ORIGINAL ARTICLE

Sulfur oxidizers dominate carbon fixationat a biogeochemical hot spot in the dark ocean

Timothy E Mattes1, Brook L Nunn2, Katharine T Marshall3, Giora Proskurowski3,Deborah S Kelley3, Orest E Kawka3, David R Goodlett4, Dennis A Hansell5 andRobert M Morris1

1Department of Civil and Environmental Engineering, University of Iowa, Iowa City, IA, USA; 2Department ofMedicinal Chemistry, University of Washington, Seattle, WA, USA; 3School of Oceanography, Universityof Washington, Seattle, WA, USA; 4Department of Pharmaceutical Sciences, University of Maryland Schoolof Pharmacy, Baltimore, MD, USA and 5Rosenstiel School of Marine and Atmospheric Science, University ofMiami, Miami, FL, USA

Bacteria and archaea in the dark ocean (4200 m) comprise 0.3–1.3 billion tons of actively cycledmarine carbon. Many of these microorganisms have the genetic potential to fix inorganic carbon(autotrophs) or assimilate single-carbon compounds (methylotrophs). We identified the functions ofautotrophic and methylotrophic microorganisms in a vent plume at Axial Seamount, wherehydrothermal activity provides a biogeochemical hot spot for carbon fixation in the dark ocean.Free-living members of the SUP05/Arctic96BD-19 clade of marine gamma-proteobacterial sulfuroxidizers (GSOs) are distributed throughout the northeastern Pacific Ocean and dominatedhydrothermal plume waters at Axial Seamount. Marine GSOs expressed proteins for sulfur oxidation(adenosine phosphosulfate reductase, sox (sulfur oxidizing system), dissimilatory sulfite reductaseand ATP sulfurylase), carbon fixation (ribulose-1,5-bisphosphate carboxylase oxygenase (RuBisCO)),aerobic respiration (cytochrome c oxidase) and nitrogen regulation (PII). Methylotrophs and ironoxidizers were also active in plume waters and expressed key proteins for methane oxidation andinorganic carbon fixation (particulate methane monooxygenase/methanol dehydrogenase andRuBisCO, respectively). Proteomic data suggest that free-living sulfur oxidizers and methylotrophsare among the dominant primary producers in vent plume waters in the northeastern Pacific Ocean.The ISME Journal advance online publication, 11 July 2013; doi:10.1038/ismej.2013.113Subject Category: Microbial ecology and functional diversity of natural habitatsKeywords: Axial; hydrothermal; proteomics; bacteria; SUP05; Arctic96BD-19; methylotroph

Introduction

Recent genomic studies demonstrate that many ofthe 6.5� 1028 bacteria that inhabit the dark ocean(4200 m) have the genetic potential to fix carbon(Reinthaler et al., 2010; Swan et al., 2011). Theseinclude autotrophic and methylotrophic bacteriathat have genes to fix inorganic carbon and assim-ilate single-carbon compounds, respectively. Hydro-thermal vents are characterized by steep physicaland chemical gradients that are established as hotfluids from the deep subsurface mix with coldoxidized seawater. The stable neutrally buoyantplumes that form above hydrothermal vents containapproximately 0.01% vent fluid (Lupton et al., 1985)and are enriched in sulfides, iron, manganese,

methane (CH4), hydrogen (H2) and other reducedcompounds relative to background seawater (Lilleyet al., 1995). This steady supply of chemical energyhas the potential to fuel autotrophic and methy-lotrophic activities in the dark ocean.

Vent-associated microbial communities are com-monly dominated by bacteria (especially, alpha-,gamma- and epsilon-proteobacteria) that likelyparticipate in the oxidation of reduced sulfurcompounds, ammonia, iron, manganese, CH4 andH2 (Huber et al., 2003, 2006, 2007; Opatkiewiczet al., 2009; Dick and Tebo, 2010; Sylvan et al.,2012). Members of the SUP05/Arctic96BD-19 cladeof marine gamma-proteobacterial sulfur oxidizers(GSOs) are among the dominant groups identifiedat venting locations (Sunamura et al., 2004;Anantharaman et al., 2013; Anderson et al., 2013).Marine GSOs were first identified in the tissues ofclams and mussels living at hydrothermal vents andcold seeps (Cavanaugh et al., 1987; Distel et al.,1988). Members of this group are closely related tothiotrophic bacteria that obtain energy from the

Correspondence: RM Morris, School of Oceanography, Universityof Washington, Seattle, WA 98195, USA.E-mail: morrisrm@uw.eduReceived 8 March 2013; revised 25 May 2013; accepted 31 May2013

The ISME Journal (2013), 1–12& 2013 International Society for Microbial Ecology All rights reserved 1751-7362/13

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oxidation of reduced sulfur compounds (Distelet al., 1988). Similar to other symbiotic relationshipsin sulfide-rich marine ecosystems, the host providesaccess to reduced sulfur sources for autotrophicbacteria and the bacterial symbionts provide thehost with a source of organic carbon (Childresset al., 1991; Robinson and Cavanaugh, 1995).

Abundant and free-living marine GSOs haverecently been identified in diverse seawater samples(Lavik et al., 2009; Walsh et al., 2009; Swan et al.,2011). Marine GSOs accounted for 45% of the 16Sribosomal RNA (rRNA) gene clones recovered froman oxygen-minimum zone in the South Atlantic and37% of the bacterial 16S rRNA genes recovered froman anoxic fjord in British Columbia (Lavik et al.,2009; Walsh et al., 2009). Marine GSOs dominatedbacterial communities (88–90%) in the plume layerin the Suiyo Seamount caldera (Sunamura et al.,2004) and were among the key groups identified indiffuse-flow hydrothermal vent fluids in 1998–2000following an eruption at Axial volcano in 1998(Huber et al., 2006). Recent studies have indicatedthat marine GSOs are abundant and active in theGuaymas Basin in the Gulf of California (Lesniewskiet al., 2012; Anantharaman et al., 2013).

We used a tandem mass spectrometry (MS/MS)-based proteomics approach to identify expressedproteins in hydrothermal plume waters at AxialSeamount, an active volcano along the Juan de FucaRidge spreading center (Caress et al., 2012; Chadwicket al., 2012; Dziak et al., 2012). We also comparedmicrobial communities in plumes with microbialcommunities in other areas of the northeasternPacific Ocean not influenced by hydrothermal sys-tems. Our results suggest that chemolithoautotrophicmarine GSOs were the dominant primary producersin hydrothermal plume fluids, with methanotrophicand iron-oxidizing bacteria contributing to a lesserextent. These data support previous findings, whichcombined suggest that this ubiquitous group of free-living marine GSOs are active in diverse deep oceanenvironments (Swan et al., 2011; Anantharamanet al., 2013; Lesniewski et al., 2012).

Materials and methods

Sample collectionAll samples were collected onboard the R/VThomas G Thompson during a University ofWashington-led research cruise in support of theNational Science Foundation’s Ocean ObservatoryInitiative—Regional Scale Nodes cruise (19 Augustto 1 September 2011) from Seattle, WA, to HydrateRidge and Axial Seamount (Figure 1). Water samplesfor microbial and chemical analyses were collectedusing a conductivity, temperature and depth(CTD) rosette profiler equipped with 12 l Niskinbottles. Samples were collected from five differentstations (CTD7 Cascadia Basin (lat: 45.8602/lon: � 127.9353), CTD8 base of Axial Seamount

(lat: 45.8202/lon: � 129.7567), CTD11 ASHES ventfield (lat: 45.9339/lon: � 130.0136), CTD13 Coquillevent (lat: 45.9264/lon: � 129.9803) and CTD17ASHES vent field (lat: 45.9340/lon: � 130.0138)).Sample numbers, depths and types of analyses areshown in Supplementary Table 1.

Contextual data and site descriptionPartial and full water column profile measurementswere conducted using a rosette-mounted instrumentpackage that included a Seabird 9plus CTD with dualtemperature and conductivity sensors, a Seabird 43oxygen sensor (calibrated to onboard Winkler titra-tions) and a WET Labs C-Star transmissometer. Usingthe downcast profile measurements, the position and

(408bp)

(324bp)

< 100m 100mPlume

Axis 1

Axi

s 2

130°W40°N

45°N

50°N

CTD7CTD8

CTDs 11,13,17Axial caldera

Cascadia BasinAxial base

–>

Figure 1 Station locations and NMS ordination analysis ofmicrobial communities in the northeastern Pacific Ocean.(a) Stations were located in the Cascadia Basin (CTD7) and atAxial Seamount (CTD8, 11, 13 and 17). (b) NMS analyses ofbacterial communities determined by TRFLP analyses. (c) NMSordination depicting the relative abundance of a 408-bp TRF thatdominated samples collected from a hydrothermal vent plume.(d) NMS ordination illustrating the relative abundance of a 324-bpTRF that was ubiquitous in samples collected at depths X100 m.Sample sizes in panels c and d indicate relative abundance.

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extent of the hydrothermal plume was identified bylarge negative deflections in beam transmission(corresponding to the high particulate load generatedfrom precipitating metal sulfides in the hydrothermalfluid) and subtle positive anomalies in temperature(corresponding to the heat input from high-tempera-ture fluids), following well-established plume identi-fication practices (Baker et al., 1993). At the summit ofAxial Seamount, hydrothermal plumes were 30–100 m thick, with the neutrally buoyant plume havinga typical rise height of 75–200 m above the seafloor.

During the profile upcast, 12 l Niskin watersampling bottles (General Oceanics, Miami, FL,USA) were triggered at depths determined to bewithin the hydrothermal plume and at regularintervals in the water column above the plume.Water samples were analyzed for CH4 and H2

concentrations using shipboard gas chromatography.Samples were headspace extracted and inlet into agas chromatograph (SRI Instruments, Torrance, CA,USA) configured with a helium carrier, a 30 m 5 Amol sieve column, a 50 1C isothermal temperatureprogram, and flame ionization and pulse dischargedetectors. This method provided the sensitivity tomeasure the low gas concentrations of backgroundseawater (CH4: 0.5–1nM, H2: 0.1–0.5 nM). Hydrother-mal fluids are enriched in both CH4 and H2 (Lilleyet al., 1982; Proskurowski et al., 2008).

Nutrients, dissolved organic carbon and total dissolvednitrogenSamples for nutrient, dissolved organic carbon andtotal dissolved nitrogen analyses were stored frozenin 60 ml high-density polyethylene bottles untilanalysis within 2 months of the completion of thecruise. Nutrient concentrations were assessed byfollowing the protocols of the WOCE HydrographicProgram using a Technicon AAII system at theUniversity of Washington. Dissolved organic carbonand total dissolved nitrogen concentrations wereassessed by high-temperature combustion using aShimadzu TOC-csh with autoinjection (Dicksonet al., 2007). Four-point standard curves usingpotassium hydrogen phthalate and potassiumnitrate were run daily to calibrate the response ofthe high-temperature combustion system. Measure-ments were quality controlled using ConsensusReference Materials distributed to the internationalcommunity by the Hansell Laboratory (Hansell,2005). The Consensus Reference Materials wereanalyzed at regular intervals during each analyticalday. Low-carbon reference water was employed todetermine system blanks. Dissolved organic nitro-gen was determined as the difference in concentra-tions of total dissolved nitrogen and dissolvedinorganic nitrogen (Supplementary Figure 1).

