Department of Physics, Alan Edwards Center for Research of Pain, Chemistry, and Anatomy and Cell Biology, McGill University Montréal, Québec, Canada H3A 2T5.
Proc Natl Acad Sci U S A. 2011 Apr 26;108(17):7010-5. doi: 10.1073/pnas.1018658108. Epub 2011 Apr 11.
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 quantal 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 GABA(B) 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 μm(2)) and reveals the presence of monomers and dimers with single-dye labeling. Finally, using GFP-tagged receptor subunits, we show that SpIDA can resolve dynamic changes in receptor oligomerization in live cells. The advantages and greater versatility of SpIDA over current techniques open the door to quantificative studies of protein interactions in native tissue using standard fluorescence microscopy.
测定蛋白质相互作用是理解细胞信号转导机制的关键，但定量分析这些原位相互作用一直是一个主要挑战。在这里，我们提出了空间强度分布分析（SpIDA），这是一种用于标准荧光显微镜获得的图像数据的分析技术。SpIDA 直接测量在单个图像中采样的荧光大分子密度和寡聚状态。该方法基于拟合从图像计算出的强度直方图，以获得荧光分子及其量子亮度的密度图。由于空间分布是通过成像获得的，因此 SpIDA 可应用于化学固定组织以及活细胞的图像分析。然而，该技术不依赖于空间相关性，从而避免了由亚细胞区室化和组织样本内的异质性引起的偏差。基于计算机的模拟和脊髓样本中免疫细胞化学染色的 GABA(B)受体的分析表明，该方法在比现有方法更广泛的密度范围内提供了更准确的测量结果。SpIDA 适用于小面积（6 μm²）内的采样，并且可以用单染料标记来揭示单体和二聚体的存在。最后，使用 GFP 标记的受体亚基，我们表明 SpIDA 可以在活细胞中解析受体寡聚化的动态变化。SpIDA 相对于现有技术的优势和更大的通用性为使用标准荧光显微镜在天然组织中定量研究蛋白质相互作用开辟了道路。
