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Bacterial Community on a Guyot in the Northwest Pacific
Ocean Influenced by Physical Dynamics and
Environmental Variables
Qian Liu
1,5
, Ying‐Yi Huo
1,2
, Yue‐Hong Wu
1
, Youcheng Bai
1
, Yeping Yuan
3
, Min Chen
4
,
Dongfeng Xu
5
, Jun Wang
5
, Chun‐Sheng Wang
1,5
, and Xue‐Wei Xu
1,5
1
Key Laboratory of Marine Ecosystem and Biogeochemistry, State Oceanic Administration & Second Institute of
Oceanography, Ministry of Natural Resources, Hangzhou, China,
2
Now at College of Life Sciences, Zhejiang University,
Hangzhou, China,
3
Ocean College, Zhejiang University, Hangzhou, China,
4
College of Ocean and Earth Sciences, Xiamen
University, Xiamen, China,
5
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of
Oceanography, Ministry of Natural Resources, Hangzhou, China
Abstract Bacterial communities in sediments of the Caiwei Seamount, a typical guyot located in the
northwest Pacific Ocean, were investigated. A total of 727,879 16S ribosomal RNA gene sequences were
retrieved from eight sediment samples of the top (mean depth = 1,407 m) and the base (mean depth = 5,525 m)
of the guyot through pyrosequencing of V6 hypervariable region and clustered into 32,844 operational
taxonomic units. Abundant‐weighted UniFrac metric partitioned bacterial assemblies into two categories
(the top community and the base community) by principal coordinates analysis, consisting with the
grouping of sampling stations by environmental variables. Differences in depth and physicochemical
properties of the surrounding environment (e.g., concentrations of dissolved oxygen and geochemical
elements) between the top and the base of the guyot may cause this partition of bacterial communities,
whereas the typical fluid flow around the guyot may potentially contribute to the bacterial dispersal and
environmental homogeneity along the same layer, resulting in the similarity of bacterial community
structure within the same region (the top or the base). The surface sediment on the top of the guyot
harbored the bacterial communities with greater diversity and evenness, represented by Gamma‐and
Deltaproteobacteria involved in sulfur cycling. At the base of the guyot, Gammaproteobacteria related to
sulfur‐oxidizing and Chloroflexi functioning in the decomposition of refractory organic matter dominated,
suggesting that the redox condition at the interface of the sediment and the water can influence
bacteria‐mediated elemental cycling, eventually shaping the physicochemical and geological characteristics
of a guyot.
Plain Language Summary Seamounts in northwest Pacific Ocean are most abundant in the
world. They have been recognized as important habitats for corals, fish, and etc. The high biodiversity in
seamount regions could be a result of efficient food and energy transfer mediated by microorganisms. In this
study, we investigated bacterial community composition, structure, and potential metabolic characteristics
at different locations of the Caiwei Seamount, a flat‐topped seamount (also called as guyot) in northwest
Pacific Ocean in order to understand the functions of the seamount ecosystem. Our results showed that the
bacterial zonation in the Caiwei Seamount was influenced by both physicochemical variables and physical
dynamics. Unique circulation of flow currents in seamount region may enhance the homogeneity of
bacterial community at the same depth, while physicochemical variation by depth could be the major factor
partitioning bacterial community vertically. The potential ecological functions of bacterial communities are
strongly associated with the regional environments. They are actively involved in sulfur and nitrogen
cycling, possibly key to energy and substrate productivity.
1. Introduction
Microbial abundance in subseafloor sediment has been estimated to be 2.9×10
29
, accounting to total prokar-
yotic cell abundance in the water column and in soil (Kallmeyer et al., 2012). They play an important role in
deep‐ocean biogeochemical processes and potentially contribute to high productivity in the deep ocean
(McNichol et al., 2018). Microorganisms have been extensively studied in different environments of
©2019. The Authors.
This is an open access article under the
terms of the Creative Commons
Attribution License, which permits use,
distribution and reproduction in any
medium, provided the original work is
properly cited.
RESEARCH ARTICLE
10.1029/2019JG005066
Key Points:
•Bacterial community on the guyot is
well partitioned by depth and
physicochemical properties
•Uniqueness of physical dynamics
may contribute to the homogeneity
of bacterial community along the
isobath of the guyot
•Redox conditions on the guyot are
potentially key to determining
bacterial community composition,
structure, and ecological function
Supporting Information:
•Supporting Information S1
Correspondence to:
X.‐W. Xu,
xuxw@sio.org.cn
Received 31 JAN 2019
Accepted 6 JUN 2019
Accepted article online 14 AUG 2019
Author Contributions:
Conceptualization: Qian Liu, Ying‐Yi
Huo, Yue‐Hong Wu
Data curation: Qian Liu
Formal analysis: Qian Liu, Ying‐Yi
Huo, Youcheng Bai, Yeping Yuan, Min
Chen, Dongfeng Xu, Jun Wang
Funding acquisition: Chun‐Sheng
Wang
Investigation: Ying‐Yi Huo
Methodology: Qian Liu, Ying‐Yi Huo,
Yue‐Hong Wu, Youcheng Bai, Min
Chen
Project administration: Chun‐Sheng
Wang
Resources: Ying‐Yi Huo
Software: Qian Liu, Ying‐Yi Huo
(continued)
LIU ET AL. 2883
Citation:
Liu, Q., Huo, Y.‐Y., Wu, Y.‐H., Bai, Y.,
Yuan, Y., Chen, M., et al. (2019).
Bacterial community on a guyot in the
northwest Pacific Ocean influenced by
physical dynamics and environmental
variables. Journal of Geophysical
Research: Biogeosciences,124,
2883–2897. https://doi.org/10.1029/
2019JG005066
Published online 11 SEP 2019
marine subseafloor, especially in extreme environments (e.g., hydrothermal vent and cold seep), where they
are active and diverse in physiology and metabolism, contributing significantly to energy flow in deep ocean
(Fullerton et al., 2017; Huber et al., 2007; López‐García et al., 2003; Meyers et al., 2014; Moyer et al., 1995;
Scott et al., 2017; Sogin et al., 2006; Teske et al., 2002).
