Defining the contribution of interpersonal microbial variation to drug metabolism

描述(由申请人提供) 摘要：个体对药物的反应差异很大。人类胃肠道中巨大的微生物群落(微生物区系)已被证明在多个层面上影响药物代谢，但目前我们无法预测一个人的微生物区系是否使他们倾向于任何药物的高效或低效代谢。由于缺乏可处理的体内模型来捕捉人类之间存在的微生物群落差异，试图研究肠道微生物群落组成的人际差异与个体对药物治疗的反应之间的联系几乎是不可能的。这些挑战的解决方案可能会对医学治疗产生深远而迅速的影响，因为了解个人的微生物区系如何决定药物的药代动力学可以指导药物处方、给药途径和剂量。与人类基因组中的多态不同，肠道微生物群落组成可以快速修改，从而为个性化医学打开了新途径的大门，在这种方法中，患者-药物相互作用的两端都得到了优化，以实现最大利益。这项建议描述了一种新的方法来衡量微生物群落组成的人际差异与药物反应之间的关系：我们将从一大群无关的人类捐赠者中移植在多个时间点捕获的肠道微生物群落到其他相同的无菌小鼠组中，并测量这些动物的药物药代动力学。使用我们开发的方法在个性化培养集合中捕获个人肠道微生物群落的大部分，我们将通过在无菌小鼠中重建这些群落的全部或部分来测试群落组成和药物代谢之间的关联。我们将应用这些方法来理解为什么常用的治疗溃疡性结肠炎的药物对35%的患者无效，尽管有令人信服的证据表明肠道微生物与药物激活和失活有关。这些阐明个人微生物群差异如何影响药物新陈代谢的新实验方法，也将适用于衡量人际微生物差异对其他人类特征的影响，包括疾病和感染的易感性，甚至行为。

DESCRIPTION (Provided by the applicant) Abstract: Individuals vary widely in drug response. The enormous microbial communities (microbiota) in the human gastrointestinal tract have been shown to influence drug metabolism at multiple levels, but we cannot currently predict whether an individual's microbiota predisposes them towards efficient or inefficient metabolism of any drug. Attempts to examine the connections between interpersonal differences in gut microbial community composition and individual response to drug therapy have been nearly impossible due to the lack of tractable in vivo models that capture the microbial community variation that exists between humans. Solutions to these challenges could have a profound and rapidly translatable impact on medical therapy because an understanding of how an individual's microbiota determines drug pharmacokinetics could guide drug prescription, routes of administration, and dosage. Unlike polymorphisms in our human genomes, gut microbial community composition can be rapidly modified, opening the door to new approaches in personalized medicine in which both sides of the patient-drug interaction are optimized for maximum benefit. This proposal describes a novel approach for measuring the connections between interpersonal differences in microbial community composition and drug response: we will transplant gut microbial communities, captured at multiple timepoints, from a large cohort of unrelated human donors into groups of otherwise identical germfree mice and measure drug pharmacokinetics in these animals. Using methods we've developed to capture the majority of an individual's gut microbial community in personalized culture collections, we will test the associations between community composition and drug metabolism by re-building these communities, in whole or in parts, in germfree mice. We will apply these approaches to understand why drugs commonly used for ulcerative colitis are ineffective for 35% of patients despite compelling evidence implicating gut microbes in both drug activation and inactivation. These new experimental approaches for elucidating how differences in personal microbiomes influence drug metabolism will also be applicable for measuring the impact of interpersonal microbial differences on other human traits including predisposition to disease and infection, and even behavior.