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Quantifying spatial correlations of fluorescent markers using enhanced background reduction with protein proximity index and correlation coefficient estimations

Nature Protocols volume 6, pages 1554–1567 (2011)Cite this article

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Abstract

Interactions of proteins are examined by detecting their overlap using fluorescent markers. The observed overlap is then quantified to serve as a measure of spatial correlation. A major drawback of this approach is that it can produce false values because of the properties of the image background. To remedy this, we provide a protocol to reduce the contribution of image background and then apply a protein proximity index (PPI) and correlation coefficient to estimate colocalization. Background heterogeneity is reduced by the median filtering procedure, comprising two steps, to reduce random noise and background, respectively. Alternatively, background can be reduced by advanced thresholding. PPI provides separate values for each channel to characterize the contribution of each protein, whereas correlation coefficient determines the overall colocalization. The protocol is demonstrated using computer-simulated and real biological images. It minimizes human bias and can be universally applied to various cell types in which there is a need to understand protein-protein interactions. Background reductions require 3–5 min per image. Quantifications take <1 min. The entire procedure takes approximately 15–30 min.

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Figure 1: Flowchart of the procedure for quantification of the spatial correlation of fluorescent markers.
Figure 2: Screenshots of the computer setup for using median filtering–based background reduction.
Figure 3: Screenshots of the computer setup for applying threshold-based background reduction.
Figure 4: Screenshots of the computer setup for performing PPI calculations.
Figure 5: Quantification of colocalization using computer-simulated dual-color images with predefined colocalization and without any background or nonspecific fluorescence.
Figure 6: Quantification of colocalization using computer-simulated dual-color images with predefined colocalization and without any background or nonspecific fluorescence.
Figure 7: Quantification of colocalization using computer-simulated dual-color images with predefined colocalization and without any background or nonspecific fluorescence.
Figure 8: Quantification of colocalization using computer-simulated dual-color mages with predefined colocalization and without any background or nonspecific fluorescence.
Figure 9: Quantification of colocalization using a real biological image with nonreduced background.
Figure 10: Quantification of colocalization on a set of computer-simulated images modeled on a real biological image shown in Figure 9.
Figure 11: Quantification of colocalization on a set of computer-simulated images modeled on a real biological image shown in Figure 9.
Figure 12: Quantification of colocalization on a real unprocessed biological image showing dual staining for platelet-activating factor receptor (PAF-R; red fluorescence) and CD4 (green fluorescence) on macrophages in conjunctiva.
Figure 13: Quantification of colocalization on the image shown in Figure 12 after median filtering background reduction and PPI estimations.
Figure 14: Quantification of colocalization on the image shown in Figure 12 after threshold-based background reduction and coefficient estimations.

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Acknowledgements

This work was partially supported by National Institutes of Health grant no. HL088640 and the American Heart Association Postdoctoral Fellowship no. 10POST4230081. We thank M. Celio (Fribourg University) for help in organizing the study.

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Authors and Affiliations

  1. Department of Anatomy and Cell Biology, Kochi University, Faculty of Medicine, Kochi, Japan

    Vadim Zinchuk

  2. Department of Anesthesiology, Division of Molecular Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA

    Yong Wu & Enrico Stefani

  3. Unit of Anatomy, Faculty of Medicine, University of Fribourg, Fribourg, Switzerland

    Olga Grossenbacher-Zinchuk

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  1. Vadim Zinchuk
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  4. Enrico Stefani
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Contributions

V.Z. conceived and organized the study, designed and conducted experiments and wrote the paper; Y.W. conducted experiments and contributed to writing, O.G.-Z. designed and conducted experiments and contributed to writing; and E.S. helped to organize the study.

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Correspondence to Vadim Zinchuk.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Pair 1: 0% colocalization. Red channel. (TIFF 769 kb)

Supplementary Fig. 2

Pair 1: 0% colocalization. Green channel. (TIFF 769 kb)

Supplementary Fig. 3

Pair 2: 25% colocalization. Red channel. (TIFF 769 kb)

Supplementary Fig. 4

Pair 2: 25% colocalization. Green channel. (TIFF 769 kb)

Supplementary Fig. 5

Pair 3: 50% colocalization. Red channel. (TIFF 769 kb)

Supplementary Fig. 6

Pair 3: 50% colocalization. Green channel. (TIFF 769 kb)

Supplementary Fig. 7

Pair 4: 75% colocalization. Red channel. (TIFF 769 kb)

Supplementary Fig. 8

Pair 4: 75% colocalization. Green channel. (TIFF 769 kb)

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Zinchuk, V., Wu, Y., Grossenbacher-Zinchuk, O. et al. Quantifying spatial correlations of fluorescent markers using enhanced background reduction with protein proximity index and correlation coefficient estimations. Nat Protoc 6, 1554–1567 (2011). https://doi.org/10.1038/nprot.2011.384

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