Seamounts are the unique environment widely distributed in deep‐ocean subseafloor (Wessel & Kroenke,
1997). They are the important habitats for marine organisms (Clark et al., 2010). The topographic‐
induced turbulent mixing at seamounts may potentially cause high primary productivity in the upper
water column (Boehlert & Genin, 1987; Polzin et al., 1997), benefiting the fish and benthic communities
in seamount areas (Clark et al., 2010; Richer de Forges et al., 2000). Most of seamounts discovered in the
world are located in the west Pacific (Kim & Wessel, 2011). Flat‐topped seamounts, also called as guyots,
are the major types in the west Pacific. The flat top is a result of coral reef growth and erosion as their
conical tops reached the sea surface during evolutionary processes (Stanley, 2005). Thus, the top of a
guyot is covered by carbonate rock with shallow‐water coral and bivalve reefs formed millions of years
ago. At the base of a guyot, it is majorly composed of manganese crust or iron‐manganese (Fe‐Mn) coat-
ing precipitating from cold water (Asavin et al., 2008). The varied compositions of sediments at different
regions of a guyot provide diverse biological habitats, indicating potential importance of guyots to the
deep‐sea ecosystem. Currently, there are a few studies on microbial communities in guyot environments,
which mostly focus on the communities associated with ferromanganese crust and potentially function-
ing in metal precipitation (Kato et al., 2018; Nitahara et al., 2011, 2017); however, the patterns of micro-
bial distribution and their relationship with guyot environment on guyots are less understood.
The Caiwei Seamount is a deep‐sea guyot located in the northeast of the eastern Marianas Basin of the
west Pacific Ocean at a latitude and longitude of 15.0–16.2°N and 154.6–155.8°E (Figure 1). The depth
of the top is between 1,500 and 1,600 m and that of the base is approximately 5,500 m. The Caiwei
Seamount is covered by cobalt‐rich crusts, the density of which increases with depth. Other mineral
resources, such as nickel, copper, iron, and manganese are also rich on the seamount (Wang et al.,
2016). The Caiwei Seamount has been extensively surveyed by the China Ocean Mineral Resources
R&D Association (COMRA) for mineral resources and megafaunal community (Wang et al., 2016; Xu
et al., 2016); however, the microorganisms that are potentially important in food web and energy transfer
in seamount ecosystem have not been investigated yet. In this study, bacterial community structure in
sediment samples of the Caiwei Seamount were studied for enhancing our understanding in (1) diversity
and genetic fingerprinting of guyot bacterial community, (2) interaction between bacterial community
structure and guyot environments, and (3) potential roles of bacteria in biogeochemical processes of
the Caiwei Seamount that could be extremely important in food and energy transfer, shaping the ecolo-
gical function of the guyot ecosystem.
2. Materials and Methods
2.1. Sample Collection and environmental Variables
Sediment samples were collected from the Caiwei Seamount located in the west Pacific Seamount Province
during the DY27 cruise of the R/V Haiyang Liu Hao in July, 2012. Using multiple corer (surface area =
0.00785 m
2
, height = 0.6 m) as well as box corer (surface area = 0.25 m
2
) systems, four sediment samples
were obtained at the flat top of the seamount (1,362–1,500 m in depth; MAMC01, MAMC02, MAMC03,
and MAMC04) and four were collected at the base of the seamount (5,269–5,920 m in depth; MABC02,
MAMC06, MABC06, and MAMC08; Figure 1 and Table S1). Box corer samples were immediately sub-
sampled using push corers. The top 5 cm of sediment were collected in all sediment cores and stored at
−20°C until analysis in the laboratory for subsequently microbiological and geochemical experiments.
Seawaters were also collected from the surface to the depths close to the seafloor near stations MAMC02
and MAMC04 at the top of the seamount (MACTD01 and MACTD04) and stations MABC02, MABC06
and MAMC08 at the base of the seamount (MACTD07, MACTD08, and MACTD06) using 8 L Niskin bottles
mounted on a rosette frame equipped with a SBE917 CTD system (Sea‐Bird Electronics, Inc.; Figure 1 and
Table S1).
Concentrations of dissolved oxygen (DO) in seawaters were measured following the Winkler method
(Winkler, 1888). For nutrient measurements, seawater samples were collected into 500‐ml high‐density
10.1029/2019JG005066
Journal of Geophysical Research: Biogeosciences
LIU ET AL.
Supervision: Yue‐Hong Wu, Chun‐
Sheng Wang
Validation: Qian Liu
Visualization: Qian Liu, Yeping Yuan
Writing ‐original draft: Qian Liu,
Ying‐Yi Huo, Yeping Yuan
Writing –review & editing: Qian Liu,
Ying‐Yi Huo, Yue‐Hong Wu, Yeping
Yuan, Min Chen, Dongfeng Xu, Chun‐
Sheng Wang
2884
polyethylene bottles and filtered onto cellulose acetate filters (47‐mm diameter and 0.45‐μm pore size).
Concentrations of ammonia, nitrite, and phosphate were determined using a standard colorimetric
method (Grasshoff et al., 1999), and nitrate concentrations were measured using a cadmium‐reduction
method coupled with diazotization (Grasshoff et al., 1999). Elemental analysis of sedimentary
concentrations of total organic carbon (TOC) and nitrogen (TON) were performed using an Elementar
Vario Micro Cube (Elementar, Germany). Elemental contents of P, S, Si, B, Ca, Na, Al, Fe, K, Mg, Zn, Cu,
Mn, Ba, Ni, Cr, Co, Li, Sr, V, and Pb were determined using inductively coupled plasma optical emission
spectrometer (ICP‐OES, Optima 8000DV, PerkinElmer, USA).
