| Literature DB >> 31629686 |
Liu Cao1, Alexey Gurevich2, Kelsey L Alexander3, C Benjamin Naman4, Tiago Leão5, Evgenia Glukhov5, Tal Luzzatto-Knaan6, Fernando Vargas6, Robby Quinn6, Amina Bouslimani6, Louis Felix Nothias6, Nitin K Singh7, Jon G Sanders8, Rodolfo A S Benitez8, Luke R Thompson9, Md-Nafiz Hamid10, James T Morton11, Alla Mikheenko2, Alexander Shlemov2, Anton Korobeynikov12, Iddo Friedberg10, Rob Knight13, Kasthuri Venkateswaran7, William H Gerwick5, Lena Gerwick5, Pieter C Dorrestein14, Pavel A Pevzner15, Hosein Mohimani16.
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.Entities:
Keywords: computational mass spectrometry; metagenomics; microbial metabolites; natural products discovery; ribosomally synthesized and post-translationally modified peptides
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Year: 2019 PMID： 31629686 PMCID： PMC6952069 DOI： 10.1016/j.cels.2019.09.004
Source DB: PubMed Journal: Cell Syst ISSN： 2405-4712 Impact factor: 10.304