Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Cultivation and functional characterization of 79 planctomycetes uncovers their unique biology

Abstract

When it comes to the discovery and analysis of yet uncharted bacterial traits, pure cultures are essential as only these allow detailed morphological and physiological characterization as well as genetic manipulation. However, microbiologists are struggling to isolate and maintain the majority of bacterial strains, as mimicking their native environmental niches adequately can be a challenging task. Here, we report the diversity-driven cultivation, characterization and genome sequencing of 79 bacterial strains from all major taxonomic clades of the conspicuous bacterial phylum Planctomycetes. The samples were derived from different aquatic environments but close relatives could be isolated from geographically distinct regions and structurally diverse habitats, implying that ‘everything is everywhere’. With the discovery of lateral budding in ‘Kolteria novifilia’ and the capability of the members of the Saltatorellus clade to divide by binary fission as well as budding, we identified previously unknown modes of bacterial cell division. Alongside unobserved aspects of cell signalling and small-molecule production, our findings demonstrate that exploration beyond the well-established model organisms has the potential to increase our knowledge of bacterial diversity. We illustrate how ‘microbial dark matter’ can be accessed by cultivation techniques, expanding the organismic background for small-molecule research and drug-target detection.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Sampling the phylum Planctomycetes.
Fig. 2: Current diversity of the planctomycetal phylum.
Fig. 3: Planctomycetal cell division.
Fig. 4: Signalling in planctomycetes.
Fig. 5: Secondary metabolite BGCs.

References

  1. Wiegand, S., Jogler, M. & Jogler, C. On the maverick Planctomycetes. FEMS Microbiol. Rev. 42, 739–760 (2018).

    CAS  PubMed  Google Scholar 

  2. Wagner, M. & Horn, M. The Planctomycetes, Verrucomicrobia, Chlamydiae and sister phyla comprise a superphylum with biotechnological and medical relevance. Curr. Opin. Biotechnol. 17, 241–249 (2006).

    CAS  PubMed  Google Scholar 

  3. Peeters, S. H. & van Niftrik, L. Trending topics and open questions in anaerobic ammonium oxidation. Curr. Opin. Chem. Biol. 49, 45–52 (2018).

    PubMed  Google Scholar 

  4. Jeske, O. et al. Developing techniques for the utilization of Planctomycetes as producers of bioactive molecules. Front. Microbiol. 7, 1242 (2016).

    PubMed  PubMed Central  Google Scholar 

  5. van Teeseling, M. C. F. et al. Anammox Planctomycetes have a peptidoglycan cell wall. Nat. Commun. 6, 6878 (2015).

    PubMed  Google Scholar 

  6. Jeske, O. et al. Planctomycetes do possess a peptidoglycan cell wall. Nat. Commun. 6, 7116 (2015).

    CAS  PubMed  Google Scholar 

  7. Boedeker, C. et al. Determining the bacterial cell biology of Planctomycetes. Nat. Commun. 8, 14853 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Devos, D. P. Re-interpretation of the evidence for the PVC cell plan supports a Gram-negative origin. Antonie Van Leeuwenhoek 105, 271–274 (2014).

    PubMed  Google Scholar 

  9. Bondoso, J. et al. Rhodopirellula lusitana sp. nov. and Rhodopirellula rubra sp. nov., isolated from the surface of macroalgae. Syst. Appl. Microbiol. 37, 157–164 (2014).

    CAS  PubMed  Google Scholar 

  10. Hirsch, P. & Müller, M. Planctomyces limnophilus sp. nov., a stalked and budding bacterium from freshwater. Syst. Appl. Microbiol. 6, 276–280 (1985).

    Google Scholar 

  11. Kulichevskaya, I. S. et al. Zavarzinella formosa gen. nov., sp. nov., a novel stalked, Gemmata-like planctomycete from a Siberian peat bog. Int. J. Syst. Evol. Microbiol. 59, 357–364 (2009).