2.2. DNA Extraction, Polymerase Chain Reaction Amplification, and Sequencing
DNA was extracted from the sediment samples (0.5 g of each sample) using the FastDNA® Spin kit for soil
(MP Biomedicals, USA). The environmental DNA was then used as polymerase chain reaction (PCR) tem-
plate, and bacterial 16S rRNA genes were amplified using primers 967F (5′‐CAACGCGAAGAACCTTACC‐
3′) and 1046R (5′‐CGACAGCCATGCANCACCT‐3′) targeting at the V6 hypervariable region (Sogin et al.,
2006). PCR amplification was performed in 50‐μl reaction volume containing 5 μl of 10 × reaction buffer,
1.5 μl of 10 mM dNTP, 1 μlof10μM each primer, 2 μl of template, and 1 μlof5U/μlPfx50
TM
DNA polymer-
ase (Invitrogen, USA), supplemented with double‐distilled water. Thirty cycles of amplification were carried
Figure 1. (a) Location of the Caiwei Seamount in the northwest Pacific Ocean; (b) sampling stations at the top and the
base of the Caiwei Seamount: water samples were collected at stations MACTD1 and MACTD4 on the top and
MACTD6, MACTD7, and MACTD8 on the base; sediment samples were collected at stations MAMC01, MAMC02,
MAMC03, and MAMC04 on the top and MAMC06, MABC06, MABC02, and MAMC08 on the base.
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Journal of Geophysical Research: Biogeosciences
LIU ET AL. 2885
out under the following conditions: denaturation at 94°C for 15 s, annealing at 57°C for 30 s, and elongation
at 68°C for 30 s. The quality and quantity of the genomic DNA were determined by 2% agarose gel
electrophoresis with DL2000 DNA marker (TaKaRa, China) and by a Qubit® fluorometer (Invitrogen,
USA) with Qubit dsDNA BR Assay kit (Invitrogen, USA). The barcoding, sequencing, and quality assurance
processes of PCR products were performed at the Beijing Genome Institute (BGI, Shenzhen). The sequen-
cing was performed using Solexa paired‐end sequencing technology (HiSeq2000 system, Illumina, USA).
The sequencing data have been deposited at NCBI Sequence Read Archive under accession
number SRR7888608‐SRR7888615.
2.3. Sequence and Statistical Analysis
Sequences analysis was performed by QIIME v1.8.0 software package (Caporaso, Kuczynski, et al., 2010).
Sequences were clustered into operational taxonomic units (OTUs) at 97% sequence identity with uclust
Figure 2. Concentrations of geochemical elements measured in sediment samples collected from the top and the base of
the Caiwei Seamount. The differences in concentration between the top and the base are all significant (p‐values≪0.05; t
test). The error bar represents standard deviation.
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LIU ET AL. 2886
v1.2.22q (Edgar, 2010). OTUs were aligned to full‐length 16S rDNA sequences with PyNAST (Caporaso,
Bittinger, et al., 2010) and assigned taxonomy with uclust (Edgar, 2010). Species diversity, richness, and rar-
efaction curves were conducted with a step size of 500 and 10 repetitions at each step. Beta diversity was ana-
lyzed with 90,330 sequences per sample, which is the smallest library.
The weighted UniFrac metric was computed to quantify the relatedness of OTUs retrieved from the top and
the base of the seamount, and the results were displayed by the principal coordinate analysis (Lozupone
et al., 2006). The similarity percentage (SIMPER, Primer 6) analysis was used to determine the sequences
that mostly contributed to community dissimilarity between top and base samples of the seamount
(Hamdan et al., 2013). Individual ttest run in R (R Development Core Team, 2011) was used to test the sta-
tistical significance of spatial differences in geochemical measurements and bacterial abundances between
top and base samples of the seamount. Principal component analysis (PCA) and redundancy analysis
(RDA) were applied to detect the similarity of environmental conditions among stations and correlations
between bacterial distribution and environmental variables, respectively (Canoco 5.1; Ter Braak &
Šmilauer, 2012).
3. Results
3.1. Physical and Geochemical Characteristics in Seawaters and Sediments
The hydrochemical characteristics in surrounding seawaters of the top and the base of the seamount were
similar (i.e., salinity, pH, and concentrations of ammonia, nitrite, nitrate, and phosphate) except tempera-
ture and DO (Table S2). Temperature was higher in seawater overlying the top of the seamount, while
DO concentrations were in an opposite trend (Table S2). Concentrations of the major geochemical elements
were in a similar range in samples collected from the same region (top or base of the Caiwei Seamount), but
significantly different between samples collected from two regions (ttest, p< 0.01; Figure 2). The sediments
from the base contained higher concentrations of metal elements (i.e., Fe, Mn, Al, and Mg) but lower in Si,
Sr, and Ca (Figure 2). TIC and TIN were the major components of TC (99.80 ± 0.38%) and TN (95.40 ± 1.77%)
in sediments at the top, respectively, while TOC and TON occupied greater proportions of TC (75.40 ±
3.69%) and TN (92.30 ± 5.92%) at the base, respectively. Samples were well explained by variations in phy-
sicochemical parameters of the sediment (Figure 3a) as well as the seawater listed in Table S2 (Figure 3b) by
PCA analysis.
