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Substrate-Controlled Succession of Marine Bacterioplankton Populations Induced by a Phytoplankton Bloom

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Science  04 May 2012:
Vol. 336, Issue 6081, pp. 608-611
DOI: 10.1126/science.1218344

Abstract

Phytoplankton blooms characterize temperate ocean margin zones in spring. We investigated the bacterioplankton response to a diatom bloom in the North Sea and observed a dynamic succession of populations at genus-level resolution. Taxonomically distinct expressions of carbohydrate-active enzymes (transporters; in particular, TonB-dependent transporters) and phosphate acquisition strategies were found, indicating that distinct populations of Bacteroidetes, Gammaproteobacteria, and Alphaproteobacteria are specialized for successive decomposition of algal-derived organic matter. Our results suggest that algal substrate availability provided a series of ecological niches in which specialized populations could bloom. This reveals how planktonic species, despite their seemingly homogeneous habitat, can evade extinction by direct competition.

Annually recurring spring phytoplankton blooms with high net primary production (NPP) characterize eutrophic upwelling zones and coastal oceans in higher latitudes. Coastal zones with water depths <200 m constitute ~7% of the global ocean surface (1), yet they are responsible for ~19% of the oceanic NPP (2) and globally account for 80% of organic matter burial and 90% of sedimentary mineralization (1). Heterotrophic members of the picoplankton—mostly Bacteria—reprocess about half of the oceanic NPP in the so-called “microbial loop” (3). The bulk of this bacterioplankton biomass is free-living, but up to 20% is attached to algae or particles (4).

The bacterial response to coastal phytoplankton blooms has been almost exclusively studied in microcosm/mesocosm experiments (58) or with limited resolution in time and biodiversity in situ (911). We observed bacterial populations during and after a phytoplankton bloom in spring 2009 at the island of Helgoland in the German Bight (54°11′03′′N, 7°54′00′′E; fig. S1A) with a high taxonomic and functional resolution. We sampled 500 liters of subsurface seawater twice a week during 2009. Samples were filtered into fractions dominated by free-living bacteria (3 to 0.2 μm in size) and algae/particle-associated bacteria (10 to 3 μm in size) (fig. S2). Algal composition was determined microscopically (fig. S3 and table S1), and microbial composition was identified via catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH, tables S2 and S3). At selected sampling times during and after the bloom, the data were complemented by comparative analysis of 16S ribosomal RNA (rRNA) gene amplicons (pyrotags, table S4) and by functional data from extensive metagenome and metaproteome analyses (table S5). In addition, physical and chemical parameters were measured daily, including temperature, turbidity, salinity, and concentrations of phosphate, nitrate, nitrite, ammonium, silicate, and chlorophyll a (table S6).

Pre-bloom bacteria (Fig. 1A) were dominated by Alphaproteobacteria (41 to 67%), composed roughly of two-thirds SAR11 clade and one-third Roseobacter clade (Fig. 1B and fig. S4B). SAR11 consisted almost exclusively of subgroup Ia (Candidatus Pelagibacter ubique) (table S4). This composition changed as the spring phytoplankton bloom commenced (12). In early April (3 to 9 April 2009), Bacteroidetes abundances increased fivefold within 1 week (from 1.5 × 105 to 7.7 × 105 cells/ml), whereas Alphaproteobacteria (from 2.1 × 105 to 5.0 × 105 cells/ml) and Gammaproteobacteria (from 0.8 × 105 to 1.8 × 105 cells/ml) abundances only approximately doubled. The Bacteroidetes consisted mostly of Flavobacteria (89 to 98%) (table S4), with a succession of Ulvibacter spp., followed by Formosa-related and Polaribacter species as the most prominent groups (Fig. 1C and fig. S4C). Gammaproteobacteria reacted later to algal decay, but with a more dense succession of peaking clades, with highest abundances in Reinekea spp. and SAR92 (Fig. 1D and fig. S4D). Reinekea spp. grew within 1 week from 1.6 × 103 cells/ml to above 1.6 × 105 cells/ml (estimated doubling time, 25 hours) and subsequently almost vanished within 2 weeks. Roseobacter clade members also showed a succession, with the NAC11-7 lineage dominating the early bacterioplankton bloom and the Roseobacter clade–affiliated (RCA) lineage dominating the late bloom (table S4).

