Dataset Information

In vivo commensal control of Clostridioides difficile virulence

ABSTRACT: We illustrate how metabolically distinct species of Clostridia can protect against or worsen Clostridioides difficile infection, modulating the pathogen's colonization, growth, and virulence to impact host survival. Gnotobiotic mice colonized with the amino acid fermenter Paraclostridium bifermentans survived infection while mice colonized with the butyrate-producer, Clostridium sardiniense, more rapidly succumbed. Systematic in vivo analyses revealed how each commensal altered the gut nutrient environment, modulating the pathogen's metabolism, regulatory networks, and toxin production. Oral administration of P. bifermentans rescued conventional mice from lethal C. difficile infection via mechanisms identified in specifically colonized mice. Our findings lay the foundation for mechanistically informed therapies to counter C. difficile disease using systems biologic approaches to define host-commensal-pathogen interactions in vivo.

ORGANISM(S): Mus musculus

PROVIDER: GSE182613 | GEO | 2021/10/04

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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. This model is hosted on BioModels Database and identified by: BIOMD0000000583. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

In vivo commensal control of Clostridioides difficile virulence

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets