Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes
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 Boulaflous-Stevens,
Ivona Kubalová,
Terezie Mandáková,
Stefan Heckmann,
Martin A. Lysak,
Martina Panatta,
Raffaella Santoro,
Daniel Schubert,
Ales Pecinka,
Devin Routh,
Célia Baroux
Affiliations
Ricardo S Randall
Department of Plant and Microbial Biology, Zürich-Basel Plant Science Center, University of Zürich, Zürich, Switzerland
Claire Jourdain
Institute of Biology, Freie Universität Berlin, Germany
Anna Nowicka
Centre of the Region Haná for Biotechnological and Agricultural Research (CRH), Institute of Experimental Botany, v. v. i. (IEB), Olomouc, Czech Republic
Kateřina Kaduchová
Centre of the Region Haná for Biotechnological and Agricultural Research (CRH), Institute of Experimental Botany, v. v. i. (IEB), Olomouc, Czech Republic
Michaela Kubová
Central European Institute of Technology (CEITEC) and Department of Experimental Biology, Masaryk University, Brno, Czech Republic
Mohammad A. Ayoub
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Seeland, Germany
Veit Schubert
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Seeland, Germany
Christophe Tatout
Institut Génétique, Reproduction et Développement (GReD), Université Clermont Auvergne, CNRS, INSERM, 63001 Clermont-Ferrand, France
Isabelle Colas
The James Hutton Institute, Errol Road, Invergowrie, DD2 5DA, Scotland UK
Kalyanikrishna
Institute of Biology, Freie Universität Berlin, Germany
Sophie Desset
Institut Génétique, Reproduction et Développement (GReD), Université Clermont Auvergne, CNRS, INSERM, 63001 Clermont-Ferrand, France
Sarah Mermet
Institut Génétique, Reproduction et Développement (GReD), Université Clermont Auvergne, CNRS, INSERM, 63001 Clermont-Ferrand, France
Aurélia Boulaflous-Stevens
Institut Génétique, Reproduction et Développement (GReD), Université Clermont Auvergne, CNRS, INSERM, 63001 Clermont-Ferrand, France
Ivona Kubalová
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Seeland, Germany
Terezie Mandáková
Central European Institute of Technology (CEITEC) and Department of Experimental Biology, Masaryk University, Brno, Czech Republic
Stefan Heckmann
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Seeland, Germany
Martin A. Lysak
Central European Institute of Technology (CEITEC) and National Centre for Biomolecular Research, Masaryk University, Brno, Czech Republic
Martina Panatta
Department of Molecular Mechanisms of Disease, DMMD, University of Zürich, Zürich, Switzerland
Raffaella Santoro
Department of Molecular Mechanisms of Disease, DMMD, University of Zürich, Zürich, Switzerland
Daniel Schubert
Institute of Biology, Freie Universität Berlin, Germany
Ales Pecinka
Centre of the Region Haná for Biotechnological and Agricultural Research (CRH), Institute of Experimental Botany, v. v. i. (IEB), Olomouc, Czech Republic
Devin Routh
Service and Support for Science IT (S3IT), Universität Zürich, Zürich, Switzerland
Célia Baroux
Department of Plant and Microbial Biology, Zürich-Basel Plant Science Center, University of Zürich, Zürich, Switzerland
ABSTRACTNucleus, 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.
