Experimental and computational framework for a dynamic protein atlas of human cell division.
Experimental and computational framework for a dynamic protein atlas of human cell division.
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.
411-415
Cai, Yin
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Hossain, MJ
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Hériché, Jean-Karim
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Politi, Antonio Zakaria
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Walther, Nike
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Koch, Birgit
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Wachsmuth, Malte
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Nijmeijer, Bianca
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Kueblbeck, Moritz
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Martinic-Kavur, Marina
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Ladurner, Rene
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Alexander, Stephanie
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Peters, Jan-Michael
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Ellenberg, Jan
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20 September 2018
Cai, Yin
a0203c52-8d1f-42ea-bd18-1d578149f32c
Hossain, MJ
bba1b875-7604-462b-a55b-ba0b54f728e8
Hériché, Jean-Karim
03041d48-adf7-4410-bb2b-94c8e9def867
Politi, Antonio Zakaria
871fe135-9a46-4bb8-b438-6584dfabfb77
Walther, Nike
2fb252f0-1e43-4a3c-9f4d-8da537217307
Koch, Birgit
93ac3f08-e7b5-46d8-bbae-b03725fcaeb9
Wachsmuth, Malte
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Nijmeijer, Bianca
c8c2fe68-1269-49ff-b01d-9047988a2416
Kueblbeck, Moritz
21b89290-812b-44e0-b46f-24e8456b934d
Martinic-Kavur, Marina
4bc2a820-fe84-4fc9-8a0d-d79731c8e57a
Ladurner, Rene
5750bb59-3587-4955-843a-6ff02c7284e3
Alexander, Stephanie
6b4dc24b-12c6-4ad5-ab36-1048c4eeae8f
Peters, Jan-Michael
cf6b1204-1061-4f6e-87be-1c3fb460fe7c
Ellenberg, Jan
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Cai, Yin, Hossain, MJ, Hériché, Jean-Karim, Politi, Antonio Zakaria, Walther, Nike, Koch, Birgit, Wachsmuth, Malte, Nijmeijer, Bianca, Kueblbeck, Moritz, Martinic-Kavur, Marina, Ladurner, Rene, Alexander, Stephanie, Peters, Jan-Michael and Ellenberg, Jan
(2018)
Experimental and computational framework for a dynamic protein atlas of human cell division.
Nature, 561 (7723), .
(doi:10.1038/s41586-018-0518-z).
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 complexes1,2,3,4. 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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Accepted/In Press date: 25 July 2018
e-pub ahead of print date: 10 September 2018
Published date: 20 September 2018
Identifiers
Local EPrints ID: 458221
URI: http://eprints.soton.ac.uk/id/eprint/458221
ISSN: 0028-0836
PURE UUID: 7de849dd-acf5-44ff-953a-8d069067ec15
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Date deposited: 01 Jul 2022 16:33
Last modified: 17 Mar 2024 04:12
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Contributors
Author:
Yin Cai
Author:
MJ Hossain
Author:
Jean-Karim Hériché
Author:
Antonio Zakaria Politi
Author:
Nike Walther
Author:
Birgit Koch
Author:
Malte Wachsmuth
Author:
Bianca Nijmeijer
Author:
Moritz Kueblbeck
Author:
Marina Martinic-Kavur
Author:
Rene Ladurner
Author:
Stephanie Alexander
Author:
Jan-Michael Peters
Author:
Jan Ellenberg
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