Antonie van Leeuwenhoek (2015) 108:329–342 DOI 10.1007/s10482-015-0485-4

ORIGINAL PAPER

Spatial distribution and abundance of ammonia-oxidizing microorganisms in deep-sea sediments of the Pacific Ocean Zhu-Hua Luo . Wei Xu . Meng Li . Ji-Dong Gu . Tian-Hua Zhong

Received: 24 October 2014 / Accepted: 18 May 2015 / Published online: 27 May 2015 Ó Springer International Publishing Switzerland 2015

Abstract Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, is performed by nitrifying microbes including ammonia-oxidizing bacteria (AOB) and archaea (AOA). In the current study, the phylogenetic diversity and abundance of AOB and AOA in deep-sea sediments of the Pacific Ocean were investigated using ammonia monooxygenase subunit A (amoA) coding genes as molecular markers. The study uncovered 3 AOB unique operational taxonomic units (OTUs, defined at sequence groups that differ by B5 %), which indicates lower diversity than AOA (13 OTUs obtained). All AOB amoA gene sequences were phylogenetically related to

Zhu-Hua Luo and Wei Xu have contributed equally to the work.

amoA sequences similar to those found in marine Nitrosospira species, and all AOA amoA gene sequences were affiliated with the marine sediment clade. Quantitative PCR revealed similar archaeal amoA gene abundances [1.68 9 105–1.89 9 106 copies/g sediment (wet weight)] among different sites. Bacterial amoA gene abundances ranged from 5.28 9 103 to 2.29 9 106 copies/g sediment (wet weight). The AOA/AOB amoA gene abundance ratios ranged from 0.012 to 162 and were negatively correlated with total C and C/N ratio. These results suggest that organic loading may be a key factor regulating the relative abundance of AOA and AOB in deep-sea environments of the Pacific Ocean. Keywords Ammonia-oxidizing archaea  Ammonia-oxidizing bacteria  Deep-sea sediments  Ammonia monooxygenase a-subunit (amoA) gene  Diversity  Abundance

Electronic supplementary material The online version of this article (doi:10.1007/s10482-015-0485-4) contains supplementary material, which is available to authorized users. Z.-H. Luo (&)  W. Xu  T.-H. Zhong Key Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography, State Oceanic Administration, 178 Daxue Road, Xiamen 361005, People’s Republic of China e-mail: [email protected]; [email protected] Z.-H. Luo  W. Xu  T.-H. Zhong Fujian Collaborative Innovation Center for Exploitation and Utilization of Marine Biological Resources, 178 Daxue Road, Xiamen 361005, People’s Republic of China

M. Li Institute for Advanced Study, Shenzhen University, Shenzhen 518060, People’s Republic of China J.-D. Gu School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, People’s Republic of China

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Introduction Nitrification, the sequential oxidation of ammonia to nitrate through nitrite, is critical in the global nitrogen cycle. Ammonia oxidation, the conversion of ammonia to nitrite, is the first and rate-limiting step of nitrification (Prosser 1989). Ammonia oxidation was previously believed to be exclusively performed by ammoniaoxidizing bacteria (AOB), which taxonomically fall into two distinct monophyletic groups, the b-proteobacteria, including Nitrosomonas and Nitrosospira, and the c-proteobacteria Nitrosococcus (Purkhold et al. 2000). This view has recently been changed by the detection of archaeal ammonia monooxygenase genes in uncultivated archaea (Venter et al. 2004; Treusch et al. 2005) and the successful isolation of an autotrophic ammoniaoxidizing marine archaeon Nitrosopumilus maritimus from a marine aquarium (Ko¨nneke et al. 2005). The contributions of ammonia-oxidizing archaea (AOA) to the nitrogen cycle have been recognized based on a series of studies on marine and terrestrial ecosystems (Avrahami and Conrad 2003; Caffrey et al. 2007; Herrmann et al. 2009; Moin et al. 2009; Christman et al. 2011; Zhang et al. 2011; Xu et al. 2014). The amoA gene encoding the a-subunit of ammonia monooxygenase (AMO) has been extensively employed as a functional genetic marker for cultivationindependent studies of the community structure and abundance of AOA and AOB in a variety of environments (Rotthauwe et al. 1997; Francis et al. 2005; Hatzenpichler et al. 2008; Park et al. 2008; Herrmann et al. 2009; Wang et al. 2009; Gubry-Rangin et al. 2010; Li et al. 2011). Widespread distribution of bacterial and archaeal amoA genes in marine environments indicates the biological significance of these ammonia oxidizers in marine ecosystems (Bernhard et al. 2007; Nakagawa et al. 2007; Wang et al. 2009; Beman et al. 2012; Zheng et al. 2013). However, the relative contributions of AOA and AOB to aerobic ammonia oxidation in marine environments remain incompletely understood (Prosser and Nicol 2008). qPCR analyses of amoA genes in a number of studies have demonstrated that AOA are usually orders of magnitude more abundant than AOB in marine systems (Wuchter et al. 2006; Mincer et al. 2007; Beman et al. 2008; De Corte et al. 2009). However, increasing evidence indicates that many coastal and estuarine sediments have a relatively higher abundance of AOB amoA genes than AOA amoA genes,

