Tutorial: guidance for quantitative confocal microscopy

When used appropriately, a confocal fluorescence microscope is an excellent tool for making quantitative measurements in cells and tissues. The confocal microscope’s ability to block out-of-focus light and thereby perform optical sectioning through a specimen allows the researcher to quantify fluorescence with very high spatial precision. However, generating meaningful data using confocal microscopy requires careful planning and a thorough understanding of the technique. In this tutorial, the researcher is guided through all aspects of acquiring quantitative confocal microscopy images, including optimizing sample preparation for fixed and live cells, choosing the most suitable microscope for a given application and configuring the microscope parameters. Suggestions are offered for planning unbiased and rigorous confocal microscope experiments. Common pitfalls such as photobleaching and cross-talk are addressed, as well as several troubling instrumentation problems that may prevent the acquisition of quantitative data. Finally, guidelines for analyzing and presenting confocal images in a way that maintains the quantitative nature of the data are presented, and statistical analysis is discussed. A visual summary of this tutorial is available as a poster (https://doi.org/10.1038/s41596-020-0307-7).

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References

  1. Pawley, J. The 39 steps: a cautionary tale of quantitative 3-D fluorescence microscopy. Biotechniques28, 884–886 (2000). 888. ArticleCASPubMedGoogle Scholar
  2. North, A. J. Seeing is believing? A beginners’ guide to practical pitfalls in image acquisition. J. Cell Biol.172, 9–18 (2006). ArticleCASPubMedPubMed CentralGoogle Scholar
  3. Hell, S., Reiner, G., Cremer, C. & Stelzer, E. H. K. Aberrations in confocal fluorescence microscopy induced by mismatches in refractive index. J. Microsc.169, 391–405 (1993). ArticleGoogle Scholar
  4. Richardson, D. S. & Lichtman, J. W. Clarifying tissue clearing. Cell162, 246–257 (2015). ArticleCASPubMedPubMed CentralGoogle Scholar
  5. Allan, V. J. Basic immunofluorescence. in Protein Localization by Fluorescence Microscopy: A Practical Approach (ed. Allan, V. J.) 1–26 (Oxford University Press, 1999).
  6. McDonald, K. L., Morphew, M., Verkade, P. & Muller-Reichert, T. Recent advances in high-pressure freezing: equipment- and specimen-loading methods. Methods Mol. Biol.369, 143–173 (2007). ArticleCASPubMedGoogle Scholar
  7. North, A. J., Chidgey, M. A., Clarke, J. P., Bardsley, W. G. & Garrod, D. R. Distinct desmocollin isoforms occur in the same desmosomes and show reciprocally graded distributions in bovine nasal epidermis. Proc. Natl Acad. Sci. USA93, 7701–7705 (1996). ArticleCASPubMedPubMed CentralGoogle Scholar
