It is well known that population sizes increase exponentially during balanced growth . Concomitantly, at the single-cell level, the sizes of individual cells themselves increase exponentially; the single-cell exponential growth-rate also determines the statistics of cell size and cell division time distributions. Seeking an integrated perspective of microbial growth dynamics under balanced conditions, we formulate a theoretical framework that takes into account observables at both single-cell and population scales. Our exact analytical solutions for both symmetric and asymmetric cell division reveal surprising effects of the stochastic single-cell dynamics on features of population growth. In particular, we find how the population growth rate is sensitive to the shape of the distribution of cell division times. We validate the model by quantitatively predicting the observed cell-age distributions without fitting parameters. Our model also provides a prescription for deducing the time for transitioning from the swarmer (reproductively quiescent ) to stalked (reproduction able) stage of the {\em C. crescentus} lifecycle ; our predictions match with previous indirect estimates. We discuss the scalings of all timescales with external parameters that control the balanced growth state . For {\em C. crescentus} cells, we show that the rate of exponential growth of single (stalked) cells governs the dynamics of the entire lifecycle, including the swarmer-to-stalked cell transition .
How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division . These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to replication-competent (stalked ) stage of the {\em Caulobacter crescentus} lifecycle . Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations . For {\em C. crescentus} cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time, and thus yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell age distribution, and the quiescence timescale .
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In particular, we find how the population growth rate is sensitive to the shape of the distribution of cell division times. We validate the model by quantitatively predicting the observed cell-age distributions without fitting parameters. Our model also provides a prescription for deducing the time for transitioning from the swarmer (reproductively quiescent
Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to replication-competent (stalked
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; our predictions match with previous indirect estimates. We discuss the scalings of all timescales with external parameters that control the balanced growth state
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the rate of exponential growth of single (stalked) cells governs the dynamics of the entire lifecycle, including the swarmer-to-stalked cell transition
a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time, and thus yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell age distribution, and the quiescence timescale