    CAS  PubMed  Google Scholar 

  12. Jeske, O., Jogler, M., Petersen, J., Sikorski, J. & Jogler, C. From genome mining to phenotypic microarrays: Planctomycetes as source for novel bioactive molecules. Antonie Van Leeuwenhoek 104, 551–567 (2013).

    CAS  PubMed  Google Scholar 

  13. O’Malley, M. A. The nineteenth century roots of ‘everything is everywhere’. Nat. Rev. Microbiol. 5, 647–651 (2007).

    PubMed  Google Scholar 

  14. Storesund, J. E., Lanzen, A., Garcia-Moyano, A., Reysenbach, A. L. & Øvreås, L. Diversity patterns and isolation of Planctomycetes associated with metalliferous deposits from hydrothermal vent fields along the Valu Fa Ridge (SW Pacific). Antonie Van Leeuwenhoek 111, 841–858 (2018).

    CAS  PubMed  Google Scholar 

  15. Storesund, J. E. & Øvreås, L. Diversity of Planctomycetes in iron-hydroxide deposits from the arctic mid ocean ridge (AMOR) and description of Bythopirellula goksoyri gen. nov., sp. nov., a novel Planctomycete from deep sea iron-hydroxide deposits. Antonie Van Leeuwenhoek 104, 569–584 (2013).

    CAS  PubMed  Google Scholar 

  16. Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645 (2014).

    CAS  PubMed  Google Scholar 

  17. Galperin, M. Y., Kristensen, D. M., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Microbial genome analysis: the COG approach. Brief. Bioinform. 20, 1063–1070 (2017).

    PubMed Central  Google Scholar 

  18. Galperin, M. Y., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res. 43, D261–D269 (2015).

    CAS  PubMed  Google Scholar 

  19. Jogler, C., Glöckner, F. O. & Kolter, R. Characterization of Planctomyces limnophilus and development of genetic tools for its manipulation establish it as a model species for the phylum Planctomycetes. Appl. Environ. Microbiol. 77, 5826–5829 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Du, S. & Lutkenhaus, J. Assembly and activation of the Escherichia coli divisome. Mol. Microbiol. 105, 177–187 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Wagstaff, J. & Löwe, J. Prokaryotic cytoskeletons: protein filaments organizing small cells. Nat. Rev. Microbiol. 16, 187–201 (2018).

    CAS  PubMed  Google Scholar 

  22. Jogler, C. et al. Identification of proteins likely to be involved in morphogenesis, cell division, and signal transduction in Planctomycetes by comparative genomics. J. Bacteriol. 194, 6419–6430 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Pilhofer, M. et al. Characterization and evolution of cell division and cell wall synthesis genes in the bacterial phyla Verrucomicrobia, Lentisphaerae, Chlamydiae, and Planctomycetes and phylogenetic comparison with rRNA genes. J. Bacteriol. 190, 3192–3202 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Rued, B. E. et al. Structure of the large extracellular loop of FtsX and its interaction with the essential peptidoglycan hydrolase PcsB in Streptococcus pneumoniae. mBio 10, e02622-18 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Fuerst, J. A. & Sagulenko, E. Beyond the bacterium: Planctomycetes challenge our concepts of microbial structure and function. Nat. Rev. Microbiol. 9, 403–413 (2011).

    CAS  PubMed  Google Scholar 

  26. van Teeseling, M. C. F., de Pedro, M. A. & Cava, F. Determinants of bacterial morphology: from fundamentals to possibilities for antimicrobial targeting. Front. Microbiol. 8, 1264 (2017).

    PubMed  PubMed Central  Google Scholar 

  27. Shi, H., Bratton, B. P., Gitai, Z. & Huang, K. C. How to build a bacterial cell: MreB as the foreman of E. coli construction. Cell 172, 1294–1305 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Hussain, S. et al. MreB filaments align along greatest principal membrane curvature to orient cell wall synthesis. eLife 7, e32471 (2018).

