DENND6A couples Arl8b to a Rab34/RILP/dynein complex regulating retrograde lysosomal trafficking and autophagy
Bibliographic record
Abstract
Abstract Lysosomes help maintain cellular proteostasis, and defects in lysosomal positioning and function lead to diseases including neurodegenerative disorders. The spatiotemporal distribution of lysosomes is regulated by small GTPases, including Rabs, which are activated by guanine nucleotide exchange factors (GEFs). DENN domain–bearing proteins are the largest family of Rab GEFs. Using a cell-based assay, we screened the DENN domain protein family member DENND6A for potential GEF activity toward all 60 Rabs and identified 20 potential DENND6A substrates, including Rab34. Here, we demonstrate that DENND6A activates Rab34, which recruits a RILP/dynein complex to the lysosomes, promoting lysosomal retrograde trafficking from the cell periphery to the minus ends of microtubules. Further, we identify DENND6A as an effector of Arl8b, a major regulatory GTPase on lysosomes. Initially known for promoting anterograde transport of lysosomes, Arl8b also facilitates lysosomal retrograde transport. We demonstrate that Arl8b recruits DENND6A to peripheral lysosomes to activate Rab34 and initiate retrograde transport, regulating nutrient-dependent lysosomal juxtanuclear repositioning and loss of DENND6A impairs autophagic flux. Our findings support a model whereby Arl8b/DENND6A/Rab34-dependent lysosomal retrograde trafficking controls autophagy.
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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) | 0.002 | 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".