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

Grapevine (Vitis spp.) is greatly influenced by climatic conditions and its economic value is therefore directly linked to environmental factors. Among these factors, temperature plays a critical role in vine phenology and fruit composition. In such conditions, elucidating the mechanisms employed by the vine to cope with heat waves becomes urgent. For the past few years, our research team has been producing molecular and metabolic data to highlight the molecular players involved in the response of the vine and the fruit to high temperatures [1]. Some of these temperature-sensitive genes are currently undergoing characterization using transgenesis approaches coupled or not with genome editing, taking advantage of the Microvine genotype [2].

Consumption of wine/alcoholic beverages remains a topic of great uncertainty and controversy worldwide. The term “no safe level” dominates the media communication and policy ever since population studies in 2018 [1,2] were published, which denied the existence of a J-curve and suggested that ANY consumption of an alcoholic beverage is harmful to health. The scientific evidence accumulated during the past decades about the health benefits of moderate wine consumption, were questioned and drinking guidelines considered to be too loose.

The first vineyards in Northern Europe were in Denmark in the 15th century, in the southern parts of Sweden and Finland in the 18th century at 55–60 degrees latitude. The grapes grown there have not been made into wine, but the grapes have been eaten at festive tables. The resurgence of viticulture has started with global warming, and currently the total area of viticulture in the Nordic countries, including Norway, is estimated to be 400–500 hectares, most of which is in Denmark. Southern Finland, like all southern parts of Northern Europe, belongs to the cool-cold winegrowing area.

Plant roots fulfil important functions as they are responsible for the acquisition of water and nutrients, for anchorage and stability, for interaction with symbionts and, in some cases, for the storage of carbohydrates. These functions are associated with the Root System Architecture (RSA, i.e. the form and the spatial arrangement of the roots in the soil). The RSA results from several biological processes (elongation, ramification, mortality…) genetically determined but with high structural plasticity.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).