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Experimental and computational framework for a dynamic protein atlas of human cell division
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Abstract
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 complexes 1-4. 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 microscopy 5. 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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“Other systematic image-based approaches have catalogued the location of human proteins in several cell types and used the locations of proteins and structures within cells to identify differences in intracellular spatial patterns among cells in distinct states6–12,19,29.”
From Integrated intracellular organization and its variations in human iPS cells (2023) · cites this paper as [8]
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Metadata
- Authors
- Cai, Y., Hossain, M. J., Hériché, J.-K., Politi, A. Z., Walther, N., Koch, B., Wachsmuth, M., Nijmeijer, B., Kueblbeck, M., Martinic-Kavur, M., Ladurner, R., Alexander, S., Peters, J.-M., & Ellenberg, J.
- Affiliations
- European Molecular Biology Laboratory (DE)
- Max Planck Institute for Biophysical Chemistry (DE)
- Max Planck Institute for Medical Research (DE)
- Research Institute of Molecular Pathology (AT)
- Corresponding author
- Ellenberg, Jan
- ORCID
- Venue
- Nature
- Published
- 2018-09
- Volume
- 561
- Issue
- 7723
- Pages
- 411-415
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6556381
- OpenAlex
- W2890313592
- Cited by
- 121
- References
- 55
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 12 · 2023: 17 · 2022: 11 · 2021: 20 · 2020: 19 · 2019: 24 · 2018: 4
- FWCI
- 9.28
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- National Institute on Drug Abuse (U01DA047728)
- National Institute of Biomedical Imaging and Bioengineering (U01EB021223)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Microtubule and mitosis dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Keywords
- mitosis, cell division, protein localization, 4D imaging, fluorescence correlation spectroscopy, human cells
- MeSH terms
- Gene Editing, HeLa Cells, Humans, Microscopy, Fluorescence, Mitosis, Time Factors, Cell Cycle Proteins, Imaging, Three-Dimensional, Green Fluorescent Proteins, Molecular Imaging
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