蛋白质组的生物信息学分析.

1、4鈔OUTLINESummary of ProtconieBottleneck in Proteome based on MS/MSQualitative Protconie AnalysisQuantitative Proteome AnalysisPost Translational Modi Heat ions( PT Ms >Summary of proteome & proteomicsInstitute f<x © HUHOSystems BiologyHuman Proteome ProjectSeattle Proteome Center(SPC)

2、EJUzurichDoparawtf ol (MnQFInstitute of Molecular Systems BiologygpmpQzhangeOMSSAOTWO MUMCFWL SOC1A1Ktvices AssociAnotwmax planck institute of biochemistryUniPrxJ.；(f 卜 of net of CANCER CLINICAL£口 PROTEOMICS wseAtcHTlic Association ofBiomolccuhr Resource FacilitiesRftwr<h TeduM)iD£7 Coe

3、mmatioss UMbauBottleneck in Proteome based on MS/MS|Data analysisthe Achilles heel of proteomicsMARCH 2OMVOLUME 21KhH «o tmMv T1M» ««twi <wnMidecwf mU ”MlawWfr_» f"ThK«f»e*. it m M.ih rntiHahW* tw »wd InI "Eawru 4 IV pu»«n * N«ttv f

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5、r*i2 MAltai y <WimftiovrwK vlut W* 4n Ant ftrw aramlwt nt3(M*J prnwiilcdW rijwv*-UMI fWtefiB hHwm UHifU. V ttiil Uae« tter nMlhvi aaBiMd aufwnawvwtm «Hab tranm尸rwwl* vMmuMt. «<mH W piM tMBtaVtftHMMl m4 fvnt MwMllMl *|uim' VrWocv.4f Ik bM 0(»r ability ! ytBerste data ww

6、oeMrips o«r ebRity te lye II" |9«<亦 z rt ih» ihw << funmIM <Wm|f«tr4RmAr*.耶o HmmJ an*li.屮flfw MhMk Ftof x 0(4.o <4 Ifc 、" pn初 <44“”低M 卯 IWMi UHIIR叩).h«wd<4. quirf4tf 卑K5w»rtn iHub. «f frvtorMcaBrpHMuj1ftl vm own to>InH sftn Mp»

7、;Mi <4 d*%0nW M»4Oi< oaMwi tirWTfw»# Mwi> »fwrnMne<E mcmr tbf mUmv. rs!Uu< iWfd aiuhtj M g AM CfMBMlOHNo matter the choice ofquuntiUitivc method, quaniitauvc protcomic data are typically very* complex and often of variable quality.The main challenge stems from incomplet

8、e data, since even today's most advanced mass spcctrome-tcrscannot sample and fragment every peptide ion present in complex samplessubset « heing identified in LC、IS/IS (liquid-chromatngriph- coupkd undem miss spectrometry ) expenmenu. Out of the identilied proteim. another wbxi is suitable

9、 fur quanusm>fi Lsually, uc higher abundance pruccins are co、cred U idenuheauon and quanuiicauon.Anna Rev. Plum BiZ 2010.61:491 516Iden tificatio nIdentification of workflowMpcTlmvnialJ protein idrntiomputadonul pan fnein identifkatioaPredictedfragmention%Theoreticalmss spectrumExperimentilmass s

10、pectrumLxpcrimentlfragmentsKracmrntnioddinj：PeptidesidentificationCompiring scoring Ionization, collhiunPeptidesfDigcslion modelingT Slatidc evaluationPeptidesMixtureRciiablcProteinidentificationProtvin datMbaikcEnzj me digntion(rouping cialunlion f irrotciti sampleHow to identify a protein/pep seq.

11、Raw data from mass spectrumMS spectra: Peptide ions (precursors mother ions)MS/MS spectra: fragment ions (product ions)example.mgf0585 19.0000 11071 8.0000 10835 12.0000 10400 9.0000 10811 8X0200 10377 367.0000 108S8 15.0400 11005 7X.OOOO 11453.6597 69100 11452.6614 12,6300 126.0000 10646113.07C0 41

12、.2700 1RTINSECONDS=236PEPMASS=838 37120TITLELocus : 07.2 File:A . I . - _ 4 4BEGIN IONS75554 7 9121212141Charge of precursor ionMass of precursor ionPeptide fragment ions： m/z intssitY chargeEnd symbol of one MS/MS soectrumPeptide ion fragmentationR.H O I IIH O I II-C-NH-C-C-OH"Zbionsv c

13、nsm/zM1062.MQIFVKTLTK141.1 Flee961.6MQirvmTK248.1 Mb?848.5MQiFvrrLTK31.32be747.4WIFVKTLTK462.3 H619.3MQIFVJCTXfTK590>4«M520.3NQIFVKTLTK89.522373.2MOIIVKTLTK836.5”2260.1MQITVKTLTK949.6 Abl149.2NQITVKTLTK1077.7 e0Available search enginesProgra mReference WehiteWtdbast search tookSEQIEST84MASCO

14、T85pFindProteinProspcctor86ProblD87XnandemXXSpectrumMillPhenvx89OMSSA4VEMS90MyriMatch91ProteinPilot147him: wwwjhci hltp:, nialrixscicncc.zm hup: ww、;p竹hllp: prospeclor.ucs匸eduhllD： loiHs.iHolcQnBXinlcr.onLUiki index.Dhiyflillc Software: Prob IDhttp httpwww.chcrruifilcni com/personaLcicbio 底 unucMmuM

15、hicscnwwwmcNandcrbil(cdu/nisi"c'biointbnna(ic5Why ProteinPilot Paragon algorithm: * Sequence approach* searchalgorithm for peptide ID： T he Paragon Algolltluiu a Next Generation Search Engine That Uses Sequence Temperalure Values and Feature Probabilities to hientify Peplides from Tandem Ma

16、ss Spec"厂 Shilov IV. Seymour SL et al 12007) MCP 6.9, 163X Unique feature hypothesis selection stagethere is greater potential for imprencment from advances in deteniiiiiing what to score, not how to score it." Shilov IV. Seymour SL et jI C(X)7)MCP6.9, 1638 Pro(Jroup1M algorithm (or protei

17、n inference Quantitative results for stable isotope label quant experiments Extensive AA Modification Catalog (vlobul & local FDR filteringID results evaluation> Filtering standard By identification confidence: Protein Unused score >1.3( means a 95% confidence) . More likely to be used. By

18、 Local FDR cutoff: less than 1% or 5% FDR. By unique peptides num. At least I unique peptide per protein group> ID statistical1 Sample name#TotalspectraMID spectraIDpercentage#ID peptidesHID proteins| ALL34504015801145.8%28125IE 4741z Feature distributionUnique peptide numberPeptide length distri

19、butionMLW4VGmtff hKMtNV*w6BlMBk r ai2Protein coverage distributionHow to quant a PSM?> Quant. Bused MS: XIC(eXtracted Ion Current)rnzg 460lsjE5RT:24B3475 47S 477 478mt / 啤 上 008060筑” Eg47&15RT254Q47&15A 477.15P7815475 47B 477<78蔦900900300Ki-2352424525255 2B21524245 2S 2S3 »tire(mi

20、n|> Quant. Based MS/MS: XIC(eXtractcd Ion Current) & intensityXICs of fragment ions: MRM.SWATHrnusa*Intensities of fragment ions (labeled marker): Itraq.TMTQuantitative ProteomeCMncoiMeinQIEHC cwtof Mue Calculate peptides' abundance : XlCs, Intensity, Spectra count Normalize pcplidcs, abu

21、ndance: mean, median, quantilc> linear regression Decide proteins* expressed abundance and Fold Change(F(3： meath mediaih totaL weighted ratio. Statistical analysis: T-test, ANOX PCAt Fishery Exact Test Decide significant expressed difTerent proteins: FC:12 l3. 15.2 tP-value less than 0.05.血 mcfM

22、tn | | Quant.Results evaluation Evaluation of bioiogical/technical replicatesPesnon's corrwlation : O.>1 *p<OfiOO1Quantified overlap between two experimentsCorrelation between two experimental replicates ratio pairs血 mcfMtn 0.960.990960.99CVBoir- 0 8CWL CTALCM価CWL 24h150 1000 0.96H4 0.96ww

23、:000 一一 ：000IZIIZIZI0S5155 15515,15> Decide Significant difTercnce expressed proteinsIf bioreplicaies or technique replicales contained, one may get a mean or median of comparable ratios, or just decide by the number of occurrence of sig. difference among the compared rcplicalcs samplesAcessiDa N

24、aae SaMescts IMF stairE VwMSCC1,FVal ns：m115:1HPVal115.114116:113FVal na：U3116:114FVrf116:114p Q09666/ NeurcHast dffer«m do«i><4OI55>W:0 0224W5!00”3WI96E 130519996小Eb；pQI5l9l?k<Tr O5=Hxt. 石up45 他(r$ow0:iTtt4onWM,IW002 29OS6109p Q13S!3Sp«n)dun. denuJ0333?0?)X5 0013725230.46

25、551610001 沁0*31139337M13025：石P'lS,廿DM AteJe pro&g4oi ces-oj o4 8：E-«OE388C:<w4u Q60FE6 < JA OSHoox dow49JVW57V0?IWI0W0J5QM3724.U£.»O.W7«?4?p Q|43>ICvtcfb«tttfdEn4OMOZHJ0CE-100现aw2SE-OJ012246200 1-0219<sp Pt>2?P1lKDCDNA depevkot protr* ksuse c«ah t

26、r QdQIEd Qlf E< FLxmc, A OS=Hmo upens GXfL denu tviof&uaic(!vte 1 ckow ! C dcuia«p PO, *T kXIJ K«fm npe It cyiockrietil 1 OS=Kc “n jpPJ9WFA$JTFMi、aril svwhaR OS=H«iic wpm do>n 002A(X，ailwwBl O>-HGN-lldimn0 41490 00221921：02123J24E.0: 45)20 OOM 积”eut90 50110 047M1C.0 5MJOS

27、B-0<o$?u002196BB1 tranftenon *na gn 刮Post Translational ModificationsPost trunslational nuKiirinition (PTM) is a step in protein biosynthesis. Proteins arc created by ribosomes transluling mRNA into polypeptide chains. These polypcplidc chains undent) PTM (such as folding, cutting and other prcKe

28、sses) before becoming (he mature protein product5 CdTbOM/pepCddse t prodjee rruture ir&uiivimod駅“Oom lor rvwie« epectromtryTlie aim is to create a community supported, comprehensive database of protein nuxlificulions for mass spectrometry applicutions. That is. accurate and verifiable value

29、s, derived from elernenlal compositions, for the mass diffcrc nccs inlrcxiuccd by all types of natural and artificial nxxli heat ions. Other important infomiation includes any mass change, (neutral loss), that occurs during MS/MS analysis, and site specificity, (which residues are susceptible to mod

30、ification and any constraints on the position of the modification within the protein or peptide)Website: hup:z Workflow for PTMsMattAaihtiBShortcoming by conventional ID workflowTop scoring peptide matches to query 1 Score greater than 17 indicates homology Score greater than 44 indicat

31、es identity Status bdr shows <>22 hi ts for this peptideScore63 >160.660 >68.61.17>16>16>16.QDeltaHitProteinPeptide-0.071gi|92686VLEDDPEAAYTTR-0.071gi|92686VLEDDPEAAYTTR0 "101192686VLEDDPEAAYTTR0.072gi|37360416SQSNLQGLDDSR-0.033gl|14195007AVTGYRDPYTEK-0.033gi|14195007AVTGYR

32、DPYTEK-0.033gi|14195007AVTGYRDPYTEK-0.033gi|1419S007AVTGYRDPIEK-0.033gi14195007AVTGYRDPYTEK0.072gl|37360416 SQSNLQGLDDSRA new concept of site location for PTMsaazr j woi axeOlotMh in vivo, and itQ-pGCiflc pbosphorybition dynamics In signaling netwofiAscoreOteen"On*幺空£* A&itiiof infomat

33、ton创EE2006Ckt24i10ri2tQ22008 94P 1DA probeb«lity>based approach for high-throughput protein phosphorylation anatysis and site localization. BgwndH SA YW 丄 G<g SA. RmhJ Gyg SPi Soc informationPTM SCOIt1W>M11OW»30 g 10l074rtix»WiW0aM» &MD?010tiai6Confident phosphorylat

34、ion site localization using the Mascot Delte ScoreSitttaLMM1. ICMflLS. 2记“ UmaJM. Matfuewr thntehrfk备 Amnor McrmMlonMl) scoreSome visualresultsSite Number DistributionRXA< RXR .E KI Gppi g£ nr. G Av£v EYE A E EQe. PG w.PhosphoSite DistributionI8T74STgro«wlBack(r»an4oitf A16. C

35、-：，Dlot »< »".» $c«r»cK»0；DJZ« !*E.E琅込， 20. ) I二二二叫寸6GO annotationI AO77J4K107871(<.汽<BTTIXK03027)P9S26|小M20:M”，w. d5238W7I36|g Hj22061叭X14| WPRQ20M<|4. W5!BM8im6|、dliM：rea«oC2<P$4Mdi tfe Gene OU4&f> Ora&MSMCh fcr procMi fir GO *

