ArticlePLoS computational biology2021
When to wake up? The optimal waking-up strategies for starvation-induced persistence.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Stress History Establishes a Transient Tolerant State That Shapes Antibiotic Survival Upon Resuscitation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Discreteness, Computation, and Rules of Life for Self-Organization Dynamics Beyond Equilibrium.Newton ((New York, N.Y.) · 2026Article
- Systematic design of pulse dosing to eradicate persister bacteria: The case of fluoroquinolones.Computers & chemical engineering · 2025Article
- Assessing methods for estimating microbial lag phase duration: a comparative analysis using Saccharomyces cerevisiae empirical and simulated data.FEMS yeast research · 2025Article
- Microbial life in slow and stopped lanes.Trends in microbiology · 2024Review
- Heterogeneous Phenotypic Responses of Antibiotic-ResistantAntibiotics (Basel, Switzerland) · 2023Article
- Review
- Systematic design of pulse dosing to eradicate persister bacteria.PLoS computational biology · 2023Article
- Memory shapes microbial populations.PLoS computational biology · 2021Article
- Phenotypic-dependent variability and the emergence of tolerance in bacterial populations.PLoS computational biology · 2021Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prolonged lag time can be induced by starvation contributing to the antibiotic tolerance of bacteria. We analyze the optimal lag time to survive and grow the iterative and stochastic application of antibiotics. A simple model shows that the optimal lag time can exhibit a discontinuous transition when the severeness of the antibiotic application, such as the probability to be exposed the antibiotic, the death rate under the exposure, and the duration of the exposure, is increased. This suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application. When the bacterial populations are able to have two phenotypes with different lag times, the fraction of the second phenotype that has different lag time shows a continuous transition. We then present a generic framework to investigate the optimal lag time distribution for total population fitness for a given distribution of the antibiotic application duration. The obtained optimal distributions have multiple peaks for a wide range of the antibiotic application duration distributions, including the case where the latter is monotonically decreasing. The analysis supports the advantage in evolving multiple, possibly discrete phenotypes in lag time for bacterial long-term fitness.
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Registered trials
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