Literature DB >> 15757681

Diversity in times of adversity: probabilistic strategies in microbial survival games.

Denise M Wolf1, Vijay V Vazirani, Adam P Arkin.   

Abstract

Population diversification strategies are ubiquitous among microbes, encompassing random phase-variation (RPV) of pathogenic bacteria, viral latency as observed in some bacteriophage and HIV, and the non-genetic diversity of bacterial stress responses. Precise conditions under which these diversification strategies confer an advantage have not been well defined. We develop a model of population growth conditioned on dynamical environmental and cellular states. Transitions among cellular states, in turn, may be biased by possibly noisy readings of the environment from cellular sensors. For various types of environmental dynamics and cellular sensor capability, we apply game-theoretic analysis to derive the evolutionarily stable strategy (ESS) for an organism and determine when that strategy is diversification. We find that: (1) RPV, effecting a sort of Parrondo paradox wherein random alternations between losing strategies produce a winning strategy, is selected when transitions between different selective environments cannot be sensed, (2) optimal RPV cell switching rates are a function of environmental lifecycle asymmetries and environmental autocorrelation, (3) probabilistic diversification upon entering a new environment is selected when sensors can detect environmental transitions but have poor precision in identifying new environments, and (4) in the presence of excess additive noise, low-pass filtering is required for evolutionary stability. We show that even when RPV is not the ESS, it may minimize growth rate variance and the risk of extinction due to 'unlucky' environmental dynamics.

Entities:  

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Year:  2005        PMID: 15757681     DOI: 10.1016/j.jtbi.2004.11.020

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  94 in total

1.  Switching and growth for microbial populations in catastrophic responsive environments.

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4.  Phenotypic variability of growing cellular populations.

Authors:  Ting Lu; Tongye Shen; Matthew R Bennett; Peter G Wolynes; Jeff Hasty
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5.  The evolution of bet-hedging adaptations to rare scenarios.

Authors:  Oliver D King; Joanna Masel
Journal:  Theor Popul Biol       Date:  2007-08-31       Impact factor: 1.570

6.  Two-locus epistasis with sexually antagonistic selection: a genetic Parrondo's paradox.

Authors:  Floyd A Reed
Journal:  Genetics       Date:  2007-05-04       Impact factor: 4.562

7.  The evolution of reversible switches in the presence of irreversible mimics.

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Review 8.  Nature, nurture, or chance: stochastic gene expression and its consequences.

Authors:  Arjun Raj; Alexander van Oudenaarden
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9.  Adaptive Bet-Hedging Revisited: Considerations of Risk and Time Horizon.

Authors:  Omri Tal; Tat Dat Tran
Journal:  Bull Math Biol       Date:  2020-04-04       Impact factor: 1.758

10.  Engineering stochasticity in gene expression.

Authors:  Jeffrey J Tabor; Travis S Bayer; Zachary B Simpson; Matthew Levy; Andrew D Ellington
Journal:  Mol Biosyst       Date:  2008-05-01
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