Modulation of Myocardin Function by the Ubiquitin E3 Ligase UBR5
Bibliographic record
Abstract
Fully differentiated mature smooth muscle cells (SMCs) are characterized by the presence of a unique repertoire of smooth muscle-specific proteins. Although previous studies have shown myocardin to be a critical transcription factor for stimulating expression of smooth muscle-specific genes, the mechanisms regulating myocardin activity are still poorly understood. We used a yeast two-hybrid screen with myocardin as bait to search for factors that may regulate the transcriptional activity of the myocardin. From this screen we identified a HECT domain-containing protein UBR5 (ubiquitin protein ligase E3 component n-recognin 5) as a myocardin-binding protein. Previous studies have shown that HECT domain-containing proteins are ubiquitin E3 ligases that play an important role in protein degradation. UBR5 has, however, also been shown to regulate transcription independent of its E3 ligase activity. In the current study we demonstrated that UBR5 localized in the nuclei of SMCs and forms a complex with myocardin in vivo and in vitro. We also show that UBR5 specifically enhanced trans-activation of smooth muscle-specific promoters by the myocardin family of proteins. In addition, UBR5 significantly augmented the ability of myocardin to induce expression of endogenous SMC marker genes independent on its E3 ligase function. Conversely, depletion of endogenous UBR5 by small interfering RNA in fibroblast cells attenuated myocardin-induced smooth muscle-specific gene expression, and UBR5 knockdown in SMCs resulted in down-regulation of smooth muscle-specific genes. Furthermore, we found that UBR5 can attenuate myocardin protein degradation resulting in increased myocardin protein expression without affecting myocardin mRNA expression. The effects of UBR5 on myocardin requires only the HECT and UBR1 domains of UBR5. This study reveals an unexpected role for the ubiquitin E3 ligase UBR5 as an activator of smooth muscle differentiation through its ability to stabilize myocardin protein.
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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".