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.

  • Article
  • Published:

Megabodies expand the nanobody toolkit for protein structure determination by single-particle cryo-EM

Nature Methods volume 18, pages 60–68 (2021)Cite this article

Subjects

Abstract

Nanobodies are popular and versatile tools for structural biology. They have a compact single immunoglobulin domain organization, bind target proteins with high affinities while reducing their conformational heterogeneity and stabilize multi-protein complexes. Here we demonstrate that engineered nanobodies can also help overcome two major obstacles that limit the resolution of single-particle cryo-electron microscopy reconstructions: particle size and preferential orientation at the water–air interfaces. We have developed and characterized constructs, termed megabodies, by grafting nanobodies onto selected protein scaffolds to increase their molecular weight while retaining the full antigen-binding specificity and affinity. We show that the megabody design principles are applicable to different scaffold proteins and recognition domains of compatible geometries and are amenable for efficient selection from yeast display libraries. Moreover, we demonstrate that megabodies can be used to obtain three-dimensional reconstructions for membrane proteins that suffer from severe preferential orientation or are otherwise too small to allow accurate particle alignment.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Molecular design of rigid antibody chimera called megabodies.
Fig. 2: Selection of megabodies from nanobody-immune libraries by yeast display.
Fig. 3: Cryo-EM datasets of the homomeric GABAA β3 receptor alone, in complex with Nb25 or bound to megabodies derived from Nb25.
Fig. 4: Megabody-enabled high-resolution structure of homopentameric β3 GABAAR in lipid nanodiscs.
Fig. 5: \({\mathrm{Mb}}_{{\mathrm{NbF3}}}^{{\mathrm{c7HopQ}}}\), an MSP-specific megabody randomizes the orientation of nanodisc-embedded β3 GABAAR particles.

Similar content being viewed by others

Data availability

DNA sequences of pMESD2, pMESD22c7, pMESP23E2, pMESP23NO, pNMB2, pNMB1m_C_Nb207 and pNS1MB plasmids have been deposited in GenBank with accession codes MT328400, MT338520, MT338521, MT338522, MT338523, MT543226 and MT543227, respectively. All megabody-expression plasmids are available from the Steyaert Lab upon request by contacting mta.requests@vib.be. X-ray structure coordinates and structure factors for \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{cHopQ}}}\), \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{c7HopQA12}}}\), \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{c7HopQG10}}}\) and \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{cYgjKNO}}}\) structures have been deposited in the Protein Data Bank under accession codes 6QD6, 6XVI, 6XV8 and 6XUX, respectively. Atomic coordinates and cryo-EM density maps of β3 GABAAR–\({\mathrm{Mb}}_{{\mathrm{Nb25}}}^{{\mathrm{c7HopQ}}}\) have been deposited in the Protein Data Bank and the Electron Microscopy Data Bank under accession codes 6QFA and EMD-4542, respectively. The cryo-EM density map of β3 GABAAR–\({\mathrm{Mb}}_{{\mathrm{NbF3}}}^{{\mathrm{c7HopQ}}}\) complex has been deposited in the Electron Microscopy Data Bank under accession code EMD-11610. The refined atomic coordinates and cryo-EM maps of WbaP–\({\mathrm{Mb}}_{{\mathrm{Nb73}}}^{{\mathrm{c7HopQ}}}\) and 5-HT3A–\({\mathrm{Mb}}_{{\mathrm{NbF3}}}^{{\mathrm{c7HopQ}}}\) complexes will be published elsewhere. Other data that support the findings of this study are available from the corresponding authors on request. Source data are provided with this paper.

References

  1. Kühlbrandt, W. The resolution revolution. Science 343, 1443–1444 (2014).

    Article  PubMed  Google Scholar 

  2. Fernandez-Leiro, R. & Scheres, S. H. W. Unravelling biological macromolecules with cryo-electron microscopy. Nature 537, 339–346 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. García-Nafría, J. & Tate, C. G. Cryo-electron microscopy: moving beyond X-ray crystal structures for drug receptors and drug development. Annu. Rev. Pharmacol. Toxicol. 60, 51–71 (2020).

    Article  PubMed  CAS  Google Scholar 

  4. Danev, R., Yanagisawa, H. & Kikkawa, M. Cryo-electron microscopy methodology: current aspects and future directions. Trends Biochem. Sci. 44, 837–848 (2019).

    Article  CAS  PubMed  Google Scholar 

  5. Glaeser, R. M. How good can single-particle cryo-EM become? What remains before it approaches its physical limits? Annu. Rev. Biophys. 48, 45–61 (2019).

    Article  CAS  PubMed  Google Scholar 

  6. Henderson, R. The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules. Q. Rev. Biophys. 28, 171–193 (1995).

    Article  CAS  PubMed  Google Scholar 

  7. Danev, R., Buijsse, B., Khoshouei, M., Plitzko, J. M. & Baumeister, W. Volta potential phase plate for in-focus phase contrast transmission electron microscopy. Proc. Natl Acad. Sci. USA 111, 15635–15640 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Danev, R. & Baumeister, W. Expanding the boundaries of cryo-EM with phase plates. Curr. Opin. Struct. Biol. 46, 87–94 (2017).

    Article  CAS  PubMed  Google Scholar 

  9. Fan, X. et al. Single particle cryo-EM reconstruction of 52 kDa streptavidin at 3.2 Angstrom resolution. Nat. Commun. 10, 2386 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Khoshouei, M., Radjainia, M., Baumeister, W. & Danev, R. Cryo-EM structure of haemoglobin at 3.2 Å determined with the Volta phase plate. Nat. Commun. 8, 16099 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Herzik, M. A., Wu, M. & Lander, G. C. High-resolution structure determination of sub-100 kDa complexes using conventional cryo-EM. Nat. Commun. 10, 1032 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Coscia, F. et al. Fusion to a homo-oligomeric scaffold allows cryo-EM analysis of a small protein. Sci. Rep. 6, 30909 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Liu, Y., Huynh, D. T. & Yeates, T. O. A 3.8 Å resolution cryo-EM structure of a small protein bound to an imaging scaffold. Nat. Commun. 10, 1864 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Yeates, T. O., Agdanowski, M. P. & Liu, Y. Development of imaging scaffolds for cryo-electron microscopy. Curr. Opin. Struct. Biol. 60, 142–149 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Naydenova, K. & Russo, C. J. Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy. Nat. Commun. 8, 629 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Glaeser, R. M. & Han, B.-G. Opinion: hazards faced by macromolecules when confined to thin aqueous films. Biophys. Rep. 3, 1–7 (2017).

    Article  CAS  PubMed  Google Scholar 

  17. Noble, A. J. et al. Routine single particle cryoEM sample and grid characterization by tomography. eLife 7, e34257 (2018).

  18. Drulyte, I. et al. Approaches to altering particle distributions in cryo-electron microscopy sample preparation. Acta Crystallogr. D Struct. Biol. 74, 560–571 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tan, Y. Z. et al. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat. Methods 14, 793–796 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Noble, A. J. et al. Reducing effects of particle adsorption to the air–water interface in cryo-EM. Nat. Methods 15, 793–795 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Naydenova, K., Peet, M. J. & Russo, C. J. Multifunctional graphene supports for electron cryomicroscopy. Proc. Natl Acad. Sci. USA 116, 11718–11724 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Martin, T. G. et al. Design of a molecular support for cryo-EM structure determination. Proc. Natl Acad. Sci. USA 113, E7456–E7463 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hamers-Casterman, C. et al. Naturally occurring antibodies devoid of light chains. Nature 363, 446–448 (1993).

    Article  CAS  PubMed  Google Scholar 

  24. Muyldermans, S. Nanobodies: natural single-domain antibodies. Annu. Rev. Biochem. 82, 775–797 (2013).

    Article  CAS  PubMed  Google Scholar 

  25. Koide, S., Koide, A. & Lipovšek, D. in Protein Engineering for Therapeutics, Part B Vol. 503 (eds Wittrup, K. D. & Verdine, G. L.) Ch. 6 (Academic Press, 2012).

