系統(tǒng)生物學II - 先進測量平臺 (2)學習資料

1.AdvancedplatformforSB?HighthroughputAutomaticLowcostHighspeedHighaccuracyBestgainofbioinformationinquantityandqualitywithunitresourceorcost.1Genomesequence：capillaryarrayelectrophoresisGeneexpressionprofiling基因表達譜:

biochip,RTPCRProteinsequence:separation&MSProteinstructure:x-raycrystallization結晶,NMRInteraction:twohybrid雙酵母雜交,TAP,biochipProteinlocalization蛋白質定位:molecularimagingMetabolite：separation&MS,NMR22.Fundamentalinstrumentmethod1、Fluorescence熒光性2、Chromatography色譜分析3、Electrophoresis電泳法4、Biochip生物芯片5、BioMassspectrometry生物質譜分析6、x-raycrystallizationX射線結晶7、NMR核磁共振8、Molecularimaging分子成像3Microdeviceforhighspeed,parallelprocessandanalysisofbiomolecules對生物分子進行快速、并行處理和分析的微型器件。2.4.Biochip42.4.1.Biochipclassificationmicro-array微陣列Microfluidics微流體“Microsystem”“Micro(Miniaturized)TotalAnalysisSystem(TAS)”

“Lab-on-a-Chip”“Biochip”5Comparison

Microarray

Microfluidics

Theory

Biointeraction

Microfluidiccontrol

Nature

Array

Network

Fabrication制造

MEMS

MEMS

Usingtime

Once

Reusable

Application

Biomedicine

Biomedicine,chemistry,environment

Industry

developed

developing

62.4.2Fabrication制造ofgenechipIn-situsynthesisPhotolithgraphicsynthesisMolecularstampMicrodottingDotcontactSprayprintPiezoelectricprint7基因芯片的制作原位合成:光刻合成技術;分子印章技術;壓電打印技術微量點樣:點接觸法;噴墨法2.4.3.Cellchip–multimicroelectrodearray82.4.3.Cellchip–chippatchclamp2.3.4.Tissuechip在基質表面固定大量的、可尋址的微小組織樣本，用于高通量檢測不同組織中DNA、RNA和蛋白質等分子的變化，稱為組織芯片。Fabricationofmicrofluidicchip:Method:

MEMS－MicroelectromechanicalSystemSi硅orglass-basedmethodPolymer聚合物-basedmethod:PDMSSpincoatSU-8Pre-exposurebakingFixmaskandwafertoholderExposurePost-exposurebakeMolddevelop,rinse,dryandclear9PourPDMS10SpincoatPDMSlayerBakePDMS

CutPDMSedgePeeloffPDMSDrillholesChannelCheckWashPlasmatreatmentAttachmentChipbakingPolymer-basedmethod:PMMA11SoftlithographyMicrofluidiccapillaryelectrophoresis微流體毛細管電泳Conventionalcapillaryelectrophoresis常見的122.1、進樣13PinchingPinchfactor:p=Ib/IsDispensefactor:d=Ibw/IsAlarieJ.P.etal.Electrophoresis2001,22,312-317.Electrokineticpinching14Is+Isw+Ib+Ibw=0

Is=IbwIsw=Ibg=Ib/Is(gatingfactor)Electrokineticgating15CZEseparationofflavinMetabolitese.g.16Applications1.DNA:genomics2.Protein:proteomics3.Metabolite:metabolomicsormetabonomics4.Clinicdiagnosis臨床診斷5.Drugscreening藥物篩選6.Singlecellanalysis7.Interactionanalysis交互分析8.Anti-bioterrorism9.Forensicanalysis法醫(yī)鑒定……17QuadrupoleMSTOFMS182.5.Bio-MSMALDI19ESI500600700800900100011001200130014001500160017001800m/z0100%998.2942.7893.2848.6808.3616.2771.5738.0617.21060.5999.61131.11061.81211.81132.51137.51305.01413.71541.91696.3160001700018000m/z0100%16951.420ESI-Q-TOFMS21Bragg

