16S-rRNA-基因在微生物生态学中的应用

第35卷第9期2015年5月生态学报ACTAECOLOGICASINICAVol.35,No.9May,2015基金项目:国家重点基础研究发展规划资助项目(2013CB733502);国家自然科学基金资助项目(41371268,31300447)收稿日期:2013鄄06鄄18;摇摇网络出版日期:2014鄄05鄄22*通讯作者Correspondingauthor.E鄄mail:[e-mail]:10.5846/stxb201306181726刘驰,李家宝,芮俊鹏,安家兴,李香真.16SrRNA基因在微生物生态学中的应用.生态学报,2015,35(9):2769鄄2788.LiuC,LiJB,RuiJP,AnJX,LiXZ.Theapplicationsofthe16SrRNAgeneinmicrobialecology:currentsituationandproblems.ActaEcologicaSinica,2015,35(9):2769鄄2788.16SrRNA基因在微生物生态学中的应用刘摇驰1,2,3,李家宝1,2,芮俊鹏1,2,安家兴1,2,李香真1,2,*1中国科学院环境与应用微生物重点实验室,成都摇6100412环境微生物四川省重点实验室,中国科学院成都生物研究所,成都摇6100413中国科学院大学,北京摇100049摘要:16SrRNA(SmallsubunitribosomalRNA)基因是对原核微生物进行系统进化分类研究时最常用的分子标志物(Biomarker),广泛应用于微生物生态学研究中。近些年来随着高通量测序技术及数据分析方法等的不断进步,大量基于16SrRNA基因的研究使得微生物生态学得到了快速发展,然而使用16SrRNA基因作为分子标志物时也存在诸多问题,比如水平基因转移、多拷贝的异质性、基因扩增效率的差异、数据分析方法的选择等,这些问题影响了微生物群落组成和多样性分析时的准确性。对当前使用16SrRNA基因分析微生物群落组成和多样性的进展情况做一总结,重点讨论当前存在的主要问题以及各种分析方法的发展,尤其是与高通量测序技术有关的实验和数据处理问题。关键词:16SrRNA基因;微生物群落;多样性;高通量测序;生物信息数据处理Theapplicationsofthe16SrRNAgeneinmicrobialecology:currentsituationandproblemsLIUChi1,2,3,LIJiabao1,2,RUIJunpeng1,2,ANJiaxing1,2,LIXiangzhen1,2,*1KeyLaboratoryofEnvironmentalandAppliedMicrobiology,ChineseAcademyofSciences,Chengdu610041,China2EnvironmentalMicrobiologyKeyLaboratoryofSichuanProvince,ChengduInstituteofBiology,ChineseAcademyofSciences,Chengdu610041,China3UniversityofChineseAcademyofSciences,Beijing100049,ChinaAbstract:The16SrRNA(smallsubunitribosomalRNA)geneisauniversalmarkerforphylogeneticreconstructionstoapproximatethetreeoflifeowingtoitspresenceinallprokaryotesanditshighconservation.Sequencingof16SrRNAgenesamplifieddirectlyfromenvironmentalsamplesiscommonlyusedtostudymicrobialcommunitycompositionanddiversity.Greatadvancesinpyrosequencingtechnologyandbioinformaticsinrecentyearsenableustoobtainsequencedatafromlarge鄄scaleenvironmentalsamplesefficientlyandcost鄄effectively.However,somecriticalproblemsneedtobeaddressedwhenthe16SrRNAgeneisusedformicrobialdiversitystudies,suchashorizontalgenetransfer(HGT),intragenomicheterogeneity,PCRamplificationefficiency,andsequencingdataanalysis.Inthisreview,wesummarizethestate鄄of鄄the鄄artapplicationsof16SrRNAgeneasabiomarkerformicrobialecologystudies,andintroducecurrentpyrosequencingtechniquesandbioinformaticsforlarge鄄scaledataanalysis.Thisreviewfocusesonfouraspects.(i)Weintroducethestructureandpropertiesofthe16SrRNAgene,e.g.theprimaryandsecondarystructure,HGTandheterogeneitiesof16SrRNAgenes.Basedoncurrentavailablemicrobialgenomes,multi鄄copyandintragenomicheterogeneitiesof16SrRNAgenesarerecognized.Thesephenomenamayseriouslybiastheestimationsofmicrobialdiversityinenvironmentalsamples.Someonlinetoolsanddatabasesusedforanalysisofthe16SrRNAgenesequencingdataarealsointroduced.Thesetoolsareused(ii)Weintroducesome16SrRNA鄄basedtechniquescommonlyusedinmicrobialecologystudies,suchasfingerprintingprofiling,hybridization,microarray,andhighthroughputpyrosequencingmethods.Wecomparetheadvantagesandlimitationsofvariousmethodsandrecommendhowtousethemproperlybasedonaspecifictarget.Differentmethodshavedifferentresolutionsanddetectionlimitations.Low鄄resolutionprofilingmethodspotentiallymisssomeimportantinformationandmakeitdifficulttodetailthephylogeneticcompositionofanenvironmentalsample.Pyrosequencingtechniqueishighlyrecommendedinthefutureformicrobialecologystudy.Severalsequencingplatforms,e.g.Roche454,IonTorrentandMiSeq,arecompared.(iii)WeevaluatethebiasesthatmaybeintroducedduringsamplepreparationandPCRprocedures,e.g.DNAextraction,primerselection,PCRoptimization,PCRproductpurification,anddataanalysis.Ampliconsequencingmethodsuffersfromahighlevelofsequencingandamplificationartifacts.ItisimportanttoselectOTU(operationaltaxonomicunits)classificationandchimeraremovingalgorithms.Inthiscase,theUchimeandUparsearerecommendedformicrobialampliconpyrosequencingreads.(iv)Weintroducesomebioinformaticstoolsforpyrosequencingdataanalysis,suchaschimeracheckanddiversityindexcalculation.ThemostpopularpipelinesforpyrosequencingdataanalysisincludeRDP,QIIMEandMothur.Inordertolinkecologicalquestionswithmicrobialcompositiondata,themethodsofecologicalstatisticsmustbeemployedtobuildtherelationshipsofmicrobialdatasetswithenvironmentalvariables.Here,weintroducesomemultiplestatisticalmethods,e.g.PCAandUniFracanalysis.Basedontheseanalyses,microbialdatabasedon16SrRNAsequencingarelinkedtotheenvironmentalvariables,andfundamentalecologicalquestionsareaddressed.Finally,werecommendresearcherstoconsidertheseproblemssystematicallywhenusing16SrRNA鄄basedtechniquesinmicrobialecologystudy.KeyWords:16SrRNAgene;microbialcommunity;microbialdiversity;pyrosequencing;bioinformatics微生物是地球上数量最多和多样性最高的生物,1g土壤中仅细菌就可能有109个。由于大多数微生物尚不能纯培养,传统的微生物研究方法,如显微镜微形态观察、选择性培养基计数、纯菌种分离和生理生化鉴定等,在微生物多样性研究中都存在很大的局限性。基于非培养基础上的分子生物学方法可以使人们快速、系统地分析环境样品中微生物组成、结构和多样性,极大地促进了微生物生态学的发展。Zuckerkandl等首次提出使用基因序列作为分子钟来分析生物间的亲缘关系[1]。Woese和Fox基于16SrRNA基因序列对原核生物的系统进化关系进行了分析,提出了著名的“三域学说冶[2]。从此,1