Systems Biology Doctoral Training Centre, University of Oxford, Oxford, United Kingdom.
Genetics. 2010 Apr;184(4):1113-9. doi: 10.1534/genetics.109.113431. Epub 2010 Jan 25.
The ability of bacteria to spontaneously switch their expressed phenotype from an identical underlying genotype is now widely acknowledged. Mechanisms behind these switches have been shown to be evolvable. Important questions thus arise: In a fluctuating environment, under what conditions can stochastic switching evolve and how is the evolutionarily optimal switching rate related to the environmental changes? Here we derive exact analytical results for the long-term exponential population growth rate in a two-state periodically changing environment, where the environmental states vary in both their duration and in their impact on the fitness of each phenotype. Using methods from statistical physics we derive conditions under which nonswitching is evolutionarily optimal, and we furthermore demonstrate that the transition between the nonswitching and switching regimes is discontinuous (a first-order phase transition). Our general analytical method allows the evolutionary effects of asymmetries in selection pressures and environmental growth rates to be quantified. The evolutionary implications of our findings are discussed in relation to their to real-world applications in the light of recent experimental evidence.
现在人们普遍承认，细菌能够自发地将其表现型从相同的潜在基因型中切换出来。这些转换背后的机制已被证明是可进化的。因此，出现了一些重要的问题：在波动的环境中，随机转换在什么条件下可以进化，以及进化上最优的转换率与环境变化有什么关系？在这里，我们针对在两种状态周期性变化的环境中，推导了长期指数种群增长率的精确解析结果，其中环境状态在持续时间和对每种表现型适应性的影响方面都发生了变化。我们使用统计物理学的方法推导出了在什么条件下不切换是进化上最优的，并且我们进一步证明了不切换和切换之间的转变是不连续的（一级相变）。我们的通用分析方法允许定量评估选择压力和环境增长率不对称的进化影响。我们的研究结果的进化意义在根据最近的实验证据在现实世界应用中进行了讨论。