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suggesting a possible shift in competitive dominance of ammonia oxidizers under certain conditions (Caffrey et al. 2007; Mosier and Francis 2008; Santoro et al. 2008; Zheng et al. 2013). Recent studies have suggested that AOA might play an important role within the nitrogen cycle in low-nutrient, low-pH, or sulfide-containing environments, which indicates a niche separation between AOA and AOB (Erguder et al. 2009; Schleper 2010). Despite the number of available studies on AOA and AOB, a complete understanding of the community structures of ammonia oxidizers and their responses to environmental variability is still lacking, especially in extreme environments, such as the deep sea. Several recent studies have been performed to detect AOA and AOB in sediments from different locations in the western Pacific Ocean, including the South China Sea (Cao et al. 2011b, c, 2012), the East China Sea (Dang et al. 2008), the Northeastern Japan Sea (Nakagawa et al. 2007), and the tropical West Pacific Continental Margin (Dang et al. 2009). AOA diversity in the hydrothermal vent samples of the Pacific Ocean has also been investigated (Wang et al. 2009; Nunoura et al. 2010). It has been demonstrated that deep-sea ecosystems in the Pacific Ocean harbor diverse and novel ammonia-oxidizing prokaryotes (Nakagawa et al. 2007; Dang et al. 2009). These studies provide information on AOA and AOB community structures and spatial distributions in the Pacific Ocean. However, as most samples investigated in these studies were collected from depths of less than 3000 m, relatively little is known about AOA/AOB community structures and their relative contributions to ammonia oxidation in the deep-sea floor of the Pacific Ocean at depths greater than 5000 m. The present study therefore aimed to investigate AOA and AOB community compositions and abundances in deep-sea sediments from three different areas of the Pacific Ocean based on amoA gene analysis. The environmental factors affecting the relative abundance of AOA and AOB were also analyzed. Materials and methods Sampling and physicochemical analysis Deep-sea sediment samples were collected from 6 locations (water depths ranging from 5017 to 7068 m)

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in the Pacific Ocean during the DY115-23 cruise of R/V ‘Hai-Yang-Liu-Hao’ from June 2011 to October 2011. Sampling sites were grouped into three different areas according to their geographic locations: Northwestern Pacific Ocean (sites CQ and CW), Mariana Trench (sites JK and JL), and Central Pacific Ocean (sites W and WS) (Fig. 1). Sediment samples were collected using a box corer (40 cm 9 40 cm 9 80 cm). Surface sediment subcore samples down to a depth of 3 cm were collected from the center of the box corer using acrylic tubes 7 cm in diameter, homogenized, and stored in sterile plastic bags for further microbial and physicochemical analysis. All sediment samples were immediately kept at -20 °C after being collected until used for DNA extraction and elemental analysis. Sediment temperature was recorded using a portable electronic thermometer at each site immediately after sediment samples were retrieved on board. The sediment samples were assayed in the laboratory for total C, total N, and C/N ratio using a vario EL III elemental analyzer (Elementar, Germany). Other physicochemical parameters were measured on board using the pore water, which was extracted from the sediments by centrifugation within 1 h after collection and then filtered with a 0.45-lm PES membrane syringe filter (Millipore, Ireland). The pH and salinity

