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.

我们的小组对天然产物（NP）的化学生物学广泛感兴趣，我们寻求识别新的分子。 通过不寻常的酶促转化形成的分子结构是一种成功的方法。 随着测序革命的发展，拥抱大数据基因组学的创新发现工作流程。 我们正在加快步伐，利用这一巨大的资源进行生物信息识别、分类和实验 表征精心挑选的新型纳米颗粒 在这个项目中，我们关注细菌纳米颗粒有几个原因：（i） 细菌是历史上最重要的分子探针和药物先导物来源。 (ii) 细菌 在遗传/分类广度、化学/代谢能力和地理方面主导着所有其他生命形式 图形/环境多样性。 (iii) 细菌倾向​​于将参与 NP 生物合成的基因整齐地组织起来。 有组织的簇，这有助于它们的生物信息识别和随后的实验表征- 该提案将大数据基因组学、合成生物学和现代化学生物学在结构和层面上结合起来。 在此，我们针对预测展示分子结果的途径进行了功能表征。 新的酶促转化，重点关注宏基因组衍生的途径，尤其是来自细菌的途径 与无脊椎动物有关。 主要研究了几个易于培养的细菌属，建立了某些分类单元： NP 的多产来源（例如土壤中的链霉菌），然而，对不易培养的细菌的了解却很少。 代表微生物多样性的绝大多数的细菌直到最近才具备了必要的条件。 作为其中一部分，出现了将宏基因组数据测序和组装成有用长度的技术。 项目中，我们重新调整了 RODEO 的用途，这是我们的开放获取、用户友好的基因组挖掘工具，用于分析数据推导 “MetaRODEO”将通过隔离和验证 我们将研究重点放在来自逆共生细菌的 NP 上。 鉴于许多物种与其低等动物宿主有着长期而密切的伙伴关系。 进化的力量无疑塑造了生物活性，改善了药代动力学，并减少了 与土壤中供体相比，来自细菌共生体的纳米颗粒对动物的毒性。 该项目涉及三个相互关联但可独立实现的具体目标，目标 I 专注于基因组。 来自无脊椎动物的一流 RiPP 的测序、生物信息学分析和分离/表征 微生物组。目标 II 以源自微生物组的生物合成途径衍生的新 RiPP 和其他 NP 为中心。 使用自由基 SAM 酶的方法扩展了 NP 的环境起源和化学特性。 我们的算法通过针对多烯大环内酯实现每个目标都将阐明新的 NP 结构并评估。 使用严格的、多层次的策略来检测生物活性。