Abstract
Resolution in optical nanoscopy (or super-resolution microscopy) depends on the localization uncertainty and density of single fluorescent labels and on the sample's spatial structure. Currently there is no integral, practical resolution measure that accounts for all factors. We introduce a measure based on Fourier ring correlation (FRC) that can be computed directly from an image. We demonstrate its validity and benefits on two-dimensional (2D) and 3D localization microscopy images of tubulin and actin filaments. Our FRC resolution method makes it possible to compare achieved resolutions in images taken with different nanoscopy methods, to optimize and rank different emitter localization and labeling strategies, to define a stopping criterion for data acquisition, to describe image anisotropy and heterogeneity, and even to estimate the average number of localizations per emitter. Our findings challenge the current focus on obtaining the best localization precision, showing instead how the best image resolution can be achieved as fast as possible.
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References
Hell, S.W. & Wichmann, J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion microscopy. Opt. Lett. 19, 780–782 (1994).
Hofmann, M., Eggeling, C., Jakobs, S. & Hell, S.W. Breaking the diffraction barrier in fluorescence microscopy at low light intensities by using reversibly photoswitchable proteins. Proc. Natl. Acad. Sci. USA 102, 17565–17569 (2005).
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).
Fölling, J. et al. Fluorescence nanoscopy by ground-state depletion and single-molecule return. Nat. Methods 5, 943–945 (2008).
Heilemann, M. et al. Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes. Angew. Chem. Int. Ed. Engl. 47, 6172–6176 (2008).
Lidke, K., Rieger, B., Jovin, T.M. & Heintzmann, R. Superresolution by localization of quantum dots using blinking statistics. Opt. Express 13, 7052–7062 (2005).
Dertinger, T., Colyer, R., Iyer, G., Weiss, S. & Enderlein, J. Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI). Proc. Natl. Acad. Sci. USA 106, 22287–22292 (2009).
Ram, S., Ward, E.S. & Ober, R.J. Beyond Rayleigh's criterion: a resolution measure with application to single-molecule microscopy. Proc. Natl. Acad. Sci. USA 103, 4457–4462 (2006).
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, 571–575 (2012).
Kanchanawong, P. et al. Nanoscale architecture of integrin-based cell adhesions. Nature 468, 580–584 (2010).
van de Linde, S., Wolter, S., Heilemann, M. & Sauer, M. The effect of photoswitching kinetics and labeling densities on super-resolution fluorescence imaging. J. Biotechnol. 149, 260–266 (2010).
Cordes, T. et al. Resolving single-molecule assembled patterns with superresolution blink-microscopy. Nano Lett. 10, 645–651 (2010).
Fitzgerald, J.E., Lu, J. & Schnitzer, M.J. Estimation theoretic measure of resolution for stochastic localization microscopy. Phys. Rev. Lett. 109, 048102 (2012).
Saxton, W.O. & Baumeister, W. The correlation averaging of a regularly arranged bacterial cell envelope protein. J. Microsc. 127, 127–138 (1982).
Van Heel, M. Similarity measures between images. Ultramicroscopy 21, 95–100 (1987).
Unser, M., Trus, B.L. & Steven, A.C. A new resolution criterion based on spectral signal-to-noise ratios. Ultramicroscopy 23, 39–51 (1987).
Beckmann, R. et al. Alignment of conduits for the nascent polypeptide chain in the ribosome-Sec61 complex. Science 278, 2123–2126 (1997).
Böttcher, B., Wynne, S.A. & Crowther, R.A. Determination of the fold of the core protein of hepatitis B virus by electron cryomicroscopy. Nature 386, 88–91 (1997).
Rosenthal, P.B. & Henderson, R. Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. J. Mol. Biol. 333, 721–745 (2003).
Barry, D.A. et al. Analytical approximations for real values of the Lambert W-function. Math. Comput. Simul. 53, 95–103 (2000).
Small, A.R. Theoretical limits on errors and acquisition rates in localizing switchable fluorophores. Biophys. J. 96, L16–L18 (2009).
Wolter, S. et al. rapidSTORM: accurate, fast open-source software for localization microscopy. Nat. Methods 9, 1040–1041 (2012).
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).
Mlodzianoski, M.J. et al. Sample drift correction in 3D fluorescence photoactivation localization microscopy. Opt. Express 19, 15009–15019 (2011).
Bates, M., Dempsey, G.T., Chen, K.H. & Zhuang, X. Multicolor super-resolution fluorescence imaging via multi-parameter fluorophore detection. ChemPhysChem 13, 99–107 (2012).
Lando, D. et al. Quantitative single-molecule microscopy reveals that CENP-A(Cnp1) deposition occurs during G2 in fission yeast. Open Biol. 2, 120078 (2012).
Sengupta, P. et al. Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis. Nat. Methods 8, 969–975 (2011).
