High-resolution analysis of diversity and variation in the human microbiome

人类微生物组多样性和变异的高分辨率分析

• 批准号: 8089309
• 负责人: Eric John Alm
• 金额: $ 24.95万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2012-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8089309
• 关键词: Address; Age; Bacterial Model; Base Sequence; Benchmarking; Biological; Cells; Classification; Clinical Research; Collaborations; Communities; Complex; Computer software; Data; Data Set; Diet; Disease; Excision; Genetic Variation; Genome; Goals; Health; Human; Human Genome Project; Human Microbiome; Individual; Institutes; Laboratories; Length; Light; Medical; Metagenomics; Methods; Microbe; Modeling; Molecular; Patients; Pattern; Phenotype; Population; Preparation; Process; Protocols documentation; Public Health; Reading; Research; Research Personnel; Resolution; Ribosomal RNA; Risk Factors; Role; Running; Sampling; Structure; Surveys; Taxon; Technology; Testing; Time; United States National Institutes of Health; Variant; Work; analytical method; base; computer code; computerized tools; cost; cost effective; design; genome sequencing; improved; insight; mathematical model; meetings; member; microbial; microbial community; microbiome; new technology; next generation; novel; open source; public health relevance; rRNA Genes; tool

DESCRIPTION (provided by applicant): This project will result in new technologies for high-throughput 16S rRNA sequencing of microbial communities. Understanding the role of the human microbiome in health and disease is an emerging field, and has been targeted as a major NIH Roadmap Initiative. Microbial community analysis by 16S rRNA sequencing is a key component of microbiome studies, together with whole genome sequencing and metagenomics. This project will establish and optimize (i) a suite of computational tools that are capable of identifying populations specifically associated with host phenotypes (broadly defined to include disease state, diet, age, risk factors, etc.), and predicting host phenotype based on microbiome data, and (ii) an experimental approach to generating partial 16S rRNA sequences that is orders of magnitude less expensive than conventional methods thus enabling unprecedented resolution in microbiome comparisons. The analytical method is an extension of previously successful modeling of bacterial population structure in environmental samples, but will be adapted to the specific requirements of microbiome research (e.g., high variation between individuals). The details of the sequencing method (efficient sample multiplexing, removal of amplification primers, and optimization of PCR conditions/primers to reduce bias), and the data generated will be generalizable to most next- generation sequencing technologies, although the proposed work will focus on the Illumina platform because of its currently favorable cost-capability attributes. A further scientific aim of this project is to use ultra-deep sequencing to expand coverage of an ongoing clinical study of IBD patients. This project will be done in tight collaboration with the Broad Institute, a major sequencing center currently involved in the Human Microbiome Project, and tools will be widely disseminated so that results obtained can have an immediate impact on the field. PUBLIC HEALTH RELEVANCE: Understanding the role of the microbiome in human health and disease is a major NIH Roadmap Initiative. The proposed work will directly impact researchers engaged in human microbiome studies by lowering the cost of deep 16S rRNA community sampling by orders of magnitude to ~$35 for >30,000X coverage of a sample, thus bringing personalized microbiome analysis within reach. In addition, the computational tools that will be developed as part of this project will help to uncover meaningful medical and biological insight from the massive data sets enabled by the proposed experimental platform and other ongoing studies.

描述（由申请人提供）：该项目将为微生物群落的高通量16S rRNA测序提供新的技术。了解人类微生物组在健康和疾病中的作用是一个新兴领域，并且已成为一项主要的NIH路线图计划。通过16S rRNA测序进行的微生物群落分析是微生物组研究的关键组成部分，以及整个基因组测序和宏基因组学。该项目将建立和优化（i）一套计算工具，能够识别与宿主表型特别相关的人群（广泛定义为包括疾病状态，饮食，年龄，危险因素等），并根据微生物组数据进行预测宿主表型，以及（II），比以下是较低的16S RRNA序列的实验方法，以实现较低的速度rRNA序列。微生物组比较。分析方法是对环境样本中细菌种群结构的先前成功建模的扩展，但将适应微生物组研究的特定要求（例如，个体之间的高差异）。测序方法的细节（有效的样品多路复用，消除放大引物的去除以及PCR条件/引物的优化以减少偏差），并且生成的数据将是大多数下一代测序技术的推广性，尽管拟议的工作将集中在Illumina平台上，因为其当前有利的成本率属性。该项目的进一步科学目的是使用超深测序来扩大对IBD患者的临床研究的覆盖范围。该项目将与Broad Institute紧密合作，该研究所目前参与了人类微生物组项目，并且工具将被广泛传播，以便获得的结果可以直接影响该领域。 公共卫生相关性：了解微生物组在人类健康和疾病中的作用是NIH路线图的主要计划。拟议的工作将直接影响从事人类微生物组研究的研究人员，通过降低16S rRNA社区的成本，通过数量级的数量级降低到约35美元，以> 30,000倍的样本覆盖范围，从而使个性化的微生物组分析在范围内。此外，将作为该项目的一部分开发的计算工具将有助于发现有意义的医学和生物学洞察力，从拟议的实验平台和其他正在进行的研究实现的大量数据集中。