Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication
Abstract
Abstract The 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.
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1619562
- Alternate Identifier(s):
- OSTI ID: 1546636
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Published Article
- Journal Name:
- Scientific Reports
- Additional Journal Information:
- Journal Name: Scientific Reports Journal Volume: 8 Journal Issue: 1; Journal ID: ISSN 2045-2322
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United Kingdom
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Theobald, Sebastian, Vesth, Tammi C., Rendsvig, Jakob Kræmmer, Nielsen, Kristian Fog, Riley, Robert, de Abreu, Lucas Magalhães, Salamov, Asaf, Frisvad, Jens Christian, Larsen, Thomas Ostenfeld, Andersen, Mikael Rørdam, and Hoof, Jakob Blæsbjerg. Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication. United Kingdom: N. p., 2018.
Web. doi:10.1038/s41598-018-36561-3.
Theobald, Sebastian, Vesth, Tammi C., Rendsvig, Jakob Kræmmer, Nielsen, Kristian Fog, Riley, Robert, de Abreu, Lucas Magalhães, Salamov, Asaf, Frisvad, Jens Christian, Larsen, Thomas Ostenfeld, Andersen, Mikael Rørdam, & Hoof, Jakob Blæsbjerg. Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication. United Kingdom. https://doi.org/10.1038/s41598-018-36561-3
Theobald, Sebastian, Vesth, Tammi C., Rendsvig, Jakob Kræmmer, Nielsen, Kristian Fog, Riley, Robert, de Abreu, Lucas Magalhães, Salamov, Asaf, Frisvad, Jens Christian, Larsen, Thomas Ostenfeld, Andersen, Mikael Rørdam, and Hoof, Jakob Blæsbjerg. Tue .
"Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication". United Kingdom. https://doi.org/10.1038/s41598-018-36561-3.
@article{osti_1619562,
title = {Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication},
author = {Theobald, Sebastian and Vesth, Tammi C. and Rendsvig, Jakob Kræmmer and Nielsen, Kristian Fog and Riley, Robert and de Abreu, Lucas Magalhães and Salamov, Asaf and Frisvad, Jens Christian and Larsen, Thomas Ostenfeld and Andersen, Mikael Rørdam and Hoof, Jakob Blæsbjerg},
abstractNote = {Abstract The 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.},
doi = {10.1038/s41598-018-36561-3},
journal = {Scientific Reports},
number = 1,
volume = 8,
place = {United Kingdom},
year = {Tue Dec 18 00:00:00 EST 2018},
month = {Tue Dec 18 00:00:00 EST 2018}
}
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https://doi.org/10.1038/s41598-018-36561-3
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Cited by: 22 works
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