Identification of Genes Involved in the Toxic Response of Saccharomyces cerevisiae against Iron and Copper Overload by Parallel Analysis of Deletion Mutants
Why this work is in the frame
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Bibliographic record
Abstract
Iron and copper are essential nutrients for life as they are required for the function of many proteins but can be toxic if present in excess. Accumulation of these metals in the human body as a consequence of overload disorders and/or high environmental exposures has detrimental effects on health. The budding yeast Saccharomyces cerevisiae is an accepted cellular model for iron and copper metabolism in humans primarily because of the high degree of conservation between pathways and proteins involved. Here we report a systematic screen using yeast deletion mutants to identify genes involved in the toxic response to growth-inhibitory concentrations of iron and copper sulfate. We aimed to understand the cellular responses to toxic concentrations of these two metals by analyzing the different subnetworks and biological processes significantly enriched with these genes. Our results indicate the presence of two different detoxification pathways for iron and copper that converge toward the vacuole. The product of several of the identified genes in these pathways form molecular complexes that are conserved in mammals and include the retromer, endosomal sorting complex required for transport (ESCRT) and AP-3 complexes, suggesting that the mechanisms involved can be extrapolated to humans. Our data also suggest a disruption in ion homeostasis and, in particular, of iron after copper exposure. Moreover, the identification of treatment-specific genes associated with biological processes such as DNA double-strand break repair for iron and tryptophan biosynthesis for copper suggests differences in the mechanisms by which these two metals are toxic at high concentrations.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it