# Development and implementation of a core genome multilocus sequence typing scheme for Yersinia enterocolitica: a tool for surveillance and outbreak detection

## TL;DR

Researchers developed a high-resolution typing method for Yersinia enterocolitica to improve tracking and outbreak detection.

## Contribution

A core genome MLST scheme for Y. enterocolitica was developed and validated for outbreak surveillance.

## Key findings

- A cgMLST scheme with 2,582 genes was validated on 890 genomes with high coverage.
- Outbreak strains were identified using single linkage clustering at four allelic differences.
- Three major complex types (CT18, CT12, CT5) were frequently associated with outbreaks in Norway.

## Abstract

Yersinia enterocolitica (Y. enterocolitica)
is the most frequent etiological agent of yersiniosis and has been
responsible for several national outbreaks in Norway and elsewhere. A
standardized high-resolution method, such as core genome Multilocus Sequence
Typing (cgMLST), is needed for pathogen traceability at the national and
international levels. In this study, we developed and implemented a cgMLST
scheme for Y. enterocolitica. We designed a cgMLST scheme
in SeqSphere + using high-quality genomes from different Y.
enterocolitica biotype sublineages. The scheme was validated if
more than 95% of targets were found across all tested Y.
enterocolitica: 563 Norwegian genomes collected between 2012
and 2022 and 327 genomes from public data sets. We applied the scheme to
known outbreaks to establish a threshold for identifying major complex types
(CTs) based on the number of allelic differences. The final cgMLST scheme
included 2,582 genes with a median of 97.9% (interquartile range
97.6%–98.8%) targets found across all tested genomes. Analysis of
outbreaks identified all outbreak strains using single linkage clustering at
four allelic differences. This threshold identified 311 unique CTs in
Norway, of which CT18, CT12, and CT5 were identified as the most frequently
associated with outbreaks. The cgMLST scheme showed a very good performance
in typing Y. enterocolitica using diverse data sources and
was able to identify outbreak clusters. We recommend the implementation of
this scheme nationally and internationally to facilitate Y.
enterocolitica surveillance and improve outbreak response in
national and cross-border outbreaks.