Biomedical subjects

Hiroshi Akashi

Publications and source records attributed to Hiroshi Akashi.

3 recordsLinked to original sources

PubMed2003

Molecular phylogeny of the Drosophila melanogaster species subgroup.

Although molecular and phenotypic evolution have been studied extensively in Drosophila melanogaster and its close relatives, phylogenetic relationships within the D. melanogaster species subgroup remain unresolved. In particular, recent molecular studies have not converged on the branching orders of the D. yakuba-D. teissieri and D. erecta-D. orena species pairs relative to the D. melanogaster-D. simulans-D. mauritiana-D. sechellia species complex. Here, we reconstruct the phylogeny of the melanogaster species subgroup using DNA sequence data from four nuclear genes. We have employed "vectorette PCR" to obtain sequence data for orthologous regions of the Alcohol dehydrogenase (Adh), Alcohol dehydrogenase related (Adhr), Glucose dehydrogenase (Gld), and rosy (ry) genes (totaling 7164 bp) from six melanogaster subgroup species (D. melanogaster, D. simulans, D. teissieri, D. yakuba, D. erecta, and D. orena) and three species from subgroups outside the melanogaster species subgroup [D. eugracilis (eugracilis subgroup), D. mimetica (suzukii subgroup), and D. lutescens (takahashii subgroup)]. Relationships within the D. simulans complex are not addressed. Phylogenetic analyses employing maximum parsimony, neighbor-joining, and maximum likelihood methods strongly support a D. yakuba-D. teissieri and D. erecta-D. orena clade within the melanogaster species subgroup. D. eugracilis is grouped closer to the melanogaster subgroup than a D. mimetica-D. lutescens clade. This tree topology is supported by reconstructions employing simple (single parameter) and more complex (nonreversible) substitution models.

Animals↗

PubMed2003

Translational selection and yeast proteome evolution.

The primary structures of peptides may be adapted for efficient synthesis as well as proper function. Here, the Saccharomyces cerevisiae genome sequence, DNA microarray expression data, tRNA gene numbers, and functional categorizations of proteins are employed to determine whether the amino acid composition of peptides reflects natural selection to optimize the speed and accuracy of translation. Strong relationships between synonymous codon usage bias and estimates of transcript abundance suggest that DNA array data serve as adequate predictors of translation rates. Amino acid usage also shows striking relationships with expression levels. Stronger correlations between tRNA concentrations and amino acid abundances among highly expressed proteins than among less abundant proteins support adaptation of both tRNA abundances and amino acid usage to enhance the speed and accuracy of protein synthesis. Natural selection for efficient synthesis appears to also favor shorter proteins as a function of their expression levels. Comparisons restricted to proteins within functional classes are employed to control for differences in amino acid composition and protein size that reflect differences in the functional requirements of proteins expressed at different levels.

Adaptation, Physiological↗

PubMed2002

Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis.

Biosynthesis of an Escherichia coli cell, with organic compounds as sources of energy and carbon, requires approximately 20 to 60 billion high-energy phosphate bonds [Stouthamer, A. H. (1973) Antonie van Leeuwenhoek 39, 545-565]. A substantial fraction of this energy budget is devoted to biosynthesis of amino acids, the building blocks of proteins. The fueling reactions of central metabolism provide precursor metabolites for synthesis of the 20 amino acids incorporated into proteins. Thus, synthesis of an amino acid entails a dual cost: energy is lost by diverting chemical intermediates from fueling reactions and additional energy is required to convert precursor metabolites to amino acids. Among amino acids, costs of synthesis vary from 12 to 74 high-energy phosphate bonds per molecule. The energetic advantage to encoding a less costly amino acid in a highly expressed gene can be greater than 0.025% of the total energy budget. Here, we provide evidence that amino acid composition in the proteomes of E. coli and Bacillus subtilis reflects the action of natural selection to enhance metabolic efficiency. We employ synonymous codon usage bias as a measure of translation rates and show increases in the abundance of less energetically costly amino acids in highly expressed proteins.

Amino Acids↗