Transcriptomic Response of Saccharomyces cerevisiae during Fermentation under Oleic Acid and Ergosterol Depletion
Bibliographic record
Abstract
Under anaerobic/hypoxic conditions, Saccharomyces cerevisiae relies on external lipid supplements to modulate membrane lipid fraction in response to different stresses. Here, transcriptomic responses of two S. cerevisiae wine strains were evaluated during hypoxic fermentation of a synthetic must with/without ergosterol and oleic acid supplementation. In the absence of lipids, the two strains, namely EC1118 and M25, showed different behaviour, with M25 significantly decreasing its fermentation rate from the 72 h after inoculum. At this time point, the whole genome transcriptomic analysis revealed common and strain-specific responses to the lack of lipid supplementation. Common responses included the upregulation of the genes involved in ergosterol biosynthesis, as well as the seripauperin and the heat shock protein multigene families. In addition, the upregulation of the aerobic isoforms of genes involved in mitochondrial electron transport is compatible with the previously observed accumulation of reactive oxygen species in the two strains during growth in absence of lipids. Considering the strain-specific responses, M25 downregulated the transcription of genes involved in glucose transport, methionine biosynthesis and of those encoding mannoproteins required for adaptation to low temperatures and hypoxia. The identification of these pathways, which are presumably involved in yeast resistance to stresses, will assist industrial strain selection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".