N-Glycan-dependent and -independent Quality Control of Human δ Opioid Receptor N-terminal Variants
Bibliographic record
Abstract
Quality control (QC) in the endoplasmic reticulum (ER) scrutinizes newly synthesized proteins and directs them either to ER export or ER-associated degradation (ERAD). Here, we demonstrate that the human δ-opioid receptor (hδOR) is subjected to ERQC in both N-glycan-dependent and -independent manners. This was shown by investigating the biosynthesis and trafficking of wild-type and non-N-glycosylated F27C variants in metabolic pulse-chase assays coupled with flow cytometry and cell surface biotinylation. Both QC mechanisms distinguished the minute one-amino acid difference between the variants, targeting a large fraction of hδOR-Cys(27) to ERAD. However, the N-glycan-independent QC was unable to compensate the N-glycan-dependent pathway, and some incompletely folded non-N-glycosylated hδOR-Cys(27) reached the cell surface in conformation incompatible with ligand binding. The turnover of receptors associating with the molecular chaperone calnexin (CNX) was significantly slower for the hδOR-Cys(27), pointing to an important role of CNX in the hδOR N-glycan-dependent QC. This was further supported by the fact that inhibiting the co-translational interaction of hδOR-Cys(27) precursors with CNX led to their ERAD. Opioid receptor pharmacological chaperones released the CNX-bound receptors to ER export and, furthermore, were able to rescue the Cys(27) variant from polyubiquitination and retrotranslocation to the cytosol whether carrying N-glycans or not. Taken together, the hδOR appears to rely primarily on the CNX-mediated N-glycan-dependent QC that has the capacity to assist in folding, whereas the N-glycan-independent mechanism constitutes an alternative, although less accurate, system for directing misfolded/incompletely folded receptors to ERAD, possibly in altered cellular conditions.
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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) | 0.000 | 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".