| Abstract | Microcystins (MCs) are a group of hepatotoxic heptapeptides that inhibit protein phosphatases, and are produced by many species of cyanobacteria. Most MCs contain the unusual β-amino acid “Adda5 ”, γ-linked D-Glu6, and N-methyldehydroalanine (Mdha 7) at positions 5–7, with more than 250 different microcystin congeners having been reported in the literature, and with new congeners being discovered regularly. In addition to methods capable of measuring total MCs or targeting known congeners, improved methods are needed for identifying new candidate MCs , to ensure the safety of recreational and drinking waters. Untargeted high resolution mass spectrometry (HRMS) methods allows for simultaneous analysis of a tens of thousands of known and unknown chemicals in complex biological or environmental samples. Typically, identification of novel MCs involves only LC–MS/MS analysis in positive ionization mode with detection of a characteristic fragment from Adda5 at m/z 135.0804. However, some MCs contain modified Addamoieties, or are otherwise modified to change the MS/MS conditions under which this fragment is generated, and are not readily detected in this manner. We have recently shown that thiol-derivatization of the Mdha7/Dha7 group in MCs is a highly effective method for identifying even trace amounts of novel MCs in complex matrices by LC–MS. Here, we present a new approach using metabolomics software for semi-automated detection of novel MCs based on mercaptoethanol derivatization, together with accurate mass detection of precursor and characteristic product ions in negative and positive ionization modes. Taken together, this approach targets any molecules containing Adda5, D-Glu6 or Mdha7/Dha7, one or more of which is present in every microcystin reported to date. Furthermore, it is these three residues that are in closest contact with the catalytic centre of protein phosphatases, and which appear to be most important for toxicity. HRMS methods using data independent acquisition scan modes were particularly well suited for this purpose, allowing for simultaneous acquisition of MS/MS data on all compounds detected. This type of data is also well suited to retrospective analysis of newly discovered MCs from previously acquired data. The application of microcystin immunoaffinity columns containing antibodies with broad specificity to the whole family of MCs (presentation by Samdal et al.) further enhances the utility of this metabolomics workflow. We demonstrate the power of the combination of these novel approaches with the identification of numerous novel MCs in field and culture samples as well as a blue-green algal matrix reference material. |
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