Evolutionary Strategies of Viruses, Bacteria and Archaea in Hydrothermal Vent Ecosystems

15 Pages·2014·1.39 MB·English

Evolutionary Strategies of Viruses, Bacteria and Archaea
in Hydrothermal Vent Ecosystems Revealed through
Metagenomics
Rika E. Anderson1*, Mitchell L. Sogin2, John A. Baross1
1SchoolofOceanographyandAstrobiologyProgram,UniversityofWashington,Seattle,Washington,UnitedStatesofAmerica,2JosephineBayPaulCenter,Marine
BiologicalLaboratory,WoodsHole,Massachusetts,UnitedStatesofAmerica
Abstract
The deep-sea hydrothermal vent habitat hosts a diverse community of archaea and bacteria that withstand extreme
fluctuationsinenvironmentalconditions.Abundantvirusesinthesesystems,ahighproportionofwhicharelysogenic,must
also withstand these environmental extremes. Here, we explore the evolutionary strategies of both microorganisms and
viruses in hydrothermal systems through comparative analysis of a cellular and viral metagenome, collected by size
fractionationofhightemperaturefluidsfromadiffuseflowhydrothermalvent.Wedetectedahighenrichmentofmobile
elementsandprovirusesinthecellularfractionrelativetomicroorganismsinotherenvironments.Weobservedarelatively
highabundanceofgenesrelatedtoenergymetabolismaswellascofactorsandvitaminsintheviralfractioncomparedto
thecellularfraction,whichsuggestencodingofauxiliarymetabolicgenesonviralgenomes.Moreover,theobservationof
stronger purifying selection in the viral versus cellular gene pool suggests viral strategies that promote prolonged host
integration. Our results demonstrate that there is great potential for hydrothermal vent viruses to integrate into hosts,
facilitatehorizontal genetransfer, and express ortransfer genesthatmanipulate the hosts’functional capabilities.
Citation:AndersonRE,SoginML,BarossJA(2014)EvolutionaryStrategiesofViruses,BacteriaandArchaeainHydrothermalVentEcosystemsRevealedthrough
Metagenomics.PLoSONE9(10):e109696.doi:10.1371/journal.pone.0109696
Editor:VladimirN.Uversky,UniversityofSouthFloridaCollegeofMedicine,UnitedStatesofAmerica
ReceivedMarch25,2014;AcceptedSeptember11,2014;PublishedOctober3,2014
Copyright:(cid:2)2014Andersonetal.Thisisanopen-accessarticledistributedunderthetermsoftheCreativeCommonsAttributionLicense,whichpermits
unrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalauthorandsourcearecredited.
DataAvailability:Theauthorsconfirmthatalldataunderlyingthefindingsarefullyavailablewithoutrestriction.Boththeviralandcellularmetagenomesare
publiclyavailableontheMG-RASTv3database,withaccessionnumbers4469452.3fortheviralmetagenomeand4481541.3forthecellularmetagenome.
Funding:FundingforsequencingoftheviralmetagenomewasprovidedbytheGordonandBettyMooreFoundation.AllotherfundingwasprovidedbyaNASA
AstrobiologyInstitutegrantthroughCooperativeAgreementNNA04CC09AtotheGeophysicalLaboratoryattheCarnegieInstitutionforScience.R.A.wasfunded
byaNSFGraduateResearchFellowshipthroughNSFgrantnumberDGE-0718124,anNSFIGERTgranttotheUniversityofWashingtonAstrobiologyProgram,and
theARCSFoundation.Thefundershadnoroleinstudydesign,datacollectionandanalysis,decisiontopublish,orpreparationofthemanuscript.
CompetingInterests:Theauthorshavedeclaredthatnocompetinginterestsexist.
*Email:[email protected]
Introduction structures [5]. Such biofilms, which are likely to occur within
the subsurface as well, host high-density communities with
The deep subsurface below hydrothermal systems hosts a high potentially highcontactrates betweenorganisms.
diversity of archaea, bacteria, and viruses that must tolerate
The dynamic, diverse and dense nature of this habitat should
extremely variable environmental conditions. High-temperature, fosterfrequentexchangeofgeneswithinthemicrobialcommunity.
reducedhydrothermalfluidsmixwithcold,oxidizedseawaterboth Previous work with vent samples has shown that the genes
above and below the seafloor to establish strong gradients in responsibleforthisprocess,includingtransposasesandintegrases,
temperature, pH, and chemical and mineralogical composition wereobservedtooccurathighfrequencyincellularmetagenomes
[1–5]. Wide variations in environmental parameters can occur from hydrothermal systems as compared to other environments
over centimeter scales. Constant fluid flux throughout and above [11,12]. Analysis of fully sequenced genomes of thermophiles,
the subsurface transports organisms from one region to the next, including many from vent systems, suggests that gene transfers
exposingthemtoarangeofenvironmentalconditions.Gradients occur more frequently among thermophiles than mesophiles or
that dominate this environment create a highly diverse microbial psychrophiles [13,14] and that these transfers sometimes cross
community consisting of both archaea and bacteria [6]. Physical domains [13–15]. The prevalence of horizontal gene transfer in
and chemical parameters vary according to fluid mixing and vent systems may expand the functional repertoire of a given
volcanic activity, leading to niche partitioning in microbial species, expanding the pangenome and providing access to
communities across both space [1] and time [7,8]. Moreover, different ecological niches. This expanded metabolic flexibility
hyperthermophiles are routinely cultured from fluids that exit at would provide a strong advantage in hydrothermal vent environ-
low temperatures (5–30uC) [9,10], indicating that organisms in ments where fluid flux and environmental gradients expose
ventsystemsarefrequentlyflushedfromtheirnativehabitats,most communitiestowideextremesintemperature,pH,andchemical
likely from the deep subsurface. Microbial communities in composition.
