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Updated: May 6, 2026

Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
Published on: March 12, 2020
Mushroom hunting by using bioinformatics: application of a predictive framework facilitates the selective
Maureen B Quin1, Christopher M Flynn, Grayson T Wawrzyn
1Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, 1479 Gortner Avenue, St. Paul, MN 55108 (USA).
Abstract:
The Basidiomycota fungi represent a diverse source of natural products, particularly the sesquiterpenoids. Recently, genome sequencing, genome mining, and the subsequent discovery of a suite of sesquiterpene synthases in Omphalotus olearius was described. A predictive framework was developed to facilitate the discovery of sesquiterpene synthases in Basidiomycota. Phylogenetic analyses indicated a conservation of both sequence and initial cyclization mechanisms used. Here, the first robust application of this predictive framework is reported. It was used to selectively identify sesquiterpene synthases that follow 1,6-, 1,10-, and 1,11-cyclization mechanisms in the crust fungus Stereum hirsutum. The successful identification and characterization of a 1,6- and a 1,10-cyclizing sesquiterpene synthase, as well as three 1,11-cyclizing Δ(6) -protoilludene synthases, is described. This study verifies the accuracy and utility of the predictive framework as a roadmap for the discovery of specific sesquiterpene synthases from Basidiomycota, and thus represents an important step forward in natural product discovery.
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