Timeseries Analysis of Two Hydrothermal Plumes at 950N East

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Geobiology (2012), 10, 178–192 DOI: 10.1111/j.1472-4669.2011.00315.x

Time-series analysis of two hydrothermal plumes at 950¢N East Paciﬁc Rise reveals distinct, heterogeneous bacterial populations J. B. SYLVAN,1 B. C. PYENSON,2 O. ROUXEL,3,4 C. R. GERMAN3 ANDK.J.EDWARDS1

1Marine Environmental Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA 2Haverford College, Haverford, PA, USA 3Woods Hole Oceanographic Institution, Woods Hole, MA, USA 4Universite´ Europeénne de Bretagne, Universite´ de Brest, Institut Universaire Europeén de la Mer (IUEM), UMR 6538, Insititut Français de Recherche pour l’Exploitation de la Mer (IFREMER), Plouzane´, France

ABSTRACT

We deployed sediment traps adjacent to two active hydrothermal vents at 950¢N on the East Pacific Rise (EPR) to assess the variability in bacterial community structure associated with plume particles on the timescale of weeks to months, to determine whether an endemic population of plume microbes exists, and to establish ecological relationships between bacterial populations and vent chemistry. Automated rRNA intergenic spacer analysis (ARISA) indicated that there are separate communities at the two different vents and temporal community variations between each vent. Correlation analysis between chemistry and microbiology indicated that shifts in the coarse particulate (>1 mm) Fe ⁄ (Fe+Mn+Al), Cu, V, Ca, Al, 232Th, and Ti as well as fine-grained particulate (<1 mm) Fe ⁄ (Fe+Mn+Al), Fe, Ca, and Co are reflected in shifts in microbial populations. 16S rRNA clone libraries from each trap at three time points revealed a high percentage of Epsilonproteobacteria clones and hypertherm- ophilic Aquificae. There is a shift toward the end of the experiment to more Gammaproteobacteria and Alpha- proteobacteria, many of whom likely participate in Fe and S cycling. The particle-attached plume environment is genetically distinct from the surrounding seawater. While work to date in hydrothermal environments has focused on determining the microbial communities on hydrothermal chimneys and the basaltic lavas that form the surrounding seafloor, little comparable data exist on the plume environment that physically and chemically connects them. By employing sediment traps for a time-series approach to sampling, we show that bacterial community composition on plume particles changes on timescales much shorter than previously known.

Received 19 May 2011; accepted 4 December 2011

Corresponding author: K. J. Edwards. Tel.: 213 821 4390; fax: 213 740 8123; e-mail: [email protected]

and NHþ over distances spanning several kilometers away INTRODUCTION 4 from the vent source (Lilley et al., 1995; Cowen et al., 1998). Hydrothermal plumes form at deep-sea hydrothermal vents, The microbiology of hydrothermal plumes has received less where hot hydrothermal fluids are injected into the water col- attention than that of the source fluids emanating from chim- umn and mix with ambient seawater. The hot, buoyant hydro- neys and active hydrothermal chimneys themselves. Given thermal fluids rise in the water column as they mix with cold, that the entire volume of the oceans cycles through hydro- oxygenated seawater until a level of neutral buoyancy is thermal plumes on timescales of just a few thousand years attained, typically after a timescale of 1 h and after dilution (comparable, for example, to the timescale for mixing of the of the vent fluid 104:1 by surrounding seawater (Lupton entire volume of the deep ocean through thermohaline circu- et al., 1985). At this point, neutrally buoyant plumes become lation), this environment warrants greater attention (Elder- dispersed by local deep ocean currents and can readily be field & Schultz, 1996; German & Von Damm, 2004). Cell detected through elevated particle concentrations as well as counts in hydrothermal plumes are consistently higher than 3 elevated hydrothermal constituents, such as He, Mn, CH4, background waters (Sunamura et al., 2004). Mn oxidation in

178 2012 Blackwell Publishing Ltd Microbiology of hydrothermal plumes at 9N EPR 179 hydrothermal plumes is elevated compared with background 2011). Furthermore, the present study builds on previously )1 seawater, up to 2 nM h (Cowen et al., 1986; Dick et al., published mineralogical and bio-inorganic chemical investiga- þ 2009). Oxidation of NH4 and CH4 is also prevalent in hydro- tions of similar vent-trap samples to those that are studied thermal plume environments, whereas these processes are here which hypothesized that microbial populations in plumes generally absent or occur at very low levels in deep water at 950¢N EPR produce the organic ligands that bind hydro- masses outside of plumes (De Angelis et al., 1993; Lam et al., thermally produced Fe2+, inhibiting its oxidation (Toner 2008). These combined evidences for microbial processes in et al., 2009). the plume environment indicate that it is a potentially unique microbial biome. MATERIALS AND METHODS The chemistry of hydrothermal plumes is directly related to the end-member chemistry of the hydrothermal fluids from Site description and sample collection which the plumes originate. The spatial and temporal variability of vent fluid chemistry at 950¢N EPR is among the most The two sediment traps (McLane Parflux Mark 78H-21; thoroughly studied of any vent field. Multiyear time-series of McLane Research Laboratories, Falmouth, MA, USA) with a annual to semi-annual sampling at this site have revealed both sampling aperture of 0.5 m2 (80 cm diameter at top, 2.5 cm temporal variability between samplings and differences diameter at bottom) and 21 cups were deployed during the between vents that are tens of meters apart (Von Damm, RESET06 cruise AT15-6 aboard the R ⁄ V Atlantis II, June ⁄ 2004). It would be expected that the microbial community in July 2006, as described previously (Mullineaux et al., 2010). the hydrothermal plumes resulting from these variable end- Briefly, before deployment, cups were filled with a solution of member fluids may also vary on short temporal and spatial 20% dimethylsulfoxide (DMSO) in ultrapure water saturated scales, but less is known about the microbial communities at with NaCl and buffered to pH 9.0 ± 0.5. DMSO was used as 950¢N than the fluid chemistry at any comparable resolution a preservative for biological samples, and the saturated NaCl of study. Sampling of hydrothermal plumes is often carried out solution ensured that particles that fell into the solution, using shipboard CTD rosettes, but sediment traps have which was denser than seawater, would remain in the sam- recently been employed to collect samples in time-series of pling cups. The combination of DMSO and saturated NaCl in hydrothermal plume fallout at the Endeavour Segment of the sediment trap collection cups has been proven successful pre- Juan de Fuca Ridge (JdFR) (Roth & Dymond, 1989; Cowen viously to prevent biological activity while preserving DNA et al., 2001), 13N EPR (German et al., 2002) and 950¢N for later study (Comtet et al., 2000). The sampling schedule (Adams et al., 2011; Bennett et al., 2011). While those studies for both traps was 6 days per bottle, starting on July 01, 2006 examined the impact of hydrothermal plumes on deep-sea (samples R1-1 and R2-1), and ending on November 03, geochemistry, they did not study plume microbiology. How- 2006 (Trap R1, sample R1-21), or November 01, 2006 (Trap ever, their time-series approach to sampling hydrothermal R2, sample R2-21). Trap moorings were anchored such that plumes did reveal that particulate organic carbon is elevated in the opening of each trap was located 4 m above the seafloor. plumes at distances of a few kilometers from the vent sites Following retrieval of Trap R2, it was discovered that a jelly- (Roth & Dymond, 1989; Cowen et al., 2001) and that plumes fish had become lodged in the opening at the bottom of the are important to the cycling of hydrothermally derived metals trap during the collection of sample 11 (which began collec- (Fe, Cu, Zn) and seawater-derived oxyanions (P, V, As) as well tion on August 30, 2006) and remained there for the duration as particle-reactive elements (REE, Th) (German et al., 2002). of the experiment. Here, we have explored the use of sediment traps for a Trap R1 was located 30 m southwest of the Bio9 vent time-series approach to understanding spatial and temporal complex within the axial summit caldera in an area with a ser- effects on the bacterial communities within hydrothermal ies of small chimneys, black smokers and spires, which hosts plumes at 950¢N EPR following the eruption in Winter Riftia pachyptila and Tevnia tubeworm populations. Trap R2 2005–2006 (Tolstoy et al., 2006). That eruption resulted in was located outside the axial summit caldera, 115 m south- elevated dissolved CH4 in hydrothermal plumes at 950¢N west of Ty and Io vents and 370 m southwest of Trap R1. EPR when compared with typical hydrothermal plume con- Ty and Io are black smokers located 350 m southeast of centrations, 1 month prior to our deployment (Cowen et al., Bio9 and are home to populations of Alvinella worms. 2007). Our study, spanning July–November 2006, included a Samples were retrieved from the traps, 15 mL was subsam- collaboration with both larval biologists, who have already pled for microbiology, and all samples were stored at 4 C reported evidence for a very disrupted contemporaneous larval until DNA extraction. supply compared with what was previously present at this site (Mullineaux et al., 2010), and geochemists who have investi- DNA extraction and ARISA gated chemical flux variations at both sites using major and trace element analyses, stable and radiogenic isotope measure- 7.5 mL of each sample was filtered onto a 0.2-lm Nuclepore ments, and organic carbon measurements (Bennett et al., filter. DNA was extracted using a CTAB phenol ⁄ chloroform

