Frontiers | Comparison of Two 16S rRNA Primers (V3–V4 and ...

The gene for the small ribosomal subunit (16S rRNA) is commonly used to study the taxonomic composition of microbial communities in their ... ThisarticleispartoftheResearchTopic MarineMicrobiomes:TowardsStandardMethodsandBestPractices Viewall 5 Articles Articles CatarinaMagalhães InterdisciplinaryCenterforMarineandEnvironmentalResearch,UniversityofPorto,Portugal LiseØvreås UniversityofBergen,Norway AlessandroVezzi UniversityofPadua,Italy MiguelSemedo InterdisciplinaryCenterforMarineandEnvironmentalResearch,UniversityofPorto,Portugal Theeditorandreviewers'affiliationsarethelatestprovidedontheirLoopresearchprofilesandmaynotreflecttheirsituationatthetimeofreview. Abstract Introduction MaterialsandMethods ResultsandDiscussion ConcludingRemarks DataAvailabilityStatement AuthorContributions Funding ConflictofInterest Acknowledgments SupplementaryMaterial Footnotes References SuggestaResearchTopic> DownloadArticle DownloadPDF ReadCube EPUB XML(NLM) Supplementary Material Exportcitation EndNote ReferenceManager SimpleTEXTfile BibTex totalviews ViewArticleImpact SuggestaResearchTopic> SHAREON OpenSupplementalData ORIGINALRESEARCHarticle Front.Microbiol.,16February2021 |https://doi.org/10.3389/fmicb.2021.637526 ComparisonofTwo16SrRNAPrimers(V3–V4andV4–V5)forStudiesofArcticMicrobialCommunities EduardFadeev1,2*†,MagdaG.Cardozo-Mino1,2,JosephineZ.Rapp3,ChristinaBienhold1,2,IanSalter1,4,VerenaSalman-Carvalho5,MassimilianoMolari2,HalinaE.Tegetmeyer2,6,PierLuigiButtigieg1,2andAntjeBoetius1,2,7 1AlfredWegenerInstituteforPolarandMarineResearch,Bremerhaven,Germany 2MaxPlanckInstituteforMarineMicrobiology,Bremen,Germany 3SchoolofOceanography,UniversityofWashington,Seattle,WA,UnitedStates 4FaroeMarineResearchInstitute,Tórshavn,FaroeIslands 5DepartmentofMicrobiology,MorrillScienceCenterIVN,UniversityofMassachusetts,Amherst,MA,UnitedStates 6CenterforBiotechnology,BielefeldUniversity,Bielefeld,Germany 7MARUM,UniversityofBremen,Bremen,Germany MicrobialcommunitiesoftheArcticOceanarepoorlycharacterizedincomparisontootheraquaticenvironmentsastotheirhorizontal,vertical,andtemporalturnover.Yet,recentstudiesshowedthattheArcticmarineecosystemharborsuniquemicrobialcommunitymembersthatareadaptedtoharshenvironmentalconditions,suchasnear-freezingtemperaturesandextremeseasonality.Thegeneforthesmallribosomalsubunit(16SrRNA)iscommonlyusedtostudythetaxonomiccompositionofmicrobialcommunitiesintheirnaturalenvironment.Severalprimersetsforthismarkergenehavebeenextensivelytestedacrossvarioussamplesets,butthesetypicallyoriginatedfromlow-latitudeenvironments.Anexplicitevaluationofprimer-setperformancesinrepresentingthemicrobialcommunitiesoftheArcticOceaniscurrentlylacking.ToselectasuitableprimersetforstudyingmicrobiomesofvariousArcticmarinehabitats(seaice,surfacewater,marinesnow,deepoceanbasin,anddeep-seasediment),wehaveconductedaperformancecomparisonbetweentwowidelyusedprimersets,targetingdifferenthypervariableregionsofthe16SrRNAgene(V3–V4andV4–V5).Weobservedthatbothprimersetswerehighlysimilarinrepresentingthetotalmicrobialcommunitycompositiondowntogenusrank,whichwasalsoconfirmedindependentlybysubgroup-specificcatalyzedreporterdeposition-fluorescenceinsituhybridization(CARD-FISH)counts.Eachprimersetrevealedhigherinternaldiversitywithincertainbacterialtaxonomicgroups(e.g.,theclassBacteroidiabyV3–V4,andthephylumPlanctomycetesbyV4–V5).However,theV4–V5primersetprovidesconcurrentcoverageofthearchaealdomain,arelevantcomponentcomprising10–20%ofthecommunityinArcticdeepwatersandthesediment.Althoughbothprimersetsperformsimilarly,wesuggesttheuseoftheV4–V5primersetfortheintegrationofbothbacterialandarchaealcommunitydynamicsintheArcticmarineenvironment. Introduction