Fig. 1

Abundances of major bacterial populations during the bacterioplankton bloom as assessed by CARD-FISH. (A) Chlorophyll a (Chl a) concentration (measured with a BBE Moldaenke algal group analyzer), 4′,6-diamidino-2-phenylindole (DAPI)–based total cell counts (TCC), and bacterial counts (probe EUB338 I-III) during the year 2009; diatom-dominated spring blooms (1) and dinoflagellate-dominated summer blooms (2) are marked with green boxes; triangles on top mark accessory samples: metagenomics (red), metaproteomics (blue), and 16S rRNA gene tag sequencing (magenta). (B) Relative abundances of selected Alphaproteobacteria: SAR11 clade (probe SAR11-486) and Roseobacter clade (probe ROS537). (C) Relative abundances of selected Flavobacteria: Ulvibacter spp. (probe ULV-995), Formosa spp. (probe FORM-181A), and Polaribacter spp. (probe POL740). (D) Relative abundances of selected Gammaproteobacteria: Reinekea spp. (probe REI731) and SAR92 clade (probe SAR92-627). Further probes that are not shown for clarity are specified in the supplementary materials (tables S2 and S3).

Metagenomes were partitioned into taxonomically coherent bins (taxobins, fig. S5A) and then used for identification, annotation, and semiquantitative analyses of the metaproteome data (12). This allowed the investigation of shifts in gene content and expression within dominating bacterial populations (table S7).

A pronounced peak in the abundance of carbohydrate-active enzymes [CAZymes (13)] accompanied the bacterial succession (fig. S5B). CAZyme frequencies and expressions were taxonomically distinct (Figs. 2 and 3). For instance, Flavobacteria and Gammaproteobacteria dominated the abundant glycoside hydrolase family 16 (GH16). Most corresponding genes were annotated as laminarinases for decomposing the algal glucan laminarin. Likewise, expressed GH30-family proteins that include β-d-fucosidases mapped exclusively to Flavobacteria. Flavobacteria also dominated GH29/GH95-family genes containing α-l-fucosidases, as well as l-fucose permease genes. Fucose is a major constituent of diatom exopolysaccharides (14, 15). Flavobacteria were also dominating GH92-family glycoside hydrolases encoding mainly alpha-mannosidase, whereas Gammaproteobacteria dominated the glycoside hydrolase family 81. Likewise, Gammaproteobacteria (SAR92 clade) and Flavobacteria dominated expression within the GH3 family.

Fig. 2

Abundances of CAZymes with relevance for external carbohydrate degradation. (Left) Copies of 20 CAZymes per megabase of metagenome sequence with class-level taxonomic classifications (12). Maximum abundances are highlighted in gray. (Right) Detailed taxonomic breakdown for four selected CAZymes showing differing taxonomic compositions; each histogram shows data for the five metagenome samples (from left to right: 11 February 2009, 31 March 2009, 7 April 2009, 14 April 2009, and 16 June 2009).

Fig. 3

Expression of CAZymes with relevance for external carbohydrate degradation; the proteome data were analyzed in a semiquantitative manner based on normalized spectral abundance factors (NSAFs) (12).

Many algal polysaccharides are sulfated (such as carragenans, agarans, ulvans, and fucans), and hence sulfatases are required for their complete degradation. Sulfatase gene frequencies peaked together with the CAZymes at 7 April and showed a mixed taxonomic composition, but the maximum in sulfatase expression occurred later in the bloom (Fig. 3) and was dominated by Flavobacteria. Expressed sulfatases were found in the Polaribacter taxobin, which corroborates recent reports of high numbers of sulfatases in Polaribacter (16). In contrast, glycoside hydrolases for decomposing nonsulfated laminarin (GH16, GH55, and GH117) had their expression maxima earlier during the initial algal die-off phase.

