Modeling cell size regulation under complex and dynamic environments

Abstract

In nature, cells face changes in environmental conditions that can modify their growth rate. In these dynamic environments, recent experiments found changes in cell size regulation. Currently, there are few clues about the origin of these cell size changes. In this work, we model cell division as a stochastic process that occurs at a rate proportional to the size. We propose that this rate is zero if the cell is smaller than a minimum size. We show how this model predicts some of the properties found in cell size regulation. For example, among our predictions, we found that the mean cell size is an exponential function of the growth rate under steady conditions. We predict that cells become smaller and the way the division strategy changes during dynamic nutrient depletion. Finally, we use the model to predict cell regulation in an arbitrary complex dynamic environment.

Stochastic Gene Expression in Proliferating Cells: Differing Noise Intensity in Single-Cell and Population Perspectives

“…It is well known that, if cells grow exponentially in cell size along the cell cycle, then such timer-based models are not able to provide cell size homeostasis, that is, the variance in cell size grows unboundedly over time [109,110]. We address this limitation by modifying the agentbased model to explicitly consider the size dynamics of individual cells and implemented size control according to adder -the size added from cell birth to division is not correlated with the newborn size [111][112][113][114][115][116]. Statistics computed from simulating these cell-size homeostatic models are presented in Appendix S8 and recapitulate the qualitative finding of Figure 3C: Protein noise in a cell population is more sensitive to fluctuations in added size compared to the single-cell perspective.…”