Context-dependent switch in chemo/mechanotransduction via multilevel crosstalk among cytoskeleton-regulated MRTF and TAZ and TGFβ-regulated Smad3
Bibliographic record
Abstract
Myocardin-related transcription factor (MRTF) and TAZ are major mechanosensitive transcriptional co-activators that link cytoskeleton organization to gene expression. Despite many similarities in their regulation, their physical and/or functional interactions are unknown. Here we show that MRTF and TAZ associate partly through a WW domain-dependent mechanism, and exhibit multilevel crosstalk affecting each other's expression, transport and transcriptional activity. Specifically, MRTF is essential for TAZ expression; TAZ and MRTF inhibit each other's cytosolic mobility and stimulus-induced nuclear accumulation; they antagonize each other's stimulatory effect on the α-smooth muscle actin (SMA) promoter, which harbours nearby cis-elements for both, but synergize on isolated TEAD-elements. Importantly, TAZ confers Smad3 sensitivity to the SMA promoter. Thus, TAZ is a context-dependent switch during mechanical versus mechano/chemical signalling, which inhibits stretch-induced but is indispensable for stretch+TGFβ-induced SMA expression. Crosstalk between these cytoskeleton-regulated factors seems critical for fine-tuning mechanical and mechanochemical transcriptional programmes underlying myofibroblast transition, wound healing and fibrogenesis.
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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".