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Whole-genome sequencing for national surveillance of Shiga toxin-producing Escherichia coli O157.
Dallman, Timothy J; Byrne, Lisa; Ashton, Philip M; Cowley, Lauren A; Perry, Neil T; Adak, Goutam; Petrovska, Liljana; Ellis, Richard J; Elson, Richard; Underwood, Anthony; Green, Jonathan; Hanage, William P; Jenkins, Claire; Grant, Kathie; Wain, John.
Afiliação
  • Dallman TJ; Public Health England, London.
  • Byrne L; Public Health England, London.
  • Ashton PM; Public Health England, London.
  • Cowley LA; Public Health England, London.
  • Perry NT; Public Health England, London.
  • Adak G; Public Health England, London.
  • Petrovska L; Animal and Plant Health Agency, Addlestone, Surrey, United Kingdom.
  • Ellis RJ; Animal and Plant Health Agency, Addlestone, Surrey, United Kingdom.
  • Elson R; Public Health England, London.
  • Underwood A; Public Health England, London.
  • Green J; Public Health England, London.
  • Hanage WP; Harvard School of Public Health, Boston, Massachusetts.
  • Jenkins C; Public Health England, London.
  • Grant K; Public Health England, London.
  • Wain J; University of East Anglia, Norwich, United Kingdom.
Clin Infect Dis ; 61(3): 305-12, 2015 Aug 01.
Article em En | MEDLINE | ID: mdl-25888672
BACKGROUND: National surveillance of gastrointestinal pathogens, such as Shiga toxin-producing Escherichia coli O157 (STEC O157), is key to rapidly identifying linked cases in the distributed food network to facilitate public health interventions. In this study, we used whole-genome sequencing (WGS) as a tool to inform national surveillance of STEC O157 in terms of identifying linked cases and clusters and guiding epidemiological investigation. METHODS: We retrospectively analyzed 334 isolates randomly sampled from 1002 strains of STEC O157 received by the Gastrointestinal Bacteria Reference Unit at Public Health England, Colindale, in 2012. The genetic distance between each isolate, as estimated by WGS, was calculated and phylogenetic methods were used to place strains in an evolutionary context. RESULTS: Estimates of linked clusters representing STEC O157 outbreaks in England and Wales increased by 2-fold when WGS was used instead of traditional typing techniques. The previously unidentified clusters were often widely geographically distributed and small in size. Phylogenetic analysis facilitated identification of temporally distinct cases sharing common exposures and delineating those that shared epidemiological and temporal links. Comparison with multi locus variable number tandem repeat analysis (MLVA) showed that although MLVA is as sensitive as WGS, WGS provides a more timely resolution to outbreak clustering. CONCLUSIONS: WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Bacteriano / Infecções por Escherichia coli / Escherichia coli Shiga Toxigênica / Vigilância em Saúde Pública Tipo de estudo: Observational_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Bacteriano / Infecções por Escherichia coli / Escherichia coli Shiga Toxigênica / Vigilância em Saúde Pública Tipo de estudo: Observational_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article