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Environmental Microbiology (2014)

doi:10.1111/1462-2920.12531

Norwegian deep-water coral reefs: cultivation and molecular analysis of planktonic microbial communities

Sigmund Jensen,1,2* Michael D. J. Lynch,3 Jessica L. Ray,4 Josh D. Neufeld3 and Martin Hovland5,6 1 Department of Biology and 5Centre for Geobiology, University of Bergen, Bergen, Norway. 2 Institute of Marine Research, Bergen, Norway. 3 Department of Biology, University of Waterloo, Waterloo, Ontario, Canada. 4 Uni Environment, Uni Research AS, Bergen, Norway. 6 Ambio Tech Team, Stavanger, Norway. Summary Deep-sea coral reefs do not receive sunlight and depend on plankton. Little is known about the plankton composition at such reefs, even though they constitute habitats for many invertebrates and fish. We investigated plankton communities from three reefs at 260–350 m depth at hydrocarbon fields off the mid-Norwegian coast using a combination of cultivation and small subunit (SSU) rRNA gene and transcript sequencing. Eight months incubations of a reef water sample with minimal medium, supplemented with carbon dioxide and gaseous alkanes at in situ-like conditions, enabled isolation of mostly Alphaproteobacteria (Sulfitobacter, Loktanella), Gammaproteobacteria (Colwellia) and Flavobacteria (Polaribacter). The relative abundance of isolates in the original sample ranged from ∼ 0.01% to 0.80%. Comparisons of bacterial SSU sequences from filtered plankton of reef and non-reef control samples indicated high abundance and metabolic activity of primarily Alphaproteobacteria (SAR11 Ia), Gammaproteobacteria (ARCTIC96BD-19), but also of Deltaproteobacteria (Nitrospina, SAR324). Eukaryote SSU sequences indicated metabolically active microalgae and animals, including codfish, at the reef sites. The plankton community composition

Received 20 September, 2013; revised 4 June, 2014; accepted 4 June, 2014. *For correspondence. E-mail sigmund.jensen@ bio.uib.no; Tel. (+47) 5558 4400; Fax (+47) 5558 4450.

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd

varied between reefs and differed between DNA and RNA assessments. Over 5000 operational taxonomic units were detected, some indicators of reef sites (e.g. Flavobacteria, Cercozoa, Demospongiae) and some more active at reef sites (e.g. Gammaproteobacteria, Ciliophora, Copepoda).

Introduction Deep-water coral reefs subsist without light and thrive in the cold at 200–500 m depths on continental margins. The Norwegian margin supports one of the world’s richest assemblages of deep-water coral reefs (Freiwald et al., 2004; Hovland, 2008). The reefs range in size from 10 m2, up to 100 km2, providing shelter and food for invertebrates and fish (Buhl-Mortensen et al., 2010). Fisheries and numerous hydrocarbon extraction fields in regions with coral reefs off the mid-Norwegian coast reinforce the importance of understanding the base of the food web for ensuring sustainable management of these productive waters. The dominant reef builder off the Norwegian coast is the scleractinian (stony) coral Lophelia pertusa, which are often associated with assemblages that include Madrepora oculata, Paragorgia arborea and Primnoa resedaeformis. Although most Norway reefs are established on clay-dominated substrates (Hovland et al., 1997), occurrences with hard stony ground and methanederived carbonate also occur (Boetius and Wenzhöfer, 2013). These coral reefs face prevailing currents on shelves that are influenced by tide and seasonal changes in wave energy and temperature (Buhl-Mortensen et al., 2010; Hovland et al., 2012). Deep-water corals differ from their shallow-water tropical counterparts by inhabiting the aphotic zone and lack zooxanthellae, which means that survival depends on organic detritus sinking from the photic zone (Van Oevelen et al., 2009) and plankton living in the reef surroundings (Freiwald et al., 2004; Roberts et al., 2009), including chemolithotrophic bacterioplankton (Henriet et al., 1998; Hovland et al., 2012). Waters of deep reefs appear eutrophic compared with the clear waters of shallow reefs. Coral polyps usually have

2 S. Jensen et al. well-developed cilia that separate planktonic organisms, such as algae and bacteria, and catch zooplankton (Sorokin, 1973; and references therein). The release of coral mucus and microalgal dimethylsulfoniopropionate (DMSP) may also stimulate and attract bacteria (Wild et al., 2008; Raina et al., 2010), providing further nutrition (Neulinger et al., 2008). Microorganisms from deep-water reef plankton have been identified by small subunit (SSU) ribosomal RNA (rRNA) genes separated by denaturing gradient gel electrophoresis (DGGE) or sequenced from clone libraries (Penn et al., 2006; Jensen et al., 2008; 2012; Neulinger et al., 2008; Hansson et al., 2009). Cultivation has been used to recover coral-associated bacteria from L. pertusa (Galkiewicz et al., 2011), but reef plankton have only been described for filter-isolated organisms. Reef communities were dominated by species of Alpha- and Gammaproteobacteria, Flavobacteria, Thaumarchaeota, Alveolata and Stramenopiles. Plankton with similar SSU rRNA gene sequences are widespread, from beneath Arctic sea ice (Bano and Hollibaugh, 2002) to the Antarctic Peninsula (Grzymski et al., 2012), in mesopelagic subtropical gyres (Brown et al., 2009; Swan et al., 2011), oxygen minimum zones (Guillou et al., 2008; Stevens and Ulloa, 2008; Walsh et al., 2009), hydrothermal vents (López-García et al., 2007), algal blooms (Teeling et al., 2012) and in tropical coral reefs (Nelson et al., 2011; McCliment et al., 2012). Improved insight, including the identity and study of rare microbial species, can be obtained using high-throughput sequencing of the SSU rRNA (Sogin et al., 2006; Huse et al., 2010). Recently, samples from a deep-chlorophyll maximum in the North Pacific gyre yielded sequences corresponding to one of the least known reef plankton organisms in culture, revealing a sulfur-oxidizing Gammaproteobacteria species from group ARCTIC96BD-19 (Marshall and Morris, 2013). Micro- and macroplankton include important autotrophic primary producers, in addition to a zooplankton link to higher trophic levels, which is fundamental for sustaining deep-water coral reefs (Roberts et al., 2009; Mueller et al., 2013). Many major questions remain unanswered: Are distinct plankton communities associated with deep-water coral reefs? What metabolisms are represented by these plankton that influence reef health and nutrition? Reef waters may stimulate distinct metabolic activities, leading to increased near-reef activities and possible synergistic relationships. In order to address these questions, we focused on Bacteria and Eukarya from seawater in the direct vicinity of living corals and approximately 30 m above three reefs off the midNorwegian coast, combining cultivation-dependent and cultivation-independent methods on extracted DNA and RNA.

