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7-2019 Host Genetics and Geography Influence Microbiome Composition in the Sponge Ircinia campana Sarah M. Griffiths
Rachael E. Antwis
Luca Lenzi
Anita Lucaci
Donald C. Behringer
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Repository Citation Griffiths, Sarah M.; Antwis, Rachael E.; Lenzi, Luca; Lucaci, Anita; Behringer, Donald C.; Butler, Mark J.; and Preziosi, Richard F., "Host Genetics and Geography Influence Microbiome Composition in the Sponge Ircinia campana" (2019). Biological Sciences Faculty Publications. 385. https://digitalcommons.odu.edu/biology_fac_pubs/385 Original Publication Citation Griffiths, S. M., Antwis, R. E., Lenzi, L., Lucaci, A., Behringer, D. C., Butler IV, M. J., & Preziosi, R. F. (2019). Host genetics and geography influence microbiome composition in the sponge Ircinia campana. Journal of Animal Ecology. doi:10.1111/ 1365-2656.13065
This Article is brought to you for free and open access by the Biological Sciences at ODU Digital Commons. It has been accepted for inclusion in Biological Sciences Faculty Publications by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. Authors Sarah M. Griffiths, Rachael E. Antwis, Luca Lenzi, Anita Lucaci, Donald C. Behringer, Mark J. Butler, and Richard F. Preziosi
This article is available at ODU Digital Commons: https://digitalcommons.odu.edu/biology_fac_pubs/385 This article isThis article by protected copyright. All rightsreserved. 10.1111/1365doi: as article this cite Please Record. of Version the and version this between differences to lead not has proofreading and but pagination review typesetting, copyediting, peer the full through been undergone and publication for accepted been has article This M15GD Manchester, # author: Corresponding 6 5 4 UK Liverpool, 3 2 UK. Manchester, Street, 1 Mark Sarah campana H Section Editor :AnnTate type Article :Research Article DR ID:0000 RACHAEL ANTWIS(Orcid GRIFFITHSDR ID:0000 M (Orcid SARAH
Department of Biological Sc Biological of Department USA. Florida, Gainesville, Florida, University of Institute, Pathogens Emerging USA. Florida, Gainesville, UniversityofFlorida, andSciences, Aquatic Fisheries Instituteof Research, for Genomic Centre UK. Salford, ofSalford, University Sciences, Life and ofEnvironment School Centre, Research and Environment Ecology
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Griffiths, [email protected] Griffiths, . s andgeography influence
: MolecularEcology 6
1 - and Richard and # 2656.13065 , Rachael E. Rachael Antwis Journal of Animal Ecology
iences, Old Dominion University, Norfolk, Virginia, USA Virginia, Norfolk, University, Oldiences, Dominion
F.
Preziosi
2 , Luca Lenzi Luca 1
microbiome composition in composition microbiome Integrative Biology, University of Liverpool, Liverpool, of University Biology, Integrative - 0002 - Manchester Metropolitan University, Chester Chester University, Metropolitan Manchester 0003 , John Dalton Building, Chester Street, Street, Chester Dalton Building, , John - 8849 - 3 4743 , Lucaci Anita - 8194)
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process, which may which process, the C. sponge
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Ircinia Ircinia 4 , 5 , This article isThis article by protected copyright. All rightsreserved. Accepted ArticleABSTRACT host Keywords: 1. 5. 4. 3. 2. - microbe interactions microbe
variability in mediating eco mediating in variability variation microbes. ofenvironmental acquisition that traits infunctional variation mayreflect variation genotypic sponge descent. by similar more makingmicrobiomes offspring, to from parent to may bedue composition microbiome sponge ofthe composition Our microbiome sites, between differentiated communities. genotype show We sequencing amplicon USA, Keys, Florida the in W of composition variation of genetic influence the weexamined Here, microbiome. and host between ecological and onevolutionary the light may shed and underexplored, are variability microbiome governing intraspecific factors However, the community. communities, are microbiomes s Marine e developed
results demonstrate that that demonstrate results B
acteria ponges are host tolarge host are ponges within and and within , that microbial community composition composition community microbial that with with ;
We also found that a found that also We indicating microsatellite
new microsatellite markers new microsatellite the more genetically similar sponges similarsponges more genetically distinct among sponge sponge among distinct ; core microbiome ; core Ircinia campana Ircinia among .
a
and key role of role key -
evolutionary dynamics of host of dynamics evolutionary locations, and shows shows and locations, s stable vertical transmission of the microbial community community of themicrobial transmission vertical stable ; both
Porifera characterised their microbiomes using using microbiomes their characterised
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. genetic diversity genetic This study This
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and diversity diversity and host and otypic the importance of importance the
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ography ; influence on microbiome microbiome on influence
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is influenced by host by host influenced is by location.
