Chemical profiling of bacterial-fungal interactions to elucidate mechanisms of growth and survival in multi-domain microbial communities

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Recently, interest in microbiomes has exploded as specific members of the microbiome are increasingly recognized to play key roles in health and disease in humans and many other hosts.[1] While many studies link microbial composition to biological outcomes, the molecular mechanisms that determine these outcomes are poorly understood. This is partially due to the difficulty of dealing with the large number of variables present in complex multi-domain microbial communities. Fermented food microbiomes offer an advantage of being relatively simple in terms of numbers of microbes present as well as the potential application to human health through diet. Specifically, cheese rinds are edible biofilms have recently been described as a simplified model system with highly reproducible patterns of microbial community succession.[2] These rinds are typically comprised of 10-12 microbes and specific cheeses, like washed or natural rind, have similar microbial genera present regardless of where the rind is aged across the world. As such, the cheese rind biofilm model can be used to establish patterns of underlying biochemical processes that drive bacterial-fungal interactions with food safety and dietary health relevance. For this study I will investigate the molecules produced by bacteria and fungus in response to different growing partners to assess the chemical output of changing growth partners. Based on phenotypic screening from collaborators Dutton and Wolfe, I have selected different filamentous fungi to pair with bacteria for metabolomic analysis. These strains were grown on cheese curd agar in isolation, with a food contaminant, E. coli, and with a natural growing partner, Pseudomonas psychrophila. I used matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry (IMS) to visualize differences in the presence and spatial distribution of molecules across all conditions. IMS data will be used in conjunction with tandem mass spectrometry data from chemical extractions of fungal and bacterial metabolites in order to identify molecules and molecular classes that mediate interactions with bacteria. Three of these fungal strains exhibit growth inhibition of E. coli, presumably by production of antimicrobial molecules. I am in the process of purifying and identifying the molecules responsible for inhibition. In the future, I will use HPLC purification and NMR of bacterial and fungal extracts to confirm suspected identity of molecules and elucidate novel structures of bioactive molecules. Successful completion of this research will deepen our understanding of how specialized metabolites are involved in fermented food microbiomes as well allow us to translate the research to detection of these molecules on the fermented foods themselves.