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- W1963722781 abstract "Staphylococcus epidermidis is part of the normal bacterial flora of human skin and a leading cause of infections associated with indwelling medical devices. Previous phylogenetic analyses of subgenomic data have been unable to distinguish between S. epidermidis strains with nosocomial or commensal lifestyles, despite the identification of specific phenotypes and accessory genes that may contribute to such lifestyles. To attempt to better define the population structure of this species, the international S. epidermidis multilocus sequence typing database was analyzed with the Bayesian clustering programs STRUCTURE and BAPS. A total of six genetic clusters (GCs) were identified. A local population of S. epidermidis from clinical specimens was classified according to these six GCs, and further characterized for antibiotic susceptibilities, biofilm, and various genetic markers. GC5 was abundant and significantly enriched for isolates that were resistant to four classes of antibiotics, high biofilm production, and positive for the virulence markers icaA, IS256, and sesD/bhp, indicating its potential clinical relevance. In contrast, GC2 was rare and contained the only isolates positive for the putative commensal marker, fdh. GC1 and GC6 were abundant but not significantly associated with any of the examined characteristics, except for sesF/aap and GC6. GC3 was rare and identified as a potential genetic sink that received, but did not donate, core genetic material from other GCs. In conclusion, population genetics analyses were essential for identifying clusters of strains that may differ in their adaptation to nosocomial or commensal lifestyles. These results provide a new, population genetics framework for studying S. epidermidis." @default.
- W1963722781 created "2016-06-24" @default.
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- W1963722781 creator A5073675083 @default.
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- W1963722781 date "2014-03-01" @default.
- W1963722781 modified "2023-10-09" @default.
- W1963722781 title "Differing lifestyles of Staphylococcus epidermidis as revealed through Bayesian clustering of multilocus sequence types" @default.
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- W1963722781 doi "https://doi.org/10.1016/j.meegid.2013.06.020" @default.
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