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from two locations twolocations from intraspecific intraspecific V4 16S rRNA V4 16S location relationship influence the the influence Alternatively,
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This article isThis article by protected copyright. All rightsreserved. & Loka Kavlekar, (Thomas, novel, of production for potential to their 2015) Uriz, that compounds of production and acidification 2018; al., et Karimi and nutrition including host complex, and numerous discovered ( and diversity abundance duetothe research host in systems model valuable considered are Porifera) (phylum Sponges environment and drivenhost both by communities, microbial these structuring forces the of an understanding requires theirmicrobiome and hosts between 2015) Foster, interactions microbe ofhost anarray encompassing communities ecological complex 2019) Kohl, & Hartup, Fontaine, Trevelline, 2017; Elinav, conservation wildlife and human medicine as diverse Knight, 2014) & Jansson, Gilbert, development and physiology health, host the Termed mu with associated communities microbial of importance inbiology shift paradigm A recent INTRODUCTION Accepted 2016 &Hentschel, Fraune, Pita, Article . among sponge hosts hosts sponge among
" Sponge (Ribes et al., et 2016) (Ribes microbiome . Understanding the ecological and evolutionary natu and evolutionary ecological the . Understanding
Moitinho - associated microbes are also of significant biotechnological due interest biotechnological ofsignificant also are microbes associated (Bauer, Kainz, (Bauer,Carmona Kainz, " and microbial symbionts symbionts microbial and , these communities these
waste waste Bharathi, 2010) Bharathi, - Silva et al., 2017; 2017; etal., Silva , reduction in host in reduction ) , and as such have been the focus of attention in fields as as fields in of attention focus the been have such , as and (Thomas et al., 2016) al., (Thomas et
, with a total of 52 bacterial phyla and candidate phyla candidate and phyla bacterial of52 , atotal with has been the discovery of the breadth, diversity and diversity breadth, the discoveryof the been has metabolis deter predation o deter predation
pharmaceutically (Blaser, Bork, Fraser, Knight, & Wang, 2013; 2013; &Wang, Knight, Fraser, Bork, (Blaser, . m
- within within
Gutierrez, & Madeo, 2018; Coyte, Schluter, & Coyte,Schluter, & 2018; Madeo, Gutierrez, influence a number a of influence (Freeman, Thacker, Baker, & Fogel, 2013; 2013; Baker, &Fogel, Thacker, (Freeman, Thomas et al Thomas et may surface fouling fouling surface their their f
the (Kashyap, Chia, (Kashyap, confer a number of benefits of a number confer . Sponge lticellular animals lticellular . Host
associated associated sponge sponge - active secondary metabolites metabolites secondary active ., 2010) - microbiome systems are are systems microbiome - - microbiome interactions are are interactions microbiome microbe and microbe and microbe host host (On, Lau, & Qian, 2006) Qian, & (On, Lau, re of the relationship relationship the re of (Antwis et al., 2017) al., et (Antwis , acclimation to ocean ocean to , acclimation microbial communities communities microbial traits associated with associated traits
(Garate, Blanquer, & Blanquer, (Garate, Nelson, Segal, Segal, & Nelson,
and plants. - microbiome microbiome
to their to their
- .
,
This article isThis article by protected copyright. All rightsreserved. compos community on information less giving techniques, sequencing Accepted (DGGE) gelelectrophoresis gradient denaturing using analysed communities bacterial and diversity (2012) Becerro Noyer and variation microbial mammals and 2018) Leaniz, de & Garcia includi systems, significant. be may also species the within variation genetic themicrobiome, in structuring host identity of strength 2013; Weigel & 2018) Voogd, &de Cleary, location geographic as such 2018) still is composition identity, species ofhost effect strong the Despite Article Turon etal., 2018) environments transmission) (i.e. associates of microbial transmission vertical of combination Uriz & Casamayor, Garate, López composition microbiome of determinant key Simil communities microbial seawater with overlap host is predominantly composition microbiome Sponge arly, arly, . Intra - Legentil, & Erwin, 2013; Schmitt et al., 2012; Thomas et al., 2016; Turon, Cáliz, Cáliz, Turon, 2016; al., et Thomas 2012; et al., Schmitt 2013; & Erwin, Legentil, i n relatively few microbial microbial few relatively Spongia lamella Spongia - specific microbiome microbiome specific
and horizontal tran horizontal and & Freeman, Thacker 2016; &Degnan, Green, Bayes, Gauthier, (Fieth, (Benson et 2010 al., (Benson
ng plants 2017) Erwin,
. have present
Indeed, h not yet been yetbeen not (
, amphibians , amphibians Wagner et al., 2016 et al., Wagner , depth found no found no relationship significant microsat between host within , 2018 . However, DGGE has a lower resolution than current thancurrent resolution alower DGGE has . However,
(Fiore, Jarett, & Lesser, 2013; Luter et al., 2 al., Luter et 2013; &Lesser, Jarett, (Fiore, and water quality quality water and variation variation smission taxa host ) ost influence ost genotype
. (Morrow, Fi ; Thisstrong
Goodrich et al., 2014) al., et Goodrich
linked are shared are sponge species species sponge (Griffiths 2018) et al., (Griffiths
has been associated with with beenassociated has of
in sponges. (Blanquer, Uriz, & Galand, 2013; Pita, Pita, 2013; Uriz, & Galand, (Blanquer, seawater microbes microbes seawater (Hentschel et al., 2002; Schmitt et al., 2012) al., Schmittet 2002; etal., (Hentschel ore, & Lesser, 2016) &Lesser, ore, )
, fish , fish et al., 2015) (Luter association
significant across ( Uren Web Uren (Thomas et al., 2016; Turon et al., al., et 2016;Turon al., et (Thomas - driven, with only a small degree of degree asmall only with driven,
s
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highly ( , environmental variation environmental Pearce et al., 2017 al., et Pearce
and host species is a is species host and
ition at lower at lower ition composition 015; Swierts, Swierts, 015; - selective host host selective (Cleary et al., etal., (Cleary ellite ellite
Turon, in several in several
2012; ) , . , This article isThis article by protected copyright. All rightsreserved. 2016) campana developed We host and development Microsatellite (Qiagen)Kit Tissue and Blood DNeasy® the DNA with technique aseptic using proc aid DNA to ethanol the of dilution prevent to and secondly bacteria, seawater attached removingloosely arinse, toact as firstly and variability 81.4757 70 approximately bottom hard (<2m) nearshore shallow w 2014, In July collection Sample M Keys, USA. Florida the campana Ircinia tocharacterise sequencing Illumina rRNA 16S and markers microsatellite polymorphic tobedetermined. therefore still This study addr disentangled. as well location from in composition microbiome and haplotype mitochondrial sponge latitude, ranks. taxonomic
Accepted Article ATERIALS essing. Prior to DNA extraction DNA to essing. Prior immediately
Florida and the Caribbean. Caribbean. the and Florida
( Table ) . , with , with using the pipeline pipeline the using We took s took We S
AND M AND The role of host sponge genotype in structuring microbial communities is is communities microbial structuring in genotype sponge role ofhost The 1, a suite of a suite e sampled 20
populations andtheir associated microbial communities intwolocations in preserved
see S see In a later study, laterstudy, In a km
individuals sampled per site sampled per individuals microbiome composition, preventing the two variables from being being from variables two preventingthe composition, microbiome
and DNAextraction and amples in a single collection instance at each site to eliminate temporal temporal eliminate to site each at instance collection asingle in amples : LongKey( ETHODS
upporting to 10 Ircinia campana Ircinia remove
it tri implemented in the the in implemented
in -
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24.81437, 24.81437, Information for full details full for Information Marino
commensal commensal , we dissected the , wedissected
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nucleotide nucleotide
et al. preservation
(Caribbean (Caribbean -
80.8307) and in .
