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Experimental and computational framework for a dynamic protein atlas of human cell division

Author

Listed:
  • Yin Cai

    (European Molecular Biology Laboratory (EMBL)
    Roche Diagnostics)

  • M. Julius Hossain

    (European Molecular Biology Laboratory (EMBL))

  • Jean-Karim Hériché

    (European Molecular Biology Laboratory (EMBL))

  • Antonio Z. Politi

    (European Molecular Biology Laboratory (EMBL)
    Max Planck Institute for Biophysical Chemistry)

  • Nike Walther

    (European Molecular Biology Laboratory (EMBL))

  • Birgit Koch

    (European Molecular Biology Laboratory (EMBL)
    Max Planck Institute for Medical Research)

  • Malte Wachsmuth

    (European Molecular Biology Laboratory (EMBL)
    Luxendo GmbH)

  • Bianca Nijmeijer

    (European Molecular Biology Laboratory (EMBL))

  • Moritz Kueblbeck

    (European Molecular Biology Laboratory (EMBL))

  • Marina Martinic-Kavur

    (Research Institute of Molecular Pathology (IMP)
    Genos, Glycoscience Research Laboratory)

  • Rene Ladurner

    (Research Institute of Molecular Pathology (IMP)
    Stanford School of Medicine)

  • Stephanie Alexander

    (European Molecular Biology Laboratory (EMBL))

  • Jan-Michael Peters

    (Research Institute of Molecular Pathology (IMP))

  • Jan Ellenberg

    (European Molecular Biology Laboratory (EMBL))

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 complexes1–4. 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.

Suggested Citation

  • Yin Cai & M. Julius Hossain & Jean-Karim Hériché & Antonio Z. Politi & Nike Walther & Birgit Koch & Malte Wachsmuth & Bianca Nijmeijer & Moritz Kueblbeck & Marina Martinic-Kavur & Rene Ladurner & Step, 2018. "Experimental and computational framework for a dynamic protein atlas of human cell division," Nature, Nature, vol. 561(7723), pages 411-415, September.
    • Handle: RePEc:nat:nature:v:561:y:2018:i:7723:d:10.1038_s41586-018-0518-z
    DOI: 10.1038/s41586-018-0518-z
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    Cited by:

    1. Gemma Noviello & Rutger A. F. Gjaltema & Edda G. Schulz, 2023. "CasTuner is a degron and CRISPR/Cas-based toolkit for analog tuning of endogenous gene expression," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Raja Chouket & Agnès Pellissier-Tanon & Aliénor Lahlou & Ruikang Zhang & Diana Kim & Marie-Aude Plamont & Mingshu Zhang & Xi Zhang & Pingyong Xu & Nicolas Desprat & Dominique Bourgeois & Agathe Espagn, 2022. "Extra kinetic dimensions for label discrimination," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

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