Several case studies have demonstrated the successful application of metabolomics in investigating plant-pathogen interactions. For example, a study by de Vos et al. ( ) used LC-MS to investigate the metabolic changes in Arabidopsis thaliana leaves infected with the bacterial pathogen Pseudomonas syringae . The authors identified several metabolites, such as glucosinolates and phenylpropanoids, that accumulated in response to infection and contributed to plant defense. Similarly, a study by used GC-MS and LC-MS to investigate the metabolic changes in tomato roots infected with the fungal pathogen Fusarium oxysporum f. sp. lycopersici . The authors identified several metabolites, including amino acids and organic acids, that were differentially accumulated in resistant and susceptible tomato cultivars, indicating their potential role in disease resistance. Another study by used LC-MS to investigate the metabolic changes in tomato plants infected with the fungal pathogen Fusarium oxysporum f. sp. lycopersici . The authors identified several metabolites, such as flavonoids and glycoalkaloids, that were differentially accumulated in resistant and susceptible tomato genotypes and could potentially be used as biomarkers for resistance breeding. Moreover, a study by O'Donnell et al. ( ) used CE-MS to investigate the metabolic responses of Arabidopsis thaliana to infection by the bacterial pathogen Pseudomonas syringae . The authors identified several metabolites, including amino acids and organic acids, that were involved in plant defense responses and could serve as targets for developing disease-resistant plants. These case studies highlight the power of metabolomics in unraveling the complex metabolic interactions between plants and their pathogens and provide valuable insights for developing disease-resistant crops.