2012 Blackwell Publishing Ltd 180 J. B. SYLVAN et al. procedure (Ausubel et al., 1999). ARISA PCR was carried out the samples to confirm analytical accuracy, which is better than according to Hewson et al. (2006). 10 ng DNA was added to 5% for all elements reported. each DNA reaction of 2.5 units of RedTaq (Sigma-Aldrich, St. Louis, MO, USA), 10X reaction buffer, 2.5 mM MgCl, Statistical analysis of ARISA results with vent chemistry 0.2 mM dNTPs, and 0.2 lM of each primer in 50-lL reac- tions. ARISA primers 78F (5¢-GYACACACCGCCCGT-3¢) Spearman’s correlation coefficients between chemical and 79R (5¢-[TET]GGGTTBCCCCATTCRG-3¢) were used. measurements and ARISA profiles were calculated using the The amplification cycle used was: denaturing cycle for 5 min BIOENV method in Primer6 with Euclidean distances and at 95 C, followed by 30 cycles of 95 C for 40 s, 56 C for 99 permutations. This analysis compares the individual 40 s and 72 C for 90 s, and a final extension for 7 min at sample chromatograms (input as a grid of samples vs. band 72 C. PCR was treated with Clean and Concentrate Kit-5 size and intensity) from ARISA with the individual chemical (Zymo Research, Irvine, CA, USA). Six nanogram of cleaned variables measured (38 in total) and determines what combi- DNA per sample was loaded in duplicate into an ABI 377XL nation of chemical variables best correlates to the observed Running Slab Gel, and bands were analyzed using ABI GENE- ARISA patterns. The BIOENV calculation takes all combina- SCAN software (Applied Biosystems, Foster City, CA, USA). tions of the 38 total elemental analyses, from single variables Initial analysis of bands was carried out using Microsoft Excel, through all possible combinations of each variable, and and statistical analyses of band ARISA profiles were carried out reports the individual or combination of elemental analyses using PRIMER6 (PrimerE, Ivybridge, UK). that yield the highest correlation with the ARISA profiles, regardless of the number of variables that correlate best (therefore, if Al+Ca together have a higher correlation to the Chemical analyses of plume particulates ARISA profiles than Al alone and ⁄ or Ca alone, it will report Trap samples were split into fine size fractions (<1 mm) and the value for Al+Ca). We here report the correlations with coarse fractions (>1 mm) using nylon sieves. Each fraction the highest values. was later filtered through 47-mm filters, dried under class- 100 laminar flow hood, and weighed to determine mass flux. Clone library construction and analysis The remaining <1 mm fraction was passed through a 10-port rotating wet sediment splitter. Between 5 and 10 mg dried Universal bacterial primers 27F and 1492R (Lane, 1991) subsamples were analyzed for Al, Ca, Fe, Mg, Si, Ti, and Mn were used to construct near full-length 16S rRNA gene using an inductively coupled plasma optical emission spec- libraries. PCR products were run on an agarose gel, cut out, trometer using standard methods established for sediment and extracted using QIAquick Gel Extraction Kit (Qiagen, trap analyses (Honjo et al., 1995). Valencia, CA, USA) according to the manufacturer’s For each sample, another subsample fraction was dissolved instructions. Fragments were cloned into the pCR 4 TOPO in concentrated acid to determine trace element composition vector using the TOPO TA Cloning Kit (Invitrogen, Grand (Ba, Sr, Ga, P, V, Co, Cu, Pb, Zn, 232Th, and 238U) by induc- Island, NY, USA) and transformants plated on LB+ ) tively coupled plasma mass spectrometry (ICP-MS). Subsam- 100 lgmL 1 ampicillin according to the manufacturer’s ples were leached overnight with 10 mL of 8 M distilled instructions. Colonies were randomly selected and grown in

HNO3 in 15-mL closed Teﬂon vials on a hot plate at 80 C. liquid culture followed by sequencing at the University of The solutions were then slowly evaporated to dryness. A sec- Florida Sequencing Services Facility. Forward and reverse ond dissolution step using 0.5 mL of concentrated ultrapure sequences were joined and edited using BIOEDIT v7.0.5

