We used a similar approach to analyze the distribution of the YFP-NCoR in the nuclei of over 100 cells selected from the transfected population using mRFP ((Figure 3)A). Within the cell population, individual cells expressed different relative levels of both mRFP and YFP-NCoR. We observed only a weak correlation between the expression of the mRFP selection marker and the YFP-labeled NCoR in the co-transfected cells ((Figure 3)B). This weak correlation allowed the selection of cells that expressed a wide range of YFP-NCoR, including cells that would not have been detected by eye through the fluorescence microscope. Therefore, the population of cells used for the analysis contained cells expressing very low levels of the YFP that would not have been captured using conventional qualitative imaging approaches. The population analysis of YFP-NCoR subnuclear distribution shown in (Figure 3)A precisely quantifies the significant relationship between fusion protein expression level and higher order protein organization. Similar concentration-dependent behavior was observed for several transcriptional corepressor proteins, as well as the nuclear receptor coactivator glucocorticoid receptor interacting protein (GRIP; Reference (51), indicating that fusion protein expression levels must be considered when comparing protein organization in different experimental cell populations. The application of these methods effectively reduces many millions of data points into a few thousand morphometric measurements. However, even these simplified morphometric data sets contain many interrelated parameters, which require statistical modeling to define the relationships between parameters. Fortunately, bioinformatics tools are being developed to manage the large amount of data generated by automated image analysis methods (23). The integration of automated analysis routines and customized database software will allow high-resolution imaging techniques to rigorously quantify the behavior of large cell populations.Figure 3.
An important application of these quantitative imaging methods is the analysis of the functional associations between specific protein partners in living cells, complementing observations made using in vitro techniques. For instance, the use of biochemical approaches to characterize multi-protein complexes that function to modify chromatin structure and control the gene expression has been invaluable in describing mechanisms underlying gene regulation (51,52,53). What is missed by the in vitro analysis, however, is the role that the organized microenvironment within the nucleus plays in the formation of these complexes. The distributions of gene regulatory factors in the nuclei of living cells are dynamic, and their recruitment to particular intranuclear sites reflects the balance of their interactions with other protein partners and their association with the chromatin (53). This is illustrated by the studies of Rivera and et al. (54) who used the cyan [cyan fluorescent protein (CFP)] and yellow (YFP) color variants to visualize the androgen receptor and the steroid receptor coactivator protein 1 in living cells and to characterize their association with the nuclear bodies formed by PML. These observations revealed the ligand-dependent translocation of CFP-labeled androgen receptor into the nucleus, where it functioned to redistribute the YFP-steroid receptor coactivator protein 1 away from the PML bodies (54). A similar approach was used to demonstrate the recruitment of transcription factors and coactivator proteins by transcription factor CAATT enhancer binding protein a (9,11). These changes in subnuclear organization likely reflect direct protein-protein interactions, but the optical resolution of the light microscope is not sufficient to detect this. Fortunately, there are imaging techniques available that allow us to further define the spatial relationships between specific protein partners in living cells.