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Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry

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  • Anne-Lise Marie

    (Northeastern University)

  • Yunfan Gao

    (Northeastern University)

  • Alexander R. Ivanov

    (Northeastern University)

Abstract

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5–500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Suggested Citation

  • Anne-Lise Marie & Yunfan Gao & Alexander R. Ivanov, 2024. "Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47772-w
    DOI: 10.1038/s41467-024-47772-w
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    References listed on IDEAS

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    1. Jennifer A. Prescher & Danielle H. Dube & Carolyn R. Bertozzi, 2004. "Chemical remodelling of cell surfaces in living animals," Nature, Nature, vol. 430(7002), pages 873-877, August.
    2. Valdemaras Petrosius & Pedro Aragon-Fernandez & Nil Üresin & Gergo Kovacs & Teeradon Phlairaharn & Benjamin Furtwängler & Jeff Op De Beeck & Sarah L. Skovbakke & Steffen Goletz & Simon Francis Thomsen, 2023. "Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
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