Decoding Microbial Diversity in the Human Gut Microbiome

项目摘要/摘要 生态多样性的概念看起来很简单：存在什么生物以及它们是如何存在的 分布式的。高通量测序的出现使十多年来观察人类 微生物组研究；然而，这些研究经常确定两者之间的相关性，而不是因果关系 微生物多样性与健康。通过机制研究，我和其他人已经证明了紧张的重要性 变异，即一个物种内寄主-微生物组相互作用中的表型和基因变异；然而， 我们的大部分理解来自有限范围的模型生物，它们不能很好地代表大型生物 在人类胃肠道中观察到的多样性。与其将菌株多样性视为一种限制和警告 在微生物组研究中，我的团队采取了一种根本不同的方法：我们将其作为一种工具来开发 机械论研究。我的研究项目的使命是了解我们的微生物群落如何 塑造人类健康和生理。我们通过利用计算生物学和大数据来实现这一点 实验室实验包括灵知生菌动物模型，以平衡还原论和生物学相关性。这个 这项提案中的研究主题提出了关于宿主和微生物界面的离散问题，但都是统一的 在他们将自然发生的菌株变异与比较基因组学结合起来作为基因分析工具的方法中 在&gt；300基因组测序细菌分离株的参考小组中发现。主题我将问一个基本问题 问：我们能否利用10年的公开数据来合理地设计功能性合成材料 社区？这些联合体将作为了解Complex的组装和功能的工具 并将有翻译应用程序作为人类粪便移植治疗的替代方案。主旋律 II将专注于了解胆汁酸的共同宿主和微生物代谢(BAS)，胆汁酸是一类 与传染病和自身免疫性疾病、癌症和代谢健康具有广泛相关性的化合物。尽管 它们的重要性、BA代谢的微生物代谢途径及其系统发育分布 特征不佳的。通过对我们的菌株文库和合成群落的综合分析得出 因此，我们将确定具有生物学意义的生物体的起源。理解这些跨物种的途径 将解决一个重要的问题：我们能否根据一个群落的新陈代谢产出的总和来预测它 零件？主题III解决了医学中的一个紧迫问题：微生物菌株变异如何有助于 药物反应中的人际差异？我们现在正在研究一种新的重要的口服给药 以前不知道与肠道微生物群相互作用的药物：抗疟疾药。建立在初步的基础上 数据显示非目标菌株可变的抗菌效果，我们将描述细菌之间的相互作用 抗疟疾药物会影响治疗效果。这些主题有一个共同和统一的目标：同时产生 资源和对宿主-微生物相互作用的基本理解，从而导致翻译应用。

PROJECT SUMMARY / ABSTRACT The ecological concept of diversity is deceptively simple: what organisms are present and how are they distributed. The advent of high-throughput sequencing enabled more than a decade of observational human microbiome studies; however, these studies frequently established correlation, but not causation, between microbial diversity and health. Through mechanistic research, I and others have shown the significance of strain variation, i.e. phenotypic and genotypic variation within a species, in host-microbiome interactions; however, most of our understanding comes from a limited range of model organisms which poorly represent the large diversity observed in the human gastrointestinal tract. Rather than view strain diversity as a limitation and caveat in microbiome research, my group takes a fundamentally different approach: we exploit it as a tool for mechanistic research. The mission of my research program is to understand how our microbial communities shape human health and physiology. We do this through leveraging computational biology and big data with wet lab experiments including gnotobiotic animal models to balance reductionism and biological relevance. The research themes in this proposal ask discrete questions about the interface of host and microbe but are unified in their approach of using naturally occurring strain variation coupled to comparative genomics as a tool for gene discovery in a reference panel of >300 genome sequenced bacterial isolates. Theme I will ask a fundamental question: can we leverage 10 years of publicly available data to rationally design functional synthetic communities? These consortia will act as both tools for understanding the assembly and function of complex communities, and will have translational applications as alternatives to human fecal transplant therapy. Theme II will focus on deconvoluting the shared host and microbial metabolism of bile acids (BAs), a family of compounds with broad relevance to infectious and autoimmune diseases, cancer, and metabolic health. Despite their importance, the microbial metabolic pathways of BA metabolism and their phylogenetic distribution are poorly characterized. Through comprehensive analysis of our strain library and synthetic communities derived thereof, we will determine the origins of biologically significant BAs. Understanding these trans-species pathways will address an important question: can we predict the metabolic output of a community based on the sum of its parts? Theme III addresses an urgent question in medicine: how does microbial strain-variation contribute to interpersonal variation in drug response? We are now working on a new class of important orally administered drugs which were not previously known to interact with the gut microbiome: antimalarials. Building on preliminary data demonstrating off-target strain-variable antibacterial effects, we will characterize how bacterial interactions with antimalarials affect therapeutic efficiency. These themes have a shared and unified goal: to generate both resources and fundamental understanding of host-microbe interactions leading to translational applications.