ArticleFrontiers in microbiology2016
Whole Genome Sequencing for Public Health Surveillance of Shiga Toxin-Producing Escherichia coli Other than Serogroup O157.
Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed, 65 citations in OpenAlex.
- Surveillance of enteropathogenicJournal of medical microbiology · 2026Article
- Mind the gap! TypingMicrobial genomics · 2026Article
- An outbreak of Shiga toxin-producingEpidemiology and infection · 2026Article
- Hybrid strains of enterotoxigenic/Shiga toxin-producingJournal of medical microbiology · 2025Article
- Epidemiology of Shiga toxin-producingJournal of medical microbiology · 2025Article
- National outbreak of Shiga toxin-producingEpidemiology and infection · 2024Article
- Genotypic analysis of Shiga toxin-producingJournal of medical microbiology · 2024Article
- A Comprehensive Review on Shiga Toxin Subtypes and Their Niche-Related Distribution Characteristics in Shiga-Toxin-ProducingMicroorganisms · 2024Review
- Analysis of Whole Genome Sequencing Data for Detection of Antimicrobial Resistance Determinants.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Whole-Genome Sequencing of Shiga Toxin-ProducingMicroorganisms · 2023Article
- Transforming Shiga toxin-producingFrontiers in microbiology · 2023Article
- Molecular characterization and phylogeny of Shiga toxin-producingFrontiers in microbiology · 2022Article
- Epidemiology and genomic analysis of Shiga toxin-producingJournal of medical microbiology · 2021Article
- Article
- Prevalence of IncFIB Plasmids Found amongPathogens (Basel, Switzerland) · 2021Article
- Epidemiological investigations identified an outbreak of Shiga toxin-producingEpidemiology and infection · 2021Article
- The emerging importance of Shiga toxin-producingJournal of medical microbiology · 2021Article
- Evidence of on-going transmission of Shiga toxin-producingEpidemiology and infection · 2021Article
- Phylogenetic structure of Shiga toxin-producingMicrobial genomics · 2021Article
- Assessing the genomic relatedness and evolutionary rates of persistent verotoxigenicMicrobial genomics · 2020Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Shiga toxin-producing Escherichia coli (STEC) are considered to be a significant threat to public health due to the severity of gastrointestinal symptoms associated with human infection. In England STEC O157 is the most commonly detected STEC serogroup, however, the implementation of PCR at local hospital laboratories has resulted in an increase in the detection of non-O157 STEC. The aim of this study was to evaluate the use of whole genome sequencing (WGS) for routine public health surveillance of non-O157 STEC by comparing this approach to phenotypic serotyping and PCR for subtyping the stx-encoding genes. Of the 102 isolates where phenotypic and genotypic serotyping could be compared, 98 gave fully concordant results. The most common non-O157 STEC serogroups detected were O146 (22) and O26 (18). All but one of the 38 isolates that could not be phenotypically serotyped (designated O unidentifiable or O rough) were serotyped using the WGS data. Of the 73 isolates where a flagella type was available by traditional phenotypic typing, all results matched the H-type derived from the WGS data. Of the 140 sequenced non-O157 isolates, 52 (37.1%) harboured stx1 only, 42 (30.0%) had stx2 only, 46 (32.9%) carried stx1 and stx2. Of these, stx subtyping PCR results were available for 131 isolates and 121 of these had concordant results with the stx subtype derived from the WGS data. Of the 10 discordant results, non-specific primer binding during PCR amplification, due to the similarity of the stx2 subtype gene sequences was the most likely cause. The results of this study showed WGS provided a reliable and robust one-step process for characterization of STEC. Deriving the full serotype from WGS data in real time has enabled us to report a higher level of strain discrimination while stx subtyping provides data on the pathogenic potential of each isolate, enabling us to predict clinical outcome of each case and to monitor the emergence of hyper-virulent strains.
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