Dynamics of the bacterial and archaeal communities in the Northern ...

Deep-Sea Research II 117 (2015) 97–107

Contents lists available at ScienceDirect

Deep-Sea Research II journal homepage: www.elsevier.com/locate/dsr2

Dynamics of the bacterial and archaeal communities in the Northern South China Sea revealed by 454 pyrosequencing of the 16S rRNA gene Xiaomin Xia, Wang Guo, Hongbin Liu n Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China

art ic l e i nf o

a b s t r a c t

Available online 29 May 2015

Dynamics of the prokaryote (bacteria and archaea) abundance and community compositions in the Northern South China Sea (NSCS) in August 2009 and January 2010 were studied by flow cytometric analysis and 454 pyrosequencing of the 16S RNA gene. Prokaryotic community structures in the NSCS varied across space and over time, and this variation was strongly correlated with NO−3 concentration. Prokaryote in estuarine and coastal waters was more abundant, but relatively less seasonally dynamic than in the open ocean. Major bacterial and archaeal lineages showed different niche preferences. Archaeal community was dominated by Marine Group I and Marine Group II. Clusters of Marine Group I varied spatially, while clusters of Marine Group II varied seasonally. Synechococcus and Prochlorococcus were two major autotrophic bacteria found in the NSCS. Synechococcus prevailed at the estuarine station in summer, while Prochlorococcus had high abundance at open-ocean stations in summer. Subcluster 5.2 Synechococcus and Sub 5.1 clade II Synechococcus were the dominant Synechococcus lineages in the NSCS, with the former dominating in the estuary during summer and the latter dominating at all other stations. Our results suggest that prokaryotic assemblages are highly complex in the NSCS and are controlled by seasonal monsoon and river discharge, showing spatiotemporal variations. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Bacterial community Archaeal community South China Sea 454 Pyrosequencing

1. Introduction Prokaryotes, which constitute the two domains bacteria and archaea, are the most abundant and diverse organisms in marine waters (DeLong, 1992; DeLong et al., 1994; Curtis et al., 2002; Pedrós-Alió, 2006; Alonso-Sáez et al., 2011). These highly diverse organisms are involved in the cycles of virtually all essential elements in marine environment such as carbon and nitrogen cycles. Their essential role in decomposing and recycling organic matter has been well recognized. Community composition, biomass and activity of these organisms critically influence carbon fluxes of marine ecosystems (Mou et al., 2008; Jiao et al., 2010a; Gantner et al., 2011). Autotrophic bacteria for example, contribute up to 60% of the total primary production in the open ocean ecosystem (Platt et al., 1983). Heterotrophic bacteria on the other hand, consume around 20–60% of total primary production in marine ecosystems (Fuhrman, 1992; Kirchman et al., 1993) and turn dissolved organic carbon into higher trophic levels via the microbial loop (Azam, 1998). Moreover, heterotrophic bacteria have recently been recognized as playing an important role in marine carbon reservation by the microbial carbon pump (Jiao et al., 2010a). n

Corresponding author. Tel.: þ 852 23587341; fax: þ852 23581559. E-mail address: [email protected] (H. Liu).

http://dx.doi.org/10.1016/j.dsr2.2015.05.016 0967-0645/& 2015 Elsevier Ltd. All rights reserved.

Comparing to bacteria, archaea are less diverse and not wellstudied organisms. Archaea, previously found to distribute only in extreme environment, were later found widely distributed in marine waters with high abundance (DeLong et al., 1994; DeLong and Pace, 2001). It has been reported that two main archaeal phyla, Euryarchaeota and Crenarchaeota, occupy different niche in marine ecosystems (Massana et al., 1997; DeLong, 2003). Euryarchaeota are more abundant in surface waters, whereas Crenarchaeota are more abundant at depth (Massana et al., 1997; Alonso-Sáez et al., 2011). Study carried out at the Hawai’i Ocean Time-series station ALOHA in the North Pacific subtropical gyre showed pelagic Crenarchaeota represents one of the ocean’s most abundant single cell types (Karner et al., 2001). In some regions, they account for more than 20% of the total picoplankton cell densities (DeLong, 2003). Understanding the variations of microbial communities in the ocean helps us to understand the long-term responses of marine microbes to environmental changes (Giovannoni and Vergin, 2012). Based on analysis of the 16S rRNA gene and flow cytometry, seasonal and spatial variations of bacterioplankton communities have been studied in many coastal and oceanic waters, such as the western English Channel (Gilbert et al., 2009, 2011), the Southern Ocean (Jamieson et al., 2012), southern California (Dillon et al., 2009) and the Mediterranean Sea (Ruiz-González et al., 2011). Many of these studies revealed apparent seasonal and spatial

98

X. Xia et al. / Deep-Sea Research II 117 (2015) 97–107

dynamics of bacterioplankton communities, and some studies pointed out that certain bacterioplankton orders (such as SAR11 and Rhodobacterales) had different seasonal abundances (Gilbert et al., 2011). These studies identified a number of different environmental parameters, such as NH+4 and total organic nitrogen concentration (Gilbert et al., 2011), phosphate concentration (Gilbert et al., 2009), temperature (Gilbert et al., 2009; Jamieson et al., 2012) and salinity (Dillon et al., 2009; Fortunato et al., 2012), affecting the dynamics of bacterioplankton communities. However, there are few studies assessing the seasonal variation of archaeal community in marine environment (Murray et al., 1998; Herfort et al., 2007; Winter et al., 2009; Hollibaugh et al., 2013). The South China Sea is a large marginal sea in the western tropical North Pacific Ocean. Its northern part is influenced by a variety of different oceanographic processes, including freshwater discharge from the Pearl River, mesoscale eddies, coastal upwelling and the interaction of different currents, modulated by the East Asian monsoon. The highly dynamic and complex hydrological condition affects the composition and function of bacteria communities along the nutrient gradient from river plume to the oligotrophic basin in different seasons. This in turn might explain the seasonal variation of carbon fluxes in this region. However, only few studies addressing bacterial and archaeal community compositions and their seasonal variations in the Northern South China Sea (NSCS) have been done so far. In recent years, high-throughput sequencing, such as 454 pyrosequencing, has been applied in the research of bacterial community composition and diversity. These applications provide less biased, more robust and high-coverage results that help to uncover many details about the distribution of bacteria in a broad range of environments. In this study, we studied the seasonal variations of free living bacterial and archaeal community compositions along a transect from the estuarine water of the Pearl River to the oligotrophic basin in the NSCS by applying the 454 pyrosequencing method.

