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Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell

Author

Listed:
  • Yu Wang

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center
    Zhejiang University)

  • Zhi-Ying Guan

    (Zhejiang University)

  • Shao-Wen Shi

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Yi-Rong Jiang

    (Zhejiang University)

  • Jie Zhang

    (China Medical University)

  • Yi Yang

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Qiong Wu

    (Zhejiang University)

  • Jie Wu

    (Zhejiang University)

  • Jian-Bo Chen

    (Zhejiang University)

  • Wei-Xin Ying

    (Zhejiang University)

  • Qin-Qin Xu

    (Zhejiang University)

  • Qian-Xi Fan

    (Zhejiang University)

  • Hui-Feng Wang

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Li Zhou

    (Shanghai Omicsolution Co.)

  • Ling Wang

    (Shanghai Omicsolution Co.)

  • Jin Fang

    (China Medical University)

  • Jian-Zhang Pan

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Qun Fang

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center
    Zhejiang University)

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.

Suggested Citation

  • Yu Wang & Zhi-Ying Guan & Shao-Wen Shi & Yi-Rong Jiang & Jie Zhang & Yi Yang & Qiong Wu & Jie Wu & Jian-Bo Chen & Wei-Xin Ying & Qin-Qin Xu & Qian-Xi Fan & Hui-Feng Wang & Li Zhou & Ling Wang & Jin Fa, 2024. "Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45659-4
    DOI: 10.1038/s41467-024-45659-4
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