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：
10066073
负责人：
Zachary Walter Beller
金额：
$ 3.15万
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/10066073
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.

项目概要/摘要肠道微生物群与人类健康的许多特征有关，催生了开发确定微生物群导向的疗法或益生元以进行安全、有效的操作。微生物群的变化是当前精准医学计划的一个高度优先目标，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，并获得对肠道群落动态的基本了解。已被证明对微生物介导的健康有益。产生这些效应的因素是（i）它们的成分复杂性（例如，生物活性是什么）聚糖？），（ii）对哪些细菌使用纤维中特定成分聚糖的了解有限，以及（iii）竞争以及细菌之间对这些聚糖的合作。纤维的数量和肠道菌群成员相互作用，决定对基于纤维的益生元的反应。了解这些相互作用及其潜在机制将为改进的开发提供信息微生物群导向的治疗。我计划通过一系列实验来验证这一假设，AIM 1 将识别纤维依赖性。由测序、培养的细菌菌株组成的人类肠道微生物模型中的细菌相互作用在将其安装在无菌小鼠体内之前，我将系统地从该模型群落中剔除细菌。引入具有代表性的“不健康”低纤维高饱和脂肪美国饮食±补充的小鼠使用纯化的植物源膳食纤维，我将分析社区操纵/纤维的影响。使用正向遗传筛选（全基因组）补充细菌基因表达和丰度。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 AIM 2 将通过新颖的方式扩展这些限生/多组学研究。使用 CRISPR 技术，可以选择性地消除已建立的目标细菌这项工作将加深我们对微生物群功能的理解。以及我们如何推动社区走向稳定、有益的状态，我将生成并分析许多内容。多组学数据集，同时接受人类微生物组领先研究人员的出色科学培训科学和计算生物学一起，以及一流的临床指导和培训。华盛顿大学SOM，这个建议将帮助我发展成为一名独立的医师科学家。