MIRA: Enzymology and Self-Resistance of Natural Product Biosynthesis

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ABSTRACT Recent progresses in microbial genome sequencing and synthetic biology have created a renaissance in natural product discovery. This timely combination offers great promise to find natural products displaying new structures and biological activities. Notwithstanding such potential, it remains difficult to i) predict product structures directly from biosynthetic gene clusters (BGCs). This is because our knowledge of enzymes that are involved in natural product biosynthesis remains limited, especially with regard to the highly programmed enzymes from eukaryotic organisms such as filamentous fungi; ii) prioritize BGCs that can lead to new-to- nature chemical structures. This is primarily due to the focus of the field on well-studied natural product families and core biosynthetic enzymes; and iii) connect the biological activity with BGCs in genome mining efforts. This represents a gap between genome mining and traditional phenotypical screen-based discovery in which natural product isolation is guided by biological activity. This MIRA grant will address these limitations with a comprehensive research program focused on fungal natural product discovery and biosynthetic investigation. The first general area of this MIRA project is to gain fundamental understanding of core enzymes that participate in the biosynthesis of fungal natural products. In particular, we will focus on understanding the iterative programming rules of fungal PKSs and NRPSs. Other aspects of core enzyme programming rules, including cyclization and noncanonical domains will be investigated. We will also investigate the unusual tailoring enzyme activities of fungal biosynthetic pathways, with emphasis on PLP-dependent and oxidative enzymes. A number of compound driven biosynthetic investigations will be conducted. The second general area of this MIRA project is to develop and refine tools for genome mining. The most important research activity in this area is based on our recently developed resistance gene guided target genome mining, in which we use an co-clustered, resistant variant of the natural product target in the BGC as a guide to discover natural product of desired biological activity. This strategy can also be used to assign biological activities to known natural products. The objectives here are two- fold: 1) to expand the list of targets that may be identified via resistance gene, to enzymes and proteins in the central dogma, protein transport, metabolism, etc. Here we will perform genome mining and/or natural product bioactivity characterization to link metabolites to targets; and 2) to understand the mechanism of resistance, which will teach us how Nature evolves resistant enzymes, and refine our understanding of how to overcome potential resistance.