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were determined using a FE 20 pH meter (Mettler Toledo, China) and a S-10 hand-held salinity refractometer meter (Atago, Japan), respectively. Ammonium, nitrate, and nitrite concentrations were measured spectrophotometrically using hypobromite oxidation method, diazo coupling method, and zinc-cadmium reduction method, respectively (GB/T12763.4 1991). Details of the collected samples and their physicochemical parameters are summarized in Table 1. DNA extraction and clone library analysis Genomic DNA was extracted from 0.5 g of sediment (wet weight) using the FastDNAÒ Spin Kit for Soil (MP Biomedicals, USA), according to the manufacturer’s protocol. Triplicate DNA extracts from each sample were pooled and kept at -20 °C until use. Primer sets amoA-1F/2R (amoA-1F 50 -GGGGTTTCT ACTGGTGGT-30 and amoA-2R 50 -CCCCTCKGSAAA GCCTTCTTC-30 , product size: 491 bp) and ArchamoAF/R (Arch-amoAF 50 -STAATGGTCTGGCTTAG ACG-30 and Arch-amoAR 50 GCGGCCATCCATCTGT ATGT-30 , product size: 635 bp) were used for bacterial and archaeal amoA gene amplification, respectively (Rotthauwe et al. 1997; Francis et al. 2005). PCR was performed using the following amplification cycle: 95 °C for 5 min, followed by 35 cycles of 95 °C for 40 s, 55 °C

Fig. 1 Map showing the sampling sites in this study

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38.70 ± 0.19

(for b-AOB) or 53 °C (for AOA) for 60 s, and 72 °C for 60 s, with a final elongation at 72 °C for 7 min. Triplicate PCR products were pooled (to minimize PCR bias), gel purified, and inserted into PGEM-T easy vectors (Progema, USA) for constructing clone libraries. Clones were randomly selected for insert screening by using PCR with primers M13/RV. PCR products of the correct size were subjected to restriction fragment length polymorphism (RFLP) analysis using the combination of two restriction endonucleases Afa I and Msp I (Takara, China). Representative clones with different digestion profiles were selected for sequencing by Majorbio (Shanghai, China) using an ABI 3730XL sequencer (ABI, USA).

0.86 ± 0.11 4.92 ± 0.17

Community structure analysis Nucleotide sequences were initially edited using the DNAstar software package (DNASTAR, USA) to remove redundant sequences and then analyzed using the BLASTn tool (http://www.ncbi.nlm.nih.gov/ BLAST/) to obtain the closest reference sequences. All representative sequences from each clone library were aligned using Clustal W (http://www.clustal.org/). Operational taxonomic units (OTUs) are defined at sequence groups that differ by B5 % using software Mothur (version 1.29.0, USA) (http://www.mothur.org/ wiki/Main_Page) by the furthest neighbor method (Wang et al. 2011). Diversity index analysis, including determination of the nonparametric richness estimator (Chao1 and Shannon) and Simpson diversity index, was performed using Mothur software (version 1.29.0, USA). The coverage of each clone library was calculated as C = [1-(n1/N)] 9 100, where n1 is the number of unique OTUs and N is the total number of clones in the library. The amoA gene sequences in this study and the reference sequences retrieved from GenBank were aligned using the MEGA 5.01 software package, and phylogenetic trees were constructed using the neighborjoining method based on the Jukes–Cantor distance model. The relative confidence of the tree topologies was estimated by performing 1000 bootstrap replicates. ND no data available

Central Pacific Ocean WS

154°000 W/ 10°030 N

34

5062

7.53

3

13.90 ± 0.35

2.82 ± 0.12

0.14 ± 0.02

40.60 ± 2.05 0.57 ± 0.08 5.49 ± 0.31 Central Pacific Ocean W

154°250 W/ 10°000 N

34

5145

7.48

3

15.11 ± 0.30

2.76 ± 0.17

0.08 ± 0.01

ND ND 2.78 ± 0.09 Mariana Trench area JL

142°230 E/ 11°030 N

34

7068

7.50

3

8.39 ± 0.25

2.95 ± 0.09

ND

41.55 ± 1.63 ND 3.07 ± 0.32 Mariana Trench area JK

141°580 E/ 11°000 N

34

6986

7.47

3

8.42 ± 0.22

2.74 ± 0.15

0.07 ± 0.01

41.98 ± 2.05 0.54 ± 0.03 1.34 ± 0.11 3.62 ± 0.18 Northwest Pacific Ocean CW

170°40E/19°500 N

34

5215

7.40

3

10.06 ± 0.25

2.78 ± 0.08

0.22 ± 0.01 0.69 ± 0.06 3.67 ± 0.49 Northwest Pacific Ocean

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CQ

171°200 E/ 19°120 N

34

5017

7.36

3

9.44 ± 0.27

2.60 ± 0.30

NO2(lmol/l) NH4? (lmol/l) C/N ratio Total N (mg/g) Total C (mg/g) T (°C) pH Depth (m) Salinity (%) Sampling area Location Sample name

Table 1 Physicochemical characteristics of the sediment samples used in this study

39.28 ± 2.23

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NO3(lmol/l)

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Quantitative PCR analysis The copy numbers of amoA genes of AOA and AOB were determined in triplicate with primer sets described above using the SYBR green qPCR method.

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Each reaction was performed in a 25 ll volume containing 1 ll of DNA template, 1 ll of each primer (10 lM), and 12.5 ll of 29 SuperReal PreMix (SYBR Green) (TIANGEN, China). The PCR protocol was performed as follows: 95 °C for 10 min followed by 45 cycles of 30 s at 95 °C, 1 min at 55 °C (for b-AOB) or 53 °C (for AOA), and 1 min at 72 °C. Negative controls containing no template DNA were subjected to the same qPCR procedure. The specificity of the qPCR amplification was verified by melting curve analysis and checked with agarose gel electrophoresis. Constructed plasmids carrying the target gene sequences (bacterial and archaeal amoA) were used as the standards. The qPCR amplification efficiencies were 95.6 % for b-AOB and 97.2 % for AOA.

from Mariana Trench (JK and JL) were replaced with the average values of the variables when performing the CCA analysis (Lepsˇ and Sˇmilauer 2003). The weight Jackknife environmental clustering analysis and principal coordinate analysis (PCoA) were conducted using online Unifrac software (http://bmf2. colorado.edu/unifrac/) to evaluate the similarity of communities. Environment cluster trees were projected in MEGA 5.01. Nucleotide sequence accession numbers b-proteobacterial and archaeal amoA gene sequences reported in this study were deposited in GenBank under accession numbers KF177910-KF178001 and KF178040-KF178182, respectively.

Statistical analyses Correlations between amoA gene community compositions, represented by the number of OTUs, and environmental factors were explored by canonical correspondence analysis (CCA) using CANOCO 4.5 software. The raw data were processed by a log transformation before running CCA (Lepsˇ and Sˇmilauer 2003). CCA was chosen to determine the relationships between the AOA and AOB community structures and the environmental factors because the longest gradient in a detrended correspondence analysis was longer than 4.0 (Lepsˇ and Sˇmilauer 2003). The missing physicochemical data in samples

Results AOB and AOA amoA gene diversity and richness A total of 704 bacterial and 801 archaeal amoA clones obtained from 6 sediment samples were subjected to PCR–RFLP analysis (Table 2). Clones were grouped into 25 and 22 distinct RFLP genotypes for AOA and AOB, respectively, which were further subjected to sequencing. Both bacterial and archaeal amoA gene sequences showed high degrees of similarity (91–100 %) to their closest matched GenBank

Table 2 Diversity and richness indices of the amoA gene sequences from the clone libraries Samples

Clone number

No. of RFLP genotypes

No. of unique amoA sequence (99 %)

OTUs (95 %)

Shannon index (H)

Simpson index (D)

Evenness (J)

Chao1 index

Coverage (%)

