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Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics

Author

Listed:
  • Zhiwei Zhou

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Mingdu Luo

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xi Chen

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yandong Yin

    (Chinese Academy of Sciences)

  • Xin Xiong

    (Chinese Academy of Sciences)

  • Ruohong Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Zheng-Jiang Zhu

    (Chinese Academy of Sciences)

Abstract

The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility – mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5–2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.

Suggested Citation

  • Zhiwei Zhou & Mingdu Luo & Xi Chen & Yandong Yin & Xin Xiong & Ruohong Wang & Zheng-Jiang Zhu, 2020. "Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18171-8
    DOI: 10.1038/s41467-020-18171-8
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    Cited by:

    1. Zhiwei Zhou & Mingdu Luo & Haosong Zhang & Yandong Yin & Yuping Cai & Zheng-Jiang Zhu, 2022. "Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Mingdu Luo & Yandong Yin & Zhiwei Zhou & Haosong Zhang & Xi Chen & Hongmiao Wang & Zheng-Jiang Zhu, 2023. "A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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