hydrothermal systems are known to form biofilms that coat Here, we use comparative metagenomics to elucidate the role
mineral surfaces, including within high-temperature chimney that viruses play in facilitating gene flow and manipulating host
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ViralandCellularInteractionsinHydrothermalVents
genetic potential in hydrothermal systems. Viruses are known to Comparative analysis of the cellular and viral metagenomes
playpivotalrolesinthetransferofgenesandthealterationofhost from this sample addressed whether viruses have the potential to
phenotype, particularly in the pelagic oceans (see Breitbart 2012 manipulate the physiology or metabolism of their hosts. The
[16] for review). Bacterial and archaeal viruses introduce foreign presence of genes facilitating horizontal gene transfer and
genetic material through transduction and expression of virally lysogenic virus integration described the genetic potential for
encodedgenesduringinfection.Transduction,orvirally-mediated theseprocessesintheventenvironment.Wecomparedtherelative
horizontal gene transfer, occurs on a massive scale in the surface abundanceofgenesintheviralandcellulargenepoolsinorderto
oceans. Up to 1014 transduction events can occur per year in determine the types of genes enriched in the viral gene pool
TampaBayestuary[17],andvirus-likeparticlesthatserveasgene relativetothecellulargenepool.Finally,weaskedhowevolution
transferagents(GTAs)mayboostthesetransductionratesbyone hasshapedtheviralandcellulargenepoolsbyexaminingrelative
million-fold[18].Virusesareknowntoencodeauxiliarymetabolic selection pressures on viral and cellular genes. Together, these
genes, or AMGs, which play critical roles in facilitating analyses provide insight into the broader question of how
biochemical or metabolic processes [19]. For example, cyanoph- evolution has shaped the genomes of viruses and their hosts in
age transcribe and express photosynthesis genes during lytic some ofthemore extremeenvironments oftheplanet.
infection of their cyanobacterial hosts [20–23], potentially to
supportthehostduringinfection,ortoredirecthostmetabolismto Materials and Methods
support phage deoxyribonucleotide biosynthesis [24]. Lysogenic
Sample collection and DNA extraction
viruses can have similar impacts on their hosts: the expression of
genesencodedbyintegratedviruses(alsoknownasproviruses,or We collected a 170-L hydrothermal vent fluid sample from
HulkventattheMainEndeavourFieldontheJuandeFucaRidge
prophage in bacteria) can manipulate host phenotype, such as in
thecaseofthecholeratoxinexpressedbyaprophageintegratedin (47u57.009 N, 129u5.819 W) as described previously [3]. No
specificpermissionswererequiredfortheselocationsorsampling
theVibriocholeraegenome[25].Selectionshouldfavorexpression
activities.Theventfluidwasobtainedusingalargebarrelsampler
ofgeneswithinlysogenicvirusesthatenhancehostfitnesswhilethe
equipped with two 100-L sterile bags. We placed the sample
virus is integrated in the genome. For example, it has been
collection funnel atop a region of diffuse venting, adjacent to a
hypothesized that proviruses express genes that suppress host
colonyoftubewormsonthesideofalargesulfidestructure.While
metabolism to conserve resources under low-energy or low-
the tube worms were surrounded by fluid at measured temper-
nutrient conditions [26].
atures of 13–30uC, the average temperature of the metagenome
Despite increasing evidence that viruses play a crucial role in
fluid sample was calculated from its silica chemistry to be about
manipulatinghostgenotypeandphenotypeinthesurfaceoceans,
125uC[3].Thisresultindicatesthatwemostlikelysampled fluid
this phenomenon has yet to be explored in the dynamic
ranging from cool background seawater to high-temperature
environment of hydrothermal vents. Viruses are abundant in
hydrothermal fluid (up to 300uC) from the sulfide structure
hydrothermal systems[27] and havethe potential toinfect many
adjacent to the sample site, illustrating the dynamic fluid flux of
different taxa of bacteria and archaea [3]. It has been suggested
these systems. The organisms collected in the sample therefore
thatupto80%ofarchaeaandbacteriainthedeepoceancontain
represent a range of habitats in the hydrothermal environment,
proviruses in their genomes [28]. Induction experiments have
including psychrophiles, mesophiles and thermophiles, and
suggestedthatprovirusesareparticularlyabundantinthegenomes
aerobic,microaerophilic,andanaerobicorganisms.Someofthese
ofarchaeaandbacteria fromhydrothermal ventfluidscompared
organisms may have been derived from deep subsurface fluids,
to those in water from the deep ocean or the deep chlorophyll
whereas others from entrained seawater. Having been sampled
maximum [29]. Considering the abundance of viruses in these
fromthesamesite,theseorganismshavethepotentialtocomeinto
systems,andlysogenicvirusesinparticular,severalquestionsarise:
contactwithintheventenvironmentduetodynamicfluidflux.We
do these viruses transfer genes between hosts? Do they express
included available metadata about thisventsample inTable S1.
fitness factors while integrated in the host genome? If so, which
We collected the cellular fraction by filtering the 170 L of
genes are expressed? Do viruses contribute to host genomic
hydrothermal vent fluid through three 0.22ml Steripaks (Milli-
plasticity and facilitate their adaptation to changing conditions?
pore, USA) while the sample and filtrate were held on ice. The
Does selection act differently on viral genes compared to cellular
filtrate was retained for subsequent virus sampling. Filters were
genes?
frozenat–80uCwhileshipboardanduntilsampleprocessing.We
To address these questions, we used a cultivation-independent
extracted DNA from one Steripak using a modified DNA
approachthatprovidesacommunity-wideperspectiveofboththe
extraction procedure described by Anderson et al. [1]. Briefly,
viralgenepoolandthebacterialandarchaealgenepool(hereafter
DNAextractionbuffer(0.1MTris-HCl,0.2 MNa-EDTA,0.1M
referred to as the ‘‘cellular’’ gene pool) in hydrothermal systems.
