (Kharas and KD: depletes HSC Numb; Wnt, Ras-MAPK, and leukemia cell Lengner population Myc pathways lines – qRT-PCR 2017) OE: accelerates HSC cell cycle Skin, mouse (Bennett et al. KD: increases cell Notch pathway, focal adhesion, keratinocytes – 2016) migration speed and extracellular matrix-receptor HITS-CLIP; focal adhesions interaction, regulation of actin RNA-seq; qPCR and cytoskeleton, adherens junctions, cytokine-cytokine receptor interaction, and p53 signaling Skin – CLIP- (Ma et al. KO: enhances hair Hh and its downstream targets qPCR assay 2017) cycle Shh, Gli1 and Ptch2 OE: delays hair cycle, maintains hair follicle stem cell quiescence HSC: mouse hematopoietic stem cells. HITS: high-throughput sequencing. CLIP: crosslinking immunoprecipitation. AHR: Aryl hydrocarbon receptor. TGFβ: transforming growth factor-β

Numb suppression by MSI2 may help to maintain the immature phenotype of SCN cells.

NUMB protein inhibits Notch and Wnt pathways (X. Cheng et al. 2008; Griner and Reuther

2010). Similarly, the previously reported low SCN expression of NeuN, a protein marker of mature neurons resulting from Rbfox3 gene expression, has been explained as a result of alternative splicing of RNA from a closely related SCN gene (Partridge and Carter 2017).

Perhaps NeuN is expressed at low levels in some SCN neurons so that it does not induce differentiation and thereby impede MSI2 activity, which is known to suppress cell differentiation by inhibiting Numb (Table 6). MSI2 can also act independently of Numb, such as during fibroblast migration (Bennett et al. 2016), and Numb does not appear to be an important MSI2 target in hematopoietic stem cells (Park et al. 2014).

Another notable result from studies manipulating MSI2 levels is that MSI2 targets TGFβ receptor expression (Table 6). Expression of the core clock protein BMAL1 is increased by

TGFβ in epithelial cells and fibroblasts of lung (Dong et al. 2016), whereas it suppresses Per1 and Per2 expression in NIH 3T3 fibroblasts (Gast et al. 2012). Interestingly, Rentas et al. also identified significant MSI2 targeting of PER1, PER2, NR1D2, and ARNTL2, suggesting effects on clock protein expression that should be examined further in the SCN.

MSI2 inhibits signaling through the aryl hydrocarbon receptor (AHR) in human hematopoietic stem cells (Rentas et al. 2016), and AHR is expressed in the SCN (Petersen et al.

2000). Several studies, but not all, link activation of AHR by exogenous ligands to changes in period or phase of circadian rhythms and altered core clock protein levels (Anderson et al. 2013).

MSI2’s regulation of the AHR pathway that in turn interacts with the circadian clock is another way it could modify rhythms. MSI2 also controls expression of AVP (Rentas et al. 2016), a major neuropeptide of SCN neurons (Cormier et al. 2015).

Although MSI1 and MSI2 may be redundant in some cells, they also have divergent functions: In astrocytes of the cerebrum MSI1 appears to control differentiation from multipotent

SVZ progenitor cells (Sakakibara and Okano 1997). MSI2 is a target of MSI1 RNA-binding in spermatogonia (Sutherland et al. 2015). Hematopoietic stem cells are disrupted by Msi2 gene

KO, but do not show a compensatory increase in Msi1 expression (Park et al. 2014). Similarly,

Msi1 is not required for developing mouse retina (Susaki et al. 2009), but its KD produces ependymal cell proliferation and disrupts stem cell production (Sakakibara et al. 2002).

A phylogenetic analysis of RRM-containing genes within the Metazoa indicates they are ancient (Birney, Kumar, and Krainer 1993). MSI2 and additional RBM family proteins CELF2,

CIRBP, hnRNP Q, LARK, and RBMP4 may have been retained during evolution of the SCN circadian clock to maintain an adaptive plasticity in translational capabilities. Cirbp is expressed at moderate levels in SCN and in other brain areas according to its Z-score. It has a reported role in controlling circadian clock genes through RNA-binding (Liu et al. 2013). Similarly, the hnRNP Q gene (Syncrip) regulates circadian rhythms in clock proteins PER1 and CRY1 but was not highly expressed in SCN.

Interestingly, Cirbp and Notch transcripts are downregulated by MSI2 KO, whereas Per1 message is elevated (Park et al. 2014). The rhythmic activity of core circadian clock protein

REV-ERB ALPHA may be regulated translationally by hnRNP Q, which is also under clock control (Kim et al. 2010), and hnRNP D represses stability of mRNA from core clock gene Cry1

(Woo et al. 2010). LARK protein expressed from Rbp4 and Rbp4a genes controls the period and amplitude of circadian rhythms in PER1 (Kojima et al. 2007). Although not significantly rhythmic at the RNA transcript level, LARK protein levels are under circadian control, which is one example of how transcriptional rhythms do not necessarily define circadian rhythms in protein levels or activity (Kojima et al. 2007).

Additional studies of the role of MSI2 and other RNA-binding proteins in the SCN should examine their RNA targets and protein partners further to evaluate molecular functions and whether these vary in response to circadian timing. For example, MSI2 interacts with SOX2 in glioma cells (Cox et al. 2013) and may operate rhythmically in stem-like SCN astrocytes or neurons. Although Msi2 expression shows circadian rhythms in liver and kidney (by CircaDB), a circadian rhythm was not detected in the SCN as a whole.

