GEOGRAPHICINFLUENCESONTHESKINMICROBIOMEOFHUMPBACKWHALES

By

KevinCharles(KC)BierlchDr.DaveJohnston,DukeUniversityMarineLab

Dr.AmyApprill,WoodsHoleOceanographicInstituteApril21,2016

Mastersprojectsubmittedinpartialfulfillmentofthe

requirementsfortheMasterofEnvironmentalManagementdegreeintheNicholasSchooloftheEnvironmentof

DukeUniversity

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ExecutiveSummary

Assessing thehealth stateofwildmarinemammalsand theirpopulations is challenging, and

thereisagrowingneedtodevelopreliableproxiesforhealthdetermination.Climatechangeandother

anthropogenicfactorsareinfluencingdiseaseprevalenceandvirulenceinthemarineenvironmentand

thereisaneedtoimprovetoolsandtechniquesformonitoringthehealthstatusofwildmarinemammals

thatarelistedasthreatenedorendangered.

Theskinisthelargestmammalianorganandservesasthefirstlineofdefensebetweenthehost

andtheirexternalenvironment.Mostresearchhasfocusedonhumanhealthandhasfoundthattheskin

microbiomecanserveasaprotectivemechanismbyaddingtotheskin’sdefenseagainstcolonizationof

potentialpathogenicbacteria.Theskinisrelativelywell-sampledinmarinemammalsandmayserveas

ausefulproxyforhealthstatus,asdemonstratedinhumans.However,beforeskinmicrobiomesbecome

useful health diagnostic tools for marine mammals, more information is needed about the factors

influencingvariabilitywithintheskinmicrobialcommunity.

I analyzed the skin microbiome of 72 apparently healthy humpback whales primarily from

Antarctica,aswellasAlaska,Hawaii,AmericanSamoa,andtheGulfofMaine.Phylogeneticandstatistical

analysesrevealedtwodominantfamiliesofbacteria(MoraxellaceaeandFlavobacteriaceae)foundon

each individualwhale.However, thereweresignificantdifferences in theskinmicrobiomesamongst

whales fromdifferent geographic areas, both globally aswell as amongst regionswithin Antarctica.

Thesefindingsprovidesupportthatthereisaspecies-specificmicrobiomeonhumpbackskinthatvaries

accordingtogeographicfactors.Thisinitialcharacterizationofthehealthyhumpbackskinmicrobiome

in Antarctica is helpful for future health diagnostic efforts aimed especially at heath-compromised

animals.Thisresearchultimatelyaimstobethebuildingblocksforexploringhowtheskinmicrobiome

canbeusedasadiagnostictoolformonitoringmarinemammalhealth.

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Introduction

Climatechangeisinfluencingdiseaseinthemarineenvironment(Burgeetal.2014).Withmany

speciesandpopulationsofmarinemammalslistedasthreatenedand/orendangeredundertheIUCN

RedListandtheEndangeredSpeciesAct,weneedtoimproveourtoolsandtechniquesformonitoring

thehealthstatusofindividualsandtheirwildpopulations.Mostofthehealthinformationwehaveon

infectious diseases in wild populations is gained from photographs and stranded marine mammals

(ThompsonandHammond,1992;Pettisetal.,2004;Wellsetal.,2004).Thesemethodsprovidealimited

glimpse into the current health state of the animal, and there is a need to develop better health

diagnostictoolsfortheseanimals.Recently,theskinmicrobiomeofhumpbackwhaleswasshownto

contain a core group of bacteria, and that shifts in this core group, as well as the emergence of

pathogens, were correlated with severe shifts in health status (Apprill et al. 2014). While marine

mammals,andtheecosystemstheyinhabit,arecurrentlyexperiencingthreatsfromclimatechange,it

isnecessarytounderstandmoreabouttheskinmicrobiomeanditspotentialuseasadiagnostictoolfor

monitoringthreatenedandendangeredmarinemammals(EvansandBjørge2013;Burgeetal.2014;

McFall-Ngaietal.2013;Apprilletal.2014).

Theskinisthelargestmammalianorganandservesasthefirstlineofdefensebetweenthehost

andtheirexternalenvironment(MoutonandBoth2012;Mahmudetal.2012).Thetermmicrobiome

refers to a specific assemblage of microorganisms, and the microbiome of the skin can serve as a

protective mechanism by adding to the skin’s defense against colonization of potential pathogenic

bacteria(Cogenetal.2010;RothandJames1988).Mostresearchontheskinmicrobiomehasfocused

onhumansanditislessexploredinothermammals(GriceandSegre2011;Fredricks2001;Larsenetal.

2010). Therefore, there is a need to explore the skin microbiomes of other mammalian species,

particularlymarinemammalsbecausetheirskinisconstantlyincontactwithseawater,whichtypically

containsordersofmagnitudemoremicroorganismsthaninair(Bowersetal.2012;DeLongetal.1999).

Humpback whales (Megaptera novaeanglia) are a particularly interesting species to study

because they are found in every ocean and undergo the longest knownmigration of anymammal

(Jacksonetal.2014).Humpbackwhalesmigratethousandsofkilometersbetweenhighlatitudesummer

feedinggroundsandlowlatitudewinterbreedinggrounds,thusexposingtheirskintoawidevarietyof

oceanic environments (Baker et al. 1990; Johnson andWolman 1984). The humpbackwhale is also

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recoveringfromoverexploitationbycommercialwhalingduringthe20thcentury(Johnstonetal.2012).

Climate change may be posing a new threat to this recovery, as the number of infectious disease

outbreaksisexpectedtoincreaseinthemarineenvironment(Burgeetal.2014).Thus,understanding

themicrobialcommunityontheskinmayhelpprovidesomeinsightformonitoringthehealthstatusof

thisrecoveringpopulation.

Arecentstudyanalyzed56humpbackwhaleskinsamplesfromtheNorthPacific,SouthPacific,

andNorthAtlanticOceansandfoundgeographic-relateddifferencesincommunityabundance,butwith

acommonalityofcoremembersofbacteriawithinthiscommunitythatwasindependentofageorsex

(Apprilletal.2014).Thiscoregroupofbacteriamayhelpserveasawayformonitoringthehealthstatus

ofthisrecoveringpopulation.Here,weexpanduponthisresearchandanalyzethemicrobiomeof72

humpbackwhaleskinsamplesfromAntarctica,apreviouslyunstudiedportionofthegeographicrange

ofhumpbackwhales,andcomparethesecommunitiestoasubsetofskinfromhumpbacksresidingin

Alaska,Hawaii,AmericanSamoa,andtheGulfofMaine.Humpbacks intheseregionsareexposedto

differentenvironmental conditionsandexhibitdifferentbehaviorswithin these regions thatmaybe

contributingtodifferencesinthecommunityabundance.Thegoalofthisstudywastodetermineifthere

isacommonalityinthemicrobialcommunitybetweenhumpbackwhalesinthesediversehabitats.This

researchultimatelyaimstobethebuildingblocksforexploringhowtheskinmicrobiomecanbeusedas

adiagnostictoolformonitoringmarinemammalhealth.

Methods

EthicsStatement

SkinsamplesfromAlaska,Hawaii,AmericanSamoa,andtheGulfofMainewerecollectedunder

NOAA permits, #1000-1617, 1071-1770-00, 774-1714, 932-1489, 633-1778, 633-1778, and with the

approvalfromtheGovernmentofAmericanSamoa.SkinsamplesfromAntarcticawerecollectedunder

NOAApermit808-735andACApermit2009-14.Allofthesampleswerecollectedinaccordancewith

permitguidelines.

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Samples

Atotalof72skinsampleswerecollectedin5differentgeographicregionsthroughouttheworld

andarelistedinTable1.

Table1.Descriptionofskinsamplesexaminedformicrobiomes

Geographiclocation Yearcollected Behavior Numberofsamples

SoutheastAlaska Summer2009 Feeding 2

Hawaii Winter2007,2008 Breeding 4

AmericanSamoa Winter2009 Breeding 2

GulfofMaine Summer2009 Feeding 3

AntarcticPeninsula Summer2010,2013 Feeding 61

SkinsampleswerecollectedfromAntarcticaandHawaiiviabiopsytechniquesusingcrossbows

equippedwithcustommadefloatingboltsandscrew-onhollowpointbiopsyplugstoobtainapieceof

skinfromtheupperflanknearthedorsalfinoftheanimal.Theseboltsaredesignedtopenetratethe

skintotheendoftheplug(0.5or1inch)andbouncebackout,securingasample(Thieleetal.2003).

Steriletoolswereusedtoretrievetheskinsample,whichwereeasilyseenbythefloatingbolt.Allofthe

skin samples fromAlaska andGulf ofMainewere collected from freshly sloughed skin. Of the two

samples fromAmericanSamoa,oneof themwascollectedvia thesebiopsytechniques listedabove,

whiletheotherwasfromsloughedskin.Marinemammalsundergosheddingofthesurfaceepidermis

quiterapidlyandthisskinisthereforeonlyslightlyolderthanbiopsiedskin(MoutonandBoth2012).We

collectedsloughedskinsamplesusingskinnetsandsieves,whichwereonlyindirectcontactwiththe

skinforamatterofseconds,andwerethenrinsedwithseawater.Weplacedcollectedsamplesonice

fornomorethan10hoursbeforefreezingthemat-80°C.Oneskinsample,ENT1a,wascollectedfrom

anentangledwhaleinHawaii.

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DNAExtraction,Amplification,andSequencing

DNAwas extracted from 1-30mg of skin,with an average of 13mg, from each sample using

QiagenDNeasyTissueKit(Cat.#69504)andquantifiedusingtheInvitrogenQubit®2.0AssayFluorometer

(LifeTechnologies,Beverly,Ma,USA).TheV4regionoftheSSUrRNAgenewasamplifiedusingbarcoded

primers(515FBand806RB)(Caporasoetal.2011;Apprilletal.2015;Paradaetal.,2015).Sampleswere

amplified in triplicate using polymerase chain reaction on a S1000® Thermal Cycler (Bio-Rad

Laboratories,Hercules,Ca,USA)asfollows:for30-35cyclesstartingwiththelidat105˚Candthen2min

95˚C,20sec95˚C,15sec55˚C,5min72˚C,andthen10minof72˚C.TriplicatePCRreactionscontained

1µLDNAsolutioncontainingof0.5xGoTaqflexibuffer,14.75µLH2O,2.5µLofa25nMMgCl2solution,

200nMofeachdNTPs,and0.25µLofa5u/µLGoTaqDNApolymerasesolutionpersample,alongwith

200nMofeachprimer.AfterPCRreaction,amplificationwasassessedbymixing5µLofeachsample

with1µLof10,000xSybrSafeDyeandrunningthisona1%/1xTBEBufferDilutiongel.Thereplicate

reactionswerepurifiedusingAgencourt®AMPure®XP(BeckmanCoulterInc.,Pasadena,Ca,USA)and

quantifiedusing InvitrogenQubit®2.0AssayFluorometer.Barcodedampliconsweresequencedusing

pairedend2x250bpMiSeqIlluminaformatattheUniversityofIllinoisW.M.KeckCenterforComparative

andFunctionalGenomicsforsequencing.

SequenceProcessing

Thesequenceswereprocessedusingmothurv.1.36.1(Schlossetal.2009).Barcodesandprimers

werefirstremoved,whichresultedwith4,139,807remainingsequencesthathadanaveragelengthof

253basepairs(bp).TheSilvaribosomalRNAsequencedatabase(v.123)alignmenttemplate(Pruesseet

al. 2007)wasused toalign sequences to the16S rRNAmolecule. Sequences thatwere identifiedas

Eukaryota,chloroplasts,mitochondria,“unknown”phylum,orasgroupswith<20,000sequenceswere

removed.Thisprocessreducedthetotalnumberofsequencesto3,913,100,withanaveragelengthof

253bp.Chimerasweredetectedandremoved,furtherreducingthenumberofsequencesto3,893,275.

ThesequenceswerethenclusteredusingMinimumEntropyDecomposition(MED)nodes.MEDapplies

shannonentropyandusestheinformation-richnucleotidepositionsacrossreadstoiterativelypartition

largedatasetswhileomittingstochasticvariation(Erenetal.2015).MEDnodesprovideamoreefficient

wayforgroupingsequencesintohomogeneousoperationaltaxonomicunits(OTUs)andwillbereferred

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to as “OTUs” for the remainder of this study. The final dataset contained 3,528,790 sequences

categorizedinto212“MEDnodes”,orOTUs.

StatisticalAnalysis

Usingmothur,thealphadiversityoftheskinmicrobialcommunitywasanalyzedbycomputing

observedOTUs,Chao’sSpeciesRichnessEstimator,Shannon’s(H’)DiversityIndex,andInverseSimpson’s

DiversityIndex,andthencomparedsamplelocationsusingANOVAfromthestatspackageinR.Both

Shannon’s and Simpson’s Diversity Indicesmeasure species richness and evenness in a community,

where Chao’s Species Richness Estimator outputs the number of taxa that likely would have been

observedatadeepersamplinglevel.Becausetherangeofsamplesizesforalllocationswassovariable

(nmin,max=1-12),withmostlocationshavingasamplesizelessthan5,moststatisticalprocessesfocused

onsixAntarcticalocationsthathadasamplesizegreaterorequalthan5(AndvordBay:10,FlandresBay:

5,GerlacheStrait:9,MargueriteBay:10,PalmerStation:5,andWilheminaBay:12).Figure1showsa

mapoftheselocationsandFigure2showsthemonthandyearthatbiopsysampleswerecollected.

