GEOMETRY AND SIZE OF SUBSTRATE TOPOGRAPHY GUIDES THE NEURAL DIFFERENTIATION OF HUMAN EMBRYONIC STEM CELLS

Abstract

Efficient derivation of neural cells from human embryonic stem cells (hESCs) remains an unmet need for the treatment of neurological disorders. The limiting factors for current methods include being labor-intensive, time consuming and expensive. The thesis is based on the hypothesis that the substrate topography, with optimal geometry and dimension, can modulate the neural differentiation of hESCs and enhance the efficiency of differentiation. A multi-architectural chip (MARC) containing fields of topographies varying in geometry and dimension was developed to facilitate high throughput analysis of topography-induced neural differentiation in vitro. The first part of the thesis showed that optimal combination of topography and biochemical cues could shorten the differentiation period and allowed derivation of neurons bearing longer neurites that were aligned along the grating axis. The second part of the thesis discusses the possible mechanisms of substrate mediated neuronal differentiation of hESCs. Inhibitor studies indicate that acto-myosin contractility plays a role in maturation of neurons. This work has shown the optimal topography needed for neural differentiation of hESC and tried to elucidate the importance of cytoskeletal components in force transmission from substrate to a cluster of hES cells.