3.2. Bacterial Diversity
A total of 727,879 sequences were retrieved from eight samples and clustered into 32,844 OTUs (0.03 cut-
off). The number of sequences of each station (90,985 ± 629) was similar, but that of OTUs ranged from
6,000 to 10,859 (Table 1). According to rarefaction analysis and Chao 1 statistic often used to estimate the
depth of coverage by sequencing, bacteria communities were under sequenced by 41–64% in samples
(Figure 4 and Table 1). The Chao 1 indices were not statistically different between top and base stations
(ttest, p= 0.71), but two top stations MAMC02 and MAMC03 as well as one base station MAMC06,
located at the northern and eastern sides of the seamount, had relatively higher Chao 1 indices in
comparison to those in sedimentary samples collected from the southern part of the seamount
(MAMC01 and MABC02; Table 1). It indicated that the northern part of the seamount potentially har-
bored more OTUs than the south. Shannon and Simpson indices were averagely greater in samples from
the top of the seamount (ttest, p< 0.01; Table 1), suggesting higher bacterial diversity and evenness in
sediments from the top of the seamount.
3.3. Phylogenetic Composition
Of total obtained bacterial sequences, Proteobacteria dominated the bacterial communities in all sediment
samples (top: 57.4 ± 1.1%, base: 54.3 ± 2.7%) followed by Acidobacteria (top: 11.5 ± 0.6%, base: 7.7 ± 0.4%)
and Gemmatimonadetes (top: 7.2 ± 0.5%, base: 9.4 ± 0.4%) in top and base sediments, respectively. The phy-
lum Chloroflexi also occupied a greater proportion in base sediments (9.1 ± 1.7%) than in the top (2.9 ± 0.4%;
ttest, p= 0.001; Figure 5 and Table 2). The rest of phylotypes were scattering over a broad taxonomic distri-
bution including Planctomycetes,Nitrospirae,Actinobacteria, the division NC10, and Bacteroidetes (>1% at
least at one location). All these dominating bacterial groups occupied approximately 96.7% and 94.8% of total
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LIU ET AL. 2887
retrieved bacterial sequences from the top and base sediments, respectively (Figure 5). Other phyla, which
are more than 0.1% but less than 1% of total retrieved bacterial sequences, are listed in Table S3.
Gammaproteobacteria were the dominant taxa within the phylum of Proteobacteria in all samples (top: 26.0
± 1.2%, base: 28.9 ± 1.5%; ttest, p= 0.04) and were mostly represented by the order Thiotrichales constituting
11.3 ± 0.5% and 19.2 ± 1.2% of total sequences in top and base sediments, respectively (ttest, p< 0.001;
Table 2). More than 98% of the sequences of Thiotrichales were classified into the Piscirickettsiaceae family,
which includes several genera of S‐oxidizing chemolithoautotrophs (Barco et al., 2017; Zhang et al., 2017).
The order Chromatiales, also called the purple sulfur bacteria capable of photosynthesis using sulfide, thio-
sulfate, H
2
,orNO
2
‐
, etc. as the electron donor under anaerobic or microaerophilic conditions (Hunter et al.,
2009), was the secondly most abundant group of Gammaproteobacteria and represented 6.5 ± 0.8% and 3.1 ±
0.3% of the retrieved sequences at the top and the base, respectively (ttest, p< 0.001; Table 2).
Deltaproteobacteria,Alphaproteobacteria, and Betaproteobacteria in the phylum Proteobacteria were also
relatively abundant (>1% of total sequences), but only Deltaproteobacteria showed a greater proportion on
the top (16.44 ± 1.10%; ttest, p< 0.001) and were mostly related to the candidate division NB1‐j and the
order Syntrophobacterales (Table 2). Deltaproteobacteria are usually related to sulfate reduction in anoxic
environments (López‐García et al., 2003; Ye et al., 2016). The order Rhodospirillales, almost 100% composed
of the family Rhodospirillacea, occurred abundantly at both locations, amounting to more than half abun-
dance of Alphaproteobacteria (Table 2). Rhodospirillacea has also been reported to function as a sulfur‐
oxidizer (Zhang et al., 2017). The proportion of Betaproteobacteria was relatively minor compared to
Gammabacteria, Deltabacteria, and Alphaproteobacteria, of which the order Burkholderiales were the major
members in sediments from top stations (>1%; Table 2). Although numbers of Nitrosomonadales in the class
Betaproteobacteria were in a small proportion (<1%), the family Nitrosomonadaceae recognized as major
ammonia oxidizers was found to be one of important identified family members at the base (Purkhold
et al., 2003; 0.99 ± 0.07%; ttest, p< 0.001). The nitrite‐oxidizing Nitrospiraceae in the order Nitrospirales
represented almost all generated Nitrospira sequences and became a major group in sediments from the
top (1.67 ± 0.23%; ttest, p< 0.001). With the cutoff of 0.1, only 2.6% and 2.3% of total sequences on average
were grouped to known genera on the top and the base, respectively.
Figure 3. Principal component analysis for samples collected from sediments (a) and seawaters (b) with geochemical data
shown in Figure 2 and listed in Table S2, respectively.
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Journal of Geophysical Research: Biogeosciences
LIU ET AL. 2888
3.4. Bacterial Community Structure
The abundance‐weighted UniFrac analysis using the principal coordinate analysis separated samples into
two distinct communities with the bacterial groups from the same region (top or base) clustering together
on the axis of PC1 (76.7%; Figure 6). Proportions of OTUs shared by top and base stations (26.6 ± 4.4%) of
the seamount were lower than those of unique OTUs they owned, while samples collected at the same region
tent to share more OTUs (top 45.6 ± 8.1%, base 40.3 ± 3.7%; Table 3). Permutational multivariate analysis of
variance analysis showed that bacterial community composition was significantly different between top and
base regions at OTU level (p= 0.036, r
2
= 0.739)
SIMPER analysis revealed that major bacterial groups (% of total reads > 1%) had different contributions to
the dissimilarity of the bacterial community structure between top and base stations if considering their
abundances and compositions (Table S4). Three OTUs belonging to the family Piscirickettsiaceae of the order
Thiotrichales (denovo28753, denovo16605, and denovo4356) and one OTU classified into the order
Chromatiales of Gammaproteobacteria (denovo16603) contributed to a total of 11.4% of the dissimilarity,
in which the formers had greater abundances in samples from the base while the latter had a higher number
of sequences in samples from the top sediments (Table S4). Two OTUs belong to the family Rhodospirillaceae
in the order Rhodospirillales of Alphaproteobacteria (denovo20286 and denovo17655), one OTU identified to
the family Syntrophobacteraceae in the order Syntrophobacterales of Deltaproteobacteria (denovo12887), and
two OTUs from Acidobacteria (denovo2989 and denovo6417) added the total contribution up to ~20% of the
dissimilarity subsequently (Table S4).
