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Bacterial and archaeal community structure of pan-Arctic Ocean sediments revealed by pyrosequencing
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Xuezheng LIN1, *, Liang ZHANG1, Yanguang LIU1, Yang LI1
Acta Oceanologica Sinica | 2017, 36(8) : 146 - 152
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Acta Oceanologica Sinica | 2017, 36(8): 146-152
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Bacterial and archaeal community structure of pan-Arctic Ocean sediments revealed by pyrosequencing
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Xuezheng LIN1, *, Liang ZHANG1, Yanguang LIU1, Yang LI1
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  • 1 The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
Published: 2017-08-01 doi: 10.1007/s13131-017-1030-2
Outline
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This study was to investigate bacterial and archaeal community structure of pan-Arctic Ocean sediments by pyrosequencing. In total, investigation of three marine sediments revealed 15 002 bacterial and 4 362 archaeal operational taxonomic units (OTUs) at the 97% similarity level. Analysis of community structure indicated that these three samples had high bacterial and archaeal diversity. The most relatively abundant bacterial group in Samples CC1 and R05 was Proteobacteria, while Firmicutes was dominant in Sample BL03. Thaumarchaeota was the most relatively abundant archaeal phylum in Samples CC1 and R05, and the relative abundance of Thaumarchaeota was almost as high as that of Euryarchaeota in Sample BL03. These two phyla accounted for nearly 100% of the archaeal OTUs. δ-Proteobacteria and γ-Proteobacteria were the two most relatively abundant classes at Proteobacterial class level, and their relative abundance was more than 60% in Samples CC1 and R05. There were also differences in the top 10 relatively abundant bacterial and archaeal OTUs among the three samples at the 97% similarity, and only 12 core bacterial OTUs were detected. Overall, this study indicated that there were distinct microbial communities and many unique OTUs in these three samples.

Arctic sediment  /  microbial community  /  diversity  /  pyrosequencing
Xuezheng LIN, Liang ZHANG, Yanguang LIU, Yang LI. Bacterial and archaeal community structure of pan-Arctic Ocean sediments revealed by pyrosequencing[J]. Acta Oceanologica Sinica, 2017 , 36 (8) : 146 -152 . DOI: 10.1007/s13131-017-1030-2
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1 Introduction
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The pan-Arctic region has various distinct habitats for microbes such as oceanic water, sea-ice, glacial ice, permafrost, tundra wetlands, subglacial soil, periglacial soil, and tundra soil (Reddy et al., 2009). Marine sediment represents one of the most complex microbial habitats on Earth. In these areas, microorganisms contribute to bulk biomass and play an important role in remineralization of organic matter (Ravenschlag et al., 2000; Tian et al., 2009). Microbial communities and their associated metabolic activities in marine sediment have profound impacts on global biogeochemical cycles (Jorgensen et al., 2012).
Marine sediment hosts the largest reservoir of organic carbon in the world and outnumbers any other environment with respect to microbial cell abundance (Whitman et al., 1998; Jorgensen et al., 2012). The heterogeneous nature of Arctic marine sediments implies that the microbial community structure might differ from geographical areas and depths of sediments throughout the pan-Arctic Ocean. The omnipresence of prokaryotic cells has recently been demonstrated (Jørgensen and Boetius, 2007; Roussel et al., 2008). In general, the microbial community in marine sediment appears to be dominated by a restricted number of bacterial and archaeal phyla (Jorgensen et al., 2012).
Compared with seawater, organic matter is 104–105 fold concentrated in sediments and is used as an energy source by microorganisms. Consequently, Arctic is regarded as a carbon sink (Trevors et al., 2010). Bacteria in sediment represent a major reservoir of genetic variability, similar to soil systems that show approximately 104 species per gram (Torsvik et al., 2002; Zeng et al., 2011). The density of prokaryotic cells in coastal and continental margin sediments is typically 108–109 cells/cm3 in the top sediment layers and declines with the depth in a logarithmic fashion (Jorgensen et al., 2012).