Results Cultivation Seawater collected from ∼ 1 m proximal to corals in the Hyme field (reef B; Supporting Information Fig. S1) yielded 2.5–2.9 × 104 colony-forming units (cfu) ml−1 following 10 and 42 days of incubation. Incubation for up to 8 months yielded a variety of colony morphologies in various shades of transparent to white, yellow, brown and red, with a maximum observed diameter of 7 mm. SSU rRNA gene sequencing of polymerase chain reaction (PCR) amplicons from the cfus identified 60 bacterial strains (Supporting Information Table S1). The strains were classified to Alpha- and Gammaproteobacteria, Flavobacteria and Actinobacteria. Dominant genera were Roseovarius, Sulfitobacter, Loktanella, Colwellia and Polaribacter, and these were affiliated with strains from deep-sea to cold-surface environments (Buchan et al., 2005; Redmond and Valentine, 2011). All cultivated strains were relatively rare in the original sample based on a comparison with the corresponding sample 16S rRNA gene data, ranging from < 0.01% to 0.80% relative abundance of total bacterioplankton (Supporting Information Fig. S2). Community structure Plankton biomass that was filtered from seawater samples collected proximal (1 m) and distal (30 m above) to Hyme reefs B, C and Morvin reef A (Supporting Information Fig. S1) yielded up to 9.1 μg of DNA and 1.4 μg of RNA litre−1. From these extracts, we estimate a maximum planktonic abundance of ∼ 4.6 × 106 cells ml−1 using a prediction of 2.0 fg DNA cell−1 (Bakken and Olsen, 1989). DNA and reverse-transcribed RNA was targeted with SSU rRNA primers, and the amplicons were subjected to pyrosequencing, resulting in 221 583 bacterial and 253 043 eukaryal sequences after quality filtering (Supporting Information Table S2). The sequences formed 4129 bacterial and 1411 eukaryal operational taxonomic units (OTUs). Of these, only 50 bacterial and 53 eukaryal OTUs recruited > 1% of sequences from any single seawater sample, representing as much as 44–82% of the sequences and typically representing both depths. Such dominant OTUs corresponded to sequences previously detected from seawater (i.e. with 90–100% identity), including sea ice, surface marine sediment, hydrothermal vents (López-García et al., 2007), Deepwater Horizon oil spill (Redmond and Valentine, 2011), oxygen minimum zones (Stevens and Ulloa, 2008; Walsh et al., 2009), algal blooms (Teeling et al., 2012) and deep-water coral reefs (Penn et al., 2006; Jensen et al., 2012). Most OTUs were low abundance; singletons contributed 2190 bacterial and 463 eukaryal OTUs. Alpha-diversity estimates were con-

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology

Activity and diversity of deep-water coral reef plankton

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Fig. 1. Principal coordinate analysis (PCoA) of planktonic Bacteria (A) and Eukarya (B) surrounding coral reefs in hydrocarbon field Morvin (reef A; 350 m depth) and Hyme (reefs B, C; 257 m depth). Shading indicates reef proximal ∼ 1 m (black) and distal 30 m (grey) samples. The plankton are represented by 474 626 sequences of SSU rRNA genes (filled symbols) and SSU rRNA transcripts (open symbols) aligned to generate Bray–Curtis distance matrices for the ordinations.

sistent among samples (Supporting Information Table S2). Beta-diversity, as visualized by principal coordinates analysis (PCoA) ordinations of Bray–Curtis distance matrices (Fig. 1 and Supporting Information Fig. S3), revealed a difference in the community structure by source (i.e. DNA or RNA). Additional separation by depth was suggested by a relatively strong delta value (> 0.30) in the multiple response permutation procedure, PCoA ordination based on the dominant sequences (Supporting Information Fig. S3) and overlap among the top 10 abundant OTUs (data not shown). At higher taxonomic levels, Proteobacteria and Alveolata were dominant, accounting for 46–69% of sequences (Fig. 2). The dominant genera were ‘Candidatus Pelagibacter’ (Pelagibacteraceae), ‘Candidatus Thioglobus’ (ARCTIC96BD-19), Gyrodinium (Dinophyceae) and Phaeocystis (Haptophyceae) (Figs 2 and 3). Several OTUs did not classify to genus and were represented by sequences within the Sargasso Sea, OLI and DH-EKD clades (Giovannoni and Stingl, 2005; Guillou et al., 2008) or were novel (e.g. eukaryal OTU4190). Low-abundance organisms were taxonomically diverse and included candidate divisions (Supporting Information Table S3), in addition to the TM7 taxa previously associated with L. pertusa (Neulinger et al., 2008). A total of 912 taxa were identified (Supporting Information Fig. S4, Table S3). Many taxa were excluded by the quality filtering (Supporting Information Table S2), especially low-abundance OTUs that did not classify to domain, mitochondria, chloroplasts, eukaryal

