Human gut metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA645218 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12339335.fastq.gz | Fastqsanger.gz | |||
| SRR12339336.fastq.gz | Fastqsanger.gz | |||
| SRR12339337.fastq.gz | Fastqsanger.gz | |||
| SRR12339338.fastq.gz | Fastqsanger.gz | |||
| SRR12339339.fastq.gz | Fastqsanger.gz |
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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
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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
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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
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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
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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.
This model is hosted on
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BIOMD0000000583.
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