Biochemical, serological, and molecular methods have been developed for the laboratory diagnosis of diseases caused by C. pseudotuberculosis (CP), but the identification of the pathogen and biovars differentiation may be time-consuming, expensive, and confusing compared with other bacteria. This study aimed to evaluate MALDI Biotyper and Overall Genome Relatedness Index (OGRI) analysis to optimize the identification and differentiation of biovars of C. pseudotuberculosis. Out of 230 strains isolated from several hosts and countries, 202 (87.8%) were precisely classified using MALDI Biotyper and the BioNumerics platform. The classification accuracies for the Ovis and Equi biovars were 80 (88.75%) and 82 (92.68%), respectively. When analyzing a sampling of these strains by Average Nucleotide Identity based on BLAST and TETRA analyses using genomic sequence data, it was possible to differentiate 100% of the strains in Equi and Ovis. Our data show that MALDI Biotyper and OGRI analysis help identify C. pseudotuberculosis at the species and biovar levels.
Keywords: Bionumerics software; C. pseudotuberculosis; Equi and Ovis biovars; MALDI-TOF; Overall Genome Relatedness Index.