    PubMed  PubMed Central  Google Scholar 

  29. Waidner, B. et al. A novel system of cytoskeletal elements in the human pathogen Helicobacter pylori. PLoS Pathog. 5, e1000669 (2009).

    PubMed  PubMed Central  Google Scholar 

  30. Jacquier, N., Viollier, P. H. & Greub, G. The role of peptidoglycan in chlamydial cell division: towards resolving the chlamydial anomaly. FEMS Microbiol. Rev. 39, 262–275 (2015).

    CAS  PubMed  Google Scholar 

  31. Ouellette, S. P., Karimova, G., Subtil, A. & Ladant, D. Chlamydia co-opts the rod shape-determining proteins MreB and Pbp2 for cell division. Mol. Microbiol. 85, 164–178 (2012).

    CAS  PubMed  Google Scholar 

  32. Jacquier, N., Frandi, A., Pillonel, T., Viollier, P. H. & Greub, G. Cell wall precursors are required to organize the chlamydial division septum. Nat. Commun. 5, 3578 (2014).

    PubMed  Google Scholar 

  33. Galperin, M. Y. What bacteria want. Environ. Microbiol. 20, 4221–4229 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Jacob-Dubuisson, F., Mechaly, A., Betton, J.-M. & Antoine, R. Structural insights into the signalling mechanisms of two-component systems. Nat. Rev. Microbiol. 16, 585–593 (2018).

    CAS  PubMed  Google Scholar 

  35. Campagne, S., Allain, F. H. & Vorholt, J. A. Extra cytoplasmic function sigma factors, recent structural insights into promoter recognition and regulation. Curr. Opin. Struct. Biol. 30, 71–78 (2015).

    CAS  PubMed  Google Scholar 

  36. Galperin, M. Y., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Phyletic distribution and lineage-specific domain architectures of archaeal two-component signal transduction systems. J. Bacteriol. 200, e00681-17 (2018).

  37. Mascher, T. Signaling diversity and evolution of extracytoplasmic function (ECF) sigma factors. Curr. Opin. Microbiol. 16, 148–155 (2013).

    CAS  PubMed  Google Scholar 

  38. Staron, A. et al. The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) sigma factor protein family. Mol. Microbiol. 74, 557–581 (2009).

    CAS  PubMed  Google Scholar 

  39. Huang, X., Pinto, D., Fritz, G. & Mascher, T. Environmental sensing in Actinobacteria: a comprehensive survey on the signaling capacity of this phylum. J. Bacteriol. 197, 2517–2535 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Pinto, D. & Mascher, T. in Stress and Environmental Regulation of Gene Expression and Adaptation in Bacteria (ed. F. J. de Bruijn) Ch. 2.6 (Wiley–Blackwell, 2016).

  41. Bayer-Santos, E. et al. Xanthomonas citri T6SS mediates resistance to Dictyostelium predation and is regulated by an ECF σ factor and cognate Ser/Thr kinase. Environ. Microbiol. 20, 1562–1575 (2018).

    CAS  PubMed  Google Scholar 

  42. Castro, A. N., Lewerke, L. T., Hastle, J. L. & Ellermeier, C. D. Signal peptidase is necessary and sufficient for site 1 cleavage of RsiV in Bacillus subtilis in response to lysozyme. J. Bacteriol. 200, e00663-17 (2018).

  43. Tracanna, V., de Jong, A., Medema, M. H. & Kuipers, O. P. Mining prokaryotes for antimicrobial compounds: from diversity to function. FEMS Microbiol. Rev. 41, 417–442 (2017).

    CAS  PubMed  Google Scholar 

  44. Calisto, R. et al. Anticancer activity in planctomycetes. Front. Mar. Sci. 5, 499 (2019).

    Google Scholar 

  45. Cimermancic, P. et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell 158, 412–421 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Medema, M. H. et al. Minimum information about a biosynthetic gene cluster. Nat. Chem. Biol. 11, 625–631 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Navarro-Muñoz, J. et al. A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data. Preprint bioRxiv https://www.biorxiv.org/content/10.1101/445270v1 (2018).

