DMS/NIGMS 1: Multi-timescale stochastic modeling to investigate epigenetic memory in bacteria

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

When a cell divides, each daughter cell contains an identical copy of its DNA. The DNA provides the blueprint for the molecules that the cell makes, and thus constitutes a genetic “memory”. However, the cell also passes a non-genetic, or “epigenetic”, memory to its daughters. Epigenetic memory consists of the molecules that the cell has already produced, and the chemical and conformational state of the DNA, which get inherited directly by the daughter cells. Even in simple organisms like bacteria, epigenetic memory is still poorly understood. In this project, the investigators will address basic questions about epigenetic memory, such as how many generations it lasts, using a new experimental device and new mathematical models. The research will be combined with the development of a course for high school teachers in the Pittsburgh area focused on interdisciplinary science. Because epigenetic memory is a fundamental property of living cells, and yet a quantitative understanding has remained elusive, the results are expected to have broad implications, particularly at the interface of the mathematical and biological sciences. The project will take advantage of the investigator's novel microfluidic technology to inform a new theory of cell growth and division dynamics, which in turn will make predictions for further experiments. The overarching goal is to accurately quantify epigenetic memory in bacteria, elucidate its determinants, and measure its sensitivity to stress-inducing environments. The goal will be achieved via two aims: (1) using discrete-time stochastic modeling to untangle multigenerational epigenetic memory timescales, and (2) combining continuous- and discrete-time stochastic modeling to investigate multigenerational noise propagation. In both aims, experiments and theory will guide each other quantitatively, leading to a richer understanding of bacterial epigenetics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.