Skip to main content
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About AEM
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
Applied and Environmental Microbiology
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Archive
    • Minireviews
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About AEM
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
Environmental Microbiology

A Long-Standing Complex Tropical Dipole Shapes Marine Microbial Biogeography

Wei Yan, Rui Zhang, Nianzhi Jiao
Shuang-Jiang Liu, Editor
Wei Yan
aState Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Institute of Marine Microbes and Ecospheres, Xiamen University, Xiamen, People's Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Wei Yan
Rui Zhang
aState Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Institute of Marine Microbes and Ecospheres, Xiamen University, Xiamen, People's Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nianzhi Jiao
aState Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Institute of Marine Microbes and Ecospheres, Xiamen University, Xiamen, People's Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shuang-Jiang Liu
Chinese Academy of Sciences
Roles: Editor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/AEM.00614-18
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

ABSTRACT

Microbial population size, production, diversity, and community structure are greatly influenced by the surrounding physicochemical conditions, such as large-scale biogeographic provinces and water masses. An oceanic mesoscale dipole consists of a cyclonic eddy and an anticyclonic eddy. Dipoles occur frequently in the ocean and usually last from a few days to several months; they have significant impacts on local and global oceanic biological, ecological, and geochemical processes. To better understand how dipoles shape microbial communities, we examined depth-resolved distributions of microbial communities across a dipole in the South China Sea. Our data demonstrated that the dipole had a substantial influence on microbial distributions, community structure, and functional groups both vertically and horizontally. Large alpha and beta diversity differences were observed between anticyclonic and cyclonic eddies in surface and subsurface layers, consistent with distribution changes of major bacterial groups in the dipole. The dipole created uplift, downward transport, enrichment, depletion, and horizontal transport effects. We also found that the edge of the dipole might induce strong subduction, indicated by the presence of Prochlorococcus and Synechococcus in deep waters. Our findings suggest that dipoles, with their unique characteristics, might act as a driver for microbial community dynamics.

IMPORTANCE Oceanic dipoles, which consist of a cyclonic eddy and an anticyclonic eddy together, are among the most contrasted phenomena in the ocean. Dipoles generate strong vertical mixing and horizontal advection, inducing biological responses. This study provides vertical profiles of microbial abundance, diversity, and community structure in a mesoscale dipole. We identify the links between the physical oceanography and microbial oceanography and demonstrate that the dipole, with its unique features, could act as a driver for microbial community dynamics, which may have large impacts on both the local and global marine biogeochemical cycles.

INTRODUCTION

It is well known that microorganisms play a key role in marine ecosystem and biogeochemical cycles. Understanding the mechanisms generating and maintaining the distribution and diversity of microbes is crucial to elucidate their ecological and biogeochemical function. Microbial population size, activity, diversity, and community structure are greatly influenced by the biotic and abiotic factors. In the ocean, hydrographic conditions are main abiotic determinants in the biogeographic patterns of marine microorganisms. Previous studies found that the microbial community structures are strongly correlated with large-scale biogeographic provinces (1) and water mass movements (2, 3). Microorganisms impacted by chemical and physical conditions of different water masses result in microbial assemblages with different diversities and activities (4, 5). Besides large-scale oceanic processes, mesoscale oceanic processes, such as eddies, are ubiquitous and play an important role in both local and global hydrography and biogeochemistry (6, 7). Mesoscale eddies enhance both vertical and horizontal mixing of different water masses, resulting in profound implications of marine microbial community and subsequent biogeochemical cycle. Cyclonic eddies (CEs; also called cold eddies), which dome the pycnocline, are well-known mechanisms that pump nutrients from depth up into the surface ocean, increasing chlorophyll concentrations and new production (7, 8). Current estimates indicate that eddy-induced nutrient fluxes support nearly half of new primary production globally (8). Anticyclonic eddies (AEs; also called warm eddies), which depress the density interface, tend to decrease the nutrient content (9) and accumulate organic matter inside their cores (10) that increases microbial respiration (11) and heterotrophic production (12, 13). In addition, eddies can also enhance the horizontal advection of water and associated bacterioplankton (14). In the future, eddy activity might be greatly elevated with increasing global warming (15, 16), buffering the surface stratification effect and resulting in profound implications for marine biogeochemistry. However, little is known about how the microbial community structure is influenced by mesoscale or submesoscale oceanic processes (13, 17, 18), which has hampered a comprehensive understanding of their ecological and biogeochemical importance.

A unique kind of eddy pair is a dipole, which consists of a CE and an AE together and is among the most contrasted phenomena in the ocean. Dipoles have subsequent eddy-eddy interactions that can generate submesoscale structures like fronts, jets, and filaments, which have strong vertical and horizontal advection, inducing biological responses (9, 19, 20). The South China Sea (SCS) in the western Pacific Ocean, characterized by the relatively frequent passage of eddies (21), is one of the largest marginal seas in the world. During the southwesterly monsoon period, the circulation in the southwestern SCS is often governed by a dipole, which consists of an AE in the south, a CE in the north, and a coastal jet sandwiched by the two eddies (22, 23). The cyclonic part of this long-lasting dipole system has been shown to have a large impact on the regional biogeochemical cycle (22, 24). The aim of our research was to explore the distribution and diversity of bacterial communities in this special dipole system. We hypothesized that dipoles, with their unique physical features, could function as a driver for the microbial community dynamics in surface, subsurface, and deep ocean waters.

RESULTS

Physical and microbial characteristics of the dipole.Satellite altimetry recorded the formation and evolution of a cyclonic-anticyclonic dipole system in the southwestern SCS in the summer of 2011, which concurred with the sampling in this study (Fig. 1; see detailed dipole evolution in Fig. S1 in the supplemental material). The CE of the dipole exhibited a negative sea level anomaly (SLA) of 15 cm and had a diameter of ∼150 km. The AE of the dipole had a positive SLA of 30 cm and a radius of ∼190 km. Between the CE and AE, there was a coastal jet that flowed northeastward and formed the dipole recirculation pattern. In this study, the eddy core was defined as within 20 km of the eddy core, which was the point of minimum/maximum velocity determined by SLA. The eddy edge was defined as at least 40 km from the eddy core. Eighteen stations were sampled for microbial parameters, including seven representative stations for detailed microbial diversity analysis. Two stations were located at the core (S71) and at the edge (S74) of the CE, and two others were located in the AE (S88 in the core; S81 at the edge). Between the two eddies, two stations (S84 and S85) were selected to represent the jet. A reference site, S101, did not experience any the influence from the dipole. We also defined our sampling depths as the surface layer (water depth of 0 to 75 m), subsurface (100 to 300 m), the mesopelagic layer (400 to 1,000 m), and the deep layer (>1,000 m).

