微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計1致謝周集中李筱婧陳永健束浩月鄺嘉良花正雙致謝周集中2InstituteforEnvironmentalGenomics,DepartmentofMicrobiologyandPlantBiology,UniversityofOklahoma,Norman,OK73019MicrobialEcologyinGenomicsEra:ChallengesandOpportunitiesZhongshanUniversity,Guangzhou,November5,2015.Jizhong(Joe)Zhoujzhou@;405-325-6073SchoolofEnvironment,TsinghuaUniversity,BeijingEarthScienceDivision,LawrenceBerkeleyLaboratory,Berkeley,CAInstituteforEnvironmentalGe3共同關(guān)心的問題采樣量（體積、重量）測序深度多少樣品是否重復(fù)是否混樣16S測序策略宏基因組與GeoChip16S與PICRUSt分析數(shù)據(jù)分析回答這些問題的根本：科學(xué)問題共同關(guān)心的問題采樣量（體積、重量）4專業(yè)：生態(tài)學(xué)

答辯人：李筱婧

導(dǎo)師：黃立南教授

中山大學(xué)碩士學(xué)位論文答辯采樣量與估算方法

對細(xì)菌物種豐富度估算的影響專業(yè)：生態(tài)學(xué)

答辯人：李筱婧

導(dǎo)師：黃立南5研究背景穩(wěn)健的微生物物種豐富度評價對于研究微生物多樣性及微生物群落的組成與功能的是必不可少的1微生物個體數(shù)目巨大，多樣性極高，占據(jù)了地球生物多樣性的絕大部分(Whitmanetal.,1998;Torsviketal.,2002)；2微生物的物種豐富度與組成一定程度上決定微生物群落功能(Belletal.,2005)，并在地球生物化學(xué)循環(huán)中扮演核心角色(Prosseretal.,2007)；3不同豐度水平的物種對細(xì)菌群落水平的多樣性有著不同程度的貢獻(xiàn)，且在微生物群落中有著不同的角色和功能(Shade&Handelsman,2011;Campbelletal.,2011)。研究背景穩(wěn)健的微生物物種豐富度評價對于研究微生物多樣性及微生6材料與方法采樣

理化Miseq

測序多樣性分析細(xì)胞

密度序列

處理1234567提取DNAqPCR

驗(yàn)證采樣樣品準(zhǔn)備數(shù)據(jù)分析材料與方法采樣

理化Miseq

測序多樣性分析細(xì)胞

密度序列7采樣采樣地：廣東大寶山礦區(qū)多金屬礦

采樣時間：2014年9月25-26日采樣水量：1ml、5ml、10ml、50ml、100ml、500ml、1L、5L和10L等9個水平（每個水平10個重復(fù)）采樣操作：1原位收集微生物細(xì)胞2原位測定溫度、pH值、溶氧值和Eh值3保存適量水樣用于細(xì)胞計數(shù)和理化測定采樣采樣地：廣東大寶山礦區(qū)多金屬礦

采樣時間：2014年98采樣量的影響采樣量的影響9整體上單個樣品所檢測到的OTUs數(shù)目與采樣量成正比，但采樣量間OTUs數(shù)目無顯著性差異；當(dāng)采樣量超過100ml，OTUs數(shù)目逐漸穩(wěn)定在同一水平,主要類群分布相似1圖3-1不同采樣量間AMD細(xì)菌群落的OTUs分布圖3-2不同采樣量間AMD細(xì)菌群落的主要類群分布SampleVolume采樣量的影響(測序量100000)

物種豐富度與組成整體上單個樣品所檢測到的OTUs數(shù)目與采樣量成正比，但采樣量10測序量的影響測序量的影響11圖3-4不同測序量間AMD細(xì)菌群落的主要類群分布測序

深度100010000100000門10

major->92.1%7.9%unassigned13

major->89.4%

9.1%unassigned23

major->90.3%

9.6%unassigned綱152334目254268科2651115屬19

71%unassigned53

76%unassigned304

76%unassignedOTUs151~254537~9021632~2432測序量的影響

物種豐富度與組成整體上單個樣品所檢測到的物種門類和豐富度與測序量成正比，但測序量間主要類群分布無顯著性差異。1表3-1不同測序量間AMD細(xì)菌群落的物種組成分布圖3-4不同測序量間AMD細(xì)菌群落的主要類群分布測序

