Evidence map›Paper›PMID 25888672›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2015

Whole-genome sequencing for national surveillance of Shiga toxin-producing Escherichia coli O157.

Timothy J Dallman, Lisa Byrne, Philip M Ashton, Lauren A Cowley, Neil T Perry, Goutam Adak, Liljana Petrovska, Richard J Ellis, Richard Elson, Anthony Underwood and 5 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

114 citing papers in PubMed.

  1. Review
  2. Mind the gap! TypingMicrobial genomics · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. An outbreak of Shiga toxin-producingEpidemiology and infection · 2025
    Article
  8. Hybrid strains of enterotoxigenic/Shiga toxin-producingJournal of medical microbiology · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Using SNP addresses forEpidemiology and infection · 2023
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Whole-genome sequencing of multidrug resistanceFrontiers in public health · 2023
    Article

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Timothy J DallmanPublic Health England, London.
Lisa ByrnePublic Health England, London.
Philip M AshtonPublic Health England, London.
Lauren A CowleyPublic Health England, London.
Neil T PerryPublic Health England, London.
Goutam AdakPublic Health England, London.
Liljana PetrovskaAnimal and Plant Health Agency, Addlestone, Surrey, United Kingdom.
Richard J EllisAnimal and Plant Health Agency, Addlestone, Surrey, United Kingdom.
Richard ElsonPublic Health England, London.
Anthony UnderwoodPublic Health England, London.
Jonathan GreenPublic Health England, London.
William P HanageHarvard School of Public Health, Boston, Massachusetts.
Claire JenkinsPublic Health England, London.
Kathie GrantPublic Health England, London.
John WainUniversity of East Anglia, Norwich, United Kingdom.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558NIGMS NIH HHS U54GM088558
6 · The paper itself

Abstract

backgroundNational 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.

methodsWe 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.

resultsEstimates 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.

conclusionsWGS 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.

Indexed as

Public Health SurveillanceDisease OutbreaksDNA, BacterialEscherichia coli InfectionsGenome, BacterialHumansPhylogenyRetrospective StudiesSequence Analysis, DNAShiga-Toxigenic Escherichia coliDNA, Bacterialnational surveillancepublic healthShiga toxin–producing Escherichia coli O157whole-genome sequencing

Identifiers

PMID25888672
PMCPMC4542925

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.