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: 7991431
• 负责人: Eric John Alm
• 金额: $ 21万
• 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/7991431
• 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; 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）：该项目将产生微生物群落高通量16 S rRNA测序的新技术。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，并已成为NIH主要路线图计划的目标。通过16 S 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，以及全基因组测序和宏基因组学。该项目将建立和优化（i）一套能够识别与宿主表型（广义上包括疾病状态、饮食、年龄、风险因素等）具体相关的人群的计算工具，和基于微生物组数据预测宿主表型，以及（ii）产生部分16 S rRNA序列的实验方法，其比常规方法便宜几个数量级，从而实现微生物组比较中前所未有的分辨率。该分析方法是先前成功模拟环境样品中细菌种群结构的延伸，但将适应微生物组研究的具体要求（例如，个体间差异较大）。测序方法的细节（有效的样品多重化、扩增引物的去除以及PCR条件/引物的优化以减少偏差）以及所生成的数据将可推广到大多数下一代测序技术，尽管所提出的工作将集中在Illumina平台上，因为其目前有利的成本能力属性。该项目的另一个科学目标是使用超深度测序来扩大正在进行的IBD患者临床研究的覆盖范围。该项目将与目前参与人类微生物组项目的主要测序中心布罗德研究所密切合作，并将广泛传播工具，以便获得的结果可以对该领域产生直接影响。 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的一项主要路线图计划。这项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，将深度16 S rRNA群落采样的成本降低几个数量级，对于>30，000 X的样本覆盖率，将其降低到约35美元，从而使个性化的微生物组分析触手可及。此外，作为该项目的一部分，将开发的计算工具将有助于从拟议的实验平台和其他正在进行的研究所支持的大量数据集中发现有意义的医学和生物学见解。