PRIMERv.7(PRIMER-ELtd.,PlymouthUK)(ClarkandWarwick2001)wasusedtoassessbeta

diversity, or between sample comparisons, of the skinmicrobial community. TheMED nodes were

squareroottransformedandassembledintoadistancematrixusingBray-Curtissimilarity.Sampleswere

arrangedinpredefinedfactors;“Antarctica/non-Antarctica”,“Population”,“Location”,and“Sex”.These

factors were explored using nonmetric multidimensional scaling (nMDS) ordination to create a 2-

demnsional representation of the microbial community and with hierarchical clustering analysis

(CLUSTER) to create similaritydendograms.PERMANOVA tests inPRIMERv.7wereused for testing

significant differences between the composition of the microbial communities and the pre-defined

factorsusingaBray-Curtissimilaritymatrixwith999permutationsunderTypeIII(partial)sumofsquares,

withsignificantlevelsconfirmedusingaMonteCarlosimulation.

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Figure1.MapdisplayssamplelocationforthesixAntarcticalocationscontaining≥5skinbiopsysamples.Greenbox indicatesMarguerite Bay location and the red box indicates the location of Andvord Bay, Flandres Bay,GerlacheStrait,PalmerStation,andWilheminaBay.Notethatsomesampleshadthesamelongitudeandlatituderecordedandthushavelessthan5pointsdisplayed,i.e.PalmerStation,FlandresBay.

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Figure2.MapdisplaysmonthandyearofsamplecollectionforthesixAntarcticalocationscontaining≥5skinbiopsysamples.GreenboxindicatesMargueriteBaylocationandtheredboxindicatesthelocationofAndvordBay,FlandresBay,GerlacheStrait,PalmerStation,andWilheminaBay.Notethatsomesampleshadthesamelongitudeandlatituderecordedandthushavelessthan5pointsdisplayed,i.e.PalmerStation,FlandresBay.

Results Anonmetricmultidimensionalscaling(nMDS)analysisanddendogramclusteringanalysisofSSU

rRNAgenes frombacteriaandarchaeacomparedusingtheBray-Curtissimilarity indexrevealedthat

Antarcticasamplesaregroupedseparatelyfromsamplesobtainedfromtheothergeographiclocations

(Figure 3a&b). PERMANOVA analysis confirmed that skin microbiomes were significantly different

betweentheAntarcticaandnon-Antarcticawhales(Table2).Althoughsamplesizeswerelowforthe

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non-Antarcticregions,theAntarcticskinmicrobiomeswerefoundtobethemostdistinctfromtheother

geographicregions(Table3).ThenMDSanalysisforsexbetweenalllocationsshowednodistinctpattern,

andthePERMANOVAanalysisdidnotrevealasignificantdifferencebetweenanimalsofdifferentsex

(Figure4,Table2).

Figure3.a)NonmetricMultidemensionalScaling(nMDS)analysisandb)adendogramclusteranalysisofskinmicrobiomesamplesfromthedifferentpopulations.

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TherelationshipbetweenthehumpbackskinmicrobiomeandspecificlocationswithinAntarctica

wasexaminedfurther.AnMDSordinationshowsaslightgroupingpatternamongstthesixAntarctica

locationswith≥5samples(Figure6).Additionally,PERMANOVAanalysisrevealedsignificantdifference

betweenthesesixlocations(Table5).GerlacheStraitwassignificantlydifferentfromtherestofthefive

locationsexceptforFlandersBay,whileFlandersBaywasonlysignificantlydifferentthanMarguerite

Bay (Table 5).Marguerite Baywas significantly different fromall five other locations except Palmer

Station(Table5),whilePalmerStationwassignificantlydifferentthanGerlacheStraitandAndvordBay

(Table5).AndvordBayissignificantlydifferentthanalllocationsexceptFlandersBayandWilheminaBay

(Table5).WilheminaBaywassignificantlydifferentfromGerlacheStraitandMargueriteBay(Table5).

Nosignificantdifferencewasdetectedbetweencommunityrichness (measuredwithobserved

OTUs)andlocationsforallsamples(F9,41=0.8,p=0.618).Whenlookingfurtherintothedifferentlocations

withinAntarctica,therewasnosignificantdifferencebetweencommunityrichnessandthesixAntarctic

locationswith≥5samples,althoughthep-valuewasjustabove0.05(F4,45=2.331,p=0.0577)(Table4).

Antarcticavs.Non-Antarctic allsamples 1 19881 8.7221 0.001*** 0.001***Globalregions allsamples 4 29713 3.324 0.001*** 0.001***Antarcticlocations samplesize≥5 15 70096 2.3933 0.001*** 0.001***Sex(m,f,u) allsamples 2 7006.3 1.4018 0.131 0.13***p≤0.001

Table2. PERMANOVAresultsexaminingtheimpactofAntarcticaandnon-Antarcticasamples,globalpopulations,Antarcticalocations,andsexontheskinmicrobiome(u=unknown)

Variation Data df SS t p p(MC)

Groups t p p(MC)Antarcticavs.GulfofMaine 1.9498 0.001*** 0.004**Antarcticavs.Hawaii 1.9951 0.001*** 0.001***Antarcticavs.AmericanSamoa 2.0181 0.001*** 0.004**Antarcticavs.Alaska 1.5358 0.011 0.04*GulfofMainevs.Hawaii 1.1605 0.119 0.293GulfofMainevs.AmericanSamoa 1.6656 0.121 0.113GulfofMainevs.Alaska 1.2677 0.099 0.232Hawaiivs.AmericanSamoa 1.0174 0.529 0.415Hawaiivs.Alaska 1.2094 0.134 0.229AmericanSamoavs.Alaska 1.3346 0.351 0.273

Table3. PERMANOVAresultscomparingskinmicrobiomesbetweenthe5majorgeographicregionssampled.df=15,SS=70096,MC=MonteCarlo

*p≤0.05,**p≤0.01,***p≤0.001

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TheaverageobservedOTUrangedbetween102-128(Table4andFigure5).DiversityIndicesremained

relativelyconsistentacrossthesixlocations(Figure5).

Figure4.NonmetricMultidemensionalScaling(nMDS)analysisofskinmicrobiomesbelongingtoanimalsofdifferentsexfromAntarctica,Alaska,Hawaii,AmericanSamoa,andtheGulfofMaine.PERMANOVAresultsrevealnosignificancebetweenthesexandtheskinmicrobiomecomposition(p=0.13).

AndvordBay(10,10) 128(17) 103-156 146.94(21.85) 113.11-179.14 2.14(0.28) 5.29(2.04)FlandresBay(5,5) 107(30) 70-147 123.78(23.51) 94-149.55 2.04(0.48) 4.84(2.19)GerlacheStrait(9,9) 118(22) 87-147 144.68(27.80) 98-188.09 2.23(0.44) 5.65(2.84)

MargueriteBay(10,10) 121(16) 91-146 138.80(22.63) 114.58-178.60 1.87(0.50) 3.48(1.91)PalmerStation(5,5) 112(28) 72-143 136.60(23.59) 103.67-166 1.90(0.90) 5.25(5.29)

WilheminaBay(12,11) 102(14) 71-121 118.44(20.00) 82.67-151 2.10(0.54) 5.72(2.84)

Table4.ObservedOTUs,Chaosrichnessestimator,andtheShannonandInverseSimpsondiversityindicesfortheskinmicrobiomesfromthesixAntarcticalocationsthathave≥5skinsamples

Sample(samples,individuals)

Avg.ObservedOTUsOTURange

Chao(st.dev.) ChaoRange

Shannon(H')(st.dev.)

