Histochemistry and Cell Biology

, Volume 141, Issue 6, pp 629–638 | Cite as

A simple method to estimate the average localization precision of a single-molecule localization microscopy experiment

  • Ulrike Endesfelder
  • Sebastian Malkusch
  • Franziska Fricke
  • Mike Heilemann
Original Paper


The localization precision is a crucial and important parameter for single-molecule localization microscopy (SMLM) and directly influences the achievable spatial resolution. It primarily depends on experimental imaging conditions and the registration potency of the algorithm used. We propose a new and simple routine to estimate the average experimental localization precision in SMLM, based on the nearest neighbor analysis. By exploring different experimental and simulated targets, we show that this approach can be generally used for any 2D or 3D SMLM data and that reliable values for the localization precision σ SMLM are obtained. Knowing σ SMLM is a prerequisite for consistent visualization or any quantitative structural analysis, e.g., cluster analysis or colocalization studies.


Single-molecule localization microscopy Fluorescence microscopy Resolution Localization precision Single-molecule fluorescence 



We thank Steve Wolter for helpful discussions. We acknowledge funding by the German Ministry of Education and Research (Grants 0315262 and 0316170D) and the cluster of excellence “Macromolecular Complexes” (CEF, DFG cluster of excellence (EXC 115)).

Supplementary material

418_2014_1192_MOESM1_ESM.docx (2.4 mb)
Supplementary material (DOCX 2453 kb) (764 kb)
Supplementary software package (ZIP 763 kb)


