Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella.
Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella.
复制标题
单细胞基因组学揭示了沙门氏菌体外进化研究中的种群结构。
DOI：
10.1099/mgen.0.000871
复制
发表时间：
2022-09
影响因子：
3.9
通讯作者：
Macaulay, Iain C.
中科院分区：
文献类型：
--
作者：
Bawn, Matt;Hernandez, Johana;Trampari, Eleftheria;Thilliez, Gaetan;Quince, Christopher;Webber, Mark A.;Kingsley, Robert A.;Hall, Neil;Macaulay, Iain C.
单细胞DNA测序有可能揭示进化中细胞群体的详细层次结构。单细胞方法越来越多地用于研究人类衰老和癌症中的克隆进化，但尚未部署到研究进化中的克隆微生物种群。在这里，我们提出了一种方法，用于单个细菌的基因组分析，在体外进化实验中使用FACS分离的单个细菌，然后进行全基因组扩增和测序。我们将其应用于一个超变菌株的实验进化， 沙门 抗生素应激（环丙沙星）。通过分析来自人群的单个细胞中的序列多态性，我们确定了亚群的存在和患病率，这些亚群在先前被证明与环丙沙星敏感性相关的基因中获得了多态性。我们还能够确定暴露于抗生素压力的人群能够在保持多样性的同时产生耐药性。这种群体结构无法从大量序列数据中解析，我们的研究结果显示了高通量单细胞测序如何增强细菌进化的实验研究。
Single-cell DNA sequencing has the potential to reveal detailed hierarchical structures in evolving populations of cells. Single cell approaches are increasingly used to study clonal evolution in human ageing and cancer but have not yet been deployed to study evolving clonal microbial populations. Here, we present an approach for single bacterial genomic analysis for in vitro evolution experiments using FACS isolation of individual bacteria followed by whole-genome amplification and sequencing. We apply this to the experimental evolution of a hypermutator strain of Salmonella in response to antibiotic stress (ciprofloxacin). By analysing sequence polymorphisms in individual cells from populations we identified the presence and prevalence of sub-populations which have acquired polymorphisms in genes previously demonstrated to be associated with ciprofloxacin susceptibility. We were also able to identify that the population exposed to antibiotic stress was able to develop resistance whilst maintaining diversity. This population structure could not be resolved from bulk sequence data, and our results show how high-throughput single-cell sequencing can enhance experimental studies of bacterial evolution.
登录
查看更多内容
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
4.4
作者：
Raghunathan, A;Ferguson, HR;Lasken, RS
通讯作者：
Lasken, RS
影响因子：
28.3
作者：
Parks, Donovan H.;Rinke, Christian;Tyson, Gene W.
通讯作者：
Tyson, Gene W.
影响因子：
3.6
作者：
Mattiuzzo, Maura;Bandiera, Antonella;Scocchi, Marco
通讯作者：
Scocchi, Marco
影响因子：
4.8
作者：
Cooper, Vaughn S.
通讯作者：
Cooper, Vaughn S.