ArticlePloS one2013
Slow protein fluctuations explain the emergence of growth phenotypes and persistence in clonal bacterial populations.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 36 citations in OpenAlex.
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- Phenotypic heterogeneity in persisters: a novel 'hunker' theory of persistence.FEMS microbiology reviews · 2022Review
- Loss of phenotypic inheritance associated withProceedings of the National Academy of Sciences of the United States of America · 2020Article
- Ribosome Provisioning Activates a Bistable Switch Coupled to Fast Exit from Stationary Phase.Molecular biology and evolution · 2019Article
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- Division rate, cell size and proteome allocation: impact on gene expression noise and implications for the dynamics of genetic circuits.Royal Society open science · 2018Article
- Making sense of snapshot data: ergodic principle for clonal cell populations.Journal of the Royal Society, Interface · 2017Article
- Single-cell protein dynamics reproduce universal fluctuations in cell populations.The European physical journal. E, Soft matter · 2015Article
- Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model.Journal of pharmacokinetics and pharmacodynamics · 2015Article
- Bistability in a metabolic network underpins the de novo evolution of colony switching in Pseudomonas fluorescens.PLoS biology · 2015Article
- Article
- Tunable stochastic pulsing in the Escherichia coli multiple antibiotic resistance network from interlinked positive and negative feedback loops.PLoS computational biology · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
One of the most challenging problems in microbiology is to understand how a small fraction of microbes that resists killing by antibiotics can emerge in a population of genetically identical cells, the phenomenon known as persistence or drug tolerance. Its characteristic signature is the biphasic kill curve, whereby microbes exposed to a bactericidal agent are initially killed very rapidly but then much more slowly. Here we relate this problem to the more general problem of understanding the emergence of distinct growth phenotypes in clonal populations. We address the problem mathematically by adopting the framework of the phenomenon of so-called weak ergodicity breaking, well known in dynamical physical systems, which we extend to the biological context. We show analytically and by direct stochastic simulations that distinct growth phenotypes can emerge as a consequence of slow-down of stochastic fluctuations in the expression of a gene controlling growth rate. In the regime of fast gene transcription, the system is ergodic, the growth rate distribution is unimodal, and accounts for one phenotype only. In contrast, at slow transcription and fast translation, weakly non-ergodic components emerge, the population distribution of growth rates becomes bimodal, and two distinct growth phenotypes are identified. When coupled to the well-established growth rate dependence of antibiotic killing, this model describes the observed fast and slow killing phases, and reproduces much of the phenomenology of bacterial persistence. The model has major implications for efforts to develop control strategies for persistent infections.
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Registered trials
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