Organization of the Sec61 Translocon, Studied by High Resolution Native Electrophoresis
Bibliographic record
Abstract
Cotranslational translocation of polypeptides into the ER is controlled by the dynamic interaction of ribosome and translocon components. Analysis of the steps involved in this process by high resolution techniques such as gel electrophoresis is precluded by the high molecular masses of these complexes. We show, here, that modifications to standard native electrophoresis protocols can overcome these problems and lead to an increase in mass range and resolution. Using the modified technique, we show that ER ribosome anchored membrane protein (RAMP) complexes resolve into 3 stable and semistable complexes which range in size between 4 and 8 MDa and are sensitive to relevant concentrations of divalent metals. We demonstrate the molecular composition of the complexes and identify a number of modular components that differentiate them. The components that are common to all three RAMP complexes include the OST translocon subcomplex, Glucosidase I and microtubule tethering protein CLIMP63. The two larger complexes further include the kinesin motor binding protein p180 and Sec61, and the largest complex includes the TRAP translocon component and apoptotic regulator BAP31. On the lumenal side, the BiP cochaperone ERdj3 resides with the three RAMP complexes. Our observations may hint at how subcompartmentalization is achieved in the ER membrane continuum.
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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 | 0.000 | 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".