Self-Consistent Metabolic Mixture Analysis by Heteronuclear NMR. Application to a Human Cancer Cell Line

Abstract

Elucidation of the chemical composition of biological samples is a main focus of systems biology and metabolomics. In order to comprehensively study these complex mixtures, reliable, efficient, and automatable methods are needed to identify and quantify the underlying metabolites and natural products. Because of its rich information content, nuclear magnetic resonance (NMR) spectroscopy has a unique potential for this task. Here we present a generalization of the recently introduced homonuclear TOCSY-based DemixC method to heteronuclear HSQC-TOCSY NMR spectroscopy. The approach takes advantage of the high resolution afforded along the (13)C dimension due to the narrow (13)C line widths for the identification of spin systems and compounds. The method combines information from both 1D (13)C and (1)H traces by querying them against an NMR spectral database using our COLMAR query web server. The complementarity of (13)C and (1)H spectral information improves the robustness of compound identification. The method is demonstrated for a metabolic model mixture and is then applied to an extract from DU145 human prostate cancer cells.