Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12202/465
Title: Comparative connectomics studies of C. elegans
Authors: Cook, Steven J.
Keywords: Neurosciences.
Issue Date: 2017
Publisher: ProQuest Dissertations & Theses
Citation: Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.;Advisors: Scott W. Emmons.
Abstract: The ability of an organism to sense, integrate, and respond to environmental stimuli is dictated by its synaptic connections. A central goal of neuroscience is therefore to understand how neurons assemble into complex circuits to process information and respond behaviorally. Synapses and circuits can be conditional, and are generated and modified by development, genotype, and experience. To comprehend how the behavioral output of an organism emerges from its synaptic connections, full wiring diagrams, or connectomes, are needed. Because various human neuropsychiatric and behavioral disorders exhibit connectopathies, or deficits in functional brain connectivity, the study of network-level brain organization is a growing area of research. Nevertheless, entire brain mapping is technically difficult and few connectomes have been mapped. Even less information is known about how the connectome develops and how its maturation yields new and different behaviors.;During my graduate studies I established new, complete, and quantitative wiring diagrams of the Caenorhabditis elegans nervous system. The roundworm C. elegans is an attractive connectomics model system due to its stereotyped cell-lineage, modest nervous system size, and rich behavioral repertoire. Although previous connectomics efforts in C. elegans have provided an invaluable understanding of the nervous system, these studies were largely limited to adult hermaphrodites and did not reconstruct and identify every connected cell in the worm. To generate full and weighted measures of connectivity for all cells I used digital reconstruction strategies for both legacy and new serial section electron micrographs (EMs). My work was driven by two broad questions. 1) How does the structure of the nervous system inform behavior and function? 2) How constant is the C. elegans connectome, and to what extent do sexual dimorphisms and inter/intra-individual differences exist?;In chapter 2, I focus on how the structure of the pharyngeal connectome, a self-contained nervous system, predicts feeding behavior. Because the pharyngeal circuit consists of only twenty neurons I was able to reconstruct multiple EM series, perform a detailed neuron-by-neuron analysis, and also evaluate network-level properties. My analysis revealed that pharyngeal neurons are more highly connected than previously reported and are assembled for fast information processing. I found that pharyngeal processing depth is shallow, with the majority of synaptic connections being directed toward muscle and non-neuronal tissues. The patterns of neuronal connections are organized into computational modules that correspond to the three functional domains of the pharynx. I also found that the centrality measures identified the most behaviorally relevant pharyngeal neurons, while also suggested novel functions for several neuronal classes. My description of the pharyngeal network emphasized how anatomical connectivity alone can predict function, and revealed distinct properties of a specialized nervous system wired to accomplish a dedicated behavior.;In chapter 3, I compare the connectomes of the C. elegans hermaphrodite and male, describing and quantifying the extent of sexual dimorphism within the nervous system. I generated full connectomes of both sexes, allowing the comparison of both sex-specific neurons and their connections, and the connectivity of sex-shared neurons. I identified hundreds of new connections in both sexes, which in a graph representation of connectivity, showed that pathways of information flow can be arranged hierarchically, revealing a largely feed forward structure of shallow (1-5 synapses) depth. I found hundreds of synaptic connections that differ between the hermaphrodite and male which could be either inter-individual differences or differences due to genetic sex. To distinguish between these possibilities, I examined a subset of these sex-differences: 7 synaptic connections that were found to be stronger in the male, 4 that were stronger in the hermaphrodite, and 4 that were similar in both sexes, using in vivo trans-synaptic fluorescent labeling. Our live imaging results from many animals showed that our predictions of sexual dimorphisms from single EM series were valid. Building upon our fluorescent studies I concluded that there is an unexpectedly large number of sex-specific connections, with roughly 10% of the core sex-shared nervous system showing dimorphic connectivity. These sex-specific connections were mainly embedded deep within the connectome at least one synapse away from any sex-specific neuron.;In chapter 4, I investigated an anatomical connection I found to show a left-right asymmetry in connectivity. Interestingly, I found that two neurons each known to exhibit asymmetric cell-fates, gene expression, and physiology are biased to have more left than right synapses. I found this asymmetry is present in 85% of animals using trans-synaptic labeling in live animals, which also revealed that this asymmetry is produced during late larval development. Unexpectedly we found that mutations known to change presynaptic cell fate did not abolish asymmetric synaptic connectivity. We next evaluated trans-synaptic signaling, and found that mutations in the insulin signaling pathway (including bioactivation and its canonical receptor daf-2) reverse, and in some animals abolish the handedness of this asymmetric connection. Together, my studies have revealed new insights into the structure, sex-specificity, and genetic determination of a diverse variety of circuits. My work has shown that genetic sex and conserved signaling pathways allow for diverse synaptic patterns in a relatively small nervous system.
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https://hdl.handle.net/20.500.12202/465
Appears in Collections:Albert Einstein College of Medicine: Doctoral Dissertations

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