Strain and contact-dependent metabolomic reprogramming reveals distinct interaction strategies between Laccaria bicolor and Trichoderma.

The genus Trichoderma (Hypocreaceae, Ascomycota) compromises over 400 known species, that are found in various soils, on plant surfaces and as plant endophytes. Interactions between the mycoparasitic Trichoderma spp. and beneficial ectomycorrhizal fungi such as Laccaria bicolor (Hydnangiaceae, Basidiomycota) can influence the structure of fungal communities and plant symbioses. In this study, we conducted in vitro dual-culture experiments involving L. bicolor and four Trichoderma strains (T. harzianum WM24a1, MS8a1, ES8g1, and T. atrobrunneum) to analyze their metabolic responses in relation to varying degrees of physical contact. Using integrated analyses of volatile organic compounds (VOCs), hyphal metabolomes, and secreted exudates, we uncovered strong contact- and strain-dependent growth inhibition patterns: Trichoderma growth was suppressed under shared headspace, whereas L. bicolor was more strongly inhibited under direct contact. Metabolomic profiling revealed distinct and strain-specific alterations in both VOC and soluble metabolite profiles during co-cultivation, with hundreds of discriminant mass features affected. Key metabolic pathways, including amino acid, carbohydrate, lipid, and secondary metabolite biosynthesis, showed differential enrichment depending on the interaction stage and fungal partner. These results demonstrate that Trichoderma-Laccaria interactions are mediated by dynamic, contact-specific chemical reprogramming and suggest that fungal recognition and competition involve coordinated changes in both volatile and non-volatile metabolite production. Our findings provide a foundation for exploring how such antagonistic interactions may influence tripartite communication in plant-associated microbial networks. They also highlight the potential role of both emitted and secreted fungal metabolites in shaping interaction dynamics through putative non-self-recognition mechanisms.