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.
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 .
What is MRSA?
What is MRSA ?
MRSA
methicillin-resistant S. aureus MRSA