Krüppel-like factor 6 (KLF6) promotes cell proliferation in skeletal myoblasts in response to TGFβ/Smad3 signaling
Bibliographic record
Abstract
BACKGROUND: Krüppel-like factor 6 (KLF6) has been recently identified as a MEF2D target gene involved in neuronal cell survival. In addition, KLF6 and TGFβ have been shown to regulate each other's expression in non-myogenic cell types. Since MEF2D and TGFβ also fulfill crucial roles in skeletal myogenesis, we wanted to identify whether KLF6 functions in a myogenic context. METHODS: KLF6 protein expression levels and promoter activity were analyzed using standard cellular and molecular techniques in cell culture. RESULTS: We found that KLF6 and MEF2D are co-localized in the nuclei of mononucleated but not multinucleated myogenic cells and, that the MEF2 cis element is a key component of the KLF6 promoter region. In addition, TGFβ potently enhanced KLF6 protein levels and this effect was repressed by pharmacological inhibition of Smad3. Interestingly, pharmacological inhibition of MEK/ERK (1/2) signaling resulted in re-activation of the differentiation program in myoblasts treated with TGFβ, which is ordinarily repressed by TGFβ treatment. Conversely, MEK/ERK (1/2) inhibition had no effect on TGFβ-induced KLF6 expression whereas Smad3 inhibition negated this effect, together supporting the existence of two separable arms of TGFβ signaling in myogenic cells. Loss of function analysis using siRNA-mediated KLF6 depletion resulted in enhanced myogenic differentiation whereas TGFβ stimulation of myoblast proliferation was reduced in KLF6 depleted cells. CONCLUSIONS: Collectively these data implicate KLF6 in myoblast proliferation and survival in response to TGFβ with consequences for our understanding of muscle development and a variety of muscle pathologies.
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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".