Mobilising ion mobility mass spectrometry for metabolomics

Eleanor Sinclair, Katherine A. Hollywood, Cunyu Yan, Richard Blankley, Rainer Breitling, Perdita Barran

    Research output: Contribution to journalArticlepeer-review

    47 Downloads (Pure)


    Chromatography-based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite-specific fragments, all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional ion separation as well as collision cross section (CCS) determination. In order to apply such an approach to a metabolomics workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift tube-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. The value of DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that the CCS values found for 86% of metabolites measured in replicate have a relative standard deviation lower than 0.2%. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening.
    Original languageEnglish
    Pages (from-to)4783-4788
    Number of pages5
    JournalThe Analyst
    Issue number19
    Early online date20 Aug 2018
    Publication statusPublished - 7 Oct 2018

    Research Beacons, Institutes and Platforms

    • Photon Science Institute
    • Manchester Institute of Biotechnology


    Dive into the research topics of 'Mobilising ion mobility mass spectrometry for metabolomics'. Together they form a unique fingerprint.

    Cite this