Low Density Lipoprotein Receptor Class A Repeats Are O-Glycosylated in Linker Regions
Bibliographic record
Abstract
The low density lipoprotein receptor (LDLR) is crucial for cholesterol homeostasis and deficiency in LDLR functions cause hypercholesterolemia. LDLR is a type I transmembrane protein that requires O-glycosylation for stable expression at the cell surface. It has previously been suggested that LDLR O-glycosylation is found N-terminal to the juxtamembrane region. Recently we identified O-glycosylation sites in the linker regions between the characteristic LDLR class A repeats in several LDLR-related receptors using the "SimpleCell" O-glycoproteome shotgun strategy. Herein, we have systematically characterized O-glycosylation sites on recombinant LDLR shed from HEK293 SimpleCells and CHO wild-type cells. We find that the short linker regions between LDLR class A repeats contain an evolutionarily conserved O-glycosylation site at position -1 of the first cysteine residue of most repeats, which in wild-type CHO cells is glycosylated with the typical sialylated core 1 structure. The glycosites in linker regions of LDLR class A repeats are conserved in LDLR from man to Xenopus and found in other homologous receptors. O-Glycosylation is controlled by a large family of polypeptide GalNAc transferases. Probing into which isoform(s) contributed to glycosylation of the linker regions of the LDLR class A repeats by in vitro enzyme assays suggested a major role of GalNAc-T11. This was supported by expression of LDLR in HEK293 cells, where knock-out of the GalNAc-T11 isoform resulted in the loss of glycosylation of three of four linker regions.
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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 | 0.001 |
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".