Metabolomic profiling of heat-stressed grape berries 

Improving our knowledge on biotic and abiotic factors that influence the composition of the grapevine mycobiome is of great agricultural significance, due to potential effects on plant health, productivity, and wine characteristics. Among the various environmental factors affecting the morphological, physiological, biochemical and molecular attributes of grapevine, drought stress is one of the most severe, becoming increasingly an issue worldwide.

Bacterial antibiotic resistance is a major current health problem. Polyphenols have demonstrated antibacterial activity, and in this work we studied the effect of oenological polyphenols on the growth of intestinal multidrug-resistant strains of human and animal origin. Two Enterococcus faecium strains, resistant to vancomycin and other antibiotics, and four Escherichia coli strains, resistant to ampicillin and other antibiotics, were included in this study. All strains showed multidrug resistant phenotypes and genotypes to at least two antibiotic families.

In grapevine, phenology from bud break to berry maturation, depends on temperature and water availability. Increases in average temperatures accelerates initiation of bud break, exposing newly formed shoots to detrimental environmental stresses. It is therefore essential to identify genotypes that could delay phenology in order to adapt to the environment. The use of different rootstocks has been applied to change scion’s characteristics, to adapt and resist to abiotic and biotic stresses[1].

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.

The presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.