Evaluation of Automated Ribotyping for Characterization of Streptococcus mutans

Objective: The aim of this work was to evaluate automated ribotyping with EcoRI restriction enzyme (RiboPrinter® microbial characterization system) for typing and identification of Streptococcus mutans, which is considered to be the principal etiological agent in human dental caries. Methods: In total, 29 clinical isolates and two reference S. mutans strains obtained from the Czech Collection of Microorganisms (http://www.sci.muni.cz/ccm/ ) were analyzed. The clinical isolates were retrieved from dental plaque of early childhood caries affected children treated in the Department of Pedodontics (Children's Teaching Hospital, Brno, Czech Republic). The automatic characterization process performed by the RiboPrinter system separated analysed strains into 24 ribogroups, however automatic identification did not assigned any strain to the species level. Further cluster analysis of obtained riboprints performed by the BioNumerics software and manual inspection and correction of the automatic ribopatterns categorization revealed two more ribogroups unrecognized by the RiboPrinter and included two single strains into already existing ribogroups. Results: Overall, 20 ribotypes containing bands ranging from approx. 60 to 6 kbp were detected among analysed strains, except strain CCM 7410 revealing an extra 0.7 kbp band. Similarity values between individual patterns obtained from dendrogram constructed with Pearson\'s correlation coefficients using UPGMA clustering method ranged from 42.3 to 97.6 %. Conclusion: Our results imply RiboPrinter® microbial characterization system as a good tool for S. mutans intraspecies typing purposes although careful inspection of obtained automatic characterization results is needed to obtain reliable outcomes. Financial support from projects 1M0528 and MSM0021622416 is acknowledged. Schlagwörter: Streptococcus mutans, oral microbiology, dental plaque, ECC, pedodontics, automated ribotyping, EcoRI restriction enzyme, rep-PCR fingerprinting, Whole-cell protein fingerprinting