Bibliographic Details
| Title: |
Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell. |
| Authors: |
Wang, Yu, Guan, Zhi-Ying, Shi, Shao-Wen, Jiang, Yi-Rong, Zhang, Jie, Yang, Yi, Wu, Qiong, Wu, Jie, Chen, Jian-Bo, Ying, Wei-Xin, Xu, Qin-Qin, Fan, Qian-Xi, Wang, Hui-Feng, Zhou, Li, Wang, Ling, Fang, Jin, Pan, Jian-Zhang, Fang, Qun |
| Source: |
Nature Communications; 2/10/2024, Vol. 15 Issue 1, p1-13, 13p |
| Subject Terms: |
AMINO acid sequence, PROTEINS, HELA cells, CELL migration, WORKFLOW, PROTEOMICS |
| Abstract: |
The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449–3500, 2278–3257 and 1621–2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight. Single-cell proteomics is of fundamental importance to capture biological heterogeneity, while limited in proteome depth. Here, the authors develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep coverage of quantifying up to 3000 protein groups in a mammalian cell. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |
