DOI: 10.7272/q6wq01zb
title: Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models

description: The gut microbiota regulates T cell functions throughout the body. We
 hypothesized that intestinal bacteria impact the pathogenesis of multiple
 sclerosis (MS), an autoimmune disorder of the central nervous system, and
 thus analyzed the microbiomes of 71 MS patients not undergoing treatment
 and 71 healthy controls. Although no major shifts in microbial community
 structure were found, we identified specific bacterial taxa that were
 significantly associated with MS. Akkermansia muciniphila and
 Acinetobacter calcoaceticus, both increased in MS patients, induced
 pro-inflammatory responses in human PBMCs and in mono-colonized mice. In
 contrast, Parabacteroides distasonis, which was reduced in MS patients,
 stimulated anti-inflammatory interleukin-10 (IL-10)-expressing human
 CD4+CD25+ T cells, and IL-10+FoxP3+ regulatory T cells (Tregs) in mice.
 Finally, microbiota transplants from MS patients into germ-free mice
 resulted in more severe symptoms of experimental autoimmune
 encephalomyelitis (EAE) and reduced proportions of IL-10+ Tregs compared
 to mice “humanized” with microbiota from healthy controls. This study
 identifies specific human gut bacteria that regulate adaptive autoimmune
 responses, suggesting therapeutic targeting of the microbiota as a novel
 treatment for MS.
description: Human fecal sample collectionFecal samples
 were collected from 71 adult patients with relapsing-remitting multiple
 sclerosis that had not received treatment for at least 3 months prior to
 the time of collection and 71 controls without autoimmune disorders at the
 University of California, San Francisco (UCSF) and the Icahn School of
 Medicine at Mt Sinai (New York, NY). The inclusion criteria specified no
 use of antibiotics or cancer therapeutics in 3 months prior to the study.
 Detailed patient information is available in Supplementary Table 1.
 Samples were collected using culture swabs (BD #220135) and stored at -80C
 until DNA extraction or bacterial isolation.16S rRNA
 amplicon sequencing and computational analysis of human and mouse
 microbiome samplesDNA was extracted from samples using
 MoBio Power Fecal DNA extraction kit (MoBio #12830) and amplicons of V4
 region of the prokaryotic 16S rRNA gene were sequenced using the Earth
 Microbiome Project standard protocol (1). Analysis was performed using
 QIIME v1.9 as described (2). Essentially, amplicon sequences were
 quality-filtered and grouped to “species-level” OTUs using SortMeRNA
 method (3) using GreenGenes version 13.8 97% dataset for closed reference.
 Sequences that did not match reference sequences in the GreenGenes
 database were dropped from the analysis. Taxonomy was assigned to the
 retained OTUs based on the GreenGenes reference sequence, and the
 GreenGenes tree was used for all downstream phylogenetic community
 comparisons. Samples were filtered to at least 10000 sequences per sample,
 and OTUs were filtered to retain only OTUs present in at least 5% of
 samples and covering at least 100 total reads. After filtering samples
 were rarefied to 10000 sequences per sample. We identified 129 total
 genera and 1462 total operational taxonomic units (OTUs) in our samples.
 We systematically compared relative abundances of individual microbial
 taxa between MS patients and controls at the genus and OTU levels by
 negative binomial Wald test using Benjamini-Hochberg correction for
 multiple comparisons (4). Alpha diversity was calculated using the Chao1
 method (5). For analysis of beta diversity, pairwise distance matrices
 were generated using the phylogenetic metric unweighted UniFrac (6) and
 used for principal coordinate analysis (PCoA). For comparison of
 individual taxa, samples were not rarefied. Instead, OTU abundances were
 normalized using variance-stabilizing transformation and taxa
 distributions were compared using Wald negative binomial test from R
 software package DESeq2 as described previously (4, 7) with
 Benjamini-Hochberg correction for multiple comparisons. All statistical
 analyses of differences between individual bacterial species were
 performed using QIIME v.1.9 or R (packages DESeq2 and phyloseq).
description: Two files are uploaded. The dataset contains both human and mice
 samples. 5set_map_for_EBI.txt: Contains the sample
 metadata5set_otus_for_EBI.txt: contains the normalized
 OTU abundances for each individualOTU abundances were
 normalized using variance-stabilizing transformation and taxa
 distributions were compared using the Wald negative binomial test from the
 R software package DESeq2 (as described in (4, 5) with Benjamini-Hochberg
 correction for multiple comparisons.