Literature DB >> 26764736

Optimality and adaptation of phenotypically switching cells in fluctuating environments.

Merzu Kebede Belete1,2,3, Gábor Balázsi1,2.   

Abstract

Stochastic switching between alternative phenotypic states is a common cellular survival strategy during unforeseen environmental fluctuations. Cells can switch between different subpopulations that proliferate at different rates in different environments. Optimal population growth is typically assumed to occur when phenotypic switching rates match environmental switching rates. However, it is not well understood how this optimum behaves as a function of the growth rates of phenotypically different cells. In this study, we use mathematical and computational models to test how the actual parameters associated with optimal population growth differ from those assumed to be optimal. We find that the predicted optimum is practically always valid if the environmental durations are long. However, the regime of validity narrows as environmental durations shorten, especially if subpopulation growth rate differences differ from each other (are asymmetric) in two environments. Furthermore, we study the fate of mutants with switching rates previously predicted to be optimal. We find that mutants which match their phenotypic switching rates with the environmental ones can only sweep the population if the assumed optimum is valid, but not otherwise.

Mesh:

Year:  2015        PMID: 26764736     DOI: 10.1103/PhysRevE.92.062716

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  7 in total

1.  Temporal encoding of bacterial identity and traits in growth dynamics.

Authors:  Carolyn Zhang; Wenchen Song; Helena R Ma; Xiao Peng; Deverick J Anderson; Vance G Fowler; Joshua T Thaden; Minfeng Xiao; Lingchong You
Journal:  Proc Natl Acad Sci U S A       Date:  2020-08-03       Impact factor: 11.205

2.  Late-Arriving Signals Contribute Less to Cell-Fate Decisions.

Authors:  Michael G Cortes; Jimmy T Trinh; Lanying Zeng; Gábor Balázsi
Journal:  Biophys J       Date:  2017-11-07       Impact factor: 4.033

3.  The emergence of metabolic heterogeneity and diverse growth responses in isogenic bacterial cells.

Authors:  Emrah Şimşek; Minsu Kim
Journal:  ISME J       Date:  2018-01-15       Impact factor: 10.302

4.  Horizontal gene transfer enables programmable gene stability in synthetic microbiota.

Authors:  Teng Wang; Andrea Weiss; Ammara Aqeel; Feilun Wu; Allison J Lopatkin; Lawrence A David; Lingchong You
Journal:  Nat Chem Biol       Date:  2022-09-01       Impact factor: 16.174

5.  Stochastic modeling of phenotypic switching and chemoresistance in cancer cell populations.

Authors:  Niraj Kumar; Gwendolyn M Cramer; Seyed Alireza Zamani Dahaj; Bala Sundaram; Jonathan P Celli; Rahul V Kulkarni
Journal:  Sci Rep       Date:  2019-07-26       Impact factor: 4.379

6.  Binary Expression Enhances Reliability of Messaging in Gene Networks.

Authors:  Leonardo R Gama; Guilherme Giovanini; Gábor Balázsi; Alexandre F Ramos
Journal:  Entropy (Basel)       Date:  2020-04-22       Impact factor: 2.524

7.  Epigenetic switching as a strategy for quick adaptation while attenuating biochemical noise.

Authors:  Mariana Gómez-Schiavon; Nicolas E Buchler
Journal:  PLoS Comput Biol       Date:  2019-10-28       Impact factor: 4.475

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.