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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| Format: | Article |
| Language: | English |
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American Society for Microbiology
2019-08-01
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| Series: | mSystems |
| Subjects: | |
| Online Access: | https://journals.asm.org/doi/10.1128/mSystems.00085-19 |
| _version_ | 1818742274835611648 |
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| author | Inge Kjærbølling Tammi Vesth Mikael R. Andersen |
| author_facet | Inge Kjærbølling Tammi Vesth Mikael R. Andersen |
| author_sort | Inge Kjærbølling |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-18T02:09:55Z |
| format | Article |
| id | doaj.art-f1d3beddecc046f2ab2eedfd768803fb |
| institution | Directory Open Access Journal |
| issn | 2379-5077 |
| language | English |
| last_indexed | 2024-12-18T02:09:55Z |
| publishDate | 2019-08-01 |
| publisher | American Society for Microbiology |
| record_format | Article |
| series | mSystems |
| spelling | doaj.art-f1d3beddecc046f2ab2eedfd768803fb2022-12-21T21:24:31ZengAmerican Society for MicrobiologymSystems2379-50772019-08-014410.1128/mSystems.00085-19Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> SpeciesInge Kjærbølling0Tammi Vesth1Mikael R. Andersen2Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, DenmarkDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, DenmarkDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, DenmarkABSTRACT 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.https://journals.asm.org/doi/10.1128/mSystems.00085-19Aspergilluscomparative genomicsgenome miningbioactive compoundsfungalgenomes |
| spellingShingle | Inge Kjærbølling Tammi Vesth Mikael R. Andersen Resistance Gene-Directed Genome Mining of 50 <italic toggle="yes">Aspergillus</italic> Species mSystems Aspergillus comparative genomics genome mining bioactive compounds fungal genomes |
| title | 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_short | 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 |
| topic | Aspergillus comparative genomics genome mining bioactive compounds fungal genomes |
| url | https://journals.asm.org/doi/10.1128/mSystems.00085-19 |
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