High-spatial-resolution multi-omics sequencing of brain lesions in multiple sclerosis

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Project Summary Multiple sclerosis (MS) is a neuroinflammatory autoimmune disease of the CNS that results in demyelination, axonal injury, and neuronal loss. Abnormal immune responses involving the trafficking of peripherally activated immune cells into the CNS are major drivers of inflammatory disease activity in relapsing multiple sclerosis, as underscored by the success of immune-targeting therapies. By contrast, the biology of non-relapsing progressive disease is thought to involve CNS-compartmentalized inflammation and degenerative disease mechanisms, which remains more refractory to therapy, due in part to the complexity of gene regulatory network coupled with cell-type-specific mechanisms of MS lesion progression. What types or subtypes of cells are affected by this process and their spatial heterogeneity in the tissue context as well as how these cells impact the tissue environments remain poorly understood, which precludes the development of strategies to target these cells to improve healthspan/lifespan or harnessing these cells or secreted factors to promote tissue remodeling and repair, highlighting a pressing need for tools to map cells and the surround environments in the tissues lesion and generate biomarkers to define spatial and phenotypic heterogeneity. This project aims to develop novel molecular barcoding scheme and downstream biochemistry in combination with novel microdevices for spatial multi-omics that allows simultaneous profiling of multi epigenomic modalities, whole transcriptome, and a panel of proteins at tissue scale and cellular level in a spatially resolved manner. We will apply the spatial multi-omics to map human brain tissue dissected from the edge of demyelinated white matter MS lesions at different stages of inflammation as well as the demyelinated lesion core, the white matter periplaque and normal white matter from neurologically healthy brains. Spatial omics data will be integrated with single-cell data to identify signatures of different affected cells and perform the tissue neighborhood analysis to define the cellular composition and molecular signatures in MS lesions. The expected outcomes and the major contributions include: (1) Fundamental knowledge on diverse cell types and their epigenomic, transcriptional and phenotypic (protein) characteristics in the context of 3D tissue organization in the MS brain lesions and (2) Offer the possibility of testing new therapeutic approaches for MS that are not targeted by currently approved treatments. The resulting data will lead to a better understanding of the relationship between tissue organization, function, and gene regulatory networks in MS.