Improving knowledge about metabolites produced by the microbiota is a key point to understand its role in human health and disease. Among them, lipoamino acid (LpAA) containing asparagine and their derivatives are bacterial metabolites which could have an impact on the host. In this study, our aim was to extend the characterization of this family. We developed a semi-targeted workflow to identify and quantify new candidates. First, the sample preparation and analytical conditions using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) were optimized. Using a theoretical homemade database, HRMS raw data were manually queried. This strategy allowed us to find 25 new LpAA conjugated to Asn, Gln, Asp, Glu, His, Leu, Ile, Lys, Phe, Trp and Val amino acids. These metabolites were then fully characterized by MS2, and compared to the pure synthesized standards to validate annotation. Finally, a quantitative method was developed by LC coupled to a triple quadrupole instrument, and linearity and limit of quantification were determined. 14 new LpAA were quantified in gram positive bacteria, Lactobacilus animalis, and 12 LpAA in Escherichia coli strain Nissle 1917.
Keywords: Lipidomic; Lipoaminoacids; Mass spectrometry; Microbiota; Suspect screening.
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