Noise-driven growth rate gain in clonal cellular populations

Mikihiro Hashimoto, Takashi Nozoe, Hidenori Nakaoka, Reiko Okura, Sayo Akiyoshi, Kunihiko Kaneko, Edo Kussell, Yuichi Wakamoto

Research output: Contribution to journalArticle

Abstract

Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a "speed limit" for proliferation.

Original languageEnglish (US)
Pages (from-to)3151-3156
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume113
Issue number12
DOIs
StatePublished - Mar 22 2016

Keywords

  • Age-structured population model
  • Cell lineage analysis
  • Growth law
  • Growth noise
  • Microfluidics

ASJC Scopus subject areas

  • General

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