Generating spatial and functional maps of cell-to-cell interactions in MS lesions

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Generating spatial and functional maps of cell-to-cell interactions in MS lesions Single nucleus RNA sequencing (sNuc-Seq) studies have greatly advanced our understanding of cellular heterogeneity in multiple sclerosis (MS) lesions. However, current CNS sNuc-Seq protocols selectively under-sample astrocyte and microglia nuclei, resulting in low resolution of population heterogeneity. Moreover, sNuc-Seq does not capture spatial information, such as distribution and interactions of cell populations within the MS lesion environment. Here, we propose to use a novel approach to sNuc-Seq of MS lesion tissue, enrichment for unrepresented/rare nuclei such as astrocytes, microglia and infiltrating immune cells through Flow sorting. We will combine this approach with advanced computational tools for denoising, imputation and batch correction to improve recovery of biological signal and resolution of cellular heterogeneity in acutely demyelinating, chronic active and remyelinating MS lesions. We will leverage the subpopulation-specific transcriptomes to computationally predict possible interactions between cell populations, based on expression of receptor-ligand pairs. We will further use a highly multiplexed histology imaging approach to localize cellular subpopulations and confirm co-localization of receptor-ligand pairs in MS lesions. We will finally conduct in vitro studies to elucidate the functional impact of selected receptor-ligand interactions. Our study will identify the constituent subpopulations and receptor-ligand interactomes that are associated with acute demyelination, chronic low-grade inflammation and remyelination. These interactions or combinations of interactions can be targeted to reduce inflammation or to enhance neurorepair in MS. Moreover, our datasets will provide a rich resource that will guide more functional studies on disease mechanisms.