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 separation as well as collision cross section (CCS) determination. In order to apply such an approach to a synthetic biology 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 time-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. Creating a useful database containing DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that 86% of the 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 which is commonly performed in synthetic biology.
Eleanor Sinclair University of Manchester
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