Identification and Cluster Analysis of Streptococcus pyogenes by MALDI-TOF Mass Spectrometry

Abstract

Background: Whole-cell matrix–assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has been successfully applied for bacterial identification and typing of many pathogens. The fast and reliable qualities of MALDI-TOF MS make it suitable for clinical diagnostics. MALDI-TOF MS for the identification and cluster analysis of Streptococcus pyogenes, however, has not been reported. The goal of our study was to evaluate this approach for the rapid identification and typing of S. pyogenes. Methods: 65 S. pyogenes isolates were obtained from the hospital. The samples were prepared and MALDI-TOF MS measurements were conducted as previously reported. Identification of unknown spectra was performed via a pattern recognition algorithm with a reference spectra and a dendrogram was constructed using the statistical toolbox in Matlab 7.1 integrated in the MALDI Biotyper 2.0 software. Results: For identification, 61 of 65 S. pyogenes isolates could be identified correctly by MALDI-TOF MS with BioType 2.0 when compared to biochemical identification (API Strep), with an accuracy of 93.85%. In clustering analysis, 44 of 65 isolates were in accordance with those established by M typing, with a matching rate of 67.69%. When only the M type prevalence in China was considered, 41 of 45 isolates were in agreement with M typing, with a matching rate of 91.1%. Conclusions: It was here shown that MALDI-TOF MS with Soft Biotype 2.0 and its database could facilitate rapi

  • computer science
  • text mining

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