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Journal of Clinical Microbiology, July 2006, p. 2524-2532, Vol. 44, No. 7
0095-1137/06/$08.00+0 doi:10.1128/JCM.02536-05
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Grupo de Biomatemática, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal,1 Instituto de Medicina Molecular e Instituto de Microbiologia, Faculdade de Medicina de Lisboa, Lisbon, Portugal,2 Department of Biostatistics and Applied Mathematics, University of Texas MD Anderson Cancer Center, Houston, Texas,3 Laboratório de Genética Molecular, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal,4 Laboratory of Microbiology, The Rockefeller University, New York, New York5
Received 6 December 2005/ Returned for modification 14 March 2006/ Accepted 10 May 2006
The studies that correlate the results obtained by different typing methodologies rely solely on qualitative comparisons of the groups defined by each methodology. We propose a framework of measures for the quantitative assessment of correspondences between different typing methods as a first step to the global mapping of type equivalences. A collection of 325 macrolide-resistant Streptococcus pyogenes isolates associated with pharyngitis cases in Portugal was used to benchmark the proposed measures. All isolates were characterized by macrolide resistance phenotyping, T serotyping, emm sequence typing, and pulsed-field gel electrophoresis (PFGE), using SmaI or Cfr9I and SfiI. A subset of 41 isolates, representing each PFGE cluster, was also characterized by multilocus sequence typing (MLST). The application of Adjusted Rand and Wallace indices allowed the evaluation of the strength and the directionality of the correspondences between the various typing methods and showed that if PFGE or MLST data are available one can confidently predict the emm type (Wallace coefficients of 0.952 for both methods). In contrast, emm typing was a poor predictor of PFGE cluster or MLST sequence type (Wallace coefficients of 0.803 and 0.655, respectively). This was confirmed by the analysis of the larger data set available from http://spyogenes.mlst.net and underscores the necessity of performing PFGE or MLST to unambiguously define clones in S. pyogenes.
Supplemental material for this article may be found at http://jcm.asm.org/.
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