TIF1β/KAP-1 Is a Coactivator of the Orphan Nuclear Receptor NGFI-B/Nur77
Bibliographic record
Abstract
In efforts to define mechanisms of transcriptional activation by the orphan nuclear receptor NGFI-B (Nur77), we identified TIF1beta by mass spectrometry within a nuclear protein complex containing NGFI-B. TIF1beta, also known as KAP-1 (KRAB domain-associated protein) or KRIP-1, acts as a transcriptional corepressor for many transcription factors, in particular for the Krüppel-associated box domain-containing zinc finger transcription factors. TIF1beta is also an intrinsic component of two chromatin remodeling and histone deacetylase complexes, the N-CoR1 and nucleosome remodeling and deacetylation complexes. In contrast to these activities, we report that TIF1beta is a coactivator of NGFI-B and that it is as potent as the SRC coactivators in this context. Using pull-down assays and immunoprecipitation, we showed that TIF1beta interacts directly with NGFI-B and with other Nur family members. NGFI-B is an important mediator of hypothalamic corticotropin-releasing hormone (CRH) activation of proopiomelanocortin (POMC) transcription, and TIF1beta enhances transcription mediated through the NGFI-B target, the Nur response element (NurRE). The NurRE binds Nur factor dimers and is responsive to signaling pathways. In keeping with the role of NGFI-B as mediator of CRH signaling, we found that TIF1beta is recruited to the POMC promoter following CRH stimulation and that TIF1beta potentiates CRH and protein kinase A signaling through the NurRE; it acts synergistically with the SRC2 coactivator. However, the actions of TIF1beta and SRC2 were mapped to different NGFI-B AF-1 subdomains. Taken together, these results indicate that TIF1beta is an important coactivator of NGFI-B-dependent transcription.
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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) | 0.001 | 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) | 0.002 | 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".