Movatterモバイル変換


[0]ホーム

URL:


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.

Advertisement

Nature
  • Article
  • Published:

Isolation of an archaeon at the prokaryote–eukaryote interface

Naturevolume 577pages519–525 (2020)Cite this article

Subjects

Abstract

The origin of eukaryotes remains unclear1,2,3,4. Current data suggest that eukaryotes may have emerged from an archaeal lineage known as ‘Asgard’ archaea5,6. Despite the eukaryote-like genomic features that are found in these archaea, the evolutionary transition from archaea to eukaryotes remains unclear, owing to the lack of cultured representatives and corresponding physiological insights. Here we report the decade-long isolation of an Asgard archaeon related to Lokiarchaeota from deep marine sediment. The archaeon—‘Candidatus Prometheoarchaeum syntrophicum’ strain MK-D1—is an anaerobic, extremely slow-growing, small coccus (around 550 nm in diameter) that degrades amino acids through syntrophy. Although eukaryote-like intracellular complexes have been proposed for Asgard archaea6, the isolate has no visible organelle-like structure. Instead,Ca. P. syntrophicum is morphologically complex and has unique protrusions that are long and often branching. On the basis of the available data obtained from cultivation and genomics, and reasoned interpretations of the existing literature, we propose a hypothetical model for eukaryogenesis, termed the entangle–engulf–endogenize (also known as E3) model.

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

Access options

Access through your institution

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

9,800 Yen / 30 days

cancel any time

Subscription info for Japanese customers

We have a dedicated website for our Japanese customers. Please go tonatureasia.com to subscribe to this journal.

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Growth curves and photomicrographs of the cultured Lokiarchaeota strain MK-D1.
Fig. 2: Syntrophic amino acid utilization of MK-D1.
Fig. 3: Microscopy characterization and lipid composition of MK-D1.
Fig. 4: Phylogeny of MK-D1 and catabolic features of Asgard archaea.
Fig. 5: Proposed hypothetical model for eukaryogenesis.

Similar content being viewed by others

Data availability

Genomes forCa. P. syntrophicum MK-D1,Halodesulfovibrio sp. MK-HDV andMethanogenium sp. MK-MG are available under GenBank BioProject accession numbersPRJNA557562,PRJNA557563 andPRJNA557565, respectively. The iTAG sequence data was deposited in BioProjectPRJDB8518 with SRA accession numbersDRR184081DRR184101. The 16S rRNA gene sequences of MK-D1,Halodesulfovibrio sp. MK-HDV,Methanogenium sp. MK-MG and clones obtained from primary enrichment culture were deposited in the DDBJ/EMBL/GenBank database under accession numbersLC490619LC490624. The gene expression data of MK-D1 in BioProjectPRJDB9032 with the accession numberDRR199588. The cryo-electron tomograms ofCa. P. syntrophicum MK-D1 have been deposited in the EMDB with accession codesEMD-0809 andEMD-0852.

References

  1. López-García, P. & Moreira, D. Open questions on the origin of eukaryotes.Trends Ecol. Evol.30, 697–708 (2015).

    Article PubMed PubMed Central  Google Scholar 

  2. Martin, W. F., Garg, S. & Zimorski, V. Endosymbiotic theories for eukaryote origin.Phil. Trans. R. Soc. Lond. B370, 20140330 (2015).

    Article CAS  Google Scholar 

  3. Eme, L., Spang, A., Lombard, J., Stairs, C. W. & Ettema, T. J. G. Archaea and the origin of eukaryotes.Nat. Rev. Microbiol.15, 711–723 (2017).

    Article CAS PubMed  Google Scholar 

  4. Koonin, E. V. Origin of eukaryotes from within archaea, archaeal eukaryome and bursts of gene gain: eukaryogenesis just made easier? Phil.Trans. R. Soc. Lond. B370, 20140333 (2015).

    Article CAS  Google Scholar 

  5. Spang, A. et al. Complex archaea that bridge the gap between prokaryotes and eukaryotes.Nature521, 173–179 (2015).

    Article ADS CAS PubMed PubMed Central  Google Scholar 

  6. Zaremba-Niedzwiedzka, K. et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity.Nature541, 353–358 (2017).

    Article ADS CAS PubMed  Google Scholar 

  7. Sousa, F. L., Neukirchen, S., Allen, J. F., Lane, N. & Martin, W. F. Lokiarchaeon is hydrogen dependent.Nat. Microbiol.1, 16034 (2016).

    Article CAS PubMed  Google Scholar 

  8. Seitz, K. W., Lazar, C. S., Hinrichs, K.-U., Teske, A. P. & Baker, B. J. Genomic reconstruction of a novel, deeply branched sediment archaeal phylum with pathways for acetogenesis and sulfur reduction.ISME J.10, 1696–1705 (2016).

