The UCSD Microbiome and Metagenomics Center

加州大学圣地亚哥分校微生物组和宏基因组学中心

• 批准号: 10386327
• 负责人: Jack Anthony Gilbert
• 金额: $ 54.98万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-23 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10386327
• 关键词: Address; Algorithms; American; Archaea; Area; Artificial Intelligence; Assimilations; Bacteria; Benchmarking; Bioinformatics; Biological Markers; California; Collaborations; Collection; Communication; Communities; Community Outreach; Computer software; Consensus; Core Facility; Cost efficiency; DNA; Data; Data Analyses; Data Provenance; Detection; Development; Elements; Ensure; Eukaryota; Faculty; Feces; Feedback; Fellowship; Generations; Goals; Health; Human; Infrastructure; International; Investments; Laboratory Research; Leadership; Libraries; Metagenomics; Microbe; Mission; National Institute of Diabetes and Digestive and Kidney Diseases; Nutritional Study; Participant; Persons; Pilot Projects; Planet Earth; Positioning Attribute; Precision Health; Preparation; Procedures; Process; Production; Protocols documentation; Quality Control; Quality of life; RNA; Recording of previous events; Reproducibility; Research; Research Design; Research Support; Resolution; Sampling; Scientific Advances and Accomplishments; Scientist; Services; Sum; Supercomputing; System; Taxonomy; Technology; Time; United States National Institutes of Health; Universities; Virus; Visualization; base; beta diversity; biobank; bioinformatics infrastructure; cost; cost efficient; data access; data format; data management; data sharing; data visualization; density; detection sensitivity; experience; improved; innovation; innovative technologies; interest; laptop; metagenome; metaproteomics; metatranscriptomics; microbial; microbiome; microbiome analysis; microbiome research; multidisciplinary; nutrition; open source; operation; precision nutrition; recruit; sample collection; statistics; stool sample; success; synthetic construct; tool; ultra high resolution; undergraduate student

Project Summary The University of California San Diego (UCSD) Microbiome and Metagenomics Center (MMC) as part of the Nutrition for Precision Health (NPH) consortium will provide rapid, robust stool sample processing, high-quality metagenomic and metatranscriptomic data generation, and best-in-class bioinformatic analysis. We will optimize our protocols for DNA and RNA extraction from stool, metagenomic and metatranscriptomic library preparation, sequencing, and bioinformatics for ultra-high resolution taxonomic and functional profiling of the microbiome, including bacteria, archaea, eukaryotes, and viruses. We will offer analytical services and expertise on study design, sample collection, statistics, artificial intelligence, and host-microbe data interpretation to support other NPH centers and develop standard operation procedures with the Research Coordinating Center (RCC). Our team has developed uniquely innovative approaches to provide metagenomic and metatranscriptomic data at a cost that facilitates application to all 17,500 samples provided by the BioBank, with robust quality control to ensure high-quality raw and processed data products. We are also able to provide absolute quantification of microbial load through our recent innovation in synthetic DNA ‘spike-ins', which also facilitates rigorous assessment of contamination and extraction efficiency. Beyond bringing cutting edge technology that we have developed to the consortium, we also propose 3 Pilot Projects: (i) long-read data assembly; (ii) multiplexed metaproteomics; and (iii) automated stool sample collection and processing, so as to improve the taxonomic and functional resolution of profiling and improve biomarker detection sensitivity using dense timeseries. Importantly, our team is also optimally positioned to develop community consensus for the analysis strategies agreed on during the planning year, as well as to address the challenges of integrating microbiome data into the NPH consortium, due to our: existing high-throughput sample processing, sequencing, and data analysis cores; tight integration among disciplinary groups; access to supercomputing infrastructure; data visualization expertise; and tight coordination with an international braintrust of scientists who have been selected based on their complementary expertise in different areas of microbiome and precision nutrition research. This center will also benefit from cross-campus institutional commitment to provide 4 undergraduate, 5 postgraduate, and 6 postdoctoral fellowships, enabling faculty engagement and the development of innovative technologies and algorithms to advance NPH consortium goals. Additionally, our existing community outreach experiences can further support the NPH consortium’s goal to provide respectful, accessible and engaging feedback to the participants. Essential to the success of the MMC is the 35% time-commitment of the PI who has an outstanding track record in leading similar scale efforts. As a key part of the NPH consortium, we aim to democratize microbiome data by reducing cost, time, and computational requirements and coordination of multidisciplinary expertise required for data analyses and interpretation to achieve the ambitious goals of precision nutrition.

项目概要 加州大学圣地亚哥分校 (UCSD) 微生物组和宏基因组学中心 (MMC) 作为该中心的一部分 精准健康营养 (NPH) 联盟将提供快速、稳健的粪便样本处理、高质量 我们将优化宏基因组和宏转录组数据生成以及一流的生物信息分析。 我们从粪便中提取 DNA 和 RNA、宏基因组和宏转录组文库制备的方案， 测序和生物信息学，用于微生物组的超高分辨率分类和功能分析， 我们将提供分析服务和研究专业知识。 设计、样本收集、统计、人工智能和宿主-微生物数据解释，以支持其他 NPH 与我们的研究协调中心 (RCC) 合作并制定标准操作程序。 团队开发了独特的创新方法来提供宏基因组和宏转录组数据 成本有利于应用于 BioBank 提供的所有 17,500 个样本，并通过严格的质量控制来 确保高质量的原始和处理数据产品。我们还能够提供绝对量化的数据。 通过我们最近在合成 DNA“spike-ins”方面的创新来减少微生物负荷，这也促进了严格的 除了带来我们拥有的尖端技术之外，还评估污染和提取效率。 我们还向联盟提出了 3 个试点项目：(i) 长读数据组装；(ii) 多路复用； 宏蛋白质组学；以及（iii）自动化粪便样本收集和处理，以改进分类学和 重要的是，使用密集时间序列提高分析的功能分辨率并提高生物标志物检测灵敏度。 我们的团队也处于最佳位置，可以就商定的分析策略达成社区共识 规划年期间，以及解决将微生物组数据整合到 NPH 中的挑战 联盟，由于我们： 现有的高通量样品处理、测序和数据分析核心； 学科群体之间的整合；获得超级计算基础设施的数据可视化专业知识； 与国际科学家智囊团密切合作，这些科学家是根据自己的能力选出的 该中心还将在微生物组和精准营养研究的不同领域提供互补的专业知识。 受益于跨校园机构承诺，提供 4 名本科生、5 名研究生和 6 名研究生 博士后奖学金，促进教师参与和创新技术的开发 此外，我们现有的社区外展经验可以。 进一步支持 NPH 联盟的目标，即向 MMC 成功的关键是具有杰出表现的 PI 投入 35% 的时间。 作为 NPH 联盟的重要组成部分，我们的目标是实现民主化。 通过减少成本、时间和计算要求以及多学科协调来获取微生物组数据 数据分析和解释所需的专业知识，以实现精准营养的宏伟目标。