A new genome-mining tool redefines the lasso peptide biosynthetic landscape

Abstract

Ribosomally synthesized and post-translationally modified peptide (RiPP) natural products are attractive for genome-driven discovery and re-engineering, but limitations in bioinformatic methods and exponentially increasing genomic data make large-scale mining difficult. We report RODEO (Rapid ORF Description and Evaluation Online), which combines hidden Markov model-based analysis, heuristic scoring, and machine learning to identify biosynthetic gene clusters and predict RiPP precursor peptides. We initially focused on lasso peptides, which display intriguing physiochemical properties and bioactivities, but their hypervariability renders them challenging prospects for automated mining. Our approach yielded the most comprehensive mapping of lasso peptide space, revealing >1,300 compounds. We characterized the structures and bioactivities of six lasso peptides, prioritized based on predicted structural novelty, including an unprecedented handcuff-like topology and another with a citrulline modification exceptionally rare among bacteria. These combined insights significantly expand the knowledge of lasso peptides, and more broadly, provide a framework for future genome-mining efforts.

Ribosomally synthesized and post-translationally modified peptide natural product discovery in the genomic era

“…Many of these tools identify complete clusters of various RiPP families through comparison to a training set of known RiPP clusters, leveraging combinations of hidden Markov models, “rules” for precursor peptide identification (e.g., short open reading frames [ORFs] rich in residues that are acted on by the associated biosynthetic enzymes), and comparison to databases of known RiPP sequences. The identification of precursor peptides remains a challenge, and a recent approach called RODEO leverages a machine-learning based approach for this purpose [20]. …”

“…Biochemical characterization of lasso peptides has indeed born out that assertion as many of the original “rules” for lasso precursor identification have been greatly expanded [20,32]. Lasso peptides are characterized by a knotted structure where the C-terminus is threaded through a macrocycle formed by a covalent bond between the N-terminal amine and an aspartate or glutamate side chain [4].…”

“…Similar workflows have led to the discovery of xanthomonins [35], lasso peptides with a previously uncharacterized ring size, and paeninodin [36], a phosphorylated lasso peptide. Recent application of RODEO to the lasso peptides revealed >1,300 compounds in the genomes [20], of which six were characterized including citrulassin, a citrulline-containing family member (Figure 3), which represents a novel PTM in RiPPs. Citrulassin also further expanded the amino acids found at the first position with a Leu, and the RODEO analysis suggests that members exist with all amino acids except Pro at position 1 [20].…”

The natural productome

“…Recent breakthroughs in crystallization allow for the X-ray single-crystal diffraction of submicrogram quantities of natural products, including those that are otherwise noncrystalline (22). Moreover, at least partially predicting small-molecule structure directly from genome sequence is becoming increasingly sophisticated (16), which has the potential to shift the role of spectroscopy from de novo structure determination into predicted structure confirmation (23) and even enable the discovery of new natural products via direct synthesis of genome-predicted structures (24).…”

“…Just as the application of more systematic approaches has powerfully enabled functional characterization in related fields, new systematic tools for characterizing the functions of natural products holds similar promise. For example, computer algorithms can increasingly predict biosynthetic gene clusters responsible for a specific functional domain of a natural product and rapidly identify many other natural products with predicted activities (23). And small-molecule microarrays allow for several thousand protein binding assays to be run in parallel rapidly providing information about the binding targets of small molecules (26).…”