singletons and Euk1Afm/518rm mismatches of, for example, sequences from Euryarchaeota group II and Pirellulales. Metabolic activity RNA has a short half-life and can therefore be used as a proxy for metabolic activity and growth for organisms identified through SSU rRNA (Blazewicz et al., 2013). Reverse-transcribed SSU rRNA amplicons from Hyme reef C (Supporting Information Fig. S1) resulted in a quality-checked number of 10 630 bacterial and 33 842 eukaryal sequences (Supporting Information Table S2). SSU rRNA transcript profiling across taxa (Supporting Information Fig. S4) suggested metabolic activities (cDNA representation) that correlated with organism abundance (DNA representation). OTUs for both data sets of DNA and cDNA were dominated by SAR11 Ia, ARCTIC96BD19, SAR324, Gyrodinium, Peridiniales and Phaeocystis (Fig. 3 and Supporting Information Fig. S4). Higher representation was observed in cDNA for Nitrospina, Strombidium, Bacillariophyta and Gadus, and in DNA for SAR11 II, SAR86, SAR406, Alveolata group I and Picozoa (Fig. 3). Organisms in the reef proximal sample appeared particularly active, as revealed by OTUs of Gadus, Copepoda, Ciliophora, novel Eukarya and Pseudomonas (Fig. 4). The transcript to gene ratios (RNA : DNA) were maximal for rare taxa, such as for affiliates of the Methylococcaceae methanotrophs and the ciliate Haptoria (Fig. 4 and Supporting Information Fig. S4).

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology

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Fig. 2. Major plankton taxa at the investigated deep-sea coral reefs. Seawater was collected above live corals at Morvin and Hyme fields, at distances ~1 m proximal (p) to reefs A, B, C and 30 m distal (d) to reefs B, C. Classification is based on SSU rRNA gene and transcript (bold) sequences.

Proximity to reef Several OTUs were represented exclusively by sequences from proximal (48–49%) or distal (14–24%) samples (Supporting Information Table S3) or they represented strong indicator OTUs (Dufrêne and Legendre, 1997) that were significantly associated with a particular sample or source (Table 1). None of these OTUs were dominant and all were represented by < 440 sequences, whether from DNA (Fig. 3) or RNA (Fig. 4), and few overlapped between proximal and distal samples. The most abundant proximal were OTUs 99 and 2954 (Fig. 4, Supporting Information Table S3), affiliating closely (99–100% identity) with metabolically active Copepoda from venting fluid seawater of the Lost City hydrothermal field (OTU99; López-García et al., 2007) and Coraliomargarita and multiple other marine Verrucomicrobia including South Atlantic gyre bacterioplankton from 800 m depth (OTU2954; Swan et al., 2011). At thresholds of P < 0.05, indicator value (IV) > 0.75 and > 50 sequences, there were 7 indicator OTUs by depth (proximal or distal), 17 by site (sampling site) and 79 by source (DNA or RNA). The most

abundant proximal indicators were OTUs 577 and 1643 (Table 1), affiliated at 99–100% identity with Flavobacteria and Cercozoa from deep-water coral and hydrothermal vent environments, respectively. Discussion Coverage from 454 pyrosequencing in this study exceeded all previous efforts based on DGGE, cloning and automated rRNA intergenic spacer analysis with plankton SSU rRNA gene sequences from deep-water coral reefs (Penn et al., 2006; Jensen et al., 2008; 2012; Neulinger et al., 2008; Hansson et al., 2009; Schöttner et al., 2012) and provided access to the rare biosphere (Sogin et al., 2006). Repeated detection of sequences at < 0.01% abundance by cultivation and in both DNA and RNA suggests that many of these low-abundance sequences represent bona fide rare biosphere microorganisms rather than sequencing artefacts. Lowabundance organisms may be responsible for key metabolic processes in the ocean (Brown et al., 2009). The transcript sequences recovered are indicative of protein

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology

Thiohalorhabdales (100% = 6) Midwater above Nyegga seep region Oceanospirillales SAR86 I/II/III (100% = 10) Morvin dw coral reef IIIb (100% = 87) Arctic Ocean ARCTIC96BD-19 (100% > 99) Morvin dw coral r Nitrospina SAR324 SAR406

(100% = 27) Morvin dw coral reef

JN832929

Dinophyceae

Gyrodinium (100% = 33) E North Pacific 5 m (100% = 5) Morvin dw coral reef (100% = 21) Kongsfjorden Svalbard Gymnodium (100% = 3) E North Pacific 500 m Peridiniales (100% = 67) Baffin Bay 70 m OLI11011 Gr I (100% = 49) E North Pacific 500 m 11511 Gr I (100% > 99) E North Pacific 500 m Strombidium (100% = 1) S Atlantic 25m

JX841764 JN832724 EU371148 JX842195 JQ956286 JX842543 JX842362 FJ032674

Thalassiosira (100% > 99) Beaufort Sea Pleurosigma (100% = 7) Bering Sea

JN934691 KC771201

Culture collection (100% = 31) Mediterranean Sea

JX660992

Pyramimonas

(100% = 76) Beaufort Sea 70 m

JF698772

(100% = 35) North Sea 5 m

JX988758

Teleostei

Gadus morhua putative eggs/larvae (100% = 5) Atl

JN132136

1737 896

S

Bacillariophyta

1640

C H

Phaeocystis

M P

Alveolata

720 1000 1157 606 911 792 1494 579

α

858

Pelagibacteraceae SAR11 Ia (100% > 99) ‘Ca. Pelagibacter ubique’ NR_074224 Ia (100% > 99) Montastraea faveolata JQ515624 Ia (100% > 99) Morvin deep-water coral reef JN832940 II (100% > 99) Northern Adriatic Sea 21 m JX864719 Rickettsiales (100% = 4) Gulf of Mexico postplume 1100 m JX879056

γ

295 1146

Picozoa

441 1383 1490 Proximal

Acc number

δ

1200 257 267 133

Consensus lineage Nearest relative (% identity #hits) origin

5

D

2107 2275 1389 71 2789

Reef C

Reef C

Reef B

Reef C

Reef C

Reef B

OTU

Reef A

Activity and diversity of deep-water coral reef plankton

(100% = 36) seawater Alaskan octocorals clone GBSar324 (100% > 99) Guayamas Basin

