Circuitry dynamics underlying opioid-dependence: Integrating structural, functional, and transcriptomic mechanisms

项目概要 一系列细胞和电路水平的适应是为了响应长期阿片类药物暴露而发展的，这些适应是 与阿片类药物成瘾的几个方面密切相关：耐受性、戒断性和可能导致阿片类药物成瘾的过程 强迫使用和复发。然而，我们仍然没有全面了解动态连接 以及大脑中表达阿片受体和肽的神经元网络的活动。因此，一个 迫切需要绘制全球细胞类型身份、转录组轨迹、变化的连接性和 细胞依赖的发生和维持的关键阿片能网络的整体活动， 和撤回。本提案旨在研究内源性 MOR 表达的结构和功能 关键皮层和皮层下大脑区域的神经回路，以确定这些回路如何维持 细胞依赖性并在 OUD 周期的不同阶段驱动全脑适应不良可塑性。在四 互补的目标，我们将首先绘制阿片能网络的结构和功能连接的变化 使用病毒遗传和组织清除方法来识别所有 MOR 表达的单突触输入 作为戒断活性 MOR 表达神经元，作为阿片类药物暴露和戒断的函数。我们随后将 将这些动态神经解剖图与细胞类型信息和基因表达变化整合起来 通过超多重原位结合单核测序和空间细胞分辨率转录组学 杂交产生数百个依赖性相关基因的解剖定位，靶向细胞 类型和复古标记的连接。最后，揭示皮质和皮质内表达 MOR 的细胞如何 在阿片类药物暴露期间实时调节皮质下目标区域，我们将使用微型头戴式 显微镜对阿片类药物暴露和戒断数周内的神经系统活动进行成像。到桥 这些实验测量并为我们的分析提供了一个通用框架，我们将采用网络 控制理论来识别驱动阿片类药物依赖状态之间转变的大脑节点，以识别 不成比例地推动每个州的潜在候选人。我们的数据集将提供正式的摘要和 公开的、可搜索的数据库记录活动、连接性和基因表达的演变 重复使用阿片类药物、戒断和戒断。

PROJECT SUMMARY A range of cellular and circuit-level adaptations develops in response to chronic opioid exposure, which are strongly linked to several facets of opioid addiction: tolerance, withdrawal and processes that may contribute to compulsive use and relapse. However, we still do not have a comprehensive picture of the dynamic connections and activities of neuronal networks in the brain that express the opioid receptors and peptides. Therefore, a critical need exists to map the global cell-type identity, transcriptomic trajectory, shifting connectivity, and ensemble activity of the key opioidergic networks underlying the onset and maintenance of cellular dependence, and withdrawal. This proposal aims to investigate the architecture and function of endogenous MOR-expressing neural circuits in key cortical and subcortical brain regions, in order to determine how these circuits maintain cellular dependence and drive brain-wide maladaptive plasticity across different stages of the OUD cycle. In four complementary aims, we will first map the shifting structural and functional connectivity of opioidergic networks using viral-genetic and tissue clearing methods to identify monosynaptic inputs to all MOR-expressing, as well as withdrawal-active MOR-expressing neurons, as a function of opioid exposure and abstinence. We will then integrate these dynamic neuroanatomical maps with cell-type information and gene expression changes by combing single-nuclei sequencing and spatial cellular-resolution transcriptomics via hyper-multiplexed in situ hybridizations to generate the anatomic localization of hundreds of dependence-related genes, targeted to cell types and retro-labeled connections. Lastly, to reveal how MOR-expressing cells within the cortical and subcortical target regions are modulated during opioid exposure in real-time, we will use miniature head-mounted microscopes to image the neural ensemble activities across weeks of opioid exposure and withdrawal. To bridge these experimental measurements and provide a common framework for our analyses, we will adopt Network Control Theory to identify brain nodes that drive the transition between opioid dependence states to identify potential candidates that disproportionately drive each state. Our datasets will provide formal summaries and a publicly available, searchable database logging the activity, connectivity, and gene expression as they evolve with repetitive opioid exposure, withdrawal, and abstinence.