Transcriptional regulation of nonfermentable carbon utilization in budding yeast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Saccharomyces cerevisiae preferentially uses glucose as a carbon source, but following its depletion, it can utilize a wide variety of other carbons including nonfermentable compounds such as ethanol. A shift to a nonfermentable carbon source results in massive reprogramming of gene expression including genes involved in gluconeogenesis, the glyoxylate cycle, and the tricarboxylic acid cycle. This review is aimed at describing the recent progress made toward understanding the mechanism of transcriptional regulation of genes responsible for utilization of nonfermentable carbon sources. A central player for the use of nonfermentable carbons is the Snf1 kinase, which becomes activated under low glucose levels. Snf1 phosphorylates various targets including the transcriptional repressor Mig1, resulting in its inactivation allowing derepression of gene expression. For example, the expression of CAT8, encoding a member of the zinc cluster family of transcriptional regulators, is then no longer repressed by Mig1. Cat8 becomes activated through phosphorylation by Snf1, allowing upregulation of the zinc cluster gene SIP4. These regulators control the expression of various genes including those involved in gluconeogenesis. Recent data show that another zinc cluster protein, Rds2, plays a key role in regulating genes involved in gluconeogenesis and the glyoxylate pathway. Finally, the role of additional regulators such as Adr1, Ert1, Oaf1, and Pip2 is also discussed.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it