Growing from a few cells: combined effects of initial stochasticity and cell-to-cell variability. Issue 153 (24th April 2019)

• Record Type: Journal Article
• Authors: Barizien, A.; Suryateja Jammalamadaka, M. S.; Amselem, G.; Baroud, Charles N.
• Is Part Of: Journal of the Royal Society interface. Volume 16:Issue 153(2019)
• Publication Date: 2019-04-24
• Subjects: microfluidics -- microbiology -- stochastic population dynamics; Physical sciences -- Research -- Periodicals; Life sciences -- Research -- Periodicals; Interdisciplinary research -- Periodicals; 570.5
• DOI: 10.1098/rsif.2018.0935
• Languages: English
• ISSNs: 1742-5689

Abstract

Abstract : The growth of a cell population from a large inoculum appears deterministic, although the division process is stochastic at the single-cell level. Microfluidic observations, however, display wide variations in the growth of small populations. Here we combine theory, simulations and experiments to explore the link between single-cell stochasticity and the growth of a population starting from a small number of individuals. The study yields descriptors of the probability distribution function (PDF) of the population size under three sources of stochasticity: cell-to-cell variability, uncertainty in the number of initial cells and generation-dependent division times. The PDF, rescaled to account for the exponential growth of the population, is found to converge to a stationary distribution. All moments of the PDF grow exponentially with the same growth rate, which depends solely on cell-to-cell variability. The shape of the PDF, however, contains the signature of all sources of stochasticity, and is dominated by the early stages of growth, and not by the cell-to-cell variability. Thus, probabilistic predictions of the growth of bacterial populations can be obtained with implications for both naturally occurring conditions and technological applications of single-cell microfluidics.