HF and 3 mL of concentrated distilled HNO3 was then used and checked for chimeras using the BELLEROPHON tool of to obtain a total digestion of the particles. The solid residue Greengenes (DeSantis et al., 2006b). The resulting was dissolved in 10 mL of 0.28 M HNO3 (Optima grade), sequences were aligned using the Greengenes NAST server and an aliquot was further diluted for multielemental ICP-MS (DeSantis et al., 2006a) and imported into ARB (Ludwig analyses. Multielemental analysis of the digests was carried out et al., 2004). The most similar cultured strains as well as on a high-resolution ICP-MS Thermo-Electron Element 2 some of the nearest neighbors from ARB for uncultured after appropriate dilution (typically 25- to 200-fold dilution clones were exported with the sequences from this study depending on the amount of digested materials). The detec- and aligned using MEGA5 (Tamura et al., 2011). Phyloge- tion limit was calculated from repeat analysis of blank ﬁlter netic trees were constructed following manual adjustment of digests. Indium was added to each sample as an internal stan- this alignment and maximum-likelihood analysis based on dard to correct for changes in instrument sensitivity. Stock the Tamura–Nei model with a Gamma distribution and 500 ) 1000 lgL 1 standards (Specpure, Spex) of each element of bootstrap replicates using MEGA5. Calculation of rarefac- interest were diluted in preparation for instrument calibration tion curves and diversity estimates, as well as comparison (ranging from 5 to 1000 ppb). A number of geo-reference between clone libraries and those of other studies, was standards (BHVO-1 and IFG) were also analyzed along with carried out using the software MOTHUR (Schloss et al., 2009).

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Clones sequenced in this study were deposited in the NCBI and the fine-grained particulate (<1 mm) Fe ⁄ (Fe+Mn+Al), database with accession numbers JN873927–JN874385. Fe, Ca, and Co) correlate best with differences in the observed distribution of bacterial communities, explaining 71% of the variation (Table 1). Fe ⁄ (Fe+Mn+Al) and Ca are the only vari- RESULTS ables for which a correlation existed for both size fractions. Automated rRNA intergenic spacer analysis was used to We cloned and sequenced the near full-length bacterial 16S provide a broad view of major differences in the bacterial com- rRNA gene from traps R1 and R2 at time points 8, 13, and 21 munity composition from sediment trap samples. Samples (42–48, 72–78, and 120–126 days, respectively). While sam- R2-11–R2-21 (66–126 days) were considered compromised ples R2-13 and R2-21 are too compromised for quantitative by the jellyfish caught in the mouth of the sediment trap; comparison to the other samples, we use the results generated therefore, these samples have not been analyzed by ARISA. here to determine bacteria that may be present in the plume at All other samples from each sediment trap were subjected to these locations. To avoid artifacts from the experimental dis- DNA extraction and ARISA PCR (n = 31). Successful ARISA ruption, clones from samples R2-13 and R2-21 were included PCR amplification was obtained from 13 samples. ARISA in the analysis of phylum level diversity (Fig. 2) and phyloge- results for the bacterial communities from Trap R1 group netic trees (Figs 3 and 4) only if they met at least one of two almost entirely separately from those in Trap R2 (Fig. 1). following criteria: (i) 97% similarity to at least one clone from Sample R2-8 (42–48 days) is the only exception; it is most samples R1-8, R1-13, R1-21, or R2-8 (not compromised) or similar to sample R1-1 (1–6 days). Sample R1-21 (ii) were Epsilonproteobacteria, Zetaproteobacteria, or Aqu- (120–126 days) is unique compared with all other samples. ificales classes of bacteria well represented at hydrothermal Bacterial communities in samples R1-2, R1-8, R1-9, R1-13, vents. These clone libraries allow for comparison between R1-17, and R1-19 (6–12, 42–48, 48–54, 72–78, 96–102, traps and also at each trap over time. and 108–114 days, respectively) all group together, as do Proteobacteria are the most common clones. Epsilonprote- samples R2-2, R2-4, and R2-5 (6–12, 18–24, and obacteria dominated samples R1-8, R1-13, and R2-8, but are 24–30 days), indicating that the samples from each trap present in all clone libraries. Gammaproteobacteria are the display a characteristic genetic signature. most common clones sequenced in samples R1-21, R2-13, We used Spearman’s correlation analysis to determine and R2-21. Planctomycetes are present in samples from both which environmental variables, measured here as elemental traps at time points 8 and 13, but not 21. Other commonly concentrations, best explain the distribution of bacterial com- occurring bacterial phyla are Bacteroidetes, Verrucomicrobia, munities seen in the ARISA dendrogram (Fig. 1). Both size and Cyanobacteria. Clones related to Tenericutes are recov- fractions of each of the 18 elemental concentrations measured ered only from samples R1-8 and R1-13. Clones related to in addition to the ratio Fe ⁄ (Fe+Mn+Al) were compared with Aquificae are recovered only from samples R1-13 and R2-8. the ARISA analysis using the BIOENV method in Primer6. Because of the high number and diversity of clones Multiple combinations of only 11 chemical parameters (the sequenced, we demarcated clones by 97% similarity to each coarse-grained Fe ⁄ (Fe+Mn+Al), Cu, V, Ca, Al, 232Th, and Ti other to define representative operational taxonomic units

0 Table 1 Spearman’s correlations between automated rRNA intergenic spacer trap analysis distributions (biology) and elemental concentrations (chemistry). Each 1 2 row represents the speciﬁc combination of variables listed, which result in the 20 associated correlation. For all reported variables in this table, the combinations yielded higher correlations than any variable on its own.

Spearman’s 40 Variables correlation

Al, Ca, Cu, 232Th, Fe ⁄ (Fe+Mn+Al), Ca 0.714 60 Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, 232Th, Fe ⁄ (Fe+Mn+Al), Ca, Fe 0.709 Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, Fe ⁄ (Fe+Mn+Al), Ca, Co 0.708 232

Bray-Curtis Similarity (%) Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, Th, Fe ⁄ (Fe+Mn+Al), Ca, Co 0.708 80 Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, 232Th, Fe ⁄ (Fe+Mn+Al), Ca, Co 0.708 Ca, Ti, Cu, 232Th, Fe ⁄ (Fe+Mn+Al),Ca 0.707 Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, 232Th, Ca, Co 0.707 100 Fe ⁄ (Fe+Mn+Al), Al, Ca, Cu, 232Th, Ca, Fe 0.707 Al, Ca, Cu, 232Th, Fe ⁄ (Fe+Mn+Al),Ca, Fe 0.706 2-4 2-2 2-5 1-2 1-9 1-8 1-1 2-8 1-21 1-13 1-17 1-18 1-19 Fe ⁄ (Fe+Mn+Al), Al, Ca, V, Cu, 0.705 232Th, Fe ⁄ (Fe+Mn+Al), Ca, Co Fig. 1 Dendrogram analysis of automated rRNA intergenic spacer analysis profiles from traps R1 (filled triangles) and R2 (open circles) as calculated using Variables in italics are >1 mm size fraction, variables in bold are <1 mm size the Bray–Curtis similarity index. fraction. Significance for all correlations is P < 0.05