diffractionequation：

DB=BF=dsin

n=2dsin

222.6.X-raycrystallization1H：2.7.NMR1924:Pauliraisedtheidea;1952:NobelPrizetoBloch(Stanford)&Purcell(Harvard)23ApplicationMolecularstructureidentificationMetabolomicsMedicaldiagnosis242.8.MolecularimagingOpticalimaging光學成像3.-Omicmeasurementplatform1.Genomicplatform2.Transcriptomicplatform3.Proteomicplatform4.Metabolomicplatform25GenomicsTranscriptomicsProteomicsMetabolomicsDNARNAProteinMetaboliteOMICS2627GenomeTranscriptomeProteomeMetabolome~30,000genes~100,000transcripts~1,000,000proteinforms?~2000to5,000metabolitesThe‘omic’s28283.1.Genomicplatform3.1.1.DNAsequencing1.Sangersequencing2.Cyclic-arraysequencing3.1.2.SNP(singlenucleotidepolymorphism,SNP)

3.Nanoporesequencing4.Hybridization-basedsequencing29Whatisgenomics?Genomicsis“thestudyoffunctions

andinteractionsofallthegenesin

thegenome,includingtheirinteractionswithenvironmentalfactors.Collins,FrancisandAlanGuttmacherNEJM,Vol.347:1512-1520.Agenomeis“alltheDNAcontained

inanorganismoracell,whichincludes

boththechromosomeswithinthe

nucleusandtheDNAinmitochondria…allourgenestogether.”30Genomics101:AnIntroductionTraditionalPublichealth

GeneticsRarediseasesSinglegenedisorders單基因失調PublichealthactivitiesNewbornscreening新生兒篩查Reproductivehealth生殖健康Geneticservices31ContemporaryGenetics

當代基因組學CommondiseasesMultiplegenes多基因Gene/environmentinteractionsPublichealthactivities/implicationsChronicdiseases慢性病Infectiousdiseases傳染病Environmentalhealth環(huán)境健康學Epidemiology流行病學32GeneticMutationsAllofusmayhaveatleastone

geneticmutation.Someareinherited.遺傳Othersoccurrandomlyorasaresultofenvironmentalfactors,suchasdiet,drugs,andinfections.Mostdiseaseshavemultifactorialcausation(geneticandenvironmental).Geneticvariationsputindividualsatincreasedriskfordevelopingcertaindiseases,buttheydonotmakeitcertainthatthosediseaseswilloccur.Geneticmutationshavebeen

identifiedthatplayarolein:Chronicdiseases慢性病CancerCardiovasculardisease心血管疾病Occupationaldiseases職業(yè)病Bladdercancer膀胱癌InfectiousdiseasesHIV/AIDS33Genesand10U.S.Killers:HeartdiseaseMalignantneoplasms惡性腫瘤Cerebrovasculardiseases腦血管疾病Chroniclower

respiratorydiseases慢性下呼吸道疾病Accidents意外事故

(unintentionalinjuries)Diabetesmellitus糖尿Influenzaandpneumonia流感和肺炎Alzheimer’sdisease阿爾茨海默氏病Nephritis,nephroticsyndrome,andnephrosis(kidneydisease)腎炎、腎病綜合征等Septicemia敗血癥34What’snewingenomics?GenetictestingTodetectmutations檢測突變Fordiseasediagnosisandprognosis預知Forthepredictionofdiseaseriskin

individualsorfamiliesSeveralhundredgenetictestsareinuse.Raregeneticdisorders家族遺傳疾病

(musculardystrophies,cysticfibrosis,Huntington’sdisease)Complexconditions(breast,ovarian,

andcoloncancers)Pharmacogenomics藥物基因組學Thedevelopmentofdrugstailored定做

tospecificsubpopulations亞種群basedongenesPharmacogenomicshasthepotentialto:DecreasesideeffectsofdrugsIncreasedrugeffectivenessMakedrugdevelopmentfasterandlesscostly35What’snewingenomics?(cont.)Recentresearchingenomicsincludes:Learningmoreaboutthegenetic

underpinnings基礎

ofchronicdiseasesDevelopingmousemodelsofhumangenesDevelopinggeneticfingerprinting基因指紋鑒別法

forchildhoodcancerConductingstemcellresearch指導干細胞研究Identifyingtumorsuppressorgenes識別腫瘤抑制基因Policydevelopments政策演變relatedto

genomicsinclude:Activitiesrelatedtoanti-discrimination反歧視andethics倫理學ExpandednewbornscreeningNewfundingforresearchonrarediseases36ThemainaimofgeneticsistounderstandthisrelationshipTalkalittlebitaboutwhereIamcomingfromGenomicMedicine:

