Retinoic acid promotes myogenesis in myoblasts by antagonizing transforming growth factor-beta signaling via C/EBPβ
Bibliographic record
Abstract
BACKGROUND: The effects of transforming growth factor-beta (TGFβ) are mediated by the transcription factors Smad2 and Smad3. During adult skeletal myogenesis, TGFβ signaling inhibits the differentiation of myoblasts, and this can be reversed by treatment with retinoic acid (RA). In mesenchymal stem cells and preadipocytes, RA treatment can function in a non-classical manner by stimulating the expression of Smad3. Smad3 can bind to and prevent the bzip transcription factor CCAAT/enhancer-binding protein beta (C/EBPβ) from binding DNA response elements in target promoters, thereby affecting cell differentiation. In skeletal muscle, C/EBPβ is highly expressed in satellite cells and myoblasts and is downregulated during differentiation. Persistent expression of C/EBPβ in myoblasts inhibits their differentiation. METHODS: Using both C2C12 myoblasts and primary myoblasts, we examined the regulation of C/EBPβ expression and activity following treatment with TGFβ and RA. RESULTS: We demonstrate that treatment with RA upregulates Smad3, but not Smad2 expression in myoblasts, and can partially rescue the block of differentiation induced by TGFβ. RA treatment reduces C/EBPβ occupancy of the Pax7 and Smad2 promoters and decreased their expression. RA also inhibits the TGFβ-mediated phosphorylation of Smad2, which may also contribute to its pro-myogenic activities. TGFβ treatment of C2C12 myoblasts stimulates C/EBPβ expression, which in turn can stimulate Pax7 and Smad2 expression, and inhibits myogenesis. Loss of C/EBPβ expression in myoblasts partially restores differentiation in the presence of TGFβ. CONCLUSIONS: TGFβ acts, at least in part, to inhibit myogenesis by upregulating the expression of C/EBPβ, as treatment with RA or loss of C/EBPβ can partially rescue differentiation in TGFβ-treated cells. This work identifies a pro-myogenic role for Smad3, through the inhibition of C/EBPβ's actions in myoblasts, and reveals mechanisms of crosstalk between RA and TGFβ signaling pathways.
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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 | 0.001 |
| 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".