InverseSimpson(st.dev.)

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Figure5.BoxplotsoftheobservedMEDnodes,richness,anddiversityindicesamongsttheskinmicrobiomesfromsixAntarcticalocationswithfiveormoresamples.Nosignificantvariationwasfoundbetweeneachdiversityindexandlocation(AB=AndvordBay,FB=FlandersBay,GS=GerlacheStrait,MB=MargueriteBay,PS=PalmerStation,WB=WelheminaBay).

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Figure6.NonmetricMultidemensionalScaling(nMDS)analysisofhumpbackskinmicrobiomesfromAntarcticalocationswith≥5samples.

Groups t p p(MC)GerlacheStraitvs.WilheminaBay 1.4817 0.044 0.047*GerlacheStraitvs.FlandresBay 0.99194 0.453 0.412

GerlacheStraitvs.MargueriteBay 2.2731 0.002 0.002**GerlacheStraitvs.PalmerStation 2.0244 0.004 0.009**GerlacheStraitvs.AndvordBay 2.0531 0.002 0.002**WilheminaBayvs.FlandresBay 0.82266 0.722 0.622

WilheminaBayvs.MargueriteBay 1.6559 0.035 0.039*WilheminaBayvs.PalmerStation 1.5352 0.057 0.081WilheminaBayvs.AndvordBay 0.97911 0.403 0.395FlandresBayvs.MargueriteBay 1.6596 0.012 0.023*FlandresBayvs.PalmerStation 1.5622 0.04 0.064FlandresBayvs.AndvordBay 1.2925 0.107 0.14

MargueriteBayvs.PalmerStation 0.80539 0.758 0.648MargueriteBayvs.AndvordBay 2.0684 0.003 0.004**PalmerStationvs.AndvordBay 2.0149 0.007 0.012*

Table5. PERMANOVAresultscomparingtheskinmicrobiomesofthesixAntarcticalocationswithsamplesizesgreaterorequalto5.df=3,SS=17186,MC=MonteCarlo

*p≤0.05,**p≤0.01

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MembersoftheMoraxellaceaeandFlavobacteriaceaefamilywerethemostconsistentmembers

ofthehumpbackskinmicrobialcommunity(Table6,Figure7).Whilesequencesfromthesetwofamilies

werepresentineverysamplefromalllocations,thereisstillvariationinthepercentageofabundance

betweenlocations(Table6,Figure7).TheaverageabundanceofMoraxellaceaefoundoneachsample

from each population was 54.37, 21.61, 20.47, 30.62, and 65.79% for Antarctica, Alaska, American

Samoa,GulfofMaine,andHawaii,respectively(Table6).TheaverageabundanceofFlavobacteriaceae

foundoneachsamplefromeachlocationwas32.81,71.99,62.55,51.29,and22.66%forAntarctica,

Alaska,AmericanSamoa,GulfofMaine,andHawaii,respectively(Table6).Antarcticaexperiencedthe

greatestranges forbothfamilies,with6.89%–99.81%forMoraxacellaceaeand0.15%–75.60%for

Flavobacteriaceae(Table6).

average stdv min max average stdv min maxAndvordBay 52.84 24.93 19.96 92.19 43.09 25.77 2.14 75.60BransfieldStrait 24.56 - - - 33.78 - - -CharlotteBay 34.20 - - - 42.53 - - -FlandresBay 51.70 29.86 29.32 91.38 34.29 23.41 4.99 68.19GerlacheStrait 32.72 30.42 6.89 89.31 46.02 24.40 4.52 70.88LTERGrid 77.00 25.67 47.37 92.36 19.57 22.51 5.80 45.55MargueriteBay 72.69 30.50 18.31 99.33 21.71 27.85 0.28 75.16PalmerDeepCanyon 49.16 43.63 13.36 97.76 22.18 18.54 0.81 34.00PalmerStation 72.38 30.48 25.73 99.81 23.78 28.66 0.15 72.40Unknown 78.18 - - - 5.07 - - -WilheminaBay 46.57 27.89 11.24 98.76 34.89 22.82 0.23 61.69

54.37 30.84 6.89 99.81 32.81 25.03 0.15 75.6021.61 29.62 0.67 42.56 71.99 36.33 46.30 97.6820.47 4.83 17.05 23.88 62.55 11.15 54.66 70.4430.62 5.38 25.36 36.12 51.29 26.70 20.99 71.3965.79 21.47 37.87 86.84 22.66 19.18 0.22 42.90

Table6.Averagepercent(%)abundanceofwhaleskin-bacterialsequencescontainingMoraxellaceaeandFlavobacteriaceaeforeachlocation.Locationswithasamplesizeof1receivea"-"forstdv,min,andmax

Antarctica

Moraxellaceae Flavobacteriaceae

Antarctica

Location

Hawaii

AlaskaAmericanSamoaGulfofMaine

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Figure 7. Total abundance and taxonomic composition of bacterial sequences, classified at the family level,presentoneachhumpbackwhaleskinsample.Discussion

Phylogeneticconsistencyofthemicrobiomeandimplicationsforhealthmonitoring

Sequencesbelonging to the familiesMoraxellaceae andFlavobacteriaceaewerepresent in all

samples. A large portion of the family Moraxellaceae sequences were identified as the genus

Psychrobacter,whiletherestremainedunclassifiedatthegenuslevelunderthereferencetaxonomy

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databaseandalgorithmusedhere.Psychrobacterhasbeenfoundinmanydifferentmarineorganisms,

includingfish,sponges,seaweeds,andalgae(Pegoraroetal.2015;TeixeiraandMerquior2014).The

genusPsychrobacterhasahighlydevelopedosmotoleranceandaremostlymadeupofpsychrophilic

bacteria,meaningtheycanhandleextremelycoldtemperatures,andarethusfoundinmanynatural

coldsalineenvironments(TeixeiraandMerquior2014).Thisgenushasalsobeenfoundtothriveinwide

temperatureranges,-10to28°C(BakermansandNealson2004).Thismayhelpexplainwhytheyarea

dominant member of the microbial community because humpback whales travel between vastly

differentenvironmentswithextremelyvariedtemperatures.Little isknownabouttheecologicalrole

thisgenusplays,butitislikelythattheyplayacommensalrolewithdegradingorganiccompoundsother

than sugars (Teixeira andMerquior 2014). Flavobacteriaceae have been found in a wide range of

habitats,includingfreshwaterandmarineenvironment(BernardetandNakagawa2006).Theyhavealso

been found in diseasedmarine and freshwater fish, and have been considered to be an emergent

pathogenundervariousfishfarmingtechniques(BernardetandNakagawa2006;Pegoraroetal.2015).

It isunlikelythatFlavobacteriaceae isplayinganypathogenicroleforthesehumpbackwhales. Ithas

beenobservedthatsomeFlavobacteriaceaearebacteriolytic,andwilllysepreycellsaftersurrounding

them(Banning,Casciotti,andKujawinski2010).ThissuggeststhatFlavobacteriaceaemayhelpwardoff

infectiouspathogenicbacteria,andmaycontributetomaintainingthehealthoftheirhost.

