Defining a biophysical basis for cell types, cell states and cellular heterogeneity at single-cell resolution

Project Summary. Cells are dynamic and highly responsive systems that integrate internal molecular signals with external biological cues to establish unique time-dependent cellular identities. These cellular identities, which we can think of as cell types, cell states, or cell fates change in the context of health and disease. Recent advances in single-cell technologies have provided the unprecedented capacity to profile cellular states, reconstruct cellular lineages, and identify putative drivers of diseases across thousands of individual cells. Our long terms goal is to comprehensively and systematically understand how the flow of biological information from underlying molecular programs to behaviors and responses define cellular identities. Building on current work within my lab, we will develop new integrated technologies to investigate how distinct molecular programs drive cell behaviors and cellular responses to perturbations at single-cell resolution. As model systems, we will investigate how distinct epigenomic programs drive senescence phenotypes, how transcriptional program modulate T-cell behaviors and responses with application for engineered cells, and lastly how mapping phenotypic changes of T-cells during differentiation could help us better understand cell types and cell commitments. Collectively, the proposed studies, which are backed by strong preliminary data, will yield substantial new information on cell-based mechanisms and provide new ways to deeply profile single cells.