(368c) Heterologous Expression of Anaerobic Gut Fungal Secondary Metabolites in Model Fungal Hosts
AIChE Annual Meeting
2024
2024 AIChE Annual Meeting
Meet the Candidates Poster Sessions
Meet the Industry Candidates Poster Session: Process & Product Development and Manufacturing in Chemicals & Pharmaceuticals
Tuesday, October 29, 2024 - 1:00pm to 3:00pm
Synthetic Biology, Drug Discovery and Development, Bioinformatics/Omics, Microbial Engineering, Natural Product Discovery
Anaerobic gut fungi (phylum Neocallimastigomycota) are a relatively unexplored source of secondary metabolite natural products. Originating from the complex gut microbiomes of large herbivores, these fungi potentially produce secondary metabolites to compete with the more abundant gut bacteria. Genome mining of four anaerobic gut fungal strains predicts approximately 150 secondary metabolite biosynthetic gene clusters, forming sequence-homologous groups for 18 polyketide synthases (PKSs) and 16 nonribosomal peptide synthetases (NRPSs). To investigate these genes, we compared heterologous expression of about 30 plasmids (representing 6 gut fungal PKSs and 6 gut fungal NRPSs) between two model, fungal hosts: Saccharomyces cerevisiae and Aspergillus nidulans. Culture samples were screened for putative secondary metabolite products using untargeted liquid chromatography with tandem mass spectrometry (LC-MS/MS). Additionally, successful heterologous expression of desired biosynthetic enzymes was determined via proteomics. Notably, host A. nidulans secondary metabolism was activated in some expression samples, as indicated by the detection of compounds, including the siderophore pistillarin and the alkaloid camptothecin, putatively identified as known Aspergillus secondary metabolites by MS/MS matching. Across expression samples, LC-MS/MS data analysis tools generated a list of potential secondary metabolite hits to pursue for isolation and structural characterization. Overall, this work presents a pipeline for studying fungal secondary metabolites biosynthetic genes and identifies areas for improvement in existing expression platforms.