Cellular And Molecular Analysis Of Neuronal Structure Plasticity In The Mammalian Cortex

Author : James Hyun-Woo Park
Publisher :
ISBN 13 : 9781369594829
Total Pages : 379 pages
Book Rating : 4.5/5 (948 download)

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Download or read book A Single-cell Analysis Approach to Understanding Molecular Organization and Plasticity in the Brain written by James Hyun-Woo Park and published by . This book was released on 2017 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell transcriptional heterogeneity pervades the fully differentiated brain. This heterogeneity is particularly prevalent in brain nuclei involved in the autonomic regulation of physiological functions such as cardiovascular homeostasis. Because neuronal function largely depends on its transcriptome, such heterogeneity confounds our understanding of how heterogeneous neurons contribute to their broader phenotypic function. In addition to the transcriptome, functional connectivity and in vivo anatomical environment are additional factors central to defining a neuron’s functional state. Given their importance, these factors may provide the added context necessary to understand how a distribution of heterogeneous neurons contributes to phenotypic function. Consequently, the overall goal of this work is to establish an organizational framework that characterizes single-neuron heterogeneity within a brain nucleus and elucidates its functional relevance. ☐ Towards this goal, we have taken a combined experimental and computational approach to determine the organizing principles driving complex interaction networks within and among transcriptionally diverse neurons within a brain nucleus. First, we generated a large-scale gene expression dataset from several hundred neurons, selected on the basis of their synaptic input types, taken from the nucleus tractus solitarius (NTS), a brainstem nucleus involved in the central regulation of blood pressure. Our analysis of these neurons revealed an organizational structure in which transcriptional variability aligns with synaptic input type along a continuum of graded gene expression. This continuum is populated by distinct neuronal subtypes characterized by gene groups exhibiting correlated expression. ☐ In order to identify the molecular mechanisms driving this correlated behavior, we next developed a fuzzy logic modeling-based methodology to model quantitatively causal gene interaction networks from single-cell transcriptomic data. Our modeling results suggest that distinct input stimuli operating on distinct network structures corresponding to these subtypes can drive neurons through various transcriptional states. These results suggest that transcriptional heterogeneity represents a neuron’s adaptive response to various inputs. Based on these results, we propose that neuronal adaptation may be a mechanism through which the NTS robustly regulates blood pressure and cardiovascular homeostasis. ☐ To test this proposal, we examined what impact adaptation to neuronal subtypes in the NTS and brainstem would have on the short-term autonomic regulation of cardiovascular homeostasis under the simulated disease state of systolic heart failure via mathematical modeling. We developed a closed-loop control model characterizing neuronal regulation of the cardiovascular system by integrating previous quantitative models that simulated various aspects of the cardiovascular system. Because the goal of this study was to investigate the effects of neuronal subtype adaptation, we incorporated brainstem neuronal subtypes, such as those identified in our analysis of the NTS. Modeling simulation results suggest that adaptation of these neuronal components can compensate for an impaired cardiovascular state due to systolic heart failure by decreasing neuronal inhibition (i.e. parasympathetic tone) of cardiac contractility. ☐ Finally, we tested the utility of a single-cell analysis approach to interpret single-cell heterogeneity throughout the brain by identifying a cellular network organization in a distinct brain nucleus – the suprachiasmatic nucleus (SCN), which regulates circadian rhythms in mammals. Similar to our analysis of the NTS, we generated and analyzed a high-dimensional gene expression dataset consisting of hundreds of transcriptionally heterogeneous SCN neurons. Our multivariate analysis of these neurons revealed both known and previously undescribed SCN neuron-types, which organize into a neuronal interaction network via known paracrine signaling mechanisms underlying the synchronizing functions of the SCN. ☐ Based on the analysis of heterogeneous single neurons, we have identified an organizational framework with which we can now interpret single-cell heterogeneity; a heterogeneous neuronal population comprises a mixture of distinct neuronal subtypes whose adaptive response to inputs is driven by distinct regulatory networks. Such adaptation provides a mechanism in which the brain is able to regulate robustly physiological functions by providing compensatory effects under perturbed or challenged states.