Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
Nat Ecol Evol. 2020 Mar;4(3):437-452. doi: 10.1038/s41559-020-1103-z. Epub 2020 Feb 24.
Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages in bacterial populations have so far prevented a detailed elucidation of evolutionary dynamics. Here, we overcome this hurdle by developing a chromosomal-barcoding technique that allows simultaneous tracking of approximately 450,000 distinct lineages in Escherichia coli, which we use to test the effect of sub-inhibitory concentrations of common antibiotics on the evolutionary dynamics of low-frequency lineages. We find that populations lose lineage diversity at distinct rates that correspond to their antibiotic regimen. We also determine that some lineages have similar fates across independent experiments. By analysing the trajectory dynamics, we attribute the reproducible fates of these lineages to the presence of pre-existing beneficial mutations, and we demonstrate how the relative contribution of pre-existing and de novo mutations varies across drug regimens. Finally, we reproduce the observed lineage dynamics by simulations. Altogether, our results provide a valuable methodology for studying bacterial evolution as well as insights into evolution under sub-inhibitory antibiotic levels.
在大型无性繁殖群体中,进化动态受到多种竞争有利谱系的强烈影响,其中大多数谱系以非常低的频率分离。然而,在细菌群体中跟踪大量这些稀有谱系的技术障碍迄今为止阻止了对进化动态的详细阐明。在这里,我们通过开发一种染色体编码技术克服了这一障碍,该技术允许同时跟踪大肠杆菌中大约 450,000 个不同的谱系,我们使用该技术来测试亚抑制浓度的常见抗生素对低频谱系进化动态的影响。我们发现,种群以与抗生素方案相对应的不同速率失去谱系多样性。我们还确定了一些谱系在独立实验中具有相似的命运。通过分析轨迹动态,我们将这些谱系的可重复命运归因于预先存在的有益突变的存在,并证明了预先存在和从头突变的相对贡献在不同的药物方案中是如何变化的。最后,我们通过模拟再现了观察到的谱系动态。总之,我们的研究结果为研究细菌进化提供了一种有价值的方法,也为亚抑制抗生素水平下的进化提供了深入的见解。