Combination of UHPLC-MS/MS-molecular networking approach and FTICR-MS for the metabolic profiling of Saccharomyces cerevisiae.

Natural products are a reliable source of bioactive molecules and represent an industrial and pharmaceutical stake. Indeed, the model yeast species Saccharomyces cerevisiae is a well-known eukaryotic organism largely used as a biotechnological tool, but still a topical subject of study. In this work, the exploration of Saccharomyces cerevisiae is taken further through an untargeted metabolomics workflow. The aim is to enrich databases and bring new information about the standard S. cerevisiae strain in a given medium. Analytical methods and bioinformatics tools were combined in a high-throughput methodology useable to dereplicate many types of biological extracts and cartography secondary metabolites. Ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analyses were carried out and spectral data were pre-processed to build molecular networks. Annotations were attributed to compounds through comparison with databases and manual investigation of networks. Ultra-high-resolution Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) brought additional information thanks to a higher dynamic range and enhanced UHPLC-MS/MS results by unveiling ambiguities and bringing accurate molecular formulae. Therefore, accurate and reliable annotated features resulted from the UHPLC-MS/MS data while FTICR-MS provided an overall cartography of metabolites thanks to van Krevelen diagrams. Various small molecules such as amino acids derivatives and indole alkaloids have been determined for the first time in this yeast. The complementarity of FTICR-MS and UHPLC-MS/MS for secondary metabolite annotation brought this new mapping of S. cerevisiae.