    Article CAS PubMed PubMed Central  Google Scholar 

  9. Dombrowski, N., Teske, A. P. & Baker, B. J. Expansive microbial metabolic versatility and biodiversity in dynamic Guaymas Basin hydrothermal sediments.Nat. Commun.9, 4999 (2018).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  10. Liu, Y. et al. Comparative genomic inference suggests mixotrophic lifestyle for Thorarchaeota.ISME J.12, 1021–1031 (2018).

    Article CAS PubMed PubMed Central  Google Scholar 

  11. Seitz, K. W. et al. Asgard archaea capable of anaerobic hydrocarbon cycling.Nat. Commun.10, 1822 (2019).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  12. Spang, A. et al. Proposal of the reverse flow model for the origin of the eukaryotic cell based on comparative analyses of Asgard archaeal metabolism.Nat. Microbiol.4, 1138–1148 (2019).

    Article CAS PubMed  Google Scholar 

  13. Pushkarev, A. et al. A distinct abundant group of microbial rhodopsins discovered using functional metagenomics.Nature558, 595–599 (2018).

    Article ADS CAS PubMed  Google Scholar 

  14. Bulzu, P.-A. et al. Casting light on Asgardarchaeota metabolism in a sunlit microoxic niche.Nat. Microbiol.4, 1129–1137 (2019).

    Article CAS PubMed  Google Scholar 

  15. Aoki, M. et al. A long-term cultivation of an anaerobic methane-oxidizing microbial community from deep-sea methane-seep sediment using a continuous-flow bioreactor.PLoS ONE9, e105356 (2014).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  16. Schink, B. & Stams, A. J. inThe Prokaryotes: Prokaryotic Communities and Ecophysiology (eds Rosenberg, E. et al.) 471–493 (Springer, 2013).

  17. Knittel, K., Lösekann, T., Boetius, A., Kort, R. & Amann, R. Diversity and distribution of methanotrophic archaea at cold seeps.Appl. Environ. Microbiol.71, 467–479 (2005).

    Article ADS CAS PubMed PubMed Central  Google Scholar 

  18. Albers, S.-V. & Meyer, B. H. The archaeal cell envelope.Nat. Rev. Microbiol.9, 414–426 (2011).

    Article CAS PubMed  Google Scholar 

  19. Marguet, E. et al. Membrane vesicles, nanopods and/or nanotubes produced by hyperthermophilic archaea of the genusThermococcus.Biochem. Soc. Trans.41, 436–442 (2013).

    Article CAS PubMed  Google Scholar 

  20. Rosenshine, I., Tchelet, R. & Mevarech, M. The mechanism of DNA transfer in the mating system of an archaebacterium.Science245, 1387–1389 (1989).

    Article ADS CAS PubMed  Google Scholar 

  21. Imachi, H. et al. Cultivation of methanogenic community from subseafloor sediments using a continuous-flow bioreactor.ISME J.5, 1913–1925 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  22. Da Cunha, V., Gaia, M., Gadelle, D., Nasir, A. & Forterre, P. Lokiarchaea are close relatives of Euryarchaeota, not bridging the gap between prokaryotes and eukaryotes.PLoS Genet.13, e1006810 (2017).

    Article PubMed PubMed Central CAS  Google Scholar 

  23. Da Cunha, V., Gaia, M., Nasir, A. & Forterre, P. Asgard archaea do not close the debate about the universal tree of life topology.PLoS Genet.14, e1007215 (2018).

    Article PubMed PubMed Central CAS  Google Scholar 

  24. Spang, A. et al. Asgard archaea are the closest prokaryotic relatives of eukaryotes.PLoS Genet.14, e1007080 (2018).

    Article PubMed PubMed Central CAS  Google Scholar 

  25. Brunk, C. F. & Martin, W. F. Archaeal histone contributions to the origin of eukaryotes.Trends Microbiol.27, 703–714 (2019).

    Article CAS PubMed  Google Scholar 

  26. Buckel, W. & Thauer, R. K. Energy conservation via electron bifurcating ferredoxin reduction and proton/Na+ translocating ferredoxin oxidation.Biochim. Biophys. Acta1827, 94–113 (2013).

    Article CAS PubMed  Google Scholar 

  27. Ma, K., Zhou, H. Z. & Adams, M. W. W. Hydrogen production from pyruvate by enzymes purified from the hyperthermophilic archaeon,Pyrococcus furiosus: a key role for NADPH.FEMS Microbiol. Lett.122, 245–250 (1994).

    Article CAS  Google Scholar 

  28. Nobu, M. K. et al. The genome ofSyntrophorhabdus aromaticivorans strain UI provides new insights for syntrophic aromatic compound metabolism and electron flow.Environ. Microbiol.17, 4861–4872 (2015).

    Article CAS PubMed  Google Scholar 

  29. Martin, W. & Müller, M. The hydrogen hypothesis for the first eukaryote.Nature392, 37–41 (1998).

    Article ADS CAS PubMed  Google Scholar 

  30. Lyons, T. W., Reinhard, C. T. & Planavsky, N. J. The rise of oxygen in Earth’s early ocean and atmosphere.Nature506, 307–315 (2014).

