A probiotic modulates the microbiome and immunity in multiple sclerosis

Abstract

Objective: Effect of a probiotic on the gut microbiome and peripheral immune function in healthy controls and relapsing-remitting multiple sclerosis (MS) patients.

Methods: MS patients (N = 9) and controls (N = 13) were orally administered a probiotic containing Lactobacillus, Bifidobacterium, and Streptococcus twice-daily for two months. Blood and stool specimens were collected at baseline, after completion of the 2-month treatment, and 3 months after discontinuation of therapy. Frozen peripheral blood mononuclear cells (PBMCs) were used for immune cell profiling. Stool samples were used for 16S rRNA profiling and metabolomics.

Results: Probiotic administration increased the abundance of several taxa known to be depleted in MS such as Lactobacillus. We found that probiotic use decreased the abundance of taxa previously associated with dysbiosis in MS, including Akkermansia and Blautia. Predictive metagenomic analysis revealed a decrease in the abundance of several KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways associated with altered gut microbiota function in MS patients, such as methane metabolism, following probiotic supplementation. At the immune level, probiotic administration induced an anti-inflammatory peripheral immune response characterized by decreased frequency of inflammatory monocytes, decreased mean fluorescence intensity (MFI) of CD80 on classical monocytes, as well as decreased human leukocyte antigen (HLA) D related MFI on dendritic cells. Probiotic administration was also associated with decreased expression of MS risk allele HLA-DQA1 in controls. Probiotic-induced increase in abundance of Lactobacillus and Bifidobacterium was associated with decreased expression of MS risk allele HLA.DPB1 in controls.

Interpretation: Our results suggest that probiotics could have a synergistic effect with current MS therapies. Ann Neurol 2018.

Figure 1. Study design flowchart

Blood and fecal samples were collected from healthy subjects (n=13) and multiple sclerosis (MS) patients (n=9) prior to (baseline), at discontinuation of probiotic LBS (2-month visit) and 3 months thereafter (5-month visit). Bacteria DNA was extracted from feces samples obtained at all 3 time points and 16S rRNA sequencing was performed using Illumina MiSeq.16S data was used to obtain predicted metagenomics by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States). Feces samples were also used for stool metabolomics profiling at all 3 time points. Immune cells profiling was performed in healthy subjects and MS patients at all 3 time points by flow cytometry. Gene expression profiling was performed on peripheral monocytes and CD4 T cells from healthy controls and MS patients using a Nanostring immunology panel array and high-throughput eukaryotic digital gene expression RNA-Seq (RNA-DGE) respectively.

Figure 2. LBS effect on alpha and beta diversity of the gut microbiome

Rarefaction curves were calculated at multiple sequence depths on MiSeq platform for Shannon entropy to compare differences in alpha-diversity at the indicated time points in A) healthy controls (n=13) and multiple sclerosis (MS) patients (n=9). Shannon index was also measured at a depth of 10000 reads in B) healthy controls (HC) and MS patients at the indicated time points determined by paired one-way ANOVA with Tukey’s post-test, *p<0.05. Principal coordinate analysis of weighted and unweighted UniFrac distances colored according to time points in C–D) healthy controls and MS patients. E) Average individual UniFrac distances calculated per subject assessed by paired one-way ANOVA with Tukey’s post-test, *p<0.05; **p<0.01; #p<0.1.

Figure 3. LBS effect on gut microbiota composition

Compositional differences in fecal microbiota before and after LBS administration in A) healthy controls (HC) and multiple sclerosis (MS) patients. B) Log10 fold change in abundance of top 20 most affected operational taxonomic units (OTUs) following LBS administration and discontinuation in controls and MS patients determined by Wilcoxon signed rank test at p<0.05. C) Effect of LBS on relative abundance of the indicated taxa in HC and MS patients determined by Wilcoxon signed rank test, *p<0.05; **p<0.01; #p<0.1. OTU = Operational taxonomic unit; NR = New Reference.

Figure 4. LBS effect on gut microbiota function

PICRUSt was used to infer the functional content of the gut microbiota based on 16S data. A) Fold change of the abundance of KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways following administration and discontinuation of LBS in healthy controls and multiple sclerosis (MS) patient assessed by Wilcoxon signed rank test with FDR (false discovery rate) <0.05. B) Effect of LBS on stool metabolites concentration in controls and MS patients determined by Wilcoxon signed rank test, *p<0.05; **p<0.01. Spearman’s correlations between microbiota abundances and stool metabolites concentration following LBS supplementation in C–D) healthy controls (HC) and MS patients. Corr Coefficient = Spearman’s correlation coefficient; OTU = Operational taxonomic unit; ADM = Adenosine monophosphate; NR = New Reference.

Figure 5. LBS effect on immune cells profile

FACS analysis was used to compare the frequencies of A–D) CD4⁺ IL-10⁺ T cells, CD39⁺ CD127^low CD25^high T cells, CD4⁺ LAP⁺ T cells and effector memory CD8 T cells in healthy controls (HC) and multiple sclerosis patients (MS) at the indicated time points determined by Wilcoxon signed rank test. *p<0.05; #p<0.1. FACS analysis was used to compare E–F) the frequencies of intermediate monocytes, inflammatory monocytes as well as CD80 mean fluorescence intensity (MFI) on classical monocytes and HLA-DR MFI on dendritic cells in HC and MS patients at the indicated time points determined by Wilcoxon signed rank test, *p<0.05; **p<0.01; #p<0.1. The following markers were used for the lineage pool: CD3, CD14, CD16, CD19, CD20, CD56.

Figure 6. LBS effect on gene expression profile in peripheral monocytes

A) Gene expression was measured in circulating monocytes using the Nanostring Immunology panel array at the indicated time points in healthy controls (n=9) and MS patients (n=7) assessed by Wilcoxon signed rank test, *p<0.05; **p<0.01. Spearman’s correlation between immune markers and operational taxonomic units (OTUs) relative abundance following LBS supplementation in B–C) healthy controls and MS patients. OTU = Operational taxonomic unit; NR = New Reference; Mono/monos = Monocytes; MFI = Mean fluorescence intensity; Corr coefficient = Correlation coefficient.