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Integrative structure and functional anatomy of a nuclear pore complex

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Abstract

Nuclear pore complexes play central roles as gatekeepers of RNA and protein transport between the cytoplasm and nucleoplasm. However, their large size and dynamic nature have impeded a full structural and functional elucidation. Here we determined the structure of the entire 552-protein nuclear pore complex of the yeast Saccharomyces cerevisiae at sub-nanometre precision by satisfying a wide range of data relating to the molecular arrangement of its constituents. The nuclear pore complex incorporates sturdy diagonal columns and connector cables attached to these columns, imbuing the structure with strength and flexibility. These cables also tie together all other elements of the nuclear pore complex, including membrane-interacting regions, outer rings and RNA-processing platforms. Inwardly directed anchors create a high density of transport factor-docking Phe-Gly repeats in the central channel, organized into distinct functional units. This integrative structure enables us to rationalize the architecture, transport mechanism and evolutionary origins of the nuclear pore complex.

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Figure 1: Defining the mass, composition and stoichiometry of the native NPC.
Figure 2: Chemical cross-linking and mass spectrometry reveals nucleoporin connectivity in the NPC.
Figure 3: Morphology of the NPC.
Figure 4: Structural dissection of the NPC.
Figure 5: Key NPC architectural features and principles.
Figure 6: The distribution of FG repeats informs the NPC transport gating mechanism.

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  • 21 March 2018

    Minor changes were made to the descriptions of the Supplementary Information files.

  • 06 April 2018

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References

  1. Ptak, C ., Aitchison, J. D. & Wozniak, R. W. The multifunctional nuclear pore complex: a platform for controlling gene expression. Curr. Opin. Cell Biol. 28, 46–53 (2014)

    CAS  PubMed  Article  Google Scholar 

  2. Nofrini, V ., Di Giacomo, D. & Mecucci, C. Nucleoporin genes in human diseases. Eur. J. Hum. Genet. 24, 1388–1395 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. Alber, F . et al. The molecular architecture of the nuclear pore complex. Nature 450, 695–701 (2007)

    CAS  PubMed  ADS  Article  Google Scholar 

  4. Stanley, G. J ., Fassati, A. & Hoogenboom, B. W. Biomechanics of the transport barrier in the nuclear pore complex. Semin. Cell Dev. Biol. 68, 42–51 (2017)

    CAS  PubMed  Article  Google Scholar 

  5. Akey, C. W. & Goldfarb, D. S. Protein import through the nuclear pore complex is a multistep process. J. Cell Biol. 109, 971–982 (1989)

    CAS  PubMed  Article  Google Scholar 

  6. Kosinski, J . et al. Molecular architecture of the inner ring scaffold of the human nuclear pore complex. Science 352, 363–365 (2016)

    CAS  PubMed  ADS  Article  PubMed Central  Google Scholar 

  7. Lin, D. H . et al. Architecture of the symmetric core of the nuclear pore. Science 352, aaf1015 (2016)

    PubMed  PubMed Central  ADS  Article  CAS  Google Scholar 

  8. Alber, F . et al. Determining the architectures of macromolecular assemblies. Nature 450, 683–694 (2007)

    CAS  PubMed  ADS  Article  Google Scholar 

  9. Fernandez-Martinez, J. et al. Structure and function of the nuclear pore complex cytoplasmic mRNA export platform. Cell 167, 1215–1228.e25 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. Shi, Y . et al. Structural characterization by cross-linking reveals the detailed architecture of a coatomer-related heptameric module from the nuclear pore complex. Mol. Cell. Proteomics 13, 2927–2943 (2014)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. Briggs, J. A. Structural biology in situ—the potential of subtomogram averaging. Curr. Opin. Struct. Biol. 23, 261–267 (2013)

    CAS  PubMed  Article  Google Scholar 

  12. Kim, S. J . et al. Integrative structure–function mapping of the nucleoporin Nup133 suggests a conserved mechanism for membrane anchoring of the nuclear pore complex. Mol. Cell. Proteomics 13, 2911–2926 (2014)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  13. Fernandez-Martinez, J . et al. Structure-function mapping of a heptameric module in the nuclear pore complex. J. Cell Biol. 196, 419–434 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. Herricks, T . et al. One-cell doubling evaluation by living arrays of yeast, ODELAY! G3 7, 279–288 (2017)

    CAS  PubMed  Article  Google Scholar 

  15. Aitchison, J. D ., Rout, M. P ., Marelli, M ., Blobel, G. & Wozniak, R. W. Two novel related yeast nucleoporins Nup170p and Nup157p: complementation with the vertebrate homologue Nup155p and functional interactions with the yeast nuclear pore-membrane protein Pom152p. J. Cell Biol. 131, 1133–1148 (1995)

    CAS  PubMed  Article  Google Scholar 

  16. Fischer, J ., Teimer, R ., Amlacher, S ., Kunze, R. & Hurt, E. Linker Nups connect the nuclear pore complex inner ring with the outer ring and transport channel. Nat. Struct. Mol. Biol. 22, 774–781 (2015)

    CAS  PubMed  Article  Google Scholar 

  17. von Appen, A . et al. In situ structural analysis of the human nuclear pore complex. Nature 526, 140–143 (2015)

    CAS  PubMed  PubMed Central  ADS  Article  Google Scholar 

  18. Marelli, M ., Lusk, C. P ., Chan, H ., Aitchison, J. D. & Wozniak, R. W. A link between the synthesis of nucleoporins and the biogenesis of the nuclear envelope. J. Cell Biol. 153, 709–724 (2001)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  19. Vollmer, B . et al. Dimerization and direct membrane interaction of Nup53 contribute to nuclear pore complex assembly. EMBO J. 31, 4072–4084 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. Seo, H. S . et al. Structural and functional analysis of Nup120 suggests ring formation of the Nup84 complex. Proc. Natl Acad. Sci. USA 106, 14281–14286 (2009)

    CAS  PubMed  ADS  Article  PubMed Central  Google Scholar 

  21. Drin, G . et al. A general amphipathic α-helical motif for sensing membrane curvature. Nat. Struct. Mol. Biol. 14, 138–146 (2007)

    CAS  PubMed  Article  Google Scholar 

  22. Mészáros, N . et al. Nuclear pore basket proteins are tethered to the nuclear envelope and can regulate membrane curvature. Dev. Cell 33, 285–298 (2015)

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  23. Upla, P . et al. Molecular architecture of the major membrane ring component of the nuclear pore complex. Structure 25, 434–445 (2017)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. Meinema, A. C . et al. Long unfolded linkers facilitate membrane protein import through the nuclear pore complex. Science 333, 90–93 (2011)

