Collaborative Research: Novel Statistical Tools for Metagenomics and Metabolomics Data

合作研究：宏基因组学和代谢组学数据的新型统计工具

• 批准号: 1903139
• 负责人: Jun Liu
• 金额: $ 35万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1903139&HistoricalAwards=false
• 关键词: Collaborative; Research; Novel; Statistical; Tools; Collaborative; Research; Novel; Statistical; Tools

Accumulating evidence suggests that disrupting intestinal microbial ecosystems can cause many serious diseases including chronic diseases such as coronary heart disease (CHD), neurobehavioral diseases such as autism, inflammatory diseases such as inflammatory bowel disease (IBD) and etc. For example, the developing infant intestinal microbiome has been implicated in central myelination and the maturation and function of microglia (CNS immune cells), a core deficiency in Autism Spectrum Disorders. Thus, the study of the gut microbial distributions and their metabolites are very important to find new therapeutic targets for many diseases. However, compared to the huge amounts of medical research on human cells, our understanding of the microbial ecosystem is very limited: the biodiversity of them is barely studied, not to mention their interactions with the human host. This project will develop a suite of statistical theory and methods as well as computational tools to facilitate the understanding of the intestinal microbial ecosystem. The proposed methods are fast, efficient, and highly accurate. They can be widely applied to any metagenomic and metabolomic investigations. Graduate students will be trained by participating in research activities. The main goal of this project is to extend our knowledge of intestinal microbial ecosystem by developing novel quantitative methods for microbial species and their metabolites detection, identification, and quantification in various diseases. The sensitivity and specificity of our methods permit accurate detection of microbial species at very low coverage levels. This is a translational technology that should find substantial use in biomedical researches and drug developments. More specifically, the PIs shall develop methods for identifying microbial species especially unknown species, reducing error in metabolomic analysis, estimating microbial and metabolite distributions, quantifying microbial or metabolites distributional differences that are associated with diseases, integrating metagenomic and metabolomic analysis together to study the microbial ecosystem, building analytical models to link metabolite profiling with species profiling to understand how metabolites interact with genetic contents and eventually affect cell metabolism.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

积累的证据表明，破坏肠道微生物生态系统会引起许多严重的疾病，包括慢性疾病，例如冠状动脉疾病（CHD），神经行为疾病，自闭症，例如自闭症，炎症性疾病，炎症性肠道疾病（IBD）等炎症性疾病等。 （CNS免疫细胞），自闭症谱系障碍的核心缺乏。因此，对肠道微生物分布及其代谢产物的研究对于找到许多疾病的新治疗靶标非常重要。但是，与人类细胞的大量医学研究相比，我们对微生物生态系统的理解非常有限：几乎没有研究它们的生物多样性，更不用说它们与人类宿主的相互作用了。该项目将开发一套统计理论和方法以及计算工具，以促进对肠道微生物生态系统的理解。提出的方法是快速，高效且高度准确的。它们可以广泛应用于任何宏基因组和代谢组学研究。研究生将通过参加研究活动来接受培训。 该项目的主要目标是通过开发针对微生物物种的新颖定量方法及其代谢物检测，鉴定和各种疾病的定量来扩展我们对肠道微生物生态系统的了解。 我们方法的灵敏度和特异性允许在非常低的覆盖率水平上准确检测微生物物种。这是一种转化技术，应该在生物医学研究和药物开发中进行大量使用。 More specifically, the PIs shall develop methods for identifying microbial species especially unknown species, reducing error in metabolomic analysis, estimating microbial and metabolite distributions, quantifying microbial or metabolites distributional differences that are associated with diseases, integrating metagenomic and metabolomic analysis together to study the microbial ecosystem, building analytical models to link metabolite profiling with species profiling to understand how代谢物与遗传含量相互作用并最终影响细胞代谢。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准被认为值得通过评估来支持。