Project description:The aim of this study was to investigate whether long term intake of pea fiber would improve colonic barrier, bacterial profile and alter colonic gene expression using DNA microarray. Fifty weaned pigs were randomly allocated into 2 groups receiving control and fibrous diet with inclusion of pea fiber from weaning age until d 160. The two diets had similar nutrient levels. Pigs fed pea fiber diet (PF diet) had markedly decreased overall average daily feed intake (ADFI) and Feed:Gain in growing and finishing period (P<0.05). In addition, long term intake of PF diet induced deeper crypt (+50 %, P<0.05), increased protein expression of colonic mucin and sIgA (+13～16 %, P<0.05). Resulting from the increased lactobacillus content (P<0.05), moreover, pigs fed PF diet had significantly higher concentration of colonic total short chain fatty acid (SCFA) and acetic acid. DNA microarray results indicated that feeding PF diet induced alterations in the expression of colonic cancer, immune response and lipid metabolism-related genes, as well as genes involved in signal pathway such as intestinal immune network for IgA production, PPAR signaling pathway and nutrient metabolism-related pathways. Collectively, our results suggested that long term intake of PF diet would improve colonic health via altering colonic bacteria profile, colonic barriers, immune and metabolism related protein or gene expressions. A total of 50 weaned pigs (Duroc×Landrace×Yorkshire, initial body weight: 7.2±0.5 kg) were randomly allocated to 2 groups with 5 pens each group and 5 pig each pen. Pigs were fed control (Control) and fibrous diets (10～20 % inclusion of pea fiber, PF) from weaning at 28 day to 160 day-old-age, which is subjected to phase feeding by weaning diet (weaning to d 30 post-weaning), growing diet (d 30～90 postweaning) and finishing diet (d 90～160 postweaning) according to their physiological stage. At d 160 postweaning, four pigs each group were selected to be slaughtered for collection of colonic tissues and DNA microarray was applied to the colonic tissues for analysis of gene expression.

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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