Ontology highlight
ABSTRACT:
PROVIDER: PRJNA650203 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12365800.fastq.gz | Fastqsanger.gz | |||
| SRR12365900.fastq.gz | Fastqsanger.gz | |||
| SRR12365801.fastq.gz | Fastqsanger.gz | |||
| SRR12365901.fastq.gz | Fastqsanger.gz | |||
| SRR12365802.fastq.gz | Fastqsanger.gz |
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Project description:Treatment of recurrent Clostridioides difficile infection with Fecal Microbiota Transplantation
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Project description:Recurrent Clostridioides difficile infection (CDI) results in significant morbidity and mortality. We previously established that CDI in mice did not protect against reinfection and was associated with poor pathogen-specific B cell memory (Bmem), recapitulating our observations with human Bmem. Herein, we demonstrate that the secreted toxin TcdB2 is responsible for subversion of Bmem responses. TcdB2 from an endemic C. difficile strain delayed IgG class switch following vaccination, attenuated IgG recall to a vaccine booster, and prevented germinal center formation. The mechanism of TcdB2 action included increased B cell CXCR4 expression and responsiveness to its ligand CXCL12, accounting for altered cell migration and a failure of germinal center-dependent Bmem. These results were reproduced in a C. difficile infection model and an FDA-approved CXCR4-blocking drug rescued germinal center formation. We therefore provide mechanistic insights into C. difficile-associated pathogenesis and illuminate a target for clinical intervention to limit recurrent disease.
2024-04-25 | GSE263792 | GEO
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2023-03-23 | E-MTAB-12660 | biostudies-arrayexpress
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
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BIOMD0000000583.
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2024-09-02 | BIOMD0000000583 | BioModels
Project description:The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the United States. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) have been used to identify therapeutic targets and uncover properties that determine cellular behaviors. Thus, we constructed C. difficile GENREs for a hypervirulent isolate (strain [str.] R20291) and a historic strain (str. 630), validating both with in vitro and in vivo data sets. Growth simulations revealed significant correlations with measured carbon source usage (positive predictive value [PPV] ≥ 92.7%), and single-gene deletion analysis showed >89.0% accuracy. Next, we utilized each GENRE to identify metabolic drivers of both sporulation and biofilm formation. Through contextualization of each model using transcriptomes generated from in vitro and infection conditions, we discovered reliance on the pentose phosphate pathway as well as increased usage of cytidine and N-acetylneuraminate when virulence expression is reduced, which was subsequently supported experimentally. Our results highlight the ability of GENREs to identify novel metabolite signals in higher-order phenotypes like bacterial pathogenesis.
2023-11-27 | MODEL2205060002 | BioModels
Project description:Fecal samples were collected from patients with recurrent Clostridium difficile infection before and after treatment with fecal microbiota transplantation. Fecal samples were frozen immediately after collections, and later put into ~50mg aliquots for later analysis (at -80 C).
2017-06-19 | ST000733 | MetabolomicsWorkbench
Project description:Biomarkers for Successful Faecal Microbiota Transplantation in Recurrent Clostridioides difficile Infection
| PRJEB75677 | ENA
Project description:Clostridioides difficile can cause severe infections in the gastrointestinal tract and affects almost half a million people in the U.S every year. Upon establishment of infection, a strong immune response is induced. We sought to investigate the dynamics of the mucosal host response during C. difficile infection.
2023-09-13 | GSE237574 | GEO