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

Sebastian Theobald, Tammi C. Vesth, Jakob Kræmmer Rendsvig, Kristian Fog Nielsen, Robert Riley, Lucas Magalhães de Abreu, Asaf Salamov, Jens Christian Frisvad, Thomas Ostenfeld Larsen, Mikael Rørdam Andersen, Jakob Blæsbjerg Hoof*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

249 Downloads (Pure)

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.
Original languageEnglish
Article number17957
JournalScientific Reports
Volume8
Number of pages12
ISSN2045-2322
DOIs
Publication statusPublished - 2018

Cite this