Analysis of 3D Cellular Organization of Fixed Plant Tissues Using a User-guided Platform for Image Segmentation

The advent of non-invasive, high-resolution microscopy imaging techniques and computational pipelines for high-throughput image processing has contributed to gain insights in plant organ morphogenesis at the cellular level. Confocal scanning laser microscopy (CSLM) allows the generation of three dimensional images constituted of serial optical sections reporting on stained subcellular structures. Fluorescent labels of cell walls or cell membranes, either chemically or through reporter proteins, are particularly useful for the analyses of tissue organization and cellular shapes in 3D. Image segmentation based on cell boundary signals is used as an input to generate 3D-segments representing cells. These digitalized, 3D objects provide quantitative data on cell shape, size, geometry, position or on (intercellular) intensity signals if additional reporters are used. Herein, we report a detailed, annotated workflow for image segmentation using microscopic data. We used it in the context of a study of tissue patterning during ovule primordium development in Arabidopsis thaliana. Whole carpels are stained for cell boundaries using a modified pseudo-Schiff propidium iodide (mPS-PI) protocol, 3D images are acquired at high resolution by CSLM, segmented and annotated for individual cell types using ImarisCell. This allows for quantitative analyses of cell shape and cell number that are relevant for tissue morphodynamic studies.