Characterization of human DRG at the single cell level via integrated transcriptomics and spatial proteomics

项目摘要-项目2 啮齿类动物背根神经节（DRG）模型在识别细胞和分子生物学方面非常有用。 参与疼痛、神经损伤、再生、变性和各种形式的外周神经损伤的机制。 神经病然而，通过在人体组织中进行验证，可以大大改善临床前发现的转化。 由于啮齿动物和人类感觉神经元之间存在差异，因此对人类内所有细胞的详细研究 DRG对于未来疼痛状态、神经损伤以及周围神经病的治疗至关重要。难度 获得人类背根神经节的方法阻碍了这方面的进展。我们的合作团队定位独特 来解决这个问题。我们已经获得了在手术过程中提取人背根神经节的专业知识， 器官捐赠者同意捐赠组织用于研究和制备活的成人DRG细胞用于 功能和分子研究。结合我们在单细胞测序、成像质量 细胞计数和生物信息学的方法，我们将在单细胞水平上定义神经元的分子概况， 和人DRG组织内的非神经元细胞。我们将整合基因表达谱与成像质量 流式细胞术（IMC），一种基于组织的蛋白质组学分析，可以检测30多种蛋白质标记物 同时在单细胞水平的组织切片上进行，同时保持细胞的空间关系。IMC 能够以单细胞分辨率同时分析各种不同的细胞类型， 能够询问细胞间的相互作用以及细胞及其结构之间的结构关系 原生微环境这种空间分辨的多重分析方法已被应用于癌症， 糖尿病，免疫学和传染病研究，识别功能不同的免疫细胞 与疾病进展、治疗结果和疾病预后的生物标志物相关的亚群。 我们将开发用于hDRG的整合IMC和单细胞转录组学分析的计算方法。 这种空间分辨、高度多重、单细胞转录组学和蛋白质组学分析的应用 疼痛研究的方法可能会重塑我们询问细胞群和基因表达的能力 在健康和疼痛条件下，神经元和非神经元细胞之间的变化及其空间关系。 通过整合人类DRG图谱的细胞、空间和功能分支， 健康和疼痛状态下的人DRG的表征。该项目将生成一个参考地图集， 人DRG以及健康人DRG组织和来自疼痛状况DRG的确定的个体间变异性 单细胞分辨率。

Project Abstract – Project 2 Rodent models of dorsal root ganglia (DRG) have been extremely useful in identifying the cellular and molecular mechanisms involved in pain, nerve injury, regeneration, degeneration, and various forms of peripheral neuropathies. However, translation of preclinical findings may be greatly improved by validation in human tissues. Since differences exist between rodent and human sensory neurons, a detailed study of all cells within human DRG is critical for future treatment of painful state, nerve injuries as well as peripheral neuropathies. The difficulty to gain access to human DRG has hampered progress on that front. Our collaborative team is uniquely positioned to tackle this problem. We have gained expertise in the surgical procedure for extraction of human DRG from organ donors consenting to tissue donation for research and the preparation of viable adult DRG cells for functional and molecular studies. Combined with our strong expertise in single cell sequencing, imaging mass cytometry and bioinformatics approaches, we will define at the single cell level the molecular profile of neuronal and non-neuronal cells within human DRG tissue. We will integrate gene expression profile with imaging mass cytometry (IMC), a tissue-based proteomic analysis that allows the detection of over 30 protein markers simultaneously on tissue sections at the single-cell level while retaining the spatial relationships of the cells. IMC enables a variety of distinct cell types to be analyzed concurrently at a single-cell resolution and is reshaping the ability to interrogate both the intercellular interactions and the architectural relationships between cells and their native microenvironment. This spatially-resolved multiplexed profiling approach has been applied to cancer, diabetes, immunology, and infectious disease research, identifying functionally distinct immune cell subpopulations associated with disease progression, treatment outcomes, and biomarkers for disease prognosis. We will develop computational approaches for integrated IMC and single cell transcriptomic analysis of hDRG. Application of this spatially-resolved, highly multiplexed, single-cell transcriptomics and proteomic profiling approach to pain research will likely reshape our ability to interrogate cell population and gene expression changes and their spatial relationships between neurons and non-neuronal cells in healthy and painful conditions. By integrating the cellular, spatial and functional branches of the human DRG atlas we will dramatically expand the characterization of human DRG in healthy and painful states. This project will generate a reference atlas for human DRG and define inter-individual variability of healthy human DRG tissue and DRG from painful conditions with single cell resolution.