TheArcticOceanisthemostrapidlychangingmarineregionontheplanetduetoitsfastwarmingcausingsubstantialsea-iceloss(PengandMeier,2018;Daietal.,2019),aswellasincreasingpollution(Peekenetal.,2018).Toassesstheimpactofglobalclimatechangeonmarinefoodwebdynamicsandelementalcycles,itisimportanttomonitorvariationsinmicrobialcommunitystructurewithtime(KarlandChurch,2014;Fuhrmanetal.,2015;Buttigiegetal.,2018).However,theArcticOceanisgenerallyunder-sampledinice-coveredregionsandinwinter(Wassmannetal.,2011),particularlywithregardtoassessmentsofitsmicrobialcommunitiesandtheirbiogeochemicalfunctions(Boetiusetal.,2015).Untilrecently,microbialmonitoringeffortsinthedeepArcticOceanconsistedof1year-roundlong-termtimeseriesattheHAUSGARTENobservatoryintheFramStrait(Soltwedeletal.,2005,2015),aswellasafewotherprocessstudies(e.g.,Kirchmanetal.,2007;Alonso-Sáezetal.,2008;Nikradetal.,2012;Wilsonetal.,2017;Mülleretal.,2018). TheArcticOceanfeaturessubstantialverticalstructurethatmayselectforspecificmicrobialtypesintheseaice(Boetiusetal.,2015;Rappetal.,2018),intheice-freeandtheice-coveredhighlystratifiedsurfacewaters(Wilsonetal.,2017;Fadeevetal.,2018),inthesinkingparticles(furtheraddressedas“marinesnow”;Fadeevetal.,2020),aswellasinthewaterandsedimentsofthedeep-seawheretemperaturesareyear-roundclosetofreezingpointtemperatures(Bienholdetal.,2012;Hoffmannetal.,2017;Wilsonetal.,2017;Rappetal.,2018;Fadeevetal.,2020).Throughouttheannualcycle,Arcticsurfacewatersbacterialandarchaealcommunitiesexhibitpronouncedfluctuationsofthedominanttaxonomicgroups(Alonso-Sáezetal.,2008;Wilsonetal.,2017;Mülleretal.,2018),whicharestronglyassociatedwithpresenceofseaiceandtheseasonalphytoplanktonblooms(Kirchmanetal.,2007;Nikradetal.,2012;Fadeevetal.,2018;Cardozo-Minoetal.,2020).Inwinter,aswellasunderice-coveredconditions,thecommunitiesaredominatedbythebacterialclassesAlphaproteobacteria(mainlytheSAR11clade),Dehalococcoidia(mainlySAR202clade),andthearchaealclassNitrososphaeria(Alonso-Sáezetal.,2008;Wilsonetal.,2017;Mülleretal.,2018).Inthesummer,andunderice-freeconditions,thecommunitiesaredominatedbythebacterialclassesBacteroidia(mainlytheorderFlavobacteriales)andGammaproteobacteria(mainlytheordersAlteromonadalesandOceanospirillales;Wilsonetal.,2017;Fadeevetal.,2018).Duringthesummer,differencesbetweenice-coveredandice-freecommunitiesalsoaffectthemicrobialdiversityofthedeepoceanandtheseafloorviaalterationsofmicrobialcommunitiesonmarinesnow(Fadeevetal.,2020). IntheframeworkoftheFRAMMicrobialObservatory(FRontiersinArcticmarineMonitoring),weareaimingtodevelopastandardizedmethodologyforlong-termobservationsofmicrobialcommunitiesinthesehighlydiverseArcticOceanenvironments,whichwillbealsocomparabletootherlong-termmicrobialtimeserieslocations(e.g.,HOTandBATS).Unlikeothertimeseriessitesoftheworld,theice-coverandtheharshconditionsoftheArcticOceanarelimitingtheaccessibilityofthesamplingsitestothesummermonths.Samplingcampaignsduringthewinter(whenmicrobialbiomassislow;Kirchmanetal.,2007;Alonso-Sáezetal.,2008)arerareandhaveonlyrecentlybeenachievedusingautonomoussamplerswithlimitedsamplingcapacities(Liuetal.,2020).Therefore,theuniqueconditionsandthecurrentlyavailabletechnologiesconstrainyear-roundmicrobialobservationstoPCR-basedapproaches(i.e.,16SrRNAgeneampliconsequencing),whichcanberealizedwithlowconcentrationsofDNA(Thomasetal.,2012).Metagenomicsapproachessuggestthatthefunctionalcapacityofmarinemicrobialcommunitiesisstronglylinkedtotheirtaxonomiccomposition(Galandetal.,2018;McNicholetal.,2020).Thus,whensupportedbycuratedtaxonomicdatabases(e.g.,SILVA16SrRNAgenereference;Quastetal.,2013),16SrRNAgeneampliconsequencingprovidesanaffordablehigh-throughputtoolforaddressingtraditionalcommunityecologyquestions,especiallyundertheconstrainedsamplingconditionsoftheArcticmarineenvironment. Acriticalstepin16SrRNAgenesequencingstudiesistheselectionofPCRprimersforDNAamplification(Armougom,2009;WangandQian,2009).Throughouttheyears,manyprimersetsweredesignedfordiversitystudiesofspecifictaxonomicgroups(e.g.,SAR11clade;Apprilletal.,2015),andattemptshavebeenmadetodevelopamoreuniversal16SrRNAgeneprimersetsthatcouldcoverclosetotheentirediversityofanaturalmicrobialcommunity(e.g.,EarthMicrobiomeProject;Caporasoetal.,2012;Gilbertetal.,2014).Thedevelopmentofprimersetsfortheamplificationof16SrRNAgenesisconductedinsilicousingreferencedatabases(e.g.,Klindworthetal.,2013).TheArcticOceanisthesmallestandshallowestofallfiveoceans,representing4%oftheareaand1%ofthevolumeoftheglobalocean.Nevertheless,itplaysanimportantroleinglobalprocessesthatarestronglyaffectedbytheongoingclimaticchangesandisconsideredrelevantforseveralEarthSystemtippingpoints(WassmannandReigstad,2011;Lentonetal.,2019).Furthermore,beingthecoldestamongtheoceans,withstrongstratificationandonlylimiteddeep-waterexchange,theArcticOceanislikelytocontainuniqueendemicmicrobialdiversitythatdrivesitsbiogeochemicalcycles(Kirchmanetal.,2009;Ghiglioneetal.,2012;Pedrós-Alióetal.,2015).AnexampleforsuchlocallyadaptedArcticdiversitywasrecentlyfoundwithArcticspecificmembersoftheubiquitousSAR11clade(Kraemeretal.,2020).Furthermore,despiteitsglobalimportance,samplingeffortintheArcticOceanislow,especiallyinandundertheseaiceandinthedeepbasin,aswellasgenerallyduringthewintertime(Wassmannetal.,2011;Royo-Llonchetal.,2020).Thus,thereferencedatabasesarelikelylackingpropercoverageofthecomplexityanddynamicsoftheArcticOceanmicrobiomesthatmayresultinbiasedrepresentationsofthembycurrentlyavailable16SrRNAgeneprimers. Oneofthemostextensivelyusedprimersetfortheinvestigationofbacterialdiversityinvariousenvironmentsisthe341F/785R(targetingtheV3–V4hypervariableregionsofthe16SrRNAgene)thatwasdevelopedbyKlindworthetal.(2013).Fortheinvestigationofmarinemicrobiomes,analternativeprimerset515F-Y/926R(targetingtheV4–V5hypervariableregionsofthe16SrRNAgene),whichisalsoabletocapturethediversityofthearchaealcommunities,hasbeendevelopedbyParadaetal.(2016).Currently,bothV3–V4andV4–V5primersetsarewidelyusedinstudiesofmarinemicrobialcommunitiesandwereextensivelytestedusingmockandnaturalcommunitiesoftemperatewaters(e.g.,Wearetal.,2018;Willisetal.,2019;McNicholetal.,2020).However,nostudyhassystematicallytestedtheperformanceoftheseprimersetsonmicrobialcommunitiesoftheArcticOcean. Inanattempttoselectthemostsuitableprimersetforthelong-termmonitoringofArcticmicrobialcommunitiesaspartoftheFRAMMolecularObservatory,wepresenthereaperformancecomparisonofthe16SrRNAgeneprimersetsV3–V4(341F/785R)andV4–V5(515F-Y/926R).OurhypothesiswasthatduetorelativelylowrepresentationofArcticmicrobialcommunitiesinpublicdatabases(duetolownumberofexistingstudies),the16SrRNAgeneprimersetsmaycapturedifferentpartsofmicrobialdiversityintheseuniqueenvironments.Totestthishypothesis,wehaveconductedadirectcomparisonofthetaxonomiccoverageandpotentialbiasesofthetwoprimersetsin37fieldsamplescollectedfromvariousenvironmentsoftheArcticOcean,includingsea-ice,surfaceanddeepwatercolumn,marinesnow,anddeep-seasediment.Asanindependentlineofvalidation,weperformedcellcountingoffivekeytaxonomicsubgroupsinasubsetofthefieldsamplesviaCARD-FISH(catalyzedreporterdeposition-fluorescenceinsituhybridization). MaterialsandMethods SampleCollection Thesamplesincludedinthisstudywerecollectedatthelong-termecologicalresearch(LTER)siteHAUSGARTENinFramStraitandthecentralArcticOcean(SupplementaryFigure1andSupplementaryTable1).Thesampleswerecollectedasfollows: •Thesea-icecoreswerecollectedusinganicecorer(9cmdiameter;KovacsEnterprise,Roseburg,OR,UnitedStates)andbrokenintosubsectionstofacilitatequickermelting.Thelower30–50cmoftheseaice(dependingontotalcorelength)wasmeltedinplasticcontainers(rinsedwithethanolandultrapurewater)at4°Cinthedark.Themeltingoftheseaicetook∼24handthesampleswereimmediatelyfilteredon0.22μmSterivexTMmembranesassoonasthelastpieceofseaicemelted.Additionalsamplesformicroscopycountswerefilteredonto0.22μmpolycarbonatemembranes(WhatmanNucleopore,Buckinghamshire,UnitedKingdom),withsterilefilteredformalinatafinalconcentrationof2%andstoredat−20°C. •Thewatersamplingwascarriedoutusing12LNiskinbottlesmountedonaCTDrosette(Sea-BirdElectronicsInc.,SBE911plusprobe,Bellevue,WA,UnitedStates)andfilteredon0.22μmSterivexTMmembranes.TheSterivexTMmembraneswerethenstoredat−20°Cuntilfurtherprocessing.Additionalsamplesformicroscopycountswerefilteredonto0.22μmpolycarbonatemembranes(WhatmanNucleopore,Buckinghamshire,UnitedKingdom),withsterilefilteredformalinatafinalconcentrationof2%andstoredat−20°C. •Thedeep-seasedimentcoreswereretrievedbyaTV-guidedmulticorer,andsubsamplesoftheuppermostcentimeterofthecoreswerecollectedwithsyringesandimmediatelystoredat−20°Cuntilfurtherprocessing. •Themarinesnowsampleswerecollectedusingsedimenttrapsofthelong-termmooringsattheLTERsiteHAUSGARTEN(Bauerfeindetal.,2009;Lalandeetal.,2013).Collectioncups(400ml)werefilledwithfilteredseawater,adjustedtoasalinityof40andpoisonedwithHgCl2(0.14%finalsolution)topreservesamplesduringdeploymentandafterrecovery(Metfiesetal.,2017).Afterrecovery,sampleswerestoredat+4°C,swimmerswereremovedandsamplesweresplitbyawetsplittingprocedure(Bodungenetal.,2013).Inthisstudy,weused1/32splitsoftheoriginaltrapsample.Sinkingparticlesfromthesedimenttrapsampleswerecollectedon0.22μmSterivexfiltersandstoredat−20°C. AllmetadataofthesamplesareaccessibleviatheDataPublisherforEarthandEnvironmentalSciencePANGAEA1,thePANGAEAeventIDsarelistedinSupplementaryTable1.SamplingmapwasproducedusingOceanDataViewv5.2.1(Schlitzer,2018). DNAIsolationand16SrRNAGeneAmpliconSequencing