    Article ADS CAS PubMed  Google Scholar 

  31. Davín, A. A. et al. Gene transfers can date the tree of life.Nat. Ecol. Evol.2, 904–909 (2018).

    Article PubMed PubMed Central  Google Scholar 

  32. Kump, L. R. et al. Isotopic evidence for massive oxidation of organic matter following the great oxidation event.Science334, 1694–1696 (2011).

    Article ADS CAS PubMed  Google Scholar 

  33. Andersson, S. G. & Kurland, C. G. Origins of mitochondria and hydrogenosomes.Curr. Opin. Microbiol.2, 535–541 (1999).

    Article CAS PubMed  Google Scholar 

  34. Fenchel, T. & Finlay, B. J. Oxygen toxicity, respiration and behavioural responses to oxygen in free-living anaerobic ciliates.J. Gen. Microbiol.136, 1953–1959 (1990).

    Article CAS  Google Scholar 

  35. Moreira, D. & López-García, P. Symbiosis between methanogenic archaea and δ-proteobacteria as the origin of eukaryotes: the syntrophic hypothesis.J. Mol. Evol.47, 517–530 (1998).

    Article ADS CAS PubMed  Google Scholar 

  36. López-García, P. & Moreira, D. Selective forces for the origin of the eukaryotic nucleus.BioEssays28, 525–533 (2006).

    Article PubMed CAS  Google Scholar 

  37. Burns, J. A., Pittis, A. A. & Kim, E. Gene-based predictive models of trophic modes suggest Asgard archaea are not phagocytotic.Nat. Ecol. Evol.2, 697–704 (2018).

    Article PubMed  Google Scholar 

  38. Martin, W. F., Tielens, A. G. M., Mentel, M., Garg, S. G. & Gould, S. B. The physiology of phagocytosis in the context of mitochondrial origin.Microbiol. Mol. Biol. Rev.81, e00008-17 (2017).

    Article CAS PubMed PubMed Central  Google Scholar 

  39. Baum, D. A. & Baum, B. An inside-out origin for the eukaryotic cell.BMC Biol.12, 76 (2014).

    Article PubMed PubMed Central CAS  Google Scholar 

  40. Hutson, S. M. & Rannels, S. L. Characterization of a mitochondrial transport system for branched chain α-keto acids.J. Biol. Chem.260, 14189–14193 (1985).

    Article CAS PubMed  Google Scholar 

  41. Hug, L. A., Stechmann, A. & Roger, A. J. Phylogenetic distributions and histories of proteins involved in anaerobic pyruvate metabolism in eukaryotes.Mol. Biol. Evol.27, 311–324 (2010).

    Article CAS PubMed  Google Scholar 

  42. Degli Esposti, M. et al. Alpha proteobacterial ancestry of the [Fe–Fe]-hydrogenases in anaerobic eukaryotes.Biol. Direct11, 34 (2016).

    Article PubMed PubMed Central CAS  Google Scholar 

  43. Pieulle, L. et al. Isolation and characterization of the pyruvate-ferredoxin oxidoreductase from the sulfate-reducing bacteriumDesulfovibrio africanus.Biochim. Biophys. Acta1250, 49–59 (1995).

    Article PubMed  Google Scholar 

  44. Liebgott, P.-P. et al. Relating diffusion along the substrate tunnel and oxygen sensitivity in hydrogenase.Nat. Chem. Biol.6, 63–70 (2010).

    Article CAS PubMed  Google Scholar 

  45. Winkler, H. H. & Neuhaus, H. E. Non-mitochondrial ATP transport.Trends Biochem. Sci.24, 64–68 (1999).

    Article CAS PubMed  Google Scholar 

  46. Gray, M. W. The pre-endosymbiont hypothesis: a new perspective on the origin and evolution of mitochondria.Cold Spring Harb. Perspect. Biol.6, a016097 (2014).

    Article PubMed PubMed Central CAS  Google Scholar 

  47. Villanueva, L., Schouten, S. & Damsté, J. S. S. Phylogenomic analysis of lipid biosynthetic genes of Archaea shed light on the ‘lipid divide’.Environ. Microbiol.19, 54–69 (2017).

    Article CAS PubMed  Google Scholar 

  48. Caforio, A. et al. ConvertingEscherichia coli into an archaebacterium with a hybrid heterochiral membrane.Proc. Natl Acad. Sci. USA115, 3704–3709 (2018).

    Article CAS PubMed PubMed Central  Google Scholar 

  49. Nakamura, K. et al. Application of pseudomurein endoisopeptidase to fluorescence in situ hybridization of methanogens within the familyMethanobacteriaceae.Appl. Environ. Microbiol.72, 6907–6913 (2006).

    Article ADS CAS PubMed PubMed Central  Google Scholar 

  50. Cevc, G. & Richardsen, H. Lipid vesicles and membrane fusion.Adv. Drug Deliv. Rev.38, 207–232 (1999).

    Article CAS PubMed  Google Scholar 

  51. Nunoura, T. et al. Microbial diversity in deep-sea methane seep sediments presented by SSU rRNA gene tag sequencing.Microbes Environ.27, 382–390 (2012).