  26. Denisov, I. G. & Sligar, S. G. Nanodiscs in membrane biochemistry and biophysics. Chem. Rev. 117, 4669–4713 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Yu, Y. & Lutz, S. Circular permutation: a different way to engineer enzyme structure and function. Trends Biotechnol. 29, 18–25 (2011).

    Article  CAS  PubMed  Google Scholar 

  28. Javaheri, A. et al. Helicobacter pylori adhesin HopQ engages in a virulence-enhancing interaction with human CEACAMs. Nat. Microbiol. 2, 16189 (2016).

    Article  CAS  PubMed  Google Scholar 

  29. Kurakata, Y. et al. Structural insights into the substrate specificity and function of Escherichia coli K12 YgjK, a glucosidase belonging to the glycoside hydrolase family 63. J. Mol. Biol. 381, 116–128 (2008).

    Article  CAS  PubMed  Google Scholar 

  30. Bailey, L. J. et al. Locking the elbow: improved antibody Fab fragments as chaperones for structure determination. J. Mol. Biol. 430, 337–347 (2018).

    Article  CAS  PubMed  Google Scholar 

  31. Spencer-Smith, R. et al. Inhibition of RAS function through targeting an allosteric regulatory site. Nat. Chem. Biol. 13, 62–68 (2017).

    Article  CAS  PubMed  Google Scholar 

  32. Uchański, T. et al. An improved yeast surface display platform for the screening of nanobody immune libraries. Sci. Rep. 9, 382 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Mitchell, L. S. & Colwell, L. J. Comparative analysis of nanobody sequence and structure data. Proteins 86, 697–706 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Jansen, M., Bali, M. & Akabas, M. H. Modular design of Cys-loop ligand-gated ion channels: functional 5-HT3 and GABA rho1 receptors lacking the large cytoplasmic M3M4 loop. J. Gen. Physiol. 131, 137–146 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Zhu, S. et al. Structure of a human synaptic GABAA receptor. Nature 559, 67–72 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Phulera, S. et al. Cryo-EM structure of the benzodiazepine-sensitive α1β1γ2S tri-heteromeric GABAA receptor in complex with GABA. eLife 7, e39383 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Miller, P. S., Masiulis, S., Malinauskas, T. & Kotecha, A. Heteromeric GABAA receptor structures in positively-modulated active states. Preprint at bioRxiv https://doi.org/10.1101/338343 (2018).

  38. Scott, S. & Aricescu, A. R. A structural perspective on GABAA receptor pharmacology. Curr. Opin. Struct. Biol. 54, 189–197 (2019).

    Article  CAS  PubMed  Google Scholar 

  39. Miller, P. S. et al. Structural basis for GABAA receptor potentiation by neurosteroids. Nat. Struct. Mol. Biol. 24, 986–992 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Miller, P. S. & Aricescu, A. R. Crystal structure of a human GABAA receptor. Nature 512, 270–275 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Laverty, D. et al. Cryo-EM structure of the human α1β3γ2 GABAA receptor in a lipid bilayer. Nature 565, 516–520 (2019).

    Article  CAS  PubMed  Google Scholar 

  42. Masiulis, S. et al. GABAA receptor signalling mechanisms revealed by structural pharmacology. Nature 565, 454–459 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Saras, A. et al. Histamine action on vertebrate GABAA receptors: direct channel gating and potentiation of GABA responses. J. Biol. Chem. 283, 10470–10475 (2008).

    Article  CAS  PubMed  Google Scholar 

  44. Mi, W. et al. Structural basis of MsbA-mediated lipopolysaccharide transport. Nature 549, 233–237 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Dang, S. et al. Cryo-EM structures of the TMEM16A calcium-activated chloride channel. Nature 552, 426–429 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Willegems, K. & Efremov, R. G. Influence of lipid mimetics on gating of ryanodine receptor. Structure 26, 1303–1313.e4 (2018).

