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

阿片类药物依赖性的电路动力学：整合结构、功能和转录组机制

• 批准号: 10509750
• 负责人: KEVIN T BEIER
• 金额: $ 75.33万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10509750
• 关键词: 3-Dimensional; Abstinence; Acute; Address; Adopted; Amygdaloid structure; Anatomy; Anterior; Architecture; Atlases; Axon; Behavior; Brain; Brain region; Cell Nucleus; Cells; Characteristics; Chronic; Classification; Comb animal structure; Coupled; Data Set; Databases; Dependence; Development; Drug usage; Epidemic; Equilibrium; Evolution; Future; Gene Expression; Gene Targeting; Genes; Genetic; Genetic Transcription; Genomics; Graph; Head; Image; In Situ Hybridization; Incidence; Label; Lifestyle-related condition; Link; Machine Learning; Maintenance; Maps; Measurement; Methods; Microscope; Modeling; Neurons; Nucleus Accumbens; Opiate Addiction; Opioid; Opioid Peptide; Opioid Receptor; Output; Pathologic; Pharmaceutical Preparations; Population; Process; Relapse; Research; Research Personnel; Resolution; Role; Sampling; Site; System; Technology; Therapeutic; Time; Tissues; Ventral Tegmental Area; Visualization; Withdrawal; addiction; behavior measurement; brain cell; cell type; cingulate cortex; control theory; endogenous opioids; experimental study; gene network; high throughput screening; improved; innovation; mathematical model; midbrain central gray substance; mu opioid receptors; neural circuit; neural network; neuroadaptation; next generation; novel; opioid exposure; opioid use disorder; opioid withdrawal; relating to nervous system; response; searchable database; theories; transcriptome sequencing; transcriptomics; virus genetics

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.

项目摘要 一系列的细胞和电路级适应性响应于慢性阿片类药物暴露，这是 与阿片类药物成瘾的几个方面密切相关：宽容，撤回和可能有助于 强迫使用和复发。但是，我们仍然没有动态连接的全面图片 大脑中神经元网络的活性表达了阿片受体和肽。因此， 存在关键需求，以绘制全局细胞类型的身份，转录组轨迹，连通性的变化和 关键的阿片类网络的集合活动，该网络是细胞依赖性开始和维持的基础 和退出。该建议旨在研究内源性表达的结构和功能 为了确定这些电路如何保持 在OUD周期的不同阶段，细胞依赖性并驱动整个大脑不良适应性可塑性。四分之一 互补的目的，我们将首先绘制阿片类网络的转移结构和功能连接 使用病毒遗传学和组织清除方法来识别所有表达的单突触输入 作为表达MOR表达神经元的戒断，作为阿片类药物暴露和戒酒的函数。然后我们会 将这些动态神经解剖图与细胞类型信息和基因表达的变化相结合 通过超多形的原位梳理单核测序和空间细胞分辨率转录组学 杂交生成数百个依赖关系基因的解剖学定位，针对细胞 类型和重新标记的连接。最后，揭示在皮质和 皮层靶区域是在阿片类药物实时暴露期间调制的，我们将使用微型头部安装 显微镜以在阿片类药物暴露和戒断的数周中对神经合奏活动进行图像。桥接 这些实验测量并为我们的分析提供了一个共同的框架，我们将采用网络 控制理论以识别驱动阿片类药物依赖状态之间过渡以识别的大脑节点 潜在的候选人不成比例地推动每个州。我们的数据集将提供正式摘要和 公开可搜索的数据库记录活动时记录活动，连接性和基因表达 重复的阿片类药物暴露，戒断和禁欲。