Research makes it easier to identify Yersinia

Researchers at the Pasteur Institut in France have developed a genomic analysis method for classifying and identifying Yersinia strains and estimating pathogenicity.

The Yersinia genus covers a range of bacteria distinguished by criteria such as whether or not they are able to cause disease. It is part of the family Enterobacteriaceae and includes 19 species. The foodborne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis cause enteric yersiniosis, a disease transmissible by food. Strains within species such as Yersinia enterocolitica also vary in pathogenic properties.

Yersinia enterocolitica is the third biggest cause of bacterial diarrhea in temperate and cold countries after Salmonella and Campylobacter. In France, infections mostly occur in isolated cases or affect small groups.

How strains were identified
“Previously, strains were identified using biochemical methods, which sometimes lack precision. They rely on metabolic reactions, leading to misidentification in the event of atypical reactions,” said Cyril Savin, deputy director of the National Reference Center (CNR) for Plague and other Yersinia Infections at the Institut Pasteur in France.

A strategy applicable to all species of Yersinia would be useful as phenotypic identification is time-consuming, labor intensive and may lead to incorrect identifications. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is also not fully reliable.

Accurate identification is essential since pathogenicity differs among Yersinia strains. It enables more effective patient monitoring and can guide public health initiatives.

Scientists in the Pasteur Institute’s Biodiversity and Epidemiology of Bacterial Pathogens Unit with the CNR and Bioinformatics and Biostatistics Hub in the Department of Computational Biology developed a genome-based method of identifying strains of the Yersinia genus based on core-genome multilocus sequence typing (cgMLST). The study was published in the journal Microbial Genomics.

Performance of the method was assessed on 1,843 isolates collected by the French National Surveillance System and analyzed in parallel using phenotypic reference methods, leading to 98.4 percent agreement at species and infra-specific — biotype and serotype — levels. For 29 isolates, incorrect phenotypic assignments resulted from atypical biochemical characteristics or lack of phenotypic resolution.

Technique could help outbreak detection
“When we scanned the sequence of numerous genes in the Yersinia genome for each strain, we realized that each bacterium has its own unique genetic profile. The method involves transforming this genetic profile into a sort of standardized barcode,” said Sylvain Brisse, head of the Biodiversity and Epidemiology of Bacterial Pathogens Unit.

By applying the method to the Yersinia genus, more than 3,000 barcodes were identified, some of which revealed new species.

The work led to a standardized language enabling all labs to recognize the codes. Public access was given to a database of barcodes, or genomic profiles, and associated identification details, enabling labs worldwide to identify Yersinia strains using their own genomic sequences.

Unrestricted sharing of baseline genomic profiles and the associated barcodes will help research on genetic relationships between strains, enable detection of outbreaks and improve understanding of how strains are transmitted between the environment, animals, food, and humans.

Using an automated classification algorithm, each genomic profile is linked to its species and genetic lineage.

“Our comparison of the genetic profiles of Yersinia strains revealed an unexpected level of biodiversity including several new and previously unknown species. Strains can now be identified extremely reliably based on their genomic profile,” said Alexis Criscuolo, a bioinformatician in the Department of Computational Biology.

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