(2017) macro the esses this esses We cut a cut We P alfinder Florida Keys USA) (FL, Florida
polymorphic microsatellite markers for markers microsatellite polymorphic -
tissue under a stereomicroscope stereomicroscope a under tissue assessed correlations between between correlations assessed organisms. organisms. . , v
oxidase I haplotype correlated with correlated haplotype I oxidase We stored samples stored We and normalised and ase ase
piece of tissue from each indivi tissue from each of piece Galaxy s gap in the literature the gap in Kemp Channel ( Kemp Channel
of methods s ponge) ponge) We thenreplaced We then extracted t thenWe extracted ervice ervice individuals )
. it One locus One locus Ircinia campana Ircinia (Griffiths etal., (Griffiths to 1
24.6768 separated by by separated
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the the ethanol, at two at two . , (Icam34)
- otal dual
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This article isThis article by protected copyright. All rightsreserved. lib the PCR, Following identification. sample incorporate ente before Coulter), minutes. 5 72°C for conditions primers the of region UK. Liverpool, Universityof Research, Genomics and PCR, sequencing andsequencing preparation PCR, library characterisation Microbiome 2017). v1.0 alleles theGeneScan using ofManchester, University the at Facility the at DNA Sequencing 3730 the DNA Analyzer using sized were PCR products 63°C seconds, for30 of95°C cycles 28 5minutes, for denaturation 95°C initial conditions: using asdescribed sequence, primer universal the with forwardprimer endof the 5’ the tagging primerand universal weu PCRproducts, label study this in analysis further from Icam34 shown) al. datanot et inprep, (Griffiths localities other sampled from individuals in well performed
raries Accepted Article
amplicon libraries libraries amplicon 3
for 90 seconds and 72°C for 30 seconds, and a final e andafinal 72°Cfor30seconds, for 90seconds the Type the (Alberto, 2009) (Alberto,
with Genemapper v3.7 with Genemapper ;
described in described however in equimolar amounts and and amounts equimolar in : 15 x 95°C for 20 seconds, 65°C for 15 seconds and 70°C for 30 seconds; 1x seconds; 30 and70°C for seconds 15 for 65°C seconds, 20 : x 95°Cfor 15 Illumina sequencing adapter sequences containing indexes (i5 and i7) fori7) and (i5 indexes containing sequences adapter sequencing Illumina
16S - it® Microsatellite Kit (Qiagen) Microsatellite it® ,
rRNA gene gene rRNA it did not not did it We purified PCR products purified We
ring into a second stage of PCR (conditions as above,cycles) 20 as ofPCR (conditions stage second a ring into Caporaso et al. (2011) Caporaso et
in in R using OTU taxonomic assignment OTU taxonomic by sed Studio
Culley et al. (2013) al. et Culley amplify a
in a in a three Qubit (Thermo Fisher Scienti Fisher (Thermo
1.1.442 for R
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used well in the study populations. We therefore excluded excluded therefore We study the populations. in well and an - - primer PCR method, using a using method, PCR primer we purified the samples again samples the we purified stage nested PCR in 5μl reaction volumes 5μlreaction PCRin nested stage
a ,
thus thus Pippin Prep (Sage Science) Science) (Sage Pippin Prep
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To fluorescently To quality checked checked quality
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using using 60°C/
to
This article isThis article by protected copyright. All rightsreserved. the using were none found while analyses, subsequent based approach set. sequence and error, 2014) Dunthorn, 99% identity threshold,and thesecond inSwarm 1.1.3 VSEARCH in implemented Twodifferent similarity. s clustered We removelow to Nsdiscarded were containing Sequences G 1990) Myers,&Lipman, Gish, Miller, (Altschul, and command, 2012) corrected were errors and 20), score quality window (minimum trimmedl c used We filtering Quality complexity. sequence increase sequencing Biosyst (Agilent Bioanalyzer selection utadapt v1.2.1 AcceptedI:9626372) Article .
