Distinct Structural Requirements of GATA-3 for the Regulation of Thymocyte and Th2 Cell Differentiation
Bibliographic record
Abstract
GATA-3, the only T cell-specific member of the GATA family of transcription factors, is essential for the intrathymic development of CD4+ T cells and for the differentiation of Th2 cells. However, whether distinct biochemical features, unique to GATA-3 compared with other GATA family members, are required to drive T cell transcriptional programs or whether the T cell-specific functions of GATA-3 can simply be ascribed to its expression pattern is unclear. Nor do we understand the protein structural requirements for each individual function of GATA-3. In this study, we report that a heterologous GATA factor, GATA-4, was competent in supporting the development of CD4+ T cells but could not fully compensate for GATA-3 in regulating the expression of Th cytokines. Specifically, GATA-3 was more potent than GATA-4 in driving the production of IL-13 due to a mechanism independent of DNA binding or chromatin remodeling of the IL-13 locus. The difference was mapped to a partially conserved region C-terminal to the second zinc finger. Converting a single proline residue located in this region of GATA-4 to its counterpart, a methionine of GATA-3, was sufficient to enhance the IL-13-promoting function of GATA-4 but had no effect on other cytokines. Taken together, our data demonstrate that the unique function of GATA-3 is conferred by both its cell type-specific expression and distinct protein structure.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".