    Article PubMed PubMed Central  Google Scholar 

  52. Toki, T., Higa, R., Ijiri, A., Tsunogai, U. & Ashi, J. Origin and transport of pore fluids in the Nankai accretionary prism inferred from chemical and isotopic compositions of pore water at cold seep sites off Kumano.Earth Planets Space66, 137 (2014).

    Article ADS  Google Scholar 

  53. Nakahara, N. et al.Aggregatilinea lenta gen. nov., sp. nov., a slow-growing, facultatively anaerobic bacterium isolated from subseafloor sediment, and proposal of the new orderAggregatilineales ord. nov. within the classAnaerolineae of the phylumChloroflexi.Int. J. Syst. Evol. Microbiol.69, 1185–1194 (2019).

    Article CAS PubMed  Google Scholar 

  54. Murakami, S., Fujishima, K., Tomita, M. & Kanai, A. Metatranscriptomic analysis of microbes in an oceanfront deep-subsurface hot spring reveals novel small RNAs and type-specific tRNA degradation.Appl. Environ. Microbiol.78, 1015–1022 (2012).

    Article ADS CAS PubMed PubMed Central  Google Scholar 

  55. Imachi, H. et al. Cultivable microbial community in 2-km-deep, 20-million-year-old subseafloor coalbeds through ~1000 days anaerobic bioreactor cultivation.Sci. Rep.9, 2305 (2019).

    Article PubMed PubMed Central CAS  Google Scholar 

  56. Miyashita, A. et al. Development of 16S rRNA gene-targeted primers for detection of archaeal anaerobic methanotrophs (ANMEs).FEMS Microbiol. Lett.297, 31–37 (2009).

    Article CAS PubMed  Google Scholar 

  57. Yamaguchi, T. et al. In situ DNA-hybridization chain reaction (HCR): a facilitated in situ HCR system for the detection of environmental microorganisms.Environ. Microbiol.17, 2532–2541 (2015).

    Article CAS PubMed  Google Scholar 

  58. Miyazaki, M. et al.Sphaerochaeta multiformis sp. nov., an anaerobic, psychrophilic bacterium isolated from subseafloor sediment, and emended description of the genusSphaerochaeta.Int. J. Syst. Evol. Microbiol.64, 4147–4154 (2014).

    Article PubMed CAS  Google Scholar 

  59. Toyooka, K. et al. Wide-range high-resolution transmission electron microscopy reveals morphological and distributional changes of endomembrane compartments during log to stationary transition of growth phase in tobacco BY-2 cells.Plant Cell Physiol.55, 1544–1555 (2014).

    Article CAS PubMed  Google Scholar 

  60. Kremer, J. R., Mastronarde, D. N. & McIntosh, J. R. Computer visualization of three-dimensional image data using IMOD.J. Struct. Biol.116, 71–76 (1996).

    Article CAS PubMed  Google Scholar 

  61. Takano, Y. et al. Insight into anaerobic methanotrophy from13C/12C- amino acids and14C/12C-ANME cells in seafloor microbial ecology.Sci. Rep.8, 14070 (2018).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  62. Okumura, T. et al. Hydrogen and carbon isotope systematics in hydrogenotrophic methanogenesis under H2-limited and H2-enriched conditions: implications for the origin of methane and its isotopic diagnosis.Prog. Earth Planet. Sci.3, 14 (2016).

    Article ADS  Google Scholar 

  63. Takano, Y., Kashiyama, Y., Ogawa, N. O., Chikaraishi, Y. & Ohkouchi, N. Isolation and desalting with cation-exchange chromatography for compound-specific nitrogen isotope analysis of amino acids: application to biogeochemical samples.Rapid Commun. Mass Spectrom.24, 2317–2323 (2010).

    Article ADS CAS PubMed  Google Scholar 

  64. Chikaraishi, Y. et al.Instrumental Optimization for Compound-specific Nitrogen Isotope Analysis of Amino Acids by Gas Chromatography/Combustion/Isotope Ratio Mass Spectrometry in Earth, Life and Isotopes (eds Ohkouchi, N. et al.) 367–386 (Kyoto Univ. Press, 2010).

  65. Leggett, R. M., Clavijo, B. J., Clissold, L., Clark, M. D. & Caccamo, M. NextClip: an analysis and read preparation tool for Nextera long mate pair libraries.Bioinformatics30, 566–568 (2014).

    Article CAS PubMed  Google Scholar 

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

    Article MathSciNet CAS PubMed PubMed Central  Google Scholar 

  67. Lin, H.-H. & Liao, Y.-C. Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes.Sci. Rep.6, 24175 (2016).

    Article ADS CAS PubMed PubMed Central  Google Scholar 

  68. Boetzer, M., Henkel, C. V., Jansen, H. J., Butler, D. & Pirovano, W. Scaffolding pre-assembled contigs using SSPACE.Bioinformatics27, 578–579 (2011).

