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

• DOI: 10.1080/19491034.2022.2144013
• Publication Date: 2022-11-30T06:22:56Z
• Authors: Ricardo S Randall; Claire Jourdain; Anna Nowicka; Kateřina Kaduchová; Michaela Kubová; Mohammad A. Ayoub; Veit Schubert; Christophe Tatout; Isabelle Colas; Kalyanikrishna; Sophie Desset; Sarah Mermet; Aurélia Boulaflou...; Ivona Kubalová; Terezie Mandáková; Stefan Heckmann; Martin A. Lysak; Martina Panatta; Raffaella Santoro; Daniel Schubert; Ales Pecinka; Devin Routh; Célia Baroux
• Keywords: 0301 basic medicine; 570; transcription factories; Green Fluorescent Proteins; sim; STED imaging; QH426-470; metaphase; Nucleus; Workflow; oligo FISH; 03 medical and health sciences; crossovers; image analysis; RNA Pol II; Genetics; meiosis; Humans; chromosome; In Situ Hybridization, Fluorescence; Cell Nucleus; mitosis; QH573-671; spatial distribution; segmentation; nuclear bodies; 500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie; 3D organization; Chromatin; quantification; Microscopy, Fluorescence; pachytene; chromatin; nuclear speckles; Cytology; Research Paper

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.