High-resolution analysis of diversity and variation in the human microbiome
High-resolution analysis of diversity and variation in the human microbiome
批准号:
8089309
负责人:
Eric John Alm
金额:
$24.95万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-06-15 至 2012-05-31
关键词:
AddressAgeBacterial ModelBase SequenceBenchmarkingBiologicalCellsClassificationClinical ResearchCollaborationsCommunitiesComplexComputer softwareDataData SetDietDiseaseExcisionGenetic VariationGenomeGoalsHealthHumanHuman Genome ProjectHuman MicrobiomeIndividualInstitutesLaboratoriesLengthLightMedicalMetagenomicsMethodsMicrobeModelingMolecularPatientsPatternPhenotypePopulationPreparationProcessProtocols documentationPublic HealthReadingResearchResearch PersonnelResolutionRibosomal RNARisk FactorsRoleRunningSamplingStructureSurveysTaxonTechnologyTestingTimeUnited States National Institutes of HealthVariantWorkanalytical methodbasecomputer codecomputerized toolscostcost effectivedesigngenome sequencingimprovedinsightmathematical modelmeetingsmembermicrobialmicrobial communitymicrobiomenew technologynext generationnovelopen sourcepublic health relevancerRNA Genestool
中文摘要
项目描述(由申请人提供):本项目将产生微生物群落高通量16S rRNA测序新技术。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,并已被列为NIH路线图倡议的主要目标。16S rRNA测序是微生物组学研究的重要组成部分,与全基因组测序和宏基因组学齐名。该项目将建立并优化(i)一套能够识别与宿主表型(广义定义为包括疾病状态、饮食、年龄、风险因素等)特异性相关的种群的计算工具,并基于微生物组数据预测宿主表型;以及(ii)生成部分16S rRNA序列的实验方法,该方法比传统方法便宜几个数量级,从而在微生物组比较中实现前所未有的分辨率。该分析方法是先前成功的环境样品中细菌种群结构建模的扩展,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(有效的样品多路处理,去除扩增引物,优化PCR条件/引物以减少偏差),以及生成的数据将适用于大多数下一代测序技术,尽管提议的工作将集中在Illumina平台上,因为其目前有利的成本-性能属性。该项目的进一步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。该项目将与布罗德研究所密切合作,布罗德研究所是目前参与人类微生物组项目的一个主要测序中心,工具将广泛传播,以便获得的结果可以立即对该领域产生影响。
英文摘要
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.
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Epigenetics of the human gut microbiome
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批准号:10176496
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项目类别:
-
资助金额:$36.81万
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财政年份:2019
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负责人:Eric John Alm
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依托单位:
Epigenetics of the human gut microbiome
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批准号:10405552
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项目类别:
-
资助金额:$36.81万
-
财政年份:2019
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负责人:Eric John Alm
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依托单位:
Epigenetics of the human gut microbiome
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批准号:9790036
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项目类别:
-
资助金额:$36.81万
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财政年份:2019
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负责人:Eric John Alm
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依托单位:
Supplement: Epigenetics of the Human Gut Microbiome
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批准号:10818796
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项目类别:
-
资助金额:$8.88万
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财政年份:2019
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负责人:Eric John Alm
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依托单位:
Epigenetics of the human gut microbiome
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批准号:10022498
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项目类别:
-
资助金额:$36.81万
-
财政年份:2019
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负责人:Eric John Alm
-
依托单位:
Epigenetics of the human gut microbiome
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批准号:10626761
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项目类别:
-
资助金额:$36.81万
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财政年份:2019
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负责人:Eric John Alm
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依托单位:
Cultivation, Nature, Ecology and Pathogenicity of the Uncultivable Oral Microbiom
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批准号:8885797
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项目类别:
-
资助金额:$146.54万
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财政年份:2014
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负责人:Eric John Alm
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依托单位:
Cultivation, Nature, Ecology and Pathogenicity of the Uncultivable Oral Microbiom
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批准号:9042341
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项目类别:
-
资助金额:$143.54万
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财政年份:2014
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负责人:Eric John Alm
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依托单位:
Cultivation, Nature, Ecology and Pathogenicity of the Uncultivable Oral Microbiom
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批准号:8737392
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项目类别:
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资助金额:$150.89万
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财政年份:2014
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负责人:Eric John Alm
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依托单位:
High-resolution analysis of diversity and variation in the human microbiome
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批准号:7991431
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项目类别:
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资助金额:$21.0万
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财政年份:2010
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负责人:Eric John Alm
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依托单位:
国内基金
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