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. 2016 Jun 28:7:12015.
doi: 10.1038/ncomms12015.

Alterations of the human gut microbiome in multiple sclerosis

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Alterations of the human gut microbiome in multiple sclerosis

Sushrut Jangi et al. Nat Commun. .

Abstract

The gut microbiome plays an important role in immune function and has been implicated in several autoimmune disorders. Here we use 16S rRNA sequencing to investigate the gut microbiome in subjects with multiple sclerosis (MS, n=60) and healthy controls (n=43). Microbiome alterations in MS include increases in Methanobrevibacter and Akkermansia and decreases in Butyricimonas, and correlate with variations in the expression of genes involved in dendritic cell maturation, interferon signalling and NF-kB signalling pathways in circulating T cells and monocytes. Patients on disease-modifying treatment show increased abundances of Prevotella and Sutterella, and decreased Sarcina, compared with untreated patients. MS patients of a second cohort show elevated breath methane compared with controls, consistent with our observation of increased gut Methanobrevibacter in MS in the first cohort. Further study is required to assess whether the observed alterations in the gut microbiome play a role in, or are a consequence of, MS pathogenesis.

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Figures

Figure 1
Figure 1. Study design.
Faecal samples were collected from MS patients (n=60) and healthy subjects (n=43). Microbial DNA was extracted from frozen faecal samples and 16s rDNA sequencing was performed using Roche 454 and Illumina platforms. Gene expression profiling was performed on circulating monocytes and T cells from MS patients (n=18) and healthy subjects (n=18) using a Nanostring platform. Peripheral blood mononuclear cells were collected from MS patients (n=18) and healthy subjects (n=18) to conduct proliferation and cytokine assays in response to specific microbial stimulation. Sera from MS patients (n=45) and healthy subjects (n=16) was collected for ELISA-based techniques to capture serologic activity directed against specific microbes. Breath samples from MS patients (n=41) and healthy subjects (n=32) were collected from a second subject cohort to determine breath methane concentrations.
Figure 2
Figure 2. Compositional differences in faecal microbiota between MS patients and healthy subjects.
(a) Relative abundances of Euryarchaeota and Verrucomicrobia in the faecal microbiota of healthy controls (n=43, grey bar), all MS patients (n=60, red) and both untreated (n=28, orange) and treated MS patient (n=32, blue) subgroups as analysed by two independent sequencing technologies, 454 (top) or MiSeq (bottom). (b) Relative abundance of prevalent microbiota (>1% in any sample group) determined from MiSeq and 454 high-throughput sequencing. (c) Relative abundances of genera in the faecal microbiota that are significantly altered between healthy controls (n=43) and MS patients (n=60; MS-effect) or between untreated (n=28) and treated MS patients (n=32) (disease effect) as analysed by two independent sequencing technologies. Significance was determined by DESeq and Benjamini–Hochberg corrected P values <0.05 with a false discovery rate threshold of 0.1. Bars represent average, and error bars depict s.e.
Figure 3
Figure 3. Correlations between microbiota abundances and immune gene expression.
(a) Gene expression was measured from circulating T cells and monocytes by the Nanostring Immunology panel in MS patients (n=18) and healthy controls (n=18). (a) canonical pathways significantly altered in MS patients and healthy subjects with an activation z-score>|1.5| in both T cells (black bars) and monocytes (grey bars) identified by Ingenuity Pathway Analysis. (b) Altered gut microbiota abundances correlate with immune gene expression in MS patients. Spearman's correlations (σ) between the relative abundance of significantly altered microbes in subject groups and the relative expression of genes from identified canonical pathways significantly altered between healthy controls and untreated MS patients. Colour and slope of ellipse indicate magnitude of correlation, with σ value superimposed on ellipse. Subject groups were either all MS patients and controls together (All), untreated MS patients alone (MS-U) or healthy controls alone (HC).
Figure 4
Figure 4. Measurement of breath methane production in MS patients (n=41) and controls (n=32).
Breath methane measured in each subject is represented on the y axis in parts-per-million on a logarithmic scale. The mean and s.e.m. are shown by the indicated horizontal lines. 28 of 41 MS patients and 24 of 32 controls had no detectable breath methane.

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References

    1. Lozupone C. A., Stombaugh J. I., Gordon J. I., Jansson J. K. & Knight R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012). - PMC - PubMed
    1. McDermott A. J. & Huffnagle G. B. The microbiome and regulation of mucosal immunity. Immunology 142, 24–31 (2014). - PMC - PubMed
    1. Kostic A. D., Xavier R. J. & Gevers D. The microbiome in inflammatory bowel disease: current status and the future ahead. Gastroenterology 146, 1489–1499 (2014). - PMC - PubMed
    1. Alkanani A. K. et al. Alterations in intestinal microbiota correlate with susceptibility to type 1 diabetes. Diabetes 64, 3510–3520 (2015). - PMC - PubMed
    1. Scher J. U. et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. Elife 2, e01202 (2013). - PMC - PubMed

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