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.

我们团队对天然产物(NP)的化学生物学有广泛的兴趣。我们寻求确定新的模式- 由不寻常的酶转化形成的集合体结构。一种成功的方法是去掉- 开发包含大数据基因组学的创新发现工作流程。伴随着测序革命 我们正在加快步伐，利用这一巨大的资源来通过生物信息进行识别、分类和实验 对精心挑选的新奇名词进行描述。在这个项目中，我们关注细菌NPs有几个原因：(I) 细菌是分子探针和药物线索的历史上最重要的来源。这类化合物再- 从根本上开创了新的生物学，也改变了许多人类疾病的治疗方法。(Ii)细菌 在遗传/分类广度、化学/新陈代谢能力和地理位置方面主导所有其他形式的生命 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，这有助于它们的生物信息学鉴定和随后的实验特征- 提顿。这一建议将大数据基因组学、合成生物学和现代化学生物学结合在一起，从结构上和 从功能上描述新的NP。在这里，我们以预测的途径为目标，展示分子结果 新的酶转化，特别是来自细菌的元基因组衍生途径 与无脊椎动物有关的生物。 对几个容易培养的细菌属进行了广泛的研究，确定了某些分类群为 NPs的丰富来源(例如土生链霉菌)。然而，在可培性较差的基础上，知识稀少。 代表绝大多数微生物多样性的细菌。直到最近才有必要的 出现了对元基因组数据进行排序并将其组合成有用长度的读数的技术。作为这项工作的一部分 项目中，我们重新调整了Rodeo的用途，这是我们的开放访问、用户友好的基因组挖掘工具，用于分析数据派生- 来自元基因组/微生物组测序项目的ING。“MetaRODEO”将通过隔离和 几个不同的NP类的特征。我们的努力集中在来自转化共生细菌的NPs上- Brates，因为许多物种与它们的低级动物宿主有着长期和亲密的伙伴关系。 进化的力量无疑塑造了生物活性，改善了药代动力学，并降低了 细菌共生体NPs与土壤共生体NPs的动物毒性比较。 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专注于基因组学 无脊椎动物中第一类RIPs的测序、生物信息学分析和分离/鉴定 微生物组。AIM II集中在来自微生物群生物合成途径的新的RIPP和其他NPs- 使用自由基SAM酶的方法。目的III阐述了NPs的环境来源和化学特征。 被我们的算法通过靶向多烯大环内酯来修正。每个目标都将阐明新的NP结构并评估 使用严格的、多层次策略的生物活动。