SARS-CoV-2 mutations affect proteasome processing to alter CD8 <sup>+</sup> T cell responses
Bibliographic record
Abstract
Abstract Viral CD8 + epitopes are generated by the cellular turnover of viral proteins, predominantly by the proteasome. Mutations located within viral epitopes can result in escape from memory T cells but the contribution of mutations in flanking regions of epitopes in SARS-CoV-2 has not been investigated. Focusing on two of the most dominant SARS-CoV-2 nucleoprotein CD8 + epitopes, we identified mutations in epitope flanking regions and investigated the contribution of these mutations to antigen processing and T cell activation using SARS-CoV-2 nucleoprotein transduced B cell lines and in vitro proteasomal processing of peptides. We found that decreased NP 9-17 -B*27:05 CD8 + T cell responses to the NP-Q7K mutation correlated with lower epitope surface expression, likely due to a lack of efficient epitope production by the proteasome, suggesting immune escape caused by this mutation. In contrast, NP-P6L and NP-D103N/Y mutations flanking the NP 9-17 -B*27:05 and NP 105-113 -B*07:02 epitopes, respectively, increased CD8 + T cell responses associated with enhanced epitope production by the proteasome. Our results provide evidence that SARS-CoV-2 mutations outside the epitope could have a significant impact on antigen processing and presentation, thereby contributing to escape from immunodominant T cell responses. Alternatively, mutations could enhance antigen processing and efficacy of T cell recognition, opening new avenues for improving future vaccine designs. One Sentence Summary Natural mutations in the flanking regions of known immunodominant SARS-CoV-2 nucleoprotein epitopes can decrease CD8 + T cell responses leading to partial escape.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".