Functional Genomics Analysis of the<i>Saccharomyces cerevisiae</i>Iron Responsive Transcription Factor Aft1 Reveals Iron-Independent Functions
Bibliographic record
Abstract
The Saccharomyces cerevisiae transcription factor Aft1 is activated in iron-deficient cells to induce the expression of iron regulon genes, which coordinate the increase of iron uptake and remodel cellular metabolism to survive low-iron conditions. In addition, Aft1 has been implicated in numerous cellular processes including cell-cycle progression and chromosome stability; however, it is unclear if all cellular effects of Aft1 are mediated through iron homeostasis. To further investigate the cellular processes affected by Aft1, we identified >70 deletion mutants that are sensitive to perturbations in AFT1 levels using genome-wide synthetic lethal and synthetic dosage lethal screens. Our genetic network reveals that Aft1 affects a diverse range of cellular processes, including the RIM101 pH pathway, cell-wall stability, DNA damage, protein transport, chromosome stability, and mitochondrial function. Surprisingly, only a subset of mutants identified are sensitive to extracellular iron fluctuations or display genetic interactions with mutants of iron regulon genes AFT2 or FET3. We demonstrate that Aft1 works in parallel with the RIM101 pH pathway and the role of Aft1 in DNA damage repair is mediated by iron. In contrast, through both directed studies and microarray transcriptional profiling, we show that the role of Aft1 in chromosome maintenance and benomyl resistance is independent of its iron regulatory role, potentially through a nontranscriptional mechanism.
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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".