step found step We alignedr ems) on a LightCycler® (Roche). We then then We (Roche). LightCycler® a ems) on ow quality bases from the reads using Sick using reads the from bases quality ow CASAVA v1.8.2 (Illumina) to base call call de and base to (Illumina) v1.8.2 CASAVA of 300 and merged merged on
in each sample; matching sequences (E sequences sample;matching each in a
We conducted c conducted We equences into operational taxonomic units (OTUs) with 99% 99% with (OTUs) units taxonomic operational into equences the Illumina MiSeq, with fragmented PhiX bacteriophage genome added to genomeadded PhiX bacteriophage fragmented with IlluminaMiSeq, the selected merged sequences of between of mergedsequences selected pre and - (Martin, 2011) (Martin, reference . 600 We removed c We 12% ofthe sequences tobechimeras, the results from both clustering steps to create a non a tocreate both from steps clustering results the ead pairs using USEARCH8 using USEARCH8 ead pairs ) and qPCR with the Illumina® Library Quantification Kit (Kapa (Kapa Kit Quantification Library Illumina® the ) andqPCRwith bp using the error the using
- . clustering algorithms were used for OTU picking; the first first the for OTU picking; used were algorithms clustering processing We assessed q assessed We - based
to remove Illumina adapter adapter Illumina to remove
himera detection VSEARCH in himera detection lusters containing fewer containing lusters
(Edgar, 2010) (Edgar, approach approach
- correct module in SPAdes v3.1.0 v3.1.0 SPAdes in module correct uantity and quality andquality uantity removed with
t
using the function ‘ function the using o search for PhiX sequences (GenBank (GenBank for oPhiX search sequences the SILVA 119 database the SILVA 119 (Edgar, 2010) (Edgar, (Mahé, Rognes, Quince, de Vargas, & Vargas, de Quince, Rognes, (Mahé,
conducted conducted reads under 10 bp in length. Sequ length. in bp under 10 reads le v1.200 (Joshi & Fass, 2011) 2011) Fass, & v1.200(Joshi le - value <10 value - de novo de multiplex indexed reads, and reads, indexed multiplex
200 - than two sequences to reduce reduce to sequences two than
quality reads. quality which and PCR primer PCRprimer and of thelibrary
and p
using both using aired
with the the with were removed for for removed were
- approach.
5 600 ) were then filtered out. filtered then ) were - cluster - end
bp.
(Bankevich et al., al., et (Bankevich
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redundant redundant pool (2 x
. We used We a The reference -
smalmem’ with with smalmem’ We used the used We sequences. sequences. de novo de - sequence sequence mergepairs' mergepairs' 250 bp using
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) encing encing
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- This article isThis article by protected copyright. All rightsreserved. Accepted 1977) Rubin, frequencies (2001) Yekutieli's and v.4.2 theWeb on Genepop loci using microsatellite between disequilibrium for linkage tested We genetics Host analys Statistical non repeated Key Long re were samples sequences; 173,000 of depth a at replacement) (without We thencreated ararefied dataset which following to 350 from2000 depths sampling at table OTU count Article uneven. were samples among We subsequent analyses. statistical subsequent We count database theSILVA119 in to those sequences tomatch assign_taxonomy.py the OTU,and in sequence therepresentative most to select classified taxonomically each of abundance the todefine VSEARCH function in ‘usearch_global’
- also also imported rarefied dataset rarefied (Rousset, table for all samples fortable all moved from subsequ from moved created ). our our
We compositional and beta and compositional in FreeNA ( FreeNA in . We calculated . We this this beta
used this dataset this dataset used 2008) we calculated Ch we calculated
a rarefied dataset a rarefied into into - es diversity analyses using this dataset, which produced similar results similar produced which dataset, this using analyses diversity
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ent analysis ent F
in QIIME 1.9.0 QIIME1.9.0 in ST using the phyloseq package ( package phyloseq the using Repeated subsampling (33 repetitions) was carried out on the the outon carried was repetitions) (33 subsampling Repeated
We converted OTU count data to relative abundance for abundance relative to data count OTU We converted with between the twosites the between ao for alpha
for ( 1 alphadiversity - single_rarefaction.py diversity diversity
significance the R function Rfunction the
use in in use
( leaving - diversity analyses diversity alpha analyses. (Caporaso et al.,2010) et (Caporaso (Quast al., 2013) et
using the EM the using threshold n =12for Kemp andn= Channel 13 for - diversity analyses diversity p.adjust and plotted taxonomic classification as abiomfile as classification taxonomic , 000 ,
and
)
by in QIIME (multi_rarefaction.py), in QIIME (multi_rarefaction.py),
for multiple tests for multiple McMurdie McMurdie . correct
We estimated n estimated We as described below; described as repeated
algorithm
rarefaction curves curves rarefaction with fewerwith sequences . ed We produced an produced We
, as sequencing depths depths , assequencing pick_rep_set.py using
for ly & Holmes, 2013 Holmes, &
OTU, and OTU, and subsampling subsampling (Dempster, Laird, & Laird, (Dempster,
null allele
using using ull
allele allele
we Benjamini Benjamini (Fig. S1) (Fig. also also OTU
) for ) for to the
. . This article isThis article by protected copyright. All rightsreserved. distance microbial dissimilarity alpha of a measure sites both p produced We Host level. genus represented. these that microbiome total ofthe the proportion calculated then and OTUs core in present be of threshold prevalence a and 0.001% of threshold detection Bray ( ( a conducted We Microbiome 2012 Smouse, & (Peakall to distances these allele overall samples between differences overestimating results, bias can data missing and alleles null calculations, GenoDive using genotypes p calculated We FreeNA. in in described as ENA method the using presence Acceptedadonis 2018 al. et Oksanen Article - genotype Curtis dissimilarities Curtis )
to test for significant differences significant for to test ,
and
as as composition frequencies We then all - measures individuals between matrices distance community microbial airwise for each site site each for microbiome analyses
airwise Euclidean genetic distances between individuals from the from the betweenindividuals distances genetic Euclidean airwise nalyses in nalyses individuals
(Chapuis & Estoup,2007) (Chapuis matrix conduct a conduct - diversity, and diversity, )
repeated th repeated and microbiome and microbiome
. ( ) ( of beta
Chao . 11.8% inLong Key 7.6 and
We calculated the core microbiome of individual samples using a using samples ofindividual coremicrobiome the calculated We
RStudio using the using RStudio
, v2.0 b27 v2.0 b27
individually with a relative abundance of at least 0.001% least at of abundance arelative with
p rinciple 1 - ,
diversity e core microbiome analysis microbiome e core Jensen JSD
(Meirmans & Van Tiendener, 2004) Tiendener, & Van (Meirmans c
and Bray and (Lahti 2017) (Lahti , oordinates oordinates
using in microbiome composition microbiome in - . Shannon W .
e tested for correlation for e tested Thus phyloseq
distance matrices based on based matrices distance - Curtis Chapuis & Estoup ( & Estoup Chapuis , we first filled filled , wefirst a
package divergence (JSD) divergence nalysis (PCoA) nalysis % in Kemp Channel Kemp % in
) (McMurdie & Holmes, 2013) &Holmes, (McMurdie
and
s host host 100
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We used a used We in missing data based on on based data missing in % (i.e. a given % (i.e. genetic in s
2007) b
between GenAlEx v. GenAlEx and Bray and etween .
