ER stress affects processing of MHC class I-associated peptides
Bibliographic record
Abstract
BACKGROUND: Viral infection and neoplastic transformation trigger endoplasmic reticulum (ER) stress. Thus, a large proportion of the cells that must be recognized by the immune system are stressed cells. Cells respond to ER stress by launching the unfolded protein response (UPR). The UPR regulates the two key processes that control major histocompatibility complex class I (MHC I)-peptide presentation: protein synthesis and degradation. We therefore asked whether and how the UPR impinges on MHC I-peptide presentation. RESULTS: We evaluated the impact of the UPR on global MHC I expression and on presentation of the H2Kb-associated SIINFEKL peptide. EL4 cells stably transfected with vectors coding hen egg lysozyme (HEL)-SIINFEKL protein variants were stressed with palmitate or exposed to glucose deprivation. UPR decreased surface expression of MHC I but did not affect MHC I mRNA level nor the total amount of intracellular MHC I proteins. Impaired MHC I-peptide presentation was due mainly to reduced supply of peptides owing to an inhibition of overall protein synthesis. Consequently, generation of H2Kb-SIINFEKL complexes was curtailed during ER stress, illustrating how generation of MHC I peptide ligands is tightly coupled to ongoing protein synthesis. Notably, the UPR-induced decline of MHC I-peptide presentation was more severe when the protein source of peptides was localized in the cytosol than in the ER. This difference was not due to changes in the translation rates of the precursor proteins but to increased stability of the cytosolic protein during ER stress. CONCLUSION: Our results demonstrate that ER stress impairs MHC I-peptide presentation, and that it differentially regulates expression of ER- vs. cytosol-derived peptides. Furthermore, this work illustrates how ER stress, a typical feature of infected and malignant cells, can impinge on cues for adaptive immune recognition.
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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) | 0.002 | 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".