Automated high through-put colocalization analysis of multichannel confocal images

The laser scanning confocal microscope (LSCM) generates images of multiple labelled fluorescent samples. Colocalization of fluorescent labels is frequently examined. Here we present an example where localization of fluorescent analogues of cloned protein were referenced to fluorescent antibodies directed against the proteins of cellular compartments. Colocalization is usually evaluated by visual inspection of signal overlap or by using commercially available software tools, but there are limited possibilities to automate the analysis of large amounts of data. We developed a simple tool using Matlab to automate the colocalization procedure and to exclude the biased estimations resulting from visual inspections of images. The script in Matlab language code automatically imports confocal images and converts them into arrays. The contrast of all images is uniformly set by linearly reassigning the values of pixel intensities to use the full 8-bit range (0–255). Images are binarized on several threshold levels. The area above a certain threshold level is summed for each channel of the image and for colocalized regions. As a result, count of pixels above several threshold levels in any number of images is saved in an ASCII file. In addition Pearson's r correlation coefficient is calculated for fluorescence intensities of both confocal channels. Using this approach quick quantitative analysis of colocalization of hundreds of images is possible. In addition, such automated procedure is not biased by the examiner's subject visualization.