Dormancy of bacteria can be induced by starvation stress as prolonged lag time, and often contributes to the antibiotic tolerance of bacteria. We analyze the optimal lag time for wake-up from the starvation to survive the iterative and stochastic application of antibiotics. By using a population dynamics model , we show that the optimal lag time exhibits a discontinuous transition from zero lag time to a finite lag time when the severeness of the application of the antibiotic is increased.  When the bacterial populations are able to split into subpopulations to have two phenotypes with different average lag time , the fraction of the finite lag time population shows continuous transition when changing the severeness of antibiotics application . The result suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application .
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 exhibits a discontinuous transition when the severeness of the antibiotic 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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Dormancy of bacteria
Prolonged lag time
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stress as prolonged lag time, and often contributes
contributing
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for wake-up from the starvation to survive
to survive and grow
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By using a population dynamics model , we show
A simple model shows
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from zero lag time to a finite lag time
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application of the
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This suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application.
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split into subpopulations to
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average lag time
lag times
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finite lag time population shows continuous transition when changing the severeness of antibiotics application . The result suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application
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