Exploring ribosomally synthesized and post-translationally modified peptides through SPECO-based genome mining

Genome mining is a computational method that automatically identifies and annotates biosynthetic gene clusters (BGCs) from genomic data, making it a valuable resource for discovering natural products (NPs) due to the wealth of sequencing data available. While different genome mining tools exhibit some similarities, each possesses unique strengths and operates in distinct manners. However, finding new ribosomally synthesized and post-translationally modified peptides (RiPPs), one of the largest yet primarily underexplored NP families in bacteria, remains challenging, primarily because many available mining tools are based on logic with inherent biases towards known RiPP families. To help address this limitation, we have developed a large-scale small peptide and enzyme co-occurrence (SPECO) analysis workflow founded on the universal biosynthetic logic of bacterial RiPPs. This logic implies that precursor and modifying enzymes are clustered together in genetic content and co-conserved, similar precursors undergo modification by homologous tailoring enzymes. In this chapter, we provide detailed instructions for utilizing SPECO to uncover new RiPP chemistry. Additionally, we present a holistic genome mining workflow that merges the capabilities of SPECO with existing bioinformatics tools, such as AlphaFold-Multimer. We use the radical S-adenosylmethionine (rSAM) enzyme as an example to provide a step-by-step guide, revealing the largely unexplored enzymology of rSAM enzymes in peptide macrocyclization. Given the rapidly increasing number of available bacterial genome sequences, we envisage that our approach will be highly applicable for discovering new enzymes for RiPPs biosynthesis.