Osmoadaptation of wine yeast (<i>Saccharomyces cerevisiae</i>) during Icewine fermentation leads to high levels of acetic acid
Bibliographic record
Abstract
AIMS: Volatile acidity (VA) production along with gene expression patterns, encoding enzymes involved in both acetic acid production and utilization, were investigated to relate gene expression patterns to the production of undesired VA during Icewine fermentation. METHODS AND RESULTS: Icewine juice and diluted Icewine juice were fermented using the Saccharomyces cerevisiae wine yeast K1-V1116. Acetic acid production increased sixfold during the Icewine fermentation vs the diluted juice condition, while ethyl acetate production increased 2·4-fold in the diluted fermentation relative to the Icewine. Microarray analysis profiled the transcriptional response of K1-V1116 under both conditions. ACS1 and ACS2 were downregulated 19·0-fold and 11·2-fold, respectively, in cells fermenting Icewine juice compared to diluted juice. ALD3 expression was upregulated 14·6-fold, and gene expressions involved in lipid and ergosterol synthesis decreased during Icewine fermentation. CONCLUSIONS: Decreased expression of ACS1 and ACS2 together with increased ALD3 expression contributes to the higher acetic acid and lower ethyl acetate levels generated by K1-V1116 fermenting under hyperosmotic stress. SIGNIFICANCE AND IMPACT OF THE STUDY: This work represents a more comprehensive understanding of how and why commercial wine yeast respond at the transcriptional and metabolic level during fermentation of Icewine juice, and how these responses contribute to increased acetic acid and decreased ethyl acetate production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".