Cultivation and functional characterization of 79 planctomycetes uncovers their unique biology


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.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


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.


  1. 1.

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

  2. 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).

  3. 3.

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

  4. 4.

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

  5. 5.

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

  6. 6.

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

  7. 7.

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

  8. 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).

  9. 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).

  10. 10.

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

  11. 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).

  12. 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).

  13. 13.

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

  14. 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).

  15. 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).

  16. 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).

  17. 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).

  18. 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).

  19. 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).

  20. 20.

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

  21. 21.

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

  22. 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).

  23. 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).

  24. 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).

  25. 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).

  26. 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).

  27. 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).

  28. 28.

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

  29. 29.

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

  30. 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).

  31. 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).

  32. 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).

  33. 33.

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

  34. 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).

  35. 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).

  36. 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. 37.

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

  38. 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).

  39. 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).

  40. 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. 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).

  42. 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. 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).

  44. 44.

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

  45. 45.

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

  46. 46.

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

  47. 47.

    Navarro-Muñoz, J. et al. A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data. Preprint bioRxiv (2018).

  48. 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).

  49. 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).

  50. 50.

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

  51. 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).

  52. 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).

  53. 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).

  54. 54.

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

  55. 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).

  56. 56.

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

  57. 57.

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

  58. 58.

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

  59. 59.

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

  60. 60.

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

  61. 61.

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

  62. 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).

  63. 63.

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

  64. 64.

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

  65. 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).

  66. 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).

  67. 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).

  68. 68.

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

  69. 69.

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

  70. 70.

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

  71. 71.

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

  72. 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).

  73. 73.

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

  74. 74.

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

  75. 75.

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

  76. 76.

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

  77. 77.

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

  78. 78.

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

  79. 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).

  80. 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).

  81. 81.

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

  82. 82.

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

  83. 83.

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

  84. 84.

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

  85. 85.

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

  86. 86.

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

  87. 87.

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

  88. 88.

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

  89. 89.

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

  90. 90.

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

  91. 91.

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

  92. 92.

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

  93. 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. 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).

  95. 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).

  96. 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).

  97. 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).

  98. 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).

  99. 99.

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

  100. 100.

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

  101. 101.

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

  102. 102.

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

  103. 103.

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

  104. 104.

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

  105. 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).

  106. 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).

  107. 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).

  108. 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).

  109. 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).

  110. 110.

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

  111. 111.

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

  112. 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).

  113. 113.

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

  114. 114.

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

  115. 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).

  116. 116.

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

  117. 117.

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

  118. 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).

  119. 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).

Download references


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

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.

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).

Download citation

Further reading