Reverse Metabolomics for the Discovery of Disease Associated Microbial Molecules

项目总结/摘要 微生物-饮食-宿主相互作用对健康和疾病的平衡至关重要。理解 这一轴心对营养精准医学的发展具有重要意义。虽然有一些 微生物制造的分子能显著影响健康的重要发现， 微生物群产生的蛋白质在结构上仍然没有被表征。此外，即使已知一种分子 而且活动是已知的，这些知识往往被埋在论文中，没有系统的 这些知识可以很容易地被数据科学家利用。这就防止了深层的 对微生物组的机械理解。本申请所应用的PAR-21-253的目标是 以及随附的RFA（RFA-DK-21-014）旨在建立微生物代谢物知识库， 被更大的科学界所使用。为了建立知识库，R 01由PAR-21资助， 253是发现赠款，将提供新的微生物代谢物及其生物活性的知识。 该提案将1）获得多达5，000，000个合成分子的MS/MS特征，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 微生物群合成偏向于常见的生物转化。这将是最大的 代谢组学参考数据集曾经组装，即使所有公共和非公共图书馆相结合; 2)我们将使用我们的大数据挖掘策略，特别是我们的质谱搜索工具，不仅 发现什么分子是由微生物，但也了解表型，疾病，器官/组织/生物流体， 3）新发现的微生物分子，在炎症中上调或下调， 肠道疾病（和其他肠道代谢紊乱）将在基于细胞的检测中进一步筛查， 动物研究，以了解新发现的微生物代谢产物的生物效应; 4）我们将 将R 01获得的所有知识转移到将由 伴随RFA。 PI和Co-I非常适合帮助建立拟议的知识库，因为他们具有以下方面的专业知识： 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），并有做非常大的项目和分享的记录 为了社区的利益，新发现的知识被公开-通常在几年前就可以获得 任何出版物（Dorrestein，Knight）。

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).