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Cited by 41Advanced Proteomics Techniques and ApplicationsSingle-cell and spatial transcriptomicsUbiquitin and proteasome pathways

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Global analysis of protein turnover dynamics in single cells

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Sabatier, Pierre, Lechner, Maico, Guzmán, Ulises H., Beusch, Christian M., Zeng, Xinlei, Wang, Longteng, Izaguirre, Fabiana, Seth, Anjali, Gritsenko, Olga, Rodin, Sergey, Grinnemo, Karl-Henrik, Ye, Zilu, Olsen, Jesper V.·2025·Cell
DOI 10.1016/j.cell.2025.03.002

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Abstract

Abstract Even with recent improvements in sample preparation and instrumentation, single-cell proteomics (SCP) analyses mostly measure protein abundances, making the field unidimensional. In this study, we employ a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ∼4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Our study represents the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional measurements beyond protein abundance. This method distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner.

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Metadata

Authors
Sabatier, P., Lechner, M., Guzmán, U. H., Beusch, C. M., Zeng, X., Wang, L., Izaguirre, F., Seth, A., Gritsenko, O., Rodin, S., Grinnemo, K.-H., Ye, Z., & Olsen, J. V.
Affiliations
  • Uppsala University (SE)
  • University of Copenhagen (DK)
  • Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
  • Xijing Hospital (CN)
Corresponding author
  • Sabatier, Pierre
  • Ye, Zilu
  • Olsen, Jesper V.
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2025-05
Volume
188
Issue
9
Pages
2433-2450.e21
ISSN
0092-8674 (ISSN-L)
DOI
10.1016/j.cell.2025.03.002
OpenAlex
W4409108775
Cited by
41
References
6
Citations by year
2026: 19 · 2025: 20
FWCI
9.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
Funders
  • Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2022-I2M-2-004)
  • Novo Nordisk Foundation (NNF21OC0072070)
  • Novo Nordisk Foundation Center for Protein Research, University of Copenhagen (NNF24SA0098829, NNF14CC0001)
  • Natural Science Foundation of Jiangsu Province (BK20240443)
  • Novo Nordisk A/S (CELFFI-2022-002843)
  • Chinese Academy of Medical Sciences
  • Fundamental Research Funds for the Central Universities (2023-RC180-03)
  • Vetenskapsrådet (2022-00323, Dnr 2022-01185, 2023-00510)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ubiquitin and proteasome pathways
Keywords
protein turnover, single-cell proteomics, HeLa cells, iPSC differentiation, protein complexes, cell cycle, cell size, cell diameter, protein abundance
MeSH terms
Cell Differentiation, HeLa Cells, Histones, Humans, Isotope Labeling, Proteins, Proteome, Proteomics, Induced Pluripotent Stem Cells, Single-Cell Analysis

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