Liquid chromatography-quadrupole time of flight tandem mass spectrometry-based targeted metabolomic study for varietal discrimination of grapes according to plant sterols content.
Grapevine and derived products are rich in a wide range of compounds and its quality mainly depends on its metabolites, as a result of viticulture practices. Plant sterols, also called phytosterols (PS), are secondary metabolites regarded as bioactive substance present in grape berries and other plant-based food. The present study deals with a metabolomic approach focusing on phytosterols family in six varieties of Rioja grapes (Cabernet Sauvignon, Tempranillo, Graciano, Garnacha, White Garnacha and Viura), in order to find significant differences among them. Liquid chromatography- mass spectrometry with a quadrupole-time of flight mass analyzer (LC-QTOF) was used to find as many metabolites as possible in the different grape berry fractions, and using statistics to help finding significant clustering of the metabolic profile of pulp, peel and seeds in relation to the variety. The best chromatographic and detection conditions were achieved by gas phase ionization via atmospheric pressure chemical ionization (APCI) in positive mode. Furthermore, analysis with electrospray (ESI) is also needed for phytosterol derivatives confirmation. Putative compounds of interest in the analyzed samples were found by an automated compound extraction algorithm (Molecular Feature Extraction, MFE) and an initial differential expression from the data was created with the aid of commercial software. Once the data were collected, the results were filtered, aligned and normalized, and evaluating applying one-way analysis of variance (ANOVA) with a 95% significance level. For sample class prediction, partial least square-discriminant analysis (PLS-DA) is used as a supervised pattern recognition method and excellent separation among the grape varieties is shown. An overall accuracy of 93.3% (pulp samples), 100.0% (peel) or 96.7% (seeds) in discriminating between grape varieties was achieved when comparing the different fractions. In general, 7 PS derivatives were identified with ID scores higher than 84%.
Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country UPV/EHU, E-01006 Vitoria-Gasteiz, Spain.
Laura
L
Millán
Central Service of Analysis of Alava, SGIker, University of the Basque Country, UPV/EHU, E-01006 Vitoria-Gasteiz, Spain.
M Carmen
MC
Sampedro
Central Service of Analysis of Alava, SGIker, University of the Basque Country, UPV/EHU, E-01006 Vitoria-Gasteiz, Spain.
Alicia
A
Sánchez
Laboratory of Pharmaceutical Chemistry & Analytical Platform, Faculty of Pharmacy, Université Libre de Bruxelles (ULB), B-1050 Brussels, Belgium, Belgium.
Cédric
C
Delporte
Laboratory of Pharmaceutical Chemistry & Analytical Platform, Faculty of Pharmacy, Université Libre de Bruxelles (ULB), B-1050 Brussels, Belgium, Belgium.
Pierre
P
Van Antwerpen
Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country UPV/EHU, E-01006 Vitoria-Gasteiz, Spain.
M Aranzazu
MA
Goicolea
Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country UPV/EHU, E-01006 Vitoria-Gasteiz, Spain. Electronic address: r.barrio@ehu.es.
Ramón J
RJ
Barrio
D002853:Chromatography, Liquid / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D010840:Phytosterols / Q000032:analysis*; D053719:Tandem Mass Spectrometry / Q000379:methods*; D027843:Vitis / Q000737:chemistry*
D010840:Phytosterols
Grape metabolomics; Grape varieties; LC-QTOF; Phytosterols