First-passage-time statistics of growing microbial populations carry an imprint of initial conditions

Eric W Jones; Joshua Derrick; Roger M Nisbet; William B Ludington; David A Sivak

doi:10.1038/s41598-023-48726-w

First-passage-time statistics of growing microbial populations carry an imprint of initial conditions

Sci Rep. 2023 Dec 4;13(1):21340. doi: 10.1038/s41598-023-48726-w.

Authors

Eric W Jones¹, Joshua Derrick², Roger M Nisbet³, William B Ludington^{2

4}, David A Sivak⁵

Affiliations

¹ Department of Physics, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada. eric_jones_2@sfu.ca.
² Department of Biological Sciences and Engineering, Carnegie Institution for Science, Baltimore, MD, 21218, USA.
³ Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.
⁴ Department of Biology, Johns Hopkins University, Baltimore, MD, 21218, USA.
⁵ Department of Physics, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.

Abstract

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. In several stochastic models of exponential growth we show power-law relationships that relate variability in the time required to reach a threshold population size to growth rate and inoculum size. Population-growth experiments in E. coli and S. aureus with inoculum sizes ranging between 1 and 100 are consistent with these relationships. We quantify how noise accumulates over time, finding that it encodes-and can be used to deduce-information about the early growth rate of a population.

MeSH terms

Escherichia coli*
Models, Biological
Population Density
Staphylococcus aureus*
Stochastic Processes

Abstract

MeSH terms

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