The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology.
Investigating neural stem cell (NSC) behaviour in vivo, which is a major area of research, requires NSC models to be developed. We carried out a multilevel characterisation of the zebrafish embryo peripheral midbrain layer (PML) and identified a unique vertebrate progenitor population. Located dorsally in the transparent embryo midbrain, these large slow-amplifying progenitors (SAPs) are accessible for long-term in vivo imaging. They form a neuroepithelial layer adjacent to the optic tectum, which has transitory fast-amplifying progenitors (FAPs) at its margin. The presence of these SAPs and FAPs in separate domains provided the opportunity to data mine the ZFIN expression pattern database for SAP markers, which are coexpressed in the retina. Most of them are involved in nucleotide synthesis, or encode nucleolar and ribosomal proteins. A mutant for the cad gene, which is strongly expressed in the PML, reveals severe midbrain defects with massive apoptosis and sustained proliferation. We discuss how fish midbrain and retina progenitors might derive from ancient sister cell types and have specific features that are not shared with other SAPs.
A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.
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