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

点击翻译按钮获取中文摘要

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.