3.5. Correlations Between Bacterial Community and Environmental Variables
The RDA analysis showed that the bacterial groups were well divided into two clusters (top and base) by
environmental factors on the axis of RDA 1, which explained 79.2% of variations. The axis of RDA 2 increased
the explained variation to 90.7% (Figure 7). BPC015 and Sva0725 in Acidobacteria, CL500‐15 in
Planctomycetes,Chromatiales in Gammaproteobacteria,Syntrophobacterales and NB1‐jin
Deltaproteobacteria, and Nitrospirales in Nitrospirae were intensely associated with TIC (%) and concentra-
tions of Ca and Si (mg/g). Similarly, the bacterial groups with higher weights at the base of the seamount,
including Thiotrichales in Gammaproteobacteria, Sva0853 in Deltaproteobacteria,Rhodobacterales in
Alphaproteobacteria, B110 in Acidobacteria, CCM11a in Planctomycetes,Acidimicrobiales in Actinobacteria,
and SAR202 in Chloroflexi, were clustered with depth and the environmental factors that were greater at
the base (e.g., TOC, TON, Fe, Mn, S, and P; Figure 7). Other metal or ions (e.g., Cu, Zn, Mg, and Na) were
strongly correlated with the selected factors, thus were not included in the analysis. Variabilities in
Pseudomonadales in Gammaproteobacteria,Burkholderiales in Betaproteobacteria, and Rhodospirillales in
Alphaproteobacteria among stations were not significantly explained by environmental variables, the propor-
tions of which were consistent in samples collected from the top and the base of the seamount.
Table 1
The Total Number of Bacterial Sequences and OTUs as Well as Indices of Biodiversity and Richness at Each Station
Sampling Station No. of Sequences No. of OTUs Chao 1 Shannon Index (H′) Simpson Index
Top
MAMC01 90,330 6,168 10,410 9.170 0.992
MAMC02 90,439 10,859 27,211 9.828 0.993
MAMC03 90,583 9,222 23,355 9.386 0.991
MAMC04 91,129 7,499 16,014 9.186 0.991
Mean ± SD 90,620 ± 307 8,437 ± 1,769 19,248 ± 6,497 9.393 ± 0.265 0.992 ± 0.001
Base
MABC02 91,649 6,000 12,464 8.202 0.982
MAMC06 90,660 7,999 22,274 8.542 0.986
MABC06 92,279 6,688 16,417 8.126 0.982
MAMC08 90,810 7,345 19,208 8.344 0.984
Mean ± SD 91,350 ± 656 7,008 ± 744 17,591 ± 3,613 8.304 ± 0.158 0.984 ± 0.002
p‐value 0.132 0.245 0.713 0.001 <0.001
Note. The p‐values were calculated by ttest.
Abbreviation: SD, standard deviation.
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4. Discussions
4.1. Factors Influencing Patterns of Bacterial Community Composition and Structure
Increasing studies have shown that microbial community composition and structure can be relatively con-
sistent in similar marine environments even though the distance was thousands of kilometers away or het-
erogeneous in environments with different characteristics but only in a few tens of kilometers (Agogué et al.,
2011; Hewson et al., 2007; Inagaki et al., 2006; Walsh et al., 2015). In this study, PCA analysis showed that
sampling stations were highly divided into two categories (top and base) by environmental variables col-
lected from surrounding waters and sediments (Figure 3), indicating environmental homogeneity at the
top or the base but great varieties between two regions. Consistently, bacterial community structure showed
similar pattern (Figures 5 and 6), supporting a tight association between bacterial community and
environmental variation.
Besides the effect of physiochemical characteristics, patterns of bacterial community composition and struc-
ture in sediments could also be influenced by fast bacteria dispersal near seafloor, which transit through
Figure 4. Rarefaction analyses of observed operational taxonomic units in sediments collected from the top (MAMC01–
MAMC04) and the base (MABC02, MAMC06, MABC06, and MAMC08).
Figure 5. Bacterial community composition identified with uclust (Edgar, 2010) in samples collected from the top and the
base of the Caiwei Seamount.
