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Regulation of adaptive behaviour during fasting by hypothalamic Foxa2.

Nature | Dec 3, 2009

http://www.ncbi.nlm.nih.gov/pubmed/19956259

The lateral hypothalamic area is considered the classic 'feeding centre', regulating food intake, arousal and motivated behaviour through the actions of orexin and melanin-concentrating hormone (MCH). These neuropeptides are inhibited in response to feeding-related signals and are released during fasting. However, the molecular mechanisms that regulate and integrate these signals remain poorly understood. Here we show that the forkhead box transcription factor Foxa2, a downstream target of insulin signalling, regulates the expression of orexin and MCH. During fasting, Foxa2 binds to MCH and orexin promoters and stimulates their expression. In fed and in hyperinsulinemic obese mice, insulin signalling leads to nuclear exclusion of Foxa2 and reduced expression of MCH and orexin. Constitutive activation of Foxa2 in the brain (Nes-Cre/+;Foxa2T156A(flox/flox) genotype) results in increased neuronal MCH and orexin expression and increased food consumption, metabolism and insulin sensitivity. Spontaneous physical activity of these animals in the fed state is significantly increased and is similar to that in fasted mice. Conditional activation of Foxa2 through the T156A mutation expression in the brain of obese mice also resulted in improved glucose homeostasis, decreased fat and increased lean body mass. Our results demonstrate that Foxa2 can act as a metabolic sensor in neurons of the lateral hypothalamic area to integrate metabolic signals, adaptive behaviour and physiological responses.

Pubmed ID: 19956259 RIS Download

Mesh terms: Adaptation, Psychological | Animals | Behavior, Animal | Fasting | Gene Expression Regulation | Hepatocyte Nuclear Factor 3-beta | Hypothalamic Hormones | Hypothalamus | Insulin | Intracellular Signaling Peptides and Proteins | Male | Melanins | Mice | Mice, Inbred C57BL | Mice, Obese | Neuropeptides | Pituitary Hormones | Promoter Regions, Genetic

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Mouse Genome Informatics (Data, Gene Annotation)

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