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Contribution of beta-arrestin-dependent receptor s.. (CB1R arrestin)
Contribution of beta-arrestin-dependent receptor signaling to the physiological regulation of the endocannabinoid system
(CB1R arrestin)
Date du début: 1 mai 2011,
Date de fin: 28 févr. 2015
PROJET
TERMINÉ
The endocannabinoid system is composed of endocannabinoids, such as anandamide and 2-arachidonoylglycerol (2-AG), their metabolizing enzymes and cannabinoid receptors. To date, two cannabinoid receptors have been identified by molecular cloning, the CB1 and CB2 receptors. The endocannabinoid system has been implicated in a number of physiological functions, and pharmacological manipulation of this system is a promising therapeutic target in a large number of different diseases and conditions, including mood and movement disorders, obesity, neuropathic pain and cancer, etc. In neurons, release of endocannabinoids can be initiated by calcium signal or by stimulation of G-protein-coupled receptors (GPCRs). Anandamide production may be regulated by a number of lipid modulating enzymes, whereas 2-AG is produced by diacylglycerol-lipases (DAGLs). Stimulation of AT1 angiotensin II receptor and other Gq-coupled-receptors leads to DAGL dependent production of endocannabinoids, but the exact mechanism of this response has not been elucidated. The mechanism of action of GPCRs involves both G-protein-dependent and -independent pathways. G-protein-independent pathways are mediated by beta-arrestin-dependent scaffolding and regulation of signaling complexes. Although the role of these proteins during AT1R signaling is well documented, their function in the G-protein independent signaling of CB1R is not known. The aim of the present project is to elucidate the role of beta-arrestin mediated signaling in the regulation of endocannabinoid production, and to elucidate the role of G-protein-independent signaling in CB1R function. The proposed project includes in vitro studies using molecular biology techniques and in vivo experiments using genetically altered mouse models to elucidate these questions.
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