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A bacterial size law revealed by a coarse-grained model of cell physiology

Bertaux, F; von Kugelgen, J; Marguerat, S; Shahrezaei, V; (2020) A bacterial size law revealed by a coarse-grained model of cell physiology. PLOS Computational Biology , 16 (9) 10.1371/journal.pcbi.1008245. Green open access

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Abstract

Universal observations in Biology are sometimes described as “laws”. In E. coli, experimental studies performed over the past six decades have revealed major growth laws relating ribosomal mass fraction and cell size to the growth rate. Because they formalize complex emerging principles in biology, growth laws have been instrumental in shaping our understanding of bacterial physiology. Here, we discovered a novel size law that connects cell size to the inverse of the metabolic proteome mass fraction and the active fraction of ribosomes. We used a simple whole-cell coarse-grained model of cell physiology that combines the proteome allocation theory and the structural model of cell division. This integrated model captures all available experimental data connecting the cell proteome composition, ribosome activity, division size and growth rate in response to nutrient quality, antibiotic treatment and increased protein burden. Finally, a stochastic extension of the model explains non-trivial correlations observed in single cell experiments including the adder principle. This work provides a simple and robust theoretical framework for studying the fundamental principles of cell size determination in unicellular organisms.

Type: Article
Title: A bacterial size law revealed by a coarse-grained model of cell physiology
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1008245
Publisher version: https://doi.org/10.1371/journal.pcbi.1008245
Language: English
Additional information: © 2020 Bertaux et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio
URI: https://discovery.ucl.ac.uk/id/eprint/10134073
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