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Published November 11, 2014 | Supplemental Material + Published
Journal Article Open

Scaling laws governing stochastic growth and division of single bacterial cells

Abstract

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.

Additional Information

© 2014 National Academy of Sciences. Edited by Nigel Goldenfeld, University of Illinois at Urbana–Champaign, Urbana, IL, and approved September 19, 2014 (received for review February 20, 2014). Published ahead of print October 27, 2014. We thank Aretha Fiebig, Ariel Amir, Rutger Hermsen, Gurol Suel, Kingshuk Ghosh, Matt Scott, Terry Hwa, William Loomis, and Leo Kadanoff for insightful discussions. We thank the National Science Foundation (NSF) (NSF PHY-1305542) and the W. M. Keck Foundation for financial support. We also acknowledge partial financial and central facilities assistance of the University of Chicago Materials Research Science and Engineering Center, supported by the NSF (NSF DMR-MRSEC 0820054). Author contributions: S.I.-B., Y.L., A.R.D., and N.F.S. designed research; S.I.-B. and C.S.W. performed research; C.S.W. developed custom software for image analysis; S.I.-B., J.T.H., Y.L., and S.C. contributed new reagents/analytic tools; S.I.-B., C.S.W., K.L., and S.B. analyzed data; S.I.-B. and G.E.C. tested the stochastic Hinshelwood cycle model; and S.I.-B., A.R.D., and N.F.S. wrote the paper. The authors declare no conflict of interest. This Direct Submission article had a prearranged editor. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1403232111/-/DCSupplemental.

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Supplemental Material - pnas.201403232SI.pdf

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August 22, 2023
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