Improving the Production of Punicic Acid in Baker’s Yeast by Engineering Genes in Acyl Channeling Processes and Adjusting Precursor Supply
Bibliographic record
Abstract
Punicic acid (PuA) is a high-value edible conjugated fatty acid with strong bioactivities and has important potential applications in nutraceutical, pharmaceutical, feeding, and oleochemical industries. Since the production of PuA is severely limited by the fact that its natural source (pomegranate seed oil) is not readily available on a large scale, there is considerable interest in understanding the biosynthesis and accumulation of this plant-based unusual fatty acid in transgenic microorganisms to support the rational design of biotechnological approaches for PuA production via fermentation. Here, we tested the effectiveness of genetic engineering and precursor supply in PuA production in the model yeast strain Saccharomyces cerevisiae . The results revealed that the combination of precursor feeding and co-expression of selected genes in acyl channeling processes created an effective “push–pull” approach to increase PuA content, which could prove valuable in future efforts to produce PuA in industrial yeast and other microorganisms via fermentation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".