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water along the route of the fluid flow, contributing to the similarity of bacterial community composition
and structure within the same region (Hamdan et al., 2013; Schauer et al., 2010). In an idealized model,
the incoming flow over the seamount is separated, creating a circulation around the seamount and forming
eddies or wakes at the lee side in a stratified ocean (Chapman & Haidvogel, 1992). The dynamics is even
more complex when the incoming flow is oscillating (i.e., tidal current). The interaction between internal
wave and bathymetry will potentially cause the reflection of internal waves or the generation of the internal
tide (Gilbert & Garrett, 1989), companied by strong turbulent mixing. Measurements of turbulent kinetic
energy near a shallow seamount show 100 to 10,000 times larger than regions far away from seamount areas
(Lueck & Mudge, 1997). Nevertheless, majority of the flow near seamounts tends to follow the isobath
despite of localized enhanced turbulent mixing regions. At the region of the Caiwei Seamount, the
Table 2
Proportions of Phylogenetic Groups in Sediment Samples Collected From the Top and the Base of the Caiwei Seamount
Taxonomy Top Mean ± SD Base Mean ± SD p‐value
Gammaproteobacteria 26.0 ± 1.18 28.9 ± 1.48 0.041
Thiotrichales 11.3 ± 0.50 19.2 ± 1.23 0.000
Chromatiales 6.52 ± 0.81 3.07 ± 0.27 0.000
Pseudomonadales 1.28 ± 0.98 1.00 ± 0.47 0.676
Deltaproteobacteria 16.4 ± 1.06 10.4 ± 0.96 0.000
NB1‐j7.64 ± 0.45 3.89 ± 0.10 0.000
Syntrophobacterales 6.33 ± 1.09 3.13 ± 0.73 0.005
Sva0853 0.47 ± 0.07 1.50 ± 0.21 0.000
Alphaproteobacteria 12.4 ± 1.70 13.7 ± 2.6 0.493
Rhodospirillales 6.24 ± 1.62 8.28 ± 2.25 0.250
Rhodobacterales 0.85 ± 0.08 1.46 ± 0.36 0.028
Betaproteobacteria 2.14 ± 0.88 1.21 ± 0.08 0.122
Burkholderiales 1.14 ± 0.97 0.18 ± 0.07 0.139
Acidobacteria 11.5 ± 0.58 7.66 ± 0.41 0.000
Acidobacteria‐62.65 ± 0.08 1.12 ± 0.11 0.000
BPC015 1.66 ± 0.13 0.66 ± 0.07 0.000
RB25 2.34 ± 0.20 0.83 ± 0.06 0.000
Sva0725 2.26 ± 0.44 0.37 ± 0.10 0.000
Sva0725 2.26 ± 0.44 0.37 ± 0.10 0.000
BPC102 1.42 ± 0.19 2.26 ± 0.45 0.025
B110 1.42 ± 0.19 2.26 ± 0.45 0.024
Solibacteres 1.03 ± 0.27 0.23 ± 0.07 0.003
Gemmatimonadetes 7.22 ± 0.49 9.44 ± 0.44 0.001
Gemm‐2 4.09 ± 0.39 3.71 ± 0.27 0.213
Gemm‐1 1.95 ± 0.08 4.60 ± 0.47 0.000
Chloroflexi 2.92 ± 0.36 9.12 ± 1.72 0.001
SAR202 2.06 ± 0.26 4.63 ± 1.20 0.011
S085 0.26 ± 0.05 3.87 ± 1.12 0.001
Planctomycetes 3.37 ± 0.37 3.16 ± 0.19 0.399
OM‐190 1.62 ± 0.21 0.71 ± 0.15 0.001
CL500‐15 1.06 ± 0.13 0.51 ± 0.13 0.002
Phycisphaerae 0.69 ± 0.16 2.01 ± 0.15 0.000
CCM11a 0.42 ± 0.09 1.11 ± 0.08 0.000
Nitrospirae 1.69 ± 0.22 0.59 ± 0.09 0.000
Nitrospira 1.69 ± 0.22 0.59 ± 0.09 0.000
Nitrospirales 1.69 ± 0.22 0.59 ± 0.09 0.000
Actinobacteria 1.40 ± 0.33 1.83 ± 0.31 0.146
Acidimicrobiia 1.05 ± 0.32 1.55 ± 0.30 0.095
Acidimicrobiales 1.05 ± 0.32 1.55 ± 0.30 0.095
NC10 1.27 ± 0.29 0.13 ± 0.03 0.001
wb1‐A12 1.27 ± 0.29 0.13 ± 0.03 0.001
Bacteroidetes 1.00 ± 0.31 1.64 ± 0.18 0.023
Note. The mean was calculated by averaging data from four stations on the top and the base, respectively. The p‐values
were calculated by ttest. Higher values are in bold.
Abbreviation: SD, standard deviation.
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LIU ET AL. 2891
northeast trade winds drive the westward surface current all year round from surface to 4,000 m. According
to the data collected with current meter (Seaguard RCM) and ADCP (WHLR75kHz) deployed at nine sites
surrounding the seamount, a huge anticyclonic eddy cycling around the seamount was detected
(Figure 8). The anticyclonic eddy was averagely stronger at the depth of approximately 1,000 m, right
Figure 6. Weighted UniFrac distances for sediment operational taxonomic units data retrieved from the top (blue dot)
and the base (red square) of the Caiwei Seamount. The results are displayed by the principal coordinate analysis
(Lozupone et al., 2006).
Table 3
Numbers of OTUs Shared Within the Sediment Samples Collected From Top and Base Stations of the Caiwei Seamount
Station
Top Base
MAMC01 MAMC02 MAMC03 MAMC04 MABC02 MAMC06 MABC06 MAMC08
Top
MAMC01 6,168 (100) 3,544 (33) 3,326 (36) 3,305 (44) 1,829 (31) 1,803 (23) 1,560 (23) 1,810 (25)
MAMC02 3,544 (58) 10,895 (100) 4,250 (46) 3,943 (53) 2,292 (38) 2,465 (31) 2,017 (30) 2,401 (33)
MAMC03 3,326 (54) 4,250 (39) 9,222 (100) 3,978 (53) 2,095 (35) 2,148 (27) 1,838 (28) 2,153 (29)
MAMC04 3,305 (54) 3,943 (36) 3,978 (43) 7,499 (100) 2,002 (33) 1,967 (25) 1,709 (26) 1,969 (27)
Base
MABC02 1,829 (30) 2,292 (21) 2,095 (23) 2,002 (27) 6,000 (100) 2,852 (36) 2,549 (38) 2,737 (37)
MAMC06 1,803 (29) 2,465 (23) 2,148 (23) 1,967 (26) 2,852 (48) 7,999 (100) 2,818 (42) 3,125 (43)
MABC06 1,560 (25) 2,017 (19) 1,838 (20) 1,709 (23) 2,549 (43) 2,818 (35) 6,688 (100) 2,728 (37)
MAMC08 1,810 (29) 2,401 (22) 2,153 (23) 1,969 (26) 2,737 (46) 3,125 (39) 2,728 (41) 7,345 (100)
Note. Numbers in the brackets are the percentages (%) of shared OTUs in total numbers of OTUs in samplesof the stations on the toprow. The gray‐shaded areas
are the comparisons between the same sample, used for differentiating from those between different samples.
