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The thermophilic fungus Oidiodendron flavum is a saprobe that is commonly isolated from soil. Here, we identified a Gram-positive bacteria-selective antimicrobial secondary metabolite from this fungal species, harzianic acid (HA). Using Bacillus subtilis strain 168 combined with dynamic bacterial morphology imaging, we found that HA targeted the cell membrane. To further study the antimicrobial activity of HA, we isolated an HA-resistant strain, Bacillus subtilis strain M9015, and discovered that the mutant had more translucent colonies than the wild type strain, showed cross resistance to rifampin, and harbored five mutations in the coding region of four distinct genes. Further analysis of these genes indicated that the mutation in atpE might be responsible for the translucency of the colonies, and mutation in mdtR for resistance to both HA and rifampin. We conclude that HA is an antimicrobial agent against Gram-positive bacteria that targets the cell membrane.

Abstract Antimicrobial resistance is a major threat to human health. Basic knowledge of antimicrobial mechanism of action (MoA) is imperative for patient care and for identification of novel antimicrobials. However, the process of antimicrobial MoA identification is relatively laborious. Here, we developed a simple, quantitative time-lapse fluorescence imaging method, Dynamic Bacterial Morphology Imaging (DBMI), to facilitate this process. It uses a membrane dye and a nucleoid dye to track the morphological changes of single Bacillus subtilis cells in response to antimicrobials for up to 60 min. DBMI of bacterial cells facilitated assignment of the MoAs of 14 distinct, known antimicrobial compounds to the five main classes. We conclude that DBMI is a simple method, which facilitates rapid classification of the MoA of antimicrobials in functionally distinct classes.

Quorum sensing (QS) is a process that regulates gene expression based on cell density. In bacteria, QS facilitates collaboration and controls a large number of pathways, including biofilm formation and virulence factor production, which lead to lower sensitivity to antibiotics and higher toxicity in the host, respectively. Inhibition of QS is a promising strategy to combat bacterial infections. In this study, we tested the potential of secondary metabolites from fungi to inhibit bacterial QS using a library derived from more than ten thousand different fungal strains. We used the reporter bacterium, Chromobacterium violaceum, and identified 39 fungal strains that produced QS inhibitor activity. These strains expressed two QS inhibitors that had been described before and eight QS inhibitors that had not been described before. Further testing for QS inhibitor activity against the opportunistic pathogen Pseudomonas aeruginosa led to the identification of gregatins as an interesting family of compounds with QS inhibitor activity. Although various gregatins inhibited QS in P. aeruginosa, these gregatins did not inhibit virulence factor production and biofilm formation. We conclude that gregatins inhibit some, but not all aspects of QS.

ABSTRACT Fungi produce a wide diversity of secondary metabolites with interesting biological activities for the health, industrial, and agricultural sectors. While fungal genomes have revealed an unexpectedly high number of biosynthetic pathways that far exceeds the number of known molecules, accessing and characterizing this hidden diversity remain highly challenging. Here, we applied a combined phylogenetic dereplication and comparative genomics strategy to explore eight lichenizing fungi. The determination of the evolutionary relationships of aromatic polyketide pathways resulted in the identification of an uncharacterized biosynthetic pathway that is conserved in distant fungal lineages. The heterologous expression of the homologue from Aspergillus parvulus linked this pathway to naphthalenone compounds, which were detected in cultures when the pathway was expressed. Our unbiased and rational strategy generated evolutionary knowledge that ultimately linked biosynthetic genes to naphthalenone polyketides. Applied to many more genomes, this approach can unlock the full exploitation of the fungal kingdom for molecule discovery. IMPORTANCE Fungi have provided us with life-changing small bioactive molecules, with the best-known examples being the first broad-spectrum antibiotic penicillin, immunosuppressive cyclosporine, and cholesterol-lowering statins. Since the 1980s, exploration of chemical diversity in nature has been highly reduced. However, the genomic era has revealed that fungal genomes are concealing an unexpected and largely unexplored chemical diversity. So far, fungal genomes have been exploited to predict the production potential of bioactive compounds or to find genes that control the production of known molecules of interest. But accessing and characterizing the full fungal chemical diversity require rational and, thus, efficient strategies. Our approach is to first determine the evolutionary relationships of fungal biosynthetic pathways in order to identify those that are already characterized and those that show a different evolutionary origin. This knowledge allows prioritizing the choice of the pathway to functionally characterize in a second stage using synthetic-biology tools like heterologous expression. A particular strength of this strategy is that it is always successful: it generates knowledge about the evolution of bioactive-molecule biosynthesis in fungi, it either yields novel molecules or links the studied pathway to already known molecules, and it reveals the chemical diversity within a given pathway, all at once. The strategy is very powerful to avoid studying the same pathway again and can be used with any fungal genome. Functional characterization using heterologous expression is particularly suitable for fungi that are difficult to grow or not genetically tractable. Thanks to the decreasing cost of gene synthesis, ultimately, only the genome sequence is needed to identify novel pathways and characterize the molecules that they produce. Such an evolution-informed strategy allows the efficient exploitation of the chemical diversity hidden in fungal genomes and is very promising for molecule discovery.