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«Connectivity, Organization, and Network Coordination of the Drosophila Central Circadian Clock by Zepeng Yao A dissertation submitted in partial ...»

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Connectivity, Organization, and Network Coordination of the Drosophila

Central Circadian Clock

by

Zepeng Yao

A dissertation submitted in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

(Molecular, Cellular and Developmental Biology)

in the University of Michigan

Doctoral Committee:

Associate Professor Orie T. Shafer, Chair

Assistant Professor Sara J. Aton

Professor Daniel B. Forger

Professor John Y. Kuwada

Professor Haoxing Xu © Zepeng Yao All rights reserved DEDICATION In Loving Memory of Grandma and Grandpa ii

ACKNOWLEDGEMENTS

First and foremost, I would like to express my deepest gratitude to my advisor, Dr. Orie Shafer. Orie is enthusiastic, patient, and fun. I am very fortunate to be one of his first students and have received lots of scientific training directly from him. Orie has given me tremendous freedom to explore my scientific interests and provided enormous support to my research throughout the years. Orie is very dedicated to the career development of his students. He spent countless hours helping with my presentations and editing my proposals and manuscripts.

Working with Orie has always been exciting and rewarding.

I would also like to express my sincere gratitude to Dr. Rich Hume. I have collaborated with Rich on the electrophysiological characterization of clock neurons over the past two years.

Rich taught me everything about electrophysiology from scratch. I am extremely fortunate again to have received training directly from him. Besides, Rich has given me lots of valuable advice on my research as well as my future career.

In addition, I would like to thank all of my committee members, Dr. John Kuwada, Dr.

Haoxing Xu, Dr. Sara Aton, and Dr. Daniel Forger for their support, critiques, and insightful discussions on my thesis research. Special thanks to Sara for the millions of reference letters she has written for me over the years.

My sincere thanks go to every current and former member of the Shafer Lab. I would like to specially thank Katie Lelito, Ann Marie Macara, and Tamara Minosyan for collaborating on the neural circuit analysis project, my first research project in the Shafer Lab. I thank Amy iii Bennett for working closely with me over the past few years and for her assistance on my research. I thank Qi Zhang, Charles “Andy” Williams, Aaron Talsma, Andrew Bahl, Bronson Gregory, Veronica Varela, and Swathi Yadlapalli for their friendship and helpful discussions. I thank the many technicians, programmers, and undergraduates who are working and have worked in the lab for technical assistance, especially Rebecca Mudri, Harper Jocque, Claire Palmarini, and Jonte Jones.

I thank the numerous colleagues for reagents and advice. I thank members of the Neurobiology Joint Lab Meeting for fun and intense scientific discussions. I thank the Scott Pletcher Lab for long-term collaboration. In addition, I thank Dr. Laura Olsen, Dr. Steven Clark, Dr. Daniel Klionsky, Dr. Anuj Kumar, Dr. John Schiefelbein, and Dr. Cunming Duan among others for their help with my Ph.D. studies. I also greatly appreciate all the help from Mary Carr, Diane Durfy, and other MCDB staff.

To all of my friends here at University of Michigan and all around the world: Thank you for your friendship, your support, and all the fun we had! I would also like to thank all of my teachers and mentors throughout my life. I am indebted to my parents, my sister, and other family members for their unconditional love and support. Last but not least, I thank my loving wife, Meiyan Jin, for everything that cannot be fully accounted for with words. She is the sunshine of my life.

–  –  –

This thesis describes the research I conducted in Dr. Orie T. Shafer’s lab, which began in January 2011. The objective of my work was to better understand the neuronal connectivity, organizing principles, and mechanisms of network coordination of circadian clock neuron networks.