MSI2 may Control SCN Cells by Regulating miRNA

It has been estimated that an individual microRNA (miRNA) can control hundreds of genes, and miRNAs may control about a third of all genes (Thomas, Lieberman, and Lal 2010).

MSI2 is a strong candidate for high-level control of SCN miRNAs. MSI2 interacts with proteins of the ELAVL (Hu) RNA-binding protein family that function in synaptic plasticity and addiction (Bryant and Yazdani 2016). ELAVL1 forms a complex with MSI2 that controls miR-7 in nervous system development and regulates miRNAs distribution (Choudhury et al. 2013;

Doxakis 2014; Meza-Sosa, Pedraza-Alva, and Perez-Martinez 2014; Loffreda et al. 2015).

Activity of the core clock genes Per1 and Per2 is altered by miR-132 and miR-219, producing effects on the rhythm’s period and its phase shifts in response to entraining light signals (H. Y. Cheng and Obrietan 2007). According to the online Mouse Genome Database

(MGD, http://www.informatics.jax.org/), MSI2 and ELAVL1 could alter the circadian clock through miRNA because they are predicted to bind and suppress miR-7, miR-132, and miR-219.

Also, miR-7 and miR-219 influence voltage-gated K+ channels, NMDA-type receptors, and intracellular Ca2+, potentially altering neuronal circadian rhythms (Mehta and Cheng 2013).

Like the circadian clock mechanism, evidence indicates ELAVL1 is regulated by pyruvate kinase in glioblastoma cells (Mukherjee et al. 2016), suggesting another way that energy demands within the organism might also alter SCN cell networks. Alternatively, ELAVL1 may

84 serve in a non-clock function in the SCN by preventing excitotoxic damage though intracellular

Ca2+ (Skliris et al. 2015); the SCN is unique among hypothalamic nuclei in receiving substantial glutamatergic retinal afferents, and protection from excessive sensory stimuli would be expected.

Stem-Like Cells Persist in SCN Explant Cultures Made from Mice of Different Mouse Strains and Across a Wide Age Range

Mice between 6 and 56 weeks old were used to prepare SCN explant cultures for ICC.

Although adult neural stem cell activity generally declines with age, stem-like cells of the SCN persisted in these cultures. Explant cultures prepared from mice of different genetic backgrounds indicated stem-like SCN cells are not limited to B6 mice and are likely found in other species. A publication that appeared after our work was completed, provided evidence that the adult human

SCN contains stem-like cells, suggesting that this may be a general property of the brain clock

(Pellegrino et al. 2018). Studies exploring what factors maintain the immature state of SCN cells are aided by the knowledge that circadian rhythms persist in SPM; interaction between circadian clock components and stem cell-related genes may provide insight into cell differentiation.

The B6 mouse line provided most of the SCN explant cultures. It offers the possibility of propagating and differentiating many SCN cells from explant cultures derived from mice of the same genetic background, thereby reducing variability in resulting data. Following differentiation, circadian properties of neurons and astrocytes could be examined in conventional culture medium. The cell line SCN 2.2 was developed from immortalized fetal rat SCN and has served in many circadian studies of neurons and glia (Earnest et al. 1999; Allen and Earnest

2002; Farnell et al. 2011; Eggleton et al. 2016). Generating a cell line from adult mouse SCN would enable studies to fully benefit from mouse genome data and allow the circadian clock to be examined in cell lines produced from individual animals following specific mutations and epigenetic or developmental alterations. Further studies of MSI2 and related RNA-binding

85 proteins in SCN cells could determine whether they provide a molecular switch regulating the persistent immature SCN state. The SCN, olfactory bulb, arcuate nucleus, hippocampus, and cerebellum are arguably the most well recognized brain areas containing a self-sustaining circadian clock (Piggins and Guilding 2011). Interestingly, these structures are also rich in cells expressing stem-cell related genes, many of which were examined here.

Conclusions

SOX2, OCT4, MSI2, nestin, and vimentin expression, and cellular co-localization of several of these proteins with GFAP provides additional evidence that diverse stem-like cells remain in the adult SCN following early development. Stem-like cells expressing these proteins proliferate coincidentally with neuronal loss in SCN explants maintained under culture conditions favorable for undifferentiated cell survival. This stem cell medium alters but does not eliminate SCN circadian rhythms. SCN cells positive for OCT4, nestin or SOX2 but negative for

GFAP suggest that SCN explants contain progenitor cells that could differentiate further, ultimately producing neurons or glial cells. The high percentage of SCN cells positive for MSI2 provides evidence for RNA-binding proteins serving an important but uncharacterized role in the stem-like state of circadian cells.

CHAPTER IV: OLIGODENDROCYTE PROGENITOR CELLS FROM THE ADULT MOUSE

SUPRACHIASMATIC NUCLEUS FORM NEURONS WITH ONGOING MYELINATION IN

VITRO

Introduction

Oligodendrocyte progenitor cells (OPCs) are mitotically active, multipotent cells of the central nervous system that differentiate to replenish myelin (Roy et al. 1999). Evidence indicates OPCs also undergo neuronal differentiation (Boulanger and Messier 2017), but how they produce neurons appropriate for specific brain regions remains unknown. Previous studies have reported adult neurogenesis from OPCs in vitro and in the cerebral cortex in vivo (Guo et al. 2010; Gaughwin et al. 2006). Further examination of this process could yield OPC cell lines for use in well controlled studies of what influences and regulates their neurogenesis. OPC cultures may also provide consistent sources of mature neurons for cell therapy to treat demyelinating and neurodegenerative disorders such as Pelizaeus-Merzbacher disease and multiple sclerosis (Goldman 2017; Tognatta and Miller 2016).

