Abstract
BackgroundBiological nitrogen fixation, with an emphasis on the legume-rhizobia symbiosis, is a key process for agriculture and the environment, allowing the replacement of nitrogen fertilizers, reducing water pollution by nitrate as well as emission of greenhouse gases. Soils contain numerous strains belonging to the bacterial genus Bradyrhizobium, which establish symbioses with a variety of legumes. However, due to the high conservation of Bradyrhizobium 16S rRNA genes - considered as the backbone of the taxonomy of prokaryotes - few species have been delineated. The multilocus sequence analysis (MLSA) methodology, which includes analysis of housekeeping genes, has been shown to be promising and powerful for defining bacterial species, and, in this study, it was applied to Bradyrhizobium, species, increasing our understanding of the diversity of nitrogen-fixing bacteria.DescriptionClassification of bacteria of agronomic importance is relevant to biodiversity, as well as to biotechnological manipulation to improve agricultural productivity. We propose the construction of an online database that will provide information and tools using MLSA to improve phylogenetic and taxonomic characterization of Bradyrhizobium, allowing the comparison of genomic sequences with those of type and representative strains of each species.ConclusionA database for the taxonomic and phylogenetic identification of the Bradyrhizobium, genus, using MLSA, will facilitate the use of biological data available through an intuitive web interface. Sequences stored in the on-line database can be compared with multiple sequences of other strains with simplicity and agility through multiple alignment algorithms and computational routines integrated into the database. The proposed database and software tools are available at http://mlsa.cnpso.embrapa.br, and can be used, free of charge, by researchers worldwide to classify Bradyrhizobium, strains; the database and software can be applied to replicate the experiments presented in this study as well as to generate new experiments. The next step will be expansion of the database to include other rhizobial species.
Highlights
Biological nitrogen fixation, with an emphasis on the legume-rhizobia symbiosis, is a key process for agriculture and the environment, allowing the replacement of nitrogen fertilizers, reducing water pollution by nitrate as well as emission of greenhouse gases
The proposed database and software tools are available at http://mlsa.cnpso.embrapa.br, and can be used, free of charge, by researchers worldwide to classify Bradyrhizobium, strains; the database and software can be applied to replicate the experiments presented in this study as well as to generate new experiments
In an additional test, considering the sequences related to B. japonicum strain SEMIA 5079 as input, we found that genes dnaK+atpD+glnll analysed with the CLUSTAL algorithm Omega resulted in the correct identification of the species and that the strain showed similarity with other strains, of 99.69% with B. japonicum USDA 6T and of 98.84% with SEMIA 511
Summary
This work was developed in order to provide a database for the taxonomic and phylogenetic identification of the genus Bradyrhizobium by using the multilocus sequence analysis (MLSA) methodology. The Results show that for the efficient use of the MLSA database it is important to know the combinations of genes that will be used in the taxonomic analysis, as well as the similarity rates that could be used for each genus. Additional file 3: Average classical measures of classification for 16 strains used as input sequences in tests We show the values for the accuracy, precision, recall and f-score achieved with the software and strains available in the proposed database, these measures were calculated using data from the result of Matrix Identity generated by the analysis of multiple genes, with the use of the proposed cut-off of 98.70% for minimum similarity. Authors’ contributions HA conceived the idea, assembled the datasets, performed the analysis, developed the computational method and contributed to drafted the manuscript; FML conceived the idea, developed the computational method and drafted the manuscript; PRS helped in the assembled the datasets and developed the computational method; MH conceived the idea, contributed to the analysis of results and helped to draft the manuscript
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