Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics

Abstract

Metabolomics aims at the comprehensive identification of metabolites in complex mixtures to characterize the state of a biological system and elucidate their roles in biochemical pathways. For many biological samples, a large number of spectral features observed by NMR spectroscopy and mass spectrometry (MS) belong to unknowns, i.e., these features do not belong to metabolites that have been previously identified, and their spectral information is not available in databases. By combining NMR, MS, and combinatorial cheminformatics, the analysis of unknowns can be pursued in complex mixtures requiring minimal purification. This chapter describes the SUMMIT MS/NMR approach covering sample preparation, NMR and MS data collection and processing, and the identification of likely unknowns with the use of cheminformatics tools and the prediction of NMR spectral properties.

Keywords: 3D NMR HSQC-TOCSY; COLMAR database; FT-ICR MS; Metabolite structure elucidation; Metabolomics; NMR-MS hybrid approach; SUMMIT MS/NMR; Unknown metabolite identification; Unknowns.