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Epigenomic regulation of metabolism in muscle by circadian clock and environment

生物钟和环境对肌肉代谢的表观基因组调节

基本信息

批准号：
8878449
负责人：
Zheng Sun
金额：
$ 24.9万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-24 至 2017-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8878449
关键词：
Address Affect Amino Acids Animal Model Animals Back Binding Biochemistry Bioinformatics Branched-Chain Amino Acids Burn injury Carbohydrates Catabolism Chromatin Circadian Rhythms Citric Acid Cycle Clinical Clinical Treatment Clinical Trials Collaborations Core Facility Coupled Darkness Data Data Set Development Diabetes Mellitus Diet Dietary Factors Disease Economic Burden Energy Metabolism Environment Euglycemic Clamping Exercise Fatty acid glycerol esters Funding Opportunities Future Gene Expression Gene Expression Alteration Gene Expression Profile Gene Targeting Genes Genetic Genetic Transcription Genome Glucose Glucose Clamp Glucose Intolerance Glycogen Glycolysis Goals Health Hepatic Histone Deacetylase Inhibitor Histones Homeostasis Inflammatory Insulin Resistance Isotopes Ketone Bodies Ketones Knockout Mice Knowledge Laboratories Lead Light Lipids Liver Malignant Neoplasms Mediating Mentors Metabolic Metabolism Methods Mitochondria Modeling Modification Molecular Monitor Mus Muscle Muscle Cells Non-Insulin-Dependent Diabetes Mellitus Nuclear Receptors Obesity Output Oxygen Consumption Pennsylvania Performance Phase Physiology Play Purine Nucleotides Recruitment Activity Regulation Research Role Running Signal Transduction Skeletal Muscle Societies Source Testing Thermogenesis Time Tissues Universities carbohydrate metabolism career circadian pacemaker data mining epigenome epigenomics feeding flexibility gene environment interaction genome-wide glucose tolerance glucose uptake histone deacetylase 3 improved insulin sensitivity lipid metabolism metabolomics mitochondrial dysfunction mouse model novel pandemic disease preference research study respiratory response small molecule

项目摘要

Project Summary The current research is to study how epigenomic modifier histone deacetylase 3 (HDAC3) regulates carbohydrates metabolism and insulin sensitivity in skeletal muscle in response to either the internal circadian clock or the external dietary factor. I have developed a novel mouse model with HDAC3 specifically depleted in skeletal muscle, and have found that the mice display disrupted metabolic circadian gene expression and exacerbated glucose intolerance that is induced by high fat diet (HFD). During the mentored phase, I will gain new expertise in genomewide epigenomic approaches that are well established in my mentor’s laboratory. I will also gain additional knowledge in muscle physiology, metabolic flux analysis, and metabolomics methods through collaboration with other laboratories and core facilities at University of Pennsylvania. The research that I propose to continue in the independent phase is to study HDAC3 in exercise endurance, fuel selection and efficiency, as well as lipid and amino acid metabolism in skeletal muscle. We have found that mice without muscular HDAC3 have surprisingly improved exercise endurance associated with a switch in fuel preference from carbohydrates towards lipid. I will characterize mitochondrial function and trace metabolic fluxes through lipid, ketone bodies, and amino acids catabolism, including the anaplerotic purine nucleotide cycle, in exercising animals as well as in isolated primary myocytes, where knockdown experiments will test the requirement of specific HDAC3 target genes for the observed fuel selection and enhanced fuel efficiency. My future career goal after independence is to decipher the epigenomic mechanism that underlies hormetic response to physical exercise in skeletal muscle. Exercise is beneficial to many aspects of health, especially in the context of obesity and diabetes. My general hypothesis is that epigenomic mechanisms underlie exercise induced beneficial metabolic remodeling. I will comprehensively characterize exerciseinduced changes in skeletal muscle transcriptome and epigenome using genomewide methods and metabolomics approaches. This is the first endeavor ever, as far as I know, to analyze exerciseinduced epigenomic changes in a genomewide scale. This unbiased method will produce comprehensive datasets, from which data mining and motif analysis will generate new hypotheses regarding novel transcription networks that respond to exercise. Biochemistry methods and metabolic flux analysis will then be used to validate these hypotheses, followed by development of genetic animal models and physiology studies. Together, these approaches will generate testable hypothesis backed up by preliminary data, which is essential for successful competition for future funding opportunities.

项目总结