FIG 1
  • Open in new tab
  • Download powerpoint
FIG 1

Sea level anomalies in the research area of the southwestern South China Sea. Shown are a surface map (A), a detailed sea level anomaly (SLA) map (B), and derived surface currents (C). The 36 stations are marked by colored dots: 7 study sites analyzed in detail (yellow), 19 flow cytometry sites (yellow and black), and 17 CTD-only sites (open dots). Cyclonic features are shown in blue and anticyclonic features in red. Maps of the sea surface anomalies and derived surface currents were produced by AVISO. S88, anticyclonic eddy core; S81, anticyclonic eddy edge; S85, jet edge; S84, jet core; S74, cyclonic eddy edge; S71, cyclonic eddy core.

The temperature field in the dipole and surrounding water showed large differences induced by the dipole (Fig. 2, left; see also Fig. S2A). In the 5-m depth, the dipole was covered with homogeneous water with relatively high temperature. From 25 m to 200 m, the CE and AE showed substantial differences in temperature, with the largest difference observed at 50 to 150 m. For example, the eddy cores showed nearly 10°C difference at 50 m and 75 m. Below 200 m, this difference decreased, but it was still visible at 500 m. The salinity distribution was similar to temperature, except that the surface water salinity was moderated by coastal water intrusion (Fig. 2, middle; see also Fig. S2B).

FIG 2
  • Open in new tab
  • Download powerpoint
FIG 2

Three-dimensional structures of temperature (°C) (left), salinity (middle), and fluorescence (right) distributions from the surface to 500 m water depth in the dipole in early September 2011.

In the surface layers (0 to 75 m), relatively high chlorophyll fluorescence was found in the jet and CE, with the highest value observed at the edge of the CE (Fig. 2, right; see also Fig. S3), which was consistent with the distributions of Synechococcus, picoeukaryotes, and heterotrophic bacterioplankton (Fig. 3). In contrast, Prochlorococcus displayed low abundance in the jet and cyclonic core but high abundance in the AE (Fig. 3). In the subsurface layers (100 to 300 m), relatively high concentrations of chlorophyll, autotrophs (Synechococcus and Prochlorococcus), and heterotrophic bacterioplankton were present in the AE and jet, particularly at the edge of these mesoscale structures (Fig. 3), indicating a subduction of biomass from surface to subsurface layers.

FIG 3
  • Open in new tab
  • Download powerpoint
FIG 3

Picoplankton distribution from the surface to a 200-m water depth in the dipole in early September 2011, as determined by flow cytometry. Abundances of heterotrophic bacterioplankton, Prochlorococcus, Synechococcus, and picoeukaryotes (cells per milliliter) are shown.

Bacterial alpha diversity responses to the dipole.About 1.2 million raw sequences were obtained for the 89 libraries from seven stations that targeted the dipole cores and edges, the jet, and a reference site (see Fig. 1 for detailed sampling locations). A total of 616,338 reads passed the quality filters with a mean read length of ∼370 bp and an average sample size of 6,925 sequences. To minimize the sequencing noise and control the variations between samples, we excluded singletons and normalized all samples with the minimal library size. This step resulted in 3,333 sequences per sample, which was sufficient to capture most of the alpha and beta diversities in water samples (25). A total of 296,637 high-quality sequences were grouped into 7,745 operational taxonomic units (OTUs) with a cutoff at 97% sequence similarity.

Alpha diversity was estimated using the Shannon index, observed species, Chao1, and phylogenetic distance (PD) in this study. The Shannon diversity index measures both OTU richness and evenness and ranged from 4.23 to 8.15 (Fig. 4; see also Table S1). The number of OTUs varied substantially, from 203 to 849 per sample (Fig. S4 and Table S2). The Chao1 metric (26) in each sample ranged from 238 to 1,726 (Table S3), and the PD (27) ranged from 19.21 to 51.86 (Table S4). All diversity indices showed similar distribution patterns: (i) in the surface water (0 to 75 m), high diversities were found at the edge of the eddies and jet, while relative low diversities were found at the core of the CE and the jet; (ii) in subsurface waters (100 to 300 m), the AE core (S88) showed significantly higher diversities than the CE core (S71) (Shannon index and observed species; P < 0.05; n = 4; two-sample t test). We also observed increased diversity in the mesopelagic and deep layers of the AE and jet compared with the reference site and CE, indicating that the dipole induced diversities reached deep waters.

FIG 4
  • Open in new tab
  • Download powerpoint
FIG 4

Distribution of the Shannon diversity index in the dipole of the South China Sea from the surface to a 2,000-m water depth.

Community structure differentiation induced by the dipole.Beta diversity was estimated with a weighted UniFrac distance matrix, which accounted for both abundance and phylogenetic distance of OTU (28). The 89 samples were divided into several major clusters showing distinct depth-related bacterial communities (Fig. 5). The bacterial communities of the AE core and jet edge (e.g., stations S88 at 75 m and 100 m and S85 at 300 m and 1,000 m) were similar to those of shallower depths at other sites (Fig. 5). This suggested that the dynamics of the bacterial community were consistent with the physical displacement of surface waters to the subsurface within the AE core. In contrast, the bacterial communities within the CE core (e.g., S71 at 100 m, 150 m, and 200 m) were most similar to those in deeper depths at other sites (Fig. 5), suggesting that those community variations track the physical displacement of mesopelagic waters into the subsurface. Samples from the coastal jet-related stations (e.g., S84 at the surface, 50 m, and 75 m and S85 at 50 m) clustered into a subgroup (Fig. 5), indicating the influence of the surface coastal jet current that might directly transport the coastal bacterial community into the open ocean. Most mesopelagic samples from the jet and AE edge stations clustered with samples from the subsurface layers of other sites (Fig. 5), indicating a deeper impact on the mesopelagic bacterial community.

FIG 5
  • Open in new tab
  • Download powerpoint
FIG 5

Heat map for the relative abundances of the 69 most abundant operational taxonomic units across all samples. Hierarchical clustering was generated from UniFrac community phylogenetic distances between samples. The heat map shows the log abundance (log [observations + 1]) for each OTU. Samples are labeled according to station number and depth and colored-coded: red, anticyclonic eddy; blue, cyclonic eddy; green, jet; white, reference site. Nodes with filled circles represent >50% jackknife support.

