Genomics Accelerated Natural Product Discovery

基因组学加速天然产物发现

• 批准号: 10793456
• 负责人: Douglas Alan Mitchell
• 金额: $ 12.09万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10793456
• 关键词: Acceleration; Algorithms; Anabolism; Animals; Bacteria; Big Data; Bioinformatics; Biological; Biology; Chemicals; Classification; Data; Development; Drug Kinetics; Emerging Technologies; Enzymes; Gene Structure; Genetic; Genome; Genomics; Geography; Invertebrates; Knowledge; Length; Life; Macrolides; Metabolic; Metagenomics; Mining; Modernization; Molecular; Molecular Probes; Molecular Structure; Natural Products; Natural Products Chemistry; Natural Source; Pathway interactions; Pharmaceutical Preparations; Polyenes; Process; Resources; Shapes; Soil; Source; Streptomyces; Structure; Taxonomy; Toxic effect; genomic data; human disease; improved; innovation; interest; metagenome; microbial; microbiome; microbiome sequencing; novel; screening; symbiont; synthetic biology; tool; user-friendly

Our group is broadly interested in the chemical biology of natural products (NPs). We seek to identify new mo- lecular structures that are formed by unusual enzymatic transformations. One successful approach was the de- velopment of an innovative discovery workflow that embraces big data genomics. With the sequencing revolution picking up pace, we are leveraging this vast resource to bioinformatically identify, classify, and experimentally characterize carefully selected novel NPs. For this project, we focus on bacterial NPs for several reasons: (i) Bacteria are the most historically significant source of molecular probes and drug leads. Such compounds re- vealed fundamentally new biology and also transformed the treatment of many human diseases. (ii) Bacteria dominate all other forms of life in terms of genetic/taxonomic breadth, chemical/metabolic capabilities, and geo- graphic/environmental diversity. (iii) Bacteria tend to organize the genes involved in NP biosynthesis into neatly organized clusters, which facilitates their bioinformatic identification and subsequent experimental characteriza- tion. This proposal unites big data genomics, synthetic biology, and modern chemical biology to structurally and functionally characterize novel NPs. Herein we target pathways predicted to showcase the molecular results of new enzymatic transformations with a strong focus on metagenome-derived pathways, especially from bacteria that associate with invertebrate animals. Several readily cultivated bacterial genera have been extensively studied, which established certain taxa as prolific sources of NPs (e.g. soil-dwelling Streptomyces). However, knowledge is sparse on less cultivable bac- teria, which represent the overwhelming majority of microbial diversity. Only relatively recently have the requisite technologies emerged to sequence and assemble metagenomic data into reads of useful length. As part of this project, we have repurposed RODEO, our open access, user-friendly genome-mining tool to analyze data deriv- ing from metagenome/microbiome sequencing projects. “MetaRODEO” will be validated through isolation and characterization of several distinct NP classes. We center our efforts on NPs from symbiotic bacteria of inverte- brates, given that numerous species have longstanding and intimate partnerships with their lower animal hosts. Evolutionary forces have undoubtedly shaped the bioactivity, improved the pharmacokinetics, and reduced the animal toxicity of NPs from bacterial symbionts compared to soil-dwelling counterparts. This project involves three interconnected but independently achievable specific aims. Aim I focuses on genomic sequencing, bioinformatics analysis, and isolation/characterization of first-in-class RiPPs from the invertebrate microbiome. Aim II centers on new RiPPs and other NPs derived from microbiome-derived biosynthetic path- ways that employ radical SAM enzymes. Aim III expands the environmental origin and chemistry of NPs identi- fied by our algorithm by targeting polyene macrolides. Each aim will elucidate new NP structures and evaluate biological activity using a rigorous, multi-tiered strategy.

我们的团队对天然产物（NPs）的化学生物学非常感兴趣。我们寻求识别新的mo-