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Composition-modified matrices improve identification of homologs of saccharomyces cerevisiae low-complexity glycoproteins.

ABSTRACT: Yeast glycoproteins are representative of low-complexity sequences, those sequences rich in a few types of amino acids. Low-complexity protein sequences comprise more than 10% of the proteome but are poorly aligned by existing methods. Under default conditions, BLAST and FASTA use the scoring matrix BLOSUM62, which is optimized for sequences with diverse amino acid compositions. Because low-complexity sequences are rich in a few amino acids, these tools tend to align the most common residues in nonhomologous positions, thereby generating anomalously high scores, deviations from the expected extreme value distribution, and small e values. This anomalous scoring prevents BLOSUM62-based BLAST and FASTA from identifying correct homologs for proteins with low-complexity sequences, including Saccharomyces cerevisiae wall proteins. We have devised and empirically tested scoring matrices that compensate for the overrepresentation of some amino acids in any query sequence in different ways. These matrices were tested for sensitivity in finding true homologs, discrimination against nonhomologous and random sequences, conformance to the extreme value distribution, and accuracy of e values. Of the tested matrices, the two best matrices (called E and gtQ) gave reliable alignments in BLAST and FASTA searches, identified a consistent set of paralogs of the yeast cell wall test set proteins, and improved the consistency of secondary structure predictions for cell wall proteins.

SUBMITTER: Coronado JE

PROVIDER: S-EPMC1459670 | biostudies-other | 2006 Apr

REPOSITORIES: biostudies-other

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Composition-modified matrices improve identification of homologs of saccharomyces cerevisiae low-complexity glycoproteins.

Coronado Juan E JE Attie Oliver O Epstein Susan L SL Qiu Wei-Gang WG Lipke Peter N PN

Eukaryotic cell 20060401 4

Yeast glycoproteins are representative of low-complexity sequences, those sequences rich in a few types of amino acids. Low-complexity protein sequences comprise more than 10% of the proteome but are poorly aligned by existing methods. Under default conditions, BLAST and FASTA use the scoring matrix BLOSUM62, which is optimized for sequences with diverse amino acid compositions. Because low-complexity sequences are rich in a few amino acids, these tools tend to align the most common residues in ...[more]

PMID: 16607010

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Project description:A major obstacle to sustainable lignocellulosic biofuel production is microbe inhibition by the combinatorial stresses in pretreated plant hydrolysate. Chemical biomass pretreatment releases a suite of toxins that interact with other stressors, including high osmolarity and temperature, which together can have poorly understood synergistic effects on cells. Improving tolerance in industrial strains has been hindered, in part because the mechanisms of tolerance reported in the literature often fail to recapitulate in other strain backgrounds. Here, we explored and then exploited variations in stress tolerance, toxin-induced transcriptomic responses, and fitness effects of gene overexpression in different Saccharomyces cerevisiae (yeast) strains to identify genes and processes linked to tolerance of hydrolysate stressors. Using six different S. cerevisiae strains that together maximized phenotypic and genetic diversity, first we explored transcriptomic differences between resistant and sensitive strains to identify common and strain-specific responses. This comparative analysis implicated primary cellular targets of hydrolysate toxins, secondary effects of defective defense strategies, and mechanisms of tolerance. Dissecting the responses to individual hydrolysate components across strains pointed to synergistic interactions between osmolarity, pH, hydrolysate toxins, and nutrient composition. By characterizing the effects of high-copy gene overexpression in three different strains, we revealed the breadth of the background-specific effects of gene fitness contributions in synthetic hydrolysate. Our approach identified new genes for engineering improved stress tolerance in diverse strains while illuminating the effects of genetic background on molecular mechanisms.Recent studies on natural variation within Saccharomyces cerevisiae have uncovered substantial phenotypic diversity. Here, we took advantage of this diversity, using it as a tool to infer the effects of combinatorial stress found in lignocellulosic hydrolysate. By comparing sensitive and tolerant strains, we implicated primary cellular targets of hydrolysate toxins and elucidated the physiological states of cells when exposed to this stress. We also explored the strain-specific effects of gene overexpression to further identify strain-specific responses to hydrolysate stresses and to identify genes that improve hydrolysate tolerance independent of strain background. This study underscores the importance of studying multiple strains to understand the effects of hydrolysate stress and provides a method to find genes that improve tolerance across strain backgrounds.

Project description:1. Protoplasts of Saccharomyces cerevisiae N.C.Y.C. 366 were prepared by incubating washed exponential-phase cells in buffered mannitol (0.8m) containing 10mm-magnesium chloride and snail gut juice (about 8mg. of protein/ml. of reaction mixture). Protoplast membranes were obtained by bursting protoplasts in ice-cold phosphate buffer (pH7.0) containing 10mm-magnesium chloride. 2. Protoplast membranes accounted for 13-20% of the dry weight of the yeast cell. They contained on a weight basis about 39% of lipid, 49% of protein, 6% of sterol (assayed spectrophotometrically) and traces of RNA and carbohydrate (glucan+mannan). 3. The principal fatty acids in membrane lipids were C(16:0), C(16:1) and C(18:1) acids. Whole cells contained a slightly greater proportion of C(16:0) and a somewhat smaller proportion of C(18:1) acids. Membrane and whole-cell lipids included monoglycerides, diglycerides, triglycerides, sterols, sterol esters, phosphatidylcholine, lysophosphatidylcholine, phosphatidylethanolamine and phosphatidylinositol+phosphatidylserine. Phosphorus analyses on phospholipid fractions from membranes and whole cells showed that membranes contained proportionately more phosphatidylethanolamine and phosphatidylinositol+phosphatidylserine than whole cells, which in turn were richer in phosphatidylcholine. Phospholipid fractions from membranes and whole cells had similar fatty acid compositions. 4. Membranes and whole cells contained two major and three minor sterol components. Gas-liquid chromatography, mass spectrometry and u.v. and i.r. spectra indicated that the major components were probably Delta(5,7,22,24(28))-ergostatetraen-3beta-ol and zymosterol. The minor sterol components in whole cells were probably episterol (or fecosterol), ergosterol and a C(29) di-unsaturated sterol. 5. Defatted whole cells contained slightly more glutamate and ornithine and slightly less leucine and isoleucine than membranes. Otherwise, no major differences were detected in the amino acid compositions of defatted whole cells and membranes.

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Composition-modified matrices improve identification of homologs of saccharomyces cerevisiae low-complexity glycoproteins.

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Composition-modified matrices improve identification of homologs of saccharomyces cerevisiae low-complexity glycoproteins.

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