Mining microbiome data to identify antagonists of grapevine downy mildew (Plasmopara viticola)

Secondary (or specialised) metabolites such as terpenes and phenolic compounds are produced by plants for various roles which include defence against pathogens and herbivores, protection against abiotic stress, and plant signalling. Additionally, these metabolites influence grapevine quality traits such as colour, aroma, taste, and nutritional value. However, the biosynthesis of these metabolites is often complex and controlled by multiple genes which in grapevine are predominantly uncharacterised.

Global climate change is currently affecting vine phenology and causing a decoupling between technological and phenolic maturity of the grapes [1]. Wine industry has to face the challenge of making quality wines from grapes with an unbalanced phenolic composition.

Plants have evolved different strategies to cope with environmental stresses and, although still debated, it was observed that they can remember past stress occurrence.
Anatomical and physiological adjustments have been observed in different grapevine cultivars after repeated drought exposure, however epigenetic, transcriptional and biochemical changes associated with drought-primed ecological memory have been poorly studied.
This work was conceived to test whether exposure to recurring events of mild drought could prime vines to endure severe drought stress. Particularly, we investigated whether the expected improved stress tolerance of Vitis vinifera cv Nebbiolo plants subjected over years to moderate and long-lasting water stress events (WS-primed) depended on molecular memory phenomena or on resetting of stress-induced signals.

Bayesian networks are widely used for knowledge representation and reasoning under uncertainty in natural resource management. We propose here a probabilistic model able to assess the quality of a vineyard. There is a rising interest for this methodology as tool for ecological and agronomic modelling.

In the context of climate change and the need to reduce inputs, optimising photosynthesis and grapevine performance requires a better understanding of the interactions between water status, nitrogen availability, and source-sink relationships.