Single-Cell Transcriptomics Identifies Brain Endothelium Inflammatory Networks in Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease characterized by infiltration of immune cells in multifocal areas of the central nervous system (CNS). The specific molecular processes allowing autoreactive immune cells to enter the CNS compartment through the blood-brain barrier (BBB) remain elusive. Using endothelial cells (ECs) enrichment and single-cell RNA sequencing (scRNA-Seq), we characterized the cells implicated in the neuroinflammatory processes in experimental auto-immune encephalomyelitis, an animal model of MS. We found an upregulation of genes associated with antigen presentation and interferon in most populations of CNS-resident cells, including ECs. Interestingly, a gradient of gene expression rather than distinct transcriptional profiles separated the arteriovenous zonation of the brain vasculature. However, differential gene expression analysis showed more transcriptomic alterations in venous ECs, suggesting their prominent role in neuroinflammation. Furthermore, analysis of ligand-receptor interactions identified important crosstalk between venous ECs and infiltrating immune subsets. To confirm the relevance of our observation in the context of human disease, we validated the protein expression of the most differentially expressed genes in MS lesions. Here, we demonstrate a landscape of the cellular heterogeneity involved in neuroinflammation and provide important molecular insights in unraveling specific cell processes that lead to the infiltration of the brain by immune cells in EAE. We extracted brains from myelin oligodendrocyte glycoprotein (MOG)-induced Experimental autoimmune encephalomyelitis (EAE) at peak of the disease and control (CTRL) mice to isolate single cells using an optimized protocol adapted from the Miltenyi Brain Dissociation Kit. Cells from each brain were subjected to scRNA-seq using a microdroplet-based method from 10X genomics.