Laboratory evolution for forced glucose-xylose co-consumption enables identification of mutations that improve mixed-sugar fermentation by xylose-fermenting Saccharomyces cerevisiae
Bibliographic record
Abstract
Simultaneous fermentation of glucose and xylose can contribute to improved productivity and robustness of yeast-based processes for bioethanol production from lignocellulosic hydrolysates. This study explores a novel laboratory evolution strategy for identifying mutations that contribute to simultaneous utilisation of these sugars in batch cultures of Saccharomyces cerevisiae. To force simultaneous utilisation of xylose and glucose, the genes encoding glucose-6-phosphate isomerase (PGI1) and ribulose-5-phosphate epimerase (RPE1) were deleted in a xylose-isomerase-based xylose-fermenting strain with a modified oxidative pentose-phosphate pathway. Laboratory evolution of this strain in serial batch cultures on glucose-xylose mixtures yielded mutants that rapidly co-consumed the two sugars. Whole-genome sequencing of evolved strains identified mutations in HXK2, RSP5 and GAL83, whose introduction into a non-evolved xylose-fermenting S. cerevisiae strain improved co-consumption of xylose and glucose under aerobic and anaerobic conditions. Combined deletion of HXK2 and introduction of a GAL83G673T allele yielded a strain with a 2.5-fold higher xylose and glucose co-consumption ratio than its xylose-fermenting parental strain. These two modifications decreased the time required for full sugar conversion in anaerobic bioreactor batch cultures, grown on 20 g L-1 glucose and 10 g L-1 xylose, by over 24 h. This study demonstrates that laboratory evolution and genome resequencing of microbial strains engineered for forced co-consumption is a powerful approach for studying and improving simultaneous conversion of mixed substrates.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".