Saccharomyces cerevisiae Gene Expression during Fermentation of Pinot Noir Wines at an Industrially Relevant Scale

Abstract

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 have previously revealed genes that underlie cellular adaptation to the grape must and wine environment 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 that observed in laboratory fermentation conditions, but also contain gene expression signatures related to yeast-environment interactions found in a production setting (e.g., presence of non-Saccharomyces microorganisms). Key genes and pathways highlighted by this work remain under-characterized, raising the need for further research to understand the roles of these genes and their impact on industrial wine fermentation outcomes.

Charting Shifts in Saccharomyces cerevisiae Gene Expression across Asynchronous Time Trajectories with Diffusion Maps

“…(C) Site-specific fermentations across sampling time as measured by °Brix (total soluble solids, used as a proxy for sugar concentration). Note that figure panels A and C include locations and fermentation curves previously published for 10 sites ( 4 ), which are displayed together with five other sites also represented in this study. Download .…”

“…Previously, inoculated primary fermentations of genetically similar Pinot noir grapes grown in California and Oregon were performed over multiple vintages at the UC Davis Teaching and Research Winery ( 4 , 9 , 30 , 31 ). In 2019, time course RNA sequencing data were collected with the aim of using S. cerevisiae gene expression as an indicator of similarities and differences across fermentations from 15 sites representing eight AVAs (see Fig.…”

“…Given the variable inputs and sensory differences described for wines from these sites ( 9 ), it was expected that there would be detectable differences in S. cerevisiae gene expression that would include genes known to impact the sensory outcome of wine ( 32 ). Yet, analysis of these data was only able to robustly identify the shared CGEP across fermentations ( 4 ). Site-specific differences were unable to be quantified because fermentations progressed at different rates, even with rigorous control of temperature at a 200-liter scale, leading to asynchronous biological progression among samples with respect to sampling time ( Fig.…”

“…During a wine fermentation, Saccharomyces cerevisiae metabolizes sugars and other nutrients to obtain energy for growth and survival, while also dealing with a common set of stresses caused by the must/wine environment. Given these general features of the system, the cellular activities of S. cerevisiae across wine fermentations are consistent, as reflected in a core gene expression program (CGEP) operating across fermentations ( 1 – 4 ). However, metabolism is not fixed, as S. cerevisiae dynamically responds to differences in the fermentation environment (e.g., nutrient levels, temperature, and varied microbial communities) to maintain cellular metabolism and overall fitness ( 1 , 2 , 5 , 6 ).…”

“…Towards this end, time series RNA sequencing of Pinot noir fermentations was previously used to identify gene expression differences across 15 unique sites representing eight American Viticultural Areas (AVAs). However, using standard analysis methods ( 17 – 22 ), only the CGEP was identified across fermentations, not gene expression patterns indicating altered S. cerevisiae metabolism that would differentiate site ( 4 ). A major issue was that sampled fermentations proceeded at different rates, leading to asynchronous biological progression among sequenced samples with respect to fermentation progress (e.g., sugar consumption).…”