Endosomal trafficking protein <scp>TBC</scp>‐2 modulates stress resistance and lifespan through <scp>DAF</scp>‐16‐dependent and independent mechanisms
Bibliographic record
Abstract
The FOXO transcription factor, DAF-16, plays an integral role in insulin/IGF-1 signaling (IIS) and stress response. In conditions of stress or decreased IIS, DAF-16 moves to the nucleus where it activates genes that promote survival. To gain insight into the role of endosomal trafficking in resistance to stress, we disrupted tbc-2, which encodes a GTPase activating protein that inhibits RAB-5 and RAB-7. We found that tbc-2 mutants have decreased nuclear localization of DAF-16 in response to heat stress, anoxia, and bacterial pathogen stress, but increased nuclear localization of DAF-16 in response to chronic oxidative stress and osmotic stress. tbc-2 mutants also exhibit decreased upregulation of DAF-16 target genes in response to stress. To determine whether the rate of nuclear localization of DAF-16 affected stress resistance in these animals, we examined survival after exposure to multiple exogenous stressors. Disruption of tbc-2 decreased resistance to heat stress, anoxia, and bacterial pathogen stress in both wild-type worms and stress-resistant daf-2 insulin/IGF-1 receptor mutants. Similarly, deletion of tbc-2 decreases lifespan in both wild-type worms and daf-2 mutants. When DAF-16 is absent, the loss of tbc-2 is still able to decrease lifespan but has little or no impact on resistance to most stresses. Combined, this suggests that disruption of tbc-2 affects lifespan through both DAF-16-dependent and DAF-16-independent pathways, while the effect of tbc-2 deletion on resistance to stress is primarily DAF-16-dependent. Overall, this work demonstrates the importance of endosomal trafficking for the proper nuclear localization of DAF-16 during stress and that perturbation of normal endosomal trafficking is sufficient to decrease both stress resistance and lifespan.
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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".