  8. Burry, R. W. Immunocytochemistry: A Practical Guide for Biomedical Research (Springer, 2010).
  9. Park, Y. G. et al. Protection of tissue physicochemical properties using polyfunctional crosslinkers. Nat. Biotechnol.37, 73–83 (2019). ArticleCASGoogle Scholar
  10. Richter, K. N. et al. Glyoxal as an alternative fixative to formaldehyde in immunostaining and super-resolution microscopy. EMBO J.37, 139–159 (2018). ArticleCASPubMedGoogle Scholar
  11. Melan, M. A. & Sluder, G. Redistribution and differential extraction of soluble proteins in permeabilized cultured cells. Implications for immunofluorescence microscopy. J. Cell Sci.101(Pt 4), 731–743 (1992). ArticlePubMedGoogle Scholar
  12. Jamur, M. C. & Oliver, C. Permeabilization of cell membranes. Methods Mol. Biol.588, 63–66 (2010). ArticlePubMedGoogle Scholar
  13. Yan, Q. & Bruchez, M. P. Advances in chemical labeling of proteins in living cells. Cell Tissue Res.360, 179–194 (2015). ArticleCASPubMedPubMed CentralGoogle Scholar
  14. Ries, J., Kaplan, C., Platonova, E., Eghlidi, H. & Ewers, H. A simple, versatile method for GFP-based super-resolution microscopy via nanobodies. Nat. Methods9, 582–584 (2012). ArticleCASPubMedGoogle Scholar
  15. Dolman, N. J., Kilgore, J. A. & Davidson, M. W. A review of reagents for fluorescence microscopy of cellular compartments and structures, part I: BacMam labeling and reagents for vesicular structures. Curr. Protoc. Cytom.65, 12.30.1–12.30.27 (2013). Google Scholar
  16. Kilgore, J. A., Dolman, N. J. & Davidson, M. W. A review of reagents for fluorescence microscopy of cellular compartments and structures, Part II: reagents for non-vesicular organelles. Curr. Protoc. Cytom.66, 12.31.1–12.31.24 (2013). Google Scholar
  17. Bordeaux, J. et al. Antibody validation. Biotechniques48, 197–209 (2010). ArticleCASPubMedPubMed CentralGoogle Scholar
  18. Pauly, D. & Hanack, K. How to avoid pitfalls in antibody use. F1000Res4, 691 (2015). ArticlePubMedPubMed CentralGoogle Scholar
  19. Stadler, C. et al. Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy. J. Proteomics75, 2236–2251 (2012). ArticleCASPubMedGoogle Scholar
  20. Stack, R. F. et al. Quality assurance testing for modern optical imaging systems. Microsc. Microanal.17, 598–606 (2011). ArticleCASPubMedGoogle Scholar
  21. Cordes, T., Maiser, A., Steinhauer, C., Schermelleh, L. & Tinnefeld, P. Mechanisms and advancement of antifading agents for fluorescence microscopy and single-molecule spectroscopy. Phys. Chem. Chem. Phys.13, 6699–6709 (2011). ArticleCASPubMedGoogle Scholar
  22. Piterburg, M., Panet, H. & Weiss, A. Photoconversion of DAPI following UV or violet excitation can cause DAPI to fluoresce with blue or cyan excitation. J. Microsc.246, 89–95 (2012). ArticleCASPubMedGoogle Scholar
  23. Frigault, M. M., Lacoste, J., Swift, J. L. & Brown, C. M. Live-cell microscopy—tips and tools. J. Cell Sci.122, 753–767 (2009). ArticleCASPubMedGoogle Scholar
  24. Ettinger, A. & Wittmann, T. Fluorescence live cell imaging. Methods Cell Biol.123, 77–94 (2014). ArticlePubMedPubMed CentralGoogle Scholar
  25. Lambert, T. J. FPbase: a community-editable fluorescent protein database. Nat. Methods16, 277–278 (2019). ArticleCASPubMedGoogle Scholar
  26. Ai, H. W., Baird, M. A., Shen, Y., Davidson, M. W. & Campbell, R. E. Engineering and characterizing monomeric fluorescent proteins for live-cell imaging applications. Nat. Protoc.9, 910–928 (2014). ArticleCASPubMedGoogle Scholar
  27. Rodriguez, E. A. et al. The growing and glowing toolbox of fluorescent and photoactive proteins. Trends Biochem. Sci.42, 111–129 (2017). ArticleCASPubMedGoogle Scholar
  28. Cranfill, P. J. et al. Quantitative assessment of fluorescent proteins. Nat. Methods13, 557–562 (2016). ArticleCASPubMedPubMed CentralGoogle Scholar
  29. Bottanelli, F. et al. Two-colour live-cell nanoscale imaging of intracellular targets. Nat. Commun.7, 10778 (2016). ArticleCASPubMedPubMed CentralGoogle Scholar
  30. 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.e6 (2019). ArticleCASPubMedPubMed CentralGoogle Scholar
