Current trends in ŒNO-NMR based metabolomics

Abstract

Present work discusses strengths and limitations of two Nuclear Magnetic Resonance outliers obtained with a water-to-ethanol solvent multi pre saturation acquisition method, recently included in the Compendium of International Methods of Analysis of Wines and Musts, published as OIV-MA-AS316-01, and their accuracy for metabolomics analysis. Furthermore, it is also presented an alternative to produce more discriminant and sensitive NMR data matrices for metabolomics studies, comprising the use of a novel NMR acquisition strategy in wines, the double pulsed-field gradient echo (DPFGE) NMR scheme, with a refocusing band-selective uniform-response pure-phase selective pulse, for a selective excitation of the 5-10 ppm chemical shift range of wine samples, that reveals novel broad aromatic 1H resonances, directly associated to complex polyphenols. Both aromatics and full binned OIV-MA-AS316-01,as well as the selective 5-10 ppm DPFGE NMR outliers were statistically analyzed with diverse non-supervised Principal Component Analysis (PCA) and supervised Partial Least Squares -Discriminant Analysis (PLS-DA), sparse (sPLS-DA) least squares- discriminant analysis, and orthogonal projections to latent structures discriminant analysis (OPLS-DA). Supervised multivariate statistical analysis of DPFGE and aromatics’ binned OIV-MA-AS316-01NMR data have shown their robustness to broadly discriminate geographical origins and narrowly differentiate between different fermentation schemes of wines from identical variety and region.