Experimental Autoimmune Encephalomyelitis is Associated with Changes of the Microbiota Composition in the Gastrointestinal Tract
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus blank sample
PROVIDER: GSE153118 | GEO | 2020/09/15
REPOSITORIES: GEO
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Project description:Multiple Sclerosis (MS) is a complex disease of the CNS believed to require one or more environmental triggers and is characterized by episodic formation of inflammatory demyelinating lesions in the brain and spinal cord. Gut dysbiosis is a common feature in MS and here, using enhanced and quantitative PCR detection, we show that people with MS are more likely to harbor and have higher abundance of epsilon toxin (ETX)-producing strains of Clostridium perfringens within their gut microbiome compared to healthy controls (HC). MS patient-derived isolates produce functional ETX and have a genetic architecture typical of highly conjugative plasmids. In the active immunization model of experimental autoimmune encephalomyelitis (EAE), where pertussis toxin (PTX) is used to overcome CNS immune privilege, we find that ETX can substitute for PTX in disease induction. In contrast to PTX-induced EAE, where inflammatory demyelination is largely restricted to the spinal cord, ETX-induced EAE results in multifocal demyelination in the corpus callosum, thalamus, cerebellum, brainstem, and spinal cord, more akin to the lesion distribution observed in MS. Transcriptional profiles from CNS endothelial cells reveal ETX-induced genes that are known to play a role in overcoming CNS immune privilege. Together, these findings support ETX-producing strains of C. perfringens as biologically plausible pathogens in MS to trigger inflammatory demyelination in the context of circulating myelin autoreactive lymphocytes.
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Project description:Leber2015 - Mucosal immunity and gut
microbiome interaction during C. difficile infection
This model is described in the article:
Systems Modeling of
Interactions between Mucosal Immunity and the Gut Microbiome
during Clostridium difficile Infection.
Leber A, Viladomiu M, Hontecillas R,
Abedi V, Philipson C, Hoops S, Howard B, Bassaganya-Riera
J.
PLoS ONE 2015; 10(7): e0134849
Abstract:
Clostridium difficile infections are associated with the use
of broad-spectrum antibiotics and result in an exuberant
inflammatory response, leading to nosocomial diarrhea, colitis
and even death. To better understand the dynamics of mucosal
immunity during C. difficile infection from initiation through
expansion to resolution, we built a computational model of the
mucosal immune response to the bacterium. The model was
calibrated using data from a mouse model of C. difficile
infection. The model demonstrates a crucial role of T helper 17
(Th17) effector responses in the colonic lamina propria and
luminal commensal bacteria populations in the clearance of C.
difficile and colonic pathology, whereas regulatory T (Treg)
cells responses are associated with the recovery phase. In
addition, the production of anti-microbial peptides by inflamed
epithelial cells and activated neutrophils in response to C.
difficile infection inhibit the re-growth of beneficial
commensal bacterial species. Computational simulations suggest
that the removal of neutrophil and epithelial cell derived
anti-microbial inhibitions, separately and together, on
commensal bacterial regrowth promote recovery and minimize
colonic inflammatory pathology. Simulation results predict a
decrease in colonic inflammatory markers, such as neutrophilic
influx and Th17 cells in the colonic lamina propria, and length
of infection with accelerated commensal bacteria re-growth
through altered anti-microbial inhibition. Computational
modeling provides novel insights on the therapeutic value of
repopulating the colonic microbiome and inducing regulatory
mucosal immune responses during C. difficile infection. Thus,
modeling mucosal immunity-gut microbiota interactions has the
potential to guide the development of targeted fecal
transplantation therapies in the context of precision medicine
interventions.
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2024-09-02 | BIOMD0000000583 | BioModels
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