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Abstract
Whole-genome sequencing (WGS)-based outbreak investigation has proven to be a valuable method for the surveillance of bacterial pathogens. Its utility has been successfully demonstrated using both gene-by-gene (cgMLST or wgMLST) and single-nucleotide polymorphism (SNP)-based approaches. Among the obstacles of implementing a WGS-based routine surveillance is the need for an exchange of large volumes of sequencing data, as well as a widespread reluctance to share sequence and metadata in public repositories, together with a lacking standardization of suitable bioinformatic tools and workflows. To address these issues, we present chewieSnake, an intuitive and simple-to-use cgMLST workflow. ChewieSnake builds on the allele calling software chewBBACA and extends it by the concept of allele hashing. The resulting hashed allele profiles can be readily compared between laboratories without the need of a central allele nomenclature. The workflow fully automates the computation of the allele distance matrix, cluster membership, and phylogeny and summarizes all important findings in an interactive HTML report. Furthermore, chewieSnake can join allele profiles generated at different laboratories and identify shared clusters, including a stable and intercommunicable cluster nomenclature, thus facilitating a joint outbreak investigation. We demonstrate the feasibility of the proposed approach with a thorough method comparison using publically available sequencing data for Salmonella enterica. However, chewieSnake is readily applicable to all bacterial taxa, provided that a suitable cgMLST scheme is available. The workflow is freely available as an open-source tool and can be easily installed via conda or docker.
Highlights
Whole-genome sequencing (WGS)-based typing approaches allow the highly discriminatory comparison of the similarity of bacterial genomes
Results of chewieSnake are in strong agreement with Enterobase, both approaches differ substantially regarding their implementation. This might be somewhat expected given that both methods rely on the same core genome multilocus sequence typing (MLST) (cgMLST) scheme
Our analyses revealed that distances in Enterobase tend to be larger, which are mainly caused by the greater number of loci available in Enterobase
Summary
Whole-genome sequencing (WGS)-based typing approaches allow the highly discriminatory comparison of the similarity of bacterial genomes. The National Center for Biotechnology Information (NCBI) pathogen detection pipeline is an SNP-based molecular typing system for global microbial surveillance based on publically available sequencing data. The National Center for Biotechnology Information (NCBI) pathogen detection pipeline is an SNP-based molecular typing system for global microbial surveillance based on publically available sequencing data1 Another high-resolution typing approach is the core genome/whole-genome multilocus sequence typing (cg/wgMLST), which was derived from the concept of classic multilocus sequence typing (MLST), with the distinction that the initial seven-gene multi-locus scheme was expanded to hundreds or thousands of gene loci (Maiden et al, 2013). CgMLST is a gene-by-gene approach, which functions by aligning complete or draft genome assemblies to a scheme consisting of a set of loci and a collection of associated numbered allele sequences. Large minimum-spanning trees can be visualized, e.g., with grapeTree (Zhou et al, 2018) or PHLYOViZ3 (Francisco et al, 2012)
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