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MetaMiner: A scalable peptidogenomics approach for discovery of ribosomal peptide natural products with blind modifications from microbial communities

TitleMetaMiner: A scalable peptidogenomics approach for discovery of ribosomal peptide natural products with blind modifications from microbial communities
Publication TypeJournal Article
Year of Publication2019
AuthorsCao L., Gurevich A., Alexander K.L, Naman C.B, Leao T., Glukhov E., Luzzatto-Knaan T., Vargas F., Quinn R., Bouslimani A., Nothias L.F, Singh N.K, Sanders J.G, Benitez R.AS, Thompson L.R, Hamid M.N, Morton J.T, Mikheenko A., Shlemov A., Korobeynikov A., Friedberg I., Knight R., Venkateswaran K., Gerwick WH, Gerwick L, Dorrestein PC, Pevzner P.A, Mohimani H.
Volume9
Pagination600-+
Date Published2019/12
Type of ArticleArticle
ISBN Number2405-4712
Accession NumberWOS:000503421500009
KeywordsBiochemistry & Molecular Biology; Biosynthetic gene clusters; Cell Biology; database search; dereplication; drug discovery; mass-spectrometry; molecular; networking; prediction; protein identification; reveals; streptomyces-coelicolor genome
Abstract

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that contain antibiotics and a variety of other bioactive compounds. The existing methods for discovery of RiPPs by combining genome mining and computational mass spectrometry are limited to discovering specific classes of RiPPs from small datasets, and these methods fail to handle unknown post-translational modifications. Here, we present MetaMiner, a software tool for addressing these challenges that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just eight genomic and metagenomic datasets, MetaMiner discovered 31 known and seven unknown RiPPs from diverse microbial communities, including human microbiome and lichen microbiome, and microorganisms isolated from the International Space Station.

DOI10.1016/j.cels.2019.09.004
Student Publication: 
No
Research Topics: 
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