  31. Wang, L. et al. A general strategy to develop cell permeable and fluorogenic probes for multicolour nanoscopy. Nat. Chem.12, 165–172 (2019). ArticlePubMedCASGoogle Scholar
  32. Grimm, J. B., Brown, T. A., English, B. P., Lionnet, T. & Lavis, L. D. Synthesis of Janelia Fluor HaloTag and SNAP-Tag ligands and their use in cellular imaging experiments. Methods Mol. Biol.1663, 179–188 (2017). ArticleCASPubMedGoogle Scholar
  33. Ferrando-May, E. et al. Advanced light microscopy core facilities: balancing service, science and career. Microsc. Res. Tech.79, 463–479 (2016). ArticlePubMedPubMed CentralGoogle Scholar
  34. Kiepas, A., Voorand, E., Mubaid, F., Siegel, P. M. & Brown, C. M. Optimizing live-cell fluorescence imaging conditions to minimize phototoxicity. J. Cell Sci.133, jcs242834 (2020). ArticleCASPubMedGoogle Scholar
  35. Laissue, P. P., Alghamdi, R. A., Tomancak, P., Reynaud, E. G. & Shroff, H. Assessing phototoxicity in live fluorescence imaging. Nat. Methods14, 657 (2017). ArticleCASPubMedGoogle Scholar
  36. Jonkman, J. E., Swoger, J., Kress, H., Rohrbach, A. & Stelzer, E. H. Resolution in optical microscopy. Methods Enzymol.360, 416–446 (2003). ArticleCASPubMedGoogle Scholar
  37. Jacques, S. L. Optical properties of biological tissues: a review. Phys. Med. Biol.58, R37–R61 (2013). ArticlePubMedGoogle Scholar
  38. Bolte, S. & Cordelieres, F. P. A guided tour into subcellular colocalization analysis in light microscopy. J. Microsc.224, 213–232 (2006). ArticleCASPubMedGoogle Scholar
  39. Dunn, K. W., Kamocka, M. M. & McDonald, J. H. A practical guide to evaluating colocalization in biological microscopy. Am. J. Physiol. Cell Physiol.300, C723–C742 (2011). ArticleCASPubMedPubMed CentralGoogle Scholar
  40. Wallace, W., Schaefer, L. H. & Swedlow, J. R. A workingperson’s guide to deconvolution in light microscopy. Biotechniques31, 1076–1078 (2001). 1080, 1082 passim. ArticleCASPubMedGoogle Scholar
  41. Jonkman, J. & Brown, C. M. Any way you slice it—a comparison of confocal microscopy techniques. J. Biomol. Tech.26, 54–65 (2015). ArticlePubMedPubMed CentralGoogle Scholar
  42. Korobchevskaya, K., Lagerholm, B. C., Colin-York, H. & Fritzsche, M. Exploring the potential of Airyscan microscopy for live cell imaging. Photonics4, 41 (2017). ArticleCASGoogle Scholar
  43. Zipfel, W. R., Williams, R. M. & Webb, W. W. Nonlinear magic: multiphoton microscopy in the biosciences. Nat. Biotechnol.21, 1369–1377 (2003). ArticleCASPubMedGoogle Scholar
  44. Axelrod, D. Total internal reflection fluorescence microscopy in cell biology. Traffic2, 764–774 (2001). ArticleCASPubMedGoogle Scholar
  45. Power, R. M. & Huisken, J. A guide to light-sheet fluorescence microscopy for multiscale imaging. Nat. Methods14, 360–373 (2017). ArticleCASPubMedGoogle Scholar
  46. Strobl, F., Schmitz, A. & Stelzer, E. H. K. Improving your four-dimensional image: traveling through a decade of light-sheet-based fluorescence microscopy research. Nat. Protoc.12, 1103–1109 (2017). ArticleCASPubMedGoogle Scholar
  47. Sigal, Y. M., Zhou, R. & Zhuang, X. Visualizing and discovering cellular structures with super-resolution microscopy. Science361, 880–887 (2018). ArticleCASPubMedPubMed CentralGoogle Scholar
  48. Wu, Y. & Shroff, H. Faster, sharper, and deeper: structured illumination microscopy for biological imaging. Nat. Methods15, 1011–1019 (2018). ArticleCASPubMedGoogle Scholar
  49. Ishikawa-Ankerhold, H. C., Ankerhold, R. & Drummen, G. P. Advanced fluorescence microscopy techniques—FRAP, FLIP, FLAP, FRET and FLIM. Molecules17, 4047–4132 (2012). ArticleCASPubMedPubMed CentralGoogle Scholar
  50. Lippincott-Schwartz, J. & Patterson, G. H. Development and use of fluorescent protein markers in living cells. Science300, 87–91 (2003). ArticleCASPubMedGoogle Scholar
  51. Lippincott-Schwartz, J., Altan-Bonnet, N. & Patterson, G. H. Photobleaching and photoactivation: following protein dynamics in living cells. Nat. Cell Biol. Suppl, S7–S14 (2003).
