School of Physics and Astronomy, The University of Edinburgh, Edinburgh, United Kingdom.
Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.
PLoS Comput Biol. 2020 May 29;16(5):e1007930. doi: 10.1371/journal.pcbi.1007930. eCollection 2020 May.
Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.
表型延迟——即基因突变和相应表型表达之间的时间延迟——在进化模型中通常被忽视,但最近的研究表明,它可能比之前假设的更为普遍。在这里,我们使用计算机模拟和理论来研究表型延迟对细菌对抗生素耐药性进化的意义。我们考虑了三种可能导致表型延迟的机制:有效多倍体、抗生素敏感分子的稀释和耐药增强分子的积累。我们发现,只有在一个狭窄的参数范围内,积累耐药分子才是相关的,但敏感分子的稀释和有效多倍体都可以在广泛的参数范围内导致表型延迟。我们进一步研究了这些机制是否会影响药物治疗下的种群生存,从而解释卢里亚-德尔布吕克波动试验中估计的突变率之间的观察差异。虽然有效多倍体机制不会影响种群生存,但敏感分子的稀释会降低药物治疗下的生存概率,并低估波动试验中的突变率。稀释机制还改变了突变体数量的卢里亚-德尔布吕克分布的形状,我们表明,这种改进的分布为之前发表的实验数据提供了更好的拟合。