  48. Weber, T. et al. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucleic Acids Res. 43, W237–W243 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Kohn, T. et al. Fuerstia marisgermanicae gen. nov., sp. nov., an unusual member of the phylum Planctomycetes from the German Wadden Sea. Front. Microbiol. 7, 2079 (2016).

    PubMed  PubMed Central  Google Scholar 

  50. Oberbeckmann, S., Kreikemeyer, B. & Labrenz, M. Environmental Factors support the formation of specific bacterial assemblages on microplastics. Front. Microbiol. 8, 2709 (2018).

    PubMed  PubMed Central  Google Scholar 

  51. Sipkema, D. et al. Multiple approaches to enhance the cultivability of bacteria associated with the marine sponge Haliclona (gellius) sp. Appl. Environ. Microbiol. 77, 2130–2140 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Rast, P. et al. Three novel species with peptidoglycan cell walls form the new genus Lacunisphaera gen. nov. in the family Opitutaceae of the verrucomicrobial subdivision 4. Front. Microbiol. 8, 202 (2017).

    PubMed  PubMed Central  Google Scholar 

  53. Schlesner, H. The development of media suitable for the microorganisms morphologically resembling Planctomyces spp., Pirellula spp., and other Planctomycetales from various aquatic habitats using dilute media. Syst. Appl. Microbiol. 17, 135–145 (1994).

    Google Scholar 

  54. Lage, O. M. & Bondoso, J. Bringing Planctomycetes into pure culture. Front. Microbiol. 3, 405 (2012).

    PubMed  PubMed Central  Google Scholar 

  55. Pascual, J. et al. Roseisolibacter agri gen. nov., sp. nov., a novel slow-growing member of the under-represented phylum Gemmatimonadetes. Int. J. Syst. Evol. Microbiol. 68, 1028–1036 (2018).

    PubMed  Google Scholar 

  56. van Kessel, M. A. H. J. et al. Complete nitrification by a single microorganism. Nature 528, 555–559 (2015).

    PubMed  PubMed Central  Google Scholar 

  57. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. O’Connell, J. et al. NxTrim: optimized trimming of Illumina mate pair reads. Bioinformatics 31, 2035–2037 (2015).

    PubMed  Google Scholar 

  59. Wingett, S. W. & Andrews, S. FastQ screen: a tool for multi-genome mapping and quality control. F1000Res. 7, 1338 (2018).

    PubMed  PubMed Central  Google Scholar 

  60. Schmieder, R. & Edwards, R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27, 863–864 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Magoc, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Zerbino, D. R. & Birney, E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821–829 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Koboldt, D. C. et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 22, 568–576 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. McKenna, A. et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Antipov, D., Korobeynikov, A., McLean, J. S. & Pevzner, P. A. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics 32, 1009–1015 (2016).

    CAS  PubMed  Google Scholar 

  68. Boetzer, M., Henkel, C. V., Jansen, H. J., Butler, D. & Pirovano, W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics 27, 578–579 (2011).

    CAS  PubMed  Google Scholar 

  69. Paulino, D. et al. Sealer: a scalable gap-closing application for finishing draft genomes. BMC Bioinform. 16, 230 (2015).

    Google Scholar 

  70. Bosi, E. et al. MeDuSa: a multi-draft based scaffolder. Bioinformatics 31, 2443–2451 (2015).

    CAS  PubMed  Google Scholar 

  71. Green, M. R. & Sambrook, J. Molecular Cloning: A Laboratory Manual. 4th edn (Cold Spring Harbor Laboratory Press, 2012).

  72. Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

    CAS  PubMed  Google Scholar 

  77. Michaelis, W. et al. Microbial reefs in the black sea fueled by anaerobic oxidation of methane. Science 297, 1013–1015 (2002).

