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

Abstract

SummaryFluorescence 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. greenand 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.

Different Domains Regulate Homomeric and Heteromeric Complex Formation among Type I and Type II Transforming Growth Factor-β Receptors

“…Fluorescence digital images were recorded using a CCD camera (CoolSnap HQ, Photometrics) coupled to an Axioimager D.1 fluorescence microscope (Carl Zeiss Microimaging) with a 100ϫ/1.4 NA oil-immersion objective as described (39). The Alexa 488 (green) and Alexa 594 (red) TIFF images were exported to Image-Pro Plus (Media Cybernetics, Bethesda, MD) and subjected to quantitative analysis of the extent of copatching using an algorithm we have recently developed (39).…”

“…The Alexa 488 (green) and Alexa 594 (red) TIFF images were exported to Image-Pro Plus (Media Cybernetics, Bethesda, MD) and subjected to quantitative analysis of the extent of copatching using an algorithm we have recently developed (39). Briefly, the program segments the patches in a user-defined region of interest, subtracts the background, and identifies the center of mass of each object in the green and red images.…”

Clustering and Lateral Concentration of Raft Lipids by the MAL Protein

“…To this end, we used antibody cross-linking of extracellularly FLAG-tagged MAL (MAL-FLAG) with primary anti-FLAG and secondary Cy3-modified anti-mouse antibodies (Figure 3d) (Lachmanovich et al, 2003). We found that similar to DiHcRED-MAL OCs, crosslinking of MAL-FLAG mediated by divalent antibodies results in a local increase in the concentrations of GPI-FP and GM1.…”

Cholesterol-sensitive Modulation of Transcytosis

“…Sequential frame acquisition was used to eliminate cross-talk between the two fluorescence channels. Colocalization was characterized using the method of Lachmanovich et al (2003). Briefly, the peaks were segmented using a local threshold set at half the maximum value of the local peak.…”