Evidence map›Paper›PMID 25373147›Full record

ArticleGenome research2015

Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains.

Stephen J Salipante, David J Roach, Jacob O Kitzman, Matthew W Snyder, Bethany Stackhouse, Susan M Butler-Wu, Choli Lee, Brad T Cookson, Jay Shendure

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed, 2 pooled it
–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

98 citing papers in PubMed, 2 syntheses or guidelines pooled it, 164 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Article
  7. A gentle introduction to pangenomics.Briefings in bioinformatics · 2024
    Review
  8. Article
  9. Article
  10. Distribution ofInternational journal of molecular sciences · 2024
    Article
  11. Clinical and Genomic Characterization of a Cohort of Patients With Klebsiella pneumoniae Bloodstream Infection.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

38 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

9 authors at 2 institutions in 2 countries.

Stephen J SalipanteDepartment of Laboratory Medicine.
David J RoachDepartment of Genome Sciences.
Jacob O KitzmanDepartment of Genome Sciences.
Matthew W SnyderDepartment of Genome Sciences.
Bethany StackhouseDepartment of Genome Sciences.
Susan M Butler-WuDepartment of Laboratory Medicine.
Choli LeeDepartment of Genome Sciences.
Brad T CooksonDepartment of Laboratory Medicine, Department of Microbiology, University of Washington, Seattle, Washington 98195, USA.
Jay ShendureDepartment of Genome Sciences, stevesal@uw.edu shendure@uw.edu.
Human Genome Sciences (United States) · USUniversity of Washington · US

Funding

Variation in Human Innate ImmunityU54AI057141 · NIAID · UNIVERSITY OF WASHINGTON · PI COOKSON, BRAD T · 2003 to 2013
$102.3M
NIAID NIH HHS 5U54AI057141-08REVNIAID NIH HHS U54 AI057141
6 · The paper itself

Abstract

Large-scale bacterial genome sequencing efforts to date have provided limited information on the most prevalent category of disease: sporadically acquired infections caused by common pathogenic bacteria. Here, we performed whole-genome sequencing and de novo assembly of 312 blood- or urine-derived isolates of extraintestinal pathogenic (ExPEC) Escherichia coli, a common agent of sepsis and community-acquired urinary tract infections, obtained during the course of routine clinical care at a single institution. We find that ExPEC E. coli are highly genomically heterogeneous, consistent with pan-genome analyses encompassing the larger species. Investigation of differential virulence factor content and antibiotic resistance phenotypes reveals markedly different profiles among lineages and among strains infecting different body sites. We use high-resolution molecular epidemiology to explore the dynamics of infections at the level of individual patients, including identification of possible person-to-person transmission. Notably, a limited number of discrete lineages caused the majority of bloodstream infections, including one subclone (ST131-H30) responsible for 28% of bacteremic E. coli infections over a 3-yr period. We additionally use a microbial genome-wide-association study (GWAS) approach to identify individual genes responsible for antibiotic resistance, successfully recovering known genes but notably not identifying any novel factors. We anticipate that in the near future, whole-genome sequencing of microorganisms associated with clinical disease will become routine. Our study reveals what kind of information can be obtained from sequencing clinical isolates on a large scale, even well-characterized organisms such as E. coli, and provides insight into how this information might be utilized in a healthcare setting.

Indexed as

Genome, BacterialAdolescentAdultAgedAged, 80 and overChildChild, PreschoolDNA, BacterialDrug Resistance, Multiple, BacterialEscherichia coliFemaleGene LibraryGenetic Association StudiesHumansInfantInfant, NewbornDNA, BacterialVirulence Factors

Identifiers

PMID25373147
PMCPMC4317167
OpenAlexW2050449050

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.