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The increase in protein activity and upregulation of G-protein coupled receptor kinase 2 (GRK2) is a hallmark of cardiac stress and heart failure. Inhibition of GRK2 improved cardiac function and survival and diminished cardiac remodeling in various animal heart failure models. The aim of the present study was to investigate the effects of GRK2 on cardiac hypertrophy and dissect potential molecular mechanisms. In mice we observed increased GRK2 mRNA and protein levels following transverse aortic constriction (TAC). Conditional GRK2 knockout mice showed attenuated hypertrophic response with preserved ventricular geometry 6 weeks after TAC operation compared to wild-type animals. In isolated neonatal rat ventricular cardiac myocytes stimulation with angiotensin II and phenylephrine enhanced GRK2 expression leading to enhanced signaling via protein kinase B (PKB or Akt), consecutively inhibiting glycogen synthase kinase 3 beta (GSK3β), such promoting nuclear accumulation and activation of nuclear factor of activated T-cells (NFAT). Cardiac myocyte hypertrophy induced by in vitro GRK2 overexpression increased the cytosolic interaction of GRK2 and phosphoinositide 3-kinase γ (PI3Kγ). Moreover, inhibition of PI3Kγ as well as GRK2 knock down prevented Akt activation resulting in halted NFAT activity and reduced cardiac myocyte hypertrophy. Our data show that enhanced GRK2 expression triggers cardiac hypertrophy by GRK2-PI3Kγ mediated Akt phosphorylation and subsequent inactivation of GSK3β, resulting in enhanced NFAT activity.
Pubmed ID: 28759639
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View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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