2012 Blackwell Publishing Ltd 182 J. B. SYLVAN et al.

16 15 3 16 1 14 1 12 14 3 11 11 1. Alphaproteobacteria 10 9 2. Betaproteobacteria 3. Deltaproteobacteria 7 4 9 4 5 4. Epsilonproteobacteria 5. Gammaproteobacteria 8 6. Zetaproteobacteria 5 7. Actinobacteria R1-8, n = 83 8. Aquificae R2-8, n = 70 9. Bacteroidetes 17 10. Chloroplast 14 15 1 3 11. Cyanobacteria 1 8 9 12. Deferribacteres 13. Firmicutes 4 other 14. Planctomycetes (non-plume, 5 15. Tenericutes 2-13 only) 5 16. Verrucomicrobia 4 17. WS3 11 9 14 13 R1-13, n = 89 R2-13, n = 78 6 7 1 2 Santelli et al. (2008) 1 4 EPR deep seawater 4 13 2 1 Fig. 2 Taxonomic breakdown of Bacteria, in each 16S rRNA gene clone library. Samples in the left column are all from Trap R1, and those on the right are other 5 (non-plume, from Trap R2. The top row is time period 8, the mid- 2-21 only) dle time period 13, and the bottom time period 21. 5 5 Data from a background deep seawater sample (non-plume) is included for comparison. This sam- 11 ple was collected in the same area as our study site in 2004 (Santelli et al., 2008). The number of clones R1-21, n = 80 n = 100 R2-21, n = 64 per library is indicated next to the sample name.

(OTUs) using the program MOTHUR (Schloss et al., 2009). While no OTUs were recovered from all six samples, or even OTUs and even entire classes of bacteria are not evenly from 5 of 6, many are recovered from 3 or 4 samples including distributed between the two sediment traps (Table S1). For at least one sample from each trap. Nine OTUs are shared example, Firmicutes and Actinobacteria are found in Trap R1, by three samples – one Alphaproteobacterium, six Epsilon- but not in Trap R2. OTUs 113F02 (Planctomycetes), 18F04, proteobacterium, one Gammaproteobacterium, and one 18E03, 18H12 and 18D03 (all Epsilonproteobacteria), and cyanobacterium (Table S1). Two of these OTUs, both 18B02 (Alphaproteobacteria) are all recovered from samples Epsilonproteobacteria (18G01 and 18H01), are shared by R1-8 and R1-13, but not from Trap R2. OTU 18B04 (Epsi- four samples (Table S1). lonproteobacteria) is present in all three samples from Trap Samples R1-8 and R1-13 share the most OTUs with each R1, but none from Trap R2. OTU 28G07 (Alphaproteobac- other, followed by R1-8 and R2-8 (Table 2 and Fig. S1). R1-8 teria) is recovered only from samples R2-8 and R2-13. These has the lowest percentage of unique sequences, 23%. Sample examples all occur in at least two samples; there are many R1-21 has the highest (79%); it shares only one OTU with OTUs that are recovered from single samples. It must be R1-8, two with R1-13, four with R2-21, and none with noted, however, that the number of clones sequenced per samples R2-8 and R2-13. Samples R1-8, R1-13, and R2-8 sample was not sufﬁciently high to draw strong conclusions share the most OTUs by absolute number. about the absence of a particular group or OTU, but can be By far, the Epsilonproteobacteria represent the most diverse used to discuss general trends in bacterial distributions. class of bacteria, with 65 OTUs (Fig. 3). Most OTUs group There are also many OTUs recovered from both traps within the orders Sulfurovumaceae or Sulfuricurvaceae, but (Table S1). OTU 121A02, a Marinobacter, is the most members of Arcobacteraeceae, Hydrogenimonaceae, and abundant OTU, recovered from samples R1-21 and R2-21. Nautillaceae are all present as well. Several Aquiﬁcae clones are

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93 RESET 18D12 97 RESET 18B11 AB015517 Deep-sea sediment clone: BD1-4 78 RESET 18H01 92 Juan de Fuca Ridge Dudley vent clone 4132B33, EU555132 68 RESET 18D01 99 RESET 28C04 56 RESET 28E04 RESET 28B06 RESET 18G09 72 RESET 28F06 RESET 113C12 68 RESET 28B11 60 RESET 28C03 RESET 18B10 62 Sulfurovum sp. str. NBC37-1, AP009179 75 Sulfurovum lithotrophicum 42BKT, NR_024802 RESET 18G06 RESET 18G04 93 RESET 18G12 Sulfurovumaceae Riftia pachyptila tube clone R76-B78, AF449251 99 RESET 113E04 RESET 113A08 RESET 18A02

83 RESET 221B05 77 RESET 18B04 Indian Ocean hydrothermal vent clone SF C23-C6 shell, AY531602 95 RESET 18H07 RESET 113G06 69 RESET 28C12 99 RESET 28D09 Indian Ocean hydrothermal vent clone SF C23-H2, AY531568 90 RESET 121A12 60 RESET 28D12 RESET 113D10 99 100 RESET 113F09 56 97 EPR White Smoker clone CH3_9_BAC, AY672522 RESET 113C11 86 RESET 18E08 88 RESET 113H03 RESET 18G01 RESET 28G04 100 RESET 18C03 RESET 18E03 66 RESET 121F08 100 RESET 18D03 95 Sulfurimonas autotrophica OK5, AB088432 Sulfurimonas autotrophica OK10, AB088431 100 98 RESET 28B05 79 RESET 18F05 Sulfuricurvaceae 66 RESET 28F05 81 93 Guaymas basin hydrothermal sediment clone CS B016, AF420352 RESET 113A02 Sulfurimonas denitrificans ATCC 33889 82 RESET 18A09 RESET 213C08 64 RESET 18B08 RESET 18H12 RESET 113A03 56 RESET 113B04 RESET 28G01 RESET 113C07 99 RESET 121B08 99 Nitratifractor salsuginis E9I37-1, AB175500 Arcobacter MA5, AB542077 RESET 213D07 100 Arcobacteraceae 81 RESET 28H10 100 RESET 18F04 99 RESET 28F12 Hydrogenimonaceae 99 Hydrogenomonas thermophila EP1-55-1, AB105408 99 RESET 113F07 52 Nautilia profundicola AmH, CP001279 RESET 121G08 RESET 113E01 67 Caminibacter profundus str. CR, AJ535664 Caminibacter mediatlanticus TB-2, NZ_ABCJ01000002 RESET 113E07 95 Nautilaceae Caminibacter hydrogeniphilus AM1116, AJ309655 RESET 113C03 RESET 28D01 RESET 113C10 RESET 113E08 72 RESET 18C07 68 RESET 121E07 99 RESET 113A07 Desulfurobacterium sp. str. SL19, AY268937 Aquifex pyrophilus Kol5a, M83548 Aquificae 98 RESET 28E03 100 RESET 28G03 0.1