2. Methods 2.1. Sample collection, analyses of environmental parameters and prokaryote abundances Samples were collected from surface at 5 stations along a transect from the Pearl River estuary to the oceanic region of the NSCS in August 2009 and January 2010 (Fig. 1, Table 1). Seawater samples were collected using Niskin bottles (12 L) attached to a conductivity, temperature, and depth (CTD) rosette multi-sampler. Environmental parameters (nitrate (NO−3 ), phosphate (PO3− 4 ), dissolved oxygen, and chlorophyll a (Chl a) concentrations) were measured as described in Kong et al. (2011) (Table 1). Temperature was measured by the CTD. Picoplankton cell densities were quantified using flow cytometry (FCM) following the methods described in Chen et al. (2012) and Liu et al. (2014). At each station, 1 L of seawater was filtered successively through a 3.0 mm and 0.22 mm (47 mm) polycarbonate membranes (PALL Corporation). Samples retained on 0.22 mm membranes were stored at 80 °C immediately after filtration, and used for DNA extraction. 2.2. DNA extraction, PCR and pyrosequencing DNA was extracted using enzyme/phenol–chloroform protocol (Riemann et al., 2008). DNA was eluted in TE buffer (Tris–EDTA buffer) and kept at 20 °C until further analysis. The bacterial 16S rRNA gene was amplified using barcoded primers 341F

(5′-adaptor þbarcodeþ CCTAYGGGRBGCASCAG-3′) and 806R (5′-adaptor þGGACTACNNGGGTATCTAAT-3′) (Yu et al., 2005). Archaeal 16S rRNA gene was amplified using barcoded primers 340F (5′-adaptor þbarcodeþCCCTAYGGGGYGCASCAG-3′) and 1000R (5′-adaptorþGGCCATGCACYWCYTCTC-3′) (Gantner et al., 2011). For bacterial 16S rRNA gene, PCR reactions contained a final concentration of 0.5 mM MgCl2, 0.5 mM of each primer (Yu et al., 2005), 0.8 mM of each dNTP and 1.0 unit of hot start polymerase (Invitrogen, USA). The template DNA concentration was about 10 ng per reaction (the template DNA was diluted to 10 ng ml 1, and 1 ml was added). The PCR cycles started with a 5 min initial denaturation at 95 °C, followed by 30 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 60 s. A final extension of 72 °C for 5 min was included before holding at 4 °C. For the amplification of 16S rRNA gene of archaea, protocol of Stephan Gantner was followed (Gantner et al., 2011). All the reactions were done in 25 ml reaction volume in triplicates. PCR products were gel-purified using the Qiaquick gel purification kit (Quiagen, Hilgen, Germany). Library quantification was done by fluorometry using the Quant-iT picoGreen dsDNA Assay Kit (Invitrogen, USA). An equal volume of each amplicon was mixed to prepare amplicon pools, and then sequenced in a two-region 454 run on a GS PicoTiterPlate using a Roche/454 GS Junior pyrosequencing system (Roche, 454 Life Sciences, Branford, CT, USA).

2.3. Data analysis Analysis of 16S rRNA data was conducted using the microbial ecology community software program Mothur (http://www. mothur.org/wiki/Download_mothur) (Schloss et al., 2009). The reads were processed by removing tags and primers, only accepting reads with an average quality score above 20 and read lengths longer than 300 nt. Data analysis was carried out following the Schloss standard operating procedure (Schloss et al., 2009). Sample coverage, ACE richness estimators and Shannon diversity index were calculated at 97% similarity. A dendrogram describing the similarity of the samples was generated using Thetayc calculators. Sequences were classified using the greengene database (http://greengenes.lbl.gov/cgi-bin/nph-index.cgi) and NCBI Blast (http://www.ncbi.nlm.nih.gov/). A neighbor-joining phylogenetic tree of Cyanobacteria 16S rRNA genes was constructed in MEGA 4 using representative sequences at a 0.03 genetic distance (Tamura et al., 2007). Nearest relatives were retrieved from the NCBI database. A heatmap showing the relative number of sequences per sample for each operational taxonomic unit (OTU) was generated in iTol (Letunic and Bork, 2007). The relationship of environmental factors and the species composition of community (based on the relative abundance of top 250 OTUs) were analyzed by the constrained linear ordination technique redundancy analysis (RDA) using CANOCO v4.5 (Microcomputer Power, USA) and the BIOENV analysis provided in PRIMER 5 software (Primer-E Ltd, UK). RDA was used to test which of the environmental factors explain the majority of the variation in the bacterial/archaeal community composition (Monte Carlo permutation test, 1000 permutations) and show relationship between major bacterial families and environmental factors. The BIOENV analysis was applied to determine the correlation between the environmental factors and bacterial/archaeal communities with the application of a Spearman’s correlation coefficient.


99

3. Results

3.2. Prokaryote abundance

3.1. Hydrographic conditions

The abundance of total prokaryotes was higher in estuarine and coastal waters than in oceanic waters in both summer and winter seasons (Fig. 2). Prokaryote abundance was slightly higher in summer than in winter in estuarine and coastal waters, whereas, in the shelf and oceanic waters, they were two to three times more abundant in winter than in summer (Fig. 2A). Synechococcus and Prochlorococcus showed different distribution patterns in the surface waters of the NSCS. Synechococcus were present at all the stations, but Prochlorococcus were only present at open ocean stations (A5, A0/A1, A11/A10) (Fig. 2B and C). In oceanic water, the abundance of Prochlorococcus was higher in in summer

Due to high load of nutrients from the Pearl River, surface waters of estuarine station NM3 and coastal station A9 had high NO−3 and PO3− 4 concentration. In summer, station NM3 was strongly influenced by the freshwaters discharged from the Pearl River, resulting in a low salinity environment. Coastal station and oceanic stations (A5, A0/A1, and A10/A11) had higher NO−3 concentration in the winter than in the summer. Fig. 1B showed that the oceanic stations (A5, A0/A1 and A10/A11) had similar environmental conditions.

Fig. 1. (A) Map showing the sampling stations in the NSCS. Samples NM3S, A9S, A5S, A0S and A11S were collected in August 2009 and NM3W, A9W, A5W, A1W and A10W were collected in January 2010. (B) Cluster based on environmental factors data showing the relationship of sample stations.

Table 1 Sample stations and environmental parameters.

Longitude (E) Latitude (N) NO− 3 (mM) a PO3− 4 (mM) Temperature (°C) Salinity (psu) Chl a (mg L 1) a

NM3S

A9S

A5S

A0S

A11S

NM3W

A9W

A5W

A1W

A10W

113.96 22.33 30.86

114 22 1.40

114.98 21 0.14

116.01 19.9 0.11

117.33 18.63 0.13

113.96 22.33 9.94

114 22 6.58

114.98 21 0.45

115.77 20.16 0.24

116.64 19.25 0.21

1.62

0.08

0.08

0.08

0.09

0.97

0.171

0.080

0.082

27.56 23.32 1.07

28.55 31.53 1.707

28.25 33.52 0.178

29.68 33.63 0.117

29.8 33.6 0.055

20.65 34.14 1.36

16.83 34 3.785

22.6 34.41 0.558

23.23 34.09 0.592

Samples with PO3− 4 below the detection limit are assigned 0.080 mM.

