Minimize the Xylitol Production in Saccharomyces cerevisiae by Balancing the Xylose Redox Metabolic Pathway
Bibliographic record
Abstract
Xylose is the second most abundant sugar in lignocellulose, but it cannot be used as carbon source by budding yeast Saccharomyces cerevisiae. Rational promoter elements engineering approaches were taken for efficient xylose fermentation in budding yeast. Among promoters surveyed, HXT7 exhibited the best performance. The HXT7 promoter is suppressed in the presence of glucose and derepressed by xylose, making it a promising candidate to drive xylose metabolism. However, simple ectopic expression of both key xylose metabolic genes XYL1 and XYL2 by the HXT7 promoter resulted in massive accumulation of the xylose metabolic byproduct xylitol. Through the HXT7-driven expression of a reported redox variant, XYL1-K270R, along with optimized expression of XYL2 and the downstream pentose phosphate pathway genes, a balanced xylose metabolism toward ethanol formation was achieved. Fermented in a culture medium containing 50 g/L xylose as the sole carbon source, xylose is nearly consumed, with less than 3 g/L xylitol, and more than 16 g/L ethanol production. Hence, the combination of an inducible promoter and redox balance of the xylose utilization pathway is an attractive approach to optimizing fuel production from lignocellulose.
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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".