RESUMEN
Dietzia strains are widely distributed in the environment, presenting an opportunistic role, and some species have undetermined taxonomic characteristics. Here, we propose the existence of errors in the classification of species in this genus using comparative genomics. We performed ANI, dDDH, pangenome and genomic plasticity analyses better to elucidate the phylogenomic relationships between Dietzia strains. For this, we used 55 genomes of Dietzia downloaded from public databases that were combined with a newly sequenced. Sequence analysis of a phylogenetic tree based on genome similarity comparisons and dDDH, ANI analyses supported grouping different Dietzia species into four distinct groups. The pangenome analysis corroborated the classification of these groups, supporting the idea that some species of Dietzia could be reassigned in a possible classification into three distinct species, each containing less variability than that found within the global pangenome of all strains. Additionally, analysis of genomic plasticity based on groups containing Dietzia strains found differences in the presence and absence of symbiotic Islands and pathogenic islands related to their isolation site. We propose that the comparison of pangenome subsets together with phylogenomic approaches can be used as an alternative for the classification and differentiation of new species of the genus Dietzia.
Asunto(s)
Actinomycetales , Genómica , Análisis de Secuencia de ADN , Filogenia , Genoma Bacteriano/genética , Secuencia de Bases , Actinomycetales/genéticaRESUMEN
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.