Carden, S., Vitiello, E., Rosa e Silva, I. et al. (8 more authors) (2023) Proteomic profiling of centrosomes across multiple mammalian cell and tissue types by an affinity capture method. Developmental Cell, 58 (21). 2393-2410.e9. ISSN 1534-5807
Abstract
Centrosomes are the major microtubule-organizing centers in animals and play fundamental roles in many cellular processes. Understanding how their composition varies across diverse cell types and how it is altered in disease are major unresolved questions, yet currently available centrosome isolation protocols are cumbersome and time-consuming, and they lack scalability. Here, we report the development of centrosome affinity capture (CAPture)-mass spectrometry (MS), a powerful one-step purification method to obtain high-resolution centrosome proteomes from mammalian cells. Utilizing a synthetic peptide derived from CCDC61 protein, CAPture specifically isolates intact centrosomes. Importantly, as a bead-based affinity method, it enables rapid sample processing and multiplexing unlike conventional approaches. Our study demonstrates the power of CAPture-MS to elucidate cell-type-dependent heterogeneity in centrosome composition, dissect hierarchical interactions, and identify previously unknown centrosome components. Overall, CAPture-MS represents a transformative tool to unveil temporal, regulatory, cell-type- and tissue-specific changes in centrosome proteomes in health and disease.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Microtubule-Organizing Center; Centrosome; Microtubules; Animals; Mammals; Proteome; Proteomics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Apr 2024 12:49 |
Last Modified: | 26 Apr 2024 12:49 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.devcel.2023.09.008 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:211893 |
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