Systems Biology of Anionic Drug and Metabolite Handling

描述（由申请人提供）：许多常用的阴离子药物（例如，抗生素、利尿剂、ACE抑制剂、NSAID）以及疾病相关的代谢物是有机阴离子，其作为由肾的近端小管运输的结果而被排泄。 参与这些药物和代谢物转运的限速基因是Oat 1/SLC 22 a6和Oat 3/SLC 22 a8。Oat 1/SLC 22 a6（NKT）和几个相关的SLC 22基因家族成员是由PI的小组首先鉴定的，并且PI的小组最近发表了Oat 1/SLC 22 a6和Oat 3/SLC 22 a8的遗传缺失的效应。 相关SLC 22转运蛋白的突变/多态性似乎与遗传性代谢疾病和复杂的代谢表型相关。 这些基因的表达及其功能在发育、成熟和衰老过程中发生显著变化;据推测，这在整个生命过程中对药物和代谢物处理的改变起作用。对药物和代谢物消除的全面理解只有在从转运蛋白到细胞，到小管，到器官的多个层次上分析这一过程时才能出现。多年来，PI的团队已经在燕麦表达和非表达条件下的这些分析水平上开发了丰富的转录组学、代谢组学和通量组学/生理学数据的数据集。有人认为，如果在有机阴离子药物/代谢物的许多水平上对来自单个实验室的这组丰富的“组学”和生理数据进行建模，则可以实现连贯的“系统”图。我们的目标是与UCSD（SA 1）的几位顶级系统生物学家合作进行单级和多尺度建模。 初步数据显示PI与这些系统生物学家的合作程度;在某些情况下，论文已经或即将合著。我们还旨在研究上述模型的肾脏药物/代谢物处理（在多个水平）在动态设置在不同时期的生活中，燕麦基因表达是已知的经历大的变化（SA 2）。实验和初始粗粒度建模将与原型有机阴离子的持续湿实验室研究并行进行，这将用于进一步约束每个级别的建模。这将反过来推动进一步的实验，这将有助于完善模型。 最终目标是为复杂代谢疾病表型的临床背景下具有预测能力的模型奠定基础（例如，高尿酸血症）和药物基因组学。

DESCRIPTION (provided by applicant): Many commonly prescribed anionic drugs (eg. antibiotics, diuretics, ACE inhibitors, NSAIDs) as well as disease-associated metabolites are organic anions that are excreted as a result of transport by the proximal tubule of the kidney. The rate limiting genes involved in transport of these drugs and metabolites are Oat1/SLC22a6 and Oat3/SLC22a8. Oat1/SLC22a6 (NKT) and several related SLC22 gene family members were first identified by the PI's group, and the effects of genetic deletion of Oat1/SLC22a6 and Oat3/SLC22a8 have recently been published by the PI's group. Mutations/polymorphisms in related SLC22 transporters appear to be associated with both inherited metabolic disease and complex metabolic phenotypes. The expression of these genes and, thus their functionality, changes markedly through development, maturity and aging; this is presumed to play a role in alterations in drug and metabolite handling throughout life. A comprehensive understanding of drug and metabolite elimination can only emerge when the process is analyzed at multiple levels-from the transporter, to the cell, to the tubule, to the organ. Over the years, the PI's group has developed a rich data set of transcriptomic, metabolomic and fluxomic/physiological data at these levels of analysis in Oat-expressing and non-expressing conditions. It is argued here that a coherent "systems" picture can be achieved if this rich set of "omics" and physiological data from a single lab is modeled at many levels for organic anionic drugs/metabolites. We aim to perform single level and multiscale modeling in collaboration with several premier systems biologists here at UCSD (SA1). Preliminary data is presented showing the extent of the PI's collaborations with these systems biologists; in some cases, papers have been or will soon be co-authored. We also aim to study the aforementioned models of renal drug/metabolite handling (at multiple levels) in a dynamic setting during different periods of life when Oat gene expression is known to undergo large changes (SA2). Experiments and initial coarse-grained modeling will be performed side-by-side with continued wet lab studies of a prototypical organic anion, which will be used to further constrain modeling at each level. This will, in turn, drive further experimentation, that will help refine the models. The ultimate goal is to set the stage for a model with predictive power in the clinical contexts of complex metabolic disease phenotypes (eg. hyperuricemia) and pharmacogenomics.