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Characterization of cuprizone mouse model at single-cell and spatial transcriptomics level[bulk RNA-seq]

ABSTRACT: We generated a comprehensive dataset utilizing the cuprizone model. This dataset encompasses bulk RNA-seq, single-nucleus RNA-seq (snRNA-seq), and spatial transcriptomics, with the aim of investigating the molecular changes linked to the cuprizone-induced demyelination phenotype. Integration of these omics dataset allowed us to investigate the changes occurring at both the single-cell and spatial levels, thereby enabling a deeper understanding of the cellular dynamics and molecular interactions associated with the cuprizone-induced demyelination phenotype.

ORGANISM(S): Mus musculus

PROVIDER: GSE255368 | GEO | 2024/11/06

REPOSITORIES: GEO

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Characterization of cuprizone mouse model at single-cell and spatial transcriptomics level[Spatial Transcriptomics]

Project description:We generated a comprehensive dataset utilizing the cuprizone model. This dataset encompasses bulk RNA-seq, single-nucleus RNA-seq (snRNA-seq), and spatial transcriptomics, with the aim of investigating the molecular changes linked to the cuprizone-induced demyelination phenotype. Integration of these omics dataset allowed us to investigate the changes occurring at both the single-cell and spatial levels, thereby enabling a deeper understanding of the cellular dynamics and molecular interactions associated with the cuprizone-induced demyelination phenotype.

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Expression data from WT and TREM2 deficient microglia in response to cuprizone mediated demyelination

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Gene expression profile in the cuprizone-induced demyelination mouse model

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Project description:Demyelination and dysregulated myelination in the CNS are hallmarks of many neurodegenerative diseases such as multiple sclerosis (MS) and leukodystrophies. Here, we studied GFAP+ astrocytes during de- and remyelination in the cuprizone mouse by exploiting the ribosomal tagging (RiboTag) technology. Analyses were performed 5 weeks after cuprizone feeding, at the peak of demyelination in the corpus callosum, and 0.5 and 2 weeks after cuprizone withdrawal, when remyelination and tissue repair is initiated. After 5 weeks of cuprizone feeding, reactive astrocytes showed inflammatory signatures with enhanced expression of genes that modulate leukocyte migration (Tlr2, Cd86, Parp14,Cxcl10). Furthermore, demyelination-induced reactive astrocytes expressed numerous ligands including Cx3cl1, Csf1, Il34, and Gas6 that act on homeostatic as well as activated microglia and thus potentially mediate activation and recruitment of microglia as well as enhancement of their phagocytosis. During early remyelination, region-specific astrocytes displayed reduced inflammatory response signatures as indicated by shut down of CXCL10 production. During late remyelination, the signatures of GFAP+ astrocytes shifted towards resolving inflammation by active suppression of lymphocyte activation and differentiation and support of glia cell differentiation. Astrocytes showed enhanced expression of osteopontin (SPP1) as well as of factors that are relevant for tissue remodelling (Timp1), regeneration and axonal repair. In conclusion, we detected highly dynamic astroglial transcriptomic signatures in the cuprizone model, which reflects excessive communication amongst glia cells and highlights different astrocyte functions during neurodegeneration and regeneration.

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Characterization of cuprizone mouse model at single-cell and spatial transcriptomics level[snRNA-seq]

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Project description:Demyelination is a hallmark of multiple sclerosis, leukoencephalopathies, cerebral vasculopathies and several neurodegenerative diseases. The cuprizone mouse model is widely used to simulate demyelination occurring in these diseases. Here, we present a high-resolution snRNA-seq analysis of gene expression changes across all brain cells in this model. We define signatures of prototypic responses to demyelination and remyelination for each cell type, including anti-stress, anti-oxidant-, metabolic-, hypoxia-, IFN-, and IL-33-driven responses, and validate them at the protein level and in IL-33R-deficient mice. We identify related transcription regulators underpinning these pathways, including STAT3, NF-κB, OLIG1 and MAFB. Furthermore, snRNA- seq data provide novel insights into how various brain cell types connect and interact, defining complex circuitries previously unknown to impact demyelination and remyelination. As an explicative example, perturbation of microglia caused by TREM2 deficiency impacts the oligodendrocyte responses to demyelination. Altogether, this study provides a rich resource for future studies investigating mechanisms underlying demyelination and remyelination.

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