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Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast.

ABSTRACT: The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor's phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time.

SUBMITTER: de Bivort BL

PROVIDER: S-EPMC2687519 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast.

de Bivort Benjamin L BL Perlstein Ethan O EO Kunes Sam S Schreiber Stuart L SL

Journal of molecular evolution 20090409 5

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor's phase. We show that this metabolic cycling has likel ...[more]

PMID: 19357800

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Project description:Every protein has a biosynthetic cost to the cell based on the synthesis of its constituent amino acids. In order to optimise growth and reproduction, natural selection is expected, where possible, to favour the use of proteins whose constituents are cheaper to produce, as reduced biosynthetic cost may confer a fitness advantage to the organism. Quantifying the cost of amino acid biosynthesis presents challenges, since energetic requirements may change across different cellular and environmental conditions. We developed a systems biology approach to estimate the cost of amino acid synthesis based on genome-scale metabolic models and investigated the effects of the cost of amino acid synthesis on Saccharomyces cerevisiae gene expression and protein evolution. First, we used our two new and six previously reported measures of amino acid cost in conjunction with codon usage bias, tRNA gene number and atomic composition to identify which of these factors best predict transcript and protein levels. Second, we compared amino acid cost with rates of amino acid substitution across four species in the genus Saccharomyces. Regardless of which cost measure is used, amino acid biosynthetic cost is weakly associated with transcript and protein levels. In contrast, we find that biosynthetic cost and amino acid substitution rates show a negative correlation, but for only a subset of cost measures. In the economy of the yeast cell, we find that the cost of amino acid synthesis plays a limited role in shaping transcript and protein expression levels compared to that of translational optimisation. Biosynthetic cost does, however, appear to affect rates of amino acid evolution in Saccharomyces, suggesting that expensive amino acids may only be used when they have specific structural or functional roles in protein sequences. However, as there appears to be no single currency to compute the cost of amino acid synthesis across all cellular and environmental conditions, we conclude that a systems approach is necessary to unravel the full effects of amino acid biosynthetic cost in complex biological systems.

Project description:The E1 protein of bovine papillomavirus (BPV) is a site-specific DNA binding protein that recognizes an 18-bp inverted repeat element in the viral origin of replication. Sequence-specific DNA binding function maps to the region from approximately amino acids 140 to 300, and isolated polypeptides containing this region have been shown to retain origin binding in vitro. To investigate the sequence and structural characteristics which contribute to sequence-specific binding, the primary sequence of this region was examined for conserved features. The BPV E1 DNA binding domain (E1DBD) contains three major hydrophilic domains (HR1, amino acids 179-191; HR2, amino acids 218 to 230; and HR3, amino acids 241 to 252), of which only HR1 and HR3 are conserved among papillomavirus E1 proteins. E1DBD proteins with lysine-to-alanine mutations in HR1 and HR3 were severely impaired for DNA binding function in vitro, while a lysine-to-alanine mutation in HR2 had a minimal effect on DNA binding. Mutation of adjacent threonine residues in HR1 (T187 and T188) revealed that these two amino acids made drastically different contributions to DNA binding, with the T187 mutant being severely defective for origin binding whereas the T188 mutant was only mildly affected. Helical wheel projections of HR1 predict that T187 is on the same helical face as the critical lysine residues whereas T188 is on the opposing face, which is consistent with their respective contributions to DNA binding activity. To examine E1 binding in vivo, a yeast one-hybrid system was developed. Both full-length E1 and the E1DBD polypeptide were capable of specifically interacting with the E1 binding site in the context of the yeast genome, and HR1 was also critical for this in vivo interaction. Overall, our results indicate that HR1 is essential for origin binding by E1, and the features and properties of HR1 suggest that it may be part of a recognition sequence that mediates specific E1-nucleotide contacts.

Project description:BackgroundSelective pressures at the DNA level shape genes into profiles consisting of patterns of rapidly evolving sites and sites withstanding change. These profiles remain detectable even when protein sequences become extensively diverged. A common task in molecular biology is to infer functional, structural or evolutionary relationships by querying a database using an algorithm. However, problems arise when sequence similarity is low. This study presents an algorithm that uses the evolutionary rate at codon sites, the dN/dS (ω) parameter, coupled to a substitution matrix as an alignment metric for detecting distantly related proteins. The algorithm, called BLOSUM-FIRE couples a newer and improved version of the original FIRE (Functional Inference using Rates of Evolution) algorithm with an amino acid substitution matrix in a dynamic scoring function. The enigmatic hepatitis B virus X protein was used as a test case for BLOSUM-FIRE and its associated database EvoDB.ResultsThe evolutionary rate based approach was coupled with a conventional BLOSUM substitution matrix. The two approaches are combined in a dynamic scoring function, which uses the selective pressure to score aligned residues. The dynamic scoring function is based on a coupled additive approach that scores aligned sites based on the level of conservation inferred from the ω values. Evaluation of the accuracy of this new implementation, BLOSUM-FIRE, using MAFFT alignment as reference alignments has shown that it is more accurate than its predecessor FIRE. Comparison of the alignment quality with widely used algorithms (MUSCLE, T-COFFEE, and CLUSTAL Omega) revealed that the BLOSUM-FIRE algorithm performs as well as conventional algorithms. Its main strength lies in that it provides greater potential for aligning divergent sequences and addresses the problem of low specificity inherent in the original FIRE algorithm. The utility of this algorithm is demonstrated using the Hepatitis B virus X (HBx) protein, a protein of unknown function, as a test case.ConclusionThis study describes the utility of an evolutionary rate based approach coupled to the BLOSUM62 amino acid substitution matrix in inferring protein domain function. We demonstrate that such an approach is robust and performs as well as an array of conventional algorithms.

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Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast.

Publications

Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast.

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