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Background Canonical studies indicate that cytochrome P450 2E1 ( CYP 2E1) plays a critical role in the metabolism of xenobiotics and ultimately participates in tissue damage. CYP 2E1 upregulates in the pathophysiological development of multiple diseases; however, the mechanism of CYP 2E1 upregulation, particularly in heart disease, remains elusive. Methods and Results We found that the level of CYP 2E1 increased in heart tissues from patients with hypertrophic cardiomyopathy; multiple mouse models of heart diseases, including dilated cardiomyopathy, hypertrophic cardiomyopathy, and myocardial ischemia; and HL -1 myocytes under stress. We determined that Myc bound to the CYP 2E1 promoter and activated its transcription by bioinformatics analysis, luciferase activity, and chromatin immunoprecipitation, and Myc expression was modulated by extracellular signal-regulated kinases 1/2 and phosphatidylinositol 3 kinase/protein kinase B pathways under stress or injury in myocardium by signal transduction analysis. In addition, the level of oxidative stress and apoptosis gradually worsened with age in transgenic mice overexpressing CYP 2E1, which was significantly inhibited with CYP 2E1 knockdown. Conclusions Our results demonstrated that CYP 2E1 is likely a sensor of diverse pathophysiological factors and states in the myocardium. Upregulated CYP 2E1 has multiple pathophysiological roles in the heart, including increased oxidative stress and apoptosis as well as energy supply to meet the energy demand of the heart in certain disease states. Our discovery thus provides a basis for a therapeutic strategy for heart diseases targeting Myc and CYP 2E1.
Pubmed ID: 30563421
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THIS 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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