36、 udn( MGONewsGO on Tw<XerFrng up(ix««GO n«wtd«GiGO n«w« RSSf«* *dGO on FK«t>ooi:workflowannotatedresultsResults statisticz 血-smrcp iozGiBliyna.iwjwi W：AMM6| SHonjnui tn 紐 Loreiivna”" pA2kRPll>tMS.fllhll m：AHinimR_rnuii rp* A43U9|GrySA HIJIKS tp A

37、WXTlnt 的山 sp <5YICKb|C1OTKMJM so A口師6I8T3 iJUJBolecular_> GO annotation resultsExtended syap2hs*“-：G0,0CgL2HSbx»X3rrl OSmn » f4pletW：OCC»5KW:9)311tGO：O043C< K'：OOK4* *ynthafe-l GO：Oi 4-Q01Ct3312W)：0003F.a>：00 W4：Neurcbla$t«ie-ajollficd G0:00Wt<(X'；0O«4

38、c4 ven H>ta-»rd Tacicr A G0:00l7il<»：c<H3731 uiF-bindlT protein :<：X)：0022S3(X):o(n?3(匸；l l f J: r；F： 丁门1： ：d：A)31 VCHCCmryI : t :：. 一】【.门 :.05tt00：cajk. . : XM»丈8:00008(Putative叮5“1 GO:O03J2i(»:C<»66：G0:«466(»:0««l'PrHclnMHogUU.proctfi

39、 «llul<rc«posp|Q«ttCFCCyt<ellc r-t s p| F62711 Sex inc/ thr e-. i- 8p|073Z2ZdiASlutanyI ?p|Pl=ir«-Fr6in STK c： pl卸听£SPRY 曲41xr“ 9p|QI6B6：晰旳 tr|fe421D«c£dlA NJ54399 U|H38UVKcr!d-llpcitt>、xcell .ell cell call Zcell_part ;cll_art eellj)artgHjartceiiul -tr. pr

40、ocess E cellular.ceA bUUsKl r h<r»le<l r >1 ""4。"I、/ "i订。cel) cli.partcell celI,part cell cellj>artblrdlr cr binding 5 blrillcM ca Mrdlr«binding binding Htv4<r»e r» «KEGG Pathway annotationKEGG PATHWAY DatabaseWirte« .押 ot .Miixuter te

41、taractiofi fmciIcmv. a ad r«M>tteicPathway MapsKEGG PATHWAY ts a collcctiof) of manualr drawn pathway maps represcrting our knowledge on the molecijhr interaction 4nd rrjicticn network% for:1. MelaboiisniGlol>3l/overvicw Carbohydrate tnery Upid Nudcgtide Ammo ood Oilier ornmo Glycan Corda

42、or/vltamn Tecpenoid/PK Other secondary metaboMe Xenobotcs Chemcl stiuauie2. Genetic IfocrrwtkMi ProceMnqX Lfivirofmicntl Inlorniliun PrgB$i(»94. CduUr Processes5. Ocfpnkmal SyMpens6 Humen Di»cdscs«nd obo on the structure rehtJO<i5hp5 (KEGG drvg stnicture maps) m:7. Dru<| DevHupm

43、enlWorkflow/ formKEGGated KO Dg/BLASTP <Results9Gene set mndiment analysts: A knowledgebased approach for interpreting genome wide eipcesskw profilesFunctional enrichmentWhy we need enrichment?Many functionnl nodes would be gathered and overlap if just annotate gcncs/protcins directly, which may

44、puzzle researchers So we hope to filter and screen it to achieve more significative functional nodesHow to achieve enrichment? Fisher's exact testCumulative supper hypergeometric (eslFunctional enrichmentr GO enrichment resultsTerac frem the Coafxmentkood ot better than Cene Ontology ter®Cl

45、uster frequencyProtein frequency of aeeP valuellbQSQUl 科1 朝"enn of1-丹246 out of 59B2 gere=. 4. IX8. 6826We-10jcut of 22S cctq, 37.饰1396 exit af 5兌2 ernes. 23.齐1.24367 弘-00.1 uIm CAOU-fKli；! A<iejfille二5 vl LIS".；：；宀：/ 二二 2G,二小L24Q$7c-08：of :茯 gre 二，12279 et of 59E2a. 7U2.T4S57<e-03c<Jt of 2©52.21 $9 out of 5982 genes, 36.8*3.2W0«le-08DUClCAI l'JKA：27 wt of JfS cer