JN833099 JN832981 JN976683 JN832943 DQ396198 JX406433

Distal < 0.01% (< 2 sequences) 0.01-0.09% 0.10-0.99% 1.00-4.99% >5.00%

Fig. 3. The heat map shows the relative abundances of SSU rRNA gene and transcript (bold) sequences, followed by classification, nearest relative, number of top BLASTN hits and a representative with origin and accession number. Abbreviations indicate Alphaproteobacteria (α), Gammaproteobacteria (γ), Deltaproteobacteria (δ), Deferribacteres (D), Stramenopiles (S), Haptophyceae (H), Chlorophyta (C), Picozoa (P) and Metazoa (M). Note that top abundant OTUs are not shared by all samples and treatments, resulting in more than five listed for each.

synthesis, thereby suggesting metabolic activity and growth (Blazewicz et al., 2013). Spring phytoplankton representatives (Teeling et al., 2012) were included among the five most abundant OTUs (Fig. 3), consistent with our samples being collected in May–June. Seasonal phytoplankton blooms have a large influence on the composition of plankton that sink from the photic zone. This supports an integral role of phytoplankton-derived carbon in deep-water coral reef

nutrition (Sorokin, 1973; Freiwald et al., 2004; Roberts et al., 2009; Van Oevelen et al., 2009; Mueller et al., 2013). Phytoplankton SSU rRNA gene and transcript sequence abundance in the samples was high (Figs 2–4 and Supporting Information Fig. S4 and Table S3). Synechococcus and algal chloroplasts were common (0.4–1.6% abundance) and Chlorophyta, Cryptophyta, Bacillariophyta and Haptophyta were enriched (8.8– 24.5% abundance). Bacillariophyta revealed a slightly

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Fig. 4. Top 50 abundant OTUs from SSU rRNA transcript sequences of the Hyme reef C plankton. The dotted line distinguishes enrichment; OTUs above the line contain transcripts enriched in the proximal sample, OTUs below the line contain transcripts enriched in the distal sample. Coloured OTUs indicate dominant and rare taxa as determined from the SSU rRNA gene sequences. OTU1490 (putative eggs or larvae) could be overestimated because of the higher contribution of template DNA by multicellular organisms (López-García et al., 2007). None of the OTUs represented any of the indicator OTUs by depth (P < 0.05). Data normalization was performed by replacing any missing sequence information (0) by a minimum number of sequences (1) and by dividing the sequence abundance on the actual total number of sequences (minus the sum of added 1).

Table 1. Reef plankton indicator OTUs by depth (P < 0.05). OTU

IV

Phylum (Class)

Nearest taxon (% identity #hits) origin and accession number

Abundance

577 (p) 862 (d) 3160 (d) 1643 (p) 572 (p) 790 (p) 1736 (d)

0.75 1.00 0.78 1.00 0.96 1.00 1.00

Bacteroidetes (Flavobacteria) Bacteroidetes (Flavobacteria) Proteobacteria (Alpha) Rhizaria (Cercozoa)a Porifiera (Demospongiae) Porifera (Demospongiae) Stramenopiles (Labyrinthulida)a

Unassigned (99% = 4) Alaskan deep-sea octocorals DQ395555 Unassigned (100% = 1) Romanche Fracture Zone JN710291 Unassigned (100% = 1) Aegan Sea 200 m AF406524 Ascetosporea (100% = 1) Lucky Strike vent 1695 m EU567276 Phorbas (100% = 21) Firestone Bay Plymouth KC902286 Mycale (100% = 7) Massachusetts coast AJ627185 Unassigned (100% = 5) Saanich Inlet 10 m JQ226503

385:51 32:36 71:65 277:10 255:4 158:4 9:45

a. Different rank. The abundance ratio is denoted by the number of SSU rRNA gene and transcript sequences (included if bold) across all proximal (p) : distal (d) samples. Indicator values (IV) denote strength of the indicator (0–1).

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology

Activity and diversity of deep-water coral reef plankton increased reef proximal abundance and activity in contrast to other phototrophs, which generally increased in reef distal abundance (0.6–3.1-fold increased) and activity (about 25% increased). This might indicate that diatoms either profit from overall higher plankton abundances at coral sites by switching to a bacteriovorus lifestyle (Zubkov and Tarran, 2008) or that other algae undergo predation by corals more than the detected diatoms. A comparison of SSU rRNA gene sequences from the Morvin plankton and a water column sample from the same depth, away from reefs, indicated higher abundance of microalgae at the reef (Jensen et al., 2012). These microalgae abundances and activities suggest more rapid transport than simply via sinking. Downwelling, driven by tidal pulses, was proposed to explain high seawater chlorophyll fluorescence in the Mingulay reef complex off Scotland (Roberts et al., 2009). Physical processes tend to increase mixing at continental shelves (Giovannoni and Stingl, 2005) and may explain how green algae and diatoms retain metabolic activity at 350 m depth. Phytoplankton likely influenced bacterioplankton communities by production of exudates or potentially by grazing (Zubkov and Tarran, 2008). Roseobacter (Alphaproteobacteria), Ulvibacter and Polaribacter (Flavobacteria) associate with blooming phytoplankton (Teeling et al., 2012) and were frequently detected in our samples (Fig. 4, Supporting Information Table S1). Roseobacters form dominant coastal bacterioplankton (Buchan et al., 2005), with strains such as the cultured Loktanella, Sulfitobacter and Roseovarius implicated in the metabolism of phytoplankton DMSP (Raina et al., 2010), inorganic sulfite and thiosulfate (Buchan et al., 2005). No reef plankton indicator OTUs associated with our cultured strains, but OTU577 affiliated with Alaskan deep-sea octocoral-associated Flavobacteria (Penn et al., 2006). Cultured Flavobacteria, including Polaribacter strains 39 and 128 revealed SSU rRNA gene sequences with no match to sequences generated from the inoculum (Fig. S2). Nonetheless, Polaribacter species at 1.5% relative abundance and 99% sequence identity (OTU562) were detected as bacterioplankton from 30 m above in the Hyme reef C sample (Fig. 4, Supporting Information Table S3). This indicates a dynamic reef seawater community structure. Distinct Flavobacteria thrive in different marine waters, such as a Moorea shallow-water coral reef in the French Polynesia (Nelson et al., 2011) or following the Deepwater Horizon oil spill (Redmond and Valentine, 2011). The observed enrichment of Flavobacteriaeae and Rhodobacteraceae in the Moorea waters may be a result of selective pressure from removal of seawater organic carbon by the reef (Nelson et al., 2011; McCliment et al., 2012). Flavobacteria may encode diatom exopolysaccharide or DMSP degradation capabili-

