Project description:Purpose: To determine whether previously observed behavioral differences in alcoholic human patients after fecal microbiota transplantation (FMT) could be transferred to mice. Methods: Fecal microbiota samples from a previously published phase 1, double-blind, randomized clinical trial of AUD-related cirrhosis patients were used to colonize germ-free mice. Fecal material was transferred to 10-15-week-old GF C57BL/6 male mice by daily gavage for 3 day. The mice were housed in sterile individually filtered cages for 15 days after which stool was collected and then they underwent the alcohol preference experiment using 2-bottle choice drinking (water and 20% ethanol v/v). Microbial DNA was isolated from stool samples by sequencing the V1 and V2 variable regions of the bacterial 16S rRNA gene were sequenced using Multitag fusion primers and sequenced on an Ion Torrent PGM next-generation sequencer. Intestinal mucosa, liver, and prefrontal cortex tissue was collected from mice at time of sacrifice. RNAseq was used to measure gene expression in pre-FMT and post-FMT samples. RNAseq data were aligned to the mouse genome (GRCm39) using STAR (version 2.7.9a) and counts were generated with HTSeq (version 0.13.5). Genes with very low counts across the study (defined as fewer than 10 counts in more than 2 samples) were eliminated before differential expression analysis. Low count genes were determined separately for each tissue type. The DESeq2 package for R was then used to measure differential expression between pre-FMT and post-FMT mice in the intestine, liver, and PFC. Benjamini and Hochberg False Discovery Rate (FDR) was used to correct for multiple testing with FDR ≤ 0.2 considered significant. Results: Mice colonized with post-FMT stool significantly reduced ethanol acceptance, intake and preference versus pre-FMT colonized mice. Microbial taxa that were higher in post-FMT humans were also associated with lower alcohol intake and preference in mice. RNAseq further showed that differential gene expression, post-FMT, occurred in the intestine rather than the liver and prefrontal cortex. Conclusions: FMT leads to significant change in gut microbiome population, which in turn alters gene expression in the intestine. FMT also significantly affects alcohol consumption. The microbiotal-intestinal interface may alter gut-liver-brain axis and reduce alcohol consumption in humans.

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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