Abbreviation: OTUs, operational taxonomic units.
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LIU ET AL. 2892
above the top layer of the seamount, driving the clockwise current transport on the top of the seamount
(average current velocity: 7.7–10.1 cm/s; Figure 8). It may potentially enhance the bacterial transit and
sinking. Similarly, at the base of the seamount, although the seamount seems acting as a barrier
among stations, the clockwise flow cycled around the seamount (average current velocity: 2.8–5.0 cm/s;
Figure 8), still being able to drive bacterial dispersal and potentially contributing to the similarity of
Figure 7. Correlations between bacterial groups and environmental factors in samples collected from sediments of the top
and the base of the Caiwei Seamount by redundancy analysis (RDA).
Figure 8. The time‐averaged observed bottom current vector of the Caiwei Seamount by nine bottom mounted mooring
stations (15 m above the bottom). An anticyclonic circulation around the seamount was detected.
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LIU ET AL. 2893
bacterial community composition and structure along the circulation of the seamount. Overall, it is con-
cluded that the bacterial community composition and structure in a guyot may be coinfluenced by physico-
chemical variables and unique physical dynamics.
4.2. Interaction Between Bacterial Community and Environmental Gradients
Although the richness of bacterial communities was similar in two regions, the significant difference in
diversity and evenness indicated the compositional and physiological heterogeneity between the top and
the base of the seamount (Dang & Lovell, 2016; Kato et al., 2018). Based on the assigned taxonomy of the
bacterial community by 16S rRNA genes in this study, the potential physiological and metabolic features
of bacteria were found relating to environmental gradients in the Caiwei Seamount.
The abundance and metabolic features of bacteria in marine sediments are related to the organic contents
and oxidation‐reduction potentials (Zobell, 1955). Usually, oxygen in the sediment is depleted rapidly from
the surface. Zonation of microbial community and activity rely on the type and the availability of electron
donors and acceptors, which have been intensely studied in dark environments (Orcutt et al., 2011). In
the Caiwei Seamount, oxygen and nutrient concentrations were measured through the water column of
the guyot (Figure S1). The oxygen concentration was found lowest at ~1,000 m, above the top of the sea-
mount (Figures S1a, S1c, and S1e). The cooccurrence of the phosphate peak and lowest pH at the same depth
suggests a rapid degradation of organic matter by microbes (Figure S1). Consequently, the reduced gradient
of oxygen in seawater near the top inhibits the diffusion of oxygen from the sediment surface to the deeper
depth and a relatively reduced environment is formed in a shallower depth of the sediment. Other electron
acceptors, such as NO
3
‐
,Fe
3+
,Mn
4+
, and SO
42‐
, may be subsequently reduced and play more important roles
in the acquisition of carbon and energy by microorganisms (Reimers et al., 2013). Moreover, a greater pro-
portion of Deltaproteobacteria related to sulfate reduction (e.g., NB1‐j) and syntrophic sulfate reduction
(Syntrophobacteales) were detected at the same layer, an indicator of low or depleted oxygen in the sediment
(Baumgartner et al., 2006; Orcutt et al., 2011).
In comparison, at the base of the Caiwei Seamount, DO concentrations in surrounding seawater were almost
2 times greater than those measured near the top of the seamount (Table S2), possibly a result of slow decom-
position of recalcitrant organic matter accumulated on the base after a long sinking process (Kallmeyer et al.,
2012). The elevated oxygen gradients enhanced the diffusion of oxygen to the deeper depth of the sediment
and affected the microniches in the sediments (D'Hondt et al., 2009). Oxidized forms of Fe and Mn were
much more abundant at the base (Figure 2), which can be formed by abiotic kinetics under aerobic condi-
tions or by microbial oxidation of reduced iron and manganese compounds (Emerson & Moyer, 2002;
Orcutt et al., 2011; Schippers & Jørgensen, 2002). However, in the sediment collected from the top 5‐cm
layer, bacteria reported that were mostly affiliated to iron oxidation in marine environments were not
detected, such as Mariprofundus ferrooxydans in Zetaproteobacteria (Emerson et al., 2007) and Leptothrix
spp. in Betaproteobacteria (Hedrich et al., 2011). This could be the bias of sampling depth. Decreased propor-
tion of sulfate‐reducing Deltaproteobacteria and increased S‐oxidizing Gammaproteobacteria both reflected
the reduction of the redox potentials as a result of increased oxygen. The presence of the phylum
Chloroflexi related to the decomposition of the refractory organic compounds is an evidence of greater pro-
portions of recalcitrant organic matter (Landry et al., 2017), reducing decomposition rate and oxygen con-
sumption. Substrates for S‐oxidizing bacteria at the base of the seamount may be from a variety of
sources, such as elemental S (S
0
), organosulfur, pyrite (FeS
2
), and Chalcopyrite (CuS). The SAR202 cluster
belonging to this phylum has been recently found metabolizing several organosulfur compounds, being a
sulfite‐oxidizer and important in sulfur turnover in the dark ocean (Mehrshad et al., 2017). Due to the accu-
mulation of complex and refractory organic matter that may reduce the efficiency of energy acquisition by
bacteria in base sediments of the seamount, and considering similar bacterial richness between the top
and the base of the seamount, there must be energy sources to compensate. Nitahara et al. (2011) has
reported that chemoautotrophs are the major energy sources for sustaining the microbial ecosystem on
the Mn crust, where both degradation of organic compounds by anaerobes and fermenters would be limited.
