Salmonella enterica serotype Typhimurium (S. Typhimurium) is a leading cause of gastroenteritis and bacteraemia worldwide, and a model organism for the study of host-pathogen interactions. Two S. Typhimurium strains (SL1344 and ATCC14028) are widely used to study host-pathogen interactions, yet genotypic variation results in strains with diverse host range, pathogenicity and risk to food safety. The population structure of diverse strains of S. Typhimurium revealed a major phylogroup of predominantly sequence type 19 (ST19) and a minor phylogroup of ST36. The major phylogroup had a population structure with two high order clades (α and β) and multiple subclades on extended internal branches, that exhibited distinct signatures of host adaptation and anthropogenic selection. Clade α contained a number of subclades composed of strains from well characterized epidemics in domesticated animals, while clade β contained multiple subclades associated with wild avian species. The contrasting epidemiology of strains in clade α and β was reflected by the distinct distribution of antimicrobial resistance (AMR) genes, accumulation of hypothetically disrupted coding sequences (HDCS), and signatures of functional diversification. These observations were consistent with elevated anthropogenic selection of clade α lineages from adaptation to circulation in populations of domesticated livestock, and the predisposition of clade β lineages to undergo adaptation to an invasive lifestyle by a process of convergent evolution with of host adapted Salmonella serotypes. Gene flux was predominantly driven by acquisition and recombination of prophage and associated cargo genes, with only occasional loss of these elements. The acquisition of large chromosomally-encoded genetic islands was limited, but notably, a feature of two recent pandemic clones (DT104 and monophasic S. Typhimurium ST34) of clade α (SGI-1 and SGI-4).
Bibliographical noteFunding Information:
RAK was funded by the BBSRC Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent project(s) BBS/ E/F/000PR10348 and BBS/E/F/000PR10352, and by projects BB/J004529/1, BB/M025489/1 and BB/ N007964/1. NH was supported by a BBSRC funding for the Earlham Institute BB/CCG1720/1. EMA was supported by the BBSRC Institute Strategic Programme Gut Microbes and Health BB/ R012490/1 and its constituent project BBS/E/F/ 000PR10356. The genome sequencing for this work was carried out by the Genomics Pipelines group at the Earlham Institute which is funded as a BBSRC National Capability (BB/CCG1720/1). EMA was funded by the BBSRC Institute Strategic Programme Gut Microbes & Health BB/R012490/1 and its constituent projects BBS/E/F/000PR10353 and BBS/E/F/000PR10356. NFA was supported by the Quadram Institute Bioscience BBSRC funded Core Capability Grant (project number BB/ CCG1860/1). This research was supported in part by the NBI Computing infrastructure for Science (CiS) group through use of HPC resources. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors also acknowledge advice and informatics support from Andrew Page and Andrea Telatin from the Quadram Institute Bioscience informatics support group.
Copyright: © 2020 Bawn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.