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A practical guide to optimization in X10 expansion microscopy

Nature Protocols volume 14, pages 832–863 (2019)Cite this article

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Abstract

Expansion microscopy is a relatively new approach to super-resolution imaging that uses expandable hydrogels to isotropically increase the physical distance between fluorophores in biological samples such as cell cultures or tissue slices. The classic gel recipe results in an expansion factor of ~4×, with a resolution of 60–80 nm. We have recently developed X10 microscopy, which uses a gel that achieves an expansion factor of ~10×, with a resolution of ~25 nm. Here, we provide a step-by-step protocol for X10 expansion microscopy. A typical experiment consists of seven sequential stages: (i) immunostaining, (ii) anchoring, (iii) polymerization, (iv) homogenization, (v) expansion, (vi) imaging, and (vii) validation. The protocol presented here includes recommendations for optimization, pitfalls and their solutions, and detailed guidelines that should increase reproducibility. Although our protocol focuses on X10 expansion microscopy, we detail which of these suggestions are also applicable to classic fourfold expansion microscopy. We exemplify our protocol using primary hippocampal neurons from rats, but our approach can be used with other primary cells or cultured cell lines of interest. This protocol will enable any researcher with basic experience in immunostainings and access to an epifluorescence microscope to perform super-resolution microscopy with X10. The procedure takes 3 d and requires ~5 h of actively handling the sample for labeling and expansion, and another ~3 h for imaging and analysis.

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Fig. 1: Outline and timing of the X10 expansion microscopy protocol.
Fig. 2: Anchoring and homogenization conditions can be optimized for the specific requirements of the sample and experiment.
Fig. 3: Assembly of a gelation chamber (Step 17).
Fig. 4: Removal of the gel from the gelation chamber and assembly of a digestion chamber (Step 22).
Fig. 5: Expansion of the homogenized sample (Steps 24 and 25).
Fig. 6: Assembly of an imaging chamber (Steps 26 and 27).
Fig. 7: Exemplary images of samples before and after expansion, and quantification of expansion factor and distortions.
Fig. 8: Expected results, exemplary images of samples before and after expansion.

Code availability

The code used and described in this paper is available as Supplementary Data 1. Additional advice on how to use it can be obtained from the authors upon reasonable request.

Data availability

All data shown in this paper are available from the authors upon reasonable request.

References

  1. Hell, S. W. & Wichmann, J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt. Lett. 19, 780–782 (1994).

    Article  CAS  Google Scholar 

  2. Klar, T. A. & Hell, S. W. Subdiffraction resolution in far-field fluorescence microscopy. Opt. Lett. 24, 954–956 (1999).

    Article  CAS  Google Scholar 

  3. Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).

    Article  CAS  Google Scholar 

  4. Rust, M. J., Bates, M. & Zhuang, X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793–795 (2006).

    Article  CAS  Google Scholar 

  5. Hess, S. T., Girirajan, T. P. K. & Mason, M. D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys. J. 91, 4258–4272 (2006).

    Article  CAS  Google Scholar 

  6. Heilemann, M. et al. Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes. Angew. Chem. Int. Ed. Engl. 47, 6172–6176 (2008).

    Article  CAS  Google Scholar 

  7. Fölling, J. et al. Fluorescence nanoscopy by ground-state depletion and single-molecule return. Nat. Methods 5, 943–945 (2008).

    Article  Google Scholar 

  8. Giannone, G. et al. Dynamic superresolution imaging of endogenous proteins on living cells at ultra-high density. Biophys. J. 99, 1303–1310 (2010).

    Article  CAS  Google Scholar 

  9. Jungmann, R. et al. Single-molecule kinetics and super-resolution microscopy by fluorescence imaging of transient binding on DNA origami. Nano Lett. 10, 4756–4761 (2010).

    Article  CAS  Google Scholar 

  10. Sharonov, A. & Hochstrasser, R. M. Wide-field subdiffraction imaging by accumulated binding of diffusing probes. Proc. Natl. Acad. Sci. USA 103, 18911–18916 (2006).

    Article  CAS  Google Scholar 

  11. Gustafsson, M. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J. Microsc. 198, 82–87 (2000).

    Article  CAS  Google Scholar 

  12. Gustafsson, M. Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. Proc. Natl. Acad. Sci. USA 102, 13081–13086 (2005).

    Article  CAS  Google Scholar 

  13. Fornasiero, E. F. & Opazo, F. Super-resolution imaging for cell biologists. Bioessays 37, 436–451 (2015).

    Article  Google Scholar 

  14. Saka, S. & Rizzoli, S. O. Super-resolution imaging prompts re-thinking of cell biology mechanisms: selected cases using stimulated emission depletion microscopy. Bioessays 34, 386–395 (2012).

