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Disease-associated genotypes of the commensal skin bacterium Staphylococcus epidermidis

  • Guillaume Méric
  • , Leonardos Mageiros
  • , Johan Pensar
  • , Maisem Laabei
  • , Koji Yahara
  • , Ben Pascoe
  • , Nattinee Kittiwan
  • , Phacharaporn Tadee
  • , Virginia Post
  • , Sarah Lamble
  • , Rory Bowden
  • , James E Bray
  • , Mario Morgenstern
  • , Keith A Jolley
  • , Martin C J Maiden
  • , Edward J Feil
  • , Xavier Didelot
  • , Maria Miragaia
  • , Herminia de Lencastre
  • , T Fintan Moriarty
  • Holger Rohde, Ruth Massey, Dietrich Mack, Jukka Corander, Samuel K Sheppard
  • MRC CLIMB Consortium
  • AO Research Institute
  • University of Oxford
  • Imperial College London
  • University of Bristol
  • Bioscientia Labor Ingelheim, Institut für Medizinische Diagnostik GmbH
  • Wellcome Sanger Institute
  • Swansea University
  • University of Helsinki
  • Lund University
  • National Institute of Infectious Diseases
  • Chiang Mai University
  • University Hospital Basel
  • Universidade Nova de Lisboa
  • Rockefeller University
  • Universität Hamburg
  • University of Oslo

Research output: Contribution to journalArticlepeer-review

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Abstract

Some of the most common infectious diseases are caused by bacteria that naturally colonise humans asymptomatically. Combating these opportunistic pathogens requires an understanding of the traits that differentiate infecting strains from harmless relatives. Staphylococcus epidermidis is carried asymptomatically on the skin and mucous membranes of virtually all humans but is a major cause of nosocomial infection associated with invasive procedures. Here we address the underlying evolutionary mechanisms of opportunistic pathogenicity by combining pangenome-wide association studies and laboratory microbiology to compare S. epidermidis from bloodstream and wound infections and asymptomatic carriage. We identify 61 genes containing infection-associated genetic elements (k-mers) that correlate with in vitro variation in known pathogenicity traits (biofilm formation, cell toxicity, interleukin-8 production, methicillin resistance). Horizontal gene transfer spreads these elements, allowing divergent clones to cause infection. Finally, Random Forest model prediction of disease status (carriage vs. infection) identifies pathogenicity elements in 415 S. epidermidis isolates with 80% accuracy, demonstrating the potential for identifying risk genotypes pre-operatively.

Original languageEnglish
Article number5034
Pages (from-to)1-11
Number of pages11
JournalNature Communications
Volume9
Issue number1
Early online date28 Nov 2018
DOIs
Publication statusPublished - 1 Dec 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy

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