NaH2PO4, 1.5 M NaCl, and 1% cetyltrimethylammonium
Specifically, we analyzed the unamplified viral and cellular
bromide) was added to each filter, then the filters were capped
metagenomesofhigh-temperaturediffuseflowhydrothermalfluid
and freeze-thawed five times. Lysozyme (50 mg/mL solution),
fromHulkhydrothermalventintheMainEndeavourFieldonthe
proteinaseK(1%solution),andSDS(20%solution)wereaddedto
JuandeFucaRidge.Wecomparedtherelativecontentofeachof
each filter and incubated. Lysate was removed from filters and
these gene pools and inferred the modes of genetic interaction
centrifuged; DNA was extracted from the supernatant using a
betweenvirusesandtheirhosts.Thisanalysisfocusedonaunique
phenol/chloroform/isoamyl extraction method described by
fluid sample that contained organisms native to a wide range of Anderson etal. [1].
ecological niches within the gradient-dominated hydrothermal
For virus collection, we concentrated the sample filtrate using
environment, all with the potential to come into contact through
tangentialflowfiltration(30 kDacutoff)toapproximately400mL
constantfluidflux.Giventhepotentialforgeneandviralexchange ina4uCcoldroom,andfrozeconcentratedfiltrateintosixaliquots
across these niches, these metagenomes can provide insights into at –80uC until further processing. One aliquot was further
interactions within the diverse communal gene pool of the concentrated by adding 10% w/v polyethylene glycol 8000
hydrothermal vent microbialcommunity. (PEG), incubating overnight at 4uC, and centrifuging at 13
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ViralandCellularInteractionsinHydrothermalVents
0006g for 50min. The pellet was resuspended in Tris-EDTA methodofstatisticalanalysisusingadifferenceofmediansanalysis,
bufferandincubatedfor15minwith0.7volumeofchloroformto to determine whether abundance differences were statistically
lyse any remaining cellular contamination. Free DNA was significant. For this analysis, we used a confidence level of 95%
removedbyincubatingwith10%DNAseIfor2 hat37uC,then anda sample size of5000todetermine significance.
inactivated by adding EDTA to a final concentration of 0.02 M.
The QIAamp MinElute Virus Spin Kit (Qiagen) was used to Fragment recruitment
extract the viral DNA, yielding approximately 90ng, which was Cellular metagenomic reads were recruited to genomes of
not amplifiedfordownstreamsequencing.PCRtestsofextracted hydrothermalventisolatesusingNUCmer,partoftheMUMmer
viral DNA using universal 16S archaeal and bacterial primers 3.0package[40],withthefollowingparametersforthecommand
showed no amplification from contaminating cellular 16S rRNA, line:-minmatch10-breaklen1200-maxgap1000-mincluster50.
whereas positive controls of DNA extracted from E. coli showed Fragment recruitments were visualized using mummerplot in the
successful amplification. MUMmer package. Coverage plots were created by using the
show-coordscommandinMUMmer,thenin-housePythonscripts
Metagenomic sequencing were used to calculate coverage for each base pair position.
The viral metagenome was generated on a Roche Genome Coverage plots were created with a convolution function in
SequencerFLX(GSFLX)withGSFLXTitanium454sequencing numpy,using a movingaverage window sizeof 50000.
protocols by the Broad Institute. For the cellular metagenome,
libraries were created using the Nexterra transposon-mediated Calculation of dN/dS
method (Epicentre) at the Josephine Bay Paul Center at the
PriortocalculationofdN/dSratiosforgenesmappedbyeach
Marine Biological Laboratory, then sequenced using Roche
metagenome, metagenomes were subjected to stringent error
Titanium454sequencingprotocolsonaGSFLX.Bothmetagen-
filtering using Prinseq [41] with the following parameters:
omes are publicly available on the MG-RAST v3 database [30],
minimumsequencelengthof60bp;minimummeanqualityscore
withaccessionnumbers4469452.3fortheviralmetagenomeand
of 30; maximum number of allowed Ns per sequence of 4; and
4481541.3 for the cellular metagenome. The viral metagenome
low-complexitythresholdof70(usingEntropy).ThedN/dSratio
waspreviouslydescribedinAndersonetal.[3]andwasuploaded
measuresselectionpressuresbycalculatingwhetherthenumberof
under MG-RAST v2,and isstill available at 4448187.3.
non-synonymous substitutions (dN) in a gene is greater or fewer
WeusedTagCleaner[31]totrimtagsfromthe59endofeach
thanthenumberexpectedbychancecomparedtothenumberof
sequence in the cellular metagenome. Assembly of both the viral
synonymous substitutions (dS). A majority-rule consensus was
and cellular metagenomes was conducted in Geneious [32] using
calculated from the mapped reads; the number of possible
the ‘‘Medium Sensitivity’’ method, with a word length of 14, a
synonymous or nonsynonymous substitutions was then tallied
maximum gap size of 2, maximum gaps per read of 15, and
and compared to the number of actual synonymous and
maximummismatchesof2.Toclassifysequencesusingdi,tri,and
nonsynonymous substitutions.
tetranucleotide analysis, we created a boutique database of
We mapped reads from both the viral and cellular metagen-
bacterial and archaeal virus sequences (Table S2) as a training
omes to the vent isolate genomes using CLC Genomics
set to accompany the existing cellular dataset in PhylopythiaS
Workbench with the criteria of 80% identity and 80% coverage,
[33],whichwasusedtoidentifyarchaea,bacteria,archaealviruses
using previously established benchmarks [42]. Mapping results
and bacterial viruses. Metagenomes were assembled in Geneious
were exported in ACE format; dN/dS was calculated for each
priortoclassificationwithPhylopythiaS;onlycontigsover1000bp
gene using the Python scripts described in Tai etal. [42].
in length wereused.
Polymorphisms were only tallied for positions with a mapping
depthofatleast5X;onlygeneswithatleast100nucleotidesat5X
Enrichment of proviruses and mobile genetic elements
depth were included in the analysis. Redundant genes were
Toidentifythenumbersofreadsineachmetagenomematching deletedfromtheanalysis;onlythedN/dSvalueforthegenewith
lysogenic viruses, metagenomes were compared to a database of higher coverage was retained. The files used to define gene
sequences from the ‘‘Prophages’’ category in the ACLAME coordinatesweredownloadedfromJGIIMG,withtheexception
database[34].Toassessabundanceofmobilegeneticelements,we ofT.kodakarensis,whichwasderivedfroma.gfffileobtainedfrom
compared all metagenomes to a dataset of Pfam seed sequences NCBI. The 95% confidence interval was calculated for all genes
[35] matching transposases, recombinases, resolvases and inte- mapped by the viral and cellular metagenomes with dN/dS less
grases, listed in Table S3, using tblastn with an e-value cutoff of than 1 (subjecttopurifying selection) usingalpha=0.05.
10–5. The number of unique reads with a match to a sequence
fromthequerysequencecollectionwastalliedandnormalizedto Results and Discussion
the number of reads in the metagenome. Only metagenomes
generatedwith454pyrosequencingwereusedfortheanalysis,so General features of the metagenomes
that all metagenomic reads had a length ranging from approxi- Metagenomicsequencingofthecellularandviralfractionsfrom
mately 100to300bp. the large sample of hydrothermal fluid yielded a total of 808,051
and 231,246 sequence reads, respectively. The cellular metagen-
Relative enrichment of gene categories omecontainedreadsfromawidevarietyofbacterialandarchaeal
We tallied gene categories by adding ‘‘abundance’’ counts for taxa, including Thermococcales, methanogens, Marine Groups I
each functional category as defined by the KEGG Orthology andII,Proteobacteria,Bacteroidetes,Firmicutes,andmanyothers,
database [36], the Clusters of Orthologous Groups (COG) reflecting the wide range of ecological niches represented in the
database [37], or the SEED Subsystems database [38] in MG- sample.Figure 1indicatesthatapproximately31%ofthecellular
RAST v3, using an e-value cutoff of 1023. For the combined metagenome and 47% of the viral metagenome (virome)
analysisof20cellularmetagenomesand23viralmetagenomes,all sequenceshadnomatchestotheM5NRdatabase(classifiedhere
abundance counts for either viral or cellular metagenomes were as‘‘Unknown’’)[43].An analysisoftheviralmetagenomealone,
tallied together. We used Xipe-Totec [39], a nonparametric including the taxa and diversity of viruses and their general host
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ViralandCellularInteractionsinHydrothermalVents
We annotated reads based on the best matches to the SEED
database, and determined the taxonomy of each contig based on
theannotationofthemajorityofthecontainedreads[3].Manyof
the long, low-coverage contigs were annotated as bacterial or
archaeal, whereas many shorter, high-coverage contigs were
annotated asunknown (Figure S2).
We considered the long, low-coverage contigs with cellular
annotation to be more likely to be derived from cellular
contamination, whereas the high-coverage, shorter contigs with
unknown annotation are more likely to be derived from viruses.
These high-coverage contigs may include certain viral genomes
that occurred at high frequency.
While we attempted to eliminate cellular contamination
through size fractionation and chloroform and DNAse treatment
prior to sequencing, and 16S PCR tests of extracted viral DNA
returnednoamplificationofcellularmaterial,wesoughttofurther
reduce cellular contamination in silico. We created a ‘‘viral
subset’’oftheviralmetagenomeconsistingofreadsassembledinto
contigswithacoverageof8orgreater,orassembledintocontigs
annotatedasviralorunknown.Theaimofproducingasubsetwas
to remove low-coverage contigs more likely to be derived from
cellular contamination. We chose a coverage cutoff of 8 because
most long contigs annotated as bacterial or archaeal had a
coverageofapproximately8orlower(FigureS2).Thegoalofthis
subsetwasnottogeneratea‘‘pure’’viralmetagenomebutrather
to reduce the number of reads that may represent cellular
contamination,whichisfrequentlyanissueinviralmetagenomics
[44,45]. While the high percentage of unknown contigs in viral
metagenomes makes any attempts at removing contamination
difficult, this subset eliminates reads from low-coverage contigs
with bacterial or archaeal annotation that are more likely to be
derivedfromcellularcontamination.Exceptinspecificcasesnoted
Figure1.Piechartsshowingbreakdownofreadclassification below,theanalysespresentedhereorinthesupplementaryfigures
forthecellularmetagenome(A)andtheviralmetagenome(B) include both the original virome as well as the ‘‘viral subset’’ so
according to annotation by the M5NR database. Reads were that bothmay becompared.
annotatedwithaminimume-valuecutoffof1e-05.
doi:10.1371/journal.pone.0109696.g001
Assessing the potential for horizontal gene transfer
Toassessthedegreetowhichcellsandvirusesinhydrothermal
range,hasbeenpublished previously[3].Closematchesbetween
ecosystemsarecapableofhorizontalgenetransferorintegrationof
CRISPR spacers identified in the cellular metagenome and
proviruses, we determined the relative abundances of provirus
sequencesintheviralmetagenomesuggestanactiveandrelatively
genes(Table1)andgenesrelatedtoDNAtransferormobilization
recent relationship between the two gene pools (see File S1).
(Table 2) in the hydrothermal vent cellular and viral metagen-
Classification of the cellular and viral metagenomes showed that
omes.Weusedthe‘‘Prophage’’datasetintheACLAMEdatabase
only2%ofthereadsfromthecellularfractionmatchedarchaeal
[34] to identify provirus-related proteins in 22 pyrosequenced
genes,whereasnearly8%oftheviralmetagenomereadsmatched
cellular metagenomes. These metagenomes were chosen to
archaeal genes (Figure1). Nucleotide signature matching of
represent a range of aquatic and terrestrial environments, while
assembled contigs longer than 1000bp using PhylopythiaS [33]
controllingforsequencingmethod.Table 1indicatesthatrelative
indicated that a disproportionate percentage of contigs in both
to the 22 cellular metagenomes, the hydrothermal vent cellular
metagenomes matched nucleotide compositional patterns of
metagenomecontainedahighpercentageofreads(approximately
archaeal viruses, given that bacterial reads dominate both 4%) that match provirus-coding regions. This result provides
metagenomes (Figure S1). The percentage of contigs matching compelling molecular evidenceof abundant provirusesincellular
bacterial nucleotide compositional patterns was greater than the genomes in vents and complements descriptions of high propor-
percentageofcontigswitharchaealpatternsbyaratioof2.8to1 tions of lysogenic cells in vents and the deep ocean based upon
inthecellularmetagenome.However,contigsmatchingbacterial mitomycinCinductionexperiments[28,29].Wealsoanalyzedthe
viruspatternsoutnumberedcontigswitharchaealviruspatternsby relative abundance of mobile genetic elements in 40 viral and
only 1.8 to 1 in the viral metagenome. Taken together, these cellular metagenomes, also selected to represent a range of
observations suggest that archaeal viruses may be disproportion- environments,andcontrolledforsequencingmethod.Wefounda
ally abundant in the vent habitat compared to the relative relative enrichment of mobile genetic elements in both the viral
abundance of bacteria toarchaea. and cellular gene pools at Hulk hydrothermal vent (Table2).