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ties (Raina et al., 2010; Teeling et al., 2012), suggesting an important heterotrophic role in blooms and reefs. Polaribacter species contain proteorhodopsin, which might be used to harvest light and gain extra energy (González et al., 2008), as suggested for other coldwater photoheterotrophs (Grzymski et al., 2012). However, proteorhodopsins are poorly understood and the Flavobacteria, SAR86, HTCC2207 (SAR92) and Pelagibacter ubique (SAR11 Ia) might not all have used their proteorhodopsins to gain surplus energy before sinking below the photic zone; for example, P. ubique have not been shown to grow better in the light (Giovannoni and Stingl, 2005; Giovannoni et al., 2005). The reef plankton were not restricted to members of phytoplankton blooms. Nitrospina nitrite oxidizers and other chemolithoautotrophs associated with deep-water coral reefs (Penn et al., 2006; Jensen et al., 2008), oxygen minimum zones (Stevens and Ulloa, 2008; Walsh et al., 2009) and surface waters of the Antarctic Peninsula (Grzymski et al., 2012) were part of the reef plankton community structure (Figs 3 and 4, Supporting Information Table S3). In winter, less phytoplankton at darkened high latitudes may allow chemotrophs to expand into surface waters. Chemolithoautroph-derived carbon has the potential to aid in the nutrition of deep-water coral reefs off the Norwegian coast during low-energy conditions in winter (Hovland et al., 2012). Mueller and colleagues (2013) used stable isotope-enriched bacteria (13C, 15N) to show that the L. pertusa consume bacterioplankton, suggesting it may represent a valuable source of nutrition. Metabolic capabilities inferred from the ‘Candidatus Thioglobus singularis’ (Marshall and Morris, 2013) implicated aprA-encoded sulfur oxidation and the assimilation of thiosulfate and glucose. ARCTIC96BD-19 cells collected directly from Atlantic and Pacific mesopelagic gyres also encoded aprA, in addition to cbbM-mediated chemolithoautotrophic CO2 assimilation (Swan et al., 2011). These authors also detected methylotrophic pathways and possibly pmoA-encoded methane oxidation in cells of uncultured SAR324 bacteria. Other reef plankton of interest included a metabolically active OTU1146 (1.0–3.5% abundance; Figs 3 and 4), which matched clone ctg_NISA008 from seawater surrounding Alaskan octocorals (Penn et al., 2006) and a SAR324 fragment (GBSar324) from the Guyamas Basin hydrocarbon-dominated vent plume (Sheik et al., 2013). Sequences from the Lucky Strike hydrothermal vent environment affiliated with a metabolically active Cercozoa suggested a reef indicator (OTU1643; Table 1). No recognized methanotrophs were isolated in culture in this study, even though the samples were obtained from above a hydrocarbon reservoir and contained cold seepassociated SSU rRNA gene sequences with > 97% identity to Methylococcaceae and Methylocystaceae (OTUs

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2281, 3476). Considering the underlying hydrocarbon field and the proximity with the seafloor, stimulation of putative methanotrophs is unlikely anything reef specific. The extant methylotroph of highest abundance was Methylophilus, occurring at ∼ 0.6% of the 16S rRNA gene sequences, consistent with the ∼ 0.4% reported for a global ocean metagenomic survey (Rusch et al., 2007). Sequences from recognized C2–C3 alkane utilizers were also of low abundance, such as OTU3844 and the corresponding isolates (i.e. 35, 36, 38, 51, 53) affiliated with Colwellia from plumes of the Deepwater Horizon spill (Redmond and Valentine, 2011). Whether reef plankton ecotypes exist remains unknown as determining niche specificity was challenging with samples from only three reefs and no samples alongside reefs. Although the reef indicator OTUs were statistically valid (Table 1), additional samples would help confirm these observations. Physiochemical conditions experienced by reef plankton at continental margins are likely to vary, especially in a spring bloom, but beneath the photic zone, bloom variation across a 30 m height gradient is considered small. The two control samples were collected to represent photic zone export (Supporting Information Table S2). Our sampling had limited ability to distinguish organisms generally associated with the seafloor and to resolve community variation. Sample handling is unlikely to have caused some taxa to appear more active than others. The cDNA was expected to reflect RNA and approximately the same template quantity was used under the same PCR conditions to recover SSU rRNA gene and transcript sequences. Pyrosequencing has a well-characterized error profile and sequences were filtered using the PYRONOISE algorithm (Quince et al., 2011) and conservative clustering, in addition to length and taxonomic filtering (e.g. removal of contaminating taxa and organelle sequences) through Automation, Extension, and Integration of Microbial Ecology (AXIOME) (Lynch et al., 2013). We are also aware of influences from life history, as some microorganisms may increase their ribosome content prior to dormancy, to quickly resume metabolic activity in response to nutrients (Blazewicz et al., 2013). However, removing all artefacts and eliminating the risk of autocorrelation would be a challenge. Nonetheless, if greater rRNA infers greater activity and growth (Blazewicz et al., 2013), our results may imply more biomass turnover in proximity to corals. The increased near-reef activity (Fig. 4) corresponds with DMSP and mucus-activated bacterioplankton respiration rates, intense trophic interactions and nutrient recycling back into the reef system (Wild et al., 2008; Raina et al., 2010). Actively dividing cells and increased bacterial abundance were observed close to shallow-water coral reef surfaces (Bourne and Webster, 2013). Potential parasites, such as OLI11011 and ciliate-infecting

Duboscquella (Guillou et al., 2008), may have been present in the reef water as dinospores but were more abundant (> 1%) than host associates recognized as potential pathogens (Vibrionales; < 0.1%) or symbionts (PAUC34f from sponge < 0.05%). Given equal uncertainty for the recovery of rare sequences across taxa, rare dormant organisms (Sogin et al., 2006) may coexist with rare active organisms being limited by grazing, viral lysis or other external factors (Campbell et al., 2011).

