课题基金 / 基金详情

Omics and Technology Core

Omics and Technology Core
组学和技术核心
批准号:
9795001
负责人:
Rima F Kaddurah-Daouk
金额:
$175.59万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-15 至 2024-08-31

项目摘要

项目成果

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中文摘要
翻译
摘要-核心1:组学和技术核心 组学和技术核心将作为一个门户网站,将项目的所有部分相互连接,并将提供 他们与高质量的基因组学,代谢组学和成像数据,将与临床和 表型信息。为了确保研究样本的最大科学产出,分析将 由各个领域的领导者和卓越中心进行。核心将与NCRAD密切合作,这将 实施标准化程序,在阿尔茨海默病中心收集样本,将协调 运输到我们的技术中心进行样品分析,并能够跟踪监管链。芯会 我还与生物信息学核心和杜克团队密切合作,以确保黄金标准的数据管理 并为整个科学界提供全面的数据挖掘。第一个子核心将进行 对收集的粪便样品进行宏基因组学分析,以分析整个微生物群落 栖息在肠道中将使用微生物DNA提取仪从标本中提取并纯化微生物基因组DNA。 市售的DNA试剂盒,之前由人类微生物组计划验证。文化- 独立的分子方法将包括鸟枪宏基因组测序, 全面的微生物群概况(细菌、病毒、古菌、真菌)。严格的序列数据分析将 利用一套先进的计算算法,根据基于分类或功能的数据 矩阵第二个子核心将对血液和粪便进行代谢组学分析,以分析宿主和 肠道微生物代谢组。综合代谢组覆盖率最好通过以下方式实现: 互补的方法,在这里,我们将应用各种先进的方法,非目标和目标 代谢组学非靶向代谢组学将利用极高分辨率质谱(MS)来检测 每个样品有数千个化合物光谱,并采用复杂的算法和广泛的数据挖掘 用于身份说明。相反,靶向代谢组学平台将利用更灵敏和定量的 MS/MS测量仅根据现有证据选择的数百种化合物, 特别是肠道微生物组的活性。全球代谢组学将是两者之间的交叉 方法,产生了几千种化合物的全扫描高分辨率MS测量,一些 通过真实的标准识别,而其他人不断添加到动态学习数据库, 检测到的化合物,进行进一步调查。第三个子核心将聚集定量磁共振 大脑成像,这为研究参与者的表型提供了额外的一层。建筑 由于ADNI项目的成功,将使用T1加权容积成像,以实现协调 跨多个站点。成像子核心将协调收集和汇总三个- 三维T1成像,并利用现有的ADCS图像信息学基础设施进行高通量数据 捕获上传和审查
英文摘要
ABSTRACT – Core 1: Omics and Technology Core The Omics and Technology Core will act as a portal that interconnects all parts of the project, and will provide them with high-quality genomics, metabolomics and imaging data, to be integrated with the clinical and phenotyping information. To ensure maximal scientific output from the study samples, analysis will be conducted by leaders in each field and centers of excellence. The core will work closely with NCRAD, that will implement standardized procedures for collection of samples across the Alzheimer Centers, will coordinate shipment to our technology hubs for sample analysis, and enable tracking of chain of custody. The core will also work closely with the bioinformatics core and the Duke team to ensure gold-standard data management and to enable comprehensive data mining for the whole scientific community. The first sub-core will conduct state of the art metagenomics analysis of collected fecal samples to profile the entire microbial community inhabiting the gut. Genomic microbial DNA will be extracted and purified from the specimens using a commercially-available DNA kit, previously validated by the Human Microbiome Project. The culture- independent molecular methods will consist of shotgun metagenomic sequencing that provides the most comprehensive microbiota profile (bacteria, viruses, archaea, fungi). Rigorous sequence data analysis will utilize a set of advanced computational algorithms, according to the taxon-based or function-based data matrices. The second sub-core will conduct metabolomics analysis of blood and feces, to profile the host and gut-microbiota metabolomes. Comprehensive metabolome coverage is best achieved via combination of complementary approaches, and here we will apply various advanced methods of untargeted and targeted metabolomics. Untargeted metabolomics will utilize very high-resolution mass spectrometry (MS) to detect many thousands of compound spectra per sample, and employ complex algorithms and extensive data mining for identity elucidation. Conversely, targeted metabolomics platforms will utilize more sensitive and quantitative MS/MS measurement of only hundreds of compounds chosen according to existing evidence, biological interest and specifically the gut microbiome activity. Global metabolomics will be a cross-over between the two approaches, producing a full-scan high-resolution MS measurement of a few thousands of compounds, some identifiable via authentic standards, while others continuously added to the dynamic learning database of detected compounds, for further investigation. The third sub-core will gather quantitative magnetic resonance imaging of the brain, which contributes an additional layer to the phenotyping of the study participants. Building from the success of the ADNI project, a T1-weighted volumetric imaging will be utilized, to allow harmonization across the multiple sites. The imaging sub-core will coordinate the collection and aggregation of three- dimensional T1 imaging, and utilize existing ADCS image informatics infrastructure for high-throughput data capture, upload, and review.
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Metabolomic Signatures for Disease Sub-classification and Target Prioritization in AMP-AD
  • 批准号:
    10084547
  • 项目类别:
  • 资助金额:
    $12.5万
  • 财政年份:
    2020
  • 负责人:
    Rima F Kaddurah-Daouk
  • 依托单位:
Administrative Core
  • 批准号:
    9795000
  • 项目类别:
  • 资助金额:
    $186.56万
  • 财政年份:
    2019
  • 负责人:
    Rima F Kaddurah-Daouk
  • 依托单位:
Project 3 - Mechanistic studies on role of gut microbiome in models for Alzheimer's disease
  • 批准号:
    9795005
  • 项目类别:
  • 资助金额:
    $44.55万
  • 财政年份:
    2019
  • 负责人:
    Rima F Kaddurah-Daouk
  • 依托单位:
Project 3 - Mechanistic studies on role of gut microbiome in models for Alzheimer's disease
  • 批准号:
    10017880
  • 项目类别:
  • 资助金额:
    $43.02万
  • 财政年份:
    2019
  • 负责人:
    Rima F Kaddurah-Daouk
  • 依托单位:
海外基金