    CAS  PubMed  ADS  Article  Google Scholar 

  25. Knockenhauer, K. E. & Schwartz, T. U. The nuclear pore complex as a flexible and dynamic gate. Cell 164, 1162–1171 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. Folkmann, A. W ., Noble, K. N ., Cole, C. N. & Wente, S. R. Dbp5, Gle1–IP6 and Nup159: a working model for mRNP export. Nucleus 2, 540–548 (2011)

    PubMed  PubMed Central  Article  Google Scholar 

  27. Saroufim, M. A. et al. The nuclear basket mediates perinuclear mRNA scanning in budding yeast. J. Cell Biol. 211, 1131–1140 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. Meseroll, R. A. & Cohen-Fix, O. The malleable nature of the budding yeast nuclear envelope: flares, fusion, and fenestrations. J. Cell. Physiol. 231, 2353–2360 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. Eibauer, M. et al. Structure and gating of the nuclear pore complex. Nat. Commun. 6, 7532 (2015)

    CAS  PubMed  ADS  Article  Google Scholar 

  30. Paradise, A., Levin, M. K., Korza, G. & Carson, J. H. Significant proportions of nuclear transport proteins with reduced intracellular mobilities resolved by fluorescence correlation spectroscopy. J. Mol. Biol. 365, 50–65 (2007)

    CAS  PubMed  Article  Google Scholar 

  31. Adams, R. L. & Wente, S. R. Uncovering nuclear pore complexity with innovation. Cell 152, 1218–1221 (2013)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. Patel, S. S., Belmont, B. J., Sante, J. M. & Rexach, M. F. Natively unfolded nucleoporins gate protein diffusion across the nuclear pore complex. Cell 129, 83–96 (2007)

    CAS  PubMed  Article  Google Scholar 

  33. Adams, R. L., Terry, L. J. & Wente, S. R. Nucleoporin FG domains facilitate mRNP remodeling at the cytoplasmic face of the nuclear pore complex. Genetics 197, 1213–1224 (2014)

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  34. Timney, B. L. et al. Simple rules for passive diffusion through the nuclear pore complex. J. Cell Biol. 215, 57–76 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. Yamada, J. et al. A bimodal distribution of two distinct categories of intrinsically disordered structures with separate functions in FG nucleoporins. Mol. Cell. Proteomics 9, 2205–2224 (2010)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

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

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  37. Faini, M ., Beck, R., Wieland, F. T. & Briggs, J. A. Vesicle coats: structure, function, and general principles of assembly. Trends Cell Biol. 23, 279–288 (2013)

    CAS  PubMed  Article  Google Scholar 

  38. Rout, M. P. & Field, M. C. The evolution of organellar coat complexes and organization of the eukaryotic cell. Annu. Rev. Biochem. 86, 637–657 (2017)

    CAS  PubMed  Article  Google Scholar 

  39. Obado, S. O. et al. Interactome mapping reveals the evolutionary history of the nuclear pore complex. PLoS Biol. 14, e1002365 (2016)

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  40. Iwamoto, M. et al. Compositionally distinct nuclear pore complexes of functionally distinct dimorphic nuclei in the ciliate Tetrahymena. J. Cell Sci. 130, 1822–1834 (2017)

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Obado, S. O ., Field, M. C. & Rout, M. P. Comparative interactomics provides evidence for functional specialization of the nuclear pore complex. Nucleus 8, 340–352 (2017)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. Bui, K. H. et al. Integrated structural analysis of the human nuclear pore complex scaffold. Cell 155, 1233–1243 (2013)

    CAS  PubMed  Article  Google Scholar 

  43. Debler, E. W. et al. A fence-like coat for the nuclear pore membrane. Mol. Cell 32, 815–826 (2008)

    CAS  PubMed  Article  Google Scholar 

  44. Rout, M. P. & Blobel, G. Isolation of the yeast nuclear pore complex. J. Cell Biol. 123, 771–783 (1993).

    CAS  PubMed  Article  Google Scholar 

  45. LaCava, J., Fernandez-Martinez, J., Hakhverdyan, Z. & Rout, M. P. Protein complex purification by affinity capture. Cold Spring Harb. Protoc. https://doi.org/10.1101/pdb.top077545 (2016)

    Article  Google Scholar 

  46. LaCava, J., Fernandez-Martinez, J., Hakhverdyan, Z. & Rout, M. P. Optimized affinity capture of yeast protein complexes. Cold Spring Harb. Protoc. https://doi.org/10.1101/pdb.prot087932 (2016)

    Article  Google Scholar 

  47. LaCava, J., Fernandez-Martinez, J. & Rout, M. P. Native elution of yeast protein complexes obtained by affinity capture. Cold Spring Harb. Protoc. https://doi.org/10.1101/pdb.prot087940 (2016)

    Article  Google Scholar 

  48. Oeffinger, M. et al. Comprehensive analysis of diverse ribonucleoprotein complexes. Nat. Methods 4, 951–956 (2007)

    CAS  Article  PubMed  Google Scholar 

  49. Hakhverdyan, Z. et al. Rapid, optimized interactomic screening. Nat. Methods 12, 553–560 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. Beynon, R. J., Doherty, M. K., Pratt, J. M. & Gaskell, S. J. Multiplexed absolute quantification in proteomics using artificial QCAT proteins of concatenated signature peptides. Nat. Methods 2, 587–589 (2005)

    CAS  PubMed  Article  Google Scholar 

  51. Shivaraju, M. et al. Cell-cycle-coupled structural oscillation of centromeric nucleosomes in yeast. Cell 150, 304–316 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. Keifer, D. Z., Motwani, T., Teschke, C. M. & Jarrold, M. F. Measurement of the accurate mass of a 50 MDa infectious virus. Rapid Commun. Mass Spectrom. 30, 1957–1962 (2016)

    CAS  PubMed  PubMed Central  Article  ADS  Google Scholar 

  53. Pratt, J. M. et al. Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes. Nat. Protocols 1, 1029–1043 (2006)

    CAS  PubMed  Article  Google Scholar 

  54. Kito, K., Ota, K., Fujita, T. & Ito, T. A synthetic protein approach toward accurate mass spectrometric quantification of component stoichiometry of multiprotein complexes. J. Proteome Res. 6, 792–800 (2007)

    CAS  PubMed  Article  Google Scholar 

  55. Ding, C. et al. Quantitative analysis of cohesin complex stoichiometry and SMC3 modification-dependent protein interactions. J. Proteome Res. 10, 3652–3659 (2011)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. Rout, M. P. & Kilmartin, J. V. Components of the yeast spindle and spindle pole body. J. Cell Biol. 111, 1913–1927 (1990).

    CAS  PubMed  Article  Google Scholar 

  57. Strambio-de-Castillia, C., Blobel, G. & Rout, M. P. Isolation and characterization of nuclear envelopes from the yeast Saccharomyces. J. Cell Biol. 131, 19–31 (1995).

