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bioRxiv · 10.1101/267658

Stochasticity of cellular growth: sources, propagation and consequences

Thomas, P.·Terradot, G.·Danos, V.·Weisse, A.
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Abstract

Cellular growth impacts a range of phenotypic responses. Identifying the sources of fluctuations in growth and how they propagate across the cellular machinery can unravel mechanisms that underpin cell decisions. We present a stochastic cell model linking gene expression, metabolism and replication to predict growth dynamics in single bacterial cells. In addition to several population-averaged data, the model quantitatively recovers how growth fluctuations in single cells change across nutrient conditions. We develop a framework to analyse stochastic chemical reactions coupled with cell divisions and use it to identify sources of growth heterogeneity. By visualising cross-correlations we then determine how such initial fluctuations propagate to growth rate and affect other cell processes. We further study antibiotic responses and find that complex drug-nutrient interactions can both enhance and suppress heterogeneity. Our results provide a predictive framework to integrate single-cell and bulk data and draw testable predictions with implications for antibiotic tolerance, evolutionary biology and synthetic biology.

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Thomas, P., Terradot, G., Danos, V., Weisse, A.. 2018-02-18. Stochasticity of cellular growth: sources, propagation and consequences. https://doi.org/10.1101/267658

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