Fourier transform ion cyclotron resonance mass spectrometry for plant metabolite profiling and metabolite identification

J. William Allwood, David Parker, Manfred Beckmann, John Draper, Royston Goodacre

    Research output: Contribution to journalArticlepeer-review


    Mass spectrometry (MS) is usually the technique of choice for metabolomic studies where the volume of sample material is too limited for applications employing nuclear magnetic resonance (NMR) spectroscopy. With the advent of ultra-high accuracy mass spectrometers such as the Orbitrap (resolution 10 5) and the Fourier Transform Ion Cyclotron Resonance (FT-ICR) analysers (resolution potentially in excess of 10 6) there is the opportunity to generate an accurate mass fingerprint (often referred to as a profile since the variables are considered as effectively discrete) of an infused sample extract. In such data representations mass "peaks" are detected in the raw data and the centroid mass intensity calculated. The resolving power and sensitivity of these ultra-high accuracy mass analysers is such that metabolite signals from molecules containing naturally abundant elemental isotopes (e.g. 13C, 41K, 15N, 17O, 34S, and 37Cl) are visible in the data. Such is the instruments precision that it allows for the calculation of highly accurate elemental compositions for the unknown signals, thus aiding greatly in the selection of potential metabolite candidates for the annotation of unknowns prior to their confirmation by comparisons to analytical standards. The application of FT-ICR-MS to plant metabolomics has thus far been limited to a few studies and clear step-by-step methodologies are as yet unavailable. This chapter presents a rigorous method for the extraction and FT-ICR-MS analysis of plant leaf tissues as well as downstream data processing. © 2011 Springer Science+Business Media, LLC.
    Original languageEnglish
    Pages (from-to)157-176
    Number of pages19
    JournalMethods in Molecular Biology
    Publication statusPublished - 2012


    • CID
    • DI
    • ESI
    • FI
    • FT-ICR-MS
    • Plant metabolomics


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