van Dijk Thomas, Hwang Sungmin, Krug Joachim, de Visser J Arjan G M, Zwart Mark P
Laboratory of Genetics, Wageningen University, Wageningen, Netherlands. These authors contributed equally.
Phys Biol. 2017 Aug 21;14(5):055005. doi: 10.1088/1478-3975/aa7f36.
Whether evolution can be predicted is a key question in evolutionary biology. Here we set out to better understand the repeatability of evolution, which is a necessary condition for predictability. We explored experimentally the effect of mutation supply and the strength of selective pressure on the repeatability of selection from standing genetic variation. Different sizes of mutant libraries of antibiotic resistance gene TEM-1 β-lactamase in Escherichia coli, generated by error-prone PCR, were subjected to different antibiotic concentrations. We determined whether populations went extinct or survived, and sequenced the TEM gene of the surviving populations. The distribution of mutations per allele in our mutant libraries followed a Poisson distribution. Extinction patterns could be explained by a simple stochastic model that assumed the sampling of beneficial mutations was key for survival. In most surviving populations, alleles containing at least one known large-effect beneficial mutation were present. These genotype data also support a model which only invokes sampling effects to describe the occurrence of alleles containing large-effect driver mutations. Hence, evolution is largely predictable given cursory knowledge of mutational fitness effects, the mutation rate and population size. There were no clear trends in the repeatability of selected mutants when we considered all mutations present. However, when only known large-effect mutations were considered, the outcome of selection is less repeatable for large libraries, in contrast to expectations. We show experimentally that alleles carrying multiple mutations selected from large libraries confer higher resistance levels relative to alleles with only a known large-effect mutation, suggesting that the scarcity of high-resistance alleles carrying multiple mutations may contribute to the decrease in repeatability at large library sizes.
进化是否可以预测是进化生物学中的一个关键问题。在此,我们着手更好地理解进化的可重复性,这是可预测性的必要条件。我们通过实验探究了突变供应和选择压力强度对从现有遗传变异中进行选择的可重复性的影响。利用易错PCR产生的不同大小的大肠杆菌抗生素抗性基因TEM - 1β - 内酰胺酶突变文库,使其经受不同的抗生素浓度。我们确定了群体是灭绝还是存活,并对存活群体的TEM基因进行了测序。我们突变文库中每个等位基因的突变分布遵循泊松分布。灭绝模式可以用一个简单的随机模型来解释,该模型假设有益突变的抽样是生存的关键。在大多数存活群体中,存在含有至少一个已知的大效应有益突变的等位基因。这些基因型数据也支持一个仅调用抽样效应来描述含有大效应驱动突变的等位基因出现的模型。因此,鉴于对突变适合度效应、突变率和群体大小的粗略了解,进化在很大程度上是可预测的。当我们考虑所有存在的突变时,所选突变体的可重复性没有明显趋势。然而,当仅考虑已知的大效应突变时,与预期相反,大文库的选择结果重复性较低。我们通过实验表明,从大文库中选择的携带多个突变的等位基因相对于仅含有一个已知大效应突变的等位基因具有更高的抗性水平,这表明携带多个突变的高抗性等位基因的稀缺可能导致大文库规模下重复性的降低。