Comparative Xylose Metabolism among the Ascomycetes C. albicans, S. stipitis and S. cerevisiae
Bibliographic record
Abstract
The ascomycetes Candida albicans, Saccharomyces cerevisiae and Scheffersomyces stipitis metabolize the pentose sugar xylose very differently. S. cerevisiae fails to grow on xylose, while C. albicans can grow, and S. stipitis can both grow and ferment xylose to ethanol. However, all three species contain highly similar genes that encode potential xylose reductases and xylitol dehydrogenases required to convert xylose to xylulose, and xylulose supports the growth of all three fungi. We have created C. albicans strains deleted for the xylose reductase gene GRE3, the xylitol dehydrogenase gene XYL2, as well as the gre3 xyl2 double mutant. As expected, all the mutant strains cannot grow on xylose, while the single gre3 mutant can grow on xylitol. The gre3 and xyl2 mutants are efficiently complemented by the XYL1 and XYL2 from S. stipitis. Intriguingly, the S. cerevisiae GRE3 gene can complement the Cagre3 mutant, while the ScSOR1 gene can complement the Caxyl2 mutant, showing that S. cerevisiae contains the enzymatic capacity for converting xylose to xylulose. In addition, the gre3 xyl2 double mutant of C. albicans is effectively rescued by the xylose isomerase (XI) gene of either Piromyces or Orpinomyces, suggesting that the XI provides an alternative to the missing oxido-reductase functions in the mutant required for the xylose-xylulose conversion. Overall this work suggests that C. albicans strains engineered to lack essential steps for xylose metabolism can provide a platform for the analysis of xylose metabolism enzymes from a variety of species, and confirms that S. cerevisiae has the genetic potential to convert xylose to xylulose, although non-engineered strains cannot proliferate on xylose as the sole carbon source.
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 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".