Genetic Dissection Reveals New Components of the NHR-49 Multi-Stress Resistance and Longevity Pathway
Bibliographic record
Abstract
Cells, tissues, and organisms encounter many environmental and endogenous stresses, and the ability to mount specific responses to these stresses is critical to achieve homeostasis and survival.Stress also occurs in many pathological states and is therefore of great biomedical relevance, both as a cause or contributor to diseases and as a potential therapeutic target.Pathways that regulate the responses to oxidative stress, hypoxia, and starvation are evolutionarily conserved from the nematode Caenorhabditis elegans to humans and involve master regulators of gene expression.One such stress response pathway engages C. elegans NHR-49, an orthologue of mammalian PPARα, which is required to survive tBOOH-induced oxidative stress, hypoxia, and starvation, and is also a key effector in many genetic longevity pathways.However, in contrast to other stress response pathways such as SKN-1/Nrf2 and HIF-1/HIF signaling, many aspects of NHR-49 signaling remain poorly understood.To map new components of this pathway, we performed reverse genetic screens, uncovering 80 candidate kinases, transcription factors, and transcriptional coregulators required for NHR-49-controlled gene activation in tBOOH, hypoxia, and/or starvation.Further analysis revealed that the kinase hpk-1/HIPK is required in the nhr-49 pathway for hypoxia and oxidative stress survival, that pseudokinase nipi-3 is required with nhr-49 for hypoxia survival, and that transcription factor nhr-80 is required with nhr-49 for hypoxia and oxidative stress survival and for the normal lifespan of wild-type C. elegans.Collectively, our data identify numerous new potential regulators in an important stress response and thus substantially enhance our understanding of stress adaptation and longevity regulation.
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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) | 0.002 | 0.001 |
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".