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Asgard archaea illuminate the origin of eukaryotic cellular complexity

Abstract

The origin and cellular complexity of eukaryotes represent a major enigma in biology. Current data support scenarios in which an archaeal host cell and an alphaproteobacterial (mitochondrial) endosymbiont merged together, resulting in the first eukaryotic cell. The host cell is related to Lokiarchaeota, an archaeal phylum with many eukaryotic features. The emergence of the structural complexity that characterizes eukaryotic cells remains unclear. Here we describe the ‘Asgard’ superphylum, a group of uncultivated archaea that, as well as Lokiarchaeota, includes Thor-, Odin- and Heimdallarchaeota. Asgard archaea affiliate with eukaryotes in phylogenomic analyses, and their genomes are enriched for proteins formerly considered specific to eukaryotes. Notably, thorarchaeal genomes encode several homologues of eukaryotic membrane-trafficking machinery components, including Sec23/24 and TRAPP domains. Furthermore, we identify thorarchaeal proteins with similar features to eukaryotic coat proteins involved in vesicle biogenesis. Our results expand the known repertoire of ‘eukaryote-specific’ proteins in Archaea, indicating that the archaeal host cell already contained many key components that govern eukaryotic cellular complexity.

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Figure 1: Identification and phylogenomics of Asgard archaea.
Figure 2: Vesicular trafficking components in Asgard archaea.

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References

  1. Embley, T. M. & Martin, W. Eukaryotic evolution, changes and challenges. Nature 440, 623–630 (2006)

    Article  ADS  CAS  PubMed  Google Scholar 

  2. 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 

  3. 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. B 370, 20140333 (2015)

    Article  CAS  Google Scholar 

  4. Martin, W. F., Garg, S. & Zimorski, V. Endosymbiotic theories for eukaryote origin. Phil. Trans. R. Soc. Lond. B 370, 20140330 (2015)

    Article  CAS  Google Scholar 

  5. Cox, C. J., Foster, P. G., Hirt, R. P., Harris, S. R. & Embley, T. M. The archaebacterial origin of eukaryotes. Proc. Natl Acad. Sci. USA 105, 20356–20361 (2008)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  6. Guy, L. & Ettema, T. J. The archaeal ‘TACK’ superphylum and the origin of eukaryotes. Trends Microbiol. 19, 580–587 (2011)

    Article  CAS  PubMed  Google Scholar 

  7. Raymann, K., Brochier-Armanet, C. & Gribaldo, S. The two-domain tree of life is linked to a new root for the Archaea. Proc. Natl Acad. Sci. USA 112, 6670–6675 (2015)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  8. McInerney, J. O., O’Connell, M. J. & Pisani, D. The hybrid nature of the Eukaryota and a consilient view of life on Earth. Nat. Rev. Microbiol. 12, 449–455 (2014)

    Article  CAS  PubMed  Google Scholar 

  9. Williams, T. A., Foster, P. G., Nye, T. M., Cox, C. J. & Embley, T. M. A congruent phylogenomic signal places eukaryotes within the Archaea. Proc. R. Soc. Lond. B 279, 4870–4879 (2012)

    CAS  Google Scholar 

  10. Gray, M. W., Burger, G. & Lang, B. F. Mitochondrial evolution. Science 283, 1476–1481 (1999)

    Article  ADS  CAS  PubMed  Google Scholar 

  11. Spang, A. et al. Complex Archaea that bridge the gap between prokaryotes and eukaryotes. Nature 521, 173–179 (2015)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Williams, T. A., Foster, P. G., Cox, C. J. & Embley, T. M. An archaeal origin of eukaryotes supports only two primary domains of life. Nature 504, 231–236 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  13. Hartman, H. & Fedorov, A. The origin of the eukaryotic cell: a genomic investigation. Proc. Natl Acad. Sci. USA 99, 1420–1425 (2002)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Klinger, C. M., Spang, A., Dacks, J. B. & Ettema, T. J. Tracing the archaeal origins of eukaryotic membrane-trafficking system building blocks. Mol. Biol. Evol. 33, 1528–1541 (2016)

