Protein families reflect the metabolic diversity of organisms and provide support for functional prediction
| Autor: | Laila A. Nahum, Margrethe H. Serres, Sulip Goswami |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Protein family
Physiology Microbial diversity media_common.quotation_subject Biology Metabolic diversity Bacterial Proteins Species Specificity Phylogenomics Databases Genetic Escherichia coli Genetics Phylogeny Transaminases media_common Comparative genomics Computational Biology Genomics Functional prediction Metabolic enzymes Evolutionary biology Pyridoxal Phosphate Pseudomonas aeruginosa Thiamine Pyrophosphate Pyruvate Decarboxylase Bacillus subtilis Diversity (politics) |
| Zdroj: | Physiological Genomics. 38:250-260 |
| ISSN: | 1531-2267 1094-8341 |
| DOI: | 10.1152/physiolgenomics.90244.2008 |
| Popis: | Comparative genomics has shown that protein families vary significantly within and across organisms in both number and functional composition. In the present work, we tested how the diversity at the family level reflects biological differences among organisms and contributes to their unique characteristics. For this purpose, we collected sequence-similar proteins of three selected families from model bacteria: Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. Protein relationships were identified using a phylogenomic approach to connect the functional diversity of enzymes to the metabolic capabilities of these organisms. All protein families studied have distinct functional compositions across the selected bacteria as supported by our Bayesian analysis. Some conserved functional features among family members included a shared reaction mechanism, cofactor usage, and/or ligand specificity. Many observations of the presence/absence of protein functions matched current knowledge of the physiology and biochemistry of the bacteria. In some cases, new functional predictions were made to family members previously uncharacterized. We believe that genome comparisons at the protein family level would also be useful in predicting metabolic diversity for organisms that are relatively unknown or currently uncultured in the laboratory. |
| Databáze: | OpenAIRE |
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