Concluding remarks Our data provide insight into deep-water coral reef plankton biodiversity and potential activity. Even though the investigated reef seawater communities were distinct from one another, it was possible to detect reef indicator OTUs, albeit only low-abundance ones. Metabolic states spanned dormant, active and cultivable species including those from the rare biosphere. The identified organisms were broadly characterized to representatives of surface water phytoplankton blooms, mesopelagic plankton, including chemolithoautotrophs and near coral zooplankton. These organisms input food resources for corals to thrive in the deep. Near corals, intense trophic interactions were indicated and a partly looped food web could be in play. Coral-associated, mucus-attracted and scavenging bacteria are likely central to these environments, forming a complex food web linked by grazers at the levels of ciliates, copepods, sponges, corals and fish. Observations made in this study provide a basis for generating hypotheses for future larger-scale sampling, laboratory incubations and complementary analysis of mRNA transcripts for increased understanding of reef ecosystem community function.

Experimental procedures Sampling sites Sampled coral reefs are located near the shelf break in the Haltenbanken region of the Norwegian Sea, 100–200 km off the coast (Supporting Information Fig. S1). This region is important for fisheries and the oil industry. Reefs GRR10 (64.36 N, 07.55 E) and GRR11 (64.36 N, 07.54 E), referred to as ‘reef C’ and ‘reef B’, respectively, are located in the Hyme (formerly ‘Gygrid’) hydrocarbon field. They form topographical high points and are generally distributed along breaks of slope on the margins of iceberg plough marks, comprising mounds of dead and sparse L. pertusa that have been colonized by the octocorals P. arborea, Paramuricea placomus, bivalves (Acesta excavata) and sponges (DeepOcean Survey Report, 2011). Reef MRR08 (65.14 N, 06.47 E), referred to as ‘reef A’, is located partly within a pockmark in the Morvin hydrocarbon field and is dominated by L. pertusa, Pa. arborea and Primnoa resedaeformis corals (Hovland, 2008).

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology

Activity and diversity of deep-water coral reef plankton Sampling Dives were performed to reef C and reef B in May 2011 using the ‘Supporter 11’ remotely operated vehicle, equipped with a 1.7-l Niskin bottle. Seawater from multiple dives was collected at 257 m depth (about 1 m above the seafloor and in 1 m proximity to live corals; ‘proximal’ samples) and at 227 m depth (30 m above the reefs; ‘distal’ samples). Onboard, plankton in 1 l of seawater were harvested in duplicate by filtration through 0.2 μm Sterivex cartridges (Millipore, Billerica, MA, USA). Excess seawater was forced from filters by flushing with air. One cartridge was frozen (−18°C) and one cartridge was filled with RNAlater (Ambion, Life Technologies, Carlsbad, CA, USA) and stored in the dark at 4°C, together with unfiltered seawater (∼ 0.5 l) collected in autoclaved Sovirel bottles. All samples were transported in a cooler bag to the lab where frozen cartridges were stored at −80°C, RNAlater-filled cartridges and unfiltered seawater were stored in the dark at ∼ 5°C. The reef A sample included in this study was pooled from equal volumes of three subsamples (W1, W2, W3) of proximal plankton DNA that had been taken in the context of an earlier study, in June 2008 at the Morvin field and 350 m depth, using Sanger sequencing (Jensen et al., 2012). These DNA samples had been kept at −80°C since extraction.

Cultivation Seawater was plated undiluted and diluted to 10−2 on plates solidified with 8 g Gelzan l−1 (Sigma-Aldrich, St. Louis, MO, USA) in artificial seawater (Morel et al., 1979) and 1/2 X NEM-1 ammonium mineral salts (Sieburth et al., 1987). Plates in replicates of six were incubated in the darkness at ∼ 5°C in a reef-analogous environment prepared with oxic atmospheres in glass jars supplemented with gases in approximately (vol/vol): 1% carbon dioxide and 10% each of either methane, ethane, propane, ammonium (NH4HCO3) or 1% sulfide. Controls were incubated outside of glass jars in ambient air and included plates with an organic medium (1/2 X R2A, Sigma-Aldrich).

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ethanol (70% v/v), air dried and suspended in nuclease-free water (Ambion, Life Technologies). To prevent loss of cells dislodged from the Sterivex filter membrane, RNAlater was collected (∼ 2 ml) and centrifuged at 13 000 r.p.m. for 20 min at 4°C to pellet cells. The supernatant was collected and stored on ice. Pellets and cartridges were processed in parallel, as described above. Protein extraction was performed using acidified phenol (pH 4.3), with the supernatant included at this stage. Clean RNA was suspended in nuclease-free water and RNA from membrane, the RNAlater pellet and the supernatant was pooled. DNA was removed using DNase (Turbo DNA-free kit) according to the manufacturer’s instructions (Ambion, Life Technologies). Removal of DNA was confirmed by a negative result in 16S rRNA gene PCR amplification using bacterial primers (9bfm/518rm), as described below. Nucleic acids were quantified spectrophotometrically using the NanoDrop 1000 (Thermo Fisher, Waltham, MA, USA) or following the addition of a fluorescent stain using the Qubit (Invitrogen, Life Technologies, Carlsbad, CA, USA). More RNA was extracted with DNA from frozen filters (up to 1.2 μg RNA l−1) compared with extraction from filters in RNAlater (up to 0.2 μg l−1).

