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Journal of Analysis and Testing

, Volume 2, Issue 3, pp 193–209 | Cite as

A Perspective on Data Processing in Super-resolution Fluorescence Microscopy Imaging

  • S. HugelierEmail author
  • M. Sliwa
  • C. Ruckebusch
Review
  • 115 Downloads

Abstract

With super-resolution microscopy, we attempt to visualize (biological) structures and processes at the sub-cellular level (i.e., nanoscale). To obtain this information, the samples are labeled with fluorophores that have a stochastic on/off switching of their emissions, which help to overcome the optical diffraction limit of around 250 nm, related to the use of optical microscopes. However, nowadays, research focuses on the imaging of live cells and thicker samples. These investigations require a high amount of simultaneously active fluorophores (i.e., high-density imaging) and are challenging due to the collapse of the single-molecule localization techniques and the increased background in the image. Therefore, recent efforts have shifted towards the development of new ways to process the data. This publication gives an introduction to wide-field super-resolution fluorescence microscopy, explaining the concepts of the technique, and then gives an overview of the recently developed methods to provide super-resolution images for high-density data of live cells and ways to overcome the issues related to the imaging of these samples.

Keywords

Super-resolution Fluorescence microscopy Nanoscopy Imaging 

Notes

Acknowledgements

C.R. and M.S acknowledge the financial support of the Agence National de la Recherche (ANR-14-CE08-0015-01 Ultrafast Nanoscopy).

