Co‐localization analysis of complex formation among membrane proteins by computerized fluorescence microscopy: application to immunofluorescence co‐patching studies

Summary Fluorescence imaging of two independently labelled proteins is commonly used to determine their co‐localization in cells. Antibody‐mediated crosslinking can mediate the patching of such proteins at the cell surface, and their co‐localization can serve to determine complex formation among them. However, manual analysis of such studies is both tedious and subjective. Here we present a digital co‐localization analysis that is independent of the fluorescence intensity, is highly consistent and reproducible between observers, and dramatically reduces the analysis time. The approach presented is based on a segmentation procedure that creates binary objects, and then determines whether objects belonging to two different groups (e.g. green‐ and red‐labelled) are co‐localized. Two methods are used to determine co‐localization. The ‘overlap’ analysis defines two objects as co‐localized if the centre of mass of one falls within the area of the other. The ‘nearest‐neighbour distance’ analysis considers two objects as co‐localized if their centres are within a threshold distance determined by the imaging modality. To test the significance of the results, the analysis of the actual images is tested against randomized images generated by a method that creates images with uncorrelated distributions of objects from the two groups. The applicability of the algorithms presented to study protein interactions in live cells is demonstrated by co‐patching studies on influenza haemagglutinin mutants that do or do not associate into mutual oligomers at the cell surface via binding to AP‐2 adaptor complexes. The approach presented is potentially applicable to studies of co‐localization by other methods (e.g. electron microscopy), and the nearest‐neighbour distance method can also be adapted to study phenomena of correlated placement.