Periodic bottlenecks play a major role in shaping the adaptive dynamics of natural and laboratory populations of asexual microbes. Here we study how they affect the ‘Extent of Adaptation’ (EoA), in such populations. EoA, the average fitness gain relative to the ancestor, is the quantity of interest in a large number of microbial experimental-evolution studies which assume that for any given bottleneck size (N₀) and number of generations between bottlenecks (g), the harmonic mean size (HM = N₀g) will predict the ensuing evolutionary dynamics. However, there are no theoretical or empirical validations for HM being a good predictor of EoA. Using experimental-evolution with Escherichia coli and individual-based simulations, we show that HM fails to predict EoA (i.e., higher N₀g does not lead to higher EoA). This is because although higher g allows populations to arrive at superior benefits by entailing increased variation, it also reduces the efficacy of selection, which lowers EoA. We show that EoA can be maximized in evolution experiments by either maximizing N₀ and/or minimizing g. We also conjecture that N₀/g is a better predictor of EoA than N₀g. Our results call for a re-evaluation of the role of population size in predicting fitness trajectories. They also aid in predicting adaptation in asexual populations, which has important evolutionary, epidemiological and economic implications.

中文翻译：

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尽管需要更大的遗传变异，但更大的数量可能会阻碍无性种群的适应。

周期性瓶颈在塑造自然和实验室无性微生物种群的适应性动力学方面起着重要作用。在这里，我们研究了它们如何影响此类人群的“适应程度”（EoA）。EoA是相对于祖先的平均适应度增益，是许多微生物实验进化研究中的关注数量，这些实验假设对于任何给定的瓶颈大小（N ₀）和瓶颈之间的世代数（g），谐波平均大小（HM  =  N ₀ g）将预测随后的演化动力学。但是，对于HM没有理论或经验上的验证是EoA的良好预测指标。使用大肠埃希氏菌的实验进化和基于个体的模拟，我们表明HM无法预测EoA（即，较高的N ₀ g不会导致较高的EoA）。这是因为尽管较高的g通过增加变异使种群能够获得更高的收益，但同时也会降低选择的效率，从而降低EoA。我们表明，通过最大化N ₀和/或最小化g，可以在进化实验中最大化EoA。我们也猜想N ₀ / g比N ₀ g更能预测EoA。我们的结果要求对人口规模在预测健身轨迹中的作用进行重新评估。它们还有助于预测无性种群的适应，这对进化，流行病学和经济都有重要意义。