TLR2 Stimulation Drives Human Naive and Effector Regulatory T Cells into a Th17-Like Phenotype with Reduced Suppressive Function
Bibliographic record
Abstract
Naturally occurring CD4(+)CD25(+)FOXP3(+) regulatory T cells suppress the activity of pathogenic T cells and prevent development of autoimmune responses. There is growing evidence that TLRs are involved in modulating regulatory T cell (Treg) functions both directly and indirectly. Specifically, TLR2 stimulation has been shown to reduce the suppressive function of Tregs by mechanisms that are incompletely understood. The developmental pathways of Tregs and Th17 cells are considered divergent and mutually inhibitory, and IL-17 secretion has been reported to be associated with reduced Treg function. We hypothesized that TLR2 stimulation may reduce the suppressive function of Tregs by regulating the balance between Treg and Th17 phenotype and function. We examined the effect of different TLR2 ligands on the suppressive functions of Tregs and found that activation of TLR1/2 heterodimers reduces the suppressive activity of CD4(+)CD25(hi)FOXP3(low)CD45RA(+) (naive) and CD4(+)CD25(hi)FOXP3(hi)CD45RA(-) (memory or effector) Treg subpopulations on CD4(+)CD25(-)FOXP3(-)CD45RA(+) responder T cell proliferation while at the same time enhancing the secretion of IL-6 and IL-17, increasing RORC, and decreasing FOXP3 expression. Neutralization of IL-6 or IL-17 abrogated Pam3Cys-mediated reduction of Treg suppressive function. We also found that, in agreement with recent observations in mouse T cells, TLR2 stimulation can promote Th17 differentiation of human T helper precursors. We conclude that TLR2 stimulation, in combination with TCR activation and costimulation, promotes the differentiation of distinct subsets of human naive and memory/effector Tregs into a Th17-like phenotype and their expansion. Such TLR-induced mechanism of regulation of Treg function could enhance microbial clearance and increase the risk of autoimmune reactions.
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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 | 0.000 | 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) | 0.000 | 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".