CQ

237

18

10

9

2.02

0.84

0.88

9

CW

140

23

10

9

2.04

0.85

0.89

9

93.6

JK

107

19

9

8

1.78

0.81

0.82

10

92.5

JL

105

12

8

6

1.32

0.32

0.74

6

94.2

W

110

15

10

9

1.66

0.76

0.72

10

91.8

WS

102

23

9

7

1.81

0.83

0.82

7

93.1

CQ

123

11

10

3

0.64

0.38

0.59

3

97.6

CW

121

21

10

3

0.88

0.55

0.80

3

97.5

JK

124

16

12

2

0.59

0.40

0.85

2

98.1

JL

110

15

11

2

0.68

0.52

0.98

2

98.1

W

110

19

15

2

0.66

0.47

0.95

2

98.1

WS

126

12

7

2

0.50

0.68

0.73

2

98.4

Archaeal 96.2

Bacterial

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sequences. Three and thirteen unique bacterial and archaeal amoA OTUs were respectively identified based on a 5 % gene sequence distance cutoff. The library coverage of amoA OTUs ranged from 91.8 to 96.2 % for AOA and from 97.5 to 98.4 % for AOB, suggesting that most of the extant diversity of ammonia-oxidizing prokaryotes has been revealed. Within each individual clone library, 2–3 AOB and 6–9 AOA amoA OTUs were recovered. Diversity indices (Shannon and Simpson) indicated that the diversity of bacterial amoA gene was lower than that of archaeal amoA gene (Table 2). Two OTUs dominated the AOB community at all sites whereas the AOA communities were more diverse. AOB showed low richness, with six amoA clone libraries comprising 3 distinct OTUs (Fig. S1). Two OTUs, OTU1 and OTU 2, appeared in all six clone libraries and respectively accounted for 52.9 and 45.4 % of the total clones in these libraries. OTU3 was shared by only two clone libraries, CQ and CW. AOA showed high richness, with 13 unique OTUs occurring in 6 amoA clone libraries (Fig. S2). Five OTUs (OTU 2, 4, and 6–8) were common and represented 80.8 % of the total 801 clones recovered in the libraries. Four OTUs (OTU 10–13) appearing only in a single sample were also observed. Bacterial and archaeal amoA gene phylogenetic diversity Phylogenetic analysis showed that all bacterial amoA sequences obtained in this study are related to Nitrosospira-like amoA sequences recovered from several marine habitats, including the South China Sea (Cao et al. 2012), deep-sea hydrothermal environments (GenBank accession number AY785990), and hadopelagic sediments in the Ogasawara Trench (Nunoura et al. 2013) (Fig. 2). Based on the nomenclature by Avrahami and Conrad (2003), Dang et al. (2010a), and Cao et al. (2012), there are three tentatively named clusters (cluster 13, 14, and 15) in the Nitrosospira-like AOB clade. Cluster 13 consists of bacterial amoA sequences from coastal environments (Bernhard et al. 2007; Kim et al. 2008; Dang et al. 2010a; Cao et al. 2012), cluster 14 mainly comprises environmental amoA sequences from deepsea sediments (Hayashi et al. 2007; Dang et al. 2010a; Cao et al. 2012), and cluster 15, also called

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‘‘Nitrosospira-like cluster B’’, is composed of environmental amoA sequences found mainly in estuarine and coastal sediments (Francis et al. 2003; Kim et al. 2008; Dang et al. 2010a; Cao et al. 2012). All bacterial amoA sequences in this study were affiliated with cluster 14. Significance analyses using UniFrac and P tests indicated no significant differences among the bacterial amoA community structures of all samples in the present study (P [ 0.05). In this study, the phylogeny of archaeal amoA genes is much more complex than that of bacteria amoA genes (Fig. 3). All archaeal amoA sequences in this study were related to amoA sequences recovered from other marine environments and phylogenetically divided into 7 clusters. No sequences fell into AOA clades associated with estuarine and terrestrial environments. The archaeal amoA sequences matched GenBank reference sequences retrieved from deep-sea sediments located at the West Pacific Continental Margin (Dang et al. 2009), New Caledonia Basin (Roussel et al. 2009), Okhotsk Sea methane seep (Dang et al. 2010b), the hydrothermal region of East Lau Spreading Center (FJ888619), the Southwest Indian Ridge (JN934405), the East Pacific Ridge hydrothermal field (GU348394), the Lau Basin hydrothermal field (JN662449), the Ogasawara Trench (Nunoura et al. 2013), and the South China Sea (Cao et al. 2011c). Four of the seven clusters (cluster 1, 2, 4, and 6) were present at all sites, accounting for approximately 88.3 % of the total clones. Cluster 3 and 5 contained sequences from four and three samples, which accounted for 5.2 and 4.5 % of the total clones, respectively. Cluster 7 only contained sequences from sample CW and accounted for 2.0 % of the total clones; this cluster showed approximately 95 % sequence identity with the reference sequence retrieved from semi-consolidated carbonate sediments at the Southwest Indian Ridge (JN934405). Significance analyses using UniFrac and P tests showed no significant differences among the archaeal amoA community structures of all samples (P [ 0.05). Both weighted Jackknife environmental clustering and PCoA analyses indicated that for the AOB, the sample CQ was distinct from all other samples (Fig. 4a, b). Furthermore, two samples from the Mariana Trench (JK and JL) were clustered together and separated from other samples for both AOA and AOB (Fig. 4c, d).

