High throughput biosynthesis of ribosomally synthesized and post-translationally modified peptide natural products

点击翻译按钮获取中文摘要

Chemicals produced by living systems, or natural products, have had a tremendous impact on human health. For example, nearly one third of all small molecule drugs approved by a regulatory agency over the past nearly four decades have been natural products or derivatives of natural products, including over 70% of antibiotics and 40% of anticancer drugs [1]. While very useful molecules have been identified among the hundreds of thousands of natural products that have been characterized to date, genome sequencing efforts over the past decade and a half have revealed that we have only characterized the products of a small fraction of the biosynthetic pathways that exist in nature. The products of these pathways have the potential to greatly impact the diagnosis and treatment of disease, and it is critical that we develop new approaches to accelerate the identification and characterization of new natural products and natural product-like compounds. Towards this critical need, my group focuses on the ribosomally synthesized and post-translationally modified peptide (RiPP) class of natural products [2], and the enzymes involved in their biosynthesis. Unique among natural product biosynthetic pathways, the substrate of the RiPP biosynthetic enzymes is a genetically encoded precursor peptide. This feature of the substrates allows for deep mutational analysis, not just of the enzymes, but of their substrates as well. We will develop a platform for high throughput examination of the substrate selectivity and activity of RiPP biosynthetic enzymes based on yeast or bacterial surface display, fluorescence activated cell sorting, and next generation sequencing. Using this platform and gene libraries encoding substrate variants we will study the substrate scope of these enzymes, and how that scope relates to the sequence of the native substrate of the enzymes. Additionally, we will perform deep mutational analysis of the enzymes to identify contributions to substrate recognition and selectivity. These studies will provide us with a deeper understanding of how these enzymes function. With this deeper understanding, we will be able to use these enzymes as tools to generate large libraries of natural product-like compounds that can be screened to identify those with useful biological activities more efficiently than current natural product discovery approaches.