Neurotrophic factor MANF regulates autophagy and lysosome function to promote proteostasis in <i>C. elegans</i>
Bibliographic record
Abstract
ABSTRACT The conserved mesencephalic astrocyte-derived neurotrophic factor (MANF) protects dopaminergic neurons but also functions in several other tissues. Previously, we showed that Caenorhabditis elegans manf-1 null mutants have increased ER stress, dopaminergic neurodegeneration, protein aggregation, slower growth, and a reduced lifespan. The multiple requirements of MANF in different systems suggest its essential role in regulating cellular processes. However, how intracellular and extracellular MANF regulates broader cellular function remains unknown. Here, we report a novel mechanism of action for manf-1 that involves the autophagy transcription factor HLH-30/TFEB-mediated signaling to regulate lysosomal function and aging. We generated multiple transgenic strains overexpressing MANF-1 and found that animals had extended lifespan, reduced protein aggregation, and improved neuronal health. Using a fluorescently tagged MANF-1, we observed different tissue localization of MANF-1 depending on the ER retention signal. Further subcellular analysis showed that MANF-1 localizes within cells to the lysosomes. These findings were consistent with our transcriptomic studies and, together with analysis of autophagy regulators, demonstrate that MANF-1 regulates protein homeostasis through increased autophagy and lysosomal activity. Collectively, our findings establish MANF as a critical regulator of the stress response, proteostasis, and aging.
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) | 0.000 | 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 | 0.001 |
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".