The Oxidative Stress Response in <i>Caenorhabditis elegans</i> Requires the GATA Transcription Factor ELT-3 and SKN-1/Nrf2
Bibliographic record
Abstract
Abstract Cellular damage caused by reactive oxygen species is believed to be a major contributor to age-associated diseases. Previously, we characterized the Caenorhabditis elegans Brap2 ortholog (BRAP-2) and found that it is required to prevent larval arrest in response to elevated levels of oxidative stress. Here, we report that C. elegans brap-2 mutants display increased expression of SKN-1-dependent, phase II detoxification enzymes that is dependent on PMK-1 (a p38 MAPK C. elegans ortholog). An RNA-interference screen was conducted using a transcription factor library to identify genes required for increased expression of the SKN-1 target gst-4 in brap-2 mutants. We identified ELT-3, a member of the GATA transcription factor family, as a positive regulator of gst-4p::gfp expression. We found that ELT-3 interacts with SKN-1 to activate gst-4 transcription in vitro and that elt-3 is required for enhanced gst-4 expression in the brap-2(ok1492) mutant in vivo. Furthermore, nematodes overexpressing SKN-1 required ELT-3 for life-span extension. Taken together, these results suggest a model where BRAP-2 acts as negative regulator of SKN-1 through inhibition of p38 MAPK activity, and that the GATA transcription factor ELT-3 is required along with SKN-1 for the phase II detoxification response in C. elegans.
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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".