Eukaryotic Elongation Factor 2 Kinase EFK-1/eEF2K promotes starvation resistance by preventing oxidative damage in C. elegans
Bibliographic record
Abstract
Cells and organisms frequently experience starvation. To survive, they mount an evolutionarily conserved stress response. A vital component in the mammalian starvation response is eukaryotic elongation factor 2 (eEF2) kinase (eEF2K), which suppresses translation in starvation by phosphorylating and inactivating the translation elongation driver eEF2. C. elegans EFK-1/eEF2K phosphorylates EEF-2/eEF2 on a conserved residue and is required for starvation survival, but how it promotes survival remains unclear. Surprisingly, we found that eEF2 phosphorylation is unchanged in starved C. elegans and EFK-1’s kinase activity is dispensable for starvation survival, suggesting that efk-1 promotes survival via a noncanonical pathway. We show that efk-1 upregulates transcription of DNA repair pathways, nucleotide excision repair (NER) and base excision repair (BER), to promote starvation survival. Furthermore, efk-1 suppresses oxygen consumption and ROS production in starvation to prevent oxidative stress. Thus, efk-1 enables starvation survival by protecting animals from starvation-induced oxidative damage through an EEF-2-independent pathway. Cells survive starvation by activating protective pathways. Here, the authors describe that kinase EFK-1/eEF2K defends against oxidative damage in long term starvation in C. elegans independently from its kinase activity and translation 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) | 0.000 | 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 | 0.001 |
| 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".