Modeling the impact of single-cell stochasticity and size control on the population growth rate in asymmetrically dividing cells

Influence of cell volume on the gene transcription rate

Cells vary in volume throughout their life cycle and in many other circumstances, while their genome remains identical. Hence, the RNA production factory must adapt to changing needs, while maintaining the same production lines. This paradox is resolved by different mechanisms in distinct cells and circumstances. RNA polymerases have evolved to cope with the particular circumstances of each case and the different characteristics of the several RNA molecule types, especially their stabilities. Here we review current knowledge on these issues. We focus on the yeast Saccharomyces cerevisiae, where many of the studies have been performed, although we compare and discuss the results obtained in other eukaryotes and propose several ideas and questions to be tested and solved in the future. TAKE AWAY.

Effects of Molecular Noise on Cell Size Control

Cells employ control strategies to maintain a stable size. Dividing at a target size (the "sizer" strategy) is thought to produce the tightest size distribution. However, this result follows from phenomenological models that ignore the molecular mechanisms required to implement the strategy. Here we investigate a simple mechanistic model for exponentially growing cells whose division is triggered at a molecular abundance threshold. We find that size noise inherits the molecular noise and is consequently minimized not by the sizer but by the "adder" strategy, where a cell divides after adding a target amount to its birth size. We derive a lower bound on size noise that agrees with publicly available data from six microfluidic studies on Escherichia coli bacteria.

Density fluctuations, homeostasis, and reproduction effects in bacteria

Single-cells grow by increasing their biomass and size. Here, we report that while mass and size accumulation rates of single Escherichia coli cells are exponential, their density and, thus, the levels of macromolecular crowding fluctuate during growth. As such, the average rates of mass and size accumulation of a single cell are generally not the same, but rather cells differentiate into increasing one rate with respect to the other. This differentiation yields a density homeostasis mechanism that we support mathematically. Further, we observe that density fluctuations can affect the reproduction rates of single cells, suggesting a link between the levels of macromolecular crowding with metabolism and overall population fitness. We detail our experimental approach and the “invisible” microfluidic arrays that enabled increased precision and throughput. Infections and natural communities start from a few cells, thus, emphasizing the significance of density-fluctuations when taking non-genetic variability into consideration.

Quantitative imaging, invisible microfluidics, and mathematical models demonstrate how the density of single E. coli cells fluctuates during the cell cycle, unmasking key homeostasis and population fitness effects.