Major bacterial group responses within the dipole.We selected the 69 most abundant OTUs, representing 60% of the sequences from the entire data set, for further analysis (Fig. 5). The most abundant OTU across all libraries was assigned to Prochlorococcus. Notably, we observed substantial amounts of Prochlorococcus and Synechococcus sequences in the mesopelagic/deep samples from S84 and S85 (Fig. 5; see also Fig. S5), as those two stations are located at the edge of the AE and were influenced by the jet current. Besides the similar abundance patterns of Prochlorococcus and Synechococcus revealed by flow cytometry, we also observed changes of their community at the ecotype level. Clustering analysis using 98% similarity separated Prochlorococcus into high-light (HL; surface) and low-light (LL; subsurface) ecotypes. Samples from 150-m layer of S85 showed a high abundance of HL Prochlorococcus (Fig. S5 and S6), indicating subduction from the surface layer into the subsurface in the jet (S85 was defined as jet edge but also near the edge of the AE). Two OTUs (OTU ID no. 2536 and 19494) from the SAR11 clade showed high similarity to sequences from surface waters of the Red Sea and presented an enrichment and downward transport pattern in the surface and subsurface waters of the AE core and a depleted pattern in the CE core and jet (Fig. 5). In contrast, other OTUs (ID no. 996, 14180, 17667, 13465, and 9875) from the SAR11 showed high similarity to sequences from the mesopelagic waters of the Hawaii Ocean Time series (HOTs) station ALOHA (29); this presented an uplifted pattern, and these OTUs were relatively enriched near the subsurface in the CE (Fig. 5).

There were 11 OTUs that belong to Rhodobacterales. The surface group OTUs (ID no. 17300, 5311, and 12073) showed the highest abundance in the surface layers of most stations and in the subsurface of the AE core (e.g., S88 at 100 m), exhibiting a downward transport pattern (Fig. 5). The deep-group OTUs (ID no. 13984, 1347, 14414, 11432, 13899, 9765, 13420, and 20496) showed relatively high abundances in the mesopelagic and deep layers but also an uplifted pattern in the CE core (Fig. 5). The Flavobacteriia group, which usually proliferate in coastal regions (30), had the highest abundances in samples from jet-influenced stations. For example, OTU ID no. 2262, which showed high similarity to sequences from the surface of coastal waters (31), also had a high abundance in the jet stations (Fig. 5), indicating that coastal OTUs might be horizontally transported by the strong coastal jet current (2 to 5 knots [Fig. 1C]) into the open ocean. SAR324 (OTU ID no. 14670 and 20842) and SAR406 (OTU ID no. 6166, 1189, 7531, and 165) both have a typical deep-water lifestyle (32–35) and showed an uplifted pattern in the CE core (Fig. 5).

Bacterial functional potential within the dipole.The predicted bacterial functional groups showed distribution patterns corresponding to the distributions of OTUs. The abundance of photoautotrophic groups decreased with depth (Fig. 6; see also Fig. S8), which was consistent with the distribution of Prochlorococcus and Synechococcus. The functional profiles also revealed that the dipole had great influence on the functional groups. Intriguingly, the chemoheterotrophic and hydrocarbon degradation groups increased at the subsurface layer (150 m) of the jet edge (S85), implying that the export of POC and DOC in this region may stimulate heterotrophic bacterial activity. It is worth noting that in the subsurface layer (150 m), nitrification groups slightly increased at the CE core (S71) and edge (S74) but significantly decreased at the AE core (S88), edge (S81), and jet edge (S85) (P < 0.05; one-sample t test; n = 3; null hypothesis was set as the value of the reference site [S101]) (Fig. 6 and S8).

FIG 6
  • Open in new tab
  • Download powerpoint
FIG 6

Heat map for predicted functional groups in the upper 500-m water columns. Samples are labeled according to station number and depth and colored-coded as in Fig. 5. Hierarchical clustering was generated from the Bray-Curtis distance between samples.

DISCUSSION

Our study obtained vertical profiles of microbial abundance, diversity, and community structure in a mesoscale dipole. The observed differences in the distribution of microbial abundance, OTUs, and functional groups between the AE and CE, their edges, and a jet suggest a significant influence from the physiochemical characteristics of mesoscale and submesoscale oceanic structures both vertically and horizontally. Previous studies revealed that in a CE, most productive regions are usually found at the rim of the eddy because shoaling of the convective mixed layer at the rim brings nutrients from deep waters and supports the development of phytoplankton (6). This is demonstrated in the SCS dipole by the relatively high concentrations of chlorophyll and autotrophic phytoplankton in surface waters at the edge of the CE. Subsequently, this high productivity may induce and support more abundant heterotrophic bacterioplankton at the edge of the CE and jet. The contrast in the distribution pattern of Prochlorococcus and Synechococcus in the cores of the CE and AE coincides with the temperature profile. The temperature difference between S71 in the CE core and S88 in the AE core was less than 0.5°C at the 5-m depth but approached 10°C at the 50- to 100-m water depth. Previous studies showed that temperature is a crucial environmental factor shaping the distribution of Prochlorococcus, which had a relatively larger positive response to the increased temperature than did Synechococcus (36, 37). High temperatures introduced by downwelling in the AE and low temperatures introduced by upwelling in the CE could boost and repress the growth of Prochlorococcus, respectively. The coastal jet between the eddies may drive the distribution of Synechococcus and Prochlorococcus as well, since Synechococcus proliferates in nutrient-rich waters (e.g., coastal or upwelling regions), whereas Prochlorococcus is better adapted to oligotrophic waters (38).

All alpha diversities were relatively low at the surface and increased with depth, reaching a maximum in the subsurface and then decreasing gradually, but an influence of the dipole on the alpha diversity both horizontally and vertically was observed. In the surface waters, higher alpha diversities were found at the edges of mesoscale structures, which is consistent with the high chlorophyll and autotrophic and heterotrophic bacterioplankton abundances in those regions. This indicates that shoaling of the nutrient-rich deep water in the convective zone stimulates population size and diversity of bacterioplankton. In the subsurface, higher diversities were found in regions that potentially downwell surface waters. This might be a result of the dipole induced export of particulate and dissolved organic matter from surface to subsurface waters, which can serve as a microbial hot spot (39–41). Higher temperatures found in the subsurface layer of the AE could activate the local microbial community and may be another reason for higher diversity. In comparison, lower temperatures observed in the subsurface water of the CE center suggest upwelling of mesopelagic water, which directly lifts the low diversity mesopelagic bacterial community and prohibits particles from sinking out of the surface layer. Because particle-attached prokaryotes generally show higher complexity than their free-living counterparts (42), a reduction in sinking particles might result in low bacterioplankton diversity, which was observed in the subsurface water of the CE core. Interestingly, a recent study found that the core of a mode water eddy in the Sargasso Sea had significantly elevated diversity relative to the edge (18). In our study, the lowest bacterial community diversity was observed in the core area at a 50-m water depth in the AE. The differences in hydrological characteristics of these two eddy systems may cause the contrasting effects on bacterial diversity. Although the rotation direction of the mode water eddy in the Sargasso Sea is the same as the AE of the SCS and their geostrophic velocities are both dominated by the main pycnocline depression, the displacement of the seasonal pycnocline in the mode water eddy tends to upwell nutrients into the surface layer throughout their intensification phase (7).

