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Open Access Highly Accessed Research article

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

Jon Bohlin1*, Lars Snipen2, Axel Cloeckaert3, Karin Lagesen4, David Ussery5, Anja B Kristoffersen46 and Jacques Godfroid7

Author affiliations

1 Norwegian School of Veterinary Science, Department of Food Safety and Infection Biology, Epicenter, Ullevålsveien 72, PO Box 8146 Dep, NO-0033 Oslo, Norway

2 Norwegian University of Life Sciences, Department of Chemistry, Biotechnology and Food Sciences, Ås, Norway

3 INRA, UR1282, Infectiologie Animale et Santé Publique, IASP, Nouzilly, F-37380, France

4 University of Oslo, Department of Informatics, Pb. 1080, 0316 Oslo, Norway

5 Center for Biological Sequence Analysis, Department of Systems Biology, Comparative genomics unit, Technical University of Denmark, DK-2800 Lyngby, Denmark

6 National Veterinary Institute, Section for epidemiology, Pb 750 Sentrum, N-0106 Oslo, Norway

7 Norwegian School of Veterinary Science, Department of Food Safety and Infection Biology, Section of Arctic Veterinary Medicine, Stakkevollveien 23, 9016 Tromsø, Norway

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Citation and License

BMC Evolutionary Biology 2010, 10:249  doi:10.1186/1471-2148-10-249

Published: 13 August 2010

Abstract

Background

Classification of bacteria within the genus Brucella has been difficult due in part to considerable genomic homogeneity between the different species and biovars, in spite of clear differences in phenotypes. Therefore, many different methods have been used to assess Brucella taxonomy. In the current work, we examine 32 sequenced genomes from genus Brucella representing the six classical species, as well as more recently described species, using bioinformatical methods. Comparisons were made at the level of genomic DNA using oligonucleotide based methods (Markov chain based genomic signatures, genomic codon and amino acid frequencies based comparisons) and proteomes (all-against-all BLAST protein comparisons and pan-genomic analyses).

Results

We found that the oligonucleotide based methods gave different results compared to that of the proteome based methods. Differences were also found between the oligonucleotide based methods used. Whilst the Markov chain based genomic signatures grouped the different species in genus Brucella according to host preference, the codon and amino acid frequencies based methods reflected small differences between the Brucella species. Only minor differences could be detected between all genera included in this study using the codon and amino acid frequencies based methods.

Proteome comparisons were found to be in strong accordance with current Brucella taxonomy indicating a remarkable association between gene gain or loss on one hand and mutations in marker genes on the other. The proteome based methods found greater similarity between Brucella species and Ochrobactrum species than between species within genus Agrobacterium compared to each other. In other words, proteome comparisons of species within genus Agrobacterium were found to be more diverse than proteome comparisons between species in genus Brucella and genus Ochrobactrum. Pan-genomic analyses indicated that uptake of DNA from outside genus Brucella appears to be limited.

Conclusions

While both the proteome based methods and the Markov chain based genomic signatures were able to reflect environmental diversity between the different species and strains of genus Brucella, the genomic codon and amino acid frequencies based comparisons were not found adequate for such comparisons. The proteome comparison based phylogenies of the species in genus Brucella showed a surprising consistency with current Brucella taxonomy.