Assembly of viral metagenome contigs yielded many short, Thus, not only do the genomes of archaea and bacteria in vents
high-coverage(.20Xcoverage)contigsshorterthan6 kb(Figure encodeahigherabundanceofmobileelements,onaverage,than
S2). The cellular metagenome did not exhibit contigs with such genomes native to other habitats, but vent viruses encode a high
highcoverageandshortlength.Incontrast,severalcontigsinthe abundance of mobile elements as well. These data suggest that
viralmetagenomehadrelativelylowcoveragebutwerequitelong. selection has favored enrichment of mobile elements in these
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ViralandCellularInteractionsinHydrothermalVents
e
m
nome geno
mber Metage 5 alMeta
Accessionnu 4443713.3 4481541.3 CAM_PROJ_Ice 4443725.3 4447970.3 4440055.3 CAM_P_000054 4441681.3 4440059.3 4440425.3 4440329.3 4440440.3 4440961.3 4459941.3 4459940.3 4440426.3 4440061.3 4440419.3 4440973.3 CAM_PROJ_Cor 4440282.3 4440041.3
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se. Reference – Thisstudy Simonetal.,2009 – Belda-Ferreetal.,2012 Anglyetal.,2009 Bakeretal.,2012 Brulcetal.,2009 Anglyetal.,2009 Rodriguez-Britoetal.,2010 Swanetal.,2010 Rodriguez-Britoetal.,2010 Biddleetal.,2008 Biddleetal.,2008 Biddleetal.,2008 Rodriguez-Britoetal.,2010 Desnuesetal.2008,Dinsdaletal.,2008 Rodriguez-Britoetal.,2010 Biddleetal.,2008 VegaThurberetal.,2009 Edwardsetal.,2006 Dinsdaleetal.,2008
a
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‘‘Prophage’’groupingoftheACLAMEdata Samplingdetails MontereyBay,California,surfacewaters,October JuandeFucaRidge,NortheastPacificOcean,2198mdepth GlacialiceoftheNorthernSchneeferner,Germany BermudaAtlanticTime-Seriessite Dentalplaquefrom25humanvolunteers Healthyaquaculturedfish,SanDiego,CA HydrothermalplumesfromGuaymasBasin,CA Fiber-adherentmicrobiomefromcowrumen Samplesfromaquaculturedfishgutcontents Salinity12–14%fromsolarsalterns,California Sulfidic,anoxicsedimentsoftheSaltonSea Watersamplesfromaquaculturefacilityraisingstripedbass PeruMarginODPLeg201Site1229,1meterbelowseafloor PeruMarginODPLeg201Site1229,50metersbelowseafloor PeruMarginODPLeg201Site1229,32metersbelowseafloor Salinity6–8%fromsolarsalterns,California HighborneCay,Bahamas Salinity27–30%fromsolarsalterns,California PeruMarginODPLeg201Site1229,16metersbelowseafloor SamplescollectedattheHawaiiInstituteforMarineBiology Waterandsedimentsinmine,714mbelowsurface,SoudanMine,MN Watersamplednearcoralreefs,ChristmasIsland eregeneratedwithshotgunpyrosequencing.
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gaproteininth Biome Openocean Hydro-thermalvent Glacialice Openocean Human Fish Hydro-thermalvent Cow Fish Saltwater Sediments Freshwater Deepbiosphere-marinesediment Deepbiosphere-marinesediment Deepbiosphere-marinesediment Saltwater Micro-bialites Saltwater Deepbiosphere-marinesediment Coral Deepbiosphere-terrestrialmine Seawater genomeslistedhere
n a
metagenomesmatchi ACLAMEPercentProphagehitsreads 97595.08 325954.03 406953.78 69132.68 55961.65 6101.18 586381.18 36781.15 5410.89 7420.68 9920.61 17120.50 4890.489 2880.455 4790.354 1110.35 8020.311 980.29 1910.157 9470.0900 1930.0778 1200.0672 25.Allmetmume-valueof10
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PercentofreadsincellTable1. MetagenomeReads MontereyBay192162 Hulkhydrothermalvent808051 Glacialice1076539 NorthAtlanticSpringBloom257471 Humanoralmicrobiota339503 Healthyfishmicrobiota51498 GuaymasBasin4970673 Cowrumen320471 Healthyfishmicrobiota60580 Mediumsalinitysaltern108725 SaltonSea161912 Tilapiafishpond344260 PeruMargin1mbsf100093 PeruMargin50mbsf63258 PeruMargin32mbsf135429 Lowsalinitysaltern31948 Microbialites257573 Highsalinitysaltern33356 PeruMargin16mbsf121414 Poritescompressacoral1053275 SoudanMine248038 LineIslands178628 Matcheswerefoundusingtblastnwithadoi:10.1371/journal.pone.0109696.t001
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ViralandCellularInteractionsinHydrothermalVents
es
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nome WaterVir 40323.3
Accessionnumber CAM_PROJ_IceMetage 4469452.3 4440055.3 4440059.3 4481541.3 4441681.3 4469452.3 4441558.3 CAM_PROJ_Reclaimed 4443713.3 4447970.3 4440065.3 4440440.3 4440419.3 CAM_P_0000545 4441621.3 4440425.3 4441623.3 4443725.3 4440961.3 4440329.3 4441625.3 4440320.34440321.344 4459941.3
2
Ref Simonetal.,2009 Thisstudy Dinsdaleetal.,2008 Anglyetal.,2009 Thisstudy Brulcetal.,2009 Andersonetal.,2011a Lopez-Buenoetal.,2009 Rosarioetal.,2009 - Belda-Ferreetal.,201 Anglyetal.,2009 Rodriguez-Britoetal.,2010 Rodriguez-Britoetal.,2010 Bakeretal.,2012 Anglyetal.,2006 Rodriguez-Britoetal.,2010 Anglyetal.,2006 – Biddleetal.,2008 Swanetal.,2010 Anglyetal.,2006 Desnuesetal.,2008 Biddleetal.,2008
