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）的化学生物学广泛感兴趣。我们试图找出新的模式- 由不寻常的酶转化形成的结构。一个成功的方法是， 建立一个创新的发现工作流程，包括大数据基因组学。随着测序革命 加快步伐，我们正在利用这一巨大的资源，生物信息学识别，分类，和实验 表征精心挑选的新型NP。对于这个项目，我们专注于细菌纳米粒子有几个原因：（i） 细菌是分子探针和药物先导的最重要的历史来源。这些化合物是- 揭示了全新的生物学，也改变了许多人类疾病的治疗方法。(ii)细菌 在遗传/分类学广度、化学/代谢能力和地理位置方面， 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成 有组织的集群，这有利于它们的生物信息学识别和随后的实验特征- 是的。该提案将大数据基因组学、合成生物学和现代化学生物学结合起来， 在功能上表征新型NP。在此，我们靶向预测展示以下分子结果的途径： 新的酶促转化，重点关注宏基因组衍生途径，特别是来自细菌的途径 与无脊椎动物有关的。 几个容易培养的细菌属已被广泛研究，建立了某些分类群， NP的多产来源（例如土壤中的链霉菌）。然而，知识是稀疏的可耕地少背- teria，代表了绝大多数微生物多样性。直到最近， 出现了将宏基因组数据测序和组装成有用长度的读段的技术。作为其中的一部分 项目，我们重新利用了牛仔竞技表演，我们的开放获取，用户友好的基因组挖掘工具，以分析数据来源， 来自宏基因组/微生物组测序项目。“MetaRODEO”将通过隔离和 几个不同的NP类的特征。我们的工作集中在无脊椎动物共生细菌的纳米颗粒上- 许多物种与它们的低等动物宿主有着长期而密切的伙伴关系。 毫无疑问，进化的力量塑造了生物活性，改善了药代动力学，并减少了药物的毒性。 与土壤共生体相比，来自细菌共生体的NP的动物毒性。 该项目涉及三个相互关联但可独立实现的具体目标。目的我专注于基因组 测序、生物信息学分析和来自无脊椎动物的一流RIPP的分离/表征 微生物组目标II集中在新的RIPPs和其他来自微生物组的生物合成途径的NP- 使用自由基SAM酶的方法。目的III扩展了NPs识别的环境起源和化学性质， 我们的算法通过靶向多烯大环内酯类药物来验证。每个目标将阐明新的NP结构并评估 生物活性使用严格的，多层次的战略。