Dietary methionine restriction (MR) produces a highly integrated series of biochemical and physiological responses that reduce adiposity, improve biomarkers of metabolic health and enhance insulin sensitivity. Our data make a compelling case that dietary MR acts through both centrally-mediated effects on energy balance, and direct effects on peripheral tissues that remodel white adipose tissue, activate thermogenesis in brown adipose tissue, and enhance insulin sensitivity. We hypothesize that sensing of dietary MR is coupled to these responses through hepatic sensing of reduced methionine through a glutathione-dependent mechanism that activates CREBH and the eIF2 kinase, PERK. The activation of CREBH and PERK results in activation eIF2?- and NRF2-dependent transcriptional programs that increase hepatic expression and release of FGF21. We hypothesize that the increase in FGF21 acts through direct and centrally-mediated mechanisms to activate thermogenesis, increase energy expenditure, reduce fat deposition, and enhance overall insulin sensitivity. We will use a combination of in vivo metabolic phenotyping and ex vivo biochemical analysis with loss of function animal models to examine the role of essential amino acid sensing in the respective responses to dietary MR. The goal of this work is to identify the nutrient sensing and signaling systems which detect the restriction of methionine and translate this dietary modification into a highly integrated and beneficial set of physiological responses.
Obesity and metabolic disease represent a growing health problem in the world and predispose affected individuals to developing more serious diseases including diabetes, heart disease, and stroke. Dietary methionine restriction produces a highly integrated series of biochemical and physiological responses that reduce adiposity, improve biomarkers of metabolic health and enhance insulin sensitivity. The pre-clinical studies proposed herein represent proof of concept testing and discovery to facilitate the development of diet-based approaches that will translate into effective treatments for metabolic disease.
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