Microbial cell countsMicrobial cells were collected from multiple depths,fixed in filtered formalin at a final concentration of

1%, stored at 4 1C overnight and subsequentlyfiltered (5–10 ml) onto 0.2 mm Osmonics polycarbo-nate filters. Total cell counts were determined bystaining cells from the whole-water and concen-trated seawater sample with the nucleic acid stain4’,6-diamidino-2-phenylindole (DAPI). The suite ofoligonucleotide probes used to enumerate bacteriawas: EUB-27R (CTGAGCCAKGATCRAACTCT), EUB-338Rpl (GCWGCCWCCCGTAGGWGT), EUB-700R(CTAHGCATTTCACYGCTACAC), EUB-700Ral (CTACGAATTTCACCTCTACAC) and EUB-1522R (AAGGAGGTGATCCANCCVCA). The negative controloligonucleotide was 338F (TGAGGATGCCCTCCGTCG) (Morris et al., 2002). Briefly, reactions wereperformed on membrane sections at 37 1C for 16 h inhybridization buffer (900 mM NaCl, 20 mM Tris(pH 7.4), 0.01% (w/v) sodium dodecyl sulfate and15% or 35% formamide) and lineage-specificCy3-labeled oligonucleotide probe suites. A controlhybridization reaction was performed with a low-stringency buffer containing 15% formamide and aCy3-labeled complementary probe (338F). Eachprobe had a final concentration of 2 ng ml�1. Optimalhybridization stringency was achieved by hybridi-zation washes (20 mM Tris (pH 7.4), 6 mM EDTA,0.01% sodium dodecyl sulfate and 70 or 150 mM

NaCl) for two 10-min intervals.DAPI and fluorescence in situ hybridization cell

counts were determined from 15 fields of view usinga Nikon 80i epifluorescence microscope equippedwith a Photometrics CoolSNAPHQ2 digital camera,filter sets appropriate for Cy3 and DAPI and theNIS-Elements Basic Research Acquisition andAnalyses package (Nikon Instruments Inc., Melville,NY, USA). For fluorescence in situ hybridization,DAPI images were segmented and overlain ontocorresponding Cy3 image segmentations to identifypositive probe signals with corresponding DAPIsignals. Negative control counts were determinedusing the same technique and subtracted frompositive probe counts to correct for autofluorescenceand nonspecific binding.

Community structural analysisMicrobial cells were collected for DNA extraction byfiltering 1 liter of seawater onto sterile Supor-2000.2 mm polyethersulfone filters. Cell lysis wasperformed as described previously (Morris et al.,2012) with the following modifications. Onboard,filters were placed in 2 ml cryovials, flash frozen inliquid nitrogen and stored at � 80 1C. To initiate celllysis, filters were thawed on ice and sliced intosections with autoclaved scissors, and then 1 ml ofsucrose lysis buffer (20 mM EDTA, 400 mM NaCl,0.75 M sucrose and 50 mM Tris–HCl, pH 8.4) and20 ml of lysozyme (1 mg ml�1) were added.The filters were incubated for 60 min at 37 1C withshaking prior to adding 20 ml proteinaseK (100 mg ml�1) and 200 ml sodium dodecyl sulfate(10%) and subsequently incubated for 2 h at 55 1C

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with shaking and then stored at � 80 1C until DNAextraction was performed.

DNA was extracted from 600 ml of cell lysateusing a DNeasy Blood and Tissue kit (QIAGEN,Germantown, MD, USA) and used for TerminalRestriction Fragment Length Polymorphism(TRFLP) analysis as described previously (Morriset al., 2012). DNA concentrations were estimated withthe Qubit fluorometer and the Qubit dsDNA HS assaykit. PCRs for TRFLP were conducted with 1–2 ngDNA per reaction by amplifying the 16S rRNA genewith 50 end-labeled phosphoramidite fluorochrome5-carboxy-fluorescein 27F_B (50-AGRGTTYGATYMTGGCTCAG-30), unlabeled 519R (50-GWATTACCGCGGCKGCTG-30) primers and Taq polymeraseas described previously (Morris et al., 2012). PCRproducts were digested overnight at 37 1C withHaeIII. Reaction products were cleaned usingcolumns containing hydrated superfine SephadexG-50. The resulting terminal restriction fragments(TRFs) were resolved along with internal sizestandards (50–500 bp) on an ABI 3730 DNA Analyzer(Applied Biosystems Life Technologies, Carlsbad, CA,USA) located at the Fred Hutchison Cancer ResearchCenter in Seattle, WA, USA.

TRF sizes were estimated with Peak Scanner 1.0(Applied Biosystems). Fragment sizes were roundedto the nearest whole number, and systematic round-ing errors were manually corrected. The resultingdata matrix contained 48 samples (rows) and 382unique 16S rRNA gene TRFs (columns). TRFs wererelativized for nonmetric multidimensional scaling(NMS) analysis by dividing the area of each fragmentby the total area using the software package PC-ORD(McCune and Grace, 2002). Sorenson distances wereused for NMS analysis with a random startingconfiguration, and the resulting solution was con-strained to two dimensions. The final stress for thetwo-dimensional solution was 14.665 with instabilityof 0.00454 when using 40 real-data runs. The axeswere rotated to maximize orthogonality (100%). Axis1 explained 25.7% and axis 2 explained 58.1% of thevariance (both axes explained 83.8% of the variance).The null hypothesis that there was no differencebetween sample groupings was rejected using themulti-response permutation procedure, which evalu-ates groupings with real and randomized data.A chance-corrected within-group agreement statisticof 0.24 indicated within-group homogeneity, and aP-value of 0 indicated that observed group differ-ences were statistically significant.

