Enterolyin S, a Polythiazole-containing Hemolytic Peptide from Enterococcus caccae.

The ß-hemolytic factor streptolysin S (SLS) is an important linear azol(in)e-containing peptide (LAP) that contributes significantly to the virulence of Streptococcus pyogenes. Despite its discovery 85 years ago, SLS has evaded structural characterizing owing to its notoriously problematic physicochemical properties. Here, we report the discovery and characterization of a structurally analogous hemolytic peptide from Enterococcus caccae, termed enterolysin S (ELS). Through heterologous expression, site-directed mutagenesis, chemoselective modification, and high-resolution mass spectrometry, we found that ELS contains an intriguing contiguous octathiazole moiety. The discovery of ELS expands our knowledge of hemolytic LAPs by adding a new member to this virulence-promoting family of modified peptides.

Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products.

Natural products (NPs) produced by microorganisms and plants are a major source of drugs, herbicides, and fungicides. Thanks to recent advances in DNA sequencing, bioinformatics, and genome mining tools, a vast amount of data on NP biosynthesis has been generated over the years, which has been increasingly exploited to develop machine learning (ML) tools for NP discovery. In this review, we discuss the latest advances in developing and applying ML tools for exploring the potential NPs that can be encoded by genomic language and predicting the types of bioactivities of NPs. We also examine the technical challenges associated with the development and application of ML tools for NP research.

A scalable platform to discover antimicrobials of ribosomal origin.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a promising source of new antimicrobials in the face of rising antibiotic resistance. Here, we report a scalable platform that combines high-throughput bioinformatics with automated biosynthetic gene cluster refactoring for rapid evaluation of uncharacterized gene clusters. As a proof of concept, 96 RiPP gene clusters that originate from diverse bacterial phyla involving 383 biosynthetic genes are refactored in a high-throughput manner using a biological foundry with a success rate of 86%. Heterologous expression of all successfully refactored gene clusters in Escherichia coli enables the discovery of 30 compounds covering six RiPP classes: lanthipeptides, lasso peptides, graspetides, glycocins, linear azol(in)e-containing peptides, and thioamitides. A subset of the discovered lanthipeptides exhibit antibiotic activity, with one class II lanthipeptide showing low µM activity against Klebsiella pneumoniae, an ESKAPE pathogen. Overall, this work provides a robust platform for rapidly discovering RiPPs.

PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction.

Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute (PfAgo)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate 101 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments. PlasmidMaker should greatly expand the potential of synthetic biology.

Discovery and Characterization of a Class IV Lanthipeptide with a Nonoverlapping Ring Pattern.

Lanthipeptides constitute a major family of ribosomally synthesized and post-translationally modified peptides (RiPPs). They are classified into four subfamilies, based on the characteristics of their lanthipeptide synthetases. While over a hundred lanthipeptides have been discovered to date, very few of them are class IV lanthipeptides and the latter are all structurally similar. Here, we identified an uncharacterized group of class IV lanthipeptides using bioinformatics analysis. One representative pathway from Streptomyces sp. NRRL S-1022 was expressed in Escherichia coli, which generated a lanthipeptide with two nonoverlapping rings that have not been reported for known class IV lanthipeptides. Further investigation into the biosynthetic mechanism revealed that multiple modification pathways are in operation in which dehydration and cyclization occur in parallel. While peptidases for maturation of class IV lanthipeptides have been elusive, two aminopeptidases encoded in the genome of Streptomyces sp. NRRL S-1022 were shown to process the modified peptide by the dual endopeptidase/aminopeptidase activity. This work opens doors to discover more class IV lanthipeptides with interesting structural features and biological activities.

Computational Tools for Discovering and Engineering Natural Product Biosynthetic Pathways.

Natural products (NPs), also known as secondary metabolites, are produced in bacteria, fungi, and plants. NPs represent a rich source of antibacterial, antifungal, and anticancer agents. Recent advances in DNA sequencing technologies and bioinformatics unveiled nature's great potential for synthesizing numerous NPs that may confer unprecedented structural and biological features. However, discovering novel bioactive NPs by genome mining remains a challenge. Moreover, even with interesting bioactivity, the low productivity of many NPs significantly limits their practical applications. Here we discuss the progress in developing bioinformatics tools for efficient discovery of bioactive NPs. In addition, we highlight computational methods for optimizing the productivity of NPs of pharmaceutical importance.