  52. Elson, E. L. Fluorescence correlation spectroscopy: past, present, future. Biophys. J.101, 2855–2870 (2011). ArticleCASPubMedPubMed CentralGoogle Scholar
  53. Kim, S. A., Heinze, K. G. & Schwille, P. Fluorescence correlation spectroscopy in living cells. Nat. Methods4, 963–973 (2007). ArticleCASPubMedGoogle Scholar
  54. Brown, C. M. et al. Raster image correlation spectroscopy (RICS) for measuring fast protein dynamics and concentrations with a commercial laser scanning confocal microscope. J. Microsc.229, 78–91 (2008). ArticleCASPubMedPubMed CentralGoogle Scholar
  55. Sprague, B. L. & McNally, J. G. FRAP analysis of binding: proper and fitting. Trends Cell Biol.15, 84–91 (2005). ArticleCASPubMedGoogle Scholar
  56. Padilla-Parra, S. & Tramier, M. FRET microscopy in the living cell: different approaches, strengths and weaknesses. Bioessays34, 369–376 (2012). ArticlePubMedGoogle Scholar
  57. Broussard, J. A., Rappaz, B., Webb, D. J. & Brown, C. M. Fluorescence resonance energy transfer microscopy as demonstrated by measuring the activation of the serine/threonine kinase Akt. Nat. Protoc.8, 265–281 (2013). ArticleCASPubMedPubMed CentralGoogle Scholar
  58. Bacia, K. & Schwille, P. Practical guidelines for dual-color fluorescence cross-correlation spectroscopy. Nat. Protoc.2, 2842–2856 (2007). ArticleCASPubMedGoogle Scholar
  59. Krieger, J. W. et al. Imaging fluorescence (cross-) correlation spectroscopy in live cells and organisms. Nat. Protoc.10, 1948–1974 (2015). ArticleCASPubMedGoogle Scholar
  60. Soderberg, O. et al. Direct observation of individual endogenous protein complexes in situ by proximity ligation. Nat. Methods3, 995–1000 (2006). ArticlePubMedCASGoogle Scholar
  61. Holman, L., Head, M. L., Lanfear, R. & Jennions, M. D. Evidence of experimental bias in the life sciences: why we need blind data recording. PLoS Biol.13, e1002190 (2015). ArticlePubMedPubMed CentralCASGoogle Scholar
  62. Kaptchuk, T. J. The double-blind, randomized, placebo-controlled trial: gold standard or golden calf? J. Clin. Epidemiol.54, 541–549 (2001). ArticleCASPubMedGoogle Scholar
  63. Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep.7, 16878 (2017). ArticlePubMedPubMed CentralCASGoogle Scholar
  64. Komura, D. & Ishikawa, S. Machine learning methods for histopathological image analysis. Comput. Struct. Biotechnol. J.16, 34–42 (2018). ArticleCASPubMedPubMed CentralGoogle Scholar
  65. Robertson, S., Azizpour, H., Smith, K. & Hartman, J. Digital image analysis in breast pathology—from image processing techniques to artificial intelligence. Transl. Res.194, 19–35 (2018). ArticlePubMedGoogle Scholar
