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UNIVERSITY OF CALIFORNIA, SAN DIEGO Deconstruction of neural circuits provides insights into complex network function A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biology by Matthew John Sternfeld Committee in charge: Professor Samuel L. Pfaff, Chair Professor Sreekanth Chalasani Professor Nicholas C. Spitzer Professor Mark H. Tuszynski Professor Eugene W. Yeo 2016 Copyright Matthew John Sternfeld, 2016 All rights reserved. Signature Page The Dissertation of Matthew John Sternfeld is approved, and it is acceptable in quality and form for publication on microfilm and electronically: ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ Chair University of California, San Diego 2016 iii Table of Contents TABLE OF CONTENTS Signature Page ................................................................iii Table of Contents ..............................................................iv List of Figures .................................................................vi List of Abbreviations ...........................................................viii List of Supplementary Materials ...................................................xi Acknowledgements ............................................................ xii Vita ........................................................................xiv Abstract of the Dissertation ......................................................xv Chapter 1 Introduction: Spinal cord patterning ........................................1 Chapter 2 Differential roles for inhibitory neurons revealed through creation of cell-type specific de novo networks ..............................................................22 Abstract ...............................................................23 Introduction ............................................................23 Results ................................................................26 Discussion .............................................................55 Author Contributions .....................................................60 Acknowledgements ......................................................60 References .............................................................60 Chapter 3 Future directions and conclusions .........................................66 Introduction ............................................................67 Neuronal subtype mixing ..................................................67 Kebab .................................................................68 Microislands ............................................................69 Spinal Cord Injury .......................................................71 CRISPR Screening. 73 Conclusion .............................................................74 References .............................................................74 Methods. .76 iv Chapter 1 Methods .......................................................77 Chapter 2 Methods .......................................................77 Chapter 3 Methods .......................................................83 References .............................................................84 v List of Figures LIST OF OF FIGURES Figure 1.1 The black box of spinal cord circuitry .......................................3 Figure 1.2 Cartesian coordinate system framework of spinal cord development ...............4 Figure 1.3 Shh regulates gene expression through modulation of GLI activity ................6 Figure 1.4 Rostrocaudal identity is defined byHox genes ................................7 Figure 1.5 Examples of classical signaling cascades involved in spinal cord patterning .........8 Figure 1.6 Generation of progenitor domains .........................................10 Figure 1.7 Transcriptional cross-repression sharpens boundaries between progenitor domains ..11 Figure 1.8 Example of a combinatorial transcription factor code .........................12 Figure 1.9 Diverse neuronal identities are specified by combinatorial transcription factor codes .15 Figure 2.1 de novo spinal networks differentiated from mESCs ..........................27 Figure 2.2 Neurosphere heterogeneity ..............................................30 Figure 2.3 Basic network properties of neurospheres ...................................32 Figure 2.4 Activity in pure excitatory networks differs greatly from inhibitory networks .......35 Figure 2.5 Representative FACS plots for generating designed neural networks .............37 Figure 2.6 Alterations in frequency and rhythmicity as pure V3 interneuron