16S rRNA gene diversityBacterial 16S rRNA gene clone libraries wereconstructed by amplifying community 16S rRNAgenes with bacterial primers 27F_B and 1492R(50-GGYTACCTTGTTACGACTT-30) as describedpreviously (Morris et al., 2012). Briefly, amplifica-tions were performed using community genomicDNA extracted from CTD17 (1450 m) and CTD7

(2850 m), using Apex Taq polymerase (GeneseeScientific, San Diego, CA, USA), and under thefollowing conditions: 35 cycles, annealing at 55 1Cfor 1 min, elongation at 72 1C for 2 min and dena-turation at 94 1C for 30 s. Amplicons were purifiedand cloned using the pGEM-T-Easy vector (Promega,Madison, WI, USA) following the manufacturer’sinstructions. The resulting transformations weresent to High Throughput Sequencing (HTSeq.org,Seattle, WA, USA), where clones were isolated andsequenced by Sanger sequencing using the M13F(50-TGTAAAACGACGGCCAGT-30) and M13R (50-CAGGAAACAGCTATGAC-30) primers (SupplementaryTable 2).

Nearly full-length 16S rRNA gene sequenceswere obtained for frequently occurring lineages byselecting and purifying a subset of clones using theQiagen plasmid mini-prep kit (QIAGEN). Sequen-cing was performed using the following primer pairsby GeneWiz Inc. (La Jolla, CA, USA): M13R, 519F(50-CAGC(A/G)GCCGCGGTAATAC-30), 338F (50-ACTCCTACGGGAGGCAGC-30) and 926R (50-CCGTCAATTC(A/C)TTT (A/G)AGTTT-30). Sequences wereassembled with the CAP3 Sequence Assembly Pro-gram (Huang and Madan, 1999) and annotated byusing the Bayesian method of Wang et al. (2007),which contained a custom training set augmentedwith marine environmental clades (Iverson et al.,2012), and the SILVA least common ancestor classi-fication tool (Pruesse et al., 2007). In silico restrictionanalysis and other DNA sequence manipulationoperations were performed with the Sequence Manip-ulation Suite (Stothard, 2000). Restriction fragmentswere verified for a subset of clones to confirmpredicted fragment sizes. Bacterial 16S rRNAsequences generated during this study were submittedto GenBank (accession nos. KC522839–KC522949).

Phylogenetic relationships of marine GSOsPhylogenetic relationships were determined using asubset of published 16S rRNA gene sequences.A marine GSO reference tree was obtained byselecting nearly complete (41300 bp), high-quality,nonredundant 16S rRNA gene sequences frompublic data sets (n¼ 65). Sequences were firstaligned and trimmed using MUSCLE and thenmanually pruned to maintain tree topology. Amaximum likelihood tree that contained only thehighest quality set of unique sequences (n¼ 50) wasconstructed using RAxML. The GTRGAMMA modelwas used to evaluate 100 tree topologies with 1000bootstrap analyses. Trees were visualized usingFigTree and rooted with Methylococcus capsulatus(GenBank accession no. AJ563935).

Plume proteomicsSeawater (B180 l) was collected from the stablehydrothermal vent plume issuing from the blacksmoker chimney Inferno (CTD17, 1450 m). Whole

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water was transferred to clean 50 l polystyrenereservoirs and concentrated to B230 ml with aPellicon 2 tangential flow filtration system equippedwith a 30-kDa Biomax Polyethersulfone cassette(Millipore Co., Billerica, MA, USA) as describedpreviously (Morris et al., 2010). Cells were collectedand concentrated in approximately 2 h. Concen-trated cells were flash frozen in liquid nitrogen andstored at � 80 1C until further processing at theUniversity of Washington. Cell counts before andafter filtration (6.9� 1010 and 2.9� 1010, respec-tively) indicate that we recovered 42% of the cellspresent in 180 l of hydrothermal vent plume water.Cells in the concentrated sample were divided intoreplicate samples (Av1 and Av2, B115 ml each) andharvested by centrifuging at 4 1C for 60 min(17 000 g). The supernatant was discarded, and cellpellets were rinsed with 100 ml of 20 mM Tris buffer(pH 7.4) and stored at � 80 1C.

Cells were lysed using a titanium sonicatingmicroprobe (20 s, 10 repetitions) in a 6 M urea and50 mM ammonium bicarbonate solution. Disulfidebonds were reduced with dithiothreitol and alky-lated with iodoacetic acid. After additions ofammonium bicarbonate and methanol, 2 mg ofsequence grade trypsin (Promega) was added toeach sample. Enzymatic digestions were incubatedfor 12 h at 37 1C. Resulting peptides were desaltedusing a macro-spin C18 column (NestGroup, South-borough, MA, USA) following the manufacturer’sguidelines prior to analysis by mass spectrometry(MS).

Peptide concentrations of Axial volcano hydro-thermal vent plume proteome replicates Av1 andAv2 were measured using the Thermo ScientificNanodrop 2000/2000c, which measures the peptidebond absorbance at wavelength of 205 nm. Approxi-mately 1mg of peptide digest was used for eachinjection into the mass spectrometer. Each sampleconsisted of a complex mixture of peptides that wasintroduced into the mass spectrometer by reverse-phase chromatography using a brand new 15 cm long,75mm internal diameter fused silica capillary columnpacked with C18 particles (Magic C18AQ, 100 A,5mm; Burker-Michrom Inc., Auburn, CA, USA) fittedwith a 2 cm long, 100mm internal diameter precolumn(Magic C18AQ, 200 A, 5mm; Michrom BioresourcesInc.). Peptides were first trapped on the precolumn(5% acetonitrile, 4 ml min� 1, 7 min). Chromatographicseparations were performed using an acidified (formicacid, 0.1% v/v) water–acetonitrile gradient (5–35%acetonitrile in 60 min) with a total run time of 95 min.

