Specific microbial ratio in the gut microbiome is associated with multiple sclerosis

Abstract

Gut microbiota dysbiosis is associated with multiple sclerosis (MS), but the causal relationship between specific gut bacteria and MS pathogenesis remains poorly understood. Therefore, we profiled the stool microbiome of people with MS (PwMS) and healthy controls (HC) using shotgun metagenomic sequencing. PwMS showed a distinct microbiome compared to HC, with Prevotella copri (PC) and Blautia species as drivers of microbial communities in HC and PwMS, respectively. Administration of MS-driving Blautia species (Blautia wexlerae; BW) to mice resulted in increased levels of gut inflammatory markers and altered microbiota with increased capacity to induce proinflammatory cytokines. Utilizing experimental autoimmune encephalomyelitis (EAE), an animal model of MS, we identified a lower gut Bifidobacterium to Akkermansia ratio as a hallmark of the disease. BW-administered mice also showed a lower Bifidobacterium to Akkermansia ratio pre-EAE induction which correlated with increased disease severity post-EAE induction. The importance of the Bifidobacterium to Akkermansia ratio at the species level, lower Bifidobacterium adolescentis to Akkermansia muciniphila (BA:AM), was validated in our MS cohort and a large International Multiple Sclerosis Microbiome Study. Thus, our findings highlight the BA:AM ratio as a potential gut microbial marker in PwMS, opening avenues for microbiome-based diagnosis, prognosis, and therapy in MS.

Keywords: gut microbial markers; gut microbiome; inflammation; microbial ratio; multiple sclerosis.

Fig. 1.

PwMS (people with MS) harbor distinct inflammatory gut microbiome irrespective of treatment. (A–C) Quantification of (A) fecal lipocalin2, (B) fecal calprotectin, and (C) plasma osteopontin levels in samples from HCs and PwMS using the ELISA. For fecal lipocalin2 and calprotectin, samples from 34 HC and 44 PwMS were included in the analysis as others were beyond detection range in the ELISA. For plasma osteopontin, samples from 33 HCs and 44 PwMS were included in the analysis as others were beyond the detection range or did not provide associated blood samples. (D) Shannon diversity between and (E) phylogenetic diversity between PwMS and HCs. (F) Bray–Curtis dissimilarity metric–based principal coordinate analysis plot depicting compositional differences in the microbial communities of PwMS and HCs. P-values represent statistical significance using the Wilcoxon test in (A–E). adonis2 test from the vegan package in R was used for significance testing in (F).

Fig. 2.

Blautia and/or Akkermansia drive the heterogeneous gut microbiome in PwMS. (A and B) Bray–Curtis dissimilarity metrics–based PCoA plot representing major bacterial taxa weighing toward samples from HCs or PwMS. adonis2 test from the vegan R package was used for statistical inference. (B) Differential analysis of the microbiome between the HCs and PwMS microbiome was performed using diff_analysis function from the microbiotaprocess package in R with other parameters being default except lda = 3 and P < 0.05 and default q < 0.3 in samples from HCs and PwMS and visualized using ggplot2.

Fig. 3.

Gut microbiota profile in mice induced with EAE. C57BL/6J female mice (4 to 6 wk old) were obtained from Jackson Laboratories (Bar Harbor, ME) and bred in the University of Iowa mouse facility. Pups at the age of 4 to 6 wk were kept on a standard normal chow diet ad libitum and randomly divided into three groups (n = 5/group). Mice in each group received PBS (control), CFA+PTX (vehicle control), or CFA+PTX+MOG_35-55 (EAE). (A) Schematic diagram of the experiment. (B) Average clinical EAE scores (mean ± SEM). (C) Shannon diversity on day 14. (D) PCoA plots showing microbiome compositional differences between groups on days 0, 7, and 14 based on Bray–Curtis dissimilarity metrics. P-value determined by adonis2 test followed by pairwise comparison and “BH” correction. Microbial taxa were collapsed at the genus level and differentially abundant taxa from (E) fecal samples and (F) colonic mucosa in the three groups on day 14, as determined using the “lefse” function in the “microbiomeMarker.” (G–I) Relative abundance (%) of bacteria enriched in colonic mucosa for (G) Faecalibaculum, (H) Bifidobacterium, and (I) Akkermansia in figure (F) in each of the three groups. (J–L) Fecal Faecalibaculum, Bifidobacterium, and Akkermansia abundances in feces of three groups over time (M) Bifidobacterium to Akkermansia ratio in feces between the three groups. (N) Bifidobacterium to Akkermansia ratio in feces between the three groups on day 14. (O) Bifidobacterium to Akkermansia ratio in colonic mucosa between the three groups on day 14. The Kruskal–Wallis test followed by pairwise comparison and “BH”-based P-value correction was used for group-wise comparison for figures (C, G–I, N, and O).

