Global analysis of protein turnover dynamics in single cells

Pierre Sabatier(Novo Nordisk Foundation), Maico Lechner(Novo Nordisk Foundation), Ulises H. Guzmán(Novo Nordisk Foundation), Christian M. Beusch(Uppsala University), Xinlei Zeng(Chinese Academy of Medical Sciences & Peking Union Medical College), Longteng Wang(Xijing Hospital), Fabiana Izaguirre(Rockefeller University), Anjali Seth(Rockefeller University), Olga Gritsenko(Uppsala University), Sergey Rodin(Uppsala University), Karl‐Henrik Grinnemo(Uppsala University), Zilu Ye(Chinese Academy of Medical Sciences & Peking Union Medical College), Jesper V. Olsen(Novo Nordisk Foundation)
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Abstract

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.


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