Project description:Clostridium difficile is an anaerobic spore-forming rod-shaped gram-positive bacterium that can infect both humans and animals. Most studies on the pathogenesis of C. difficile have focused on its toxins and their effect on the host cells. Recently, we utilized microarrays to identify conserved and divergent genes associated with virulence in C. difficile isolates from humans and animals. Our data provided the first clue toward a complex mechanism underlying host adaptation and pathogenesis. Microarray technology offers an efficient high-throughput tool to study the transcriptional profiles of pathogens and infected host cells. Transcriptomes of C. difficile after exposure to environmental and antibiotic stresses and those of human epithelial colorectal Caco-2 cells upon TcdA treatment have been analyzed. To our knowledge, there are still no reports on the transcriptomic study of host-pathogen interactions for C. difficile infection (CDI). In vitro analyses of interplay between host and pathogen are essential to unravel the mechanisms of infection and to investigate the host response to infection. We therefore employed microarrays to study both bacterial and human cellular transcriptome kinetics during CDI to Caco-2 cells. Here we present a large-scale analysis of transcriptional profiles to reveal molecular determinants playing a role in C. difficile pathogenesis and the host response. We found that there were 254 and 224 differentially-expressed genes after CDI in C. difficile and Caco-2 cells, respectively. These genes are clustered according to their functional categories and their potential roles in pathogenesis and host response are discussed. Our results will not only increase our understanding on the host-pathogen interaction, but may also provide targets for drug development. Clostridium difficile: Control vs Infection (time course) mRNA with genomic DNA of tested and reference strains Caco-2 cells: Control vs Infected with Clostridium difficile Time-course experiments of Caco-2 cells infected with C. difficile for 30, 60 and 120 min

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.

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Clostridium difficile infection patient microbiome

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