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. 2019 Mar 7:10:385.
doi: 10.3389/fimmu.2019.00385. eCollection 2019.

Lactobacillus reuteri Reduces the Severity of Experimental Autoimmune Encephalomyelitis in Mice by Modulating Gut Microbiota

Baokun He  1 , Thomas K Hoang  1 , Xiangjun Tian  2 , Christopher M Taylor  3 , Eugene Blanchard  3 , Meng Luo  3 , Meenakshi B Bhattacharjee  4 , Jasmin Freeborn  1 , Sinyoung Park  1 , Jacob Couturier  5 , John William Lindsey  6 , Dat Q Tran  1 , Jon Marc Rhoads  1 , Yuying Liu  1
Affiliations

Lactobacillus reuteri Reduces the Severity of Experimental Autoimmune Encephalomyelitis in Mice by Modulating Gut Microbiota

Baokun He et al. Front Immunol. .

Abstract

The gut microbiome plays an important role in immune function and has been implicated in multiple sclerosis (MS). However, how and if the modulation of microbiota can prevent or treat MS remain largely unknown. In this study, we showed that probiotic Lactobacillus reuteri DSM 17938 (L. reuteri) ameliorated the development of murine experimental autoimmune encephalomyelitis (EAE), a widely used animal model of MS, a model which is primarily mediated by TH17 and TH1 cells. We discovered that L. reuteri treatment reduced TH1/TH17 cells and their associated cytokines IFN-γ/IL-17 in EAE mice. We also showed that the loss of diversity of gut microbiota induced by EAE was largely restored by L. reuteri treatment. Taxonomy-based analysis of gut microbiota showed that three "beneficial" genera Bifidobacterium, Prevotella, and Lactobacillus were negatively correlated with EAE clinical severity, whereas the genera Anaeroplasma, Rikenellaceae, and Clostridium were positively correlated with disease severity. Notably, L. reuteri treatment coordinately altered the relative abundance of these EAE-associated taxa. In conclusion, probiotic L. reuteri changed gut microbiota to modulate immune responses in EAE, making it a novel candidate in future studies to modify the severity of MS.

Keywords: IFN-γ/IL-17; Lactobacillus reuteri; TH1/TH17 cells; experimental autoimmune encephalomyelitis; gut microbiota.

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Figures

Figure 1
Figure 1
Lactobacillus reuteri ameliorates autoimmune disease in EAE mice. (A) Scheme of the experimental timeline for administering L. reuteri to EAE mice and measuring clinical scores. (B) Clinical scores of C57BL/6J mice with EAE to compare with administered MRS and L. reuteri (n = 37–40 mice per group). (C) The representative images of H&E staining, CD3 staining and CD68 staining of spinal cord slides from Ctrl, EAE, and EAE+LR mice (n = 10 mice per group). Arrows indicate immune cell infiltration, defined as encircled areas in H&E staining of EAE and EAE+LR specimens. (D) The average areas of inflammatory infiltration among group comparisons are shown (see Materials and Methods). (E) The average numbers of CD3+ cell count per defined area of inflammatory infiltration among group comparisons (see Materials and Methods). (F) The average numbers of CD68+ cell count per defined area of inflammatory infiltration among group comparisons (see Materials and Methods). Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. EAE+LR vs. EAE. ###p < 0.001. EAE vs. Ctrl.
Figure 2
Figure 2
L. reuteri treatment decreases TH1/TH17 cells and their associated cytokines, and reduces MOG35−55-stimulated cell proliferation in EAE mice. (A) PBMCs. (a) the frequency of IFN-γ+ CD4+ T cells (TH1), (b) the absolute number of IFN-γ+ CD4+ T cells, (c) the frequency of IL-17+ CD4+ T cells (TH17), and (d) the absolute number of IL-17+ CD4+ T cells. (B) Spleen. (a) The frequency of IFN-γ+ CD4+ T cells, (b) the absolute number of IFN-γ+ CD4+ T cells, (c) the frequency of IL-17+ CD4+ T cells, and (d) the absolute number of IL-17+ CD4+ T cells. (C) Plasma IL-17 and IFN-γ levels. (D) The percentage of cell proliferation of splenocytes isolated from the mice at d12 post-immunization responded to in vitro MOG35−55 stimulation (see Materials and Methods) in Ctrl, EAE, and EAE+LR mice (n = 10 mice per group). Data are presented as mean ± SEM. In vitro stimulation assays of PBMCs and splenocytes were performed in triplicate. *p < 0.05, **p < 0.01,***p < 0.001. EAE+LR vs. EAE. ##p < 0.01, ###p < 0.001. EAE vs. Ctrl.
Figure 3
Figure 3
L. reuteri treatment modulates the diversity of the gut microbiota. (A) Gut microbial Phylogenetic Diversity (PD) whole tree analysis, comparing groups of Ctrl, EAE, and EAE+LR mice (n = 7–10 mice per group). (B) Unweighted UniFrac-based 3D PCoA analysis of gut microbiota of Ctrl, EAE, and EAE+LR mice (n = 7–10 mice per group). Data are presented as mean ± SEM. **p < 0.01. EAE+LR vs. EAE. ##p < 0.01. EAE vs. Ctrl.
Figure 4
Figure 4
L. reuteri treatment remodels EAE-associated intestinal microbiota at the phylum level. (A) Relative abundance of bacteria at the phylum level for Ctrl, EAE, and EAE+LR mice (n = 7–10 mice per group). (B) Relative abundance of Bacteroidetes, Proteobacteria, and Deferribacteres at the phylum level for Ctrl, EAE, and EAE+LR mice (n = 7–10 mice per group). Data are presented as mean ± SEM. *p < 0.05, ***p < 0.001. EAE+LR vs. EAE. #p < 0.05, ###p < 0.001. EAE vs. Ctrl.
Figure 5
Figure 5
L. reuteri treatment remodels EAE-associated intestinal microbiota at the Genus level. (A) Relative abundance of predominant bacteria (> 1% of total bacteria) at the genus level for Ctrl, EAE, and EAE+LR mice (n = 7–10 mice per group). (B) The Spearman correlation between gut microbiota (o, order; f, family; g, genus) and the EAE clinical scores of all mice. (C) Relative abundance of Prevotella, Anaeroplasma, S24-7, and Rikenellaceae were compared among the mice of Ctrl, EAE, and EAE+LR groups, respectively, (n = 7–10 mice per group). Data are presented as mean ± SEM. **p < 0.01, ***p < 0.001. EAE+LR vs. EAE. ###p < 0.001. EAE vs. Ctrl.
Figure 6
Figure 6
Predictive model based on the relative abundance profile at the genus level using Random Forest analysis. (A) Predictive power of individual genera (Top 20 most important bacteria at genus level) with three group (Ctrl, EAE, and EAE+LR) comparisons assessed by Random Forest (RF) analysis (o, order; f, family; g, genus). (B) Heatmap based on the relative abundance of bacteria from (A) top 20 most important bacteria at the genus level of Ctrl, EAE, and EAE+LR mice. (C) Predictive power of individual genera (Top 30 most important bacteria at genus level) with two group (EAE and EAE+LR) comparisons assessed by RF analysis. (D) Heatmap based on the relative abundance of bacteria from (C) top 30 most important bacteria at the genus level of EAE and EAE+LR mice. Hierarchical clustering shows that Ctrl, EAE, or EAE+LR samples tend to cluster together, respectively.
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