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Reconstitution and real-time quantification of membrane remodeling by single proteins and protein complexes


Cellular membrane processes, from signal transduction to membrane fusion and fission, depend on acute membrane deformations produced by small and short-lived protein complexes working in conditions far from equilibrium. Real-time monitoring and quantitative assessment of such deformations are challenging; hence, mechanistic analyses of the protein action are commonly based on ensemble averaging, which masks important mechanistic details of the action. In this protocol, we describe how to reconstruct and quantify membrane remodeling by individual proteins and small protein complexes in vitro, using an ultra-short (80- to 400-nm) lipid nanotube (usNT) template. We use the luminal conductance of the usNT as the real-time reporter of the protein interaction(s) with the usNT. We explain how to make and calibrate the usNT template to achieve subnanometer precision in the geometrical assessment of the molecular footprints on the nanotube membrane. We next demonstrate how membrane deformations driven by purified proteins implicated in cellular membrane remodeling can be analyzed at a single-molecule level. The preparation of one usNT takes ~1 h, and the shortest procedure yielding the basic geometrical parameters of a small protein complex takes 10 h.

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Fig. 1: Main geometric and electrical parameters of usNT.
Fig. 2: Experimental setup for usNT production and the protein delivery system.
Fig. 3: Step-by-step procedure for the preparation of the experimental chamber.
Fig. 4: The nonlinear current–voltage (I/U) characteristics of the usNT lumen.
Fig. 5: Box plot of the bending rigidity moduli (k) obtained by the procedure described in Box 2.
Fig. 6: Signal-to-noise ratio in the usNT conductance measurements.
Fig. 7: Representative examples of the usNT conductance behaviors in different experimental conditions.
Fig. 8: Representative examples of elementary constriction events produced by individual protein species.
Fig. 9: Bending rigidity of the usNT membrane with bound proteins.
Fig. 10: Self-limited character of membrane deformations produced by Dyn1 in the presence of GTP.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request. The source data underlying Figs. 5, 7b, 8d, 9 and 10 are provided as Source Data files.


  1. 1.

    Groves, J. T. Bending mechanics and molecular organization in biological membranes. Annu. Rev. Phys. Chem. 58, 697–717 (2007).

    CAS  PubMed  Google Scholar 

  2. 2.

    Bassereau, P. et al. The 2018 biomembrane curvature and remodeling roadmap. J. Phys. D. Appl. Phys. 51, 343001 (2018).

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Roux, A. et al. Membrane curvature controls dynamin polymerization. Proc. Natl Acad. Sci. USA 107, 4141–4146 (2010).

    CAS  PubMed  Google Scholar 

  4. 4.

    Pinot, M., Goud, B. & Manneville, J.-B. Physical aspects of COPI vesicle formation. Mol. Membr. Biol. 27, 428–442 (2010).

    CAS  PubMed  Google Scholar 

  5. 5.

    Capraro, B. R. et al. Kinetics of endophilin N-BAR domain dimerization and membrane interactions. J. Biol. Chem. 288, 12533–12543 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Shnyrova, A. V., Frolov, V. A. & Zimmerberg, J. Domain-driven morphogenesis of cellular membranes. Curr. Biol. 19, R772–R780 (2009).

  7. 7.

    Groves, J. T. & Kuriyan, J. Molecular mechanisms in signal transduction at the membrane. Nat. Struct. Mol. Biol. 17, 659–665 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Zimmerberg, J. & Kozlov, M. M. How proteins produce cellular membrane curvature. Nat. Rev. Mol. Cell Biol. 7, 9–19 (2006).

    CAS  PubMed  Google Scholar 

  9. 9.

    McMahon, H. T. & Gallop, J. L. Membrane curvature and mechanisms of dynamic cell membrane remodelling. Nature 438, 590–596 (2005).

    CAS  PubMed  Google Scholar 

  10. 10.

    Zhu, C., Das, S. L. & Baumgart, T. Nonlinear sorting, curvature generation, and crowding of endophilin N-BAR on tubular membranes. Biophys. J. 102, 1837–1845 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Callan-Jones, A., Sorre, B. & Bassereau, P. Curvature-driven lipid sorting in biomembranes. Cold Spring Harb. Perspect. Biol. 3, 1–14 (2011).

    Google Scholar 

  12. 12.

    Hsieh, W. T. et al. Curvature sorting of peripheral proteins on solid-supported wavy membranes. Langmuir 28, 12838–12843 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Antonny, B. et al. Membrane fission by dynamin: what we know and what we need to know. EMBO J. 35, 2270–2284 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Jia, H. & Schwille, P. Bottom-up synthetic biology: reconstitution in space and time. Curr. Opin. Biotechnol. 60, 179–187 (2019).

    CAS  PubMed  Google Scholar 

  15. 15.

    Liu, A. P. & Fletcher, D. A. Biology under construction: in vitro reconstitution of cellular function. Nat. Rev. Mol. Cell Biol. 10, 644–650 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Huang, S.-C. J. et al. Formation, stability, and mobility of one-dimensional lipid bilayers on polysilicon nanowires. Nano Lett. 7, 3355–3359 (2007).