  66. Howard, V. & Reed, M. G. Unbiased Stereology: Three-Dimensional Measurement in Microscopy (Springer, 1998).
  67. Kipanyula, M. J. & Sife, A. S. Global trends in application of stereology as a quantitative tool in biomedical research. Biomed. Res. Int.2018, 1825697 (2018). ArticlePubMedPubMed CentralGoogle Scholar
  68. Jonkman, J. E. et al. An introduction to the wound healing assay using live-cell microscopy. Cell Adh. Migr.8, 440–451 (2014). ArticlePubMedPubMed CentralGoogle Scholar
  69. Zimmermann, T., Marrison, J., Hogg, K. & O’Toole, P. Clearing up the signal: spectral imaging and linear unmixing in fluorescence microscopy. Methods Mol. Biol.1075, 129–148 (2014). ArticlePubMedGoogle Scholar
  70. Jonkman, J., Brown, C. M. & Cole, R. W. Quantitative confocal microscopy: beyond a pretty picture. Methods Cell Biol.123, 113–134 (2014). ArticlePubMedGoogle Scholar
  71. Oreopoulos, J., Berman, R. & Browne, M. Chapter 9—Spinning-disk confocal microscopy: present technology and future trends. in Methods in Cell Biology: Quantitative Imaging in Cell Biology Vol. 123 (eds Waters, J. C. & Wittman, T.) 153–175 (Academic Press, 2014).
  72. Model, M. A. & Blank, J. L. Concentrated dyes as a source of two-dimensional fluorescent field for characterization of a confocal microscope. J. Microsc.229, 12–16 (2008). ArticleCASPubMedGoogle Scholar
  73. International Organization for Standardization. Microscopes—Confocal microscopes—Optical data of fluorescence confocal microscopes for biological imaging. ISO Standard No. 21073:2019 (2019).
  74. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods9, 676–682 (2012). ArticleCASPubMedGoogle Scholar
  75. Arena, E. T. et al. Quantitating the cell: turning images into numbers with ImageJ. Wiley Interdiscip. Rev. Dev. Biol.6, e260 (2017). ArticleGoogle Scholar
  76. Linkert, M. et al. Metadata matters: access to image data in the real world. J. Cell Biol.189, 777–782 (2010). ArticleCASPubMedPubMed CentralGoogle Scholar
  77. Arganda-Carreras, I. et al. Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification. Bioinformatics33, 2424–2426 (2017). ArticleCASPubMedGoogle Scholar
  78. Tinevez, J. Y. et al. TrackMate: an open and extensible platform for single-particle tracking. Methods115, 80–90 (2017). ArticleCASPubMedGoogle Scholar
  79. McQuin, C. et al. CellProfiler 3.0: next-generation image processing for biology. PLoS Biol.16, e2005970 (2018). ArticlePubMedPubMed CentralCASGoogle Scholar
  80. Bray, M. A. et al. Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. Nat. Protoc.11, 1757–1774 (2016). ArticleCASPubMedPubMed CentralGoogle Scholar
  81. Weigert, M. et al. Content-aware image restoration: pushing the limits of fluorescence microscopy. Nat. Methods15, 1090–1097 (2018). ArticleCASPubMedGoogle Scholar
  82. Belthangady, C. & Royer, L. A. Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction. Nat. Methods16, 1215–1225 (2019). ArticleCASPubMedGoogle Scholar
  83. Royer, L. A. et al. ClearVolume: open-source live 3D visualization for light-sheet microscopy. Nat. Methods12, 480–481 (2015). ArticleCASPubMedGoogle Scholar
  84. Cromey, D. W. Avoiding twisted pixels: ethical guidelines for the appropriate use and manipulation of scientific digital images. Sci. Eng. Ethics16, 639–667 (2010). ArticlePubMedPubMed CentralGoogle Scholar
  85. Cromey, D. W. Digital images are data: and should be treated as such. Methods Mol. Biol.931, 1–27 (2013). CASPubMedPubMed CentralGoogle Scholar
  86. Goodwin, P. C. Quantitative deconvolution microscopy. Methods Cell Biol.123, 177–192 (2014). ArticlePubMedGoogle Scholar
  87. Allan, C. et al. OMERO: flexible, model-driven data management for experimental biology. Nat. Methods9, 245–253 (2012). ArticleCASPubMedPubMed CentralGoogle Scholar
  88. Ellenberg, J. et al. A call for public archives for biological image data. Nat. Methods15, 849–854 (2018). ArticleCASPubMedPubMed CentralGoogle Scholar
