Fusarium wilt in eggplant caused by F. oxysporum f. sp. melongenae is a major devastating soil-borne disease on a worldwide scale. Effectors play important roles in the interactions in pathogen-plant interactions. Identifying effectors is essential for elucidating the pathogenic mechanisms of phytopathogenic fungi. In this study, bioinformatic prediction approaches, including SignalP v5.0, TMHMM v2.0, WoLF PSORT, PredGPI, and EffectorP, were employed to screen for candidate secreted effector proteins (CSEPs) in F. oxysporum f. sp. melongenae. A total of 1019 proteins exhibiting characteristics typical of classical secretory proteins were identified, 301 of which demonstrated carbohydrate activity, and 194 CSEPs were identified. Furthermore, a total of 563 proteins from F. oxysporum f. sp. melongenae under induced conditions were identified using mass spectrometry-based label-free quantitative proteomics. These findings suggest a potential role of these CSEPs in the interaction between F. oxysporum f. sp. melongenae and eggplant, thereby contributing to a deeper understanding of the pathogenic mechanisms of F. oxysporum f. sp. melongenae and strategies for disease management.
Keywords: F. oxysporum f. sp. melongenae; LC-MS; bioinformatic prediction; effector proteins.