0.080 24.12 33.8 0.72

100


Alphaproteobacteria (45.3% of total sequences) and Gammaproteobacteria (19.8% of total sequences) were the two dominant classes across five classes found in the NSCS. Most of the archaeal 16S rRNA gene sequences were assigned to archaeal phyla Euryarchaeota (70.0% of total reads) and Crenarchaeota (29.9% of total reads). Three marine archaeal groups were found in surface waters of the NSCS. Group II Euryarchaeota was the most abundant archaeal group, followed by Marine Group I and Marine Group III archaea. Marine Group I was further divided into two subclusters: Group I cluster α, which was closely related to Nitrosopumilaceae archaeon MY1 (autotrophic ammonia-oxidizing archaeon), and Group I cluster β, which was affiliated with Nitrosopumilus maritimus. Marine Group II also contained two subclusters, but had more OTUs than Marine Group I. Most of the Marine Group II cluster α archaea were assigned into a clade represented by unidentified Euryarchaeote SB95-40 (Surface water of Santa Barbara Channel); cluster β archaea were highly similar to uncultured Euryarchaeote ME-450-30 (Alboran Sea at 450 m depth (Massana et al., 2000) ) (Fig. S3, Fig. 4). 3.4. Spatial and seasonal variation in prokaryotic community structure

Fig. 2. Cell abundance of total prokaryotes (A), Synechococcus (B) and Prochlorococcus (C) in surface water of the NSCS.

than in winter, while the abundance of Synechococcus showed the opposite. In summer, Synechococcus concentration increased rapidly along the transect from oceanic water to estuarine water, reaching a maximum abundance of 1.43 105 cells mL 1 in NM3S (Fig. 2B). 3.3. Distribution of bacterial and archaeal phylotypes across all samples In total, 91,201 raw bacterial 16S rRNA gene sequences and 36,739 raw archaeal 16S rRNA gene sequences were obtained from 10 samples. All 16S rRNA gene sequences of bacteria and archaea can be downloaded from website: http://ihome.ust.hk/ liulab/ 454.html. After removing the noise, poor-quality reads, and chimeric sequences, a total of 67,488 and 34,349 high quality bacterial and archaeal 16S rRNA gene sequences were recovered, respectively. At 3% and 5% phylogenetic distances, coverage of all samples except A9S were higher than 80, which indicates that the surveying effort covered the full extent of taxonomic diversity (Table S1). Based on the greengene database, all 16S rRNA gene sequences were affiliated with 27 bacterial phyla (2 unknown) and 2 archaeal phyla (Figs. 3 and S1) with confidence score thresholds of 80%. Proteobacteria, Cyanobacteria, Bacteroidetes, Actinobacteria, SAR406 and WPS-2 were the most abundant bacterial phyla accounting for 72.0%, 9.1%, 5.6%, 4.9%, 2.8% and 1.1% of total bacterial 16S rRNA gene sequences, respectively. The rest 21 phyla each contributed to less than 1.0% of total bacterial abundance (Table S1, Fig. S2). Within proteobacterial community,

Bacterial community structures in the NSCS varied across space and over time. The relative abundance of Proteobacteria increased from estuarine station NM3 to oceanic station A0 in summer (Fig. 3), but showed no apparent spatial variation in winter. Within proteobacterial community, Alphaproteobacteria was the dominant class in all samples except A0S. A0S sample was dominated by Gammaproteobacteria (41.3%) and most Gammaproteobacteria in A0S could be further classified into family Moraxellaceae which was rare in other samples (33.8% of A0S reads, but only 0.2–0.7% in other samples). High abundances of Cyanobacteria occurred in estuarine, coastal and shelf waters in summer but in oceanic waters in January, which matched the results of FCM analysis. In coastal and oceanic waters whereby an adverse seasonal variation pattern was detected between the distributions of phyla SAR406, and phyla WPS-2 (Fig. 3). At the family level, niche differentiation of some bacteria could be observed. In coastal, shelf and basin waters, SAR11 cluster, ZA3612c (belong to order Oceanospirillales) and HTCC2188 (order Oceanospirillales) were more abundant in January, whereas the abundances of Rhodobacteraceae, Moraxellaceae, Erythrobacteraceae, Flammeovirgaceae, and Hyphomonadaceae were higher in August (Fig. 5). Some bacterial families such as Rhodobacteraceae, Flavaobacteriaceae, Synechococcus, OM60, Oceaospirilceae, SUP05, and Methylophilaceae, tended to prevailed in high nutrient estuarine and coastal water. In contrast, SAR11 cluster, Moraxellaceae, ZA3612c, and Idiomarinaceae represented a large percentage of bacterial community in oligotrophic oceanic waters (Fig. 5). Most of the Cyanobacteria sequences recovered from 10 samples were affiliated with Synechococcus and Prochlorococcus. Different from other samples which were dominated by PE type subcluster 5.1 clade II Synechococcus (represented by WH8109), station NM3S was dominated by PC type subcluster 5.2 Synechococcus, plastid of Amylax triacantha and Cyanobacterium sp. Prochlorococcus sequences could only be found in shelf and oceanic waters (A5, A1, A0, A10 and A11), and its relative abundance was higher in samples A5S and A10W than in other samples (Fig. 6). Similar to bacteria, major archaeal lineages also had different niche preferences. The abundance of Marine Group I generally exhibits a decreasing trend along the transect from estuary to open ocean, whereas Marine Group II vice versa (Fig. S3). Clusters of Marine group I varied spatially, while clusters of Marine group II varied seasonally. Marine group I cluster α and β dominated in the


101

Fig. 3. Relative abundances of archaea and bacteria phylogenetic groups in the NSCS; (A) archaea in summer, (B) archaea in winter, (C) bacterial in summer, and (D) bacterial in winter.

oceanic water and in estuarine and coastal waters, respectively. Marine group II cluster α prevailed in summer and was replaced by Marine group II cluster β in winter (Fig. 4). Bacterial and archaeal community diversity and richness were estimated using Shannon index and ACE index. Our results showed that archaeal community was less diverse than bacterial community in the NSCS (Table S1). The highest bacterial community diversity was recorded in A9 for both seasons, while the highest archaeal community diversity was found in A5 in summer and in A1 in winter. Bacterial community in estuarine, coastal and shelf waters was more diverse in summer, but in oceanic water it was more diverse in winter. Among all the samples, A9S had the highest bacterial and archaeal species richness. 3.5. Community similarity and correlations between communities and environmental variables Bacterial and archaeal community compositions were compared by the Libshuff analysis and similarity indices calculation. Paired comparisons between ten samples indicated that all prokaryotic communities were significantly different from each other (p o0.05). The dissimilarity values between bacterial communities ranged from 0.520 to 0.897, and between archaeal communities ranged from 0.018 to 0.997.