References

  1. 1.
    Betzig E. Proposed method for molecular optical imaging. Opt Lett. 1995;20:237–9.CrossRefGoogle Scholar
  2. 2.
    Betzig E, et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science. 2006;313:1642–5.CrossRefGoogle Scholar
  3. 3.
    Hell S, Wichmann J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt Lett. 1994;19:780–2.CrossRefGoogle Scholar
  4. 4.
    Klar T, Jakobs S, Dyba M, Egner A, Hell S. Fluorescence microscopy with diffraction resolution barrier broken by stimulated emission. Proc Natl Acad Sci USA. 2000;97:8206–10.CrossRefGoogle Scholar
  5. 5.
    Moerner W, Kador L. Optical detection and spectroscopy of single molecules in a solid. Phys Rev Lett. 1989;62:2535–8.CrossRefGoogle Scholar
  6. 6.
    Dickson R, Cubitt A, Tsien R, Moerner W. On/off blinking and switching behaviour of single molecules of green fluorescent protein. Nature. 1997;388:355–8.CrossRefGoogle Scholar
  7. 7.
    Novotny L, Hecht B. Principles of nano-optics. 2nd ed. Cambridge: Cambridge University Press; 2012.CrossRefGoogle Scholar
  8. 8.
    Abbe E. Beiträge zur Theorie des Mikroskops und der mikroskopischen Wahrnehmung. Arch Für Mikrosk Anat. 1873;9:413–8.CrossRefGoogle Scholar
  9. 9.
    Strutt J. On the theory of optical images, with special reference to the microscope. Philos Mag. 1896;42:167–95.CrossRefGoogle Scholar
  10. 10.
    Huang B, Bates M, Zhuang X. Super resolution fluorescence microscopy. Annu Rev Biochem. 2009;78:993–1016.CrossRefGoogle Scholar
  11. 11.
    Shroff H, Galbraith C, Galbraith J, Betzig E. Live-cell photoactivated localization microscopy of nanoscale adhesion dynamics. Nat Methods. 2008;5:417–23.CrossRefGoogle Scholar
  12. 12.
    Hell S. Toward fluorescence nanoscopy. Nat Biotechnol. 2003;21:1347–55.CrossRefGoogle Scholar
  13. 13.
    Hell S. Far-field optical nanoscopy. Science. 2007;316:1153–8.CrossRefGoogle Scholar
  14. 14.
    Ovesný M, Křížek P, Borkovec J, Svindrych Z, Hagen G. ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging. Bioinf Oxf Engl. 2014;30:2389–90.CrossRefGoogle Scholar
  15. 15.
    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. 2009;106:22287–92.CrossRefGoogle Scholar
  16. 16.
    Holden S, Uphoff S, Kapanidis A. DAOSTORM: an algorithm for high- density super-resolution microscopy. Nat Methods. 2011;8:279–80.CrossRefGoogle Scholar
  17. 17.
    Ito S, et al. Restricted diffusion of guest molecules in polymer thin films on solid substrates as revealed by three-dimensional single-molecule tracking. Chem Commun Camb Engl. 2015;51:13756–9.CrossRefGoogle Scholar
  18. 18.
    Enderlein J. Positional and temporal accuracy of single molecule tracking. Single Mol. 2000;1:225–30.CrossRefGoogle Scholar
  19. 19.
    Kusumi A, Tsunoyama T, Hirosawa K, Kasai R, Fujiwara T. Tracking single molecules at work in living cells. Nat Chem Biol. 2014;10:524–32.CrossRefGoogle Scholar
  20. 20.
    Tsujita K, et al. Coordination between the actin cytoskeleton and membrane deformation by a novel membrane tubulation domain of PCH proteins is involved in endocytosis. J Cell Biol. 2006;172:269–79.CrossRefGoogle Scholar
  21. 21.
    Li D, et al. Extended-resolution structured illumination imaging of endocytic and cytoskeletal dynamics. Science. 2015;349:aab3500.CrossRefGoogle Scholar
  22. 22.
    Habuchi S, et al. Reversible single-molecule photoswitching in the GFP-like fluorescent protein Dronpa. Proc Natl Acad Sci USA. 2005;102:9511–6.CrossRefGoogle Scholar
  23. 23.
    Dedecker P, Mo G, Dertinger T, Zhang J. Widely accessible method for superresolution fluorescence imaging of living systems. Proc Natl Acad Sci USA. 2012;109:10909–14.CrossRefGoogle Scholar
  24. 24.
    Rust M, Bates M, Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat Methods. 2006;3:793–6.CrossRefGoogle Scholar
  25. 25.
    Betzig E, et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science. 2006;313:1642–5.CrossRefGoogle Scholar
  26. 26.
    Hess S, Girirajan T, Mason M. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys J. 2006;91:4258–72.CrossRefGoogle Scholar
  27. 27.
    Huang B, Bates M, Zhuang X. Super resolution fluorescence microscopy. Annu Rev Biochem. 2009;78:993–1016.CrossRefGoogle Scholar
  28. 28.
    Lin E, Alessio A. What are the basic concepts of temporal, contrast, and spatial resolution in cardiac CT? J Cardiovasc Comput Tomogr. 2009;3:403–8.CrossRefGoogle Scholar
  29. 29.
    Mondal P. Temporal resolution in fluorescence imaging. Front Mol Biosci. 2014;1:1–10.CrossRefGoogle Scholar
  30. 30.
    Zhu L, Zhang W, Elnatan D, Huang B. Faster STORM using compressed sensing. Nat Methods. 2012;9:721–3.CrossRefGoogle Scholar
  31. 31.
    Yamanaka M, Smith N, Fujita K. Introduction to super-resolution microscopy. Microsc Oxf Engl. 2014;63:177–92.CrossRefGoogle Scholar
  32. 32.
    Min J, et al. FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data. Sci Rep. 2014;4:srep04577.Google Scholar
  33. 33.
    Hugelier S, et al. Sparse deconvolution of high-density super-resolution images. Sci Rep. 2016;6:srep21413.CrossRefGoogle Scholar
  34. 34.
    Hugelier S, Eilers P, Devos O, Ruckebusch C. Improved superresolution microscopy imaging by sparse deconvolution with an interframe penalty. J Chemom. 2017;31:e2847.CrossRefGoogle Scholar
  35. 35.
    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. 2009;106:22287–92.CrossRefGoogle Scholar
  36. 36.
    Ruckebusch C, et al. Mapping pixel dissimilarity in wide-field super-resolution fluorescence microscopy. Anal Chem. 2015;87:4675–82.CrossRefGoogle Scholar
