Application of Automated Microorganism Identification Systems for Verification of Taxonomic Appurtenance of the Collection Strains of Pathogenic Bacteria

Objective of the study is to optimize the algorithm for authenticity specification of pathogenic bacteria strains and to evaluate its efficacy for nomenclature examination of the isolates, Bacillus genus, from the State Collection of Pathogenic Bacteria functioning at the premises of RusRAPI “Microbe”, the authenticity of which bore scrutiny. Materials and methods. Methodological approach is based on application of automated microorganism identification systems: bacteriological analyzer Vitek 2, automatic ribotyping station DuPont Qualicon RiboPrinter System, and mass-spectrometer MicroFlex MALDI Biotyper, followed by complex assessment of the results obtained, using BioNumerics 7.1 software product. Results and conclusions. It is established that automated analyzers perform reasonably accurate identification of the investigated microorganisms in reference to their specie appurtenance. Vitek 2 shows the best efficiency. Unlike other analyzers, it allows for differentiation of B. anthracis STI-1 strain from a group of bacilli, B. cereus specie. It is of note that different systems range B. megaterium 5 strain in different ways. Carried out complex analysis of the results, obtained from all the three automated devices, using BioNumerics 7.1 software, relegates B. megaterium 5 to B. licheniformis with a high degree probability. Thus, it is necessary to include in the algorithm several techniques with subsequent complex analysis of the data obtained to specify authenticity and taxonomic appurtenance of the collection strains under nomenclature examination.

аутентичность коллекционных штаммов, бактериологический анализатор Vitek 2, система RyboPrinter, Maldi-Tof масс-спектрометрия, таксономическая принадлежность, кластерный анализ, authenticity of the collection strains, bacteriological analyzer Vitek 2, RiboPrinter system, MALDI-TOF mass-spectrometry, taxonomy appurtenance, cluster analysis

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