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Nat Commun. 2018 Nov 28;9(1):5034. doi: 10.1038/s41467-018-07368-7.

Disease-associated genotypes of the commensal skin bacterium Staphylococcus epidermidis.

Author information

1
The Milner Centre for Evolution, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
2
Swansea University Medical School, Swansea University, Singleton Campus, Swansea, SA2 8PP, UK.
3
Department of Mathematics and Statistics, University of Helsinki, Helsinki, 00100, Finland.
4
Medical Protein Chemistry, Department of Translational Medicine, Lund University, Malmö, 205 02, Sweden.
5
Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, 162-8640, Japan.
6
MRC Cloud-based Infrastructure for Microbial Bioinformatics (CLIMB) Consortium, Bath, BA2 7AY, UK.
7
Integrative Research Centre for Veterinary Preventive Medicine, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
8
Graduate School, Maejo University, Chiang Mai, 50290, Thailand.
9
AO Research Institute Davos, Davos, 7270, Switzerland.
10
Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
11
Department of Zoology, University of Oxford, Oxford, OX1 3SZ, UK.
12
Department of Orthopaedic Surgery and Traumatology, University Hospital Basel, Basel, 4031, Switzerland.
13
Department of Infectious Disease Epidemiology, Imperial College, London, SW7 2AZ, UK.
14
Laboratory of Molecular Genetics, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, 2775-412, Portugal.
15
Laboratory of Microbiology and Infectious Diseases, The Rockefeller University, New York, New York, 10065, USA.
16
Institut für Medizinische Mikrobiologie, Virologie & Hygiene, Universität Hamburg, Hamburg, 20246, Germany.
17
School of Cellular and Molecular Medicine, University of Bristol, Bristol, BS8 1TD, UK.
18
Bioscientia Labor Ingelheim, Institut für Medizinische Diagnostik GmbH, Ingelheim, 55218, Germany.
19
Department of Biostatistics, University of Oslo, Oslo, 0372, Norway.
20
Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK.
21
The Milner Centre for Evolution, University of Bath, Claverton Down, Bath, BA2 7AY, UK. s.k.sheppard@bath.ac.uk.
22
MRC Cloud-based Infrastructure for Microbial Bioinformatics (CLIMB) Consortium, Bath, BA2 7AY, UK. s.k.sheppard@bath.ac.uk.
23
Department of Zoology, University of Oxford, Oxford, OX1 3SZ, UK. s.k.sheppard@bath.ac.uk.

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.

PMID:
30487573
PMCID:
PMC6261936
DOI:
10.1038/s41467-018-07368-7
[Indexed for MEDLINE]
Free PMC Article

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