Author
Listed:
- Diana Mahdessian
(KTH - Royal Institute of Technology)
- Anthony J. Cesnik
(KTH - Royal Institute of Technology
Stanford University
Chan Zuckerberg Biohub, San Francisco)
- Christian Gnann
(KTH - Royal Institute of Technology
Chan Zuckerberg Biohub, San Francisco)
- Frida Danielsson
(KTH - Royal Institute of Technology)
- Lovisa Stenström
(KTH - Royal Institute of Technology)
- Muhammad Arif
(KTH - Royal Institute of Technology)
- Cheng Zhang
(KTH - Royal Institute of Technology)
- Trang Le
(KTH - Royal Institute of Technology)
- Fredric Johansson
(KTH - Royal Institute of Technology)
- Rutger Schutten
(KTH - Royal Institute of Technology)
- Anna Bäckström
(KTH - Royal Institute of Technology)
- Ulrika Axelsson
(KTH - Royal Institute of Technology)
- Peter Thul
(KTH - Royal Institute of Technology)
- Nathan H. Cho
(Chan Zuckerberg Biohub, San Francisco)
- Oana Carja
(Stanford University
Chan Zuckerberg Biohub, San Francisco
Carnegie Mellon University)
- Mathias Uhlén
(KTH - Royal Institute of Technology)
- Adil Mardinoglu
(KTH - Royal Institute of Technology
King’s College London)
- Charlotte Stadler
(KTH - Royal Institute of Technology)
- Cecilia Lindskog
(Uppsala University)
- Burcu Ayoglu
(KTH - Royal Institute of Technology)
- Manuel D. Leonetti
(Chan Zuckerberg Biohub, San Francisco)
- Fredrik Pontén
(Uppsala University)
- Devin P. Sullivan
(KTH - Royal Institute of Technology)
- Emma Lundberg
(KTH - Royal Institute of Technology
Stanford University
Chan Zuckerberg Biohub, San Francisco)
Abstract
The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer1–3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.
Suggested Citation
Diana Mahdessian & Anthony J. Cesnik & Christian Gnann & Frida Danielsson & Lovisa Stenström & Muhammad Arif & Cheng Zhang & Trang Le & Fredric Johansson & Rutger Schutten & Anna Bäckström & Ulrika Ax, 2021.
"Spatiotemporal dissection of the cell cycle with single-cell proteogenomics,"
Nature, Nature, vol. 590(7847), pages 649-654, February.
Handle:
RePEc:nat:nature:v:590:y:2021:i:7847:d:10.1038_s41586-021-03232-9
DOI: 10.1038/s41586-021-03232-9
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Citations
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Cited by:
- Juan Manuel Valverde & Geronimo Dubra & Michael Phillips & Austin Haider & Carlos Elena-Real & Aurélie Fournet & Emile Alghoul & Dhanvantri Chahar & Nuria Andrés-Sanchez & Matteo Paloni & Pau Bernadó , 2023.
"A cyclin-dependent kinase-mediated phosphorylation switch of disordered protein condensation,"
Nature Communications, Nature, vol. 14(1), pages 1-23, December.
- Daniel Dimitrov & Dénes Türei & Martin Garrido-Rodriguez & Paul L. Burmedi & James S. Nagai & Charlotte Boys & Ricardo O. Ramirez Flores & Hyojin Kim & Bence Szalai & Ivan G. Costa & Alberto Valdeoliv, 2022.
"Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data,"
Nature Communications, Nature, vol. 13(1), pages 1-13, December.
- Ana Martinez-Val & Dorte B. Bekker-Jensen & Sophia Steigerwald & Claire Koenig & Ole Østergaard & Adi Mehta & Trung Tran & Krzysztof Sikorski & Estefanía Torres-Vega & Ewa Kwasniewicz & Sólveig Hlín B, 2021.
"Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution,"
Nature Communications, Nature, vol. 12(1), pages 1-17, December.
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