Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species

ABSTRACT Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. However, it is currently an unfeasible task to characterize all biosynthetic gene clusters and to identify...

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Autores principales:	Inge Kjærbølling, Tammi Vesth, Mikael R. Andersen
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	Aspergillus comparative genomics genome mining bioactive compounds fungal genomes Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/f1d3beddecc046f2ab2eedfd768803fb
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spelling	oai:doaj.org-article:f1d3beddecc046f2ab2eedfd768803fb2021-12-02T19:46:18ZResistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species10.1128/mSystems.00085-192379-5077https://doaj.org/article/f1d3beddecc046f2ab2eedfd768803fb2019-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00085-19https://doaj.org/toc/2379-5077ABSTRACT Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. However, it is currently an unfeasible task to characterize all biosynthetic gene clusters and to identify possible uses of the compounds. Therefore, a rational approach is needed to identify a short list of gene clusters responsible for producing valuable compounds. To this end, several bioactive clusters include a resistance gene, which is a paralog of the target gene inhibited by the compound. This mechanism can be used to identify these clusters. We have developed the FRIGG (fungal resistance gene-directed genome mining) pipeline for identifying this type of biosynthetic gene cluster based on homology patterns of the cluster genes. In this work, the FRIGG pipeline was run using 51 Aspergillus and Penicillium genomes, identifying 72 unique families of putative resistance genes. The pipeline also identified the previously characterized resistance gene inpE from the fellutamide B cluster, thereby validating the approach. We have successfully developed an approach to identify putative valuable bioactive clusters based on a specific resistance mechanism. This approach will be highly useful as an ever-increasing amount of genomic data becomes available; the art of identifying and selecting the right clusters producing novel valuable compounds will only become more crucial. IMPORTANCE Species belonging to the Aspergillus genus are known to produce a large number of secondary metabolites; some of these compounds are used as pharmaceuticals, such as penicillin, cyclosporine, and statin. With whole-genome sequencing, it became apparent that the genetic potential for secondary metabolite production is much larger than expected. As an increasing number of species are whole-genome sequenced, thousands of secondary metabolite genes are predicted, and the question of how to selectively identify novel bioactive compounds from this information arises. To address this question, we have created a pipeline to predict genes involved in the production of bioactive compounds based on a resistance gene hypothesis approach.Inge KjærbøllingTammi VesthMikael R. AndersenAmerican Society for MicrobiologyarticleAspergilluscomparative genomicsgenome miningbioactive compoundsfungalgenomesMicrobiologyQR1-502ENmSystems, Vol 4, Iss 4 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Aspergillus comparative genomics genome mining bioactive compounds fungal genomes Microbiology QR1-502
spellingShingle	Aspergillus comparative genomics genome mining bioactive compounds fungal genomes Microbiology QR1-502 Inge Kjærbølling Tammi Vesth Mikael R. Andersen Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
description	ABSTRACT Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. However, it is currently an unfeasible task to characterize all biosynthetic gene clusters and to identify possible uses of the compounds. Therefore, a rational approach is needed to identify a short list of gene clusters responsible for producing valuable compounds. To this end, several bioactive clusters include a resistance gene, which is a paralog of the target gene inhibited by the compound. This mechanism can be used to identify these clusters. We have developed the FRIGG (fungal resistance gene-directed genome mining) pipeline for identifying this type of biosynthetic gene cluster based on homology patterns of the cluster genes. In this work, the FRIGG pipeline was run using 51 Aspergillus and Penicillium genomes, identifying 72 unique families of putative resistance genes. The pipeline also identified the previously characterized resistance gene inpE from the fellutamide B cluster, thereby validating the approach. We have successfully developed an approach to identify putative valuable bioactive clusters based on a specific resistance mechanism. This approach will be highly useful as an ever-increasing amount of genomic data becomes available; the art of identifying and selecting the right clusters producing novel valuable compounds will only become more crucial. IMPORTANCE Species belonging to the Aspergillus genus are known to produce a large number of secondary metabolites; some of these compounds are used as pharmaceuticals, such as penicillin, cyclosporine, and statin. With whole-genome sequencing, it became apparent that the genetic potential for secondary metabolite production is much larger than expected. As an increasing number of species are whole-genome sequenced, thousands of secondary metabolite genes are predicted, and the question of how to selectively identify novel bioactive compounds from this information arises. To address this question, we have created a pipeline to predict genes involved in the production of bioactive compounds based on a resistance gene hypothesis approach.
format	article
author	Inge Kjærbølling Tammi Vesth Mikael R. Andersen
author_facet	Inge Kjærbølling Tammi Vesth Mikael R. Andersen
author_sort	Inge Kjærbølling
title	Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
title_short	Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
title_full	Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
title_fullStr	Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
title_full_unstemmed	Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species
title_sort	resistance gene-directed genome mining of 50 <italic toggle="yes">aspergillus</italic> species
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/f1d3beddecc046f2ab2eedfd768803fb
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_version_	1718376059725938688

Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species

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