Journal article
Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication
New Bioactive Compounds, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark1
Natural Product Discovery, Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark2
Fungal Biomedicine and Biology, Section for Synthetic Biology, Department of Biotechnology and Biomedicine, Technical University of Denmark3
Network Engineering of Eukaryotic Cell factories, Section for Synthetic Biology, Department of Biotechnology and Biomedicine, Technical University of Denmark4
Department of Biotechnology and Biomedicine, Technical University of Denmark5
Section for Synthetic Biology, Department of Biotechnology and Biomedicine, Technical University of Denmark6
Eukaryotic Molecular Cell Biology, Section for Synthetic Biology, Department of Biotechnology and Biomedicine, Technical University of Denmark7
Joint Genome Institute8
Federal University of Viçosa9
Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark10
Fungal Chemodiversity, Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark11
...and 1 moreThe increased interest in secondary metabolites (SMs) has driven a number of genome sequencing projects to elucidate their biosynthetic pathways. As a result, studies revealed that the number of secondary metabolite gene clusters (SMGCs) greatly outnumbers detected compounds, challenging current methods to dereplicate and categorize this amount of gene clusters on a larger scale.
Here, we present an automated workflow for the genetic dereplication and analysis of secondary metabolism genes in fungi. Focusing on the secondary metabolite rich genus Aspergillus, we categorize SMGCs across genomes into SMGC families using network analysis. Our method elucidates the diversity and dynamics of secondary metabolism in section Nigri, showing that SMGC diversity within the section has the same magnitude as within the genus.
Using our genome analysis we were able to predict the gene cluster responsible for biosynthesis of malformin, a potentiator of anti-cancer drugs, in 18 strains. To proof the general validity of our predictions, we developed genetic engineering tools in Aspergillus brasiliensis and subsequently verified the genes for biosynthesis of malformin.
| Language: | English |
|---|---|
| Publisher: | Nature Publishing Group UK |
| Year: | 2018 |
| Pages: | 17957 |
| ISSN: | 20452322 |
| Types: | Journal article |
| DOI: | 10.1038/s41598-018-36561-3 |
| ORCIDs: | 0000-0001-7042-8326 , 0000-0003-1606-5709 , Larsen, Thomas Ostenfeld , Andersen, Mikael Rørdam , Hoof, Jakob Blæsbjerg , Vesth, Tammi C. , Nielsen, Kristian Fog and Frisvad, Jens Christian |
