Understanding the contributions of microbiome-encoded drug metabolizing enzymes

项目摘要 相对于母体化合物，药物代谢物可以具有不同的功效和毒性特征，并且 药物代谢中的人际差异可以决定不良反应。值得注意的是， 低生物利用度，在延迟释放制剂中递送，或通过胆汁排泄， 在胃肠道中有大量的细菌肠道微生物组携带着一种集体基因 内容比人类基因组大150倍，编码丰富的酶库，具有潜在的 代谢药物的能力，个体之间差异很大。因此，微生物组有可能 影响血清药物和代谢物暴露。然而，用于鉴定活性药物的可扩展的体外系统 微生物种类、酶和候选药物代谢物不可用。我们理解 微生物组介导的药物代谢在很大程度上仅限于轶事实例，并且尚不清楚肠道是否 微生物编码代谢许多药物的酶。确定数量贡献的战略 肠道微生物药物代谢对血清药物和代谢物暴露的影响也不可用。 我们开发了高通量的方法，生成代谢的代谢组学时间序列曲线， 数百种药物，数百种人类肠道微生物群落和物种，揭示微生物组- 编码负责这些转化的酶，并鉴定产生的候选药物代谢产物， 一个结果。我们还提供证据表明，将gnotobiotics与基于生理学的药代动力学相结合， 建模可以定量解开宿主和微生物对血清药物代谢物暴露的贡献， 体内，使用由宿主和微生物组转化为单一代谢物的药物作为概念证明。 在本提案的目标1中，我们提出了一个计划，以建立第一个药物代谢酶库， 人类肠道微生物组。这些结果将揭示人类肠道微生物是否编码酶， 代谢许多药物，以及编码药物代谢酶的微生物组基因是否作为 个体微生物组的药物代谢能力的预测性生物标志物。在目标2中，我们描述了一个 开发和测试广义宿主-微生物组药代动力学模型的策略， 微生物将药物转化为多种代谢产物，并在模型中包括肠肝循环 topology.如果成功，这些目标将建立广泛适用的方法，以确定何时以及如何 微生物组可能有助于药物和其他小分子的代谢。

Project Summary Drug metabolites can have distinct efficacy and toxicity profiles relative to the parent compound, and interpersonal variation in drug metabolism can determine adverse reactions. Notably, oral drugs that exhibit low bioavailability, are delivered in delayed release formulations, or are excreted through bile can encounter enormous densities of bacteria in the gastrointestinal tract. The gut microbiome carries a collective gene content 150-fold larger than the human genome, encodes a rich repository of enzymes with the potential capacity to metabolize drugs, and varies widely between individuals. The microbiome thus has the potential to impact serum drug and metabolite exposure. However, scalable in vitro systems for identification of active microbial species, enzymes, and candidate drug metabolites are not available. Our understanding of microbiome-mediated drug metabolism is largely limited to anecdotal examples, and it is unknown whether gut microbes encode enzymes that metabolize many drugs. Strategies for determining the quantitative contribution of gut microbial drug metabolism to serum drug and metabolite exposure are also not available. We developed high-throughput approaches that generate metabolomic time-series profiles of the metabolism of hundreds of drugs by hundreds of human gut microbial communities and species, uncover the microbiome- encoded enzymes responsible for these transformations, and identify candidate drug metabolites produced as a result. We also provide evidence that combining gnotobiotics with physiologically-based pharmacokinetic modeling can quantitatively disentangle host and microbial contributions to serum drug metabolite exposure in vivo, using a drug that is converted into a single metabolite by host and microbiome as a proof of concept. In Aim 1 of this proposal, we present a plan to establish the first repertoire of drug-metabolizing enzymes in the human gut microbiome. These results will reveal whether human gut microbes encode enzymes that metabolize many drugs and whether microbiome genes encoding drug-metabolizing enzymes serve as predictive biomarkers of the drug-metabolizing capacity of an individual's microbiome. In Aim 2, we describe a strategy to develop and test generalized host-microbiome pharmacokinetic models that capture host and microbial conversion of a drug into multiple metabolites and include enterohepatic circulation in the model topology. If successful, these aims will establish broadly applicable approaches to identify when and how the microbiome could contribute to the metabolism of drugs and other small molecules.