School of Physics and Astronomy, The University of Edinburgh, Peter Guthrie Tait Road, Edinburgh, EH9 3FD, United Kingdom.
Centre for Synthetic and Systems Biology, The University of Edinburgh, Edinburgh, EH9 3FD, United Kingdom.
Sci Rep. 2018 Jun 12;8(1):8941. doi: 10.1038/s41598-018-27095-9.
Stochastic phenotype switching has been suggested to play a beneficial role in microbial populations by leading to the division of labour among cells, or ensuring that at least some of the population survives an unexpected change in environmental conditions. Here we use a computational model to investigate an alternative possible function of stochastic phenotype switching: as a way to adapt more quickly even in a static environment. We show that when a genetic mutation causes a population to become less fit, switching to an alternative phenotype with higher fitness (growth rate) may give the population enough time to develop compensatory mutations that increase the fitness again. The possibility of switching phenotypes can reduce the time to adaptation by orders of magnitude if the "fitness valley" caused by the deleterious mutation is deep enough. Our work has important implications for the emergence of antibiotic-resistant bacteria. In line with recent experimental findings, we hypothesise that switching to a slower growing - but less sensitive - phenotype helps bacteria to develop resistance by providing alternative, faster evolutionary routes to resistance.
随机表型转换被认为在微生物群体中发挥有益作用，通过导致细胞分工，或者确保至少部分群体在环境条件的意外变化中存活。在这里，我们使用计算模型来研究随机表型转换的另一种可能功能：作为一种即使在静态环境中也能更快适应的方式。我们表明，当遗传突变导致种群适应性降低时，转换为具有更高适应性（生长速度）的替代表型可能会给种群足够的时间来发展补偿性突变，从而再次提高适应性。如果由有害突变引起的“适应性低谷”足够深，那么表型转换的可能性可以将适应时间减少几个数量级。我们的工作对出现抗生素耐药菌具有重要意义。与最近的实验结果一致，我们假设向生长速度较慢但敏感性较低的表型转换有助于细菌通过提供更快的进化途径来获得耐药性，从而产生耐药性。