Archaea are best known for their ability to thrive in extreme environments; however, recent molecular studies have shown that organisms from this prokaryotic domain of life are ubiquitous. Archaea play important roles in essential environmental processes such as the carbon and nitrogen cycles (Chaban et al., 2006; Albers and Pohlschröder, 2009). Despite their significant ecological roles, most archaeal community have been analyzed in hydrothermal sediments (Kormas et al., 2006; Wang et al., 2009; Nunoura et al., 2010) and hot springs (Segerer et al., 1993; Hetzer et al., 2007), while there have been only a few studies on the archaeal community of Arctic sediments based on traditional culture-independent approaches (Tian et al., 2009; Hamdan et al., 2013). It is now widely accepted that microbial community analysis should be culture-independent, and utilize molecular identification methods such as sequencing of 16S rRNA genes (Chun et al., 2010). Several studies on the bacterial diversity in Arctic marine sediments have been carried out using traditional culture-independent approaches such as PCR-DGGE and 16S rRNA libraries, and these studies have revealed higher diverse microbial communities than that characterized by conventional culture-dependent approaches (Li et al., 2009; Tian et al., 2009; Zeng et al., 2011). However, investigation of microbial community is insufficient due to the low throughput of traditional culture-independent approaches (Zeng et al., 2013). In recent years, pyrosequencing has been employed in various microbiological disciplines (Rothberg and Leamon, 2008; Jaenicke et al., 2011; Abbai et al., 2012; Li et al., 2013).
Pyrosequencing has been used to enumerate and contrast marine microbial diversity in Arctic waters (Galand et al., 2009; Kirchman et al., 2010; Comeau et al., 2011; Bowman et al., 2012; Comeau et al., 2012; Zeng et al., 2013). However, there has been few investigation of the microbial community of Arctic sediments by pyrosequencing (Hamdan et al., 2013). In this study, the bacterial and archaeal community structures of three pan-Arctic Ocean sediments were investigated using the Roche 454 GS FLX Titanium platform, and the differences in microbial community among these samples were discussed.
2 Materials and methods
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2.1 Samples and chemical analysis
Surface marine sediment (0–5 cm) was collected during the 5th Chinese National Arctic Expedition from July to September, 2012, and stored at –80°C until further analysis. Total nitrogen (TN), total carbon (TC) and total organic carbon (TOC) contents in the samples were analyzed using elemental analyser (Vario EL Ⅲ, Elementar, Germany). The sampling dates, locations, depths and some physicochemical characters of samples were summarized in Table 1.
2.2 DNA extraction, amplification and sequencing
DNA was extracted from 1 g sediment using PowerMax Soil DNA isolation Kit (12988-10, MOBIO Laboratories, Inc, Carlsbad, CA) following the manufacturer’s protocol.
The V1-V3 hypervariable regions of the bacterial 16S rRNA gene were amplified using the forward primer 8F (5′-AGAGTTTGATCCTGGCTCAG-3′) and the reverse primer 533R (5′-TTACCGCGGCTGCTGGCAC-3′) (Zeng et al., 2013). The partial archaeal 16S rRNA gene was amplified using the forward primer Arch341F (5′-ACGGGGYGCAGCAGGCGCGA-3′) and the reverse primer Arch915R (5′-GTGCTCCCCCGCCAATTCCT-3′) (Zheng et al., 2013). The target 16S rRNA gene fragments were pyrosequenced using the Roche 454 Genome Sequencer FLX Titanium platform at Majorbio Bio-Pharm Technology Co., Ltd., Shanghai, China, as previously described (Wu et al., 2012).
2.3 Filtering and removal of noise from amplicon sequence data
Sequencing reads from different samples were separated by unique barcodes. The barcode, linker, and PCR primer sequences at both sides were then removed from the original sequencing reads. Next, the dataset was filtered and noise was removed using software Seqcln (http://sourceforge.net/projects/ seqclean) and Mothur (http://www.mothur.org/wiki/Main_ Page).
2.4 Sequence analysis
The raw sequence data were processed, and the reads were removed if at least one of the following criteria was met: (1) the average quality score was lower than 25, (2) reads were shorter than 200 bp, and (3) number of ambiguous bases was greater than 0.
The Mothur database (http://www.mothur.org/wiki/main_ page) was used for taxonomic assignment of each pyrosequencing read. All sequences were classified from phylum to species according to the Mothur program using the default setting. If the similarity was below the cutoff point, the read was assigned to an unclassified group.
2.5 Diversity and community structure analysis
Sequences were aligned and compared with those available in the Bacterial SILVA database (http://www.arb-silva.de) using the Kmer Searching method (http://www.mothur.org/wiki/ align.seqs) and representative sequences for shared OTUs were obtained. The Good’s coverage, the index of community richness (Chao estimator and Ace estimator) and the index of community diversity (Shannon index and Simpson index) were also obtained using the method described at http://www.mothur.org/ wiki.
