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UBC Theses and Dissertations

Mechanisms underlying PTP sigma-mediated synaptic differentiation and neuronal diversity Bomkamp, Claire


Brain function is dependent on both the properties of the individual neurons of which it is made up, as well as the precise pattern of connections between them. Both aspects of brain circuitry are determined in large part by the expression of specific genes. The products of these genes, including adhesion molecules, ion channels, and transcription factors, go on to shape neurons’ properties and as well as their connectivity. Neurons direct their connectivity in part by expressing trans-synaptic cell adhesion molecules, which act as “molecular velcro” in order to form physical connections between axons and dendrites. These adhesion molecules are able to recruit the necessary components for synaptic transmission, through mechanisms which are incompletely understood. Chapter 2 focuses on one presynaptic adhesion molecule, PTPσ, and its interaction with intracellular scaffolding proteins. PTPσ is a phosphatase, but I found that its phosphatase activity is not needed for its ability to induce new synapses. However, interaction with the presynaptic scaffolding protein liprin-α is required. Because liprin-α binds to multiple presynaptic components, this finding suggests a mechanism through which PTPσ recruits liprin-α to nascent synapses, and liprin-α in turn recruits other components, eventually leading to recruitment of vesicles, calcium channels, and everything else necessary for functional presynaptic release. Phenotypes of individual neurons, including electrophysiological activity and morphology, are known to be under genetic control. However, given the number of genes expressed by one organism and the difficulty of experimentally exploring the consequences of loss of function of any one gene, our understanding of the molecular underpinnings of any particular phenotype remains incomplete. In Chapter 3, I took the approach of searching for correlations between gene expression and neuronal phenotypes in a publicly available dataset. I found that controlling for broad cell class (that is, whether cells are inhibitory or excitatory) made a substantial difference to the results, and found much better correspondence with other datasets and with previously published literature when I took this step. In this work, I generated many testable hypotheses regarding the relationship between specific genes and neuronal phenotypes, which I hope will help to guide future studies.

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