A Scalable Platform to Discover Antimicrobials of Ribosomal Origin

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PROJECT SUMMARY/ABSTRACT Natural products have been by far the most prolific source of chemical matter that has been developed into modern antibacterial and antifungal drugs by the pharmaceutical industry. However, despite the pressing need for new drugs to address the alarming rise of drug resistance, especially amongst Gram-negative bacterial pathogens, the rate of discovering natural products has diminished. In this R01 project, we propose to develop a scalable platform to produce novel ribosomal natural products, i.e. ribosomally synthesized and posttranslationally modified peptides (RiPPs). With more than two dozen distinct classes of RiPPs identified thus far, and several new classes being identified each year, RiPPs represent a promising addition to the antibacterial and antifungal drugs biosynthesized by polyketide and non-ribosomal pathways yet they remain vastly underexploited by comparison. Specifically, we will integrate bioinformatics, synthetic biology, and analytical chemistry tools to develop a Fully Automated, Scalable, and high-Throughput (FAST) pipeline for the discovery and characterization of one thousand novel RiPPs from uncharacterized RiPP biosynthetic gene clusters (BGCs) of both known and unknown classes. The resultant novel RiPPs will be assayed for their antibacterial and antifungal activities as well as other related biological activities towards neglected and tropical diseases (tuberculosis and malaria) through a collaboration with Lilly's Open Innovation Drug Discovery Program (openinnovation.lilly.com). This project represents the first large-scale attempt at unlocking the potential of RiPPs as a source of new antibacterial and antifungal drugs, which based on their genetic compactness, are ideally suited for the synthetic biology methods and goals described within. For this project, we propose three interrelated but independently achievable specific aims. Aim 1 will discover novel RiPPs from known classes using lower throughput methods. Aim 2 will scale up the discovery of novel RiPPs from known classes using the FAST pipeline. Aim 3 will predict and produce RiPPs from classes that have not yet been reported, which will ensure a variety of novel natural product scaffolds. Success in the overall project will change the paradigm for natural product discovery and will potentially have a profound impact on the pharmaceutical industry.