Fig. 3 16S rRNA phylogenetic tree of Epsilonproteobacteria and Aquiﬁcae clones retrieved in this study. Clones in tree are all <97% similar with all others in this study, as determined by MOTHUR. For a full reporting of all clones, see Table S1. Alignments of sequences from this study and their nearest cultured organisms in the Greengenes database as well as some close uncultured clones from the ARB database were constructed using MEGA5. The tree was constructed using the maximum- likelihood algorithm with 500 bootstraps. Bootstrap values >50% are reported. Aquiﬁcae are used as an outgroup. NCBI accession numbers for sequences from cultured representatives and environmental clones are given following the species ⁄ clone name.

2012 Blackwell Publishing Ltd 184 J. B. SYLVAN et al.

99 Marinobacter RESET 18D05 RESET 121E02 99 Alcanivorax sp. str. Oha-1, AB053130 81 RESET 113D11 99 Haliea sp. str. SY02, GU124598 99 RESET 113B10 RESET 18A03 5252 99 RESET 113H01 Umboniibacter marinipuniceus str. KMM 3892, AB467280 82 RESET 113E10 Saccharophagus degradans str. 2-40, NC_007912 98 RESET 28C07 99 RESET_28C08 Colwellia psychrerythraea str. 34H, CP000083 99 RESET 18A04 99 Photobacterium leiognathi str. RM1, AY292947 Gammaproteobacteria 96 RESET 18F06 RESET 113B08 99 Pseudoalteromonas sp. str. JL-S1, AY745839 RESET 113G04 Kangiella koreensis str. DSM 16069, CP001707 RESET 113G05 55 Calyptogena phaseoliformis symbiont str. KT-2, AB479082 Legionella pneumophila str. Lens, CR628337 99 RESET 121D05 99 RESET 113E02 71 RESET 28F11 Codakia orbicularis gill symbiont, X84979 RESET 113H06 98 RESET 113C01 Cycloclasticus pugetii str. PS-1, NR_025955 88 Thioalkalivibrio sp. str. HL-EbGR7 CP001339 RESET 113E12 RESET_221C01 Zetaproteobacteria 99 Mariprofundus ferrooxydans str. PV-1, AATS01000005 99 RESET 18D02 Erythrobacter longus str. EG6, AM691106 99 RESET 113F11 99 Croceitomaculum antarcticum str. IMCC3195, EF495229 Thalassobius sp. str. ZS6-23, FJ196059 88 88 RESET 18C02 RESET_121G02 99 RESET 18B06 RESET 113F03 Alphaproteobacteria Roseobacter sp. str. P81, EU195951 Thiosulfate oxidizing sediment strain DIII4, AF254106 Silicibacter sp. str. LS103, FJ937914 Phaeobacter caerulensis str. LMG 24369, AM943630 Ruegeria atlantica str. SS-05, EU624444 51 Rhodobacteraceae RESET 28G07

91 RESET_28G08 RESET_28H02 99 RESET 18E11 Calditerrivibrio nitroreducens, AB364234 Deferribacteres

94 RESET 113B09 Uncultured anammox sediment clone Kazan-3B-30/BC19-3B-30, AY592196 Acidobacteria 56 RESET 121D12 99 Loihi Seamount basalt clone P7X3b1D06, EU491086 0.05

Fig. 4 16S rRNA phylogenetic tree of Alphaproteobacteria, Gammaproteobacteria, Zetaproteobacteria, Acidobacteria, and Deferribacteres clones retrieved in this study. Clones in tree are all <97% similar with all others in this study, as determined by MOTHUR. For a full reporting of all clones, see Table S1. Alignments of sequences from this study and their nearest cultured organisms in the Greengenes database as well as some close uncultured clones from the ARB database were constructed using MEGA5. The tree was constructed using the maximum-likelihood algorithm with 500 bootstraps. Bootstrap values >50% are reported. Acidobacteria and Def- erribacteres are used outgroups. The Marinobacter branch is expanded in Fig. S1. NCBI accession numbers for sequences from cultured representatives and environmental clones are given following the species ⁄ clone name.

detected, related to Aquifex and Desulfurobacterium. Many of (Photobacterium leiognathi str. RM1, Umboniibacter marinip- the Gammaproteobacterial OTUs recovered (Fig. 4) are uniceus str. KMM 389, Calyptogena phaseoliformis symbiont most closely related to pyschrophiles (Colwellia), symbionts str. KT-2, and Codakia orbicularis gill symbiont), organisms

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Table 2 Number of shared OTUs between samples calculated at 0.03% simi- other as are R2-8 and R2-13. One basalt rock from Vailulu’u larity level. Outlined boxes indicate number of OTUs unique to that sample and Seamount, near Samoa, is more similar to a hydrothermal total number of OTUs for that sample (in parentheses). Note that total number plume also from the western Paciﬁc. Samples from of OTUs is based on rarefaction analysis and therefore biased by sample size background water and hydrothermal plumes in the Guaymas Basin look very similar to each other (Dick & Tebo, 2010).

