In vitro models of the human brain enable high-throughput genetic and chemical screens that can advance our understanding of complex neuro-developmental and ?degenerative diseases and inform therapeutic development. Large-scale screens involve perturbing thousands of genes in an unbiased manner that will elucidate the mechanisms underlying neurological diseases, which often implicate many different pathways. Ideal models for large-scale screens should be homogenous, robust, and scalable. However, current methods for generating in vitro models of the brain generally involve differentiating human embryonic stem cells (hESCs) into neural cells using exogenous factors or small molecules, a process that is labor-intensive, time- consuming, and produces non-homogeneous cell types. Furthermore, many cell types in the brain cannot be derived from hESCs. Thus there is a need to develop an efficient method that can generate more complete in vitro models of the human brain. We propose to develop a screening platform for systematically identifying transcription factors (TFs) that drive differentiation of hESCs into target neural cell types. Differentiation methods based on overexpression of TFs has been shown by previously studies to efficiently and rapidly generate target cell types. Since TFs use endogenous regulatory pathways, this approach may produce higher fidelity models.
In Aim 1, we will identify TFs that can differentiate hESCs into radial glia, neural progenitors in the developing central nervous system that are capable of differentiating into neurons, astrocytes, and oligodendrocytes.
In Aim 2, we will use these candidate TFs to develop a high-throughput screening platform for identifying TFs that direct differentiation into specific cell types of interest. We will then demonstrate the versatility of our screen by apply our method in Aim 3 to identify TFs that differentiate radial glia into astrocytes. Our proposed work will advance our understanding of gene regulation in neural development and provide robust, scalable cellular models for studying the brain. These contributions will be essential for developing better therapies for neurological diseases. Additionally, the transcription factor screening platform will be a valuable resource for systematic discovery of novel TFs that direct differentiation into other cell types of interest.
Models of the human brain can advance our understanding of complex neurological diseases and inform therapeutic development. Current models of the brain, however, lack some of the relevant cell types and generally involve labor-intensive and time- consuming processes. The proposed work will establish a screening platform for systematically identifying transcription factors that differentiate stem cells into target neural cell types, which will advance our understanding of neural development and provide robust, scalable models for studying the brain.