    Article  CAS  PubMed  Google Scholar 

  15. Surkont, J. & Pereira-Leal, J. B. Are there Rab GTPases in Archaea? Mol. Biol. Evol. 33, 1833–1842 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Dey, G., Thattai, M. & Baum, B. On the archaeal origins of eukaryotes and the challenges of inferring phenotype from genotype. Trends Cell Biol. 26, 476–485 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Koonin, E. V. Archaeal ancestors of eukaryotes: not so elusive any more. BMC Biol. 13, 84 (2015)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Archibald, J. M. Endosymbiosis and eukaryotic cell evolution. Curr. Biol. 25, R911–R921 (2015)

    Article  CAS  PubMed  Google Scholar 

  19. Martin, W. F., Neukirchen, S., Zimorski, V., Gould, S. B. & Sousa, F. L. Energy for two: new archaeal lineages and the origin of mitochondria. BioEssays 38, 850–856 (2016)

    Article  PubMed  Google Scholar 

  20. Villanueva, L., Schouten, S. & Damsté, J. S. Phylogenomic analysis of lipid biosynthetic genes of Archaea shed light on the ‘lipid divide’. Environ. Microbiol. (2016)

  21. 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 

  22. Mariotti, M. et al. Lokiarchaeota marks the transition between the archaeal and eukaryotic selenocysteine encoding systems. Mol. Biol. Evol. 33, 2441–2453 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. 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 

  24. Takai, K. & Horikoshi, K. Genetic diversity of Archaea in deep-sea hydrothermal vent environments. Genetics 152, 1285–1297 (1999)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Delsuc, F., Brinkmann, H. & Philippe, H. Phylogenomics and the reconstruction of the tree of life. Nat. Rev. Genet. 6, 361–375 (2005)

    Article  CAS  PubMed  Google Scholar 

  26. Lartillot, N. & Philippe, H. A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process. Mol. Biol. Evol. 21, 1095–1109 (2004)

    Article  CAS  PubMed  Google Scholar 

  27. Raiborg, C. & Stenmark, H. The ESCRT machinery in endosomal sorting of ubiquitylated membrane proteins. Nature 458, 445–452 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  28. Yutin, N. & Koonin, E. V. Archaeal origin of tubulin. Biol. Direct 7, 10 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Tahirov, T. H., Makarova, K. S., Rogozin, I. B., Pavlov, Y. I. & Koonin, E. V. Evolution of DNA polymerases: an inactivated polymerase-exonuclease module in Pol epsilon and a chimeric origin of eukaryotic polymerases from two classes of archaeal ancestors. Biol. Direct 4, 11 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Sacher, M., Kim, Y. G., Lavie, A., Oh, B. H. & Segev, N. The TRAPP complex: insights into its architecture and function. Traffic 9, 2032–2042 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Podar, M., Wall, M. A., Makarova, K. S. & Koonin, E. V. The prokaryotic V4R domain is the likely ancestor of a key component of the eukaryotic vesicle transport system. Biol. Direct 3, 2 (2008)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Barlowe, C. et al. COPII: a membrane coat formed by Sec proteins that drive vesicle budding from the endoplasmic reticulum. Cell 77, 895–907 (1994)

    Article  CAS  PubMed  Google Scholar 

  33. Lee, M. C., Miller, E. A., Goldberg, J., Orci, L. & Schekman, R. Bi-directional protein transport between the ER and Golgi. Annu. Rev. Cell Dev. Biol. 20, 87–123 (2004)

    Article  CAS  PubMed  Google Scholar 

  34. Gould, S. B., Garg, S. G. & Martin, W. F. Bacterial vesicle secretion and the evolutionary origin of the eukaryotic endomembrane system. Trends Microbiol. 24, 525–534 (2016)

    Article  CAS  PubMed  Google Scholar 

  35. Devos, D. et al. Components of coated vesicles and nuclear pore complexes share a common molecular architecture. PLoS Biol. 2, e380 (2004)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Fournier, D. et al. Functional and genomic analyses of alpha-solenoid proteins. PLoS One 8, e79894 (2013)

