Systemic Inflammatory Responses in Ulcerative Colitis Patients and Clostridium difficile Infection

Colon-targeted oral nanoliposomes loaded with psoralen alleviate DSS-induced ulcerative colitis

Oral administration, while convenient, but complex often faces challenges due to the complexity of the digestive environment. In this study, we developed a nanoliposome (NLP) encapsulating psoralen (P) and coated it with chitosan (CH) and pectin (PT) to formulate PT/CH-P-NLPs. PT/CH-P-NLPs exhibit good biocompatibility, superior to liposomes loaded with psoralen and free psoralen alone. After oral administration, PT/CH-P-NLPs remain stable in the stomach and small intestine, followed by a burst release of psoralen after reaching the slightly alkaline and gut microbiota-rich colon segment. In the DSS-induced ulcerative colitis of mice, PT/CH-P-NLPs showed significant effects on reducing inflammation, mitigating oxidative stress, protecting the integrity of the colon mucosal barrier, and modulating the gut microbiota. In conclusion, the designed nanoliposomes demonstrated the effective application of psoralen in treating ulcerative colitis.

Genetic Deletion of LRP5 and LRP6 in Macrophages Exacerbates Colitis-Associated Systemic Inflammation and Kidney Injury in Response to Intestinal Commensal Microbiota

Extraintestinal manifestations are common in inflammatory bowel disease and involve several organs, including the kidney. However, the mechanisms responsible for renal manifestation in inflammatory bowel disease are not known. In this study, we show that the Wnt-lipoprotein receptor-related proteins 5 and 6 (LRP5/6) signaling pathway in macrophages plays a critical role in regulating colitis-associated systemic inflammation and renal injury in a murine dextran sodium sulfate-induced colitis model. Conditional deletion of the Wnt coreceptors LRP5/6 in macrophages in mice results in enhanced susceptibility to dextran sodium sulfate colitis-induced systemic inflammation and acute kidney injury (AKI). Furthermore, our studies show that aggravated colitis-associated systemic inflammation and AKI observed in LRP5/6^LysM mice are due to increased bacterial translocation to extraintestinal sites and microbiota-dependent increased proinflammatory cytokine levels in the kidney. Conversely, depletion of the gut microbiota mitigated colitis-associated systemic inflammation and AKI in LRP5/6^LysM mice. Mechanistically, LRP5/6-deficient macrophages were hyperresponsive to TLR ligands and produced higher levels of proinflammatory cytokines, which are associated with increased activation of MAPKs. These results reveal how the Wnt-LRP5/6 signaling in macrophages controls colitis-induced systemic inflammation and AKI.

Probiotics Exhibit Strain-Specific Protective Effects in T84 Cells Challenged With Clostridioides difficile-Infected Fecal Water

Clostridioides difficile infection (CDI) is frequently associated with intestinal injury and mucosal barrier dysfunction, leading to an inflammatory response involving neutrophil localization and upregulation of pro-inflammatory cytokines. The severity of clinical manifestations is associated with the extent of the immune response, which requires mitigation for better clinical management. Probiotics could play a protective role in this disorder due to their immunomodulatory ability in gastrointestinal disorders. We assessed five single-strain and three multi-strain probiotics for their ability to modulate CDI fecal water (FW)-induced effects on T84 cells. The CDI-FW significantly (p < 0.05) decreased T84 cell viability. The CDI-FW-exposed cells also exhibited increased pro-inflammatory cytokine production as characterized by interleukin (IL)-8, C-X-C motif chemokine 5, macrophage inhibitory factor (MIF), IL-32, and tumor necrosis factor (TNF) ligand superfamily member 8. Probiotics were associated with strain-specific attenuation of the CDI-FW mediated effects, whereby Saccharomyces boulardii CNCM I-1079 and Lacticaseibacillus rhamnosus R0011 were most effective in reducing pro-inflammatory cytokine production and in increasing T84 cell viability. ProtecFlor™, Lactobacillus helveticus R0052, and Bifidobacterium longum R0175 showed moderate effectiveness, and L. rhamnosus GG R0343 along with the two other multi-strain combinations were the least effective. Overall, the findings showed that probiotic strains possess the capability to modulate the CDI-mediated inflammatory response in the gut lumen.

Decreased secondary faecal bile acids in children with ulcerative colitis and Clostridioides difficile infection

BACKGROUND

Patients with ulcerative colitis (UC) have an increased risk of Clostridioides difficile infection (CDI). There is a well-documented relationship between bile acids and CDI.

AIMS

To evaluate faecal bile acid profiles and gut microbial changes associated with CDI in children with UC.

