Insulin-dependent transcriptional control in L6 rat myotubes is associated with modulation of histone acetylation and accumulation of the histone variant H2A.Z in the proximity of the transcriptional start site
Bibliographic record
Abstract
Besides its direct metabolic effects, insulin induces transcriptional alterations in its target tissues. However, whether such changes are accompanied by epigenetic changes on the chromatin template encompassing insulin responsive genes is unclear. Here, mRNA levels of insulin-responsive genes hexokinase 2 (Hk2), insulin receptor substrate (Irs2), and the PI3K subunit p85β (Pik3r2) were compared in control versus insulin-stimulated L6 myotubes. Chromatin immunoprecipitation (ChIP) was performed with antibodies directed to histone H2A, histone variant H2A.Z, acetylated histone H3 on lysines 9/14, and acetylated H2A.Z. Insulin induced a more than 2-fold Hk2 mRNA increase, while Irs2 and Pik3r2 were downregulated. ChIP to H2A and H2A.Z showed higher H2A.Z accumulation around the transcriptional start site (TSS) of these insulin-modulated genes, while H2A.Z accumulation was lower distally to the TSS in the Hk2 promoter. H2A.Z levels and H3K9/14 acetylation correlated on several loci along the Hk2 gene, and H3K9/14 as well as H2A.Z acetylation was enhanced by insulin treatment. On the contrary, reduced H3K9/14 acetylation was observed in insulin-repressed Irs2 and Pik3r2, and recovery of acetylation by treatment with the histone deacetylase inhibitor trichostatin A reverted insulin-induced Irs2 downregulation. The chromatin regions encompassing selected insulin-responsive genes are thus featured by accumulation of H2A.Z around the TSS. H2A.Z accumulation facilitates insulin-dependent modulation of pharmacologically treatable H3K9/14 and H2A.Z acetylations. Indeed, inhibition of histone deacetylases by TSA treatment reverted insulin induced Irs2 gene downregulation. Dysregulated histone acetylation may thus be potentially targeted with histone deacetylase inhibitors.
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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 | 0.001 |
| 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) | 0.002 | 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".