4.8 Article

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

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-27778-4

Keywords

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Funding

  1. Ministry of Science and Technology [MOST 107-2113-M-001-032-MY3, MOST 107-2113-M-001-023-MY3, MOST 1102113-M-001-019-MY2, MOST 110-2113-M-001-020-MY3]
  2. Academia Sinica [ASTP-108-ML06, AS-iMATE-108-21]
  3. Academia Sinica, Taiwan

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Single-cell proteomics can reveal cellular heterogeneity and functional networks underlying biological processes. We present a streamlined workflow combining microfluidic chips and data-independent acquisition mass spectrometry for single-cell proteomic analysis. This workflow allows for efficient isolation, counting, imaging, and sample processing of cells in a single device, enabling the analysis of protein groups in individual mammalian cells. The chip-DIA workflow provides a basis for advanced single-cell proteomics applications.
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 similar to 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 <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

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