GenomicDNAwasisolatedinacombinedchemicalandmechanicalprocedureusingthePowerWaterDNAIsolationKitforseaice,water,andsedimenttrapsandusingthePowerSoilDNAIsolationKitforsedimentsamples(MOBIOLaboratories,Inc.,Carlsbad,CA,UnitedStates).PriortoDNAisolation,the0.22μmSterivexTMmembranecartridgesoftheseawaterandseaicesampleswerecrackedopeninordertoplacethefiltersintothekit-suppliedbeadbeatingtubes.Theisolationwascontinuedaccordingtothemanufacturer’sinstructions,andDNAwasstoredat−20°C.Librarypreparationwasperformedaccordingtothestandardinstructionsofthe16SMetagenomicSequencingLibraryPreparationprotocol(IlluminaTM,Inc.,SanDiego,CA,UnitedStates).Twodifferenthypervariableregionsofthebacterial16SrRNAgenewereamplifiedusingaliquotsoftheisolatedDNAfromeachsample.TheV3–V4regionwasamplifiedusingtheS-D-Bact-0341-b-S-17(5′-CCTACGGGNGGCWGCAG-3′)andtheS-D-Bact-0785-a-A-21(5′-GACTACHVGGGTATCTAATCC-3′)primers(Klindworthetal.,2013).TheV4–V5regionswasamplifiedusingthe515F-Y(5′-GTGYCAGCMGCCGCGGTAA-3′)andthe926R(5′-CCGYCAATTYMTTTRAGTTT-3′)primers(Paradaetal.,2016).SequenceswereobtainedontheIlluminaMiSeqTMplatformina2×300bppaired-endrunandforsurfacewatersamplesontheIlluminaHiSeqTMplatformina2×250bppaired-endrun(CeBiTec,Bielefeld,Germany),followingthestandardinstructionsofthe16SMetagenomicSequencingLibraryPreparationprotocol. Rawpaired-end,primer-trimmedreadsweredepositedintheEuropeanNucleotideArchive(ENA;Harrisonetal.,2019)underaccessionnumberPRJEB31938.ThedatawerearchivedusingthebrokerageserviceoftheGermanFederationforBiologicalData(GFBio;Diepenbroeketal.,2014). BioinformaticsandStatisticalAnalyses Therawpaired-endreadswereprimer-trimmedusingcutadapt(Martin,2011).FurtheranalyseswereconductedusingRv4.0.02inRStudiov1.2.50423.ThelibrarieswereprocessedusingDADA2v1.16(Callahanetal.,2016a),followingthesuggestedworkflow(Callahanetal.,2016b).ThereadsinMiSeqlibrariesweretruncatedat255bplengthforforwardreadsandat200bplengthforreversereads,tofacilitatethetechnicalqualitydropattheendofthereads.ReadsinbothMiSeqandHiSeqwerethentrimmedforlow-qualitybasesandmergedbasedonaminimumoverlapof10bp.Chimerasandampliconsequencevariants(ASVs)thatwereobservedinonlyonesamplewerefilteredout.TherepresentativesequencesweretaxonomicallyclassifiedagainstSILVA16SrRNAgenereferencedatabaserelease138(Quastetal.,2013;Yilmazetal.,2014).TheASVsthatweretaxonomicallyunclassifiedatphylumrankorwerenotassignedtobacterialorarchaeallineageswereexcludedfromfurtheranalysis.Furthermore,allASVsthatweretaxonomicallyassignedtomitochondriaandchloroplastwereremovedfromthedataset. SampledatamatricesweremanagedusingtheRpackage“phyloseq”v1.32(McMurdieandHolmes,2013),andplotsweregeneratedusingtheRpackage“ggplot2”v3.3.0(Gómez-Rubio,2017).ThesamplerarefactionanalyseswereconductedusingtheRpackage“iNEXT”v2.0.20(Hsiehetal.,2016).Totesttheeffectofthedifferentprimersetsonthetaxonomiccompositionofthemicrobialcommunities,aswellastotestfordifferencesbetweenmicrobialcommunitiesofdifferenttypesofsamples,atwo-waypermutationmultivariateanalysisofvariance(“Two-wayPERMANOVA”)ofJensen–ShannonDivergencedistancematrixwasconducted(usingthefunction“adonis2”intheRpackage“vegan”v.2.5.6;Oksanenetal.,2007). Scriptsforprocessingdatacanbeaccessedathttps://github.com/edfadeev/Arctic-16S-Primers-comparison/. CatalyzedReporterDepositionFluorescenceinsituHybridization Bothseaiceandseawatersamplesweredirectlyfixedin4%formalinfor4hat4°C,filteredonto0.22μmpolycarbonateTrack-EtchedTMmembranes(WhatmanNucleopore,Buckinghamshire,UnitedKingdom),andstoredat−20°C.TheCARD-FISHwasappliedbasedontheprotocolestablishedbyPernthaleretal.