The community structure and major OTU distribution showed a stratified depth-related pattern, consistent with previous findings in the open ocean (2, 33, 43), but substantial influences from the dipole were also observed. The community structure shifted upward and downward in the dipole, indicating downwelling in the AE and its edge and upwelling in the CE, respectively. The single group of surface samples from the coastal jet demonstrated the influence of the coastal jet current that could directly relocate the coastal community to the open ocean. The upward clustering of mesopelagic samples from the jet and AE indicate a deeper impact of those mesoscale structures on microbial communities compared with the CE. In addition, the dipole may impact the distribution of dominant bacterial OTUs by uplift, downward transport, enrichment, depletion, and horizontal transport effects. The SAR11 clade, possibly the most abundant bacterium in the ocean (44, 45), shows that the distribution pattern of its surface and deep water ecotypes are clearly affected by the dipole. Those results agree with the fact that the SAR11 surface ecotype thrives in oligotrophic waters and is depleted in the nutrient-rich upwelling region; thus, the deep ecotype could be a tracer of deep-water intrusion (18). The coastal group of Flavobacteriia found in the jet was evidence of horizontal transport of the coastal community by the strong jet current. The typical deep-water OTUs (SAR324 and SAR406) found in the subsurface of the CE indicate an intrusion of deep water in the CE core, consistent with a previous finding from a mode water eddy that also generated upwelling at its core (18). Prochlorococcus plays a key role in the global carbon and energy cycles, and our finding of this bacterium in the mesopelagic layer at the edge of the AE is consistent with the new discovery of Prochlorococcus well below the euphotic layer in the western Pacific Ocean (46). Recent studies indicate that physical-biological interactions have profound implications on the nitrogen fixation in mesoscale structures in the North Pacific Ocean (47). Functional profiling showed an increased abundance of nitrification groups at the subsurface layer of the CE and decreased pattern in the AE and the jet, suggesting that the dipole may have profound impacts on local biogeochemical cycling through the shift of bacterial community structure.

The results of flow cytometry, clustering of bacterial communities, and downward transport pattern of major OTUs, along with chlorophyll and temperature characteristics, indicate an intrusion of surface water into the subsurface layer in the AE core and edge as well as the jet. Our results are consistent with a recent study using gliders during the North Atlantic spring bloom, which demonstrated that particulate organic carbon could be exported to the subsurface by negative vorticity in submesoscale structures along the perimeter of eddies (39). These results are contradictory to a previously common conclusion that there is no biological response in the dark interior of AEs, compared with CEs, which can push nutrient-rich isopycnals into the euphotic zone and increase biological production (6). Thus, we suggest that AEs may also act as a hot spot in the marine microbial ecosystem.

In summary, our study showed that mesoscale features of a dipole in the SCS result in heterogeneous microbial communities. Although the interaction of the dipole and microbial community is complicated and far from being understood, together with previous physical and microbial oceanography studies on mesoscale eddies, we propose that the dipole may affect the microbial community in four possible ways: (i) upwelling may directly inject nutrients into the surface waters from the deep ocean and coastal regions, which may stimulate phytoplankton and bacterioplankton development, e.g., the high Synechococcus abundance and chlorophyll fluorescence found in the CE and jet; (ii) vertical water mass movements change the temperature profile and may influence the microbial diversity, e.g., the high alpha diversities found in the subsurface of the AE; (iii) the dipole may accumulate organic matter, enhance particulate organic carbon export, and stimulate the bacterial activity, e.g., the increase in chemoheterotrophic and hydrocarbon degradation groups at the subsurface layer of the jet and the CE edge; and (iv) the strong vertical mixing and horizontal advection induced by the dipole may directly relocate the microbial community, e.g., the high Flavobacteriia abundance found in the jet and the Prochlorococcus found in the deep layer of the AE edges. Based on the above ideas, a conceptual model was proposed; it is shown in Fig. 7. Dipoles are among the most common and dynamic phenomena in the global oceans, and their activities might be greatly elevated with increasing global warming. In light of this, our study showed their profound impacts on marine microbial distribution and diversity, as well as functional potential, and that dipoles may act as a driver for local and global biogeochemical processes.

FIG 7
  • Open in new tab
  • Download powerpoint
FIG 7

Schematic depicting the influence of the dipole on the bacterial community. Cyclonic features are shown in blue, anticyclonic features in orange, and coastal jet in green.

MATERIALS AND METHODS

Eddy tracking and physical oceanographic observations.Satellite altimetry data from AVISO and shipboard acoustic Doppler current profile data allowed the accurate tracking of the dipole in the SCS and high-resolution sampling of 12 or more depths from surface waters to the bottom (Fig. 1; see also Fig. S1). Salinity, temperature, turbidity, oxygen, and fluorescence were recorded for 36 physical oceanography stations using a SeaBird 911 plus conductivity-temperature-depth (CTD) system, mounted on a rosette sampler. Eighteen stations were sampled for microbial parameters, including seven representative stations for detailed microbial diversity analysis.

Picoplankton abundance.For picoplankton abundance analysis, an aliquot of each sample (1.8 ml) was fixed with glutaraldehyde (0.5% [vol/vol] final concentration), incubated in the dark for 15 min, flash-frozen in liquid nitrogen, and then stored at −80°C. Prochlorococcus, Synechococcus, heterotrophic bacterioplankton, and picoeukaryotes were analyzed using a flow cytometer (EPICS Altra II; Beckman Coulter, USA) following methods described previously (48). To achieve accurate enumeration of the cells, BD Trucount control beads were used for the flow rate calibration.

DNA sampling and extraction and PCR amplification.Seawater for microbial diversity analysis was prefiltered over 20-μm mesh to remove large particles. Then 2 liters of seawater was filtered onto 0.22-μm polycarbonate filters (Millipore; GTTP' 47-mm diameter) under low pressure (less than −0.03 MPa) and the filters were stored at −80°C until further analysis. Environmental DNA was extracted using the Powerwater DNA isolation kit (MoBIO laboratories, Carlsbad, CA) according to the manufacturer's protocol.

The 16S rRNA gene fragments were amplified by PCR from purified DNA using primers F515 (GTGNCAGCMGCCGCGGTAA) and R926 (CCGYCAATTYMTTTRAGTTT), which cover the V4 and the V5 regions (49). A unique 8-bp barcode was added to the 5′ end of the forward primer sequence to label the samples. PCR was carried out in triplicate using a 25-μl reaction volume containing 12.5 μl of Premix Ex Taq (TaKaRa, Dalian, China), 200 nM each primer, 1 μl of template, and 1 μl of 5-μg/μl bovine serum albumin (BSA), under the following conditions: initial denaturation at 95°C for 3 min, followed by 30 cycles of 95°C for 30 s, 55°C for 45 s, and 72°C for 45 s, and a final extension at 72°C for 10 min. Triplicate PCR products were pooled and purified using a MiniBEST agarose gel DNA purification kit (TaKaRa). Library preparation and sequencing were conducted with Titanium chemistry on a 454 Life Science genome sequencer FLX platform according to the standard protocol.

