NMR- and UHPLC-MS-based metabolomics for the discrimination of different resistant Vitis vinifera L. cultivar woods

Abstract

Vitis cultivars exhibit different susceptibility to pathogens such as botrytis or downy mildew and the selection of resistant species is important for a sustainable wine production without use of harmful pesticides. In order to highlight biomarkers that can be related to Vitis resistance to common diseases, woods of resistant vitis cultivars were profiled by NMR and UHPLC-TOF-MS [1] and analysed based on differenzial metabolomics [2]. Three different samples of Vitis wood, one resistant to botrytis, one resistant to downy mildew and one susceptible to both phytopathogenic microorganisms were used in this study. The wood samples of specific specimens were divided in 18 groups (6 per cultivar) and extracted separately with EtOAc to offer statistical confidence. Two different sample preparation protocols were developed and applied in parallel for the NMR (600MHz) and UHPLC-TOF-MS analysis of the extracts, respectively. Multivariate data analysis using both supervised (PLS-DA) and unsupervised (PCA) methods and different scaling methods revealed a clear distinction between the three groups as well as in the discrimination between the two different resistant species. A high convergence regarding the discrimination patterns between NMR and UHPLC-TOF-MS data was obtained. The NMR and MS variables derived from the loading plots were attributed to specific biomarkers. This statistical model could be efficiently applied for the determination of resistant cultivars of Vitis as well as for the identification of novel biomarkers involved in resistance phenomena.