Statistical Physics of Noninteracting Bacterial Populations

Genetically identical bacterial cells in identical environments display significant variability in their phenotypic behavior; they grow at different rates, divide at different sizes, and have different generation times. With recent advances in single-cell technologies, now we can measure not only the distributions of these quantities but also the subtle correlations between these variables both within and across generations. These statistical descriptions have paved the way for the phenomenological models of cellular growth and division. In this talk, I will take these phenomenological models as the microscopic dynamics of individual cells to quantitatively predict the macroscopic properties of populations both in batch and chemostat settings. In particular, I derive the growth rate of the population, the rate at which a population approaches its steady state, and the rate of neutral genetic drift from the single-cell variables.