Colocalization Colormap

Independent fluorescent labelling of two different elements is a commonly used method to determine their colocalization in two superimposed microscopic images. The common algorithms utilised in this process are based on the comparison of general distributions of fluorescence intensities and do not provide any spatial representation of colocalization within the analyzed specimens. To overcome this limitation an advance to colocalization analysis has been proposed by Jaskolski et al. (2010). This website contains Colocalization Colormap ImageJ plugin that implements the Jaskolski's algorithm. This innovative method produces a pseudo-color map of correlations between pairs of corresponding pixels in two original input images, thereby offering quantitative visualisation of colocalization.

Spatial representation of colocalization

In the course of the analysis, the plugin calculates normalized mean deviation product (nMDP) as a measure of correlation between corresponding pairs of pixels according to the genuine formula .

Further the program generates image that contains spatial distribution of calculated nMDP values (ranging from -1 to 1). The distribution is based on a color scale in which negative nMDP values are represented by cold colors (segregation). On the other hand, values above 0 are represented by hot colors (colocalization). Consecutively, this allows for creation of spatial map of colocalization.

Map of colocalization created with Colocalization Colormap plugin.

(A) Neuronal body and dendritic processes stained with antibody against MAP2 protein. (B) Immunoreactivity of CD44 adhesion molecule in the brain. (C-D) Color map presenting colocalization between adhesion molecule and MAP2 neuronal marker.

Measurement of colocalization.

Plugin calculates index of correlation (Icorr). The index represents fraction of positively correlated (colocalized) pixels in analysed images which allows for very sensitive quantitative measurement of colocalization.

Simulated data

Method implemented to the plugin was tested on artificial images generated to simulate progressive separation of two fluorescent labels. To do this, confocal image was duplicated and the duplicated image was rotated 15º, 30º, 45º, and 60º clockwise. Single planes of these two artificial channels were then analysed with Colocalization Colormap plugin to create maps of colocalization and calculate corresponding Icorrs.

Evaluation of Colocalization Colormap plugin.

A-M) Pixels in original (green channel) confocal images were translocated (red channel) to simulate progressive separation of overlapping fluorescent foci. I-M) nMDP distribution demonstrating gradual decrease of colocalization (hot colors) between the two analysed objects.