Single-Cell Dissection of Ensembles and Cell Types Mediating Opioid Action in the Rodent Brain

物质使用障碍（SUD）是一种以强迫性使用物质为特征的衰弱性疾病，尽管主观认识到与其使用相关的缺点。长期使用该物质会导致戒断和依赖性的发展，阻碍对其使用的有意控制。在所有物质中，类阿片是对我们社会造成最大负面影响的物质之一。动物和人类的研究表明，阿片类药物使用障碍（OUD）涉及几个大脑区域，特别是多巴胺系统的各种成分。主要的多巴胺神经元聚集在中脑的黑质部（SNc）和腹侧被盖区（VTA）。传统上，它们的活性与化合价相关，例如，促进对奖励刺激的接近行为。在它们的上游，涉及两个主要回路：一个包括投射到腹侧被盖区的中脑核，另一个包括投射到SNc的背侧纹状体。因此，本研究的范围是在这两个回路的细胞中进行深入的转录组学，以剖析小鼠大脑中介导阿片类药物作用的基因、通路和细胞类型。 我们将使用这些数据来预测驱动基因，调控区域，通路和参与阿片类成瘾行为出现的细胞类型。最后，为了测试这些预测驱动因素的因果作用，我们将使用阿片类药物自我给药，这是成瘾领域使用的经典范例。通过将一组丰富的行为协议与最先进的转录组学，表观基因组学和计算数据分析相结合，我们的目标是获得具有前所未有的单细胞分辨率水平的多模态数据，用于识别OUD小鼠模型中受影响的基因，途径和细胞类型。

Substance use disorder (SUD) is a debilitating condition characterized by compulsive use of a substance, in spite of the subjective recognition of the drawbacks associated with its use. Chronic use of the substance leads to the development of withdrawal and dependence, hindering intentional controls over its use. Among all substances, opioids are among the ones that pose the greatest negative impact on our society. Animal and human studies have implicated several brain regions involved in opioid use disorder (OUD), in particular various components of the dopamine system. Major dopamine-containing neurons are clustered in regions of the midbrain called the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA). Classically, their activities correlate with valence, e.g., promoting approach behavior to rewarding stimuli. Upstream of them, two major circuits are involved: one including the nucleus accumbens projecting onto the VTA, and the other including the dorsal striatum projecting onto the SNc. The scope of this study is thus to conduct in-depth transcriptomics across the cells of these two circuits to dissect genes, pathways, and cell types mediating opioid action in the mouse brain. We will use these data to predict driver genes, regulatory regions, pathways, and cell types involved in the emergence of opioid addiction behaviors. Finally, to test the causal role of these predicted drivers, we will use opioid self-administration, a classical paradigm used in the field of addiction. By combining a rich set of behavioral protocols with state-of-the-art transcriptomics, epigenomics, and computational data analysis, we aim to obtain multi-modal data with an unprecedented level of single-cell resolution for identifying genes, pathways, and cell types affected in mouse models of OUD.