    Article  CAS  PubMed  Google Scholar 

  47. McGoldrick, L. L. et al. Opening of the human epithelial calcium channel TRPV6. Nature 553, 233–237 (2018).

    Article  CAS  PubMed  Google Scholar 

  48. Dörr, J. M. et al. The styrene–maleic acid copolymer: a versatile tool in membrane research. Eur. Biophys. J. 45, 3–21 (2016).

    Article  PubMed  CAS  Google Scholar 

  49. Carlson, M. L. et al. The Peptidisc, a simple method for stabilizing membrane proteins in detergent-free solution. eLife 7, e34085 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Frauenfeld, J. et al. A saposin-lipoprotein nanoparticle system for membrane proteins. Nat. Methods 13, 345–351 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Ritchie, T. K., Grinkova, Y. V., Bayburt, T. H. & Denisov, I. G. Chapter 11—reconstitution of membrane proteins in phospholipid bilayer nanodiscs. Methods Enzymol. 464, 211–231 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. McLean, M. A., Gregory, M. C. & Sligar, S. G. Nanodiscs: a controlled bilayer surface for the study of membrane proteins. Annu. Rev. Biophys. 47, 107–124 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Nemecz, Á., Prevost, M. S., Menny, A. & Corringer, P.-J. Emerging molecular mechanisms of signal transduction in pentameric ligand-gated ion channels. Neuron 90, 452–470 (2016).

    Article  CAS  PubMed  Google Scholar 

  54. Wu, S. et al. Fabs enable single particle cryoEM studies of small proteins. Structure 20, 582–592 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Dutka, P. et al. Development of ‘Plug and Play’ fiducial marks for structural studies of GPCR signaling complexes by single-particle cryo-EM. Structure 27, 1862–1874.e7 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Jiang, X.-M. et al. Structure and sequence of the rfb (O antigen) gene cluster of Salmonella serovar typhimurium (strain LT2). Mol. Microbiol. 5, 695–713 (1991).

    Article  CAS  PubMed  Google Scholar 

  57. Whitfield, C. & Paiment, A. Biosynthesis and assembly of group 1 capsular polysaccharides in Escherichia coli and related extracellular polysaccharides in other bacteria. Carbohydr. Res. 338, 2491–2502 (2003).

    Article  CAS  PubMed  Google Scholar 

  58. Nakane, T. et al. Single-particle cryo-EM at atomic resolution. Nature 587, 152–156 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lyumkis, D. Challenges and opportunities in cryo-EM single-particle analysis. J. Biol. Chem. 294, 5181–5197 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Renaud, J.-P. et al. Cryo-EM in drug discovery: achievements, limitations and prospects. Nat. Rev. Drug Discov. 17, 471 (2018).

    Article  CAS  PubMed  Google Scholar 

  61. Boriack-Sjodin, P. A., Margarit, S. M., Bar-Sagi, D. & Kuriyan, J. The structural basis of the activation of Ras by Sos. Nature 394, 337–343 (1998).

    Article  CAS  PubMed  Google Scholar 

  62. Scholz, O., Thiel, A., Hillen, W. & Niederweis, M. Quantitative analysis of gene expression with an improved green fluorescent protein. Eur. J. Biochem. 267, 1565–1570 (2000).

    Article  CAS  PubMed  Google Scholar 

  63. Taylor, R. G., Walker, D. C. & McInnes, R. R. E. coli host strains significantly affect the quality of small scale plasmid DNA preparations used for sequencing. Nucleic Acids Res. 21, 1677–1678 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Molday, R. S. & Mackenzie, D. Monoclonal antibodies to rhodopsin: characterization, cross-reactivity, and application as structural probest. Biochemistry 22, 653–660 (1983).