    Article  Google Scholar 

  15. Baddeley, D. & Bewersdorf, J. Biological insight from super-resolution microscopy: what we can learn from localization-based images. Annu. Rev. Biochem. 87, 965–989 (2018).

  16. Schermelleh, L., Heintzmann, R. & Leonhardt, H. A guide to super-resolution fluorescence microscopy. J. Cell Biol. 190, 165–175 (2010).

    Article  CAS  Google Scholar 

  17. Dani, A., Huang, B., Bergan, J., Dulac, C. & Zhuang, X. Superresolution imaging of chemical synapses in the brain. Neuron 68, 843–856 (2010).

    Article  CAS  Google Scholar 

  18. Sahl, S. J., Hell, S. W. & Jakobs, S. Fluorescence nanoscopy in cell biology. Nat. Rev. Mol. Cell Biol. 18, 685–701 (2017).

    Article  CAS  Google Scholar 

  19. Xu, K., Zhong, G. & Zhuang, X. Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 339, 452–456 (2013).

    Article  CAS  Google Scholar 

  20. D’Este, E. et al. Subcortical cytoskeleton periodicity throughout the nervous system. Sci. Rep. 6, 22741 (2016).

    Article  Google Scholar 

  21. Sidenstein, S. C. et al. Multicolour multilevel STED nanoscopy of actin/spectrin organization at synapses. Sci. Rep. 6, 26725 (2016).

    Article  CAS  Google Scholar 

  22. Hoopmann, P. et al. Endosomal sorting of readily releasable synaptic vesicles. Proc. Natl. Acad. Sci. USA 107, 19055–19060 (2010).

    Article  CAS  Google Scholar 

  23. Westphal, V. et al. Video-rate far-field optical nanoscopy dissects synaptic vesicle movement. Science 320, 246–249 (2008).

    Article  CAS  Google Scholar 

  24. Willig, K. I., Rizzoli, S. O., Westphal, V., Jahn, R. & Hell, S. W. STED microscopy reveals that synaptotagmin remains clustered after synaptic vesicle exocytosis. Nature 440, 935–939 (2006).

    Article  CAS  Google Scholar 

  25. Chojnacki, J. et al. Maturation-dependent HIV-1 surface protein redistribution revealed by fluorescence nanoscopy. Science 338, 524–528 (2012).

    Article  CAS  Google Scholar 

  26. Kittel, R. J. et al. Bruchpilot promotes active zone assembly, Ca2+ channel clustering, and vesicle release. Science 312, 1051–1054 (2006).

    Article  CAS  Google Scholar 

  27. Böhme, M. A. et al. Active zone scaffolds differentially accumulate Unc13 isoforms to tune Ca2+ channel-vesicle coupling. Nat. Neurosci. 19, 1311–1320 (2016).

    Article  Google Scholar 

  28. Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015).

    Article  CAS  Google Scholar 

  29. Gao, R., Asano, S. M. & Boyden, E. S. Q&A: expansion microscopy. BMC Biol. 15, 50 (2017).

    Article  Google Scholar 

  30. Cho, I., Seo, J. Y. & Chang, J. Expansion microscopy. J. Microsc. 271, 123–128 (2018).

    Article  CAS  Google Scholar 

  31. Chang, J. B. et al. Iterative expansion microscopy. Nat. Methods 14, 593–599 (2017).

    Article  CAS  Google Scholar 

  32. Truckenbrodt, S. et al. X10 expansion microscopy enables 25 nm resolution on conventional microscopes. EMBO Rep. 19, e45836 (2018).

  33. Chozinski, T. J. et al. Expansion microscopy with conventional antibodies and fluorescent proteins. Nat. Methods 13, 485–488 (2016).

    Article  CAS  Google Scholar 

  34. Zhao, Y. et al. Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy. Nat. Biotechnol. 35, 757–764 (2017).

    Article  CAS  Google Scholar 

  35. Tillberg, P. W. et al. Protein-retention expansion microscopy of cells and tissues labeled using standard fluorescent proteins and antibodies. Nat. Biotechnol. 34, 987–992 (2016).

    Article  CAS  Google Scholar 

  36. Jiang, N. et al. Super-resolution imaging of Drosophila tissues using expansion microscopy. Mol. Biol. Cell 29, 1413–1421 (2018).

    Article  CAS  Google Scholar 

  37. Freifeld, L. et al. Expansion microscopy of zebrafish for neuroscience and developmental biology studies. Proc. Natl. Acad. Sci. USA 114, E10799–E10808 (2017).

