RESUMEN
Tomato is a major crop suffering substantial yield losses from diseases, as fruit decay at a postharvest level can claim up to 50% of the total production worldwide. Due to the environmental risks of fungicides, there is an increasing interest in exploiting plant immunity through priming, which is an adaptive strategy that improves plant defensive capacity by stimulating induced mechanisms. Broad-spectrum defence priming can be triggered by the compound ß-aminobutyric acid (BABA). In tomato plants, BABA induces resistance against various fungal and bacterial pathogens and different methods of application result in durable protection. Here, we demonstrate that the treatment of tomato plants with BABA resulted in a durable induced resistance in tomato fruit against Botrytis cinerea, Phytophthora infestans and Pseudomonas syringae. Targeted and untargeted metabolomics were used to investigate the metabolic regulations that underpin the priming of tomato fruit against pathogenic microbes that present different infection strategies. Metabolomic analyses revealed major changes after BABA treatment and after inoculation. Remarkably, primed responses seemed specific to the type of infection, rather than showing a common fingerprint of BABA-induced priming. Furthermore, top-down modelling from the detected metabolic markers allowed for the accurate prediction of the measured resistance to fruit pathogens and demonstrated that soluble sugars are essential to predict resistance to fruit pathogens. Altogether, our results demonstrate that metabolomics is particularly insightful for a better understanding of defence priming in fruit. Further experiments are underway in order to identify key metabolites that mediate broad-spectrum BABA-induced priming in tomato fruit.
RESUMEN
In comparison to the exponential increase of genotyping methods, phenotyping strategies are lagging behind in agricultural sciences. Genetic improvement depends upon the abundance of quantitative phenotypic data and the statistical partitioning of variance into environmental, genetic, and random effects. A metabolic phenotyping strategy was adapted to increase sample throughput while saving reagents, reducing cost, and simplifying data analysis. The chemical profiles of stem extracts from maize plants grown under low nitrogen (LN) or control trial (CT) were analyzed using optimized protocols for direct-injection electrospray ionization mass spectrometry (DIESI-MS). Specific ions significantly decreased or increased because of environmental (LN versus CT) or genotypic effects. Biochemical profiling with DIESI-MS had a superior cost-benefit compared to other standard analytical technologies (e.g., ultraviolet, near-infrared reflectance spectroscopy, high-performance liquid chromatography, and gas chromatography with flame ionization detection) routinely used for plant breeding. The method can be successfully applied in maize, strawberry, coffee, and other crop species.