) distance distance )
. I PERMANOVA PERMANOVA
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and implemented implemented and agglo We site each each - then Curtis Curtis OTU
1 merated to merated 6.503 6.503 s
multi values matrix across across using ,
used used vegan - must based based - locus locus
as as This article isThis article by protected copyright. All rightsreserved. tobewell considered be can therefore sites and samples, the among variation total 0.021) Keyand between Long differentiation genetic Pairwise (Table manycases in observed were deficiencies heterozygosity and many loci, for were high failures) (genotyping alleles missing of and proportion the frequencies allele Null (Table Icam4) and up to1 A individuals. sampled the amongst present We foundn genetics Population RESULTS taxa. this individuals, vary across matrices. distance genetic reduced and at boththe OTU levels,and and genus also We removed LongKey in (0.462) Icam3 and Icam23(0.077) in present only data was missing f and h further, moreconservative datafile genetic (Euclidean) Accepted Article requencies
igh proportions of missing data. ofmissing proportions igh . The first and second PCoAexplained and coordinatesofthe only . Thefirst principle 8
extracted Bray extracted alleles per locus, but two of the loci were monomorphic in Kemp Channel (Icam32 (Icam32 KempChannel in were monomorphic of loci two locus,the but per alleles Icam3 at Long Key, atLong Icam3
o identical multi using using (Icam24, Icam26 and Icam10 in both sites, Icam3 in Kemp Channel samples) KempChannel Icam3 in sites, both in Icam10 and Icam26 (Icam24, M S
antel testswith999 permutations. 2 ). - No significant linkage disequilibrium occurred amo occurred disequilibrium linkage No significant Curtis distance matrices forco matrices distance Curtis - locus genotypes in the dataset, indicating no clones clones no indicating dataset, the in genotypes locus metric describes metric giving final datasets of 5 loci for each site for loci each of 5 datasets final giving Following removal of loci with high high with loci removalof Following
with to correlation for tests test Mantel used the individuals a individuals the As the the As , - cross all sites, a sites, all cross removing loci with loci removing mixed genetically mixed
variation in taxonomic We re microbiota across and within within and across re microbiota Kemp Channel was low was Channel Kemp re not separated (Fig. by site re not separated
relative abundances of these core core of these relative abundances
composition of the core does not doesnot of core the composition repeated the analyses with a with analyses the repeated ll loci were polymorphic, ranging ranging polymorphic, were ll loci .
high null allele frequencies .
(>0.16) (>0.16) ng any loci pairs. pairs. any loci ng 15.81
( . We F were null allele allele null ST
the full S % of the the % of =
1). The The 1). 2 then sites sites ).
, This article isThis article by protected copyright. All rightsreserved. genera Proteobacteria Synechococcus PAUC43f, PAUC32f, Truepera, Acidobacterium, Nirtosopumilus, Candidatus MSI70, Actinobacterium Cerasicoccus, Granul OM75clade, Acidobacteria, Defluviicoccus, Rhodovulum, included 63.0 and Key, in Long sponges 69.6 comprised microbiome core the level, genus At the evident are differences 12.4% ofthe variation in microbiome composition explained by site at LongKey andKempChannel ( a was There samples all dominan most the was Anaerolineae S2 (Fig. (1.5%) Actinobacteria (1.6%) and Gemmatimonadetes (3.8%), SBR1093 PAUC34f (4.3%), the of (62.6% of sp aligned to be could 241 = (mean sequences assembled 426,014 and between 118,370 with samples leaving ( samples remaining than the sequences sample. per assembled o and 99.61% 97.10 Between Channel). Kemp and Key Long from each conducted successfully We community Microbial o Accepted Article bacterial 22 nges nges , 448 ±13 448 ) . The remaining phyla formed less than than 1% of less phylaformed . Theremaining Desulfovibrionales, Chloroflexi, Pseudospirillium, PAWS52f, Nitrosococcus, Nitrosococcus, PAWS52f, Pseudospirillium, Chloroflexi, Desulfovibrionales, ranging from 4,165 to 14,503 OTUs 14,503 to 4,165 from ranging
(Fig.
statistically statistically ,
758 S.E. 758 total reads total phyla phyla
S3 a ) . and onearchaeal composition taxon
. , Fig. S1 , Fig. ,
O One sample albeit subtle, significant ), ut ofa total of31
followed , PCR amplification and Illumina sequencing sequencing and Illumina PCR amplification with ) % . Between 80.77 and 87.57% of the filtered sequence set sequence filtered the of 87.57% and 80.77 . Between
31,567 OT (±
adonis, adonis,
difference in in microbiome difference by Proteobacteria (17.5%), Acidobacteria (6.4%), (6.4%), Acidobacteria (17.5%), by Proteobacteria 1.6) 1.6)
t from Kemp Channel from Kemp
at botht class phylum for sponges in Kemp Channel. These genera genera These KempChannel. in sponges for 28,163 F , 1,31 567 567 OTUs, , forming large proportions of the microbiomes of the of microbiomes proportions large , forming Us
(Fig. S1) (Fig.
