Rapid Open-Source SNP-Based Clustering Offers an Alternative to Core Genome MLST for Outbreak Tracing in a Hospital Setting

快速开源的基于SNP的聚类方法为医院环境中的疫情追踪提供了一种替代核心基因组MLST的方法

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Abstract

Traditional genotyping methods for infection control of antimicrobial-resistant bacteria in healthcare settings have been supplemented by whole-genome sequencing (WGS), often relying on a gene-based approach, e.g., core genome multilocus sequence typing (cgMLST), to cluster-related samples. In this study, we compared clusters of methicillin-resistant Staphylococcus aureus (MRSA) and Enterococcus faecium analyzed with the commercial cgMLST software Ridom SeqSphere+ and with an open-source single-nucleotide polymorphism (SNP)-based phylogenetic analysis pipeline (PAPABAC). A total of 5,655 MRSA and 2,572 E. faecium patient isolates, collected between 2013 and 2018, were processed. Clusters of 1,844 MRSA and 1,355 E. faecium isolates were compared to cgMLST results, and epidemiological data were included when available. The phylogenies inferred by the two different technologies were highly concordant, and the MRSA SNP tree re-captured known hospital-related outbreaks and epidemiologically linked samples. PAPABAC has the advantage over Ridom SeqSphere+ to generate stable, referable clusters without the need for sequence assembly, and it is a free-of-charge, open-source alternative to the commercial software.

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