    Article  CAS  PubMed  Google Scholar 

  65. Polovinkin, L. et al. Conformational transitions of the serotonin 5-HT3 receptor. Nature 563, 275–279 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hassaïne, G. et al. in Membrane Protein Structure and Function Characterization: Methods and Protocols (ed. Lacapere, J.-J.) 211–231 (Springer, 2017) https://doi.org/10.1007/978-1-4939-7151-0_8.

  67. Desmyter, A. et al. Crystal structure of a camel single-domain VH antibody fragment in complex with lysozyme. Nat. Struct. Biol. 3, 803–811 (1996).

    Article  CAS  PubMed  Google Scholar 

  68. Pardon, E. et al. A general protocol for the generation of nanobodies for structural biology. Nat. Protoc. 9, 674–693 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. De Genst, E., Saerens, D., Muyldermans, S. & Conrath, K. Antibody repertoire development in camelids. Dev. Comp. Immunol. 30, 187–198 (2006).

    Article  PubMed  CAS  Google Scholar 

  70. Pardon, E., Steyaert, J. & Wyns, L. Epitope tag for affinity-based applications. Patent WO2011147890 (2011).

  71. De Genst, E. J. et al. Structure and properties of a complex of alpha-synuclein and a single-domain camelid antibody. J. Mol. Biol. 402, 326–343 (2010).

    Article  PubMed  CAS  Google Scholar 

  72. Uchański, T. et al. Constructing and purifying megabodies starting from individual nanobody sequences. Protoc. Exch. (2020) https://doi.org/10.21203/rs.3.pex-1033/v1.

  73. Geertsma, E. R. & Dutzler, R. A versatile and efficient high-throughput cloning tool for structural biology. Biochemistry 50, 3272–3278 (2011).

    Article  CAS  PubMed  Google Scholar 

  74. Zell, R. & Fritz, H. J. DNA mismatch-repair in Escherichia coli counteracting the hydrolytic deamination of 5-methyl-cytosine residues. EMBO J. 6, 1809–1815 (1987).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Kabsch, W. XDS. Acta Crystallogr. D Struct. Biol. 66, 125–132 (2010).

    Article  CAS  Google Scholar 

  76. Smart, O. S. et al. Exploiting structure similarity in refinement: automated NCS and target-structure restraints in BUSTER. Acta Crystallogr. D Biol. Crystallogr. 68, 368–380 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D Biol. Crystallogr. 66, 12–21 (2010).

    Article  CAS  PubMed  Google Scholar 

  79. Kyte, J. & Doolittle, R. F. A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157, 105–132 (1982).

    Article  CAS  PubMed  Google Scholar 

  80. Baker, N. A., Sept, D., Joseph, S., Holst, M. J. & McCammon, J. A. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl Acad. Sci. USA 98, 10037–10041 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. 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 

  82. Shkumatov, A. V. & Strelkov, S. V. DATASW, a tool for HPLC-SAXS data analysis. Acta Crystallogr. D Biol. Crystallogr. 71, 1347–1350 (2015).

    Article  CAS  PubMed  Google Scholar 

  83. Franke, D. et al. ATSAS 2.8: a comprehensive data analysis suite for small-angle scattering from macromolecular solutions. J. Appl. Crystallogr. 50, 1212–1225 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Svergun, D., Barberato, C. & Koch, M. H. J. CRYSOL—a program to evaluate X-ray solution scattering of biological macromolecules from atomic coordinates. J. Appl. Crystallogr. 28, 768–773 (1995).

    Article  CAS  Google Scholar 

  85. Rakestraw, J. A., Sazinsky, S. L., Piatesi, A., Antipov, E. & Wittrup, K. D. Directed evolution of a secretory leader for the improved expression of heterologous proteins and full-length antibodies in Saccharomyces cerevisiae. Biotechnol. Bioeng. 103, 1192–1201 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Chao, G. et al. Isolating and engineering human antibodies using yeast surface display. Nat. Protoc. 1, 755–768 (2006).

    Article  CAS  PubMed  Google Scholar 

  87. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Tegunov, D. & Cramer, P. Real-time cryo-electron microscopy data preprocessing with Warp. Nat. Methods 16, 1146–1152 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–297 (2017).

