4.4 Article

Whole-Genome Sequencing for Outbreak Investigations of Methicillin-Resistant Staphylococcus aureus in the Neonatal Intensive Care Unit: Time for Routine Practice?

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INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY
卷 36, 期 7, 页码 777-785

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CAMBRIDGE UNIV PRESS
DOI: 10.1017/ice.2015.73

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  1. NIH/NCATS Clinical and Translational Science Award [UL1 TR000064]

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BACKGROUND. Infants in the neonatal intensive care unit (NICU) are at increased risk for methicillin-resistant Staphylococcus aureus (MRSA) acquisition. Outbreaks may be difficult to identify due in part to limitations in current molecular genotyping available in clinical practice. Comparison of genome-wide single nucleotide polymorphisms (SNPs) may identify epidemiologically distinct isolates among a population sample that appears homogenous when evaluated using conventional typing methods. OBJECTIVE. To investigate a putative MRSA outbreak in a NICU utilizing whole-genome sequencing and phylogenetic analysis to identify recent transmission events. DESIGN. Clinical and surveillance specimens collected during clinical care and outbreak investigation. PATIENTS. A total of 17 neonates hospitalized in a 43-bed level III NICU in northeastern Florida from December 2010 to October 2011 were included in this study. METHODS. We assessed epidemiological data in conjunction with 4 typing methods: antibiograms, PFGE, spa types, and phylogenetic analysis of genome-wide SNPs. results. Among the 17 type USA300 isolates, 4 different spa types were identified using pulsed-field gel electrophoresis. Phylogenetic analysis identified 5 infants as belonging to 2 clusters of epidemiologically linked cases and excluded 10 unlinked cases from putative transmission events. The availability of these results during the initial investigation would have improved infection control interventions. CONCLUSION. Whole-genome sequencing and phylogenetic analysis are invaluable tools for epidemic investigation; they identify transmission events and exclude cases mistakenly implicated by traditional typing methods. When routinely applied to surveillance and investigation in the clinical setting, this approach may provide actionable intelligence for measured, appropriate, and effective interventions.

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