丹麦哥本哈根大学Jesper V. Olsen小组研究出单细胞蛋白质周转动力学的全局分析。这一研究成果发表在2025年3月31日出版的国际学术期刊《细胞》上。

在这项研究中，研究团队采用脉冲稳定同位素标记的氨基酸在细胞培养（pSILAC）的方法，同时分析蛋白质丰度和单细胞（SC-pSILAC）的周转率。使用最先进的SCP工作流程，课题组研究人员证明了两个SILAC标签可以从单个HeLa细胞中的约4,000个蛋白质中检测到，概括了已知的生物学。研究人员对人类诱导多能干细胞（iPSCs）的定向分化进行了大规模的时间序列SC-pSILAC分析，包括6次采样，超过2个月，分析了1000个细胞。蛋白质周转动力学强调了与核心组蛋白周转的蛋白质复合物的分化特异性协同调节，区分分裂和非分裂细胞。最后，将细胞直径与单个蛋白质的丰度相关联表明，组蛋白和一些细胞周期蛋白不随细胞大小而变化。SC-pSILAC方法提供了单细胞生物学中蛋白质动力学的多维视图。

据悉，单细胞蛋白质组学（SCPs）已经取得了显著的进步，但它在很大程度上仍然是单维的，主要集中在蛋白质丰度上。

附：英文原文

Title: Global analysis of protein turnover dynamics in single cells

Author: Pierre Sabatier, Maico Lechner, Ulises H. Guzmán, Christian M. Beusch, Xinlei Zeng, Longteng Wang, Fabiana Izaguirre, Anjali Seth, Olga Gritsenko, Sergey Rodin, Karl-Henrik Grinnemo, Zilu Ye, Jesper V. Olsen

Issue&Volume: 2025-03-31

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.

DOI: 10.1016/j.cell.2025.03.002

Source: https://www.cell.com/cell/abstract/S0092-8674(25)00275-2