Reverse transcription of RNA Purified and pooled from RNAlater and DNA coextracts, RNA was converted to single-stranded cDNA by reverse transcription using the iScript kit (Bio-Rad, Hercules, CA, USA). Five μl of RNA, diluted to 1.0 and 0.1 ng μl−1, were mixed with random hexamers and nuclease-free water. Potential secondary structures in the RNA were removed by heating to 65°C for 5 min, followed by immediate cooling on ice. Firststrand cDNA synthesis was performed following addition of reaction mix and RNAse H+ reverse transcriptase. Controls for DNA contamination omitted the addition of reverse transcriptase or template. Reactions in 20 μl were performed in a PTC-200 thermocycler (Bio-Rad) at 25°C for 5 min, followed by 42°C for 30 min and 85°C for 5 min.

Evaluation of domain-specific primers Nucleic acid purification Nucleic acids were extracted from both frozen and RNAlaterpreserved plankton using a modified alkaline-SDS lysis protocol (Somerville et al., 1989), scaled to fit 1.5 ml microcentrifuge tubes as previously described (Jensen et al., 2012). Briefly, cartridges were thawed on ice and cells lysed with lysozyme (9.0 mg ml−1) in sucrose (20% w/v), ethylenediaminetetraacetic acid (EDTA) (40 mM), Tris-HCl (50 mM, pH 8.0) at 37°C for 30 min on a rotary shaker. Following addition of SDS (1% w/v) and proteinase K (0.6 mg ml−1), lysis continued on the shaker at 55°C for 2 h. Lysates were purified from proteins with chloroform : phenol : isoamyl alcohol extraction (25:24:1, pH 8.0) followed by chloroform : isoamyl alcohol (24:1). Nucleic acids were precipitated in polyethylene glycol (PEG) 6000 solution (20% w/v) and NaCl (1 M), amended with 0.25% w/v of glycogen (Roche, Mannheim, Germany) at room temperature overnight. Nucleic acids were pelleted by centrifugation at 13 000 r.p.m. for 30 min at 4°C and washed in ice-cold

Published SSU rRNA gene primers were evaluated for taxon coverage using the SILVA 104 (Quast et al., 2013) reference alignment in ARB (Ludwig et al., 2004). Nucleotide modifications for improved coverage were verified using the RDP-II implementation of PROBEMATCH (Cole et al., 2009) and the SILVA TESTPROBE algorithm (Quast et al., 2013). The variable regions V1-V3 were flanked on the 5′ side using primer 9bfm (5′-GAGTTTGATYHTGGCTCAG-3′) of Mühling and colleagues (2008) for high specificity and coverage of the domain Bacteria and primer Euk1Af (5′-CTGG TKGATYCTGCCAG-3′) of Diéz and colleagues (2001), modified by inclusion of two degenerate positions (underlined) for maximal coverage of the domain Eukarya. The ‘universal’ primer 518r (5′-ATTACCGCGGSTGCTGG-3′) of Muyzer and colleagues (1993) was modified by inclusion of one degenerate position (underlined) and flanked the 3′ side of the region. PCR with primers 9bfm/518rm (Bacteria) and Euk1Afm/518rm (Eukarya) were expected to produce amplicons of ∼ 500 bp.

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PCR amplification and sequencing Cultured isolates were characterized by whole cell colony PCR and gene sequencing, beginning by amplification with 16S rRNA gene primers 27f/1492r (Lane, 1991) and Dynazyme II (Finnzymes, Espoo, Finland). Reaction mixtures (20 μl) contained 0.5 μl template, 0.5 μM of each primer, 250 μM of each dNTP, 20 μg ml−1 of bovine serum albumin and 0.4 U of DNA polymerase in 1X buffer. The PCR was performed in the thermocycler with denaturation at 95°C for 1 min followed by 30 cycles of denaturation at 94°C for 1 min, annealing at 60°C for 1 min, extension at 72°C for 2 min and with a final extension at 72°C for 7 min. Amplicons for GS-FLX 454 Titanium pyrosequencing were generated using a two-step protocol (Berry et al., 2011). Reaction mixtures were as described above, with 10–100 ng DNA or cDNA, Phusion polymerase in HF buffer (Finnzymes) and primers 9bfm/518rm or Euk1Afm/518rm. The first PCR step was performed without sequencing adapters for 20 cycles, with an initial denaturation at 98°C for 1 min, cycling at 98°C for 10 s, 53°C for 30 s, 72°C for 1 min and a final 72°C for 5 min. Reactions were performed in triplicate for each sample. Two μl of pooled and cleaned (ExoSAP-IT, GE Healthcare, UK) template from the first-step reaction was used as template for a second-step reaction, performed for 10 cycles with primers added sequencing adapters at the 5′ end. All amplicons were checked for size and purity by agarose gel electrophoresis followed by staining with ethidium bromide (Sambrook and Russell, 2001). Sanger sequencing was performed from primer 27f on cleaned (ExoSAP-IT) amplicons using the BigDye 3.1 chemistry (Perkin-Elmer) and an ABI 3700 PE sequencer (Applied Biosystems). Amplicons for pyrosequencing were purified using Agencourt AMPure beads (Beckman Coulter Genomics, Beverly, MA, USA) and quantified using a fluorescent stain-based kit and a Qubit fluorometer (Invitrogen). Emulsion PCR and pyrosequencing (from primer 518rm) was performed at the Norwegian HighThroughput Sequencing Centre (University of Oslo).