TheconsistencyofMoraxellaceaeandFlavobacteriaceae-affiliatedmicroorganismsontheskin

ofallhumpbackwhalessuggestsaco-evolutionaryrelationshipthatmayserveasanimportanthealth

indicatorforhumpbacks.Althoughusingmicrobiomesforhealthdiagnosisisstillanemergingareaof

research,identifyingcoremicrobiomesinhealthyindividualsisoneofthekeyfactorsindevelopingthis

tool.Forexample,studieshaveshownthatchangesinresidentmicrobialcommunitieshaveinfluenced

disease such as antibiotic-associated diarrhea, human immunodeficiency virus, bacterial vaginosis,

obesity,andcardiovasculardiseaseinhumans(Rosenthaletal.,2011).

Developing a health assessment tool for cetaceans is critically important. An increase in the

numberofdifferentkindsofskinlesionsreportedoncetaceansoverthepastdecadeshasbeennoted,

with a larger number of viruses, pathogenic bacteria, and fungi associated with lesions of

immunocompromised cetaceans and of thosewith higher exposure to pollution (Mouton and Both

2012).Climatechangeisinfluencinginfectiousdiseasesinthemarineenvironmentandthenumberof

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diseasebreakouts in certain taxaareexpected to increase,basedonphysiological state (stressedor

immunocompromised)and/ormicrobialactivity(increasedgrowthandvirulence)(Burgeetal.2014).

Duetolackofdataandtheindirectnatureofclimatechangeonthesediseases,nostudieshaveshown

adefinitivecausalrelationshipbetweenclimatechangeandincreasesininfectiousdiseasesinmarine

mammals(Burgeetal.,2014).Despitethislackofdata,insightcanbegainedfromthefewexamples

available that have shown associations between climate events and infectious diseases caused by

microbialinfectionsinmarinemammals.BelowareafewexamplestakenfromBurgeetal.,2014:

• 1988:Phocinedistempervirusoutbreakinharborsealswasassociatedwith“unseasonably”

warmtemperaturesinnorthernEurope.

• 1990–1992:CetaceanmorbillivirusaffectingmultiplecetaceanspeciesintheMediterranean

wasassociatedwithhighwinter seasurface temperatures, lowrainfall, and reducedprey

availability.

• 2000: Canine distemper virus epizootic in Caspian seals was associated with warm

temperaturesandearlydisappearanceoficecoverintheCaspianSea.

It may seem unlikely that skin microbes could provide insight into something like cetacean

morbillivirus,butimbalancesordisruptionsintheskin-microbiomecanaltertheimmuneresponseof

thehostatseverallevels(ScharschmidtandFischbach2013).Alaboratorystudyfoundthatmicewith

skin disorders had an altered abundance of the core bacterial members of their skin microbiome

(Scharschmidtet al. 2009). Following thisexample, changes in coremembersofbacteria in the skin

microbiomeofhumpbackwhales,suchasMoraxellaceaeandFlavobacteriaceae,couldposeahigher

riskofattaininginfectiousdiseases.Moreresearchisneededtolookatwhatrolesthemembersofthese

bacterialcommunitiesareplaying.

Withclimatechangealteringtheoceanenvironment,itisimportanttounderstandhowdifferent

species and the ecosystems they inhabitwill be affected. Burge et al., 2014 calls formore adaptive

managementstrategiesthatincludebetterlong-termhealthandpopulationmonitoringandforecasting

toolstounderstandhowmobilevertebrateswillbeaffected.Whileadditionalresearchisneeded,the

skin-microbiomeisapotentiallyusefultoolthatwillhelpaidinassessingthepopulationstateofacertain

species.

19

VariationintheskinmicrobiomewithinAntarctica

It is interesting that while Antarctica was significantly different from the other populations,

variationstillexistsamongstthelocationssurroundingtheWesternAntarcticaPeninsula(WAP).Thisis

especially interestingbecause there is evidence that humpbackwhales donot reside in constrained

locationsalongWAPandwillmovetodifferentlocationsthroughouttheforagingseason(Curticeetal.

2015). No significant differencewas detected between the six locationswith ≥ 5 samples and their

diversity(richnessandevenness)indices,suggestingthatbehaviorandotherenvironmentalfactorsat

thelocallevelmaybeinfluencingthislocalvariation.Inhumans,ithasbeenfoundthatthereisashared

common type of bacteria found on the palms of hands, but also interpersonal variation linked to

individualhabits,evenbetweenanindividuals’dominantandnon-dominanthand(Fiereretal.2008).

Withthisspecificvariationinhumans,itisnotunreasonablethatvariationintheskinmicrobiomemay

becausedbyfactorssuchastheyearandtimeduringtheforagingseasonskinsampleswerecollected,

offshore vs. inshore location, ocean currents, behavior, close proximity to other animals, and even

freshwaterreleasedfromameltingglacier.Itisimportanttonotethatnoseawatersamplescollected

inproximitytothebiopsysiteswereanalyzedforthisstudy.However,ithasbeenshowninprevious

studies that the microbial community on humpback whale skin is significantly different than the

communitypresentinseawater(Apprilletal.2011;Apprilletal.2014)andthereforevariationinthe

skinmicrobiomeisnotattributedtocontaminationfromthesurroundingwater.

Humpbackwhalestravelthousandsofkilometersbetweenforagingandbreedingsites,andthus

needanefficientwaytoobtainandstoreenergy.Antarcticaisaprolifichotspotbecausecircumpolar

currents travel up deep canyons along the continent and bring up phytoplankton-rich waters that

support the abundance of krill (Prézelin et al. 2000). Krill are an essential part of the food web in

Antarctica,especiallyforhumpbackwhales(Curticeetal.2015).Thereisevidencethatthemovement

patternsofhumpbackwhalesreflectkrill,astheymovefromoffshoretoinshoreinAntarcticwatersover

thecourseoftheaustralsummerforagingseason,which isdefinedasJanuarytoJune(Curticeetal.

2015).Thesemovementpatternsmayhelpexplainsomeofthevariationseenbetweenthedifferent

locationswithinAntarctica.

20

Inearlysummer,krillarefoundfartherawayfromthecontinentalshelfandaggregateneardeep

water canyonswherenutrient richupwelling creates ideal conditions for themtodeposit theireggs

(Klincketal.2004;Nicol2006).Duringthelaterpartofsummerandautumn,krillmoveinshore,closer

intothebaywheretheygrouptogetherandlettheseaicecoverandprotectthemforthewinter(Nicol

2006).ThismayhelpexplainwhytheskinmicrobiomeofhumpbackwhalessampledinMargueriteBay

issignificantlydifferentfromallotherlocationsexceptPalmerStation.Allbutoneoftheskinsamples

fromMargueriteBayandPalmerStationwerecollectedduringthebeginningoftheforagingseasonin

January2013andbothlocationssitrightontopofadeepwatercanyon(Figure2).Thesamplelocations

inMargueriteBayarefartheroutsideofthebaycomparedtotheotherbaylocations(Figure1),sowe

wouldthusexpectthatasthesummermonthscontinued,thelocationsofthesewhaleswouldmove

closer towards shore. The fact that the sampleswere collected in January and in 2013may alsobe

contributingtosomeofthedifferencesweareseeing,sincealotoftheothersampleswerecollectedat

different times (Figure 2). Both Palmer Station andMarguerite Bay are also the two locationsmost

exposedtoopenocean(Figure1).TheotherfourlocationsareprotectedfromopenoceanbyAnvers

andBrabantIsland(Figure1).Acombinationoftheopenoceancurrents,deepwaterupwelling,theyear

andtimeofsamplecollection,andahighabundanceofkrillandtheireggspotentiallymaybeinfluencing

thecolonizationofthemicrobialenvironment.

WhileGerlacheStraitandFlandres,Andvord,andWelheminaBayareallprotectedfromopen

ocean,GerlacheStraitisstillsignificantlydifferentfromallotherlocationsexceptforFlandresBay.This

isparticularly interestingsincethereisoverlapbetweenGerlacheStraitsamplesandWelheminaand

AndvordBay(Figure1).Thisalsomaybeattributedtothedateandyearthesampleswerecollected.

MostofthesamplesfromGerlacheStraitandFlandersBaywerecollectedlateintheforagingseason,

MayandJune,andin2010(Figure2).Thissuggeststhateitherorbothyearandthetimeduringthe

foragingseasonmaybeinfluencingthesevariationsinthemicrobialdiversity.

Asidefromthetimeframethatsampleswerecollected,otherbehaviorandlocalenvironmental

factors may be influencing some of the variation between the Antarctic locations.Welhemina and

AndvordBaybothhavesamplesdeeperinthebaycomparedtoonesinFlandersBay,whichhasallofits

samplesrightatthemouthofthebay(Figure1).Previousstudieshavefoundthathumpbackwhales

travelingthroughGerlacheStraithaveshortresidencytimesandvariablehomeranges(Nicol2006).This

21

suggeststhatthewhalesaremostlyintransitandwillbeactivelyswimmingcomparedtowhaleswithin

baysthatfocustheiractivityonforaging(Curticeetal.2015).Sincestraitstypicallyhaveagreaterwater

velocitythanbays,wewouldexpectthesewhalesmaybeexperiencingconsistentlystrongercurrents.

Whalesforagingclosertoshoreinbaysaremostlikelyincloserproximitytootherwhalesforagingwhich

couldpotentially influencetheskin-microbialcommunityviaclosercontact.Theyalsoarefeedingon

denserkrillpatchesandaremoreexposedtofreshwaterfromthemeltingseaicedeepinthesebays,

whichcouldpossiblychangetheconditionsforthemicrobialcommunitypresent.

Thecombinationoftheyearanddateduringtheforagingseasonskinsampleswerecollected,

swimminginhighorlowvelocitywaters,beingincloseproximitytootherwhalesandgroupsofkrill,and

the increase in freshwater from melting sea ice, may all be contributing to the differences in the

colonizationofthemicrobialcommunity.

Conclusion

Thisstudysupportsthenotionthathumpbackwhalesshareacoregroupofbacteriaontheskin,

Moraxellaceae andFlavobacteriaceae. These two families of bacteriamay helpmaintain the overall

healthoftheirhost,althoughmoreresearchisneededontherolestheyareplayinginthemicrobial

community on the skin of humpback whales. Greater phylogenetic resolutionmay also help better

identifymembersofthehumpbackwhalemicrobiome.Antarcticskinsamplesharborauniquemicrobial

communitycomparedtootherlocationsaroundtheworld.Still,localvariationwithinAntarcticaseems

likelyandmaybeattributedtotheyearanddateduringtheforagingseasonskinsampleswerecollected,

swimminginhighorlowvelocitywaters,beingincloseproximitytootherwhalesandgroupsofkrill,and

exposure to salinity changes frommelting sea ice. Future studies examining specific drivers of skin

microbiomevariabilityareneeded.Overall,thisresearchservesasthepreliminarystepsforexploring

howtheskinmicrobiomecanbeusedasahealthdiagnostictool.

22

References:

Apprill,A.,S.McNally,R.Parsons,andL.Weber.2015.'MinorrevisiontoV4regionSSUrRNA806Rgeneprimergreatly increasesdetectionofSAR11bacterioplankton',AquaticMicrobialEcology,75:129-37.

Apprill,A.,T.A.Mooney,E.Lyman,A.K.Stimpert,andM.S.Rappe.2011.'Humpbackwhalesharbouracombinationofspecificandvariableskinbacteria',EnvironMicrobiolRep,3:223-32.

Apprill,A.,J.Robbins,A.M.Eren,A.A.Pack,J.Reveillaud,D.Mattila,M.Moore,M.Niemeyer,K.M.Moore, and T. J. Mincer. 2014. 'Humpback whale populations share a core skin bacterialcommunity:towardsahealthindexformarinemammals?',PLoSOne,9:e90785.

Baker, C. S., S.R. Palumbi, R.H. Lambertsen,M.T.Weinrich, J. Calambokidis, and S.J. O'Brien. 1990.'InfluenceofseasonalmigrationongeographicdistributionofmitochondrialDNAhaplotypesinhumpbackwhales',Nature,344:500.

Bakermans, C., and K. H. Nealson. 2004. 'Relationship of Critical Temperature to MacromolecularSynthesisandGrowthYieldinPsychrobactercryopegella',JournalofBacteriology,186:2340-45.

Banning,E.C.,K.L.Casciotti,andE.B.Kujawinski.2010.'Novelstrainsisolatedfromacoastalaquifersuggestapredatoryroleforflavobacteria',FEMSMicrobiolEcol,73:254-70.

Bernardet, Jean-François, and Yasuyoshi Nakagawa. 2006. 'An Introduction to the FamilyFlavobacteriaceae':455-80.

Bowers, RobertM., IanB.McCubbin, AnnaG.Hallar, andNoah Fierer. 2012. 'Seasonal variability inairbornebacterialcommunitiesatahigh-elevationsite',AtmosphericEnvironment,50:41-49.

Burge,C.A.,C.MarkEakin,C.S.Friedman,B.Froelich,P.K.Hershberger,E.E.Hofmann,L.E.Petes,K.C.Prager,E.Weil,B. L.Willis, S.E. Ford,andC.D.Harvell.2014. 'Climatechange influencesonmarineinfectiousdiseases:implicationsformanagementandsociety',AnnRevMarSci,6:249-77.

Caporaso,J.G.,C.L.Lauber,W.A.Walters,D.Berg-Lyons,C.A.Lozupone,P.J.Turnbaugh,N.Fierer,andR.Knight.2011.'Globalpatternsof16SrRNAdiversityatadepthofmillionsofsequencespersample',PNAS,108:4516-22.

Clark,K.R.,andR.M.Warwick.2001.'ChangeinMarineCommunities:AnApproachtoStatisticalAnalysisandInterpretation.',Plymouth:PRIMER-E.

