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Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan

Nature Microbiology volume 5, pages 1026–1039 (2020)Cite this article

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Abstract

Brown algae are important players in the global carbon cycle by fixing carbon dioxide into 1 Gt of biomass annually, yet the fate of fucoidan—their major cell wall polysaccharide—remains poorly understood. Microbial degradation of fucoidans is slower than that of other polysaccharides, suggesting that fucoidans are more recalcitrant and may sequester carbon in the ocean. This may be due to the complex, branched and highly sulfated structure of fucoidans, which also varies among species of brown algae. Here, we show that ‘Lentimonas’ sp. CC4, belonging to the Verrucomicrobia, acquired a remarkably complex machinery for the degradation of six different fucoidans. The strain accumulated 284 putative fucoidanases, including glycoside hydrolases, sulfatases and carbohydrate esterases, which are primarily located on a 0.89-megabase pair plasmid. Proteomics reveals that these enzymes assemble into substrate-specific pathways requiring about 100 enzymes per fucoidan from different species of brown algae. These enzymes depolymerize fucoidan into fucose, which is metabolized in a proteome-costly bacterial microcompartment that spatially constrains the metabolism of the toxic intermediate lactaldehyde. Marine metagenomes and microbial genomes show that Verrucomicrobia including ‘Lentimonas’ are abundant and highly specialized degraders of fucoidans and other complex polysaccharides. Overall, the complexity of the pathways underscores why fucoidans are probably recalcitrant and more slowly degraded, since only highly specialized organisms can effectively degrade them in the ocean.

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Fig. 1: ‘Lentimonas’ sp. CC4 has a megaplasmid and distinct genetic loci for the degradation of sulfated polysaccharides.
Fig. 2: Degradation of complex fucoidans by specialized ‘Lentimonas’ spp.
Fig. 3: Differential proteomics reveals pathways for fucoidan degradation.
Fig. 4: Enzymatic specificity of degradation pathways for diverse fucoidans.
Fig. 5: High metabolic burden to express dedicated pathways for fucoidans including a fucose-specific BMC.
Fig. 6: Verrucomicrobia are abundant and specialized polysaccharide degraders.

Data availability

The data generated and analysed in the current study are publicly available. The genomic and transcriptomic data presented in this study were deposited under the accession code PRJEB34624 in the European Nucleotide Archive using the data brokerage service of the German Federation for Biological Data, in compliance with the minimal information about any (x) sequence (MIxS) standard77,78,79. Mass spectrometry data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015328. The miTAGs from OSD and Tara Oceans were deposited at https://figshare.com/articles/16S_miTAGs_Sichert_et_al_2019/9904793. Strain ‘Lentimonas’ sp. CC4 was deposited at the Deutsche Sammlung von Mikroorganismen und Zellkulturen under accession DSM 110005. Reads of all genomes were deposited under accession SAMEA6101985 to SAMEA6101992 and assemblies are deposited under GCA_902726575, GCA_902726585, GCA_902726595, GCA_902726605, GCA_902728225, GCA_902728235, GCA_902728245 and GCA_902728255. The reads for ‘Lentimonas’ sp. CC4 and ‘Lentimonas’ sp. CC6 are deposited under the accessions SAMEA6101984 and SAMEA6101969, respectively.

Code availability

The workflow for analysing the metagenomic and miTAG data can be found at https://github.com/mschecht/lentimonas_env_analysis/.

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Acknowledgements

We thank K. Caspersen for help with metabolite measurements and N. Dubilier for providing access to mass spectrometry resources. We thank T. Ferdelman and K. Imhoff for expertise in sulfate quantification, M.-K. Zühlke for submission of the proteome data to PRIDE, I. Kostadinov of German Federation for Biological Data for sequence data deposition and B. Hüttel from the Max Planck-Genome-Centre Cologne for assistance with genome sequencing and assembly. A.S. and M.S.S. are members of the International Max Planck Research School of Marine Microbiology (MarMic). J.H.H. acknowledges funding from the Max-Planck-Gesellschaft and from the Emmy Noether Program of the DFG (grant no. HE 7217/1-1). M.F.P. acknowledges support from the US Department of Energy (DE-SC0008743). We thank A. Bolte for the HPAEC-PAD measurements and acknowledge support from the HGF-POSY project. The work of S.M., T.S. and D.B. was financially supported by grants (nos. BE 3869/4-1 and SCHW 595/10-1) of the DFG in the framework of the research unit FOR 2406 ‘Proteogenomics of Marine Polysaccharide Utilization’ (POMPU). F.U. was supported by a scholarship from the Institute of Marine Biotechnology.

