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

IF 2.9 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS BMC Bioinformatics Pub Date : 2024-08-27 DOI:10.1186/s12859-024-05913-4

Mondher Khdhiri, Ella Thomas, Chanel de Smet, Priyanka Chandar, Induja Chandrakumar, Jean M Davidson, Paul Anderson, Samuel D Chorlton

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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 .

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refMLST：基于参考的多焦点序列分型可实现通用细菌分型。

背景：细菌爆发基因组调查的常用方法（包括 SNP 和逐基因方法）分别受到背景基因组和等位基因计划要求的限制。因此，这些方法只适用于部分已知生物，而对新型病原体或研究较少的病原体则无法奏效。我们引入了 refMLST，这是一种使用细菌参考基因组的逐基因方法，可形成一种可扩展、可重现且稳健的方法来执行疫情调查：结果：与 chewieSnake 等常用工具相比，当应用于包括 1263 个肠炎沙门氏菌、331 个小肠结肠炎耶尔森氏菌和 6526 个空肠弯曲菌基因组在内的多种导致疫情爆发的细菌时，refMLST 实现了一致的聚类、更高的分辨率和更快的处理速度。结论：refMLST 是一种新颖的多焦点序列分型方法，适用于任何具有公共参考基因组的细菌物种，不需要策划方案，并能自动考虑基因重组。可用性和实施：refMLST 可在 https://bugseq.com/academic 免费供学术界使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Bioinformatics 生物-生化研究方法

CiteScore

5.70

自引率

3.30%

发文量

506

审稿时长

4.3 months

期刊介绍： BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.