Here, we developed an approach for analyzing the colocalization relationships between three molecular entities, termed “conditional colocalization analysis.” It is based on the spatial point pattern analysis of detected objects in microscopy images, applicable to images of both punctate and non-punctate objects. With the advent of single-molecule localization microscopy, which yields data in the form of point coordinates, there have been many developments in colocalization analysis through point pattern analysis ( Andronov et al., 2016 Malkusch et al., 2012 Pageon et al., 2016 Williamson et al., 2020). For the latter, colocalization analysis can be thought of as a spatial point pattern analysis task ( Diggle, 2014 Lagache et al., 2015). Depending on the nature of the objects and the biological question, object-based colocalization analysis can then employ intensity ( Manders et al., 1993), area/volume overlap ( Mascalchi and Cordelieres, 2019), or inter-object distances (usually between object centroids Boutte et al., 2006 Helmuth et al., 2010 Lachmanovich et al., 2003 Lagache et al., 2018 Pastorek et al., 2016). Ĭolocalization analysis generally falls into one of two categories: (i) pixel/voxel-based, such as the Pearson correlation coefficient ( Aaron et al., 2018 Adler et al., 2008 Bolte and Cordelières, 2006) and (ii) object-based, where first objects are detected or segmented in the images and then the colocalization between objects is analyzed ( Lagache et al., 2015 Mascalchi and Cordelieres, 2019).
IMAGEJ COLOCALIZATION ANALYSIS SOFTWARE
The software for conditional colocalization analysis is available at. We benchmark the approach and showcase its application to investigate receptor-downstream adaptor colocalization relationships in the context of functionally relevant plasma membrane locations. Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two entities is influenced, positively or negatively, by their colocalization with a third entity. Here, we describe an approach, termed “conditional colocalization analysis,” for analyzing the colocalization relationships between three molecular entities in three-color microscopy images. However, almost all colocalization analyses are designed for two-color images, limiting the type of information that they reveal. It provides information on the localization of molecules within subcellular compartments and allows the interrogation of known molecular interactions in their cellular context. Colocalization analysis of multicolor microscopy images is a cornerstone approach in cell biology.
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