  38. Cahoon, C. K. et al. Superresolution expansion microscopy reveals the three-dimensional organization of the Drosophila synaptonemal complex. Proc. Natl. Acad. Sci. USA 114, E6857–E6866 (2017).

  39. Cipriano, B. H. et al. Superabsorbent hydrogels that are robust and highly stretchable. Macromolecules 47, 4445–4452 (2014).

    Article  CAS  Google Scholar 

  40. Asano, S. M. et al. Expansion microscopy: protocols for imaging proteins and RNA in cells and tissues. Curr. Protoc. Cell Biol. 80, e56 (2018).

  41. Wang, G., Moffitt, J. R. & Zhuang, X. Multiplexed imaging of high-density libraries of RNAs with MERFISH and expansion microscopy. Sci. Rep. 8, 4847 (2018).

    Article  Google Scholar 

  42. Chen, F. et al. Nanoscale imaging of RNA with expansion microscopy. Nat. Methods 13, 679–684 (2016).

    Article  CAS  Google Scholar 

  43. Gao, R. et al. Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution. Science 363, eaau8302 (2019).

    Article  Google Scholar 

  44. Halpern, A. R., Alas, G. C. M., Chozinski, T. J., Paredez, A. R. & Vaughan, J. C. Hybrid structured illumination expansion microscopy reveals microbial cytoskeleton organization. ACS Nano 11, 12677–12686 (2017).

    Article  CAS  Google Scholar 

  45. Wang, Y. et al. Combined expansion microscopy with structured illumination microscopy for analyzing protein complexes. Nat. Protoc. 13, 1869–1895 (2018).

  46. Gao, M. et al. Expansion stimulated emission depletion microscopy (ExSTED). ACS Nano 12, 4178–4185 (2018).

    Article  CAS  Google Scholar 

  47. Gambarotto, D. et al. Imaging beyond the super-resolution limits using ultrastructure expansion microscopy (U-ExM). Nat. Methods 16, 71–74 (2019).

    Article  CAS  Google Scholar 

  48. Tong, Z. et al. Ex-STORM: expansion single molecule super-resolution microscopy. Preprint at https://www.biorxiv.org/content/10.1101/374140v1 (2016).

  49. Ku, T. et al. Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues. Nat. Biotechnol. 34, 973–981 (2016).

    Article  CAS  Google Scholar 

  50. Murakami, T. C. et al. A three-dimensional single-cell-resolution whole-brain atlas using CUBIC-X expansion microscopy and tissue clearing. Nat. Neurosci. 21, 625–637 (2018).

    Article  CAS  Google Scholar 

  51. Mikhaylova, M. et al. Resolving bundled microtubules using anti-tubulin nanobodies. Nat. Commun. 6, 7933 (2015).

    Article  CAS  Google Scholar 

  52. Maidorn, M., Rizzoli, S. O. & Opazo, F. Tools and limitations to study the molecular composition of synapses by fluorescence microscopy. Biochem. J. 473, 3385–3399 (2016).

    Article  CAS  Google Scholar 

  53. Ries, J., Kaplan, C., Platonova, E., Eghlidi, H. & Ewers, H. A simple, versatile method for GFP-based super-resolution microscopy via nanobodies. Nat. Methods 9, 582–584 (2012).

    Article  CAS  Google Scholar 

  54. Hell, S., Reiner, G., Cremer, C. & Stelzer, E. H. K. Aberrations in confocal fluorescence microscopy induced by mismatches in refractive index. J. Microsc. 169, 391–405 (1993).

    Article  Google Scholar 

  55. Wegel, E. et al. Imaging cellular structures in super-resolution with SIM, STED and localisation microscopy: a practical comparison. Sci. Rep. 6, 27290 (2016).

    Article  CAS  Google Scholar 

  56. Sahl, S. J. & Moerner, W. E. Super-resolution fluorescence imaging with single molecules. Curr. Opin. Struct. Biol. 623, 778–787 (2013).

    Article  Google Scholar 

  57. Hell, S. W. Far-field optical nanoscopy. Science 316, 1153–1158 (2007).

    Article  CAS  Google Scholar 

  58. Banker, G. A. & Cowan, W. M. Rat hippocampal neurons in dispersed cell culture. Brain Res. 126, 397–425 (1977).

    Article  CAS  Google Scholar 

  59. Kaech, S. & Banker, G. Culturing hippocampal neurons. Nat. Protoc. 1, 2406–2415 (2006).

    Article  CAS  Google Scholar 

  60. Truckenbrodt, S. et al. Newly produced synaptic vesicle proteins are preferentially used in synaptic transmission. EMBO J. 37, e98044 (2018).

