Metabolome-guided genome mining of RiPP natural products.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs. Ribosomally synthesized and post-translationally modified peptides (RiPPs) from microorganisms show high chemical diversity and exhibit potent biological properties. The computational detection of novel classes of RiPPs is hampered by their short length and the lack of universally conserved genes. The high false-positive rate of class-independent computational detection approaches can be addressed by validation via mass spectrometry-based metabolomics. [ABSTRACT FROM AUTHOR]