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Author notes

  1. Christopher H. Corzett

    Present address: Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA

  2. Antonio Fernandez-Guerra

    Present address: Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark

  3. These authors contributed equally: Andreas Sichert, Christopher H. Corzett.

Authors and Affiliations

  1. Max Planck Institute for Marine Microbiology, Bremen, Germany

    Andreas Sichert, Matthew S. Schechter, Antonio Fernandez-Guerra, Manuel Liebeke & Jan-Hendrik Hehemann

  2. Center for Marine Environmental Sciences, MARUM, University of Bremen, Bremen, Germany

    Andreas Sichert, Antonio Fernandez-Guerra & Jan-Hendrik Hehemann

  3. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Christopher H. Corzett & Martin F. Polz

  4. Pharmaceutical Biotechnology, Institute of Pharmacy, University of Greifswald, Greifswald, Germany

    Frank Unfried, Stephanie Markert & Thomas Schweder

  5. Institute of Marine Biotechnology, Greifswald, Germany

    Frank Unfried, Stephanie Markert & Thomas Schweder

  6. Microbial Proteomics, Institute of Microbiology, University of Greifswald, Greifswald, Germany

    Dörte Becher

  7. Division of Microbial Ecology, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

    Martin F. Polz

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Contributions

J.-H.H. and M.F.P. initiated the study and directed the project. C.H.C. and A.S. conducted the experiments. C.H.C. isolated the strains. F.U., S.M. and T.S. conducted the proteome analysis for which D.B. provided resources. M.S.S. and A.F.-G. analysed the OSD and Tara Oceans. M.L. conducted the gas chromatography–mass spectrometry measurements and provided metabolomics resources. A.S., J.-H.H. and M.F.P. prepared the manuscript and received input from all authors.

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Correspondence to Jan-Hendrik Hehemann.

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Extended data

Extended Data Fig. 1 Genome comparison of isolated ‘Lentimonas’ strains including the closest reference genome of Coraliomargarita akajimensis DSM 45221.

Contigs of Illumina sequenced genomes (LCC4 to LCC19) were aligned to the PacBio genome of LCC4. The heatmap shows their average nucleotide identity based on Blast (ANIb). The text inside each cell shows the ANIb and in brackets, the percentage of sequences that could be aligned between contigs.

Extended Data Fig. 2 Genome overview showing transcript levels and relative protein abundances of identified PULs in ‘Lentimonas’ sp. CC4.

The outermost ring shows the genes and the text label their annotation. The next five rings from outside to inside show the protein abundance as a heatmap of riBAQ z-scores during growth on galactose, ι-carrageenan, fucose, fucoidan from Cladosiphon okamuranus and Fucus vesiculosus. The three innermost rings show a heatmap of log2-transformed transcript levels (in TPM) during growth on mannose, ι-carrageenan and fucoidan from F. vesiculosus.

Extended Data Fig. 3 Depolymerization of fucoidans and ι-carrageenan by ‘Lentimonas’ sp. CC4.

a, Separation of charged polysaccharides via C-PAGE to monitor the change of molecular weight. Gel images show the first and last time point of ‘Lentimonas’ sp. CC4 during growth on fucoidans and ι-carrageenan. b, HPAEC-PAD chromatogram using the PA100 column to profile production of oligosaccharides during growth on different substrates. Cultures were grown in triplicates and representative chromatograms and gel images are shown. Chromatograms are color coded according to lag (blue), exponential (organge, green, red, purple) and stationary (brown) growth phase.

Extended Data Fig. 4 Comparison between RNAseq and proteome analysis.

a, Gene per gene comparison of transcripts per million (TPM) between ‘Lentimonas’ sp. CC4 and CC6 under the same growth condition. The graph shows a hexbin plot, in which adjacent datapoints are binned into hexagons and the number of data points per hexbin are represented by the colored gradient. In total, the transcription of 4005 genes across eight conditions (n = 32040) was compared. b, Gene per gene expression of CAZymes and sulfatases that are significantly upregulated comparing CC4 growing on fucoidan from F. vesiculosus versus ι-carrageenan in proteomics and transcriptomics. The data points are colored by a kernel density estimation using a normal distribution of the binary logarithm of the TPM and riBAQ values. In total, the expression of 128 genes was compared (n = 128).

Extended Data Fig. 5 Phylogenetic tree of GH29 enzymes from ‘Lentimonas’ sp. CC4.

Colored boxes along the tree branches comprise proteins over 50% identity and colored boxed around leaves denote their gene regulation according to their membership in a cluster of co-regulated enzymes (Fig. 3a). Node labels indicate the bootstrap support value and as outgroup, we used a GH107 enzyme which display structural similarities to GH29 enzymes24.

Extended Data Fig. 6 CAZyme and sulfatase content of operons of ‘Lentimonas’ sp. CC4.

The heatmap shows the copy number of each enzyme family per operon. Rows and columns are arranged according to hierarchical clustering using the ‘cityblock’ distance metric. Only operons with at least one differentially expressed enzyme are shown.

Extended Data Fig. 7 Quantification of cross-reactivity by batch enzyme extracts.

a, Release of reducing ends by batch enzyme extracts extracted from ‘Lentimonas’ sp. CC4 on different substrates. Rows represent substrates that were used to grow ‘Lentimonas’ sp. CC4 prior to enzyme extraction and columns represent substrates used for the enzyme reaction. Colored data points represent the reducing ends measured via the PAHBAH assay over time and the colored line denotes a fit of the data to a saturation curve. b, Left, the rate of released reducing ends after 30 minutes of the reaction in the linear part of the reaction. Right, the rate of released reducing ends normalized to the maximum rate per substrate. The height of the bar denotes the mean and the error bar the standard deviation from biologically independent experiments (n ≥ 3).

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Sichert, A., Corzett, C.H., Schechter, M.S. et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol 5, 1026–1039 (2020). https://doi.org/10.1038/s41564-020-0720-2

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