Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 108; no. 17; pp. 7010 - 7015
• Main Authors: Godin, Antoine G., Costantino, Santiago, Lorenzo, Louis-Etienne, Swift, Jody L., Sergeev, Mikhail, Ribeiro-da-Silva, Alfredo, De Koninck, Yves, Wiseman, Paul W., Snyder, Solomon H.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 26-04-2011; National Acad Sciences
• Subjects: Animals; Antibodies; Biological Sciences; Cells; CHO Cells; Computer Simulation; Cricetinae; Cricetulus; Density; Dimers; Fluorescence; Green Fluorescent Proteins - genetics; Green Fluorescent Proteins - metabolism; Histograms; Microscopy; Monomers; Particle density; Pixels; Protein Multimerization - physiology; Proteins; Rats; Rats, Sprague-Dawley; Receptors; Receptors, GABA-B - genetics; Receptors, GABA-B - metabolism; Recombinant Fusion Proteins - genetics; Recombinant Fusion Proteins - metabolism; Signal noise; Signal transduction; Spinal cord; Spinal Cord - cytology; Spinal Cord - metabolism; Tissues
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1018658108

Measuring protein interactions is key to understanding cell signaling mechanisms, but quantitative analysis of these interactions in situ has remained a major challenge. Here, we present spatial intensity distribution analysis (SpIDA), an analysis technique for image data obtained using standard fluorescence microscopy. SpIDA directly measures fluorescent macromolecule densities and oligomerization states sampled within single images. The method is based on fitting intensity histograms calculated from images to obtain density maps of fluorescent molecules and their qua ç ta I brightness. Because spatial distributions are acquired by imaging, SpIDA can be applied to the analysis of images of chemically fixed tissue as well as live cells. However, the technique does not rely on spatial correlations, freeing it from biases caused by subcellular compartmentalization and heterogeneity within tissue samples. Analysis of computer-based simulations and immunocytochemically stained GABAB receptors in spinal cord samples shows that the approach yields accurate measurements over a broader range of densities than established procedures. SpIDA is applicable to sampling within small areas (6 µm²) and reveals the presence of monomers and dimers with single-dye labeling. Finally, using GFP-tagged receptor subunits, we show that SplDA can resolve dynamic changes in receptor oligomerization in live cells. The advantages and greater versatility of SplDA over current techniques open the door to quantificative studies of protein interactions in native tissue using standard fluorescence microscopy.