OPCs have a described heterogeneity (Leong et al. 2014), but they have not been well characterized relative to the brain region where they reside. For example, it is unclear whether all

OPCs within major brain areas are essentially identical or instead have variable functionality, perhaps based on their microenvironment, which may serve in neural circuit plasticity though neuron replacement or addition.

The local cell environment in the adult brain might dictate the neuronal type that OPCs generate and the neuropeptide produced. OPCs might instead be programmed with a capability to produce neurons appropriate for specific brain areas either before or after migration to their final location during early brain development (Tomassy, Dershowitz, and Arlotta 2016). Adult brain

OPCs are far less understood than other neural stem cells (NSCs) that are also self-renewing and

87 differentiate into three major cell types (neurons, astrocytes, and oligodendrocytes) of the adult brain (Nogueira et al. 2014). Currently, only two sites in the adult brain are well understood as locations for NSCs and neurogenesis, the subventricular zone of the lateral ventricles (Lois and

Alvarez-Buylla 1993) and the subgranular zone in the dentate gyrus of the hippocampus.

However, there is evidence that certain other brain areas, including the hypothalamus, also contain NSCs (Saaltink et al. 2012).

Within the hypothalamus, cells with characteristics of NSCs have been identified in the adult suprachiasmatic nucleus (SCN), which contains the master circadian clock in many species

(Geoghegan and Carter 2008). The SCN receives retinal light signals directly and synchronizes the timing of numerous additional circadian clocks in cells of organs throughout the body. Daily cycles of sleep, physical activity, cell division, hormone production, and many other metabolic processes are controlled by these clocks through the near-24-hour rhythms they generate.

Whether the circadian clock of the SCN is influenced by ongoing or episodic OPC proliferation or differentiation remains an unexplored question. To better understand the reported immature characteristics of the SCN (Beligala, De, and Geusz 2018) and to determine whether OPC differentiation provides neuronal phenotypes common to the SCN, we developed a new method for culturing OPCs from small brain structures such as the SCN. We also show that the cells can differentiate into oligodendrocytes, neurons and, more specifically, at least one important type of

SCN-specific peptidergic neuron.

Materials and Methods

Animals

Mice were bred and maintained in cycles of 12 h light and 12 h dark to entrain their circadian system. Food and water were provided ad libitum. Males and females of C57BL/6 (B6) and C3H mouse strains were used to evaluate how broadly stem-like cells occur in the SCN.

Some B6 mice contained the Per1::luc transgene, and some C3H mice contained a fos::luc transgene. Animals were 4 to 33 weeks old at the time of tissue harvesting, except where noted.

Animal procedures were approved by the BGSU Institutional Animal Care and Use Committees of BGSU and met National Institutes of Health guidelines.

Microdissected SCN Explant Cultures and Differentiation Studies

For SCN explant cultures, surgical reductions of each SCN in 300-µm coronal brain sections were made with three scalpel cuts to remove the ependymal cell layer and optic chiasm tissue as shown in Figure 12A. Explants were placed in glass-bottom culture dishes (Mattek) or plastic culture dishes containing a medium designed for OPC culture (OPM) consisting of

NeuralX (NLX) serum-free NSC medium with added growth factors: fibroblast growth factor-2

(FGF2), platelet-derived growth factor-AA (PDGF-AA), and GS22 supplement (Barratt et al.

2016). To test whether the OPCs, which proliferated to form a cell monolayer, are capable of producing oligodendrocytes, neurons and astrocytes, BrainPhys (BP) medium supplemented with

SM1 and NeuralQ (NLQ) medium with 1% FBS were independently used to induce differentiation.

Additionally, floating and proliferating cell clusters formed after the explants were removed and a monolayer had formed. After 15 weeks in OPM, the cell clusters were dissociated in BP medium to test whether they differentiate into neurons. We also tested the capability of the floating cell clusters to proliferate, form neurospheres, and differentiate.

Immunocytochemistry (ICC) and Confocal Microscopy

For ICC of SCN immediately after sectioning, 150 µm-thick coronal sections were made from ice-chilled brains removed immediately after isoflurane anesthesia and decapitation. For immunofluorescence imaging, cultures were fixed in 4% formalin in phosphate-buffered saline, pH 7.2, for 1 hr at room temperature, and then standard ICC was performed. Indirect

89 immunofluorescence staining with confocal microscopy was used to examine the resulting cell monolayers for the presence of markers for OPCs (oligodendrocyte transcription factor 2: Olig2, platelet derived growth factor receptor alpha: PDGFRA, neural/glial antigen-2: NG2), oligodendrocytes (myelin basic protein: MBP, myelin oligodendrocyte glycoprotein: MOG), neuroblasts (doublecortin: DCX), astrocytes (glial fibrillary acidic protein: GFAP), stem cells

(nestin), immature neurons (Class III-β tubulin: Tuj-1), and mature neurons (microtubule associated protein 2: MAP2, vasoactive intestinal peptide: VIP, neuronal nuclei: NeuN). Fixed samples were rinsed, permeablized with Triton X-100, blocked with normal goat serum, incubated overnight at 4°C with primary antibodies, rinsed, and then incubated for 2 hours with appropriate secondary antibody conjugated with either Alexa Fluor 488, Alexa Fluor 568 or

Alexa Fluor 647 (Life Technologies) at room temperature on a shaker, which was followed by a final rinse.

