The relationship between host diet, the gut microbiota, and host transcription

描述（由申请人提供）：我们肠道中的微生物（即我们的微生物群）以及我们摄入的食物都代表了我们生理上的环境扰动。当我们摄入不同的食物时，肠道中每种物种的丰度都会发生巨大的变化，而这些食物的化学成分同样也会因肠道中微生物群的特定代谢能力而发生独特的变化。因此，我们的饮食、我们的微生物群和我们的生理构成了一个独特而复杂的基因、有机体和营养物质相互作用的系统。计算建模为理解和控制复杂系统提供了一系列工具；正是本着这种精神，我们的实验室继续开发统计模型，以了解我们的饮食、微生物群和健康之间的关系。为了实现这些长期目标，该应用程序有两个特定的目标，重点是预测模型，涉及从不同个体分离的六种定义的人类来源的微生物群。目标1：在我们之前成功使用含有10种人类肠道细菌的灵生小鼠来预测每种细菌对宿主饮食中特定成分扰动的丰度的基础上，我们的目标是通过模拟从不同人类供体分离并移植到灵生小鼠体内的六种定义微生物群的反应来理解我们的饮食和肠道微生物之间的定量关系。八种人类常吃食物的饮食紊乱。这些模型将深入了解控制饮食和微生物群之间规则的人际差异（例如，从两个不同供体分离出的大肠杆菌物种对相同食物的反应方式是否相似）。此外，Aim 1将提供有关饮食和微生物群之间关系的有价值的初步数据，这些数据将用于优化Aim 2的设计，其中我们将定义饮食，肠道微生物群和宿主转录变异之间的相互关系。通过在无菌动物和含有Aim 1中定义的微生物群的动物的背景下系统地干扰宿主饮食，我们计划模拟和量化宿主小肠、结肠和肝脏中受特定饮食成分、微生物群或饮食和微生物群组合影响的转录变化。

DESCRIPTION (provided by applicant): The set of microbes in our gut (i.e., our microbiota) as well as the food we ingest, both represent environmental perturbations to our physiology. The abundance of each species in our gut is dramatically altered as we consume different foods, while the chemical composition of these of foods is likewise uniquely modified in our intestines by the specific metabolic capabilities of the group of microbial organisms that resides there. Thus our diets, our microbiota, and our physiology represent a unique and complex system of interacting genes, organisms, and nutrients. Computational modeling provides a series of tools to understand and control complex systems; it is in this vein that our lab continues to develop statistical models to understand the relationship between our diet, our microbiota, and our health. Towards these long-term goals, this application has two specific aims focused on predictive models involving six defined human-derived microbiotas isolated from different individuals. Aim 1 - Building on our previous success in using gnotobiotic mice harboring a defined community of 10 human-gut bacteria to predict the abundance of each species in response to specific ingredient perturbations to the host diet, we aim to understand the quantitative relationship between our diets and our gut microbes by modeling the responses of six defined microbiota, isolated from different human donors and transplanted into gnotobiotic mice, to diet perturbations of eight commonly eaten human foods. These models will provide insight into the interpersonal variations governing the rules between diet and the microbiota (e.g., does an Escherichia coli species isolated from two different donors response to similar ways to the same food). In addition, Aim 1 will provide valuable preliminary data about the relationship between diet and the microbiota that will be used to optimize the design of Aim 2 where we will define the interrelationship between diet, the gut microbiota, and host transcriptional variation. By systematically perturbing the host diet in the context of germ-free animals and animals harboring the defined microbiotas from Aim 1, we plan to model and quantify the transcriptional changes in the host small intestine, colon, and liver that are influenced by specific diet ingredients, the microbiota, or a combination of diet and the microbiota.