    CAS  PubMed  Google Scholar 

  78. Meyerdierks, A. et al. Insights into the genomes of archaea mediating the anaerobic oxidation of methane. Environ. Microbiol. 7, 1937–1951 (2005).

    CAS  PubMed  Google Scholar 

  79. Meyerdierks, A. et al. Metagenome and mRNA expression analyses of anaerobic methanotrophic archaea of the ANME-1 group. Environ. Microbiol. 12, 422–439 (2010).

    CAS  PubMed  Google Scholar 

  80. Muyzer, G., Teske, A., Wirsen, C. O. & Jannasch, H. W. Phylogenetic relationships of Thiomicrospira species and their identification in deep-sea hydrothermal vent samples by denaturing gradient gel electrophoresis of 16S rDNA fragments. Arch. Microbiol. 164, 165–172 (1995).

    CAS  PubMed  Google Scholar 

  81. Yilmaz, P. et al. The SILVA and “All-species living tree project (LTP)” taxonomic frameworks. Nucleic Acids Res. 42, D643–D648 (2014).

    CAS  PubMed  Google Scholar 

  82. Pruesse, E., Peplies, J. & Glöckner, F. O. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28, 1823–1829 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—approximately maximum-likelihood trees for large alignments. PloS ONE 5, e9490 (2010).

    PubMed  PubMed Central  Google Scholar 

  84. Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 1, gkz239 (2019).

    Google Scholar 

  85. Markowitz, V. M. et al. IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Res. 40, D115–D122 (2012).

    CAS  PubMed  Google Scholar 

  86. Lechner, M. et al. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinform. 12, 124 (2011).

    Google Scholar 

  87. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).

    CAS  PubMed  Google Scholar 

  89. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Ronquist, F. & Huelsenbeck, J. P. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574 (2003).

    CAS  PubMed  Google Scholar 

  91. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2017).

  92. Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).

    CAS  PubMed  Google Scholar 

  93. Rodriguez-R, L. M. & Konstantinidis, K. T. The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes. Preprint at PeerJ Prepr. 4, e1900v1901 (2016).

  94. Scornavacca, C., Berry, V., Lefort, V., Douzery, E. J. & Ranwez, V. PhySIC_IST: cleaning source trees to infer more informative supertrees. BMC Bioinform. 9, 413 (2008).

    Google Scholar 

  95. Lagkouvardos, I. et al. IMNGS: a comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies. Sci. Rep. 6, 33721 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Kaas, R. S., Friis, C., Ussery, D. W. & Aarestrup, F. M. Estimating variation within the genes and inferring the phylogeny of 186 sequenced diverse Escherichia coli genomes. BMC Genom. 13, 577 (2012).

    CAS  Google Scholar 

  97. Koonin, E. V. & Wolf, Y. I. Genomics of bacteria and archaea: the emerging dynamic view of the prokaryotic world. Nucleic Acids Res. 36, 6688–6719 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Huerta-Cepas, J. et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 44, D286–D293 (2016).

    CAS  PubMed  Google Scholar 

  99. Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  100. Marchler-Bauer, A. et al. CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Res. 45, D200–D203 (2017).

    CAS  PubMed  Google Scholar 

  101. Ingerson-Mahar, M. & Gitai, Z. A growing family: the expanding universe of the bacterial cytoskeleton. FEMS Microbiol. Rev. 36, 256–266 (2012).

    CAS  PubMed  Google Scholar 

  102. Graumann, P. L. Cytoskeletal elements in bacteria. Annu. Rev. Microbiol. 61, 589–618 (2007).

    CAS  PubMed  Google Scholar 

  103. Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44, D279–D285 (2016).

