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.

Analysing the flanking sequences surrounding genes of interest is often highly relevant to understanding the role of mobile genetic elements (MGEs) in horizontal gene transfer, particular for antimicrobial-resistance genes. Here, we present Flanker, a Python package that performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of MGEs without prior knowledge of their structure. These clusters, known as ‘flank patterns’ (FPs), are based on Mash distances, allowing for easy comparison of similarity across sequences. Additionally, Flanker can be flexibly parameterized to fine-tune outputs by characterizing upstream and downstream regions separately, and investigating variable lengths of flanking sequence. We apply Flanker to two recent datasets describing plasmid-associated carriage of important carbapenemase genes (bla OXA-48 and bla KPC-2/3) and show that it successfully identifies distinct clusters of FPs, including both known and previously uncharacterized structural variants. For example, Flanker identified four Tn4401 profiles that could not be sufficiently characterized using TETyper or MobileElementFinder, demonstrating the utility of Flanker for flanking-gene characterization. Similarly, using a large (n=226) European isolate dataset, we confirm findings from a previous smaller study demonstrating association between Tn1999.2 and bla OXA-48 upregulation and demonstrate 17 FPs (compared to the 5 previously identified). More generally, the demonstration in this study that FPs are associated with geographical regions and antibiotic-susceptibility phenotypes suggests that they may be useful as epidemiological markers. Flanker is freely available under an MIT license at https://github.com/wtmatlock/flanker.

Plasmids carry genes conferring antimicrobial resistance (AMR), and other clinically important traits; their ability to move within and between species may provide the machinery for rapid dissemination of such genes. Despite this, existing studies using complete plasmid assemblies, which are essential for reliable inference, have been small and/or limited to those carrying particularly antimicrobial resistance genes (ARGs). In this study, we sequenced 1,880 complete plasmids from 738 isolates from bloodstream infections (BSI) in 2009 (194 isolates) and 2018 (368 isolates) in Oxfordshire, UK, plus a stratified selection from intervening years (176 isolates). We demonstrate that plasmids are largely, but not entirely, constrained to host species, although there is substantial overlap between species of plasmid gene-repertoire. Plasmids carrying ARGs (including those encoding carbapenemases) share a putative "backbone" of core genes with those carrying no such genes. Most ARGs are carried by a relatively small number of plasmid groups with biological features that are predictable. These findings suggest that future surveillance should, in addition to tracking plasmids currently associated with clinically important genes, focus on identifying and monitoring the dissemination of high-risk plasmid groups with the potential to rapidly acquire and disseminate these genes.

Analysing the flanking sequences surrounding genes of interest is often highly relevant to understanding the role of mobile genetic elements (MGEs) in horizontal gene transfer, particular for antimicrobial resistance genes. Here, we present Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of MGEs without prior knowledge of their structure. Flanker clusters flanking sequences based on Mash distances, allowing for easy comparison of similarity and the extent of this similarity across sequences. Additionally, Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence. We apply Flanker to two recent datasets describing plasmid-associated carriage of important carbapenemase genes (blaOXA-48 and blaKPC-2/3) and show that it successfully identifies distinct clusters of flanking sequences (flank patterns), including both known and previously uncharacterised structural variants. We demonstrate that flank patterns are linked to geographical regions and carbapenem phenotypes, suggesting they may be useful as epidemiological markers. Flanker is freely available under an MIT license at https://github.com/wtmatlock/flanker.

Plasmids enable the dissemination of antimicrobial resistance (AMR) in common Enterobacterales pathogens, representing a major public health challenge. However, the extent of plasmid sharing and evolution between Enterobacterales causing human infections and other niches remains unclear, including the emergence of resistance plasmids. Dense, unselected sampling is highly relevant to developing our understanding of plasmid epidemiology and designing appropriate interventions to limit the emergence and dissemination of plasmid-associated AMR. We established a geographically and temporally restricted collection of human bloodstream infection (BSI)-associated, livestock-associated (cattle, pig, poultry, and sheep faeces, farm soils) and wastewater treatment work (WwTW)-associated (influent, effluent, waterways upstream/downstream of effluent outlets) Enterobacterales. Isolates were collected between 2008-2020 from sites <60km apart in Oxfordshire, UK. Pangenome analysis of plasmid clusters revealed shared 'backbones', with phylogenies suggesting an intertwined ecology where well-conserved plasmid backbones carry diverse accessory functions, including AMR genes. Many plasmid 'backbones' were seen across species and niches, raising the possibility that plasmid movement between these followed by rapid accessory gene change could be relatively common. Overall, the signature of identical plasmid sharing is likely to be a highly transient one, implying that plasmid movement might be occurring at greater rates than previously estimated, raising a challenge for future genomic One Health studies.

Horizontal gene transfer in Enterobacterales allows mobile genetic elements to move between strains, species, and genera. In particular, the movement of plasmids is a known route for rapid dissemination of antimicrobial resistance (AMR) genes. However, it is difficult to establish to what extent plasmids are shared between Enterobacterales causing human infections and those from non-human sources, such as livestock or the environment. While some previous studies have found only limited evidence for genetic overlap, these have often been limited in size, restricted to drug-resistant isolates, and have used fragmented genome assemblies. Here, we report a collection of geographically and temporally restricted isolates from human bloodstream infections (BSI), environmental soils, livestock (cattle, pigs, poultry, sheep), wastewater (influent, effluent), and rivers. Isolates were all collected between 2008-2018 from sampling sites <60km apart. The combined dataset contains 1,458 complete Enterobacterales genomes, including 3,697 circularised plasmids of which one third were unclassifiable. We find eight groups of near-identical plasmids seen in both human BSI and non-human isolates, of which two are conjugative F-type plasmids carrying AMR genes. We cluster plasmids based on alignment-free distances and find that 73/247 (30%) plasmid clusters contain plasmids from both human BSI and non-human isolates. Pangenome-style analyses of the 69 most prevalent clusters (1,832/3,697 plasmids) reveals sets of shared core genes alongside accessory gene repertoires. Core-gene phylogenies suggest an intertwined ecology where well-conserved putative plasmid 'backbones' carry diverse accessory functions, potentially linked to niche adaptation. Furthermore, we show that closely related human and non-human plasmids are frequently found across distantly related bacterial hosts. Our findings underline the importance of diverse sampling in 'One Health' approaches for AMR management.

IncF plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum β-lactamases, particularly in Enterobacteriaceae. 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 IncF 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 IncF plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The recent association of IncF plasmids with AMR likely reflects their suitability for rapid niche adaptation.

Global consumption of antibiotics has accelerated the evolution of bacterial antimicrobial resistance. Yet, the risks from increasing bacterial antimicrobial resistance are not restricted to human populations: transmission of antimicrobial resistant bacteria occurs between humans, farms, the environment and other reservoirs. Policies that take a ‘One Health’ approach deal with this cross-reservoir spread, but are often more restrictive concerning human actions than policies that focus on a single reservoir. As such, the burden of justification lies with these more restrictive policies. We argue that an ethical justification for preferring One Health policies over less restrictive alternatives relies on empirical evidence as well as theory. The ethical justification for these policies is based on two arguments: (i) comparatively greater effectiveness, and (ii) comparatively better tracking of moral responsibility. Yet the empirical assumptions on which these claims rest are limited by existing empirical knowledge. Using livestock farming as an example, we suggest that scientific research into characterising antimicrobial resistance and linking practices to outcomes ought to be guided (at least in part) by the imperative to supply the context-specific data needed to ethically justify preferring a One Health policy over less restrictive alternatives.