(2002),usinghorseradish-peroxidase(HRP)–labeledoligonucleotideprobes(4Ulm,Germany;SupplementaryTable4).AllprobeswerecheckedforspecificityandcoverageoftheirtargetgroupsagainsttheSILVA16SrRNAgenereference.Allfilterswereembeddedin0.2%low-gelling-pointagaroseandtreatedwith10mgmL–1lysozymesolution(Sigma-AldrichChemieGmbH,Hamburg,Germany)for1hat37°C.Subsequently,endogenousperoxidaseswereinactivatedbysubmergingthefilterpiecesin0.15%H2O2inmethanolfor30min,beforerinsinginMilli-Qwateranddehydrationin96%ethanol.Then,thefilterswerecoveredinahybridizationbufferandaprobeconcentrationof0.2ngμL–1.Hybridizationwasperformedat46°Cfor2.5h,followedbywashinginapre-warmedwashingbufferat48°Cfor10min,and15minin1xPBS.Signalamplificationwascarriedoutfor45minat46°Cwithanamplificationbuffercontainingeithertyramide-boundAlexa488(1μg/mL–1)orAlexa594(0.33μgmL–1).Afterward,thecellswerecounterstainedin1μg/mL–1DAPI(4′,6-diamidino-2-phenylindole;ThermoFisherScientificGmbH,Bremen,Germany)for10minat46°C.AfterrinsingwithMilli-Qwaterand96%ethanol,thefilterpieceswereembeddedina4:1mixofCitifluor(CitifluorLtd.,London,UnitedKingdom)andVectashield(VectorLaboratories,Inc.,Burlingame,UnitedStates)andstoredovernightat−20°Cforlatermicroscopyevaluation. AutomatedImageAcquisitionandCellCounting ThefilterswereevaluatedmicroscopicallyunderaZeissAxioImager.Z2stand(CarlZeissMicroImagingGmbH,Jena,Germany),equippedwithamultipurposefullyautomatedmicroscopeimagingsystem(MPISYS),aColibriLEDlightsourceilluminationsystem,andamulti-filterset62HE(CarlZeissMicroImagingGmbH,Jena,Germany).Picturesweretakenviaacooledcharged-coupled-device(CCD)camera(AxioCamMRm;CarlZeissAG,Oberkochen,Germany)witha63xoilobjective,anumericalapertureof1.4,andapixelsizeof0.1016μm/pixel,coupledtotheAxioVisionSE64Rel.4.9.1software(CarlZeissAG,Oberkochen,Germany)asdescribedbyBennkeetal.(2016).ExposuretimeswereadjustedaftermanualinspectionwiththeAxioVisionRel.4.8softwarecoupledtotheSamLoc1.7software(Zederetal.,2011),whichwasalsousedtodefinethecoordinatesofthefiltersontheslides.Forimageacquisition,channelsweredefinedwiththeMPISYSsoftware,andaminimumof55fieldsofviewwithaminimumdistanceof0.25mmwereacquiredofeachfilterpiecebyrecordingaz-stackofsevenimagesinautofocus. CellenumerationwasperformedwiththesoftwareAutomatedCellMeasuringandEnumerationTool(ACMETool3,2018-11-09;M.Zeder,TechnobiologyGmbH,Buchrain,Switzerland).CellswerecountedasobjectsaccordingtomanuallydefinedparametersseparatelyfortheDAPIandFISHchannels. ResultsandDiscussion Inthisstudy,aliquotsof37DNAsamplesfromdifferentenvironmentsintheArcticOcean(seaice,surfaceanddeepoceanwater,marinesnow,andseafloorsediment;SupplementaryTable1)weresequencedusingtwocommonprimerssetsthatamplifyeithertheV3–V4ortheV4–V5hypervariableregionsinthe16SrRNAgeneandweresubjectedtothesamebioinformaticworkflow.Bothprimersetsshowedasimilardecreaseinthenumberofsequencesthroughouttheworkflow,with62±13%and68±9%ofsequencesretainedpersample,respectively.Thefinaldatasetsconsistedof3,318,649sequencesintheV3–V4datasetthatwereassignedto12,045ASVsand3,340,628sequencesintheV4–V5datasetthatwereassignedto14,505ASVs(SupplementaryTable2).Inaddition,theASVswhichweretaxonomicallyassignedtoeukaryotic,mitochondrialorchloroplastsequences,aswellasASVsunclassifiedatphylumrank,werealsoremovedfromfurtheranalysis(ca.9%andca.17%ofsequencesinV3–V4andV4–V5datasets,respectively).Inbothdatasets,anasymptoticextrapolationoftherarefactioncurvesdidnotfurtherincreasethenumberofobservedASVs(SupplementaryFigure2).Although,mostlikelyfurthermicrobialdiversityremainstobeuncoveredinallsampledenvironments,therarefactioncurvessuggestthatoursamplescontainedmostofthepotentialcommunityrichnesscoveredbybothprimersets.Inseaice,surfacewater(<30mdepth)andmarinesnow,bothprimersetsshowedsimilarcommunityrichness(Figure1).However,inthedeep-watercommunities(>600mdepth),richnesswassignificantlydifferentbetweentheprimersets(WilcoxonSigned-RankTest;p<0.01),withca.40%morebacterialASVsintheV3–V4.Incontrast,thesedimentcommunityrichnesswassignificantlyhigherintheV4–V5dataset(Wilcoxonsigned-ranktest;p<0.01),withuptodoubletheamountofbacterialASVscomparedtotheV3–V4dataset.Themaintaxonomicgroups,typicallyobservedintheArcticmarineenvironment,suchastheclassesAlphaproteobacteria,Bacteroidia,andGammaproteobacteria,dominatedbothdatasets(eachcomprising10–30%ofsequencesinV3–V4andV4–V4datasets,respectively).However,withinthesegroupssignificantdifferencesbetweendatasetsinthenumberofobservedASVsweredetected. FIGURE1 