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Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry

Author

Listed:
  • Sofani Tafesse Gebreyesus

    (Academia Sinica
    Academia Sinica
    National Taiwan University)

  • Asad Ali Siyal

    (Academia Sinica
    Academia Sinica
    National Tsing Hua University)

  • Reta Birhanu Kitata

    (Academia Sinica)

  • Eric Sheng-Wen Chen

    (Academia Sinica)

  • Bayarmaa Enkhbayar

    (Academia Sinica
    Academia Sinica)

  • Takashi Angata

    (Academia Sinica)

  • Kuo-I Lin

    (Academia Sinica)

  • Yu-Ju Chen

    (Academia Sinica
    National Taiwan University
    Academia Sinica
    Academia Sinica and National Taiwan University)

  • Hsiung-Lin Tu

    (Academia Sinica
    Academia Sinica
    Academia Sinica
    Academia Sinica and National Taiwan University)

Abstract

Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and

Suggested Citation

  • Sofani Tafesse Gebreyesus & Asad Ali Siyal & Reta Birhanu Kitata & Eric Sheng-Wen Chen & Bayarmaa Enkhbayar & Takashi Angata & Kuo-I Lin & Yu-Ju Chen & Hsiung-Lin Tu, 2022. "Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-021-27778-4
    DOI: 10.1038/s41467-021-27778-4
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    References listed on IDEAS

    as
    1. Ruedi Aebersold & Matthias Mann, 2016. "Mass-spectrometric exploration of proteome structure and function," Nature, Nature, vol. 537(7620), pages 347-355, September.
    2. Elly Sinkala & Elodie Sollier-Christen & Corinne Renier & Elisabet Rosàs-Canyelles & James Che & Kyra Heirich & Todd A. Duncombe & Julea Vlassakis & Kevin A. Yamauchi & Haiyan Huang & Stefanie S. Jeff, 2017. "Profiling protein expression in circulating tumour cells using microfluidic western blotting," Nature Communications, Nature, vol. 8(1), pages 1-12, April.
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    Cited by:

    1. Fengchao Yu & Guo Ci Teo & Andy T. Kong & Klemens Fröhlich & Ginny Xiaohe Li & Vadim Demichev & Alexey I. Nesvizhskii, 2023. "Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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