2.6 Nucleotide sequence accession numbers
Bacterial and Archaeal 16S rRNA gene sequences derived from pyrosequencing have been deposited in GenBank under accession number SRP034720, SRP034817 and SRP034818.
3 Results
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3.1 Overview of pyrosequencing
In this study, the bacterial and archaeal communities of three pan-Arctic Ocean sediments collected from different latitude were investigated. Pyrosequencing using the Roche 454 GS FLX Titanium system yielded a total of 79 124 valid bacterial sequences with an average length of 411 bp, and a total of 39 526 valid archaeal sequences with an average length of 362 bp. After the low quality reads were discarded, the final dataset contained 59 130 bacterial and 24 110 archaeal trimmed sequences in total. The number of different bacterial/archaeal sequences, namely OTUs, decreased substantially when placed into groups that share ≥97%, ≥95% and ≥90% similarity. At the 97% similarity level, a total of 3 640, 5 768, and 5 594 bacterial OTUs, and a total of 1 425, 1 165, and 1 772 archaeal OTUs were obtained from Samples BL03, CC1 and R05 respectively (Table 2).
3.2 Analysis of community diversity
The richness and diversity indexes of the microbial community structure at the 97% similarity level were summarized in Table 3. The higher Good’s coverage of 0.88 (bacteria) and 0.90 (archaea) suggested that the number of unique sequence types sampled from these libraries almost approached the total number of unique sequences (Chelius and Triplett, 2001). The high Shannon index and low Simpson index indicated high bacterial and archaeal diversity in these sediments. As a whole, the overall bacterial richness was notably higher than the archaeal richness. The bacterial richness of Sample BL03 was lower than that of Samples CC1 and R05, probably due to the lower content of TN, TOC and TC in Sample BL03 (Table 1). There was a positive correlations between bacterial richness and a total of TN, TOC and TC contents among the three samples we tested (R2=0.70). However, there were no significant differences in archaeal richness among the three samples tested. These results further confirm that marine sediment is a complex microbial habitat with high microbial diversity that contributes to bulk biomass.
3.3 Taxonomic composition
All bacterial and archaeal sequences were classified from phylum to species according to the Mothur program (http:// www.mothur.org/wiki/classify.seqs). The trimmed bacterial sequences were assigned to 24, 20 and 23 phyla or groups from Samples BL03, CC1 and R05 respectively. However, only three archaeal phyla and one unclassified archaea were assigned in each sample.
Although the same taxa were generally present in all samples, the relative abundance varied substantially among different microbial communities. The ten most relatively abundant bacterial phyla of each sample were shown as Fig. 1. Although the composition of the ten most relatively abundant phyla seemed similar, their relative abundances were remarkably different. Compared with Sample BL03, Samples CC1 and R05 shared a more similar bacterial community structure at the phylum level. Proteobacteria was most relatively abundant in Samples CC1 and R05, and the sequences belonging to this phylum accounted for more than 60% of the bacterial sequences. However, Firmicutes was the most relatively abundant phylum in Sample BL03, and sequences affiliated with this phylum accounted for more than 40% of the bacterial sequences.
The three samples contained three archaeal phyla and one unclassified archaea. Thaumarchaeota and Euryarchaeota were the dominant phyla, and the sequences belonging to these two phyla accounted for almost 100% of the total archaeal sequences (Fig. 2). Compared with Euryarchaeota, the sequences belonging to Thaumarchaeota were more abundant, and the relative abundance was nearly 80% in Samples CC1 and R05.
3.4 Taxonomic distributions of Proteobacterial and archaeal class
Proteobacteria was the most relatively abundant bacterial phylum among the three samples investigated. All Proteobacterial classes except ζ-Proteobacteria (Zetaproteobacteria) existed in each of these samples, and their taxonomic distributions also exhibited differences (Fig. 3). δ-Proteobacteria and γ-Proteobacteria were the two most abundant classes among the three samples, the relative abundance ranged from 9.3% (BL03) to 47.4% (R05) and from 5.3% (BL03) to 31.6% (CC1) respectively.
There was also similar taxonomic composition of archaeal class between Sample CC1 and Sample R05. The sequences affiliated with no_rank_Thaumarchaeota were dominant among the three samples, and it was up to 80% in Sample CC1. Halobacteria, a class belonging to Euryarchaeota, was the major class following no_rank_ Thaumarchaeota in all these three samples investigated (Fig. 4).