    Article CAS PubMed  Google Scholar 

  69. Seemann, T. Prokka: rapid prokaryotic genome annotation.Bioinformatics30, 2068–2069 (2014).

    Article CAS PubMed  Google Scholar 

  70. Marchler-Bauer, A. & Bryant, S. H. CD-Search: protein domain annotations on the fly.Nucleic Acids Res.32, W327–W331 (2004).

    Article CAS PubMed PubMed Central  Google Scholar 

  71. Marchler-Bauer, A. et al. CDD: NCBI’s conserved domain database.Nucleic Acids Res.43, D222–D226 (2015).

    Article CAS PubMed  Google Scholar 

  72. Jones, P. et al. InterProScan 5: genome-scale protein function classification.Bioinformatics30, 1236–1240 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  73. Petersen, T. N., Brunak, S., von Heijne, G. & Nielsen, H. SignalP 4.0: discriminating signal peptides from transmembrane regions.Nat. Methods8, 785–786 (2011).

    Article CAS PubMed  Google Scholar 

  74. Yin, Y. et al. dbCAN: a web resource for automated carbohydrate-active enzyme annotation.Nucleic Acids Res.40, W445–W451 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  75. Rawlings, N. D., Barrett, A. J. & Finn, R. Twenty years of the MEROPS database of proteolytic enzymes, their substrates and inhibitors.Nucleic Acids Res.44, D343–D350 (2016).

    Article CAS PubMed  Google Scholar 

  76. Fischer, M. & Pleiss, J. The Lipase Engineering Database: a navigation and analysis tool for protein families.Nucleic Acids Res.31, 319–321 (2003).

    Article CAS PubMed PubMed Central  Google Scholar 

  77. Søndergaard, D., Pedersen, C. N. S. & Greening, C. HydDB: a web tool for hydrogenase classification and analysis.Sci. Rep.6, 34212 (2016).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  78. Boutet, E., Lieberherr, D., Tognolli, M., Schneider, M. & Bairoch, A. UniProtKB/Swiss-Prot.Methods Mol. Biol.406, 89–112 (2007).

    CAS PubMed  Google Scholar 

  79. Lima, T. et al. HAMAP: a database of completely sequenced microbial proteome sets and manually curated microbial protein families in UniProtKB/Swiss-Prot.Nucleic Acids Res.37, D471–D478 (2009).

    Article CAS PubMed  Google Scholar 

  80. Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability.Mol. Biol. Evol.30, 772–780 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  81. Kozlov, A. M., Darriba, D., Flouri, T., Morel, B. & Stamatakis, A. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference.Bioinformatics35, 4453–4455 (2019).

    Article CAS PubMed PubMed Central  Google Scholar 

  82. Ronquist, F. et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space.Syst. Biol.61, 539–542 (2012).

    Article PubMed PubMed Central  Google Scholar 

  83. Pruesse, E., Peplies, J. & Glöckner, F. O. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.Bioinformatics28, 1823–1829 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  84. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools.Nucleic Acids Res.41, D590–D596 (2013).

    Article CAS PubMed  Google Scholar 

  85. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies.Bioinformatics30, 1312–1313 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  86. Camacho, C. et al. BLAST+: architecture and applications.BMC Bioinformatics10, 421 (2009).

    Article PubMed PubMed Central CAS  Google Scholar 

  87. Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data.Bioinformatics28, 3150–3152 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  88. UniProt Consortium. UniProt: a worldwide hub of protein knowledge.Nucleic Acids Res.47, D506–D515 (2019).

    Article CAS  Google Scholar 

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

    Article CAS PubMed PubMed Central  Google Scholar 

  90. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses.Bioinformatics25, 1972–1973 (2009).

    Article PubMed PubMed Central CAS  Google Scholar 

  91. Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.Syst. Biol.59, 307–321 (2010).

    Article CAS PubMed  Google Scholar 

  92. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—approximately maximum-likelihood trees for large alignments.PLoS ONE5, e9490 (2010).

    Article ADS PubMed PubMed Central CAS  Google Scholar 

  93. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data.Bioinformatics30, 2114–2120 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  94. Magoc, T., Wood, D. & Salzberg, S. L. EDGE-pro: estimated degree of gene expression in prokaryotic genomes.Evol. Bioinform. Online9, 127–136 (2013).

    Article PubMed PubMed Central  Google Scholar 

  95. Axley, M. J. & Grahame, D. A. Kinetics for formate dehydrogenase ofEscherichia coli formate-hydrogenlyase.J. Biol. Chem.266, 13731–13736 (1991).

    Article CAS PubMed  Google Scholar 

  96. Itoh, T., Suzuki, K. & Nakase, T.Thermocladium modestius gen. nov., sp. nov., a new genus of rod-shaped, extremely thermophilic crenarchaeote.Int. J. Syst. Bacteriol.48, 879–887 (1998).

    Article PubMed  Google Scholar 

  97. Zillig, W. et al. The archaebacteriumThermofilum pendens represents, a novel genus of the thermophilic, anaerobic sulfur respiringThermoproteales.Syst. Appl. Microbiol.4, 79–87 (1983).