深度12測序量的影響（500ml樣品）

常見種和稀有種的覆蓋度隨著測序量的上升，新增的常見種逐漸減少，而稀有種的增幅不一；測序量超過10000條即可檢測到50%的常見種，而測序量需超過50000才可檢測到50%的稀有種。3圖3-6AMD細(xì)菌群落中常見種和稀有種的數(shù)目

（柱圖表示新增數(shù)目，折線圖表示累積數(shù)目）98%80%測序量的影響（500ml樣品）

常見種和稀有種的覆蓋度隨著測1397%cutoffThreerunsofMiSeqOTUOverlapsamongThreeTagswithMiSeq54soilsamplesSameDNAsfromeachsampleamplifiedandsequencedbythreetags>10,000sequencespertechnicalreplicate<15%ofoverlapforwasobservedforidenticalcommunitiesThisissimilartopyrosequencing,indicatingthatthisartifactissequencing-technologydependent

(A)

(C)(B)(D)12.9±0.9%16.03%13%16.03%13%16.03%13%11.2±0.9%17.4%12.2%17.4%12.2%17.4%12.2%13.7±0.9%15.07%13.7%15.07%13.7%15.07%13.7%11.5±0.6%16.7%12.8%16.7%12.8%16.7%12.8%97%cutoffOTUOverlapsamongT14EffectsofSequencingEffortonOTUOverlaps:neverreach100%UclustUPARSE

Deepsequencingto16MreadspersampleOTUoverlapincreaseswithsequencingdepth,butwithsaturationat60%30Kpersamplecouldbereasonablesampleeffortspersample15EffectsofSequencingEfforto估算方法的影響估算方法的影響16模型LognormalPareto

(powerlaw)Exponential參數(shù)

*KStest

1000

01998BESTLognormal

PowerLaw

Exponential圖3-7AMD細(xì)菌群落物種豐度分布模型擬合比較估算方法的影響（500ml樣品，測序量50000）

參數(shù)估算利用三種常用參數(shù)模型擬合并經(jīng)KS檢驗(yàn)后，Exponential模型的擬合效果比Lognormal和PowerLaw更佳。1表3-2不同擬合模型間參數(shù)和KS檢驗(yàn)結(jié)果模型LognormalPareto

(powerlaw)E17結(jié)論進(jìn)行采樣設(shè)計時，采樣量設(shè)置為100-500ml，每個樣品的測序量為30000，可以獲得比較穩(wěn)定的物種豐富度觀測值和物種組成；123進(jìn)行數(shù)據(jù)分析時，應(yīng)考慮綜合考慮序列數(shù)據(jù)的取舍標(biāo)準(zhǔn)和估算方法的選擇，尤其是參數(shù)模型的選取與比較，需要綜合考慮錄入模型的數(shù)據(jù)范圍、驗(yàn)證方法以及擬合優(yōu)度評價體系；本研究所得到的物種豐富度估算雖然可以用于研究細(xì)菌群落組成和豐度分布，但對于細(xì)菌種子庫的研究，尤其是稀有種的估算，還需要結(jié)合時間或空間系列的樣品才能更好地估算稀有種的豐富度。結(jié)論進(jìn)行采樣設(shè)計時，采樣量設(shè)置為100-500ml，每18CEE結(jié)論不同的目的選擇不同的測序深度絕對多樣性的估計：測序深度30000及以上研究方法的探索相對多樣性的估計：測序深度10000足夠絕大多數(shù)研究水體采樣量100-500ml（16S）正確選擇估算參數(shù)更重要CEE結(jié)論不同的目的選擇不同的測序深度19UncoveringthesoilmicrobialdiversityinasubtropicalforestReporter:YongjianChenSupervisor:Prof.WenshengShuResearchinterests:communityecologybiogeographyecophylogeneticsUncoveringthesoilmicrobial20Soilmicrobialdiversityinforest/Heishiding(HSD)plotHeishidingNatureReserve(111

