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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. 

ABSTRACT Modern taxonomic classification is often based on phylogenetic analyses of a few molecular markers, although single-gene studies are still common. Here, we leverage genome-scale molecular phylogenetics (phylogenomics) of species and populations to reconstruct evolutionary relationships in a dense data set of 710 fungal genomes from the biomedically and technologically important genusAspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific forAspergillusand provided profile Hidden Markov Models for each, facilitating their use by others. Examining the resulting phylogeny helped resolve ongoing taxonomic controversies, identified new ones, and revealed extensive strain misidentification (7.59% of strains were previously misidentified), underscoring the importance of population-level sampling in species classification. These findings were corroborated using the current standard, taxonomically informative loci. These findings suggest that phylogenomics of species and populations can facilitate accurate taxonomic classifications and reconstructions of the Tree of Life.IMPORTANCEIdentification of fungal species relies on the use of molecular markers. Advances in genomic technologies have made it possible to sequence the genome of any fungal strain, making it possible to use genomic data for the accurate assignment of strains to fungal species (and for the discovery of new ones). We examined the usefulness and current limitations of genomic data using a large data set of 710 publicly available genomes from multiple strains and species of the biomedically, agriculturally, and industrially important genusAspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly availableAspergillusgenomes are misidentified. Our work highlights the usefulness of genomic data for fungal systematic biology and suggests that systematic genome sequencing of multiple strains, including reference strains (e.g., type strains), of fungal species will be required to reduce misidentification errors in public databases. 

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. 

Aspergillus fumigatus causes a range of human and animal diseases collectively known as aspergillosis. A . fumigatus possesses and expresses a range of genetic determinants of virulence, which facilitate colonisation and disease progression, including the secretion of mycotoxins. Gliotoxin (GT) is the best studied A . fumigatus mycotoxin with a wide range of known toxic effects that impair human immune cell function. GT is also highly toxic to A . fumigatus and this fungus has evolved self-protection mechanisms that include (i) the GT efflux pump GliA, (ii) the GT neutralising enzyme GliT, and (iii) the negative regulation of GT biosynthesis by the bis -thiomethyltransferase GtmA. The transcription factor (TF) RglT is the main regulator of GliT and this GT protection mechanism also occurs in the non-GT producing fungus A . nidulans . However, the A . nidulans genome does not encode GtmA and GliA. This work aimed at analysing the transcriptional response to exogenous GT in A . fumigatus and A . nidulans , two distantly related Aspergillus species, and to identify additional components required for GT protection. RNA-sequencing shows a highly different transcriptional response to exogenous GT with the RglT-dependent regulon also significantly differing between A . fumigatus and A . nidulans . However, we were able to observe homologs whose expression pattern was similar in both species (43 RglT-independent and 11 RglT-dependent). Based on this approach, we identified a novel RglT-dependent methyltranferase, MtrA, involved in GT protection. Taking into consideration the occurrence of RglT-independent modulated genes, we screened an A . fumigatus deletion library of 484 transcription factors (TFs) for sensitivity to GT and identified 15 TFs important for GT self-protection. Of these, the TF KojR, which is essential for kojic acid biosynthesis in Aspergillus oryzae , was also essential for virulence and GT biosynthesis in A . fumigatus , and for GT protection in A . fumigatus , A . nidulans , and A . oryzae . KojR regulates rglT , gliT , gliJ expression and sulfur metabolism in Aspergillus species. Together, this study identified conserved components required for GT protection in Aspergillus species. 

Aspergillus fumigatus is a major human pathogen. In contrast, Aspergillus fischeri and the recently described Aspergillus oerlinghausenensis , the two species most closely related to A. fumigatus , are not known to be pathogenic. Some of the genetic determinants of virulence (or "cards of virulence") that A . fumigatus possesses are secondary metabolites that impair the host immune system, protect from host immune cell attacks, or acquire key nutrients. To examine whether secondary metabolism-associated cards of virulence vary between these species, we conducted extensive genomic and secondary metabolite profiling analyses of multiple A. fumigatus , one A. oerlinghausenensis , and multiple A. fischeri strains. We identified two cards of virulence (gliotoxin and fumitremorgin) shared by all three species and three cards of virulence (trypacidin, pseurotin, and fumagillin) that are variable. For example, we found that all species and strains examined biosynthesized gliotoxin, which is known to contribute to virulence, consistent with the conservation of the gliotoxin biosynthetic gene cluster (BGC) across genomes. For other secondary metabolites, such as fumitremorgin, a modulator of host biology, we found that all species produced the metabolite but that there was strain heterogeneity in its production within species. Finally, species differed in their biosynthesis of fumagillin and pseurotin, both contributors to host tissue damage during invasive aspergillosis. A. fumigatus biosynthesized fumagillin and pseurotin, while A. oerlinghausenensis biosynthesized fumagillin and A. fischeri biosynthesized neither. These biochemical differences were reflected in sequence divergence of the intertwined fumagillin/pseurotin BGCs across genomes. These results delineate the similarities and differences in secondary metabolism-associated cards of virulence between a major fungal pathogen and its nonpathogenic closest relatives, shedding light onto the genetic and phenotypic changes associated with the evolution of fungal pathogenicity.