Endoplasmic Reticulum (ER) Mannosidase I Is Compartmentalized and Required for <i>N</i>-Glycan Trimming to Man<sub>5–6</sub>GlcNAc<sub>2</sub> in Glycoprotein ER-associated Degradation
Bibliographic record
Abstract
We had previously shown that endoplasmic reticulum (ER)-associated degradation (ERAD) of glycoproteins in mammalian cells involves trimming of three to four mannose residues from the N-linked oligosaccharide Man(9)GlcNAc(2). A possible candidate for this activity, ER mannosidase I (ERManI), accelerates the degradation of ERAD substrates when overexpressed. Although in vitro, at low concentrations, ERManI removes only one specific mannose residue, at very high concentrations it can excise up to four alpha1,2-linked mannose residues. Using small interfering RNA knockdown of ERManI, we show that this enzyme is required for trimming to Man(5-6)GlcNAc(2) and for ERAD in cells in vivo, leading to the accumulation of Man(9)GlcNAc(2) and Glc(1)Man(9)GlcNAc(2) on a model substrate. Thus, trimming by ERManI to the smaller oligosaccharides would remove the glycoprotein from reglucosylation and calnexin binding cycles. ERManI is strikingly concentrated together with the ERAD substrate in the pericentriolar ER-derived quality control compartment (ERQC) that we had described previously. ERManI knockdown prevents substrate accumulation in the ERQC. We suggest that the ERQC provides a high local concentration of ERManI, and passage through this compartment would allow timing of ERAD, possibly through a cycling mechanism. When newly made glycoproteins cannot fold properly, transport through the ERQC leads to trimming of a critical number of mannose residues, triggering a signal for degradation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".