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.




AuthorsHirvonen JJ, Pasanen T, Tissari P, Salmenlinna S, Vuopio J, Kaukoranta SS

Publication year2012

JournalEuropean Journal of Clinical Microbiology and Infectious Diseases

Journal name in sourceEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology

Journal acronymEur J Clin Microbiol Infect Dis

Number in series11

Volume31

Issue11

First page 2935

Last page2942

Number of pages8

ISSN1435-4373

DOIhttps://doi.org/10.1007/s10096-012-1644-4


Abstract

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.




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