Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions. Here, we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag, HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use (1) as three-dimensional resolution standards for calibration and quality control, (2) to quantify absolute labeling efficiencies and (3) as precise reference standards for molecular counting. These cell lines will enable the broader community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements.
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All processed data (lists of localizations) and for each condition at least one example file of raw data (camera frames of blinking fluorophores) are deposited on BioStudies (https://www.ebi.ac.uk/biostudies/BioImages/studies/S-BIAD8).
Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).
Rust, M. J., Bates, M. & Zhuang, X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793–795 (2006).
Xu, K., Zhong, G. & Zhuang, X. Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 339, 452–456 (2013).
Mund, M. et al. Systematic nanoscale analysis of endocytosis links efficient vesicle formation to patterned actin nucleation. Cell 174, 884–896.e17 (2018).
Szymborska, A. et al. Nuclear pore scaffold structure analyzed by super-resolution microscopy and particle averaging. Science 341, 655–658 (2013).
Ball, G. et al. SIMcheck: a toolbox for successful super-resolution structured illumination microscopy. Sci. Rep. 5, 15915 (2015).
Culley, S. et al. Quantitative mapping and minimization of super-resolution optical imaging artifacts. Nat. Methods 15, 263–266 (2018).
Sage, D. et al. Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software. Nat. Methods 16, 387–395 (2019).
Steinhauer, C., Jungmann, R., Sobey, T. L., Simmel, F. C. & Tinnefeld, P. DNA origami as a nanoscopic ruler for super-resolution microscopy. Angew. Chem. Int. Ed. 48, 8870–8873 (2009).
Iinuma, R. et al. Polyhedra self-assembled from DNA tripods and characterized with 3D DNA-PAINT. Science 344, 65–69 (2014).
Huang, B., Jones, S. A., Brandenburg, B. & Zhuang, X. Whole-cell 3D STORM reveals interactions between cellular structures with nanometer-scale resolution. Nat. Methods 5, 1047–1052 (2008).
Huang, B., Wang, W., Bates, M. & Zhuang, X. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008).
von Appen, A. et al. In situ structural analysis of the human nuclear pore complex. Nature 526, 140–143 (2015).
Durisic, N., Laparra-Cuervo, L., Sandoval Álvarez, Á., Borbely, J. S. & Lakadamyali, M. Single-molecule evaluation of fluorescent protein photoactivation efficiency using an in vivo nanotemplate. Nat. Methods 11, 156–162 (2014).
Zanacchi, F. C. et al. A DNA origami platform for quantifying protein copy number in super-resolution. Nat. Methods 14, 789–792 (2017).
Finan, K., Raulf, A. & Heilemann, M. A set of homo-oligomeric standards allows accurate protein counting. Angew. Chem. Int. Ed. 54, 12049–12052 (2015).
Zanacchi, F. C., Manzo, C., Magrassi, R., Derr, N. D. & Lakadamyali, M. Quantifying protein copy number in super-resolution using an imaging-invariant calibration. Biophys. J. 116, 2195–2203 (2019).
Löschberger, A. et al. Super-resolution imaging visualizes the eightfold symmetry of gp210 proteins around the nuclear pore complex and resolves the central channel with nanometer resolution. J. Cell Sci. 125, 570–575 (2012).
McEvoy, A. L. et al. mMaple: a photoconvertible fluorescent protein for use in multiple imaging modalities. PLoS ONE 7, e51314 (2012).
Keppler, A., Pick, H., Arrivoli, C., Vogel, H. & Johnsson, K. Labeling of fusion proteins with synthetic fluorophores in live cells. Proc. Natl Acad. Sci. USA 101, 9955–9959 (2004).
Los, G. V. et al. HaloTag: a novel protein labeling technology for cell imaging and protein analysis. ACS Chem. Biol. 3, 373–382 (2008).
Klar, T. A., Jakobs, S., Dyba, M., Egner, A. & Hell, S. W. Fluorescence microscopy with diffraction resolution barrier broken by stimulated emission. Proc. Natl Acad. Sci. USA 97, 8206–8210 (2000).
Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015).
Gustafsson, N. et al. Fast live-cell conventional fluorophore nanoscopy with ImageJ through super-resolution radial fluctuations. Nat. Commun. 7, 12471 (2016).
Pesce, L., Cozzolino, M., Lanzanò, L., Diaspro, A. & Bianchini, P. Measuring expansion from macro- to nanoscale using NPC as intrinsic reporter. J. Biophotonics 12, e201900018 (2019).
Gambarotto, D. et al. Imaging cellular ultrastructures using expansion microscopy (U-ExM). Nat. Methods 16, 71 (2019).
Demmerle, J., Wegel, E., Schermelleh, L. & Dobbie, I. M. Assessing resolution in super-resolution imaging. Methods 88, 3–10 (2015).
Nieuwenhuizen, R. P. J. et al. Measuring image resolution in optical nanoscopy. Nat. Methods 10, 557–562 (2013).
Schlichthaerle, T. et al. Direct visualization of single nuclear pore complex proteins using genetically-encoded probes for DNA-PAINT. Angew. Chem. Int. Ed. 58, 13004–13008 (2019).
Li, Y., Wu, Y.-L., Hoess, P., Mund, M. & Ries, J. Depth-dependent PSF calibration and aberration correction for 3D single-molecule localization. Biomed. Opt. Express 10, 2708–2718 (2019).
Fricke, F., Beaudouin, J., Eils, R. & Heilemann, M. One, two or three? Probing the stoichiometry of membrane proteins by single-molecule localization microscopy. Sci. Rep. 5, 14072 (2015).
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).
Grimm, J. B. et al. Bright photoactivatable fluorophores for single-molecule imaging. Nat. Methods 13, 985–988 (2016).
Dempsey, G. T., Vaughan, J. C., Chen, K. H., Bates, M. & Zhuang, X. Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging. Nat. Methods 8, 1027–1036 (2011).
Hartwich, T. M. et al. A stable, high refractive index, switching buffer for super-resolution imaging. Preprint at bioRxiv https://doi.org/10.1101/465492 (2018).
Klehs, K. et al. Increasing the brightness of cyanine fluorophores for single-molecule and superresolution imaging. Chem. Phys. Chem. 15, 637–641 (2014).
Ong, W. Q., Citron, Y. R., Schnitzbauer, J., Kamiyama, D. & Huang, B. Heavy water: a simple solution to increasing the brightness of fluorescent proteins in super-resolution imaging. Chem. Commun. 51, 13451–13453 (2015).
Ori, A. et al. Cell type‐specific nuclear pores: a case in point for context‐dependent stoichiometry of molecular machines. Mol. Syst. Biol. 9, 648–648 (2013).
Otsuka, S. et al. Nuclear pore assembly proceeds by an inside-out extrusion of the nuclear envelope. eLife 5, e19071 (2016).
Annibale, P., Vanni, S., Scarselli, M., Rothlisberger, U. & Radenovic, A. Quantitative photo activated localization microscopy: unraveling the effects of photoblinking. PLoS ONE 6, e22678 (2011).
Lee, S.-H., Shin, J. Y., Lee, A. & Bustamante, C. Counting single photoactivatable fluorescent molecules by photoactivated localization microscopy (PALM). Proc. Natl Acad. Sci. USA 109, 17436–17441 (2012).
Rollins, G. C., Shin, J. Y., Bustamante, C. & Pressé, S. Stochastic approach to the molecular counting problem in superresolution microscopy. Proc. Natl Acad. Sci. USA 112, E110–E118 (2014).
Puchner, E. M., Walter, J. M., Kasper, R., Huang, B. & Lim, W. A. Counting molecules in single organelles with superresolution microscopy allows tracking of the endosome maturation trajectory. Proc. Natl Acad. Sci. USA 110, 16015–16020 (2013).
Baldering, T. N. et al. Synthetic and genetic dimers as quantification ruler for single-molecule counting with PALM. Mol. Biol. Cell 30, 1369–1376 (2019).
Kim, S. J. et al. Integrative structure and functional anatomy of a nuclear pore complex. Nature 555, 475–482 (2018).
Rajoo, S., Vallotton, P., Onischenko, E. & Weis, K. Stoichiometry and compositional plasticity of the yeast nuclear pore complex revealed by quantitative fluorescence microscopy. Proc. Natl Acad. Sci. USA 115, E3969–E3977 (2018).
Wang, S., Moffitt, J. R., Dempsey, G. T., Xie, X. S. & Zhuang, X. Characterization and development of photoactivatable fluorescent proteins for single-molecule-based superresolution imaging. Proc. Natl Acad. Sci. USA 111, 8452–8457 (2014).
Beck, M., Lučić, V., Förster, F., Baumeister, W. & Medalia, O. Snapshots of nuclear pore complexes in action captured by cryo-electron tomography. Nature 449, 611–615 (2007).
Deschamps, J., Mund, M. & Ries, J. 3D superresolution microscopy by supercritical angle detection. Opt. Express 22, 29081–29091 (2014).
Erdmann, R. S. et al. Labeling strategies matter for super-resolution microscopy: a comparison between halotags and SNAP-tags. Cell Chem. Biol. 26, 584–592 (2019).
Pleiner, T. et al. Nanobodies: site-specific labeling for super-resolution imaging, rapid epitope-mapping and native protein complex isolation. eLife 4, e11349 (2015).
Göttfert, F. et al. Strong signal increase in STED fluorescence microscopy by imaging regions of subdiffraction extent. Proc. Natl Acad. Sci. USA 114, 2125–2130 (2017).