DISCUSSION Sampling for this study occurred following an eruptive event at the site in January 2006 (Tolstoy et al., 2006), during OTU, operational taxonomic unit. which lava reached as far as 2 km away from the ridge axis (Soule et al., 2007). Methane concentrations measured in the isolated from sediment (Haliea sp. str. SY02, Cycloclasticus hydrothermal plume at 950¢ N EPR during May 2006 pugetii str. PS-1 and Kangiella koreensis str. DSM16069) and revealed concentrations up to 350 nM, 100X greater than typ- known sulfur oxidizers (Thioalkalvibrio sp. str. HL-EbGR7). ical plume measurements for stable hydrothermal plumes and Marinobacter are particularly diverse, forming 18 different >4X greater than measurements made after the 1991 eruption OTUs as defined by the 97% cutoff (Fig. S2). Nearly all of the (Love et al., 2008). The eruptions killed off much of the resi- Alphaproteobacterial OTUs fall within the Rhodobactera- dent macrobiological communities, and post-eruption larval ceae. OTUs that fell within the Acidobacteria are most closely studies found that resident species had been replaced by vent related to uncultured clones from Loihi Seamount and Kazan communities from 300 km away (Mullineaux et al., 2010). Mud Volcano. Here, we describe bacterial community composition in Rarefaction curves for the six clone libraries show that the descending particles from two different active hydrothermal three samples with the highest proportion of Epsilonproteo- vents at 950¢ N EPR during a 4-month time-series from bacteria, R1-8, R1-13, and R2-8, display the steepest rarefac- August to November 2006. Our samples are the same as those tion slopes (Fig. S3). Chao1, ACE, and Inverse Simpson’s collected by Mullineaux et al. (2010). diversity indices all indicate R2-8 to be the most diverse Automated rRNA intergenic spacer analysis was used to sample, followed by R1-13 and R1-8, in agreement with the investigate variability between 13 of the samples collected by rarefaction analysis (Table S2). All clones recovered were used the sediment traps. The same methodology has been success- for this analysis; therefore, diversity may have been higher in fully used to investigate microbial diversity across a deep-sea samples R2-13 and R2-21 if there had not been a disruption halocline (Daffonchio et al., 2006), to illustrate a predictable in sampling. seasonality in surface water bacterial communities collected To test the hypothesis that hydrothermal plume particles during a time-series experiment (Fuhrman et al., 2006), and comprise a unique deep ocean habitat with endemic bacterial to investigate correlations between bacterial communities and communities, we compared 16S rRNA gene clone libraries environmental variables in a time-series study (Steele et al., from this study with those from basalts (Santelli et al., 2008; 2011). Here, ARISA shows that bacterial community compo- Mason et al., 2009; Sudek et al., 2009), deep seawater (Pham sition is variable on the timescale of weeks and also the spatial et al., 2008; Santelli et al., 2008; Dick & Tebo, 2010), direct scale between the two vents. Bottles sampled consecutively in hydrothermal fluids (Huber et al., 2006), and hydrothermal the same trap are sometimes less similar than those taken a plumes (Nakagawa et al., 2005a; Dick & Tebo, 2010). We month or longer apart (Fig. 1). As an example, in Fig. 1, restricted our selection of studies to those in which universal sample R1-2 is much less similar to sample R1-1 than samples 16S rRNA primers were used on uncultured samples, and for R1-9 and R1-13. Similarly, sample R1-8 is much more similar whom clone frequency was reported. We included all to samples R1-18 than it is to R1-9, which was sampled sequences from samples R2-13 and R2-21 for this analysis. immediately following R1-8. This is not specific to samples We used the Morisita–Horn index of similarity because it from Trap R1. Sample R2-5 is more similar to sample R2-2 accounts for proportion of OTUs in a sample and is not biased than it is to sample R2-4. The chemistry of hydrothermal by sampling effort, which was different between the studies in vents is known to be variable from year to year, a topic studied this analysis. extensively at this study site (Von Damm, 2004), and recent Samples from time period 8 and 13 form their own clade work indicates that it is also variable on much shorter (Fig. 5), as do basalts from the EPR, Loihi Seamount, and timescales (Bennett et al., 2011). While our samples represent JdFR. Despite partial blockage of sample R2-13, it still groups particles falling out of a hydrothermal plume, and therefore with samples R1-8, R1-13, and R2-8. As with the ARISA den- the observed changes in the microbial community are a drogram (Fig. 1), analysis of the clone libraries indicates that result of changes in both the hydrothermal environment the communities in the two traps were different from each (chemistry and microbiology) and also the overlying water other – samples R1-8 and R1-13 are most similar to each column (manifested as particles falling into the traps of a

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A Hawaii basalts6 EPR basalts6 JdFR basalts3 Vailulu’u basalt7 Iheya North hydrothermal plumes4 1-13 1-8 2-8 2-13 EPR deep seawater6 2-21 1-21 HOTS, 4000 m seawater5 Baby Bare hydrothermal fluids2 Guaymas plume1 Guaymas deep seawater1 50 60 70 80 90 100

% Similarity, Morisita-Horn Index basalts hydrothermal plumes deep seawater (non-hydrothemal input) direct hydrothermal fluids

Fig. 5 (A) Cluster analysis of samples from this study with 16S rRNA gene clone libraries from basalts, deep seawater, hydrothermal plumes, and end-member hydrothermal fluids. All clone libraries were constructed using universal bacterial 16S rRNA primers with environmental samples. Environments are color coded by squares next to each sample. Samples were first reported in: 1 – Dick & Tebo (2010), 2 – Huber et al. (2006), 3 – Mason et al. (2009), 4 – Nakagawa et al. (2005a), 5 – Pham et al. (2008), 6 – Santelli et al. (2008), and 7 – Sudek et al. (2009). (B) Map of sample locations included in the cluster analysis. non-hydrothermal origin, as discussed below), the ARISA orifice during the time period of this study revealed that results show that bacterial communities on hydrothermal Bio9¢, which is part of the Bio9 vent complex, had similar Fe plume particles are also variable over short timescales. concentrations to Ty vent, but only 40% of the H2S content,

Overall, there is also a difference between the two particle yielding higher Fe ⁄ H2S (339 at Bio9¢, 132 at Ty) ratios for sample sets. Three of four samples from Trap R2 form their the Bio9 vent complex (and resultant plumes) than the Ty ⁄ Io own branch on the cladogram (Fig. 1), and seven of nine sam- area (Bennett et al., 2011). Therefore, we should expect that ples from Trap R1 form a separate branch of the cladogram. plumes emanating from different vents potentially contain This is strong evidence for different communities in the two different bacterial communities. plumes. There are multiple likely causes for this. First, individ- Additionally, our particle traps were placed at different dis- ual vents appear to harbor unique microbial communities. tances from the vents. Trap R1 was located just 30 m from This is evidenced here and also at Axial Seamount, on the Juan Bio9 and, hence, would have underlain the most particle- de Fuca Ridge (Opatkiewicz et al., 2009), where individual laden lower reaches of the buoyant hydrothermal plume. By vents, while variable over a 6-year study period, harbor contrast, Trap R2 was deployed 115 m from Ty ⁄ Io and, prokaryotic communities unique to each vent. Also, samples hence, may only have underlain the uppermost fringes of of direct hydrothermal ﬂuid collected from within the vent the buoyant plume as well as the non-buoyant plume.