    CAS  PubMed  Article  Google Scholar 

  58. Rout, M. P. & Strambio-de-Castillia, C. in Cell Biology: A Laboratory Handbook 2 (ed. Celis, J. E. ) 143–151 (Academic, 1998)

    Google Scholar 

  59. Cadene, M. & Chait, B. T. A robust, detergent-friendly method for mass spectrometric analysis of integral membrane proteins. Anal. Chem. 72, 5655–5658 (2000).

    CAS  PubMed  Article  Google Scholar 

  60. Fenyo, D. et al. MALDI sample preparation: the ultra thin layer method. J. Vis. Exp. 192, 192 (2007).

    Google Scholar 

  61. Field, H. I., Fenyö, D. & Beavis, R. C. RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database. Proteomics 2, 36–47 (2002).

    CAS  PubMed  Article  Google Scholar 

  62. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008)

    CAS  Article  PubMed  Google Scholar 

  63. Schwanhäusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011)

    PubMed  ADS  Article  CAS  Google Scholar 

  64. Contino, N. C., Pierson, E. E., Keifer, D. Z. & Jarrold, M. F. Charge detection mass spectrometry with resolved charge states. J. Am. Soc. Mass Spectrom. 24, 101–108 (2013)

    CAS  PubMed  ADS  Article  Google Scholar 

  65. Shi, Y. et al. A strategy for dissecting the architectures of native macromolecular assemblies. Nat. Methods 12, 1135–1138 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  66. Leitner, A. et al. Expanding the chemical cross-linking toolbox by the use of multiple proteases and enrichment by size exclusion chromatography. Mol. Cell. Proteomics 11, M111.014126 (2012)

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  67. Yang, B. et al. Identification of cross-linked peptides from complex samples. Nat. Methods 9, 904–906 (2012)

    CAS  PubMed  Article  Google Scholar 

  68. Cevher, M. A. et al. Reconstitution of active human core Mediator complex reveals a critical role of the MED14 subunit. Nat. Struct. Mol. Biol. 21, 1028–1034 (2014)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  69. Sun, J. et al. The architecture of a eukaryotic replisome. Nat. Struct. Mol. Biol. 22, 976–982 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. Zheng, S. Q. et al. UCSF tomography: an integrated software suite for real-time electron microscopic tomographic data collection, alignment, and reconstruction. J. Struct. Biol. 157, 138–147 (2007)

    CAS  PubMed  Article  Google Scholar 

  71. 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)

    CAS  Article  PubMed  Google Scholar 

  72. Galaz-Montoya, J. G., Flanagan, J., Schmid, M. F. & Ludtke, S. J. Single particle tomography in EMAN2. J. Struct. Biol. 190, 279–290 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. Galaz-Montoya, J. G. et al. Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography. J. Struct. Biol. 194, 383–394 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. Yang, Q., Rout, M. P. & Akey, C. W. Three-dimensional architecture of the isolated yeast nuclear pore complex: functional and evolutionary implications. Mol. Cell 1, 223–234 (1998).

    CAS  PubMed  Article  Google Scholar 

  75. Beck, M. et al. Nuclear pore complex structure and dynamics revealed by cryoelectron tomography. Science 306, 1387–1390 (2004)

    CAS  PubMed  ADS  Article  Google Scholar 

  76. von Appen, A. & Beck, M. Structure determination of the nuclear pore complex with three-dimensional cryo electron microscopy. J. Mol. Biol. 428, 2001–2010 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  77. Ludtke, S. J. Single-particle refinement and variability analysis in EMAN2.1. Methods Enzymol. 579, 159–189 (2016)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. Iwanczyk, J. et al. Structure of the Blm10–20 S proteasome complex by cryo-electron microscopy. Insights into the mechanism of activation of mature yeast proteasomes. J. Mol. Biol. 363, 648–659 (2006)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  79. Elad, N. et al. The dynamic conformational landscape of γ-secretase. J. Cell Sci. 128, 589–598 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Kucukelbir, A., Sigworth, F. J. & Tagare, H. D. Quantifying the local resolution of cryo-EM density maps. Nat. Methods 11, 63–65 (2014)

    CAS  Article  PubMed  Google Scholar 

  81. Bharat, T. A. & Scheres, S. H. Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION. Nat. Protocols 11, 2054–2065 (2016)

    CAS  Article  PubMed  Google Scholar 

  82. Bharat, T. A., Russo, C. J., Löwe, J., Passmore, L. A. & Scheres, S. H. Advances in single-particle electron cryomicroscopy structure determination applied to sub-tomogram averaging. Structure 23, 1743–1753 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. Sampathkumar, P. et al. Atomic structure of the nuclear pore complex targeting domain of a Nup116 homologue from the yeast, Candida glabrata. Proteins 80, 2110–2116 (2012). 10.1002/prot.24102

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  84. Sampathkumar, P. et al. Structure of the C-terminal domain of Saccharomyces cerevisiae Nup133, a component of the nuclear pore complex. Proteins 79, 1672–1677 (2011)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  85. Sampathkumar, P. et al. Structures of the autoproteolytic domain from the Saccharomyces cerevisiae nuclear pore complex component, Nup145. Proteins 78, 1992–1998 (2010). 10.1002/prot.22707

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  86. Sampathkumar, P. et al. Structure, dynamics, evolution, and function of a major scaffold component in the nuclear pore complex. Structure 21, 560–571 (2013)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  87. Edelstein, A. D. et al. Advanced methods of microscope control using μManager software. J. Biol. Methods 1, e10 (2014)

    PubMed  Article  Google Scholar 

  88. Ludtke, S. J., Baldwin, P. R. & Chiu, W. EMAN: semiautomated software for high-resolution single-particle reconstructions. J. Struct. Biol. 128, 82–97 (1999)

    CAS  Article  PubMed  Google Scholar 

  89. Yang, Z., Fang, J., Chittuluru, J., Asturias, F. J. & Penczek, P. A. Iterative stable alignment and clustering of 2D transmission electron microscope images. Structure 20, 237–247 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  90. Russel, D. et al. Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies. PLoS Biol. 10, e1001244 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  91. Schneidman-Duhovny, D., Pellarin, R. & Sali, A. Uncertainty in integrative structural modeling. Curr. Opin. Struct. Biol. 28, 96–104 (2014)

    CAS  PubMed  Article  Google Scholar 

  92. Sali, A. et al. Outcome of the first wwPDB Hybrid/Integrative Methods Task Force Workshop. Structure 23, 1156–1167 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  93. LoPiccolo, J. et al. Assembly and molecular architecture of the phosphoinositide 3-kinase p85α homodimer. J. Biol. Chem. 290, 30390–30405 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  94. Luo, J. et al. Architecture of the human and yeast general transcription and DNA repair factor TFIIH. Mol. Cell 59, 794–806 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  95. Robinson, P. J. et al. Molecular architecture of the yeast Mediator complex. eLife 4, e08719 (2015)

