Chemical and Synthetic Genetic Array Analysis Identifies Genes that Suppress Xylose Utilization and Fermentation in <i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
Though highly efficient at fermenting hexose sugars, Saccharomyces cerevisiae has limited ability to ferment five-carbon sugars. As a significant portion of sugars found in cellulosic biomass is the five-carbon sugar xylose, S. cerevisiae must be engineered to metabolize pentose sugars, commonly by the addition of exogenous genes from xylose fermenting fungi. However, these recombinant strains grow poorly on xylose and require further improvement through rational engineering or evolutionary adaptation. To identify unknown genes that contribute to improved xylose fermentation in these recombinant S. cerevisiae, we performed genome-wide synthetic interaction screens to identify deletion mutants that impact xylose utilization of strains expressing the xylose isomerase gene XYLA from Piromyces sp. E2 alone or with an additional copy of the endogenous xylulokinase gene XKS1. We also screened the deletion mutant array to identify mutants whose growth is affected by xylose. Our genetic network reveals that more than 80 nonessential genes from a diverse range of cellular processes impact xylose utilization. Surprisingly, we identified four genes, ALP1, ISC1, RPL20B, and BUD21, that when individually deleted improved xylose utilization of both S. cerevisiae S288C and CEN.PK strains. We further characterized BUD21 deletion mutant cells in batch fermentations and found that they produce ethanol even the absence of exogenous XYLA. We have demonstrated that the ability of laboratory strains of S. cerevisiae to utilize xylose as a sole carbon source is suppressed, which implies that S. cerevisiae may not require the addition of exogenous genes for efficient xylose fermentation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".