    CAS  PubMed  Google Scholar 

  17. 17.

    Zhou, X., Moran-Mirabal, J. M., Craighead, H. G. & McEuen, P. L. Supported lipid bilayer/carbon nanotube hybrids. Nat. Nanotechnol. 2, 185–190 (2007).

    CAS  PubMed  Google Scholar 

  18. 18.

    Artyukhin, A. B. et al. Functional one-dimensional lipid bilayers on carbon nanotube templates. J. Am. Chem. Soc. 127, 7538–7542 (2005).

    CAS  PubMed  Google Scholar 

  19. 19.

    Li, X. et al. A nanostructure platform for live-cell manipulation of membrane curvature. Nat. Protoc. 14, 1772–1802 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Shi, Z. & Baumgart, T. Dynamics and instabilities of lipid bilayer membrane shapes. Adv. Colloid Interface Sci. 208, 76–88 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Shnyrova, A. V. et al. Geometric catalysis of membrane fission driven by flexible dynamin rings. Science 339, 1433–1436 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Harmandaris, V. A. & Deserno, M. A novel method for measuring the bending rigidity of model lipid membranes by simulating tethers. J. Chem. Phys. 125, 204905 (2006).

  23. 23.

    Fang, Y., Rand, R. P., Leikin, S. & Kozlov, M. M. Chain-melting reentrant transition in bimolecular layers at large separations. Phys. Rev. Lett. 70, 3623–3626 (1993).

    CAS  PubMed  Google Scholar 

  24. 24.

    Frolov, V. A., Lizunov, V. A., Dunina-Barkovskaya, A. Y., Samsonov, A. V. & Zimmerberg, J. Shape bistability of a membrane neck: a toggle switch to control vesicle content release. Proc. Natl Acad. Sci. USA 100, 8698–8703 (2003).

    CAS  PubMed  Google Scholar 

  25. 25.

    Houghtaling, J. et al. Estimation of shape, volume, and dipole moment of individual proteins freely transiting a synthetic nanopore. ACS Nano 13, 5231–5242 (2019).

    CAS  PubMed  Google Scholar 

  26. 26.

    Bashkirov, P. V. et al. GTPase cycle of dynamin is coupled to membrane squeeze and release, leading to spontaneous fission. Cell 135, 1276–1286 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Roux, A. The physics of membrane tubes: soft templates for studying cellular membranes. Soft Matter 9, 6726–6736 (2013).

    CAS  Google Scholar 

  28. 28.

    Simunovic, M., Prévost, C., Andrew, C. J. & Bassereau, P. Physical basis of some membrane shaping mechanisms. Philos. Trans. R. Soc. Lond. A 374, 20160034 (2016).

  29. 29.

    Rosenboom, H. & Lindau, M. Exo-endocytosis and closing of the fission pore during endocytosis in single pituitary nerve terminals internally perfused with high calcium concentrations. Proc. Natl Acad. Sci. 91, 5267–5271 (1994).

    CAS  PubMed  Google Scholar 

  30. 30.

    Debus, K. & Lindau, M. Resolution of patch capacitance recordings and of fusion pore conductances in small vesicles. Biophys. J. 78, 2983–2997 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Velasco-Olmo, A., Ormaetxea Gisasola, J., Martinez Galvez, J. M., Vera Lillo, J. & Shnyrova, A. V. Combining patch-clamping and fluorescence microscopy for quantitative reconstitution of cellular membrane processes with giant suspended bilayers. Sci. Rep. 9, 7255 (2019).

  32. 32.

    Bashkirov, P. V., Chekashkina, K. V., Akimov, S. A., Kuzmin, P. I. & Frolov, V. A. Variation of lipid membrane composition caused by strong bending. Biochem. Mosc. Suppl. Ser. A 5, 205–211 (2011).

    Google Scholar 

  33. 33.

    Bashkirov, P. V. Membrane nanotubes in the electric field as a model for measurement of mechanical parameters of the lipid bilayer. Biochem. Mosc. Suppl. Ser. A 1, 176–184 (2007).

    Google Scholar 

  34. 34.

    Chappie, J. S. et al. A pseudoatomic model of the dynamin polymer identifies a hydrolysis-dependent powerstroke. Cell 147, 209–222 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Stowell, M. H. B., Marks, B., Wigge, P. & McMahon, H. T. Nucleotide-dependent conformational changes in dynamin: evidence for a mechanochemical molecular spring. Nat. Cell Biol. 1, 27–32 (1999).

    CAS  PubMed  Google Scholar 

  36. 36.

    Ando, T. High-speed atomic force microscopy and its future prospects. Biophys. Rev. 10, 285–292 (2018).

    CAS  PubMed  Google Scholar 

  37. 37.

    Colom, A., Redondo-Morata, L., Chiaruttini, N., Roux, A. & Scheuring, S. Dynamic remodeling of the dynamin helix during membrane constriction. Proc. Natl Acad. Sci. USA 114, 5449–5454 (2017).

    CAS  PubMed  Google Scholar 

  38. 38.

