Impact of Gut Bacterial Interactions on the Response to Fiber-Based Prebiotics

项目概要/摘要 肠道微生物群与人类健康的许多特征有关， 微生物群定向治疗剂或益生元。确定安全、有效操作的策略/试剂 微生物群是当前精准医学倡议的高度优先目标。实现这一目标需要 描述益生元对肠道微生物影响的程度和机制的临床前模型 和宿主生物学，并获得肠道群落动态的基本了解。纤维食品 已被证明对健康具有有益的微生物介导的作用。了解膳食纤维 产生这些效果受到（i）它们的组成复杂性（例如，什么是生物活性 聚糖？），(ii)有限的知识，哪些细菌使用纤维中的特定成分聚糖，和（iii）竞争 以及细菌之间对这些聚糖的合作我假设多糖成分 纤维和肠道社区成员相互作用，决定对纤维益生元的反应。 了解这些相互作用及其潜在机制，将有助于开发更好的 微生物群导向疗法。 我计划通过一系列的实验目标来检验这个假设。AIM 1将识别光纤依赖 由测序的培养细菌菌株组成的人类肠道微生物群模型中的细菌相互作用 安装在gnotobiotic小鼠。我将系统地从这个模型社区中删除细菌， 向喂食代表性“不健康”低纤维高饱和脂肪USA饮食±补充剂的小鼠中引入 用一种纯植物来源的膳食纤维。我将分析社区操纵/纤维的影响 补充细菌基因表达和丰度。使用正向遗传筛选（全基因组 转座子突变体库）和基于质谱的蛋白质组学和代谢组学，我将描述 细菌纤维反应的遗传决定因素和纤维制剂的生物活性成分 跨信息社区环境。AIM 2将通过一种新的方法来扩展这些gnotobiotic/multi-omic研究。 使用CRISPR技术，允许从已建立的细菌中选择性去除靶细菌， 社区在纤维补充饮食的背景下。这项工作将完善我们对微生物群功能的理解 以及我们如何推动一个社区走向稳定、有益的状态。我将生成并分析许多 多组学数据集，同时接受来自人类微生物组领先研究人员的优秀科学培训 科学和计算生物学。加上一流的临床指导和培训， 华盛顿大学的SOM，这个建议将帮助我发展成为一个独立的医生，科学家。

Project Summary/Abstract The gut microbiota has been linked to many features of human health, spawning efforts to develop microbiota-directed therapeutics or prebiotics. Identifying strategies/reagents for safe, efficacious manipulation of the microbiota is a high priority goal of current precision medicine initiatives. Achieving this goal requires informative preclinical models to describe the magnitude and mechanism of prebiotics’ effects on gut microbes and host biology, and to obtain a fundamental understanding of gut community dynamics. Fiber-based foods have been shown to have beneficial microbially-mediated effects on health. Understanding how dietary fibers produce these effects is confounded by (i) their compositional complexity (e.g., what are the bioactive glycans?), (ii) limited knowledge of which bacteria use specific constituent glycans in fiber, and (iii) competition and cooperation between bacteria over these glycans. I hypothesize that the polysaccharide components of fibers and gut community membership interact to dictate responses to fiber-based prebiotics. Knowledge of these interactions, and their underlying mechanisms, will inform development of improved microbiota-directed therapeutics. I plan to test this hypothesis in a series of experimental aims. AIM 1 will identify fiber-dependent bacterial interactions in a model human gut microbiota composed of sequenced, cultured bacterial strains installed in gnotobiotic mice. I will systematically omit bacteria from this model community prior to its introduction into mice fed a representative ‘unhealthy’ low fiber high saturated fat USA diet ± supplementation with a purified plant-derived dietary fiber. I will analyze the effects of community manipulation/fiber supplementation on bacterial gene expression and abundance. Using forward genetic screens (whole genome transposon mutant libraries) and mass spectrometry-based proteomics and metabolomics, I will characterize the genetic determinants of bacterial fiber responses and the bioactive components of fiber preparations across informative community contexts. AIM 2 will extend these gnotobiotic/multi-omic studies through a novel use of CRISPR technology that allows for selective depletion of targeted bacteria from an established community in a fiber-supplemented diet context. This work will refine our understanding of microbiota function and how we might drive a community toward stable, beneficial states. I will generate and analyze many multi-omic datasets while receiving excellent scientific training from leading researchers in human microbiome science and computational biology. Together, with the stellar clinical mentorship and training provided by Washington University SOM, this proposal will help me to develop into an independent physician-scientist.