Automated Genome Mining of Ribosomal Peptide Natural Products

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• 作者：Hosein Mohimani ; Roland D. Kersten ; Wei-Ting Liu ; Mingxun Wang ; Samuel O. Purvine ; Si Wu ; Heather M. Brewer ; Ljiljana Pasa-Tolic ; Nuno Bandeira ; Bradley S. Moore ; Pavel A. Pevzner ; Pieter C. Dorrestein
• 刊名：ACS Chemical Biology
• 出版年：2014
• 出版时间：July 18, 2014
• 年：2014
• 卷：9
• 期：7
• 页码：1545-1551
• 全文大小：385K
• ISSN：1554-8937

文摘

Ribosomally synthesized and posttranslationally modified peptides (RiPPs), especially from microbial sources, are a large group of bioactive natural products that are a promising source of new (bio)chemistry and bioactivity.1 In light of exponentially increasing microbial genome databases and improved mass spectrometry (MS)-based metabolomic platforms, there is a need for computational tools that connect natural product genotypes predicted from microbial genome sequences with their corresponding chemotypes from metabolomic data sets. Here, we introduce RiPPquest, a tandem mass spectrometry database search tool for identification of microbial RiPPs, and apply it to lanthipeptide discovery. RiPPquest uses genomics to limit search space to the vicinity of RiPP biosynthetic genes and proteomics to analyze extensive peptide modifications and compute p-values of peptide-spectrum matches (PSMs). We highlight RiPPquest by connecting multiple RiPPs from extracts of Streptomyces to their gene clusters and by the discovery of a new class III lanthipeptide, informatipeptin, from Streptomyces viridochromogenes DSM 40736 to reflect that it is a natural product that was discovered by mass spectrometry based genome mining using algorithmic tools rather than manual inspection of mass spectrometry data and genetic information. The presented tool is available at cyclo.ucsd.edu.