HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes. A gap exists between large-scale genome mining and mass spectral datasets for natural product discovery. Here the authors bridge the gap by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra.

Automated summary

Recent analyses have identified over a million biosynthetic gene clusters in public microbial genomes, with the majority of their natural products remaining unknown. Additionally, GNPS has billions of mass spectra of natural products without known structures and biosynthetic genes. To bridge the gap between genome mining and mass spectral datasets for natural product discovery, the authors developed HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which allows for in silico database search of tandem mass spectra.