    CAS  PubMed  Google Scholar 

  104. Eddy, S. R. Accelerated profile HMM searches. PLoS Comp. Biol. 7, e1002195 (2011).

    CAS  Google Scholar 

  105. Marchler-Bauer, A. et al. CDD: a database of conserved domain alignments with links to domain three-dimensional structure. Nucleic Acids Res. 30, 281–283 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    CAS  PubMed  Google Scholar 

  107. Hoang, T. T., Karkhoff-Schweizer, R. R., Kutchma, A. J. & Schweizer, H. P. A broad-host-range Flp-FRT recombination system for site-specific excision of chromosomally-located DNA sequences: application for isolation of unmarked Pseudomonas aeruginosa mutants. Gene 212, 77–87 (1998).

    CAS  PubMed  Google Scholar 

  108. Herrero, M., de Lorenzo, V. & Timmis, K. N. Transposon vectors containing non-antibiotic resistance selection markers for cloning and stable chromosomal insertion of foreign genes in Gram-negative bacteria. J. Bacteriol. 172, 6557–6567 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Rivas-Marin, E., Canosa, I., Santero, E. & Devos, D. P. Development of genetic tools for the manipulation of the Planctomycetes. Front. Microbiol. 7, 914 (2016).

    PubMed  PubMed Central  Google Scholar 

  110. Krzywinski, M. I. et al. Circos: an information aesthetic for comparative genomics. Genome Res. 19, 1639–1645 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Pritchard, L., Glover, R. H., Humphris, S., Elphinstone, J. G. & Toth, I. K. Genomics and taxonomy in diagnostics for food security: soft-rotting enterobacterial plant pathogens. Anal. Methods 8, 12–24 (2016).

    Google Scholar 

  113. Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 11, 119 (2010).

    Google Scholar 

  114. Lagesen, K. et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 35, 3100–3108 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  115. Galperin, M. Y. A census of membrane-bound and intracellular signal transduction proteins in bacteria: bacterial IQ, extroverts and introverts. BMC Microbiol. 5, 35 (2005).

    PubMed  PubMed Central  Google Scholar 

  116. Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29–W37 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).

    PubMed  PubMed Central  Google Scholar 

  118. Gomez-Santos, N., Perez, J., Sanchez-Sutil, M. C., Moraleda-Munoz, A. & Munoz-Dorado, J. CorE from Myxococcus xanthus is a copper-dependent RNA polymerase sigma factor. PLoS Genet. 7, e1002106 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. Sonnhammer, E. L., von Heijne, G. & Krogh, A. A hidden Markov model for predicting transmembrane helices in protein sequences. Proc. Int. Conf. Intell. Syst. Mol. Biol. 6, 175–182 (1998).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We appreciate the help of C. Wiegand, A. Scharmach and B. Schink in naming the isolates appropriately according to community standards. We are also grateful to I. Lagkouvardos and A. Kioukis for enabling our analyses on the IMNGS platform. We thank L. van Niftrik for providing bacterial biomass from anaerobic lab-scale bioreactors. The GHOSTDABS project provided the left-most image in the upper panel of Fig. 1. We further thank J. Piel for scientific discussion and C. Spröer for help with the sequencing of the planctomycetal strains. This work was funded by the Deutsche Forschungsgemeinschaft (grant no. JO 893/4-1) and the Volkswagen foundation (experiment no. 89256). M.Y.G. was funded by the NIH IRP at the US National Library of Medicine. Work in the Mascher lab was supported by the Deutsche Forschungsgemeinschaft (grant no. MA2837/2-2) and the Bundeministerium für Bildung und Forschung in the framework of the ERAnet Synthetic Biology (project: ERASynBio2-ECFexpress). R.A. and A.M. were funded by the Max Planck Society.

