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  • Title: Emerging multidrug resistance in community-associated Staphylococcus aureus involved in skin and soft tissue infections and nasal colonization.
    Author: Lee GC, Dallas SD, Wang Y, Olsen RJ, Lawson KA, Wilson J, Frei CR.
    Journal: J Antimicrob Chemother; 2017 Sep 01; 72(9):2461-2468. PubMed ID: 28859442.
    Abstract:
    BACKGROUND: Staphylococcus aureus is a major pathogen causing significant morbidity and mortality worldwide. The emergence of MDR S. aureus strains in the community setting has major implications in disease management. However, data regarding the occurrence and patterns of MDR community-associated S. aureus sub-clones is limited. OBJECTIVES: To use whole-genome sequences to describe the diversity and distribution of resistance mechanisms among community-associated S. aureus isolates. METHODS: S. aureus isolates from skin and soft tissue infections (SSTIs) and nasal colonization were collected from patients within 10 primary care clinics from 2007 to 2015. The Illumina Miseq platform was used to determine the genome sequences for 144 S. aureus isolates. Phylogenetic and bioinformatics analyses were performed using in silico tools. The resistome was assembled and compared with the phenotypically derived antibiogram. RESULTS: Approximately one-third of S. aureus isolates in the South Texas primary care setting were MDR. A higher proportion of SSTI isolates were MDR in comparison with nasal colonization isolates. Individuals with MDR S. aureus SSTIs were more likely to be African American and obese. Furthermore, S. aureus populations are able to acquire and lose antimicrobial resistance genes. USA300 strains were differentiated by a stable chromosomal mutation in gyrA conferring quinolone resistance. The resistomes were highly predictive of antimicrobial resistance phenotypes. CONCLUSIONS: These findings highlight the high prevalence and epidemiological factors associated with MDR S. aureus strains in the community setting and demonstrate the utility of next-generation sequencing to potentially quicken antimicrobial resistance detection and surveillance for targeted interventions.
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