    PubMed  PubMed Central  Article  Google Scholar 

  96. Webb, B. et al. Modeling of proteins and their assemblies with the Integrative Modeling Platform. Methods Mol. Biol. 1091, 277–295 (2014)

    CAS  PubMed  Article  Google Scholar 

  97. Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–D705 (2012)

    CAS  PubMed  Article  Google Scholar 

  98. Gautier, R., Douguet, D., Antonny, B. & Drin, G. HELIQUEST: a web server to screen sequences with specific α-helical properties. Bioinformatics 24, 2101–2102 (2008)

    CAS  PubMed  Article  Google Scholar 

  99. Niepel, M. et al. The nuclear basket proteins Mlp1p and Mlp2p are part of a dynamic interactome including Esc1p and the proteasome. Mol. Biol. Cell 24, 3920–3938 (2013)

    PubMed  PubMed Central  Article  Google Scholar 

  100. Šali, A. & Blundell, T. L. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779–815 (1993)

    PubMed  Article  Google Scholar 

  101. Söding, J., Biegert, A. & Lupas, A. N. The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res. 33, W244–W248 (2005)

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  102. Söding, J. Protein homology detection by HMM–HMM comparison. Bioinformatics 21, 951–960 (2005)

    PubMed  Article  Google Scholar 

  103. Buchan, D. W., Minneci, F., Nugent, T. C., Bryson, K. & Jones, D. T. Scalable web services for the PSIPRED protein analysis workbench. Nucleic Acids Res. 41, W349–W357 (2013)

    PubMed  PubMed Central  Article  Google Scholar 

  104. Jones, D. T. Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol. 292, 195–202 (1999)

    CAS  Article  PubMed  Google Scholar 

  105. Ward, J. J., McGuffin, L. J., Bryson, K., Buxton, B. F. & Jones, D. T. The DISOPRED server for the prediction of protein disorder. Bioinformatics 20, 2138–2139 (2004)

    CAS  PubMed  Article  Google Scholar 

  106. Marsden, R. L., McGuffin, L. J. & Jones, D. T. Rapid protein domain assignment from amino acid sequence using predicted secondary structure. Protein Sci. 11, 2814–2824 (2002)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  107. Lupas, A., Van Dyke, M. & Stock, J. Predicting coiled coils from protein sequences. Science 252, 1162–1164 (1991)

    CAS  PubMed  ADS  Article  Google Scholar 

  108. Trigg, J., Gutwin, K., Keating, A. E. & Berger, B. Multicoil2: predicting coiled coils and their oligomerization states from sequence in the twilight zone. PLoS ONE 6, e23519 (2011)

    CAS  PubMed  PubMed Central  ADS  Article  Google Scholar 

  109. Algret, R. et al. Molecular architecture and function of the SEA complex, a modulator of the TORC1 pathway. Mol. Cell. Proteomics 13, 2855–2870 (2014)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  110. Raveh, B. et al. Slide-and-exchange mechanism for rapid and selective transport through the nuclear pore complex. Proc. Natl Acad. Sci. USA 113, E2489–E2497 (2016)

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  111. Schneidman-Duhovny, D., Hammel, M. & Sali, A. FoXS: a web server for rapid computation and fitting of SAXS profiles. Nucleic Acids Res. 38, W540–W544 (2010)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  112. Schneidman-Duhovny, D., Kim, S. J. & Sali, A. Integrative structural modeling with small angle X-ray scattering profiles. BMC Struct. Biol. 12, 17 (2012)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  113. Kawabata, T. Multiple subunit fitting into a low-resolution density map of a macromolecular complex using a Gaussian mixture model. Biophys. J. 95, 4643–4658 (2008)

    CAS  PubMed  PubMed Central  ADS  Article  Google Scholar 

  114. Jonic´, S. et al. Denoising of high-resolution single-particle electron-microscopy density maps by their approximation using three-dimensional Gaussian functions. J. Struct. Biol. 194, 423–433 (2016)

    PubMed  Article  CAS  Google Scholar 

  115. Hanot, S. et al. Multi-scale Bayesian modeling of cryo-electron microscopy density maps. Preprint at https://www.biorxiv.org/content/early/2018/02/09/113951 (2017)

  116. Rout, M. P. et al. The yeast nuclear pore complex: composition, architecture, and transport mechanism. J. Cell Biol. 148, 635–651 (2000).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  117. Shen, M. Y. & Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci. 15, 2507–2524 (2006)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  118. Campelo, F. & Kozlov, M. M. Sensing membrane stresses by protein insertions. PLOS Comput. Biol. 10, e1003556 (2014)

    PubMed  PubMed Central  ADS  Article  CAS  Google Scholar 

  119. Viswanath, S., Chemmama, I. E., Cimermancic, P. & Sali, A. Assessing exhaustiveness of stochastic sampling for integrative modeling of macromolecular structures. Biophys. J. 113, 2344–2353 (2017)

    CAS  PubMed  PubMed Central  ADS  Article  Google Scholar 

  120. Siegel, S. Nonparametric Statistics for the Behavioral Sciences (McGraw-Hill, 1956)

  121. McCarroll, D. Simple Statistical Tests for Geography (Chapman and Hall/CRC, 2016)

  122. McDonald, J. H. Handbook of Biological Statistics 3rd edn (Sparky House, 2014)

  123. Daura, X. et al. Peptide folding: when simulation meets experiment. Angew. Chem. Int. Ed. Engl. 38, 236–240 (1999)

    CAS  Article  Google Scholar 

  124. Kuzmanic, A. & Zagrovic, B. Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors. Biophys. J. 98, 861–871 (2010)

    CAS  PubMed  PubMed Central  ADS  Article  Google Scholar 

  125. Read, R. J. et al. A new generation of crystallographic validation tools for the Protein Data Bank. Structure 19, 1395–1412 (2011)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  126. Montelione, G. T. et al. Recommendations of the wwPDB NMR Validation Task Force. Structure 21, 1563–1570 (2013)

    CAS  PubMed  Article  Google Scholar 

  127. Henderson, R. et al. Outcome of the first Electron Microscopy Validation Task Force meeting. Structure 20, 205–214 (2012)

    CAS  Article  PubMed  Google Scholar 

  128. Trewhella, J. et al. Report of the wwPDB Small-Angle Scattering Task Force: data requirements for biomolecular modeling and the PDB. Structure 21, 875–881 (2013)

    CAS  PubMed  Article  Google Scholar 

  129. Leitner, A. et al. Chemical cross-linking/mass spectrometry targeting acidic residues in proteins and protein complexes. Proc. Natl Acad. Sci. USA 111, 9455–9460 (2014)

    CAS  PubMed  ADS  Article  PubMed Central  Google Scholar 

  130. Erzberger, J. P. et al. Molecular architecture of the 40S·eIF1·eIF3 translation initiation complex. Cell 158, 1123–1135 (2014)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  131. Alber, F., Förster, F., Korkin, D., Topf, M. & Sali, A. Integrating diverse data for structure determination of macromolecular assemblies. Annu. Rev. Biochem. 77, 443–477 (2008)

    CAS  PubMed  Article  Google Scholar 

  132. Alber, F ., Chait, B. T ., Rout, M. P. & Sali, A. in Protein–Protein Interactions and Networks: Identification, Characterization and Prediction (eds Panchenko, A . & Przytycka, T. ) 99–114 (Springer, 2008)

  133. Ermak, D. L. & Mccammon, J. A. Brownian dynamics with hydrodynamic interactions. J. Chem. Phys. 69, 1352–1360 (1978)

    CAS  ADS  Article  Google Scholar 

  134. Hough, L. E. et al. The molecular mechanism of nuclear transport revealed by atomic-scale measurements. eLife 4, e10027 (2015)

    PubMed  PubMed Central  Article  Google Scholar 

  135. Milles, S. et al. Plasticity of an ultrafast interaction between nucleoporins and nuclear transport receptors. Cell 163, 734–745 (2015)

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  136. Sakiyama, Y., Mazur, A., Kapinos, L. E. & Lim, R. Y. Spatiotemporal dynamics of the nuclear pore complex transport barrier resolved by high-speed atomic force microscopy. Nat. Nanotechnol. 11, 719–723 (2016)

    CAS  PubMed  ADS  Article  Google Scholar 

  137. van der Maarel, J. R. C. Introduction to Biopolymer Physics (World Scientific, 2008)

  138. Denning, D. P., Patel, S. S., Uversky, V., Fink, A. L. & Rexach, M. Disorder in the nuclear pore complex: the FG repeat regions of nucleoporins are natively unfolded. Proc. Natl Acad. Sci. USA 100, 2450–2455 (2003).

    CAS  PubMed  ADS  Article  PubMed Central  Google Scholar 

  139. Lemke, E. A. The multiple faces of disordered nucleoporins. J. Mol. Biol. 428, 2011–2024 (2016)

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  140. Lim, R. Y. et al. Flexible phenylalanine–glycine nucleoporins as entropic barriers to nucleocytoplasmic transport. Proc. Natl Acad. Sci. USA 103, 9512–9517 (2006)

    CAS  PubMed  ADS  Article  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank B. Webb (UCSF) for help with the Integrative Modelling Platform, the Rockefeller University Outreach Program for support for A.S.C., the NYULMC OCS Microscopy Core, K. Uryu and the EMRC Resource Center (Rockefeller University) for assistance with negative-stain electron microscopy, F. Alber, M. C. Field, N. Ketaren, S. Obado, R. Hayama and D. Simon for feedback and critical reading of the manuscript, and L. Herlands for support and encouragement. The work was supported by a NSF GRF 1650113 (I.E.C.), a NSF grant CHE-1531823 (M.F.J.), the SIMR (J.L.G.), NIH grants R01 GM080477 (J.L.G.), U54 GM103511 (B.T.C., A.S., J.D.A. and M.P.R.), R01 GM112108 (M.P.R. and J.D.A.), P41 GM109824 (M.P.R., A.S., J.D.A. and B.T.C.), P50 GM076547 (J.D.A.), R01 GM063834 (C.W.A.), R01 GM080139 (S.J.L.), P41 GM103314 (B.T.C.), R01 GM083960 (A.S.) and U54 DK107981 (M.P.R. and J.D.A.). We are grateful for the support provided by G. Blobel, who inspired the work presented here.

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Contributions

The order of first co-authors was determined through a random selection process. I.N., J.F.-M., A.S.C., R.W. and M.P.R. performed the affinity purifications; W.Z., J.F.-M., R.W., R.M., E.Y.J., M.P.R. and B.T.C. performed the quantitative mass spectrometry; M.S., B.D.S., J.R.U. and J.L.G. performed the calibrated imaging; J.A.H.. B.T.C. and M.F.J. performed the charge detection mass spectrometry; Y.S., J.F.-M., R.W., I.N., J.W. and B.T.C. performed the chemical crosslinking with mass spectrometry; C.W.A., S.J.L., I.N., Z.Y. and M.J.d.l.C. performed the cryo-ET; S.J.K. performed the small-angle X-ray scattering; T.H., J.F.-M. and J.D.A. performed the phenotypic profiling; P.U. and D.L.S. performed the negative-stain electron microscopy; S.J.K., B.R., I.E.C., R.P., I.E., C.H.G. and A.S. performed the integrative structure computations; S.J.L., C.W.A., B.T.C., A.S. and M.P.R. supervised the project; S.J.K., J.F.-M., I.N., Y.S., W.Z., B.R., S.J.L., C.W.A., B.T.C., A.S. and M.P.R. wrote the manuscript.

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Correspondence to Steven J. Ludtke, Christopher W. Akey, Brian T. Chait, Andrej Sali or Michael P. Rout.

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Extended data figures and tables

Extended Data Figure 1 Integrative structure determination of the S. cerevisiae NPC at 9 Å precision.

a, Schematic of integrative structure determination of the S. cerevisiae NPC. Random initial structures of the Nups and their sub-complexes were optimized by satisfying spatial restraints implied by the input information. b, The full description of integrative structure determination of the S. cerevisiae NPC, proceeded through four stages8,90,91,92 (Supplementary Table 3): (1) gathering data, (2) representing subunits and translating data into spatial restraints, (3) configurational sampling to produce an ensemble of structures that satisfies the restraints and (4) analysing and validating the ensemble structures and data (Extended Data Figs 7, 8Supplementary Tables 2–4 and Methods). The integrative structure modelling protocol (stages 2, 3 and 4) was scripted using the Python modelling interface package version 4d97507, which is a library for modelling macromolecular complexes based on our open-source IMP package90 version 2.6 (https://integrativemodeling.org). c, Convergence of the structure score for the 5,529 good-scoring NPC structures; the scores do not continue to improve as more structures are computed, essentially independently of each other. The error bar represents the standard deviations of the best scores, estimated by repeating sampling of NPC structures ten times (n?=?10, mean score values plotted). The red dotted line indicates the total score threshold (88,644.1) that defines the good-scoring NPC structures (Methods). d, Distribution of scores for structure samples 1 (red) and 2 (blue), comprising the 5,529 good-scoring NPC structures (nsample1?=?2,359 and nsample2?=?3,170 structures). The non-parametric Kolmogorov–Smirnov two-sample test120,121 (two-sided) indicates that the difference between the two score distributions is insignificant (P value (1.0)?>?0.05). In addition, the magnitude of the difference is small, as demonstrated by the Kolmogorov–Smirnov two-sample test statistic, D, of 0.045. Thus, the two score distributions are effectively equal. e, Three criteria for determining the sampling precision (y axis), evaluated as a function of the r.m.s.d. clustering threshold123 (x axis) (n?=?5,529 structures). First, the P value is computed using the χ2-test (one-sided) for homogeneity of proportions122 (red dots). Second, an effect size for the χ2-test is quantified by the Cramer’s V value (blue squares). Third, the population of structures in sufficiently large clusters (containing at least ten structures from each sample) is shown as green triangles. The vertical dotted grey line indicates the r.m.s.d. clustering threshold at which three conditions are satisfied (χ2-test P value (0.75)?>?0.05 (red, horizontal dotted line), Cramer’s V (0.065)?<?0.10 (blue, horizontal dotted line) and the population of clustered structures (0.90)?>?0.80 (green, horizontal dotted line)), thus defining the sampling precision of 9?Å. The three solid curves (in red, blue and green) were drawn through the points to help visualize the results. f, Population of sample 1 and 2 structures in the three clusters obtained by threshold-based clustering123 using an r.m.s.d. threshold of 12?Å. The dominant cluster (cluster 1) contains 80.3% of the structures. Cluster precision is shown for each cluster. The precision of the dominant cluster defines the structure precision.

