Curdlan, a Microbial beta-Glucan, Has Contrasting Effects on Autoimmune and Viral Models of Multiple Sclerosis

FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY(2022)

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摘要
Multiple sclerosis (MS) is an immune-mediated disease characterized by inflammatory demyelination and axonal degeneration in the central nervous system (CNS). Bacterial and fungal infections have been associated with the development of MS; microbial components that are present in several microbes could contribute to MS pathogenesis. Among such components, curdlan is a microbial 1,3-beta-glucan that can stimulate dendritic cells, and enhances T helper (Th) 17 responses. We determined whether curdlan administration could affect two animal models for MS: an autoimmune model, experimental autoimmune encephalomyelitis (EAE), and a viral model, Theiler's murine encephalomyelitis virus (TMEV)-induced demyelinating disease (TMEV-IDD). We induced relapsing-remitting EAE by sensitizing SJL/J mice with the myelin proteolipid protein (PLP)(139-151) peptide and found that curdlan treatment prior to PLP sensitization converted the clinical course of EAE into hyperacute EAE, in which the mice developed a progressive motor paralysis and died within 2 weeks. Curdlan-treated EAE mice had massive infiltration of T cells and neutrophils in the CNS with higher levels of Th17 and Th1 responses, compared with the control EAE mice. On the other hand, in TMEV-IDD, we found that curdlan treatment reduced the clinical scores and axonal degeneration without changes in inflammation or viral persistence in the CNS. In summary, although curdlan administration exacerbated the autoimmune MS model by enhancing inflammatory demyelination, it suppressed the viral MS model with reduced axonal degeneration. Therefore, microbial infections may play contrasting roles in MS depending on its etiology: autoimmunity versus viral infection.
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关键词
animal models, CNS demyelinating diseases, neuropathology, persistent virus infections, Picornaviridae infections, fungal infections, principal component analysis, bioinformatics
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