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

Background

Organ and tissue morphodynamic studies in plants rely on the analysis of the three-dimensional process of growth along development progression. The evolution of cell number, cell size and cell shape allows interpreting events of proliferation, cellular expansion and anisotropy, respectively (Roeder et al., 2011; Barbier de Reuille et al., 2015; Bassel and Smith, 2016; Coen and Rebocho, 2016). While time-lapse imaging appears in principle as the method of choice, it is not easily applicable to all plant organs, sometimes embedded in inaccessible structures, and image quality often compromise on robust quantitative analyses over a large number of samples and at the cellular level. A complementary, robust alternative is to stain and record three dimensional images of optically cleared tissue/organ at high-resolution, at consecutive time points in order to reconstruct a developmental progression. These 3D images can then be digitally segmented into individual cell objects, from which measurements of number, different descriptors of cell shape and cell size can be extracted. Whole-mount tissue clearing and staining of the cell wall using the modified pseudo-Schiff propidium iodide (mPS-PI) protocol (Truernit et al., 2008) is widely used in the plant community for 3D shape analyses (Sankar et al., 2014; Yoshida et al., 2014; Hervieux et al., 2016). It is described here with only minor modifications and specific notes enabling high-quality sample preparation for the delicate carpel structures. In addition, while plant tissue imaging using confocal scanning laser microscopy became common practice in many labs, specific knowledge on how to fine-tune the optical and software-controlled image recording remains elusive and often kept ‘in house’. Here we provide detailed recommendations aimed at guiding the user towards producing high-quality, high-resolution 3D images suitable for robust qualitative and quantitative analyses. For image segmentation, different open-source algorithms proved invaluable for tissue morphodynamic studies in plants and Drosophila, namely: MARS-ALT (Fernandez et al., 2010), MorphographX (Barbier de Reuille et al., 2015) and RACE (Stegmaier et al., 2016). Yet, these interfaces usually require computational skills to fine-tune segmentation parameters, correct manually for wrongly segmented objects, customize cell labelling when tissue models are not available in the software and export quantitative data for downstream analyses. An alternative solution for biologists lacking this expertise lies in the use of commercially available software with a streamlined user interface. We present here one option with Imaris, a software for 3D visualization and image processing. We report a detailed, annotated workflow applied to ovule tissue analyses but that is of broad application to analyze various plant tissues.