The UPGMA dendrogram showed that the bacterial community of the samples collected in August branched more closely to each other than those collected in January. Archaeal communities were separated into three groups. The first and second groups were formed by samples collected from shelf and oceanic waters in winter and summer, respectively, and the third group was formed by samples collected at estuarine and coastal stations (Fig. 7). Bacterial/archaeal communities in estuarine and coastal waters differed markedly from communities in shelf and oceanic waters. Amplitudes of seasonal variation of bacterial and archaeal communities gradually increased from estuary to open ocean. Comparing community variability with environmental conditions, bacterial community composition was most strongly correlated with the combination of NO−3 , PO3− 4 and Chl a (ρ ¼0.613), whereas archaeal community composition was most strongly correlated with the combination of NO−3 , temperature and salinity (ρ ¼ 0.754). Considering individual factors, the variable that yielded the highest correlation with bacterial (ρ ¼0.481) and archaeal (ρ ¼ 0.676) community compositions was NO−3 (Table 2). RDA analysis showed abundances of Flavobacteriaceae, Alterobacteriaceae, OM60, Oceanospirillaceae, SUP05, Cryomorphaceae, ZA3412c and Methylophilaceae were positively related to NO−3 , PO3− 4 and Chl a concentrations. Abundances of Moraxellaceae, Erythrobacteraceae, Flammeovirgaceae and Hyphomonadaceae were

102


Fig. 4. Neighbor-joining tree depicting major archaea lineages based on top 50 OTU representative sequences. Bootstrap analysis was conducted using 1000 replicates. Bootstrap values are shown for branches with 450% bootstrap support. Bar size indicates relative abundance of each OTU.

positively correlated with temperature, but negatively correlated with NO−3 , PO3− 4 and Chl a concentrations (Fig. S4).

4. Discussion 4.1. Seasonal and spatial variation of prokaryotic abundance and autotrophic pico-phytoplankton abundance in the NSCS The variation of the abundance of prokaryotic microorganisms in marine surface waters reflects broad environmental changes, such as nutrient conditions, temperature and organic matter contents (Gilbert et al., 2011). Consistent with previous studies (Yuan et al., 2011; Zhou et al., 2011), we found that the abundance of prokaryotic microorganisms was higher at high nutrient estuarine and coastal stations than at oceanic stations (Fig. 2). An opposite seasonal pattern of the abundance of prokaryotes was observed in estuarine and oceanic waters. A higher abundance of prokaryotic cells occurred in estuarine and coastal waters in the NSCS during summer (Fig. 2A), when river runoff was strong (Dong et al., 2004). However, in oceanic NSCS, higher prokaryotic abundance occurred in winter (Fig. 2A) when primary productivity was relatively high (Liu et al., 2013). The abundance and activity of prokaryotic cells are thought as one of the factors determining the carbon flux in estuarine and oceanic waters through the microbial carbon pump (Jiao et al., 2010a, 2010b). Their seasonal and spatial

variations could explain part of the spatio-temporal variation of carbon flux observed in the NSCS (Zhai et al., 2013). Marine autotrophic pico-prokaryotes Prochlorococcus and Synechococcus not only play an essential role in global primary production (Partensky et al., 1999b; Flombaum et al., 2013), but they are also an important part of marine food webs. Niche differentiation between Prochlorococcus and Synechococcus has been widely reported (Partensky et al., 1999a; Zwirglmaier et al., 2008). Prochlorococcus dominate in oligotrophic oceanic waters, while Synechococcus are widely distributed in global ocean and are highly abundant in nutrient-rich environments, such as coastal waters and upwelling regions. In this study, we found that Prochlorococcus were the main picophytoplankton group in oligotrophic shelf and oceanic waters, whereas Synechococcus were the major picophytoplankton group in coastal and estuarine waters. Interestingly, more than 1.7 105 cells mL 1 of Prochlorococcus was recorded at station A5 in summer; however, this organism was generally absent at nearby station A9. This result indicates that Prochlorococcus are restricted in the shelf and oceanic waters of the NSCS. Chen et al. suggested that high concentrations of nutrients and heavy metals might be one of the reasons for the absence of Prochlorococcus in estuary and coast in the NSCS (Chen et al., 2011). Nevertheless, further studies are needed to confirm which factors (biotic or abiotic factors) control the distribution of Prochlorococcus in the NSCS (Zwirglmaier et al., 2008). Seasonal variation of Synechococcus showed different pattern along the transect (Fig. 2B). In coastal waters influenced by Pearl


River plume, high abundance of Synechococcus occurred in summer, indicating temperature was the main factor controlling Synechococcus growth (Jing et al., 2009; Liu et al., 2014). In shelf, slope and oceanic waters, Synechococcus abundance was higher in winter than in summer, in contrary to the distribution pattern of Prochlorococcus (Fig. 2). Previous studies reported that the highest productivity in both the shelf and deep basin of the SCS occurs in

103

winter (Liu et al., 2002; Lee Chen, 2005). However, these studies might have underestimated the contribution of pico-phytoplankton as they only calculated the production of phytoplankton larger than 0.7 mm (the nominal retention size of GF/F filter) (Partensky et al., 1999b). Our study indicates that Synechococcus and Prochlorococcus are the most important primary producers in coastal and oceanic waters of NSCS, respectively, during summer.

Fig. 5. (A) Relative abundances of the most abundant bacterial families. (B) Comparison of bacteria families in summer and winter at each station (relative abundance of bacterial families in summer minus relative abundance in winter).

Fig. 6. Phylogenetic tree based on analysis of the representative 16S rRNA gene sequences of phylum Cyanobacteria. The tree was constructed using the neighbor-joining method in MEGA. Bootstrap analysis was conducted using 1000 replicates. Bootstrap values are shown for branches with 450% bootstrap support. Bar size indicates relative abundance of each OTU.

