Author(s): Le Flche P, Jacques I, Grayon M, Al Dahouk S, Bouchon P,
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Abstract BACKGROUND: The classification of Brucella into species and biovars relies on phenotypic characteristics and sometimes raises difficulties in the interpretation of the results due to an absence of standardization of the typing reagents. In addition, the resolution of this biotyping is moderate and requires the manipulation of the living agent. More efficient DNA-based methods are needed, and this work explores the suitability of multiple locus variable number tandem repeats analysis (MLVA) for both typing and species identification. RESULTS: Eighty tandem repeat loci predicted to be polymorphic by genome sequence analysis of three available Brucella genome sequences were tested for polymorphism by genotyping 21 Brucella strains (18 reference strains representing the six 'classical' species and all biovars as well as 3 marine mammal strains currently recognized as members of two new species). The MLVA data efficiently cluster the strains as expected according to their species and biovar. For practical use, a subset of 15 loci preserving this clustering was selected and applied to the typing of 236 isolates. Using this MLVA-15 assay, the clusters generated correspond to the classical biotyping scheme of Brucella spp. The 15 markers have been divided into two groups, one comprising 8 user-friendly minisatellite markers with a good species identification capability (panel 1) and another complementary group of 7 microsatellite markers with higher discriminatory power (panel 2). CONCLUSION: The MLVA-15 assay can be applied to large collections of Brucella strains with automated or manual procedures, and can be proposed as a complement, or even a substitute, of classical biotyping methods. This is facilitated by the fact that MLVA is based on non-infectious material (DNA) whereas the biotyping procedure itself requires the manipulation of the living agent. The data produced can be queried on a dedicated MLVA web service site.
This article was published in BMC Microbiol
and referenced in Journal of Proteomics & Bioinformatics