  61. Bajorath, J., Hinrichs, W. & Saenger, W. The enzymatic activity of proteinase K is controlled by calcium. Eur. J. Biochem. 176, 441–447 (1988).

    Article  CAS  Google Scholar 

  62. Glynn, M. W. & McAllister, A. K. Immunocytochemistry and quantification of protein colocalization in cultured neurons. Nat. Protoc. 1, 1287–1296 (2006).

    Article  CAS  Google Scholar 

  63. Schneider Gasser, E. M. et al. Immunofluorescence in brain sections: simultaneous detection of presynaptic and postsynaptic proteins in identified neurons. Nat. Protoc. 1, 1887–1897 (2006).

    Article  CAS  Google Scholar 

  64. Richter, K. N. et al. Glyoxal as an alternative fixative to formaldehyde in immunostaining and super‐resolution microscopy. EMBO J. 37, 139–159 (2018).

  65. Laftah, W. A., Hashim, S. & Ibrahim, A. N. Polymer hydrogels: a review. Polym. Plast. Technol. Eng. 50, 1475–1486 (2011).

    Article  CAS  Google Scholar 

  66. Osada, Y., Gong, J. & Tanaka, Y. Polymer gels. J. Macromol. Sci. Part C Polym. Rev. 1, 339–366 (2012).

    Google Scholar 

  67. Zohuriaan-Mehr, M. J. & Kabiri, K. Superabsorbent polymer materials: a review. Iran. Polym. J. 17, 451–477 (2008).

    CAS  Google Scholar 

  68. Lee, W. & Wu, R. Superabsorbent polymeric materials. 1. Swelling behaviors of crosslinked poly(sodium acrylate-co-hydroxyethyl methacrylate) in aqueous salt solution. J. Appl. Polym. Sci. 62, 1099–1114 (1996).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank E. De Gaulejac and D. Lorenz for critically reading the manuscript. We thank S. Kabatas for helpful discussions. S.T. has received funding, as an ISTplus Fellow, from the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie grant agreement no. 754411. J.G.D. gratefully acknowledges funding by the Austrian Science Fund (FWF; I 3600-B27). This work was further supported by grants to S.O.R. from the European Research Council (ERC-2013-CoG NeuroMolAnatomy) and the Deutsche Forschungsgemeinschaft (DFG; SFB1286/Z03).

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Authors and Affiliations

  1. Institute of Neuro- and Sensory Physiology, University of Göttingen Medical Center, Göttingen, Germany

    Sven Truckenbrodt & Silvio O. Rizzoli

  2. Center for Biostructural Imaging of Neurodegeneration, University of Göttingen Medical Center, Göttingen, Germany

    Sven Truckenbrodt & Silvio O. Rizzoli

  3. Institute of Science and Technology Austria, Klosterneuburg, Austria

    Sven Truckenbrodt, Christoph Sommer & Johann G. Danzl

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Contributions

S.T., J.G.D., and S.O.R. prepared the manuscript. S.T. prepared the figures. S.T. performed the experiments and imaging. C.S. wrote the Python Anaconda scripts provided here for alignment of pre- and post-expansion images, expansion factor determination, and distortion analysis.

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Correspondence to Sven Truckenbrodt.

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Related link

Key reference using this protocol

Truckenbrodt, S. et al. EMBO Rep. 19, e45836 (2018): http://embor.embopress.org/content/early/2018/07/09/embr.201845836

Integrated supplementary information

Supplementary Figure 1 Measuring the expansion factor manually.

(a) The same images as shown in Fig. 7 for determining the expansion factor via the script provided with this manuscript are used here for manual determination of the expansion factor. 10 distance measurements were taken, using the respective tool in ImageJ, between landmark points that are easily identifiable in the pre- and post-expansion image. The lines for distance measurements were separately drawn manually in both images. Corresponding lines are numbered in both images. Scale bar: 20 µm. (b) Results of the same 10 manual distance measurements, together with the ratio of the measurement after expansion over the measurement before expansion. The average ratio is indicated below, and serves as the expansion factor for this image: 7.98. The manual measurement is consistent with the automatic measurement via the script (expansion factor: 8.0, see Fig. 7), but is considerably more time-consuming.

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1

Reporting Summary

Supplementary Data 1

Script for analyzing pre- and post-expansion images.

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Truckenbrodt, S., Sommer, C., Rizzoli, S.O. et al. A practical guide to optimization in X10 expansion microscopy. Nat Protoc 14, 832–863 (2019). https://doi.org/10.1038/s41596-018-0117-3

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