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This article isThis article by protected copyright. All rightsreserved. in observed been has microbiome descent transmi microbiome H geno Host vary in in microbiomevariability intraspecific influence genetics populations sponge the between composition differedin significantly microbiomes sponge communities microbial similar campana had genotype Host DISCUSSION of thegenetic datasets(all p>0.100). level genus OTUor the either at distance microbiome and core distance datasets (Bray diversity community microbial We found microbiome composition and genotype host between Relationship sp.) 1.3 T microbiome ogether t ogether Accepted correlated werepositively similarity andmicrobiome similarity genetic ost Article % highest highest
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more similar microbiomes. Evidence for vertical transmission of the of the transmission vertical for Evidence microbiomes. more similar by spatial scale by spatial -
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(Proteobacteria sp.) and eleventh (Bacteria (Bacteria and eleventh sp.) (Proteobacteria the other significant relationships between genetic genetic between relationships significant using the full and reduced reduced and full the using diversity and diversity
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This article isThis article by protected copyright. All rightsreserved. varying 2004) & Clark, Sceurman, (Lazzaro, 2017) &Docherty, Nevitt, Jennings, Hoover, Pearce, been found in environment. the microbes genetic Alternatively, s variable are from extractsisolated to cellular approach, experimental 2012) Thomas, diverse highly are which thesponge, by produced metabolites secondary of Selection genotype microbiome the al., 2018) microbiome contribute also environment from the of microbes transmission Horizontal larvae. growing in present arealready physiology and health host for important gained from theinheritance ofparental host 2015) al., et Sipkema 2007; Haygood, & Pawlik, Wong, Chui, Lee, 2005; & Vishnyakov, Lindquist, & Hentschel, 2007) Accepted microbiome. sponge the to microbes seawater varying attract could compounds pecific Article commonly found in sponges. As sponge secondary metabolites metabolites secondary As sponge sponges. in found commonly - species fidelity of microbiomes in sponges. in ofmicrobiomes fidelity species gene expression patterns in response to a potentially pathogenic bacteria pathogenic toapotentially inresponse patterns expression gene (Noyer, Thomas, & Becerro, 2011; Puyana et al., 2015) et al., Puyana 2011; &Becerro, (Noyer, Thomas, - . specific selection of seawater microbes. selectionofseawater specific As such, ecological interactions interactions ecological such, As
to affect microbiome composition composition microbiome to affect (Fieth et al., 2016; Maldonado & Riesgo, 2009; Sipkema et al., 2015; Turon et Turon 2015; etal., Sipkema 2009; &Riesgo, Maldonado al., 2016; et (Fieth environmental environmental
. and The relationships observed in this study may therefore be driven by driven maybe study therefore this observed in relationships The
include antimicrobial compounds compounds antimicrobial include
variation may encode variable responses in the host immune system to system hostimmune the in responses variable mayencode variation Tout eta microbes , as well as other other wellas , as In other species, In otherspecies, polymorphism genes inimmunityrelated a l. sponge, with particular enrichment of bacteria of enrichment particular with sponge,
( 2017) . In addition, genotype. Inaddition,
imposed by imposed , and is thought to be a significant driver of the high high ofthe driver be a significant thought to is , and
microbiomes, as favourable symbionts that are that symbionts favourable as microbiomes,
showed that seawater bacteria exhibit chemotaxis chemotaxis exhibit bacteria seawater that showed with (Bolnick et al., 2014; Kubinak et al., 2015; 2015; al., et Kubinak et al.,2014; (Bolnick
sponge sponge seawater seawater
Many evolutionary advantages can be can advantages Many evolutionary
host host Qian, 2009; Sharp, Eam, Faulkner, & Faulkner, Eam, Sharp, 2009; Qian,
and ( genetic variation could could variation genetic Kelman et al., 2001 al., et Kelman species species
microbes microbes responses to pathogenic bacteria bacteria to pathogenic responses - specific immune response immune specific (Ereskovsky, Gonobobleva, Gonobobleva, (Ereskovsky, , the production of the production c can intra be ould
s be (Genta )
. Using anin . Using to thesponge
key in shaping inshaping key result from result
- l taxa that - specifically specifically Jouve & Jouve ,
have genotype host ,
and -
has situ situ
- This article isThis article by protected copyright. All rightsreserved. &Hoegh Tyson, Accepted organisms marine benthic anumberof in location geographic samples. across observed variation microbiome sites thisstudy in structure microbiome driverof was largest the Location location Geographic composition. community th of proportion small a relatively Thomas, 2017) & Cullen, (Esteves, al., et2012) Costello composition community andultimately succession determining microbes in which order and o selection Furthe 2015) (Degnan, Article inv receptors recognition pattern AqNLR sponges 2005, 2007) bacteria differentiate and recognise can that environment the and organism 1984) Vacelet, place takes food bacteria distinct system immune innate arelatively sophisticated have sponges system, immune acquired have an been observed inthecoral are onlyare r to these potential mechanisms, mechanisms, potential these r to
extracellular microbial communities in the mesohyl tissue where phagocytosis of of where phagocytosis in the tissue mesohyl communities microbial extracellular (Müller & Müller, 2003) &Müller, (Müller (nucleotide . H f owever, there is evidence of polymorphism of the the of polymorphism of evidence is owever, there
seawater bacteria bacteria seawater . There is There approximately approximately . This system includes receptor proteins at the interface between the the between interface at the proteins receptor system includes . This . -
Guldberg, 2015; Rubio 2015; Guldberg, - binding domain and Leucine and domain binding
, with competitive interactions occurring among community members members community among occurring interactions , withcompetitive
currently
(Wehrl, Steinert, & Hentschel, 2007; Wilkinson, Garrone, & & Garrone, 2007; Wilkinson, &Hentschel, Steinert, (Wehrl, Acropora millepora Acropora 7 join 0 is ,
no eviden no km ap which
olved in detecting and binding a range of microbial ligands ligands of microbial range a binding and detecting in olved
e microbiome could increase its reach in reach shaping its increase could e microbiome likely tobe a sponge microbiome a microbiome sponge . Because of this, influence of the host genotype on even on genotype host the of influence this, of . Because art has been speculated to speculated been has the sponge itself cannot be considered in isolation; isolation; in considered be cannot itself sponge the - Portillo, Kersting, Linares, Ramos Linares, Kersting, Portillo, , ce that immune response immune that response ce location accounted for12.4% accounted location
performed by the performed (Wright et al., et 2017) (Wright
- Microbiomes vary within species by species vary within Microbiomes rich repeat containing) genes, which are which genes, containing) rich repeat may
have secondary effec have secondary
Amphimedon queenslandica queenslandica Amphimedon
entire (Pantos, Bongaerts, Dennis, Dennis, Bongaerts, (Pantos, aid the (historical contingency; (historical . varies varies
. Although the sampling the . Although Although they do not donot they Although holobiont. The timing timing The holobiont.
