Global analysis of protein turnover dynamics in single cells
Single-cell proteomics (SCPs) has advanced significantly, yet it remains largely unidimensional, focusing primarily on protein abundances. In this study, we employed a pulsed stable isotope labeling by amino acids in cell culture (pSILAC) approach to simultaneously analyze protein abundance and turnover in single cells (SC-pSILAC). Using a state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ∼4,000 proteins in single HeLa cells recapitulating known biology. We performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSCs) encompassing 6 sampling times over 2 months and analyzed >1,000 cells. Protein turnover dynamics highlighted differentiation-specific co-regulation of protein complexes with core histone turnover, discriminating dividing and non-dividing cells. Lastly, correlating cell diameter with the abundance of individual proteins showed that histones and some cell-cycle proteins do not scale with cell size. The SC-pSILAC method provides a multidimensional view of protein dynamics in single-cell biology.
Authors
- Zilu Ye (ORCID: https://orcid.org/0000-0001-8829-6579)
- Karl‐Henrik Grinnemo (ORCID: https://orcid.org/0000-0002-6100-6209)
- Anjali Seth (ORCID: https://orcid.org/0000-0003-4701-2562)
- Ulises H. Guzmán (ORCID: https://orcid.org/0000-0003-1665-7659)
- Fabiana Izaguirre (ORCID: https://orcid.org/0009-0008-5335-0780)
- Pierre Sabatier (ORCID: https://orcid.org/0000-0002-2734-1791)
- Jesper Velgaard Olsen (ORCID: https://orcid.org/0000-0002-4747-4938)
- Longteng Wang (ORCID: https://orcid.org/0000-0002-0904-8081)
- Sergey Rodin (ORCID: https://orcid.org/0000-0002-6954-1986)
- Maico Lechner (ORCID: https://orcid.org/0009-0006-7471-6003)
- Olga Gritsenko
- Xinlei Zeng
- Christian M Beusch
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Novo Nordisk Foundation (DK)
- Suzhou Institute of Systems Medicine (CN)
- Xijing Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- Cell
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1016/j.cell.2025.03.002
- Citations
- 22
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 16.64