"Analysis of in vitro Self-Assembling Networks" by Liang Yang

Analysis of in vitro Self-Assembling Networks

Date of Award

Spring 2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Biomedical Engineering (ENAS)

First Advisor

Levchenko, Andre

Abstract

A major challenge to the study of physiological and pathological neurodevelopment is the complexity ofthe nervous system. It is therefore essential to use simpler models that can still capture the key features of the in vivo neurogenesis and functioning of neuronal circuits. To address these challenges, in my thesis work, I establish and characterize an in vitro network model, differentiated from human embryonic and induced pluripotent stem cells (hESCs and iPSCs), capturing the neuronal architecture and accessible to detailed structure and function analysis. Furthermore, this neuronal network is then tested as a disease model to better understand idiopathic Autism Spectrum Disorders (ASD) based on patient derived iPSCs. In this work, I obtained the following key results: (1) The structure and connectivity of self-organizing neuronal network emerging from hESCs has been characterized based on measurements of morphological characteristics at the cellular and network levels, using computational modeling and transcriptome classifications; (2) The functional network properties were characterized based on calcium activity through confocal imaging, following diverse pharmacological perturbations. In particular, I focused on the analysis of synchronized oscillation, using synaptic receptor blockers, demonstrating that the network activity is highly associated synaptic transmission. In the subsequent work I sought to develop the ASD model that would complement animal models that have been historically used in this filed. The model I developed may help address the debate of how to model idiopathic ASD due to the limited knowledge about the genetic determinants of the disease. The purpose of this part of research was to further test current major hypothesis etiology of idiopathic ASD that emerged based on post-mortem studies, i.e., that it is due to imbalance between populations of excitatory and inhibitory neurons. The model I developed based on patient derived iPSC provides possibilities to study this and other hypothesis related to this polygenetic disease. Specifically, I used fibroblasts from ASD-patients and non-affected immediate family members (as biological control), which were reprogrammed to iPSCs and further differentiated into self-organizing neuronal networks. The calcium activity measurements have shown unexpected altered activity in patient cohorts vs. controls, strongly suggesting an increasing population of excitatory neurons participating in network activity.

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