Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, United States.
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, United States.
Elife. 2024 Sep 6;13:e93146. doi: 10.7554/eLife.93146.
When examining bacterial genomes for evidence of past selection, the results depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by d/d, the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with opposite implications for dynamical intuition and applications of d/d. Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the d/d decay given only dozens of locally fluctuating selective pressures, which is realistic in the context of genomes. The success of the adaptive reversion model argues for interpreting low values of d/d obtained from long timescales with caution as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short timescales.
当检查细菌基因组以寻找过去选择的证据时,结果在很大程度上取决于所选基因组之间的突变距离。即使在细菌物种内部,突变距离较大的基因组表现出更强的净化选择证据,如 d/d 所示,即非同义突变与同义突变的归一化比值。在这里,我们表明,当应用于现有肠道微生物组数据时,这种尺度依赖性(弱净化选择)的经典解释会导致有问题的突变积累。我们提出了一种替代的适应性回复模型,该模型对动态直觉和 d/d 的应用具有相反的意义。由于种群规模大、世代时间短和环境多变,回复在微生物组中几乎可以在宿主内种群中发生和扩散。我们使用分析和模拟方法表明,适应性回复可以仅在数十个局部波动的选择压力下解释 d/d 的衰减,这在 基因组的背景下是现实的。适应性回复模型的成功表明,即使在适应性扩散频繁的情况下,也应该谨慎解释从长时间尺度获得的低 d/d 值,因为它们可能会出现。因此,我们的工作反转了细菌进化中一个旧观察结果的解释,说明了突变回复随时间塑造基因组景观的潜力,并强调了在短时间尺度上研究细菌基因组进化的重要性。