Sequence analysis.Sequence analyses were conducted using QIIME 1.8.0 (50). The sequences were filtered for quality score (>25), length (greater than 300 bp but less than 460 bp), number of homopolymers (<6), absence of ambiguous bases, and absence of mismatches in the barcode and primer. Sequences were assigned to each sample based on the barcode. OTUs were identified using uclust at a 97% similarity level, and a representative sequence was selected for further analysis (51). Taxonomy was assigned using uclust with the Greengenes data set (52). OTUs were removed with a eukaryotic or archaeal assignment by using RDP classifier (53). The representative sequences were aligned using PyNast (54). Chimeric sequences were removed using ChimeraSlayer (55). OTUs with only one occurrence (singletons) were removed because they could have been a result of sequencing error (56) and could inflate the actual diversity estimation (57). To control for variation in the number between samples, the libraries were normalized to the minimum sample size (3,333). A phylogenetic tree was constructed from the filtered alignment with FastTree (58). The Shannon index, PD tree, Chao1, and observed species were calculated. For beta diversity analysis, a weighted UniFrac distance matrix was used to measure the abundance-weighted phylogenetic distances between samples (28). UniFrac distances were used for clustering and an OTU heat map was created through GENE-E (https://software.broadinstitute.org/GENE-E/). In addition, for a detailed analysis of cyanobacterial community, cyanobacterial OTU were identified using uclust at a 98% similarity level, which more accurately discriminates Prochlorococcus and Synechococcus (59). The ecotypes of the top 10 Prochlorococcus and top 10 Synechococcus OTUs were determined by phylogenetic trees based on neighbor-joining method with 1,000 resamplings. Hierarchical clustering of cyanobacterial communities was generated from Bray-Curtis distance between samples.

Functional annotation of prokaryotic taxa.In order to investigate the functional potential of bacterial communities within the dipole, we related taxonomically annotated OTUs with metabolic function groups using Functional Annotation of Prokaryotic Taxa v.1.1 (FAPROTAX) (60). Each OTU was compared against FAPROTAX database with default settings. A total of 2,380 out of 7,745 OTUs (30.7%) were assigned to least one functional group, and an output functional table was created with 22,137 functional annotations. Hierarchical clustering was generated from Bray-Curtis distance between samples.

Accession number(s).The entire sequence data set has been deposited in NCBI Sequence Read Archive (SRA) under BioProject number PRJNA416113.

ACKNOWLEDGMENTS

We thank the captain and crew of the R/V Dongfanghong-2 for ensuring smooth sampling.

This study was supported by the National Natural Science Foundation of China (grants 41522603, 91428308, and 31570172). R.Z. was partially supported by the Qingdao National Laboratory for Marine Science and Technology (grant QNLM2016ORP0303).

W.Y., R.Z., and N.J. designed the project and the experiments. W.Y. performed the sampling and laboratory experiments. W.Y. and R.Z. performed oceanographic, biological, and bioinformatic analyses. W.Y. and R.Z. prepared the manuscript.

We declare no conflicts of interest.

FOOTNOTES

    • Received 15 March 2018.
    • Accepted 23 June 2018.
    • Accepted manuscript posted online 6 July 2018.
  • Address correspondence to Rui Zhang, ruizhang{at}xmu.edu.cn, or Nianzhi Jiao, jiao{at}xmu.edu.cn.
  • Citation Yan W, Zhang R, Jiao N. 2018. A long-standing complex tropical dipole shapes marine microbial biogeography. Appl Environ Microbiol 84:e00614-18. https://doi.org/10.1128/AEM.00614-18.

  • Supplemental material for this article may be found at https://doi.org/10.1128/AEM.00614-18.

REFERENCES

  1. 1.↵
    1. Friedline CJ,
    2. Franklin RB,
    3. McCallister SL,
    4. Rivera MC
    . 2012. Bacterial assemblages of the eastern Atlantic Ocean reveal both vertical and latitudinal biogeographic signatures. Biogeosciences 9:2177–2193. doi:10.5194/bg-9-2177-2012.
    OpenUrlCrossRef
  2. 2.↵
    1. Agogué H,
    2. Lamy D,
    3. Neal PR,
    4. Sogin ML,
    5. Herndl GJ
    . 2011. Water mass-specificity of bacterial communities in the North Atlantic revealed by massively parallel sequencing. Mol Ecol 20:258–274. doi:10.1111/j.1365-294X.2010.04932.x.
    OpenUrlCrossRefPubMedWeb of Science
  3. 3.↵
    1. Galand PE,
    2. Potvin M,
    3. Casamayor EO,
    4. Lovejoy C
    . 2010. Hydrography shapes bacterial biogeography of the deep Arctic Ocean. ISME J 4:564–576. doi:10.1038/ismej.2009.134.
    OpenUrlCrossRefPubMedWeb of Science
  4. 4.↵
    1. Zhang R,
    2. Lau SCK,
    3. Ki J-S,
    4. Thiyagarajan V,
    5. Qian P-Y
    . 2009. Response of bacterioplankton community structures to hydrological conditions and anthropogenic pollution in contrasting subtropical environments. FEMS Microbiol Ecol 69:449–460. doi:10.1111/j.1574-6941.2009.00726.x.
    OpenUrlCrossRefPubMedWeb of Science
  5. 5.↵
    1. Zhang Y,
    2. Zhao Z,
    3. Dai M,
    4. Jiao N,
    5. Herndl GJ
    . 2014. Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea. Mol Ecol 23:2260–2274. doi:10.1111/mec.12739.
    OpenUrlCrossRef
  6. 6.↵
    1. Lévy M
    . 2008. The modulation of biological production by oceanic mesoscale turbulence, p 219–261. In Weiss JB, Provenzale A (ed), Transport and mixing in geophysical flows. Springer, Berlin, Germany.
  7. 7.↵
    1. McGillicuddy DJ,
    2. Anderson LA,
    3. Bates NR,
    4. Bibby T,
    5. Buesseler KO,
    6. Carlson CA,
    7. Davis CS,
    8. Ewart C,
    9. Falkowski PG,
    10. Goldthwait SA,
    11. Hansell DA,
    12. Jenkins WJ,
    13. Johnson R,
    14. Kosnyrev VK,
    15. Ledwell JR,
    16. Li QP,
    17. Siegel DA,
    18. Steinberg DK
    . 2007. Eddy/wind interactions stimulate extraordinary mid-ocean plankton blooms. Science 316:1021–1026. doi:10.1126/science.1136256.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. McGillicuddy DJ,
    2. Robinson AR,
    3. Siegel DA,
    4. Jannasch HW,
    5. Johnson R,
    6. Dickey TD,
    7. McNeil J,
    8. Michaels AF,
    9. Knap AH
    . 1998. Influence of mesoscale eddies on new production in the Sargasso Sea. Nature 394:263–266. doi:10.1038/28367.
    OpenUrlCrossRefWeb of Science
  9. 9.↵
    1. Klein P,
    2. Lapeyre G
    . 2009. The oceanic vertical pump induced by mesoscale and submesoscale turbulence. Annu Rev Marine Sci 1:351–375. doi:10.1146/annurev.marine.010908.163704.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Arístegui J,
    2. Barton ED,
    3. Montero MF,
    4. Garcia-Munoz M,
    5. Escanez J
    . 2003. Organic carbon distribution and water column respiration in the NW Africa-Canaries Coastal Transition Zone. Aquat Microb Ecol 33:289–301. doi:10.3354/ame033289.
    OpenUrlCrossRef
  11. 11.↵
    1. Arístegui J,
    2. Montero MF
    . 2005. Temporal and spatial changes in plankton respiration and biomass in the Canary Islands region: the effect of mesoscale variability. J Mar Syst 54:65–82. doi:10.1016/j.jmarsys.2004.07.004.
    OpenUrlCrossRef
  12. 12.↵
    1. Ewart CS,
    2. Meyers MK,
    3. Wallner ER,
    4. McGillicuddy DJ, Jr,
    5. Carlson CA
    . 2008. Microbial dynamics in cyclonic and anticyclonic mode-water eddies in the northwestern Sargasso Sea. Deep Sea Res Part II Top Stud Oceanogr 55:1334–1347. doi:10.1016/j.dsr2.2008.02.013.
    OpenUrlCrossRef
  13. 13.↵
    1. Baltar F,
    2. Arístegui J,
    3. Gasol JM,
    4. Lekunberri I,
    5. Herndl GJ
    . 2010. Mesoscale eddies: hotspots of prokaryotic activity and differential community structure in the ocean. ISME J 4:975–988. doi:10.1038/ismej.2010.33.
    OpenUrlCrossRefPubMedWeb of Science
  14. 14.↵
    1. Williams RG,
    2. Follows MJ
    . 1998. The Ekman transfer of nutrients and maintenance of new production over the North Atlantic. Deep Sea Res Part I Oceanogr Res Pap 45:461–489. doi:10.1016/S0967-0637(97)00094-0.
    OpenUrlCrossRef
  15. 15.↵
    1. Oliver E,
    2. OKane TJ,
    3. Holbrook NJ
    . 2015. Projected changes to Tasman Sea eddies in a future climate. J Geophys Res Oceans 120:7150–7165. doi:10.1002/2015JC010993.
    OpenUrlCrossRef
  16. 16.↵
    1. Matear RJ,
    2. Chamberlain MA,
    3. Sun C,
    4. Feng M
    . 2013. Climate change projection of the Tasman Sea from an eddy-resolving ocean model. J Geophys Res Oceans 118:2961–2976. doi:10.1002/jgrc.20202.
    OpenUrlCrossRef
  17. 17.↵
    1. Zhang Y,
    2. Jiao N,
    3. Sun Z,
    4. Hu A,
    5. Zheng Q
    . 2011. Phylogenetic diversity of bacterial communities in South China Sea mesoscale cyclonic eddy perturbations. Res Microbiol 162:320–329. doi:10.1016/j.resmic.2010.12.006.
    OpenUrlCrossRefPubMedWeb of Science
  18. 18.↵
    1. Nelson CE,
    2. Carlson CA,
    3. Ewart CS,
    4. Halewood ER
    . 2014. Community differentiation and population enrichment of Sargasso Sea bacterioplankton in the euphotic zone of a mesoscale mode-water eddy. Environ Microbiol 16:871–887. doi:10.1111/1462-2920.12241.
    OpenUrlCrossRefWeb of Science
  19. 19.↵
    1. Levy M,
    2. Iovino D,
    3. Resplandy L,
    4. Klein P,
    5. Madec G,
    6. Tréguier AM,
    7. Masson S,
    8. Takahashi K
    . 2012. Large-scale impacts of submesoscale dynamics on phytoplankton: local and remote effects. Ocean Model 43-44:77–93.
    OpenUrlCrossRef
  20. 20.↵
    1. Lapeyre G,
    2. Klein P
    . 2006. Impact of the small-scale elongated filaments on the oceanic vertical pump. J Mar Res 64:835–851. doi:10.1357/002224006779698369.
    OpenUrlCrossRef
  21. 21.↵
    1. Wang G,
    2. Su J,
    3. Chu PC
    . 2003. Mesoscale eddies in the South China Sea observed with altimeter data. Geophys Res Lett 30:2121. doi:10.1029/2003GL018532.
    OpenUrlCrossRef
  22. 22.↵
    1. Hu J,
    2. Gan J,
    3. Sun Z,
    4. Zhu J,
    5. Dai M
    . 2011. Observed three-dimensional structure of a cold eddy in the southwestern South China Sea. J Geophys Res 116:C05016. doi:10.1029/2010JC006810.
    OpenUrlCrossRef
  23. 23.↵
    1. Gan J,
    2. Qu T
    . 2008. Coastal jet separation and associated flow variability in the southwest South China Sea. Deep Sea Res Part I Oceanogr Res Pap 55:1–19. doi:10.1016/j.dsr.2007.09.008.
    OpenUrlCrossRef
  24. 24.↵
    1. Jiao N,
    2. Zhang Y,
    3. Zhou K,
    4. Li Q,
    5. Dai M,
    6. Liu J,
    7. Guo J,
    8. Huang B
    . 2014. Revisiting the CO2 “source” problem in upwelling areas—a comparative study on eddy upwellings in the South China Sea. Biogeosciences 11:2465–2475. doi:10.5194/bg-11-2465-2014.
    OpenUrlCrossRef
  25. 25.↵
    1. Lundin D,
    2. Severin I,
    3. Logue JB,
    4. Östman Ö,
    5. Andersson AF,
    6. Lindström ES
    . 2012. Which sequencing depth is sufficient to describe patterns in bacterial α- and β-diversity? Environ Microbiol Rep 4:367–372. doi:10.1111/j.1758-2229.2012.00345.x.
    OpenUrlCrossRefPubMed
  26. 26.↵
    1. Chao A
    . 1984. Nonparametric estimation of the number of classes in a population. Scand J Stat 11:265–270.
    OpenUrlWeb of Science
  27. 27.↵
    1. Faith DP
    . 1992. Conservation evaluation and phylogenetic diversity. Biol Cons 61:1–10. doi:10.1016/0006-3207(92)91201-3.
    OpenUrlCrossRefWeb of Science
  28. 28.↵
    1. Hamady M,
    2. Lozupone C,
    3. Knight R
    . 2010. Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4:17–27. doi:10.1038/ismej.2009.97.
    OpenUrlCrossRefPubMedWeb of Science
  29. 29.↵
    1. Swan BK,
    2. Martinez-Garcia M,
    3. Preston CM,
    4. Sczyrba A,
    5. Woyke T,
    6. Lamy D,
    7. Reinthaler T,
    8. Poulton NJ,
    9. Masland EDP,
    10. Gomez ML,
    11. Sieracki ME,
    12. DeLong EF,
    13. Herndl GJ,
    14. Stepanauskas R
    . 2011. Potential for chemolithoautotrophy among ubiquitous bacteria lineages in the dark ocean. Science 333:1296–1300. doi:10.1126/science.1203690.
    OpenUrlAbstract/FREE Full Text
  30. 30.↵
    1. Alonso C,
    2. Warnecke F,
    3. Amann R,
    4. Pernthaler J
    . 2007. High local and global diversity of Flavobacteria in marine plankton. Environ Microbiol 9:1253–1266. doi:10.1111/j.1462-2920.2007.01244.x.
    OpenUrlCrossRefPubMedWeb of Science
  31. 31.↵
    1. Wang W,
    2. Zhong R,
    3. Shan D,
    4. Shao Z
    . 2014. Indigenous oil-degrading bacteria in crude oil-contaminated seawater of the Yellow Sea, China. Appl Microbiol Biotechnol 98:7253–7269. doi:10.1007/s00253-014-5817-1.
    OpenUrlCrossRef
  32. 32.↵
    1. Wright TD,
    2. Vergin KL,
    3. Boyd PW,
    4. Giovannoni SJ
    . 1997. A novel delta-subdivision proteobacterial lineage from the lower ocean surface layer. Appl Environ Microbiol 63:1441–1448.
    OpenUrlAbstract/FREE Full Text
  33. 33.↵
    1. DeLong EF
    . 2006. Community genomics among stratified microbial assemblages in the ocean's interior. Science 311:496–503. doi:10.1126/science.1120250.
    OpenUrlAbstract/FREE Full Text
  34. 34.↵
    1. López-García P,
    2. López-López A,
    3. Moreira D,
    4. Rodríguez-Valera F
    . 2001. Diversity of free-living prokaryotes from a deep-sea site at the Antarctic Polar Front. FEMS Microbiol Ecol 36:193–202. doi:10.1111/j.1574-6941.2001.tb00840.x.
    OpenUrlCrossRefPubMedWeb of Science
  35. 35.↵
    1. Gordon DA,
    2. Giovannoni SJ
    . 1996. Detection of stratified microbial populations related to Chlorobium and Fibrobacter species in the Atlantic and Pacific oceans. Appl Environ Microbiol 62:1171–1177.
    OpenUrlAbstract/FREE Full Text
  36. 36.↵
    1. Flombaum P,
    2. Gallegos JL,
    3. Gordillo RA,
    4. Rincón J,
    5. Zabala LL,
    6. Jiao N,
    7. Karl DM,
    8. Li WKW,
    9. Lomas MW,
    10. Veneziano D,
    11. Vera CS,
    12. Vrugt JA,
    13. Martiny AC
    . 2013. Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. Proc Natl Acad Sci U S A 110:9824–9829. doi:10.1073/pnas.1307701110.
    OpenUrlAbstract/FREE Full Text
  37. 37.↵
    1. Johnson ZI,
    2. Zinser ER,
    3. Coe A,
    4. McNulty NP,
    5. Woodward EMS,
    6. Chisholm SW
    . 2006. Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental gradients. Science 311:1737–1740. doi:10.1126/science.1118052.
    OpenUrlAbstract/FREE Full Text
  38. 38.↵
    1. Partensky F,
    2. Blanchot J,
    3. Vaulot D
    . 1999. Differential distribution and ecology of Prochlorococcus and Synechococcus in oceanic waters: a review. Bull Inst Oceanogr (Monaco) 19:457–476.
    OpenUrl
  39. 39.↵
    1. Omand MM,
    2. D'Asaro EA,
    3. Lee CM,
    4. Perry MJ,
    5. Briggs N,
    6. Cetini I,
    7. Mahadevan A
    . 2015. Eddy-driven subduction exports particulate organic carbon from the spring bloom. Science 348:222–225. doi:10.1126/science.1260062.
    OpenUrlAbstract/FREE Full Text
  40. 40.↵
    1. Azam F,
    2. Long RA
    . 2001. Oceanography: sea snow microcosms. Nature 414:495–498. doi:10.1038/35107174.
    OpenUrlCrossRefPubMedWeb of Science
  41. 41.↵
    1. Azam F,
    2. Malfatti F
    . 2007. Microbial structuring of marine ecosystems. Nat Rev Microbiol 5:782–791. doi:10.1038/nrmicro1747.
    OpenUrlCrossRefPubMedWeb of Science
  42. 42.↵
    1. Zhang Y,
    2. Xiao W,
    3. Jiao N
    . 2016. Linking biochemical properties of particles to particle-attached and free-living bacterial community structure along the particle density gradient from freshwater to open ocean. J Geophys Res Biogeosci 121:2261–2274. doi:10.1002/2016JG003390.
    OpenUrlCrossRef
  43. 43.↵
    1. Kirchman DL,
    2. Cottrell MT,
    3. Lovejoy C
    . 2010. The structure of bacterial communities in the western Arctic Ocean as revealed by pyrosequencing of 16S rRNA genes. Environ Microbiol 12:1132–1143. doi:10.1111/j.1462-2920.2010.02154.x.
    OpenUrlCrossRefPubMedWeb of Science
  44. 44.↵
    1. Giovannoni SJ,
    2. Britschgi TB,
    3. Moyer CL,
    4. Field KG
    . 1990. Genetic diversity in Sargasso Sea bacterioplankton. Nature 345:60–63. doi:10.1038/345060a0.
    OpenUrlCrossRefPubMedWeb of Science
  45. 45.↵
    1. Rappé MS,
    2. Giovannoni SJ
    . 2003. The uncultured microbial majority. Annu Rev Microbiol 57:369–394. doi:10.1146/annurev.micro.57.030502.090759.
    OpenUrlCrossRefPubMedWeb of Science
  46. 46.↵
    1. Jiao N,
    2. Luo T,
    3. Zhang R,
    4. Yan W,
    5. Lin Y,
    6. Johnson ZI,
    7. Tian J,
    8. Yuan D,
    9. Yang Q,
    10. Zheng Q,
    11. Sun J,
    12. Hu D,
    13. Wang P
    . 2014. Presence of Prochlorococcus in the aphotic waters of the western Pacific Ocean. Biogeosciences 11:2391–2400. doi:10.5194/bg-11-2391-2014.
    OpenUrlCrossRef
  47. 47.↵
    1. Church MJ,
    2. Mahaffey C,
    3. Letelier RM,
    4. Lukas R,
    5. Zehr JP,
    6. Karl DM
    . 2009. Physical forcing of nitrogen fixation and diazotroph community structure in the North Pacific subtropical gyre. Global Biogeochem Cycles 23:GB2020. doi:10.1029/2008GB003418.
    OpenUrlCrossRef
  48. 48.↵
    1. Marie D,
    2. Partensky F,
    3. Vaulot D,
    4. Brussaard C
    . 2001. Enumeration of phytoplankton, bacteria, and viruses in marine samples. Curr Protoc Cytom Chapter 11:Unit 11.11.
  49. 49.↵
    1. Quince C,
    2. Lanzén A,
    3. Davenport RJ,
    4. Turnbaugh PJ
    . 2011. Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12:38. doi:10.1186/1471-2105-12-38.
    OpenUrlCrossRefPubMed
  50. 50.↵
    1. Caporaso JG,
    2. Kuczynski J,
    3. Stombaugh J,
    4. Bittinger K,
    5. Bushman FD,
    6. Costello EK,
    7. Fierer N,
    8. Peña AG,
    9. Goodrich JK,
    10. Gordon JI,
    11. Huttley GA,
    12. Kelley ST,
    13. Knights D,
    14. Koenig JE,
    15. Ley RE,
    16. Lozupone CA,
    17. McDonald D,
    18. Muegge BD,
    19. Pirrung M,
    20. Reeder J,
    21. Sevinsky JR,
    22. Turnbaugh PJ,
    23. Walters WA,
    24. Widmann J,
    25. Yatsunenko T,
    26. Zaneveld J,
    27. Knight R
    . 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. doi:10.1038/nmeth.f.303.
    OpenUrlCrossRefPubMedWeb of Science
  51. 51.↵
    1. Edgar RC
    . 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461. doi:10.1093/bioinformatics/btq461.
    OpenUrlCrossRefPubMedWeb of Science
  52. 52.↵
    1. DeSantis TZ,
    2. Hugenholtz P,
    3. Larsen N,
    4. Rojas M,
    5. Brodie EL,
    6. Keller K,
    7. Huber T,
    8. Dalevi D,
    9. Hu P,
    10. Andersen GL
    . 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072. doi:10.1128/AEM.03006-05.
    OpenUrlAbstract/FREE Full Text
  53. 53.↵
    1. Wang Q,
    2. Garrity GM,
    3. Tiedje JM,
    4. Cole JR
    . 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267. doi:10.1128/AEM.00062-07.
    OpenUrlAbstract/FREE Full Text
  54. 54.↵
    1. Caporaso JG,
    2. Bittinger K,
    3. Bushman FD,
    4. DeSantis TZ,
    5. Andersen GL,
    6. Knight R
    . 2010. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266–267. doi:10.1093/bioinformatics/btp636.
    OpenUrlCrossRefPubMedWeb of Science
  55. 55.↵
    1. Haas BJ,
    2. Gevers D,
    3. Earl AM,
    4. Feldgarden M,
    5. Ward DV,
    6. Giannoukos G,
    7. Ciulla D,
    8. Tabbaa D,
    9. Highlander SK,
    10. Sodergren E,
    11. Methé B,
    12. DeSantis TZ,
    13. Petrosino JF,
    14. Knight R,
    15. Birren BW
    . 2011. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21:494–504. doi:10.1101/gr.112730.110.
    OpenUrlAbstract/FREE Full Text
  56. 56.↵
    1. Quince C,
    2. Lanzén A,
    3. Curtis TP,
    4. Davenport RJ,
    5. Hall N,
    6. Head IM,
    7. Read LF,
    8. Sloan WT
    . 2009. Accurate determination of microbial diversity from 454 pyrosequencing data. Nat Methods 6:639–641. doi:10.1038/nmeth.1361.
    OpenUrlCrossRefPubMedWeb of Science
  57. 57.↵
    1. Kunin V,
    2. Engelbrektson A,
    3. Ochman H,
    4. Hugenholtz P
    . 2010. Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ Microbiol 12:118–123. doi:10.1111/j.1462-2920.2009.02051.x.
    OpenUrlCrossRefPubMedWeb of Science
  58. 58.↵
    1. Price MN,
    2. Dehal PS,
    3. Arkin AP
    . 2009. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 26:1641–1650. doi:10.1093/molbev/msp077.
    OpenUrlCrossRefPubMedWeb of Science
  59. 59.↵
    1. Moore LR,
    2. Rocap G,
    3. Chisholm SW
    . 1998. Physiology and molecular phylogeny of coexisting Prochlorococcus ecotypes. Nature 393:464–467. doi:10.1038/30965.
    OpenUrlCrossRefPubMedWeb of Science
  60. 60.↵
    1. Louca S,
    2. Parfrey LW,
    3. Doebeli M
    . 2016. Decoupling function and taxonomy in the global ocean microbiome. Science 353:1272–1277. doi:10.1126/science.aaf4507.
    OpenUrlAbstract/FREE Full Text
  • Copyright © 2018 American Society for Microbiology.

