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Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria

Nature volume 522, pages 98–101 (2015)Cite this article

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Abstract

Interactions between primary producers and bacteria impact the physiology of both partners, alter the chemistry of their environment, and shape ecosystem diversity1,2. In marine ecosystems, these interactions are difficult to study partly because the major photosynthetic organisms are microscopic, unicellular phytoplankton3. Coastal phytoplankton communities are dominated by diatoms, which generate approximately 40% of marine primary production and form the base of many marine food webs4. Diatoms co-occur with specific bacterial taxa3, but the mechanisms of potential interactions are mostly unknown. Here we tease apart a bacterial consortium associated with a globally distributed diatom and find that a Sulfitobacter species promotes diatom cell division via secretion of the hormone indole-3-acetic acid, synthesized by the bacterium using both diatom-secreted and endogenous tryptophan. Indole-3-acetic acid and tryptophan serve as signalling molecules that are part of a complex exchange of nutrients, including diatom-excreted organosulfur molecules and bacterial-excreted ammonia. The potential prevalence of this mode of signalling in the oceans is corroborated by metabolite and metatranscriptome analyses that show widespread indole-3-acetic acid production by Sulfitobacter-related bacteria, particularly in coastal environments. Our study expands on the emerging recognition that marine microbial communities are part of tightly connected networks by providing evidence that these interactions are mediated through production and exchange of infochemicals.

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Figure 1: Growth characteristics of the P. multiseries–Sulfitobacter sp. SA11 co-culture.
Figure 2: Model of P. multiseries–Sulfitobacter interactions based on transcriptomic and targeted metabolite analyses.
Figure 3: Detection of IAA and IAA biosynthesis in the marine environment.

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Primary accessions

GenBank/EMBL/DDBJ

Gene Expression Omnibus

Sequence Read Archive

Data deposits

The data reported in this paper are presented in Supplementary Information and archived at the following databases: 16S rDNA sequences, GenBank accession numbers KM033232–KM033280; transcriptomes, Gene Expression Omnibus accession number GSE65189; metatranscriptomes, Sequence Read Archive accession number PRJNA272345; SA11 genome, Integrated Microbial Genomes (IMG) submission 11682.

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Acknowledgements

We thank U. John for the antibiotic recipe, L. Gram for providing Phaeobacter strains, J. Tsai for preparing the SA11 DNA for sequencing, the captain and crew of the R/V Kilo Moana and the R/V Thomas G. Thompson for help during the cruises, D. French for Extended Data Fig. 5, and T. Chiang for discussions. This work was supported in part by Gordon and Betty Moore Foundation grant GBMF3776 to E.V.A, and support from National Science Foundation (NSF) award OCE-1228770 to A.E.I., OCE-1205233 to E.V.A., and OCE-1342694 to M.A.M. S.A.A. was partly supported by a NSF/National Institutes of Health Pacific Northwest Consortium postdoctoral fellowship. H.M.V. was partly supported by a Natural Sciences and Engineering Research Council of Canada Postgraduate Scholarship – Master’s grant.

Author information

Authors and Affiliations

  1. School of Oceanography, University of Washington, Seattle, 98195, Washington, USA

    S. A. Amin, H. M. van Tol, L. T. Carlson, K. R. Heal, R. L. Morales, C. T. Berthiaume, M. S. Parker, B. Djunaedi, A. E. Ingalls & E. V. Armbrust

  2. Chemistry Faculty, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates,

    S. A. Amin

  3. Department of Microbiology, University of Washington, Seattle, 98195, Washington, USA

    L. R. Hmelo & M. R. Parsek

  4. Department of Microbiology, University of Georgia, Athens, 30602, Georgia, USA

    B. P. Durham

  5. Department of Marine Science, University of Georgia, Athens, 30602, Georgia, USA

    M. A. Moran

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Contributions

S.A.A., L.R.H., B.D., B.P.D. and H.V.T. conducted experiments; B.P.D. isolated and prepared bacterial transcriptomic and metatranscriptomic samples; R.L.M. isolated all other nucleic acids and prepared libraries for sequencing; C.T.B. quality-trimmed sequenced data, assembled the SA11 genome and translated the metatranscriptome; M.S.P. quality-trimmed and quantified the PC9 transcriptomes; L.T.C. and K.R.H. collected environmental metabolome samples and performed MS analyses; S.A.A., L.R.H., M.R.P., A.E.I., M.A.M., and E.V.A. designed experiments; S.A.A. and L.T.C. analysed the data. All authors were involved in manuscript writing.

Corresponding authors

Correspondence to S. A. Amin or E. V. Armbrust.

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Extended data figures and tables

Extended Data Figure 1 Phylogeny of P. multiseries-associated bacteria.