Mass spectrometry was performed on replicatesAv1 and Av2 independently using the ThermoFisher linear ion trap–Orbitrap (LTQ-OT) hybridtandem mass spectrometer (Thermo Fisher, SanJose, CA, USA). Peptides were analyzed using adata-independent method termed Precursor Acqui-sition Independent from Ion Count (PAcIFIC)(Panchaud et al., 2009). Rather than requiring themass spectrometer to select ions for fragmentation

based on MS1 data, the PAcIFIC method system-atically fragments ions at all m/z channels(Panchaud et al., 2011). Each method file includesthe full 95 min linear high-performance liquidchromatography gradient of 5–35% acetonitrile over60 min (see above) and covers a 21.5 m z�1 rangeusing 14 contiguous, unique channels that span2.5 m z�1 in the mass spectrometer. This results in atotal of 45 method files per PAcIFIC analytical cycleto cover a full m/z range of 400–1400.

Protein identificationsTandem mass spectra were interrogated against acomposite database containing deduced proteinsequences from lineages identified in the CTD17clone library and lineages that are dominant in thedeep ocean (background seawater). The databasecontained marine GSOs ‘Candidatus Vesicomyosociusokutanii HA’, ‘Candidatus Ruthia magnifica Cm’,the SUP05 metagenome (Walsh et al., 2009) andSCGC AAA001-B15 (Arctic96BD-19 draft genome);the methylotrophs Methylobacter tundripaludumSV96 and Methylomicrobium alcaliphilum; iron-oxidizing bacteria Gallionella capsiferriformansES-2 and Sideroxydans lithotrophicus ES-1; abun-dant lineages in seawater ‘Candidatus Pelagibacterubique HTCC1062’ and ‘Candidatus Pelagibacterubique HTCC1002’; ammonia-oxidizing archaeaNitrosopumilus maritimus SCM1, an unculturedmarine group II (Iverson et al., 2012); an incompletehydrothermal vent metagenome (Xie et al., 2011);and common contaminants. SEQUEST (versionUW2011.01.1) was used to correlate observedtandem mass spectra to peptide sequence viatheoretical tandem mass spectra from the compositedatabase described above (Eng et al., 1994, 2008).For a detailed discussion of database considerationsin community proteomics, see the publication byMorris et al. (2010). SEQUEST parameters includeda 3.75-Da peptide mass tolerance on MS1 spectra,specifying trypsin as the enzyme; variable oxidationmodification on methionine (15.9949 Da) and staticmodification on cysteine residues (57.021464 Da)resulting from alkylation.

Results

Distribution of marine GSOs in the northeastern PacificOceanTRFLP profiles from CTD 7, 8, 11 and 13 wereconducted to place hydrothermal vent plume com-munities in a larger regional context (Figure 1a).Community structural analyses identified threedistinct groupings (Figure 1b). Microbial commu-nities in the surface layer (o100 m) were distinctfrom communities at depths X100 m, and microbialcommunities directly over hydrothermal vents weredistinct from those in background seawater. TRFLPprofiles just above hydrothermal vents at Axial andCoquille were dominated by a 408-bp TRF, which

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had the strongest positive correlation with ordina-tion axis 1 (0.761; Table 1). The 408 bp TRFwas identified as a marine GSO by constructing a16S rRNA gene clone library (57 clones) fromvent plume waters (CTD17, 1450 m) (Figure 1c).A different marine GSO TRF (324 bp) was observedin relatively low abundance in vent plume samples(0.1–3.2%) and at relatively high abundance inbackground seawater X100 m, where it reached10% (Figure 1d). This fragment identity was con-firmed by constructing another 16S rRNA gene clonelibrary (53 clones) from 2850 m at the CTD7 station.GSO abundance was not correlated with any singleenvironmental variable measured in this study.

Diversity of marine GSOs in the northeastern PacificOceanMaximum likelihood phylogenetic analyses ofnearly full-length 16S rRNA gene sequences indi-cate that marine GSOs identified in this study areclosely related to marine GSOs that inhabit sym-biont, open ocean, coastal and hydrothermal ventenvironments (Figure 2). These include sequencesrecovered from Saanich Inlet, the Yellow Sea,Monterey Bay, the Arabian Sea, the Benguelaupwelling system, Suiyo Seamount, the Arcticand Antarctic, and the deep ocean (Bano andHollibaugh, 2002; Fuchs et al., 2005; Murray andGrzymski, 2007; Kato et al., 2009; Lavik et al., 2009;Walsh et al., 2009; Zaikova et al., 2010). TheArctic96BD-19 subclade is comprised of two mono-phyletic lineages, including one that includes theoriginal Arctic96BD-19 clone and the only knowncultured marine GSO (Marshall and Morris, 2013).

The SUP05 subclade is comprised of two or morelineages, including one that includes symbiontsof deep-sea clams and one that includes symbiontsof deep-sea mussels and free-living representativesthat inhabit both open ocean and coastalenvironments.

Dominance of marine GSOs in plume watersHydrothermal vent plume waters were sampled overthe Inferno vent (Figure 3a). Cell concentrationsincreased by 4.5-fold from 9.58� 104 cells per ml at750 m to an average of 4.27� 105 cells per ml(±3.69� 104 cells per ml) below 1445 m over theASHES vent field (Figure 3b). A 3–4% drop in beamtransmission and a less obvious positive deflectionin temperature at 1340–1470 m water depth definethe stable and neutrally buoyant hydrothermalplume directly over the Inferno hydrothermal ventat ASHES. Accompanying water sample measure-ments of CH4 concentrations and DAPI counts clearlyshow the enrichment of gases and cells in the plumerelative to background levels. Dissolved oxygen abovethe Inferno plume shows an oxygen-minimum zone at800–1100 m water depth and oxygen concentrationsin the plume environment of B25mmol kg�1. Micro-bial biomass was subsequently concentrated from180 l of water collected at the same location (CTD17,1450 m) for 16S rRNA gene and MS/MS proteomicanalysis of the Inferno vent plume microbial commu-nity (Supplementary Figure 2). Similar shifts inmicrobial cell counts, CH4 and beam transmissionwere not observed at non-venting background loca-tions (Supplementary Figure 2).

