Quantifying Colocalisation in Biological Fluorescence Microscopy

Martin Oheim, Université Paris Descartes, Paris, France
Maia Brunstein, Université Paris Descartes, Paris, France

Published online: November 2018

DOI: 10.1002/9780470015902.a0026800

Abstract

One of the basic concepts in biological fluorescence microscopy is the separation of photons from spectrally distinct fluorophores into different colour channels for studying questions concerning the colocalisation, coclustering or interaction of fluorescently labelled proteins, organelles or membranes on fluorescence images. The quantitative use of colocalisation information, however, is not without pitfalls, and the validity of arguments based on the comparison of dual‐colour fluorescence images depends on which molecular targets are labelled and how; which combinations of fluorophores, excitation wavelengths and filters are chosen; how images are acquired and at which spatiotemporal resolution and by which means they are analysed. Unfortunately, no consensual metrics for quantifying colocalisation has emerged. Interrogations as to how colocalisation is best quantified currently make surface again in the context of superresolution microscopies that are increasingly being used in the life sciences. We focus on the practice of the colocalisation imaging workflow and point out problematic steps, guiding the reader to make more informed statements beyond the common ‘red‐plus‐green‐equals‐yellow’ approach.

Key Concepts

  • Colocalisation measurements are only as good as the raw images they are calculated from – hence, the entire imaging workflow must be understood and quality controlled.
  • Molecules do not occupy the same place. They are, by definition, not ‘colocalised’. Their imperfect images overlap, and both their proximity and the available spatial resolution determine the amount of colocalisation.
  • More often than not, colocalisation will be partial, and therefore only interpretable with some reference or when compared among conditions.
  • Measures of colocalisation need to be held against the random colocalisation arising when structures are placed independently at the same density on an equivalent area.
  • Colocalisation measurements are more meaningful when presented along with positive and negative controls and when the fluctuation of colocalisation within subfields of view, or – for live cells – over time, is reported.
  • Fluorophore concentrations, acquisition parameters, intensity ranges and image processing and segmentation rules should be made explicit to allow comparison of data across experiments and laboratories.
  • Colocalisation studies must always be considered relative to the available spectral, spatial (and for live cells also temporal) resolution, which needs to be explicitly stated.

Keywords: colocalisation; correlation; image analysis; fluorescence microscopy; resolution; noise; background; segmentation; objects; ImageJ

Figure 1. Assessing colocalisation. (a) TIRF‐SIM superresolution image of mTOR (labelled with an antibody directed against mTOR, green) and lysosomal membrane (labelled with an antibody against LAMP‐1, red). Putative sites of colocalisation are shown in yellow pseudocolour. Scale bar, 5 µm. (b) Scattergram, that is pixel‐by‐pixel representation of the intensity in the green channel vs. intensity in the red channel of the image shown in panel a. (c) Van Steesel graph of the image pair shown in panel a, that is variation of Pearson's correlation coefficient (PCC) from upon introduction of a relative pixel shift Δx. The bell‐shaped curve centred on zero shift indicates a true colocalisation. Note the drop in PCC to nonzero values around 0.1.
Figure 2. Correlation‐ rather than intensity‐based thresholding. (a) Median intensity of the image shown in Figure a in which each pixel represents the median intensity of the eight neighbouring pixels. (b) Thresholded correlation‐amplitude map of the green and red channel in panel a. Scale bar, 5 µm.
close

References

Adler J and Parmryd I (2010) Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient. Cytometry. Part A : The Journal of the International Society for Analytical Cytology 77A: 733–742.

Adler J and Parmryd I (2014) Quantifying Colocalization: Thresholding, Void Voxels and the H coef. PLoS ONE 9: e111983.

Bacia K, Kim SA and Schwille P (2006) Fluorescence cross‐correlation spectroscopy in living cells. Nature Methods 3: 83–89.

Barlow AL, MacLeod A, Noppen S, Sanderson J and Guérin CJ (2010) Colocalization analysis in fluorescence micrographs: verification of a more accurate calculation of pearson's correlation coefficient. Microscopy and Microanalysis 16: 710–724.

Bolte S and Cordelières F (2006) A guided tour into subcellular colocalization analysis in light microscopy. Journal of Microscopy 224: 213–232.

Brunstein M and Oheim M (2016) Dependence of descriptors of co‐localization on microscope spatiotemporal resolution and the choice of regions of interest. Microscopy Research and Technique. DOI: 10.1002/jemt.22790. [Epub ahead of print].

Cognet L, Leduc C and Lounis B (2014) Advances in live‐cell single‐particle tracking and dynamic super‐resolution imaging. Current Opinion in Chemical Biology 20: 78–85.

Comeau JW, Costantino S and Wiseman PW (2006) A guide to accurate fluorescence microscopy colocalization measurements. Biophysical Journal 91: 4611–4622.

Cordelieres FP and Bolte S (2008)Proceedings of the 2nd ImageJ User and Developer Conference: 6–7.

Cordelieres FP and Bolte S (2014) Experimenters' guide to colocalization studies: finding a way through indicators and quantifiers, in practice. Methods in Cell Biology 123: 395–407.

Costes SV, Daelemans D, Cho EH, et al. (2004) Automatic and quantitative measurement of protein‐protein colocalization in live cells. Biophysical Journal 86: 3993–4003.