Chapter 2 was published in Journal of Neurophysiology (2012; 108(2):684-96), with author listed as Zepeng Yao (Z.Y.), Ann Marie Macara (A.M.M.), Katherine R. Lelito (K.R.L), Tamara Y. Minosyan (T.Y.M.), and Orie T. Shafer (O.T.S.). Z.Y., A.M.M, and K.R.L were cofirst authors. Z.Y., A.M.M., K.R.L., T.Y.M., and O.T.S. designed the research; Z.Y., A.M.M., K.R.L., and T.Y.M. performed experiments; Z.Y., A.M.M., K.R.L., and T.Y.M. analyzed data;

Z.Y., A.M.M., K.R.L., T.Y.M., and O.T.S. interpreted results of experiments; Z.Y., A.M.M., and K.R.L. prepared figures; Z.Y., A.M.M., K.R.L., and O.T.S. drafted manuscript; O.T.S. edited and revised manuscript; O.T.S. approved final version of manuscript. Z.Y. specifically generated the data for Figures 2.3, 2.5 and 2.7.

Chapter 3 has not yet been published. A manuscript comprising this chapter is in preparation for publication, with authors listed as Zepeng Yao (Z.Y.), Richard I. Hume (R.I.H.), and Orie T. Shafer (O.T.S.). Z.Y., R.I.H., and O.T.S. designed the research; Z.Y. performed experiments and analyzed data; Z.Y., R.I.H., and O.T.S. interpreted results of experiments; Z.Y.

and O.T.S. wrote the manuscript.

–  –  –

Zepeng Yao (Z.Y.) and Orie T. Shafer (O.T.S.). Z.Y. and O.T.S. designed the research; Z.Y.





performed experiments and analyzed data; Z.Y. and O.T.S. interpreted results of experiments;

Z.Y. and O.T.S. wrote the paper.

Chapter 5 has not yet been published. A manuscript comprising this chapter is in preparation for publication, with authors listed as Zepeng Yao (Z.Y.), Amelia J. Bennett (A.J.B.), Jenna L. Clem (J.L.C.), and Orie T. Shafer (O.T.S.). Z.Y. and O.T.S. designed the study. Z.Y.

conducted all the experiments. A.J.B. analyzed the phase of activity peaks in light/dark cycles for individual flies; J.C. quantified the PER immunostaining intensity of the CRY+ DN1ps; Z.Y.

performed the remaining analyses. Z.Y. and O.T.S. wrote the paper.

–  –  –

DEDICATION

ACKNOWLEDGEMENTS

PREFACE

LIST OF TABLES

LIST OF FIGURES

ABSTRACT

CHAPTER 1. Introduction

1.1 Circadian clocks

1.2 Drosophila offers an excellent model for the study of circadian clocks

1.3 Molecular clocks

1.4 Anatomy and neurochemistry of the Drosophila clock neuron network

1.5 Models of the Drosophila clock neuron network function

1.6 References

CHAPTER 2. Analysis of functional neuronal connectivity in the Drosophila brain.

................. 13

2.1

Abstract

2.2 Introduction

2.3 Methods

2.4 Results

2.5 Discussion

–  –  –

2.7 References

CHAPTER 3. GABAergic and glutamatergic inhibition of the lateral clock neurons differentially regulates daytime and nighttime sleep in Drosophila

3.1 Abstract

3.2 Introduction

3.3 Results

3.4 Discussion

3.5 Materials and Methods

3.6 Acknowledgements

3.7 References

CHAPTER 4. The Drosophila circadian clock is a variably coupled network of multiple peptidergic units

4.1 Abstract

4.2 Results

4.3 Materials and Methods

4.4 Supplementary Results

4.5 Acknowledgments

4.6 References and Notes

CHAPTER 5. The Drosophila circadian clock neuron network features diverse coupling modes and requires network-wide coherence for robust free-running rhythms

5.1 Abstract

5.2 Introduction

–  –  –

5.4 Discussion

5.5 Materials and Methods

5.6 Supplementary Results

5.7 Acknowledgements

5.8 References

CHAPTER 6. Concluding Remarks

6.1 A new approach to address functional neuronal connectivity in the Drosophila brain

6.2 Physiological connectivity within the Drosophila clock neuron network.................. 169

6.3 Electrophysiological characterization of the critical LNd clock neurons

6.4 Diverse modes of coupling between the various clock neuron groups

6.5 The Drosophila clock neuron network consists of multiple oscillators and requires network-wide coherence for robust free-running rhythms

6.6 References

–  –  –

Table 4.S1.

Locomotor activity rhythms of control flies, and flies overexpressing different forms of DBT or SGG in all the clock neurons in constant darkness.

Table 4.S2.

Locomotor activity rhythms of control flies, and flies overexpressing different forms of DBT or SGG only in the PDF positive clock neurons in constant darkness................... 123 Table 4.S3.

Locomotor activity rhythms of control flies, and Pdfr- mutant flies overexpressing different forms of DBT or SGG only in the PDF positive neurons in constant darkness... 124 Table 4.S4.

Locomotor activity rhythms of control flies, and flies overexpressing different forms of DBT or SGG only in the PDF negative clock neurons in constant darkness.................. 125 Table 4.S5.

Locomotor activity rhythms of control flies, and flies with period-rescued PDF positive neurons with or without DBT co-overexpression in constant darkness................ 126 Table 4.S6.

The numbers of neurons and brains examined for PER protein rhythms in Fig. 4.4, D to F.

Table 4.S7.

The numbers of neurons and brains examined for PER immunostaining intensity in Fig. 4.4, I and J

Table 5.S1.

Expression patterns of GAL4 drivers.

Table 5.S2.

Summary of free-running locomotor activity rhythms.

–  –  –

Figure 1.1.

Population average activity profile of wild type Canton-S flies.

Figure 1.2.

The core feedback loop of the Drosophila molecular clock.

Figure 1.3.

A schematic of the clock neurons and their projections in the adult fly brain............. 6 Figure 1.4.

Neurochemistry of the Drosophila clock neuron network.

Figure 2.1 Schematic of dual binary, ATP/P2X2 excitation approach to network interrogation.

36 Figure 2.2 Bath application of ATP results in the excitation of P2X2-expressing deep brain neurons during live imaging experiments.

Figure 2.3 LexA operator-driven P2X2 and genetically encoded sensors for excitation and live imaging.

Figure 2.4 Bath-applied ATP reliably and repeatedly activates deeply situated P2X2-expressing neurons in the explanted adult brain.

Figure 2.5 Independent expression of P2X2 and genetically encoded sensor in the fly brain by dual binary systems supports the excitation of specific neuronal subsets.

Figure 2.6 Gal4-based excitation and LexA-based live imaging for an established excitatory connection in the larval brain.

Figure 2.7 LexA-based excitation and GAL4-based live imaging to test a predicted peptidergic connection deep within the adult brain.

Figure 3.1.

Spontaneous tonic and burst firing of the LNds

Figure 3.1–figure supplement 1.

Electrophyiological parameters of whole-cell LNd recordings. 69

–  –  –

Figure 3.2–figure supplement 1.

The nicotine-induced LNd currents are largely networkindependent.

Figure 3.3.

GABA inhibits the LNds through GABAA receptors.

Figure 3.3–figure supplement 1.

The GABA-induced LNd currents are largely networkindependent.

Figure 3.4.

Glutamate inhibits the LNds through the glutamate-gated chloride channel GluClα. 72 Figure 3.4–figure supplement 1.

The glutamate-induced currents in the LNds are largely networkindependent.

Figure 3.5.

The DN1ps inhibit the LNds.

Figure 3.5–figure supplement 1.

Perfusion of 250 µM ATP results in consistent and nearmaximal excitation of the P2X2-expressing DN1ps.

Figure 3.6.

RNAi-mediated knock-down of GABAAR expression in the LNds results in reduced nighttime sleep.

Figure 3.6–figure supplement 1.

RNAi-mediated knock-down of GABAAR expression in the lateral clock neurons results in reduced nighttime sleep.

Figure 3.7.

RNAi-mediated knock-down of GluClα expression in the lateral clock neurons results in increased daytime sleep.

Figure 3.7–figure supplement 1.

RNAi-mediated knock-down of GluClα expression in the LNds and the LNvs differentially affects daytime sleep.

Figure 3.8.

A summary model for the differential regulation of daytime and nighttime sleep by GABAergic and glutamatergic inhibition of the lateral clock neurons.

–  –  –

signaling over a limited temporal range

Figure 4.2 The PDF negative clock neurons exert independent control over free-running activity rhythms.

Figure 4.3.

Pigment-dispersing factor modulates only half of the PDF-negative dorsal lateral neurons.

Figure 4.4.



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