Figure1.Chao1richnessestimatesinthedifferentsampletypes.Differentprimersetsrepresentedbycolorsandshapes.Pleasenotethedifferencesofy-axisbetweenthepanels. IntheV3–V4dataset,theBacteroidiaandGammaproteobacteriashowedthehighestdifferencesinnumberofobservedASVswithineachclass(i.e.,typerichness)comparedtotheV4–V5dataset(SupplementaryTable2).ThefamilyFlavobacteriaceae(classBacteroidia)comprised18%ofallsequencesinbothdatasets;however,intheV3–V4dataset,itconsistedofonethirdmoreASVscomparedtotheV4–V5dataset(totalof278and196ASVs,respectively;Figure2).ThisdifferenceinthenumberofobservedASVswasmainlyassociatedwithASVsofthegenusPolaribacter(totalof28and14ASVs,respectively),akeyheterotrophicbacteriumthatrespondstophytoplanktonbloomsinmid-andhigh-latitudes(Gómez-Pereiraetal.,2010;Fadeevetal.,2018;Avcıetal.,2020).TheordersAlteromonadales,Cellvibrionales,andOceanospirillales(allwithintheclassGammaproteobacteria),whichcomprised4–6%ofallsequencesintheV3–V4datasetand3%ofallsequencesintheV4–V5dataset,alsoshoweddifferencesbetweendatasetsinthenumberofobservedASVs(SupplementaryTable3).EachoftheseGammaproteobacteriaorderscontainedtwotimesmoreASVsintheV3–V4dataset,comparedtotheV4–V5dataset(thelargestdifferencewasintheorderAlteromonadales,withtotalof113and49ASVs,respectively).Thesetaxonomicgroupsaretypicallyassociatedwithorganicmatterdegradation(Buchanetal.,2014),andwerepreviouslyshowntodominateseaicemicrobialcommunitiesassociatedwithalgalaggregates(Rappetal.,2018),aswellassurfacewatersduringphytoplanktonblooms(Fadeevetal.,2018).Furthermore,thefamilyWoeseiaceae(classGammaproteobacteria)alsoconsistedofca.30%moreASVsintheV3–V4dataset,comparedtotheV4–V5dataset(totalof127and98ASVs,respectively;Figure2).Thisbacterialfamilyisabundantindeep-seasedimentsaroundtheglobe,includingtheArcticOcean(Bienholdetal.,2016;Hoffmannetal.,2020). FIGURE2 Figure2.MajortaxonomicfamiliesinV3–V4andV4–V5datasets.Thex-axisrepresentsthetotalsequenceproportionofeachfamilyinV3–V4(leftpanel)andV4–V5(rightpanel)datasets.ThenumbersateachcolumnrepresentthenumberofobservedASVsaffiliatedwitheachtaxonomicfamily.Differenttaxonomicclassesarerepresentedbycolorcode.Onlyfamiliesthatcomprisedatleast1%ofsequencesinatleastoneofthedatasetswereincludedinthevisualization. ComparedtotheV3–V4dataset,theV4–V5datasetconsistedofatleastonethirdmoreASVsintheclassesPhycisphaerae(totalof206and117ASVs,respectively)andPlanctomycetes(totalof299and244ASVs,respectively).ThisdifferenceinthenumberofobservedASVswasmainlyassociatedwiththefamiliesPirellulaceaethatcomprisedca.2%ofallsequencesinbothdatasets(Figure2),aswellasPhycisphaeraceaethatcomprisedlessthan1%ofallsequences(SupplementaryTable3)inbothdatasets.ThesetaxonomicgroupshavebeenpreviouslyshowntobeassociatedwithsinkingparticlesinthedeepoceanandarealsoabundantinArcticdeep-seasediments(Fadeevetal.,2020).Furthermore,thearchaealclassNitrososphaeriawasalmostabsentfromtheV3–V4dataset,withonlyafewsequencesassociatedwithfourASVs,comparedto168ASVsintheV4–V5datasetthatcomprised7%ofthetotalsequences(Figure2).MarinemembersoftheArchaeaingeneral,andtheclassNitrososphaeriainparticular,areabundantintheArcticmarineenvironmentandcanreachuptoonefifthofthecellsinArcticmicrobialcommunities(Mülleretal.,2018;Cardozo-Minoetal.,2020).Takentogether,theseobservationssuggestthatonASVlevelthediversityofdifferenttaxonomicgroupsarecaptureddifferentlybythetwoprimersets.Thisispotentiallyaresultofdifferencesintheregionalhypervariabilityofthe16SrRNAgenewithindifferenttaxonomicgroups(Yangetal.,2016;Kerriganetal.,2019).Inaddition,aswaspreviouslyshownforvarioustaxonomicgroups,suchastheSAR11clade,differencesincaptureddiversitymayoccuralsoduetospecificitydifferencesoftheprimersetstothetargeted16SrRNAgeneregion(Paradaetal.,2016). DespitetheobserveddifferencesonanASVlevel,theoveralltaxonomiccompositionwasconsistentbetweenthedatasets(Figure3).Sampledseaice,surfacewater,andmarinesnowcommunitiesweredominatedbyheterotrophicbacteriaoftheclassesBacteroidia(mainlythegenusPolaribacter)andGammaproteobacteria(mainlythegeneraintheorderAlteromonadales),withequivalentrelativesequenceabundancestothosedescribedinpreviousreports(Bowmanetal.,2012;Eronen-Rasimusetal.,2016;Hatametal.,2016;Wilsonetal.,2017;Fadeevetal.,2018,2020;Rappetal.,2018).Atdepth,pelagiccommunitiesweredominatedbysequencesoftheclassAlphaproteobacteria,SAR324clade,andthearchaealclassNitrososphaeria,allofwhichwerepreviouslyobservedtodominatedeepArcticwaters,aswellassurfacecommunitiesduringtheArcticwinter(Wilsonetal.,2017;Fadeevetal.,2020).Thesedimentcommunities,whichhavepreviouslybeenshowntoharborthehighesttaxonomicdiversityamongthedescribedArcticenvironmentsbyfar(Bienholdetal.,2012;Hoffmannetal.,2017;Rappetal.,2018),weredominatedinsequenceabundanceofGammaproteobacteria. FIGURE3 