Cogen,A.L.,K.Yamasaki,K.M.Sanchez,R.A.Dorschner,Y.Lai,D.T.MacLeod,J.W.Torpey,M.Otto,V.Nizet,J.E.Kim,andR.L.Gallo.2010.'Selectiveantimicrobialactionisprovidedbyphenol-soluble

23

modulins derived from Staphylococcus epidermidis, a normal resident of the skin', J InvestDermatol,130:192-200.

Curtice,C.,D.W.Johnston,H.Ducklow,N.Gales,P.N.Halpin,andA.S.Friedlaender.2015.'Modelingthe spatial and temporal dynamics of foragingmovements of humpbackwhales (Megapteranovaeangliae)intheWesternAntarcticPeninsula',MovEcol,3:13.

DeLong,E.F.,L.T.Taylor,T.L.Marsh,andC.M.Preston.1999.'VisulaizationandEnumerationofMarinePlanktonic Archaea and Bacteria by Using Polyribonucleotide Probes and Fluorescent In SituHybridization',AppliedEnvironmentalMicrobiology,65:5554-63

Eren,A.M.,H.G.Morrison,P.J.Lescault,J.Reveillaud,J.H.Vineis,andM.L.Sogin.2015.'Minimumentropydecomposition:unsupervisedoligotypingforsensitivepartitioningofhigh-throughputmarkergenesequences',ISMEJ,9:968-79.

Evans,P.G.,andA.Bjørge.2013.'Impactsofclimatechangeonmarinemammals',MCCIPScienceReview,2013:134-48.

Fierer,N.,M.Hamady,C.L.Lauber,andR.Knight.2008.'Theinfluenceofsex,handedness,andwashingonthediversityofhandsurfacebacteria',PNAS,105:17994-99.

Fredricks,D.N.2001.'Microbialecologyofhumanskininhealthanddisease',JInvestigDermatolSympProc,6:167-9.

Grice,E.A.,andJ.A.Segre.2011.'Theskinmicrobiome',NatRevMicrobiol,9:244-53.

Jackson,J.A.,D.J.Steel,P.Beerli,B.C.Congdon,C.Olavarria,M.S.Leslie,C.Pomilla,H.Rosenbaum,andC.S.Baker.2014.'Globaldiversityandoceanicdivergenceofhumpbackwhales(Megapteranovaeangliae)',ProcBiolSci,281.

Johnson, J.H., and A.A. Wolman. 1984. 'The Humpback Whale,Megaptera novaeangliae',MarineFisheriesReview,46:30-37.

Johnston,D.W.,A.S.Friedlaender,A. J.Read,andD.P.Nowacek.2012. 'Initialdensityestimatesofhumpback whales Megaptera novaeangliae in the inshore waters of the western AntarcticPeninsuladuringthelateautumn',EndangeredSpeciesResearch,18:63-71.

Klinck, JohnM., Eileen E. Hofmann, Robert C. Beardsley, Baris Salihoglu, and Susan Howard. 2004.'Water-mass properties and circulation on the west Antarctic Peninsula Continental Shelf inAustralFallandWinter2001',DeepSeaResearchPartII:TopicalStudiesinOceanography,51:1925-46.

Larsen,N.,F.K.Vogensen,F.W.vandenBerg,D.S.Nielsen,A.S.Andreasen,B.K.Pedersen,W.A.Al-Soud,S.J.Sorensen,L.H.Hansen,andM.Jakobsen.2010.'Gutmicrobiotainhumanadultswithtype2diabetesdiffersfromnon-diabeticadults',PLoSOne,5:e9085.

24

Mahmud, L., N.F. AdullManan,M.H. Ismail, and J.Mahmud. 2012. 'Characterisation of soft tissuesbiomechanical properties using 3DNumerical Approach',Business Engineering and IndustrialApplicationsColloquium(BEIAC),IEEE:801-06.

McFall-Ngai,M.,M.G.Hadfield,T.C.Bosch,H.V.Carey,T.Domazet-Loso,A.E.Douglas,N.Dubilier,G.Eberl,T.Fukami,S.F.Gilbert,U.Hentschel,N.King,S.Kjelleberg,A.H.Knoll,N.Kremer,S.K.Mazmanian,J.L.Metcalf,K.Nealson,N.E.Pierce,J.F.Rawls,A.Reid,E.G.Ruby,M.Rumpho,J.G.Sanders,D.Tautz,andJ.J.Wernegreen.2013.'Animalsinabacterialworld,anewimperativeforthelifesciences',ProcNatlAcadSciUSA,110:3229-36.

Mouton,Marnel,andAlfredBoth.2012. 'CutaneousLesions inCetaceans:An IndicatorofEcosystemStatus?'.

Nicol,Stephen.2006. 'Krill,Currents,andSea Ice:Euphausiasuperbaand ItsChangingEnvironment',BioScience,56:111.

Parada,A.E.,D.M.NeedhamandJ.A.Fuhrman(2015)."Everybasematters:assessingsmallsubunitrRNAprimersformarinemicrobiomeswithmockcommunities,timeseriesandglobalfieldsamples."EnvironMicrobiol.Pettis,H.M.,R.M.Rolland,P.K.Hamilton,S.Brault,A.R.KnowltonandS.D.Kraus(2004)."VisualhealthassessmentofNorthAtlanticrightwhales(Eubalaenaglacialis)usingphotographs."CanadianJournalofZoology82(1):8-19.Pegoraro,N.,R.Calado,L.N.Duarte,S.C.Manco,F.J.Fernandes,A.R.Polonia,D.F.Cleary,andN.C.

Gomes.2015. 'Molecularanalysisofskinbacterialassemblagesfromcodfishandpollockafterdry-saltedfishproduction',JFoodProt,78:983-9.

Prézelin,B.B.,E.E.Hofmann,C.Mangelt,andJ.M.Klinck.2000.'ThelinkagebetweenUpperCircumpolarDeep Water (UCDW) and phytoplankton assemblages on the west Antarctic Peninsulacontinentalshelf',JournalofMarineResearch,58:165-202.

Pruesse,E.,C.Quast,K.Knittel,B.M.Fuchs,W.Ludwig,J.Peplies,andF.O.Glockner.2007.'SILVA:acomprehensiveonlineresourceforqualitycheckedandalignedribosomalRNAsequencedatacompatiblewithARB',NucleicAcidsRes,35:7188-96.

Rosenthal,M.,D.Goldberg,A.Aiello,E.LarsonandB.Foxman(2011)."Skinmicrobiota:microbialcommunitystructureanditspotentialassociationwithhealthanddisease."InfectGenetEvol11(5):839-848.Roth,R.R.,andW.D.James.1988.'MicrobialEcologyoftheSkin',AnnualReviewofMicrobiology,42:

441-64.

Scharschmidt, T. C., and M. A. Fischbach. 2013. 'What Lives On Our Skin: Ecology, Genomics andTherapeuticOpportunitiesOftheSkinMicrobiome',DrugDiscovTodayDisMech,10.