49'09''~111

55'01''East,23

25'15''~23

30'02''North),GuangdongprovinceofChinaSubtropicalevergreenbroad-leavedforestArea:50ha(1000×500m)all218838free-standingplantswithdiameter≥1cmatbreastheight(DBH),representing237speciesweretaggedandmappedspatiallyCTFSnetworkSoilmicrobialdiversityinfo21Soilsamplingandanalyses30m30m1708soilsamplesfocalpointMeasuresoilchemicalproperties:moisture,pH,electricconductivity,organiccarbon,nitrogen,P,Ca,Mg,AlDNAextractionPCRamplificationV4regionof16srDNA(bacteria)ITS2(fungi)250bppair-endsequencingonIlluminaMiSeqgrids:30×30mSoilsamplingandanalyses30m221.1SoilmicrobialcommunitycompositionBacterialassemblagesarephylum-rich(9phylawithrelativeabundance>1%)butvaryslightlyamongsamplesFungalassemblagesarephylum-poor(3phylaconsistedmostofallfungalsequences)butvaryremarkablyamongsamples1.1Soilmicrobialcommunityc231.4Species-accumulationcurvesNumberofOTUstendedtobeasymptotictotheupperboundvalueasnumberofsamplesincrease,implyingthatfewnewlyobservedspeciesweredetectedtowardstheendofoursampling1.4Species-accumulationcurve24Tedersooetal.,Science201440soilcoresfromnaturalcommunitiesineachof365sitesacrosstheworldamixtureofsixITS3primersandITS4ngsfivehalf-plates454MapsofglobalsamplingTedersooetal.,Science2014425Sampling32forests192sites3replications/siteGradientsGeographyClimateVegetationElevationSoilEnv.Scales10m~3,000kmSampling32forests263.Conclusions

Themostlikelylower-boundestimatedOTUsnumberis39,244(95%confidenceinterval(CI)=39,221–39,274)and14,223(95%CI=14,221–14,225)forbacteriaandfungi,respectively.Niche-basedenvironmentalcontrolprocessesdominantlygovernsoilbacterialcommunityassembly,whereasdispersal-basedspatialprocessesappeartobethemaindriverofsoilfungalcommunityassembly.Similarbelowgroundsoilmicrobialcommunitycompositionisaccompaniedbysimilarabovegroundplantcommunitycomposition.3.ConclusionsThemostlikely27CEE結(jié)論對格局的研究而言，樣品多多益善大樣地研究，500個樣品是基本數(shù)量樣品數(shù)量的重要性，遠(yuǎn)高于測序深度的重要性對于最復(fù)雜的土壤樣品，3000-5000有效序列足夠?qū)τ谝粋€和幾個樣品的情況，3000-5000有效序列也足夠，但一定要結(jié)合宏基因組/宏轉(zhuǎn)錄組/宏蛋白組/宏代謝組/SIP等/單細(xì)胞基因組等深度研究與個性化分析CEE結(jié)論對格局的研究而言，樣品多多益善2816S測序策略V3（150）；V4（320）；V3+V4（480）；V4+V5（400-450）；V6建議：V4；V4+V5不建議：V3；V6；V3+V4理由：測序質(zhì)量/數(shù)據(jù)量/分析精度/文獻(xiàn)可比性的平衡16S測序策略V3（150）；V4（320）；V3+V4（429宏基因組與GeoChip宏基因組與GeoChip30Whatarethefunctional

activitiesofamicrobialcommunity?Whataretherelationshipsbetweenmicrobialcommunityfunctional

structureandecosystemfunctioning?Howdoesmicrobialcommunityfunctionalstructurerespondtoenvironmentalchangessuchasclimatewarming?FromstructuretofunctionsWhatarethefunctionalactivi31OpenformatdetectionCouldnotassurethesamegenes/proteins/organismscanbecomparedacrossdifferentsamples.TheresultscouldbeexpectedandthusareopenHighthroughputSequencing454sequencing,Illumina,PacBioProteomics,MetabolomicsFunctionalmetagenomicsSinglecellgenomicsClosedformatEnsurethatthesamegenes/proteins/organismscanbecomparedacrossdifferentsamples.Theresultscanbeexpected,andthusareclose.BioLogPlatesPhyloChip:16SgenesGeoChip:functionalgenesI.HighThroughputOmicTechnologiesOpenformatdetectionI.HighT3297%cutoff1runofpyrosequencing11.7±3.3%13.3±3.3%7.4±2.1%9.1±2.5%24.3%6.0%25.1%5.8%24.3%6.0%25.1%5.8%24.3%6.0%25.1%5.8%20.1%8.8%20.3%9.1%20.1%8.8%20.3%9.1%20.1%8.8%20.3%9.1%(A)(C)(B)(D)ForwardprimerSingletonsnotremovedForwardprimerSingletonsremovedReverseprimerSingletonsnotremovedReverseprimerSingletonsremovedOTUOverlapsamongThreeTagswithpyrosequencing24samples,warmingvsnonwarming60tags<15%ofoverlapwasobservedforidenticalcommunitiesTechnicalvariationsarebigZhouetal.2011.ReproducibilityandQuantitationofAmpliconSequencing-BasedDetection.ISMEJ.5:1303-1313.97%cutoff11.7±3.3%13.3±3.3%7.33Technicalreproducibilitymeasuredbysimilarityamongtechnicalreplicates6forestsitesfromNorthAmerica(PanamatoOregon),3soilsamples/site,3technicalreplicates/soilsample,altogether,54datasets.AlltechnicalreplicateswereanalyzedwithGeoChip(180Kprobes),16Ssequencing(>80KReads),andshotgunsequencing(>10Gbpersample).Sorensensimilarity:Qualitative;Bray-Curtis:QuantitativeTechnicalreproducibilitymeas34Replicates!Replicates!Replicates!IncreasingsamplingeffortsAmelioratingthepotentialproblemoflowreproducibilityZhou,etal.2015.High-ThroughputMetagenomicTechnologiesforComplexMicrobialCommunityAnalysis:OpenandClosedFormats.mBio6(1):e02288-1435Replicates!AmelioratingthepCEE評論對于任何實(shí)驗(yàn)研究，重復(fù)都是必須的對于生態(tài)學(xué)調(diào)查，重復(fù)一般是以環(huán)境梯度/樣品的空間分布替代的永遠(yuǎn)不要混樣CEE評論對于任何實(shí)驗(yàn)研究，重復(fù)都是必須的36Microarrays:

Glassslidesorothersolidsurfacecontainingthousandsofgenesarrayedbyautomatedequipment.FGAscontainprobesfromthegenesinvolvedinvariousgeochemical,ecologicalandenvironmentalprocesses.C,N,S,PcylcingsOrganiccontaminantdegradationMetalresistanceandreductionAntibioticresistanceTypicalformat:50meroligonucleotidearraysUsefulforstudyingmicrobialcommunitiesFunctionalgenediversityandactivityLimitedphylogeneticdiversity.GeoChiporFunctionalGeneArrays

(FGAs)Microarrays:Glassslidesoro37GeoChip:AhighthroughputtoolforlinkingcommunitystructuretofunctionsHe,Z,TJGentry,CWSchadt,LWu,JLiebich,SCChong,ZHuang,WWu,BGu,PJardine,CCriddle,andJ.Zhou.2007.GeoChip:acomprehensivemicroarrayforinvestigatingbiogeochemical,ecologicalandenvironmentalprocesses.TheISMEJ.1:67-77.Highlightedby:

ApressreleasebyNaturePressOfficeReportedbymanyNewspapers

NationalEcologyObservatoryNetworks(NEON),RoadmapNationalAcademyofSciences,MetagenomicsreportR&D100,amongmostoutstanding100technologicalinnovationsandbreakthroughin2009GeoChip:Ahighthroughputtoo38R&D100,amongmostoutstanding100technologicalinnovationsandbreakthroughin2009R&D100AwardR&D100,amongmostoutstand39GeoChipRoadmap20022005200720132402