Deschout H, Zanacchi FC, Mlodzianoski M, et al. (2014) Precisely and accurately localizing single emitters in fluorescence microscopy. Nature Methods 11: 253–266.

Dunn KW, Kamocka MM and McDonald JH (2011) A practical guide to evaluating colocalization in biological microscopy. American Journal of Physiology. Cell Physiology 300: C723–C742.

Gavrilovic M and Wählby C (2009) Quantification of colocalization and cross‐talk based on spectral angles. Journal of Microscopy 234: 311–324.

Haustein E and Schwille P (2003) Ultrasensitive investigations of biological systems by fluorescence correlation spectroscopy. Methods 29: 153–166.

Herce H, Casas‐Delucchi C and Cardoso MC (2013) New image colocalization coefficient for fluorescence microscopy to quantify (bio‐) molecular interactions. Journal of Microscopy 249: 184–194.

Hu C‐D and Kerppola TK (2003) Simultaneous visualization of multiple protein interactions in living cells using multicolor fluorescence complementation analysis. Nature Biotechnology 21: 539–545.

Kerppola TK (2008) Bimolecular fluorescence complementation (BiFC) analysis as a probe of protein interactions in living cells. Annual Review of Biophysics 37: 465–487.

Landmann L and Marbet P (2004) Colocalization analysis yields superior results after image restoration. Microscopy Research and Technique 64: 103–112.

Li Q, Lau A, Morris TJ, et al. (2004) A syntaxin 1, Gαo, and N‐type calcium channel complex at a presynaptic nerve terminal: analysis by quantitative immunocolocalization. Journal of Neuroscience 24: 4070–4081.

Li D, Hérault K, Silm K, et al. (2013) Lack of evidence for vesicular glutamate transporter expression in mouse astrocytes. Journal of Neuroscience 33: 4434–4455.

Manders E, Stap J, Brakenhoff G, Van Driel R and Aten J (1992) Dynamics of three‐dimensional replication patterns during the S‐phase, analysed by double labelling of DNA and confocal microscopy. Journal of Cell Science 103: 857–862.

Manders E, Verbeek F and Aten J (1993) Measurement of colocaliztaion of objects in dual‐colour confocal images. Journal of Microscopy 169: 375–382.

McDonald JH and Dunn KW (2013) Statistical tests for measures of colocalization in biological microscopy. Journal of Microscopy 252: 295–302.

Moomaw B (2007) Camera technologies for low light imaging: overview and relative advantages. Methods in Cell Biology 81: 251–283.

Nadrigny F, Li D, Kemnitz K, et al. (2007) Systematic colocalization errors between acridine orange and EGFP in astrocyte vesicular organelles. Biophysical Journal 93: 969–980.

Oheim M and Li D (2007) Quantitative colocalisation imaging: concepts, measurements, and pitfalls. In: Imaging Cellular and Molecular Biological Functions, pp. 117–155. Berlin, Heidelberg, New York: Springer.

Oheim M (2010) Instrumentation for live‐cell imaging and main formats. Methods in Molecular Biology 591: 3–16.

Padilla‐Parra S, Audugé N, Coppey‐Moisan M and Tramier M (2008) Quantitative FRET analysis by fast acquisition time domain FLIM at high spatial resolution in living cells. Biophysical Journal 95: 2976–2988.

Pearson K (1901) On lines and planes of closest fit to systems of points in space. Philosophical Magazine Series 6 2: 559–572.

Sahoo PK, Soltani S and Wong AK (1988) A survey of thresholding techniques. Computer Vision, Graphics, and Image Processing 41: 233–260.

Schmied JJ, Gietl A, Holzmeister P, et al. (2012) Fluorescence and super‐resolution standards based on DNA origami. Nature Methods 9: 1133–1134.

Sibarita J‐B (2005) Deconvolution microscopy. Advances in Biochemical Engineering/Biotechnology 95: 201–243.

van Steensel B, van Binnendijk EP, Hornsby CD, et al. (1996) Partial colocalization of glucocorticoid and mineralocorticoid receptors in discrete compartments in nuclei of rat hippocampus neurons. Journal of Cell Science 109: 787–792.

Wang S, Fan J, Pocock G and Yuan M (2016) Structured correlation detection with application to colocalization analysis in dual‐channel fluorescence microscopic imaging. arXiv 1604.0158v1.

Waters JC (2009) Accuracy and precision in quantitative fluorescence microscopy. The Journal of Cell Biology 185: 1135–1148.

Wu Q, Merchant F and Castleman K (2010) Microscope Image Processing. Cambridge (MA) (now a group of Elsevier): Academic Press.

Zhu D, Nicoulaud S, Kleinert C, et al. (2009) Identifying components of astroglial autofluorescence using the spectral separability index, Xijk. Biophysical Journal 96: 31a–32a.

Further Reading

Related Sub-Topics:

Techniques in Cell Biology | Optical Microscopy
Contact Editor close
Submit a note to the editor about this article by filling in the form below.

* Required Field

Article Title: Quantifying Colocalisation in Biological Fluorescence Microscopy
 
How to Cite close
Oheim, Martin, and Brunstein, Maia(Nov 2018) Quantifying Colocalisation in Biological Fluorescence Microscopy. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0026800]