Detection and dynamics of volatile/non-volatile metabolite induction in a fungal co-culture through a miniaturised MS-based metabolomic approach

Microbial co-cultivation has emerged as a promising way for activating cryptic biosynthetic pathways and discovering novel antimicrobial metabolites [1]. For the success of such studies, a key element remains the development of standardized co-cultivation methods compatible with high throughput analytical procedures [2]. In our continuous studies on the dynamic stress induction of bioactive natural products in co-culture conditions, we have extended the investigations to modifications of the microbial volatile metabolome that might be of im-portance in the understanding of the interaction between microorganisms. For this, an MS metabolomic strategy based on the analysis of volatile and non-volatile frac-tions of the fungal cultures directly grown in 20 ml vials was applied. The head space of each sample was profiled by SPME-GC-MS while the whole culture medium was analyzed by LC-HRMS after solvent extraction. This strategy was implemented for screening volatile/non-volatile metabolite inductions in an ecologically relevant fungal co-culture of Eutypa lata (Pers.) Tul. & C. Tul. (Diatrypaceae) and Botryospheria obtusa (Schwein.) Shoemaker (Botry-osphaeriaceae), two wood decaying fungi interacting in the context of esca disease of grape-vine [3]. Multivariate data analysis combining Analysis of Variance (ANOVA) and Orthogonal Partial Least Squares (OPLS) conducted to the selection of specific induced molecules related to each factor of the study. A time-series study during nine days showed characteristic me-tabolite induction patterns. Interesting relationships between the dynamics of volatile/non-volatile metabolite de novo formation and up- or down-regulation could be highlighted. Some of the induced compounds (e.g., 2-nonanone) are bioactive and known to be produced by oth-er microorganisms. The developed strategy could help elucidating the microbial inter- and intra-species communication. Moreover it could be used for efficiently identifying signaling molecules with potential antimicrobial activity.