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      Dissolved storage glycans shaped the community composition of abundant bacterioplankton clades during a North Sea spring phytoplankton bloom

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          Abstract

          Background

          Blooms of marine microalgae play a pivotal role in global carbon cycling. Such blooms entail successive blooms of specialized clades of planktonic bacteria that collectively remineralize gigatons of algal biomass on a global scale. This biomass is largely composed of distinct polysaccharides, and the microbial decomposition of these polysaccharides is therefore a process of prime importance.

          Results

          In 2020, we sampled a complete biphasic spring bloom in the German Bight over a 90-day period. Bacterioplankton metagenomes from 30 time points allowed reconstruction of 251 metagenome-assembled genomes (MAGs). Corresponding metatranscriptomes highlighted 50 particularly active MAGs of the most abundant clades, including many polysaccharide degraders. Saccharide measurements together with bacterial polysaccharide utilization loci (PUL) expression data identified β-glucans (diatom laminarin) and α-glucans as the most prominent and actively metabolized dissolved polysaccharide substrates. Both substrates were consumed throughout the bloom, with α-glucan PUL expression peaking at the beginning of the second bloom phase shortly after a peak in flagellate and the nadir in bacterial total cell counts.

          Conclusions

          We show that the amounts and composition of dissolved polysaccharides, in particular abundant storage polysaccharides, have a pronounced influence on the composition of abundant bacterioplankton members during phytoplankton blooms, some of which compete for similar polysaccharide niches. We hypothesize that besides the release of algal glycans, also recycling of bacterial glycans as a result of increased bacterial cell mortality can have a significant influence on bacterioplankton composition during phytoplankton blooms.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40168-023-01517-x.

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          Most cited references72

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                csidhu@mpi-bremen.de
                inga.kirstein@awi.de
                Cedric.Meunier@awi.de
                johannes.rick@awi.de
                Vera.Fofonova@awi.de
                Karen.Wiltshire@awi.de
                nsteinke@mpi-bremen.de
                svidal@mpi-bremen.de
                jheheman@mpi-bremen.de
                huettel@mpipz.mpg.de
                schweder@uni-greifswald.de
                bfuchs@mpi-bremen.de
                ramann@mpi-bremen.de
                hteeling@mpi-bremen.de
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                17 April 2023
                17 April 2023
                2023
                : 11
                : 77
                Affiliations
                [1 ]GRID grid.419529.2, ISNI 0000 0004 0491 3210, Max Planck Institute for Marine Microbiology, ; Celsiusstraße 1, 28359 Bremen, Germany
                [2 ]GRID grid.10894.34, ISNI 0000 0001 1033 7684, Alfred Wegener Institute for Polar and Marine Research, Biologische Anstalt Helgoland, ; P.O. Box 180, 27483 Helgoland, Germany
                [3 ]GRID grid.10894.34, ISNI 0000 0001 1033 7684, Alfred Wegener Institute for Polar and Marine Research, ; Hafenstraße 43, 25992 List/Sylt, Germany
                [4 ]GRID grid.10894.34, ISNI 0000 0001 1033 7684, Alfred Wegener Institute for Polar and Marine Research, ; Klußmannstraße 3, 27570 Bremerhaven, Germany
                [5 ]GRID grid.7704.4, ISNI 0000 0001 2297 4381, Center for Marine Environmental Sciences, , MARUM, University of Bremen, ; Leobener Straße 8, 28359 Bremen, Germany
                [6 ]GRID grid.4372.2, ISNI 0000 0001 2105 1091, Max Planck Genome Centre Cologne, ; Carl Von Linné-Weg 10, 50829 Cologne, Germany
                [7 ]GRID grid.5603.0, Institute of Pharmacy, , University of Greifswald, ; Felix-Hausdorff-Straße 3, 17489 Greifswald, Germany
                [8 ]GRID grid.482724.f, Institute of Marine Biotechnology, ; Walther-Rathenau-Straße 49a, 17489 Greifswald, Germany
                Author information
                http://orcid.org/0000-0003-1386-1881
                http://orcid.org/0000-0003-2580-2694
                http://orcid.org/0000-0002-4070-4286
                http://orcid.org/0000-0002-7842-9347
                http://orcid.org/0000-0002-5956-1844
                http://orcid.org/0000-0002-7148-0529
                http://orcid.org/0000-0002-0464-0158
                http://orcid.org/0000-0002-9408-2849
                http://orcid.org/0000-0002-8700-2564
                http://orcid.org/0000-0001-7165-1714
                http://orcid.org/0000-0002-7213-3596
                http://orcid.org/0000-0001-9828-1290
                http://orcid.org/0000-0002-0846-7372
                http://orcid.org/0000-0003-1889-7859
                Article
                1517
                10.1186/s40168-023-01517-x
                10108472
                37069671
                c1abac40-95c2-42ec-985d-d8a5fdca584b
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 18 November 2022
                : 15 March 2023
                Funding
                Funded by: Max Planck Institute for Marine Microbiology (2)
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                algal bloom,algal polysaccharide,alpha-glucan,bacterioplankton,bacteroidota,beta-glucan,helgoland roads lter,laminarin

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