Interplay between ChREBP and SREBP-1c coordinates postprandial glycolysis and lipogenesis in livers of mice.
Albert G LindenShili LiHwa Y ChoiFei FangMasashi FukasawaKosaku UyedaRobert E HammerJay D HortonLuke J EngelkingGuosheng LiangPublished in: Journal of lipid research (2018)
Lipogenesis in liver is highest in the postprandial state; insulin activates SREBP-1c, which transcriptionally activates genes involved in FA synthesis, whereas glucose activates carbohydrate-responsive element-binding protein (ChREBP), which activates both glycolysis and FA synthesis. Whether SREBP-1c and ChREBP act independently of one another is unknown. Here, we characterized mice with liver-specific deletion of ChREBP (L-Chrebp-/- mice). Hepatic ChREBP deficiency resulted in reduced mRNA levels of glycolytic and lipogenic enzymes, particularly in response to sucrose refeeding following fasting, a dietary regimen that elicits maximal lipogenesis. mRNA and protein levels of SREBP-1c, a master transcriptional regulator of lipogenesis, were also reduced in L-Chrebp-/- livers. Adeno-associated virus-mediated restoration of nuclear SREBP-1c in L-Chrebp-/- mice normalized expression of a subset of lipogenic genes, while not affecting glycolytic genes. Conversely, ChREBP overexpression alone failed to support expression of lipogenic genes in the livers of mice lacking active SREBPs as a result of Scap deficiency. Together, these data show that SREBP-1c and ChREBP are both required for coordinated induction of glycolytic and lipogenic mRNAs. Whereas SREBP-1c mediates insulin's induction of lipogenic genes, ChREBP mediates glucose's induction of both glycolytic and lipogenic genes. These overlapping, but distinct, actions ensure that the liver synthesizes FAs only when insulin and carbohydrates are both present.
Keyphrases
- high fat diet induced
- binding protein
- genome wide
- insulin resistance
- type diabetes
- blood glucose
- genome wide identification
- poor prognosis
- bioinformatics analysis
- glycemic control
- adipose tissue
- genome wide analysis
- gene expression
- cell proliferation
- wild type
- machine learning
- oxidative stress
- small molecule
- long non coding rna
- cancer therapy
- skeletal muscle
- deep learning
- heat stress