Quantitative image analysis of cell behavior and molecular dynamics during tissue morphogenesis

Abstract

The cell behaviors that drive tissue morphogenesis, such as division, migration, or death, are regulated at the molecular scale. Understanding how molecular events determine cell behavior requires simultaneous tracking and measurement of molecular and cellular dynamics. To this end, we have developed SIESTA, an integrated tool for Scientific ImagE SegmenTation and Analysis that enables quantification of cell behavior and molecular events from image data. Here we use SIESTA to show how to automatically delineate cells in images (segmentation) using the watershed algorithm, a region-growing method for boundary detection. For images in which automated segmentation is not possible due to low or inappropriate contrast, we use a minimal path search algorithm to semiautomatically delineate the cells. We use the segmentation results to quantify cellular morphology and molecular dynamics in different subcellular compartments, and demonstrate the whole process by analyzing cell behavior and the dynamics of the motor protein non-muscle myosin II during axis elongation in a Drosophila embryo. Finally, we show how image analysis can be used to quantify molecular asymmetries that orient cell behavior, and demonstrate this point by measuring planar cell polarity in Drosophila embryos. We describe all methods in detail to allow their implementation and application using other software packages. The use of (semi) automated quantitative imaging enables the analysis of a large number of samples, thus providing the statistical power necessary to detect subtle molecular differences that may result in differences in cell behavior.