networks mature or increase in size ................................................................39 Figure 2.7 Cholinergic antagonists do not alter pure motor neuron network activity ..........41 Figure 2.8 E/I ratio controls speed and rhythmicity in heterogeneous networks ..............43 Figure 2.9 V1 interneurons alter activity rate of V3 interneuron networks ..................45 Figure 2.10 Tight control of neuronal contribution to de novo networks ....................47 Figure 2.11 V1 interneurons disrupt rhythmic activity when added to V3 networks ...........49 Figure 2.12 V1 interneurons generate subnetworks within motor neuron networks ...........50 Figure 2.13 Synchronous activity observed in non-MN+V1 networks .....................52 Figure 2.14 Recruitment of V1 interneurons alters network activity in a manner dependent upon cellular makeup of base network ..................................................54 Figure 2.15 mESC derived neurons appropriately express known markers ..................57 Figure 3.1 Kebabs demonstrate propagation of network activity ..........................70 Figure 3.2 Younger neurospheres have higher outgrowth capability than older neurospheres ...70 vi Figure 3.3 Microislands can be used to generate small neuronal networks ..................72 Figure 3.4 Cells derived from mESCs successfully fill lesion in SCI animal ................72 vii List of Abbreviations LIST OF ABBREVIATIONS µV microVolt 5-HT Serotonin ACSF Artificial cerebrospinal fluid ALS Amyotrophic lateral sclerosis bHLH Basic helix–loop–helix transcription factor BMP Bone morphogenetic protein C.V. Coefficient of variation CAG CAG promoter Chx10 Visual System Homeobox 2 CNQX 6-Cyano-7-nitroquinoxaline-2,3-dione CNS Central nervous system CPG Central pattern generator Cre Cre recombinase dF/F Change in fluorescence divided by baseline fluorescence dhβe Dihydro-β-erythroidine hydrobromide dI1 Dorsal interneuron Class 1 dI2 Dorsal interneuron Class 2 dI3 Dorsal interneuron Class 3 dI4 Dorsal interneuron Class 4 dI5 Dorsal interneuron Class 5 dI6 Dorsal interneuron Class 6 dILA Late-born dorsal interneuron class A dILB Late-born dorsal interneuron class B DTA Diptheria toxin subunit A e Mouse embryonic day E/I Excitatory-to-inhibitory ratio En1 Engrailed Homeobox 1 viii ESC Embryonic stem cell ESC-MN ESC-derived motor neuron GABA Gamma aminobutyric acid Gata3 GATA Binding Protein 3 GCaMP3 Genetically encoded calcium indicator GFP Green fluorescent protein Hb9 Motor Neuron And Pancreas Homeobox 1 HMC Hypaxial motor column I.C.V. Interval coefficient of variation iPS Induced pluripotent stem cell LIM-HD LIM homeodomain transcription factor LMC Lateral motor column LMCl LMC lateral division LMCm LMC medial division LSL Lox-stop-lox mESC Mouse embryonic stem cell Min Minute MMC Medial motor column MN Motor neuron MN+V1 Mixed networks of MNs and V1 interneurons Neo Neomycin NMA N-Methyl-DL-aspartic acid NMDA N-Methyl-D-aspartic acid OLP Oligodendrocyte precursor P Mouse postnatal day p0 V0 interneuron progenitor domain p1 V1 interneuron progenitor domain p2 V2 interneuron progenitor domain p3 V3 interneuron progenitor domain ix PC Principle component PCR Polymerase chain reaction pdI1 dI1 dorsal interneuron progenitor domain pdI2 dI2 dorsal interneuron progenitor domain pdI3 dI3 dorsal interneuron progenitor domain pdI4 dI4 dorsal interneuron progenitor domain pdI5 dI5 dorsal interneuron progenitor domain pdI6 dI6 dorsal interneuron progenitor domain pdIL dILA–dILB late-born interneuron progenitor domain PGC Preganglionic motor column pMN Motor neuron progenitor domain polyA Polyadenylation tail R26 Rosa locus R26/C R26 with inserted CAG promoter RA Retinoic acid ROI Region of interest SAG Smoothened agonist Sec Second Shh Sonic hedgehog Sim1 Single-minded family bHLH transcription factor 1 SMA Spinal muscular atrophy V0 Ventral interneuron Class 0 V1 Ventral interneuron Class 1 V2 Ventral interneuron Class 2 V3 Ventral interneuron Class 3 V3-/- Genetic ablation of V3 interneurons V3+V1 Mixed networks of V3 and V1 interneurons x List of Supplementary Materials LIST OF SUPPLEMENTARY MATERIALS Video 2.1: Spontaneous activity of heterogeneous neurospheres (1000 nM SAG) Video 2.2: Spontaneous activity of heterogeneous neurospheres (5 nM SAG) Video 2.3: Activity of heterogeneous neurospheres (1000 nM SAG) in CNQX Video 2.4: Spontaneous activity of heterogeneous neurospheres (1000 nM SAG) prior to evoked condition Video 2.5: Activity of heterogeneous neurospheres (1000 nM SAG) in evoked condition Video 2.6: Activity of plated, pure V3 interneuron network