Early detection of Plasmopara viticola-infected leaves through FT-ICR-MS metabolic profiling

Abstract

Grapevine (Vitis vinifera L.) is one of the most important crops in the world. Domesticated V. vinifera cultivars frequently used for wine production are highly susceptible to different diseases, including downy mildew, one of the most destructive vineyard diseases, caused by Plasmopara viticola. Downy mildew affects all green parts of the vine, causing yield reduction and significant production losses. To cope with this threat, the application of chemical products is currently the mainly strategy, with severe environmental and economic costs. The development of alternative sustainable disease-control strategies is crucial. Early detection of infected plants is not easy, since observable disease symptoms normally appear 7-10 days after pathogen inoculation. Thus, the development of early detection techniques is very important to control downy mildew spread. In the present work, we followed an untargeted metabolomics approach using Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR-MS) to analyse the chemical profile of infected and non-infected grapevine leaves. Chemical formulas were used to build Van Krevelen diagrams and compositional space plots, which do not require full metabolite identification and provide an easy screening method. Based only on the chemical profile and representation plots, we were able to discriminate between infected and non-infected grapevine leaves as soon as 24 h post-inoculation. Moreover, our results show that lipids, carbohydrates and polyketides are the most altered metabolite groups in P. viticola-infected plants when compared with control samples.