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

项目摘要-项目2 背根神经节(DRG)的啮齿动物模型在鉴定细胞和分子方面非常有用 涉及疼痛、神经损伤、再生、退变和各种形式的外周的机制 神经病。然而，通过在人体组织中进行验证，临床前研究结果的翻译可能会得到极大的改善。 由于啮齿动物和人类的感觉神经元之间存在差异，因此对人类内部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疾病的治疗至关重要。困难之处 获得人类DRG的机会阻碍了这方面的进展。我们的协作团队处于独特的位置 来解决这个问题。我们在提取人背根神经节的外科手术中获得了专业知识。 器官捐赠者同意捐赠组织用于研究和制备可存活的成人背根神经节细胞 功能和分子研究。结合我们在单细胞测序、成像质量方面的强大专业知识 细胞学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图谱 以及人背根神经节组织内的非神经细胞。我们将把基因表达谱与成像质量结合起来 细胞学(IMC)，一种基于组织的蛋白质组分析，允许检测30多个蛋白质标记物 同时在单细胞水平的组织切片上，同时保留细胞的空间关系。IMC 允许以单个单元格分辨率同时分析各种不同的单元格类型，并正在重塑 能够询问细胞间的相互作用以及细胞与其之间的体系结构关系 自然微环境。这种空间分辨的多路复用简档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。 我们将开发整合IMC和单细胞转录分析hDRG的计算方法。 这种空间分辨的、高度多元化的单细胞转录组学和蛋白质组学的应用 疼痛研究的方法可能会重塑我们询问细胞群体和基因表达的能力 健康和痛苦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，我们将极大地扩展 人类背根神经节在健康和痛苦状态下的特征。该项目将生成一个参考地图集 并定义健康的人DRG组织和疼痛条件下的DRG的个体间变异性 单元格分辨率。

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.