  37. 37.
    Cox S, et al. Bayesian localization microscopy reveals nanoscale podosome dynamics. Nat Methods. 2012;9:195–200.CrossRefGoogle Scholar
  38. 38.
    Rosten E, Jones G, Cox S. ImageJ plug-in for Bayesian analysis of blinking and bleaching. Nat Methods. 2013;10:97–8.CrossRefGoogle Scholar
  39. 39.
    Mukamel E, Babcock H, Zhuang X. Statistical deconvolution for superresolution fluorescence microscopy. Biophys J. 2012;102:2391–400.CrossRefGoogle Scholar
  40. 40.
    Ghiglia D, Romero L, Mastin G. Systematic approach to two-dimensional blind deconvolution by zero-sheet separation. J Opt Soc Am Part Opt Image Sci. 1993;10:1024–36.CrossRefGoogle Scholar
  41. 41.
    de Rooi J, Eilers P. Deconvolution of pulse trains with the L0 penalty. Anal Chim Acta. 2011;705:218–26.CrossRefGoogle Scholar
  42. 42.
    Candes E, Wakin M. An introduction to compressive sampling. IEEE Signal Process Mag. 2008;25:21–30.CrossRefGoogle Scholar
  43. 43.
    Candes E, Fernandez-Granda C. Towards a mathematical theory of super-resolution. Commun Pure Appl Math. 2014;67:906–56.CrossRefGoogle Scholar
  44. 44.
    Babcock H, Moffitt J, Cao Y, Zhuang X. Fast compressed sensing analysis for super-resolution imaging using L1-homotopy. Opt Express. 2013;21:28583–96.CrossRefGoogle Scholar
  45. 45.
    de Rooi J, Ruckebusch C, Eilers P. Sparse deconvolution in one and two dimensions: applications in endocrinology and single-molecule fluorescence imaging. Anal Chem. 2014;86:6291–8.CrossRefGoogle Scholar
  46. 46.
    Tikhonov A. Solution of incorrectly formulated problems and the regularization method. Sov Math. 1963;4:1035–8.Google Scholar
  47. 47.
    Dertinger T, Colyer R, Vogel R, Enderlein J, Weiss S. Achieving increased resolution and more pixels with superresolution optical fluctuation imaging (SOFI). Opt Express. 2010;18:18875–85.CrossRefGoogle Scholar
  48. 48.
    Dertinger T, Heilemann M, Vogel R, Sauer M, Weiss S. Superresolution optical fluctuation imaging with organic dyes. Angew Chem Int Ed Engl. 2010;49:9441–3.CrossRefGoogle Scholar
  49. 49.
    Girsault A, et al. SOFI simulation tool: a software package for simulating and testing super-resolution optical fluctuation imaging. PLoS One. 2016;11:e0161602.CrossRefGoogle Scholar
  50. 50.
    Dertinger T, Xu J, Naini O, Vogel R, Weiss S. SOFI-based 3D superresolution sectioning with a widefield microscope. Opt Nanoscopy. 2012;1:2.CrossRefGoogle Scholar
  51. 51.
    Sanchez F, Toft J, van den Bogaert B, Massart D. Orthogonal projection approach applied to peak purity assessment. Anal Chem. 1996;68:79–85.CrossRefGoogle Scholar
  52. 52.
    Sage D, et al. Quantitative evaluation of software packages for single-molecule localization microscopy. Nat Methods. 2015;12:717–24.CrossRefGoogle Scholar
  53. 53.
    Hoogendoorn E, et al. The fidelity of stochastic single-molecule super-resolution reconstructions critically depends upon robust background estimation. Sci Rep. 2014;4:srep03854.Google Scholar
  54. 54.
    de Rooi J, Devos O, Sliwa M, Ruckebusch C, Eilers P. Mixture models for two-dimensional baseline correction, applied to artifact elimination in time-resolved spectroscopy. Anal Chim Acta. 2013;771:7–13.CrossRefGoogle Scholar
  55. 55.
    Currie I, Durban M, Eilers P. Generalized linear array models with applications to multidimensional smoothing. J R Stat Soc Ser B Stat Methodol. 2006;68:259–80.CrossRefGoogle Scholar
  56. 56.
    Wolter S, et al. RapidSTORM: accurate, fast open-source software for localization microscopy. Nat Methods. 2012;9:1040–1.CrossRefGoogle Scholar
  57. 57.
    Berglund A. Nonexponential statistics of fluorescence photobleaching. J Chem Phys. 2004;121:2899–903.CrossRefGoogle Scholar
  58. 58.
    Hirschfeld T. Quantum efficiency independence of the time integrated emission from a fluorescent molecule. Appl Opt. 1976;15:3135–9.CrossRefGoogle Scholar
  59. 59.
    Wells K, Sandison D, Strickler J, Webb W. Quantitative fluorescence imaging with laser scanning confocal microscopy. In: Pawley J, editor. The handbook for biological confocal microscopy. Wisconsin: IMR Press; 1989. p. 27–39.Google Scholar
  60. 60.
    Peeters Y, et al. Correcting for photodestruction in super-resolution optical fluctuation imaging. Sci Rep. 2017;7:srep10470.CrossRefGoogle Scholar
  61. 61.
    Vicente N, Diaz Zamboni J, Adur J, Paravani E, Casco V. Photobleaching correction in fluorescence microscopy images. J Phys: Conf Ser. 2007;90:012068.Google Scholar
  62. 62.
    Geissbuehler S, et al. Live-cell multiplane three-dimensional super-resolution optical fluctuation imaging. Nat Comm. 2014;5:5830.CrossRefGoogle Scholar
  63. 63.
    Deschout H, et al. Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions. Nat Comm. 2016;7:13693.CrossRefGoogle Scholar
  64. 64.
    Barsic A, Grover G, Piestun R. Three-dimensional super-resolution and localization of dense clusters of single molecules. Sci Reports. 2014;4:srep5388.CrossRefGoogle Scholar
  65. 65.
    Nehme E, Weiss L, Michaeli T, Shechtman Y. Deep-STORM: super-resolution single-molecule microscopy by deep learning. Optica. 2018;5:458–64.CrossRefGoogle Scholar
  66. 66.
    Niehörster T, et al. Multi-target spectrally resolved fluorescence lifetime imaging microscopy. Nat Methods. 2015;13:257–65.CrossRefGoogle Scholar

Copyright information

© The Nonferrous Metals Society of China 2018

Authors and Affiliations

  1. 1.Université de Lille, LASIR CNRSVilleneuve d’Ascq CedexFrance

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