The parasite cytokine mimic <i>Hp</i>‐TGM potently replicates the regulatory effects of TGF‐β on murine CD4<sup>+</sup> T cells
Bibliographic record
Abstract
Abstract Transforming growth factor‐beta (TGF‐β) family proteins mediate many vital biological functions in growth, development and regulation of the immune system. TGF‐β itself controls immune homeostasis and inflammation, including conversion of naïve CD4 + T cells into Foxp3 + regulatory T cells (Tregs) in the presence of interleukin‐2 and T‐cell receptor ligands. The helminth parasite Heligmosomoides polygyrus exploits this pathway through a structurally novel TGF‐β mimic ( Hp ‐TGM), which binds to mammalian TGF‐β receptors and induces Tregs. Here, we performed detailed comparisons of Hp ‐TGM with mammalian TGF‐β. Compared with TGF‐β, Hp‐ TGM induced greater numbers of Foxp3 + Tregs (iTregs), with more intense Foxp3 expression. Both ligands upregulated Treg functional markers CD73, CD103 and programmed death‐ligand 1, but Hp‐ TGM induced significantly higher CD39 expression than did TGF‐β. Interestingly, in contrast to canonical TGF‐β signaling through Smad2/3, Hp‐ TGM stimulation was slower and more sustained. Gene expression profiles induced by TGF‐β and Hp‐ TGM were remarkably similar, and both types of iTregs suppressed T‐cell responses in vitro and experimental autoimmune encephalomyelitis‐driven inflammation in vivo . In vitro, both types of iTregs were equally stable under inflammatory conditions, but Hp ‐TGM‐induced iTregs were more stable in vivo during dextran sodium sulfate‐induced colitis, with greater retention of Foxp3 expression and lower conversion to a ROR‐γt + phenotype. Altogether, results from this study suggest that the parasite cytokine mimic, Hp‐ TGM, may deliver a qualitatively different signal to CD4 + T cells with downstream consequences for the long‐term stability of iTregs. These data highlight the potential of Hp‐ TGM as a new modulator of T‐cell responses in vitro and in vivo .
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".