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nt. Samplingdetails GlacialiceoftheNorthernSchneeferner,Germa JuandeFucaRidge,NortheastPacificOce2198mdepth Healthyaquaculturedfish,SanDiego,CA Samplesfromaquaculturedfishgutcontents JuandeFucaRidge,NortheastPacificOce2198mdepth Fiber-adherentmicrobiomefromcowrumen JuandeFucaRidge,NortheastPacificOce2198mdepth Freshwateroligotrophiclake,ByersPeninsula,Antarctica(summer) Viralfractionofreclaimedwater MontereyBay,California,October2000,surfacewaters Dentalplaquefrom25humanvolunteers Samplesfromaquaculturedfishgutcontents Watersamplesfromaquaculturefacilityraisingstripedbass Salinity27–30%fromsolarsalterns,California HydrothermalplumesfromGuaymasBasin,CA 10–3246m,Fall2002,ArcticOcean Salinity12–14%fromsolarsalterns,California 0–245m,sampledoverseveraldates,BayofBritishColumbia BermudaAtlanticTime-Seriessite PeruMarginODPLeg201Site1229,1meterbelowseafloor Sulfidic,anoxicsedimentsoftheSaltonSea 0–164m,sampledoverseveraldates,GulfofMexico PozasAzules,Mexico;RioMesquites,Mexico;HighborneCay,Bahamas PeruMarginODPLeg201Site1229,50metersbelowseafloor
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PercentTable2. Meta-genomes Glacialice Hydro-thermalvent Healthyfishmicrobiota Healthyfishmicrobiota Hydro-thermalvent Cowrumen Hydro-thermalvent AntarcticLakesummer Reclaimedwater MontereyBay Humanoralmicrobiota Healthyfishmicrobiota TilapiaPond Highsalinitysaltern GuaymasBasin ArcticOcean Mediumsalinitysaltern BayofBritishColumbia NorthAtlanticSpringBloom PeruMargin1mbsf SaltonSea GulfofMexico Micro-bialites PeruMargin50mbsf
PLOSONE | www.plosone.org 6 October2014 | Volume 9 | Issue 10 | e109696
ViralandCellularInteractionsinHydrothermalVents
All
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Ref Edwardsetal.,2006 Lopez-Buenoetal.,2009 VegaThurberetal.,2009 Rodriguez-Britoetal.,2010 Biddleetal.,2008 Swanetal.,2010 Rodriguez-Britoetal.,2010 Rodriguez-Britoetal.,2010 Rodriguez-Britoetal.,2010 Biddleetal.,2008 VegaThurberetal.,2009 McDanieletal.,2008 Rodriguez-Britoetal.,2010 Breitbartetal.,2009 Anglyetal.,2006 esfoundusingtblastn
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Samplingdetails Waterandsedimentsinmine,714mbelowsurface,SoudanMine,MN Freshwateroligotrophiclake,ByersPeninsula,Antarctica(spring) PoritescompressacoralsamplescollectedattheHawaiiInstituteforMarineBiology Salinity6–8%fromsolarsalterns,California PeruMarginODPLeg201Site1229,32metersbelowseafloor Sulfidic,anoxicsedimentsoftheSaltonSea Watersamplesfromaquaculturefacilityraisingstripedbass Salinity6–8%fromsolarsalterns,California Salinity12–14%fromsolarsalterns,California PeruMarginODPLeg201Site1229,16metersbelowseafloor PoritescompressacoralsamplescollectedattheHawaiiInstituteforMarineBiology ProphagesinducedwithmitomycinCfromTampaBaywatersamples Salinity27–30%fromsolarsalterns,California HighborneCay,Bahamas 80m,sampledJune2005,SargassoSea atabasefileincludedinsupplementarymaterial).
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Cont.Table2. Meta-genomesCellularorviralReads SoudanMinecellular248038 AntarcticLakespringviral31691 Coralviral36354 Lowsalinitysalternviral56810 PeruMargin32mbsfcellular135429 SaltonSeaviral27689 TilapiaPondviral231521 Lowsalinitysalterncellular31948 Mediumsalinityviral33291saltern PeruMargin16mbsfcellular121414 Coralcellular105327 TampaBayviral257075 Highsalinitysalternviral136564 Microbialitescellular257573 SargassoSeaviral399343 Theseincludetransposases,integrases,recombimetagenomeslistedhereweregeneratedwithdoi:10.1371/journal.pone.0109696.t002
PLOSONE | www.plosone.org 7 October2014 | Volume 9 | Issue 10 | e109696
ViralandCellularInteractionsinHydrothermalVents
Figure2.RecruitmentplotofmetagenomicreadstoCaminibactermediatlanticusTB-2.Cellularmetagenomicreadsweremappedtothe
longestcontigofthedraftgenomeofC.mediatlanticusTB-2,withpercentsimilarityonthey-axisandbasepairnumbersonthex-axis(A).Coverage
plot of read recruitment is shown per base pair, with blue line showing actual coverage and green line showing a convolution function of the
coverageplotusingaweightingof50000(B).PercentGCplotforthesamecontigisshownonthesamescale,withbasepairnumbersmarkedbelow
(C),andareannotatedwithCRISPRlociandrecombinasesorintegrasesfoundonthecontig.OrangeshadingshowsthelocationofCRISPRlocionthe
genome;greenshadingshowsthelocationoftwometagenomicislands.
doi:10.1371/journal.pone.0109696.g002
cellularandviralgenomes,potentiallyleadingtoincreasedratesof [46].However,identificationofauxiliarymetabolicgenes(AMGs)
horizontal geneflow among cells andviruses. intheseviralgenomesisdifficult,partlyduetothehighabundance
ofunknowngenesandpartlybecausetheboundariesbetweenthe
Evidence of genomic plasticity in vent genomes viral andcellular genomeare not always clearlydelineated.
