3DCellAtlas Meristem: a tool for the global cellular annotation of shoot apical meristems

Abstract

Modern imaging approaches enable the acquisition of 3D and 4D datasets capturing plant organ development at cellular resolution. Computational analyses of these data enable the digitization and analysis of individual cells. In order to fully harness the information encoded within these datasets, annotation of the cell types within organs may be performed. This enables data points to be placed within the context of their position and identity, and for equivalent cell types to be compared between samples. The shoot apical meristem (SAM) in plants is the apical stem cell niche from which all above ground organs are derived. We developed 3DCellAtlas Meristem which enables the complete cellular annotation of all cells within the SAM with up to 96% accuracy across all cell types in Arabidopsis and 99% accuracy in tomato SAMs. Successive layers of cells are identified along with the central stem cells, boundary regions, and layers within developing primordia. Geometric analyses provide insight into the morphogenetic process that occurs during these developmental processes. Coupling these digital analyses with reporter expression will enable multidimensional analyses to be performed at single cell resolution. This provides a rapid and robust means to perform comprehensive cellular annotation of plant SAMs and digital single cell analyses, including cell geometry and gene expression. This fills a key gap in our ability to analyse and understand complex multicellular biology in the apical plant stem cell niche and paves the way for digital cellular atlases and analyses. Electronic supplementary material The online version of this article (10.1186/s13007-019-0413-0) contains supplementary material, which is available to authorized users.

A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

“…Staining with TO-PRO-3 also allowed the identification of cells undergoing mitosis ( Figure 1D ). Available computational pipelines for near-automatic, geometry-based cell type identification ( Montenegro-Johnson et al, 2015 ; Montenegro-Johnson et al, 2019 ; Schmidt et al, 2014 ) failed to provide reasonably good and consistent results. This was likely due to the ovule exhibiting a more complex tissue architecture.…”

“…The applied approach, however, was incompatible with fluorescent stains. Full 3D processing of live imaged data sets has also been possible in some systems, such as the shoot apex but is limited by light penetration to outer layers ( Montenegro-Johnson et al, 2019 ; Refahi et al, 2020 ; Willis et al, 2016 ).…”

A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

“…1D). Available computational pipelines for near-automatic, geometry-based cell type identification (Montenegro-Johnson et al, 2015; Montenegro-Johnson et al, 2019; Schmidt et al, 2014) failed to provide reasonably good and consistent results. This was likely due to the ovule exhibiting a more complex tissue architecture.…”

“…The generated surface mesh was then smoothed several times using the process with 10 passes. For mature ovules cell type annotation, we used the MGX process (a modified 3DCellAtlas Meristem tool (Montenegro-Johnson et al, 2019)) with the 3D cell meshes in the workspace and the tissue surface mesh in the workspace using a cone angle parameter of 1.2. This process correctly classified about 60 percent of cells based on the layer they belong to.…”

Double or Nothing? Cell Division and Cell Size Control

“…Although arabidopsis cells can be grown in liquid culture and can be synchronised using similar techniques [55], the relevance of the results to developmental contexts is difficult to interpret. Recent advances in live cell imaging and image analysis mean that intact tissues can now be imaged over multiple days and each individual cell and its daughters can be tracked over time as they progress through the cell cycle [46,[56][57][58][59]. Instead of synchronising the behaviour of cells, cell-to-cell variation is utilised to identify different behaviours.…”