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Measuring image resolution in optical nanoscopy

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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Figure 1: The FRC principle and trade-off between localization uncertainty and labeling density.
Figure 2: The effect of localization density and data processing on resolution.
Figure 3: Spurious correlations from a two-color localization microscopy image.
Figure 4: 3D resolution.

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References

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

    Article  CAS  Google Scholar 

  2. 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).

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

    Article  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. Lidke, K., Rieger, B., Jovin, T.M. & Heintzmann, R. Superresolution by localization of quantum dots using blinking statistics. Opt. Express 13, 7052–7062 (2005).

    Article  Google Scholar 

  8. 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).

    Article  CAS  Google Scholar 

  9. 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).

    Article  CAS  Google Scholar 

  10. 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).

    Article  Google Scholar 

  11. Kanchanawong, P. et al. Nanoscale architecture of integrin-based cell adhesions. Nature 468, 580–584 (2010).

    Article  CAS  Google Scholar 

  12. 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).

    Article  CAS  Google Scholar 

  13. Cordes, T. et al. Resolving single-molecule assembled patterns with superresolution blink-microscopy. Nano Lett. 10, 645–651 (2010).

    Article  CAS  Google Scholar 

  14. Fitzgerald, J.E., Lu, J. & Schnitzer, M.J. Estimation theoretic measure of resolution for stochastic localization microscopy. Phys. Rev. Lett. 109, 048102 (2012).

    Article  Google Scholar 

  15. Saxton, W.O. & Baumeister, W. The correlation averaging of a regularly arranged bacterial cell envelope protein. J. Microsc. 127, 127–138 (1982).

    Article  CAS  Google Scholar 

  16. Van Heel, M. Similarity measures between images. Ultramicroscopy 21, 95–100 (1987).

    Article  Google Scholar 

  17. Unser, M., Trus, B.L. & Steven, A.C. A new resolution criterion based on spectral signal-to-noise ratios. Ultramicroscopy 23, 39–51 (1987).

    Article  CAS  Google Scholar 

  18. Beckmann, R. et al. Alignment of conduits for the nascent polypeptide chain in the ribosome-Sec61 complex. Science 278, 2123–2126 (1997).

    Article  CAS  Google Scholar 

  19. 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).

    Article  Google Scholar 

  20. 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).

    Article  CAS  Google Scholar 

  21. Barry, D.A. et al. Analytical approximations for real values of the Lambert W-function. Math. Comput. Simul. 53, 95–103 (2000).

    Article  Google Scholar 

  22. Small, A.R. Theoretical limits on errors and acquisition rates in localizing switchable fluorophores. Biophys. J. 96, L16–L18 (2009).

    Article  CAS  Google Scholar 

  23. Wolter, S. et al. rapidSTORM: accurate, fast open-source software for localization microscopy. Nat. Methods 9, 1040–1041 (2012).

    Article  CAS  Google Scholar 

  24. 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).

    Article  CAS  Google Scholar 

  25. Mlodzianoski, M.J. et al. Sample drift correction in 3D fluorescence photoactivation localization microscopy. Opt. Express 19, 15009–15019 (2011).

    Article  Google Scholar 

  26. 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).

    Article  CAS  Google Scholar 

  27. 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).

    Article  Google Scholar 

  28. Sengupta, P. et al. Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis. Nat. Methods 8, 969–975 (2011).

    Article  CAS  Google Scholar 

  29. Veatch, S.L. et al. Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting. PLoS ONE 7, e31457 (2012).

    Article  CAS  Google Scholar 

  30. Annibale, P., Vanni, S., Scarselli, M., Rothlisberger, U. & Radenovic, A. Identification of clustering artifacts in photoactivated localization microscopy. Nat. Methods 8, 527–528 (2011).

    Article  CAS  Google Scholar 

  31. 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).

    Article  CAS  Google Scholar 

  32. 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).

    Article  Google Scholar 

  33. Toprak, E. et al. Defocused orientation and position imaging (DOPI) of myosin V. Proc. Natl. Acad. Sci. USA 103, 6495–6499 (2006).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  35. Mukamel, E.A. & Schnitzer, M.J. Unifed resolution bounds for conventional and stochastic localization fluorescence microscopy. Phys. Rev. Lett. 109, 168102 (2012).

    Article  Google Scholar 

  36. Hell, S.W. Towards fluorescence nanoscopy. Nat. Biotechnol. 21, 1347–1355 (2003).

    Article  CAS  Google Scholar 

  37. Scheres, S.H. & Chen, S. Prevention of overfitting in cryo-EM structure determination. Nat. Methods 9, 853–854 (2012).

    Article  CAS  Google Scholar 

  38. 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).

    Article  Google Scholar 

  39. Holden, S.J., Uphoff, S. & Kapanidis, A.N. DAOSTORM: an algorithm for high-density super-resolution microscopy. Nat. Methods 8, 279–280 (2011).

    Article  CAS  Google Scholar 

  40. Zhu, L., Zhang, W., Elnatan, D. & Huang, B. Faster STORM using compressed sensing. Nat. Methods 9, 721–723 (2012).

    Article  CAS  Google Scholar 

  41. 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).

  42. Cleveland, W.S. Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).

    Article  Google Scholar 

  43. 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).

    Article  Google Scholar 

  44. 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).

    Article  CAS  Google Scholar 

  45. 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).

    Article  CAS  Google Scholar 

  46. 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).

    Article  CAS  Google Scholar 

  47. 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).

  48. 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).

    Article  CAS  Google Scholar 

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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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Authors

Contributions

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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Correspondence to Sjoerd Stallinga or Bernd Rieger.

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The authors declare no competing financial interests.

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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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