Phylogenetic and Functional Analysis of the Vertebrate Cytochrome P450 2 Family
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Cytochrome P450 (CYP) proteins compose a highly diverse superfamily found in all domains of life. These proteins are enzymes involved in metabolism of endogenous and exogenous compounds. In vertebrates, the CYP2 family is one of the largest, most diverse and plays an important role in mammalian drug metabolism. However, there are more than 20 vertebrate CYP2 subfamilies with uncertain evolution and fairly discrete subfamily composition within vertebrate classes, hindering extrapolation of knowledge across subfamilies. To better understand CYP2 diversity, a phylogenetic analysis of 196 CYP2 protein sequences from 16 species was performed using a maximum likelihood approach and Bayesian inference. The analyses included the CYP2 compliment from human, fugu, zebrafish, stickleback, medaka, cow, and dog genomes. Additional sequences were included from rabbit, marsupial, platypus, chicken, frog, and salmonid species. Three CYP2 sequences from the tunicate Ciona intestinalis were utilized as the outgroup. Results indicate a single ancestral vertebrate CYP2 gene and monophyly of all CYP2 subfamilies. Two subfamilies (CYP2R and CYP2U) pre-date vertebrate diversification, allowing direct comparison across vertebrate classes, while all other subfamilies originated during vertebrate diversification, often within specific vertebrate lineages. Analysis of site-specific evolution indicates that some substrate recognition sites (SRS) previously proposed for CYP genes do not have elevated rates of evolution, suggesting that these regions of the protein are not necessarily important in recognition of CYP2 substrates. Type II functional divergence analysis identified multiple residues in the active site of CYP2F, CYP2A, and CYP2B proteins that have undergone radical biochemical changes and may be functionally important.
KeywordsCytochrome P450 Vertebrate CYP2 phylogeny Functional divergence P450 active sites
We would like to thank Dr. David Nelson (University of Tennessee) for assigning nomenclature to our de novo gene annotations and Drs. Brian Golding and Jonathan Stone (McMaster University) for computer cluster access to run our Bayesian analyses and access to PAUP* software for posterior probability node analysis, respectively. We are thankful to Emily Smith and Dr. Golding for helpful comments and suggestions during manuscript revision. This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant #328204 to JYW). The Department of Biology, McMaster University provided partial support for N.K.
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