Valproate inhibits MAP kinase signalling and cell cycle progression in S. cerevisiae
Bibliographic record
Abstract
The mechanism of action of valproate (VPA), a widely prescribed short chain fatty acid with anticonvulsant and anticancer properties, remains poorly understood. Here, the yeast Saccharomyces cerevisiae was used as model to investigate the biological consequences of VPA exposure. We found that low pH strongly potentiates VPA-induced growth inhibition. Transcriptional profiling revealed that under these conditions, VPA modulates the expression of genes involved in diverse cellular processes including protein folding, cell wall organisation, sexual reproduction, and cell cycle progression. We further investigated the impact of VPA on selected processes and found that this drug: i) activates markers of the unfolded protein stress response such as Hac1 mRNA splicing; ii) modulates the cell wall integrity pathway by inhibiting the activation of the Slt2 MAP kinase, and synergizes with cell wall stressors such as micafungin and calcofluor white in preventing yeast growth; iii) prevents activation of the Kss1 and Fus3 MAP kinases of the mating pheromone pathway, which in turn abolishes cellular responses to alpha factor; and iv) blocks cell cycle progression and DNA replication. Overall, our data identify heretofore unknown biological responses to VPA in budding yeast, and highlight the broad spectrum of cellular pathways influenced by this chemical in eukaryotes.
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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) | 0.001 | 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".