  89. Fay, D. S. & Gerow, K. A biologist’s guide to statistical thinking and analysis. WormBook Jul 9, 1–54 (2013).
  90. Vaux, D. L. Basic statistics in cell biology. Annu. Rev. Cell Dev. Biol.30, 23–37 (2014). ArticleCASPubMedGoogle Scholar
  91. Lacoste, J., Young, K. & Brown, C. M. Live-cell migration and adhesion turnover assays. Methods Mol. Biol.931, 61–84 (2013). ArticleCASPubMedGoogle Scholar
  92. Krzywinski, M. & Altman, N. Visualizing samples with box plots. Nat. Methods11, 119–120 (2014). ArticleCASPubMedGoogle Scholar
  93. Krzywinski, M. & Altman, N. Significance, P values and t-tests. Nat. Methods10, 1041–1042 (2013). ArticleCASPubMedGoogle Scholar
  94. Wasserstein, R. L., Schirm, A. L. & Lazar, N. A. Moving to a world beyond “p< 0.05”. Am. Stat.73, 1–19 (2019). ArticleGoogle Scholar
  95. Hibbs, A. R., MacDonald, G. & Garsha, K. Chapter 36: Practical confocal microscopy. in Handbook of Biological Confocal Microscopy 3rd edn (ed. Pawley, J. B.) (Springer, 2006).
  96. Wang, H., Lacoche, S., Huang, L., Xue, B. & Muthuswamy, S. K. Rotational motion during three-dimensional morphogenesis of mammary epithelial acini relates to laminin matrix assembly. Proc. Natl Acad. Sci. USA110, 163–168 (2013). ArticleCASPubMedGoogle Scholar
  97. Cole, R. W., Jinadasa, T. & Brown, C. M. Measuring and interpreting point spread functions to determine confocal microscope resolution and ensure quality control. Nat. Protoc.6, 1929–1941 (2011). ArticleCASPubMedGoogle Scholar

Acknowledgements

J.J. thanks the AOMF staff for helpful discussions, Courtney McIntosh for the images in Supplementary Fig. 1, and the Princess Margaret Foundation for ongoing financial support of the AOMF. G.D.W. thanks A*STAR and the National Research Foundation’s Shared Infrastructure Support Grant for continued support of the A*STAR Microscopy Platform and John Common for samples (Box 2). C.M.B. acknowledges Alex Kiepas (McGill University), who collected the adhesion dynamics data for the statistics section of the paper including Fig. 10, and the ABIF for general support and access to the Diskovery spinning disk TIRF microscope for collecting the adhesion dynamics data. K.I.A. thanks the Francis Crick Institute for their CALM support, and facility colleagues for helpful discussion. A.J.N. thanks the Rockefeller University for its continued support of the Frits and Rita Markus Bio-Imaging Resource Center (BIRC), the Sohn Conference Foundation for funding the Leica SP8 confocal microscope used to generate Figs. 3 and 4 and the facility staff and users for stimulating discussions.

Author information

Authors and Affiliations

  1. Advanced Optical Microscopy Facility (AOMF), University Health Network, Toronto, Ontario, Canada James Jonkman
  2. Advanced BioImaging Facility (ABIF), McGill University, Montreal, Quebec, Canada Claire M. Brown
  3. A*STAR Microscopy Platform (AMP), Skin Research Institute of Singapore, A*STAR, Singapore, Singapore Graham D. Wright
  4. Crick Advanced Light Microscopy Facility (CALM), The Francis Crick Institute, London, UK Kurt I. Anderson
  5. Bio-Imaging Resource Center, The Rockefeller University, New York, NY, USA Alison J. North
  1. James Jonkman