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- Saccharomyces cerevisiae oxidative response evaluation by cyclic voltammetry and gas chromatography−mass spectrometryPublication . Castro, Cristiana C.; Gunning, Caitriona; Oliveira, Carla M.; Couto, José A.; Teixeira, José A.; Martins, Rui C.; Ferreira, António C. SilvaThis study is focused on the evaluation of the impact of Saccharomyces cerevisiae metabolism in the profile of compounds with antioxidant capacity in a synthetic wine during fermentation. A bioanalytical pipeline, which allows for biological systems fingerprinting and sample classification by combining electrochemical features with biochemical background, is proposed. To achieve this objective, alcoholic fermentations of a minimal medium supplemented with phenolic acids were evaluated daily during 11 days, for electrochemical profile, phenolic acids, and the volatile fermentation fraction, using cyclic voltametry, high-performance liquid chromatography−diode array detection, and headspace/solid-phase microextraction/gas chromatography−mass spectrometry (target and nontarget approaches), respectively. It was found that acetic acid, 2- phenylethanol, and isoamyl acetate are compounds with a significative contribution for samples metabolic variability, and the electrochemical features demonstrated redox-potential changes throughout the alcoholic fermentations, showing at the end a similar pattern to normal wines. Moreover, S. cerevisiae had the capacity of producing chlorogenic acid in the supplemented medium fermentation from simple precursors present in the minimal medium.
- New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemakingPublication . Franco-Duarte, Ricardo; Umek, Lan; Mendes, Inês; Castro, Cristiana C.; Fonseca, Nuno; Martins, Rosa; Ferreira, António César Silva; Sampaio, Paula; Pais, Célia; Schuller, DoritDuring must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of mostcorrelated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.