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Fig. 2 Neighbor-joining phylogenetic tree showing the affiliation of AOB amoA gene sequences recovered from the deep-sea sediments of the Pacific Ocean in this study. The total number of clones grouped to that OTU was listed after the clone name.

Bootstrap values higher than 50 % of 1000 resamplings are shown at branch points. Scale bar represents 0.05 nucleotide substitutions per site

AOB and AOA amoA gene abundance in deep-sea sediments

AOA/AOB amoA gene abundance ratios range from 0.17 to 162. While AOB were 1–10 times more abundant than AOA in the Central Pacific Ocean area (sites W and WS), AOA were about two orders of magnitude more abundant than AOB in the Northwest Pacific Ocean (sites CQ and CW) and Mariana Trench (sites JK and JL) areas. Comparison of AOB amoA gene abundances in sediments from six locations demonstrated that AOB are significantly more

AOB amoA gene copy numbers ranged from 5.28 9 103 copies/g sediment (wet weight) to 2.29 9 106 copies/g sediment (wet weight), while AOA amoA gene copy numbers ranged from 1.68 9 105 copies/g sediment (wet weight) to 1.89 9 106 copies/g sediment (wet weight) (Fig. 5).

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Antonie van Leeuwenhoek (2015) 108:329–342 b Fig. 3 Neighbor-joining phylogenetic tree showing the affilia-

tion of AOA amoA gene sequences recovered from the deep-sea sediments of the Pacific Ocean in this study. The total number of clones grouped to that OTU was listed after the clone name. Bootstrap values higher than 50 % of 1000 resamplings are shown at branch points. Scale bar represents 0.1 nucleotide substitutions per site

abundant in Central Pacific Ocean sampling areas (sites W and WS) than in Northwest Pacific Ocean (sites CQ and CW) and Mariana Trench (sites JK and JL) sampling areas (one-way ANOVA, P \ 0.05). No significant difference among AOA abundances in different locations was observed (P [ 0.05). amoA gene composition and environmental variables Correlations of AOB and AOA amoA community compositions among sediments from the six locations

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with environmental factors were investigated through canonical correspondence analysis (CCA). The environmental variables in the first two CCA dimensions explained 98.6 % of the total variance in the bacterial amoA genotype composition and 100 % of the cumulative variance of the genotype-environment relationship (Fig. 6a). The results indicated that AOB community structures in the sediments of the Pacific Ocean were significantly correlated with pH (P = 0.034, F = 13.005, 499 Monte Carlo permutations), and this factor alone provided 78.6 % of the total CCA explanatory power. Although the contribution of two other measured environmental factors was not statistically significant (P [ 0.153, 499 Monte Carlo permutations), the combination of these two variables provided additionally 14.3 % of the total CCA explanatory power. Relationship between AOA communities and environmental parameters was also investigated (Fig. 6b).

Fig. 4 Weighted Jackknife environmental clustering and PCoA analyses for AOB (a and b) and AOA (c and d)

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Fig. 5 Relative abundance of the AOB and AOA amoA genes in the deep-sea sediments of the Pacific Ocean. Error bars show the standard deviations of triplicate independent qPCR reactions. Bars with different letters are significantly different at p \ 0.05 (one-way ANOVA)

The first two axes explained 60.7 % of the total variance in the archaeal amoA genotype composition and 67.2 % of the cumulative variance of the archaeal amoA–environment relationship. Only NO2- contributed significantly (P = 0.042, F = 3.810, 499 Monte Carlo permutations) to the archaeal amoA genotype– environment relationship, and this factor alone provided 28 % of the total CCA explanatory power. Although the contributions of three other measured environmental factors were not statistically significant (P [ 0.136, 499 Monte Carlo permutations), the combination of these variables provided additionally 30 % of the total CCA explanatory power. CCA analysis further indicated that environmental factors may influence the abundance of ammonia oxidizers. AOA/AOB amoA copy number ratios were negatively correlated with total C (Fig. 6c).

