Systems Biology of Anionic Drug and Metabolite Handling

说明书（由申请人提供）：许多常用的阴离子药物(如：抗生素、利尿剂、ACE抑制剂、非甾体抗炎药)以及与疾病相关的代谢物都是有机阴离子，通过肾近端小管运输而排出体外。参与这些药物和代谢物运输的限速基因是Oat1/SLC22a6和Oat3/SLC22a8。Oat1/SLC22a6 （NKT）和几个相关的SLC22基因家族成员最早是由PI’s团队发现的，而Oat1/SLC22a6和Oat3/SLC22a8基因缺失的影响最近也由PI’s团队发表。SLC22相关转运体的突变/多态性似乎与遗传性代谢疾病和复杂代谢表型相关。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，这在一生中药物和代谢物处理的改变中起作用。只有从转运体、细胞、小管到器官等多个层面对药物和代谢物的消除过程进行分析，才能全面了解药物和代谢物的消除。多年来，PI的团队已经开发了丰富的转录组学、代谢组学和通量组学/生理学数据集，在这些水平上分析燕麦表达和非表达条件。本文认为，如果在有机阴离子药物/代谢物的多个层面上对来自单个实验室的丰富的“组学”和生理数据进行建模，就可以获得一个连贯的“系统”图景。我们的目标是与加州大学圣地亚哥分校（SA1）的几位顶级系统生物学家合作，进行单层面和多尺度的建模。初步数据显示了PI与这些系统生物学家的合作程度；在某些情况下，论文已经或即将由他人共同撰写。我们还旨在研究上述肾脏药物/代谢物处理模型（在多个水平上），在不同的生命阶段，当燕麦基因表达发生较大变化时（SA2）。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。反过来，这将推动进一步的实验，这将有助于完善模型。最终目标是为在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。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.