RNF13 Regulates the Endolysosomal Pathway Through Interaction with the Small GTPase Arl8B
Bibliographic record
Abstract
The endolysosomal system is a dynamic intracellular network essential for cargo degradation, recycling, and spatial compartmentalization. Proper coordination of endosome maturation and positioning is critical for lysosomal function and receptor fate. This study identifies an additional role for the E3 ubiquitin ligase RNF13 in controlling endolysosomal dynamics through its interaction with the small GTPase Arl8B. Predictive structural modeling and co-immunoprecipitation revealed that RNF13 binds to Arl8B via residues Glu22 and Phe55 of Arl8B and Leu244 of RNF13. Binding occurs with a modest preference for the GDP-bound Arl8B over GTP-bound state, suggesting that RNF13 may engage an inactive fraction of Arl8B to influence endolysosomal positioning and assembly of Arl8B-dependent trafficking complexes. Disrupting RNF13-Arl8B binding alters Arl8B localization and redistributes lysosomes toward the cell periphery without changing the abundance of endolysosomal markers. Functionally, perturbing this interaction selectively alters epidermal growth factor receptor (EGFR) trafficking kinetics, consistent with a delayed progression of cargo toward lysosomal degradation rather than a general defect in endocytosis. Although overexpression of the Arl8B effector PLEKHM1 enhances RNF13-Arl8B association, this is better explained by a shared Arl8B binding interface and does not imply direct cooperativity between RNF13 and PLEKHM1. Together, these findings identify RNF13 as a regulator of lysosomal organization and cargo transport, operating through Arl8B binding and ubiquitination that can occur without a proportional change in Arl8B abundance under our assay conditions. This work reveals an additional layer of regulation in endolysosomal trafficking, highlighting RNF13 as a regulatory node influencing cargo progression through degradative pathways.
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".