Discussion Very few studies have focused on ammonia-oxidizing microorganisms in deep-sea sediments, and deep-sea environments remain among the least explored regions of the Earth. The deep-sea is recognized as an extreme environment characterized by the absence of sunlight, predominantly low temperatures, and high hydrostatic pressure (up to 110 MPa). These extreme environmental conditions endow the deep sea with

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great potential to host numerous unique organisms. The current study revealed the presence of bacterial and archaeal amoA genes in deep-sea sediments from the Pacific Ocean. About 8.6 % of the AOA and 3.5 % of the AOB amoA clone sequences in this study did not match any published sequence (\95 %), which indicates that some unique archaea and bacteria capable of ammonia oxidation may exist in deep-sea regions of the Pacific Ocean. The archaeal amoA genes were much more diverse than the AOB amoA genes, which is consistent with previous studies on deep-sea sediments and hydrothermal vent systems (Nakagawa et al. 2007; Cao et al. 2011a; Xu et al. 2014). Both AOA and AOB, however, were of lower OTU richness than that reported in most previous studies (Dang et al. 2008, 2009, 2010a; Cao et al. 2011a, c, 2012), which could be attributed to the unique characteristics inherent among the geographical locations of sampling sites. In this study, the sediment samples were collected from the open ocean with water depths greater than 5000 m; these depths are much greater than those reported in previous studies on the estuarine and coastal environments of the Pacific Ocean. Phylogenetic analysis indicated that all AOB amoA gene sequences discovered in the present study were closely related to uncultured b-proteobacterial AOB recovered from other Pacific Ocean environments (Cao et al. 2012; Nunoura et al. 2013). All AOB amoA sequences were grouped in the Nitrosospira-like clade, and no sequences were affiliated with the Nitrosomonas-like clade (Fig. 2). Nitrosospira and Nitrosomonas have been demonstrated to prefer different habitats; Nitrosospira favors clean water with low ammonia levels, whereas Nitrosomonas is commonly observed in polluted environments with high ammonia levels, such as in wastewaters, activated sludge, biofilm reactors, and biofilters (Zhang et al. 2011; Cao et al. 2012; Wang and Gu 2012). Nitrosospira has also been reported to prefer highsalinity environments, whereas Nitrosomonas is dominant in low-salinity environments (Dang et al. 2010a; Jin et al. 2011). Generally, AOB communities were found to vary along the salinity gradient in estuaries, with communities at the freshwater end composed of both Nitrosomonas and Nitrosospira-like sequences, while communities at the marine end tend to be dominated by Nitrosospira-like sequences (Bernhard and Bollmann 2010). Cao et al. (2012) also reported that the dominant genus of AOB changed

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Fig. 6 CCA ordination plots for the relationship between the AOB (a) and AOA (b) community compositions with the environmental parameters in the deep-sea sediments of the Pacific Ocean. (c) CCA ordination plots for the relationship between environment parameters and qPCR-estimated amoA gene abundance. Correlations between environmental variables and CCA axes are represented by the length and angle of arrows (environmental factors)

from Nitrosomonas to Nitrosospira along the gradient from coastal to the open sea, suggesting that the ecological niches of these two genera are influenced by both salinity and anthropogenic influence. Nitrosomonas was reported to be the dominant AOB in mangroves and marshes (Cao et al. 2011b, 2012; Li et al. 2011), whereas Nitrosospira was recognized as