    Article  CAS  PubMed  Google Scholar 

  91. Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Zivanov, J., Nakane, T. & Scheres, S. H. W. A Bayesian approach to beam-induced motion correction in cryo-EM single-particle analysis. IUCrJ 6, 5–17 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Swint-Kruse, L. & Brown, C. S. Resmap: automated representation of macromolecular interfaces as two-dimensional networks. Bioinformatics 21, 3327–3328 (2005).

    Article  CAS  PubMed  Google Scholar 

  94. Afonine, P. V. et al. Real-space refinement in PHENIX for cryo-EM and crystallography. Acta Crystallogr. D Struct. Biol. 74, 531–544 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Burnley, T., Palmer, C. M. & Winn, M. Recent developments in the CCP-EM software. Acta Crystallogr. D Biol. Crystallogr. 73, 469–477 (2017).

    Article  CAS  Google Scholar 

  96. Terwilliger, T. C., Adams, D. & Urzhumtsev, A. New tools for the analysis and validation of cryo-EM maps and atomic models. Acta Crystallogr. D Biol. Crystallogr. 74, 814–840 (2018).

    Article  Google Scholar 

  97. Smart, O. S., Neduvelil, J. G., Wang, X., Wallace, B. A. & Sansom, M. S. P. HOLE: a program for the analysis of the pore dimensions of ion channel structural models. J. Mol. Graph. 14, 354–360 (1996).

    Article  CAS  PubMed  Google Scholar 

  98. Denisov, I., Baas, B., Grinkova, Y. & Sligar, S. Cooperativity in cytochrome P450 3A4—linkages in substrate binding, spin state, uncoupling, and product formation. J. Biol. Chem. 282, 7066–7076 (2007).

    Article  CAS  PubMed  Google Scholar 

  99. Wagner, T. et al. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Commun. Biol. 2, 218 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  100. Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Punjani, A., Zhang, H. & Fleet, D. J. Non-uniform refinement: adaptive regularization improves single particle cryo-EM reconstruction. Preprint at bioRxiv https://doi.org/10.1101/2019.12.15.877092 (2019).

Download references

Acknowledgements

We thank A.V. Shkumatov and R.K. Singh for support with SAXS experiments, and H. De Greve for providing the GFP+-expressing E. coli strain. We thank Instruct-ERIC, part of the European Strategy Forum on Research Infrastructures (ESFRI), Instruct-ULTRA (EU H2020 grant no. 731005) and the Research Foundation—Flanders (FWO) for support with nanobody discovery and for funding the PhD training of T.U. We thank E. Beke for the technical assistance during megabody recloning. We thank Diamond Light Source, Harwell, UK, for access to crystallographic beamlines I03 and I24, and SAXS beamline B21. Cryo-EM studies of GABAA receptor were supported by the UK Medical Research Council grants no. MR/L009609/1 and no. MC_UP_1201/15 to A.R.A. We thank S. Chen, G. Cannone, G. Sharov and A. Yeates for support at the MRC-LMB EM facility; and J. Grimmett, T. Darling and T. Pratt for help with IT and high-performance computing. Cryo-EM studies of 5-HT3A receptor were supported by the ERC Starting grant no. 637733 Pentabrain, and the Fondation pour la Recherche Médicale grant no. SPF201809007073 to U.L.-S. We thank G. Schoehn and the IBS electron microscopy facility, supported by the Rhône-Alpes Region, the FRM, the FEDER and the GIS-IBISA. Cryo-EM studies of WbaP transferase were performed at Oxford Particle Imaging Centre founded by a Wellcome Trust JIF award (grant no. 060208/Z/00/Z) and supported by equipment grants from WT (grant no. 093305/Z/10/Z). We thank B. Qureshi for support with electron microscopy.

