The structure and location of SIMP/STT3B account for its prominent imprint on the MHC I immunopeptidome
Bibliographic record
Abstract
Proteins show drastic discrepancies in their contribution to the collection of self-peptides that shape the repertoire of CD8 T cells (MHC I self-immunopeptidome). To decipher why selected proteins are the foremost sources of MHC I-associated self-peptides, we chose to study SIMP/STT3B because this protein generates very high amounts of MHC I-associated peptides in mice and humans. We show that the endoplasmic reticulum (ER)-associated degradation pathway and MHC I processing intersect at SIMP/STT3B. Relevant key features of SIMP/STT3B are its lysine-rich region, its propensity to misfold and its location in the ER membrane in close proximity to the immunoproteasome. Moreover, we show that coupling to SIMP/STT3B can be used to foster MHC I presentation of a selected peptide, here the ovalbumin peptide SIINFEKL. These data yield novel insights into relations between the cell proteome and the MHC I immunopeptidome. They suggest that the contribution of a given protein to the MHC I immunopeptidome results from the interplay of at least three factors: the presence of degrons (degradation signals), the tendency of the protein to misfold and its subcellular localization. Furthermore, they indicate that substrates of the ER-associated degradation pathway may have a prominent imprint on the MHC I self-immunopeptidome.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".