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Virus infections have been associated with acute and chronic inflammatory central nervous system (CNS) diseases, e.g., acute flaccid myelitis (AFM) and multiple sclerosis (MS), where animal models support the pathogenic roles of viruses. In the spinal cord, Theiler's murine encephalomyelitis virus (TMEV) induces an AFM-like disease with gray matter inflammation during the acute phase, 1 week post infection (p.i.), and an MS-like disease with white matter inflammation during the chronic phase, 1 month p.i. Although gut microbiota has been proposed to affect immune responses contributing to pathological conditions in remote organs, including the brain pathophysiology, its precise role in neuroinflammatory diseases is unclear. We infected SJL/J mice with TMEV; harvested feces and spinal cords on days 4 (before onset), 7 (acute phase), and 35 (chronic phase) p.i.; and examined fecal microbiota by 16S rRNA sequencing and CNS transcriptome by RNA sequencing. Although TMEV infection neither decreased microbial diversity nor changed overall microbiome patterns, it increased abundance of individual bacterial genera Marvinbryantia on days 7 and 35 p.i. and Coprococcus on day 35 p.i., whose pattern-matching with CNS transcriptome showed strong correlations: Marvinbryantia with eight T-cell receptor (TCR) genes on day 7 and with seven immunoglobulin (Ig) genes on day 35 p.i.; and Coprococcus with gene expressions of not only TCRs and IgG/IgA, but also major histocompatibility complex (MHC) and complements. The high gene expression of IgA, a component of mucosal immunity, in the CNS was unexpected. However, we observed substantial IgA positive cells and deposition in the CNS, as well as a strong correlation between CNS IgA gene expression and serum anti-TMEV IgA titers. Here, changes in a small number of distinct gut bacteria, but not overall gut microbiota, could affect acute and chronic immune responses, causing AFM- and MS-like lesions in the CNS. Alternatively, activated immune responses would alter the composition of gut microbiota.
Pubmed ID: 32733435
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View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
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View all literature mentionsMus musculus with name SJL/J from IMSR.
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