Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication

Theobald, Sebastian; Vesth, Tammi Camilla; Rendsvig, Jakob Kræmmer Haar; Nielsen, Kristian Fog; Riley, Robert; Abreu, Lucas M.; Salamov, Asaf; Frisvad, Jens Christian; Larsen, Thomas Ostenfeld; Andersen, Mikael Rørdam; Hoof, Jakob Blæsbjerg

doi:10.1038/s41598-018-36561-3

Cited by 39 publications

(39 citation statements)

References 67 publications

(79 reference statements)

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“…Annotation of SMGC families using MIBiG (genetic dereplication). SMGC families were annotated based on the MIBiG database 67 . Known gene clusters were coupled to SMGC families, making it possible to predict the compounds or derivatives thereof a species can potentially produce.…”

Section: Methodsmentioning

confidence: 99%

“…Dereplicating secondary metabolism predicts toxin producers. To assess the potential for SM production qualitatively, we used a pipeline of "genetic dereplication" where predicted clusters are associated with verified characterized clusters (from the MIBiG database 66 ) in a guilt-by-association method 67 . Based on this, 20 cluster families were coupled to a compound family (Fig.…”

Section: Secondary Metabolism In Section Flavi Is Diverse and Prolificmentioning

confidence: 99%

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A comparative genomics study of 23 Aspergillus species from section Flavi

et al. 2020

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Section Flavi encompasses both harmful and beneficial Aspergillus species, such as Aspergillus oryzae, used in food fermentation and enzyme production, and Aspergillus flavus, food spoiler and mycotoxin producer. Here, we sequence 19 genomes spanning section Flavi and compare 31 fungal genomes including 23 Flavi species. We reassess their phylogenetic relationships and show that the closest relative of A. oryzae is not A. flavus, but A. minisclerotigenes or A. aflatoxiformans and identify high genome diversity, especially in sub-telomeric regions. We predict abundant CAZymes (598 per species) and prolific secondary metabolite gene clusters (73 per species) in section Flavi. However, the observed phenotypes (growth characteristics, polysaccharide degradation) do not necessarily correlate with inferences made from the predicted CAZyme content. Our work, including genomic analyses, phenotypic assays, and identification of secondary metabolites, highlights the genetic and metabolic diversity within section Flavi.

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Section: Methodsmentioning

confidence: 99%

Section: Secondary Metabolism In Section Flavi Is Diverse and Prolificmentioning

confidence: 99%

A comparative genomics study of 23 Aspergillus species from section Flavi

et al. 2020

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“…[12,13]. Today, fungi represent a vast and generally untapped pool for new lead compounds with pharmaceutical and agricultural applications [14]. However, efforts in genome mining for the search of RiPP BGCs, that encode for the machinery responsible to produce secondary metabolites, have thus far been focused on bacterial genomes due to the lack of a large database of fungal RiPPs [11,15].…”

Section: Introductionmentioning

confidence: 99%

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp

et al. 2020

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Background: Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a highly diverse group of secondary metabolites (SM) of bacterial and fungal origin. While RiPPs have been intensively studied in bacteria, little is known about fungal RiPPs. In Fungi only six classes of RiPPs are described. Current strategies for genome mining are based on these six known classes. However, the genes involved in the biosynthesis of theses RiPPs are normally organized in biosynthetic gene clusters (BGC) in fungi. Results: Here we describe a comprehensive strategy to mine fungal genomes for RiPPs by combining and adapting existing tools (e.g. antiSMASH and RiPPMiner) followed by extensive manual curation based on conserved domain identification, (comparative) phylogenetic analysis, and RNASeq data. Deploying this strategy, we could successfully rediscover already known fungal RiPPs. Further, we analysed four fungal genomes from the Trichoderma genus. We were able to find novel potential RiPP BGCs in Trichoderma using our unconventional mining approach. Conclusion: We demonstrate that the unusual mining approach using tools developed for bacteria can be used in fungi, when carefully curated. Our study is the first report of the potential of Trichoderma to produce RiPPs, the detected clusters encode novel uncharacterized RiPPs. The method described in our study will lead to further mining efforts in all subdivisions of the fungal kingdom.

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“…The interpretation step can infuse knowledge of BGC phylogenetic distribution, inferences about the molecules encoded (e.g., prevalence and structural variance), and avoidance of known compounds (dereplication). To date, the application of such large-scale genome mining approaches to fungi has been largely limited to individual biosynthetic enzymes (10) or datasets of <100 genomes from wellstudied taxonomic groups (11)(12)(13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

An Interpreted Atlas of Biosynthetic Gene Clusters from 1000 Fungal Genomes

Robey

Caesar

Drott

et al. 2020

Preprint

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Fungi are prolific producers of natural products, compounds which have had a large societal impact as pharmaceuticals, mycotoxins, and agrochemicals. Despite the availability of over 1000 fungal genomes and several decades of compound discovery efforts from fungi, the biosynthetic gene clusters (BGCs) encoded by these genomes and the associated chemical space have yet to be analyzed systematically. Here we provide detailed annotation and analyses of fungal biosynthetic and chemical space to enable genome mining and discovery of fungal natural products. Using 1037 genomes from species across the fungal kingdom (e.g., Ascomycota, Basidiomycota, and non-Dikarya taxa), 36,399 predicted BGCs were organized into a network of 12,067 gene cluster families (GCFs). Anchoring these GCFs with reference BGCs enabled automated annotation of 2,026 BGCs with predicted metabolite scaffolds. We performed parallel analyses of the chemical repertoire of Fungi, organizing 15,213 fungal compounds into 2,945 molecular families (MFs). The taxonomic landscape of fungal GCFs is largely species-specific, though select families such as the equisetin GCF are present across vast phylogenetic distances with parallel diversifications in the GCF and MF. We compare these fungal datasets with a set of 5,453 bacterial genomes and their BGCs and 9,382 bacterial compounds, revealing dramatic differences between bacterial and fungal biosynthetic logic and chemical space. These genomics and cheminformatics analyses reveal the large extent to which fungal and bacterial sources represent distinct compound reservoirs. With a >10-fold increase in the number of interpreted strains and annotated BGCs, this work better regularizes the biosynthetic potential of fungi for rational compound discovery.Significance StatementFungi represent an underexploited resource for new compounds with applications in the pharmaceutical and agriscience industries. Despite the availability of >1000 fungal genomes, our knowledge of the biosynthetic space encoded by these genomes is limited and ad hoc. We present results from systematically organizing the biosynthetic content of 1037 fungal genomes, providing a resource for data-driven genome mining and large-scale comparison of the genetic and molecular repertoires produced in fungi and compare to those present in bacteria.

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Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication

Cited by 39 publications

References 67 publications

A comparative genomics study of 23 Aspergillus species from section Flavi

A comparative genomics study of 23 Aspergillus species from section Flavi

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp

An Interpreted Atlas of Biosynthetic Gene Clusters from 1000 Fungal Genomes

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