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Identification of tagged glycans with a protein nanopore

Author

Listed:
  • Minmin Li

    (Chinese Academy of Sciences
    East China University of Technology)

  • Yuting Xiong

    (Chinese Academy of Sciences
    East China University of Technology)

  • Yuchen Cao

    (Chinese Academy of Sciences)

  • Chen Zhang

    (Ganjiang Chinese Medicine Innovation Center)

  • Yuting Li

    (Ganjiang Chinese Medicine Innovation Center)

  • Hanwen Ning

    (Zhongnan University of Economics and Law)

  • Fan Liu

    (Chinese Academy of Sciences)

  • Han Zhou

    (Chinese Academy of Sciences
    Ganjiang Chinese Medicine Innovation Center)

  • Xiaonong Li

    (Ganjiang Chinese Medicine Innovation Center)

  • Xianlong Ye

    (Ganjiang Chinese Medicine Innovation Center)

  • Yue Pang

    (Liaoning Normal University)

  • Jiaming Zhang

    (Zhongnan University of Economics and Law)

  • Xinmiao Liang

    (Chinese Academy of Sciences
    Ganjiang Chinese Medicine Innovation Center)

  • Guangyan Qing

    (Chinese Academy of Sciences)

Abstract

Structural complexity of glycans derived from the diversities in composition, linage, configuration, and branching considerably complicates structural analysis. Nanopore-based single-molecule sensing offers the potential to elucidate glycan structure and even sequence glycan. However, the small molecular size and low charge density of glycans have restricted direct nanopore detection of glycan. Here we show that glycan sensing can be achieved using a wild-type aerolysin nanopore by introducing a facile glycan derivatization strategy. The glycan molecule can induce impressive current blockages when moving through the nanopore after being connected with an aromatic group-containing tag (plus a carrier group for the neutral glycan). The obtained nanopore data permit the identification of glycan regio- and stereoisomers, glycans with variable monosaccharide numbers, and distinct branched glycans, either independently or with the use of machine learning methods. The presented nanopore sensing strategy for glycans paves the way towards nanopore glycan profiling and potentially sequencing.

Suggested Citation

  • Minmin Li & Yuting Xiong & Yuchen Cao & Chen Zhang & Yuting Li & Hanwen Ning & Fan Liu & Han Zhou & Xiaonong Li & Xianlong Ye & Yue Pang & Jiaming Zhang & Xinmiao Liang & Guangyan Qing, 2023. "Identification of tagged glycans with a protein nanopore," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37348-5
    DOI: 10.1038/s41467-023-37348-5
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    References listed on IDEAS

    as
    1. Buddini Iroshika Karawdeniya & Y. M. Nuwan D. Y. Bandara & Jonathan W. Nichols & Robert B. Chevalier & Jason R. Dwyer, 2018. "Surveying silicon nitride nanopores for glycomics and heparin quality assurance," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    2. J. Hofmann & H. S. Hahm & P. H. Seeberger & K. Pagel, 2015. "Identification of carbohydrate anomers using ion mobility–mass spectrometry," Nature, Nature, vol. 526(7572), pages 241-244, October.
    3. Parisa Bayat & Charlotte Rambaud & Bernard Priem & Matthieu Bourderioux & Mélanie Bilong & Salomé Poyer & Manuela Pastoriza-Gallego & Abdelghani Oukhaled & Jérôme Mathé & Régis Daniel, 2022. "Comprehensive structural assignment of glycosaminoglycan oligo- and polysaccharides by protein nanopore," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Chan Cao & Nuria Cirauqui & Maria Jose Marcaida & Elena Buglakova & Alice Duperrex & Aleksandra Radenovic & Matteo Dal Peraro, 2019. "Single-molecule sensing of peptides and nucleic acids by engineered aerolysin nanopores," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
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