Multiple sclerosis is a chronic inflammatory disease of the central nervous system (CNS). It is widely accepted that autoimmune response against the antigens of the CNS is the essential pathogenic force in the disease. It has recently become increasingly appreciated that activated encephalitogenic cells tend to migrate toward gut associated lymphoid tissues (GALTs) and that interrupted balance between regulatory and inflammatory immunity within the GALT might have decisive role in the initiation and propagation of the CNS autoimmunity. Gut microbiota composition and function has the major impact on the balance in the GALT. Thus, our aim was to perform analyses of gut microbiota in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. Albino Oxford (AO) rats that are highly resistant to EAE induction and Dark Agouti (DA) rats that develop EAE after mild immunization were compared for gut microbiota composition in different phases after EAE induction. Microbial analyses of the genus Lactobacillus and related lactic acid bacteria showed higher diversity of Lactobacillus spp. in EAE-resistant AO rats, while some members of Firmicutes and Proteobacteria (Undibacterium oligocarboniphilum) were detected only in feces of DA rats at the peak of the disease (between 13 and 16 days after induction). Interestingly, in contrast to our previous study where Turicibacter sp. was found exclusively in non-immunized AO, but not in DA rats, in this study it was detected in DA rats that remained healthy 16 days after induction, as well as in four of 12 DA rats at the peak of the disease. Similar observation was obtained for the members of Lachnospiraceae. Further, production of a typical regulatory cytokine interleukin-10 was compared in GALT cells of AO and DA rats, and higher production was observed in DA rats. Our data contribute to the idea that gut microbiota and GALT considerably influence multiple sclerosis pathogenesis.
This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 January 2017.
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