2012 Blackwell Publishing Ltd Microbiology of hydrothermal plumes at 9N EPR 187

Consequently, it is to be expected that Trap R1 would receive Trap R2 is lower than to Trap R1 (because it is further from a more significant hydrothermal component of its total input the vent orifice), resulting in a higher degree of dilution of the than Trap R2. To examine differences in hydrothermal input hydrothermal flux by particles settling from the overlying between the two traps, we use the ratio of Fe to (Fe+Mn+Al). water column, which can be considered relatively constant, Fe, Mn, and Al are all elevated in hydrothermal fluids relative over time, at both sites. to seawater, but Fe ⁄ Al and Mn ⁄ Al ratios in hydrothermal flu- Our results from the cloning and sequencing of 16S rRNA ids are well above detrital values (German & Von Damm, from three concurrent samples in both traps revealed a succes- 2004). As Mn and Al generally remain in the dissolved phase sion in the bacterial community during the course of the in the near-vent non-buoyant plume, purely hydrothermal experiment. Epsilonproteobacteria were present in all the samples contain nearly no particulate Al or Mn but high par- samples, as is indicative of hydrothermal systems (Sunamura ticulate Fe, so they should exhibit Fe ⁄ (Fe+Mn+Al) ratios of et al., 2004; Nakagawa et al., 2005b; Campbell et al., 2006). 1. The greater the Mn and Al component, by contrast, the Rarefaction curves were steepest for the three samples with lower the Fe ⁄ (Fe+Mn+Al) should be, consistent with a lower the highest proportion of Epsilonproteobacteria (R1-8 was hydrothermal input (Bostro¨m et al., 1969; German et al., 52%, R1-13 was 60%, and R2-8 was 44% Epsilonproteobacte- 1990). For this study, Fe ⁄ (Fe+Mn+Al) values reveal that Trap ria). This suggests that the diversity within the Epsilonproteo- R1 contains almost exclusively hydrothermal input bacteria drives overall diversity within these samples. In other (Fe ⁄ (Fe+Mn+Al) 0.90), whereas Trap R2, as was to be pre- studies, Epsilonproteobacteria are similarly found to be the dicted because it was located further from the active vent site, drivers of intervent diversity at Axial Seamount (Opatkiewicz was less influenced by hydrothermal input (Fe ⁄ (Fe+Mn+Al) et al., 2009), and specifically, the presence or absence of 0.66; Table S3). Sulfurovum appears to be a major driver for this diversity Finally, mineralogical changes can also occur as particles tra- (Huber et al., 2007). vel down-plume, away from their hydrothermal source. Previ- Clones from the genera Sulfurovum, Sulfurimonas, and ous work has shown that sediment traps placed 1.5–20 m and Caminibacter dominated our samples (Fig. 3 and Table S1). 300 m away from active hydrothermal chimneys at the Totem Sulfurimonas autotrophica and Sulfurimonas denitrificans, vent site, 13N EPR, collected particles with very different the closest cultured representatives to the clones recovered compositions – the nearer traps, placed within the summit here, are known to chemolithoautotrophically oxidize caldera, collected 4–7 times higher Fe fluxes (derived from reduced sulfur compounds under microaerophilic conditions hydrothermal input) than the trap placed 300 m away, using O2 as an electron acceptor (Inagaki et al., 2003; Sievert outside the caldera (German et al., 2002). As hydrothermal et al., 2008). S. denitrificans can additionally use H2 and particles travel away from their vent of origin, sulfide and NO3 as an electron donor and acceptor, respectively. Sulfur- sulfate minerals tend to be deposited rapidly while oxy- ovum lithotrophicum also chemolithoautotrophically oxidizes hydroxide materials disperse further afield; this may poten- reduced sulfur, but not H2, while reducing O2 or NO3 tially influence the bacterial community (Cowen & German, (Inagaki et al., 2004; Takai et al., 2005). Members of the 0 2003). Caminibacter genus are strictly H2 oxidizers that use O2,S, In this study, we find a significant correlation between the or NO3 as electron acceptors (Alain et al., 2002; Miroshni- >1 mm size fraction of Fe ⁄ (Fe+Mn+Al), Cu, V, Ca, Al, Ti, chenko et al., 2004; Campbell et al., 2006) and can grow and 232Th, the <1 mm size fraction of Fe ⁄ (Fe+Mn+Al), Fe, autotrophically (Caminibacter profundus and Caminibacter Ca and Co, and bacterial community composition. It is inter- mediatlanticus) or mixotrophically (Caminibacter hydrogen- esting that Fe ⁄ (Fe+Mn+Al) and Ca are the only elements for iphilus). Members of Sulfurimonas and Sulfurovum can grow which both size fractions are significant – the former is an indi- at mesophilic temperatures, while members of the Caminib- cation of the relative proportion of hydrothermal influence in acter genus are moderately thermophilic. Given the lifestyles a sample while the latter is likely an indicator of both hydro- of these Epsilonproteobacteria, the hydrothermal plume par- thermal input (in the form of anhydrite) and, more probably, ticles collected here, rich in reduced sulfur compounds and biogenic (detrital) input from the overlying surface ocean. Al, containing microniches where microaerophilic conditions can Ti, and 232Th, by contrast, are all clear indicators of detrital be maintained, are ideal substrates, especially for members of input, presumably from eolian deposition that, like any Sulfurimonas and Sulfurovum. Ca-rich biogenic input, must have settled from the surface The biggest difference between time point 8 and time ocean. Given the fresh bare-rock settings of these axial vent points 13 and 21 was an increase in proportion of Gammapro- sites, surrounded by fresh lava-flows (Soule et al., 2007), we teobacteria and Alphaproteobacteria while the proportion of do not anticipate that local sediment resuspension is a likely Epsilonproteobacteria diminished. Many of the Gammaprote- candidate for biogenic or detrital inputs to these traps. Rather, obacteria clones from time points 13 and 21 samples were the correlation between microbial communities and indicators related to known heterotrophic species (Table S4) common of non-hydrothermal (biogenic and detrital) input to Trap R2 to hydrothermal environments. In particular, samples R1-21 most likely reflect the fact that the total hydrothermal input to and R2-21 are dominated by Marinobacter, a genera known