S‐oxidizing bacteria have been recognized as one group of major primary producers in benthic environ-
ments, supporting heterotrophic bacteria and benthic organisms (Ye et al., 2016). Moreover, OTUs classified
as ammonia‐oxidizing chemolithoautotrophic bacterium Nitrosospira in the Betaproteobacteria were also
ndetected within sediment samples from the base of the seamount. Although ammonia‐oxidizing
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LIU ET AL. 2894
Thaumarchaeota were not analyzed in this study, they have been reported as the major group of chemoau-
throphs in sediments of similar guyot environment in northwest Pacific Ocean (Kato et al., 2018; Nitahara
et al., 2011, 2017). Therefore, the domination of sulfur‐oxidizing bacteria and ammonia‐oxidizing microbes
at the base of the seamount may play vital roles in food and energy supply.
4.3. Comparison of Bacterial Community on Guyots to Other Seafloor Environments
The bacterial community composition in sediments of the Caiwei Seamount is similar to that in abyssal
environment enriched with polymetallic nodules and other guyots that have been explored in Pacific
Ocean (Kato et al., 2018; Liao et al., 2011; Lindh et al., 2017; Nitahara et al., 2011, 2017; Shulse et al.,
2016), but had key difference from active seamount environments (López‐García et al., 2003; Moyer et al.,
1995; Scott et al., 2017; Teske et al., 2002). The family Piscirickettsiaceae and the order Chromatiales in
Gammaproteobacteria, the family Rhodospirillales in Alphaproteobacteria,Chlorflexi and
Deltaproteobacteria found in the Caiwei Seamount are also the common groups in deep‐sea surface sediment
as well as at seafloor with polymetallic nodule, even with similar relative abundances in the samples
(Shulse et al., 2016). Although we did not sequence archaeal 16S rRNA in this study, as removing sequence
contamination from total bacterial sequences, we found that about 75% of detected archaeal sequences were
identified to be Thaumarchaeota (data not shown), similar to results from the seafloor and seamount in
Pacific Ocean (Kato et al., 2018; Nitahara et al., 2011, 2017; Zinke et al., 2018). It is believed that
Thaumarchaeota could be the key group in the Caiwei Seamount and play an important role in guyot
ecosystem. It needs to be investigated in future studies.
Two ubiquitous groups Zetaproteobacteria and Epsiloproteobacteria in hydrothermal vents were not
retrieved from any sequence pool of the Caiwei Seamount in this study. Iron‐oxidizing bacteria
Zetaproteobacteria have been mostly described as “gradient organisms”because they tend to colonize at
the interface between aerobic and anoxic zones (Hedrich et al., 2011). Thus, the nondetection of
Zetaproteobacteria in the Caiwei Seamount could be due to lower surrounding temperature and chemical
gradient at the interface between sediment and water column (Scott et al., 2017). The presence of
Epsiloproteobacteria usually related to the oxidation of hydrogen sulfide in deep‐sea sediments where vents
surround and the hydrogen sulfide is abundantly supplied (López‐García et al., 2003). In sediment environ-
ments of the Caiwei Seamount, the redox potentials may not be low to the level with rapid and plenty supply
of hydrogen sulfide by sulfate‐reducers as the sources to support the growth of Epsiloproteobacteria.
Different from hydrothermal system, bacterial communities in the Caiwei Seamount are dominated by
the sulfur‐cycle associated groups commonly existing on the surface of oligotrophic oceanic sediments.
5. Conclusions
Currently, there are only a few studies on microbial community in seamounts located in the northwest
Pacific Ocean, but most focused on communities in niches associated with Fe‐Mn crusts. In this study, we
investigated bacterial community compositions and structures from locations featured by different environ-
mental characteristics in order to understand the diversity of microniches, microorganisms, and metabolic
potentials in a guyot ecosystem. Our results indicate that the bacterial community structures and composi-
tions are similar in sediments from the same region (top or base of the seamount) but different between two
regions, highly associated with the depth and environmental variables, such as DO concentrations, elemen-
tal densities, and availabilities of organic matter. The homogeneity of microniches and bacterial commu-
nities at the same depth of the Caiwei Seamount suggests a key effect of physical dynamics on guyot
environment and biological community, while heterogeneous patterns vertically emphasize the important
of physicochemical characteristics on the formation of bacterial niches. Bacterial metabolic potentials
inferred from bacterial community compositions also suggest a strong interaction between microbial mod-
ification and environmental impact.
More than 90% of OTUs were not assigned to genus level, indicating that a large proportion of unknown spe-
cies, diversity, and hidden functions in guyot ecosystem need to be explored in future. As we are working on
isolating new species through culture methods, we will apply metagenomic analysis on guyot samples to
reveal unknown genetic diversity and functions, increasing sequencing resolution to identify key species
as well as their spatio‐temporal variations in guyot ecosystem.
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LIU ET AL. 2895
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Acknowledgments
We would like to thank the crew of R/V
Haiyang Liu Hao and the scientists who
joint the cruise and helped with
samplings. We thank Dr. Hong Cheng
for assisting with the submission of
sequencing data to NCBI, as well as
Dr. Changming Dong and Mr.
Xingliang Jiang from Nanjing
University of Information Science and
Technology for providing the vector
diagram of Figure 1. The research was
funded by grants from China Ocean
Mineral Resources R & D Association
(COMRA) Special Foundation (grants
No.DY135‐E2‐2‐05 and No. DY135‐E2‐
2‐02), Scientific Research Fund of
Second Institute of Oceanography,
MNR (grant No. JB1703) and the
National Natural Science Foundation of
China (grants No. 41706150 and No.
41876182).Complying with AGU's data
policy, the sequencing data can be
accessed at NCBI Sequence Read
Archive under accession number
SRR7888608‐SRR7888615, and others
can be accessed from the text and sup-
porting information.
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