Calnuc Function in Endosomal Sorting of Lysosomal Receptors
Bibliographic record
Abstract
Calnuc is a ubiquitous Ca(2+)-binding protein present on the trans-Golgi network (TGN) and endosomes. However, the precise role of Calnuc in these organelles is poorly characterized. We previously highlighted the role of Calnuc in the transport of LRP9, a new member of a low-density lipoprotein (LDL) receptor subfamily that cycles between the TGN and endosomes. The objective of this study was to explore the role of Calnuc in the endocytic sorting of mannose-6-phosphate receptor (MPR) and Sortilin, two well-characterized lysosomal receptors that transit between the TGN and endosomes. Using biochemical and microscopy assays, we showed that Calnuc depletion [by small interfering RNA (siRNA)] causes the misdelivery to and degradation in lysosomes of cationic-independent mannose-6-phosphate receptor (CI-MPR) and Sortilin due to a defect in the endosomal recruitment of retromers, which are key components of the endosome-to-Golgi retrieval machinery. Indeed, we demonstrated that Calnuc depletion impairs the activation and membrane association of Rab7, a small G protein required for the endosomal recruitment of retromers. Overall, our data indicate a novel role for Calnuc in the endosome-to-TGN retrograde transport of lysosomal receptors through the regulation of Rab7 activity and the recruitment of retromers to endosomes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".