A novel approach for the identification of new biomarkers of wine consumption in human urine using untargeted metabolomics

Wine, a sensitive and intricate agricultural product, is being affected by climate change, which accelerates grapevine phenological stages and alters grape composition and ripening. This influences the synthesis of key aroma compounds, shaping wine’s sensory attributes [1]. The complex aroma profile, resulting from compound interactions, presents a metabolomics challenge to identify these indicators and their environmental change responses, which is being addressed using diverse analytical techniques.

The increasingly frequent heat waves during grape ripening pose challenges for premium wine grape production. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 and 2022 using Manto negro wine grapes to study the effect of two irrigation strategies and different light exposure levels on grape quality.

Two of the most harmful microbial metabolites for human health that can be present in wines and either fermented or raw foods are biogenic amines (BA) and ochratoxine A (OTA). Winemakers are aware of the need to avoid their presence in wine by using different strategies, one of them is the use of enzymes. Some recombinant laccases have been characterized and revealed as potential tools to degrade these toxic compounds in wine[1], specifically biogenic amines[2].

Cover cropping in vineyard is a sustainable and alternative soil management system to conventional tillage that is gaining more and more importance among winegrowers and is being promoted, among other organizations, by the European Union through the eco-schemes of the Common Agricultural Policy.
However, the use of cover crops in Mediterranean viticultural environments is conditioned, to a large extent, by the availability of irrigation water which, in a context of global warming like the one we are experiencing, must be adjusted to savings strategies, supplying to the vine only what it needs in each moment.

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.