    Article CAS PubMed  Google Scholar 

Download references

Acknowledgements

We thank H. Ohno and T. Yamaguchi for assistance with HCR-FISH analysis; T. Terada for help with NanoSIMS sample preparation; M. Isozaki for assistance with cultivation experiments; T. Kubota for assistance with chemical analysis; K. Takishita, A. Yabuki, T. Shiratori, A. Ohashi, F. Inagaki, T. Nunoura, S. Kawagucci, T. Shibuya, S. Ishii, S. Suzuki, Y. Tsukatani, C. Chen, Y. Kuruma and R. C. Robinson for advice and discussion; A. Miyashita, Y. Yashiro, K. Aoi, M. Ehara, M. Aoki and Y. Saito for assistance with operating the bioreactor; and J. Ashi and the RVYokosuka and RVShinkai 6500 operation team during cruise YK06-03 (JAMSTEC) and the shipboard scientists and crews of the RVChikyu Shakedown Cruise CK06-06 for their assistance in collecting samples. This study was partially supported by grants from the Japan Society for the Promotion of Science (JSPS) (KAKENHI grants 18687006, 21687006, 24687011, 15H02419 and 19H01005 to H.I., 18H03367 to M.K.N., 26710012, 18H02426, 18H05295 to H.T., 18H04468 and 18K18795 to M.I. and Grant-in-Aid for JSPS Fellow 16J10845 to N.N.). This work was also supported by JSPS KAKENHI grant number JP16H06280, Grant-in-Aid for Scientific Research on Innovative Areas–Platforms for Advanced Technologies and Research Resources ‘Advanced Bioimaging Support’ and the Cooperative Study Program (19-504) of National Institute for Physiological Sciences.

Author information

Author notes
  1. These authors contributed equally: Hiroyuki Imachi, Masaru K. Nobu

Authors and Affiliations

  1. Institute for Extra-cutting-edge Science and Technology Avant-garde Research (X-star), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan

    Hiroyuki Imachi, Nozomi Nakahara, Miyuki Ogawara, Yoshihiro Takaki, Masayuki Miyazaki, Yumi Saito, Sanae Sakai, Eiji Tasumi, Yuko Yamanaka & Ken Takai

  2. Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Masaru K. Nobu, Nozomi Nakahara, Yoichi Kamagata & Hideyuki Tamaki

  3. Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka, Japan

    Nozomi Nakahara & Takashi Yamaguchi

  4. Kochi Institute for Core Sample Research, X-star, JAMSTEC, Nankoku, Japan

    Yuki Morono & Motoo Ito

  5. Biogeochemistry Program, Research Institute for Marine Resources Utilization, JAMSTEC, Yokosuka, Japan

    Yoshinori Takano

  6. Department of Marine and Earth Sciences, Marine Work Japan, Yokosuka, Japan

    Katsuyuki Uematsu

  7. Research Institute for Global Change, JAMSTEC, Yokosuka, Japan

    Tetsuro Ikuta

  8. Research Institute for Marine Resources Utilization, JAMSTEC, Yokosuka, Japan

    Yohei Matsui

  9. National Institute for Physiological Sciences, Okazaki, Japan

    Kazuyoshi Murata & Chihong Song

  10. Section for Exploration of Life in Extreme Environments, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institute of Natural Sciences, Okazaki, Japan

    Ken Takai

Authors
  1. Hiroyuki Imachi
  2. Masaru K. Nobu
  3. Nozomi Nakahara
  4. Yuki Morono
  5. Miyuki Ogawara
  6. Yoshihiro Takaki
  7. Yoshinori Takano
  8. Katsuyuki Uematsu
  9. Tetsuro Ikuta
  10. Motoo Ito
  11. Yohei Matsui
  12. Masayuki Miyazaki
  13. Kazuyoshi Murata
  14. Yumi Saito
  15. Sanae Sakai
  16. Chihong Song
  17. Eiji Tasumi
  18. Yuko Yamanaka
  19. Takashi Yamaguchi
  20. Yoichi Kamagata
  21. Hideyuki Tamaki
  22. Ken Takai

Contributions

H.I. conceived the study and carried out the deep-marine sediment sampling. H.I., N.N., M.O., M.M. and S.S. conducted cultivation and culture-based experiments. M.K.N. performed metabolic reconstruction and phylogenetic analyses. M.K.N. and Y. Takaki performed genome analysis. H.I., N.N., Y. Morono, M.O., T.I., M.I., K.M., C.S. and K.U. carried out the microscopy and NanoSIMS work. M.O., Y.S. and Y.Y. performed qPCR, SSU rRNA gene analysis and DNA/RNA sequencing. Y. Takano, Y. Matsui and E.T. performed chemical analysis. H.I., M.K.N., N.N., Y. Morono, Y. Takaki, Y. Takano, K.M., C.S., T.Y., Y.K., H.T. and K.T. conducted data interpretation. H.I., M.K.N., Y. Takano, H.T., Y.K. and K.T. wrote the manuscript with input from all co-authors. All authors have read and approved the manuscript submission.