Predictive,personalized,andpre-emptive預測、個性化、先發(fā)制人371.SangersequencingPNAS,74(1977)560.Maxim-GilbertMethod38SangerMethodH2OXdNTPddNTP39Smithetal.Nature,321(1986)674.Couplingwithfluorescenttag熒光標記insteadof*PProberetal.Science,238(1987)336.40FrancisCollins

DirectorofHGPatNIHHumanGenomeProject(HGP)CollinsF.,GalasD.Science,262(1993)43.4142GenomicsTimelines43CapillaryElectrophoresis毛細管電泳444546Laserinducedfluorescencedetector激光激發(fā)熒光成像47ABI3700DNASequencerbyDr.Dovichi’sGroupatUA(UW)CapillaryArrayElectrophoresis毛細管陣列電泳48FourKeystonesforSangerSequencingddNTPchainterminationstrategy雙脫氧核苷酸鏈終止2.Fluorescentlabel

熒光標記3.Capillaryelectrophoresisseparation

毛細管電泳分離4.Laserinducedfluorescencedetection

激光激發(fā)熒光成像檢測49ProtocolofSangerSequencing方案1.GenomicDNAisfragmentedwithshotgunstrategy;2.Clonedtoaplasmid質粒vectorandusedtotransformE.coli;3.BacterialcolonyispickedandplasmidDNAisolated;4.Eachcyclesequencingreactiontakesplacewithinamicroliter-scalevolume,generatingaladderofddNTP-terminated,dye-labeledproducts;5.High-resolutionelectrophoreticseparationwithfourchannellaserinducedfluorescencedetection;6.Dataanalysis(bioinformatics):base-callingalignmentofsequencereads

denovoassembly(e.g.,BLASTorBLAT)genomebrowsingandannotationdatamining……50Advantage1.Longread-lengths(1000bp)2.Highrawaccuracy(99.999%)Disadvantage1.Biologicalbias偏離2.Relativehighcost

0.5$/1kb

5M$for1GB(10-foldcoverage)TheSangersequencingissuitableforsmall-scaleprojectsinthekilobase-to-megabaserange.Thisisaconsequenceofitsgreater‘granularity’(thatis,theabilitytoefficientlyoperateateithersmallorlargeproductionscales)relativetothesecondgenerationtechnologies.51Dr.Mathies’groupatU.C.BerkeleyNewdevelopment:MicrofluidicCapillaryArrayElectrophoresis微流體毛細管陣列電泳OneandHalfgenerationDNASequencer522.Cyclic-arraysequencingThesecondgenerationDNAsequencing:sequencing-by-synthesisDefinition定義:Theconceptofcyclic-arraysequencingcanbedefinedasthesequencingofadense稠密arrayofDNAfeaturesbyiterativecycles迭代循環(huán)ofenzymaticmanipulationandimaging-baseddatacollection.GeneralProtocol:1.LibrarypreparationbyrandomfragmentationofDNA;2.invitroligationofcommonadaptorsequences;3.Generationofclonally無性繁殖clustered聚集成群amplicons擴增(insitupolonies,emulsionPCRorbridgePCR);4.Cyclicarraysequencing;5.Dataanalysis.Category:1.454sequencing(RocheAppliedScience,Basel);2.Solexa(Illumina,SanDiego);3.SOLiD(AppliedBiosystems,FosterCity)4.Polonator(Dover,Harvard)5.SingleMoleculeSequencer(Helicos,Cambridge…)531.454sequencingStep1:54Step2:AninvitroconstructedadaptorflankedshotgunlibraryisPCRamplifiedinthecontextofawater-in-oilemulsion.OneofthePCRprimersistetheredtothesurface(5’-attached)ofmicron-scalebeadsthatarealsoincludedinthereaction.Alowtemplateconcentrationresultsinmostbead-containingcompartmentshavingeitherzerooronetemplatemoleculepresent.PCRampliconsarecapturedtothesurfaceofthebead.Afterbreakingtheemulsion,beadsbearingamplificationproductscanbeselectivelyenriched.EachclonallyamplifiedbeadwillbearonitssurfacePCRproductscorrespondingtoamplificationofasinglemoleculefromthetemplatelibrary.55Clonallyamplified

28-

mbeadsgeneratedbyemulsionPCRserveas

sequencing

features,arepre-incubatedwithBacillus

stearothermophilus(Bst)polymeraseandsingle-strandedbindingprotein,andarefurtherrandomlydeposited

toamicrofabricatedarrayofpicoliter-scalewells

(withdimensionssuchthatonlyonebeadwillfitperwell).