    Takeda, T. et al. Dynamic clustering of dynamin-amphiphysin helices regulates membrane constriction and fission coupled with GTP hydrolysis. Elife 7, e30246 (2018).

  39. 39.

    Vicidomini, G., Bianchini, P. & Diaspro, A. STED super-resolved microscopy. Nat. Methods 15, 173–182 (2018).

    CAS  PubMed  Google Scholar 

  40. 40.

    Dar, S., Kamerkar, S. C. & Pucadyil, T. J. A high-throughput platform for real-time analysis of membrane fission reactions reveals the mechanism of dynamin function. Nat. Cell Biol. 17, 1588–1596 (2015).

  41. 41.

    Madsen, K. L., Bhatia, V. K., Gether, U. & Stamou, D. BAR domains, amphipathic helices and membrane-anchored proteins use the same mechanism to sense membrane curvature. FEBS Lett. 584, 1848–1855 (2010).

    CAS  PubMed  Google Scholar 

  42. 42.

    Espadas, J. et al. Dynamic constriction and fission of endoplasmic reticulum membranes by reticulon. Nat. Commun. 10, 5327 (2019).

    PubMed  PubMed Central  Google Scholar 

  43. 43.

    Simunovic, M. et al. Friction nediates scission of tubular membranes scaffolded by BAR proteins. Cell 170, 172–184.e11 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Schmid, S. L. & Frolov, V. A. Dynamin: functional design of a membrane fission catalyst. Annu. Rev. Cell Dev. Biol. 27, 79–105 (2011).

    CAS  PubMed  Google Scholar 

  45. 45.

    Ferguson, S. M. & De Camilli, P. Dynamin, a membrane-remodelling GTPase. Nat. Rev. Mol. Cell Biol. 13, 75–88 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Mattila, J. P. et al. A hemi-fission intermediate links two mechanistically distinct stages of membrane fission. Nature 524, 109–113 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Capraro, B. R., Yoon, Y., Cho, W. & Baumgart, T. Curvature sensing by the epsin N-terminal homology domain measured on cylindrical lipid membrane tethers. J. Am. Chem. Soc. 132, 1200–1201 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Tunuguntla, R. H., Escalada, A., A Frolov, V. & Noy, A. Synthesis, lipid membrane incorporation, and ion permeability testing of carbon nanotube porins. Nat. Protoc. 11, 2029–2047 (2016).

    CAS  PubMed  Google Scholar 

  49. 49.

    Kong, L. et al. Cryo-EM of the dynamin polymer assembled on lipid membrane. Nature 560, 258–262 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Gracià, R. S., Bezlyepkina, N., Knorr, R. L., Lipowsky, R. & Dimova, R. Effect of cholesterol on the rigidity of saturated and unsaturated membranes: fluctuation and electrodeformation analysis of giant vesicles. Soft Matter 6, 1472–1482 (2010).

    Google Scholar 

  51. 51.

    Pan, J., Mills, T. T., Tristram-Nagle, S. & Nagle, J. F. Cholesterol perturbs lipid bilayers nonuniversally. Phys. Rev. Lett. 100, 198103 (2008).

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This work was partially supported by NIH R01GM121725 to V.A.F.; Spanish Ministry of Science, Innovation and Universities and FEDER grant BFU2015-70552-P to V.A.F. and A.V.S.; Russian Science Foundation grant 17-75-30064 to P.V.B.; and the Fundación Biofísica Bizkaia and the Basque Excellence Research Centre (BERC) program of the Basque Government and the Ministry of Science and Higher Education of the Russian Federation.

Author information




Conceptualization, V.A.F., P.V.B., A.V.S.; methodology, V.A.F., P.V.B.; investigation, K.C., P.A., J.V.L., P.V.B.; theoretical analysis, V.A.F., P.I.K., P.V.B.; writing of original draft, V.A.F., P.V.B., A.V.S.; review and editing, all authors; funding acquisition, V.A.F., P.V.B., A.V.S.; resources, V.A.F., P.V.B., A.V.S.; supervision, V.A.F., P.V.B., A.V.S.

Corresponding authors

Correspondence to Pavel V. Bashkirov or Vadim A. Frolov.

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The authors declare no competing interests.

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Peer review information Nature Protocols thanks Patricia Bassereau and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key references using this protocol

Frolov, V. A. et al. Proc. Natl Acad. Sci. USA 100, 8698–8703 (2003):

Bashkirov, P. V. et al. Cell 135, 1276–1286 (2008):

Shnyrova, A. V. et al. Science. 339, 1433–1436 (2013):

Mattila, J.-P. et al. Nature 524, 109–113 (2015):

Supplementary information

Source data

Source Data Fig. 5

Statistical source data.

Source Data Fig. 7

Source data (two columns x and y axes).

Source Data Fig. 8

Source data (two columns x and y axes).

Source Data Fig. 9

Statistical source data (two columns for gray and black histograms).

Source Data Fig. 10

Statistical source data (for the histograms in Fig. 10a and b).

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Bashkirov, P.V., Kuzmin, P.I., Chekashkina, K. et al. Reconstitution and real-time quantification of membrane remodeling by single proteins and protein complexes. Nat Protoc 15, 2443–2469 (2020).

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