Investigation of metal toxicity leads to the identification of novel translation associated genes in yeast (Saccharomyces cerevisiae)
Bibliographic record
Abstract
Heavy metal and metalloid pollutants in our environment are among the most concerning types of contaminations. Major chronic diseases in humans such as renal and cardiovascular diseases, and neurological decline, are strongly associated with heavy metals and metalloids. Therefore, investigation and understanding the molecular mechanisms of cellular responses and detoxification processes that overcome the toxicity of these compounds in living organisms is very important. To date, several genes are identified to play central roles in cellular detoxification process. The expression of such genes can be influenced at both the transcriptional and/or translational levels by the heavy metals. As a fundamental step in the gene expression pathway, we focused on the regulation of translation initiation under stress imposed by heavy metals and metalloids. Although a wealth of information exists on the process of eukaryotic translation, a comprehensive understanding of regulation of translation initiation under stress conditions is lacking. The growing list of novel factors affecting this process further indicate the existence of other novel players, which are yet to be discovered. In the current study, we sought out to identify novel genes encoding regulatory factors known that affect yeast translation initiation during stress when general translation seems to be shut down. Utilizing systems biology techniques, we investigated the effect of specific gene deletions under heavy metal and metalloid conditions on the general process of translation and internal initiation of translation (an alternative mode of translation mediated by specific RNA structures). We explicitly investigated the role of four of identified potential translation regulating genes based on their activity in heavy metals and metalloids sensitivity. We also performed a high-throughput plasmid-based screening of a library of non-essential gene deletion strains (~4500), using the baker's yeast (Saccharomyces cerevisiae) as our model organism to identify novel genes that are involved in internal translation initiation. To this end, we identified dozens of potential novel genes that may be involved in internal translation initiation. We further investigated the role of five potential factors to support their newly identified activity.
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.
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 | 0.001 |
| 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".