Speaker
Description
The control of gene expression by epigenetic factors, along with gene expression noise, results in a distribution of cell states amongst genetically identical cells. Previous studies have explored the role of gene expression in proliferation and vice versa, which, in turn, shapes cellular heterogeneity within a population. However, in these studies, the population was assumed to be well-mixed. As crowding, migration, local interactions, and other factors are key features of spatial population dynamics, their consideration has important implications for cell growth and migration. Thus, space introduces additional complexity into the feedback between gene regulation and the population's growth rate, modulating cellular heterogeneity within a population with respect to non-spatial contexts. We have developed spatial agent-based models in which cells divide and migrate, along with non-spatial models as a control. The division and migratory rates of cells are governed by their cell states, and an underlying gene regulatory network models the dynamics of cell states. With the developed framework, we compare the roles of regulation and stochasticity in shaping population-level heterogeneity in spatial and non-spatial contexts, and highlight how non-genetic phenotypic selection operates differently in these contexts.
