Interactions of wine polyphenols with dead or living Saccharomyces cerevisiae Yeast Cells and Cell Walls: polyphenol location by microscopy

A part, at least, of the fruity aroma of red wines is the consequence of perceptive interactions between various aromatic compounds, particularly ethyl esters and acetates, which may contribute to the perception of fruity aromas, specifically thanks to synergistic effects.1,2 The question of the indirect impact of non-fruity compounds on this particular aromatic expression has not yet been widely investigated. Among these compounds higher alcohols (HA) represent the main group, from a quantitative standpoint, of volatiles in many alcoholic beverages. Moreover, some bibliographic data suggested their contribution to the aromatic complexity by either increasing or masking flavors of wine, depending of their concentrations.

Leaf removal in the bunch zone is a common viticultural practice with several objectives, yet it has been difficult to conclusively link the physiological mechanism(s) and metabolic berry impact to this widely practiced treatment. We used a field-omics approach1 in a Sauvignon blanc high altitude model vineyard, showing that the early leaf removal in the bunch zone caused quantifiable and stable responses (over years) in the microclimate where the main perturbation was increased exposure. We provide an explanation for how leaf removal leads to the shifts in grape metabolites typically linked to this treatment and confirm anecdotal evidence and previous reports that leaf removal treatment at an early stage of berry development affects “quality-associated” metabolites (monoterpenes and norisoprenoids).

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.

Vitis vinifera L. is the most widely cultivated Vitis species which includes numerous cultivars. Owing to their superior quality of grapes, these cultivars were long considered the only suitable for the production of fine wines. However, the lack of resistance genes in V. vinifera against major grapevine pathogens, requires for its cultivation frequent spraying with large amount of fungicides. Thus, the search for alternative and more sustainable methods to control the grapevine pathogens have brought the breeders to focus their attention on other Vitis species. In fact, wild Vitis genotypes present multiple resistance traits against pathogens, such as powdery mildew, downy mildew and phylloxera.