30 Citations (SciVal)

Abstract

F-type plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum β-lactamases, particularly in Enterobacterales. Organising this plasmid diversity is challenging, and current knowledge is largely based on plasmids from clinical settings. Here, we present a network community analysis of a large survey of F-type plasmids from environmental (influent, effluent and upstream/downstream waterways surrounding wastewater treatment works) and livestock settings. We use a tractable and scalable methodology to examine the relationship between plasmid metadata and network communities. This reveals how niche (sampling compartment and host genera) partition and shape plasmid diversity. We also perform pangenome-style analyses on network communities. We show that such communities define unique combinations of core genes, with limited overlap. Building plasmid phylogenies based on alignments of these core genes, we demonstrate that plasmid accessory function is closely linked to core gene content. Taken together, our results suggest that stable F-type plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The association of F-type plasmids with AMR may reflect their suitability for rapid niche adaptation.

Original languageEnglish
Pages (from-to)2322-2335
Number of pages14
JournalISME Journal
Volume15
Issue number8
Early online date1 Mar 2021
DOIs
Publication statusPublished - 31 Aug 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s).

Data Availability Statement

Plasmid sequence data, metadata (Table S1), Mash edge list
(Table S3), community validation metadata (Table S4),
PlasmidFinder output (Table S9), Plasmid MLST output
(Table S10) and Abricate NCBI output (Table S11) are
available in a figshare collection (https://doi.org/10.6084/m9.
figshare.c.5066684.v3). Other data can be found in ref. [21].

Acknowledgements

Thanks to Fowler P for his comments on
the draft.

Funding

This work was funded by the Antimicrobial Resistance Cross-council Initiative supported by the seven research councils [grant NE/N019989/1]. The UKCEH component of the REHAB consortirum was supported by the The Natural Environment Research Council (NERC) [grant NE/N019660/1]. Crook, George, Peto, Sheppard, Stoesser and Walker are supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare-Associated Infections and Antimicrobial Resistance at the University of Oxford in partnership with Public Health England (PHE) [grant HPRU-2012–10041 and NIHR200915]. Walker, Crook and Peto are also supported by the NIHR Oxford Biomedical Research Centre. Walker is an NIHR Senior Investigator. The computational aspects of this research were funded from the NIHR Oxford BRC with additional support from a Wellcome Trust Core Award Grant [grant 203141/Z/16/Z]. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England. Matlock is supported by a scholarship from the Medical Research Foundation National PhD Training Programme in Antimicrobial Resistance Research (MRF-145-0004-TPG-AVISO).

ASJC Scopus subject areas

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics

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