Heilemann, M., Margeat, E., Kasper, R., Sauer, M. & Tinnefeld, P. Carbocyanine dyes as efficient reversible single-molecule optical switch. J. Am. Chem. Soc. 127, 3801–3806 (2005).
Bates, M., Blosser, T. & Zhuang, X. Short-range spectroscopic ruler based on a single-molecule optical switch. Phys. Rev. Lett. 94, 108101 (2005).
Koch, B. et al. Generation and validation of homozygous fluorescent knock-in cells using CRISPR–Cas9 genome editing. Nat. Protoc. 13, 1465–1487 (2018).
Sun, X. et al. Development of SNAP-Tag fluorogenic probes for wash-free fluorescence imaging. Chem. Bio. Chem. 12, 2217–2226 (2011).
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).
Mund, M., Kaplan, C. & Ries, J. Localization microscopy in yeast. Meth. Cell Biol. 123, 253–271 (2014).
Khmelinskii, A., Meurer, M., Duishoev, N., Delhomme, N. & Knop, M. Seamless gene tagging by endonuclease-driven homologous recombination. PLoS ONE 6, e23794 (2011).
Deschamps, J., Rowald, A. & Ries, J. Efficient homogeneous illumination and optical sectioning for quantitative single-molecule localization microscopy. Opt. Express 24, 28080–28090 (2016).
Li, Y. et al. Real-time 3D single-molecule localization using experimental point spread functions. Nat. Methods 15, 367–369 (2018).
Smith, C. S., Joseph, N., Rieger, B. & Lidke, K. A. Fast, single-molecule localization that achieves theoretically minimum uncertainty. Nat. Methods 7, 373–375 (2010).
Mortensen, K. I., Churchman, L. S., Spudich, J. A. & Flyvbjerg, H. Optimized localization analysis for single-molecule tracking and super-resolution microscopy. Nat. Methods 7, 377–381 (2010).
J.V.T. and P.H. are candidates for joint PhD degrees from EMBL and Heidelberg University. PA-JF549 and Halo-Cy5 were a kind gift of L. Lavis, HHMI Janelia Research Campus. We thank the EMBL advanced light microscopy facility for their help. This work was supported by the European Research Council (grant no. ERC CoG-724489 to J.R., M.M., P.H. and J.V.T.), the National Institutes of Health Common Fund 4D Nucleome Program (grant no. U01 EB021223/U01 DA047728 to J.E. and J.R.), the Allen Distinguished Investigator Program through The Paul G. Allen Frontiers Group (J.E.), the UK Biotechnology and Biological Sciences Research Council (grant nos. BB/M022374/1, BB/P027431/1, BB/R000697/1 and BB/S507532/1 to R.H. and P.M.P.), the Wellcome Trust (203276/Z/16/Z, R.H. and P.M.P.), the EMBL Interdisciplinary Postdoc Programme (EIPOD) under Marie Curie Actions COFUND (Y.L.), the Human Frontier Science Program (RGY0065/2017 to J.R.) and the European Molecular Biology Laboratory (J.V.T., K.C., P.H., S.K.P., K.C.K., Y.L., Y.W., M.M., U.M., B.N., M.K., V.J.S., J.E. and J.R.). V.J.S. acknowledges support by the Boehringer Ingelheim Fonds.
The authors declare no competing interests.
Peer review information Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Integrated supplementary information
(a-d) Southern blots of (a) Nup96-SNAP, (b) Nup96-Halo, (c) Nup96-mMaple, (d) Nup96-mEGFP. Blots on the left were generated from probes against Nup96-C-term and blots on the right were generated from probes against respective tags. The presence of a single band was indicative of a homozygous knock-in (in red). (e) Western blot of the homozygous cell lines probed with an anti-Nup98 antibody. Reduction of band intensity in Nup96-WT indicates the specificity of the antibody to Nup96. siRNA concentrations used: 0.6 µg, 1.2 µg and 1.8 µg. Representative images of one (a-d) or two (e) independent experiments are shown. Full scans of all blots are shown in Supplementary Fig. 11.
Supplementary Figure 2 SMLM with total internal reflection fluorescence (TIRF) excitation on Nup96-SNAP-AF647.
In the majority of cells, the lower nuclear envelope is sufficiently close to the coverslip to be efficiently excited with TIRF. Representative images from two independent experiments are shown. Scale bars 1 µm.
(a) Logarithmic power spectrum for Fig. 1f–i. (b) Fourier Ring Correlation for Fig. 1m–q including resolution estimates. To calculate these curves, the localizations were divided into ten time windows, and the correlation was computed between even and odd time windows. A correction for spurious correlation due to re-activations was not applied. (c) Histogram of radii resulting from a ring fit to Fig. 1p. From the average measured radius <R> = 174 ± 25 nm and the known radius (Fig. 2) the expansion factor was estimated to be 3.2. Values depict mean ± SD.
