Project description:Clostridioides difficile interactions with the gut mucosa are crucial for colonisation and establishment of infection, however key infection events during the establishment of disease are still poorly defined. To better understand the initial events that occur during C. difficile colonisation, we employed a dual RNA-sequencing approach to study the host and bacterial transcriptomic profiles during C. difficile infection in a dual-environment in vitro human gut model. Temporal changes in gene expression were analysed over 3-24h post infection and comparisons were made with uninfected controls.
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.
Project description: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.
Project description:Frequent and excessive use of antibiotics prime patients to Clostridioides difficile infection (CDI) that leads to fatal pseudomembranous colitis, with limited treatment options. In earlier reports, we used a drug repurposing strategy and identified amoxapine (an antidepressant), doxapram (a breathing stimulant), and trifluoperazine (an antipsychotic), which provided significant protection to mice against lethal infections with several pathogens, including C. difficile. However, the mechanisms of action of these drugs were not known. Here we provide evidence that all three drugs offered protection against experimental CDI by reducing bacterial burden and toxin levels, although the drugs were neither bacteriostatic nor bactericidal in nature and had minimal impact on the composition of the microbiota. Drug-mediated protection was dependent on the presence of the microbiota, implicating its role in evoking host defenses that promoted protective immunity. By utilizing RNA-seq, we identified that each drug increased expression of several innate immune response-related genes, including those involved in the recruitment of neutrophils, production of interleukin (IL)-33, and the IL-22 signaling pathway. The RNA-seq data on selected genes were confirmed by qRT-PCR and protein assays. Focusing on amoxapine, which had the best anti-CDI outcome, we demonstrated that neutralization of IL-33 or depletion of neutrophils resulted in loss of drug efficacy. Overall, our lead drugs promote disease alleviation and survival in the murine model through activation of IL-33 and by clearing the pathogen through host defense mechanisms that critically include an early influx of neutrophils.
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.
Project description:Clostridioides difficile is a major cause of healthcare-associated diarrhea in adult patients. Laboratory diagnosis of C. difficile infection (CDI) is challenging as there is no single test combining high sensitivity and specificity, rapid turnaround time and cost efficiency. They also offer no or little correlation with the clinical outcome. Recently, host-based methods have shown satisfactory performance for the diagnosis of infectious diseases. The aim of this study was to discover CDI-specific host biomarkers that correlate with disease stage and severity.
Project description:Gene expression level of Clostridioides difficile (C. difficile) strain R20291 comparing control C. difficile carring pMTL84151 as vector plasmid with C. difficile conjugated with a pMTL84151-03890 gene. Goal was to determine the effects of 03890 gene conjugation on C. difficile strain R20291 gene expression.
Project description:The intestines house a diverse microbiota that must compete for nutrients to survive, but the specific limiting nutrients that control pathogen colonization are not clearly defined. Clostridioides difficile colonization typically requires prior disruption of the microbiota, suggesting that outcompeting commensals for resources is key in establishing C. difficile infection (CDI). The immune protein calprotectin (CP) is released into the gut lumen during CDI to chelate zinc (Zn) and other essential nutrient metals. Yet, the impact of Zn limitation on C. difficile colonization is unknown. To define C. difficile responses to Zn limitation, we performed RNA sequencing on C. difficile exposed to CP. In media with CP, C. difficile upregulated genes involved in metal homeostasis and amino acid metabolism.
Project description:Clostridioides difficile is one of the most common nosocomial pathogens and a global public health threat. Upon colonization of the gastrointestinal tract, C. difficile is exposed to a rapidly changing polymicrobial environment and a dynamic metabolic milieu. Despite the link between the gut microbiota and susceptibility to C. difficile, the impact of synergistic interactions between the microbiota and pathogens on the outcome of infection is largely unknown. Here, we show that microbial cooperation between C. difficile and Enterococcus has a profound impact on the growth, metabolism, and pathogenesis of C. difficile.. Through a process of nutrient restriction and metabolite cross-feeding, E. faecalis shapes the metabolic environment in the gut to enhance C. difficile fitness and increase toxin production. These findings demonstrate that members of the microbiota, such as Enterococcus, have a previously unappreciated impact on C. difficile behavior and virulence.
Project description:The Clostridioides difficile toxins TcdA and TcdB are responsible for diarrhea and colitis. The aim of this project was to explore the effects of the toxins on epithelial barrier function and the molecular mechanisms for diarrhea and inflammation. RNA-seq of toxin-treated intestinal cell monolayers was performed to describe the C. difficile-mediated effects. mRNA profiles from intestinale epithelial cells were generated by deep sequencing using Illumina NovaSeq 6000. This data provide the basis for subsequent upstream regulator analysis.