Genome-scale metabolic modelling also holds great promise to study plant-pathogen interactions. This computational systems biology perspective implies structural and comparative genomics, transcriptomics, and protein-protein interactions [167]. The calculation of metabolite coefficients for genome-scale metabolic flux predictions requires highresolution metabolome **data** (easily provided by today's Orbitrap and Q-TOF technologies) and high-resolution temporal sampling, as emphasized by a typical experimental design of phytopathological metabolomics (Figure 1). In this context, genome-scale metabolic models of potato and tomato leaves and Phytophthora have simulated the metabolic fluxes during infection [121,168]. Interesting molecular aspects, involving photosynthesis suppression by the pathogen, were demonstrated, as well as the uptake of nutrients by Phytophthora following the infection cycle phases. It should be noted that stage-specific profiles of the joint metabolism of the host and pathogen could be refined by integrating high-resolution **data** from the tomato infection metabolome [121].