Lytic bacteriophages facilitate antibiotic sensitization of Enterococcus faecium.

Enterococcus faecium, a commensal of the human intestine, has emerged as a hospital-adapted, multi-drug resistant (MDR) pathogen. Bacteriophages (phages), natural predators of bacteria, have regained attention as therapeutics to stem the rise of MDR bacteria. Despite their potential to curtail MDR E. faecium infections, the molecular events governing E. faecium-phage interactions remain largely unknown. Such interactions are important to delineate because phage selective pressure imposed on E. faecium will undoubtedly result in phage resistance phenotypes that could threaten the efficacy of phage therapy. In an effort to understand the emergence of phage resistance in E. faecium, three newly isolated lytic phages were used to demonstrate that E. faecium phage resistance is conferred through an array of cell wall-associated molecules, including secreted antigen A (SagA), enterococcal polysaccharide antigen (Epa), wall teichoic acids, capsule, and an arginine-aspartate-aspartate (RDD) protein of unknown function. We find that capsule and Epa are important for robust phage adsorption and that phage resistance mutations in sagA, epaR, and epaX enhance E. faecium susceptibility to ceftriaxone, an antibiotic normally ineffective due to its low affinity for enterococcal penicillin binding proteins. Consistent with these findings, we provide evidence that phages potently synergize with cell wall (ceftriaxone and ampicillin) and membrane-acting (daptomycin) antimicrobials to slow or completely inhibit the growth of E. faecium Our work demonstrates that the evolution of phage resistance comes with fitness defects resulting in drug sensitization and that lytic phages could serve as effective antimicrobials for the treatment of E. faecium infections.

Changes in the Association Between Diagnostic Testing Method, Polymerase Chain Reaction Ribotype, and Clinical Outcomes From Clostridioides difficile Infection: One Institution's Experience.

BACKGROUND: In Clostridioides difficile infection (CDI), the relationship between clinical, microbial, and temporal/epidemiological trends, disease severity and adverse outcomes is incompletely understood. In a follow-up to our study from 2010-2013, we evaluate stool toxin levels and C. difficile polymerase chain reaction (PCR) ribotypes. We hypothesized that elevated stool toxins and infection with ribotype 027 associate with adverse outcomes. METHODS: In 565 subjects at the University of Michigan with CDI diagnosed by positive testing for toxins A/B by enzyme immunoassay (EIA) or PCR for the tcdB gene, we quantified stool toxin levels via a modified cell cytotoxicity assay (CCA), isolated C. difficile by anaerobic culture, and performed PCR ribotyping. Severe CDI was defined by Infectious Diseases Society of America (IDSA) criteria, and primary outcomes were all-cause 30-day mortality and a composite of colectomy, intensive care unit admission, and/or death attributable to CDI within 30 days. Analyses included bivariable tests and logistic regression. RESULTS: 199 samples were diagnosed by EIA; 447 were diagnosed by PCR. Toxin positivity associated with IDSA severity but not primary outcomes. In 2016, compared with 2010-2013, ribotype 106 newly emerged, accounting for 10.6% of strains, ribotype 027 fell from 16.5% to 9.3%, and ribotype 014-027 remained stable at 18.9%. Ribotype 014-020 associated with IDSA severity and 30-day mortality (P = .001). CONCLUSIONS: Toxin positivity by EIA and CCA associated with IDSA severity but not with subsequent adverse outcomes. The molecular epidemiology of C. difficile has shifted, which may have implications for the optimal diagnostic strategy for and clinical severity of CDI.

Anti-toxin antibody is not associated with recurrent Clostridium difficile infection.

Clostridium difficile infection (CDI) recurs in ∼20% of patients. Prior studies indicated that antibody responses directed against the C. difficile toxins A and B were potentially associated with lower risk of recurrent CDI. Here we tested the hypothesis that circulating anti-toxin IgG antibody levels associate with reduced risk of recurrent CDI. A cohort study with prospective enrollment and retrospective data abstraction examined antibody levels in 275 adult patients at the University of Michigan with CDI. We developed an enzyme linked immunosorbent assay to detect IgG antibodies against toxin A and toxin B in sera obtained at the time of diagnosis. Logistic regression examined the relationship between antibody levels and recurrence, and sensitivity tests evaluated for follow-up and survivor biases, history of CDI, and PCR ribotype. Follow-up data were available for 174 subjects, of whom 36 (20.7%) had recurrence. Comparing antibody levels vs. recurrence and CDI history, anti-toxin A levels were similar, while anti-toxin B levels had a greater range of values. In unadjusted analysis, detection of anti-toxin A antibodies, but not anti-toxin B antibodies, associated with an increased risk of recurrence (OR 2.71 [1.06, 8.37], P = .053). Adjusting for confounders weakened this association. The results were the same in sensitivity analyses. We observed a borderline increased risk of recurrence in patients positive for anti-toxin A antibodies, and sensitivity analyses showed this was not simply a reflection of prior exposure status. Future studies are needed to assess how neutralizing antibody or levels after treatment associate with recurrence.