  1. Banterle N, Bui KH et al (2013) Fourier ring correlation as a resolution criterion for super-resolution microscopy. J Struct Biol 183(3):363–367PubMedCrossRefGoogle Scholar
  2. Betzig E, Patterson GH et al (2006) Imaging intracellular fluorescent proteins at nanometer resolution. Science 313:1642–1645PubMedCrossRefGoogle Scholar
  3. Bobroff N (1986) Position measurement with a resolution and noise-limited instrument. Rev Sci Instrum 57(6):1152–1157CrossRefGoogle Scholar
  4. Cheezum MK, Walker WF et al (2001) Quantitative comparison of algorithms for tracking single fluorescent particles. Biophys J 81(4):2378–2388PubMedCentralPubMedCrossRefGoogle Scholar
  5. Churchman LS, Flyvbjerg H et al (2006) A non-Gaussian distribution quantifies distances measured with fluorescence localization techniques. Biophys J 90(2):668–671PubMedCentralPubMedCrossRefGoogle Scholar
  6. DeSantis MC, DeCenzo SH et al (2010) Precision analysis for standard deviation measurements of immobile single fluorescent molecule images. Opt Express 18(7):6563–6576PubMedCentralPubMedCrossRefGoogle Scholar
  7. Deschout H, Neyts K et al (2012) The influence of movement on the localization precision of sub-resolution particles in fluorescence microscopy. J Biophotonics 5(1):97–109PubMedCrossRefGoogle Scholar
  8. Endesfelder U, van de Linde S et al (2010) Subdiffraction-resolution fluorescence microscopy of myosin-actin motility. ChemPhysChem 11(4):836–840PubMedCrossRefGoogle Scholar
  9. Endesfelder U, Malkusch S et al (2011) Chemically induced photoswitching of fluorescent probes—a general concept for super-resolution microscopy. Molecules 16(4):3106–3118PubMedCrossRefGoogle Scholar
  10. Fitzgerald JE, Lu J et al (2012) Estimation theoretic measure of resolution for stochastic localization microscopy. Phys Rev Lett 109(4):048102PubMedCentralPubMedCrossRefGoogle Scholar
  11. Heilemann M, van de Linde S et al (2008) Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes. Angew Chem Int Ed 47(33):6172–6176CrossRefGoogle Scholar
  12. Huang B, Wang W et al (2008) Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319(5864):810–813PubMedCentralPubMedCrossRefGoogle Scholar
  13. Jia H, Yang J et al (2010) Minimum variance unbiased subpixel centroid estimation of point image limited by photon shot noise. J Opt Soc Am A Opt Image Sci Vis 27(9):2038–2045PubMedCrossRefGoogle Scholar
  14. Kubitscheck U, Kuckmann O et al (2000) Imaging and tracking of single GFP molecules in solution. Biophys J 78(4):2170–2179PubMedCentralPubMedCrossRefGoogle Scholar
  15. Lando D, Endesfelder U et al (2012) Quantitative single-molecule microscopy reveals that CENP-A(Cnp1) deposition occurs during G2 in fission yeast. Open Biol 2(7):120078PubMedCentralPubMedCrossRefGoogle Scholar
  16. Loschberger A, van de Linde S et al (2012) 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(Pt 3):570–575PubMedCrossRefGoogle Scholar
  17. Moerner WE, Kador L (1989) Optical detection and spectroscopy of single molecules in a solid. Phys Rev Lett 62(21):2535–2538PubMedCrossRefGoogle Scholar
  18. Mortensen KI, Churchman LS et al (2010) Optimized localization analysis for single-molecule tracking and super-resolution microscopy. Nat Methods 7(5):377–381PubMedCentralPubMedCrossRefGoogle Scholar
  19. Mukamel EA, Schnitzer MJ (2012) Unified resolution bounds for conventional and stochastic localization fluorescence microscopy. Phys Rev Lett 109(16):168102PubMedCentralPubMedCrossRefGoogle Scholar
  20. Muranyi W, Malkusch S et al (2013) Super-resolution microscopy reveals specific recruitment of HIV-1 envelope proteins to viral assembly sites dependent on the envelope C-terminal tail. PLoS Pathog 9(2):e1003198PubMedCentralPubMedCrossRefGoogle Scholar
  21. Nieuwenhuizen RPJ, Lidke KA et al (2013) Measuring image resolution in optical nanoscopy. Nat Methods 10(6):557PubMedCrossRefGoogle Scholar
  22. Ober RJ, Ram S et al (2004) Localization accuracy in single-molecule microscopy. Biophys J 86(2):1185–1200PubMedCentralPubMedCrossRefGoogle Scholar
  23. Oliphant TE (2007) Python for scientific computing. Comput Sci Eng 9(3):10–20CrossRefGoogle Scholar
  24. Olivier N, Keller D et al (2013) Resolution doubling in 3D-STORM imaging through improved buffers. PLoS ONE 8(7):e69004PubMedCentralPubMedCrossRefGoogle Scholar
  25. Orrit M, Bernard J (1990) Single pentacene molecules detected by fluorescence excitation in a p-terphenyl crystal. Phys Rev Lett 65(21):2716–2719PubMedCrossRefGoogle Scholar
  26. Ram S, Ward ES et al (2006) Beyond Rayleigh’s criterion: a resolution measure with application to single-molecule microscopy. Proc Natl Acad Sci USA 103(12):4457–4462PubMedCentralPubMedCrossRefGoogle Scholar
  27. Rust MJ, Bates M et al (2006) Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat Methods 3(10):793–795PubMedCentralPubMedCrossRefGoogle Scholar
  28. Schindelin J, Arganda-Carreras I et al (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9(7):676–682PubMedCrossRefGoogle Scholar
  29. Shannon CE (1949) Communication in the presence of noise. Proc Inst Radio Eng 37(1):10–21Google Scholar
  30. Small AR (2009) Theoretical limits on errors and acquisition rates in localizing switchable fluorophores. Biophys J 96(2):L16–L18PubMedCentralPubMedCrossRefGoogle Scholar
  31. Steinhauer C, Jungmann R et al (2009) DNA origami as a nanoscopic ruler for super-resolution microscopy. Angew Chem Int Ed 48(47):8870–8873CrossRefGoogle Scholar
  32. Thompson RE, Larson DR et al (2002) Precise nanometer localization analysis for individual fluorescent probes. Biophys J 82:2775–2783PubMedCentralPubMedCrossRefGoogle Scholar
  33. Truan Z, Tarancon Diez L et al (2013) Quantitative morphological analysis of arrestin2 clustering upon G protein-coupled receptor stimulation by super-resolution microscopy. J Struct Biol 184(2):329–334PubMedCrossRefGoogle Scholar
  34. Vaughan JC, Jia S et al (2012) Ultrabright photoactivatable fluorophores created by reductive caging. Nat Methods 9(12):1181–1184PubMedCentralPubMedCrossRefGoogle Scholar
  35. Vaughan JC, Dempsey GT et al (2013) Phosphine quenching of cyanine dyes as a versatile tool for fluorescence microscopy. J Am Chem Soc 135(4):1197–1200PubMedCentralPubMedCrossRefGoogle Scholar
  36. Wolter S, Schuttpelz M et al (2010) Real-time computation of subdiffraction-resolution fluorescence images. J Microsc 237(1):12–22PubMedCrossRefGoogle Scholar
  37. Wolter S, Endesfelder U et al (2011) Measuring localization performance of super-resolution algorithms on very active samples. Opt Express 19(8):7020–7033PubMedCrossRefGoogle Scholar
  38. Yau W, Zhiping L et al (2011) Limit of the accuracy of parameter estimation for moving single molecules imaged by fluorescence microscopy. Signal Process IEEE Trans 59(3):895–911CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Institute of Physical and Theoretical ChemistryJohann Wolfgang Goethe University Frankfurt am MainFrankfurt am MainGermany

Personalised recommendations