Reverse Metabolomics for the Discovery of Disease Associated Microbial Molecules

项目摘要/摘要 微生物区系-饮食-宿主的相互作用对健康和疾病的平衡至关重要。理解 这一轴心将对营养精准医学的发展起到重要作用。尽管有一些 重要的发现，微生物制造的分子对健康有重大影响，大多数分子 由微生物群产生的物质在结构上仍未确定。此外，即使当一个分子已知 而活动是已知的，这种知识往往埋藏在论文中，并没有一个系统的 数据科学家可以很容易地利用这些知识的组织。这防止了深层次的 对微生物组的机械理解。本申请所适用的PAR-21-253的目标 与RFA(RFA-DK-21-014)配套的是建立一个微生物代谢产物知识库，该知识库可以 被更大的科学界使用。为了建立知识库，在PAR-21下资助的R01‘S- 253是发现基金，将提供有关新的微生物代谢物及其生物活性的知识。 这项提议将1)获得高达500万个合成分子的MS/MS签名，使用 组合/多样性驱动的合成，使用人类可获得的饮食和宿主前体 微生物区系。合成偏向于常见的生物转化。这将是世界上最大的 代谢组学参考数据集，即使所有公共和非公共图书馆组合在一起； 2)我们将使用我们的大数据挖掘策略，特别是我们的质谱分析搜索工具，不仅 了解微生物制造的分子，但也了解表型、疾病、器官/组织/生物体液， 食物关联；3)新发现的在炎症中上调或下调的微生物分子 肠道疾病(和其他肠道代谢紊乱)将在基于细胞的检测和结肠炎中进一步筛查。 动物研究，以了解新发现的微生物代谢物的生物学效应；4)我们将 将此R01获得的所有知识转移到将由 随行的RFA。 由于PI和CO-I在以下方面的专业知识，他们非常适合帮助建立拟议的知识库 微生物代谢组学(Dorrestein)、合成(Dorrestein，Siegel)、微生物组(Dorrestein，Knight， Raffatellu)，数据科学(Dorrestein，Knight)，以及在做超大型项目和分享方面的记录 为社区造福而公开发现的新知识--通常在多年前提供 任何出版物(多雷斯坦、奈特)。

Project Summary/Abstract The Microbiota-Diet-Host interactions are critical to the balance of health and disease. Understanding this axis will be important to the development of nutritional precision medicine. Although there are some important discoveries where microbes make molecules that dramatically affect health, most of the molecules produced by microbiota still remain structurally uncharacterized. In addition, even when a molecule is known and the activity is known, this knowledge tends to be buried in papers and there is not a systematic organization of this knowledge that can be readily leveraged by data scientists. This prevents a deep mechanistic understanding of the microbiome. The goal of PAR-21-253 to which this application is applying to and the accompanying RFA (RFA-DK-21-014) is to build a microbial metabolite knowledgebase that can be used by the larger scientific community. In order to build the knowledgebase, the R01’s funded under PAR-21- 253 are discovery grants that will provide the knowledge of new microbial metabolites and their bioactivities. This proposal will 1) obtain MS/MS signatures for up to 5,000,000 molecules synthesized, using combinatorial/diversity driven synthesis, using diet and host precursors that are accessible to human microbiota. The synthesis is biased towards common bio-transformations. This will be the largest metabolomics reference data set ever assembled, even when all public and non-public libraries are combined; 2) we will use our big data mining strategies, especially our mass spectrometry search tools, to not only discover what molecules are made by microbes, but also understand phenotype, disease, organ/tissue/biofluid, food associations; 3) the newly discovered microbial molecules that are up or down regulated in inflammatory bowel disease (and other gut metabolic disorders) will be further screened in cell-based assays and colitis animal studies to understand the biological effects of the newly discovered microbial metabolites; 4) we will transfer all the knowledge obtained by this R01 to the knowledgebase that will be created by the accompanying RFA. The PIs and Co-Is are well suited to help build the proposed knowledge base, due to their expertise in microbial metabolomics (Dorrestein), synthesis (Dorrestein, Siegel), microbiome (Dorrestein, Knight, Raffatellu), data science (Dorrestein, Knight) and having a track record of doing very large projects and share newly discovered knowledge publicly for the benefit of the community – generally made available years before any publication (Dorrestein, Knight).