Glycolytic exoenzymes initiate bacterial utilization of complex algal polysaccharides. As a result, shorter sugar oligomers and monomers become increasingly available and allow fast-growing opportunistic bacteria with a broader substrate spectrum to grow. Differences in nutritional strategies were apparent even between taxonomic classes; for example, in the expression of transport systems for nutrient uptake (Fig. 4A).

Fig. 4

Transporter components and phosphorus acquisition proteins of dominant taxa during the bacterioplankton bloom. (A) Expression of transporter components: starch utilization SusD-family proteins (SusD), TBDTs, TTTs, TRAPs, and ABCs. (B) Expression of proteins involved in phosphorus acquisition.

TonB-dependent transporter (TBDT) components dominated expressed transport proteins in Flavobacteria, whereas adenosine triphosphate (ATP)–binding cassette (ABC), tripartite ATP-independent periplasmic (TRAP), and tripartite tricarboxylate transporters (TTT) for low-molecular-weight (LMW) substrates were expressed only at low levels (Fig. 4A). TBDTs, originally thought to be restricted to complexed iron(III) (17) and vitamin B12 uptake, allow uptake of compounds that exceed the typical 600- to 800-dalton substrate range of normal porins (18, 19). Within Bacteroidetes, TBDTs are often colocalized with carbohydrate degradation modules (fig. S6) (16, 2022), and thus the substrate spectrum of these transporters may be much wider than anticipated (23), including oligosaccharides. TBDTs constituted no less than 13% of the expressed proteins identified during the bacterioplankton bloom at 31 March but only 7% in a non bloom sample at 11 February (fig. S7). This observation highlights the importance of TBDTs and corroborates a report of high TBDT expression in a coastal upwelling zone (24). In high-NPP zones, the capacity to take up oligomers as soon as they become transportable may constitute a major advantage over competitors restricted to smaller substrates.

In the Gammaproteobacteria, SAR92 featured a similar transporter expression profile as the Flavobacteria, whereas Reinekea spp. exhibited high expression of ABC and, to a lesser extent, TRAP transporters, indicating a different nutritional strategy with emphasis on the uptake of monomers (Fig. 4A).

Likewise, Alphaproteobacteria showed high expression levels of ABC and TRAP transporters and low levels of TBDTs and TTTs. This reflects the ecological strategy of the dominating SAR11. The well-studied representative Pelagibacter ubique HTCC 1062 thrives under oligotrophic conditions by means of high-affinity ABC and TRAP transporters and a constitutively expressed energy-producing proteorhodopsin (2527). Our data confirmed constitutive proteorhodopsin expression and transporter components as the most abundant expressed proteins in the SAR11 clade, which corroborates previous findings (28). Members of the metabolically diverse, opportunistic alphaproteobacterial Roseobacter clade (2931) exhibited LMW transporter expression levels that exceeded those of SAR11 (Fig. 4A). Although Roseobacter clade cells were two to four times less abundant than SAR11, they are larger, which may explain greater Roseobacter transporter expression.

Multiple factors may contribute to bacterioplankton bloom termination, such as predation by flagellate protozoa, viral lysis, and nutrient depletion. Phosphate limitation can spur algal exudate production, which might serve to promote the growth of phycosphere bacteria that remineralize and acquire phosphate more effectively (32); however, under phosphate limitation, algae and bacteria will compete. Phosphate dropped below the detection limit early in the phytoplankton bloom (fig. S1C), and the expression of several phosphate and phosphonate ABC-type uptake systems in various bacterial taxobins increased over the progression of the bloom (Fig. 4B). Gammaproteobacteria and SAR11 tended to use ABC-type phosphate transporters, as discovered in earlier studies (28), whereas flavobacterial Polaribacter spp. used phosphate:sodium symporters, and alphaproteobacterial Rhodobacterales spp. used phosphonate transporters.

