INFORMATIC STRATEGIES AND TECHNOLOGIES FOR THE DIRECTED DISCOVERY OF NONRIBOSOMAL PEPTIDES

Abstract

<p>Nonribosomal peptides (NRPs) are a major class of natural products known for their biological activities and are employed therapeutically as immunosupressants, anticancer agents, and antibiotics. Nonribosomal peptides are microbial products, biosynthesized by large assembly line-like enzymes, known as nonribosomal peptide synthetases (NRPSs) that can be found in large gene clusters within the genome. With the advent of genome sequencing, the gene clusters for known NRPs are easily identified within producing organisms, but more strikingly, this sequencing reveals that microbes often contain many gene clusters with no known products suggesting traditional methods of isolation are overlooking the majority of NRPs.</p> <p>Extensive studies of NRPS functions have revealed assembly line logic for the biosynthesis of NRPs and using this knowledge, the NRP products of NRPS gene clusters can be predicted. In this research, products from both a simple dimodular NRPS from <em>Staphylococcus aureus </em>and a complex 11 module NRPS from <em>Delftia acidovorans </em>were predicted and used to successfully identify and isolate two novel NRPs, aureusimine and delftibactin.<em> </em>Theses compounds fell outside traditional NRP activities, one being a virulence regulator and the other a gold-complexing metallophore. Subsequent biosynthetic studies of the aureusimine gene cluster within the heterologous host, <em>Escherichia coli</em>, provide insight into NRPS flexibility for the creation of NRP natural variants and highlighted the utility of <em>E. coli </em>for the heterologous production of NRPs.</p> <p>Realizing single NRP predictions are not always accurate, a strategy was devised to use a genomically predicted NRP fragment barcode databases with the LC-MS/MS dereplication algorithm, iSNAP, to chemoinformatically identify and physically locate genetically predicted NRPs within crude extracts. This final contribution eliminates the need for bioactivity guided approaches to discovery and provides a strategy to systematically discover all predicted NRPs from cryptic gene clusters. This thesis delivers strategies and technologies for the directed discovery of NRPs from microbial sources.</p>