maintena
of thetotal intra - Esplá, & Antón, &Antón, Esplá, (Wiens etal., (Wiens - nce ofnce sp ecifically in ecifically ts on on ts
This article isThis article by protected copyright. All rightsreserved. the that theory to support lends taxa. This ofcore abundances drive not does taxa, it Therefore, ourresults show thatwhile genotype exerts aneffectonnon ph the same microbial of abundance relative in variation here to refers composition individuals, all in astaxafound study in this defined was core the As OTU level. or genus atthe composition core microbiome on genotype host of any effect w composition, microbiome total genotype on of host effect significant a Despite microbiomeCore ex Kemp Channel t Mantel relationships. to bebetween appears effect responsible I. campana difference microbiome the dif genetic no effectively was there genetics host investigate to as a replication form of twosites sampled data, environmental or collect communities bacterial seawater sample not study, wedid In this campana (i.e. spatial scale local a relatively on even that show results haplotype. Our mitochondrial host with correlated also which Caribbean, the in (2017) al. et Marino is notuniversal finding e (Fiore Ferrier Allemand, & Water, de van 2018;
Accepted of genotype influence tend the Article as on microbiome composition composition microbiome on t al., 2013; Luter et al., 2015; Marino et al., 2017; Swierts et al., 2018) al., et Swierts 2017; al., et 2015;Marino al., Luter et t al.,2013;
investigating environmental effects was not the objective of this study ofthis objective the wasnot effects environmental investigating
can vary among sampling sites. sampling varyamong can
microbiome composition at larger spatial spatial atlarger composition microbiome for this pattern this for ; t his could be the result of genotype x environment interactions xenvironment genotype of result the could be his
showed a latitudinal gradient in microbiome composition in in composition microbiome in gradient latitudinal showed a est statistic values were statistic est
- López (Pita, site variation int variation site s
remain found
at larger spatial scales. spatial at larger between sites
when considered considered when ferentiation between the sponge populations sponge the between ferentiation unknown - Legentil, & Erwin, 2013;Pita, Turon, etal., 2013) he strength of host genotype host strength of he - Pagès, 2018) Pagès,
.
However, mostly ,
within the Florida Keys), Keys), Florida the within
indicate that environmental variation drives variation that environmental indicate across scales
higher for Long Key than those for for those Key than Long for higher , including i , including host host ylotypes among individuals. individuals. among ylotypes
. Th locations. In addition, there In addition, locations. genotype genotype e environmental parameters parameters environmental n some sponge species species n somesponge - . micr
also also However, - core microbiome core microbiome microbiomes microbiomes obiome obiome had a significant asignificant had , although this this , although . ,
I. c and could could and at each site, site, at each Instead e did not find find e did not because ampana .
of
,
we I.
This article isThis article by protected copyright. All rightsreserved. than OTU and stability transmission successful for more important being ranks taxonomic due toalevel offunctional redundancy within microbialgenera, with characteristics at higher genus larger However, the function. holobiont in role important possibly 2012) & Handelsman, Shade 2017; Ainsworth, members oropportunistic transient than rather microbiome, of the members important stable,functionally to aims identity concept microbiome core The studies. within microbiome ‘core’ appears the apparent (Astudillo to relative observed differences the that suggesting respectively, Channel Kemp Keyand Long in microbiome total the of 69% and formed63% study our in genera microbial study. core The this in OTUs used taxonomi microbial wider toencompass likely are However, microbiome. coreOTUsfound 119 among18 sponges on studies previous respe KempChannel, Keyand Long in total microbiome the of 1.3% and 1.2% made up ofthe understanding to furtherour particular, in relationships. microbiome 2018) form in role important an has transmission horizontal At
Accepted Article the 99% OTU level, the core microbiome core the OTUlevel, 99% the ctively. This core community appears small compared to results reported in some some in reported results to compared small appears core community This ctively. - we , as species replicates we used we used replicates species
symbiotic, relationship with the two core OTUs observed, indicating a potentially apotentially indicating OTUsobserved, two core withthe relationship symbiotic, - Garcí the associated methodologies associated the may a etal., 2017)
expect vertical transmission to produce significant genotype significant toproduce transmission vertical expect this study this
Howev (Marino et al., 2017; Turon et et 2018) al., Turon 2017; al., et (Marino . Furthermore previous
I. campana er, some refin some er, used 97% OTU clustering, which means individual OTUs individual means which OTUclustering, used 97% (n33) = ir
significance, role and transmission and role significance, (Turon et al., 2018) etal., (Turon
work primarily reflect work
was substantially larger than in many previous in manyprevious than larger substantially was
, the to define and identify ‘core’ taxa taxa ‘core’ identify and to define
individuals, comprising 79.2 79.2 comprising individuals, in . ement our
Ircinia campana Ircinia higher the number of replicates, the smaller thesmaller replicates, number of the higher c variation in contrast to 99% clustering of of clustering 99% to contrast in variation c
study ing the core microbiome microbiome core the ing
of thecore microbiome concept
was comprised of two OTUs, which which oftwoOTUs, comprised was , and in this study the number of of number the study , this in and (Hernandez
- methodical differences methodical lev
appears to have a strong, to astrong, have appears el core observed maybe coreel observed . Marino et al. (2017) al. et Marino .