Havingfoundevidenceforgenetransferandviralintegrationin To better identify regions that have been transferred in vent
the genomes of vent cells and viruses, we sought evidence for genomes, we compared genomes from bacterial or archaeal
either lysogenic virus integration or gene transfer events in other isolates with sequences sampled directly from the environment.
hydrothermal vent isolates. Of the 34 available fully sequenced This strategy can identify potential hypervariable regions, or
vent genomes, 20 (59%) contain integrated viruses (Table S4). ‘‘genomicislands,’’thatdisplaylowercoveragethantherestofthe
Mostof these virusesencode capsidgenes orgenes suchas DNA genome [47–49]. Previous work with Haloquadratum walsbyi
ligases, which have been identified before as being particularly DSM 16790 [48] and Prochlorococcus genomes [47] used this
abundant in the viral fraction of this hydrothermal vent sample techniquetoidentifygenomicislandsthatmostlikelyrepresented
PLOSONE | www.plosone.org 8 October2014 | Volume 9 | Issue 10 | e109696
ViralandCellularInteractionsinHydrothermalVents
regions of virally-mediated lateral gene transfer; in the case of databases, we annotated reads in both the viral and cellular
Prochlorococcus, these genes are differentially expressed under metagenomes according to three functional databases: the SEED
light andnutrient stress[47]. Subsystems database [38], the Clusters of Orthologous Groups
We performed fragment recruitment of the hydrothermal vent (COG) database [37], and the KEGG Orthology (KO) database
cellular metagenome against the genomes of all isolates of [36] (Figures 3 and 4). Among all three databases, certain trends
hydrothermal vent bacteria and archaea available in the NCBI appeared. First, in all three cases the results indicated a high
database. In most cases, the metagenome did not recruit to the similarity in the overall relative abundances between functional
isolate genomes with high enough coverage to yield useful data. genesinthecellularandviralfractions.Asimilarstudyofrelative
Nautilia profundicola AmH successfully recruited reads at high abundances of functional groups in viral and cellular metagen-
coverage,butnometagenomicislandswerefound.Recruitmentof omes,conductedbyKristensenetal.[44]basedondatacollected
thecellularmetagenometothelongestcontig(ABCJ01000001)of byDinsdaleet al.[53],foundasimilartrend.Whilesomeofthisis
the draft genome of Caminibacter mediatlanticus TB-2, a most likely due to cellular contamination in the viral fraction, as
chemolithotrophic, nitrate-ammonifying Epsilonproteobacterium well as the presence of viruses in the cellular fraction, Kristensen
that was isolated from the walls of a hydrothermal vent chimney et al. suggest this trend may also be due in part to the choice of
ontheMid-AtlanticRidge[50],yieldedanumberofregionswith available functional categories, which encompass functions that
relatively low coverage (Figure2). The first, a region with aregenerallycellularratherthanviral.However,despitethelikely
relativelylowcoveragebetween160000and200000bp,contains presenceofcontaminationinthesedatasets,directcomparisonin
a series of CRISPR loci. CRISPR regions are dedicated to viral thiswayenablesustocomparetherelativeenrichmentofcertain
andplasmidimmunitybyeffectivelycreatingalibraryofprevious types of genes in the viral and cellular gene pools. Comparisons
infection,andthereforearehighlyspecifictoagivenenvironment. betweentheviralsubsetandthecellularmetagenomeareshownin
Therefore recruitment to CRISPR loci should naturally yield Figures 3 and 4; comparisons between the cellular metagenome,
lower coverage, particularly for a metagenome sampled in a original virome,andviralsubset are shown inFigure S3.
different geographic location than this isolate. Aside from the There was a statistically significant enrichment of reads
CRISPRregion,recruitmentyieldedtwodistinctgenomicislands: matching phage, prophage, and transposable elements in the
one region of approximately 40kbp, followed by a second low- viromerelativetothecellularmetagenome(2.3%vs.1.5%).These
coverage region of approximately 15kbp (Figure 2), separated annotations were made according to the SEED Subsystems
fromeachotherbya20kbpregionthatincludesaribosome.The classification (Figure 3A), and we used Xipe-Totec [39] to assess
first genomic island coincides with a region with relatively high statisticalsignificance.Mostviralgenehitsweretodistantlyrelated
GCcontent,whichsuggeststhisregionwastransferredintotheC. head-tailvirusesandcyanophage.Thelowpercentageofmatches
mediatlanticus genome. A phage integrase gene is located toviralsequencesoverallislikelydueinparttotherelativelackof
approximately 58kbp downstream of the 39 end of the first environmental viral sequences in public databases. We also
genomic island, though its presence there is not necessarily observed an enrichment of reads matching cofactors, vitamins,
conclusiveevidencethattheregionwasintroducedbyavirus.The prosthetic groups and pigments in the viral fraction (Figure 3A),
firstgenomicislandbeginsnearatRNAgene,acommonsitefor whichfalls inline withstudies identifying these types ofgenes on
integration of horizontally transferred regions [51]. Many of the cyanophage genomes. Genes encoding vitamin B12 [53,54], and
genesinboththefirstandsecondgenomicislandsencodeproteins thepigmentspsbA/D[55–58]andpebS[23]havepreviouslybeen
that interact with the environment, including sugar and nitrate identified on cyanophage genomes. These virally encoded genes
membrane transporters, and proteins related to energy metabo- arethoughttosupplementhostmetabolismduringinfection,and
lism, including hydrogenases (Table S5). Possession of a diverse similar processes mayoccur inthisvent ecosystem.
