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Whole-Genome-Based Public Health Surveillance of Less Common Shiga Toxin-Producing Escherichia coli Serovars and Untypeable Strains Identifies Four Novel O Genotypes

Shiga toxin-producing Escherichia coli (STEC) and the STEC subgroup enterohemorrhagic E. coli cause intestinal infections with symptoms ranging from watery diarrhea to hemolytic-uremic syndrome (HUS). A key tool for the epidemiological differentiation of STEC is serotyping. The serotype in combinati...

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Detalles Bibliográficos
Autores principales: Lang, Christina, Hiller, Miriam, Konrad, Regina, Fruth, Angelika, Flieger, Antje
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6760944/
https://www.ncbi.nlm.nih.gov/pubmed/31366691
http://dx.doi.org/10.1128/JCM.00768-19
Descripción
Sumario:Shiga toxin-producing Escherichia coli (STEC) and the STEC subgroup enterohemorrhagic E. coli cause intestinal infections with symptoms ranging from watery diarrhea to hemolytic-uremic syndrome (HUS). A key tool for the epidemiological differentiation of STEC is serotyping. The serotype in combination with the main virulence determinants gives important insight into the virulence potential of a strain. However, a large fraction of STEC strains found in human disease, including strains causing HUS, belongs to less frequently detected STEC serovars or their O/H antigens are unknown or even untypeable. Recent implementation of whole-genome sequence (WGS) analysis, in principle, allows the deduction of serovar and virulence gene information. Therefore, here we compared classical serovar and PCR-based virulence marker detection with WGS-based methods for 232 STEC strains, focusing on less frequently detected STEC serovars and nontypeable strains. We found that the results of WGS-based extraction showed a very high degree of overlap with those of the more classical methods. Specifically, the rate of concordance was 97% for O antigens (OAGs) and 99% for H antigens (HAGs) of typeable strains and >99% for stx(1), stx(2), or eaeA for all strains. Ninety-eight percent of nontypeable OAGs and 100% of nontypeable HAGs were defined by WGS analysis. In addition, the novel methods enabled a more complete analysis of strains causing severe clinical symptoms and the description of four novel STEC OAG loci. In conclusion, WGS is a promising tool for gaining serovar and virulence gene information, especially from a public health perspective.