2012 Blackwell Publishing Ltd 188 J. B. SYLVAN et al. to be common in hydrothermal environments (Kaye & at the class level (Dick & Tebo, 2010). These authors found Baross, 2000; Edwards et al., 2003; Kaye et al., 2011). The few Epsilonproteobacteria in the non-buoyant plumes above presence of these Marinobacter clones in both traps (and the hydrothermal field, despite their abundance on the chim- therefore not likely due to the jellyfish caught in only Trap neys and sediments on the seafloor in this area. However, they R2) indicates a shift in bacterial communities in the plume recovered representatives from the SUP05 clade of Gamma- during this period. The diversity of clones within the Marin- proteobacteria, which are known sulfur oxidizers common in obacter genus (Fig. S2) indicates these different OTUs may other hydrothermal plumes and oxygen minimum zones have different ecological niches. Known niches among cul- (Sunamura et al., 2004; Walsh et al., 2009; German et al., tured representatives of the Marinobacter include Fe-oxida- 2010). Perhaps the niche filled by Epsilonproteobacteria at tion, hydrocarbon degradation, and a variety of organic 950¢N EPR is filled by SUP05 Gammaproteobacteria in the degradation pathways (Gauthier et al., 1992; Edwards et al., Guaymas plumes. 2003; Antunes et al., 2007). Similar niche partitioning Another study found Beta- and Gammaproteobacterial among species with nearly identical 16S rRNA genes is well ammonia oxidizers in plumes over the Endeavour Segment of documented in marine bacteria (Rocap et al., 2002; Acinas the Juan de Fuca Ridge (Lam et al., 2008). It is possible that et al., 2004) and may be the case here. our lack of detection of bacterial ammonia oxidizers and met- Also present during this last sampling period were clones hanotrophs results from their lack of association with particles. that fall within Halomonas Group 2A and Group 2C (Fig. The studies cited above used Niskin bottles to collect their S4). Members of Halomonas Group 2A appear to form a clade samples at plume depth. Therefore, hydrothermal particles of subsurface Halomonads, while members of Halomonas and planktonic cells were both sampled, whereas we collected Group 2C appear associated with massive sulfide deposits almost exclusively sinking particles in our sediment traps. (Kaye et al., 2011), and an iron-oxidizing Halomonas was Previous work has shown that while there is some overlap recently isolated from hydrothermally influenced subsurface between the membership of particle-attached and free-living crust (Smith et al., 2011). The presence of these organisms is bacteria in hydrothermal environments, differences do exist, therefore indicative of hydrothermal input, although a shift including the elevated presence of Epsilonproteobacteria in from the earlier samples. the particle-attached population (Huber et al., 2003). Our Some of the Gammaproteobacteria recovered from later work confirms the association of Epsilonproteobacteria with samples are indicative of water column populations. These hydrothermal particles, even at >100 m away from the venting include the clones related to Colwellia psycherythraea, P. leio- source of the particles. gnathi, and Pseudoalteromonas sp. str. JL-S1, which are all It is also possible that the short duration of time the samples residents of the deep ocean water column (Table S3). These could have traveled within the plumes from any vent source clones were primarily recovered from Trap R2, which was less to these traps would not be long enough to allow methane- hydrothermally influenced than Trap R1 (Table S3). and ammonia-oxidizing microbes to bloom. At the slow Most of the Alphaproteobacteria clones recovered fall lateral current speeds present above the EPR near 950¢N ) within the Rhodobacteraceae family, and all of these fall (0.01 m s 1; Thurnherr et al., 2011) and 115 m from Ty within the Roseobacter clade. A recent survey of 32 Roseo- and Io vents to Trap R2, it would take at least 3 h to travel the bacter genomes revealed that 72% contained the soxB gene, horizontal distance (vertical travel time is not considered which codes for the SoxB component of the periplasmic thio- because the plume is likely traveling horizontally with the cur- sulfate-oxidizing Sox enzyme complex and is therefore indica- rents as it rises). In that case, because only a few hours might tive of the capability for S-oxidation (Newton et al., 2010). have elapsed from when the fluids left the vent until the parti- Therefore, while not all Roseobacters are capable of S-oxida- cles fell into our sampling devices, the populations reported tion, many are and it is possible that those found here, in an here may be comprised largely of organisms entrained into the environment with elevated concentrations of reduced S com- buoyant plume as opposed to those that have developed pounds, are among those participating in S-oxidation. In par- in situ within the dispersing non-buoyant plume. We might ticular, 27 clones related to Sulfitobacter dubious str. KMM especially expect this to be the case for Trap R1, but to evalu- 3554 were recovered from sample R2-21. Although only ate this further would require additional study involving the recovered from R2-21, S. dubious is known to oxidize deployment of traps farther afield from the EPR 950¢N vent reduced S and therefore is likely a resident of the plume site and at a greater height off bottom, so that only particles environment. settling from the non-buoyant hydrothermal plume (together Few investigations have focused specifically on hydrother- with surface ocean biogenic and detrital inputs) could settle mal plume microbiology since the introduction of molecular into those traps, without any buoyant hydrothermal plume methods in oceanography. A recent study found that while input. clones indicative of aerobic methanotrophy were enriched in Our analysis of bacterial communities from hydrothermal non-buoyant plume samples from Guaymas Basin vs. back- and deep seawater communities (Fig. 5) revealed that ground samples, plume and background samples were similar samples from EPR plume particles are unique (time points 8

2012 Blackwell Publishing Ltd Microbiology of hydrothermal plumes at 9N EPR 189 and 13) from the other communities. They are dissimilar to traps and Lauren Mullineaux and her laboratory for assistance hydrothermal plume samples collected in Guaymas Basin preparing the traps and sharing the samples. We thank Brandy (Dick & Tebo, 2010), likely due to the differences in host Toner assistance in sample collection and for helpful conversa- environments (bare-rock vs. sediment-hosted vents) and sam- tions throughout. Finally, we thank three anonymous pling methods discussed above. Samples R1-21 and R2-21 reviewers for helpful comments that helped improve the are most similar to each other and most closely related to manuscript. This work was supported by the NSF Marine background seawater from the deep EPR. The high numbers Geology and Geophysics program as part of the Ridge 2000 of Marinobacter and Alphaproteobacteria clones in these program, the Science and Technology program, and the samples likely drive this similarity – 19% of the clones in the Gordon and Betty Moore Foundation. background deep EPR sample are Marinobacter. REFERENCES SUMMARY Acinas SG, Klepac-Ceraj V, Hunt DE, Pharino C, Ceraj I, Distel DL, We found bacterial communities on hydrothermal plume Polz MF (2004) Fine-scale phylogenetic architecture of a complex particles at 950¢N to be heterogeneous on the timescale of bacterial community. Nature 430, 551–554. Adams DK, Mcgillicuddy DJ, Zamudio L, Thurnherr AM, Liang XF, weeks. This work illustrates the use of a time-series approach Rouxel O, German CR, Mullineaux LS (2011) Surface-Generated to studying hydrothermal plumes, an environment that is Mesoscale Eddies Transport Deep-Sea Products from Hydrother- difficult and expensive to sample. 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Fig. S4 16S rRNA phylogenetic tree of Gammaproteobacteria clones recovered Table S4 Ecophysiology of Zetaproteobacteria, Alphaproteobacteria and Gam- during this study, with representative Alphaproteobacteria, Zetaproteobacteria maproteobacteria clones recovered from time points 13 and 21. and Deferribacteres included to root the tree. References Table S1 Distribution of OTUs in clone libraries from this study. OTUs with an asterisk (*) next to their name are from the group ‘other (non-plume)’ in Fig. 2. Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by Table S2 Diversity indices as calculated by MOTHUR. Ranges given are 95% conﬁ- the authors. Any queries (other than missing material) should dence intervals for each index. be directed to the corresponding author for the article. Table S3 Relative hydrothermal component of the particulates collected [calculated as the ratio of Fe to (Fe+Mn+Al)].

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