Representative images from three independent experiments are shown. Scale bars 10 µm (upper panel) and 1 µm (lower panel).
(a) Nup96-SNAP-AF647. R = 53.7 ± 2.1 nm (N = 3, nC = 6 nNPC = 1856). (b) Nup96-Halo-Cy5. R = 54.5 ± 2.6 nm (N = 2, nC = 6 nNPC = 4959). (c) Nup96-mMaple. R = 55.4 ± 3.5 nm (N = 3, nC = 6 nNPC = 4276). (d) Nup96-GFP-Nanobody-Q-AF647. R = 55.0 ± 1.9 nm (N = 2, nC = 6 nNPC = 2913). (e) Nup96-GFP-Antibody-AF647. R = 64.3 ± 2.6 nm N = 2, nC = 6 nNPC = 3158). (f) Box plots of the radii for the different labels. Each data point corresponds to one cell. The center of the box plot shows the median, while lower and upper boundaries indicate the 25th and 75th percentiles, respectively. N denotes the number of biologically independent experiments, nC the number of imaged cells and nNPC the number of analyzed NPCs. Values show weighted mean ± SD, based on nNPC. Measurements were performed in GLOX/MEA blinking buffer (a,b,d,e) or 50 mM Tris in D2O (c).
Supplementary Figure 6 Depth induced aberrations lead to local deformations in z (related to Fig. 2j).
Distance between rings plotted vs the z-position a) before correction and b) after correction (N = 2, nC = 8, nNPC = 7234). Straight lines are the linear fit of the ring distance for each cell. Before correction these values are highly correlated (Pearson coefficient −0.27 ± 0.10), after correcting for the localization errors, the correlation is reduced (Pearson coefficient 0.04 ± 0.15). N denotes the number of biologically independent experiments, nC the number of imaged cells and nNPC the number of analyzed NPCs. Values depict mean ± SD.
Error in determining ELE (inferred ELE – true ELE) in dependence on (a) the brightness of the fluorophores, (b) the labeling efficiency, (c) the number of re-activations for bright (5000 photons) fluorophores and for (d) dim (500 photons) fluorophores and (e) in dependence on the number of nuclear pores analyzed. (f) Statistical accuracy (SEM) in determining the ELE in dependence on the number of nuclear pores. Unless otherwise indicated the simulation parameters were: labeling efficiency 0.5 (a,e,f) and 0.3 (c,d), number of photons = 5000, on average 1 re-activation, background 20 photons, 900 nuclear pores. Error bars denote mean ± SD.
ELE of Nup107-SNAP labeled with BG-AF647 and stored at 4 °C imaged (a) on the day of sample preparation, (b) two months after sample preparation and (c) two years after sample preparation. Representative images from one independent experiment are shown. Scale bars 1 µm.
Representative images of two (a-f,I,k,m,n,p), three (g,j,o,r), four (h), five (l) or six (q) independent experiments are shown. Scale bars 100 nm.
(a) Lanes 1 & 2: 2 different cell line clones under tetracycline (tet) induction. Lanes 3–7: clone no. 10 under tet induction for 4-0 days. Lane 8: blank. Lane 9: HEK293T wildtype. Lane 10: ladder. GAPDH is used as loading control. Clone 10 was used for all subsequent experiments and 2 days of tet induction was sufficient to knock down endogenous Nup107 and induce expressions of mMaple-Nup107. (b) Dose titration of tet concentration to induce mMaple-Nup107 expression. 10 ng/mL was sufficient to knock down endogenous Nup107 and induce expressions of mMaple-Nup107. Increasing tet concentration resulted in increasing expression of mMaple-Nup107. A tet concentration of 1 mg/mL was used for all subsequent experiments. (c) Recovery of endogenous expression of Nup107 after removal of tet from media. Expression of endogenous Nup107 can be observed after 1 day off tet induction with an increasing trend the longer tet is removed. The opposite trend is observed for expression levels of mMaple-Nup107. Representative images of one independent experiment are shown. Full scans of all blots are shown in Supplementary Fig. 12.
(a-e) Original Southern blots for U2OS cell line validation with the probes indicated above each blot. The clones chosen for all subsequent experiments are marked with a red asterisk. (f) Original Western blots for U2OS cell line validation decorated for Nup96 and GAPDH, respectively.
(a-c) Original Western blots for HEK293T cell validation and tetracycline titration decorated for Nup107 and GAPDH, respectively.
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Thevathasan, J.V., Kahnwald, M., Cieśliński, K. et al. Nuclear pores as versatile reference standards for quantitative superresolution microscopy. Nat Methods 16, 1045–1053 (2019). https://doi.org/10.1038/s41592-019-0574-9
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