104


4.2. Seasonal and spatial variations of prokaryote community in the NSCS Spatial variation of bacterial community along environmental gradients from estuary to marine environments has been reported by several studies (Crump et al., 1999; Campbell and Kirchman, 2012; Ortega-Retuerta et al., 2012). However, few researches combined the studies of spatial pattern with temporal trend. To the best of our knowledge, this study is the first to investigate the spatiotemporal variation of bacterial and archaeal communities in the NSCS using high throughput sequencing method. Seasonality of bacterial communities in Pearl River estuary is modulated by the changes of freshwater discharge; while in the shelf and oceanic waters it is more related to the seasonal changes of ocean currents (Su, 2004). Although significant environmental changes occurred in estuarine waters between summer and winter (Fig. 1), the degree of seasonal variation of bacterial/archaeal communities decreased gradually from open ocean to estuary in

Fig. 7. UPGMA dendrogram showing relationship among bacterial (A) and archaeal (B) communities at 0.05 genetic distance in NSCS.

the NSCS (Fig. 7), in contrast to the finding in Delaware Estuary (Kirchman et al., 2005). This could be due to two reasons; (1) bacterial/archaeal community compositions were strongly correlated with the concentration of NO−3 in the NSCS (Table 2). As the concentration of NO−3 was high in estuary and coast it might not be limiting the growth of bacteria. In oligotrophic waters, however, NO−3 concentration was low and this could be a key limiting factor influencing the bacterial community. Therefore, bacterial community composition would undergo dramatic temporal shifts in relation to the seasonal variations in oceanic water. (2) Bacterial/archaeal community harbored in oceanic waters differed greatly from that in estuarine and coastal waters (Fig. 7), and the oceanic community could potentially be less resilient to changing environmental conditions. For example, SAR11 cluster lineages dominated in oceanic waters and showed apparent temporal variations in our study (Fig. 5). Previous studies suggested that SAR11 shows strong repeatable seasonal patterns that are related to the changes of primary production and DOC concentration (Eilers et al., 2001; Gilbert et al., 2011). However, we found that the abundance of the SAR11 lineages in the Pearl River estuary was low and their seasonal variation was also not remarkable in the NSCS (Fig. S5). We further found that the spatial variation of bacterial communities was more dynamic in summer than in winter. Spatial heterogeneity has been reported as an important factor which influences both the dynamics and the resistance of the bacterioplankton communities to changing environmental conditions (Yeo et al., 2013). During our summer cruise, a meso-scale cyclonic eddy and Kuroshio intrusion were recorded (Yuan et al., 2014). Coastal upwelling occurs frequently in the NSCS during summer (Xie et al., 2003). These processes could significantly influence phytoplankton and bacterial abundance (Chen et al., 2011; Yuan et al., 2011; Song et al., 2012). Our results suggest that physical processes like meso-scale eddies, advection of the Kuroshio Current and large fresh water discharge during summer could create a more complex environment and result in higher spatial dynamics of bacteria community. Comparing with the estuarine and oceanic waters, coastal waters often have the highest diversity of prokaryotes (Du et al., 2013; Gao et al., 2010). In agreement with that, we also found the highest diversity of bacterioplankton community in coastal waters of the NCSC in both summer and winter. We further found that rare species (o 0.1% reads of each sample) mainly contributed to this high diversity of bacterial community in coastal waters (Fig. S6). Certain rare species could be highly active and might be important as members of a seed bank of dormant bacteria waiting for suitable environmental conditions to grow (Sogin et al., 2006; Campbell et al., 2011). High numbers of rare species found in

Table 2 Pearson correlation coefficients between bacterial/archaeal communities and environmental variables. Combined environmental factors

Correlation coefficient

Variability explained

Single environmental factor

Correlation coefficient

Variability explained

0.167

Bacteria 3− NO− 3 , PO4 , Chl a , Chl a NO− 3

0.613

0.341

NO− 3

0.481

0.607

0.235

PO3− 4

0.453

0.172

NO− 3 , Chl a

0.547

0.24

Chl a

0.428

0.074

3− NO− 3 , PO4 , temperature, Chl a

0.484

0.605

Salinity

0.171

0.159

temperature Archaea NO− 3 , temperature, Salinity

0.483

0.447

Temperature

0.115

0.194

0.745

0.742

0.367

0.733

0.571

NO− 3 Salinity

0.676

NO− 3 , Chl a

0.503

0.378

PO3− 4 , temperature NO− 3 , temperature, salinity, Chl a

0.73

0.601

0.318

0.885

PO3− 4 Chl a

0.475

0.725

0.423

0.21

NO− 3,

PO3− 4 ,


coastal waters may explain why bacterial community shifted quickly in response to environment changes, but maintained in high abundance (Fig. 2). 4.3. Different niche preference of bacterial/archaeal lineages Previous studies showed that bacterial communities in estuarine waters are greatly different from communities in oceanic surface waters (Gilbert et al., 2009; Giovannoni and Vergin, 2012). At the family level, some major bacterial groups showed niche partition in estuarine, coastal and oceanic waters of the NSCS (Fig. 5A). Fortunato et al. suggested that freshwater SAR11, Oceanospirillales, and Flavobacteria groups can be the indicator taxa of estuary and plume environments, whereas SAR406 (A714017 in greengene phylogenies), SUP05, Prochlorococcus and SAR11 are the indicator taxa of coastal ocean environments (Fortunato et al., 2013). In the NSCS, we observed a similar distribution pattern of these indicator taxa (Figs. 4 and S4). Furthermore, we found that families OM60 and Methylophilaceae were potential indicators of estuarine and coastal waters, and Subcluster 5.2 Synechococcus could be the indicator of low salinity estuarine water (Figs. 4 and S4). High abundance of Synechococcus in estuarine and coastal waters in summer consisted of different Synechococcus lineages (Fig. 5). Subcluster 5.2 Synechococcus dominated in estuarine water, whereas subcluster 5.1 clade II Synechococcus dominated in coastal water. This result is in agreement with a previous study which suggests that PC type Synechococcus is more abundant in low salinity, but high nutrient environment, while PE type subcluster 5.1 clade II Synechococcus prevail in high temperature, high salinity and relatively low nutrient coastal waters (Liu et al., 2014). OM60 and Methylophilaceae were found to have high relative abundance in estuarine and coastal waters, demonstrating that they prefer to grow in highly productive environments (Giovannoni et al., 2008; Yan et al., 2009). Based on clone library and 454 pyrosequencing methods, previous studies indicated that marine Euryarchaeota ranges from 15% to 100% of total archaeal community in marine photic waters (Moeseneder et al., 2001; Bano et al., 2004; Galand et al., 2009; Yin et al., 2013). This group was also the most abundant archaea in the oceanic surface waters of the NSCS, ranging from 67.1% to 99.6% of total archaea. This group tends to enrich putative anaerobic respiration components and degrades organic matter through anaerobic pathways (Massana et al., 2000; Galand et al., 2009). High abundance of this archaea in the NSCS oceanic waters suggests that the surface waters of the NSCS are rich in organic matters and contain a wide distribution of oxygen-depleted microenvironments. Niche partitioning of marine Crenarchaeota across the water column was widely reported (Galand et al., 2009; Hu et al., 2011a, 2011b). Based on their niches, Crenarchaeota is further divided into two clusters as shallow cluster and deep cluster (Galand et al., 2009). A recent study in the SCS indicated that most Crenarchaeota are able to oxidize ammonia (Hu et al., 2011a). We found that there were different Crenarchaeota groups dominating in coastal and oceanic waters of NSCS. Crenarchaeota were more abundant in estuarine waters which indicates that their distribution is closely related to nutrient condition, in contrast to the finding in the Arctic Ocean (Galand et al., 2009). It has been reported that archaeal abundance varies with seasons and space (DeLong, 2003). However, studies on the seasonal variation of archaeal community in marine environments are limited (Murray et al., 1998; Bano et al., 2004; Herfort et al., 2007). In this study, we found apparent seasonal fluctuation in the abundance of different archaeal clusters in Marine Group II the dominant archaeal group in oceanic surface water. Cluster α, which mainly contains sequences from surface waters, tended to peak in summer, while cluster β composed of sequences from

