Essential biological functions, such as mitosis, require tight coordination of hundreds of proteins in space and time. Localization, the timing of interactions and changes in cellular structure are all crucial to ensure the correct assembly, function and regulation of protein complexes1,2,3,4. Imaging of live cells can reveal protein distributions and dynamics but experimental and theoretical challenges have prevented the collection of quantitative data, which are necessary for the formulation of a model of mitosis that comprehensively integrates information and enables the analysis of the dynamic interactions between the molecular parts of the mitotic machinery within changing cellular boundaries. Here we generate a canonical model of the morphological changes during the mitotic progression of human cells on the basis of four-dimensional image data. We use this model to integrate dynamic three-dimensional concentration data of many fluorescently knocked-in mitotic proteins, imaged by fluorescence correlation spectroscopy-calibrated microscopy5. The approach taken here to generate a dynamic protein atlas of human cell division is generic; it can be applied to systematically map and mine dynamic protein localization networks that drive cell division in different cell types, and can be conceptually transferred to other cellular functions.
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All images processed in this study including original images, concentration maps, segmentation mask for both cellular and chromosomal volume and concentration maps are available in the Image Data Resource (http://idr.openmicroscopy.org51) under DOI: 10.17867/10000112. Further data and code are available as follows: all images are also available for download on the mitotic cell atlas website http://www.mitocheck.org/mitotic_cell_atlas/downloads/v1.0.1/mitotic_cell_atlas_v1.0.1_fulldata.zip (~0.5 TB).The data supporting the spatio-temporal mitotic cell model and the analysis is available from the mitotic cell atlas website (http://www.mitocheck.org/mitotic_cell_atlas/downloads/v1.0.1) and contains: i) segmentation masks for the landmarks (that is, cell boundary and chromosome mass(es)) as TIFF files (directory ‘mitotic_cell_model/binary_masks’) and snapshots of the 3D rendering of each of the spatial models in VRML and TIFF formats (directory ‘mitotic_cell_model/snapshots’). ii) Two movies (orthogonal and oblique views) created from 3D reconstructed average landmarks (cell boundary and chromosome mass(es); directory ‘mitotic_cell_model/movies’). iii) Average concentrations of each protein at individual mitotic stages as mat files, TIFF stacks, and tab-delimited text files (directory ‘protein_distributions’). iv) Feature data used for the analysis (to produce Fig. 4, Extended Data Figs. 7, 8d, e, 9) in a tab-delimited text file (file ‘cell_features.txt’). This file can be used directly as input to the notebooks available in the code repository. This file also contains the mitotic standard time and stage assigned to each cell image. v) Canonical localization data (file ‘canonical_mitotic_clusters.h5’). vi) Dynamic graph (file ‘dynamic_graph_adjacency_matrices.h5’).
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We thank T. Hyman and I. Poser for donating multiple mouse BAC protein–GFP cell lines and T. Hirota for giving us the eGFP–CENPA cell line. The automatic imaging would not have been possible without R. Höfler and D. W. Gerlich, who developed the Micronaut software. We thank all members of the Ellenberg and Peters laboratories for support, especially M. Isokane, M. J. Roberti, J. Mergenthaler, S. Otsuka, W. Tang and D. Cisneros for generating cell lines, reagents and constructs. We thank A. Callegari for supporting the U2OS data generation. We also thank W. Huber, B. Fischer, B. Klaus and L. P. Coelho for discussions, the EMBL mechanical and electronic workshop, the EMBL advanced light microscopy facility, the EMBL flow cytometry core facility and the IMP BioOptics Facility for their support. This study has benefited from the collaboration with Carl ZEISS Jena, especially with T. Ohrt. The work was supported by grants from EU-FP7-MitoSys (Grant Agreement 241548) to J.E. and J.M.P., EU-FP7-SystemsMicroscopy NoE (Grant Agreement 258068), EU-H2020-iNEXT (Grant Agreement 653706) and the 4D Nucleome/4DN National Institutes of Health common fund (5 U01 EB021223-04 / 8 U01 DA047728-04) all to J.E., as well as by the European Molecular Biology Laboratory (Y.C., M.J.H., J.-K.H., A.Z.P., N.W., B.K., M.W., B.N., M.K., S.A. and J.E.). Y.C. and N.W. were also supported by the EMBL International PhD Programme (EIPP). Research in the laboratory of J.M.P. was further supported by Boehringer Ingelheim, the Austrian Science Fund (FWF special research program SFB F34 ‘Chromosome Dynamics’ and Wittgenstein award Z196-B20), the Austrian Research Promotion Agency (Headquarter grants FFG-834223 and FFG-852936) and the European Research Council (ERC) under the European Union Horizon 2020 research and innovation programme (Grant Agreement 693949).
Nature thanks R. Murphy, J. Swedlow and the other anonymous reviewer(s) for their contribution to the peer review of this work.