The Cellular Trafficking of the Secretory Proprotein Convertase PCSK9 and Its Dependence on the LDLR
Bibliographic record
Abstract
Mutations in the proprotein convertase PCSK9 gene are associated with autosomal dominant familial hyper- or hypocholesterolemia. These phenotypes are caused by a gain or loss of function of proprotein convertase subtilisin kexin 9 (PCSK9) to elicit the degradation of the low-density lipoprotein receptor (LDLR) protein. Herein, we asked whether the subcellular localization of wild-type PCSK9 or mutants of PCSK9 and the LDLR would provide insight into the mechanism of PCSK9-dependent LDLR degradation. We show that the LDLR is the dominant partner in regulating the cellular trafficking of PCSK9. In cells lacking the LDLR, PCSK9 localized in the endoplasmic reticulum (ER). In cells expressing the LDLR, PCSK9 sorted to post-ER compartments (i.e. endosomes in cell lines and Golgi apparatus in primary hepatocytes), where it colocalized with the LDLR. In cell lines, PCSK9 also colocalized with the LDLR at the cell surface, requiring the presence of the C-terminal Cys/His-rich domain of PCSK9. We provide evidence that PCSK9 promotes the degradation of the LDLR by an endocytic mechanism, as small interfering RNA-mediated knockdown of the clathrin heavy chain reduced the functional activity of PCSK9. We also compared the subcellular localization of natural mutants of PCSK9 with that of the wild-type enzyme in human hepatic (HuH7) cells. Whereas the mutants associated with hypercholesterolemia (S127R, F216L and R218S) localized to endosomes/lysosomes, those associated with hypocholesterolemia did not reach this compartment. We conclude that the sorting of PCSK9 to the cell surface and endosomes is required for PCSK9 to fully promote LDLR degradation and that retention in the ER prevents this activity. Mutations that affect this transport can lead to hyper- or hypocholesterolemia.
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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) | 0.001 | 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".