Capture depletion of grapevine DNA: an approach to advance the study of microbial community in wine

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

“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.

Inactive dry yeast treatments in the vineyard are a tool used with the aim to improve the concentration and quality of secondary metabolites in grapes, leading to a better differentiation of the wines made from grapes differently treated. In this work, a foliar spraying treatment with yeast derivatives specifically designed to be used with the patent pending application technology of Lallemand Inc. Canada (LalVigne® Mature, Lallemand Inc., Montreal, Canada) was tested on Vitis vinifera L. cv. Barbera and Nebbiolo black winegrapes. The aim was to evaluate the effect of this treatment on the phenolic compounds accumulation, the skin physical-mechanical properties and the related phenolic extractability. Prior to analysis, the berries were sorted by flotation in order to evaluate their distribution by density class, and to determine the skin texture parameters of berries with different sugar contents, thus understanding also the ripening effect.

Limited information is available on grape wall-derived polymeric structure/composition and how this changes during fermentation. Commercial winemaking operations use enzymes that target the polysaccharide-rich polymers of the cell walls of grape tissues to clarify musts and extract pigments during the fermentations. In this study we have assessed changes in polysaccharide composition/ turnover throughout the winemaking process by applying recently developed cell wall profiling approaches to both wine and pomace polysaccharides. The methods included gas chromatography for monosaccharide composition (GC-MS), infra-red (IR) spectroscopy and comprehensive microarray polymer profiling
(CoMPP) using cell wall probes.

The assessment of red wine mouthfeel relies primarily on the sensory description of its tannic properties. This evaluation could be improved by gaining a better understanding of the physicochemical properties of these tannins. Hence, the objectives of the present study were threefold: (1) to gain an insight into the sensory properties of subpopulations of proanthocyanidic tannins of different molecular sizes obtained through several ultrafiltration steps, (2) to quantify the kinetics of haze formation of these proanthocyanidic tannins in a dynamic polyvinylpyrrolidone (PVP) precipitation test, (3) to determine whether a correlation exists between the sensory and the precipitation data.