Control with stochastic components: How cells achieve homeostasis and exploit fluctuations

Abstract

Cells are chemical reactors where reactions among molecules such as DNA, RNA, and proteins implement the sophisticated programs that support life. Biological molecules undergo thermal motion, and even when they have the propensity to react together, they only do so probabilistically. Therefore, biological processes are fundamentally stochastic because of the very nature of these probabilistic biochemical reactions. This stochasticity, which manifests as cell to cell variability in mRNA and protein levels even in clonal populations of genetically identical cells, is accurately quantifiable with modern experimental techniques. In this talk, I illustrate using a number of examples of how an iterative cycle of rigorous computational modeling and quantitative experimentation can generate profound insights into the control mechanisms used by cells to dampen or exploit their stochastic fluctuations. I also discuss the challenges inherent in connecting measurements of stochastic biochemical circuits to their modeling and analysis, and highlight many exciting opportunities in this field.