Corresponding authors

Correspondence toHiroyuki Imachi orMasaru K. Nobu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature thanks Sonja-Verena Albers, Petr G. Leiman, James McInerney, Christa Schleper and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data figures and tables

Extended Data Fig. 1 Growth of MK-D1.

a, Effect of temperature on growth of MK-D1. Data are mean ± s.d. of triplicate determinations. Each data point is shown as a dot. The temperature range test was performed twice with similar results.b,c, The amino acid concentrations and growth curves of MK-D1 in pure cocultures at 20 °C. Results from cultures 1 (b) and 2 (c) are shown. Please note that the initial concentrations of amino acids were normalized to 100%. Total amino acids and several representative amino acids (Val, valine; Leu, leucine; Ile, isoleucine) are independently shown for the duplicate culture samples. Detailed iTAG-based community compositions of the cultures are shown in Supplementary Table1.

Extended Data Fig. 2 Circular representation of MK-D1 genome.

From the outside to the centre: the distribution of the coding sequences based on the conserved (orange) or non-conserved (grey) genes in the first circle, non-coding RNAs in the second circle, GC content showing deviation from average (40.7%) in the third circle, and GC skew in the fourth circle. The GC content and GC skew were calculated using a sliding window of 2 kb in step of 10 kb. The coding sequences and RNA genes illustrate the findings for plus and minus strands.

Extended Data Fig. 3 Other representative photomicrographs of MK-D1 cultures andMethanobacterium sp. strain MO-MB1.

a,b, Fluorescence images of cells from enrichment cultures after 8 (a) and 11 (b) transfers stained with DAPI (violet) and hybridized with nucleotide probes that target MK-D1 (green) and Bacteria (red). The images are different fields of view to those shown in Fig.1b, c, which were taken at the same time.c, A fluorescence image of cells in the enrichments after 11 transfers hybridized with nucleotide probes that target MK-D1 (green) and Archaea (but with one mismatch against MK-D1; red). Large and irregular coccoid-shaped cells stained by only ARC915 are probablyMethanogenium.d,e, Dividing cells of MK-D1 with a bleb. The top-right inset image ine shows a magnification of the bleb.f,g, Cryo-EM images of MK-D1 cells and large membrane vesicles (white arrows).h,i, Ultrathin sections of MK-D1 cells with a membrane vesicle. The imagei shows a magnified image ofh.j,k, SEM images of MK-D1 cells with protrusions.l, Ultrathin section of a MK-D1 cell with a protrusion.m,n, Photomicrographs of pure culture of Methanobacterium sp. strain MO-MB1 cells stained with SYBR Green I. Phase-contrast (m) and fluorescence (n) images of the same field are shown.a,b, The FISH experiments were performed three times with similar results.d,e,j,k, The SEM images are representative ofn = 122 recorded images that were obtained from four independent observations from four culture samples. The lipid composition experiments were repeated twice and gave similar results.f,g, The cryo-EM images are representative ofn = 14 recorded images that were taken from two independent observations from two culture samples.h,i,l, The ultrathin-section images are representative ofn = 131 recorded images that were obtained from six independent observations from six culture samples.m,n, The SYBR Green I staining experiment was performed once, but all 10 recorded images showed similar results. Detailed iTAG analyses of cultures are shown in Supplementary Table1.

Extended Data Fig. 4 Ribosomal protein- and 16S rRNA gene-based phylogeny of MK-D1.

a, Phylogenomic tree of MK-D1 and select cultured archaea, eukaryotes and bacteria based on 31 ribosomal proteins conserved across the three domains (Supplementary Table7). Ribosomal protein sequences of MK-D1, the organisms shown in the tree and MAGs of uncultured archaeal lineages (Supplementary Table8) were aligned individually using MAFFT. MAG-derived sequences (except forCa. Korarchaeum) were then removed for tree construction. After removing all-gap positions and concatenation, the maximum-likelihood tree was constructed using RAxML-NG. Bootstrap values around critical branching points are also shown. In total, 14,875 sites of the alignment were used for tree construction.b, A ribosomal protein-based phylogenomic tree constructed using MrBayes. Bayesian inference phylogenies were calculated using MrBayes 3.2.7a and a ribosomal protein concatenated alignment used for Fig.4a.c, Phylogenetic tree of MK-D1 and related archaea based on 16S rRNA genes. The 16S rRNA gene sequences were aligned using SINA against the Silva v.132 alignment and the maximum-likelihood tree was calculated using RAxML.

Extended Data Fig. 5 Amino acid, cofactor and nucleotide biosynthesis capacities of MK-D1 and other Asgard archaea.

Genomes that encode proteins for the synthesis of amino acids, cofactors and nucleotides from pyruvate or acetyl-CoA (dark blue) and synthesis from other intermediates (light blue) are indicated. Those without complete pathways from pyruvate and/or acetyl-CoA are indicated in white.Halodesulfovibrio sp. strain MK-HDV andMethanogenium sp. strain MK-MG isolated in this study are also shown.

Extended Data Fig. 6 Maximum-likelihood tree of Asgard archaea urocanate hydratase.

Urocanate hydratase (HutU) homologues were obtained by BLASTp analysis of the Asgard archaea sequences against the UniProt database (release 2019_06). Of homologues with sequence similarity ≥40% and overlap ≥70%, representative sequences were selected using CD-HIT with a clustering cut-off of 70% similarity (otherwise default settings were used). Additional homologues with verified biochemical activity, sequence similarity ≥30% and overlap ≥70% were obtained by BLASTp analysis of the Asgard archaea sequences against the UniProt/SwissProt database (2019_05). Sequences were aligned using MAFFT v.7 with default settings and trimmed using trimAl v.1.2 with default settings. The maximum-likelihood tree was constructed using RAxML-NG using fixed empirical substitution matrix (LG), 4 discrete GAMMA categories, empirical amino acid frequencies from the alignment and 100 bootstrap replicates. In total, 876 sites of the alignment were used for tree construction.

Extended Data Fig. 7 Maximum-likelihood tree of Asgard archaeal-threonine/l-serine dehydratase.

a, Tree calculated for target Asgard archaeal-threonine/l-serine dehydratase (TdcB) and homologues. TdcB homologues were obtained by BLASTp analysis of the Asgard archaea sequences against the UniProt reference proteome and SwissProt database (release 2019_06). Of homologues with sequence similarity ≥40%, overlap ≥70% and predicted prosite domain PS00165 (serine/threonine dehydratases pyridoxal-phosphate attachment site), representative sequences were selected using CD-HIT with a clustering cut-off of 70% similarity (otherwise default settings were used). Additional homologues with verified biochemical activity, sequence similarity ≥30% and overlap ≥70% were obtained by BLASTp analysis of the Asgard archaea sequences against the UniProt/SwissProt database (2019_05). Sequences were aligned using MAFFT v.7 with default settings. Positions with gaps in more than 10% of the sequences were excluded from the alignment using trimAl v.1.2 (-gt 0.9; and otherwise default settings were used). The maximum-likelihood tree was constructed using PhyML using a fixed empirical substitution matrix (LG), 4 discrete GAMMA categories, empirical amino acid frequencies from the alignment and 100 bootstrap replicates (-b 100 -d aa -m LG -v e). In total, 308 sites of the alignment were used for tree construction.b, Tree calculated for a subset of sequences contained in a section of the original tree (branches that are coloured blue). Sequences were realigned and trimmed as described fora. In total, 308 sites of the alignment were used for tree construction.

Extended Data Table 1 SSU rRNA gene clones obtained from the primary and six successive transferred enrichment cultures
Extended Data Table 2 Carbon isotope fractionation values in MK-D1 cultures after 120 days incubation with and without stable isotope labelled amino acids
Extended Data Table 3 Growth of MK-D1 after incubation of 120 days with a range of substrates

Supplementary information

Supplementary Information

This file contains Supplementary Notes 1–9, Supplementary Methods, Supplementary Figures 1–18, and Supplementary References.

Supplementary Tables

This file contains Supplementary Tables 1–10

Supplementary Video 1

| Tilt-series images of a single cell of MK-D1

Supplementary Video 2

| Z-slices of the tomographic three-dimensional reconstruction from the tilt-series in Supplementary Video 1

Supplementary Video 3

| Animation of the same MK-D1 cell as in Supplementary Video 2 The cell envelope and membrane vesicles are colored in light blue and pink, respectively.

Supplementary Video 4

| Tilt-series images of MK-D1 cells

Supplementary Video 5

| Z-slices of the tomographic three-dimensional reconstruction from the tilt-series in Supplementary Video 4

Supplementary Video 6

| Animation of the same MK-D1 cells as in Supplementary Video 5 The cell envelope and membrane vesicles are colored in light blue and pink, respectively.

Rights and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Imachi, H., Nobu, M.K., Nakahara, N.et al. Isolation of an archaeon at the prokaryote–eukaryote interface.Nature577, 519–525 (2020). https://doi.org/10.1038/s41586-019-1916-6

Download citation

This article is cited by

Comments

Commenting on this article is now closed.

  1. Rafting Tara

    Should be named after Lyn Margules

    Rafting Tara

  2. Him who has understanding

    Macro-evolution (I donothere speak of speciation) hasneveroccurred anywhere. This entire paper is based upon speculation and nonsense, and reflects alackof actual scientific and other understanding regarding life itself and how genomes actually work, etc. God created life on Earth exactly as recorded in Genesis 1 to 2 only thousands of years ago.

Access through your institution
Buy or subscribe

Associated content

Meet the relatives of our cellular ancestor

  • Christa Schleper
  • Filipa L. Sousa
NatureNews & Views

Advertisement

Search

Advanced search

Quick links

Nature Briefing

Sign up for theNature 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

[8]ページ先頭

©2009-2025 Movatter.jp