β-catenin interacts with the TAZ1 and TAZ2 domains of CBP/p300 to activate gene transcription
Bibliographic record
Abstract
Abstract The transcriptional co-regulator β-catenin is a critical effector of the canonical Wnt-signalling pathway, which plays a crucial role in regulating cell fate and maintaining tissue homeostasis. Deregulation of the Wnt/β-catenin pathway is characteristic in the development of major types of cancer, where accumulation of β-catenin promotes cancer cell proliferation and renewal. β-catenin gene expression is facilitated through recruitment of co-activators such as histone acetyltransferases CBP/p300; however, the mechanism of their interaction is not fully understood. Here we investigate the interaction between the C-terminal transactivation domain of β-catenin and CBP/p300. Using a combination of pulldown assays, isothermal titration calorimetry, and nuclear resonance spectroscopy we determine the disordered C-terminal region of β-catenin binds promiscuously to the TAZ1 and TAZ2 domains of CBP/p300. We then map the interaction site of the C-terminal β-catenin transactivation domain onto TAZ1 and TAZ2 using chemical-shift perturbation studies. Luciferase-based gene reporter assays indicate Asp750-Leu781 is critical to β-catenin gene activation, and mutagenesis revealed that acidic and hydrophobic residues within this region are necessary to maintain TAZ1 binding. These results provide a mechanistic understanding of Wnt/β-catenin gene regulation that underlies cell development and provide a framework to develop methods to block β-catenin dependent signalling in the future.
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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".