Fluorescence in situ hybridization, TRFLP andclone library analyses suggest that a single bacteriallineage dominated the Inferno hydrothermal ventplume (Table 1 and Supplementary Figure 3).Bacteria accounted for 94% of microbial cell counts,suggesting that archaea were a minor component ofthe plume community. TRFLP and clone libraryanalyses were therefore conducted using bacteria-specific 16S rRNA gene primers. TRFLP analysesrevealed the dominance of a 408-bp TRF (48%).A 16S rRNA gene clone library confirmed theidentity of the bacterial lineage that produced thisand other abundant fragments (Table 1). Themajority of clones recovered from plume waters(62%) were marine GSOs with 193, 324, 406 and408 bp TRFs. Most of them had a 408-bp TRF (28clones). Five clones were closely related to methy-lotrophs, and two clones were closely related toknown iron oxidizers (Table 1 and SupplementaryTable 2).

Dominant activities identified in plume watersWe identified key proteins expressed by plumecommunities using an MS/MS-based proteomicapproach. The presence of 16S rRNA genesequences associated with marine GSOs,

Table 1 16S rRNA gene clones recovered from the Infernohydrothermal vent plume

Taxonomicassignment

PredictedTRF (bp)

ObservedTRF (bp)

Numberof clones

Pearson andKendall

correlations

NMSaxis 1

NMSaxis 2

SUP05 193 194 1 0.220 � 0.356Gallionellaceae 221 220 2 0.496 0.006Methylobacter sp. 255 254 2 �0.110 0.204Methylobacter sp. 257 256 2 �0.018 � 0.042Gamma-proteobacteria 259 257 1 �0.074 0.078SAR11 293 291 2 0.079 0.665Methylomonas sp. 322 322 1 0.229 � 0.124SUP05/Arctic96BD-19 323 324 3 �0.085 0.329Arctic96BD-19 327 323 1 �0.085 0.329SAR324 406 404 3 �0.152 � 0.855SUP05 408 406 1 0.044 0.267SUP05 410 408 28 0.761 0.143

Abbreviations: NMS, nonmetric multidimensional scaling; rRNA,ribosomal RNA; TRF, terminal restriction fragment.Clones were sequenced, grouped by predicted TRFs and annotationsand summed to determine the number of clones recovered for eachlineage (total observed). Representative clones were selected for eachgroup, amplified, restricted and matched to TRFs observed inenvironmental samples. TRF correlations with NMS axes 1 and 2correspond to fragments observed in the environmental TRFLP profiles.

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methylotrophs and iron oxidizers in the CTD17clone library informed the construction of a proteinsequence database for identifying MS/MS spectra, asdescribed in the Materials and methods section. Weconfidently identified 239 proteins with X2 pep-tides in replicate Av1 (Supplementary Table 3)and 131 proteins with X2 peptides in replicateAv2 (Supplementary Table 4). Although fewerproteins were identified in Av2, nearly all (94%) ofthe proteins identified in Av2 were also identifiedin Av1 (Supplementary Table 5). Differencesin the total number of proteins identified inreplicate samples may result from differencesin the amount of biomass obtained during sampleprocessing.

Marine GSOs, methylotrophs and iron oxidizerswere active in the Inferno plume (Figure 4). Ofthe MS/MS spectra assigned to these lineages,

93% were from proteins expressed by marine GSOsand 5% were from proteins expressed by methano-trophs and iron oxidizers (Figure 4a). Half of theremaining 2% of MS/MS spectra were assigned toproteins expressed by members of the SAR11 clade,and half were assigned to proteins expressed byother proteobacteria (Supplementary Tables 3 and4). A significant fraction of the marine GSO proteins(75%) were identified using a SUP05 genomesequence obtained from a Saanich Inlet metagenome.The remaining marine GSO proteins were identifiedusing genome sequences obtained from marine GSOsymbionts (Figure 4b). SUP05 proteins identifiedusing symbiont genomes, such as cytochromec oxidase (COX), are likely to be present in ventplume GSOs and symbionts but not present or notidentified in GSOs from Saanich Inlet (Walsh et al.,2009). COX genes were also present and expressed

Figure 2 Phylogenetic analysis of SUP05/Arctic96BD-19 16S rRNA gene clones recovered from the Inferno vent plume and backgroundseawater (1000 m). Sequences obtained in this study were aligned with those used to generate a robust maximum likelihood referencetree that contained nearly complete (1300 bp), high-quality, nonredundant reference sequences from cultures (*), environment clones andsymbionts. Bootstrap values X70 (1000 replicates) are reported above the nodes, except where indicated for lower values (^).Methylococcus capsulatus was selected as an outgroup. SUP05/Arctic96BD-19 subclade designations (black bars) are based on the studyby Walsh et al. (2009). Symbiont and free-living (open ocean, coastal and vent) designations (right) indicate the environment from whicheach rRNA sequence was obtained.

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by SUP05 cells in hydrothermal vent plumes fromthe Guaymas Basin (Anantharaman et al., 2013).

Metabolism, genetic information processing andenvironmental information processing were thedominant functional classifications identified usingthe Kyoto Encyclopedia of Genes and Genomes.Of the MS/MS spectra assigned to these categories,43.1% were associated with metabolism, 26% wereassociated with genetic information and processingand 8% were associated with environmental infor-mation processing (i.e., nitrogen regulatory proteinPII) (Figure 4c). A total of 96 metabolic proteinswere identified; the majority of these proteins(56.4%) were associated with energy metabolism(Figure 4d). Proteomic evidence of energy, carbohy-drate, amino acid, nucleotide, vitamin and cofactor,and lipid metabolism supports the conclusion thatthe bacteria identified in Inferno plume waters wereactive.