3.5 Ten most abundant bacterial and archaeal OTUs at the 97% similarity level
The ten most abundant bacterial OTUs at the 97% similarity level were summarized to further understand the important bacteria in pan-Arctic sediments (Table 4). There were distinct differences among the ten most abundant OTUs in the three samples. The most abundant OTU in Sample BL03 was affiliated with Lactococcus piscium. The high relative abundance of 32.7% implied that this species was the dominant species in Sample BL03. Conversely, the relative abundance of the most abundant OTU in Samples CC1 and R05 accounted for only 5.8% and 10.9%, respectively, indicating that there was no obvious dominant species among these samples.
There was obvious dominant archaeal OTUs in all three samples, the relative abundance of sequences affiliated with Group_C3_uncultured_crenarchaeote was up to 66.1% in Sample CC1. The abundant OTU in Sample R05 were affiliated with Group_C3_uncultured_crenarchaeote, Candidatus_ Nitrosopumilus_unidentified_archaeon and Deep_Sea_Hydrothermal_Vent_Gp_6_ marine_metagenome, with a total abundance of up to 80.4%. Even in Sample BL03, the relative abundance of OTU affiliated with Deep_Sea_Hydrothermal_Vent_ Gp_6_uncultured_ archaeon was also up to 20.6% (Table 5). These findings indicated that archaeal diversity was lower than bacterial diversity, with the relative abundance of the top ten OTUs being more than 90% in Samples CC1 and R05, while that of bacteria was only about 50%.
3.6 Abundant versus rare bacterial OTUs
The Venn diagram shows the number of OTUs unique to a single sample or shared by two or three samples. Abundant or core bacterial OTUs at the 97% similarity level were compared with rare and unique OTUs among the three samples (Fig. 5a). Only 12 core bacterial OTUs were detected in the three samples, most of which were affiliated with Proteobacteria. The vast majority of OTUs were singletons. For example, they accounted for 98.95% of total bacterial OTUs in Sample BL03. Sample BL03 only shared 25 and 37 OTUs with Samples CC1 and R05, respectively; however, Sample CC1 shared 1401 OTUs with Sample R05, which implied that there were similar bacterial communities in these two samples. The dendrogram also indicated that Samples CC1 and R05 had similar bacterial communities (Fig. 5b).
4 Discussion
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High-throughput pyrosequencing, a newly-developed powerful tool for studying microbial communities, has been used to investigate marine bacterial communities in the polar region (Bowman et al., 2012; Zeng et al., 2013; Hamdan et al., 2013). Compared with the previous studies on bacterial diversity by conventional culture-independent approaches (Tian et al., 2009; Zeng et al., 2011), higher diversity was detected by pyrosequencing, although both approaches revealed a similar composition of the major bacterial groups. The bacterial diversity based on the 16S rRNA clone library showed that sequences of sediment from the deep Sta. DBS1 fell into 15 phyla (Zeng et al., 2011), which were also detected in our study; however, our study showed that more than 20 bacterial phyla were presented in the three samples investigated. The newly-detected bacterial phyla included Aquificae, Armatimonadetes, Spirochaetes and Gemmatimonadetes. Only nine bacterial phyla were identified from 463 clones from the 16S rRNA clone library of four surface sediment samples (0–5 cm) collected from the Pacific Arctic Ocean (Li et al., 2009). The bacterial community richness, Chao estimator and ACE estimator, were more than 20 000; meanwhile, there were more than 5 000 OTUs at the level of 97% similarity. However, a previous study based on a 16S rRNA library showed a species richness of only about 250 (Zeng et al., 2011).
As a whole, due to the similar depth, TN, TC and TOC contents, there were similar bacterial and archaeal communities in Samples CC1 and R05. Taxonomic distributions of the ten most abundant phyla of bacteria (Fig. 1) and archaea (Fig. 2) in the three samples indicated Samples CC1 and R05 had similar microbial community structure. Furthermore, there were much more shared OTUs between Sample CC1 and Sample R05 (Fig. 5a); meanwhile, the dendrogram also showed there were similar bacterial communities in these two samples (Fig. 5b).
