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SUMMARY Previous comparative and experimental evolution studies have suggested how fungi may rapidly adapt to new environments, but direct observation ofin situselection in fungal populations is rare due to challenges with tracking populations over human time scales. We monitored a population ofPenicillium solitumover eight years in a cheese cave and documented a phenotypic shift from predominantly green to white strains. Diverse mutations in thealb1gene, which encodes the first protein in the DHN-melanin biosynthesis pathway, explained the green to white shift. A similar phenotypic shift was recapitulated with analb1knockout and experimental evolution in laboratory populations. The most common genetic disruption of thealb1genomic region was caused by putative transposable element insertions upstream of the gene. White strains had substantial downregulation in global transcription, with genetically distinct white strains possessing divergent shifts in expression of different biological processes. White strains outcompeted green strains in co-culture, but this competitive advantage was only observed in the absence of light, suggesting that loss of melanin is only adaptive in dark conditions. Our results illustrate how fermented food production by humans provides opportunities for relaxed selection of key fungal traits over short time scales. Unintentional domestication of microbes by cheesemakers may provide opportunities to generate new strains for innovation in traditional cheese production. 

Abstract IntroductionFungi biosynthesize chemically diverse secondary metabolites with a wide range of biological activities. Natural product scientists have increasingly turned towards bioinformatics approaches, combining metabolomics and genomics to target secondary metabolites and their biosynthetic machinery. We recently applied an integrated metabologenomics workflow to 110 fungi and identified more than 230 high-confidence linkages between metabolites and their biosynthetic pathways. ObjectivesTo prioritize the discovery of bioactive natural products and their biosynthetic pathways from these hundreds of high-confidence linkages, we developed a bioactivity-driven metabologenomics workflow combining quantitative chemical information, antiproliferative bioactivity data, and genome sequences. MethodsThe 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their biosynthetic pathways were identified using metabologenomics. ResultsWe isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 µM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated—Omics datasets. ConclusionsThis work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery. 

Introduction Fungi biosynthesize chemically diverse secondary metabolites with a wide range of biological activities. Natu- ral product scientists have increasingly turned towards bioinformatics approaches, combining metabolomics and genomics to target secondary metabolites and their biosynthetic machinery. We recently applied an integrated metabologenomics workflow to 110 fungi and identified more than 230 high-confidence linkages between metabolites and their biosynthetic pathways. Objectives To prioritize the discovery of bioactive natural products and their biosynthetic pathways from these hundreds of high-confidence linkages, we developed a bioactivity-driven metabologenomics workflow combining quantitative chemical information, antiproliferative bioactivity data, and genome sequences. Methods The 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their bio- synthetic pathways were identified using metabologenomics. Results We isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 μM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated—Omics datasets. Conclusions This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabolog- enomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery. 

ABSTRACT Potent antimicrobial metabolites are produced by filamentous fungi in pure culture, but their ecological functions in nature are often unknown. Using an antibacterial Penicillium isolate and a cheese rind microbial community, we demonstrate that a fungal specialized metabolite can regulate the diversity of bacterial communities. Inactivation of the global regulator, LaeA, resulted in the loss of antibacterial activity in the Penicillium isolate. Cheese rind bacterial communities assembled with the laeA deletion strain had significantly higher bacterial abundances than the wild-type strain. RNA-sequencing and metabolite profiling demonstrated a striking reduction in the expression and production of the natural product pseurotin in the laeA deletion strain. Inactivation of a core gene in the pseurotin biosynthetic cluster restored bacterial community composition, confirming the role of pseurotins in mediating bacterial community assembly. Our discovery demonstrates how global regulators of fungal transcription can control the assembly of bacterial communities and highlights an ecological role for a widespread class of fungal specialized metabolites. IMPORTANCE Cheese rinds are economically important microbial communities where fungi can impact food quality and aesthetics. The specific mechanisms by which fungi can regulate bacterial community assembly in cheeses, other fermented foods, and microbiomes in general are largely unknown. Our study highlights how specialized metabolites secreted by a Penicillium species can mediate cheese rind development via differential inhibition of bacterial community members. Because LaeA regulates specialized metabolites and other ecologically relevant traits in a wide range of filamentous fungi, this global regulator may have similar impacts in other fungus-dominated microbiomes. 

Abstract Lipo-chitooligosaccharides (LCOs) are signaling molecules produced by rhizobial bacteria that trigger the nodulation process in legumes, and by some fungi that also establish symbiotic relationships with plants, notably the arbuscular and ecto mycorrhizal fungi. Here, we show that many other fungi also produce LCOs. We tested 59 species representing most fungal phyla, and found that 53 species produce LCOs that can be detected by functional assays and/or by mass spectroscopy. LCO treatment affects spore germination, branching of hyphae, pseudohyphal growth, and transcription in non-symbiotic fungi from the Ascomycete and Basidiomycete phyla. Our findings suggest that LCO production is common among fungi, and LCOs may function as signals regulating fungal growth and development.