- Agreda, Agreda, –
87.0% ofthe total may be (Turon et al., et al., (Turon - core core Gates, & Gates,
required required
and -
,
This article isThis article by protected copyright. All rightsreserved. Accepted2016; Webster & Reusch, 2017) acclimation et al.,2015; Robblee et al., 1991) Kearney 1999; &Robblee, Fourqurean 2018; Weisz, Butler,& 2017; &Dolan, (Butler 2010) Kelly, mortality events mass numerous 2016) &Galand, Cebrian, fasciculata example, and thei species marine of andsurvival forhealth implications huge with microbiomes, associated host in and theenvironment within both communities microbial change to predicted are also is relationship. of the understanding our Further work onthemechanisms Articledemonstrate wit dynamics ecological toimpact diversity in composition that show We remarks Concluding genotype obscure associat stable identifying et al.,2009) OTU/ species astrict than useful more be therefore may groups a core defining As such, characteristics. level important r ecosystems r ecosystems ocean warming warming ocean , which
and resilience to climate change scenarios climate change to resilience and . Furthermore, as our findings show that microbiomes vary by genotype, bygenotype, vary thatmicrobiomes show findings our as . Furthermore, due tocyanobacterial blooms caused by decadesofecosystem instability Furthermore, a
g n I. campana enetic diversity has an important influence in shaping microbiome in shaping influence important an diversity has enetic
e
in the context of global climate change. Ocean warming and acidification acidification and warming Ocean change. climate global contextof the in co - have been have been specific host specific -
evolutionary relationship between sponges and microbial communities. communities. microbial and sponges between relationship evolutionary (Lesser, Fiore, Slattery, & Zaneveld, 2016; Qiu et al., 2019) al., Qiuet 2016; Zaneveld, & Fiore, Slattery, (Lesser, nature and eco and nature . In Florida Bay, Bay, Florida . In i species the using host ions n the Mediterranean n the results . These u nderstanding nderstanding implicated in disease and mass mortalities mortalities mass and disease in implicated - microbe symbioses. microbe symbioses. . ( With this in mind, understanding individual mind,in understanding With this . Microbiomes potentially have a huge importance in in haveimportance ahuge potentially . Microbiomes underl Butler ying
- et al.,1995; Stevely,Sweat, Bert, Sim evolutionary dynamics of dynamics evolutionary these these highlight the potential for intraspecific genetic genetic intraspecific for potential the highlight I hin sponge hin .
campana host host in terms of wider phylogenetic or functional or phylogenetic in of wider terms
trigger drivers of genotype
-
- ed level core microbiome approach may approach core microbiome level populations have already suffered microbe relationships, and and relationships, microbe
in marine organisms organisms marine in
microbial imbalances imbalances microbial interspecific interspecific - microbiome relationships microbiome - level approach approach level
the the sponge microbiome variability variability microbiome (Blanquer, Uriz, Uriz, (Blanquer, - (Ribes et al., al., et (Ribes level drivers of level - - i microbiome microbiome n Smith, & Smith, (Turnbaugh (Turnbaugh I. .
For
will aid aid will -
This article isThis article by protected copyright. All rightsreserved. Information Supporting PRJNA528609 deposited is development microsatellite for used numbers PRJNA506340 SRA NCBI the from available data are sequence rRNAamplicon 16s accessibility Data manuscript. and LL SG, M S Author contributions ofintere noconflict declare authors SR. The permit under Commission andWildlife Fish Florida the of permission with equipment. lab of use Facilityforthe DNA Sequencing Manchester Service Galaxy thePalfinder of use for Facility Core generation data in collecting in assistance their development. helpful advice in to SMG. awarded studentship PhD a NERC by aNBAF funded was study This Acknowledgements future stressors. of face the in conservation management and in species assist may variation microbiome
AcceptedM Article G and RFP conceived and designed the study; SG the designed and conceived RFP G and J B and DCB collected the samples; S samples; the DCBcollected B and conducted MF987878 MF987878
Thanks to students from University of Florida and Old Dominion University for for University and OldDominion Florida of from University to students Thanks ) ). Microsatellite .
study design study The code used for analyses in R is available as a RMarkdown file inthe file aRMarkdown as available in R is for analyses codeused The
. the analysis the
Thanks to P. Briggs and the University of Manchester Bioinformatics Bioinformatics Manchester of the University and P. Briggs to Thanks to MF987887
.
samples ,
; loci sample a providing for toand C.Freeman S M - .
NERC
sequences are logged in NCBI in are logged sequences G and R and G Raw Illumina sequencing data from from data sequencing Raw Illumina , and
pilot projectgrantawarded toSMG andRFP, and to the staff at CGR Liverpool for their assistance their for CGRLiverpool at staff to the E M sts. sts. T A wrote the the A wrote hanks to J. Rowntree and G. Fox for their G. Foxfortheir Rowntree and to J. hanks G and AL carried out the labwork the out carried AL and G
in the NCBI SRA (accession number number NCBISRA(accession the in
a n ,
d RFP
to P. Fullwood at the University of attheUniversity to P.Fullwood manuscript , MB and DCB DCB MBand ,
GenBank under accession accession under GenBank Samples were collected collected were Samples ; all authors revised the the revised ; all authors ( accession Ircinia campana Ircinia
for SAL secured funding; funding; secured
microsatellite microsatellite - 13 ;
number S - 0582A M G,
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