4.5 Article

Single- cell genomics reveals population structures from in vitro evolutionary studies of Salmonella

期刊

MICROBIAL GENOMICS
卷 8, 期 9, 页码 -

出版社

MICROBIOLOGY SOC
DOI: 10.1099/mgen.0.000871

关键词

evolution; genomics; salmonella; single-cell

资金

  1. BBSRC Tools and Resources Development Fund Grant [BB/R022526/1]
  2. BBSRC Institute Strategic Programme Microbes in the Food Chain [BB/R012504/1, BBS/E/F/000PR10349]
  3. Core strategic Program of the Earlham Institute [BB/CCG1720/1]
  4. BBSRC New Investigator Grant [BB/P022073/1]

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Single-cell DNA sequencing can reveal hierarchical structures in cell populations and facilitate studies of clonal evolution. This study presents a single bacterial genomic analysis approach for in vitro evolution experiments and applies it to Salmonella's experimental evolution. The results show that the population exposed to antibiotic stress can develop resistance while maintaining diversity. This study demonstrates how high-throughput single-cell sequencing can enhance experimental studies of bacterial evolution.
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.

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