25

Scharschmidt,T.C.,K.List,E.A.Grice,R.Szabo,NiscComparativeSequencingProgram,G.Renaud,C.C.Lee, T. G. Wolfsberg, T. H. Bugge, and J. A. Segre. 2009. 'Matriptase-deficient mice exhibitichthyoticskinwithaselectiveshiftinskinmicrobiota',JInvestDermatol,129:2435-42.

Schloss,P.D.,S.L.Westcott,T.Ryabin,J.R.Hall,M.Hartmann,E.B.Hollister,R.A.Lesniewski,B.B.Oakley,D.H.Parks,C.J.Robinson,J.W.Sahl,B.Stres,G.G.Thallinger,D.J.VanHorn,andC.F.Weber.2009.'Introducingmothur:open-source,platform-independent,community-supportedsoftwarefordescribingandcomparingmicrobialcommunities',ApplEnvironMicrobiol,75:7537-41.

Teixeira,LúciaMartins,andVâniaLúciaCarreiraMerquior.2014.'TheFamilyMoraxellaceae':443-76.

Thiele, D., S. Moore, J. Hildebrand, A. Sirovic, A. S. Friedlaender, D. Glasgow, R. Leaper, K. VanWaerebeek,M.McDonald,S.Wiggins,R.Pirzl,F.Viddi,andE.E.Hofmann.2003.'InternationalWhalingCommission-SouthernOceanGLOBEC/CCAMLRcollaborationCruisereport2003-2004.UnpublishedpapersubmittedtotheInternationalWhalingCommissionScientificCommittee.

Thompson,P.M.andP.S.Hammond(1992)."TheUseofPhotographytoMonitorDermalDiseaseinWildBottlenoseDolphins(Tursiopstruncatus)."Springer,RoyalSwedishAcademyofSciences21(2):135-137.Wells,R.,H.Rhinehart,L.Hansen,J.Sweeney,F.Townsend,R.Stone,D.R.Casper,M.Scott,A.HohnandT.Rowles(2004)."BottlenoseDolphinsasMarineEcosystemSentinels:DevelopingaHealthMonitoringSystem."EcoHealth1(3).

Appendix(onnextpages,26-28:

26

Samples Sex SkincollectionmethodMn_13_32d F BiopsyMn_13_32i U BiopsyMn_13_36a F BiopsyMn_13_36b F BiopsyMn_13_36d M BiopsyMn_13_36e M BiopsyMn_13_36f F BiopsyMn_13_36g F BiopsyMn_13_39b F BiopsyMn_13_47c M Biopsy

BransfieldStrait B142b M BiopsyCharlotteBay Mn_13_48f M Biopsy

B156a F BiopsyB156d M BiopsyMn_13_38a F BiopsyMn_13_38b F BiopsyMn_13_38c M BiopsyB133a F BiopsyB135b F BiopsyB135c M BiopsyB144a M BiopsyB144b M BiopsyB144c F BiopsyB151a F BiopsyB151b F BiopsyMn_13_32a F BiopsyMn_13_10a M BiopsyMn_13_10b M BiopsyMn_13_10c M BiopsyMn_13_15a F BiopsyMn_13_15c M BiopsyMn_13_15h M BiopsyMn_13_15i M BiopsyMn_13_16b M BiopsyMn_13_16d M BiopsyMn_13_16e F BiopsyMn_13_16f F BiopsyMn_13_16g M BiopsyMn_13_16h M BiopsyMn_13_30c M BiopsyMn_13_6c M BiopsyMn_13_6d F BiopsyMn_13_30d M BiopsyMn_13_30e F BiopsyMn_13_30f F BiopsyMn_13_30g F BiopsyMn_13_35b M BiopsyMn_13_52a F Biopsy

Unknown Mn_13_30a U BiopsyB139a F BiopsyB139b F BiopsyMn_13_37a F BiopsyMn_13_37b F BiopsyMn_13_37d M BiopsyMn_13_40a F BiopsyMn_13_40b M BiopsyMn_13_40m M BiopsyMn_13_42a F BiopsyMn_13_42b F BiopsyMn_60a M BiopsyMn_60b M BiopsyMn_SEAK1_a U SloughedMn_SEAK2_a U SloughedMn_FBNMS015 M SloughedMn_FBNMS016 M BiopsyMn_CCS44 U SloughedMn_CCS64a M SloughedMn_CCS93 F SloughedMn_ENT1a M SloughedfromentanglementMn_WH44 M BiopsyMn_WH45a U BiopsyMn_WH57 M Biopsy

Alaska

AmericanSamoa

GulfofMaine

Hawaii

LocationSupplementaryTable.Summaryofhumpbackwhaleskinsamplesanalyzedinthisstudy

Antarctica

AndvordBay

FlandresBay

GerlacheStrait

LTERGrid

MargueriteBay

PalmerDeepCanyon

PalmerStation

WilheminaBay

27

RCode:#KCBierlich#March,2016#AnalysisofSequenceddata#MastersProject##Checkingdistributionsread.csv("Matrix_Count_Group.groups.summary.csv",header=T)count<-read.csv("Matrix_Count_Group.groups.summary.csv",header=T)par(mfrow=c(2,2))hist(count$sobs,main="Observed")hist(count$chao,main="Chao")hist(count$invsimpson,main="invSimpson")hist(count$shannon,main="Shannon")#RelativelyNormal.invSimpsonistheleastnormalofthegroup##Checkingdistributionsofthe6Locationsdiv<-read.csv("DiversityTests.csv",header=T)par(mfrow=c(2,2))hist(div$observed,main="Observed")hist(div$chao,main="Chao")hist(div$invsimpson,main="invSimpson")hist(div$shannon,main="Shannon")#ANOVA-DiversityTestaov(lm(chao~factor(location),data=div))summary(aov(chao~factor(location),data=div))aov(lm(observed~factor(location),data=div))summary(aov(observed~factor(location),data=div))aov(lm(invsimpson~factor(location),data=div))summary(aov(invsimpson~factor(location),data=div))aov(lm(shannon~factor(location),data=div))summary(aov(shannon~factor(location),data=div))#Sonowlet'sboxplotthemobs<-read.csv("Observed.csv",header=T)chao<-read.csv("Chao.csv",header=T)simp<-read.csv("invsimpson.csv",header=T)shan<-read.csv("Shannon.csv",header=T)

28

par(mfrow=c(2,2))boxplot(obs,col="beige",#horizontal=T,main="ObservedOTUs",#xlab="",angle=-45,ylim=c(60,200),ylab="",las=1)boxplot(chao,col="beige",#horizontal=T,main="ChaoRichnessEstimate",ylim=c(60,200),ylab="",las=1)boxplot(simp,col="beige",#horizontal=T,main="Simpson'sReciprocalIndex",ylim=c(0,16),ylab="",las=1)boxplot(shan,col="beige",#horizontal=T,main="Shannon'sDiversity",#ylim=c(0,16),ylim=c(0,3.5),ylab="",las=1)#QuickExamplesofSummaryStatssummary(div$chao)sd(div$chao)