Chemolithoautotrophy and methanotrophy in plumewatersProteomic analysis suggests that hydrothermal ventplume marine GSOs oxidized sulfur, fixed inorganiccarbon, respired oxygen and sensed nitrogen

availability in plume waters. Marine GSOs andmethylotrophs expressed key proteins associatedwith carbon fixation (Figure 5). Marine GSOsexpressed proteins from several sulfur oxidationpathways, including key proteins for thiosulfateoxidation (sox), dissimilatory sulfite reductase,adenosine phosphosulfate reductase and ATP sul-furylase (SAT) (Figure 5a). Several key metabolicproteins were identified in addition to thoseinvolved in sulfur metabolism, including compo-nents of the Calvin–Benson–Basham cycle (ribulose-1,5-bisphosphate carboxylase oxygenase (RuBisCO)and a putative RuBisCO regulator), subunits I and IIof COX and a nitrogen regulatory protein (PII).

The majority of methylotrophic proteins identi-fied were associated with CH4 and methanol oxida-tion (58.4% of spectra) (Figure 5b). These proteinsincluded the b-subunit (PmoB) of particulatemethane monooxygenase (pMMO), which is acharacteristic of aerobic methanotrophs, and metha-nol dehydrogenase (XoxF). We also identified aputative methylotrophic transketolase, which couldparticipate in formaldehyde fixation via the ribulosemonophosphate pathway for carbon fixation used bysome methylotrophs (Trotsenko et al., 1986). Theformaldehyde-activating enzyme (Fae) was also

46° 00 N

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Figure 3 (a) Axial Seamount, located in the northeastern Pacific Ocean on the Juan de Fuca Ridge 460 km west of the Oregon coast, isinfluenced by hot spot and mid-ocean ridge processes. The bathymetry represents 1-m resolution mapping conducted after the 2011eruption, and the black outline describes the boundary of the 2011 lava flows (Caress et al., 2012). Vertical water column profiles wereconducted directly over locations of known hydrothermal venting, including nos. 11 and 17 at the ASHES hydrothermal field and no. 13at the Coquille vent. (b) Vertical profile of the bottom 800 m above the ASHES vent field. A background cast was performed 215 km east ofAxial Seamount at 45.91N� 127.91W (Supplementary Figure 2).

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identified, but with lower confidence (one peptidewith a protein probability of 1), which suggests thatthe Inferno plume harbored type I methanotrophsthat assimilated carbon via the ribulose monopho-sphate pathway.

Discussion

These analyses suggest that free-living marine GSOswere the dominant primary producers in Infernoplume waters at Axial Seamount in 2011. Microbialcommunity analysis suggests that members of theSUP05 subclade dominated hydrothermal plumewaters at Axial volcano (ASHES and Coquille),whereas those from the Arctic96BD-19 subcladewere more abundant in background seawater(X100 m). This suggests that vent plume commu-nities harbor diverse marine GSOs dominated bymembers of the SUP05 subclade and that membersof the Arctic96BD-19 subclade are more ubiquitousin the northeastern Pacific Ocean. We also identifiedproteins linking energy metabolism with carbonfixation, aerobic respiration and nitrogen regulationin both marine GSOs and type I methanotrophs(Figure 5).

Our findings are consistent with recent observa-tions that marine GSOs are among the active anddominant lineages at hydrothermal vents. MarineGSOs were among the dominant lineages in plumeand diffuse-flow fluids at the Main Endeavour Fieldand at Axial Seamount on the Juan de Fuca Ridge

(Anderson et al., 2013). A meta-transcriptomic studyfrom Guaymas Basin hydrothermal plumes in theGulf of California revealed that mRNA transcriptsfrom ammonia oxidizers (amoAC), methanotrophs(pmoABC) and marine GSOs (soxAY) were greater inabundance than background seawater abundances(Lesniewski et al., 2012). Methanotrophs dominatedplume activities in the Guaymas Basin, whereasmarine GSOs dominated plume activities at Axialvolcano and ammonia oxidizers were not a signifi-cant component of the Inferno plume community.Both methodological approaches revealed the domi-nant lineages and key functions expressed inplumes. Differences are likely due to location andvent chemistry, as the sediment-rich Guaymas Basinprovides an abundance of reduced carbon andnitrogen compounds (Lesniewski et al., 2012).

Known bacterial sulfur oxidation systems fall intoone of three basic groups. The first group consists ofbacteria capable of complete oxidation of reducedsulfur compounds to sulfate. These organisms havea full set of sulfur oxidation genes (sox) includinga core set (soxABXYZ) and supplementary genes(soxCDEFGHTRSVW) (Friedrich et al., 2005).A second group uses the branched thiosulfateoxidation pathway via an incomplete sox system(soxABXYZ, but not soxC or soxD) and the dsrsystem (Friedrich et al., 2001, 2005; Ghosh and Dam,2009). Once the more reduced sulfur compoundshave been exhausted, this group stores elementalsulfur in globules for later oxidation to sulfite by dsrproteins (e.g., sulfite reductase) and to sulfate by

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Figure 4 Dominant active bacterial groups and cellular functions expressed by bacteria and archaea in the Inferno hydrothermal ventplume. (a) Dominant active bacterial groups determined by consensus annotation of identified proteins, expressed in terms of totalspectral counts in replicates Av1 (solid black bars) and Av2 (shaded gray bars). (b) Breakdown of GSO consensus protein annotations.Blue: uncultured SUP05 metagenome; red: deep-sea clam symbiont Ruthia magnifica; green: deep-sea clam symbiont (c) Dominant KyotoEncyclopedia of Genes and Genomes categories expressed in terms of total spectral counts in replicates Av1 (solid black bars) and Av2(shaded gray bars). (d) Key Kyoto Encyclopedia of Genes and Genomes metabolic functions expressed by bacteria and archaea. Relativeabundance was determined by summing spectral counts for all proteins identified by two or more peptides in each category.

