FUNCTIONAL ORGANIZATION OF CENTRAL AND PERIPHERAL

CIRCADIAN OSCILLATORS IN MAMMALS

by

Caroline Hee-Jeung Ko

A thesis submitted in conformity with the requirements for the degree of Ph.D. Graduate Department of Psychology

University of Toronto

© Copyright by Caroline H. Ko 2009

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Functional Organization of Central and Peripheral Circadian Oscillators in Mammals.

Caroline Hee-Jeung Ko, Ph.D. 2009. Department of Psychology, University of Toronto.

ABSTRACT

The suprachiasmatic nucleus (SCN) of the anterior hypothalamus has long been

considered a master circadian pacemaker that drives rhythms in physiology and behavior

in mammals. The recent discovery of self-sustained and cell-autonomous circadian

oscillators in peripheral tissues has challenged this position. This dissertation tested the

general hypothesis that the SCN has properties that distinguish it from other oscillators,

thereby positioning it atop a circadian hierarchy. The general approach was to compare

the consequences of altering the molecular circadian clock on tissue-autonomous

rhythmicity in mice. In the first experiments, the role of the SCN as a master clock was

tested by manipulating the expression of a circadian gene in the brain. Specifically, the

expression of the short period tau mutation of casein kinase-1-epsilon (CK1ε) was

controlled in an anatomically- and a temporally-specific manner via a tetracycline

transactivator regulatory system. This inducible expression of CK1εtau affected the

period of activity rhythms when expressed in the SCN, but did not affect the tissue-

autonomous rhythmic properties in the peripheral tissues. Second, real-time

bioluminescence imaging of tissues from PER2::LUCIFERASE mice revealed that

period and phase of different circadian oscillators were tissue specific. Various circadian

gene mutations (Cry1-/-, Cry2-/-, Cry1-/-;Cry2-/-, Clock∆19/∆19) produced little difference in

rhythmic properties between the SCN and peripheral oscillators, although Cry1-/- SCN

had more robust and persistent rhythms compared with the periphery. Third, the loss of

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Bmal1, which produces behavioral arrhythmicity, eliminated rhythms in the peripheral

tissues, but not in the SCN. Bmal1-/- SCN rhythms were highly variable in period and

amplitude, fitting a stochastic, but not a deterministic model of rhythm generation.

Unlike mutations in other circadian genes, rhythmicity was completely abolished in

single SCN neurons in Bmal1-/- mice, indicating that rhythms in Bmal1-/- SCN tissue are a

property of the tissue organization rather than an averaging of single-cell autonomous

rhythms. The SCN, therefore, has a unique anatomical organization that contributes to

long-term stability and temporal organization of the circadian hierarchy.

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ACKNOWLEDGMENT

I have been blessed to find not only a great advisor but two in Drs. Martin Ralph and Joseph Takahashi. Each of them has provided me, in individual but complementary ways, with scientific training and career guidance. Because of them, I have had a unique opportunity to thrive in two different learning atmospheres: Dept. of Psychology at University of Toronto and Dept. of Neurobiology and Physiology at Northwestern University. It has been an experience and I thank them for the opportunity. I thank my committee members, Drs. John Yeomans and Richard Stephenson, for their professionalism, encouragement, and constructive criticisms; and Drs. Michael Lehman and John Peever for sharing their insights. Also, I am grateful to the Department of Psychology for understanding my absence. The work included in this dissertation could not have been completed without the help from Jennifer Mie Kasanuki, Erika Jang, and Bradford Chong – talented undergraduates who helped with animal colony management; Eun Joo Song – research specialist who generated the transgenic mice; Andrew Schook – in situ technician; and, Drs. Daniel Forger, Andrew Liu, David Welsh, Yujiro Richard Yamada, and Ethan Buhr – collaborators who helped with data collection and analysis. I am also indebted to Drs. David Ferster, Phil Lowrey and Seung-Hee Yoo for their generosity in sharing their knowledge and wisdom. To friends and colleagues from both Ralph lab and Takahashi lab: I appreciated your individuality and the group dynamics. Thank you for providing the laughter and even a few drops of tears (so to speak). We have, indeed, grown to be a family. Special thanks go out to Drs. Erin McDearmon Blondell, Hee-kyung Hong, and Marleen de Groot – your friendship extends beyond the walls of the lab and I count on it to continue. I thank Angie Lee, Edgar Ho, Larry Kim and William Nguyen – you freely offered your friendship (which included your time, cars, houses, food, etc.) so that I could perform at my best, especially when I was uprooted between Toronto and Evanston. To C. Charles Dauk: thank you for cheering me through the last stretch (perhaps the toughest part) and lifting my spirit. My family has always shown insurmountable patience and understanding. They have been the source of unconditional love and support that gives me strength. Dad, mom, and Dan: you are my foundation that I stand on. I love you! To Father in Heaven, who has blessed me with all the people and measures in my life: I am grateful for you have readied me to close this chapter. I look forward with excitement to begin anew. Lastly, I hope to have made my late grandmothers proud. This thesis is dedicated to these women of my history and to my parents who have challenged me to dream and have believed in me.

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TABLE OF CONTENTS

ABSTRACT........................................................................................................................ii

ACKNOWLEDGMENTS..................................................................................................iv

TABLE OF CONTENTS.....................................................................................................v

LIST OF TABLES..............................................................................................................ix

LIST OF FIGURES.............................................................................................................x

LIST OF ABBREVIATIONS...........................................................................................xii

LIST OF APPENDICES....................................................................................................xv

CHAPTER 1. INTRODUCTION.......................................................................................1

1.1 Circadian systems and their adaptive significance

1.2 Circadian organization in mammals

1.2.1 Pacemaker model: Input – Pacemaker – Output

1.2.2 The suprachiasmatic nucleus (SCN) as the master circadian oscillator

1.2.3 Non-SCN oscillators

1.3 Structure and function of the molecular clock in mammals

1.3.1 Core components of the molecular clock

1.3.2 Circadian regulation by casein kinase 1 epsilon (CK1ε)

1.3.3 Phenotypic effects of circadian mutations

1.4 Functional organization of the SCN

1.4.1 Anatomy of the SCN

1.4.2 Cell-autonomous oscillators

1.5 Organization of peripheral oscillators

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1.5.1 SCN output and peripheral oscillators

1.5.2 Discovery of self-sustained, cell-autonomous peripheral oscillators

1.5.3 Comparison of the structure and function of the molecular clocks between

the SCN and peripheral oscillators

1.6 Hypothesis

CHAPTER 2. METHODS................................................................................................25

2.1 The conditional expression of CK1ε transgene

2.1.1 Review of the tetracycline transactivator system

2.1.2 Characterization of tTA promoter lines using β-galactosidase staining

2.1.3 Generation and characterization of TetO-CK1ε transgenic mice

2.1.4 Generation of PER2::LUCIFERASE + CaMK2α-driven CK1ε(tau) mice,

bioluminescence imaging, and data analysis

2.2 PER2::LUCIFERASE reporter line and clock mutants

2.2.1 Background: PERIOD2::LUCIFERASE (PER2::LUC) knock-in mouse

2.2.2 Generation of PER2::LUC x circadian mutant mice

2.2.3 Tissue explant culture and bioluminescence imaging

2.2.4 Bioluminescence data analysis

CHAPTER 3. CONDITIONAL EXPRESSION OF CK1ε(tau): EFFECTS ON

BEHAVIORAL RHYTHMS AND MOLECULAR OSCILLATORS IN TRANSGENIC

MICE..................................................................................................................................40

3.1 Introduction

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3.2 Generation and characterization of the transgenic mice

3.2.1 Characterization of the tTA promoter lines

3.2.2 Characterization of tetO-HA-CK1ε transgenic mice

3.3 Behavioral effects of tetO-driven CK1ε expression

3.4 Effect of tetO-driven tau transgene expression as displayed by PER2::LUC

bioluminescence imaging

3.5 Chapter 3 – Summary and discussion

CHAPTER 4. ORGANIZATION OF THE CIRCADIAN MOLECULAR CLOCK IN

THE CENTRAL AND PERIPHERAL OSCILLATORS.................................................58

4.1 Introduction

4.2 Effect of circadian gene mutations on periodicity of PER2::LUC molecular clock

output in the SCN and peripheral oscillators

4.2.1 PER2::LUC bioluminescence rhythms in the SCN compared to the wheel-

running behavioral rhythms

4.2.2 Effect of circadian gene mutations on periodicity of PER2::LUC rhythms

in the peripheral oscillators compared to the SCN

4.3 Effect of circadian gene mutations on coordination of phase relationships among

the oscillators

4.3.1 Peripheral oscillators are phase-coordinated in clock mutant mice

4.3.2 Tissue-autonomous oscillator re-setting via forskolin treatment

4.4 Effect of circadian gene perturbations on robustness and persistence of

PER2::LUC rhythms in peripheral oscillators

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4.5 Chapter 4 – Summary and discussion

CHAPTER 5. INTRINSIC NETWORK OSCILLATIONS IN THE SCN AS

REVEALED IN Bmal1 MUTANT MICE.........................................................................81

5.1 Introduction

5.2 Characterization of the rhythmic PER2::LUC output in the Bmal1-/- SCN

5.2.1 Bmal1-/- SCN explants display non-circadian, stochastic PER2::LUC

rhythms

5.2.2 Single-cell recording of PER2::LUC rhythms reveal Bmal1-/- SCN neurons

are arrhythmic

5.3 Intercellular coupling drives a network oscillator in the Bmal1-/- SCN

5.4 Chapter 5 – Summary and discussion

CHAPTER 6. GENERAL DISCUSSION........................................................................99

APPENDIX A..................................................................................................................106

APPENDIX B..................................................................................................................112

APPENDIX C..................................................................................................................119

APPENDIX D..................................................................................................................121

APPENDIX E..................................................................................................................123

REFERENCES................................................................................................................130

CURRICULUM VITAE..................................................................................................148

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LIST OF TABLES

Table 1.1. Mouse circadian clock and clock-related genes.........................................14

Table 4.1. Mean period (± std dev) of PER2::LUC bioluminescence........................63

Table A.1. Mouse circadian mutants and observed circadian and physiological

phenotypes...............................................................................................124

x

LIST OF FIGURES

Figure 1.1. The three-component model of the pacemaker............................................4

Figure 1.2. Transcriptional-translational feedback loops of the mammalian circadian

clock.............................................................................................................9

Figure 2.1. The tetracycline transactivator system.......................................................27

Figure 3.1. Schematic diagram of the tetracycline regulatory (tet) system and

constructs used to generate CK1ε transgenic mouse lines.........................42

Figure 3.2. Analysis of tTA lines using -galactosidase staining................................45

Figure 3.3. Characterization of the tetO-driven CK1 lines.........................................47

Figure 3.4. Wheel-running activity records from mice expressing tetO-driven tau

transgene in the SCN.................................................................................49

Figure 3.5. Wheel-running activity records from mice expressing tetO-driven tau

transgene in brain regions other than the SCN..........................................50

Figure 3.6. Expression analysis of the Scg2-driven CK1 transgene in the SCN........52

Figure 3.7. Wheel-running activity records from mice expressing tetO-driven wild

type CK1 transgene in the SCN...............................................................53

Figure 3.8. Tissue-specific transgene protein expression analysis and PER2::LUC

bioluminescence records from CaMK2α-tTA + tetO-HA-CK1ε(tau)

tissues.........................................................................................................55

Figure 4.1. PER2::LUC bioluminescence in ClockΔ19 mutant mice..........................64

Figure 4.2. PER2::LUC bioluminescence in Cryptochrome (Cry) mutant mice.........66

Figure 4.3. PER2::LUC bioluminescence in Bmal1 mutant mice...............................67

xi

Figure 4.4. Phase map for central and peripheral circadian oscillators of PER2::LUC

mice............................................................................................................70

Figure 4.5. Phase map for peripheral circadian oscillators of PER2::LUC mice – acute

response to forskolin..................................................................................73

Figure 4.6. Phase map for peripheral circadian oscillators of PER2::LUC mice –

steady-state phase for forskolin-induced circadian rhythms......................74

Figure 4.7. Robustness and persistence of PER2::LUC rhythms in peripheral

oscillators...................................................................................................76

Figure 5.1. Detailed view of PER2::LUC bioluminescence from wild type and

Bmal1-/- SCN explants...............................................................................84

Figure 5.2. Inter-peak interval analysis of PER2::LUC bioluminescence in SCN

explants......................................................................................................85

Figure 5.3. Stochastic rhythmicity in Bmal1-/- SCN is not cell autonomous...............88

Figure 5.4. Uncoupling SCN cells abolishes stochastic rhythms from Bmal1-/- SCN

explants......................................................................................................90

Figure 5.5. Single-cell rhythmicity before-, during-, ad after-TTX treatment from cells

within an intact SCN slice..........................................................................92

Figure A.1. Vector map for plasmid tetO-HA-CK1ε..................................................107

Figure A.2. PER2::LUC bioluminescence records from wild type and Bmal1-/-

olfactory bulbs.........................................................................................120

Figure A.3. Schematic diagram of simulated intercellular coupling...........................122

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LIST OF ABBREVIATIONS

Apoc3 Apolipoprotein C-III

AR Arrhythmic

AVP Arginine vasopressin

AVP-V1a AVP Receptor 1A

bHLH Basic Helix-Loop-Helix

BIC Bicuculline

BNST Bed Nucleus of Stria Terminalis

CA Coupling Agent

CaMK2 Calcium-CalModulin-dependent Kinase II

CCG Clock-Controlled Gene

CK1/ Casein Kinase 1 Epsilon/Delta

CRE cAMP Responsive Element

CREB CRE binding protein

CT Circadian Time

DD Constant Dark

DMH Dorsomedial Hypothalamus

FEO Food-Entrainable Oscillator

GABA Gamma-aminobutyric Acid

GSK3 Glycogen Synthase Kinase III Beta

Hsp60 Heat-Shock Protein 60

IGL Intergeniculate Leaflet

xiii

LD Light-Dark

LRE Light-responsive Element

LUC Luciferase

mPOA Medial Preoptic Area of the Hypothalamus

NPAS2 Neuronal PAS domain protein 2

NR Not Rhythmic (within circadian period range)

NSE Neuron-specific Enolase

PAS Period-Arnt-Single-minded

PCR Polymerase Chain Reaction

PKA Protein Kinase A

PMT Photomultiplier Tube

PTX Pertussis Toxin

PVT Paraventricular Thalamic Nuclei

RHT Retinohypothalamic Tract

RF Restricted-Feeding

ROR Retinoic acid-related Orphan Receptor

RRE ROR Response Element

Scg2 Secretogranin 2

SCN Suprachiasmatic Nucleus

tetO tTA-responsive Tetracycline Operator

TRE Tetracycline-Response Element

tTA tetracycline TransActivator

TTX Tetrodotoxin

xiv

VIP Vasoactive Intestinal Peptide

Vipr2 VIP receptor 2

VMH Ventromedial Hypothalamus

WT Wild Type

ZT Zeitgeber Time

xv

LIST OF APPENDICES

Appendix A.....................................................................................................................106

• Figure A.1. Vector map for plasmid tetO-HA-CK1ε.

• Hamster CK1ε cDNA sequence.

• Alignment of hamster and mouse CK1ε sequences.

Appendix B.....................................................................................................................112

• In Situ protocol.

Appendix C.....................................................................................................................119

• Figure A.2. PER2::LUC bioluminescence records from wild type and Bmal1-/-

olfactory bulbs.

Appendix D.....................................................................................................................121

• Figure A.3. Schematic diagram of simulated intercellular coupling.

Appendix E.....................................................................................................................123

• Table A.1. Mouse circadian mutants and observed circadian and physiological

phenotypes.

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CHAPTER 1. INTRODUCTION

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1.1 Circadian systems and their adaptive significance

Organisms at essentially all levels of phylogeny produce biological rhythms that

reflect the major physical cycles of the environment. These endogenously generated

rhythms match the regular changes generated by movements of the earth and moon, and

their revolution about the Sun; hence, they have periods of about a day, about a month

(circalunar), about a year (circannual), and about one tidal cycle (circatidal). The best

understood of these systems biologically is the circadian clock, which is found

ubiquitously in nature. The word circadian derives from the Latin words circa (about)

and dies (day). Hence, circadian rhythms are cycles that occur with a periodicity of ~24

hours. In organisms from cyanobacteria to humans, circadian timing systems are

responsible for pervasive regulation of physiological and behavioral processes that match

the day (Lowrey and Takahashi, 2004; Reppert and Weaver, 2002; Takahashi et al.,

2008).

The ubiquity of circadian function among organisms has led to the assertion that

biological rhythms have provided significant adaptive advantage over the course of

evolutionary time. Moreover, the structure of circadian oscillators is very similar at the

molecular genetic level across phylogenetically distant species. This attests not only to

the importance of biological clocks, but also to the ancient derivation of circadian

mechanisms.

Biological clocks are thought to have evolved for two primary adaptive reasons.

First, they provide organisms with a temporal organization of function. For example,

cellular recovery (i.e., cardiovascular remodeling) may be coordinated with time of low

demand, thereby optimizing the efficient balance of energy acquisition and use. Second,

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this temporal organization can synchronize organisms with external environmental

demands, leading the organisms to anticipate and prepare for regular changes in their

environments. For example, a diurnal animal becomes active in anticipation of the dark-

light transition, which confers a selective advantage – “early bird gets the worm”.

Timing is important not only for the individual in a rhythmic physical

environment, but also in relation to other organisms. Predators hunt when prey are most

active, thereby reducing their effort to acquire food by conserving energy at non-optimal

times. Furthermore, species that feed on similar diets can avoid competition by foraging

at different times of day. The control of these behavioral rhythms is reliant on the

temporal coordination among different biological processes within an organism.

Consequently, a significantly reduced fitness has been associated with loss of

clock function. For example, studies have shown that when a component of the

endogenous clock is altered, or when the internal clock’s periodicity does not match the

environmental cycle, organisms experience decreased life span and reproductive deficits

(Hurd and Ralph, 1998; Klarsfeld and Rouyer, 1998; Miller et al., 2004; Pittendrigh and

Minis, 1972).

1.2 Circadian organization in mammals

1.2.1 Pacemaker model: Input – Pacemaker – Output

Although the anatomical location of the clock differs among species, all circadian

systems can be generalized in a three-component model (Figure 1.1). The components

are 1) a pacemaker, a molecular clock that has a period of approximately 24 hours and

continues to keep time even in the absence of environmental timing cues;

4

Figure 1.1. The three-component model of the pacemaker. (A) The circadian system is depicted as a pathway that comprises inputs (entraining signals), the mechanism that generates the circadian rhythms (oscillator), and outputs. (B) At the system level, environmental time cue (e.g., light) reaches the circadian pacemaker in the SCN, which then drives output rhythms as diverse as the activity-rest cycle and the metabolism of the liver and other organs. (C) Cellular clocks (the molecular clocks) regulate the rhythmic expression of genes and other cellular functions. RHT = retinohypothalamic tract.

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2) an input pathway that conveys time cues to the pacemaker; and 3) output pathways by

which the pacemaker can influence biological systems and behavior. It is important to

note further that a hierarchy of oscillators exists in multicelluar organisms. Not only is

there a master pacemaker, but the individual systems, tissues and cells are also equipped

to generate rhythms autonomously (Welsh et al., 2004; Yoo et al., 2004).

In mammals, the master pacemaker is located in the hypothalamic

suprachiasmatic nucleus (SCN). The SCN is also referred to as the central oscillator;

hence, ‘peripheral’ oscillator in mammals often refers to any tissue exclusive of the SCN.

The major environmental cue that conveys time-of-day information to the SCN is light.

The SCN receives direct retinal light input via the retinohypothalamic tract (RHT) and, in

turn, synchronizes and coordinates the rhythms of peripheral tissues (Ko and Takahashi,

2006; Lowrey and Takahashi, 2004; Reppert and Weaver, 2002).

1.2.2 The SCN as the master circadian oscillator

In early 1970s, two independent groups of researchers (Dr. Moore’s group from

University of Chicago, and Drs. Stephan and Zucker from University of California –

Berkeley) speculated that the photoreceptors in the retina must have access to the

circadian pacemaker for entrainment to the day-night cycle. Hence, initial efforts led

researchers to investigate the visual pathways. Surprisingly, interrupting both the

primary optic tracts and the accessory optic system did not affect entrainment (Stephan

and Zucker, 1972a, b). Further investigations revealed that a separate, but direct

retinohypothalamic pathway terminates in the SCN (Moore and Lenn, 1972), and

subsequent lesion studies identified the SCN as a brain region responsible for measurable

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circadian behaviors (e.g., activity, sleep, and drinking) (Moore and Eichler, 1972;

Stephan and Zucker, 1972a).

Conclusive evidence that the endogenous circadian pacemaker is contained within

the SCN came from a series of experiments by Ralph and colleagues (1990; 1993). In the

late 1980s, a hamster was discovered with significantly shortened freerunning period of

wheel-running activity. Subsequent breeding experiments showed that this trait was

heritable and that the mutation, which was named “tau,” acted in a semi-dominant

fashion: the normal freerunning period for hamsters is approximately 24.1 hours, the

mutant hamster displayed the freerunning period of approximately 22 hours, and the

homozygous offspring had a freerunning period of 20 hours1 (Ralph and Menaker, 1988).

Ralph and colleagues demonstrated the transfer of circadian period from one animal to

another using SCN tissue grafts. When the SCN of a hamster was ablated then replaced

with an SCN transplant from a different tau genotype, the restored behavioral rhythms

had periods that always reflected the genotype of the donor (Ralph et al., 1990).

Moreover, SCN chimeras produced by tissue grafts can express behavioral rhythms of

two tau genotypes simultaneously (Ralph et al., 1993).

Importantly, not all rhythms are restored by SCN grafts, e.g., circadian

neuroendocrine rhythms. These neuroendocrine rhythms appear to require intact neural

projections from the SCN (Kalsbeek et al., 2000; Perreau-Lenz et al., 2003) whereas

diffusible (or humoral) signals from the SCN grafts are sufficient to restore the

behavioral rhythms (Silver et al., 1996).

1 After 12 years, Lowrey and colleagues (2000) identified that tau hamster phenotype is due to a mutation in Casein kinase 1 epsilon (CK1ε), a homolog of the Drosophila circadian gene doubletime (dbt). The function of CK1ε in the molecular mechanisms of the circadian clock is discussed in section 1.3.

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1.2.3 Non-SCN oscillators

In mammals, the SCN sits atop the hierarchy of circadian oscillators that are

found throughout an organism. The non-SCN oscillators may be self-sustainable and

utilize the same molecular mechanisms described for the SCN, or they may be dependent

on separate neuronal or systemic activity. The first category of non-SCN oscillators is

evident in various isolated tissue cultures where molecular circadian oscillations can be

followed ex vivo (Yoo et al., 2004). The second category of SCN-independent

oscillations is represented by two inducible behavioral rhythms. One is a food-

entrainable oscillation (FEO) produced by daily restricted feeding. Its existence is

reflected in daily anticipatory behavior that precedes the scheduled feeding time. The

other behavioral rhythm can be produced by daily injection or chronic treatment with

methamphetamine or d-amphetamine. Furthermore, the chronic methamphetamine-

induced rhythm can be entrained by scheduled daily feeding (Honma et al., 1992). These

behavioral oscillations are unaffected by disrupted molecular mechanisms in the SCN

(Coward et al., 2001) and persist in the complete absence of the SCN (Honma et al.,

1987).

Recent studies also suggest the presence of a learning oscillator, which allows

animals to express a context preference only when the temporal-phase information

coincides with their previous experiences (Cain et al., 2004; Ralph et al., 2002). SCN-

lesioned animals are able to retain the time information for cognitive processing even

when their behavioral and physiological oscillations are arrhythmic (Ko et al., 2003).

Therefore, not only are non-SCN oscillators abundant, but it is also possible that distinct

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cellular or biochemical mechanisms may enable organisms to sustain ~24-hour

behavioral rhythms.

1.3 Structure and function of the molecular clock in mammals

1.3.1 Core components of the molecular clock

Since the 1990’s, a large body of literature has accumulated which describes the

core molecular mechanisms responsible for the generation of circadian rhythms in

mammals. Findings illustrate that while the mammalian clock is perhaps more complex

than in other organisms, the basic features of this circadian clock are very similar and

evolutionarily conserved throughout phylogeny. The molecular clock mechanisms in the

SCN and the peripheral oscillators appear to utilize similar components. The SCN clock

comprises a network of transcriptional and translational feedback loops that drive

rhythmic, ~24-hour expression patterns of core clock components (Lowrey and

Takahashi, 2004; Reppert and Weaver, 2002; Shearman et al., 2000b). A current view of

this organization is presented in Figure 1.2. Core clock components are defined as genes

whose protein products are necessary for the generation and regulation of circadian

rhythms within individual cells throughout the organism (Takahashi, 2004). Some of

these are considered to be “state variables” in that their levels of expression define

circadian phase. Other components may not define specific phases but their expression

and activity are critical for normal rhythm generation and entrainment.

In the primary feedback loop, the positive elements include members of the basic

helix-loop-helix (bHLH)-PAS (Period-Arnt-Single-minded) transcription factor family,

CLOCK and BMAL1. CLOCK and BMAL1 heterodimerize and initiate transcription of

9

Figure 1.2. Transcriptional-translational feedback loops of the mammalian circadian clock. CLOCK and BMAL1 are transcription factors that activate transcription of the Per and Cry genes. The resulting PER and CRY proteins heterodimerize, translocate to the nucleus and interact with the CLOCK:BMAL1 complex to inhibit their own transcription. After a period of time, the PER:CRY repressor complex is degraded and CLOCK:BMAL1 can then activate a new cycle of transcription. The secondary autoregulatory feedback loop is composed of Rev-erbα, which is a direct target of the CLOCK:BMAL1 complex. REV-ERBα feeds back to repress Bmal1 transcription and competes with a retinoic acid-related orphan receptor (ROR) to bind ROR response elements (RREs) in the Bmal1 promoter. Key kinases for PER phosphorylation are casein kinase 1 delta (CK1δ) and CK1ε. One of the roles for phosphorylation of clock proteins is to target them for polyubiquitylation and degradation by the 26S proteasomal pathway. The β-TrCP1 and FBXL3 ubiquitin ligase complexes have been implicated in targeting the PER and CRY proteins, respectively. LRE: Light responsive element (e.g., CRE, cAMP responsive element); CCG: Clock-controlled genes. [Figure modified from Ko & Takahashi, 2006.]

10

target genes containing E-box cis-regulatory enhancer sequences (CACGTG /T),

including Period (in mice, Per1, Per2 and Per3) and Cryptochrome (Cry1 and Cry2)

(Bunger et al., 2000; Gekakis et al., 1998; King et al., 1997; Yoo et al., 2005). Negative

feedback is achieved by PER:CRY heterodimers that translocate to the nucleus to repress

their own transcriptions by acting on CLOCK:BMAL1 complex (Kume et al., 1999; Lee

et al., 2001). Transcriptional feedback repression of the CLOCK:BMAL1 complex

activity is fundamental to maintenance of circadian rhythmicity (Sato et al., 2006).

Another regulatory loop is induced by CLOCK:BMAL1 heterodimers activating

transcription of retinoic acid-related orphan nuclear receptors, Rora and Rev-erbα

(Akashi and Takumi, 2005; Preitner et al., 2002; Triqueneaux et al., 2004). RORa and

REV-ERBα subsequently compete to bind retinoic acid-related orphan receptor response

elements (RREs) present in Bmal1 promoter. In fact, all members of ROR (a, b, and c)

and REV-ERB (α and β) are able to regulate Bmal1 through RREs (Guillaumond et al.,

2005). RORs activate transcription of Bmal1 (Akashi and Takumi, 2005; Guillaumond et

al., 2005; Sato et al., 2004) whereas REV-ERBs repress the transcription process

(Guillaumond et al., 2005; Liu et al., 2008; Preitner et al., 2002). Hence, the circadian

oscillation of Bmal1 is both positively and negatively regulated by RORs and REV-

ERBs, respectively.

1.3.2 Circadian regulation by casein kinase 1 epsilon (CK1ε)

The autoregulatory feedback loops described above take approximately 24 hours

to complete a cycle and constitute a circadian molecular clock. This molecular clock is

governed by post-translational modifications such as phosphorylation and ubiquitination.

These processes significantly contribute to the precision of the mammalian clock by

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affecting the stability and nuclear translocation of aforementioned core clock proteins.

Casein kinase 1 epsilon and casein kinase 1 delta (CK1ε and CK1δ) are considered

essential factors that regulate the core circadian protein turnover in mammals (Akashi et

al., 2002; Eide et al., 2002; Eide et al., 2005; Lowrey et al., 2000; Xu et al., 2005). These

kinases phosphorylate PER protein, which targets PER for polyubiquitylation and

degradation by the 26S proteasomal pathway via the F box ubiquitin ligase β-TrCP1

(Eide et al., 2005; Shirogane et al., 2005). The degradation of CRY protein, however,

requires its binding to the F box protein FBXL3 (Busino et al., 2007; Godinho et al.,

2007; Reischl et al., 2007; Shirogane et al., 2005; Siepka et al., 2007).  Whether CRYs

are modified post-translationally prior to FBXL3 binding is unclear. In addition, a small

ubiquitin-related modifier protein (SUMO) modification of BMAL1 has been proposed

as another level of post-translational regulation (Cardone et al., 2005). 

The importance of the post-translational regulation within the core mechanism of

the circadian clock is corroborated by the fact that mutations in CK1ε and CK1δ can have

dramatic effects on circadian periods. Mutations in CK1ε and CK1δ result in altered

kinase activities in vitro and cause shorter circadian periods in mammals (Gallego et al.,

2006; Lowrey et al., 2000; Xu et al., 2005). In particular, the mechanism by which the

tau mutant CK1ε regulates the circadian clock has been a debate over the recent years.

CK1ε phosphorylates the circadian repressor proteins PER and CRY, and regulates their

protein stability (Akashi et al., 2002; Camacho et al., 2001; Eide et al., 2005; Keesler et

al., 2000) and nuclear localization (Vielhaber et al., 2000). Time-course studies have

shown that the phosphorylation of PER proteins varies over the course of 24 hours, with

the peak level of phosphorylation occurring when the repression of the positive factors

12

CLOCK and BMAL1 is maximal. There are many CK1ε sites on PER proteins (Gallego

et al., 2006), but the function of only a subset of these sites is known. The tau mutation

(the C to T transversion at amino acid position 178; see Appendix A) decreases the

activity of the kinase almost eightfold in vitro; which led to a model that the decreased

kinase activity renders a shorter period (Lowrey et al., 2000). However, this conclusion

is at odds with the findings that CK1 inhibitors produce longer periods (Eide et al., 2005),

and it is difficult to reconcile with the findings that both long and short period mutants in

CK1 (as found in Drosophila, Kloss et al., 1998; Price et al., 1998) have decreased kinase

activity. Recently, Gallego and colleagues (2006) tested this enigma by incorporating a

comprehensive mathematical modeling of the clock. What they have found is that

although the tau mutant CK1ε has decreased kinase activity on most substrates, it has an

increased site-specific activity on the residues that regulate the stability of PER.

Therefore, in the mammalian circadian clock, the tau mutation results in a gain-of-kinase-

function in vivo.

It is likely that there are other regulatory components yet to be discovered in the

circadian system. Recently, glycogen synthase kinase 3β (GSK3β) has been reported as

another circadian regulatory enzyme. GSK3β has a rhythmic activity (peaking at the end

of the day), but its protein expression level is constant (Iitaka et al., 2005). The target

proteins of GSK3β kinase activity overlap CK1ε and CK1δ, and include the PER and

CRY proteins (Harada et al., 2005; Iitaka et al., 2005). In addition, GSK3β

phosphorylates and stabilizes REV-ERBα (Yin et al., 2006).

13

1.3.3 Phenotypic effects of circadian mutations

The molecular mechanism underlying the mammalian clockwork has been most

extensively studied in the mouse. Experimental animals harboring naturally-occurring,

chemically-induced, or targeted mutations have been critical to understand the role of

each clock component in overall functionality of the molecular clock. A current list of

mammalian clock and clock-related gene mutations are listed in Table 1.1.

Mice carrying homozygous Clock allele mutation (Clock∆19/∆19) display a long circadian

period that becomes arrhythmic with prolonged exposure to constant darkness (Vitaterna

et al., 1994; Vitaterna et al., 2006). The mutant CLOCK protein renders functionally

defective CLOCK:BMAL1 heterodimers and, as a consequence, induces markedly

blunted molecular rhythms in the SCN (Gekakis et al., 1998; Jin et al., 1999; King et al.,

1997). Furthermore, mice homozygous for a null allele of Bmal1 have severely disrupted

behavioral and molecular rhythms (Bunger et al., 2000). These observations have

suggested CLOCK and BMAL1 as critical components of the molecular clock. However,

a recent study has reported that CLOCK-deficient (Clock-/-) mice are able to generate

normal behavioral and molecular rhythms (DeBruyne et al., 2006), challenging the long-

standing idea that CLOCK and BMAL1 are at the heart of initiating and sustaining

circadian rhythms. Neuronal PAS domain protein 2 (NPAS2), a paralogue of CLOCK,

has been implicated in the possible compensation for the loss of CLOCK activity in the

SCN (DeBruyne et al., 2006, DeBruyne et al., 2007a; Reick et al., 2001); however,

peripheral tissues from Clock-/- mice fail to sustain tissue-autonomous circadian rhythms

in culture (DeBruyne et al., 2007b). The autonomy of the SCN and peripheral oscillators

are discussed in section 1.5.

14

Table 1.1. Mouse circadian clock and clock-related genes.

Average circadian time at peak

transcript level

Gene SCN Periphery Allele Mutant behavioral circadian phenotype

Bmal1 (Arntl)

15-21 22-02 Bmal1-/- Arrhythmic

Clock Constitutive 21-03 Clock∆19/∆19 4 hr longer pd/ Arrhythmic

Clock-/- 0.5 hr shorter pd

Per1 4-8 10-16 Per1brdm1 1 hr shorter pd

Per1ldc 0.5 hr shorter pd/ Arrhythmic

Per1-/- 0.5 hr shorter pd

Per2 6-12 14-18 Per2brdm1 1.5 hr shorter pd/ Arrhythmic

Per2ldc Arrhythmic

Per3 4-9 10-14 Per3-/- 0-0.5 hr shorter pd

Cry1 8-14 14-18 Cry1-/- 1 hr shorter pd

Cry2 8-14 8-12 Cry2-/- 1 hr longer pd Rev-erbα (Nr1d1)

2-6 4-10 Rev-erbα-/- 0.5 hr shorter pd/ Disrupted photic

entrainment

Rora 6-10 Arrhythmic/ Various staggerer

0.5 hr shorter pd/ Disrupted photic

entrainment

Rorb 4-8 18-22 Rorβ-/- 0.5 hr longer pd

Rorc N/A 16-20/ Various Rorγ-/- Unknown

Npas2 N/A 0-4 Npas2-/- 0.2 hr shorter pd

CK1ε (Csnk1ε)

Constitutive Constitutive CK1εtau 4 hr shorter pd

CK1δ (Csnk1δ )

Constitutive Constitutive Csnk1δ-/+ 0.5 hr shorter pd

15

The idea of functional substitution or partial compensation has been previously

suggested in the negative elements of the molecular clock. The clock continues to

oscillate when a single gene is mutated within the PER or CRY family (Bae et al., 2001;

Cermakian et al., 2001; van der Horst et al., 1999; Vitaterna et al., 1999; Zheng et al.,

2001; Zheng et al., 1999), though disruption of Per1 and Per2 genes together (or Cry1

and Cr2 genes) causes behavioral and molecular loss of circadian rhythmicity (Bae et al.,

2001; Vitaterna et al., 1999; Zheng et al., 2001). The role of each clock gene, however,

cannot be entirely compensated by the other components since individual mutation in

PERs or CRYs results in different circadian periodicity: Per1-/- mice show slightly

shorter (~0.5 to 1 hour) freerunning periods than the wild type mice; Per2-/- mice exhibit

even shorter (~1.5 hour) freerunning periods and some animals can become arrhythmic in

constant conditions; and, Per3 null mutant mice maintain molecular and behavioral

circadian rhythms and do not have a critical role in the feedback loops (Shearman et al.,

2000a). Cry1-/- mice display ~1 hour shorter and Cry2-/- mice display ~1 hour longer

freerunning periods than the wild type mice.

1.4 Functional organization of the SCN

1.4.1 Anatomy of the SCN

The rodent SCN is a bilateral pair of nuclei, each made up of approximately

10,000 neurons. The nuclei reside in the anterior hypothalamus immediately dorsal to the

optic chiasm and lateral to the third ventricle. Functional and anatomical studies suggest

that the nuclei contain two major divisions, known as the shell and the core (Leak and

Moore, 1997). While there are some species-specific differences, the shell and core are

16

generally organized in a similar manner across mammals (Moore et al., 2002). The core

is immediately superior to the optic chiasm, and receives direct input from the visual

system via the RHT (Moore and Lenn, 1972). This makes the core responsible for

integrating light information. Another defining characteristic of the core is its high level

of vasoactive intestinal peptide (VIP) expression: approximately 25% of the SCN

neurons express VIP, and these neurons reside almost exclusively in the core. Neurons

within the core densely innervate each other and neurons in the shell, but they account for

only a minority of projections from the SCN to other brain regions (Watts et al., 1987).

The shell, which in most mammals encapsulates the core, receives the majority of

its inputs from the core. Shell neurons make few projections back to the core, but are

responsible for the majority of SCN efferents (Swanson and Cowan, 1975). Retrograde

tracing studies have shown that shell neurons make monosynaptic connections to the

medial preoptic area of the hypothalamus (mPOA), the dorsomedial (DMH) and

ventromedial (VMH) hypothalamus, the paraventricular thalamic nuclei (PVT), the

lateral septum, and the bed nucleus of stria terminalis (BNST), among others (Leak and

Moore, 2001). Multi-synaptic efferents connect shell neurons to endocrine organs such

as the pineal gland (Larsen, 1999) and adrenal cortex (Buijs et al., 1999) via the

autonomic nervous system (ANS). The shell is delineated by vasopressin (AVP)-

containing neurons (Moore et al., 2002). Vasopressin is of particular interest because its

expression in the SCN is directly controlled by core clock genes and is rhythmic even

under constant conditions (Jin et al., 1999).

The pattern of neural connections into, out of, and within the SCN suggests a

relatively simple subdivision of labor. First, the core receives photic input, integrates this

17

input via activation of immediate early genes and their downstream genes (Beaule and

Amir, 1999; Castel et al., 1997; Kornhauser et al., 1990; Romijn et al., 1996; Shigeyoshi

et al., 1997), and then conveys phase-resetting information to the shell. The shell, which

is responsible for the majority of SCN efferents, follows by phase-coordinating circadian

activity throughout the brain and the periphery. Within the SCN, VIP signaling through

VPAC2 receptors (also known as Vipr2) has been shown to contribute to circadian

synchrony (Aton et al., 2005; Harmar et al., 2002; Maywood et al., 2006).

1.4.2 Cell-autonomous oscillators

Although the SCN is divided into the two sub-divisions, rhythmic SCN neurons

are found throughout the SCN (Leak and Moore, 2001). Individual neurons in the SCN

slice exhibit autonomous circadian rhythms in electrical activity, membrane conductance,

calcium concentration, and circadian gene expression (de Jeu et al., 1998; Gillette et al.,

1995; Gillette and Tischkau, 1999; Liu et al., 2007b; Welsh et al., 1995; Yamaguchi et

al., 2003). Further, these autonomous rhythms persist in dissociated SCN neuronal

culture (Herzog et al., 1998; Liu et al., 2007b; Welsh et al., 1995). These studies indicate

that circadian rhythms are an intrinsic property of individual SCN cells and are not

dependent on functional inter-neuronal connections.

The activity of individual neurons from the same SCN varies with a broad

distribution of phase and period. In measurements from dissociated cells in culture, the

intrinsic periods among individual neurons differ up to ~8 hours (20 to 28.3 hours), while

measurement from cells in organotypic SCN cultures show more restricted period (22.4

to 25 hours), suggesting that intact neuronal connections, while may not be necessary for

the generation of rhythmicity, do contribute to phase coupling (Herzog et al., 1997;

18

Herzog et al., 1998; Honma et al., 1998; Welsh et al., 1995). The mean period for the

entire SCN is equivalent to the species-specific period in locomotor activity (Herzog et

al., 1998; Liu et al., 1997).

1.5 Organization of peripheral oscillators

1.5.1 SCN output and peripheral oscillators

The SCN is responsible for coordinating peripheral oscillators so that a coherent

rhythm is orchestrated at the organismal level (Yamazaki et al., 2000; Yoo et al., 2004).

The SCN affects the periphery via neuronal and humoral output, which then regulate

physiological and behavioral processes.

The most common group of SCN efferents are the projections to other nuclei in

the hypothalamus. Kalsbeek and Bujis (2002) have grouped SCN targets in the

hypothalamus into three categories: 1) Endocrine neurons that directly control pituitary

function; 2) Interneurons, which likely act as integrators of circadian and non-circadian

information and regulate endocrine neuronal function; and 3) Autonomic neurons, which

regulate the function of the peripheral nervous system.

In addition to regulating physiology and behavior via endocrine and neural output,

the SCN also modulates physiology by phase-coordinating oscillators that are present in

peripheral cells. The analysis of circadian gene expression in SCN neurons, peripheral

cells and cultured fibroblasts has revealed that all known clock genes have the same

circadian expression pattern in different cell types (Balsalobre et al., 1998; Zylka et al.,

1998); however, the phase of the gene expression in peripheral cells is delayed by about 4

hours when compared to the one in the SCN.

19

1.5.2 Discovery of self-sustained, cell-autonomous peripheral oscillators

In recent years, a significant discovery has been that peripheral oscillators

generate and maintain self-sustained, cell-autonomous rhythms in the absence of the SCN

(Balsalobre et al., 2000b; Brown et al., 2005; Liu et al., 2007b; Nagoshi et al., 2004;

Welsh et al., 2004). Although it has been well established that most mammalian tissues

possess circadian clocks with a molecular makeup similar to that operative in SCN

neurons (Yagita et al., 2001), the rapid loss of amplitude in their oscillations initially led

to the hypothesis that they are not self-sustained (Yamazaki et al., 2000). This view has

been challenged during the past few years. For example, circadian expression of a clock

protein, PER2, in tissue explants from a variety of organs has been shown to persist for

up to 3 weeks in culture, even when the tissues are derived from SCN-lesioned animals

(Yoo et al., 2004). It is important to note, however, that the peripheral clocks from mice

with SCN ablations are no longer well coordinated and display large phase differences

from tissue to tissue in individual animals. Hence, daily resetting cues from the SCN

seem necessary for phase organization of peripheral oscillators in an intact animal.

Nonetheless, the observation that cells within a given tissue are still synchronized in the

absence of any SCN-derived resetting signals raises the possibility that there are tissue-

specific, or systemic signals that strengthen the coherence of rhythms within each system.

Additional evidence for self-sustained peripheral oscillators comes from studies

reporting on the circadian gene expression in fibroblasts, which reveal that even at the

single-cell level, the fibroblasts contain highly robust circadian oscillators (Brown et al.,

2005; Nagoshi et al., 2004; Welsh et al., 2004). These cellular oscillators can transiently

be synchronized by a variety of substances that activate known signaling pathways,

20

including serum shock, glucocorticoids, and temperature pulses (Balsalobre et al., 2000a;

Balsalobre et al., 1998; Prolo et al., 2005; Yagita and Okamura, 2000).

1.5.3 Comparison of the structure and function of the molecular clocks between the

SCN and peripheral oscillators

Many peripheral tissues, such as the SCN, display rhythmic expression of various

clock genes indicating that the molecular details of clock operation may be similar

between the central and peripheral oscillators. However, some clock genes exhibit

varying rhythmic properties across the tissues. For example, Clock mRNA cycles in the

peripheral tissues, but it is constitutively expressed in the SCN. Members of the Ror

family (a, b, and c) present strikingly different expression patterns across tissues with

varying circadian peak times (Akashi and Takumi, 2005; Guillaumond et al., 2005; Liu et

al., 2008; Sato et al., 2004): Rorc is not expressed in the SCN, but shows rhythmic

expression in the peripheral tissues and participates in the peripheral molecular

clockwork; Rorb, however, is expressed in the SCN and retina, but not in the other

peripheral tissues; Rora expression is ubiquitous, but it only displays robust circadian

rhythm in the SCN and only slight, if not damped, oscillations in peripheral tissues.

Interestingly, mice lacking functional Rora, staggerer (Hamilton et al., 1996), have

normal clock gene rhythms in peripheral tissues including Bmal1 mRNA rhythm; this

suggests that ROR proteins (a, b, and c) may contribute to rhythmic Bmal1 activation

with tissue-specificity (Emery and Reppert, 2004; Sato et al., 2004).

It also appears that the activity of the transcription factors promoting circadian

gene expression patterns is specific to the target gene and/or the tissue (DeBruyne et al.,

2006). There is a modest effect of CLOCK deficiency on the amplitude of the Rev-erbα

21

oscillations in the SCN, but its effect is much more severe in the liver. Per1 is robustly

rhythmic in CLOCK-deficient liver with its absolute level considerably elevated in

comparison to that of the wild type. However, Per1 level in the CLOCK-deficient SCN

is more damped and lower in its absolute level compared to the wild type. Furthermore,

Clock∆19 mutation induces tissue-dependent disruption of Per2 mRNA rhythms –

circadian rhythmicity of Per2 persists in the CLOCK∆19 mutant liver and muscle, but it is

severely blunted in the kidney and heart (Noshiro et al., 2005).

One way of interpreting the tissue-specific difference is to suppose that the

molecular clocks may vary in their intrinsic rhythmic properties across the tissues.

However, the difference can also be attributed to tissue-specific regulatory inputs and/or

regulatory mechanisms in the clock output pathways. For instance, organs receive not

only signals generated by the SCN but also specific physiological/systematic signals that

influence their rhythmic properties (Kornmann et al., 2007; Stokkan et al., 2001; Zambon

et al., 2003). As well, the identification of the circadian transcripts in microarray studies

has revealed that the transcriptional circadian regulation includes various clock-

controlled genes (CCGs, see Figure 1.2) whose distributions are tissue-specific

(McCarthy et al., 2007; Miller et al., 2007; Panda et al., 2002; Storch et al., 2002).

1.6 Hypothesis

The information about the cellular and molecular organization of the circadian

oscillators is now quite extensive. Still, the current view of the mammalian clocks is very

static, albeit a set of snapshots at various circadian time points. Fortunately, with

22

continued advancement of technology, the dynamic changes and the critical control

mechanisms can begin to be addressed.

The general aim of this dissertation is to determine whether and in what specific ways the

generation of circadian rhythms differs among central and peripheral tissues. This task is

undertaken by examining the production of circadian rhythms in the SCN and non-SCN

tissues under situations where parts of the clock are altered. The experiments presented

here are first steps in an effort to examine the tissue-autonomous properties of the

mammalian circadian molecular clocks.

We tested the following specific hypotheses: Hypothesis 1: That the structure and

function of the inherent circadian molecular clocks are the same across the tissues;

Hypothesis 2: Tissue-specific differences observed in molecular clock operation are due

to differences in intercellular signaling mechanisms (coupling) among circadian

oscillators rather than due to alterations in the organization of the molecular machinery.

An alternative viable hypothesis is that tissue differences in clock operation are

due to: 1) Differential reliance on regulatory inputs that are specifically from the SCN;

and/or, 2) Tissue-specific systemic regulatory mechanisms. However, these cannot be

addressed at this time due to the lack of information on the nature of these signals.

We have utilized two new molecular tools in mice to test our hypotheses. One of

these uses the tetracycline gene-regulation (tet) system, which allows an inducible and a

tissue-specific manipulation of a target gene in vivo. The tet system requires two

independent lines of transgenic mice: one line expresses the tetracycline-controlled

transactivator (tTA) under the control of a specific promoter (giving spatial control of

gene expression), and a second line carries a tTA-responsive tetracycline operator (tetO)

23

sequence upstream of the target gene of interest (providing temporal control of gene

expression). The target gene is expressed only when both transgenes are present within a

mouse (bitransgenic) and the expression can be reversed by administering doxycycline

(tetracycline derivative) via drinking water.

In Chapter 3, we report development of two separate lines of tetO transgenic

mice: tetO-HA-CK1ε(tau) and tetO-HA-CK1ε(wt). CK1ε was chosen over other

available target genes for three main reasons. First, it is one of the fundamental factors

that regulate the core circadian protein turnover in mammals and govern the precision of

the ~24-hour molecular clock. Second, the well-characterized tau mutation in hamsters is

semi-dominant suggesting that the mutant phenotype could be detectable in the presence

of the wild type alleles. Third, CK1ε is not itself a state variable of the circadian system,

so that altering the expression of CK1ε should not interfere with primary actions of clock

genes or transcripts; hence, the basic underlying molecular interactions would stay intact

and only the regulatory mechanism would be affected. The expression of the CK1ε

transgenes is guided by four different tTA promoter lines – two different lines of NSE-

tTA (lines A and B; Chen et al., 1998), CaMK2α-tTA (Mayford et al., 1996), and Scg2-

tTA (Hong et al., 2007). Lastly, we have combined the PER2::LUCIFERASE knock-in

reporter line (described below) with the CaMK2α-driven tau bitransgenic line to measure

the effect of the tau mutation on circadian regulation of the molecular clock in a tissue-

specific manner.

The second molecular tool is a genetically engineered, PER2::LUCIFERASE

(PER2::LUC) knock-in mouse – a reporter line with luciferase gene fused in-frame to the

3’ end of the endogenous Per2 gene (Yoo et al., 2004). The PER2::LUC mice provide a

24

means for monitoring circadian rhythms by real-time bioluminescence measurements in

isolated tissues and cells. In these mice, we have found that both the SCN and peripheral

tissues show robust and self-sustained circadian rhythms under ex vivo culture conditions,

but that there are tissue-specific circadian phase and period properties. In addition, SCN-

lesioned PER2::LUC mice display a gradual loss of phase coordination among peripheral

tissues.

In Chapter 4 and 5, we investigate the tissue-autonomous rhythmic properties of

the SCN and peripheral oscillators by crossing the PER2::LUC mice with mice carrying

mutated clock genes (Bmal1, Clock∆19, Cry1, and Cry2). We report in Chapter 4 both

consistencies and differences in how the central and peripheral clocks respond to the

partial loss of the molecular system. In Chapter 5, we focus our attention specifically on

the loss of Bmal1 within the SCN. Our results demonstrate that there is a distinct

difference between the rhythmic properties of the SCN versus peripheral oscillators – the

SCN oscillator is more robust and persistent against genetic defects compared to the

peripheral oscillators. We believe this is due to the SCN possessing a unique way to

augment intercellular coupling that establishes an improved network oscillator with

increased period stability and a coherent, sustainable output. This unique characteristic

of the SCN attests to its role as the master circadian pacemaker.

25

CHAPTER 2. METHODS

26

2.1 The conditional expression of CK1ε transgene

2.1.1 Review of the tetracycline transactivator system

The tetracycline gene-regulation system, hereafter referred to as the “tet” system,

is divided into two major components: the regulatory system and the response system

(Figure 2.1). In order to effectively induce the gene of interest in a mouse, the mouse

must carry both the regulatory and response transgenes (referred to as bitransgenic). The

first critical component of the tet system is a regulatory protein known as the tetracycline-

controlled transactivator (tTA). tTA is a hybrid protein created by fusion of the

tetracycline repressor (TetR) in E. Coli (Gossen and Bujard, 1992) and the C-terminal

transactivation domain of the Herpes simplex virus VP16 (Triezenberg et al., 1988). The

VP16 domain converts TetR from a transcriptional repressor to a transcriptional activator.

The regulatory protein tTA is encoded by the pTet-Off regulator plasmid (Clontech

Laboratories, Inc.; also described by Gossen and Bujard, 1992).

The second critical component is a response plasmid, which expresses a gene of

interest (GeneX; CK1ε(wt) or CK1ε(tau) in the current project) under control of the

tetracycline-response element (TRE). TRE consists of seven direct repeats of tet operator

(tetO) sequences, and the response plasmid (pTRE2, Clontech Laboratories, Inc.; also

described by Gossen and Bujard, 1992) is designed with TRE located just upstream of the

minimal cytomegalovirus promoter (PminCMV) leading the gene of interest. Hence, the

transgene remains silent unless tTA is bound to TRE, which activates the PminCMV. In

addition, PminCMV lacks the strong enhancer elements associated with the CMV immediate

27

Figure 2.1. The tetracycline transactivator system. The tetracycline-controlled transactivator (tTA; the regulatory system) is a fusion of the wild type tetracycline repressor protein (TetR) to the VP16 activation domain (AD) of herpes simplex virus. In the absence of the inducer, tetracycline or its derivative doxycycline (dox), tTA binds to the tetracycline-response element (TRE; the response system that is composed of tetO promoter sequences) and transcribes of the gene of interest. The transcription is stopped with addition of dox. PminCMV: minimal cytomegalovirus promoter.

28

early promoter. Because these enhancer elements are missing, “leaky” expression of the

gene of interest from TRE is prevented in the absence of binding by tTA.

Overall, in this tet system, the gene of interest cannot be transcribed (or pTRE2-

GeneX plasmid is not active) without binding tTA to TRE. Furthermore, binding of tTA

to TRE can be controlled by administering tetracycline or its derivative, doxycycline

(dox): tTA cannot bind to the TRE when tetracycline or dox is present.2

The tet system has been successfully used to obtain inducible, brain-specific

expression of targeted genes under the control of the neuron-specific enolase (NSE)

promoter (Chen et al., 1998; Kelz et al., 1999) and the forebrain-specific calcium-

calmodulin-dependent kinase II (CaMK2α) promoter (Krestel et al., 2001; Mansuy et al.,

1998; Mayford et al., 1996). Two different founder lines are available using the NSE

promoter: NSE-tTA line A, and line B. The expression patterns determined by the NSE-

tTA(A/B) mice are different from each other and from those of the CaMK2α -tTA mice.

The difference between NSE lines A and B is explainable by transgene position effects;

and, the difference caused by two different genes (NSE versus CaMK2α) is further

explained by gene-specific endogenous expression patterns. Most recently, we have

developed another tTA line using the secretogranin II promoter (Scg2-tTA; Hong et al.,

2007) with SCN-enriched transgene expression. We first searched for SCN-enriched

transcripts with brain-specific expressions from already available comprehensive mouse

tissue expression databases (Panda et al., 2002; Su et al., 2002), and found about 35

2 The system described here is referred to as the Tet-Off gene expression system. As stated, in the Tet-Off system, gene expression is turned on/off when tetracycline or doxycycline is absent/present. However, there is another available system called the Tet-On system. In the Tet-On system, gene expression is turned on by the addition of tetracycline or doxycycline. The Tet-On system is described in Gossen et al. (1995). In short, the Tet-On system is similar to the Tet-Off system, but the regulatory protein is based on a “reverse” tetracycline repressor, rTetR.

29

candidate genes. One of these genes, Scg2, showed very high constitutive expression in

the SCN with a limited expression pattern to brain, pituitary and adrenal glands (Mahata

et al., 1991).

All four promoter lines NSE-tTA(lines A and B), CaMK2α-tTA, and Scg2-tTA

were crossed to mice carrying a tetO promoter-lacZ reporter construct (Mayford et al.,

1996) to compare tTA expressions in the brain. We tested two independent tetO-lacZ

lines, namely lines lac1 and lac2 (provided by Dr. Mark Mayford, Scripps Research

Institute, San Diego, CA).

2.1.2 Characterization of tTA promoter lines using β-galactosidase staining

The tetO-lacZ mice were crossed with NSE-tTA(A/B), CaMK2α -tTA, and Scg2-

tTA mice to produce bitransgenic mice carrying both the tetracycline-regulatory and the

tetracycline-responsive transgenes. Single-transgenic, tetO-lacZ, littermate mice were

used as controls to test leaky expression. Mice were deeply anesthetized with

ketamine/xylazine cocktail (10mg/ml ketamine; 2mg/ml xylazine) at 0.01ml/g body

weight then transcardially perfused with chilled phosphate-buffered saline (PBS; pH 7.3)

with 0.1% heparin, followed by 4% paraformaldehyde PBS. Brains were removed and

postfixed for 30 minutes in the same fixative on ice, then stored overnight in 20% sucrose

PBS at 4°C. Brains were frozen on dry ice, embedded in M-1 embedding matrix

(Lipshaw), and sectioned coronally at 50µm thickness. Free-floating sections were

collected in a wash buffer (PBS with 2mM MgCl2, 0.02% NP-40; pH 7.3). Sections were

incubated for 24 hours at 37°C in an X-gal staining solution containing 1mg/mL X-gal

(5-bromo-4-chloro-3-indolyl-β-D-galactoside (Gold Biochemical) dissolved in dimethyl

sulfoxide), 5mM K3Fe(CN)6, and 5mM K4Fe(CN)6 in the wash buffer. Finally, sections

30

were rinsed three times in the wash buffer, then mounted in aqueous mounting medium

(3:1 glycerol:PBS) on gelatin-coated glass slides.

2.1.3 Generation and characterization of tetO-HA-CK1ε transgenic mice

Construction of plasmids3

Two different plasmids were prepared: tetO-HA-CK1ε(tau) and tetO-HA-

CK1ε(wt). Hamster CK1ε(wt) and CK1ε(tau) cDNAs in pET-30 Ek/LIC vector were

provided by Dr. Phillip Lowrey (Lowrey et al., 2000; Northwestern University, Evanston,

IL; currently at Rider University, Lawrenceville, NJ). The tetracycline-responsive vector,

pTRE2, was purchased from Clontech Laboratories, Inc.

The CK1ε cDNA was released from the pET-30-CK1ε by restriction enzyme

digestion with BglII and NotI restriction endonucleases. pTRE2 was cut with BamHI and

NotI restriction endonucleases. The released BglII-NotI CK1ε cDNA fragment was

ligated into BamHI-NotI sites of the pTRE2 vector. The new plasmid was designated as

tetO-CK1ε, in which the CK1ε was under the control of tetracycline-regulated promoter.

The tetO-CK1ε was further modified by placing a hemagglutinin epitope tag (HA)

at the 5’-terminal of the CK1ε cDNA. The HA tag was inserted into the amino terminal

of CK1ε because several lines of evidence suggest that the carboxyl-terminal tails of

CK1ε contain an important phosphate transfer domain (Lowrey et al., 2000; Rivers et al.,

1998). The HA epitope was cloned in frame, directly upstream of the CK1ε cDNA via

Taq polymerase chain reaction (PCR) using pET-30-CK1ε as the template. The forward

primer was designed to contain the BglII restriction endonuclease site at the 5’ end,

which was followed by the HA-epitope sequence (33-basepairs, bp) and the first 18-bp

3 General protocols were adapted from Sambrook, J., and Russell, D.W. (2001). Molecular cloning: a laboratory manual, 3rd edn (Cold Spring Harbor, Cold Spring Harbor Laboratory Press).

31

sequence of the CK1ε cDNA. The reverse primer was designed to contain the EagI

restriction endonuclease site at the 3’ end following the last 18-bp sequence of the CK1ε

cDNA. The BglII and EagI sites were put in to ensure that the resulting PCR products

could be released and ligated to the final vector of choice pTRE2. The following

oligonucleotides were used to produce HA-CK1ε : (forward) 60-mer, 5’-GGA AGA TCT

ATG TAC CCA TAC GAT GTT CCA GAT TAC GCT CCT ATG GAG CTA CGT

GTG GGG-3’; (reverse) 33-mer, 5’-CGG AGC GGC CGC TCA CTT CCC GAG ATG

GTC AAA-3’. These and all subsequent oligonucleotides were synthesized by Integrated

DNA Technologies.

The amplified PCR products (HA-CK1ε) were then inserted into pCRII-TOPO

vector using the TOPO TA Cloning kit from Invitrogen Corporation. The HA-CK1ε was

then released by digestion with BglII and EagI restriction endonucleases. The released

BglII-EagI HA-CK1ε fragment was ligated into BamHI-EagI sites of the pTRE2 vector.

The new plasmids were designated as tetO-HA-CK1ε(tau) and tetO-HA-CK1ε(wt).

Appendix A includes the vector map for this plasmid (Figure A.1), hamster CK1ε cDNA

sequence, and the alignment of hamster and mouse CK1ε sequences.

Animals

The tetO-HA-CK1ε constructs were digested with AatII and AseI restriction

endonucleases, which released a DNA fragment containing the promoter, open reading

frame, and β-globin polyA signal. Following the linearization, these plasmids were

purified by electroelution and microinjected into the pronuclei of oocytes from CD1

mice. Tail DNA from resulting mice was isolated and analyzed for the transgene by

PCR. The transgenes from both constructs were detected with the primers CK1ε-LF: 22-

32

mer, 5’-AGC TCG TTT AGT GAA CCG TCA G-3’ and CK1ε-RT: 22-mer, 5’-TCA

ATG ATG TAG ACC AGG TTG C-3’. Transgenic copy number was determined using

Southern hybridization with a CK1ε probe (bases 8866-9516; 650bp); the signal was

quantified using a Storm Phosphoimager (Molecular Dynamics, Amersham Pharmacia)

with the ImageQuant software package (Amersham Pharmacia). Five founder mice were

obtained from tetO-HA-CK1ε(tau) and three founders were obtained from the tetO-HA-

CK1ε(wt). The founder mice were crossbred with wild type CD1 mice to generate F1

mice.

Circadian Behavior

Mice were raised in a 12-hour light:12-hour dark cycle (LD 12:12) from birth.

After weaning, animals were group-housed (2-5 per cage) and, at approximately 8 weeks

of age, were transferred into individual cages equipped with running wheels. After 2

weeks of entrainment to LD 12:12, animals were kept under constant darkness (DD) for

approximately 4 weeks to observe their freerunning period. Afterwards, mice were

provided with doxycycline (10µg/ml) drinking water for 4 weeks. Newly mixed drinking

water was provided every 3 days, at which time the amount of water consumption was

noted for each animal. Water replacements were conducted in complete darkness during

the animal’s active period to minimize disturbance to their circadian cycle (night vision

optical instrument was used as a visual aid).

Locomotor (running wheel) activity was recorded continuously by ClockLab

(Actimetrics, Wilmette, IL) and was displayed and analyzed using a customized MatLab

software package (ClockLab Analysis; Actimetrics, Wilmette, IL). In Chapter 3, we

report the results.

33

Western Blotting

Animals were kept in LD 12:12 for at least 7 seven days prior to the tissue

collection. Tissues were collected approximately around zeitgeber time (ZT) 12; the time

light comes “on” is defined as zeitgeber time 0 (ZT0), hence, ZT12 signifies when the

light goes “off”. Tissues were kept on ice at all times until the electrophoresis step. Each

tissue was homogenized separately in 1 ml aliquots of pre-chilled extraction buffer

(100mM KCl, 20mM HEPES (pH 7.5), 5% glycerol, 2.5mM EDTA, 2.5mM NaF, 5mM

DTT, 0.1% Triton X-100, 0.5mM PMSF, 10µg/ml aprotinin, 10µg/ml leupeptin, 2µg/ml

pepstatin A). Homogenates were centrifuged at 12,000 x g for 15 minutes at 4°C and a

portion (~100µg/lane) of the supernatant was separated on 10% SDS-PAGE gels.

Following the electrophoresis, proteins were transferred to PVDF (Immobilon-P,

Millipore) membrane. The membrane was probed with the 3F10 rat monoclonal anti-HA

antibody (1:500; Roche Applied Science) followed by anti-rat IgG secondary antisera

horseradish peroxidase (1:2000; Jackson ImmunoResearch Laboratories) or anti-actin-

peroxidase antibody (1:1000; Santa Cruz Biotechnology) according to the manufacturer’s

protocol. Proteins were visualized with a chemiluminescence detection system (ECL

Western blotting detection analysis system; Amersham Pharmacia) and with subsequent

exposure to autoradiographic film.

In Situ Hybridization

Mice were sacrificed by cervical dislocation; the brains were removed

immediately, frozen on dry ice, and stored at -80°C. The brain was sectioned at 20µm;

alternate sections were hybridized with a 33P-labelled HA oligoprobe (5'-ATA AGA

GCG TAA TCT GGA ACA TCG TAT GGG TAC ATA GAT-3') and a 33P-labelled

34

CK1ε oligoprobe (5’-TCT TGT AGA ACT TGC TCT CGA TGT GGA GCT GGG

GAT-3'). The CK1ε riboprobe was PCR-generated using a forward primer 5’-GTG GGG

TGG ACA ATG ACT TC-3' and a reverse primer 5’-AAC AAC CAC AAT AAA GCT

CAA AAA-3' to amplify a 519-bp product corresponding to the COOH-terminal region

of CK1ε (which diverges in sequence from other CKI isoforms). Hybridization and wash

procedures, exposure, image analysis, and signal quantification were as previously

described (Lowrey et al., 2000) and the detailed description is provided in Appendix B.

Immunocytochemistry

Animals were anesthetized with ketamine/xylazine cocktail between ZT11-13 and

transcardially perfused with 0.9% saline solution, followed by 4% paraformaldehyde in

0.1M phosphate buffer (PB; pH 7.2). Brains were removed and postfixed for 24 to 48

hours at 4°C in 4% paraformaldehyde PB, then 50µm coronal sections were collected

using a VibroSlice microtome (World Precision Instruments). The brain slices were

incubated in mouse anti-HA1.1 biotin labeled monoclonal antibody (BIOT-101L-100;

1:200; Covance Research Products) for 24 hours at 4°C. Sections were then incubated

for 60 minutes at room temperature with an avidin-biotin-peroxidase reagent (ABC Elite;

Vector Laboratories). Immunoreactivity was revealed with nickel-enhanced

diaminobenzidine (DAB) reaction.

2.1.4 Generation of PER2::LUCIFERASE + CaMK2α-driven CK1ε(tau) mice,

bioluminescence imaging, and data analysis

We combined the PER2::LUCIFERASE (PER2::LUC) reporter line with

conditional expression of a mutant clock gene, CK1ε(tau), under the control of

CaMK2α promoter. The combination allows us not only to control both spatial and

35

temporal expression, but also to measure in real time the tissue-specific effects of the

CK1ε tau mutation on circadian regulation of the molecular clock. Mice were bred from

a PER2::LUC homozygous parent (129SvEv X C57BL/6J N6) mated with a CaMK2α-

tTA x tetO-HA-CK1ε(tau) bitransgenic (129S1 X C57BL/6J N6) mouse. Bitransgenic

pups and tetO-HA-CK1ε(tau) single-transgenic littermate controls harboring the

PER2::LUC reporter were used for the experiment. PER2::LUC bioluminescence

imaging and data analysis steps are reported below in sections 2.2.3 and 2.2.4.

2.2 PER2::LUCIFERASE reporter line and clock mutants

2.2.1 Background: PERIOD2::LUCIFERASE (PER2::LUC) knock-in mouse

The firefly luciferase acts on its substrate luciferin to produce bioluminescence.

Although LUCIFERASE protein is relatively stable, the half-life of its activity is quite

short (~4-5 hours; as measured by bioluminescence levels) (Plautz et al., 1997). This

dynamic feature of luciferase activity makes it possible to measure clock gene expression

in vivo. When a clock-regulated promoter is used to drive luciferase expression,

bioluminescence can be recorded in real time from live samples for days or weeks to

directly measure circadian gene expression. The luciferase has been successfully used as

a transgene to monitor circadian rhythms in several organisms, including cyanobacteria,

Arabidopsis, and Drosophila (Kondo et al., 1997; Millar et al., 1995; Plautz et al., 1997;

Stanewsky et al., 1997).

In the early 2000s, this approach was applied in the rat (Abe et al., 2002; Stokkan

et al., 2001; Yamazaki et al., 2000; Yamazaki et al., 2002), in which the mouse Per1

promoter was used to drive luciferase expression. The bioluminescence was measured in

36

cultured tissue explants from mPer1-luc transgenic rats to assess the relationship between

the SCN and the periphery in response to environmental changes. The findings revealed

a dichotomy between the SCN and peripheral oscillators – the SCN can express

persistent, self-sustained oscillations (>30 cycles in isolation), whereas peripheral

rhythms damp out after two to seven cycles. Another set of studies using mouse as an

animal model, with either luciferase or jellyfish green fluorescent protein (GFP) driven

by the mouse Per1 promoter, also reported the same dichotomy (Kuhlman et al., 2000;

Yamaguchi et al., 2000). This has led to a widely accepted hierarchical model of the

mammalian circadian system in which the SCN acts as a master pacemaker,

independently able to both generate and sustain its own circadian oscillations and

necessary to drive circadian oscillations in peripheral cells.

In 2004, however, Yoo and colleagues reported another reporter mouse with the

luciferase gene fused in-frame to the 3’ end of the endogenous mouse Per2 gene. The

PER2::LUC knock-in mouse provided compelling evidence that circadian clocks of

peripheral organs are also self-sustained; individual peripheral tissues explants from these

mice displayed a persistent rhythmicity for up to 20 days independent of SCN input.

Furthermore, unique circadian phase and period properties of individual tissues from

different organs were revealed. It was suggested, therefore, that the SCN function more

to coordinate the appropriate phase relationships among peripheral tissues than to drive

the circadian rhythms in peripheral tissues (Yoo et al., 2004).

The demonstration of circadian oscillators in peripheral organs has not only

changed the general view of the mammalian circadian timing system, but it has also

opened new experimental routes to investigate the mechanisms underlying circadian

37

rhythm generation. When we assume that circadian rhythm at an organismal level

reflects a collective activity of many individually competent oscillators, each oscillating

with its own clock machinery, we can then explore how these oscillators interact and

influence each other to generate a cohesive rhythmic output. One of the goals of this

dissertation is to better understand the structure and function of these oscillators at the

level of specific tissues. We begin by examining the qualitative differences in molecular

circadian clocks in the SCN and peripheral tissues by crossing the PER2::LUC mice with

mice carrying mutated clock genes (Bmal1, Clock∆19, Cry1, and Cry2).

2.2.2 Generation of PER2::LUC x circadian mutant mice

PER2::LUC mice were genetically engineered with the luciferase gene fused in-

frame to the 3’ end of the endogenous mouse Per2 gene (Yoo et al., 2004). Mice were

bred from PER2::LUC homozygous parents ((129SvEv X C57BL/6J)F2) mated with

Bmal1-/+ (129S1 X C57BL/6J N8), Clock∆19/+ (C57BL/6J coisogenic), Cry1-/- (129S1 X

C57BL/6J N7), or Cry2-/- (129S1 X C57BL/6J N8) mice. From the first generation of

pups, mice carrying a copy of the Per2::luc (luc/+) and heterozygous mutation in a

corresponding clock gene were then crossed to obtain wild type, heterozygous and

homozygous mutants harboring the PER2::LUC reporter. Genotypes were determined by

multiplex polymerase chain reactions (PCR) on genomic DNA from tail biopsies as

described in previous papers (Bunger et al., 2000; King et al., 1997; Thresher et al., 1998;

Vitaterna et al., 1999; Yoo et al., 2004).

Mice were raised in LD 12:12 from birth. After weaning, animals were group-

housed (2-5 per cage) until the experimental phase. The experiments reported in Chapter

38

4 were done with mice at the N4 and N5 backcross generations of C57BL/6J. Mice used

in Chapter 5 were at the N8 backcross generation of C57BL/6J.

Circadian Behavior

Prior to culturing the tissues for bioluminescence imaging, a group of mice was

tested for wheel-running behavior. At approximately 8 weeks of age, mice were

transferred into individual cages equipped with running wheels. After 2 weeks of

entrainment to LD 12:12, animals were kept under DD for an additional 4 weeks to

observe freerunning period. They were returned to LD 12:12 for at least 2 weeks before

their tissues were harvested for the bioluminescence experiment.

Locomotor (running wheel) activity was recorded continuously by the ClockLab

data collection program (Actimetrics, Wilmette, IL) and was displayed and analyzed

using a customized MatLab software package (ClockLab Data Analysis; Actimetrics,

Wilmette, IL).

2.2.3 Tissue explant culture and bioluminescence imaging

Animals were sacrificed by cervical dislocation between ZT11 and ZT13. The

tissues were removed immediately, and put in Hank balanced salt solution (HBSS; with

10mM Hepes, 25units/ml penicillin, and 25µg/ml streptomycin) on ice. The brain slice

containing the SCN was sectioned at 300µm followed by free-hand, knife dissection of

just the SCN resulting in a tissue about 1mm x 1mm in size. The peripheral tissues were

dissected at approximately 1mm3 in size with the exception of the pituitary, which was

cultured as whole. The dissected tissues were cultured on Millicell culture membrane

(PICM ORG 50, Millipore) with 1.2ml DMEM media (Cellgro), supplemented with

10mM Hepes (pH 7.2), 2% B27 (Invitrogen), 25units/ml penicillin, 25µg/ml

39

streptomycin, and 0.1mM luciferin (Promega). Media change consisted of simply lifting

the Millicell culture membrane and placing it into a new culture dish prepared with fresh

media. For peripheral tissues, forskolin [10µM] was administered for ~30 minutes to

reinitiate the rhythms before being placed into the fresh media.

Cultures were maintained at 36°C either in an incubator or in a temperature-

controlled room. The bioluminescence was continuously monitored with photomultiplier

tube (PMT) detector assemblies (LumiCycle, Actimetrics, Wilmette, IL). Dark counts

(nonspecific counts) from the PMTs were measured with media and subtracted from

overall bioluminescence to represent the appropriate light emission from cultured SCN

tissues.

2.2.4 Bioluminescence data analysis

All bioluminescence analyses were performed by the LumiCycle Analysis

Program (Actimetrics, Wilmette, IL). The peak phase was calculated as the highest point

of bioluminescence oscillation and was defined as a reference phase, circadian time (CT)

12 since PER2 protein level peaks approximately around CT12. Mean periods were

estimated by Levenberg-Marquardt (LM) curve fitting in the LumiCycle Analysis

Program. For inter-peak interval measures (Chapter 5), raw data were baseline fitted then

peak-to-peak durations were calculated by manually identifying individual peaks.

Spectral analysis (FFT-Relative Power) was used to measure amplitude of the rhythms

using ClockLab Data Analysis software (Actimetrics, Wilmette, IL); relative brightness

and damping coefficient were measured using LumiCycle Analysis Program. Results are

reported in Chapters 4 and 5.

40

CHAPTER 3. CONDITIONAL EXPRESSION OF CK1ε(tau): EFFECTS ON

BEHAVIORAL RHYTHMS AND MOLECULAR OSCILLATORS

IN TRANSGENIC MICE

41

3.1 Introduction

Recent studies have shown that peripheral cells and tissues contain independent,

self-sustained circadian oscillators and suggest that a common molecular clock

mechanism is shared among central and peripheral pacemakers. However, the extent to

which phase and period of each tissue rely on functional molecular organization is

unclear. Various central and peripheral tissues oscillate with different periods, and their

phase relationship with each other and the outside world differ (Yoo et al., 2004).

Tissue-specific periods and oscillator phases could reflect differences in 1) organization

of the core molecular clock; 2) regulatory input; and/or 3) modification due to

intercellular coupling. To better understand the function of the circadian clocks, we have

developed tools to manipulate circadian genes in a conditional and tissue-specific manner

in vivo and in vitro. In this chapter, we report such an approach using the tetracycline-

regulatory (tet) system to manipulate the expression of the CK1ε(tau) gene and its wild

type control.

In Figure 3.1, we present a schematic diagram of the tet system and constructs

used for generating the tTA transactivator and target tetO transgenic lines. Detailed

description of the tet system is provided in Chapter 2. Briefly, two independent lines of

transgenic mice are required: one line expresses tetracycline transactivator (tTA) under

the control of a specific promoter (defining spatial expression), and a second line carries

a tTA-responsive tetracycline operator (tetO) sequence that drives expression of a

downstream target gene of interest (controlling temporal expression). When both the tTA

and tetO transgenes are introduced into a single mouse (bitransgenic) through mating, the

42

Figure 3.1. Schematic diagram of the tetracycline regulatory (tet) system and constructs used to generate CK1ε transgenic mouse lines. The expression of tetracycline transactivator (tTA) is driven by four independent promoter lines (NSE(A/B), CaMK2α, and Scg2). tTA binds to tTA-responsive tetracycline operator (tetO) that drives expression of the HA-tagged CK1ε (WT or tau) in the absence of doxycycline (Dox) but not in its presence.

43

tetO-linked gene is activated but only in those cells that express tTA. This expression

can be reversed by administering a tetracycline derivative, doxycycline (dox), which

inhibits tTA from binding to the tetO promoter.

We chose to use CK1ε as our inducible target gene because it is one of the post-

translational regulatory factors that ensure the precision of the circadian molecular clock

(Akashi et al., 2002; Eide et al., 2002; Lowrey et al., 2000). In addition, its mutant allele,

tau, shortens the circadian period (Lowrey et al., 2000; Ralph and Menaker, 1988). The

semi-dominant nature of the mutation allows expression and detection of the mutant

phenotype in the presence of the wild type allele (Wang et al., 2007). Importantly,

altering the expression of this kinase interferes only with a regulatory process of the

molecular clock without the added complication of abridging the underlying molecular

clock mechanisms. Mutations that affect the canonical clock genes were also considered.

However, by definition, these are considered to be state variables of the system and,

unlike CK1ε, are rhythmically expressed and regulated.

We used four tTA lines to drive the target gene expression to different brain

regions: neuron-specific enolase (NSE) promoter lines A and B, NSE(A/B)-tTA (Chen et

al., 1998); a calcium-calmodulin-dependent kinase II (CaMK2) promoter line, CaMK2α-

tTA (Mayford et al., 1996); and a secretogranin II (Scg2) promoter line, Scg2-tTA (Hong

et al., 2007; McDearmon et al., 2006). Two lines of tetO-HA-CK1ε transgenic mice

were generated to produce conditional expression of both the wild type and the short-

period allele of CK1ε, tau. In order to distinguish the CK1ε transgenes from the

endogenous CK1ε, we fused a hemagglutinin (HA) epitope tag on 5’ end of the cDNA,

which does not interfere with the kinase function (Gallego et al., 2006).

44

In this chapter, we report the effect of tetO-driven CK1ε (wild type and tau)

transgenes on circadian locomotor behavior. We then combine the PER2::LUC and tet

systems to visualize and compare the regulatory function of CK1ε in tissue-autonomous

molecular clocks.

3.2 Generation and characterization of the transgenic mice

3.2.1 Characterization of the tTA promoter lines

The four tTA mouse lines, NSE-tTA (lines A and B), CaMK2α-tTA, and Scg2-tTA,

were crossed to two tetO-lacZ reporter lines, lac1 and lac2 (provided by Dr. Mark

Mayford, Scripps Research Institute, San Diego, CA; Mayford et al., 1996); and the

expression patterns in the brain were visualized with β-galactosidase (β-gal) staining.

The four promoters directed β-gal signals with different patterns but no useful difference

was seen by visual inspection between lac1 and lac2 lines, so only the lac1 reporter line

was continued. Results from lac1 lines are presented in Figure 3.2. In general, the

NSE(A)-tTA driven lacZ expression was confined to striatum with modest expression in

the amygdala and hippocampus; the NSE(B)-tTA driven lacZ expression was mainly

confined to striatum and cerebellum; and both CaMK2α-tTA and Scg2-tTA produced very

high lacZ expressions throughout the forebrain albeit with different patterns. Most

importantly, both CaMK2α and Scg2 promoters generated high level of lacZ expression

in the SCN, whereas lacZ expression was absent in the SCN under the control of NSE

(SCN region is indicated with red arrow in Figure 3.2). These results predict that the

CK1ε transgene expression would not result in behavioral or molecular change in

45

Figure 3.2. Analysis of tTA lines using -galactosidase staining. Induction of the tetO-lacZ (lac1) transgene by NSE-tTA (lines A and B, top), CaMK2α-tTA (bottom left), and Scg2-tTA (bottom right) line is shown. The location of the SCN is indicated for each of the tTA lines by red arrow. The two NSE-tTA lines do not show lacZ expression in the SCN, whereas CaMK2α- and Scg2-tTA lines exhibit high level of lacZ expression.

46

circadian rhythms in the two NSE lines, and that these animals may serve as experimental

controls.

3.2.2 Characterization of tetO-HA-CK1ε transgenic mice

Five founder mice were obtained from tetO-HA-CK1ε(tau) and three founders

were obtained from the tetO-HA-CK1ε(wt). All founder lines were crossed with each of

the tTA expressing lines described in section 3.2.1 to produce bitransgenic mice. First,

their wheel-running behavior was monitored for entrainment to LD, freerunning period,

and the effect of dox on freerunning period. The presence of the transgene was

confirmed by Southern blot hybridization, and the transgene copy number ranged from

one to ten copies. Following the behavioral testing, the brain pattern of the transgene

expression was assessed by in situ hybridization using an oligo probe targeted to the HA

tag. We selected tetO-HA-CK1ε(tau) line 30 and tetO-HA-CK1ε(wt) line 43 as

representative lines because 1) the tetO transgene was ubiquitously expressed throughout

the brain including the SCN; 2) the single transgenic littermate controls exhibited

comparable circadian locomotor activity rhythms with the wild type; and, in the case of

the tau bitransgenic mice, 3) the expression of the tau transgene in the SCN shortened the

period of circadian locomotor activity rhythm, but a wild type freeruning period was

restored when the transgene expression was repressed with dox treatment.

The expression pattern of tetO-driven CK1ε (tau and wt) generally mirrored that

of tetO-lacZ under the control of the four tTA lines (Figure 3.3A). Only the bitransgenic

mice showed clear hybridization with the HA-specific probe. Single-transgenic and wild

type mice did not show any expression of the HA tag. Both NSE lines failed to express

the CK1ε transgenes in the SCN, whereas CaMK2α and Scg2 showed high level of

47

Figure 3.3. Characterization of the tetO-driven CK1 lines. (A) Representative coronal brain sections showing tetO-driven lacZ and CK1 expression using -gal staining and in situ hybridization with HA probe. (B) Western blot analysis of transgenically induced CK1 protein in brain lysates using HA-specific antibody. There was no detection of CK1 proteins in the tissues from single-transgenic tetO-line animals (lanes 2, 4, 5, and 7).

48

CK1ε in the SCN. Transgenic copy number was roughly the same between tetO-HA-

CK1ε(tau) and tetO-HA-CK1ε(wt) lines at approximately 1 to 2 copies. In order to test

for leakiness of the tetO promoter, we also inspected whether the single transgenic mice

expressed the transgene protein using the anti-HA antibody against the brain lysates; both

tetO target lines exhibited tightly regulated inducible expression (Figure 3.3B).

3.3 Behavioral effects of tetO-driven CK1ε expression

Over-expression of the tau mutant CK1ε allele in the SCN using CaMK2α-tTA

and Scg2-tTA as the transactivator lines shortened the period of circadian behavioral

rhythm by approximately 40 minutes in bitransgenic animals (Figure 3.4). When the tau

transgene expression was subsequently repressed with dox treatment via drinking water

[10µg/ml], a wild type freerunning period was restored (yellow highlighted areas; Figure

3.4); and reverted back to shorter period upon removal of dox. The CK1ε transgene

expression can be repeatedly turned on and off as demonstrated in Scg2-tTA + tetO-HA-

CK1ε(tau) actograms (Figure 3.4B). A shortening of the circadian period of locomotor

activity was not observed when tau mutant CK1ε was expressed in brain regions other

than the SCN; as in NSE(A/B)-tTA + tetO-HA-CK1ε(tau) lines (Figure 3.5).

The magnitude of the period change caused by over-expression of the tau mutant

CK1ε in bitransgenic mice is comparable to the behavioral change reported by Wang et

al. (2007) in hamsters. In that study, wild type CK1ε transgene was transferred into the

SCN of tau mutant hamsters using in vivo electroporation, which lengthened the animal’s

average freerunning period by ~40 minutes. The ~40-minute difference observed

between experimental and control groups in both cases is relatively small in comparison

49

Fi

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3.4

. W

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50

Figure 3.5. Wheel-running activity records from mice expressing tetO-driven tau transgene in brain regions other than the SCN. Representative actograms from lines NSE(A)-tTA + tetO-CK1(tau) and NSE(B)-tTA + tetO-CK1(tau). Mice were kept under light-dark cycle (LD) for 2 weeks then released into constant darkness (DD). Days under doxycycline treatment are highlighted in yellow. Graphs indicate mean DD period ± SEM. Pairwise comparison: bitransgenic versus each control group, p > 0.10; Paired t-test: bitransgenic on water versus dox, p > 0.12.

51

to the 2-hour period shortening seen in genomic tau mutant hamsters and mice (Lowrey

et al., 2000; Meng et al., 2008; Ralph and Menaker, 1988). Whereas there are numerous

explanations for this difference, one possibility is the level of transgene expression in the

SCN pacemaker cells. The transgene copy number or the expression level of HA tag

from in situ hybridization does not explicate the actual change in CK1ε transcript level in

vivo. Hence, we measured the relative transgene expression levels using in situ

hybridization with a CK1ε-specific oligo probe (Figure 3.6A and B). We also explored

the spatial distribution of the transgene within the SCN by immunocytochemical analysis

(Figure 3.6C).

Immunocytochemical analysis demonstrated that Scg2-driven CK1ε transgene

expression is in the majority of cells in the SCN, encompassing both the core and the

shell regions. However, in situ hybridization analysis revealed that tetO-driven tau

transgene expression only accounts for about 35% of overall CK1ε expression. This

indicates that the ratio of tau to wild type CK1ε alleles is about 1:3 in the bitransgenic

mouse, which is substantially less than the ratio in heterozygous tau mutant hamsters.

Unfortunately we cannot assume that the level of expression has a linear relationship with

the change in phenotype. Thus, gene expression remains one possible explanation for

effects on behavioral phenotype that needs to be explored in detail.

Contrary to the tau transgene expression, in situ hybridization analysis showed

that tetO-driven wild type CK1ε expression almost doubled the endogenous level of

CK1ε transcript in the SCN under the control of Scg2 promoter (Figure 3.6B; right panel).

Significantly, we did not observe an altered circadian phenotype in these mice (Figure

3.7).

52

Figure 3.6. Expression analysis of the Scg2-driven CK1 transgene in the SCN. (A & B) In situ analysis of CK1 transgene shows inducible expression: the elevated level of CK1 transgene in a bitransgenic brain returns to the control level on dox treatment. (C) Immunocytochemical analysis indicates that the transgene expression is in the majority of the SCN cells including the core and shell subregions.

53

Figure 3.7. Wheel-running activity records from mice expressing tetO-driven wild type CK1 transgene in the SCN. Representative actograms from lines CaMK2α -tTA + tetO-CK1(wt) and Scg2-tTA + tetO-CK1(wt). Mice were kept under light-dark cycle (LD) for 2 weeks then released into constant darkness (DD). Days under doxycycline treatment are highlighted in yellow. Graphs indicate mean DD period ± SEM. Pairwise comparison (bitransgenic versus each control group): CaMK2α -tTA lines, p > 0.13; Scg2-tTA lines, p > 0.23. Paired t-test: CaMK2α-driven bitransgenic on water versus dox, p < 0.02; Scg2-driven bitransgenic on water versus dox, p > 0.22.

54

3.4 Effect of tetO-driven tau transgene expression as displayed by PER2::LUC

bioluminescence imaging

In order to determine the tissue-autonomous effects of tau mutation on the central

and peripheral oscillators, we crossed CaMK2α-tTA + tetO-HA-CK1ε(tau) bitransgenic

mice with the PER2::LUC reporter line. Western blot analyses showed that CaMK2α

driven CK1ε expression was brain-specific, and that the expression was very high in the

olfactory bulb (Figure 3.8A; also see Figure 3.2). Previous studies have reported that the

olfactory bulb (OB) contains an SCN-independent circadian pacemaker that expresses

rhythms with a similar phase and amplitude as the SCN (Abraham et al., 2005; Granados-

Fuentes et al., 2004a; Granados-Fuentes et al., 2004b). Hence, we selected the OB as a

representative peripheral oscillator and compared its rhythmic properties to that of the

SCN with conditional expression of the tau mutant CK1ε gene. Lung tissue was also

cultured from the same animals and used as a control tissue that does not express the tau

transgene (Figure 3.8B).

The shortening of the period observed in behavioral rhythms of CaMK2α-tTA +

tetO-HA-CK1ε(tau) mice, owing to the expression of tau mutant CK1ε transgene in the

SCN, was also reflected in PER2::LUC rhythms of the bitransgenic SCN explants.

Adding dox [0.1µg/ml] to the culture media turned off the tau transgene expression and

lengthened the period (paired t-test, p < 0.05); and when dox was removed from the

media, the period returned to the initial period before the dox treatment. This period of

the bitransgenic SCN tissue on dox did not differ significantly from the control group

tissues (paired t-test, p > 0.42). Hence, rhythmic properties observed in the molecular

output from the SCN of tau bitransgenic mice mirrored the observed behavioral

55

Figure 3.8. Tissue-specific transgene protein expression analysis and PER2::LUC bioluminescence records from CaMK2α-tTA + tetO-HA-CK1ε(tau) tissues. (A) Western blot analysis of tetO-driven CK1ε expression with and without dox treatment determined by HA-specific antibody. (B) Mean bioluminescence rhythms from CaMK2α-tTA + tetO-HA-CK1ε(tau) bitransgenic mice before (dark grey), during (yellow) and after (light grey) the dox treatment (top), and mean period ± SEM values (bottom). AG: adrenal gland; Lun: lung; Liv: liver; Pit: pituitary; Br: brain; OB: olfactory bulb; Cer: cerebellum.

A

B

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phenotype. Furthermore, shortening of the PER2::LUC oscillation, as well as the effect

of dox treatment, was also shown in the OB explants from the same mice (paired t-test, p

< 0.05). This suggests that the mechanism with which tau mutation affects the molecular

clock is consistent between the SCN and the OB oscillator.

CaMK2α promoter, however, did not direct the tau transgene expression to the

lung, and no changes in rhythms were observed from these explants. We can conclude

from this that the molecular oscillator within the lung is self-sufficient, and that disrupted

molecular clocks in the brain, especially within the central pacemaker in the SCN, do not

influence intrinsic rhythmic properties of the lung clock in vitro.

3.5 Chapter 3 – Summary and discussion

The tau mutation leads to an altered CK1ε kinase function, and results in an

accelerated circadian clock (Gallego et al., 2006; Lowrey et al., 2000). However, until

recently, this evidence was only available from in vitro studies. In this chapter, we have

provided direct functional evidence of the dominant-negative property of the tau

mutation on mammalian circadian clocks in the SCN and OB using the tet inducible

system. The accelerated locomotor activity rhythms emerged only when the tetO-driven

tau transgene was expressed in the SCN – confirming the SCN as a central pacemaker

that directs circadian behavior. However, the accelerated period in the SCN of a

bitransgenic animal did not manifest in the animal’s isolated peripheral tissue (i.e., lung)

that did not express the tau mutant transgene. This supports the notion from previous

studies that peripheral tissues contain self-sustained, SCN-independent circadian

57

oscillators with properties that are potentially subject to tissue-specific regulation

(Kornmann et al., 2007; Yoo et al., 2004).

In contrast, the tissue-autonomous impact of tau mutation was consistent between

SCN and OB tissue explants where the transgene is expressed. So, in this case, an

alteration in a post-translational regulatory mechanism has the same effect on molecular

clock operations in two distinct tissues.

Some studies, however, suggest that this may not be the case in all tissues. In

particular, in early 2008, Meng and colleagues (2008) reported a tau mutant mouse that

shows variable effects of the mutation on peripheral tissues. In their study, tau mutation

was introduced via the genome (knock-in) and it was less effective at shortening the

period of peripheral tissues compared to the SCN. It has also been reported that tissues

from wild type mice display different phase and periodicity of molecular oscillations

(Yoo et al., 2004). These differences may be attributed to tissue-specific regulatory

mechanisms within the clock cells, and CK1ε appears to be a reasonable candidate to

play a role since the regulation of kinase activity could be tissue specific. Alternatively,

there may be differences between the SCN and peripheral oscillators in the core structure

of their molecular clockwork. We explore this question in Chapter 4 by evaluating

tissue-autonomous rhythmic properties in mice with altered clock genes (Bmal1,

Clock∆19, Cry1, and Cry2).

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CHAPTER 4. ORGANIZATION OF THE CIRCADIAN MOLECULAR

CLOCK IN THE CENTRAL AND PERIPHERAL OSCILLATORS

59

4.1 Introduction

Circadian period can be adjusted by manipulating expression of a regulatory

protein kinase, CK1ε. Over-expression of the mutant allele, CK1ε(tau), on a wild type

background (Chapter 3) shortens the period, and introduction of the wild type allele on a

mutant background lengthens the period (Wang et al., 2007). The magnitude of the effect

on period depends upon the biochemical context in which the two alleles are mixed.

CK1ε(tau) shortens period by 2 hours when introduced via the genome (Meng et al.,

2008), but by only ~40 minutes when introduced via a transgene. The period difference

likely depends on the relative concentrations of tau and wild type protein products of

CK1ε, as well as on the background cellular expression of its isomer CK1δ. Thus, a way

of obtaining natural differences among different tissues in circadian period or phase may

be the tissue-specific regulation of CK1ε/δ. A recent study by Meng and colleagues

(2008) has supported this notion by showing that the effect of tau mutation is variable

across tissues – the impact of tau mutation is less on peripheral tissues than on the SCN.

However, it is yet unknown which attribute of kinase function is responsible for the

tissue-specific differences.

Alternative means of regulating circadian organization throughout the whole

animal might include tissue- or cell-specific regulation of the components (canonical

clock genes) of the molecular circadian oscillator, regulation of intercellular coupling

within the tissues, or systematic organization through differential responsiveness to

signals coming from the SCN or other organs. In this chapter, we address the question of

whether the intrinsic structure and function of the molecular circadian clock is conserved

from a master clock, the SCN, to peripheral oscillators.

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To assess the rhythmic properties of individual tissues, we crossed mice carrying

altered clock genes (Bmal1, Clock∆19, Cry1, and Cry2) to the PER2::LUC reporter line.

Tissue explants from various organs were then cultured ex vivo and bioluminescence was

continuously measured in real time. If the structure and function of the molecular clock

remain consistent across the tissues, changes in core clock components should have

comparable effects on the dynamics of molecular circadian rhythms in all tissues.

Alternatively, if phase or period setting is controlled predominantly outside the molecular

clock loops, then mutations should have effects that depend on the regulatory pathways

within each tissue. We selected core clock components Bmal1, Clock∆19, Cry1, and Cry2

for analyses to encompass both the positive and negative limbs of the clock loops. We

also included diverse physiological systems (pituitary, liver, lung and cornea) as

representative peripheral tissues for comparisons.

Our current method offers significant advantages over previous molecular assays

to test tissue-autonomous rhythmic properties: First, we can test the roles of clock

components more directly under the ex vivo culturing condition, which allows for

observation of peripheral oscillators exclusive of the influence from the SCN-to-

periphery synchronization; Second, the continuous, real-time measures of the molecular

rhythms over several cycles provide greater temporal resolution compared to previous

assays that typically measured gene expression with 4- to 6-hour resolution for 1 to 2

cycles.

In general, we find that disruption in particular core components of the molecular

clock has comparable effects on both SCN and peripheral oscillators. When a mutation

causes the SCN pacemaker to become arrhythmic, the peripheral oscillators are also

61

arrhythmic. When the altered clock is able to produce rhythmicity in the circadian range,

the period adjusts in an equivalent manner across the tissues. This suggests that the

inherent structure and function of the circadian molecular clock remain the same. In

other words, the roles of clock components in the organization of the molecular clock

remain consistent from the SCN to peripheral oscillators.

Furthermore, in the mutant animals that remain rhythmic, comparable phase

relationships are observed among the examined tissues. This observation highlights

SCN’s uncompromising role as a master coordinator. Despite genetic disruptions, the

SCN entrains (or maintains relative coordination) to a light-dark (LD) cycle and conducts

organization of peripheral oscillators.

The most interesting finding, however, is that the SCN oscillator appears to be

more robust and persistent against genetic defects than peripheral oscillators. This

suggests a tissue-dependent, systemic difference between the SCN and peripheral

oscillators. This is likely due to the SCN neurons possessing a unique way to augment

intercellular coupling that establishes an improved network oscillator.

4.2 Effect of circadian gene mutations on periodicity of PER2::LUC molecular

clock output in the SCN and peripheral oscillators

4.2.1. PER2::LUC bioluminescence rhythms in the SCN compared to the wheel-running

behavioral rhythms

The most common approach to characterizing biological clock properties has

involved genetic disruption followed by behavioral (e.g., wheel-running activity) assays

(Lowrey and Takahashi, 2004; Takahashi, 2004). To address whether the PER2::LUC

62

molecular oscillations from the SCN are comparable to the previously reported

behavioral phenotypes, we measured PER2::LUC rhythms in SCN explants from various

circadian mutant mice and compared these with locomotor activity patterns (Table 4.1).

Overall, the rhythmic properties observed in the SCN of circadian mutant mice mirror the

behavioral phenotypes; moreover, these results validate the use of the real-time

bioluminescence approach in studying circadian mutants.

Clock∆19 is a semi-dominant mutation that lengthens circadian period by ~1-hour

in heterozygotes (Clock∆19/+) and by ~4-hours in homozygotes (Clock∆19/∆19). With

prolonged exposure to constant darkness (>2 weeks), Clock∆19/∆19 mice fail to express

persistent circadian rhythms at the behavioral level (Vitaterna et al., 1994; Vitaterna et

al., 2006). Consistent with the behavioral patterns, Clock∆19/+ and Clock∆19/∆19 SCN

explants displayed rhythms with ~1-hour and ~5-hours longer periods compared to wild

type controls, respectively (Figure 4.1); however, even after a prolonged time in culture

(3 to 4 weeks), Clock∆19/∆19 SCN slices did not damp or become arrhythmic.

CLOCK, along with its partner BMAL1, drives the expression of Per and Cry

genes. Mammalian Cry has two forms, Cry1 and Cry2, both of which can repress the

CLOCK:BMAL1 heterodimeric transcription factor. However, Cry1 and Cry2 have

opposing effects on the period of the clock. Cry1-/- mice display ~1-hour shorter and

Cry2-/- mice display ~1-hour longer behavioral freerunning periods than the wild type

mice; and, disruption of Cry1 and Cry2 genes together causes behavioral and molecular

arrhythmicity (van der Horst et al., 1999; Vitaterna et al., 1999). In Cry1-/- and Cry2-/-

SCN explants, PER2::LUC rhythms were also shorter and longer, respectively, compared

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to the wild type counterparts, while SCN explants from Cry1-/-;Cry2-/- mice were

arrhythmic (Figure 4.2).

BMAL1, as mentioned above, is a positive regulator of circadian gene expression

as a part of CLOCK:BMAL1 transcription factor complex. Bmal1 is considered to rest

near the top of the circadian gene hierarchy in mammals because it is the only example of

a single-gene mutation that results in complete loss of both behavioral and molecular

circadian rhythms (Bunger et al., 2000). The Bmal1 mutant allele is recessive since the

phenotype of Bmal1+/- mice is not different from that of wild type mice. As well, the

period of PER2::LUC bioluminescence rhythms from Bmal1+/- SCN explants did not

differ from those of wild type SCN slices. However, Bmal1-/- SCN explants showed

unexpected stochastic rhythms with variable period lengths; the inter-peak duration

ranged from 4.5 to 37.2 hours with a mean value at 17.8 hours (± 5.54SD hrs) (Figure

4.3; also see Chapter 5). This aberrant rhythmicity of Bmal1-/- SCN explants came as a

surprise since the activity rhythms of these animals show complete loss of circadian

rhythmicity. Because of its uniqueness, we have committed Chapter 5 to explore the

Bmal1-/- SCN rhythms. For the remainder of the current chapter, we attend to

consistencies and other notable differences in molecular clock operation across the

central and peripheral tissues.

4.2.2. Effect of circadian gene mutations on periodicity of PER2::LUC rhythms in the

peripheral oscillators compared to the SCN

The changes in periodicity observed in the locomotor activity rhythms and in the

SCN slices were generally reflected across peripheral tissue explants from circadian

mutant mice. When the genetic mutation resulted in a longer period in the SCN (as in

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67

68

Clock∆19/+ or Cry2-/-), the period of the peripheral tissues also lengthened; and, when the

SCN was rendered arrhythmic, no circadian rhythmicity could be detected from the

peripheral tissues (as in Cry1-/-;Cry2-/-). In addition, tissue-specific relative period

lengths were observed. Regardless of the genotype, a shorter period occurred in either

cornea or pituitary with a longer period occurring in the SCN (see Table 4.1). Hence, the

effects of genetic mutation on tissue-dependent circadian periodicity were kept relatively

consistent in different tissues. These results support our hypothesis that the molecular

structure may be conserved from the SCN to peripheral oscillators, and that genetic

alteration in core components have similar effects on circadian clocks throughout the

body.

In some cases, however, we observed divergence between the SCN and peripheral

oscillators in how they were affected by a genetic mutation. As mentioned above, we

observed lengthened, yet persistent rhythmicity in Clock∆19/∆19 SCN explants, and

uncharacteristic, stochastic rhythmicity in Bmal1-/- SCN slices; nevertheless, peripheral

tissues from both of these mutant mice were completely arrhythmic. Tissues from Cry1-/-

mice were particularly puzzling: First, the SCN explants showed robust circadian

rhythmicity, yet most of the peripheral tissues showed unexpectedly damped rhythms.

Second, not all peripheral tissues were severely damped – pituitaries generally showed

measurable rhythmicity with a shorter period that is characteristic of the Cry1 loss-of-

function mutation, whereas liver tissues were severely damped if not completely

arrhythmic. Hence, in Cry1-/- tissues, we observed not only a difference in the effect of

the mutation between the central and peripheral oscillators, but also differences among

the peripheral oscillators.

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Overall, it is clear that when a specific component of the molecular clock is

disrupted, the consequence of that is different between the SCN and peripheral

oscillators. This dichotomy between the SCN and peripheral tissues suggests that the

SCN may be able to compensate for the genetic disruptions, preserve its rhythmic output

to the peripheral systems, and maintain hierarchical dominance in mammalian circadian

organization. To better understand the organization of circadian system, we performed

further analyses on phase coordination, robustness (amplitude), and persistence

(damping) of the oscillators.

4.3 Effect of circadian gene mutations on coordination of phase relationships

among the oscillators

Phase of a tissue observed ex vivo has been shown to reflect the in vivo phase

(Stokkan et al., 2001; Yamazaki et al., 2000; Yamazaki et al., 2002; Yoo et al., 2004). To

better understand the organization of peripheral oscillators, we constructed phase maps

for the SCN and peripheral tissues using the peak of the bioluminescence oscillation

between the first 12 to 36 hours in culture (Figure 4.4). Only the tissues that showed

robust circadian rhythmicity were selected for phase analyses, which led us to exclude

peripheral tissues from Bmal1-/-, Clock∆19/∆19, Cry1-/-, and Cry1-/-;Cry2-/- mice.

All SCN explants (harvested from wild type, Bmal1+/-, Clockm/+, and Cry2-/- mice)

displayed peak PER2::LUC expression at ~CT 12. This is consistent with that seen in

vivo from wild type mice (Field et al., 2000) and with the previous finding from

PER2::LUC mice (Yoo et al., 2004). Peripheral tissues from these mice were rhythmic

and exhibited delayed phases relative to the peak phase of the SCN. Furthermore, each

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Figure 4.4. Phase map for central and peripheral circadian oscillators of PER2::LUC mice. The peak of the circadian oscillation was determined during the first 12 to 36 hours in culture. Individual peak times were plotted against the time of last lights on (ZT0) – black bar indicates the mean phase value. Tissues were harvested on the phase hour 12 (ZT12; lights off) and hours 24 to 48 mimics the next LD cycle indicated by white (light) and shaded (dark) area. Data for SCN, pituitary, liver, lung, and cornea are shown.

71

peripheral tissue expressed characteristic, relative phase coordination of PER2::LUC

peak expression to the SCN and with each other. For example, the liver tended to phase

lead the other peripheral tissues that were studied, and the lung tended to phase lag

behind all of the other studied peripheral tissues.

Interestingly, in the phase map for Cry2-/- tissues, we find slightly altered patterns

in that the liver clock seems to lag behind the other tissues. This suggests that Cry2 may

play a role in setting the liver clock and that this role of Cry2 for the operation of the

circadian clock may not be consistent across all tissues. It is important to consider,

however, that output pathways (see Figure 1.1) can feed back to the oscillator to exert

phase-shifting effects, subtle period changes, and modulation of clock gene expression

(Edgar et al., 1991; Maywood et al., 1999; Van Reeth and Turek, 1989) and that circadian

clocks in various tissues may entrain independently to external time cues, such as light

and food (Damiola et al., 2000; Schibler and Sassone-Corsi, 2002; Stokkan et al., 2001;

Wu et al., 2008). For example, the daily restricted-feeding cycle can alter the phase of

the rhythms in liver independently of the SCN (Stokkan et al., 2001) and shifting the

feeding schedule has different effects on liver versus heart clocks (Wu et al., 2008).

These findings allow us to hypothesize that the structure and function of the inherent

circadian molecular clocks are consistent across tissues, but their responses to various

signals that set the clock are different.

The above, however, can only be stated for animals that sustain tissue-

autonomous rhythmicity. Questions still remain about organization of peripheral

oscillators in arrhythmic animals or animals that maintain robust circadian rhythmicity in

the SCN but demonstrate damped tissue-autonomous rhythms in the periphery (i.e.,

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Cry1-/- or Clock mice∆19/∆19). The advancement of technology in in vivo imaging may

“unlock” future methods that lead to better understanding about the circadian

organization.

4.4 Effect of circadian gene mutations on tissue-autonomous resetting of the

peripheral oscillators via forskolin treatment

We explored the tissue-autonomous resetting mechanism of the peripheral

oscillators by applying a cAMP analog, forskolin [10uM] (Figure 4.5). Forskolin

treatment elicits synchronization of dispersed cellular oscillators, and reinitiates high

amplitude rhythmicity in damped peripheral tissues (Abe et al., 2002; Izumo et al., 2003;

Yagita and Okamura, 2000). All peripheral tissues were completely damped prior to

forskolin treatment, and all responded with an acute, immediate rise in PER2::LUC level

to the treatment. Surprisingly, this response was seen even in tissues that are otherwise

arrhythmic (from Bmal1-/-, Clock∆19/∆19, or Cry1-/-;Cry2-/- mice). The phase analyses of

the forskolin-induced, acute PER2::LUC oscillations showed that there was a tissue-

autonomous resetting to the treatment that was not affected by genotype.

Steady-state phase, in contrast to the acute response, varied across the tissues and

between genotypes (Figure 4.6). Furthermore, phase maps derived from these responses

differed sufficiently from the phase organization displayed at the time of initial culture

(see Figure 4.4). This indicates that different tissues from various circadian mutants

respond differently to the chemical perturbation. Furthermore, it suggests that the

characteristic phase map observed at the time of initial culture is not due to tissue-specific

resetting of the rhythms due to the culturing process.

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Figure 4.5. Phase map for peripheral circadian oscillators of PER2::LUC mice – acute response to forskolin. First peak of the circadian oscillation was determined during the first 12 hours following the forskolin treatment (time 0). Individual peak times were plotted with black bar indicating the average value. Data for pituitary, liver, lung, and cornea are shown.

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Figure 4.6. Phase map for peripheral circadian oscillators of PER2::LUC mice – steady-state phase for forskolin-induced circadian rhythms. Steady-state peak of the circadian oscillation was determined following the forskolin treatment (time 0). Individual peak times were plotted with black bar indicating the average value. Data for pituitary, liver, lung, and cornea are shown.

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It is worthy of note that the forskolin treatment triggered two to three circadian

fluctuations in some of the arrhythmic peripheral tissues following the acute rise in

PER2::LUC level. These rhythms were weak and dissipated fast. However, it suggests

an inducible mechanism that can keep a ~24-hour timing at the tissue level even when the

circadian molecular clock has been disrupted. It is likely that a continuous stimulation

(or feedback) is necessary to continue this operation, such as in the daily restricted-

feeding paradigm.

4.5 Effect of circadian gene perturbations on robustness and persistence of

PER2::LUC rhythms in peripheral oscillators

Clock∆19 mutation reduces circadian amplitude in the running-wheel activity

rhythms as well as in Per1 and Per2 mRNA expression rhythms and in PER2::LUC

bioluminescence rhythms in the SCN (Vitaterna et al., 2006). As expected, reduced

circadian amplitude was clearly represented in PER2::LUC bioluminescence rhythms of

Clock∆19/+ peripheral tissues (Figure 4.7A). The effect of Clock∆19 mutation was, in fact,

seemingly more severe on the peripheral oscillators. When a peripheral oscillator

contains two copies of the mutant Clock gene (Clock∆19/∆19), its rhythmic output was

completely damped.

We were surprised to find Cry1-/- peripheral explants showed damped rhythms

whereas the Cry1-/- SCN rhythms were intact with high amplitude. Forskolin treatment

could briefly restart oscillations in some of the Cry1-/- peripheral samples: 2 of 13 Cry1-/-

livers, 5 of 16 Cry1-/- lungs, and 2 of 9 Cry1-/- corneas showed damped rhythms during

initial culture, but the rhythms were induced briefly (2-3 days) following forskolin

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Figure 4.7. Robustness and persistence of PER2::LUC rhythms in peripheral oscillators. (A) Robustness of PER2::LUC rhythms as determined by relative FFT spectral power. (B) Persistence of PER2::LUC rhythms as determined by damping coefficient. The coefficient represents number of days required for the amplitude of the rhythm to decrease to 1/e (~36.79%) of the starting value (Izumo et al., 2003). Values are presented as mean ± SEM.

77

treatment. In contrast, Cry2-/- peripheral tissues exhibited more robust (high amplitude)

and persistent (reduced damping) rhythms even in comparison to the wild type

counterparts (Figure 4.7B). Previous studies have alluded to different contributions of

Cry1 and Cry2 to the circadian clock operation although definitive mechanisms are still

unknown (Oster et al., 2002). Our results also indicate that functions of the two family

members are not redundant: Cry1 is essential to sustain circadian rhythms in peripheral

tissues, whereas Cry2 deficiency affects circadian periodicity and persistence of the

rhythms. Either Cry1 or Cry2 is required for intact rhythmicity.

4.6 Chapter 4 – Summary and discussion

We found that SCN is sufficient to evoke behavioral rhythms in the absence of

distant peripheral oscillators, as demonstrated by persistent SCN and behavioral rhythms

observed in Cry1-/- mice despite damped peripheral oscillators. This and the comparable

periods of PER2::LUC bioluminescence rhythms in the SCN and behavioral activity

rhythms reveal the SCN as a pacemaker for circadian behavior in circadian mutant mice.

The rhythmic nature of the SCN, however, is not always translated to

corresponding behavior. We find that the Clock∆19/∆19 SCN slices sustain persistent

oscillations whereas the locomotor activity rhythms of these mice have been shown to

become arrhythmic with prolonged (2 to 5 weeks) exposure to constant darkness

(Nakamura et al., 2002; Vitaterna et al., 1994). Wheel-running activity is a complex

rhythmic output that is far downstream from the molecular oscillations taking place in the

SCN, and may be confounded by association with feeding, phenotypic variability, and

pleiotropy of the underlying gene mutation (Bucan and Abel, 2002; Takahashi, 2004). It

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is possible that other phenotypic effects of Clock∆19 mutation may dissociate the SCN-to-

behavior organization.

The effects of circadian gene perturbations on peripheral oscillators are generally

consistent with those on the SCN: in most genetic backgrounds, the direction of

periodicity change is compatible and a certain level of coherency is conserved in the

phase-coordination. We can infer from this that the structure and function of the

molecular clock are conserved from the SCN to peripheral oscillators, and that genetic

alterations in core components have similar effects on the clocks throughout the body.

Nonetheless, a clear dichotomy between the SCN and peripheral oscillators is observed in

Cry1-/-, Clock∆19/∆19 and Bmal1-/- tissue explants in which the SCN exhibits significantly

more persistent rhythms compared to the damped peripheral oscillators.

While we were conducting the PER2::LUC tissue explant study, we discovered

that similar experiments were being conducted in the laboratory of Dr. Steve Kay

(University of California – San Diego, CA). Our two groups arrived independently at the

same conclusions and began to collaborate. We decided that the Kay group would focus

on the negative limb of the core clockwork and that we would focus on the positive

limb.4 We turned our attention first to Cry1 and its requirement for persistent rhythms in

peripheral tissues. Findings from our collaboration were reported in the Liu et al.

(2007b) study.

Importantly, we found that Per1 and Cry1 are required to sustain cell-autonomous

circadian rhythms: both primary fibroblasts and dissociated SCN neurons from Per1-/-

4 The decision was based on the facts that 1. They were ahead of me in terms of testing Per mutants; 2. They had not observed the SCN rhythms from Bmal1-/- mice at the time; and, 3. I had data from more peripheral tissues whereas they only tested SCN and Lung explants.

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and Cry1-/- mice were mostly arrhythmic, albeit some transient rhythmicity was present in

the SCN neurons. Organotypic culture of the SCN slice, however, preserved the

circadian rhythmic output. Therefore, we concluded that cell-to-cell coupling, which

establishes an oscillator network within the SCN, compensates for Per1 and Cry1

deficiency preserving sustained rhythmicity in mutant SCN slices and behavior. Cry2

and Per3 deficiencies, on the other hand, only resulted in periodicity changes.

Further mathematical simulations by Dr. Francis J. Doyle’s group (University of

California – Santa Barbara) demonstrated that oscillator coupling can compensate for

compromised single-cell oscillators (also reported in Liu et al., 2007b). In this model, a

simple coupling mechanism was introduced to defective single-cell oscillators (as

observed in uncoupled Per1-/- or Cry1-/- neurons) by making the Per transcription rate

dependent on the Per mRNA levels in nearby cells, weighted by their proximity. This

recovered stable, persistent circadian rhythms from the population of cells.

The SCN circadian clock is more than just the sum of its cells. Our results (Liu et

al., 2007b) demonstrate that the integrated SCN circadian pacemaker is qualitatively

more robust than its component cellular oscillators. Studies have confirmed that the

individual SCN neurons as well as the peripheral cells (i.e., mouse fibroblast cells and

liver cells) are oscillators that exhibit self-sustained, cell-autonomous circadian rhythms

(Balsalobre et al., 2000b; Brown et al., 2005; Herzog et al., 1998; Liu et al., 2007b;

Nagoshi et al., 2004; Welsh et al., 2004). At the single-cell level, the intrinsic rhythmic

properties seem to remain the same across the tissues with or without genetic

perturbation; at the tissue level, however, differences in rhythmic properties have been

noted (most likely due to systemic differences cellular organization to form an oscillator

80

network). A tissue-oscillator (considered as a “population” oscillator) is composed of

many individual component (or “unit”) cellular oscillators (Ohta et al., 2005; Rougemont

and Naef, 2006; Yamaguchi et al., 2003). This implies that even when the tissue-

oscillator is damped, some underlying mechanisms (such as coupling) amongst cellular

oscillators can temporarily generate rhythmicity when forced into synchrony; we

observed this even in arrhythmic peripheral tissue-oscillators following forskolin

treatment.

Overall, our findings indicate that the inherent molecular organization and

function of the cell-autonomous clock remain the same throughout the body. Hence, the

roles of clock gene components remain consistent from the SCN to peripheral oscillators

at the cellular level. At the tissue-level, however, intercellular communication can mask

genetic defects in individual clock cells, which has been detected only in the SCN.

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CHAPTER 5. INTRINSIC NETWORK OSCILLATIONS IN THE SCN

AS REVEALED IN Bmal1 MUTANT MICE

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5.1 Introduction

In this chapter, we explore the uncharacteristic PER2::LUC rhythmicity observed

in the Bmal1-/- SCN. Bmal1 is the only known clock gene whose loss-of-function leads

to a complete loss of circadian rhythmicity at the behavioral level (Bunger et al., 2000).

In addition, the circadian rhythms of Per1 and Per2 mRNA expression in the SCN are

abolished in Bmal1-/- mice. Hence, it was a great surprise to observe fluctuations in

PER2 levels in the SCNs lacking functional BMAL1 (see Figures 4.3 and 5.1).

The SCN is comprised of individual neurons that exhibit cell-autonomous

circadian rhythms. The activity of individual neurons within the same SCN, however,

shows a wide distribution of phase and period. Intact neuronal connections, which may

not be necessary for the generation of rhythmicity, seem to contribute to phase coupling

or synchronization between SCN neurons (Herzog et al., 1997; Honma et al., 1998).

Furthermore, intercellular coupling can compensate for intrinsically compromised

cellular oscillators such as those in Cry1-/- and Per1-/- SCNs as discussed in the previous

chapter (Liu et al., 2007b). The exact mechanism by which the SCN establishes a

synchronized neural network is yet to be determined, nonetheless, we demonstrate here

that intercellular signaling mechanisms (coupling) among SCN neuronal oscillators

contribute to the generation of rhythmicity in the Bmal1-/- SCN.

5.2 Characterization of the rhythmic PER2::LUC output in the Bmal1-/- SCN

5.2.1 Bmal1-/- SCN explants display non-circadian, stochastic PER2::LUC rhythms

Wild type and Bmal1-/- SCN explants show persistent PER2::LUC

bioluminescence rhythms for more than 35 days in culture. Long-term raw and baseline-

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subtracted bioluminescence records are shown for wild type and Bmal1-/- SCN explants

in Figure 5.1. Fast Fourier transform (FFT) spectrograms of the baseline-subtracted

records (bottom left) show a tightly regulated frequency (about one cycle per day) for the

wild type SCN; however, shorter and more variable frequency components are observed

in the Bmal1-/- SCN. Double-plotted raster plots (bottom right) illustrate the stable

PER2::LUC rhythmicity in the wild type SCN and the unstable rhythms in Bmal1-/- SCN.

Because of the highly variable period and instability of the rhythmicity from Bmal1-/-

SCN, we refer to these fluctuations as stochastic.

Due to the stochastic nature of the rhythms in the Bmal1-/- SCN, period estimates

based on averages of long time series do not adequately describe the cycle-to-cycle

variability. Hence, we measured individual peak-to-peak intervals of the PER2::LUC

expression patterns from each SCN explant (Figure 5.2A). The mean inter-peak intervals

observed in the wild type and Bmal1+/- SCN explants were circadian at about 24 hours

(24.3 ± 1.03 SD hrs and 24.0 ± 0.86 SD hrs, respectively). Furthermore, these values

were similar to the periods estimated by Levenberg-Marquardt (LM) curve fitting of the

entire time series using the LumiCycle Analysis Program (see Table 4.1). By contrast,

the Bmal1-/- SCN fluctuations had a significantly shorter average inter-peak interval

length of 17.8 hours (ANOVA, F2,1841 = 422.8; p < 0.0001) with a much greater variance

(SD = 5.54 hrs) than wild type or Bmal1+/- SCN explants.

Using the inter-peak interval data, we determined the Serial Correlation

coefficient of successive intervals (rs) (Figure 5.2B). A negative serial correlation

reflects the likelihood that a long cycle will be followed by a short cycle, or vice versa,

which is a characteristic feature of pacemaker-driven systems (Pittendrigh and Daan,

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Figure 5.1. Detailed view of PER2::LUC bioluminescence from wild type and Bmal1-/- SCN explants. All SCN explants show persistent PER2::LUC rhythms for >35 days. (A) Raw records (top) and FFT spectrograms (bottom). FFT spectrograms show a tightly regulated frequency (cycles per day) for the wild type SCN; however, shorter and more variable frequency components are observed in the Bmal1-/- SCN. (B) Double-plotted raster plots of the four records shown in A. They illustrate stable PER2::LUC rhythmicity in the wild type SCN and instability of the rhythms in Bmal1-/- SCN.

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Figure 5.2. Inter-peak interval analysis of PER2::LUC bioluminescence in SCN explants. (A) Histograms of inter-peak intervals for the PER2::LUC rhythmic expression patterns. The Bmal1-/- SCN explants show a significantly shorter average inter-peak interval and a much broader distribution compared to wild type or Bmal1+/- SCNs. Histograms represent 433 inter-peak intervals from 23 wild type SCN explants, 212 intervals from 6 Bmal1+/- SCN explants, and 1239 intervals from 19 Bmal1-/- SCN explants. (B) Serial Correlation Coefficient (rs) of successive inter-peak intervals from A. A negative serial correlation reflects the likelihood that a long cycle will be followed by a short cycle, or vice versa. rs estimates were calculated from successive 10 inter-peak interval epochs. Histograms represent 36 rs estimates from 23 wild type SCN explants, 18 rs estimates from 6 Bmal1+/- SCN explants, and 85 rs estimates from 19 Bmal1-/- SCN explants.

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1976). This particular property insures maintenance of reliable oscillation with a set

period (Pittendrigh and Daan, 1976). The average serial correlation coefficient for both

wild type and Bmal1+/- SCN explants were negative (rs = -0.17, p < 0.01 (one-sample t-

test); rs = -0.16, p < 0.05, respectively) as would be expected from a circadian pacemaker

process; however, the coefficient for the Bmal1-/- SCN was positive (rs = 0.07, p < 0.05)

suggesting that long intervals were more likely to be followed by another long interval

and short interval followed by another short interval. This positive serial correlation

coefficient differs from the pacemaker-driven processes seen in wild type and Bmal1+/-

SCN explants and is consistent with an oscillator with either a highly labile period or a

“random walk” process (Beek et al., 2002).

Given that the PER2::LUC expression from Bmal1-/- peripheral organs are not

rhythmic, we then asked whether the observed SCN rhythm is an inherent property of the

SCN or a general property of neuronal structures. As discussed in Chapter 3, the

olfactory bulb contains an SCN-independent circadian pacemaker that expresses rhythms

with a similar phase and amplitude as the SCN (Abraham et al., 2005; Granados-Fuentes

et al., 2004a). The olfactory bulb from Bmal1-/- failed to show temporal variations in

PER2::LUC expression like the other peripheral tissues (Figure A.2; Appendix C).

Hence, the stochastic rhythm generation is a unique characteristic of the Bmal1-/- SCN

pacemaker.

5.2.2 Single-cell recording of PER2::LUC rhythms reveal Bmal1-/- SCN neurons are

arrhythmic

Previous studies have demonstrated that cell-autonomous rhythms are not

disturbed by uncoupling cellular oscillators by chemical disruption (Yamaguchi et al.,

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2003), mechanical dissociation (Herzog et al., 1998; Liu et al., 2007b; Welsh et al., 1995)

or by genetic disruption of VIP signaling (Aton et al., 2005; Maywood et al., 2006). On

the other hand, we have shown that genetic disruption of core clock loop can impair

individual cellular oscillators (such as in Cry1-/- or Per1-/- dissociated SCN neurons); and

yet, provided that the coupling mechanism is intact, the SCN can overcome the genetic

disruption and generate circadian rhythmicity as a network oscillator (Liu et al., 2007b).

To determine whether stochastic PER2::LUC rhythms from Bmal1-/- SCN explant are

cell-autonomous, we studied PER2::LUC bioluminescence at a single cell level in

collaboration with Drs. David Welsh and Steve Kay (University of California – San

Diego, CA),

We first imaged the overt bioluminescence expression patterns from Bmal1-/-

SCN explants and analyzed bioluminescence intensity from individual neurons (Figure

5.3A). The SCN cells in an intact organotypic slice were tightly synchronized and

exhibited stochastic rhythms comparable to those seen in the Bmal1-/- SCN explants using

luminometry. Separately, we cultured dissociated SCN neurons and imaged

bioluminescence from individual single cells (Figure 5.3B). In contrast to the cells in an

intact organotypic slice, dissociated Bmal1-/- neurons did not express detectable circadian

rhythms (242/243 cells). Dissociated wild type SCN neurons generally exhibited

circadian rhythms that are persistent with high amplitude.

These results clearly indicate that cellular clocks lacking BMAL1 cannot sustain

rhythmicity, circadian or otherwise; and the lack of rhythmicity in dissociated SCN cells

indicates that the stochastic rhythmicity observed in Bmal1-/- SCN explants cannot be

observed at the cell-autonomous level and likely arises from intercellular network

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Figure 5.3. Stochastic rhythmicity in Bmal1-/- SCN is not cell autonomous. (A) Bioluminescence images of a Bmal1-/- SCN explant culture at peak and trough phases. Numbers indicate hours after start of imaging. Scalebar = 500 µm. (B) Heatmap plots of bioluminescence intensity of individual Bmal1-/- neurons in an intact organotypic SCN slice. Forty cells are presented, with each horizontal line representing a single cell. These cells show tightly synchronized stochastic rhythms that are comparable to rhythms seen in the SCN ensemble. (C) PER2::LUC rhythms (top) and corresponding FFT Spectrograms (bottom) for first 4 cells shown in B (i.e., coupled in Bmal1-/- SCN explant). (D) Bioluminescence images of dissociated individual Bmal1-/- SCN neurons showing arrhythmic bioluminescence patterns. Numbers and scale bar are as in A. (E) Heatmap plots of bioluminescence intensity of 40 individual Bmal1-/- neurons in dispersed culture imaged in D showing complete absence of stochastic rhythmicity. (F) PER2::LUC rhythms (top) and corresponding FFT spectrograms (bottom) for first 4 cells shown in E (i.e., dispersed Bmal1-/- SCN cells).

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interactions. In other words, like the Per1- or Cry1-deficient SCN network of oscillators

(as discussed in Chapter 4 and Liu et al., 2007b), cell-to-cell coupling may be an

important factor for stochastic rhythm generation in Bmal1-/- SCN.

5.3 Intercellular coupling drives a network oscillator in the Bmal1-/- SCN

For the SCN to act as a dominant circadian pacemaker, individual cells within the

SCN must synchronize to environmental cycles and to each other. Studies show that

SCN neurons are not homogeneous in function – these neurons differ in their pacemaking

property, neuropeptide expression, response to environmental timing cues, and the

rhythms they control (reviewed in Antle and Silver, 2005; Aton and Herzog, 2005; Liu et

al., 2007a); hence, in order for the SCN to function as a coherent network oscillator,

heterogeneous mixture of pacemaker cells must be able to communicate with each other.

To date, relatively little is known about intercellular synchronization within the

SCN. The current understanding suggests that sodium-dependent action potentials are

required to coordinate the timing between cells (Honma et al., 2000; Schwartz et al.,

1987; Welsh et al., 1995; Yamaguchi et al., 2003); and that gap junctions contribute to

synchronization through rhythmic electrical coupling between adjacent neurons (Colwell,

2000; Long et al., 2005). GABA and VIP are two major neurotransmitters that are

known to function as synchronizing factors in the SCN. To determine whether

intercellular coupling contributes to the stochastic PER2::LUC rhythms observed in the

Bmal1-/- SCN explants, we treated the SCN explants with various chemicals that are

known to “un-couple” the SCN neurons (Figure 5.4).

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Figure 5.4. Uncoupling SCN cells abolishes stochastic rhythms from Bmal1-/- SCN explants. (A-D) Representative records of PER2::LUC rhythms of the SCN explants from wild type (blue) and Bmal1-/- (red) mice. Data are shown following a medium change (day 8); shaded area indicates when SCN explants were changed to fresh medium containing vehicle solution (A), Tetrodotoxin (B), Bicuculline (C), and Pertussis toxin (D). (E) Relative values of PER2::LUC luminescence brightness and FFT power for SCN explants from B-D. Values for time intervals (± SEM) before, during, and after the treatment are graphed for each genotype and treatment. Relative brightness: there was no significant genotype effect by ANOVA (F1,36 = 0.01, p > 0.16), but significant drug effect in luminescence level (F2,36 = 0.01, p < 0.00003; Tukey-Kramer, p < 0.05). Relative FFT Power: There were both significant genotype and drug effects (F1,45 = 0.01, p < 0.008 and F2,36 = 0.01, p < 0.0005, respectively; Tukey-Kramer, p < 0.05).

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Tetrodotoxin (TTX)

Tetrodotoxin (TTX) is commonly used to prevent action potentials by selectively

and reversibly blocking voltage-dependent Na+ channels. TTX application has been

shown to desynchronize neurons within an intact SCN (Yamaguchi et al., 2003), which

suggests that action potentials and/or consequent neuronal transmission are required to

maintain SCN synchrony.

Under continuous TTX administration, wild type SCN tissue showed persistent

PER2::LUC rhythms. However, the amplitude of the rhythm diminished cycle by cycle

(damping), which is attributed to intercellular desynchrony across an otherwise rhythmic

population. On the other hand, the Bmal1-/- SCN exhibited an immediate, complete

arrhythmicity of PER2::LUC output when treated with TTX. The PER2::LUC rhythms

returned immediately upon removal of TTX in both wild type and Bmal1-/- SCNs (Figure

5.4B). In addition, single-cell imaging of neurons in an organotypic SCN slices before,

during, and after TTX clearly demonstrated that un-coupling cells results in arrhythmic

single-cells like SCN neurons in dispersed culture (Figure 5.5; collaboration with Ethan

Buhr, Northwestern University, Evanston, IL).

Bicuculline (BIC)

GABA is a likely neurotransmitter to mediate synchrony with the SCN because:

1. Most (if not all) SCN neurons express GABA and its receptors (Abrahamson and

Moore, 2001; Moore et al., 2002); 2. GABA is released in a daily rhythm within the SCN

(Itri and Colwell, 2003); 3. Daily application of exogenous GABA synchronizes firing-

rate rhythms of SCN neurons (Liu and Reppert, 2000); and, 4. Application of GABAA

receptor antagonist, bicuculline (BIC), effectively blocks GABA-

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evoked inhibitory postsynaptic currents preventing inter-regional synchronization

between dorsal and ventral SCN (Albus et al., 2005).

Bicuculline application to wild type SCN showed gradual damping of the

PER2::LUC peak-to-trough amplitude; however, it also showed heightened overall

luminescence expression level indicating higher level of PER2. The increase in

luminescence level was also seen in Bmal1-/- SCN with BIC treatment, but the rhythmic

nature of PER2::LUC was eliminated. When BIC was removed, the wild type SCN

rhythm was immediately restored, however, the Bmal1-/- SCN took some time (1-2 days)

to recover its rhythmicity. See Figure 5.4C.

Pertussis Toxin (PTX)

VIP, along with GABA, meets most of the criteria for a synchronizing factor

within the SCN. VIP is synthesized by ventromedial SCN neurons that receive direct

input from retinal ganglion cells, hence relaying the information about the environmental

cycles to the rest of the SCN. In vitro studies show that VIP is rhythmically released

from the SCN (Shinohara et al., 1995); and, VIP responses are mediated through a G

protein-coupled VPAC2 receptor, which is expressed by most VIP efferent target neurons

(namely, AVP-expressing neurons of the dorsal SCN) (Kalamatianos et al., 2004; Kallo

et al., 2004). Furthermore, loss of VIP or VPAC2 disrupts locomotor behavior rhythms in

mice, abolishes circadian firing rhythms in the majority of SCN neurons, and disrupts

synchrony between rhythmic neurons (Aton et al., 2005; Harmar et al., 2002; Maywood

et al., 2006).

Pertussis toxin (PTX) irreversibly inactivates Gi and Go protein activity by

preventing their inhibition of adenylyl cyclase; and, its treatment has been shown to both

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decrease the synchrony between rhythmic neurons and abolish rhythms in a subset of

neurons within the SCN (Aton et al., 2006). PTX application to wild type SCN

significantly reduced the peak-to-trough amplitude leading to rhythmic damping, as it has

been consistently observed with TTX and BIC treatments. Bmal1-/- SCN responded to

the PTX in a similar fashion as it did to BIC treatment – the PER2::LUC rhythmicity was

completely abolished with overall increase in luminescence level. Unlike the other two

treatments, rhythms did not return when PTX was removed in either wild type or Bmal1-/-

SCN, intuitively due to the irreversible nature of PTX; however, a trace of rhythmicity

was detected in the wild type SCN. See Figure 5.4D.

5.4 Chapter 5 – Summary and discussion

As a network oscillator, the wild type SCN exhibits a period that represents the

average period of the individual cellular oscillators. In the case of Cry1-/-, Per1-/- and

Bmal1-/- SCNs, however, we observe the SCN’s unique ability to generate rhythmicity

from non-rhythmic cells. In Bmal1-/- SCN, almost none of the individual cells were

rhythmic. However, ~5-10% of the dissociated SCN neurons from Cry1-/- and Per1-/-

SCNs showed weak or transient rhythms with periods within the circadian range (Liu et

al., 2007b). These remaining rhythmic cells appear to be sufficient to generate circadian

rhythms in coupled Cry1-/- and Per1-/- SCN populations, which is in sharp contrast to the

stochastic rhythms seen in Bmal1-/- SCN. In other words, even though these individual

rhythms may be “sloppy”, their rhythmic properties can be magnified when coupled.

Much of what we now understand about the SCN’s network property stems from

computational modeling studies. The key concept is that synchronization among

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heterogeneous population of oscillators reduces variability in period output, which

improves cycle-to-cycle precision (reviewed in Indic et al., 2007). This is demonstrated

by increased amplitude and accuracy of rhythms observed in the wild type SCN network

compared to the dispersed cells (Herzog et al., 2004).

Limit-cycle models have been often used to describe the behavior of the SCN at

the intercellular population and intracellular molecular levels. These models have been

useful in understanding the dynamics of the circadian pacemaker; however, they consider

the pacemaker as a single oscillatory unit which we know is not the case. A model of

circadian oscillators that combines intracellular and intercellular dynamics at the single-

cell level is needed to complement and extend the experimental data to understand

intercellular synchrony, and how coupling can compensate for the loss of a genetic

component.

We shared our experimental data with Drs. Daniel Forger and Yujiro Yamada

(University of Michigan, Ann Arbor, MI) to design a new model that can incorporate our

observations, and in the process found that interplay between network coupling and

molecular noise is necessary for a functional SCN neuronal network (Ko et al.,

submitted).

The model is based on a previously published stochastic mammalian circadian

clock computational model (Forger and Peskin, 2005). In the current model, we

examined the effects of reducing the BMAL activator concentration to a level at which

there is no expression of BMAL1, but a low concentration of other activators (e.g.,

BMAL2, a paralog of BMAL1) is present. BMAL2 is regionally co-expressed in the

SCN and forms transcriptionally active heterodimers with the CLOCK and NPAS2

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proteins (Hogenesch et al., 2000; Ikeda et al., 2000). Furthermore, BMAL1 and BMAL2

show similar sensitivity to CRY1-mediated transcriptional repression (data courtesy of

Dr. Andrew Liu from University of Memphis, Memphis, TN), which suggests that the

core negative feedback loop of the circadian oscillator could remain functional in the

presence of BMAL2. The total level of Bmal2 expression is about 10% of the level of

Bmal1 in wild type mouse, and Bmal2 expression levels are unaffected by the Bmal1

loss-of-function mutation. Thus, we estimated that in a Bmal1-/- mouse, the level of

Bmal2 is about 10% of the wild type level of Bmal1. The 10% BMAL activator

simulations faithfully captured the stochastic behavior and the complete lack of circadian

rhythmicity of PER2::LUC expression seen in dissociated Bmal1-/- SCN neurons.

Coupling was introduced to the model by a CRE element where a factor (e.g.,

CREB) can bind and activate transcription of Per1 and Per2 for a secreted coupling agent

(CA). The ‘coupling’ factor is equivalent to AVP or VIP and mediates signaling between

SCN neurons. Figure A.3 depicts simulated intercellular coupling (Appendix D). In

addition, the role of the molecular noise was tested by a deterministic version of the same

proposed model. Strikingly, when a population of cells using the deterministic model

was coupled, rhythmicity could not be recovered at low activator levels (as would be the

case in Bmal1-/- tissues). Our analysis concludes that the noise alone could not restore the

rhythmicity in individual cells, nor is the coupling mechanism alone sufficient to induce

oscillations in a population of cells without noise. What is necessary to induce rhythms

in a population is both molecular noise and intercellular coupling.

All biochemical reactions are affected by molecular noise including the circadian

timing system. Molecular noise is a key contributor to the stochastic nature of

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intracellular rhythmicity (Elowitz and Leibler, 2000); and, overcoming the molecular

noise has been proposed as a key principle in the design of circadian clocks (Barkai and

Leibler, 2000). In some cases, biological systems can utilize noise to enhance their

function (Kaern et al., 2005). For example, the firing records of individual neurons are

often irregular, but when a group of these neurons are coupled in a network, inhibitory

coupling can permit shifting of the noise thereby reducing the noise at the frequencies of

interest. Hence, signal-to-noise ratio can be improved selectively for important

frequencies (Mar et al., 1999).

A novel finding in the modeling results is that molecular noise can be an integral

part of the functional SCN network. Molecular noise is amplified by a coupling

mechanism among SCN neurons and can ‘kick start’ oscillations within the network.

Future modeling work, using more detailed models of electrical (Bush and Siegelman,

2006; Sim and Forger, 2007) and chemical (Bernard et al., 2007; Hao et al., 2006; To et

al., 2007) signaling in the SCN, will be useful to identify the cause of noise-induced

oscillations.

The relative contribution of BMAL1 versus BMAL2 to circadian rhythmicity

remains to be determined. There seem to be substantial differences in the tissue

distributions of the two BMALs, as indicated by the relative concentrations of BMAL1

vs. BMAL2 transcripts in various human tissues (Maemura et al., 2000; Schoenhard et

al., 2002). BMAL1 expression is circadianly regulated, but the circadian variation in

mammalian BMAL2 expression has not been reported (Maemura et al., 2000; Okano et

al., 2001). Importantly, BMAL1 deficiency in mice results in the loss of behavioral and

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molecular circadian rhythms, indicating that BMAL1 and BMAL2 are not redundant in

their capacity (Bunger et al., 2000).

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CHAPTER 6. GENERAL DISCUSSION

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Over the last decade, there have been many significant advances in understanding

of the molecular genetic and cellular bases of circadian timing in mammals. The once

prominent role of the SCN as a master pacemaker driving and sustaining circadian

rhythms in peripheral tissues has been challenged; and it is now acknowledged that most

major organ systems and cell types contain local, autonomous circadian clocks. The

molecular mechanisms that sustain these local oscillators appear to function similarly to

those that are attributed to the SCN. Indeed, mutations in the canonical clock genes

produce altered periodicity in both the SCN and the periphery. Therefore, the role of the

SCN and even the definition of a “circadian system” have been re-written.

Still, peripheral oscillators are not wholly independent of the SCN despite their

existence in tissues throughout the body, and their ability to function as competent

clocks. They can operate in isolation and are settable without the SCN input, but they

remain subject to entrainment signals from the SCN. The transplant and parabiosis

experiments have demonstrated this relationship (Guo et al., 2005; Guo et al., 2006).

Therefore, the SCN remains atop the hierarchy of oscillators as a primary pacemaker that

orchestrates physiological systems into a circadian program that is synchronized with the

daily cycles of the environment.

Understanding how the SCN operates as a master conductor and how the

members of the orchestra (peripheral oscillators) respond to the signals from the SCN are

outstanding questions that have much relevance for an animal’s wellbeing as well as for

human health. As a first step, our strategy has been to understand the underlying

molecular mechanisms of the SCN and peripheral clock operations. Specifically, we

asked whether and in what ways the generation of circadian rhythms differs between the

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SCN and peripheral tissues by examining tissue-autonomous properties of the

mammalian circadian clock in genetically modified mice.

In Chapter 3, the role of the SCN as a master pacemaker was tested by

manipulating the expression of a regulatory component of the molecular circadian

clock (CK1ε, wild type and tau) in the brain. Using the tet system, the CK1ε expression

was controlled with anatomical and temporal specificity. The inducible expression of

CK1εtau affected the period of activity rhythms when expressed in the SCN, but did not

affect the tissue-autonomous rhythmic properties in the peripheral tissues. In Chapter 4,

real-time bioluminescence imaging of tissues from PER2::LUC mice revealed that period

and phase of the oscillators varied from tissue-to-tissue. Various circadian gene

mutations (Cry1-/-, Cry2-/-, Cry1-/-;Cry2-/-, and Clock∆19/∆19) produced little difference in

rhythmic properties between the SCN and peripheral oscillators, although Cry1-/- SCN

had more robust and persistent rhythms compared with the periphery. The loss of Bmal1,

however, eliminated rhythms in the peripheral tissues, but not in the SCN. This was

examined in detail in Chapter 5.

The continued generation of rhythms in the Bmal1-/- SCN was surprising given

that activity rhythms are abolished in the Bmal1-/- mouse. In addition, rhythmicity was

completely abolished in single SCN neurons from the Bmal1-/- mice, unlike the mutations

in other circadian genes. The rhythms generated by the Bmal1-/- SCN were highly

variable in both period and amplitude, fitting a stochastic model of rhythm generation.

The results indicate that rhythms in Bmal1-/- SCN tissue are a property of the cellular

organization of the SCN rather than the averaging of rhythms from a population of

single-cell autonomous clocks.

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The findings presented here support the conclusion that the SCN is organized

differently from the peripheral oscillators, and in such a way that circadian oscillations

are promoted by the anatomical organization of the nucleus itself. Thus, in the absence

of a functional molecular clock, the tissue can generate an approximate, albeit variable,

circadian cycle. There has been no previous evidence that SCN organization is necessary

for rhythm generation, as various types of single cells are capable of doing this.

However, the data presented in Chapters 4 and 5 show that rhythms from the SCN do not

damp as quickly at those from other tissues in the presences of different circadian gene

mutations. It seems likely that the coupling of cells and the organization of the

pacemaker ensemble in the SCN not only enables the retention of a weak rhythm in the

Bmal1-/- SCN, but also accounts for the reduced damping of rhythms from this tissue.

The organization itself may contribute to long-term stability of SCN function, thereby

providing a stronger and more accurate control over the temporal organization of the

circadian hierarchy.

The studies of the SCN in vitro, particularly the examination of Bmal1-/- cells,

also produced an unexpected finding in that accurate models of circadian organization

need to take into account molecular noise as well as intercellular coupling in the

molecular circadian clock. The coupling alone was not sufficient to reproduce the

physiological data presented in Chapter 5. The strictly deterministic model was

inadequate despite its complexity and the use of empirical data. Whereas there may not

be a definable purpose for noise in any system, it is important to acknowledge that it

exists. Furthermore, the noise will have an impact on mathematical models, especially as

the models become more refined and its components more precise.

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This unique organization of the SCN by no means obviates the need for the

molecular clock. The pace of a tissue oscillator is consistent with the average pace of the

single cells, and disruption of a clock component (genetic mutation) has similar effects on

the “speed” of the oscillators, both within and between different tissues. Still, peripheral

tissues in isolation display characteristic periods that can vary as much as ~2 hours from

the period of the SCN or from each other. Furthermore, these oscillators have been

shown to reset at different rates to a shifted environment (e.g., LD cycle). This suggests a

regulatory mechanism that is outside the primary circadian transcriptional feedback loop

that can modify the feedback process. One such mechanism may involve the secondary

loop composed of REV-ERBα and ROR, and another may involve the rate of

proteasomal degradation of circadian proteins.

As discussed previously, members of the Ror family show strikingly different

expression patterns across tissues with varying circadian peak times. Their influence on

rhythmic expression of BMAL1 could result in a tissue-specific setting or resetting of the

clock. It has been shown that in the absence of Rorc (loss-of-function mutation, -/-), not

only Bmal1, but also Cry1, Clock, and Npas2 transcriptions show blunted rhythm

amplitude in the liver. On another note, heat-shock protein 60 (Hsp60), arginine

vasopressin receptor 1A (AVP-V1a), and apolipoprotein C-III (Apoc3) also showed

reduced rhythm amplitude in these liver tissues from Rorc-/- mice. These results further

suggest a role for the REV-ERBα/ROR-secondary loop in systemic or tissue-specific

regulation of expression patterns of target genes (Liu et al., 2008).

The rate of degradation of circadian proteins certainly appears to have tissue-

autonomous effects in setting the period of the clock. Peripheral tissues from the tau

104

mutant mice show decreased magnitude of impact from the mutation: pituitary, lung and

kidney tissues exhibited ~2.5-hour shortening versus ~4-hour shortening observed in the

SCN; and, lung and kidney tissues showed accelerated rate of damping compared to the

SCN (Meng et al., 2008). In contrast to the period-shortening tau mutation, the recently

reported Fbxl3Ovtm (“Overtime”; also known as “After hours”, Afh) mutation results in

long-period phenotypes in mice, owing to a defect in targeting CRY1 and CRY2 for

degradation (Godinho et al., 2007; Siepka et al., 2007). A closer look at the reported

circadian period values from Afh mutant mice show that kidney and lung tissues from

these mice show greater period lengthening compared to the SCN or liver tissues

(Maywood et al., 2007).

These dynamics of period determination, however, do not convey the role of

peripheral oscillators and how they are coordinated in the intact organism. It is evident

that the SCN communicates phase information to peripheral oscillators, but the signals

from the SCN are not the only entraining cues. In fact, SCN can only weakly enforce

phase organization of peripheral oscillators. For examples, SCN resets rapidly to

advancing or delaying the LD cycle by 6 hours, while peripheral oscillators can take over

a week to resynchronize to the new cycle (Yamazaki et al., 2000); when animals are put

to RF paradigm, the daily timing of food availability overrides phase control of peripheral

oscillators by the SCN (Damiola et al., 2000; Stokkan et al., 2001); and, daily injection of

methamphetamine shifts Per expressions in the striatum without affecting its expression

in the SCN (Iijima et al., 2002). Thus, in certain situations, peripheral clocks appear to

prioritize systems-specific entraining cues over the cues from the SCN.

105

It has often been the case that findings of circadian property from one tissue (most

popularly, the SCN and liver) are generalized to the rest of the organism. Our results

caution this practice: 1) the contribution of intercellular coupling and molecular noise

make the SCN unique in the circadian oscillator hierarchy – the SCN network oscillator

is significantly different from other tissue oscillators; and 2) circadian operation of one

peripheral tissue oscillator appears to vary from another.

Understanding the molecular, genetic and cellular bases of both central and

peripheral circadian biology is therefore imperative to understanding how circadian

rhythm influences human physiology. Several studies have shown that circadian

disruptions contribute to disorders of diverse physiological processes (reviewed in

Hastings et al., 2003; and Takahashi et al., 2008; also see Appendix D, Table A.1).

These studies have relied on the use of gross experimental measures such as ablation of

the entire master circadian pacemaker, the SCN, or via genetic alterations of circadian

clock function in all tissues. These approaches consequently result, by and large, in

defective regulation of sleep-wake cycle, locomotor activity, hormonal regulation and

feeding behavior. The transgenic mouse models that permit tissue-specific conditional

regulation of circadian gene expression (such as the tet system) allow for a finer

dissection of the mechanisms that underlie systemic biology. Furthermore, combined

with real-time imaging, these approaches can now address the relative role of the local

control of circadian rhythms in peripheral tissues.

106

APPENDIX A

107

Figure A.1. Vector map for plasmid tetO-HA-CK1ε.

108

Hamster (Mesocricetus auratus) casein kinase I epsilon cDNA sequence (1251 base pairs)

1 ATGGAGCTGCGTGTGGGGAATAAGTACCGCCTGGGCCGAAAGATCGGCAG 50

51 TGGGTCCTTTGGAGACATCTACTTGGGTGCCAACATTGCCTCTGGTGAGG 100

101 AAGTAGCCATCAAACTCGAATGTGTGAAAACAAAGCACCCGCAGCTCCAC 150

151 ATAGAGAGCAAGTTCTACAAGATGATGCAAGGAGGAGTGGGGATCCCGTC 200

201 CATCAAGTGGTGCGGGGCTGAGGGTGACTACAATGTGATGGTCATGGAGC 250

251 TGCTGGGGCCCAGTCTCGAGGACCTCTTCAACTTCTGTTCCCGAAAGTTC 300

301 AGCCTCAAGACAGTGCTGCTGCTGGCCGACCAGATGATCAGCCGCATCGA 350

351 GTACATCCACTCCAAGAACTTCATCCACCGGGACGTGAAACCGGATAACT 400

401 TTCTCATGGGCTTGGGGAAGAAAGGCAACCTGGTCTACATCATTGACTTC 450

451 GGCCTGGCCAAGAAGTACCGTGATGCCCGCACCCACCAGCATATCCCCTA 500

*Site of Tau mutation (CT)

501 CCGGGAAAACAAGAACCTGACTGGCACTGCCCGCTATGCCTCCATCAACA 550

551 CCCACCTGGGCATCGAGCAAAGCCGTCGAGATGACCTGGAGAGCTTGGGC 600

601 TATGTGCTGATGTACTTCAACCTGGGCTCCCTGCCCTGGCAGGGTCTCAA 650

651 AGCCGCCACCAAGCGTCAGAAGTACGAGCGGATCAGTGAGAAGAAGATGT 700

701 CAACGCCCATTGAGGTCCTCTGCAAAGGCTACCCCTCCGAGTTCTCAACA 750

751 TACCTCAACTTCTGCCGCTCCCTGCGGTTCGATGACAAGCCCGACTACTC 800

801 CTACCTGCGCCAGCTCTTCCGCAACCTCTTTCACCGGCAGGGTTTCTCCT 850

109

851 ACGACTACGTCTTCGACTGGAACATGCTCAAATTCGGTGCAGCCCGGAAT 900

901 CCCGAGGACGTAGACCGGGAGCGACGAGAACACGAACGGGAAGAGAGGAT 950

951 GGGGCAGTTGCGGGGGTCCGCGACCAGAGCCCTGCCCCCTGGCCCACCCA 1000

1001 CAGGGGCTACTGCCAATCGACTCCGCAGTGCAGCCGAGCCTGTGGCTTCC 1050

1051 ACGCCTGCCTCTCGAATCCAGCAAGCTGGCAATACTTCTCCCAGAGCGAT 1100

1101 CTCACGGGCCGACCGGGAGAGGAAGGTGAGCATGCGACTCCACAGAGGCG 1150

1151 CACCTGCCAACGTCTCCTCCTCAGACCTCACTGGGCGGCAAGAGGTCTCC 1200

1201 CGGATTTCAGCCTCACAGACAAGCGTGCCATTTGACCATCTCGGGAAATG 1250

1251 A

110

111

112

APPENDIX B

113

In-situ Hybridization Protocol (From the laboratory of Dr. Joseph Takahashi)

Tissue fixation *do not fix tissue until probes are completely made* Supplies and equipment: • Timer • Vacuum desiccator • Stir plate & stirbar(s) • Slide rack(s) & transfer handle(s) • RNAse-free staining jars with covers • 4% Paraformaldehyde (chilled) • 0.1M Triethanolamine (TEA), pH 8.0 • 2X SSC • Acetic anhydride • RNAse-free H2O (treated with DEPC) • 50% EtOH • 75% EtOH • 95% EtOH • 100% EtOH Preparation / notes: 1. Paraformaldehyde should be chilled and used at 4-15˚C for fixation. 2. All fixation steps following the paraformaldehyde step are carried out at room

temperature. 3. Acetic anhydride degrades quickly when mixed with TEA; add acetic anhydride to

dry staining jar first and do not add TEA until slides are suspended in place (see below).

Fixation:

Time Reagent Reusable Notes 5-10 min

4% paraformaldehyde 2X at most

Vapors dangerous; dispose of in chemical waste

5 min 2X SSC Yes Dip 0.1M TEA, pH 8.0 Yes 10 min TEA/acetic anhydride No First add small stirbar and 1.0 mL

acetic anhydride to dry jar, then suspend slides above the stir bar and add 400 mL TEA; begin stirring immediately.

Dip 2X SSC Yes 3 min 50% EtOH Yes Dehydration series 3 min 75% EtOH Yes 3 min 95% EtOH Yes

114

3 min 100% EtOH Yes Desiccation: Place slide rack(s) in vacuum desiccator, hybridize after slides have dried but within 24 hrs. Preparation of RNA probe (Adapted from Ambion MAXIScript Kit Protocol) Transcription reaction: Add the following amounts of the indicated reagents in the order shown to a 1.5 mL microfuge tube:

Nuclease-free (DEPC-treated) dH2O up to 20 µL DNA template TBD 10x transcription buffer 2 µL 10 mM ATP 1 µL 10 mM CTP 1 µL 10 mM GTP 1 µL 33P-UTP (2000 Ci/mmol, NEN # NEG-607H) 5 µL Cold UTP *see below T7 RNA polymerase 2 µL *Cold UTP is added to make final UTP concentration of 4-50 µM depending on what specific activity of the final product you want.

Mix contents then incubate reaction for 1 hour at 37oC.

Removal of Template DNA: 1. To assure that the transcript does not protect its DNA template, denature the

transcription reaction at 95oC for 2 minutes then immerse in ice. 2. Add 1 µL DNase 1. 3. Incubate at 37oC for 15 minutes.

Purification of RNA probe: use Pharmacia ProbeQuant G50 spin columns. The desired activity range for in-situ probes is 1-5 x 107 cpm / mL hybridization solution. Hybridization Supplies and equipment: • Probe mix reagents as listed below • Cocktail reagents as listed below • 65˚C water bath • Vortex • Centrifuge • Incubator

115

• Incubation tray(s) • Heavyweight aluminum foil • Bench-kote (plastic-backed) • DEPC-H2O Preparation / notes: 1. Pre-heat incubator to appropriate hybridization temperature (Tm of probe – 20˚C).

47˚C is a standard hybridization temperature, but may not be appropriate for certain probes.

2. Cover incubation tray(s) with one layer of heavyweight aluminum foil and one layer of bench-kote (plastic side facing down, onto aluminum foil). Saturate bench-kote with DEPC water. Pre-heat tray(s) in incubator.

3. Add hybridization solution.

For 1 mL total hybridization solution, mix separately (all reagents RNAse-free): Probe mix Cocktail 75 µL yeast tRNA (10 mg/mL) 500 µL formamide 1-5 x 107 cpm labeled probe 60 µL 5M NaCl DEPC-H2O to 168 µL total 10 µL 1M Tris, pH 8.0 2 µL 0.5M EDTA 20 µL 50X Denhardt’s solution 200 µL 50% Dextran sulfate 10 µL 1M DTT 30 µL DEPC-H2O

1. Keep cocktail at ~ 42˚C (room temp acceptable but cocktail will be more viscous). 2. Heat probe mix to 65˚C for 5 min. to break down secondary structure, then store on

ice. Add to cocktail and vortex/centrifuge solution immediately before applying to slides.

3. Pipet hybridization mix down midline of each cover slip, lay slide upside-down onto cover slip, allowing the weight of the slide to distribute the mix over the sections. Avoid bubbles but do not apply pressure to cover slip or slide – this risks damaging the morphology of the tissue.

4. After the hybridization solution has spread evenly over the entire contact area of the slide/cover slip, flip each slide and cover slip over so that the cover slip is on top.

5. Incubate slides for 12-18 hrs at the appropriate hybridization temperature. Post-hybridization wash Supplies and equipment: • Slide rack(s) and handle(s) • Small forceps • EtOH dehydration series from fixation procedure (50%, 75%, 95%, 100%) • Water bath at 37˚C

116

• Water bath / shaker at 60˚C • 4X SSC • 2X SSC • 10 mg/mL RNAse A • 0.1X SSC • 1X SSC Preparation / notes: 1. Pre-heat water bath to 37˚C, add 2X SSC per jar and heat in water bath. Exact

volume of 2X SSC is necessary to ensure appropriate final concentration of RNAse A.

2. Pre-heat water bath / shaker to 60˚C, heat 0.1X SSC in bath. 3. Transfer slides from incubation trays to slide rack(s). Many of the cover slips will

slide off during this transfer step; remove the remaining cover slips with a forceps at the transfer between the two 4X SSC steps.

4. Thaw and add RNAse A to the jar of 2X SSC immediately before inserting slide rack. Wash protocol:

Time Reagent Temp. Reusable Notes 10 min 4X SSC RT No Dispose of contents in radioactive

waste. After this step, remove any remaining cover slips with forceps. Soak jars in a Contrad or Radiacwash solution overnight to decontaminate.

10 min 4X SSC RT No 30 min 2X SSC +

RNAse A 37˚C No Thaw and add RNAse A to 2X

SSC immediately before inserting slide rack.

30 min 2X SSC 37˚C No 30 min 0.1X SSC 60˚C No Shake gently 10 min 1X SSC RT No 3 min 50% EtOH RT Yes Dehydration series 3 min 75% EtOH RT Yes 3 min 95% EtOH RT Yes 3 min 100% EtOH RT Yes

Desiccation: Place slide rack(s) in vacuum desiccator until ready to proceed to autoradiography. Be sure that slides are completely dry before proceeding to the next step; any moisture on the slides will ruin the emulsion on the autoradiography film. Image analysis Supplies and equipment: • High resolution 35mm film scanner (Polaroid SprintScan 35 Plus)

117

• Image acquisition software (i.e. Adobe Photoshop) • Image analysis software (i.e. NIH-Image)

Preparation / notes: • Scans films at 2700 dpi and 8-bit grayscale image depth; at these settings, each image

uses 10.4 MB of disk space. • Use NIH-Image v1.61 for image analysis. This application is available for free

download from the NIH-Image home page: http://rsb.info.nih.gov/nih-image/ Separate application (Adobe Photoshop) is used for image acquisition because of an incompatibility between the Polaroid scanner driver and NIH-Image.

Calibration: 1. Select 3rd degree polynomial for line type. 2. Check to see that the indicated “R2” value is as close as possible to 1.00 (generally

0.95 to 0.99). If this value is lower, the calibration will yield less accurate results; this is often a result of long exposure times in which the bands of greatest activity saturated the film. In these instances, disregard the saturated bands and go with a calibration with fewer values. Another option is to measure an area on the film of zero activity and use this as a “zero” point in the calibration.

Image Analysis – SCN Quantitation: 1. Using the ellipse tool, select the area of the SCN you want to quantify. 2. Select Analyze, Measure or press “Command-1”. 3. Move the ellipse from the selected area to a region of the left lateral hypothalamus for

background measurement. On screen, this is typically about 1.5-2” away from the SCN, 45º dorsolaterally.

4. Measure the region. 5. Repeat on the right brain of the same section. Reagent preparation Note: All reagents listed should be prepared in RNAse-free glassware and with RNAse-free equipment (i.e. stirbars, spatulas, etc.). DEPC (diethyl pyrocarbonate)-H2O, 1 L:

1. In fume hood, add 1 mL DEPC to 1 L ddH2O contained in a screw-top, autoclavable bottle.

2. Fasten top securely and shake vigorously to mix the DEPC with the H2O. 3. Vent bottle and allow it to sit in hood overnight with top partially unscrewed. 4. Autoclave water bottles to inactivate DEPC.

4% buffered paraformaldehyde, 1 L:

1. Combine: 2.6 g monobasic sodium phosphate 21.7 g dibasic sodium phosphate 800 mL DEPC-H2O

118

2. Stir on hot plate, bring solution to 50-60˚C. 3. Add 40.0 g paraformaldehyde, stir for 5 min or until paraformaldehyde is in

solution. 4. Add 5-20 NaOH pellets to clear solution. 5. Let solution cool to RT. 6. Bring pH to 7.4. 7. Bring total volume to 1 L with DEPC-H2O and filter; store at 4˚C.

0.1M TEA (triethanolamine), 1 L:

1. Add 18.56 g TEA to 900 mL DEPC-H2O. 2. Bring pH to 8.0. 3. Bring total volume to 1 L with DEPC-H2O.

20X SSC (saline sodium citrate), 2 L:

1. Combine: 350.6 g NaCl 176.4 g sodium citrate 1.5 L DEPC-H2O

2. Adjust pH to 7.0. 3. Bring total volume to 2 L with DEPC-H2O.

119

APPENDIX C

120

Figure A.2. PER2::LUC bioluminescence records from wild type (A) and Bmal1-/-

(B) olfactory bulbs. The olfactory bulb from Bmal1-/- show loss of circadian rhythmicity

and fail to show stochastic rhythms observed in the SCN.

121

APPENDIX D

122

Figure A.3. Schematic diagram of simulated intercellular coupling.

The CLOCK:BMAL complex activates production of coupling agents (CA; e.g., VIP or

AVP). CAs are secreted and act on cell-surface receptors on neighboring SCN neurons,

triggering cell-signaling pathways. The final product of the receptor pathways, CREB,

binds to a CRE element upstream of PER.

PKA: Protein kinase A, a cAMP activated protein kinase; CRE: cAMP response element;

CREB: CRE binding protein, a transcription factor.

123

APPENDIX E

124

Table A.1. Mouse circadian mutants and observed circadian and physiological phenotypes.

Gene Circadian phenotype Ref. Associated physiological abnormality Ref.

Bmal1/Mop3 (Arntl)

Null mutant

Loss-of-circadian activity rhythm in DD [1]

Infertility

Decreased adult body weight Increased tendon calcification

Abnormal gluconeogenesis and lipogenesis

Hypersensitive to chemotherapeutic agent

Premature aging syndrome Increased sleep fragmentation

[1-8]

ClockΔ19 Antimorph

Semidominant, 4 hr longer period

followed by loss-of-circadian activity rhythm

in DD

[9]

Hyperphagic & Obese

Abnormal gluconeogenesis Hypersensitive to

chemotherapeutic agent Enhanced response to cocaine

Mania phenotype Decreased duration of sleep

time

[3,7,10-12]

Clock

Null mutant

0.5 hr shorter period [13] ND

Npas2/Mop4 Null mutant

0.2 hr shorter period [14]

Impaired memory

Reduced sleep amount during night time

[14-15]

Clock & Npas2

Double null mutant

Complete loss of circadian activity rhythm in DD [16] ND

Per1 Null mutant

0-0.5 hr shorter period/

some animals lose circadian activity rhythm in DD

[17-19]

Lack of sensitization to

cocaine

[20]

Per2 Per2tm1Brd

Null mutant

1.5 hr shorter period and tendency for loss of

circadian rhythm [18,21]

Increased tumor development

following genotoxic stress Hyper-sensitization to cocaine

Improper alcohol intake Early onset of sleep

[20,22-24]

125

Per1 & Per2 Double null

mutant

Complete loss of circadian activity rhythm in DD

[17-18] ND

Per3

Null mutant

0-0.5 hr shorter period [25]

ND

Cry1

Null mutant

1 hr shorter period [26-27] ND

Cry2

Null mutant

1 hr longer period [28]

ND

Cry1 & Cry2 Double null

mutant

Complete loss of circadian activity rhythm in DD

[26-27]

Delayed hepatocyte

regeneration Resistant to chemotherapeutic

agent’s toxicity Increased NREM sleep drive

[3,22,29]

CK1ε

(Csnk1e) tau mutant

Semidominant, 4 hr shorter period [30]

Reduced growth rate

Enhanced metabolic rate

[31-32]

CK1δ

(Csnk1d) Null mutant

ND Postnatal (within days) lethal [33]

CK1δ

(Csnk1d) T44A mutant

0.5 hr shorter period [33] ND

Rev-erbα (Nr1d1)

Null mutant

0.5 hr shorter period/ Altered photic entrainment [34] ND

Rora Staggerer mutant 0.5 hr shorter period [35]

Cerebellar ataxia

Abnormal bone metabolism

[36-37]

Rorb Null mutant 0.5 hr longer period [38]

Locomotor difficulties

Retinal degeneration/blind Male reproductive abnormality

during first 6 mo of age

[38]

126

Rorc

Null mutant

ND

Disrupted lymphoid organ

development

[39-40]

Timeless

Null mutant

ND Embryonic lethal [41]

Dec1/Stra13/

Sharp2/Clast5 (Bhlhb2)

Null mutant

No circadian deficit in clock gene expression [42]

Impaired T lymphocyte

activation Age-related autoimmune

disease Defect in skeletal muscle

regeneration following injury

[43-44]

Melanopsin

(Opn4) Null mutant

Reduced phase-shift response to light

[45-46]

Diminished pupilary light reflex [47]

Vip Null mutant

Abnormal entrainment to

LD cycles Dissociated circadian

wheel-running rhythms in DD

Reduced amplitude in behavioral rhythms in DD

[48-49]

Impaired temporal regulation of

metabolism and feeding [50]

Vipr2 Null mutant

Abnormal entrainment to

LD cycles Dissociated circadian

wheel-running rhythms in DD

Reduced amplitude in behavioral rhythms in DD Impaired responses to light

[48,51] Impaired temporal regulation

of metabolism and feeding

[50]

Nocturnin (Ccrn41)

Null mutant

No circadian behavioral deficits [52]

Resistance to diet-induced

obesity

[52]

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