Confocal microscopy was performed as described in our previous study of neurosphere cultures (Malik, Jamasbi, et al. 2015; Malik, Kondratov, et al. 2015). Briefly, cells were imaged with a DMI3000B inverted microscope (Leica Microsystems, Buffalo Grove, IL, USA) equipped with a Spectra X LED light engine (Lumencore, Beaverton, OR, USA), X-Light spinning-disk confocal unit (CrestOptics, Rome, Italy) and a Rolera Thunder cooled-CCD camera

(Photometrics) with Metamorph software controlling image acquisition and data analysis

(Molecular Devices, Sunnyvale, CA, USA). Confocal images were collected in a Z-series with

10X and 20X objectives and using standard DAPI, fluorescein, rhodamine, and Cy5 filter wavelengths. The distribution of cell types was then determined, and cell counts were obtained using Metamorph Multi-Wavelength Cell Scoring Application Module after background intensity was subtracted based on the highest intensity measurements from controls in which

90 primary antibody was omitted. Cells having a brightness within the top 75% of the intensity range were counted as positive.

Microelectrode Array (MEA) Recordings

SCN OPC cultures maintained in OPM on MEAs coated with poly-D-lysine and laminin

(PDL) were induced to differentiate by switching to BP medium. After several days, extracellular electrical recordings from the MEAs were performed to identify any spontaneous action potential spikes using the MEA2100 system from Harvard Bioscience. The MEA was maintained at 37°C, and medium was exchanged with a medium consisting of phenol red-free, high glucose MEM with bicarbonate levels reduced to that of HBSS (Cellgro, Corning).

Penicillin and streptomycin were added and pH was buffered to 7.2 by using 10 mM HEPES.

Data were analyzed to count and characterize action potentials using Multi Channel

Analyzer software (Multi Channel Systems). The 60 electrodes of the MEA were monitored simultaneously for neuronal activity (spikes) by sampling at 10 KHz. Only spikes with amplitudes greater than six standard deviations above noise were included in the analysis. The time when each spike occurred and the 3-ms of data around each spike were saved for subsequent analysis.

The cells growing on the MEA were imaged with a color camera and inverted microscope. Cells present near each active electrode of the MEA were examined to correlate cell morphology with action potential production. One of the two MEA types used contained transparent conductors that carry signals from the electrodes to the preamplifiers. These conductors, composed of indium-tin oxide, allowed us to visualize cells near the electrodes, which were less obvious in the second MEA type used.

Results

OPCs, which are Scattered in the SCN, Migrate from the Explant Edge, Proliferate, and Form a Monolayer

Expression of OPC markers PFGFRA and Olig2 in cells scattered within the SCN in coronal brain sections that were formalin-fixed immediately after sectioning provided evidence of OPCs in the SCN (Figure 12B). This dissection and rapid fixation approach is similar to ICC methods used to characterize cell types in mouse SCN brain slice cultures that provided a view of the tissue immediately before long-term bioluminescence imaging began (Evans et al. 2011).

Explants were prepared from brain slices that were surgically-reduced by microdissection to remove the optic chiasm and ependymal cells along with the ventricular zone as shown in

Figure 1A, thereby eliminating these possible sources of OPCs and stem-like cells from outside the SCN. During culture in OPM, cells migrated out from the edges of the explant and formed a monolayer of cells attached to the bottom of the dish (Figure 12C). Explants also showed distinctive changes in morphology and tissue rearrangement.

Figure 12: Cells expressing OPC markers identified in the SCN and after they migrate from the SCN explant edge, proliferate, and form a monolayer. A: Scalpel cuts made in 300-

µm-thick brain slices to isolate the SCN for explant cultures. Figure derived from images in the

Allen Institute for Brain Science. B: Cells scattered within the SCN express PDGFRA (red) and

Olig2 (green) in additional 150-µm-thick brain slices prepared for ICC. Blue: Hoechst-labeled nuclei. Scale bar = 100 µm C: Monolayer of cells after 25 days in culture formed from one SCN explant attached to dish. Made from a 13-week-old C3H mouse. Scale bar = 100 µm.

Cells in the Monolayer Express OPC and Proliferation Markers

About 87% of the cells in the monolayer formed by the explants expressed PDGFRA, a marker for OPCs, whereas fewer cells expressed NG2, which is known to be present in early

OPCs (Figure 13A-B). Additionally, most of the monolayer cells expressed nestin, a NSC marker protein (Figure 13C) recently shown to be expressed in OPCs. The cells also co- expressed proliferating cell nuclear antigen (PCNA), a marker of dividing cells, and Olig2, another marker for OPCs (Figure 13D), indicating that these progenitor cells proliferate in culture.

The same experimental approach was used to examine the presence of OPCs in another hypothalamic nucleus, the supraoptic nucleus (SON), that is lateral and not adjacent to the SCN.

It was evident that the explants made from the SON produced a very similar cell monolayer in which most of the cells expressed OPC markers Olig2 and PDGFRA (Figure 13E).

Figure 13: Cell monolayers seeded from explants in OPM and then expanded express OPC markers and cell proliferation marker PCNA. A: Most cells express PDGFRA (green) and fewer cells express NG2 (red). B: Percentages of cells positive for PDGFRA and NG2. C: Most of the cells express nestin, a stem cell marker, shown to be expressed in OPCs. D: PCNA (red) and Olig2 (green) co-expression indicates dividing OPCs. E: Most of the cells in a monolayer formed by explants from hypothalamic supraoptic nucleus (SON) express PDGFRA (red) and

Olig2 (green). Blue: Hoechst nuclear stain. Scale bar = 100 µm for all.

Cells in the Monolayer Have the Potential to Differentiate into Neurons or Oligodendrocytes

Depending on Culture Media

After explant cultures were maintained in OPM for at least 7 days, explants were removed and cell monolayer cultures remaining were switched to BP or NLQ medium to induce differentiation. BP medium is known to support neuronal differentiation, and NLQ medium has been used to induce OPCs to differentiate into mature oligodendrocytes. Upon switching to BP and NLQ medium, the cells in the monolayer formed neuron-like and oligodendrocyte-like cells, respectively (Figure 14).

Figure 14: Cells in the monolayer form neuron-like and glial-like cells after treatment with

BP and NLQ, respectively. A: The monolayer in OPM (NLX). B: Cells in BP medium forming a network of clusters with processes. C: Cells in NLQ medium forming oligodendrocyte-like cells. Scale bar = 100 µm for all.

ICC experiments of BP-treated cells provided evidence for expression of neuronal markers. About 42% of the cells were positive for VIP (Figure 15A-B), which is abundantly expressed in SCN neurons, primarily in the ventral region. This result suggests that the neurons formed by OPCs are location specific, able to form neurons appropriate for the SCN. In addition, most of the BP-treated cells expressed MAP2 (Figure 15A-B), another neuronal marker.

When switching the monolayer cultures from OPM to BP, explants were separated and continued as cultures in a separate dish containing OPM. These explants yielded proliferating floating clumps that were then dissociated by transferring them to BP medium. This approach resulted in cells attached to the dish that were neuron-like as evident by their morphology and expression of immature neuronal marker Tuj-1 (Figure 15C).

In the cultures treated with BP, a subset of cells expressed DCX (Figure 15D), a marker for neuroblasts. Most of the cells in BP are also positive for neuronal markers synapsin and

NeuN (Figure 15E).

D E

Figure 15: Cells produce markers for neurons and neuroblasts after treatment with BP medium to induce differentiation. A: Cells in the monolayer treated with BP show VIP, which is expressed abundantly in SCN neurons. VIP (green), and neuronal marker protein MAP2 (red).

B: Percentages of cells positive for MAP2 and VIP. About 42% of the BP-treated cells were positive for VIP, suggesting local specificity of OPC-derived neuronal cell fate. Scale bar = 100

µm for A, D and E. C: Cluster of neuron-like cells formed by dissociating floating clumps of

99 cells in BP that were initially maintained in OPM for 15 weeks. The cells express neuronal marker protein Tuj-1 (green) and, to a lesser extent, GFAP (red). Scale bar = 50 µm. Cells in BP

(D&E; Top) D: TUJ1 (green), DCX (red). E: Synapsin (green), NeuN (red). Blue: Hoechst- labeled nuclei. D&E; Bottom: During differentiation, a large number of cells entered the neuronal lineage, as shown by a significant increase in Tuj-1. *Significant difference from

NeuralX (OPM) by ANOVA and Scheffe test (p<0.05). Total DCX+ cells, that are neuroblasts, increased almost two-fold. NeuN+ cells also increased significantly. The number of cells lacking both markers of immature neurons (DCX-/TUJ-) declined in BP.

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When treated with BP, some of the OPCs in monolayers differentiated into mature oligodendrocytes forming a mixed culture of neurons and oligodendrocytes (Figure 16). As evident in ICC images, these oligodendrocytes clustered around nascent neurons and provided initial myelination.

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A B

Figure 16: Some OPCs differentiate into oligodendrocytes in BP medium and appear to provide myelination to nascent neurons. A subset of cells in the monolayer treated with BP show markers for oligodendrocytes. (A&B; Top) A: Olig2 (green), MBP (red), Hoechst-labeled nuclei (blue). B: MECP2 (green), MOG (red). Cells positive for oligodendrocyte markers cluster around neurons. Scale bar = 100 µm for all. (A-B; Bottom) A: A small percentage of cells positive for Olig2 and oligodendrocyte marker myelin basic protein (OLIG2+/MBP+) increased in BP. B: About 64% of the BP-treated cells express both MECP2 and MOG, which indicates these are myelinated neurons.

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OPCs are naturally programmed to form mature oligodendrocytes in the nervous system.

In an attempt to test whether the OPCs from SCN can give rise to oligodendrocytes in vitro, monolayer cultures were switched to NLQ medium. These cells then differentiated into an oligodendrocyte-like phenotype, and ICC confirmed the expression of oligodendrocyte markers

MBP (Figure 17A) and MOG (Figure 17B) in most of those cells. MBP is a major constituent of the myelin sheath of oligodendrocytes, and MOG is a glycoprotein expressed on the surface of oligodendrocytes and myelin sheath. In NLQ-treated cultures, cells express GFAP (Figure 17C), suggesting that some cells can differentiate into astrocytes.

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Figure 17: Cells produce markers for mature oligodendrocytes and astrocytes when treated with NLQ medium to induce differentiation. (A-C; Top) A: MBP (red), PDGFRA (green). B:

MOG (red), Olig2 (green). C: MBP (red), GFAP (green). Blue: Hoechst-labeled nuclei. Scale bar = 100 µm for all. (A-C; Bottom) A: About 84% of the cells express MBP. Most of these

MBP positive cells also express PDGFRA indicating that they are still differentiating into mature oligodendrocytes. B: Out of the total number of cells, 36% were positive for MOG. C: About

36% of the NLQ-treated cells were positive for GFAP.

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Cells of BP-Treated Cultures on MEAs Produce Neural Impulses

To further test whether SCN OPCs give rise to neurons, OPC monolayers were grown on

MEAs and recordings were made from all electrodes. Spontaneously generated action potentials were detected as shown by recordings in Figure 18 from the most active electrode in each of two

MEA dishes. Action potentials were recorded at 78% of the 60 MEA electrodes, and the number of spikes ranged from 1 to 57 during 5-minute recordings. This low spike frequency relative to mature neurons resembles the reduced number of action potentials elicited by immature hippocampal neurons after adult neurogenesis, despite the higher excitability of nascent neurons

(Pedroni et al. 2014).

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Figure 18: OPC cultures produce neural impulses after differentiation in BP medium.

Shown are recordings from the most active electrode in each of two MEA dishes with upward and downward spikes separated. Overlay plots are single units within 3-ms windows. The number of spikes at the electrode of the first dish were A: 30 and B: 27, and from the second dish were C: 6, D: 18.

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Discussion

The present study demonstrated that SCN OPCs can migrate from neural tissue explants in culture and continue to proliferate as a monolayer of cells when maintained in OPM. This medium has been used previously to cause purified rat glial precursor cells to proliferate (Barratt et al, 2016). The current study determined that OPCs residing in the SCN can differentiate in vitro and spontaneously generate neurons expressing VIP, which is present at high levels in the

SCN and few other brain areas. VIP neurons generate circadian rhythms and synapse with neurons projecting from the SCN (Tokuda et al. 2018). The ability to produce SCN-derived VIP cells readily from OPCs could facilitate in vitro studies and perhaps SCN cell implant experiments testing the possible role of OPCs in circadian rhythm generation, cell network properties, and distribution of clock timing information within and outside the SCN.

Unlike better known adult NSCs, OPCs may produce a wide range of neuron types and understanding this greater complexity and its control could be valuable for developing neural regenerative therapies. Interactions between the cell-replenishing properties of OPCs and the stem-like properties of adult SCN cells are possible because of the growth factors produced from stem and progenitor cells that control neural cell proliferation and differentiation. One question is whether OPCs in the SCN are responsive to a microenvironment promoting the apparent developmentally arrested state of some SCN cell types. Similarly, SCN OPCs might be distinct from OPCs elsewhere in the nervous system by providing growth factors and other paracrine signaling molecules helping to maintain SCN cell stemness.

A recent meta-analysis provided a comprehensive examination of genes highly expressed in RNA isolated from mouse SCN (Brown et al. 2017), and upon further analysis we found that within the 20 most SCN-enriched genes reported nine have stem cell or developmental GO

Biological Process designations: Ahl1, Calcr, Cckar, Chodl, Gpld1, Hap1, Ngb, Scn9a, and

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Zcchc12. Although typically distributed sparsely in the brain, OPCs could contain these SCN- enriched transcripts and may have contributed to the overall transcriptomics results, a possibility that should be examined by cytology. Similarly, an exploration of the most highly expressed genes in the SCN relative to the rest of brain, identified through in situ hybridization, revealed that 36% have known or suspected functions in neurogenesis, development or associated cell-cell interactions (Beligala, De, and Geusz 2018). Whether these histological results also include SCN

OPCs requires further analysis.

The neurons produced from SCN OPCs in the current study may have properties of immature neurons characterized in the adult dentate gyrus. Their low frequency of spontaneous action potentials is consistent with newly generated neurons (Pedroni et al. 2014), although the

SCN has a low firing rate even during the phase of the circadian cycle when the cells are most active. Also, it may be found that the electrically active neurons derived from OPC cultures produce protein markers of immature cells or lack functional synapses. Our results indicate these cells display a range of cell maturation, expressing markers of immature and mature neurons. Similarly, the cells induced to form oligodendrocytes showed a subset with myelin- producing capabilities, suggesting they could be used in addressing research questions on circadian clock control of nerve and axonal fiber tract repair.

Along with the OPCs released from the explants that proliferated as attached cultures, smaller cells formed floating clusters that also differentiated into cells with neuronal markers on

PDL-coated culture dishes. Many stem cells prefer to grow as suspension cultures, sometimes in tight spheroids that were not observed in this study. Instead, the floating cells formed loosely attached clusters even after several passages to new culture dishes. Whether the floating cells are the same cell type as the attached OPCs is not clear, but they could be in a less differentiated state with greater stem cell potency that might generate a wider range of neuronal types. It is also

108 possible that neurons we generated were also derived from the floating cells, which requires a closer examination of differentiation events.

Additional studies are also needed to determine whether the developing or mature neurons derived from OPCs can generate circadian rhythms in electrical activity and neuropeptide secretion like those in intact SCN. If the immature neurons show an ability to produce circadian rhythms, then similar stem-like or neuroblast-like cells characterized in the

SCN may also contain circadian clocks. The ability to record impulses of OPC-derived neurons with MEAs is important because SCN circadian rhythms have been recorded previously with this method (Herzog, Takahashi, and Block 1998;Herzog et al. 1997). Ultimately, circuit properties of the cells could be examined as well, along with intracellular recordings, to understand how developmental and synaptic plasticity impacts SCN timing properties.

Conclusions

OPC cell cultures can be prepared from the adult mouse SCN and then induced through controlled differentiation to generate cultures enriched in spontaneously excitable neurons and cells resembling oligodendrocytes that might be further manipulated to produce myelin. This ability to produce SCN neurons on demand could enable more consistent and powerful studies of the molecular circadian timing mechanism and intercellular communication modulating circadian rhythms in neural activity.

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CHAPTER V: CONCLUSIONS AND FUTURE DIRECTIONS

Summary of Conclusions

According to our results, most of the genes expressed prominently in the SCN have stem cell-related functions. These roles include stem and progenitor cell proliferation, differentiation, migration, axon lengthening, synapse formation and neural circuit formation. Stem cell proteins

SOX2, OCT4, MSI2, nestin, and vimentin are expressed in SCN cells providing evidence of stem-like cells in the SCN after early development. Scattered throughout the tissue, as in many other brain regions, the SCN also contains OPCs that have been shown to have multipotent properties. These OPCs can be cultured and induced to differentiate into spontaneously excitable neurons and cells resembling oligodendrocytes that might be further manipulated to produce myelin for use in understanding and treating myelin deficiency diseases.

Our results provide additional evidence that the mature SCN contains cells with regenerative properties. These cells can provide plasticity enabling circadian rhythms to adjust to changing environmental timing cues, seasonal behavioral cycles or aging. An SCN cell line can be prepared that may provide a consistent source of rhythmic cells that would enable simpler genetic manipulation of key mammalian clock genes. They may also provide abundant material for characterizing low-abundance proteins serving in clock functions, myelination, and the possible role of the clock in OPC differentiation.

Limitations

Our meta-analysis provided a robust list of stem cell-related genes that are highly expressed in the SCN compared to the rest of the brain. A similar bioinformatics approach has been previously used to find genes that are differentially expressed in the SCN compared to other brain regions, which identified 2346 genes that were enriched in the SCN (Brown et al. 2017).

Although such studies based on meta-analysis of transcriptomic datasets are powerful enough to

110 provide new avenues for understanding SCN physiology, there were some limitations associated.

In our meta-analysis, certain analyses were limited by the availability of data in databases. For example, out of the 25 genes analyzed, only 19 could be used in the differential search because the remaining weren’t available in the Allen Brain Atlas. Target gene expression wasn’t available for some of these genes and hence did not generate a fold change value. Furthermore, the Allen Brain Atlas does not specify a time of the day at which the tissues were collected, ignoring the circadian variation of expression of the genes that cycle rhythmically. The Fine

Structure Search tool selects against genes that cycle in expression and are near their minimal expression early in the day, or if the oscillation caused variation in results from these genes. An example is VIP, which is excluded from the FSS list.

Our study about the expression of stem cell-related proteins in the SCN mainly focused on juvenile and adult mice and did not take into consideration factors such as age, sex, and mouse strain. Previous studies have shown that there are changes in SCN gene expression that occur with age (Banks, Nolan, and Peirson 2016). An example is the expression of SIRT1 which declines with age and has been shown to affect the stability of the molecular clock (Chang and

Guarente 2013). Similarly, there are reports about sexual differences in SCN gene expression

(Kuljis et al. 2013). A sex difference in the number of VIP neurons has been shown in humans

(Zhou, Hofman, and Swaab 1995; Swaab et al. 2003) and jerboas (Lakhdar-Ghazal, Kalsbeek, and Pevet 1992). Additionally, androgen receptors were shown to be more highly expressed in male mice than in females causing a sex difference in circadian rhythms (Iwahana et al. 2008).

Accordingly, for a more robust understanding about the stem-like cells in the SCN, a thorough analysis taking age, sex and strain of the mouse into consideration would be beneficial.

The chapter about in vitro neurogenesis from SCN OPCs demonstrates that these OPCs can proliferate, form a cell monolayer and differentiate into neurons, oligodendrocytes or

111 astrocytes upon treatment with appropriate culture conditions. In this study, higher cell counts were observed for OPC markers PDGFRA and Olig2, whereas the percentage of NG2-positive cells was significantly lower in the monolayer. For immunostaining of NG2, we used a mouse monoclonal anti-NG2 antibody. If we had instead used an antibody against AN2 which is the mouse homologue of the rat proteoglycan NG2 (Stegmüller et al. 2002) or even a polyclonal anti-NG2 antibody, immunoreactivity may have been enhanced.

The current study also determined that OPCs residing in the SCN can differentiate in vitro and generate VIP-positive neurons, which are present at high levels in the SCN and few other brain areas. It was interesting to observe that OPCs have the potential to generate region- specific neurons in vitro. Previously it was shown that OPCs derived from the hindbrain can differentiate into mature oligodendrocytes in vivo when transplanted into the forebrain but still keep the hind brain identity as shown by the expression of hindbrain markers HOXA2 and

HOXB4 (Lu et al. 2013). This result, along with ours, implies that OPCs have the ability to generate region-specific mature cell types. This ability could facilitate in vitro studies and perhaps SCN cell implant experiments testing the role of OPCs in circadian rhythm generation and cell network properties.

Relevance to Medical Fields

Neural stem and progenitor cells are highly proliferative and have the potential to differentiate into all the main cell types of the nervous system. Therefore, they are an excellent source of cells for cellular replacement therapies for diseases caused by a loss of a particular cell type. There are several reports about successfully applying neural stem cell therapies to improve cognition and promote synaptic growth in Alzheimer’s disease (Ager et al. 2015; Q. Zhang et al.

2016). Furthermore, human mesenchymal stem cell-based therapies have been used for treating neurodegenerative diseases such as Parkinson’s disease, amyotrophic lateral sclerosis, and

112 multiple system atrophy in rodent models (Volkman and Offen 2017). Studies have also shown that hESC-derived OPC transplantation into spinal cord injury sites in rats can result in remyelination and functional repair (Faulkner and Keirstead 2005). Accordingly, it is highly possible that SCN-derived neural stem cells or glial progenitors can serve as a source of a continuous supply of cells for stem cell-based therapies to treat neurodegenerative diseases.

Future Directions

Changes in cell-cell contacts are reported to alter the period of SCN rhythms and circadian rhythms in behavior. Furthermore, stem cells are known to have plasticity in their cell- cell contacts. Also, stem-like properties of SCN cells may allow for more flexible and adaptive circadian rhythms. Based on this rationale, the stem-like cells and glial progenitors in the SCN described in this study should be further characterized.

The neurogenesis capability of SCN OPCs can be further confirmed using patch clamp experiments to record action potentials. Pharmacological experiments can also be used for further testing of action potential properties. Additionally, a cell line can be produced that could be a continuous supply of genetically similar cells and large numbers of neurons to enable improved molecular and electrical studies.

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APPENDIX A: SUPPLEMENTAL FIGURES

Supplemental Figure 1: SCN explants lose neurons with time in SPM. Explant after 1 (A) and 8 (B) days in culture showing Hoechst-stained nuclei (blue) and cells positive for VIP

(green). Cultures were made from 9-week-old B6 mice. Scale bar: 100 µm.

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Supplemental Figure 2: Example of Hoechst-labeled cell nuclei in SCN brain section.

Shown is the DAPI-channel image used with Figure 8D for cell counting. Scale bar = 100 µm.

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APPENDIX B: COPYRIGHTS

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APPENDIX C: LIST OF ABBREVIATIONS

ABA Allen Brain Atlas

AHR Aryl hydrocarbon receptor

ARH Arcuate nucleus of the hypothalamus

BLI Bioluminescence imaging

BMAL1 Brain and muscle ARNT-like protein 1

BP BrainPhys medium

CCG Clock-controlled gene

CLIP Cross-linking immunoprecipitation

CLOCK Circadian locomotor output cycles kaput

CRY Cryptochrome

DCL Doublecortin-like protein

DCX Doublecortin

DG Dentate gyrus

ECM Extracellular matrix

EGF Epidermal growth factor

EMT Epithelial-to-mesenchymal transition

FGF2 Fibroblast growth factor-2

FSS Fine structure search

GFAP Glial fibrillary acidic protein

GO BP Gene ontology bioprocess

GRP Gastrin-releasing peptide

HITS High-throughput sequencing

HSC Mouse hematopoietic stem cells

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ICC Immunocytochemistry

ISH In situ hybridization

KD Knockdown

KO Knockout

LPO Lateral preoptic area

MAP2 Microtubule associated protein 2

MBP Myelin basic protein

MEA Microelectrode array

MOG Myelin oligodendrocyte glycoprotein

MSI2 Musashi RNA-binding protein 2

NeuN Neuronal nuclei

NG2 Neural/glial antigen-2

NLQ NeuralQ medium

NLX NeuralX medium

NSC Neural stem cell

OB Olfactory bulb

OC Optic chiasm

OCT4 Octamer binding protein-4

OE Overexpression

Olig2 Oligodendrocyte lineage transcription factor 2

OPC Oligodendrocyte progenitor cell

OPM OPC culture medium

PCNA Proliferating cell nuclear antigen

PDGFAA Platelet-derived growth factor-AA

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PDGFRA Platelet-derived growth factor receptor alpha

PDL Poly-D-lysine and laminin

PE Periventricular nucleus

PER Period

PK2 Prokineticin 2

PVH Paraventricular hypothalamic nucleus

PVHd PVH descending division

RHT retinohypothalamic tract

RMS Rostral migratory stream

ROI Region-of-interest

ROR Retinoic acid receptor-related orphan nuclear receptor

RRE RORs/REV-ERBs-response element

RRM RNA recognition motif

SPM Stem and progenitor cell culture medium

SCN Suprachiasmatic nucleus

SGZ Subgranular zone

SO Supraoptic nucleus

SVZ Subventricular zone

Tuj-1 Class III beta tubulin

VIP Vasoactive intestinal polypeptide

3V Third ventricle

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APPENDIX D: IACUC APPROVAL

DATE: January 22, 2019

TO: Michael Geusz, PhD FROM: Bowling Green State University Institutional Animal Care and Use Committee

PROJECT TITLE: [1181520-3] Molecular biology and biomedical applications of circadian clock cells IACUC REFERENCE #: SUBMISSION TYPE: Continuing Review/Progress Report

ACTION: APPROVED APPROVAL DATE: January 22, 2019 EXPIRATION DATE: January 16, 2021 REVIEW TYPE: Designated Member Review

Thank you for your submission of Continuing Review/Progress Report materials for the above referenced research project. The Bowling Green State University Institutional Animal Care and Use Committee has APPROVED your submission. All research must be conducted in accordance with this approved submission. Please make sure that all members of your research team read the approved version of the protocol.

The following modifications have been approved:

• Continuing Review/Progress Report - AnnualRenewal_1181520_122918.pdf (UPDATED: 12/29/2018)

Report all NON-COMPLIANCE issues regarding this project to this committee.

Please note that any revision to previously approved materials must be approved by this committee prior to initiation. Please use the Addendum Request form for this procedure.

If you have any questions, please contact the Office of Research Compliance at 419-372-7716 or [email protected]. Please include your project title and reference number in all correspondence with this committee.

This letter has been electronically signed in accordance with all applicable regulations, and a copy is retained within Bowling Green State University Institutional Animal Care and Use Committee's records.

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