Enzymatic Basis of Proxamidine Biosynthesis in the Mushroom Laccaria proxima

• Applicant: Professor Dr. Dirk Hoffmeister
• Subject Area: Metabolism, Biochemistry and Genetics of Microorganisms
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 565361431

Due to multiple bioactivities and their structural diversity, the amino acid-derived metabolites represent an outstanding group in the repertoire of microbial natural products. In this regard, the mushroomtype fungi show a propensity for compounds which originate from a monomeric amino acid. The scurfy deceiver Laccaria proxima is a symbiotic mushroom native to Central European Forests. This mushroom’s herbicidal metabolites are the proxamidines whose chemical structure is derived from a monomeric amino acid, Ltryptophan. The proxamidine structure is highly unusual: firstly, the tryptophan undergoes regioselective hydroxylation at position 4, which is an extremely rare modification in natural products. Furthermore, the proxamidines feature an unusual eight-membered heterocycle containing a formamidine moiety. The project aims at elucidating the proxamidine biosynthesis and at characterizing the involved enzymes. Of particular interest is the presumably regioselective enzyme PrxH1, a monooxygenase, which is expected to catalyze the unusual hydroxylation of tryptophan at position 4. A second monooxygenase, PrxH2, is hypothetically responsible to produce the unique eight-membered ring. A third enzyme which deserves attention is PrxP, a particular type of prenyltransferase previously undescribed for fungi. During the transfer reaction, a five-membered nitrogen-containing ring is formed which is a part of the structure of the putative PrxH2 substrate. The primary objective of this project is to elucidate unusual reactions of natural product biosyntheses. Beyond this objective, the characterized enzymes enhance the possibilities to biocatalytically synthesize complex bioactive compounds. Furthermore, this work addresses a more general knowledge gap as natural product biosyntheses in basidiomycetes are still poorly understood. Bioinformatics is lacking essential data for computer-based analysis of genomic sequences regarding encoded metabolic capacity. This deficit is even more severe as the basidiomycetes represent both a phylum of 30,000+ species and a prolific source of bioactive compounds. In the long run, the results of this work help improve and refine software for such analyses, ultimately enabling to reliably predict monomeric amino acid-derived compounds from basidiomycete genomic data.

• DFG Programme: Research Grants