Proteobacteria were dominant in Samples CC1 and R05, and it was similar to the previous studies in the Arctic sediment by conventional culture-independent approaches (Tian et al., 2009; Zeng et al., 2011). However, the relative abundance of Proteobacteria class was different from previous studies (Tian et al., 2009). It was notably that only ζ-Proteobacteria of six Proteobacterial classes was not detected in our study, which was consistent with the investigation of Hamdan et al. (2013). Firmicutes was the dominant phyla in Sample BL03, which was also consistent with the results of Hamdan et al. (2013) showing that Firmicutes and Chloroflexi were the dominant phyla in Arctic sediments.
There were more TN and TOC in Samples CC1 and R05 (Table 1), which might have been due to the rich nutrient input by the Pacific waters flowing northward through the Bering Strait and more organic materials settling in the sediments (Cooper et al., 1997), and the rich nutrients from the mainland and increased nutrients sedimented from the surface water. Correspondingly, these two samples had higher bacterial richness than Sample BL03. Furthermore, due to the similar depth and physicochemical characters (Table 1), Samples CC1 and R05 had similar microbial community.
The diversity of archaea generally appears to be much lower than that of bacteria, and marine archaea could be 5–10 times less diverse than bacteria (Galand et al., 2009). Thaumarchaeota, the dominant archaeal phylum among the three samples investigated, is a phylum of Archaea that was proposed in 2008 after the genome of Cenarchaeum symbiosum was sequenced and found to differ significantly from other members of the hyperthermophilic phylum Crenarchaeota (Brochier-Armanet et al., 2008). This recently proposed phylum may represent the deepest branching lineage in the archaeal phylogeny emerging before the divergence between Euryarchaeota and Crenarchaeota (Muller et al., 2010). All organisms of this lineage identified to date are chemolithoautotrophic ammonia-oxidizers that may play important roles in biogeochemical cycles, such as the nitrogen cycle and the carbon cycle. This novel phylum comprises all known archaeal ammonia oxidizers as well as several clusters of environmental sequences representing microorganisms with unknown energy metabolism (Pester et al., 2011). The dominance of ammonia-oxidizing Thaumarchaeota among the three samples tested indicates that this archaeal phylum might play an important role in the nitrogen and carbon cycles (Wang et al., 2009).
According to the definition of Galand et al. (2009), abundant phylotypes are those representing grater than 1% within a sample, while rare phylotypes have an abundance less than 0.01% within a sample. Sequences affiliated with Lactococcus piscium accounted for 32.7% of total bacterial sequences in Sample Bl03; however, this sample also comprised a higher number bacterial OTUs (206) containing only one trimmed sequence, which only accounted for 1.46% of the total bacterial trimmed sequences. L. piscium was firstly isolated from salmonid fish and proposed as a novel strain by Williams et al. (1990). L. piscium was shown to grow in a variety of modified atmosphere packaged (MAP) meat products, including broiler, pork, turkey, and minced meat made of beef and pork, where they belonged to the predominating microbiota (Rahkila et al., 2012). The reason that why so many sequences were affiliated with L. piscium in BL03 was unclear and much more sediments near this location should be pyrosequenced.
The low coverage obtained even with pyrosequencing and the fact that the rarefaction curve did not level off indicate that more data should be obtained using this approach to better understand the complex microbial communities in marine sediments. In addition, due to the heterogeneous natures of marine sediments, large-scale pyrosequencing should be carried out, which might lead to intriguing observations that encourage future analysis.
Acknowledgements
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The authors thank the sampling assistances of the 5th Chinese National Arctic Expedition.
Funding
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  • The Chinese Polar Environment Comprehensive Investigation and Assessment Program under contract No. CHINARE2014-03-05; the National Natural Science Foundation of China under contract No. 41176174; the Innovation and Development Regional Demonstration Program of Marine Economy under contract No. 12PYY001SF08-HYYS-1.
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Year 2017 volume 36 Issue 8
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doi: 10.1007/s13131-017-1030-2
  • Receive Date：2016-06-17
  • Online Date：2026-04-16
  • Published：2017-08-01
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  • Received：2016-06-17
  • Accepted：2016-08-08
Funding
The Chinese Polar Environment Comprehensive Investigation and Assessment Program under contract No. CHINARE2014-03-05; the National Natural Science Foundation of China under contract No. 41176174; the Innovation and Development Regional Demonstration Program of Marine Economy under contract No. 12PYY001SF08-HYYS-1.
Affiliations
    1 The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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