3 research outputs found
Scaling laws governing stochastic growth and division of single bacterial cells
Uncovering the quantitative laws that govern the growth and division of
single cells remains a major challenge. Using a unique combination of
technologies that yields unprecedented statistical precision, we find that the
sizes of individual Caulobacter crescentus cells increase exponentially in
time. We also establish that they divide upon reaching a critical multiple
(1.8) of their initial sizes, rather than an absolute size. We show
that when the temperature is varied, the growth and division timescales scale
proportionally with each other over the physiological temperature range.
Strikingly, the cell-size and division-time distributions can both be rescaled
by their mean values such that the condition-specific distributions collapse to
universal curves. We account for these observations with a minimal stochastic
model that is based on an autocatalytic cycle. It predicts the scalings, as
well as specific functional forms for the universal curves. Our experimental
and theoretical analysis reveals a simple physical principle governing these
complex biological processes: a single temperature-dependent scale of cellular
time governs the stochastic dynamics of growth and division in balanced growth
conditions.Comment: Text+Supplementar
Bridging the Timescales of Single-Cell and Population Dynamics
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 the replication-competent (stalked) stage of the Caulobacter crescentus life cycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For 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