A Chemogenomic Screen in Saccharomyces cerevisiae Uncovers a Primary Role for the Mitochondria in Farnesol Toxicity and Its Regulation by the Pkc1 Pathway
Bibliographic record
Abstract
The isoprenoid farnesol has been shown to preferentially induce apoptosis in cancerous cells; however, the mode of action of farnesol-induced death is not established. We used chemogenomic profiling using Saccharomyces cerevisiae to probe the core cellular processes targeted by farnesol. This screen revealed 48 genes whose inactivation increased sensitivity to farnesol. The gene set indicated a role for the generation of oxygen radicals by the Rieske iron-sulfur component of complex III of the electron transport chain as a major mediator of farnesol-induced cell death. Consistent with this, loss of mitochondrial DNA, which abolishes electron transport, resulted in robust resistance to farnesol. A genomic interaction map predicted interconnectedness between the Pkc1 signaling pathway and farnesol sensitivity via regulation of the generation of reactive oxygen species. Consistent with this prediction (i) Pkc1, Bck1, and Mkk1 relocalized to the mitochondria upon farnesol addition, (ii) inactivation of the only non-essential and non-redundant member of the Pkc1 signaling pathway, BCK1, resulted in farnesol sensitivity, and (iii) expression of activated alleles of PKC1, BCK1, and MKK1 increased resistance to farnesol and hydrogen peroxide. Sensitivity to farnesol was not affected by the presence of the osmostabilizer sorbitol nor did farnesol affect phosphorylation of the ultimate Pkc1-responsive kinase responsible for controlling the cell wall integrity pathway, Slt2. The data indicate that the generation of reactive oxygen species by the electron transport chain is a primary mechanism by which farnesol kills cells. The Pkc1 signaling pathway regulates farnesol-mediated cell death through management of the generation of reactive oxygen species.
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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 | 0.000 |
| 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".