METHODS

This study was conducted at Children's Hospital Los Angeles. Faecal bile acids and gut microbial genes related to bile acid metabolism were measured in 29 healthy children, 23 children with mild to moderate UC without prior CDI (UC group), 16 children with mild to moderate UC with prior CDI (UC+CDI group) and 10 children without UC with prior CDI (CDI group).

RESULTS

Secondary faecal bile acids, especially lithocholic acid (3.296 vs 10.793, P ≤ 0.001) and ursodeoxycholic acid (7.414 vs 10.617, P ≤ 0.0001), were significantly lower in children with UC+CDI when compared to UC alone. Secondary faecal bile acids can predict disease status between these groups with 84.6% accuracy. Additionally, gut microbial genes coding for bile salt hydrolase, 7α-hydroxysteroid dehydrogenase and 7α/β-dehydroxylation were all diminished in children with UC+CDI compared to children with UC alone.

CONCLUSIONS

Bile acids can distinguish between children with UC based on their prior CDI status. Bile acid profile changes can be explained by gut microbial genes encoding for bile salt hydrolase, 7α-hydroxysteroid dehydrogenase and 7α/β-dehydroxylation. Bile acid profiles may be helpful as biomarkers to identify UC children who have had CDI and may serve as future therapeutic targets.

The adaptive immune response to Clostridioides difficile: A tricky balance between immunoprotection and immunopathogenesis

Clostridioides difficile (C. difficile) is the major cause of hospital-acquired gastrointestinal infections in individuals following antibiotics treatment. The pathogenesis of C. difficile infection (CDI) is mediated mainly by the production of toxins that induce tissue damage and host inflammatory responses. While innate immunity is well characterized in human and animal models of CDI, adaptive immune responses remain poorly understood. In this review, the current understanding of adaptive immunity is summarized and its influence on pathogenesis and disease outcome is discussed. The perspectives on what we believe to be the main pending questions and the focus of future research are also provided. There is no doubt that the innate immune response provides a first line of defense to CDI. But, is the adaptive immune response a friend or a foe? Probably it depends on the course of the disease. Adaptive immunity is essential for pathogen eradication, but may also trigger uncontrolled or pathological inflammation. Most of the understanding of the role of T cells is based on findings from experimental models. While they are a very valuable tool for research studies, more studies in human are needed to translate these findings into human disease. Another main challenge is to unravel the role of the different T cell populations on protection or induction of immunopathogenesis.

Immune Profiling To Predict Outcome of Clostridioides difficile Infection

Clostridioides difficile infection is the most common health care-associated infection in the United States with more than 20% patients experiencing symptomatic recurrence. The complex nature of host-bacterium interactions makes it difficult to predict the course of the disease based solely on clinical parameters. In the present study, we built a robust prediction model using representative plasma biomarkers and clinical parameters for 90-day all-cause mortality. Risk prediction based on immune biomarkers and clinical variables may contribute to treatment selection for patients as well as provide insight into the role of immune system in C. difficile pathogenesis.

There is a pressing need for biomarker-based models to predict mortality from and recurrence of Clostridioides difficile infection (CDI). Risk stratification would enable targeted interventions such as fecal microbiota transplant, antitoxin antibodies, and colectomy for those at highest risk. Because severity of CDI is associated with the immune response, we immune profiled patients at the time of diagnosis. The levels of 17 cytokines in plasma were measured in 341 CDI inpatients. The primary outcome of interest was 90-day mortality. Increased tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), C-C motif chemokine ligand 5 (CCL-5), suppression of tumorigenicity 2 receptor (sST-2), IL-8, and IL-15 predicted mortality by univariate analysis. After adjusting for demographics and clinical characteristics, the mortality risk (as indicated by the hazard ratio [HR]) was higher for patients in the top 25th percentile for TNF-α (HR = 8.35, P = 0.005) and IL-8 (HR = 4.45, P = 0.01) and lower for CCL-5 (HR = 0.18, P ≤ 0.008). A logistic regression risk prediction model was developed and had an area under the receiver operating characteristic curve (AUC) of 0.91 for 90-day mortality and 0.77 for 90-day recurrence. While limited by being single site and retrospective, our work resulted in a model with a substantially greater predictive ability than white blood cell count. In conclusion, immune profiling demonstrated differences between patients in their response to CDI, offering the promise for precision medicine individualized treatment.

Systemic Inflammatory Mediators Are Effective Biomarkers for Predicting Adverse Outcomes in Clostridioides difficile Infection

Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI.

Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile. Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment.