Circadian Rhythms and Biological Clocks Part B (eBook)

Amita Sehgal (Herausgeber)

eBook Download: PDF | EPUB

2015 | 1. Auflage
414 Seiten
Elsevier Science (Verlag)
978-0-12-803381-4 (ISBN)

Infos

Two new volumes of Methods in Enzymology continue the legacy of this premier serial with quality chapters authored by leaders in the field. Circadian Rhythms and Biological Clocks Part A and Part B is an exceptional resource for anybody interested in the general area of circadian rhythms. As key elements of timekeeping are conserved in organisms across the phylogenetic tree, and our understanding of circadian biology has benefited tremendously from work done in many species, the volume provides a wide range of assays for different biological systems.  Protocols are provided to assess clock function, entrainment of the clock to stimuli such as light and food, and output rhythms of behavior and physiology.  This volume also delves into the impact of circadian disruption on human health.  Contributions are from leaders in the field who have made major discoveries using the methods  presented here.

• Continues the legacy of this premier serial with quality chapters authored by leaders in the field
• Covers research methods in biomineralization science
• Keeping with the interdisciplinary nature of the circadian rhythm field, the volume includes diverse approaches towards the study of rhythms, from assays of biochemical reactions in unicellular organisms to monitoring of behavior in humans.

Inhalt

Front Cover 1
Circadian Rhythms and Biological Clocks, Part B 4
Copyright 5
Contents 6
Contributors 12
Preface 18
Part I: Dissecting the Central Clock Circuit 20
Chapter One: Measuring Synchrony in the Mammalian Central Circadian Circuit 22
1. Introduction 23
1.1. What is synchrony? 23
1.2. What is circadian synchrony? 23
1.3. Goals of this review 24
2. Monitoring SCN Rhythms with Cellular Resolution 25
3. Isolating Data from Single Cells 25
4. Defining a Rhythm 28
4.1. Plotting rhythmic data for visual inspection 28
5. Period Synchrony: Methods to Extract and Compare Periods Between Cells 29
5.1. Do cells share the same period? 34
6. Phase Synchrony: Methods to Extract and Compare Phase Relationships Between Cells 35
7. Perturbations Reveal Synchronization Mechanisms 36
8. Methods Awaiting Application in Circadian Biology 36
9. Step-by-Step Instructions for Measuring Synchrony in SCN Slice 37
9.1. Bioluminescence recordings using a charge-coupled device camera 37
9.2. Image processing 37
9.3. Single-cell tracking 37
9.4. Data presentation 38
Acknowledgments 38
References 38
Chapter Two: Patch-Clamp Electrophysiology in Drosophila Circadian Pacemaker Neurons 42
1. The Drosophila Circadian Network 42
2. Circadian Control of Neuronal Activity 46
2.1. Intrinsic currents 47
2.2. Synaptic currents 47
3. Methods for Patch-Clamp Electrophysiology 49
3.1. Equipment 50
3.2. Solutions 51
3.3. Drosophila brain dissection 52
3.4. Recordings 52
3.5. Assessing the quality of the recording 53
3.6. Relevant data in current clamp 55
3.7. Relevant data in voltage clamp 56
4. Conclusion 58
Acknowledgments 58
References 58
Chapter Three: Glial Cell Regulation of Rhythmic Behavior 64
1. Introduction 65
2. Studies of Glial Cell Function in Circadian Behavior and Sleep 66
2.1. Glia and circadian behavior 66
2.2. Mammalian astrocytes and the sleep homeostat 69
2.3. Glia-neuron communication regulates Drosophila sleep 70
2.4. Microglial clocks, synaptic strength, and sleep 72
3. Potential Circadian Glia-Neuron Signaling Molecules 73
3.1. Glial clocks and ATP rhythms 73
3.2. Glial neurotrophic factors and cytokines in circadian behavior 75
3.3. Secreted molecules mediating glia-neuron communication in Drosophila 77
4. Molecular Genetic Strategies for Studying the Glial Regulation of Drosophila Rhythms 78
4.1. Glia-selective genetic perturbation methods 78
4.2. Glial expression profiling and cell-specific targeted genetic screens 79
4.3. Glial microRNAs as regulators of rhythmicity 80
Appendix A. Protocol for TRAP Profiling of Fly Glial Cells 82
A.1. Bead preparation 83
A.2. Sample preparation 84
A.3. Immunoprecipitation 84
A.4. RNA extraction for RNA-seq library preparation 84
A.5. Reagents 85
References 86
Chapter Four: Neurophysiological Analysis of the Suprachiasmatic Nucleus: A Challenge at Multiple Levels 94
1. Introduction 95
2. Part I: Clock Mechanisms at the Cellular Level 96
2.1. The molecular feedback loops and beyond 96
2.2. Cytosolic oscillators 97
2.3. Role of neuropeptides 98
2.4. Circadian modulation of excitability 99
2.5. The road back: Neuronal activity impacts clock gene expression 100
3. Part II: The SCN as a Multi-Oscillator 101
3.1. Using acute slice preparations to study phase resetting 101
3.2. Using acute slices to study photoperiod-encoding mechanisms 104
3.3. Using acute slices to study synchronization within the SCN 106
3.4. Rescue of single-cell deficiencies by the neuronal network 107
4. Part III: In Vivo Electrophysiology Recordings from the SCN in Anesthetized and Freely Moving Animals 107
4.1. Example1: In vivo electrophysiology studies of photic entrainment 109
4.2. Example2: In vivo studies indicate influence of behavioral activity and sleep stage on the SCN 110
5. Conclusions 112
Acknowledgments 114
References 114
Part II: Entrainment of Central and Peripheral Clocks 122
Chapter Five: Photic Entrainment in Drosophila Assessed by Locomotor Activity Recordings 124
1. Introduction 125
2. Different Light Regimes Used to Entrain Locomotor Activity of Fruit Flies 126
2.1. Rectangular light-dark cycles 126
2.1.1. 12h light and 12h darkness 127
2.1.2. Long and short photoperiods 128
2.1.3. Varying light intensity or wavelength 128
2.1.4. Light-moonlight cycles 129
2.2. Simulating gradual changes in light intensity 130
2.2.1. Simulating dawn and dusk 130
2.2.2. Simulating more natural conditions 130
3. Methods to Measure Locomotor Activity 131
3.1. Home-made recording systems 131
3.2. Commercially available Trikinetics system 132
3.3. Camera-based recording system 132
4. Data Analysis and System Comparison 134
4.1. Designing actograms 134
4.2. Creating average activity profiles 135
4.3. Further analyses based on average days of individual flies 137
4.3.1. Calculating activity levels 137
4.3.2. Analysis of morning anticipation 139
4.3.3. Determining M and E peaks 139
4.3.4. Siesta determination 140
References 140
Chapter Six: Photic Regulation of Clock Systems 144
1. Introduction 145
2. The Suprachiasmatic Nuclei 145
3. The Molecular Circadian Clock 146
4. Peripheral Clocks 146
5. Photoentrainment and Melanopsin 148
6. Entrainment of the Molecular Clock 150
7. Molecular Photoentrainment 152
8. Studying the Effects of Light on the Circadian Clock 154
8.1. Locomotor activity 154
8.1.1. Entrainment to light-dark cycle 154
8.1.2. Period (tau) in constant dark or constant ligh 154
8.1.3. Phase shifting 155
8.1.4. Negative masking 156
8.2. SCN gene induction 156
8.3. Clock gene reporter transgenics 156
8.4. In vivo electrophysiology 157
9. Conclusions 157
Acknowledgments 158
References 158
Chapter Seven: Response of Peripheral Rhythms to the Timing of Food Intake 164
1. Introduction 165
2. Animal Strain and Age 168
3. Animal Room and Equipment 168
4. Facilities to Accommodate Feeding Schedule 169
5. Diet 170
6. Monitoring Eating Pattern 171
7. Physiological Readout of Eating Pattern 172
8. Feeding Paradigms 173
8.1. Assessing the pace of resetting of peripheral clock to a change in eating pattern 173
8.2. Assessing the contribution of circadian clock and feeding pattern on peripheral molecular rhythms 174
8.3. Amplitude and phase of expression of peripheral clock under timed feeding or ad libitum condition 175
9. Mouse Tissue Collection 176
10. Transcript, Protein, and Metabolome Expression Analysis 177
11. Conclusion 177
References 178
Part III: Clocks and Metabolic Physiology 182
Chapter Eight: Circadian Regulation of Cellular Physiology 184
1. Introduction 185
2. Materials 186
2.1. Circadian in vitro studies (in synchronized C2C12 myotubes) 186
2.2. Circadian in vivo studies (48h constant darkness experiments in mice) 187
3. Methods 188
3.1. Circadian in vitro cell-based methods (in synchronized C2C12 myotubes) 188
3.1.1. Advantages of cell-based models to test circadian control of metabolism 188
3.1.2. Circadian control of mitochondrial bioenergetics 189
3.1.3. In vitro bioenergetics measurements in synchronized cells 190
3.2. In vivo bioenergetics measurements-48h DD mouse collection 196
4. Notes 199
4.1. Circadian in vitro cell-based methods 199
4.2. In vivo bioenergetics measurements-48h DD mouse collection 200
Acknowledgments 201
References 202
Chapter Nine: Analysis of the Redox Oscillations in the Circadian Clockwork 204
1. Introduction: Circadian and Redox Coupling in the Cell 205
2. The Biochemical Properties of the Peroxiredoxin System 208
2.1. The catalytic cycle of peroxiredoxins 208
2.2. Oxidative inactivation and oligomerization 211
3. Analysis of PRX Redox Oscillations 214
3.1. Methodology and important considerations 214
3.2. Protocol 217
3.2.1. Sample preparation 217
3.2.1.1. Cultured cells 217
3.2.2. Gel electrophoresis and protein transfer to nitrocellulose membranes for blotting 220
3.2.3. Immunoblotting 221
3.2.4. Normalization and controls 224
3.2.5. Alternative methods for the measuring of PRX overoxidation 225
3.3. Example: Circadian cycles of PRX oxidation in fruit flies 226
Acknowledgments 226
References 226
Chapter Ten: Clocks and Cardiovascular Function 230
1. Introduction 231
2. Circadian Analysis of Physiological Parameters with Radiotelemetry 233
3. Primary Cell Culture of Macrophages 234
3.1. Peritoneal macrophage culture 234
3.2. Bone marrow-derived macrophages 235
4. Circadian Variation in Thrombogenesis 237
4.1. Time to vessel occlusion 237
4.2. Real-time fluorescence intravital microscopy quantification of thrombosis 239
5. Atherosclerosis and Vascular Integrity in Models of Clock Disruption 240
5.1. En face analysis of aortas 241
5.2. Aortic root sectioning and staining 241
5.3. Wire-mediated vascular injury 242
6. Clocks and Myocardial Dysfunction 243
6.1. Mouse echocardiography 243
6.2. Isolation of adult ventricular mouse cardiomyocytes 244
7. Conclusion 245
References 245
Part IV: Circadian Rhythms in Humans 248
Chapter Eleven: Measuring Circadian Clock Function in Human Cells 250
1. Introduction 251
2. Studies of Circadian Clock Properties Using Reporters 252
3. Ex Vivo and In Vitro Studies of Human Circadian Clocks 255
4. Similar Technologies to Study Other Major Signaling Pathways 256
5. Cell-Based Approaches to Study Gene Expression Variation and Human Interindividual Differences in Drug Responses 258
6. Promise of In Vitro Gene Expression Profiling 261
7. Specific Protocols 263
7.1. Cell lines for the measurement of human circadian properties 263
7.2. Generation and production of lentiviral vectors 264
7.3. Transduction of primary skin fibroblasts and real-time bioluminescence measurement of human circadian properties in ... 264
7.4. Bioluminescence measurement of the transcriptional activation of different signaling pathways 265
7.5. Use of lentiviral reporters in longitudinal in vivo imaging of signaling pathways within a growing tumor 266
8. Perspectives 267
Acknowledgments 268
References 268
Chapter Twelve: Human Activity and Rest In Situ 276
1. Introduction 277
2. Probing Activity and Sleep by Questionnaires 278
2.1. The Munich ChronoType Questionnaire 278
2.2. The power of big numbers 279
2.2.1. Chronotype and development 281
2.2.2. Chronotype and light exposure 282
2.3. The concept of social jetlag 284
3. Measuring Activity and Sleep by Actimetry 286
3.1. The method of actimetry 286
3.2. Specialized software 287
3.3. Viewing activity time series 289
3.4. Trends and smoothing 291
3.5. Applying cosine fits 291
3.6. Averaged daily profiles 293
3.7. Detecting sleep in activity 295
4. Concluding Remarks 297
References 300
Chapter Thirteen: Phenotyping of Neurobehavioral Vulnerability to Circadian Phase During Sleep Loss 304
1. Prevalence and Consequences of Sleep Loss 305
2. Sleep-Wake and Circadian Regulation: Two-Process Model 305
3. Subjective and Objective Measures for Circadian Variation in Performance 310
4. Circadian Variation Assessment in Neurobehavioral Functions 311
5. Sleep Deprivation and Performance 313
6. Cumulative Effects on Performance from Chronic Sleep Restriction 314
7. Phenotypic Individual Differences in Response to Sleep Deprivation 316
8. The PVT: Example of a Behavioral Assay for Phenotyping Responses to Sleep Loss 319
9. Conclusions 320
Acknowledgments 322
References 322
Chapter Fourteen: Genetics of Human Sleep Behavioral Phenotypes 328
1. Introduction 328
2. Clinical Phenotyping 330
2.1. Overview 330
2.2. Methods 330
2.2.1. Recruitment and sampling of potential affected subjects 330
2.2.2. Self-reports and interviews 331
2.2.3. Physiological measurements for circadian rhythm 333
3. Identification of Associated Genetic Variants 334
3.1. Overview 334
3.2. Methods 335
3.2.1. Collecting DNA samples 335
3.2.2. Mapping the locations of the associated genetic variants by linkage analysis 335
3.2.3. Identify the associated genetic variants 336
4. Modeling Human Sleep Phenotypes in Rodents 337
4.1. Overview 337
4.2. Methods 337
4.2.1. Generation of mouse models 337
4.2.2. Sleep phenotyping of mouse models 338
5. Concluding Remarks 340
Acknowledgments 341
References 341
Chapter Fifteen: Sleep and Circadian Rhythm Disruption and Recognition Memory in Schizophrenia 344
1. Introduction 345
2. Sleep and Circadian Rhythm Disruption in Schizophrenia 346
2.1. Patients 346
2.2. Schizophrenia-relevant mouse models 346
2.3. Using running wheels to assess rest–activity rhythms: A cautionary note 348
3. Recognition Memory Deficits in Schizophrenia 348
3.1. Patients 348
3.2. Schizophrenia-relevant mouse models 350
4. Recognition Memory Deficits After the Direct Manipulation of Sleep and Circadian Rhythms 353
4.1. Sleep deprivation 353
4.2. Abnormal photic input 353
4.3. Core clock gene manipulation 354
5. Dual-Process Theory of Recognition 355
5.1. Hippocampus-dependent, recollection-like mechanism 356
5.2. Perirhinal cortex-dependent, familiarity-based mechanism 356
6. Which is Impaired, Recollection or Familiarity? 357
6.1. Recognition memory deficits in schizophrenia-relevant mouse models 357
6.2. Recognition memory deficits after the direct manipulation of sleep and circadian rhythms 358
7. Is There an Association Between Sleep and Circadian Function and Recognition Memory in Schizophrenia? 358
7.1. Human studies 358
7.2. Animal studies 359
8. Summary of the Chapter and Some Unresolved Issues 360
Acknowledgments 361
References 361
Author Index 370
Subject Index 404
Color Plate 415

Textauszug

Chapter One

Measuring Synchrony in the Mammalian Central Circadian Circuit

Erik D. Herzog*,1; István Z. Kiss†; Cristina Mazuski*    * Department of Biology, Washington University, St. Louis, Missouri, USA
† Department of Chemistry, Saint Louis University, St. Louis, Missouri, USA
1 Corresponding author: email address: [e-mail]

Abstract

Circadian clocks control daily rhythms in physiology and behavior across all phyla. These rhythms are intrinsic to individual cells that must synchronize to their environment and to each other to anticipate daily events. Recent advances in recording from large numbers of cells for many circadian cycles have enabled researchers to begin to evaluate the mechanisms and consequences of intercellular circadian synchrony. Consequently, methods have been adapted to estimate the period, phase, and amplitude of individual circadian cells and calculate synchrony between cells. Stable synchronization requires that the cells share a common period. As a result, synchronized cells maintain constant phase relationships to each (e.g., with cell 1 peaking an hour before cell 2 each cycle). This chapter reviews how circadian rhythms are recorded from single mammalian cells and details methods for measuring their period and phase synchrony. These methods have been useful, for example, in showing that specific neuropeptides are essential to maintain synchrony among circadian cells.

Keywords

Circadian

Fourier transform

Period gene

Vasoactive intestinal polypeptide

Rayleigh plot

Synchronization Index

1 Introduction

1.1 What is synchrony?

When a good marching band enters the field, the players step at exactly the same moment. The drummers keep time so that each band member synchronizes their paces to their neighbors’. The musicians perform with the same period. As they march across the field, the line of trumpeters might arrive at midfield first followed by, perhaps, the trombonists. The trombonists share the same period as the trumpeters, but are phase delayed in their time of arrival. In this way, they synchronize their periodicity while assuming unique phase relationships. Period synchrony (also called frequency entrainment) does not require oscillators to peak together. Instead, synchronized oscillators can establish unique, and stable, phase relationships with other oscillators in the population (phase synchrony or phase locking). In nature, noise (internal and external to the oscillators) introduces a small, bounded variation in the phase differences. Many studies of mechanical, electrical, chemical, and biological oscillators have focused on mechanisms that can produce period synchrony and conditions that can alter phase synchrony (Pikovsky, Rosenblum, & Kurths, 2003; Strogatz, 2003).

1.2 What is circadian synchrony?

Daily changes at both cellular and systemic levels arise from biological oscillators that keep near 24-h rhythms and entrain to the 24-h cues associated with day and night. These self-sustained circadian rhythms are intrinsic to individual cells. The period of the individual cells depends predominantly on their genetics and light–dark history, and less so on the ambient temperature (i.e., their period is temperature compensated) or other environmental inputs. These cells must synchronize to each other and the environment to coordinate daily rhythms including feeding-fasting, waking–sleeping, hormone levels, metabolism, and gene expression. Circadian synchrony describes when cells (or organisms) express the same, near 24-h period (Bloch, Herzog, Levine, & Schwartz, 2013). Much like the synchronized marching of a band of musicians, circadian clocks are often comprises populations of cells that share the same daily period, but with some cells leading (by up to 12 h) other cells. Critically, oscillators may share the same period and a constant phase relationship for one of three reasons: (1) they communicate with each other, (2) they both receive the same synchronizing signal from other cells or the environment, or (3) coincidence. By measuring circadian synchrony following a perturbation, we can distinguish whether cells are entraining each other, to their environment, or simply express the same near 24-h period by chance.

Synchrony among circadian cells has been described in single-celled organisms like cyanobacteria and dinoflagellates and metazoans including plants, fungi, flies, and rodents. In a few cases, there is evidence that the synchrony arises primarily due to environmental inputs (e.g., cyanobacteria, dinoflagellates, and plants) while cells in other systems appear to have evolved the ability to synchronize to each other (e.g., fungi, flies, and rodents).

To illustrate how to measure and use synchrony in a circadian system, this chapter will focus on the mammalian suprachiasmatic nucleus (SCN). The SCN of mice and humans contains approximately 20,000 cells with many of them functioning as individual self-sustained circadian oscillators. SCN cells receive information about local day–night changes indirectly from other cell types. For example, the cells of the SCN normally entrain to input from the retina and other brain areas so that their peak metabolism and electrical activity occur during the day. For the SCN to function as a circadian pacemaker, individual SCN cells must synchronize to each other to coordinately drive rhythms in neural activity and transmitter release. Strikingly, the degree of phase synchrony among SCN cells can change with conditions. During short winter days, for example, SCN cells tend to peak together whereas, they spread out their times of peak activity during the long days of summer.

1.3 Goals of this review

This chapter aims to review how to measure synchrony between circadian cells with a focus on analyzing single-cell SCN slice bioluminescence recordings. Briefly, we summarize methods for discriminating circadian rhythms from single cells. We then discuss the strengths and weaknesses of independent methods that quantify period and phase synchrony among a population of oscillating cells. Finally, we provide examples of how perturbations affect cell–cell synchrony in the SCN.

2 Monitoring SCN Rhythms with Cellular Resolution

To study synchrony among SCN cells, researchers have used a variety of direct and indirect indicators of circadian physiology. The best methods share the following features: (1) relatively noninvasive monitoring of single-cell physiology, (2) high-frequency sampling for more than 4 days, (3) sensitive enough to detect circadian rhythms above background, (4) a dynamic range that allows recording of daily, biological changes without saturating, and (5) can be combined with genetic or pharmacological perturbations. To date, circadian synchrony has been assessed based on daily rhythms in cytosolic calcium, gene expression, firing rate, and cAMP activity (Table 1). Figure 1 illustrates a representative, long-term recording of PERIOD2 (PER2) protein levels from SCN neurons using the PER2-luciferase (PER2::LUC) knockin reporter.

Table 1

Methods that have been used to monitor circadian rhythms with cellular resolution

Intracellular calcium

Fluorescent calcium-sensitive reporter

Yellow Cameleon 2.1 or 3.6 or 6.0, or GCaMP3-WPRE

0.5 s every 60 min

Brancaccio, Maywood, Chesham, Loudon, and Hastings (2013), Ikeda and Ikeda (2014), Ikeda et al. (2003), Enoki, Kuroda, et al. (2012), Enoki, Ono, Hasan, Honma, and Honma (2012), and Irwin and Allen (2013)

Gene expression

Bioluminescent (luciferase) or fluorescent (e.g., destabilized GFP) reporter of transcription or translation

Per1::Luc, Per1:GFP, Per1-Venus, PER2::LUC, Per2-DsRED, or Bmal1::Luc

Integrated over 15–60 min

Day and Schaufele (2008), Hastings, Reddy, McMahon, and Maywood (2005), Herzog, Aton, Numano, Sakaki, and Tei (2004), Welsh, Imaizumi, and Kay (2005), Welsh and Kay (2005), Welsh and Noguchi (2012), Yoo et al. (2004), Cheng et al. (2009), Kuhlman, Quintero, and McMahon (2000), Yamaguchi et al. (2003), and Yamazaki et al. (2000)

Firing rate

Multielectrode array

MEA 60 or MED 64

Sampled every 50 μs to report spikes per second

Herzog (2007) and Honma et al. (2011)

cAMP activity

Bioluminescent (luciferase) reporter of CREB activity or fluorescent (e.g., destabilized GFP) reporter cAMP levels

CRE::Luc, ELISA kit, or ICUE2

Integrated over 60 min

Brancaccio et al. (2013), An, Irwin, Allen, Tsai, and Herzog (2011), and O'Neill, Maywood, Chesham, Takahashi, and Hastings (2008)

Figure 1 Recording circadian rhythms in gene expression from a SCN slice culture. (A) An image of a SCN carrying the PER2::Luc reporter construct with two representative cells encircled with regions of interest (ROI). With single-cell resolution, at least 100 ROIs can be identified from...

Produkt-Details

• Erscheint lt. Verlag: 24.2.2015
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie
• Themenwelt: Naturwissenschaften ► Biologie ► Biochemie
• Themenwelt: Naturwissenschaften ► Biologie ► Humanbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Zoologie
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Angewandte Physik
• ISBN-10: 0-12-803381-9 / 0128033819
• ISBN-13: 978-0-12-803381-4 / 9780128033814