Systems Pharmacology for overcoming cell variability

项目概要： 单细胞 RNA-Seq 的最新技术进展凸显了以下可能性： 迄今为止，在多种组织和细胞中许多细胞类型中尚未认识到细胞间的变异性 器官。这种变异性导致单一类型的细胞具有多种亚型。这种可变性 导致不同的细胞生物学能力，这对药物治疗具有重要影响 对于复杂的疾病。考虑变量的系统药理学方法 亚型的反应可能有助于开发有效的联合疗法。我们的 系统药理学方法包括计算模型的整合，借此我们 结合图论和动力学模型来分析单细胞转录组数据，从而 确定模型系统中涉及的相关监管途径和子网络，该模型系统产生 全细胞对受体刺激的反应，在体内可以发挥恢复作用 对药物反应的病理生理学。基于这些标准我们一直在研究G蛋白 耦合大麻素 1 受体调节体外原代神经元的神经突生长以鉴定 用于联合药物治疗的可靶向节点，可进行测试以治疗视神经损伤 在大鼠体内。损伤后，将两种受体激动剂药物应用于细胞体，另两种药物应用于细胞体 损伤部位的两种药物可恢复视觉中的光依赖性电生理信号 皮质。尽管我们在视觉皮层中可靠地看到信号，但恢复信号的幅度是 小。我们假设识别细胞亚型中负责长神经突的基因 使用单细胞 RNA-Seq 将绘制细胞机制，以确定用于再生的药物 更致密的轴突束并导致光刺激电生理的更大恢复 视觉皮层中的信号。为了检验这个假设，我们有三个具体目标：1）将分析 单细胞转录组对受体激活反应的变异性以确定决定因素 控制细胞在细胞群中伸出长神经突。 2）将使用计算系统 生物学开发集成网络和动力学模型来识别亚细胞过程 以及调节长神经突细胞中上调和下调基因表达的药物。 3) 将使用大鼠视神经损伤模型来测试神经突延长药物是否与或 替代目前的四种药物组合会导致再生密度增加 纤维和视觉皮层电生理反应的更高振幅。我们 预计这将提供对亚细胞过程的一般基本理解 控制全细胞反应中细胞间的变异性以及如何将其用于有效的药物治疗。

Project Summary: Recent technological advances in single cell RNA-Seq have highlighted the possibility of a hitherto unrecognized cell-to cell variability in many cell types across a wide range of tissues and organs. Such variability results in the multiple subtypes of cells of a single type. This variability results in differing cell biological capabilities, which has important consequences for drug therapy for complex diseases. A systems pharmacology approach that takes into account variable responses of the subtypes could be useful in development of effective combination therapy. Our systems pharmacology approaches includes integration of computational modeling whereby we combine graph theory and dynamical models to analyze single cell transcriptomic data so as to identify relevant regulatory pathways and subnetworks involved in a model system that produces a whole cell response to receptor stimulation which in vivo can play a role recovery from pathophysiology in response to drugs. Based on these criteria we have been studying G protein coupled cannabinoid 1 receptor regulated neurite outgrowth of primary neurons in vitro to identify targetable nodes for combination drug therapy that can be tested to treat injury to the optic nerve in rats in vivo. After injury, two receptor agonists drugs applied at the cell body and the two other two drugs at the injury site restores light dependent electrophysiological signals in the visual cortex. Although we see signal reliably in the visual cortex, the amplitude of restored signal is small. We hypothesize that identifying genes responsible for long neurites in subtypes of cells using single cell RNA-Seq will map cellular mechanisms to identify drugs for regeneration of denser axonal bundles and lead to greater restoration of the light stimulated electrophysiological signals in the visual cortex. To test this hypothesis we have three specific aims: 1) Will analyze variability of single cell transcriptomic responses to receptor activation to identify the determinants that control cells to put out long neurites in a population of cells. 2) Will use computational systems biology to develop integrated network and dynamical models to identify the subcellular processes and drugs that regulate the expression of up and downregulated genes in cells with long neurites. 3) Will use the optic nerve injury model in rats to test if neurite lengthening drugs along with or substituting for the current four-drug combination results in increased density of regenerated fibers and higher amplitude of the electrophysiological responses in the visual cortex. We anticipate this will provide general fundamental understanding of the subcellular processes that control cell-to cell variability in whole cell responses and how to use it for efficacious drug therapy.