Decoding Microbial Diversity in the Human Gut Microbiome

解码人类肠道微生物组中的微生物多样性

• 批准号: 10713170
• 负责人: Jordan Adam Bisanz
• 金额: $ 38.3万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10713170
• 关键词: Address; Affect; Animal Model; Anti-Bacterial Agents; Antimalarials; Autoimmune Diseases; Big Data; Bile Acids; Biological; Communicable Diseases; Communities; Complex; Computational Biology; Coupled; Data; Equilibrium; Family; Gastrointestinal tract structure; Genetic Variation; Genome; Genotype; Gnotobiotic; Goals; Health; High-Throughput Nucleotide Sequencing; Human; Human Microbiome; Libraries; Malignant Neoplasms; Medicine; Metabolic; Metabolic Pathway; Microbe; Mission; Oral Administration; Organism; Output; Pathway interactions; Pharmaceutical Preparations; Phenotype; Phylogenetic Analysis; Physiology; Research; Resources; Shapes; Sum; Therapeutic; Variant; bile acid metabolism; comparative genomics; fecal transplantation; gene discovery; gut microbiome; host microbiome; host-microbe interactions; laboratory experiment; microbial; microbial community; microbiome research; model organism; programs; rational design; response; tool; translational applications; transplantation therapy

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.

项目摘要 /摘要 多样性的生态概念看似简单：存在哪些生物以及它们如何 分布式。高通量测序的出现实现了十多年的观察性人类 微生物组研究；但是，这些研究经常建立相关性，但没有因果关系 微生物多样性和健康。通过机械研究，I和其他人表现出菌株的重要性 宿主 - 微生物组相互作用中的变异，即物种内的表型和基因型变异；然而， 我们的大部分理解来自有限的模型生物，这些生物代表大型的生物 在人类胃肠道中观察到的多样性。而不是将应变多样性视为限制和警告 在微生物组研究中，我的小组采用了根本不同的方法：我们将其作为一种工具 机械研究。我的研究计划的使命是了解我们的微生物社区如何 塑造人类健康和生理学。我们通过利用湿的计算生物学和大数据来做到这一点 实验室实验，包括gnotobiotic动物模型，以平衡还原主义和生物学相关性。这 该提案中的研究主题询问有关主机和微生物界面的离散问题，但是统一的 在使用自然发生的应变变异的方法中，耦合与比较基因组学作为基因的工具 在> 300个基因组测序细菌分离株的参考面板中发现。主题我会问一个基本 问题：我们可以利用10年的公开数据来合理设计功能合成 社区？这些联盟将充当理解复杂的组装和功能的工具 社区，并将具有翻译应用作为人类粪便移植疗法的替代方法。主题 II将重点放在胆汁酸（BAS）的共享宿主和微生物代谢上，这是一个家族 与感染和自身免疫性疾病，癌症和代谢健康相关的化合物。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是 特征不佳。通过全面分析我们的应变库和合成社区得出的 其中，我们将确定生物学上显着的BAS的起源。了解这些跨物种途径 将解决一个重要的问题：我们可以根据其的总和来预测社区的代谢输出 部分？主题III解决了医学上的紧急问题：微生物应变变差如何有助于 药物反应的人际变化？我们现在正在研究一系列新的重要口头管理 以前不知道与肠道微生物组相互作用的药物：抗疟疾。基于初步 数据证明了不靶向应变变量的抗菌作用，我们将表征细菌相互作用 抗疟疾会影响治疗效率。这些主题具有共同的统一目标：同时生成 资源和对宿主 - 微生物相互作用的基本理解，导致转化应用。