Figure3.Taxonomiccompositionsofthemicrobialcommunities.Differenttaxonomicclassesarerepresentedbycolorcode.Classeswithsequenceproportionbelow2%wereclassifiedas“Othertaxa”. Inordertocomparethedifferencesinrepresentationoftaxonomicgroupsbetweentheprimersets,wecombinedsequenceabundancesofallASVsaccordingtotheirtaxonomicaffiliationatgenusrank(i.e.,thehighestpossiblesharedbetweenthedatasetstaxonomicresolution).IntheV3–V4dataset,theASVsweremergedinto306differentgeneraand279lineagesthatwereaffiliatedtohighertaxonomicranks(i.e.,wereunclassifiedonagenusrank).IntheV4–V5dataset,theASVsweremergedinto280differentgeneraand299lineagesthatwereaffiliatedtohighertaxonomicranks.Overall,489(72%ofthetotal)lineageswereobservedinbothdatasetsatthisleveloftaxonomicresolution.IntheV3–V4datasettherewere96(14%ofthetotal)lineagesthatwereabsentfromtheV4–V5dataset,buttogethertheycomprisedlessthan1%ofthesequencesintheV3–V4dataset.Ontheotherhand,intheV4–V5datasettherewere90(13%ofthetotal)lineagesthatwereabsentfromtheV3–V4dataset,andtogethertheycomprised5%ofthesequencesintheV4–V5dataset.Inaddition,thedissimilarityofcommunitycompositionsinmergedV3–V4andV4–V5datasetsrevealedconsistentandsignificantdifferencebetweenthemicrobiomescapturedbybothprimersets(Two-wayPERMANOVAtest;F4,64=86.29,R2=0.83,pvalue<0.001;Figure4).Onlyasmallfractionofthetotalvariancewasassociatedwiththedifferencebetweentheprimersets(Two-wayPERMANOVAtest;F1,64=7.59,R2=0.02,pvalue<0.001).Nosignificantcombinedeffectofdifferentprimersetsondifferentsampletypeswasobserved(Two-wayPERMANOVAtest;pvalue>0.05).Takentogether,theseresultsconfirmthat,eventhoughtheprimersetsshoweddifferentsensitivitytodiversityattheASVlevel,bothofthemreflectsimilartaxonomiccompositiondowntothegenusrank. FIGURE4 Figure4.Non-metricMulti-dimensionalScaling(NMDS)ofthemicrobialcommunitiesinmergedV3–V4andV4–V5datasets,basedonJensen-ShannonDivergence.Thedifferenttypesofsamplesarerepresentedbycolors,andtheprimersetarerepresentedbyshapes.Ellipsesencompassclusteringofeachmicrobiometypewithnormalconfidenceof0.95. TheresearchattheFRAMMicrobialObservatoryisfocusedontheseasonalandinterannualdynamicsoftheArcticOceanassociatedwithchangesinseaiceextentandprimaryproductioninthesurfaceocean(e.g.,Metfiesetal.,2017;Fadeevetal.,2018,2020).Tofurtherevaluatetheperformanceofthetwoprimersetsintheselong-termmonitoredenvironments,wecomparedthesequencerepresentationofselectedtaxonomicgroups,whichareassociatedwithdistinctstagesofseasonaldynamics(Fadeevetal.,2018),tomicroscopicallycountedcellsusingCARD-FISHcombinedwithanautomatedimageacquisition(Cardozo-Minoetal.,2020).Fluorescenceinsituhybridizationtechniqueshavetheadvantageofprovidingabsoluteabundancesof(viable)cellsthatcanbedirectlycomparedbetweensamples.InmicroscopycountsofbothseaiceandsurfacewatercommunitiesthehighestobservedcellabundancewasoftheclassBacteroidia(upto35and26%ofthetotalmicrobialcommunity,respectively),whichwasconsistentwiththerepresentationofthistaxonomicgroupbybothprimersets.Insurfacewatercommunities,highlevelsofconsistencybetweenthemicroscopycountsandbothprimersetswereobservedalsointherepresentationofAlteromonadalesandPolaribacter(Table1).Ontheotherhand,therepresentation,bybothprimersets,oftheclassGammaproteobacteriainseaiceandsurfacewatercommunitieswas2–4timeshigherincomparisontotheproportionobservedinmicroscopycounts(upto9and18%,respectively).Incontrast,theproportionalabundanceoftheSAR11cladewas5–10timeshigherinthemicroscopycounts,comparedtoitsrepresentationbybothprimersets(Table1).Ourresultssuggestthatatleastforsometaxonomicgroups(i.e.,Polaribacter),bothprimersetsmayprovideaconsistentsemi-quantitativerepresentation.However,microscopyresultsmustbeinterpretedunderseveralmethodologicalcaveats,knowingthatlowcellularribosomecontentorlowefficiencyoftheprobemayaltertherepresentationofindividualtaxainourcellcounts(AmannandFuchs,2008).Therefore,theobservedinconsistencyintherepresentationofsometaxonomicgroups(i.e.,SAR11clade)mayalsoresultfromtheselimitations.Inordertofurtherinvestigatethequantitativeperformanceoftheprimersets,furtherinvestigation,usingtechniquessuchasmockcommunities(Yehetal.,2019)ormetagenomics(McNicholetal.,2020),isrequired. TABLE1 Table1.Overviewofcellabundancesandsequenceproportionsrangeinselectedtaxonomicgroups. ConcludingRemarks