Epigenomic regulation of metabolism in muscle by circadian clock and environment
Epigenomic regulation of metabolism in muscle by circadian clock and environment
批准号:
8878449
负责人:
Zheng Sun
金额:
$24.9万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-24 至 2017-08-31
关键词:
AddressAffectAmino AcidsAnimal ModelAnimalsBackBindingBiochemistryBioinformaticsBranched-Chain Amino AcidsBurn injuryCarbohydratesCatabolismChromatinCircadian RhythmsCitric Acid CycleClinicalClinical TreatmentClinical TrialsCollaborationsCore FacilityCoupledDarknessDataData SetDevelopmentDiabetes MellitusDietDietary FactorsDiseaseEconomic BurdenEnergy MetabolismEnvironmentEuglycemic ClampingExerciseFatty acid glycerol estersFunding OpportunitiesFutureGene ExpressionGene Expression AlterationGene Expression ProfileGene TargetingGenesGeneticGenetic TranscriptionGenomeGlucoseGlucose ClampGlucose IntoleranceGlycogenGlycolysisGoalsHealthHepaticHistone Deacetylase InhibitorHistonesHomeostasisInflammatoryInsulin ResistanceIsotopesKetone BodiesKetonesKnockout MiceKnowledgeLaboratoriesLeadLightLipidsLiverMalignant NeoplasmsMediatingMentorsMetabolicMetabolismMethodsMitochondriaModelingModificationMolecularMonitorMusMuscleMuscle CellsNon-Insulin-Dependent Diabetes MellitusNuclear ReceptorsObesityOutputOxygen ConsumptionPennsylvaniaPerformancePhasePhysiologyPlayPurine NucleotidesRecruitment ActivityRegulationResearchRoleRunningSignal TransductionSkeletal MuscleSocietiesSourceTestingThermogenesisTimeTissuesUniversitiescarbohydrate metabolismcareercircadian pacemakerdata miningepigenomeepigenomicsfeedingflexibilitygene environment interactiongenome-wideglucose toleranceglucose uptakehistone deacetylase 3improvedinsulin sensitivitylipid metabolismmetabolomicsmitochondrial dysfunctionmouse modelnovelpandemic diseasepreferenceresearch studyrespiratoryresponsesmall molecule
中文摘要
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英文摘要
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.
期刊论文(0)
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科研奖励(0)
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海外基金