105

surface and deep waters, peaked in winter (Massana et al., 2000). Seasonal variation of different phylogenetic clusters in Marine group II supports the view that there are niche differences in closely related groups in Marine Group II (Lincoln et al., 2014). Comparing with Marine Group II archaea, Marine Group I archaea, which was abundant in estuarine and coastal waters, did not show apparent patterns of seasonal variation. This could be the reason for the high degree of difference in seasonal variation between estuarine and coastal archaeal community and oceanic archaeal community.

5. Conclusions This study demonstrates that bacterial and archaeal communities varied along the transect from eutrophic river plume to oligotrophic open ocean in the NSCS, and their distribution patterns were different between summer and winter seasons. Bacterial communities in estuarine water differed remarkably from communities in oceanic water. Autotrophic picocyanobacteria Synechococcus and Prochlorococcus showed niche differentiation, with Synechococcus abundant in coastal and estuarine waters in summer and Prochlorococcus more abundant in oceanic water. Subcluster 5.1 clade II Synechococcus dominated in coastal water, while subcluster 5.2 Synechococcus dominated in estuarine water. Euryarchaeota was the dominant archaea in the oceanic surface water, whereas Crenarchaeota was more abundant in estuarine and coastal waters. Moreover, abundance of two clusters of Marine Group II archaea, which was dominant in oceanic surface waters, varied between different seasons. We also found that the seasonal variations of archaeal and bacterial communities were more dynamic in shelf and basin waters than in coastal and estuarine waters. Some bacterial species could be the indicator taxa of specific environments, such as SUP05 and OM60. The next step is to confirm whether the observed seasonal and spatial pattern of bacterial/archaeal communities in the NSCS surface water is stable and predictable.

Acknowledgments We thank Liangliang Kong for collecting the DNA samples and Bingzhang Chen for analyzing the FCM samples. This study was supported by the National Basic Research Program (“973” Program) of China through Grant no. 2009CB421203 and the Research Grants Council of Hong Kong RGF Grants (661912 and 661813) provided to H. Liu.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.dsr2.2015.05.016.

References Alonso-Sáez, L., Andersson, A., Heinrich, F., Bertilsson, S., 2011. High archaeal diversity in Antarctic circumpolar deep waters. Environ. Microbiol. Rep. 3, 689–697. Azam, F., 1998. Microbial control of oceanic carbon flux: the plot thickens. Science 280, 694–695. Bano, N., Ruffin, S., Ransom, B., Hollibaugh, J.T., 2004. Phylogenetic composition of Arctic Ocean archaeal assemblages and comparison with Antarctic assemblages. Appl. Environ. Microbiol. 70, 781–789. Campbell, B.J., Kirchman, D.L., 2012. Bacterial diversity, community structure and potential growth rates along an estuarine salinity gradient. ISME J. 7, 210–220.