Maximum likelihood tree showing the 16S rRNA phylogeny of all bacterial strains cultivated from P. multiseries isolates. Colour of bacterial strain designation indicates which isolate of P. multiseries a bacterial strain originated from: red, PC9; blue, PnCLNN-17; green, PC4; magenta, GGA2 (see Extended Data Table 1). Genera/clades that were considered to be associated with P. multiseries (contained two or more isolates from different diatom cultures with >99% 16S rRNA identity) are highlighted in grey. Bootstrap values greater than 50 are indicated at the branch points. Detailed information about each isolate is provided in Supplementary Information Table 1.

Extended Data Figure 2 Effect of select bacterial strains on growth of P. multiseries.

a, Growth of P. multiseries PC9 in the presence of different representative bacteria from its consortium (open circles) relative to axenic growth (filled circles). Bacterial representatives (Limnobacter, SA37; Marinobacter, SA14; Croceibacter, SA60; Sulfitobacter, SA52; see Extended Data Table 2) were inoculated at ∼1 × 105 cells per millilitre relative to ∼4,000 cells per millilitre axenic PC9. Error bars, s.d. from triplicate cultures. b, Growth of P. multiseries IOES-1 in axenic culture or with SA11. Error bars, s.d. from four replicates.

Extended Data Figure 3 Select metabolite analyses from the P. multiseries–Sulfitobacter sp. SA11 co-culture and the environment.

a, Dissolved ammonium concentrations in a medium blank, in axenic P. multiseries PC9, and in PC9 with SA11 (co-culture). Error bars, the range from duplicate supernatants. b, UPLC–ESI–MS/MS chromatograms of tryptophan in axenic PC9 or co-culture supernatants. Tryptophan was detected in positive ion mode by SRM from m/z 188 to 118. A 500 pM tryptophan standard is shown for retention time comparison. Tryptophan concentrations in the diatom monoculture and co-culture were 448 ± 106 pM and 202 ± 20 pM, respectively. c, UPLC–ESI–MS/MS chromatograms of IAA from surface water at station 1, SA11, and co-culture (with PC9) supernatants. IAA was detected in positive ion mode by SRM from m/z 176 to 130. A 0.5 pM IAA standard is shown for retention time comparison. IAA concentrations in the co-culture and SA11 monoculture were 6.1 ± 0.4 pM and 540 ± 280 pM, respectively.

Extended Data Figure 4 Effect of multiple exogenous IAA additions on P. multiseries GGA2.

Axenic GGA2 was grown in synthetic seawater media and 50 nM IAA was added at times indicated by the red arrows. Error bars, s.d. from six cultures.

Extended Data Figure 5 Map of stations in the North Pacific Ocean where seawater samples were collected.

Surface and chlorophyll maximum waters were collected for targeted metabolite analysis (all stations indicated) and metatranscriptomics (stations 1 and 3). Station 8 coincides with historic station PAPA and station 16 coincides with station ALOHA. The different stations exhibit dramatic differences in chemical and physical characteristics. For example, stations 1 and 3 are nutrient-rich coastal sites, station 8 is iron-limited, and stations 14 and 16 reside within the North Pacific Gyre and are oligotrophic. The map was created with Esri ArcGIS and Esri ArcMap 10.1 software.

Extended Data Figure 6 IAA biosynthesis pathways in bacteria examined in the North Pacific Ocean metatranscriptomes.

IAA biosynthesis in bacteria is divided into tryptophan-dependent and -independent pathways. Known bacterial enzymes involved in IAA biosynthesis all belong to the former (italic names). Dotted arrows represent biosynthetic steps with no known enzymes in bacteria18. Enzyme names are coloured according to the different pathways present in Roseobacter genomes: green, IAN pathway; red, IAM pathway; cyan, TAM pathway. Grey enzyme names were not included in our analysis because either no homologues were found in Roseobacter genomes or, in the case of IAAld dehydrogenase (belonging to the aldehyde dehydrogenase family), the presence of multiple homologues within a given genome that were involved in multiple pathways not related to IAA biosynthesis prevented our ability to decide on a reliable query for blast analysis. IAAld, indole-3-acetaldehyde; IPy, indole-3-pyruvate. This figure was modified from ref. 18.

Extended Data Table 1 Diatom species and isolates used in this study
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Extended Data Table 2 Specific growth rate promotion of P. multiseries isolate PC9 in co-culture with different bacteria
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Extended Data Table 3 Specific growth rate promotion of different diatoms in co-culture with Sulfitobacter sp. SA11
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Extended Data Table 4 The effect of single IAA additions on the growth of P. multiseries GGA2
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Amin, S., Hmelo, L., van Tol, H. et al. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature 522, 98–101 (2015). https://doi.org/10.1038/nature14488

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