Clostridioides difficile infection surveillance in intensive care units and oncology wards using machine learning.

OBJECTIVE: Screening individuals admitted to the hospital for Clostridioides difficile presents opportunities to limit transmission and hospital-onset C. difficile infection (HO-CDI). However, detection from rectal swabs is resource intensive. In contrast, machine learning (ML) models may accurately assess patient risk without significant resource usage. In this study, we compared the effectiveness of swab surveillance to daily risk estimates produced by an ML model to identify patients who will likely develop HO-CDI in the intensive care unit (ICU) setting. DESIGN: A prospective cohort study was conducted with patient carriage of toxigenic C. difficile identified by rectal swabs analyzed by anaerobic culture and polymerase chain reaction (PCR). A previously validated ML model using electronic health record data generated daily risk of HO-CDI for every patient. Swab results and risk predictions were compared to the eventual HO-CDI status. PATIENTS: Adult inpatient admissions taking place in University of Michigan Hospitals' medical and surgical intensive care units and oncology wards between June 6th and October 8th, 2020. RESULTS: In total, 2,979 admissions, representing 2,044 patients, were observed over the course of the study period, with 39 admissions developing HO-CDIs. Swab surveillance identified 9 true-positive and 87 false-positive HO-CDIs. The ML model identified 9 true-positive and 226 false-positive HO-CDIs; 8 of the true-positives identified by the model differed from those identified by the swab surveillance. CONCLUSION: With limited resources, an ML model identified the same number of HO-CDI admissions as swab-based surveillance, though it generated more false-positives. The patients identified by the ML model were not yet colonized with C. difficile. Additionally, the ML model identifies at-risk admissions before disease onset, providing opportunities for prevention.

Longitudinal genomic surveillance of carriage and transmission of Clostridioides difficile in an intensive care unit.

Despite enhanced infection prevention efforts, Clostridioides difficile remains the leading cause of healthcare-associated infections in the United States. Current prevention strategies are limited by their failure to account for patients who carry C. difficile asymptomatically, who may act as hidden reservoirs transmitting infections to other patients. To improve the understanding of asymptomatic carriers' contribution to C. difficile spread, we conducted admission and daily longitudinal culture-based screening for C. difficile in a US-based intensive care unit over nine months and performed whole-genome sequencing on all recovered isolates. Despite a high burden of carriage, with 9.3% of admissions having toxigenic C. difficile detected in at least one sample, only 1% of patients culturing negative on admission to the unit acquired C. difficile via cross-transmission. While patients who carried toxigenic C. difficile on admission posed minimal risk to others, they themselves had a 24-times greater risk for developing a healthcare-onset C. difficile infection than noncarriers. Together, these findings suggest that current infection prevention practices can be effective in preventing nosocomial cross-transmission of C. difficile, and that decreasing C. difficile infections in hospitals further will require interventions targeting the transition from asymptomatic carriage to infection.

Proton Pump Inhibitor-Induced Gut Dysbiosis Increases Mortality Rates for Patients with Clostridioides difficile Infection.

Clostridioides difficile infection (CDI) is associated with high mortality rates among patients with chronic illnesses. We aimed to identify avoidable risk factors to reduce the mortality rate in CDI patients. A total of 306 patients with diarrhea and clinical suspicion of CDI were enrolled, and fecal samples were gathered from 145 patients. CDI was diagnosed by fecal positivity for the C. difficile tcdB gene. Risk factors associated with death within 180 days were identified using Cox regression analysis. The fecal microbiota was determined through bacterial 16S rRNA gene sequencing. Of the patients with diarrhea, 240 (mean age, 69.1 years) were positive for CDI, and 91 died within 180 days. Multivariate analysis revealed that male sex, high Charlson Comorbidity Index and McCabe scores, high serum C-reactive protein levels, low hematocrit levels, low absolute eosinophil counts, high neutrophil/lymphocyte ratios, and daily use of proton pump inhibitors (PPIs) were independent risk factors for overall mortality. Cumulative analyses confirmed the association of duration-dependent PPI use with a high mortality rate. Fecal microbiota analyses showed associations of decreased relative abundance of Ruminococcus gnavus (P = 0.001) and Prevotella copri (P = 0.025) and increased relative abundance of Parabacteroides merdae (P = 0.001) and Clostridioides difficile (P = 0.040) with higher mortality rates in patients with CDI. Moreover, these microbiota changes were correlated with the duration of PPI use. IMPORTANCE This article demonstrates that daily PPI use was the only avoidable risk factor for death. With more extended PPI use, the mortality rate was higher in patients with CDI. Decreases in Prevotella copri and Ruminococcus gnavus and increases in Parabacteroides merdae and Clostridioides difficile in line with daily PPI use duration were significantly associated with the death of CDI patients. Our findings provide in-depth insights into the cautious use of PPIs in chronically ill patients with CDI.

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

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.IMPORTANCE 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.