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Epigenomic regulation of metabolism in muscle by circadian clock and environment

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
批准号:
8878449
负责人:
Zheng Sun
金额:
$24.9万
依托单位:
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

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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.
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