Norovirus-Specific CD8+ T Cell Responses in Human Blood and Tissues
Bibliographic record
Abstract
Background & Aims Noroviruses (NoVs) are the leading cause of acute gastroenteritis worldwide and are associated with significant morbidity and mortality. Moreover, an asymptomatic carrier state can persist following acute infection, promoting NoV spread and evolution. Thus, defining immune correlates of NoV protection and persistence is needed to guide the development of future vaccines and limit viral spread. Whereas antibody responses following NoV infection or vaccination have been studied extensively, cellular immunity has received less attention. Data from the mouse NoV model suggest that T cells are critical for preventing persistence and achieving viral clearance, but little is known about NoV-specific T-cell immunity in humans, particularly at mucosal sites. Methods We screened peripheral blood mononuclear cells from 3 volunteers with an overlapping NoV peptide library. We then used HLA-peptide tetramers to track virus-specific CD8 + T cells in peripheral, lymphoid, and intestinal tissues. Tetramer + cells were further characterized using markers for cellular trafficking, exhaustion, cytotoxicity, and proliferation. Results We defined 7 HLA-restricted immunodominant class I epitopes that were highly conserved across pandemic strains from genogroup II.4. NoV-specific CD8 + T cells with central, effector, or tissue-resident memory phenotypes were present at all sites and were especially abundant in the intestinal lamina propria. The properties and differentiation states of tetramer + cells varied across donors and epitopes. Conclusions Our findings are an important step toward defining the breadth, distribution, and properties of human NoV T-cell immunity. Moreover, the molecular tools we have developed can be used to evaluate future vaccines and engineer novel cellular therapeutics.
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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) | 0.003 | 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".