Cell-type specific molecular and functional analyses to target dorsal horn pain circuitry in mice and non-human primates

项目摘要 持续性疼痛仍然是一个主要的临床问题，因为它的高患病率和缺乏 有足够的治疗选择。脊髓背角是整合脊髓的主要部位 躯体感觉信息和基于电路的转换是持续性疼痛的基础。 我们的总体目标是开发针对背角回路的新型疼痛疗法 治疗机械性超感痛症。我们使用细胞类型特异性的趋化受体靶向来识别 在不影响急性感觉的情况下介导机械性痛觉异常的脊髓背角神经元 在老鼠身上。小鼠是这些研究中常用的模型系统，因为它们通常 与人类的相似性、基因操作的简便性以及可用的大量工具。 然而，以脊髓背角神经元为靶点进行治疗需要 理解物种间的细胞和分子保守性。恒河猴是 在系统发育上与人类更相似，并使用重新设计的工具可以作为证据- 原理模型体系。为此，我们分析了细胞的分子和细胞组织 用单细胞转录和原位杂交的方法研究猕猴的背角。我们 将这些数据与老鼠和人类的数据进行比较，生成了一份协调的背角图谱 不同物种的细胞类型。在这里，我们将识别人类猕猴的表观遗传景观 和小鼠背角神经元使用单核RNA和ATAC-Seq数据 机器学习辅助的生物信息学方法来识别 推动细胞类型特定基因在不同物种之间的强劲表达。我们将对候选人进行筛选 对于小鼠和猕猴的细胞类型特异性，然后使用细胞类型特异性RES 系统地生成背角跨物种的功能图谱。建议进行的研究 这里将为单细胞转录组生成大规模的可搜索数据库并打开 小鼠、猕猴和人类的染色质区域。重要的是，我们将拥有知识和 进行猕猴新疗法原理验证研究所需的病毒载体 机械性超感痛症。

Project Summary Persistent pain remains a major clinical problem because of its high prevalence and the lack of adequate treatment options. The spinal dorsal horn is a major site for the integration of somatosensory information and for circuit-based transformations that underlie persistent pain. The overall goal our work is to develop novel pain therapies that target the dorsal horn circuitry for mechanical allodynia. We use cell type-specific targeting of chemogenic receptors to identify spinal dorsal horn neurons that mediate mechanical allodynia without affecting acute sensation in mice. Mice are a commonly used model system for these studies because of their general similarity to humans, the ease of genetic manipulations and the large number of tools available. However, targeting spinal dorsal horn neurons for therapeutic purposes requires an understanding of the cellular and molecular conservation between species. Rhesus macaque are phylogenetically more similar to humans and with re-engineered tools can serve as a proof-of- principle model system. To this end, we analyzed the molecular and cellular organization of the macaque dorsal horn by single cell transcriptomics and in situ hybridization methods. We compared these data to mouse and human data to generate a harmonized atlas of dorsal horn cell types across species. Here we will 1) Identify the epigenetic landscape of human, macaque and mouse dorsal horn neurons using single nucleus RNA- and ATAC-Seq data together with machine learning-assisted bioinformatic approaches to identify regulatory elements (REs) that drive robust cell type-specific gene expression across species. We will 2) screen candidate REs for cell-type specificity in mice and subsequently macaque and then use the cell type-specific REs to systematically generate a functional map of the dorsal horn across species. Studies proposed here will generate large-scale searchable databases for single cell transcriptomics and open chromatin regions in mice, macaque and human. Importantly, we will have the knowledge and viral vectors needed to pursue macaque proof-of-principle studies of novel therapies for mechanical allodynia.