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  37. Field, M. C., Sali, A. & Rout, M. P. Evolution: on a bender–BARs, ESCRTs, COPs, and finally getting your coat. J. Cell Biol. 193, 963–972 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Schlacht, A. & Dacks, J. B. Unexpected ancient paralogs and an evolutionary model for the COPII coat complex. Genome Biol. Evol. 7, 1098–1109 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Dacks, J. B. & Field, M. C. Evolution of the eukaryotic membrane-trafficking system: origin, tempo and mode. J. Cell Sci. 120, 2977–2985 (2007)

    Article  CAS  PubMed  Google Scholar 

  40. Ku, C. et al. Endosymbiotic origin and differential loss of eukaryotic genes. Nature 524, 427–432 (2015)

    Article  ADS  CAS  PubMed  Google Scholar 

  41. Pittis, A. A. & Gabaldón, T. Late acquisition of mitochondria by a host with chimaeric prokaryotic ancestry. Nature 531, 101–104 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ettema, T. J. Evolution: mitochondria in the second act. Nature 531, 39–40 (2016)

    Article  ADS  CAS  PubMed  Google Scholar 

  43. Koonin, E. V. & Yutin, N. The dispersed archaeal eukaryome and the complex archaeal ancestor of eukaryotes. Cold Spring Harb. Perspect. Biol. 6, a016188 (2014)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Shively, J. M. in Complex Intracellular Structures in Prokaryotes (ed. Jessup M. Shively ) 3–22 (Springer Berlin Heidelberg, 2006)

  45. Küper, U., Meyer, C., Müller, V., Rachel, R. & Huber, H. Energized outer membrane and spatial separation of metabolic processes in the hyperthermophilic archaeon Ignicoccus hospitalis. Proc. Natl Acad. Sci. USA 107, 3152–3156 (2010)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  46. Klingl, A. S-layer and cytoplasmic membrane—exceptions from the typical archaeal cell wall with a focus on double membranes. Front. Microbiol. 5, 624 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  47. Yutin, N., Wolf, M. Y., Wolf, Y. I. & Koonin, E. V. The origins of phagocytosis and eukaryogenesis. Biol. Direct 4, 9 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Martijn, J. & Ettema, T. J. From archaeon to eukaryote: the evolutionary dark ages of the eukaryotic cell. Biochem. Soc. Trans. 41, 451–457 (2013)

    Article  CAS  PubMed  Google Scholar 

  49. Poole, A. M. & Gribaldo, S. Eukaryotic origins: how and when was the mitochondrion acquired? Cold Spring Harb. Perspect. Biol. 6, a015990 (2014)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Lane, N. & Martin, W. The energetics of genome complexity. Nature 467, 929–934 (2010)

    Article  ADS  CAS  PubMed  Google Scholar 

  51. Saw, J. H. et al. Exploring microbial dark matter to resolve the deep archaeal ancestry of eukaryotes. Phil. Trans. R. Soc. Lond. B 370, 20140328 (2015)

    Article  Google Scholar 

  52. Baker, B. J. et al. Genomic inference of the metabolism of cosmopolitan subsurface Archaea, Hadesarchaea. Nat. Microbiol. 1, 16002 (2016)

    Article  CAS  PubMed  Google Scholar 

  53. Castelle, C. J. et al. Genomic expansion of domain Archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr. Biol. 25, 690–701 (2015)

    Article  CAS  PubMed  Google Scholar 

  54. Hirayama, H. et al. Culture-dependent and -independent characterization of microbial communities associated with a shallow submarine hydrothermal system occurring within a coral reef off Taketomi Island, Japan. Appl. Environ. Microbiol. 73, 7642–7656 (2007)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  55. Lever, M. A. et al. A modular method for the extraction of DNA and RNA, and the separation of DNA pools from diverse environmental sample types. Front. Microbiol. 6, 476 (2015)

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Peng, Y., Leung, H. C., Yiu, S. M. & Chin, F. Y. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28, 1420–1428 (2012)