Sequence processing and analysis Sanger sequences were read directly from the chromatograms and manually corrected. Pyrosequences and readquality data were extracted from the flowgram files using mothur (Schloss et al., 2009). Sequencing errors were filtered from the dataset using the mothur implementation of PYRONOISE (Quince et al., 2011); barcodes, primers and sequences of < 200 nucleotides in length were discarded. Chimeras were removed using the de novo option in UCHIME (Edgar et al., 2011). The previous detection of rRNA sequences from Acinetobacter in glycogen (Bartram et al., 2009), combined with the visualization of nucleic acids following gel electrophoresis of a glycogen sample, led us to remove a total of 37 111 Acinetobacter sequences from the data set. All subsequent pyrosequence analyses were managed using the AXIOME v. 1.6 pipeline (Lynch et al., 2013). Sequence alignments were performed using ssu-align (Nawrocki and Eddy, 2010) and the sequences were clustered to OTUs using UCLUST (Edgar, 2010). Rank abundance, Shannon’s diversity and Chao species richness estimation (Chao, 1987) calculations were performed at 97% identity for

each sample. Analysis of alpha- and beta-diversity was performed using both AXIOME-specific and QIIME (Caporaso et al., 2010) analyses. Ordination of beta-diversity included PCoA of Bray–Curtis distances (Lozupone et al., 2006). Indicator species analysis (Dufrêne and Legendre, 1997) based on depth, site and source was performed on 97% OTUs from all sequences and are for clarity referred to as ‘indicator OTUs’. Taxonomy was assigned at a threshold of 0.75 by the RDP-II CLASSIFIER V. 2.2 (Wang et al., 2007) trained against Greengenes database for Bacteria (DeSantis et al., 2006) and SILVA release 108 (non-redundant reference; SSU Ref NR) for Eukarya (Quast et al., 2013). Finer classification and the assessment of habitat association were explored using the SILVA taxonomy (Quast et al., 2013) and BLASTN V. 2.2.28+ (Altschul et al., 1997). Standalone BLASTN searches were used for the comparison of sequences from the cultured and pyrosequencing data sets. These sequences were aligned in SINA (Pruesse et al., 2012) and a phylogenetic comparison was performed in ARB (Ludwig et al., 2004).

Data submission The SSU rRNA gene sequences from isolated strains were submitted to GenBank (KF477324-KF477383). Pyrosequence flowgrams from SSU rRNA gene and transcript sequences from filter-isolated plankton were submitted to the NCBI Sequence Read Archive under the BioProject PRJNA216954.

Acknowledgements We thank DeepOcean Subsea Services and the crew of Volstad Surveyor for collecting seawater from Hyme. Special thanks to Thomas H. Marthinsen for sample handling and filtration. Lorentz Vikra provided organization and the survey report. We also thank Tanja Barth for the propane, Heidi Kongshaug for confirming glycogen (Roche) impurities, Ave Tooming-Klunderud for the pyrosequencing technical support and Frede Thingstad for helpful comments. This project was supported by Statoil ASA (contract 4502189878) and a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Supporting information Additional Supporting Information may be found in the online version of this article at the publisher’s web-site: Fig. S1. Map indicating the position of the reef plankton sampling sites. The sites are located at the Haltenbanken fishing ground. Reef A (65.14 N, 06.47 E) at 350 m depth and partly down a pockmark in the Morvin field ∼ 200 km off the mid-Norwegian coast. Reef B (64.36 N, 07.54 E) and reef C (64.36 N, 07.55 E) are at a distance of ∼ 100 km SSE and are separated by ∼ 0.5 km at 257 m depth on topographical high points in the Hyme field. Fig. S2. Comparison of SSU rRNA gene sequences from cultured and filter-isolated data sets from proximal samples. Tabulated data indicate strain sequence abundance in plankton from the reef B inoculum, reef A, reef C and the sequence identities. For multiple strains in affiliation with the same plankton OTU, the lowest possible BLASTN score is given. The sequences were clustered into a maximum likelihood tree (PhyML) using ARB (Ludwig et al., 2004) and alignment spans Escherichia coli positions 268-519, excluding ambiguities, missing data and positions where the frequency of a nucleotide occurring is < 50%. The sequences fall into

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the classes Alphaproteobacteria, Gammaproteobacteria, Actinobacteria and Flavobacteria (branch truncation separates phyla). OTUs in bold include SSU rRNA transcript sequences. The scale bar indicates 0.10 changes per nucleotide. Fig. S3. Principal coordinates analysis (PCoA) ordination based on a modified collection of the reef plankton data set. Reef A is Morvin field, reefs B and C are Hyme field. Dotted lines indicate differences between plankton communities of proximal (reef) and distal (control) samples. The data sets deviate from data set of Fig. 1 by the following modifications. The upper two plots include many taxa that had been excluded by the quality filtering, especially low-abundance OTUs that did not classify to domain, mitochondria, chloroplasts, eukaryal singletons and Euk1Afm/518rm mismatches of, for example, sequences from Euryarchaeota group II and Pirellulales. The middle two plots exclude OTUs of less than 10 sequences. The lower two plots exclude all OTUs of less than 1% relative abundance and are not rarefied down to the cDNA library (Table 1).The organisms are represented by sequences of SSU rRNA genes (filled symbols) and SSU rRNA transcripts (open symbols), aligned to generate the PCoA underlying distance matrix (Bray–Curtis). Fig. S4. Plankton community composition at the investigated deep-sea coral sites. Taxonomic affiliations of OTUs were determined to the lowest possible rank. Each data point represents one taxon (Supporting Information Table S3 for details). The dotted line indicates a SSU rRNA transcript to gene ratio of one and the shaded region indicates rare to zero sequence abundance. Note that because samples and treatments contained different total number of sequences (Supporting Information Table S2), percentages between sample and treatment vary. Data normalization was performed by replacing any missing sequence information (0) by a minimum percentage of sequences (0.003). Table S1. Colony-forming unit (cfu) derived strains from seawater proximal to coral reef B. Table S2. Reef plankton diversity indices and community similarities. Samples were collected above the reefs, proximal ∼ 1 m (350 m, 257 m) and distal 30 m (227 m) to live corals. Recovered nucleic acid (NA) sequences from SSU rRNA genes (g) and transcripts (c) were clustered at 97% identity (∼ 250 nucleotides) and low quality sequences removed (−%). Good’s coverage was above 85% for all samples [1-(singletons/sequences) × 100]. Table S3. (A, B) Identified taxa and their SSU rRNA sequence abundances. The taxa are listed alphabetically to the lowest possible rank.

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology