Genetic Control of Metabolic Flux in Response to Diet

项目摘要/摘要 尽管对人类和模型生物进行了多年的研究，但对于哪一种仍然没有明确的共识。 饮食与人类健康最相容。然而，这一说法的前提是单一饮食是理想的 对每个人都是。然而，在人类中，对包括身体在内的各种饮食的新陈代谢反应存在很大的差异 体重、糖耐量和血脂。不同基因的小鼠表现出同样的代谢变异性， 这表明遗传学在驱动饮食反应方面起着关键作用。此外，两者中的微生物群 人类和小鼠通过饮食营养物质和产品的新陈代谢来促进饮食反应。 强效代谢物。这个项目的前提是基因与饮食和肠道微生物群的相互作用 影响新陈代谢健康。使用一个远缘繁殖的小鼠模型系统，该系统具有与整个 人类种群，多样性远超种群，我们将遗传作图与饮食相互作用的基因座 以及影响心脏代谢表型的微生物群。我们将测试两种饮食，一种是低脂肪/高碳水化合物饮食 和高脂肪/低碳水化合物的饮食。将对小鼠进行葡萄糖耐量、胰岛素抵抗、 体重增加，以及血脂和代谢物的循环水平。使用15种稳定的同位素示踪剂，我们将进行 使用基于质谱学的同位素分析来测量代谢通量，使我们能够询问 多种组织中碳水化合物、脂肪和蛋白质代谢的主要途径。这将是第一次 代谢流受到了遗传筛选的影响。我们还将绘制肠道微生物组成和基因图谱 对关键代谢组织：肝脏、脂肪、肌肉和肠道的调节。这些研究将提供 这些表型的全面遗传图谱。通过鉴定共同映射的表型，我们 将进行中介分析，以构建连接基因座、代谢物、微生物组分类群的因果网络 和生理表型。我们将优先考虑与人类具有显著新陈代谢的基因座共线的基因座 GWAS中的协会。这些结果将提供代谢标记物，帮助预测个人的 对特定饮食的代谢反应，这是将饮食与个人相匹配的第一步。

PROJECT SUMMARY/ABSTRACT Despite many years of research in humans and model organisms, there remains no clear consensus about which diet is most compatible with human health. However, the premise of this statement is that a single diet is ideal for everyone. Yet, among humans, there is a wide range in metabolic response to various diets, including body weight, glucose tolerance, and plasma lipids. Genetically diverse mice show this same metabolic variability, suggesting that genetics plays a key role in driving diet-responsiveness. In addition, the microbiome in both humans and mice contributes to diet responsiveness through its metabolism of dietary nutrients and production of potent metabolites. The premise of this project is that genetic interactions with diet and the gut microbiome affect metabolic health. Using an outbred mouse model system that has as much genetic diversity as the entire human population, the Diversity Outbred population, we will genetically map the gene loci that interact with diet and the microbiome to affect cardiometabolic phenotypes. We will test two diets, a low-fat/high carbohydrate diet and a high-fat/low carbohydrate diet. The mice will be phenotyped for glucose tolerance, insulin resistance, weight gain, and circulating levels of lipids and metabolites. Using 15 stable isotope tracers, we will conduct metabolic flux measurements using mass spectrometry-based isotopomer analysis, enabling us to interrogate the major pathways of carbohydrate, lipid, and protein metabolism in multiple tissues. This will be the first time metabolic flux has been subjected to a genetic screen. We will also map gut microbial composition, and gene regulation in key metabolic tissues: liver, adipose, muscle and intestine. These studies will deliver comprehensive genetic maps of these phenotypes. Through the identification of phenotypes that co-map, we will perform mediation analysis to construct causal networks that link gene loci, metabolites, microbiome taxa and physiological phenotypes. We will prioritize loci that are syntenic to human loci with significant metabolic associations in GWAS. These results will provide metabolic markers that can help predict an individual’s metabolic response to specific diets, the first step towards matching diets to individuals.