Evidence map›Paper›PMID 24850346›Full record

ArticleJournal of clinical microbiology2014

Whole-genome sequencing for high-resolution investigation of methicillin-resistant Staphylococcus aureus epidemiology and genome plasticity.

Dhruba J SenGupta, Lisa A Cummings, Daniel R Hoogestraat, Susan M Butler-Wu, Jay Shendure, Brad T Cookson, Stephen J Salipante

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Hospital Epidemiology of Methicillin-ResistantBioMed research international · 2018
    Article
  9. Article
  10. Article
  11. Article
  12. The implications of whole-genome sequencing in the control of tuberculosis.Therapeutic advances in infectious disease · 2016
    Review
  13. Article
  14. Article
  15. Article
  16. Article
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

7 authors.

Dhruba J SenGuptaDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
Lisa A CummingsDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
Daniel R HoogestraatDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
Susan M Butler-WuDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
Jay ShendureDepartment of Genome Sciences, University of Washington, Seattle, Washington, USA.
Brad T CooksonDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA Department of Microbiology, University of Washington, Seattle, Washington, USA.
Stephen J SalipanteDepartment of Laboratory Medicine, University of Washington, Seattle, Washington, USA stevesal@uw.edu.

Funding

Variation in Human Innate ImmunityU54AI057141 · NIAID · UNIVERSITY OF WASHINGTON · PI COOKSON, BRAD T · 2003 to 2013
$102.3M
Institute of Translational Health SciencesUL1TR000423 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$49.4M
NCATS NIH HHS UL1 TR000423NCATS NIH HHS UL1TR000423NIAID NIH HHS U54 AI057141NIAID NIH HHS U54AI057141-08REV
6 · The paper itself

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a major challenge in health care, yet the limited heterogeneity within this group hinders molecular investigations of related outbreaks. Pulsed-field gel electrophoresis (PFGE) has been the gold standard approach but is impractical for many clinical laboratories and is often replaced with PCR-based methods. Regardless, both approaches can prove problematic for identifying subclonal outbreaks. Here, we explore the use of whole-genome sequencing for clinical laboratory investigations of MRSA molecular epidemiology. We examine the relationships of 44 MRSA isolates collected over a period of 3 years by using whole-genome sequencing and two PCR-based methods, multilocus variable-number tandem-repeat analysis (MLVA) and spa typing. We find that MLVA offers higher resolution than spa typing, as it resolved 17 versus 12 discrete isolate groups, respectively. In contrast, whole-genome sequencing reproducibly cataloged genomic variants (131,424 different single nucleotide polymorphisms and indels across the strain collection) that uniquely identified each MRSA clone, recapitulating those groups but enabling higher-resolution phylogenetic inferences of the epidemiological relationships. Importantly, whole-genome sequencing detected a significant number of variants, thereby distinguishing between groups that were considered identical by both spa typing (minimum, 1,124 polymorphisms) and MLVA (minimum, 193 polymorphisms); this suggests that these more conventional approaches can lead to false-positive identification of outbreaks due to inappropriate grouping of genetically distinct strains. An analysis of the distribution of variants across the MRSA genome reveals 47 mutational hot spots (comprising ∼ 2.5% of the genome) that account for 23.5% of the observed polymorphisms, and the use of this selected data set successfully recapitulates most epidemiological relationships in this pathogen group.

Indexed as

Genetic VariationGenome, BacterialDNA, BacterialHumansMethicillin-Resistant Staphylococcus aureusMolecular EpidemiologyMolecular Sequence DataMolecular TypingSequence Analysis, DNAStaphylococcal InfectionsDNA, Bacterial

Identifiers

PMID24850346
PMCPMC4136142

What OpenQuestion holds

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Registered trials

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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.