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We have shown that ethanol in concentrations of 0.0001%-10% significantly enhances 3H-thymidine uptake in cultured human mammary carcinoma cell line MCF-7. Methanol only enhances 3H-thymidine uptake in a concentration of 0.01%. [ABSTRACT FROM AUTHOR]

During fermentation, Saccharomyces cerevisiae metabolizes sugars and other nutrients to obtain energy for growth and survival, while also modulating these activities in response to cell-environment interactions. Here, differences in S. cerevisiae gene expression were explored over a time course of fermentation and used to differentiate fermentations, using Pinot noir grapes from 15 unique sites. Data analysis was complicated by the fact that the fermentations proceeded at different rates, making a direct comparison of time series gene expression data difficult with conventional differential expression tools. This led to the development of a novel approach combining d iffusion map ping with continuous d ifferential e xpression analysis (termed DMap-DE). Using this method, site-specific deviations in gene expression were identified, including changes in gene expression correlated with the non- Saccharomyces yeast Hanseniaspora uvarum, as well as initial nitrogen concentrations in grape musts. These results highlight novel relationships between site-specific variables and Saccharomyces cerevisiae gene expression that are linked to repeated fermentation outcomes. It was also demonstrated that DMap-DE can extract biologically relevant gene expression patterns from other contexts (e.g., hypoxic response of Saccharomyces cerevisiae) and offers advantages over other data dimensionality reduction approaches, indicating that DMap-DE offers a robust method for investigating asynchronous time series gene expression data. IMPORTANCE In this work, Saccharomyces cerevisiae gene expression was used as a biosensor to capture differences across and between fermentations of Pinot noir grapes from 15 unique sites representing eight American Viticultural Areas. This required development of a novel analysis method, DMap-DE, for investigation of asynchronous gene expression data. It was demonstrated that DMap-DE reveals biologically relevant shifts in gene expression related to cell-environment interactions in the context of hypoxia and fermentation. Using these data, it was discovered that gene expression by non- Saccharomyces yeasts and initial nitrogen content in grape musts are correlated with differences in gene expression among fermentations. These findings highlight important relationships between site-specific variables and gene expression that may be used to understand why foods and beverages, including wine, possess sensory characteristics associated with or derived from their place of origin.

Saccharomyces cerevisiae metabolism produces ethanol and other compounds during the fermentation of grape must into wine. Thousands of genes change expression over the course of a wine fermentation, allowing S. cerevisiae to adapt to and dominate the fermentation environment. Investigations into these gene expression patterns previously revealed genes that underlie cellular adaptation to the grape must and wine environments, involving metabolic specialization and ethanol tolerance. However, the majority of studies detailing gene expression patterns have occurred in controlled environments that may not recapitulate the biological and chemical complexity of fermentations performed at production scale. Here, an analysis of the S. cerevisiae RC212 gene expression program is presented, drawing from 40 pilot-scale fermentations (150 liters) using Pinot noir grapes from 10 California vineyards across two vintages. A core gene expression program was observed across all fermentations irrespective of vintage, similar to that of laboratory fermentations, in addition to novel gene expression patterns likely related to the presence of non- Saccharomyces microorganisms and oxygen availability during fermentation. These gene expression patterns, both common and diverse, provide insight into Saccharomyces cerevisiae biology critical to fermentation outcomes under industry-relevant conditions. IMPORTANCE This study characterized Saccharomyces cerevisiae RC212 gene expression during Pinot noir fermentation at pilot scale (150 liters) using industry-relevant conditions. The reported gene expression patterns of RC212 are generally similar to those observed under laboratory fermentation conditions but also contain gene expression signatures related to yeast-environment interactions found in a production setting (e.g., the presence of non- Saccharomyces microorganisms). Key genes and pathways highlighted by this work remain undercharacterized, indicating the need for further research to understand the roles of these genes and their impact on industrial wine fermentation outcomes., (Copyright © 2021 Reiter et al.)

Ribosomal DNA amplicon sequencing of grape musts has demonstrated that microorganisms occur nonrandomly and are associated with the vineyard of origin, suggesting a role for the vineyard, grape, and wine microbiome in shaping wine fermentation outcomes. Here, ribosomal DNA amplicon sequencing from grape musts and RNA sequencing of eukaryotic transcripts from primary fermentations inoculated with the wine yeast Saccharomyces cerevisiae RC212 were used to profile fermentations from 15 vineyards in California and Oregon across two vintages. These data demonstrate that the relative abundance of fungal organisms detected by ribosomal DNA amplicon sequencing correlated with neither transcript abundance from those same organisms within the RNA sequencing data nor gene expression of the inoculated RC212 yeast strain. These data suggest that the majority of the fungi detected in must by ribosomal DNA amplicon sequencing were not active during the primary stage of these inoculated fermentations and were not a major factor in determining RC212 gene expression. However, unique genetic signatures were detected within the ribosomal DNA amplicon and eukaryotic transcriptomic sequencing that were predictive of vineyard site and region. These signatures included S. cerevisiae gene expression patterns linked to nitrogen, sulfur, and thiamine metabolism. These genetic signatures of site offer insight into specific environmental factors to consider with respect to fermentation outcomes and vineyard site and regional wine characteristics. IMPORTANCE The wine industry generates billions of dollars of revenue annually, and economic productivity is in part associated with regional distinctiveness of wine sensory attributes. Microorganisms associated with grapes and wineries are influenced by region of origin, and given that some microorganisms play a role in fermentation, it is thought that microbes may contribute to the regional distinctiveness of wine. In this work, as in previous studies, it is demonstrated that specific bacteria and fungi are associated with individual wine regions and vineyard sites. However, this work further shows that their presence is not associated with detectable fungal gene expression during the primary fermentation or the expression of specific genes by the inoculate Saccharomyces cerevisiae strain RC212. The detected RC212 gene expression signatures associated with region and vineyard site also allowed the identification of flavor-associated metabolic processes and environmental factors that could impact primary fermentation outcomes. These data offer novel insights into the complexities and subtleties of vineyard-specific inoculated wine fermentation and starting points for future investigations into factors that contribute to regional wine distinctiveness., (Copyright © 2021 Reiter et al.)

Metabolite profiles of white wines, including Chardonnay, Pinot gris, Riesling, Sauvignon blanc, and Viognier varieties, were determined using both gas chromatography-coupled time-of-flight mass spectrometry (GC-TOF-MS) and proton nuclear magnetic resonance spectroscopy ((1)H NMR). A total of 108 metabolites were identified by GC-TOF-MS, and 51 metabolites were identified by (1)H NMR; the majority of metabolites identified include the most abundant compounds found in wine (ethanol, glycerol, sugars, organic acids, and amino acids). Compositional differences in these wines correlating to the wine sensory property "body", or viscous mouthfeel, as scored by a trained panel were identified using partial least-squares (PLS) regression. Independently calculated GC-TOF-MS and NMR-based PLS models demonstrate potential for predictive models to replace expensive, time-consuming sensory panels. At the modeling stage, correlations between the measured and predicted values have coefficients of determination of 0.83 and 0.75 for GC-TOF-MS and (1)H NMR, respectively. Additionally, the MS- and NMR-based models present new insights into the chemical basis for wine mouthfeel properties.