Genomic and Metabolic Guided Discovery of Bacterial Natural Products

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Authors

Chiriac, Dragos

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thesis

Language

eng

Keyword

bioinformatics , machine learning , natural products , biosynthesis

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Abstract

Natural products from bacteria have long been the source of inspiration of new pharmaceutical compounds spanning from immunosuppressants to antimicrobials. Rapid discovery of bacterial natural products is hampered by several roadblocks in identification, dereplication, and activation. The goal of my thesis was to explore these roadblocks and identify novel solutions to streamline natural product discovery. The first chapter provides background on natural product discovery and biosynthesis. It gives insight into how several genomic and metabolic tools work in order to dereplicate and guide the isolation of novel natural products. Throughout the thesis, the need for a genomic mining tool capable of finding natural product analogues is highlighted and used to explore medicinal space. Chapter two introduces the concept of scaffold guided genomic mining and propose how we can use it to identify novel therapeutic analogues with different drug-like properties. To overcome current challenges in biosynthetic gene cluster comparison needed for scaffold guided genomic mining a new method for defining gene clusters based on natural language processing algorithms was created. I then built the analogous cluster comparison information tool to streamline identification and dereplication of analogous gene clusters. Chapter 3 demonstrates the utility of the tool to identify a prodigiosin analogue BE-18591 in Streptomyces. The tambjamine like molecule BE-18591 had previously been isolated but no known biosynthetic gene cluster was known to produce it. The compound was isolated and the gene cluster architecture was compared to other known analogues to identify its biosynthetic origin. Chapter 4 provides personal outlook on how the tool described herein will be used in the future and what the landscape of natural product discovery will look like in the coming years.

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