Genes24,243Probes150

GeneFamilies28,000Probes292

GeneFamilies83,992Probes549

GeneFamilies2010268,059Probes2,433

GeneFamiliesThemostcomprehensivehighthroughputmetagenomictechnologyforcharacterizingmicrobialcommunityfunctionalstructureandactivities.GeoChipRoadmap20022005200720140SummaryofGeoChip5.0probeinformationbyfunctionalgenecategoryGenecategoryNo.ofgenesincategoryNo.ofprobesdesignedNo.ofcoveredsequencesCarboncycling1714499787764Nitrogen401150324631Sulphur28850312657Phosphorus637837141Antibioticresistance352293459141MetalResistance14556552134681OrganicRemediation3493079659064Stress1233411987270Algalvirus1915382981Bacteriaphage4110952083EnergyProcess1112561647Environtoxins36191794Fungifunction109860411457Pigments3632294910Protists8329944017Soilbenefit50955914424Soilbornepathogeirulence898879222532Virus4438629462othercategory511184719874Total2,433268,059570,042SummaryofGeoChip5.0probei41Detectingfunctions:Geochemicalprocesses,ecologicalprocessesBroaddetection:~2500functionalgenecategoriesofimportancetoecology,geochemistryandenvironmentalsciencesHigherresolution:Species-strainlevelresolutionQuantitative:noPCRisinvolvedLowcost:<

$0.2gene/sampleSpeed:VeryquickMainadvantagesofGeoChip

(Comparedtootherapproaches,16S-based454sequencing,PhyloChip)Detectingfunctions:Geochemic42GeoChipFish-outWorkflowGeoChipFish-outWorkflow43KeydifferencesbetweenopenandcloseformatdetectionOpenformatCloseformatSensitivitytorandomsamplingerrorsHighLowEffectsbydominantorganismsYesNoFindingnewthingsYesNo/YesSensitivitytocontaminatedDNAsYesNoDataanalysisVeryslowrightnowRapidZhou,etal.2015.High-ThroughputMetagenomicTechnologiesforComplexMicrobialCommunityAnalysis:OpenandClosedFormats.mBio6(1):e02288-14Keydifferencesbetweenopena44EnvironmentalremediationBiodiversityWangetal.2009.PNAS,106:4840-4845Zhouetal.2008.PNAS,105:7768-7773zvaluesarelessthan0.1ClimatechangeZhouetal.,2011.NatureClimateChange,2:106-110Chanetal.2013.PNAS,110:8990-8995Hazenetal.2010.Science,330:204-208

Zhouetal.2014.PNAS,111:E836-E845

EcologicalTheoryWangetal.,2014.NatureComm.DOI:10.1038/ncomms5799EnvironmentalremediationBiodi45CEE結(jié)論復(fù)雜樣品，推薦Geochip實(shí)驗(yàn)研究的處理與重復(fù)樣品，推薦Geochip旨在新發(fā)現(xiàn)（新基因/新的代謝途徑/進(jìn)化/基因水平轉(zhuǎn)移/基因突變等）的研究：高通量測序CEE結(jié)論復(fù)雜樣品，推薦Geochip46PICRUSt分析：基于16S的微生物宏基因組預(yù)測Reporter:ShuHao-yueLaboratoryofPollutionandRestorationEcologyPICRUSt分析：基于16S的微生物宏基因組預(yù)測Repor47微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計48AcentralquestioninbiologyishowbiodiversityinfluencesecosystemfunctioningItremainsunclearhowmicrobialcommunitycompositionisrelatedtoecosystemfunctioningThekeytoaddressingthisissueistherelationshipbetweenphylogenyandfunctionaltraitsbiodiversityIntroductionecosystemfunctioningAcentralquestioninbiology49Hypothesis:

functionaltraitsbasedoncomplexgeneticsystemsintegraltotheorganismevolveslowlyandwillbemorephylogeneticallyconserved(traitA).simpletraitsconsistingoffewinteractingproteinswillbemoredispersedorcompletelyrandomlydistributed(traitB,C)Hypothesis:5093%(83out89)ofthetraitswerenonrandomlydistributed93%(83out89)ofthetraits51微生物生態(tài)：科學(xué)問題與實(shí)驗(yàn)設(shè)計52PICRUStalgorithmPICRUStalgorithm53PICRUStrecapitulatesHMPmetagenomes530(HMP)samples(both16SrRNA&shotgunmetagenomesequencing),>700draftandfinishedreferencegenomes.Spearmanr=0.82,P<0.0