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APS reductase (i.e., AprAB) and ATP sulfurylase(i.e., SAT) (Hensen et al., 2006; Ghosh and Dam,2009). Lastly, other bacteria oxidize reduced sulfurcompounds via formation of a tetrathionate inter-mediate. These organisms have no sox genes or anincomplete set of sox genes (Ghosh and Dam, 2009).Environmental genomic data suggest that marineGSOs harbor incomplete sets of sox and dsr genes,oxidizing sulfur via the formation of a tetrathionateintermediate or via the branched thiosulfateoxidation pathway. This also suggests that theyproduce and store elemental sulfur in globules(Walsh et al., 2009). The marine GSO isolate,

Thioglobus singularis strain GSO-PS1, formed externalsulfur globules when grown on seawater media(Marshall and Morris, 2013). This suggests thatmembers of the Arctic96BD-19 subclade oxidizesulfur via the formation of a tetrathionate inter-mediate or via the branched thiosulfate oxidationpathway. Proteomic data provide further evidencesuggesting that marine GSOs utilized the branchedthiosulfate oxidation pathway (Figure 5).

In a previous study, critical genes for carbonfixation via the Calvin–Benson–Basham cycle(RuBisCO) were noted in the partial SUP05 meta-genome, whereas genes for a complete tricarboxylicacid cycle, required for heterotrophic growth, wereabsent, suggesting that SUP05 GSOs are obligatechemolithoautotrophs (Walsh et al., 2009). RuBisCOgenes were also noted in partial Arctic96BD-19genomes (Swan et al., 2011). We observed marineGSO RuBisCO proteins in the Inferno vent plume,providing functional evidence that free-livingmarine GSOs fixed inorganic carbon. Iron oxidizersalso contributed to primary production in theplume, as evidenced by the expression of an ironoxidizer RuBisCo (Supplementary Table 3).

Free-living members of the SUP05 subclade areknown to thrive in low-oxygen waters (Walsh et al.,2009; Zaikova et al., 2010) and hydrothermal ventplumes (Sunamura et al., 2004), whereas membersof the Arctic96BD-19 GSO clade have been identi-fied in oxygenated inshore and offshore waters, athydrothermal vents and cold seeps and in thesurface layer and deep ocean (Bano andHollibaugh, 2002; Fuchs et al., 2005; Murray andGrzymski, 2007; Kato et al., 2009; Lavik et al., 2009;Swan et al., 2011). The Inferno hydrothermal ventplume was sufficiently oxygenated (dissolvedoxygen ranged from 27.6 to 28.6 mmol kg�1) forGSOs to respire aerobically, thus the discovery ofCOX subunits I and II provides direct evidence thataerobic respiration was employed (Figure 5). Muchless is known about GSO sulfur oxidation inoxygenated waters throughout the deep ocean,where hydrogen sulfide is not present at highconcentrations but less reduced forms of sulfur areavailable for further oxidation.

The presence of CH4 oxidation proteins (pMMO)in the Inferno plume is consistent with the presenceof both CH4 and oxygen (Figure 3). The PmoA andPmoC polypeptides of pMMO were not observed.PmoA and PmoC are fully membrane bound,whereas PmoB has soluble domains (Liebermanand Rosenzweig, 2005). Membrane-bound peptidesare difficult to extract and ionize due to theirhydrophobic nature, reducing the chance of identi-fication using a whole-cell MS/MS proteomicapproach. However, we also identified a methanoldehydrogenase formaldehyde-activating enzyme(Fae) and putative methylotrophic transketolase thatcould participate in formaldehyde fixation via theribulose monophosphate pathway (Trotsenko et al.,1986). In combination, these data suggest that the

SoxAYB

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Figure 5 Illustration of sulfur oxidation and methanotrophicproteins expressed by bacteria in the Inferno hydrothermal ventplume. (a) Sulfur oxidation proteins expressed in the plume areindicated in green, regulatory proteins in orange, aerobicrespiratory proteins in red and carbon fixation proteins in blue.(b) Methane oxidation proteins expressed in the plume areindicated in yellow and regulatory proteins in orange. Proteinsidentified by one peptide are in gray. Dsr, dissimilatory sulfitereductase; sox, sulfur oxidation system; PII, nitrogen regulatoryprotein PII; COX, cytochrome c oxidase; CBB, Calvin–Benson–Basham cycle; pMMO, particulate methane monooxygenase(PmoB); PQQ-dep MDH, PQQ-dependent methanol dehydrogen-ase; GlnK, nitrogen regulatory protein (homolog of PII); Gs,glutamine synthetase; UT/UR, uridylyl transferase/uridylyl-removing enzyme; Apr, adenosine phosphosulfate reductase;SAT, ATP sulfurylase.

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Inferno vent plume harbored type I methanotrophsthat assimilated carbon from CH4 using pMMO,methanol dehydrogenase and the ribulose mono-phosphate pathway (Figure 5).

It is clear from the organisms and enzymesidentified in vent plumes that reduced compoundsemitted from the deep subsurface have the potentialto impact carbon cycling in the deep ocean whenthey mix with seawater and stimulate growth of asubset of free-living marine bacteria and archaea.Sulfur oxidizers, methylotrophs and iron oxidizersexpressed key proteins associated with carbonfixation. Broader spatial and temporal studies offunctions expressed in hydrothermal vent plumeswill provide further insights into carbon cycling inthe dark ocean and connectivity between the deepsubsurface and deep ocean biospheres.

Conflict of Interest

The authors declare no conflict of interest.

Acknowledgements

We thank chief scientists J Delaney and D Kelley andofficers and crew of the R/V Thomas G Thompson. Thisstudy was supported by grants from the National ScienceFoundation OCE-1232840 (RM Morris) and OCE-0825790(BL Nunn) and National Institutes of Health5P30ES007033-12 and 1S10RR023044. DAH was sup-ported by OCE-1153930. TEM was supported by aUniversity of Iowa Career Development Award.

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