A rapid segmentation method of cell boundary for developing embryos using machine learning with a personal computer

Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes

Nucleus, chromatin, and chromosome organization studies heavily rely on fluorescence microscopy imaging to elucidate the distribution and abundance of structural and regulatory components. Three-dimensional (3D) image stacks are a source of quantitative data on signal intensity level and distribution and on the type and shape of distribution patterns in space. Their analysis can lead to novel insights that are otherwise missed in qualitative-only analyses. Quantitative image analysis requires specific software and workflows for image rendering, processing, segmentation, setting measurement points and reference frames and exporting target data before further numerical processing and plotting. These tasks often call for the development of customized computational scripts and require an expertise that is not broadly available to the community of experimental biologists. Yet, the increasing accessibility of high- and super-resolution imaging methods fuels the demand for user-friendly image analysis workflows. Here, we provide a compendium of strategies developed by participants of a training school from the COST action INDEPTH to analyze the spatial distribution of nuclear and chromosomal signals from 3D image stacks, acquired by diffraction-limited confocal microscopy and super-resolution microscopy methods (SIM and STED). While the examples make use of one specific commercial software package, the workflows can easily be adapted to concurrent commercial and open-source software. The aim is to encourage biologists lacking custom-script-based expertise to venture into quantitative image analysis and to better exploit the discovery potential of their images.Abbreviations: 3D FISH: three-dimensional fluorescence in situ hybridization; 3D: three-dimensional; ASY1: ASYNAPTIC 1; CC: chromocenters; CO: Crossover; DAPI: 4',6-diamidino-2-phenylindole; DMC1: DNA MEIOTIC RECOMBINASE 1; DSB: Double-Strand Break; FISH: fluorescence in situ hybridization; GFP: GREEN FLUORESCENT PROTEIN; HEI10: HUMAN ENHANCER OF INVASION 10; NCO: Non-Crossover; NE: Nuclear Envelope; Oligo-FISH: oligonucleotide fluorescence in situ hybridization; RNPII: RNA Polymerase II; SC: Synaptonemal Complex; SIM: structured illumination microscopy; ZMM (ZIP: MSH4: MSH5 and MER3 proteins); ZYP1: ZIPPER-LIKE PROTEIN 1.

In vivo high-content imaging and regression analysis reveal non-cell autonomous functions of Shroom3 during neural tube closure

During neural tube closure, neural ectoderm cells constrict their apical surfaces to bend and fold the tissue into a tube that will become the central nervous system. Recent data from mice and humans with neural tube defects suggest that key genes required for neural tube closure can exert non-cell autonomous effects on cell behavior, but the nature of these effects remains obscure. Here, we coupled tissue-scale, high-resolution time-lapse imaging of the closing neural tube of Xenopus to multivariate regression modeling, and we show that medial actin accumulation drives apical constriction non-autonomously in neighborhoods of cells, rather than solely in individual cells. To further explore this effect, we examined mosaic crispant embryos and identified both autonomous and non-autonomous effects of the apical constriction protein Shroom3.