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the major AOB in deep-sea environments (Hayashi et al. 2007; Nakagawa et al. 2007; Cao et al. 2012; Xu et al. 2014). Our results were in agreement with these reports and suggested that Nitrosospira are better adapted to the deep-sea sedimentary environments than Nitrosomonas. Of the three newly defined clusters of the Nitrosospira clade (Avrahami and Conrad 2003; Dang et al. 2010a; Cao et al. 2012), all AOB amoA sequences in the present study were affiliated with cluster 14 (Fig. 2), which is consistent with previous findings implying Cluster 14 to be the dominant AOB in deep-sea sedimentary environments (Hayashi et al. 2007; Dang et al. 2010a; Cao et al. 2012). In addition, the present results showed that all archaeal amoA gene sequences were grouped into the marine sediment clade, consisting of sequences from other deep-sea sedimentary environments, such as the West Pacific Continental Margin, New Caledonia Basin, Okhotsk Sea methane seep, and the South China Sea (Dang et al. 2009, 2010b; Roussel et al. 2009; Cao et al. 2011c; Nunoura et al. 2013). None of the archaeal amoA sequences fell into AOA clades associated with estuarine and terrestrial environments, indicating that the samples in the present study were not affected by terrestrial influence. These findings further suggest the presence of deep-sea adapted phylotypes. Although most of previous studies have reported that AOA are far more abundant than AOB in marine environments (Wuchter et al. 2006; Mincer et al. 2007; Park et al. 2008; Cao et al. 2011a, b; Jin et al. 2011), there are also reports of AOB outnumbering AOA (Mosier and Francis 2008; Zheng et al. 2013; Xu et al. 2014). Environmental factors affecting the relative abundance of AOA and AOB are still not well understood. In this study, the amoA gene abundance was not largely different among AOA but highly varied among AOB within the samples from different sites. AOB are significantly more abundant in samples from the Central Pacific Ocean area (sites W and WS) than in those from the Northwest Pacific Ocean (sites CQ and CW) and Mariana Trench (sites JK and JL) areas. AOB are about one order of magnitude more abundant than AOA in samples W and WS but about two orders of magnitude less abundant in samples CQ, CW, JK, and JL (Fig. 5). Elemental analysis showed that the samples W and WS had higher levels of total C and C/N ratios than the other samples (Table 1). CCA analysis demonstrated that AOA/AOB amoA gene

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abundance ratios were correlated negatively with total C (Fig. 6c), indicating that the higher-total C sites (W and WS) had a higher bacterial amoA gene abundance than the lower-total C sites. Organic loading has been suggested to be an important factor regulating the distribution and abundance of ammonia oxidizers in marine systems (Bernhard and Bollmann 2010). Urakawa et al. (2006) reported that nutrients and organic inputs from the river run-off and phytoplankton bloom created the gradient of spatial distribution and abundance of AOB in estuarine sediments. Lagostina et al. (2015) reported that the relative abundance of archaeal and bacterial amoA decreased from the oligotrophic sediments to eutrophic sediments. Zheng et al. (2013) reported similar findings with the present study that bacterial amoA gene abundance in intertidal sediments was correlated positively with total organic carbon, while no significant correlations were found between archaeal amoA gene abundance and environment factors. Similar trends were also observed in soils. Leininger et al. (2006) reported that AOB amoA gene copy numbers significantly increased with the increased amount of carbon and nitrogen in the agricultural soils, whereas AOA amoA gene copies did not change significantly. Adair and Schwartz (2008) reported a significant positive relationship between AOB amoA gene abundance and soil C/N ratio, but there was no correlation between the AOA population sizes and soil C/N ratio. These observations and our findings suggested that the carbon content and C/N ratio may play important roles in the selection of the dominant ammonia-oxidizer phylotypes in the environment. Archaea have mostly been known to out-compete bacteria in conditions of chronic energy stress, including environmental stresses and low energy availability (Valentine 2007; Hoehler and Jørgensen 2013). Archaea have developed some special biochemical mechanisms to thrive in energy stress, including low-permeability membranes and specific catabolic pathways, while bacteria focus more on exploiting new or variable energy resources (Valentine 2007). Therefore, AOB may gain a competitive advantage over AOA in ecological niches with high carbon intensity of energy supply. In summary, the AOA and AOB diversity and abundance in deep-sea Pacific Ocean sediments were investigated through amoA gene analysis. The AOA amoA gene showed higher diversity than the AOB

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amoA gene. Phylogenetic analysis illustrated the presence of deep-sea adapted phylotypes of AOA and AOB. The AOA amoA gene abundances were similar among different sites, while higher AOB amoA gene abundances were found at two of the six sites. Total C and C/N ratio were suggested to be major factors affecting relative abundance of AOA and AOB. The information obtained collectively provides important clues for understanding the ammoniaoxidizing microbial communities in the deep-sea environment of the Pacific Ocean. Acknowledgments The work was financially supported by the China Ocean Mineral Resources R&D Association (COMRA) Program (DY125-15-R-01) and the National Key Basic Research Program of China (‘‘973’’-Program, 2015CB755903).

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