A multi-organ metabolic model of tomato predicts plant responses to nutritional and genetic perturbations.

Predicting and understanding plant responses to perturbations require integrating the interactions between nutritional sources, genes, cell metabolism, and physiology in the same model. This can be achieved using metabolic modeling calibrated by experimental data. In this study, we developed a multi-organ metabolic model of a tomato (Solanum lycopersicum) plant during vegetative growth, named Virtual Young TOmato Plant (VYTOP) that combines genome-scale metabolic models of leaf, stem and root and integrates experimental data acquired from metabolomics and high-throughput phenotyping of tomato plants. It is composed of 6,689 reactions and 6,326 metabolites. We validated VYTOP predictions on five independent use cases. The model correctly predicted that glutamine is the main organic nutrient of xylem sap. The model estimated quantitatively how stem photosynthetic contribution impacts exchanges between the different organs. The model was also able to predict how nitrogen limitation affects vegetative growth and the metabolic behavior of transgenic tomato lines with altered expression of core metabolic enzymes. The integration of different components, such as a metabolic model, physiological constraints, and experimental data, generates a powerful predictive tool to study plant behavior, which will be useful for several other applications, such as plant metabolic engineering or plant nutrition.

Unravelling physiological signatures of tomato bacterial wilt and xylem metabolites exploited by Ralstonia solanacearum.

The plant pathogen Ralstonia solanacearum uses plant resources to intensely proliferate in xylem vessels and provoke plant wilting. We combined automatic phenotyping and tissue/xylem quantitative metabolomics of infected tomato plants to decipher the dynamics of bacterial wilt. Daily acquisition of physiological parameters such as transpiration and growth were performed. Measurements allowed us to identify a tipping point in bacterial wilt dynamics. At this tipping point, the reached bacterial density brutally disrupts plant physiology and rapidly induces its death. We compared the metabolic and physiological signatures of the infection with drought stress, and found that similar changes occur. Quantitative dynamics of xylem content enabled us to identify glutamine (and asparagine) as primary resources R. solanacearum consumed during its colonization phase. An abundant production of putrescine was also observed during the infection process and was strongly correlated with in planta bacterial growth. Dynamic profiling of xylem metabolites confirmed that glutamine is the favoured substrate of R. solanacearum. On the other hand, a triple mutant strain unable to metabolize glucose, sucrose and fructose appears to be only weakly reduced for in planta growth and pathogenicity.