    Article  CAS  PubMed  Google Scholar 

  58. Boisvert, S., Raymond, F., Godzaridis, E., Laviolette, F. & Corbeil, J. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol. 13, R122 (2012)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Dick, G. J. et al. Community-wide analysis of microbial genome sequence signatures. Genome Biol. 10, R85 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat. Methods 11, 1144–1146 (2014)

    Article  CAS  PubMed  Google Scholar 

  61. Brady, A. & Salzberg, S. L. Phymm and PhymmBL: metagenomic phylogenetic classification with interpolated Markov models. Nat. Methods 6, 673–676 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Brown, C. T. et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature 523, 208–211 (2015)

    Article  ADS  CAS  PubMed  Google Scholar 

  63. Albertsen, M. et al. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nat. Biotechnol. 31, 533–538 (2013)

    Article  CAS  PubMed  Google Scholar 

  64. 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 

  65. 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)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  68. Lowe, T. M. & Eddy, S. R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25, 955–964 (1997)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  71. Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Archaeal clusters of orthologous genes (arCOGs): an update and application for analysis of shared features between Thermococcales, Methanococcales, and Methanobacteriales. Life 5, 818–840 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44 (D1), D279–D285 (2016)

    Article  CAS  PubMed  Google Scholar 

  73. Letunic, I., Doerks, T. & Bork, P. SMART: recent updates, new developments and status in 2015. Nucleic Acids Res. 43, D257–D260 (2015)

    Article  CAS  PubMed  Google Scholar 

  74. Söding, J., Biegert, A. & Lupas, A. N. The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res. 33, W244–W228 (2005)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N. & Sternberg, M. J. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protocols 10, 845–858 (2015)

    Article  CAS  PubMed  Google Scholar 

  76. Pettersen, E. F. et al. UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004)

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Guy, L., Saw, J. H. & Ettema, T. J. The archaeal legacy of eukaryotes: a phylogenomic perspective. Cold Spring Harb. Perspect. Biol. 6, a016022 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  79. Yutin, N., Puigbò, P., Koonin, E. V. & Wolf, Y. I. Phylogenomics of prokaryotic ribosomal proteins. PLoS One 7, e36972 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  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. Criscuolo, A. & Gribaldo, S. BMGE (block mapping and gathering with entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evol. Biol. 10, 210 (2010)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  83. Lartillot, N., Rodrigue, N., Stubbs, D. & Richer, J. PhyloBayes MPI: phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment. Syst. Biol. 62, 611–615 (2013)

    Article  CAS  PubMed  Google Scholar 

  84. Nguyen, L. T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015)

    Article  CAS  PubMed  Google Scholar 

  85. Minh, B. Q., Nguyen, M. A. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. 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 

  87. Viklund, J., Ettema, T. J. & Andersson, S. G. Independent genome reduction and phylogenetic reclassification of the oceanic SAR11 clade. Mol. Biol. Evol. 29, 599–615 (2012)

    Article  CAS  PubMed  Google Scholar 

  88. Susko, E. & Roger, A. J. On reduced amino acid alphabets for phylogenetic inference. Mol. Biol. Evol. 24, 2139–2150 (2007)

    Article  CAS  PubMed  Google Scholar 

  89. Sukumaran, J. & Holder, M. T. DendroPy: a Python library for phylogenetic computing. Bioinformatics 26, 1569–1571 (2010)

