Genomic comparisons of Brucella spp. and closely related bacteria using base compositional and proteome based methods

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Bacterial classification within the genus Brucella is challenging due to genomic homogeneity.
• Phenotypic differences among Brucella species contrast with their similar genomes.
• Diverse methods are employed to resolve Brucella taxonomy.

Purpose of the Study:

• To evaluate various bioinformatical methods for classifying Brucella species.
• To compare DNA-based and proteome-based genomic analyses.
• To assess the utility of different genomic signatures for Brucella taxonomy.

Main Methods:

• Analysis of 32 Brucella genomes using bioinformatical approaches.
• Oligonucleotide-based methods: Markov chain genomic signatures, codon/amino acid frequencies.
• Proteome-based methods: all-against-all BLAST protein comparisons, pan-genomic analyses.

Main Results:

• Proteome comparisons strongly align with current Brucella taxonomy, linking gene gain/loss with marker gene mutations.
• Markov chain genomic signatures reflect host preference, while codon/amino acid frequencies show minor species differences.
• Proteome analyses reveal greater diversity within Agrobacterium than between Brucella and Ochrobactrum species.

Conclusions:

• Proteome-based methods and Markov chain genomic signatures effectively differentiate Brucella species and strains.
• Genomic codon and amino acid frequencies are inadequate for detailed Brucella comparisons.
• Proteome-based phylogenies confirm the existing Brucella taxonomy.