Details

Autor(en) / Beteiligte

• Méric, Guillaume
• Mageiros, Leonardos
• Pensar, Johan
• Laabei, Maisem
• Yahara, Koji
• Pascoe, Ben
• Kittiwan, Nattinee
• Tadee, Phacharaporn
• Post, Virginia
• Lamble, Sarah
• Bowden, Rory
• Bray, James E
• Morgenstern, Mario
• Jolley, Keith A
• Maiden, Martin C J
• Feil, Edward J
• Didelot, Xavier
• Miragaia, Maria
• de Lencastre, Herminia
• Moriarty, T Fintan
• Rohde, Holger
• Massey, Ruth
• Mack, Dietrich
• Corander, Jukka
• Sheppard, Samuel K

Titel

Disease-associated genotypes of the commensal skin bacterium Staphylococcus epidermidis

Ist Teil von

• Nature communications, 2018-11, Vol.9 (1), p.5034-11, Article 5034

Ort / Verlag

England: Nature Publishing Group

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• 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.