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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 &lt;1 min. The entire procedure takes approximately 15-30 min.

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