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Matlock, W.

Publications and source records attributed to Matlock, W..

2 recordsLinked to original sources

Flanker: a tool for comparative genomics of gene flanking regions

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. These clusters, known as flank patterns, are based on Mash distances, allowing for easy comparison of 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 flank patterns, including both known and previously uncharacterised structural variants. For example, Flanker identified four Tn4401 profiles that could not be sufficiently characterised using TETyper or MobileElementFinder, demonstrating the utility of Flanker for flanking gene characterisation. Similarly, using a large (n=226) European isolate dataset, we confirm findings from a previous smaller study demonstrating association between Tn1999.2 and blaOXA-48 upregulation and demonstrate 17 flank patterns (compared to the 5 previously identified). More generally the demonstration in this study that flank patterns are associated with to 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. Data SummaryNCBI accession numbers for all sequencing data used in this study is provided in Supplementary Table 1. The analysis performed in this manuscript can be reproduced in a binder environment provided on the Flanker Github page (https://github.com/wtmatlock/flanker).

bioinformatics

Genomic network analysis of an environmental and livestock IncF plasmid population

IncF plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum {beta}-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.

bioinformatics