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

肠道细菌相互作用对纤维益生元反应的影响

基本信息

批准号：
10166599
负责人：
Zachary Walter Beller
金额：
$ 5.05万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2023-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10166599
关键词：
Address Affect Animals Bacteria Bacterial Genes Bacterial Polysaccharides Bacteroides Biochemical Biology Biomass CRISPR/Cas technology Carbohydrates Clinical Clustered Regularly Interspaced Short Palindromic Repeats Communities Complex Computational Biology DNA Data Set Development Diet Dietary Fiber Dietary Supplementation Disease Environment Excision Fiber Food Functional disorder Gene Expression Genetic Determinism Genetic Screening Genome Gnotobiotic Goals Harvest Health Health Promotion Human Human Microbiome In Vitro Individual Knowledge Libraries Link Mass Spectrum Analysis Mediating Mentorship Metabolism Methods Microbe Modeling Mus Nutrient Organism Pathogenicity Pattern Physicians Pisum sativum Plants Polysaccharides Pre-Clinical Model Precision Medicine Initiative Preparation Proteomics Reagent Reproducibility Research Personnel Resolution Resources Sampling Scientist Series Specificity Stimulus Structure Supplementation System Testing Therapeutic Time Training Universities Washington Work base design experimental arm experimental study fitness fruits and vegetables gut bacteria gut microbes gut microbiota human model improved in vivo knock-down member metabolomics microbial microbial community microbiome research microbiota microorganism interaction multiple omics mutant novel novel strategies prebiotics precision medicine protein expression repaired response saturated fat targeted treatment whole genome

项目摘要

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.

项目摘要/摘要肠道微生物群与人类健康的许多特征有关，产生了发展的努力微生物群定向治疗或益生元。确定策略/试剂以进行安全，高效的操纵微生物群是当前精确医学计划的高优先级目标。实现这一目标需要信息丰富的临床前模型，以描述益生元对肠道微生物的影响的大小和机制并托管生物学，并获得对肠道社区动态的基本理解。基于纤维的食物已证明对微生物介导的对健康有有益的影响。了解饮食纤维产生的这些效果被（i）它们的复合复杂性（例如，生物活性是什么）（ii）对哪种细菌在纤维中使用特定组成的聚糖和（iii）竞争的有限知识有限和细菌在这些聚糖上的合作。我假设多糖组件纤维和肠道社区成员的互动，以决定对基于纤维的益生元的反应。了解这些互动及其潜在机制，将为发展的发展提供信息微生物群定向治疗。我计划在一系列实验目标中检验这一假设。 AIM 1将识别纤维依赖性模型中的细菌相互作用人类肠道微生物群，由测序的，培养的细菌菌株组成安装在gnotobiotic小鼠中。我将系统地省略该模型社区的细菌引入喂养代表的“不健康”低纤维高饱和脂肪的美国饮食±补充的小鼠的简介带有纯化的植物衍生的饮食纤维。我将分析社区操纵/纤维的影响补充细菌基因表达和抽象。使用正向遗传筛选（整个基因组转座子突变库）和基于质谱的蛋白质组学和代谢组学，我将表征细菌纤维反应的遗传决定剂和纤维制剂的生物活性成分跨越有益的社区环境。 AIM 2将通过新颖使用CRISPR技术，可以从已建立的在纤维补充饮食环境中的社区。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社区朝着稳定，有益的国家迈进。我将生成并分析许多多运动数据集在接受人类微生物组领先研究人员的出色科学培训的同时科学与计算生物学。共同提供了出色的临床心理和培训华盛顿大学SOM，该建议将帮助我发展成为独立的身体科学家。