A Web-Enabled Database for Rapid Metagenomic Biocatalyst Discovery and Validation

用于快速发现和验证宏基因组生物催化剂的网络数据库

• 批准号: 9048941
• 负责人: Jeffrey Kim
• 金额: $ 74.9万
• 依托单位: RADIANT GENOMICS, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9048941
• 关键词: Acoustics; Address; Advanced Development; Apache; Automation; Basic Science; Biochemical; Biodiversity; Bioinformatics; Biological Assay; Biomanufacturing; Characteristics; Cloud Computing; Cluster Analysis; Collection; Communities; Complement; Complex; Computer Simulation; DNA; DNA biosynthesis; Data; Data Set; Databases; Development; Economics; Environment; Enzymes; Feedback; Gene Delivery; Genes; Genetic Engineering; Genetic Variation; Genomics; Goals; Guanine + Cytosine Composition; Imagery; Laboratories; Length; Libraries; Liquid substance; Metadata; Metagenomics; Methods; Microfluidics; Mining; Molecular Biology; Natural Products; Nucleotides; Nutrient; Organism; Outcome; Performance; Phase; Preparation; Principal Component Analysis; Process; Property; Proteins; Protocols documentation; Recovery; Reporting; Research; Research Infrastructure; Research Personnel; Sampling; Services; Site; Source; Structure; System; Technology; Time; Traction; Validation; Variant; base; combinatorial; computer infrastructure; cost; distributed data; e-commerce; gene synthesis; improved; interest; meetings; metabolic engineering; metagenome; metagenomic sequencing; nanolitre; novel; prediction algorithm; programs; public health relevance; research and development; sample fixation; search engine; success; thermostability; tool; web-enabled

 DESCRIPTION (provided by applicant): Radiant Genomics proposes to develop an integrated enzyme discovery service, the Enzyme Variant Engine (EVE), built upon the largest cloned metagenomic sequence collection reported to date. The goal is to combine a publicly­accessible search engine, richly­annotated sequence database, arrayed sample library, and LIMS automation platform to deliver novel enzyme variants to end­users for lower cost, in less time, and from a greater pool of biodiversity than alternative options, such as DNA synthesis. Importantly, this service overcomes a major bottleneck in enzyme discovery that has traditionally focused on easily­cultivated organisms which are now known to represent less than 1% of biodiversity. Phase I research and development milestones were met or exceeded. In particular, we successfully demonstrated a high­efficiency sequencing workflow that will allow us to sequence and assemble our clone library, which is predicted to encode ~600M genes, >99% of which are derived from uncultivated and essentially unstudied organisms. We next demonstrated a combinatorial barcoding strategy that yields assemblies with an average length of >30 kilobases, a dramatic improvement in metagenomic contiguity. This feature enables the discovery of clusters of functionally related genes, such as those that encode complex natural products and nutrient fixation. These services were successfully integrated into an online search engine and e­commerce platform available at www.eve.bio. Finally, we developed and demonstrated infrastructure for an automated LIMS gene recovery system that can recover thousands of genes of interest from our arrayed library per week. The success of Phase I research was complemented by general improvements in sequencing cost­efficiency and cloud­computing. The EVE service has gained commercial traction and we believe further development will benefit basic research while positively impacting a broad range of biomanufacturing processes. Based on customer feedback, the aims of this proposal are 1) continued sequencing of the library using contiguity­preserving strategies 2) scaling of computational infrastructure 3) development of advanced enzyme selectors and 4) third­party database integration. The overall outcome of this program will be a centralized search engine which allows end­users to rapidly select and receive genes identified in bioinformatic analyses. These genes will be accessible for lower cost, in less time, and from a greater pool of genetic diversity than existing services. Overall, we believe that our platform will improve our understanding of sequence­to­function relationships and annotation for metagenomic environments, helping to bridge the gap between in silico and biochemical characterization from unexplored pools of genetic diversity.

 描述（由申请人提供）：Radiant Genomics 提议开发一种集成的酶发现服务，即酶变体引擎（EVE），该服务建立在迄今为止报道的最大的克隆宏基因组序列集合的基础上。目标是结合一个可公开访问的、带有丰富注释的搜索引擎。序列数据库、阵列样品库和 LIMS 自动化平台，可以比 DNA 合成等替代方案以更低的成本、更短的时间和更大的生物多样性库向最终用户提供新型酶变体。重要的是，这项服务克服了酶发现的一个主要瓶颈，该瓶颈传统上专注于易于培养的生物体，目前已知这些生物体仅占生物多样性的不到 1%，特别是，我们成功地证明了高效测序工作流程使我们能够对克隆文库进行测序和组装，预计该文库可编码约 600M 基因，其中 >99% 来自未培养且基本上未经研究的生物体。条形码策略产生平均长度> 30 kilobase的组装，宏基因组连续性的显着改善使得能够发现功能相关的基因簇，例如编码复杂天然产物和营养固定的基因簇。最后，我们开发并演示了自动化 LIMS 基因恢复系统的基础设施，该系统每周可以从我们的阵列库中恢复数千个感兴趣的基因。第一阶段的研究得到了测序成本效率和云计算方面的总体改进的补充，EVE 服务已经获得了商业吸引力，我们相信进一步的发展将有利于基础研究，同时对广泛的生物制造过程产生积极影响。建议是 1) 使用连续性保留策略继续对文库进行测序 2) 扩展计算基础设施 3) 开发先进的酶选择器和 4) 第三方数据库集成 该计划的总体成果将是一个集中式搜索引擎。允许最终用户快速选择和接收在生物信息分析中识别的基因。与现有服务相比，这些基因将以更低的成本、更短的时间从更大的遗传多样性库中获得。宏基因组环境的序列与功能关系和注释，有助于弥合计算机模拟和未探索的遗传多样性库的生化表征之间的差距。