The impact of branched chain and aromatic amino acids on fermentation kinetics and aroma biosynthesis by wine yeast Saccharomyces cerevisiae

Contribution Sparkling wines elaborated following the traditional method undergo a second fermentation in closed bottles of base wines, followed by aging of wines with lees for at least 9 months. Most of the sparkling wines elaborated are white and rosé ones, although the production of red ones is highly increasing. One of the initial problems in red sparkling wine processing is to obtain suitable base wines that should have moderate alcohol content and astringency and adequate color intensity; which is difficult to obtain when grapes must be harvested at low phenolic and industrial maturity stage. The low phenolic maturity degree in the red grapes makes essential to choose an adequate winemaking methodology to obtain the base wines because the extracted polyphenols will vary according the winemaking technique: carbonic maceration or destemmed-crushed grapes.

A method of suspect screening analysis to study grape metabolomics, was developed [1]. By performing ultra-high performance liquid chromatography (UHPLC) – high-resolution mass spectrometry (HRMS) analysis of the grape extract, averaging 320-450 putative grape compounds are identified which include mainly polyphenols. Identification of metabolites is performed by a new HRMS-database of putative grape and wine compounds expressly constructed (GrapeMetabolomics) which currently includes around 1,100 entries.

Malolactic fermentation (MLF) is a secondary step in the vinification process and it follows alcoholic fermentation (AF) which is predominantly carried out by Saccharomyces cerevisiae. These two processes result in the degradation of metabolites to produce secondary metabolites which also contribute to the final wine flavour and quality. AF results in the production of ethanol and carbon dioxide from sugars and MLF stems from the degradation of L-malic acid (a dicarboxylic acid) to L-lactic acid (a monocarboxylic acid). The latter process results in a smoother texture as the acidity of the wine is reduced by the process, it also adds to the flavour complexity of the wine.

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.

Polyphenols are present in a wide variety of plants and foods such as tea, cacao and grape1. An important sub-class of these compounds is the flavanols present in grapes and wines as monomers (e.g (+)-catechin or (-)-epicatechin), or polymers also called condensed tannins or proanthocyanidins. They have important antioxidant properties2 but their biosynthesis remains partly unknown. Some recent studies have focused on the role of glycosylated intermediates that are involved in the transport of the monomers and may serve as precursors in the polymerization mechanism3, 4. The global objective of this work is to identify flavanol glycosides in grapes or wines, describe their structure and determine their abundance during grape development and in wine.