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Whole-Genome Sequencing for High-Resolution Investigation of Methicillin-Resistant Staphylococcus aureus Epidemiology and Genome Plasticity
Author(s) -
Dhruba J. SenGupta,
Lisa A. Cummings,
Daniel R. Hoogestraat,
Susan M. ButlerWu,
Jay Shendure,
Brad T. Cookson,
Stephen J. Salipante
Publication year - 2014
Publication title -
journal of clinical microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.349
H-Index - 255
eISSN - 1070-633X
pISSN - 0095-1137
DOI - 10.1128/jcm.00759-14
Subject(s) - staphylococcus aureus , genome , whole genome sequencing , biology , methicillin resistant staphylococcus aureus , staphylococcal infections , microbiology and biotechnology , genetics , bacteria , gene
Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a major challenge in health care, yet the limited heterogeneity within this group hinders molecular investigations of related outbreaks. Pulsed-field gel electrophoresis (PFGE) has been the gold standard approach but is impractical for many clinical laboratories and is often replaced with PCR-based methods. Regardless, both approaches can prove problematic for identifying subclonal outbreaks. Here, we explore the use of whole-genome sequencing for clinical laboratory investigations of MRSA molecular epidemiology. We examine the relationships of 44 MRSA isolates collected over a period of 3 years by using whole-genome sequencing and two PCR-based methods, multilocus variable-number tandem-repeat analysis (MLVA) and spa typing. We find that MLVA offers higher resolution than spa typing, as it resolved 17 versus 12 discrete isolate groups, respectively. In contrast, whole-genome sequencing reproducibly cataloged genomic variants (131,424 different single nucleotide polymorphisms and indels across the strain collection) that uniquely identified each MRSA clone, recapitulating those groups but enabling higher-resolution phylogenetic inferences of the epidemiological relationships. Importantly, whole-genome sequencing detected a significant number of variants, thereby distinguishing between groups that were considered identical by both spa typing (minimum, 1,124 polymorphisms) and MLVA (minimum, 193 polymorphisms); this suggests that these more conventional approaches can lead to false-positive identification of outbreaks due to inappropriate grouping of genetically distinct strains. An analysis of the distribution of variants across the MRSA genome reveals 47 mutational hot spots (comprising ∼ 2.5% of the genome) that account for 23.5% of the observed polymorphisms, and the use of this selected data set successfully recapitulates most epidemiological relationships in this pathogen group.

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