106


Campbell, B.J., Yu, L., Heidelberg, J.F., Kirchman, D.L., 2011. Activity of abundant and rare bacteria in a coastal ocean. Proc. Natl. Acad. Sci. 108, 12776–12781. Chen, B., Wang, L., Song, S., Huang, B., Sun, J., Liu, H., 2011. Comparisons of picophytoplankton abundance, size, and fluorescence between summer and winter in Northern South China Sea. Cont. Shelf Res. 31, 1527–1540. Chen, B., Liu, H., Huang, B., 2012. Environmental controlling mechanisms on bacterial abundance in the South China Sea inferred from generalized additive models (GAMs). J. Sea Res. 72, 69–76. Crump, B.C., Armbrust, E.V., Baross, J.A., 1999. Phylogenetic analysis of particleattached and free-living bacterial communities in the Columbia River, its estuary, and the adjacent coastal ocean. Appl. Environ. Microbiol. 65, 3192–3204. Curtis, T.P., Sloan, W.T., Scannell, J.W., 2002. Estimating prokaryotic diversity and its limits. Proc. Natl. Acad. Sci. 99, 10494–10499. DeLong, E.F., 1992. Archaea in coastal marine environments. Proc. Natl. Acad. Sci. 89, 5685–5689. DeLong, E.F., 2003. Oceans of archaea. ASM News – Am. Soc. Microbiol. 69, 503. DeLong, E.F., Pace, N.R., 2001. Environmental diversity of bacteria and archaea. Syst. Biol. 50, 470–478. DeLong, E.F., Wu, K.Y., Prézelin, B.B., Jovine, R.V., 1994. High abundance of archaea in Antarctic marine picoplankton. Nature 371, 695–697. Dillon, J.G., McMath, L.M., Trout, A.L., 2009. Seasonal changes in bacterial diversity in the Salton Sea. Hydrobiologia 632, 49–64. Dong, L., Su, J., Ah Wong, L., Cao, Z., Chen, J.-C., 2004. Seasonal variation and dynamics of the Pearl River plume. Cont. Shelf Res. 24, 1761–1777. Du, J., Xiao, K., Li, L., Ding, X., Liu, H., Lu, Y., Zhou, S., 2013. Temporal and spatial diversity of bacterial communities in coastal waters of the South China Sea. PloS One 8, e66968. Eilers, H., Pernthaler, J., Peplies, J., Glöckner, F.O., Gerdts, G., Amann, R., 2001. Isolation of novel pelagic bacteria from the German Bight and their seasonal contributions to surface picoplankton. Appl. Environ. Microbiol. 67, 5134–5142. Flombaum, P., Gallegos, J.L., Gordillo, R.A., Rincón, J., Zabala, L.L., Jiao, N., Karl, D.M., Li, W.K., Lomas, M.W., Veneziano, D., 2013. Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. Proc. Natl. Acad. Sci. 110, 9824–9829. Fortunato, C.S., Eiler, A., Herfort, L., Needoba, J.A., Peterson, T.D., Crump, B.C., 2013. Determining indicator taxa across spatial and seasonal gradients in the Columbia River coastal margin. ISME J. 7, 1899–1911. Fortunato, C.S., Herfort, L., Zuber, P., Baptista, A.M., Crump, B.C., 2012. Spatial variability overwhelms seasonal patterns in bacterioplankton communities across a river to ocean gradient. ISME J. 6, 554–563. Fuhrman, J., 1992. Bacterioplankton roles in cycling of organic matter: the microbial food web. In: Falkowski, Paul G., Woodhead, Avril D., Vivirito, Katherine (Eds.), Primary Productivity and Biogeochemical Cycles in the Sea. Springer, New York, pp. 361–383. Galand, P.E., Casamayor, E.O., Kirchman, D.L., Potvin, M., Lovejoy, C., 2009. Unique archaeal assemblages in the Arctic Ocean unveiled by massively parallel tag sequencing. ISME J. 3, 860–869. Gantner, S., Andersson, A.F., Alonso-Sáez, L., Bertilsson, S., 2011. Novel primers for 16S rRNA-based archaeal community analyses in environmental samples. J. Microbiol. Methods 84, 12–18. Gao, Z., Johnson, Z.I., Wang, G., 2010. Molecular characterization of the spatial diversity and novel lineages of mycoplankton in Hawaiian coastal waters. ISME J. 4, 111–120. Gilbert, J.A., Field, D., Swift, P., Newbold, L., Oliver, A., Smyth, T., Somerfield, P.J., Huse, S., Joint, I., 2009. The seasonal structure of microbial communities in the Western English Channel. Environ. Microbiol. 11, 3132–3139. Gilbert, J.A., Steele, J.A., Caporaso, J.G., Steinbrück, L., Reeder, J., Temperton, B., Huse, S., McHardy, A.C., Knight, R., Joint, I., 2011. Defining seasonal marine microbial community dynamics. ISME J. 6, 298–308. Giovannoni, S.J., Hayakawa, D.H., Tripp, H.J., Stingl, U., Givan, S.A., Cho, J.C., Oh, H.M., Kitner, J.B., Vergin, K.L., Rappé, M.S., 2008. The small genome of an abundant coastal ocean methylotroph. Environ. Microbiol. 10, 1771–1782. Giovannoni, S.J., Vergin, K.L., 2012. Seasonality in ocean microbial communities. Science 335, 671–676. Herfort, L., Schouten, S., Abbas, B., Veldhuis, M.J., Coolen, M.J., Wuchter, C., Boon, J.P., Herndl, G.J., Sinninghe Damsté, J.S., 2007. Variations in spatial and temporal distribution of Archaea in the North Sea in relation to environmental variables. FEMS Microbiol. Ecol. 62, 242–257. Hollibaugh, J.T., Gifford, S.M., Moran, M.A., Ross, M.J., Sharma, S., Tolar, B.B., 2013. Seasonal variation in the metratranscriptomes of a Thaumarchaeota population from SE USA coastal waters. ISME J. 8, 685–698. Hu, A., Jiao, N., Zhang, C.L., 2011a. Community structure and function of planktonic Crenarchaeota: changes with depth in the South China Sea. Microb. Ecol. 62, 549–563. Hu, A., Jiao, N., Zhang, R., Yang, Z., 2011b. Niche partitioning of marine group I Crenarchaeota in the euphotic and upper mesopelagic zones of the East China Sea. Appl. Environ. Microbiol. 77, 7469–7478. Jamieson, R.E., Rogers, A.D., Billett, D.S.M., Smale, D.A., Pearce, D.A., 2012. Patterns of marine bacterioplankton biodiversity in the surface waters of the Scotia Arc, Southern Ocean. FEMS Microbiol. Ecol. 80, 452–468. Jiao, N., Herndl, G.J., Hansell, D.A., Benner, R., Kattner, G., Wilhelm, S.W., Kirchman, D.L., Weinbauer, M.G., Luo, T., Chen, F., 2010a. Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. Nat. Rev. Microbiol. 8, 593–599.

