IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-63075-0.html
   My bibliography  Save this article

A functionally tunable magnetic nanochains platform for N-glycoproteomic analysis of extracellular vesicles from ultratrace biofluids

Author

Listed:
  • Mingyang Li

    (Southeast University
    Nanjing Medical University)

  • Xiaorong Song

    (Southeast University)

  • Haixia Tu

    (Nanjing Medical University)

  • Jie Sun

    (Southeast University)

  • Yuanyuan Deng

    (Southeast University)

  • Bing Wang

    (Nanjing Medical University)

  • Yuhan Cai

    (Southeast University)

  • Yulian Wang

    (Nanjing Medical University)

  • Bin Li

    (Southeast University)

  • Yue Wang

    (Nanjing Medical University)

  • Xiangzheng Zhang

    (Nanjing Medical University)

  • Dong Wei

    (Southeast University)

  • Xiaoyu Yang

    (Nanjing Medical University)

  • Yueshuai Guo

    (Nanjing Medical University)

  • Xiang Li

    (Southeast University)

  • Jie Gu

    (Jiangnan University)

  • Jie Ni

    (Southeast University)

  • Yifan Zhou

    (Southeast University)

  • Zhongze Gu

    (Southeast University)

  • Zhuoying Xie

    (Southeast University)

  • Yan Li

    (Nanjing Medical University)

  • Xuejiang Guo

    (Nanjing Medical University
    Innovation Center of Suzhou Nanjing Medical University)

Abstract

Extracellular vesicles (EVs) carry complex glycoproteins critical mediators of disease progression and hold great potential for liquid biopsy applications. However, their low abundance presents significant analytical challenges. This study develop a versatile platform for EV N-glycoproteomic analysis (EVGpro), which enables tandem EV capture, EV protein digestion, and enrichment of N-glycopeptides. Functionalized magnetic nanochains with cell-penetrating peptides (octa-arginine, R8) enable efficient EV isolation, followed by on-chain hydrolysis to expose PEG2000 for ultrasensitive glycopeptide enrichment. The streamlined EVGpro platform identified up to 17 times more EV glycoproteins than ultracentrifugation across seven biofluids, profiling 398 EV glycoproteins from just 1 μL tear. Applied to seminal plasma, EVGpro uncover disease-specific glycoprotein signatures and identified previously unreported subtypes of asthenozoospermia. This robust and scalable approach advances the sensitive detection of disease biomarkers and molecular subtypes from diverse biofluids to enable precision medicine.

Suggested Citation

  • Mingyang Li & Xiaorong Song & Haixia Tu & Jie Sun & Yuanyuan Deng & Bing Wang & Yuhan Cai & Yulian Wang & Bin Li & Yue Wang & Xiangzheng Zhang & Dong Wei & Xiaoyu Yang & Yueshuai Guo & Xiang Li & Jie , 2025. "A functionally tunable magnetic nanochains platform for N-glycoproteomic analysis of extracellular vesicles from ultratrace biofluids," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63075-0
    DOI: 10.1038/s41467-025-63075-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-63075-0
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-63075-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ronghui Lou & Ye Cao & Shanshan Li & Xiaoyu Lang & Yunxia Li & Yaoyang Zhang & Wenqing Shui, 2023. "Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Xueguang Zhang & Gelin Huang & Ting Jiang & Lanlan Meng & Tongtong Li & Guohui Zhang & Nan Wu & Xinyi Chen & Bingwang Zhao & Nana Li & Sixian Wu & Junceng Guo & Rui Zheng & Zhiliang Ji & Zhigang Xu & , 2024. "CEP112 coordinates translational regulation of essential fertility genes during spermiogenesis through phase separation in humans and mice," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    3. Zhaoxiang Cai & Sofia Apolinário & Ana R. Baião & Clare Pacini & Miguel D. Sousa & Susana Vinga & Roger R. Reddel & Phillip J. Robinson & Mathew J. Garnett & Qing Zhong & Emanuel Gonçalves, 2024. "Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Hui Peng & He Wang & Weijia Kong & Jinyan Li & Wilson Wen Bin Goh, 2024. "Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Ute Distler & Han Byul Yoo & Oliver Kardell & Dana Hein & Malte Sielaff & Marian Scherer & Anna M. Jozefowicz & Christian Leps & David Gomez-Zepeda & Christine Toerne & Juliane Merl-Pham & Teresa K. B, 2025. "Multicenter evaluation of label-free quantification in human plasma on a high dynamic range benchmark set," Nature Communications, Nature, vol. 16(1), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63075-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.