Fig. 4.

Alteration of gut microbiome communities in PC-, PV-, and BW-administered mice. (A) Schematic experimental outline. C57BL/6J female mice (4 to 6 wk old) were randomly divided into three groups (n = 9-10/group) and treated with antibiotics cocktail (combination of vancomycin, neomycin, ampicillin, and metronidazole supplemented with Splenda) for a 3 d-period to deplete the gut microbiome. Mice in each group were then administered with PC, PV, or BW followed by FMT. Fecal samples were collected at different time points as shown by red triangles for microbiome community assessment. (B) Differentially enriched bacterial taxa at the genus level after mice were administered PC, PV, or BW (day 27). P-adjusted values ≤ 0.05 was used for significance testing. (C) Bifidobacterium:Akkermansia ratio over time on days 9, 13, 17, 22, and 27 in PC-, PV-, and BW-administered mice. The Kruskal–Wallis test followed by pairwise comparison and “BH”-based P-value correction was performed in (C).

Fig. 5.

Administering Blautia species increases gut inflammatory markers and lowers Bifidobacterium:Akkermansia ratio. (A and B) Quantification of fecal lipocalin2 and calprotectin on day 27. (C–G) Determination of levels of cytokines TNF α (C), IL6 (D), CXCL1 (E), IL12/23 (F), and IL10 (G) in supernatants of BMDMs cultured with fecal lipopolysaccharides extracted from fecal sample of day 27 mice were administered PC, PV, or BW. (H–N) Spearman correlation of Bifidobacterium:Akkermansia ratio to fecal lipocalin2, calprotectin, and cytokines levels in (A–G). The Kruskal–Wallis test followed by pairwise comparison and “BH”-based P-value correction was performed for (A–G) between the groups.

Fig. 6.

Increased EAE severity in mice administered with BW is associated with lower Bifidobacterium:Akkermansia ratio and elevated IL6 and IL-12/23. (A) Average clinical EAE scores (mean ± SEM) of mice administered with PC, PV, and BW over time after day 27 in Fig. 4A. Two-way ANOVA was performed to compare mean EAE scores of mice in each group with other group on a specific day and P-values represent P-adjusted values that were obtained after correcting for multiple comparison using the Tukey method in GraphPadPrism10.3.0. No significance was observed between groups on day 0 to day 12. Significant differences with adjusted-P-values on day 14, 15 and 17 are shown in figure. (B) Cumulative EAE scores of mice from (A). One-way ANOVA using Brown–Forsythe and Welch ANOVA tests was used for statistical comparison in GraphPadPrism10.3.0. (C–J) Spearman correlation of pre-EAE induction (day 27) Bifidobacterium:Akkermansia ratio to (C) cumulative EAE scores (D) lipocalin2 (E) calprotectin (F) TNFα (G) IL6 (H) CXCL1 (I) IL-12/23 and (J) IL10 levels from Fig. 5 A–G.

Fig. 7.

A lower B. adolescentis to A. muciniphila ratio (BA:AM ratio) is a gut microbial marker in PwMS. Normalized abundance of (A) B. adolescentis and (B) A. muciniphila. (C) BA:AM ratio in HC (n = 51) and PwMS patients (n = 45) from our cohort. Normalized abundance of (D) B. adolescentis and (E) A.muciniphila. (F) BA:AM ratio in the iMSMS cohort (15) consisting of household HCs (n = 576) and PwMS (n = 576). Normalized abundance of (G) B. adolescentis and (H) A. muciniphila in the iMSMS cohort (I) BA:AM ratio in PwMS with different types of the disease, RRMS, SPMS, or PPMS, and (J) in healthy household controls and treated and untreated PwMS patients from the iMSMS cohort. Spearman correlation of the BA:AM ratio with (K) EDSS, (L) MSSS, and (M) disease duration from the iMSMS cohort. The Kruskal–Wallis test followed by pairwise comparison was performed in (G–J), and adjusted P-values after “BH” correction are shown.