TounderstandthelinksbetweentherapidenvironmentalchangesintheArcticregionandthedynamicsofmicrobialcommunitiesintheArcticOcean,thereisaneedforrobustmethodsaddressingchangesindiversityandrelativeabundance.Inordertoconductsuchobservationsusinga16SrRNAgenetag-sequencingapproach,optimallyasimilarextractionmethodandasinglePCRprimersetshouldbeselected,whichcanbeappliedtoallenvironmentsoftheArcticOcean(seaice,watercolumn,anddeep-seasediment).Themostsuitableprimersetfor16SrRNAamplificationandsequencingfromenvironmentalsamplesshouldproducehigh-qualityampliconlibrariesandcoverwithminimumbiasesthevarietyofpresentorganisms,aswellastheirrelativeabundances.Wehavefoundthatatalltaxonomicranksdowntogenus,bothprimersetsrepresenttheoverallrichnessofthemajorbacterialtaxonomicgroupsatcomparablelevelsacrossthedifferentArcticOceanbiomes.Therelativesequenceabundanceofsomedominanttaxonomicgroups,suchasthePolaribacter,correspondswiththeirproportionalrepresentationviamicroscopiccellcounts.OthertaxonomicgroupssuchastheSAR11cladestronglydifferbetweenthemolecularandthemicroscopicalrepresentations.However,thisdiscrepancymaybeduetolimitationsofthemicroscopicalquantification.OnanASVlevel,bothprimersetscapturethediversitywithinthemostabundanttaxonomicgroupsdifferently,andthus,theuseofeachprimersetmaydependonthetargetgroups.However,themainadvantageoftheV4–V5primersetisitsadditionalcoverageofthearchaealdomain,withoutcompromisingthedetectionofothertaxonomicgroups.MembersoftheArchaeacompriseasubstantialfractionofArcticmarinemicrobialcommunities,particularlyduringthedarkseasonandindeepwaters.Thus,giventhedemonstratedsimilaritiesanddifferences,weendorsetheuseoftheV4–V5primersetforcapturingcomprehensiveinsightsintomicrobialcommunitydynamicsoftheArcticmarineenvironment. DataAvailabilityStatement Thedatasetspresentedinthisstudycanbefoundinonlinerepositories.Thenamesoftherepository/repositoriesandaccessionnumber(s)canbefoundinthearticle/SupplementaryMaterial. AuthorContributions EFandABdesignedthestudy.CB,IS,MM,andJRprovidedtheenvironmentalsamplesforthestudy.HTconductedthesequencingofthesamples.MC-MandVS-CconductedtheCARD-FISHcounts.EFanalyzedthedataandwrotethemanuscript.Allauthorscontributedtothefinalversionofthemanuscript. Funding ThisworkwasconductedintheframeworkoftheHGFInfrastructureProgramFRAMoftheAlfred-Wegener-InstituteHelmholtzCenterforPolarandMarineResearch.TheprojecthasreceivedfundingfromtheEuropeanResearchCouncil(ERC)undertheEuropeanUnion’sSeventhFrameworkProgram(FP7/2007-2013)researchprojectABYSS(grantagreementno.294757)awardedtoAB.AdditionalfundingcamefromtheAustrianScienceFund(FWF)M-2797toEF.ThispublicationisEprintID53010oftheAlfredWegenerInstituteforPolarandMarineResearch,Bremerhaven,Germany. ConflictofInterest Theauthorsdeclarethattheresearchwasconductedintheabsenceofanycommercialorfinancialrelationshipsthatcouldbeconstruedasapotentialconflictofinterest. Acknowledgments WethankDanielSherforacriticalreviewofthemanuscript.WewouldalsoliketothankJanaBäger,JakobBarz,andTheresaHargesheimerforDNAextractionsandlibrarypreparations. 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GoogleScholar Keywords:microbialcommunities,ampliconsequencing,methodcomparison,universalprimers,ArcticOcean,molecularobservatory Citation:FadeevE,Cardozo-MinoMG,RappJZ,BienholdC,SalterI,Salman-CarvalhoV,MolariM,TegetmeyerHE,ButtigiegPLandBoetiusA(2021)ComparisonofTwo16SrRNAPrimers(V3–V4andV4–V5)forStudiesofArcticMicrobialCommunities.Front.Microbiol.12:637526.doi:10.3389/fmicb.2021.637526 Received:03December2020;Accepted:28January2021;Published:16February2021. Editedby: CatarinaMagalhães,UniversityofPorto,Portugal Reviewedby: MiguelSemedo,UniversityofPorto,Portugal AlessandroVezzi,UniversityofPadua,Italy LiseØvreås,UniversityofBergen,Norway Copyright©2021Fadeev,Cardozo-Mino,Rapp,Bienhold,Salter,Salman-Carvalho,Molari,Tegetmeyer,ButtigiegandBoetius.Thisisanopen-accessarticledistributedunderthetermsoftheCreativeCommonsAttributionLicense(CCBY).Theuse,distributionorreproductioninotherforumsispermitted,providedtheoriginalauthor(s)andthecopyrightowner(s)arecreditedandthattheoriginalpublicationinthisjournaliscited,inaccordancewithacceptedacademicpractice.Nouse,distributionorreproductionispermittedwhichdoesnotcomplywiththeseterms. *Correspondence:EduardFadeev,[email protected] †Presentaddress:EduardFadeev,DepartmentofFunctionalandEvolutionaryEcology,UniversityofVienna,Vienna,Austria COMMENTARY ORIGINALARTICLE Peoplealsolookedat SuggestaResearchTopic>