Multiple sclerosis-associated changes in the composition and immune functions of spore-forming bacteria
Baranzini, Sergio; Cekanaviciute, Egle (2018), Multiple sclerosis-associated changes in the composition and immune functions of spore-forming bacteria, UC San Francisco Dash, Dataset, https://doi.org/10.7272/Q6FB5136
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by adaptive and innate immune system dysregulation. Recent work has revealed moderate alteration of gut microbial communities in subjects with MS and in experimental, induced models. However, a mechanistic understanding linking the observed changes in the microbiota and the presence of the disease is still missing. Chloroform-resistant, spore-forming bacteria, which primarily belong to the classes Bacilli and Clostridia in the phylum Firmicutes, have been shown to exhibit immunomodulatory properties in vitro and in vivo, but they have not yet been characterized in the context of human disease. This study addresses the community composition and immune function of this bacterial fraction in MS. We identify MS-associated spore-forming taxa (primarily in the class Clostridia) and show that their presence correlates with impaired differentiation of IL-10 secreting, regulatory T lymphocytes in-vitro. Colonization of antibiotic-treated mice with spore-forming bacteria allowed us to identify some bacterial taxa favoring IL-10+ lymphocyte differentiation and others inducing differentiation of pro-inflammatory, IFN+ T lymphocytes. However, when fed into antibiotic-treated mice, both MS and control derived spore-forming bacteria were able to induce immunoregulatory responses. Our analysis also identified Akkermansia muciniphila as a key organism that may interact either directly or indirectly with spore-forming bacteria to exacerbate the inflammatory effects of MS-associated gut microbiota. Thus, changes in the spore-forming fraction may influence T lymphocyte-mediated inflammation in MS. This experimental approach of isolating a subset of microbiota based on its functional characteristics may be useful to investigate other microbial fractions at greater depth.
Isolation of spore-forming bacteria from human fecal samples
Fecal samples were collected from 25 adult patients with RRMS that had not received disease- modifying or steroid treatment for at least 3 months prior to the time of collection and 24 subjects without MS or any other autoimmune disorder (controls) at the University of California, San Francisco (UCSF). The inclusion criteria specified no use of antibiotics or oncologic therapeutics in 3 months prior to the study. All individuals signed a written informed consent in accordance with the sampling procedure approved by the local Institutional Review Board. Samples were stored in collection vials (Fisher #NC9779954) at -80° C until bacterial isolation.
Spore-forming bacteria were isolated based on their resistance to chloroform as described previously (Atarashi 2013). Briefly, total bacteria were isolated from stool samples by suspending ~0.5mg stool sample in 1.5ml PBS, passing it three times through a 70um cell strainer and washing twice with 1.5ml PBS by spinning at 8000rpm. The resulting suspension was diluted in 5ml PBS, mixed with chloroform to the final concentration of 3%, and incubated on a shaker for 1h at room temperature. After incubation, chloroform was removed from the solution by bubbling nitrogen (N2) gas for 30min. Chloroform-treated bacteria were then cultured on OxyPRAS Brucella Blood Agar plates (Oxyrase #P-BRU-BA) for 96 hours followed by Brucella Broth (Anaerobe Systems #AS-105) for 48 hours, and isolated for sequencing, in vitro experiments and in vivo experiments.
16S rRNA amplicon sequencing and computational analysis
DNA was extracted from mouse fecal or human chloroform-resistant bacterial culture samples using MoBio Power Fecal DNA extraction kit (MoBio #12830) according to manufacturer’s instructions. For each sample, PCR targeting the V4 region of the prokaryotic 16S rRNA gene was completed in triplicate using the 515/806 primer pair, and amplicons were sequenced on NextSeq at the Microbiome Profiling Services core facility at UCSF using the sequencing primers and procedures described in the Earth Microbiome Project standard protocol. Analysis was performed using QIIME v1.9 as described. Essentially, amplicon sequences were quality-filtered and grouped to “species-level” OTUs via SortMeRNA method, using Greengenes v.13.8 97% dataset for closed reference. Sequences that did not match reference sequences in the Greengenes database were dropped from 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. 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. Alpha diversity was calculated using the Chao1 method. For analysis of beta diversity, pairwise distance matrices were generated using the phylogenetic metric unweighted UniFrac and used for principal coordinate analysis (PCoA). For comparison of individual taxa, samples were not rarefied. Instead, OTU and taxa distributions were compared based on raw counts using Wald negative binomial test from R software package DESeq2 as described previously with Benjamini-Hochberg correction for multiple comparisons. For visualization purposes variance stabilizing transformation was applied with local fit type. Linear correlations between bacterial taxa and lymphocyte proportions were computed after variance-stabilizing transformation of bacterial abundances. Human sample sequencing was performed in two batches and they were used as a covariate for calculation.
There are two datasets in this submission:
1) mouse (
National Multiple Sclerosis Society, Award: CA_1072-A-7