The Role of Enteric RORγt+ Regulatory T Cells in Altering Systemic Vaccine Responses Following Oral Antigen Exposure
Bibliographic record
Abstract
Many promising vaccine candidates and licensed vaccines lead to variable immune responses within humans and can fail to elicit protection against critical pathogens. Recent studies suggest that environmental exposures in the gastrointestinal (GI) tract could contribute to a reduction in vaccine efficacy via immune tolerance at this site. Tolerogenic mechanisms in the GI tract are partly achieved by the characteristic high abundance of regulatory T cells (Tregs). Subsets of regulatory T cells have been recently described; specifically, RORγt+ FoxP3+ Tregs could contribute to tolerating orally acquired antigens. This subset relies on the presence of commensal bacteria for development and has been described in regulating Type 2 associated immune responses. Currently, it is unclear which Treg subsets control systemic vaccine responses following oral antigen pre-exposure. In this study, we implemented a conditional RORγt+ Tregs knock-out (cKO) mouse model to examine the role of this subset in the suppression of systemic antibody titers after oral exposure to vaccine antigen. Following oral exposure to the model antigen ovalbumin (OVA) prior to immunization, we found similar induction of vaccine-induced antibody responses in mice lacking RORγt+ Tregs compared to sufficient controls. cKO mice exhibit higher frequencies of IL-33R+ and GATA3+ Tregs at baseline in the gut, suggesting that there is possible compensation from other subsets upon loss of expression of RORγt+ in Tregs. By utilizing a variety of adjuvants in our model, we have determined that vaccine-specific IgG1 is suppressed following oral antigen exposure, but not IgG2c, regardless of adjuvant strength or skew. In RORγt+ Treg cKO mice, use of different adjuvants led to similar findings; no differences were observed in the maintenance of tolerance to systemic OVA vaccination in cKO mice upon use of various adjuvants. Methods were explored to understand antigen-specific CD4+ response upon oral exposure prior to systemic vaccination; adoptive transfer of OVA-specific OT-II cells will continue to be explored in future studies. Taken together, our data suggest that RORγt+ Tregs are not solely responsible for controlling tolerance to oral antigens in a murine model of tolerance to a systemic vaccine.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".