All Rights Reserved.

PreviousNext
Back to top
Download PDF
Citation Tools
A Long-Standing Complex Tropical Dipole Shapes Marine Microbial Biogeography
Wei Yan, Rui Zhang, Nianzhi Jiao
Applied and Environmental Microbiology Aug 2018, 84 (18) e00614-18; DOI: 10.1128/AEM.00614-18

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print

Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this Applied and Environmental Microbiology article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
A Long-Standing Complex Tropical Dipole Shapes Marine Microbial Biogeography
(Your Name) has forwarded a page to you from Applied and Environmental Microbiology
(Your Name) thought you would be interested in this article in Applied and Environmental Microbiology.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A Long-Standing Complex Tropical Dipole Shapes Marine Microbial Biogeography
Wei Yan, Rui Zhang, Nianzhi Jiao
Applied and Environmental Microbiology Aug 2018, 84 (18) e00614-18; DOI: 10.1128/AEM.00614-18
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

mesoscale dipole
microbial communities

Related Articles

Cited By...

About

  • About AEM
  • Editor in Chief
  • Editorial Board
  • Policies
  • For Reviewers
  • For the Media
  • For Librarians
  • For Advertisers
  • Alerts
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Article Types
  • Ethics
  • Contact Us

Follow #AppEnvMicro

@ASMicrobiology

       

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

 

Print ISSN: 0099-2240; Online ISSN: 1098-5336