suiteofhydrogenasescanenhancemetabolicflexibilityinvariable We observed a statistically significant enrichment of reads
redox conditions, and has been observed in other Epsilonproteo- matching amino acids and derivatives in the cellular fraction
bacteria isolatedfromhydrothermal vents [52]. relative to the viral fraction, according to the COG (Figure 3B)
The presence of this hypervariable region indicates that andKO(Figure4A)databases.Theseincludegenesrelatedtothe
genomic islands from genomes in vent environments encode biosynthesis and metabolism of various amino acids, and are
genes related to environmental interactions and energy metabo- evidently not commonly carried on viral genomes in vent
lism. The genomic island shown here is unique to a vent isolate ecosystems, suggesting that viruses rely on their hosts for amino
from the Mid-Atlantic Ridge. The C. mediatlanticus strains acidbiosynthesis.
present in our sample on the Juan de Fuca Ridge most likely We also observed enrichment in reads related to replication,
have genomic islands of their own, though these cannot be recombination and repair in the viral fraction, as annotated by
identifiedwithoutafullysequencedstrainfromtheJuandeFuca both the COG and KO databases (Figure3B, Figure 4A). These
Ridge.NoneofthesequencedstrainsfromtheJuandeFucaRidge genes probably serve necessary functions in the synthesis and
had high enough coverage with our metagenome to identify replication of viralDNA during thecourseof viralinfection, and
genomicislands.However,thegenomicislandonC.mediatlanti- include genes like DNA and RNA polymerase, which are
cusprovidesevidenceofhorizontaltransferofgenesthatfacilitate commonly encoded on viral genomes. The ‘‘replication and
metabolic flexibility in an environment that is very similar to the repair’’ category includes DNA ligases, which occur at very high
Juan de Fuca Ridge. From this we can hypothesize that genes
abundances inthevirome,aspreviously reported [46].
related to environmental interactions and metabolic activity are
Finally,wealsoobservedastatisticallysignificantenrichmentof
transferred in our samplesite.
genes related to energy metabolism as annotated by the KO
database. Among reads annotated as matching the energy
Quantification of relative gene enrichment in the viral metabolism sub-category, 6.5% from the cellular metagenome
fraction and 8.4% from the viral subset were annotated as sulfur
Wenextsoughttodeterminewhetherthereweredifferencesin metabolism, whereas 8.2% of cellular versus 3.7% of viral
the relative enrichment of gene types in the cellular and viral metagenomereadsannotatedasbelongingtomethanemetabolism
fractions. In order to account for biases or omissions in various (Figure 4B). The enrichment of energy metabolism genes corre-
PLOSONE | www.plosone.org 9 October2014 | Volume 9 | Issue 10 | e109696
ViralandCellularInteractionsinHydrothermalVents
Figure 3. Functional comparisons of the hydrothermal vent cellular and viral subset metagenomes according to the SEED
subsystemsandClustersofOrthologousGroups(COG)databases.MetagenomeswereannotatedinMG-RASTwithaminimume-valueof
1e-03andaminimumidentitycutoffof60%.Asingleasteriskindicatesasignificantdifferenceinabundancebetweentheviralsubsetandthecellular
metagenome.A)MatchestotheSEEDsubsystemsdatabase;B)matchestotheCOGdatabase.
doi:10.1371/journal.pone.0109696.g003
sponds with what we might expect given the observation of regarding these metagenomes are summarized in Table S6; the
auxiliary metabolic genes (AMGs) in viral genomes from the functional profiling analysis is depicted in Figure S4. The overall
surfaceoceans.Asimilarenrichmentinenergymetabolismgenes patternsofrelativegeneabundancebetweentheviralandcellular
was found in the viral fraction relative to the cellular fraction in fractionsweresimilartothoseobservedinoursample.Specifically,
samples from the Indian Ocean [59]. Similarly, photosynthesis inotherenvironmentsfunctionalannotationsofviralandcellular
genes encoded in cyanophage are known to be expressed during metagenomic reads were strongly correlated, but viral metagen-
viral infection [20,60,61], and modeling work has indicated that omes were more enriched in reads annotated as nucleotide
these photosynthesis genes can enhance host fitness [62,63]. For metabolism and replication and repair. However, the relative
lytic viruses, energy metabolism genes may be expressed as a enrichment of genes related to energy metabolism in the viral
meanstosupplementhostmetabolismortoredirectresourcesfor fraction, while apparent in the vent environment, was not a
phage particle synthesis. Our analysis of fragment recruitment universal characteristic ofviruses inother environments.
(Figure 2) indicated that genes related to energy metabolism had
been successfully transferred between genomes in the past, and Does selection operate differentially on viral and cellular
virusesarepotentialvectorsforsuchgenetransfer.Onepotential genes?
explanation for this enrichment, in line with the fragment Integral to the study of viral and cellular evolution is
recruitmentresults,isthathighlyabundantprovirusesinthevent understanding how selection shapes the viral and cellular gene
systemexpressthesegeneswhileintegratedinthehostgenome.By pools,andwhichgenesaresubjecttostrongerorweakerselection.
providingtheirhostswithneworsupplementalmeansofsurviving Differing life strategies for cells and viruses, as well as disparate
a challenging, dynamic environment, these proviruses boost host rolesforfunctionalgeneswithineachoftherespectivegenepools,
fitness, andinturn,enhance theirownfitness. shouldleavedifferentselectivesignaturesongeneswithineachof
Tocomparethese resultswithothercellular-viral metagenome these gene pools. To measure differential selection among viral
comparisons, we conducted an analysis of 20 cellular metagen- and cellular genes, we calculated dN/dS ratios of genes encoded
omes and 23 viral metagenomes from other environments, all by the viral and cellular fractions. The challenge of calculating
sequenced with 454 pyrosequencing and annotated with the KO dN/dS ratios with shotgun metagenomic data is that the short
database.Eachofthecellularmetagenomeshadatleastoneviral sequencesmakeitdifficulttoalignlongblocksofsequencestothe
counterpart sampled from the same environment. Metadata same region of a gene. To circumvent this problem, we used the
PLOSONE | www.plosone.org 10 October2014 | Volume 9 | Issue 10 | e109696