Extended Data Figure 2 Quantitative analysis of the mass and stoichiometry of the endogenous NPC (part 1).

a, A multipronged approach to accurately define the mass, stoichiometry and composition of native macromolecular assemblies. Schematic is shown of the multiple orthologous methods that are integrated within our strategy for the analysis of native assemblies. The main experimental methods are listed on top, followed by the characteristic that they help to quantify (in blue) and the type of sample to which they were applied. The final outcome of each method is indicated (black arrows); the steps of each method that are compared to serve as a cross-check control are indicated (blue dashed lines). At bottom, the integration of the different data points into a final comprehensive description of the endogenous assembly is depicted. Small cartoon insets of the NPC are used to illustrate the analysis. b, SDS-PAGE analysis of the affinity-captured S. cerevisiae NPCs isolated from an MLP1–PPX-PrA tagged strain (n?>?20 independent experiments). Molecular weight marker values (Mw) are indicated to the left of the gel lane. Dots signify the main protein components of the isolated NPCs as identified by liquid chromatography–mass spectrometry (Extended Data Fig. 3c). Proteins are grouped and coloured by functional categories or membership of discrete macromolecular assemblies. Nups, blue; mRNA transport factors (TFs), red; transport factors, orange; transcription-export (TREX), green; contaminants and/or others, grey. For gel source data, see Supplementary Fig. 1. c, Cryo-electron microscopy analysis of the affinity-captured NPCs (n?>?20 independent experiments). The particles have a clear preferred orientation (Methods). Some side views are presented in the inset. The central transporter is present in every NPC (indicated by ‘T’). Scale bar, 1,000?Å. d, Schematic showing the primary amino acid sequence of the 148.2?kDa synthetic QconCAT-A. It includes two peptides for each Nup (thick bars), arranged in the indicated order. The native three amino acid residues flanking regions (thin bars) of each peptide were included to preserve the native trypsin target sequence. A N-terminal 3×FLAG tag was included, as well as a C-terminal 6×His tag for purification under denaturing conditions. The stringent criteria used for the selection of the QconCAT peptides are described in the Methods. e, MALDI mass spectrometry spectrum of intact, purified full-length QconCAT-A labelled with stable isotope, showing that a single species was detected. Numbers above peaks denote the QconCAT-A protein species with n positive charges and the 2M QconCAT-A protein dimer. The measured molecular weight of the QconCAT-A labelled with stable isotope was 149,049 ± 38 Da, consistent with its calculated molecular weight of 148,200 Da (Methods).

Extended Data Figure 3 Quantitative analysis of the mass and stoichiometry of the endogenous NPC (part 2).

a, Left, schematic localization of the Nup–GFP reporters selected for the in vivo calibrated imaging stoichiometry analyses. Nups were selected to represent every major NPC module and to provide comprehensive coverage of the assembly. Right, Kernel density estimation of distributions of GFP proteins per Nup were calculated from the calibrated imaging data. n?=?48–178. b, Heat map of a yeast cell expressing Nup85–GFP. Image (left) was acquired as described in Methods. In addition, for illustration purposes, a maximum projection along the z axis was performed, and the image was smoothed with a Gaussian blur of radius 1. A heat map was used to illustrate intensity units in raw photon counts. For the area outlined in a red rectangle, a 2D distribution of photon counts and the corresponding Gaussian fit are shown (right). c, Stoichiometries of main components associated with the affinity-captured NPCs, as determined by label-free mass spectrometry quantification (at least three peptides per protein). Proteins are grouped and coloured by functional categories or membership of discrete macromolecular assemblies. The TREX complex components are included in the ‘Transport & Associated Factors’ category and labelled with an asterisk. QconCAT-derived stoichiometries for all the Nups (dark grey bars) are shown for comparison.

Extended Data Figure 4 Cryo-ET strategy and the resulting 3D cryo-ET map of the NPC exhibiting non-enforced local C2-symmetry axes in the inner ring.

a, Diagram describing the methodology used to obtain the whole S. cerevisiae NPC cryo-ET map (Methods). b, 2D class averages are shown (protein in white), which were calculated using the original unaligned sub-tomograms projected along the z axis. The overall thickness of the S. cerevisiae NPC is apparent in a side-view class, and the local C2-symmetry axes in the inner ring are also apparent (indicated with ‘2’). The transporter density is present in every class. c, Left, top view of the cryo-ET map with the two local C2-symmetry axes indicated by arrows and labels (sym 1 and sym 2). They are 22.5° apart, owing to the C8-symmetry axis. Right, 2D projections of the top view, and two side views along the two local C2-symmetry axes (side 1 and side 2 projected along axes sym 1 and sym 2, respectively). d, Seven cross-sections of the cryo-ET map are shown on the right (labelled 1–7) with their positions in the 3D map indicated in the side view on the left. The local C2-symmetry of the inner ring is apparent in cross-sections 2–6, mirrored about the central section in panel 4. Labels throughout: C, cytoplasm; N, nucleoplasm; T, central transporter; S, core scaffold; MR, membrane ring; IR, inner ring. Scale bar, 100?Å.

