Center for Quantitative Biology: A focus on "omics", from organisms to single cells Supplement 1

人类胃肠道内有一个多样而密集的微生物群体， 肠道菌群这种微生物群体产生多种代谢物， 影响人体生理学。两类主要的肠道微生物群依赖性代谢物 是色氨酸代谢和胆汁酸代谢的生物活性副产物。的 微生物群的复杂性、个体间的差异以及色氨酸和 胆汁酸代谢产物的产生导致了知识差距周围的关系 代谢物通量和宿主基因表达之间的关系。解决这些知识是具有挑战性的 由于所需的技术专长的广度和深度，为了克服这一点，我们 组建了一个跨学科的团队。在这里，我们提出了一个团队研究项目， 来自用复杂或确定的微生物群定殖的小鼠的多组学数据生成， 与缺乏微生物群的无菌小鼠进行比较。我们将开发和使用先进的 新的多维数据分析方法，以揭示微生物群依赖的影响 代谢物通量对宿主基因表达的影响。在项目1和2中，PI Sundrud和Ross将 生成各种色氨酸和胆汁酸代谢物的定量代谢组学分析数据 从常规定殖的小鼠和用确定的微生物群定殖的无菌小鼠 由14种能够产生不同代谢物的人肠道来源的分离物组成。 宏基因组和转录组数据集，包括批量和单细胞RNA测序， 从每组的多个组织中产生，特别强调对肠 免疫细胞群体。在项目3和4中，PI Song和Hoen将开发和实施 将这些多组学数据整合到模型中的新方法， 代谢物丰度和宿主基因表达之间的关系。所有这些 项目代表了团队合作研究的新领域，并将建立 全面的数据集和模型，用于未来的合作赠款申请。

The human gastrointestinal tract harbors a diverse and dense population of microbes termed the gut microbiota. This microbial population produces diverse metabolites that collectively influence human physiology. Two prominent classes of gut microbiota-dependent metabolites are the bioactive byproducts of tryptophan metabolism and bile acid metabolism. The complexity of the microbiota, its variation across individuals, and the diversity of tryptophan and bile acid metabolites produced has resulted in a knowledge gap surrounding the relationship between metabolite flux and host gene expression. Addressing this knowledge is challenging due to the breadth and depth of technical expertise required and, to surmount this, we have assembled an interdisciplinary team. Here, we propose a team research project that leverages multi-omic data generation from mice colonized with either a complex or defined microbiota in comparison with germfree mice lacking microbiota. We will develop and employ sophisticated new multi-dimensional data analysis methods to reveal the impact of microbiota-dependent metabolite flux on host gene expression. In projects 1 and 2, PIs Sundrud and Ross will generate quantitative metabolomic profiling data of diverse tryptophan and bile acid metabolites from conventionally colonized mice and gnotobiotic mice colonized with a defined microbiota consisting of 14 human-gut-derived isolates capable of producing diverse metabolites. Metagenomic and transcriptomic datasets including bulk and single-cell RNA sequencing will be generated from multiple tissues in each group, with a specific emphasis on analysis of intestinal immune cell populations. In projects 3 and 4, PIs Song and Hoen will develop and implement new methodologies for integrating these multi-omic data into models which map the relationships between metabolite abundances and host gene expression. Together, these projects represent new areas of collaborative research for the team and will establish comprehensive datasets and models for future collaborative grant applications.