Epigenetic licensing of Th17 and Treg cell differentiation (P1197)
Bibliographic record
Abstract
Abstract Naïve CD4+ T helper (Th) cells acquire a range of fates depending on the cytokine milieu and anatomical location. For example, IL-17 producing Th17 and Foxp3+ regulatory (Treg) cells are dependent upon TGFβ1 and are critical for intestinal homeostasis. G9a is a histone lysine methyltransferase with di-methyl activity towards histone H3 lysine 9. H3K9me2 is a highly conserved histone modification and is commonly linked to transcriptional repression. In this study we examine the role of G9a in the control of Th17 and Treg cell differentiation. Using chromatin immunoprecipitation (ChIP) we found that there is a concomitant loss H3K9me2 and increase in H3K9Ac (an activating histone modification) at lineage specific genes of WT Th17 and Treg cells compared to naive. Meanwhile, naïve G9a-/- T cells have low levels H3K9me2 that results in enhanced sensitivity to TGFβ1 and an increase in the differentiation of both Th17 and Treg cells in vitro. Using the T cell transfer colitis model, we found that transfer of G9a-deficient T cells fails to cause the weight loss and colonic inflammation typical of the model. Furthermore, T effector-cell production of IFNγ was significantly reduced and IL-17 was enhanced when G9a-/- T cells were transferred. In addition, compared to WT controls, a higher proportion of G9a-deficient T cells express Foxp3. We conclude that G9a-dependent H3K9me2 is a homeostatic epigenetic checkpoint that controls the magnitude of Th17 and Treg cell responses.
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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) | 0.006 | 0.002 |
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".