工作流程
可扩展性
计算机科学
蛋白质组学
灵敏度(控制系统)
单细胞分析
炸薯条
计算生物学
细胞
化学
纳米技术
生物
材料科学
工程类
数据库
基因
电信
生物化学
电子工程
作者
Zilu Ye,Pierre Sabatier,Leander van der Hoeven,Maico Lechner,Teeradon Phlairaharn,Ulises H. Guzmán,Zhen Liu,Haoran Huang,Min Huang,Xiangjun Li,David Hartlmayr,Fabiana Izaguirre,Anjali Seth,Hiren J. Joshi,Sergey Rodin,Karl‐Henrik Grinnemo,Ole B. Hørning,Dorte B. Bekker‐Jensen,Nicolai Bache,Jesper V. Olsen
标识
DOI:10.1038/s41592-024-02558-2
摘要
Single-cell proteomics (SCP) promises to revolutionize biomedicine by providing an unparalleled view of the proteome in individual cells. Here, we present a high-sensitivity SCP workflow named Chip-Tip, identifying >5,000 proteins in individual HeLa cells. It also facilitated direct detection of post-translational modifications in single cells, making the need for specific post-translational modification-enrichment unnecessary. Our study demonstrates the feasibility of processing up to 120 label-free SCP samples per day. An optimized tissue dissociation buffer enabled effective single-cell disaggregation of drug-treated cancer cell spheroids, refining overall SCP analysis. Analyzing nondirected human-induced pluripotent stem cell differentiation, we consistently quantified stem cell markers OCT4 and SOX2 in human-induced pluripotent stem cells and lineage markers such as GATA4 (endoderm), HAND1 (mesoderm) and MAP2 (ectoderm) in different embryoid body cells. Our workflow sets a benchmark in SCP for sensitivity and throughput, with broad applications in basic biology and biomedicine for identification of cell type-specific markers and therapeutic targets.
科研通智能强力驱动
Strongly Powered by AbleSci AI