Author information

Authors and Affiliations

  1. Structural Biology Brussels, Vrije Universiteit Brussel, VUB, Brussels, Belgium

    Tomasz Uchański, Baptiste Fischer, Valentina Kalichuk, Alexandre Wohlkönig, Thomas Zögg, Han Remaut, Wim Vranken, Els Pardon & Jan Steyaert

  2. VIB-VUB Center for Structural Biology, VIB, Brussels, Belgium

    Tomasz Uchański, Baptiste Fischer, Valentina Kalichuk, Alexandre Wohlkönig, Thomas Zögg, Han Remaut, Wim Vranken, Els Pardon & Jan Steyaert

  3. MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK

    Simonas Masiulis, Andrija Sente & A. Radu Aricescu

  4. CNRS, Université Grenoble Alpes, CEA, Institut de Biologie Structurale, Grenoble, France

    Uriel López-Sánchez, Eleftherios Zarkadas & Hugues Nury

  5. Rosalind Franklin Institute, Rutherford Appleton Laboratory, Didcot, UK

    Miriam Weckener & James H. Naismith

  6. Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

    Philip Ward, James H. Naismith & A. Radu Aricescu

  7. Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium

    Wim Vranken

Authors
  1. Tomasz Uchański
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Simonas Masiulis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Baptiste Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Valentina Kalichuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Uriel López-Sánchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Eleftherios Zarkadas
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Miriam Weckener
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Andrija Sente
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Philip Ward
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Alexandre Wohlkönig
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Thomas Zögg
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Han Remaut
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. James H. Naismith
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Hugues Nury
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Wim Vranken
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. A. Radu Aricescu
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Els Pardon
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Jan Steyaert
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.P. and J.S. conceived the project. T.U. cloned, generated and produced megabodies, and performed binding kinetic measurements, yeast display selection and flow-cytometric analysis. T.U. crystallized, H.R. collected and B.F. processed X-ray diffraction data of \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{cHopQ}}}\). T.U. crystallized, B.F. collected and T.U. processed X-ray diffraction data for \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{c7HopQA12}}}\), \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{c7HopQG10}}}\) and \({\mathrm{Mb}}_{{\mathrm{Nb207}}}^{{\mathrm{cYgjKNO}}}\). V.K. performed TSA and SAXS experiments. S.M. produced β3 GABAA receptor. S.M. and T.U. collected and processed the electron microscopy data for β3 GABAA receptor. U.L.-S., E.Z. and H.N. produced, collected and processed the electron microscopy data for the 5-ΗΤ3Α receptor. M.W., A.S., P.W. and J.H.N. produced, collected and processed the electron microscopy data for WbaP. B.F. and A.W. purified SOS1 and KRAS. T.Z. purified FIXa. W.V. implemented the computational modeling. T.U., A.R.A. and J.S. wrote the manuscript. All authors participated in discussion and revision of the manuscript.

Corresponding authors

Correspondence to A. Radu Aricescu or Jan Steyaert.

Ethics declarations

Competing interests

V.I.B., V.U.B. and L.M.B. have filed patent applications on the megabody technology: WO2019/086548 (inventors: J.S., E.P., T.U. and W.V.) and EP19204412.1 (inventors: J.S., T.U., A.R.A. and S.M.).

Additional information

Peer review information Arunima Singh was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Supplementary information

Supplementary Information

Supplementary Figs. 1–27 and Tables 1–6.

Reporting Summary

Supplementary Video 1

Histamine binding mode in GABAA β3 homomeric receptor.

Supplementary Table 7

Supplementary Fig. 8.

Supplementary Table 8

Source Data Supplementary Fig. 9.

Supplementary Table 9

Source Data Supplementary Fig. 14.

Supplementary Table 10

Source Data Supplementary Fig. 17.

Supplementary Table 11

Source Data Supplementary Fig. 23.

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Uchański, T., Masiulis, S., Fischer, B. et al. Megabodies expand the nanobody toolkit for protein structure determination by single-particle cryo-EM. Nat Methods 18, 60–68 (2021). https://doi.org/10.1038/s41592-020-01001-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-020-01001-6

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research