    Article  CAS  PubMed  Google Scholar 

  90. Makarova, K. S., Krupovic, M. & Koonin, E. V. Evolution of replicative DNA polymerases in Archaea and their contributions to the eukaryotic replication machinery. Front. Microbiol. 5, 354 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank L. Guy, S. L. Jørgensen, T. Williams, N. Lartillot, B. Quang Minh and J. Dacks for useful advice and discussions. We are grateful to D. R. Colman and C. Takacs-Vesbach for collecting the YNP sediment samples under permit #YELL-2010-SCI-5344, to the Japan Agency for Marine-Earth Science & Technology (JAMSTEC) for taking sediment samples from the Taketomi shallow submarine hydrothermal system, and to the Ngāti Tahu Ngāti Whaoa Runanga Trust for their enthusiasm for our research, and assistance in access and sampling of the Ngatamariki geothermal features. We acknowledge the Yellowstone Center for Resources for their assistance and for facilitating this research. We thank A. Simpson for suggesting the name ‘Heimdallarchaeota’. Sequencing of the White Oak River and Colorado River sediment metagenomes was conducted at the Joint Genome Institute, a US Department of Energy Office of Science User Facility, via the Community Science Program. The remaining metagenomes were sequenced at the National Genomics Infrastructure sequencing platforms at the Science for Life Laboratory at Uppsala University, a national infrastructure supported by the Swedish Research Council (VR-RFI) and the Knut and Alice Wallenberg Foundation. We thank the Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) at Uppsala University and the Swedish National Infrastructure for Computing (SNIC) at the PDC Center for High-Performance Computing for providing computational resources. This work was supported by grants of the European Research Council (ERC Starting grant 310039-PUZZLE_CELL), the Swedish Foundation for Strategic Research (SSF-FFL5) and the Swedish Research Council (VR grant 2015-04959) to T.J.G.E., by Marie Curie IIF (331291 to J.H.S.) and IEF (625521 to A.S.) grants by the European Union to the Ettema laboratory, by grants to Bo Barker Jørgensen (Aarhus University, Denmark) from the European Research Council (ERC Advanced Grant 294200-MICROENERGY) and the Danish National Research Foundation (DNRF104) to support the Center for Geomicrobiology at Aarhus University, and by the US Department of Energy (Sustainable Systems Scientific Focus Area grant DE-AC02-05CH11231 to J.F.B.).

Author information

Authors and Affiliations

Authors

Contributions

T.J.G.E. conceived the study. A.Sc., P.S., K.U.K., M.B.S. and T.N. took/provided environmental samples. L.J. purified environmental DNA and prepared sequencing libraries. K.Z.-N., E.F.C, J.H.S., K.A., J.F.B, K.W.S., B.J.B. and E.V. performed metagenomic sequence assemblies and metagenomic binning analyses. K.Z.-N., E.F.C., J.H.S., A.Sp. and T.J.G.E. analysed genomic data and performed phylogenetic analyses. A.Sp., D.B., E.F.C. and T.J.G.E analysed genomic signatures. K.Z.-N., E.F.C., J.H.S., A.Sp. and T.J.G.E. wrote, and all authors edited and approved, the manuscript.

Corresponding author

Correspondence to Thijs J. G. Ettema.

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Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks J. Gilbert, E. Koonin, A. Roger and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Sample origin, metagenomics workflow and global distribution of Asgard archaea.

a, World map showing the sampling locations of the current study. Abbreviations of the sites mentioned are as follows: LC, Loki’s Castle; CR, Colorado River aquifer (USA); LCB, Lower Culex Basin (Yellowstone National Park, USA); WOR, White Oak River (USA); AB, Aarhus Bay (Denmark); RP, Radiata Pool (New Zealand); and TIV, Taketomi Island Vent (Japan). The world map was drawn using the Matplotlib Basemap Toolkit (http://matplotlib.org/basemap/). b, Simplified schematic overview of the metagenomics approach that was used to obtain Asgard genomes. Software used during the assembly and binning processes are shown in grey. c, Normalized distribution of major Asgard archaeal groups across various environments based on 16S rRNA gene survey datasets. Numbers on the right side of the bar graph represent total number of identified sequences.

Extended Data Figure 2 Bayesian phylogenetic inference of 48 concatenated marker genes.

The tree was inferred using CAT + GTR model and rooted with Bacteria, showing high support for the phylogenetic affiliation between Asgard archaea and eukaryotes (support value in red). Numbers at branches represent posterior probabilities and scale bar indicates the number of substitutions per site.

Extended Data Figure 3 Asgard genomes encode an expanded GTPase repertoire.

Graph showing small Ras and Arf-type GTPases (containing any of the following domains: IPR006762, IPR024156, IPR006689, IPR006687, IPR001806, IPR003579, IPR020849, IPR003578, IPR021181, IPR031260, IPR002041, IPR019009) per Asgard genomic bin normalized to the total amount of proteins predicted per genome and compared with selected eukaryotic, archaeal and bacterial taxa. Numbers refer to the total amount of GTPases per genome.