Extended Data Figure 5 Resolution estimates for the cryo-ET map of the NPC and comparison of cross-sections between the intermediate, final and RELION cryo-ET maps.

a, b, Top (a) and side (b) views of the cryo-ET map are colour-coded according to local resolution estimates (colour bar), and are shown at a low threshold to reveal weaker density features at the periphery of the NPC that are more flexible. c, Cross-sections are shown at a reduced scale, colour coded according to local resolution estimates (colour bar). A remnant of the pore membrane (M) is present, encircling the entire mid-line of the NPC. Sections 3–5 are shown at a higher threshold. In section 3, the inner-ring region is indicated by ‘spokes’. In section 4, local C2-symmetry axes are indicated by dashed arrows. d, Thick sections of the inner ring are shown at a higher threshold, as viewed along the membrane plane. Note that the inner ring (indicated) is almost entirely in the 20–25?Å resolution range. C, cytoplasmic side; N, nuclear side; CR, cytoplasmic ring; NR, nuclear ring; M, pore membrane; T, central transporter. e, Comparison of five cross-sections (cross-section number on left) in the inner-ring region of the NPC between cryo-ET maps in different stages of the reconstruction process (Extended Data Fig. 4a): intermediate map (left column), final map (middle column) and an independent validation map, reconstructed with RELION at a twice-reduced Å per pixel size (right column). Details on the reconstruction of maps are provided in Methods.

Extended Data Figure 6 2D classification of projections from 1,864 original NPC sub-tomograms aligned with their C8-symmetry axis nearly along the z axis.

a, In total, 18 good class averages are shown after maximum likelihood classification (using RELION 1.481,82) without symmetry imposed. Each class average (on the left) is paired with a C8-symmetry enforced image of itself (on the right). Central transporter densities are present in each of the class averages (both with and without imposed C8-symmetry), indicating that the central transporter is generally present in these particles. b, An expanded view of a large class from a shows bridges (indicated) between the core scaffold and the central transporter, both before (left) and after averaging (right) using the C8-symmetry of the NPC. S, core scaffold; MR, membrane ring; T, central transporter. Matching panels in a and b are marked with white dots. c, d, The cryo-ET 3D map is presented as in Fig. 3 and is zoomed in to show the meshwork of bridges between the scaffold and the central transporter, as viewed from the cytoplasm and the nucleoplasm, respectively.

Extended Data Figure 7 Validation of the NPC structure (part 1).

ac, Satisfaction of the chemical cross-links. a, Identified chemical cross-links were mapped onto the integrative structure of the entire NPC, as shown in front (upper) and top (lower) views. Satisfied cross-links, with Cα–Cα distances that fall within the distance threshold of 35?Å in at least one good-scoring NPC structure, are shown in blue. Violated cross-links, with Cα–Cα distances that are larger than 35?Å, are shown in orange. The histogram on the right shows the distribution of the cross-linked Cα–Cα distances, validating the NPC structure. b, Mapping of the cross-links onto the cytoplasmic and nucleoplasmic connector Nups (Nup116, Nup100, Nup145N, Nup1 and Nup60). Front (right) and side (left) views show how the NPC outer rings are connected to the inner ring through a network of connector Nups across the length of the spoke. c, Mapping of the cross-links onto the inner (and membrane) and outer rings, in front (upper) and top (lower) views. dg, Satisfaction of data and considerations that were not used to compute the structure. d, Our integrative structure of the NPC (left) was compared a previously published topological map3,8 (right). The two structures are consistent with each other, though our integrative structure is defined at an order of magnitude higher precision. e, Satisfaction of affinity purification and overlay assays data (composites); our current structure satisfies all 82 composites determined by affinity purification and overlay assays3,8, even though these data were not used in its determination. For example, Pom152, Pom34, Ndc1, Nup157 and Nup170 are connected with each other (left), consistent with the previously published composites determined using the affinity purification data3,8 (right). f, Satisfaction of SAXS data; the atomic structures of eight Nups are consistent with the corresponding SAXS profiles for their constructs9,12,23,83,84,85,86 (Supplementary Tables 2, 6 and Methods). For example, the SAXS profile calculated from the atomic structure of Pom152718–1148 (red curve) using FoXS111 is well-matched (χ?=?1.48) to the corresponding experimental SAXS profile23 (black dots; n?=?20 exposures). For visualization purposes, the Pom152718–1148 structure (represented as a ribbon) is shown along with the best fit of the ab initio shape (represented as a transparent envelope) computed from the experimental SAXS profile. g, Satisfaction of the negative-stain electron microscopy 2D class averages for the Nic96 complex; the structures of the Nic96 complex (composed of Nic96, Nsp1, Nup49 and Nup57) in the dominant cluster can be projected well on 2D class averages obtained for the natively isolated complex (n?=?5,458 particles; Methods). The experimental class averages were satisfied by the structure with cross-correlation coefficients of 0.85 and 0.80, respectively (Methods).

Extended Data Figure 8 Validation of the NPC structure (part 2), showing consistency between the NPC structure and the cryo-ET density map.

The cryo-ET density map is shown at a high-density threshold (grey) to reveal details of the inner ring. A representative structure of the inner ring is shown docked into the density, showing the excellent fit. All Nups are coloured as in Fig. 4. The pore membrane is indicated by M. a, Full eight-spoke inner ring (scale bar, 100 Å). bd, front (b), top (c) and back (d) views of three spokes with neighbours coloured brown and grey (scale bar, 50 Å). e, Different views of a single spoke (scale bar, 50 Å) are shown within the density map. f, Thick cross-sections are shown through a single spoke in the inner ring, as viewed from the central C8-symmetry axis (scale bar, 50?Å); MBMs (see Fig. 5) are indicated.

Extended Data Figure 9 Functional analysis of the fitness of nucleoporin mutants using ODELAY.

a, The fitness defect phenotype was quantified and plotted (mean Z-score; n?=?6 experiments, containing at least 200–300 individuals per point; see Methods for details) for each nucleoporin truncation or C-terminal protein-A tagged mutant in order of decreasing fitness (increasing number of units), as observed by ODELAY assay14 (Methods). Strains for which truncations in a haploid background were found to lead to lethality after tetrad dissection (Nic96 and Nup192) were assigned the maximum level of defect and plotted on top of the rest (diploid), on the basis of the fitness phenotype observed for the indicated Nic96 and Nup192 mutants in a diploid background (in which a wild-type copy of the nucleoporin is also present and expressed). Six divisions were assigned based on decreasing levels of fitness9,13; white (wild type) to dark purple (severe defect). AU, arbitrary unit; error bar?=?standard deviation. b, Mapping of the colour code described in a into the NPC components. Horizontal lines represent the amino acid residue length of each protein and truncated version; amino acid residue positions are shown on top of the lines.

