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refMLST: reference-based multilocus sequence typing enables universal bacterial typing

Authors: Mondher Khdhiri; Ella Thomas; Chanel de Smet; Priyanka Chandar; Induja Chandrakumar; Jean M. Davidson; Paul Anderson; +1 Authors

refMLST: reference-based multilocus sequence typing enables universal bacterial typing

Abstract

Abstract Background Commonly used approaches for genomic investigation of bacterial outbreaks, including SNP and gene-by-gene approaches, are limited by the requirement for background genomes and curated allele schemes, respectively. As a result, they only work on a select subset of known organisms, and fail on novel or less studied pathogens. We introduce refMLST, a gene-by-gene approach using the reference genome of a bacterium to form a scalable, reproducible and robust method to perform outbreak investigation. Results When applied to multiple outbreak causing bacteria including 1263 Salmonella enterica , 331 Yersinia enterocolitica and 6526 Campylobacter jejuni genomes, refMLST enabled consistent clustering, improved resolution, and faster processing in comparison to commonly used tools like chewieSnake. Conclusions refMLST is a novel multilocus sequence typing approach that is applicable to any bacterial species with a public reference genome, does not require a curated scheme, and automatically accounts for genetic recombination. Availability and implementation : refMLST is freely available for academic use at https://bugseq.com/academic .

Related Organizations
Keywords

Epidemiology, QH301-705.5, Computer applications to medicine. Medical informatics, Multilocus sequence typing, R858-859.7, Salmonella enterica, Bacterial Typing Techniques, Disease Outbreaks, Campylobacter jejuni, Genomic, Reference genome, Biology (General), Genome, Bacterial, Software, Multilocus Sequence Typing, Yersinia enterocolitica

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Top 10%
Green
gold