Towards a More Reliable Identification of Isomeric Metabolites Using Pattern Guided Retention Validation

Reliable analyte identification is critical in metabolomics experiments to ensure proper interpretation of data. Due to chemical similarity of metabolites (as isobars and isomers) identification by mass spectrometry or chromatography alone can be difficult. Here we show that isomeric compounds are quite common in the metabolic space as given in common metabolite databases. Further, we show that retention information can shift dramatically between different experiments decreasing the value of external or even in-house compound databases. As a consequence the retention information in compound databases should be updated regularly, to allow a reliable identification. To do so we present a feasible and budget conscious method to guarantee updates of retention information on a regular basis using well designed compound mixtures. For this we combine compounds in “Ident-Mixes”, showing a way to distinctly identify chemically similar compounds through combinatorics and principle of exclusion. We illustrate the feasibility of this approach by comparing Gas chromatography (GC)–columns with identical properties from three different vendors and by creating a compound database from measuring these mixtures by Liquid chromatography–mass spectrometry (LC–MS). The results show the high influence of used materials on retention behavior and the ability of our approach to generate high quality identifications in a short time.