Extended Data Figure 10 Proposed evolutionary origin of the NPC from a later amalgam of membrane coating complexes.

a, Diagram depicting how the NPC may have originated from an ancestral coatomer module through a series of duplications, divergence and secondary loss events. Top, the origin of an ancestral proto-NPC coatomer module from an amalgamation of COPI-like and COPII-like complexes. Middle, the initial duplication leading to the origin of the inner and outer rings, and their associated coiled bundles. Presumed secondary losses removed the additional COPII-like subunit of the inner-ring protomer; loss of the adaptin-like subunit from the outer ring may have occurred here, or later in only certain lineages. Bottom, another duplication and divergence within each spoke may then have generated two parallel and laterally-offset paralogous columns; in the outer ring, a COPII-like subunit was then lost from one of the duplicates. The coiled bundles of the outer rings gave rise to the cytoplasmic export complex and nuclear basket by subsequent duplication; the export complex itself is a duplicate with a dimer of trimeric coiled bundles in its core. Outer-ring duplications are not shown. Relevant nucleoporin domains are depicted as follows: β-propellers (cyan circles), α-solenoids (pink bars) and coiled-coil domains (orange sticks). Left, diagrams (grey) exemplify the path of duplications within the whole NPC. Examples of ribbon representations for each module are presented. The anchoring points of the coiled-coil cytoplasmic Nup82 complex and the nuclear basket (orange densities) into an equivalent region of the outer-ring Nup84 complex (grey density) are shown. b, Conserved structural motifs connecting spokes in the outer and inner rings. Diagram showing how the spoke-to-spoke connection is established through similar head-to-head connections of heterodimers containing one COPI-like and one COPII-like subunits in both the outer (left) and the inner (right) NPC rings. Top, nucleoporin domains coloured as in a; bottom, COPI-like Nups in red, COPII-like Nups in blue.

Extended Data Figure 11 Position of the FG-repeat anchor points and heat mapping of the FG repeats.

a, Three views of the complete structure of the NPC are shown with major structural features (coloured as in Fig. 4 and Supplementary Table 2) and a snapshot of modelled FG-repeat regions (indicated in green). For each Nup, the localization probability density of the ensemble of structures is shown with a representative structure from the ensemble embedded within it. See also Supplementary Videos 1, 2, 3. Scale bar, 200?Å. b, Positions of FG-repeat anchor points within the ensemble of solutions are depicted as green surfaces; the Nups to which they belong are labelled in the centre image. Left, side view of three spokes; centre, side view of one spoke; right, top view of three spokes. Scale bar, 100?Å. c, Heat mapping of the type of FG-repeat region of each FG Nup (FXFG/FG type, red; GLFG type, blue), showing partitioning of the FG types to different regions of the central transporter. Identity of mapped Nups is shown in the diagram on the right. Scale bar.100?Å. d, Heat mapping of the effect on NPC permeability of the truncation of an FG repeat in each FG Nup, relative to the wild-type strain (p/pWT); the severity of the permeability defect is indicated in increasing intensity of shades of blue from minor defect (light green) to severe defect (dark blue), thereby defining the FG repeats that are most important in maintaining the passive permeability barrier. Identities of mapped Nups are shown in the diagram on the right. Scale bar, 100?Å.

Extended Data Figure 12 Comparison of the S. cerevisiae NPC structure and human NPC core scaffold.

a, Comparison between the inner rings in the structure of the S. cerevisiae NPC (first row) and the core scaffold of the human NPC (second row) (Protein Data Bank code: 5IJN6). Yeast Nups are coloured as in Fig. 4; human Nup homologues are coloured as their yeast counterparts. All copies of human Nup155 are coloured as yeast Nup157, and all copies of human Nup205/Nup188 are coloured as yeast Nup192. Only homologue Nups present in both yeast and human are shown. The human NPC core scaffold includes two additional copies of Nup155 that are absent in yeast (owing to the different stoichiometry between organisms). Yeast Nup53 and Nup59 are not shown because their counterparts are not present in the human NPC core scaffold. b, Major differences in the inner ring between the S. cerevisiae and human NPCs are highlighted, in the cross-sectional view near the equator. c, Positions of yeast Nups homologous to oncogenic human Nups (in parentheses) are shown in red, mapped onto three spokes of the NPC.

Supplementary information

Life Sciences Reporting Summary (PDF 72 kb)

Supplementary Information

This file contains the images from the Cryo-ET raw data (tilt series) and reconstructed tomograms, as well as the “Gold standard” refinement procedure for the final Cryo-ET map; and Supplementary Figure 1: Gel source data for Extended Data Fig. 2B. (PDF 11282 kb)

Supplementary Information

This file contains full supplementary table legends for tables 1-9, supplementary results and discussion, full supplementary video legends, and supplementary references. (PDF 484 kb)

Supplementary Tables

This file contains supplementary tables 1 -9. Supplementary Table 1 contains a list of 3,077 chemical cross-linked peptides identified via mass spectrometry. Supplementary Table 2 contains a representations of the S. cerevisiae NPC components (all 32 Nups) for integrative structure determination. Supplementary Table 3 contains a summary of the integrative structure determination, thoroughness of configurational sampling, and structure precision. Supplementary Table 4 contains a summary of spatial restraints used for the integrative structure determination and data satisfaction. Supplementary Table 5 contains a S. cerevisiae strains used in this study. Supplementary Table 6 contains an analysis of 147 SAXS profiles for 18 Nups. Supplementary Table 7 contains a list of peptides selected to construct QconCAT-A and B. Supplementary Table 8 contains a label-free MS analysis of native affinity captured NPCs and associated proteins. Supplementary Table 9 contains a cryo-electron tomographic data collection, processing, and refinement. (see Supplementary Information document for full table legends) (ZIP 4029 kb)

Supplementary Data

This file contains Source Data (part 1) for SAXS. It contains the SAXS data for Nup133, Nup120, Nup84, Nup85, Pom152, Nup145, Nup100, and Nup116. (ZIP 14369 kb)

Supplementary Data

This file contains Source Data (part 2) for SAXS. It contains the SAXS data for Nup188, Nup192, Nup2, Nup53, Nup59, Nup60, Nup82, Nsp1, Mlp1, and Mlp2. (ZIP 16649 kb)

Integrative structure and functional anatomy of the yeast Nuclear Pore Complex.

For each Nup (color-coded according to Supplementary Table 2B-H; same as Fig. 4), the localization probability density of the ensemble of structures is shown along with a representative atomic structure (where available) embedded within the localization density. A model of the pore membrane region is shown in light grey. First, we show a summary of the data used to compute the NPC structure. Second, the structure is rotated and shown in different orientations. (MP4 27862 kb)

Structural dissection of the yeast Nuclear Pore Complex.

Structural dissection of the yeast Nuclear Pore Complex. Using the same representation as in Supplementary Video 1, the structure of the NPC is dissected into its component modules and nucleoporins, emphasizing the spoke-to-spoke connections. (MP4 29186 kb)

Architectural and functional features of the yeast Nuclear Pore Complex.

Using the same representation as in Supplementary Video 1, first we show the position of the membrane interacting region, extended disordered connectors, and FG repeat anchor points are shown. Second, we a show a Brownian dynamics simulation of FG repeats. Third, we show the localization density of the FG repeats in the central channel. (MP4 19662 kb)

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Kim, S., Fernandez-Martinez, J., Nudelman, I. et al. Integrative structure and functional anatomy of a nuclear pore complex. Nature 555, 475–482 (2018). https://doi.org/10.1038/nature26003

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