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Optimising genomic approaches for identifying vancomycin-resistant Enterococcus faecium transmission in healthcare settings

Author

Listed:
  • Charlie Higgs

    (The University of Melbourne)

  • Norelle L. Sherry

    (The University of Melbourne
    The University of Melbourne
    Austin Health)

  • Torsten Seemann

    (The University of Melbourne
    The University of Melbourne)

  • Kristy Horan

    (The University of Melbourne)

  • Hasini Walpola

    (The University of Melbourne)

  • Paul Kinsella

    (Royal Melbourne Hospital)

  • Katherine Bond

    (Royal Melbourne Hospital)

  • Deborah A. Williamson

    (The University of Melbourne
    Royal Melbourne Hospital
    The Peter Doherty Institute for Infection and Immunity)

  • Caroline Marshall

    (The Peter Doherty Institute for Infection and Immunity)

  • Jason C. Kwong

    (The University of Melbourne
    Austin Health)

  • M. Lindsay Grayson

    (Austin Health
    The University of Melbourne)

  • Timothy P. Stinear

    (The University of Melbourne)

  • Claire L. Gorrie

    (The University of Melbourne
    The University of Melbourne)

  • Benjamin P. Howden

    (The University of Melbourne
    The University of Melbourne
    Austin Health)

Abstract

Vancomycin-resistant Enterococcus faecium (VREfm) is a major nosocomial pathogen. Identifying VREfm transmission dynamics permits targeted interventions, and while genomics is increasingly being utilised, methods are not yet standardised or optimised for accuracy. We aimed to develop a standardized genomic method for identifying putative VREfm transmission links. Using comprehensive genomic and epidemiological data from a cohort of 308 VREfm infection or colonization cases, we compared multiple approaches for quantifying genetic relatedness. We showed that clustering by core genome multilocus sequence type (cgMLST) was more informative of population structure than traditional MLST. Pairwise genome comparisons using split k-mer analysis (SKA) provided the high-level resolution needed to infer patient-to-patient transmission. The more common mapping to a reference genome was not sufficiently discriminatory, defining more than three times more genomic transmission events than SKA (3729 compared to 1079 events). Here, we show a standardized genomic framework for inferring VREfm transmission that can be the basis for global deployment of VREfm genomics into routine outbreak detection and investigation.

Suggested Citation

  • Charlie Higgs & Norelle L. Sherry & Torsten Seemann & Kristy Horan & Hasini Walpola & Paul Kinsella & Katherine Bond & Deborah A. Williamson & Caroline Marshall & Jason C. Kwong & M. Lindsay Grayson &, 2022. "Optimising genomic approaches for identifying vancomycin-resistant Enterococcus faecium transmission in healthcare settings," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28156-4
    DOI: 10.1038/s41467-022-28156-4
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    Cited by:

    1. Ouli Xie & Cameron Zachreson & Gerry Tonkin-Hill & David J. Price & Jake A. Lacey & Jacqueline M. Morris & Malcolm I. McDonald & Asha C. Bowen & Philip M. Giffard & Bart J. Currie & Jonathan R. Carape, 2024. "Overlapping Streptococcus pyogenes and Streptococcus dysgalactiae subspecies equisimilis household transmission and mobile genetic element exchange," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Mona L. Taouk & George Taiaroa & Sebastian Duchene & Soo Jen Low & Charlie K. Higgs & Darren Y. J. Lee & Shivani Pasricha & Nasra Higgins & Danielle J. Ingle & Benjamin P. Howden & Marcus Y. Chen & Ch, 2024. "Longitudinal genomic analysis of Neisseria gonorrhoeae transmission dynamics in Australia," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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