A1 Refereed original research article in a scientific journal
Outbreak analysis and typing of MRSA isolates by automated repetitive-sequence-based PCR in a region with multiple strain types causing epidemics.
Authors: Hirvonen JJ, Pasanen T, Tissari P, Salmenlinna S, Vuopio J, Kaukoranta SS
Publication year: 2012
Journal: European Journal of Clinical Microbiology and Infectious Diseases
Journal name in source: European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
Journal acronym: Eur J Clin Microbiol Infect Dis
Number in series: 11
Volume: 31
Issue: 11
First page : 2935
Last page: 2942
Number of pages: 8
ISSN: 1435-4373
DOI: https://doi.org/10.1007/s10096-012-1644-4
The usefulness and performance of repetitive-sequence-based polymerase chain reaction (rep-PCR), the DiversiLab system, in the epidemiological surveillance for methicillin-resistant Staphylococcus aureus (MRSA) strain typing was assessed. MRSA isolates from five distinct outbreaks with precise epidemiological data (n = 69) and from the culture collection of well-characterized MRSA strains (n = 132) consisting of 35 spa and 23 pulsed-field gel electrophoresis (PFGE) types were analyzed. The typing results of the DiversiLab system in outbreak analysis were compared to the spa and PFGE typing methods. The DiversiLab system proved to be a reliable tool for the rapid first-line typing of MRSA isolates, showing a good reliability in distinguishing MRSA strains in an area where several MRSA types were causing epidemics. This, however, required that the automatic clustering was combined with manual interpretation using the pattern overlay function when the strain types showing high similarity were clustered together. All outbreaks were distinguished with the DiversiLab system and the PFGE method, but not with the spa typing method. The overall discriminatory power of the DiversiLab system in differentiating diverse MRSA strains proved to be good. We also demonstrated that, in addition to the genetic relatedness analysis of MRSA strains, it is important to obtain accurate epidemiological information in order to perform reliable epidemiological surveillance studies.