Core O: HIGH THROUGHPUT SEQUENCING

该提案的一个中心主题是一个通用的实验设计，它研究了五个模型系统中的非类固醇抗炎药的反应，酵母、人类细胞、鱼、小鼠和人(参见系统药理学核心中的实验设计)。这些模型系统中的每一个都提供了向非甾体抗炎药反应提供信息的优势。因为酵母没有环氧合酶(COX)，但确实有强大的遗传学，我们正在利用它们来识别调节靶标效应的基因和网络。我们建议使用人类细胞来了解非甾体抗炎药如何在多种细胞类型中调节细胞自主网络功能。斑马鱼和小鼠是研究与非类固醇抗炎药反应相关的生理学的理想模型系统，例如非类固醇抗炎药如何改变疼痛和血压。 此外，它们是寻找影响非甾体抗炎药作用的修饰基因的优秀系统。虽然斑马鱼拥有优雅的正向遗传屏幕，但老鼠是反向遗传学的主导生物，我们在这项资助中提供了一系列条件基因敲除小鼠。我们最终的模型系统--人类受试者--是这些研究的基石。我们将研究受试者对非甾体抗炎药的反应，重点是生理参数，如对疼痛和血压的反应。此外，我们将调查 这些人类受试者的个体差异。在所有系统中，我们将整合基因组信息与药物水平和前列腺素类化合物以及反映药物暴露和反应的无偏见(例如代谢组和脂组学)定量输出。 大多数关于非类固醇抗炎药的生理效应的研究都集中在单个模型系统中一个或几个基因的作用上。在这里，我们开发了一种21世纪的方法，通过模型系统在网络层面上研究药物反应。要做到这一点，我们需要通用技术。在分子图谱核心中，我们建议使用脂质组学、代谢组学和蛋白质组学来研究这些小分子是如何代谢的， 在各种实验设计中影响前列腺素信号，并改变蛋白质的表达。 在这一核心中，我们利用高通量测序方面的最新进展，现在可以对RNA表达动态、染色质修饰、微生物组调节和基因组序列进行全基因组分析。这是一个快速变化的地区。为了确保我们始终与时俱进，我们聘请了PacBio首席科学官兼加州大学旧金山分校教授Eric Schadt，他正在开发第三代技术以解决 这些问题。

A central theme in this proposal is a generic experimental design that investigates NSAID responses in five model systems, yeast, human cells, fish, mice, and man (see experimental design in the Systems Pharmacology Core). Each of these model systems offers advantages to inform NSAID responses. Because yeast don't have cyclooxygenases (COXs), but do have powerful genetics, we are using them to identify the genes and networks that regulate off target effects. We propose using human cells to understand how NSAIDs regulate cell autonomous network function in multiple cell types. Zebrafish and mice are ideal model systems for studying physiology relevant to NSAID response, e.g. how NSAIDs modify pain and blood pressure. Furthermore, they are excellent systems to find modifier genes that impact NSAID action. While zebrafish have elegant forward genetic screens, the mouse is the dominant organism for reverse genetics, and we have an array of conditional knockout mice available in this grant. Our final model system, human subjects, is the bedrock on which these studies lay. We will study NSAID response in human subjects focusing on physiological parameters such as response to pain and blood pressure. Furthermore, we will investigate individual differences in these human subjects. In all systems, we will integrate genomic information with drug levels and prostanoids and unbiased (e.g. metabolomic and lipidomic) quantitative outputs reflecting drug exposure and response. Most investigation of the physiological effects of NSAIDs has focused on the role of one or a few genes in a single model system. Here we develop a 21st-century approach that studies drug response at the network level across model systems. To do this, we need common technologies. In the Molecular Profiling Core, we propose using lipidomics, metabolomics, and proteomics to study how these small molecules are metabolized, influence prostaglandin signaling, and change the expression of proteins in a variety of experimental designs. In this core, we leverage recent advances in high throughput sequencing that now enable whole genome analysis of RNA expression dynamics, chromatin modifications, microbiome regulation, and genome sequence. This is a rapidly moving area. To ensure we stay relevant, we've enlisted Eric Schadt, Chief Scientific Officer of PacBio and Professor at UCSF, who is developing third-generation technologies to address these issues.