In the first response to the phytoplankton bloom, flavobacterial Ulvibacter and Formosa spp. dominated (tables S2 and S4). Within these clades, TBDT components were among the proteins with the highest expression levels. This corroborates reports that specific Flavobacteria are tightly coupled to diatoms (7). Bacteroidetes have also been identified as major bacteria attached to marine snow (33, 34), which agrees with their presumed role as fast-growing r strategists with specialization on the initial attack of highly complex organic matter (16, 21, 35). Hence, algal blooms lead to a multifold increase of colonization surfaces for Bacteroidetes, which respond with increased production of exoenzymes (36). After algal lysis, Bacteroidetes are the first to profit.

The second phase of the bacterioplankton succession coincided with a shift in algal composition (fig. S3) and was characterized by a pronounced peak of gammaproteobacterial Reinekea spp. that reached up to 16% of the bacteria (14 April 2009). Reinekea spp. featured a different expression profile, with high expression levels of transporters for peptides, phosphate, monosaccharides, and other monomers. These in situ data agree with the studies on cultured Reinekea species (3739) that found broad generalist substrate spectra. The increase of alphaproteobacterial Roseobacter clade RCA during this phase might also be attributed to the Roseobacter's opportunistic life-style (29) and is consistent with previous findings of free-living RCA phylotypes in the German Bight during diatom blooms (40).

The third phase of the spring 2009 bacterioplankton succession was dominated by flavobacterial Polaribacter and gammaproteobacterial SAR92 clade species, together with a secondary spike in Formosa spp. (Fig. 1, C and D). At this time, Polaribacter and Formosa dominated the particle/algae-attached fraction (table S8). Hence this phase with high sulfatase expression (Fig. 3) reflected another change of ecological niches (12).

Taken together, the bacterial response to coastal phytoplankton blooms was more dynamic than previously anticipated and consisted of a succession of distinct populations with distinct functional and transporter profiles. Thus, the diatom-induced growth of specific bacterioplankton clades most likely resulted from the successive availability of different algal primary products (bottom-up control), which provided the series of ecological niches in which specialized populations could bloom. As a result, we are now beginning to uncover the relevant predictors for defining the ecological niches of planktonic species (41) and thus can tackle the “paradox of the plankton” (42), which is how these species evade extinction by direct competition in a seemingly homogeneous habitat with limited resources.

Supplementary Materials

www.sciencemag.org/cgi/content/full/336/6081/608/DC1

Materials and Methods

Supplementary Text

Figs. S1 to S12

Tables S1 to S4

References (43102)

Movie S1

References and Notes

  1. Further information is available as supplementary materials on Science Online.
  2. Acknowledgments: We thank T. Hammer and T. Ferdelman for critical reading of the manuscript; M. Meiners, E. Karamehmedovic, B. Voigt, and V. Damare for sample processing; F. Ruhnau and L. Sayavedra for work on transporters; M. Zeder for automated counting; and R. Hahnke and J. Harder for help with probe testing. We are also grateful to our colleagues from the Bundesamt für Seeschifffahrt und Hydrographie for provision of operational model output. Analyses and visualizations used in fig. S1, D to F, were produced with the Giovanni online data system, developed and maintained by the NASA Goddard Earth Sciences Data and Information Service Center. We acknowledge the Moderate Resolution Imaging Spectroradiometer mission scientists and associated NASA personnel for these data. The sequence data reported in this study can be obtained from the European Bioinformatics Institute (study number ERP001227; www.ebi.ac.uk/ena/data/view/ERP001227). The German Federal Ministry of Education and Research (BMBF) supported this study by funding the Microbial Interactions in Marine Systems project (MIMAS, project 03F0480A, http://mimas-project.de).
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