Withpyrosequencing,eachcycleconsistsof

theintroductionofasinglenucleotidespecies,

followedbyadditionofsubstrate(luciferin,

adenosine5’-phosphosulphate)todrivelight

productionatwellswherepolymerase-driven

incorporationofthatnucleotidetookplace.

Thisisfollowedbyanapyrasewashtoremove

unincorporatednucleotide.Step3:Strategyforcyclicarraysequencing56PPPPPPPPPOHPPATPATPATP+luciferin+luciferin+luciferinPPPPPP57PPPPPPPPPOHPPATPATPATP+luciferin+luciferin+luciferinPPPPPP581-mer2-mer3-mer4-merBrightnessofflashisproportionaltonumberofnucleotidesaddedFlashbrightnessTCACTTCAAGGGT…Flashistoobright59ATGCReadlength350-400bp200cycles~0.5Gb/run603.Advantage&Disadvantage:

Thekeyadvantageofthe454platformis

read-length.Forexample,the454FLXinstrumentgenerates~400,000

readsperinstrument-runatlengthsof200to300bp.itmaybethemethodofchoiceforcertainapplicationswherelongread-lengthsarecritical(e.g.,denovoassemblyandmetagenomics)

Themajorlimitationofthe454technologyrelatestohomopolymers(thatis,consecutiveinstancesofthesamebase,suchasAAAorGGG).Becausethereisnoterminatingmoietypreventingmultipleconsecutiveincorporationsatagivencycle.Asaconsequence,thedominanterrortypeforthe454platformisinsertion-deletion,ratherthansubstitution.612.Solexa62Step1:GenomicDNALibraryPreparation63Step2:

ClusterGeneration(BridgePCR)hybridizetothelawnofprimersextendedbypolymerases12345Double-strandedmoleculeisdenaturedOriginaltemplateshouldbewashedawayNewlysynthesizedcovalentlyattachedadjacentprimerstoformabridgeHybridizedprimerisextendedbypolymerasesDouble-strandedbridgeisformed6467891011Double-strandedbridgeisdenaturedResult:twocopiessingle-strandedtemplatesadjacentprimerstoformbridgesextendedbypolymerasesmultiplebridgesareformeddsDNAbridgesdenaturedReversestrandscleavedandwashedawayLeavingaclusterwithforwardstrandsonlySequencingprimerishybridizedtoadapter65Step3:SequencingEachsequencingcycleincludesthesimultaneousadditionofamixtureoffourmodifieddeoxynucleotidespecies,eachbearingoneoffourfluorescentlabelsandareversiblyterminatingmoietyatthe3’hydroxylposition.AmodifiedDNApolymerasedrivessynchronousextensionofprimedsequencingfeatures.Thisisfollowedbyimaginginfourchannelsandthencleavageofboththefluorescentlabelsandtheterminatingmoiety.66Automationisimportant!67Nebulizer~400bpIllumina68PPPPPPPPPPSTOPSTOPSTOPSTOPPP69MetzgerM(2009)NatureReviewsGenetics11:31-4670GCTGA…71Flowcell8lanesForpicturetaking:Eachlaneisbrokenupinto100tiles拼貼,eachfluorisimagedseparately–2400picturestakenpercycleCameratimeisthelimitingstep!72PPPPPPPPPPSTOPChemistryproblem1:terminatorisretained保留outofphase73PPPPPPPPPPPSTOPChemistryproblem2:fluor熒光劑isretained74Readlength30–120bp~3–30Gb/runGAIIIllumina>100Gb/runHiSeq90x106reads/lane*102bp/read=9x109bp/lane*16lanes/run=144Gb/run753.Features:Read-lengthsupto36bparecurrentlyroutine.Longerreadsarepossiblebutmayincurahighererrorrate.Read-lengthsarelimitedbymultiplefactors多因素thatcausesignaldecayanddephasing移相,suchasincompletecleavageoffluorescentlabelsorterminatingmoieties.Thedominant顯性的errortypeissubstitution代替,rather

thaninsertionsordeletions(Homopolymers均聚物arecertainlylessof

anissuethan454).Averagerawerrorratesareontheorderof1–1.5%.Higheraccuracybaseswitherrorratesof0.1%orlesscanbeidentifiedthroughqualitymetrics質量度量學associatedwitheachbase-call.763.SOLiDSimilarto454platform,inSOLiDstrategygDNAwasfragmentedbyshotgun,andthenamplified放大withEmulsionPCR.微乳液PCR法77Clonallyamplifiedbeadsareusedtogenerateadisordered,densearrayofsequencingfeatures.Sequencingisperformedwithaligase,ratherthanapolymerase,eachsequencingcycleintroducesapartiallydegeneratepopulationoffluorescentlylabeledoctamers.Thepopulationisstructuredsuchthatthelabelcorrelateswiththeidentityofthecentral2bpintheoctamer(thecorrelationwith2bp,ratherthan1bp,isthebasisoftwobaseencoding).Afterligationandimaginginfourchannels,thelabeledportionoftheoctamer(thatis,‘zzz’)iscleavedviaamodifiedlinkagebetweenbases5and6,leavingafreeendforanothercycleofligation.Severalsuchcycleswilliterativelyinterrogateanevenlyspaced,discontiguoussetofbases.Thesystemisthenreset(bydenaturationoftheextendedprimer),andtheprocessisrepeatedwithadifferentoffset(aprimersetbackfromtheoriginalpositionbyoneorseveralbases)suchthatadifferentsetofdiscontiguousbasesisinterrogatedonthenextround.787980Features:814.SingleMoleculeSequencerThereisnoclonalamplificationsteprequired.Poly-A–tailedtemplatemoleculesarecapturedbyhybridizationtosurface-tetheredpoly-Toligomerstoyieldadisorderedarrayofprimedsinglemoleculesequencingtemplates.TemplatesarelabeledwithCy3,suchthatimagingcanidentifythesubsetofarraycoordinateswhereasequencingreadisexpected.Eachcycleconsistsofthepolymerase-drivenincorporationofasinglespeciesoffluorescentlylabelednucleotideatasubsetoftemplates,followedbyfluorescenceimagingofthefullarrayandchemicalcleavageofthelabel.Helicos82MetzgerM(2009)NatureReviewsGenetics11:31-4683105to140Megabasesperhour~35bpaveragereadlength84(2009)Volume27:847Helicos,28Xcoverage,84Gb752CNVs2.8MSNPs85IonTorrentSingle-moleculesequencing86GuptaPK.(2008)Single-moleculeDNAsequencingtechnologiesforfuturegenomicsresearch.TrendsBiotechnol.26:602-11+-Single-moleculesequencing87GuptaPK.(2008)Single-moleculeDNAsequencingtechnologiesforfuturegenomicsresearch.TrendsBiotechnol.26:602-11+-88GuptaPK.(2008)Single-moleculeDNAsequencingtechnologiesforfuturegenomicsresearch.TrendsBiotechnol.26:602-1189PacificBiosciences

Single-moleculesequencing90ZMW:ahole,tensofnanometersindiameter,fabricatedina100nmmetalfilmdepositedonasilicondioxidesubstrate detectionvolume20zeptoliters(10-21liters).excitationemissionemission91PacBiotechnologybackgrounder:/index.php?q=technology-introduction92WhentheDNApolymeraseencountersthenucleotidecomplementarytothenextbaseinthetemplate,itisincorporatedintothegrowingDNAchain.Duringincorporation,theenzymeholdsthenucleotideintheZMWsdetectionvolumefortensofmilliseconds,ordersofmagnitudelongerthantheaveragediffusingnucleotide.Thesystemdetectsthisasaflashofbrightlightbecausethebackgroundisverylow.ThepolymeraseadvancestothenextbaseandtheprocesscontinuestorepeatPacBiotechnologybackgrounder:/index.php?q=technology-introduction93multiplereadsofthesamemolecule94EidJetal.(2009)MoleculesReal-TimeDNASequencingfromSinglePolymerase

Molecules.Science323,133PMID:1902304495Doesitwork?150bpcirculartemplate~93%rawaccuracy15xcoverage99.3%accuracy96PacBioclaimsthat,by2013,thetechnologywillbeabletogivea‘raw’humangenomesequenceinlessthan3min,andacompletehigh-qualitysequencein15min.GuptaPK.(2008)Single-moleculeDNAsequencingtechnologiesforfuturegenomicsresearch.TrendsBiotechnol.26:602-11~2-5bp/sec97Comparison98IonTorrent99Nature475:348(2011)~100bpreads30Mb/run