Jiao, N., Tang, K., Cai, H., Mao, Y., 2010b. Increasing the microbial carbon sink in the sea by reducing chemical fertilization on the land. Nat. Rev. Microbiol. 9, 75. Jing, H., Zhang, R., Pointing, S.B., Liu, H., Qian, P., 2009. Genetic diversity and temporal variation of the marine Synechococcus community in the subtropical coastal waters of Hong Kong. Can. J. Microbiol. 55, 311–318. Karner, M.B., DeLong, E.F., Karl, D.M., 2001. Archaeal dominance in the mesopelagic zone of the Pacific Ocean. Nature 409, 507–510. Kirchman, D.L., Dittel, A.I., Malmstrom, R.R., Cottrell, M.T., 2005. Biogeography of major bacterial groups in the Delaware Estuary. Limnol. Oceanogr. 50, 1697–1706. Kirchman, D.L., Keel, R.G., Simon, M., Welschmeyer, N.A., 1993. Biomass and production of heterotrophic bacterioplankton in the oceanic subarctic Pacific. Deep Sea Res. Part I: Oceanogr. Res. Pap. 40, 967–988. Kong, L., Jing, H., Kataoka, T., Sun, J., Liu, H., 2011. Phylogenetic diversity and spatiotemporal distribution of nitrogenase genes (nifH) in the northern South China Sea. Aquat. Microb. Ecol. 65, 15–27. Lee Chen, Yl, 2005. Spatial and seasonal variations of nitrate-based new production and primary production in the South China Sea. Deep Sea Res. Part I: Oceanogr. Res. Pap. 52, 319–340. Letunic, I., Bork, P., 2007. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 23, 127–128. Lincoln, S.A., Wai, B., Eppley, J.M., Church, M.J., Summons, R.E., DeLong, E.F., 2014. Planktonic Euryarchaeota are a significant source of archaeal tetraether lipids in the ocean. Proc. Natl. Acad. Sci. 111, 9858–9863. Liu, F., Tang, S., Chen, C., 2013. Impact of nonlinear mesoscale eddy on phytoplankton distribution in the northern South China Sea. J. Mar. Syst. 123, 33–40. Liu, H., Jing, H., Wong, T.H., Chen, B., 2014. Co‐occurrence of phycocyanin‐and phycoerythrin‐rich Synechococcus in subtropical estuarine and coastal waters of Hong Kong. Environ. Microbiol. Rep. 6, 90–99. Liu, K.K., Chao, S.Y., Shaw, P.T., Gong, G.C., Chen, C.C., Tang, T., 2002. Monsoon-forced chlorophyll distribution and primary production in the South China Sea: observations and a numerical study. Deep Sea Res. Part I: Oceanogr. Res. Pap. 49, 1387–1412. Massana, R., DeLong, E.F., Pedrós-Alió, C., 2000. A few cosmopolitan phylotypes dominate planktonic archaeal assemblages in widely different oceanic provinces. Appl. Environ. Microbiol. 66, 1777–1787. Massana, R., Murray, A.E., Preston, C.M., DeLong, E.F., 1997. Vertical distribution and phylogenetic characterization of marine planktonic Archaea in the Santa Barbara Channel. Appl. Environ. Microbiol. 63, 50–56. Moeseneder, M., Winter, C., Arrieta, J., Herndl, G., 2001. Terminal-restriction fragment length polymorphism (T-RFLP) screening of a marine archaeal clone library to determine the different phylotypes. J. Microbiol. Methods 44, 159–172. Mou, X., Sun, S., Edwards, R.A., Hodson, R.E., Moran, M.A., 2008. Bacterial carbon processing by generalist species in the coastal ocean. Nature 451, 708–711. Murray, A., Preston, C., Massana, R., Taylor, L., Blakis, A., Wu, K., DeLong, E., 1998. Seasonal and spatial variability of bacterial and archaeal assemblages in the coastal waters near Anvers Island, Antarctica. Appl. Environ. Microbiol. 64, 2585–2595. Ortega-Retuerta, E., Joux, F., Jeffrey, W.H., Ghiglione, J.-F., 2012. Spatial variability of particle-attached and free-living bacterial diversity in surface waters from the Mackenzie River to the Beaufort Sea (Canadian Arctic). Biogeosci. Discuss. 9, 17401–17435. Partensky, F., Blanchot, J., Vaulot, D., 1999a. Differential distribution and ecology of Prochlorococcus and Synechococcus in oceanic waters: a review. Bull. Inst. Oceanogr. Monaco 19, 457–476. Partensky, F., Hess, W., Vaulot, D., 1999b. Prochlorococcus, a marine photosynthetic prokaryote of global significance. Microbiol. Mol. Biol. Rev. 63, 106–127. Pedrós-Alió, C., 2006. Marine microbial diversity: can it be determined? Trends Microbiol. 14, 257–263. Platt, T., Rao, D.S., Irwin, B., 1983. Photosynthesis of picoplankton in the oligotrophic ocean. Nature 301, 702–704. Riemann, L., Leitet, C., Pommier, T., Simu, K., Holmfeldt, K., Larsson, U., Hagström, Å., 2008. The native bacterioplankton community in the central Baltic Sea is influenced by freshwater bacterial species. Appl. Environ. Microbiol. 74, 503–515. Ruiz-González, C., Lefort, T., Martí, G., Montserrat Sala, M., Sommaruga, R., Simó, R., Gasol, J.M., 2011. Seasonal patterns in the sunlight sensitivity of bacterioplankton from Mediterranean surface coastal waters. FEMS Microbiol. Ecol. 79, 661–674. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541. Sogin, M.L., Morrison, H.G., Huber, J.A., Welch, D.M., Huse, S.M., Neal, P.R., Arrieta, J. M., Herndl, G.J., 2006. Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc. Natl. Acad. Sci. 103, 12115–12120. Song, X., Lai, Z., Ji, R., Chen, C., Zhang, J., Huang, L., Yin, J., Wang, Y., Lian, S., Zhu, X., 2012. Summertime primary production in northwest South China Sea: interaction of coastal eddy, upwelling and biological processes. Cont. Shelf Res. 48, 110–121. Su, J., 2004. Overview of the South China Sea circulation and its influence on the coastal physical oceanography outside the Pearl River Estuary. Cont. Shelf Res. 24, 1745–1760.


Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599. Winter, C., Kerros, M.E., Weinbauer, M.G., 2009. Seasonal changes of bacterial and archaeal communities in the dark ocean: evidence from the Mediterranean Sea. Limnol. Oceanogr. 54, 160. Xie, S.P., Xie, Q., Wang, D., Liu, W.T., 2003. Summer upwelling in the South China Sea and its role in regional climate variations. J. Geophys. Res. – Ocean. (1978– 2012) 108, 3261. Yan, S., Fuchs, B.M., Lenk, S., Harder, J., Wulf, J., Jiao, N.Z., Amann, R., 2009. Biogeography and phylogeny of the NOR5/OM60 clade of Gammaproteobacteria. Syst. Appl. Microbiol. 32, 124–139. Yeo, S.K., Huggett, M.J., Eiler, A., Rappé, M.S., 2013. Coastal bacterioplankton community dynamics in response to a natural disturbance. PloS One 8, e56207. Yin, Q., Fu, B., Li, B., Shi, X., Inagaki, F., Zhang, X.-H., 2013. Spatial variations in microbial community composition in surface seawater from the ultra-oligotrophic center to rim of the South Pacific Gyre. PloS One 8, e55148. Yu, Y., Lee, C., Kim, J., Hwang, S., 2005. Group-specific primer and probe sets to detect methanogenic communities using quantitative real-time polymerase chain reaction. Biotechnol. Bioeng. 89, 670–679.

107

Yuan, X., He, L., Yin, K., Pan, G., Harrison, P.J., 2011. Bacterial distribution and nutrient limitation in relation to different water masses in the coastal and northwestern South China Sea in late summer. Cont. Shelf Res. 31, 1214–1223. Yuan, Y., Liao, G., Yang, C., Liu, Z., Chen, H., Wang, Z.-G., 2014. Summer Kuroshio Intrusion through the Luzon Strait confirmed from observations and a diagnostic model in summer 2009. Prog. Oceanogr. 121, 44–59. Zhai, W.D., Dai, M.H., Chen, B.S., Guo, X.H., Li, Q., Shang, S.L., Zhang, C.Y., Cai, W.J., Wang, D.X., 2013. Seasonal variations of sea–air CO2 fluxes in the largest tropical marginal sea (South China Sea) based on multiple-year underway measurements. Biogeosciences 10, 7775–7791. Zhou, W., Long, A., Jiang, T., Chen, S., Huang, L., Huang, H., Cai, C., Yan, Y., 2011. Bacterioplankton dynamics along the gradient from highly eutrophic Pearl River Estuary to oligotrophic northern South China Sea in wet season: implication for anthropogenic inputs. Mar. Pollut. Bull. 62, 726–733. Zwirglmaier, K., Jardillier, L., Ostrowski, M., Mazard, S., Garczarek, L., Vaulot, D., Not, F., Massana, R., Ulloa, O., Scanlan, D.J., 2008. Global phylogeography of marine Synechococcus and Prochlorococcus reveals a distinct partitioning of lineages among oceanic biomes. Environ. Microbiol. 10, 147–161.