Extended Data Figure 4 Phylogenetic analysis of oligosaccharyl-transferase-complex-related proteins.

a, Bayesian inference of STT3-domain proteins (598 aligned amino acid positions) present in all three domains of life. This phylogenetic tree was rooted with bacterial sequences. Numbers at branches refer to Bayesian and non-parametric RAxML bootstrap values, respectively. b, Unrooted maximum likelihood phylogenetic analysis of ribophorin domain proteins (357 aligned amino acid positions) including all prokaryotic homologues identified so far. Numbers at branches show slow, non-parametric maximum-likelihood bootstrap support values. Scale bars indicate the number of substitutions per site.

Extended Data Figure 5 Genomic conservation links ESCRT and ubiquitin modifier systems.

Schematic overview of ubiquitin and ESCRT gene clusters identified in Asgard genomes. Contiguous contigs from Heimdallarchaeote AB_125 are represented with a double line at the end of the contig. E1-like and putative deubiquitinating proteins not belonging to any ubiquitin cluster are not shown.

Extended Data Figure 6 Phylogenetic analyses of selected ESPs.

a, Tubulin protein family maximum-likelihood tree, highlighting Odinarchaeota homologues branching basal to major eukaryotic tubulin families (red clades). Green clade reflects bacterial tubulin genes probably acquired horizontally from eukaryotes. The tree was rooted with thaumarchaeal artubulins. b, Unrooted maximum-likelihood phylogenetic tree of the replicative polymerase B family depicting a Heimdallarchaeote LC_3 sequence and its corresponding protein model (red), branching basal to the eukaryotic Pol-ε (protein model in grey: PDB ID 4M8O of S. cerevisiae). Bootstrap support values of ≥99, ≥90 and ≥50 for major clades are indicated by black, grey and white circles, respectively. Eukaryotic, bacterial and archaeal clades are shaded red, green and purple, respectively. c, PFAM domain topology analysis of family B polymerases, indicating that the heimdallarchaeal homologue lacks the C-terminal DUF1744 domain characteristic of eukaryotic Pol-ε. d, Unrooted maximum-likelihood tree of RPL28e homologues, including eukaryotic RPL28e and MAK16, a RPL28e-like sequence identified in the Heimdallarchaeote LC_3 genome and a metagenomic homologue. Eukaryotic MAK16 proteins (implicated in rRNA maturation) contain an additional C-terminal domain absent in the heimdallarchaeal protein. a, b, d, Scale bars indicate the number of substitutions per site and numbers at branches show slow, non-parametric maximum-likelihood bootstrap support values.

Extended Data Figure 7 Asgard ESPs are enriched for intracellular trafficking and secretion functions.

Overview of functional classification (arCOGs and EggNOG categories) of Asgard proteins assigned to major taxonomic levels. Taxonomic levels are shown in different colours. Note that, in some cases, one protein can be assigned to more than one functional category.

Extended Data Figure 8 Eukaryotic signatures in Asgard archaea.

Schematic representation of a eukaryotic cell in which ESPs that have been identified in Asgard archaea are highlighted, including their phylogenetic distribution pattern. The overall picture indicates that the archaeal ancestor of eukaryotes already contained many key components underlying the emergence of cellular complexity that is characteristic of eukaryotes. DUB, deubiquitinating enzyme; MVB, multi-vesicular body; ER, endoplasmatic reticulum.

Extended Data Table 1 Assembly statistics and quality metrics of reconstructed Asgard genome bins
Extended Data Table 2 Overview of presence/absence pattern of Asgard ESPs

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This file contains Supplementary Methods, Supplementary Discussions 1-4, Supplementary References, Supplementary Tables 1-14 and Supplementary Figures 1-5, which provide more details into annotations, applied methods and phylogenetic analyses. (PDF 5144 kb)

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Zaremba-Niedzwiedzka, K., Caceres, E., Saw, J. et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature 541, 353–358 (2017). https://doi.org/10.1038/nature21031

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