100101IonTorrentreadquality102Applicationsofnext-generationsequencing1033.Nanoporesequencing1041054.Hybridization-basedsequencing雜交MicroarrayDNAbiochipIntermsofsequencing,limitationsofmicroarraysincludethefollowing:(i)sequencesthatarerepetitiveorsubjecttocrosshybridizationcannoteasilybeinterrogated被詢問;(ii)itremainsunclearhowdenovosequencingcanbeachievedwithhybridization;(iii)withoutverycarefuldataanalysis,falsepositivesposeanimportantproblem,anditisnotclearhowtoobtaintheequivalentofredundant多余的coveragethatispossiblewithconventional常用的andcyclic-arraysequencing.Ithaditsgreatestimpactinthecontextofgenome-wideassociationstudies,whichrelyonarray-basedinterrogation(thatis,genotypingbyhybridization)ofahighlydefinedsetofdiscontiguousgenomiccoordinates.106SNP1073.2.TranscriptomicplatformNowthatmoreandmoregenomesequencesarebeingcompleted,newquestionsariselikewhatarethefunctionalrolesofdifferentgenesandinwhatcellularprocessesdotheyparticipate.Howaregenesregulatedandhowdogenesandgeneproductsinteract.Howdoesgeneexpressionlevelsdifferinvariouscelltypesandstatesandhowisgeneexpressionchangedbyvariousdiseasesortreatments.AlthoughmRNAisnottheultimateproductofagene,transcriptionisthefirststepingeneregulationandinformationaboutthetranscriptlevelsisneededforunderstandinggeneregulatorynetworks.Thus,thenewchallengeistoidentifyallgenes,theirexpressionpatternsandtheirfunction.

Transcriptomics

orglobalanalysisofgeneexpression,alsocalledgenome-wideexpressionprofiling,isoneofthetoolsthatisusedtogetanunderstandingofgenesandpathwaysinvolvedinbiologicalprocesses.Theideaunderlyingthisapproachiscalled“guiltbyassociation”,whichmeansthatgenesshowingsimilarityinexpressionpatternmaybefunctionallyrelatedandunderthesamegeneticcontrolmechanism.108ESTsequencing

SAGE:SerialanalysisofgeneexpressioncDNAmicroarraysandoligo-microarrays109

TheSAGEmethod

isbasedoncountingsequencetagsof10-15bpfromcDNAlibraries.Thesetagsarelinkedtogetherinachainandclonedintoavectorfromwhichtheyaresequenced.IncontrasttoESTsequencing,SAGEisbestappliedtoorganismswhosegenomicsequencesareknownorthathaveasubstantialcDNAsequencedatabaseinordertoidentifythegenesthataresequenced.Becauseonlyshortpiecesofsequencearesequencedpergene,theinsertswiththemultiplesequencetagshavetobesequencedseveraltimestoreducetheamountofsequencingmistakes.Inaddition,alargenumberoftagshavetobesequencedinordertoquantifytheexpressionofgenesthathavealowexpressionlevel.SAGE110DNAchip111Microarraydataandannotation112WhatisProteomics?Proteomics

includesnotonlytheidentificationandquantificationofproteins,butalsothedeterminationoftheirlocalizations,modifications,interactions,activities,and,ultimately,theirfunctions.

StanFieldsinScience,2001.1133.3.ProteomicplatformGenome

staticabletoamplify(PCR)homogeneousnovariabilityinamountProteome

dynamic–conditiondependentnoamplificationnon-homogenous(cell-specific)highvariabilityinamount(>106)為什么有蛋白質組學Comparison:Genome-Proteome1143.3.1、Identification&Quantitation3.1.1、From2DGEtoMS3.1.2、FromMDLCtoMS3.1.3、Quantative

Proteomics:SIT&ICAT3.1.4、Microarray-basedproteomics3.1.5、Singlecellproteomics115BLOTStain/BlotImage/DatabaseOrganTissueCells2-DArrayIPGSamplePrepFractionationSolubilizationSDSPAGEOOOOOOOOOOOOOOOOOOOOOOOOOSpotCutterMALDI-TOFMSNanoESI-MS/MSMassSpec2-DArrayProteinID

