Optimizing ethanol yield during fermentation is important for efficient production of fuel alcohol, as well as wine and other alcoholic beverages. However, increasing ethanol concentrations during fermentation can create problems that result in arrested or sluggish sugar-to-ethanol conversion. The fundamental cellular basis for these problem fermentations, however, is not well understood. Small-scale fermentations were performed in a synthetic grape must using 22 industrial Saccharomyces cerevisiae strains (primarily wine strains) with various degrees of ethanol tolerance to assess the correlation between lipid composition and fermentation kinetic parameters. Lipids were extracted at several fermentation time points representing different growth phases of the yeast to quantitatively analyze phospholipids and ergosterol utilizing atmospheric pressure ionization-mass spectrometry methods. Lipid profiling of individual fermentations indicated that yeast lipid class profiles do not shift dramatically in composition over the course of fermentation. Multivariate statistical analysis of the data was performed using partial least-squares linear regression modeling to correlate lipid composition data with fermentation kinetic data. The results indicate a strong correlation (R(2) = 0.91) between the overall lipid composition and the final ethanol concentration (wt/wt), an indicator of strain ethanol tolerance. One potential component of ethanol tolerance, the maximum yeast cell concentration, was also found to be a strong function of lipid composition (R(2) = 0.97). Specifically, strains unable to complete fermentation were associated with high phosphatidylinositol levels early in fermentation. Yeast strains that achieved the highest cell densities and ethanol concentrations were positively correlated with phosphatidylcholine species similar to those known to decrease the perturbing effects of ethanol in model membrane systems.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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