Author information

Authors and Affiliations

Authors

Contributions

S.W., M.J. and C.J. designed the study. M.J., T.K., A.H., P.R., J.E.S., O.M.L. and L.Ø. cultivated the planctomycetes and established axenic cultures. M.J., C.B., T.K., A.H., P.R., S.O., O.J., J.E.S., T.P., B.J.M., P.H., R.-W.M., F.B., M.L., A.M.S., A.-K.K., L.Ø., A.M. and C.J. were involved in the sampling, sample processing and basic enrichments. S.W., J.V. and B.B. sequenced and assembled the genomes. E.R.-M. and D.P.D. constructed the deletion mutants, A.M. and R.A. constructed the planctomycetal fosmid, S.L. obtained the planctomycetal MAGs and O.M.L. isolated DNA for sequencing. C.B., T.K., S.H.P., M.R. and C.J. performed the microscopy. H.O.d.C., M.S.M.J., T.M., J.O., M.H.M. and R.A. provided expertise and supervision. S.W., D.P., J.V., N.K., M.H.M., M.Y.G. and C.J. analysed and interpreted data. S.W. and C.J. wrote the manuscript with major contributions from M.J., C.B., D.P., J.V., S.O., N.K., R.A., M.H.M, L.Ø. and M.Y.G., and with help and approval from all authors.

Corresponding author

Correspondence to Christian Jogler.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–46, Supplementary Tables 8, 9 and 11–13, Supplementary Table legends, Supplementary Video legends, Supplementary Data legends and Supplementary References.

Reporting Summary

Supplementary Table 1

Strain information.

Supplementary Table 2

16S rRNA gene identity-based similarity matrix.

Supplementary Table 3

Planctomycetal orthologous groups of strict and soft core genome genes.

Supplementary Table 4

Pan and core genome analysis of the defined planctomycetal clades.

Supplementary Table 5

Identification of genes related to cell division and peptidoglycan biosynthesis.

Supplementary Table 6

Signal transduction systems.

Supplementary Table 7

Results of the identification and analysis of ECF sigma factors.

Supplementary Table 10

Results of AntiSMASH 3.0 analysis.

Supplementary Data 1

16S rRNA gene sequence analysis of 9002 non-redundant Planctomycetes in Newick format.

Supplementary Data 2

Multilocus sequence analysis tree c90cov50ML in Newick format.

Supplementary Data 3

Multilocus sequence analysis tree c90cov50BI in Newick format.

Supplementary Data 4

Multilocus sequence analysis tree c90cov70ML in Newick format.

Supplementary Data 5

Multilocus sequence analysis tree c90cov70BI in Newick format.

Supplementary Data 6

Multilocus sequence analysis tree c95cov50ML in Newick format.

Supplementary Data 7

Multilocus sequence analysis tree c95cov50BI in Newick format.

Supplementary Data 8

Multilocus sequence analysis tree c95cov70ML in Newick format.

Supplementary Data 9

Multilocus sequence analysis tree c95cov70BI in Newick format.

Supplementary Data 10

Maximum likelihood 16S rRNA tree in Newick format.

Supplementary Data 11

Bayesian interference 16S rRNA tree in Newick format.

Supplementary Data 12

Maximum likelihood RpoB tree in Newick format.

Supplementary Data 13

Bayesian interference RpoB tree in Newick format.

Supplementary Data 14

Maximum likelihood ribosomal protein tree in Newick format.

Supplementary Data 15

Bayesian interference ribosomal protein tree in Newick format.

Supplementary Data 16

Binary gene content analysis tree in Newick format.

Supplementary Data 17

Amino acid identity Neighbour joining tree in Newick format.

Supplementary Data 18

Veto method supertree analysis in Newick format.

Supplementary Data 19

Voting method supertree analysis in Newick format.

Supplementary Video 1

Lateral budding of ‘Kolteria novifilia’ Pan216.

Supplementary Video 2

Division of ‘Saltatorellus ferox’ Poly30 by budding and binary fission.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wiegand, S., Jogler, M., Boedeker, C. et al. Cultivation and functional characterization of 79 planctomycetes uncovers their unique biology. Nat Microbiol 5, 126–140 (2020). https://doi.org/10.1038/s41564-019-0588-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-019-0588-1

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing