ABSTRACT
Results from single cell imaging, facilitated by high resolution microscopy, have demonstrated cell-to-cell variability within the same cell population in contexts ranging from cell growth to cell migration. Recent studies suggest that such variability conveys important information about diseased states. However, manual analysis and interpretation of heterogeneous calcium oscillation based on time-lapsed images, as practiced today, is tedious, and essentially infeasible for large datasets. As a practical alternative, we present an integrated platform that includes calcium imaging using confocal microscope, algorithmic cell segmentation, and statistical analysis. Automated quantification of cell crowding via cell segmentation and statistical analysis of cell-to-cell variability on a representative dataset indicates that the heterogeneity in GPCR (G-protein coupled receptor) mediated calcium oscillation is a function of cell crowding.