ImageDatabase

DatabaseSearchPROTEOMEBROWSERMassPrep3.1.1、From2DGEtoMS1162DGE:Snapshotsofacell細胞快照117118TheFirstDimension:IEF119TheSecondDimension:SDS1201211221231564Mouseliver肝臟proteinsIPG4-5IPG4-7IPG5-6IPG6-714912181429124IPG4-7IPG4-7MouseliverproteinsIPG5-6IPG6-7125GelStain著色劑CoomassieStainSilverStainFluorescentStain126GelcuttingGelPickerPickerheadRinsestationCameraandlightassemblyGeltrayMicrotitre-platesandracks127GelDigestionRinsestationSampleneedlesBuffervalvecontrolEnzymecontainerGelplug(sample)platesPeptideextractplates128SamplePreparationforMS

樣品制備WashDryplugsCollectenzymeIncubateAddenzymeExtractpeptidesinnewplates129MALDI-TOF

基質輔助激光解吸電離飛行質譜130mPMF131mPMFSequencing132ProteinIDbyESI-MS/MS.表達序列標簽(EST)133LCESI-MS/MSIsolateddigestedproteinsCapLCdataprocessinganddatabasesearchingresultsbrowserQ-TofautomatedESI-MS/MS134

.+++++++++SAMPLESOLUTIONNEBULISATIONATMOSPHERICPRESSURESKIMMERVACUUMIONEVAPORATION+++++++++++++ESI135ESI136Q-Tof(MS-MS)137EST138FindSequenceTag139ProteinIDbyLC/MS/MS從新測序(DeNovo)140DeNovosequencing16O/18Olabeledy’’ionsun-labeledbions(N-terminal)(C-terminal)141142Threelevelsofproteomicsequencing

Instrument儀器IdentificationPMF

MALDITOF

50％EST

LC/MS/MS

80％DeNovo LC/MS/MS

>80％143FlexibilityandVariationinthe

ProteomicsProcess

Labelling

and

Quantitation

Separation

Sample

Processing

IdentificationCharacterisation

Protein

Function

AssaysSamplePrepandFractionation

Samples:

Tissues

CellsSerum...Information:Proteins

Targets

Markers...144NumberofProteinsperGenomeHaemophilus 1742E.coli 4413Yeast 6600Caenorhabditis 18000Drosophila 13000Human 80000!

Evenwiththebest2Dgeltechnology,multipleproteinsaremigratingtogetherinE.coliandyeastsamples.145Laborintensive勞動密集Timeconsuming耗費時間Difficulttohandleandautomate難以自動化操作Samplesimbeddedingel樣品嵌入Poorabilitytohandleproteinsthatare

hydrophobic疏水的acidicorbasic酸性的MWT<10kDaor>200kDaphosphorylated,glycosylated磷酸化和糖基化的membranebound薄膜束縛

LargeabundantproteinsmasksmalleronesSampleloading(sensitivity)limitedto<250ugand<500ulinvolumeHighresolutionseparationresolve>1,000proteinsIsoelectricpoint等電點andMWTinfoRunsinparallelHistoricalmethodofchoice2-DGelsforProteomics:

LimitationsAdvantages1463.1.2、FromMDLCtoMS147Prefractionation初步分離Removelargeabundantproteins(IgG,albumin)tohelpimprove2D-gelsensitivityEnrichlowabundantproteinstoboost醉翁急啊sensitivityRunGelIncompatible不相容的Samples(“gel-challenged”)Replace/augment2D-gelswithMDLCTechnologyReplace2D-gelswithcompleteMDLCPerformMDLCfollowedby1-DSDSPAGEUseMDLCwithICATtechnologyProteinTargetPurificationFunctionalProteomicsAnalyzeprotein-proteininteractionsWhereCanChromatography色譜技術

TechniquesHelpinProteomics?148ChromatographyforProteomicsBroadsamplerangeEasilyscaledforpreparativeConcentratesamplestoboostsensitivityHandlesanytypeofproteinStraightforwardautomation簡單的自動化proteinsstayinliquidphaseEasytocollectfractionsFlexibilityinchemistryandexperimentdesignSamplepreptoMDLCCleanersamplesimprovequalityofMShits.NoPIorMWTinformationAdvantagesLimitations149MDLCScenarios情節(jié)

for