Pparα and fatty acid oxidation coordinate hepatic transcriptional architecture
Cavagnini, K. S.; Wolfgang, M. J.
Show abstract
Fasting requires tight coordination between the metabolism and transcriptional output of hepatocytes to maintain systemic glucose and lipid homeostasis. Genetically-defined deficits in hepatic fatty acid oxidation result in dramatic fasting-induced hepatocyte lipid accumulation and induction of genes for oxidative metabolism, thereby providing a mouse model to interrogate the mechanisms by which the liver senses and transcriptionally responds to fluctuations in lipid levels. While fatty acid oxidation is required for a rise in acetyl-CoA and subsequent lysine acetylation following a fast, changes in histone acetylation (total, H3K9ac, and H3K27ac) associated with transcription do not require fatty acid oxidation. Instead, excess fatty acids prompt induction of lipid catabolic genes largely via ligand-activated Ppar. We observe that active enhancers in fasting mice are enriched for Ppar binding motifs, and that inhibition of hepatic fatty acid oxidation results in elevated enhancer priming and acetylation proximal to Ppar binding sites within regulatory elements largely associated with genes in lipid metabolism. Also, a greater number of Ppar-associated H3K27ac signal changes occur at active enhancers compared to promoters, suggesting a genomic mechanism for Ppar to tune target gene expression levels. Overall, these data demonstrate the requirement for Ppar activation in maintaining transcriptionally permissive hepatic genomic architecture particularly when fatty acid oxidation is limiting. HIGHLIGHTSO_LIFasting-induced transcription and histone acetylation are largely independent of acetyl-CoA concentration. C_LIO_LIDeficits in fatty acid oxidation prompt epigenetic changes and Ppar-sensitive transcription. C_LIO_LIFasting prompts enhancer priming and acetylation proximal to Ppar binding sites independent of Ppar. C_LIO_LIPatterns of Ppar target genes can be distinguished by epigenetic marks at promoters and enhancers. C_LI
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Vitamin B2 enables peroxisome proliferator-activated receptor α regulation of fasting glucose availability 96%
- Control of brown adipose tissue adaptation to nutrient stress by the activin receptor ALK7 95%
- Intermittent fasting induces rapid hepatocyte proliferation to restore the hepatostat in the mouse liver. 95%
Similar papers in this journal
- Sperm Histone H3 Lysine 4 tri-methylation serves as a metabolic sensor of paternal obesity and is associated with the inheritance of metabolic dysfunction 96%
- Loss of Carnitine Palmitoyltransferase 1a Reduces Docosahexaenoic Acid-Containing Phospholipids and Drives Sexually Dimorphic Liver Disease in Mice 95%
- Nipsnap1- A Regulatory Factor Required for Long-Term Maintenance of Non-Shivering Thermogenesis 95%
Similar papers in this journal
- Ketogenesis Impact on Liver Metabolism Revealed by Proteomics of Lysine β-hydroxybutyrylation 96%
- ADH5-mediated NO Bioactivity Maintains Metabolic Homeostasis in Brown Adipose Tissue 95%
- Hepatocyte Membrane Potential Regulates Serum Insulin and Insulin Sensitivity by Altering Hepatic GABA Release 94%
Similar papers in this journal
- Methyl-Metabolite Depletion Elicits Adaptive Responses to Support Heterochromatin Stability and Epigenetic Persistence 94%
- Structural and systems characterization of phosphorylation on metabolic enzymes identifies sex-specific metabolic reprogramming in obesity 92%
- Increased demand for NAD+ relative to ATP drives aerobic glycolysis 92%
Similar papers in this journal
- Integrated genomic analysis of AgRP neurons reveals that IRF3 regulates leptin's hunger-suppressing effects 95%
- X chromosome dosage drives statin-induced dysglycemia and mitochondrial dysfunction 95%
- A sexually dimorphic hepatic cycle of periportal VLDL generation and subsequent pericentral VLDLR-mediated lipoprotein re-uptake 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.