RESUMO
Algae biomass is formed by an extremely complex set of metabolites, and its molecular characterization has been very challenging. We report the characterization of microalgae extracts via traveling wave ion mobility-mass spectrometry (TWIM-MS) by two different analysis strategies. First, the extracts were analyzed by direct infusion electrospray ionization (ESI) with no previous chromatographic separation (DI-ESI-TWIM-MS). Second, the samples were screened for metabolites and lipids using an untargeted high-throughput method that employs ultrahigh-performance liquid chromatography (UHPLC) using data-independent analysis (DIA) - MSE (UHPLC-HDMSE). Sixteen different microalgae biomasses were evaluated by both strategies. DI-ESI-TWIM-MS was able, via distinct drift times, to set apart different classes of metabolites, with the differences in the profiles of each microalga readily evident. With the UHPLC-HDMSE approach, 1251 different compounds were putatively annotated across 16 samples with 210 classified as lipids. From the normalized abundance for each annotated compound category, a detailed profiling in terms of metabolites, lipids, and lipid classes of each sample was performed. The reported workflow represents a powerful tool to determine the most suitable biotechnological applications for a given alga type and may allow for real-time monitoring of the algae composition distribution as a function of growth conditions, feedstocks, and the like. The determination of collision cross section results in improved confidence in the identification of triacylglycerols in samples, highly applicable to biofuels production. The two analysis strategies explored in this work offer powerful tools for the biomass industry by aiding in the identification of ideal strains and culture conditions for a specific application, saving analysis time and facilitating identification of a large number of constituents at once.
