Regulatory T cells aid <i>Leishmania major</i> immune evasion by suppressing effector responses against the parasite in an antigen-specific manner
Bibliographic record
Abstract
Abstract Despite the generation of a strong T cell response, clearance of Leishmania major is incomplete and leaves a pool of chronically infected cells. Understanding of the persistence is lacking, but Leishmania major driven induction of the immunosuppressive microenvironment through recruitment of regulatory T cells at the site of infection has been proposed to prevent parasite clearance in vivo. Here, we used a novel TCR transgenic mouse model, where CD4+ T cells recognize an immunodominant peptide derived from Leishmania-glycosomal phosphoenolpyruvate carboxykinase (PEPCK), to visualize the dynamics of anti-L. major CD4+ T cell responses and characterize mechanisms which restrain their effector function. We show that PEPCK-specific Tregs are able to suppress nearly 80% of IFNg produced by PEPCK-specific Th1 cells in vitro though the production of IL-10, while decreasing IL-12, TNF, and IL-2. Intravital microscopy studies characterizing PEPCK-specific CD4+ T cell migration dynamics in live mice show a significant recruitment of adoptively transferred cells to the lesion site in vivo, displaying cellular behaviors consistent with antigen recognition, yet augmented at the chronic stage, indicating a fundamentally altered environment. Injection of heat-killed L. major into mice which have already healed a L. major infection, distal to the original lesion, induced a rapid expansion of PEPCK-specific Tregs at the original site of infection, which suppressed endogenous anti-Leishmania response through IL-10 and led to parasite expansion and lesion reactivation. Our results show that antigen recognition by Tregs plays an important role in suppressing effector responses against L. major and thus maintaining concomitant immunity. Research funded by a grant from the GSK-CIHR Partnered Chair Program
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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 | 0.001 |
| 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".