Veatch, S.L. et al. Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting. PLoS ONE 7, e31457 (2012).
Annibale, P., Vanni, S., Scarselli, M., Rothlisberger, U. & Radenovic, A. Identification of clustering artifacts in photoactivated localization microscopy. Nat. Methods 8, 527–528 (2011).
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).
von Middendorff, C., Egner, A., Geisler, C., Hell, S.W. & Schönle, A. Isotropic 3D nanoscopy based on single emitter switching. Opt. Express 16, 20774–20788 (2008).
Toprak, E. et al. Defocused orientation and position imaging (DOPI) of myosin V. Proc. Natl. Acad. Sci. USA 103, 6495–6499 (2006).
Gustafsson, M.G.L. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J. Microsc. 198, 82–87 (2000).
Mukamel, E.A. & Schnitzer, M.J. Unifed resolution bounds for conventional and stochastic localization fluorescence microscopy. Phys. Rev. Lett. 109, 168102 (2012).
Hell, S.W. Towards fluorescence nanoscopy. Nat. Biotechnol. 21, 1347–1355 (2003).
Scheres, S.H. & Chen, S. Prevention of overfitting in cryo-EM structure determination. Nat. Methods 9, 853–854 (2012).
Huang, F., Schwartz, S.L., Byars, J.M. & Lidke, K.A. Simultaneous multiple-emitter fitting for single molecule super-resolution imaging. Biomed. Opt. Express 2, 1377–1393 (2011).
Holden, S.J., Uphoff, S. & Kapanidis, A.N. DAOSTORM: an algorithm for high-density super-resolution microscopy. Nat. Methods 8, 279–280 (2011).
Zhu, L., Zhang, W., Elnatan, D. & Huang, B. Faster STORM using compressed sensing. Nat. Methods 9, 721–723 (2012).
Tukey, J.W. An introduction to the calculations of numerical spectrum analysis. in Spectral Analysis of Time Series (ed. Harris, B.) 25–46 (Wiley, New York, 1967).
Cleveland, W.S. Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).
Wolter, S., Endesfelder, U., van de Linde, S., Heilemann, M. & Sauer, M. Measuring localization performance of super-resolution algorithms on very active samples. Opt. Express 19, 7020–7033 (2011).
Xu, K., Babcock, H.P. & Zhuang, X. Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton. Nat. Methods 9, 185–188 (2012).
Ghosh, R.N. & Webb, W.W. Automated detection and tracking of individual and clustered cell surface low density lipoprotein receptor molecules. Biophys. J. 66, 1301–1318 (1994).
Lee, G.M., Ishihara, A. & Jacobson, K.A. Direct observation of Brownian motion of lipids in a membrane. Proc. Natl. Acad. Sci. USA 88, 6274–6278 (1991).
Bates, M., Jones, S.A. & Zhuang, X. Stochastic optical reconstruction microscopy: a method for superresolution fluorescence imaging. in Imaging: A Laboratory Manual (ed. Yuste, R.) Ch. 35, 547–576 (Cold Spring Harbor Laboratory Press, 2011).
Hanser, B.M., Gustafsson, M.G., Agard, D.A. & Sedat, J.W. Phase-retrieved pupil functions in wide-field fluorescence microscopy. J. Microsc. 216, 32–48 (2004).
Acknowledgements
We thank K. Jalink for encouragement and support; S. Schwartz, F. Huang, J. Byars and S. Liu for assistance with experiments; and V. van Ravesteijn and P. Kruit for providing scanning electron microscope data. We appreciate the thoughtful comments of T. Young and L. van Vliet. R.P.J.N. and D.L.P. are supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Research (NWO) and which is partly funded by the Ministry of Economic Affairs, Agriculture and Innovation. K.A.L. was supported by US National Science Foundation CAREER Award #0954836 and US National Institutes of Health grant P50GM085273.
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R.P.J.N., S.S. and B.R. devised the conceptual framework and derived theoretical results. Simulations were done by R.P.J.N. Experimental data sets were acquired by R.P.J.N. (Fig. 2a–i), D.L.P. (Fig. 2j–n), K.A.L. (Figs. 2a–i and 4) and M.B. (Fig. 3). Data were analyzed by R.P.J.N., M.B., S.S. and B.R. D.G. provided research advice. The paper was written by R.P.J.N., D.G., S.S. and B.R.
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Supplementary Text and Figures
Supplementary Figures 1–16 and Supplementary Notes 1–7 (PDF 5383 kb)
Supplementary Software
Matlab code and ImageJ plugin to compute FRC resolution (ZIP 15962 kb)
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Nieuwenhuizen, R., Lidke, K., Bates, M. et al. Measuring image resolution in optical nanoscopy. Nat Methods 10, 557–562 (2013). https://doi.org/10.1038/nmeth.2448
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DOI: https://doi.org/10.1038/nmeth.2448