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逆境中的多样性:微生物生存博弈中的概率策略

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

作者信息

Wolf Denise M, Vazirani Vijay V, Arkin Adam P

机构信息

Physical Biosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA.

出版信息

J Theor Biol. 2005 May 21;234(2):227-53. doi: 10.1016/j.jtbi.2004.11.020. Epub 2005 Jan 24.

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.

摘要

群体多样化策略在微生物中普遍存在,包括致病细菌的随机相变(RPV)、某些噬菌体和艾滋病毒中观察到的病毒潜伏,以及细菌应激反应的非遗传多样性。这些多样化策略在何种精确条件下具有优势尚未得到明确界定。我们构建了一个基于动态环境和细胞状态的群体生长模型。反过来,细胞状态之间的转变可能会受到细胞传感器对环境的可能存在噪声的读数的影响。对于各种类型的环境动态和细胞传感器能力,我们应用博弈论分析来推导生物体的进化稳定策略(ESS),并确定该策略何时是多样化。我们发现:(1)当无法感知不同选择环境之间的转变时,会选择RPV,它实现了一种帕隆多悖论,即失败策略之间的随机交替产生了获胜策略;(2)最佳RPV细胞切换率是环境生命周期不对称性和环境自相关的函数;(3)当传感器能够检测到环境转变但在识别新环境方面精度较差时,进入新环境时的概率性多样化会被选择;(4)在存在过量加性噪声的情况下,进化稳定性需要低通滤波。我们表明,即使RPV不是ESS,它也可能使生长率方差和由于“不幸”的环境动态导致的灭绝风险最小化。

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