Molecular networking and LOTUS-based in silico fragmentation spectral database dereplication for the chemical exploration of Epicoccum nigrum

The accurate and trustworthy identification of novel molecules in complex extracts (such as those derived from microorganisms) is a critical task of Natural Products (NPs) research. In this context, the integration of high-resolution mass spectrometry and molecular networking offers a powerful and effective approach for precise molecular annotation.

In this study, an integrated metabolomics strategy, including Feature Based Molecular Networking (FBMN) in combination with in silico fragmented spectral database dereplication (ISDB) was used to explore the metabolome of Epicoccum nigrum. In particular, the molecular annotation procedure was performed using the latest version of the ISDB which includes a comprehensive collection of molecular structures compiled in LOTUS together with the associated metadata documenting biological sources of the metabolites. This comprehensive metabolomics approach allowed for the mapping of the metabolome of Epicoccum nigrum, a saprotrophic fungal microorganism that plays a significant role in various ecological and biotechnological contexts. Interestingly, the detailed inspection of the FBMN and employed annotation procedure led to the identification of a molecular cluster related to isoindolin derivatives presenting two putatively new molecules. Moreover, the highlighted features were among the most intense of the metabolite profile and thus could be reasonably targeted for isolation and full structure NMR elucidation.

These results confirm the utility of FBMN, in combination with recently developed taxonomically informed metabolite annotation processes, in exploring microbial metabolomes and for prioritising the isolation of potential novel compounds.

Conflict of Interest

The authors declare no conflict of interest.

Publikationsverlauf

Artikel online veröffentlicht:
16. November 2023