Enterococci enhance Clostridioides difficile pathogenesis

Smith, Alexander B.; Jenior, Matthew L.; Keenan, Orlaith; Hart, Jessica L.; Specker, Jonathan T.; Abbas, Arwa; Rangel, Paula C; Di, Chao; Green, Jamal; Bustin, Katelyn A.; Gaddy, Jennifer A.; Nicholson, Maribeth R; Laut, Clare; Kelly, Brendan J; Matthews, Megan L.; Evans, Daniel R.; Tyne, Daria Van; Furth, Emma E.; Papin, Jason A.; Bushman, Frederic D.; Erlichman, Jessi; Baldassano, Robert N.; Silverman, Michael A.; Dunny, Gary M.; Prentice, Boone M.; Skaar, Eric P.; Zackular, Joseph P.

doi:10.1038/s41586-022-05438-x

Cited by 99 publications

(98 citation statements)

References 59 publications

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“…A relevant study recently published in Nature has confirmed that enterococci enhance C. difficile pathogenesis as they reshape the metabolic environment in the gut, favouring C. difficile colonization, toxin production and virulence. 32 According to this new evidence, the differences in spectrum of activity against enterococci between piperacillin/tazobactam and cephalosporins might explain the different impact on CDI recurrence observed in our study. A reasonable hypothesis is that the disruption of gut microbiome induced by piperacillin/tazobactam might be less deleterious than that induced by cephalosporins or other options, as piperacillin/tazobactam might preserve against enterococci dominance in the microbiota, promoting a gut environment less prone to CDI recurrence.…”

Section: Discussionmentioning

confidence: 49%

Role of previous systemic antibiotic therapy on the probability of recurrence after an initial episode of Clostridioides difficile infection treated with vancomycin

Merchante

Herrero

Valverde-Fredet

et al. 2023

JAC-Antimicrobial Resistance

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Objectives To investigate the role of previous antibiotic therapy in the risk of recurrence after a Clostridioides difficile infection (CDI) treated with vancomycin. Methods Multicentre observational study. Patients with a CDI episode achieving clinical cure with oral vancomycin and followed up 8 weeks were included. Previous antibiotic exposure up to 90 days was collected. Multivariate analysis of predictors of recurrence adjusted by the propensity score (PS) of being previously treated with each non-CDI antibiotic was performed. Results Two hundred and forty-one patients were included; 216 (90%) had received systemic antibiotics. Fifty-three patients (22%) had a CDI recurrence. Rates of recurrence were lower in those treated with piperacillin/tazobactam in the last month when compared with those not receiving piperacillin/tazobactam [3 (7%) versus 50 (25%); P = 0.01], whereas higher rates were seen in those treated with cephalosporins in the last month [26/87 (30%) versus 27/154 (17%); P = 0.03]. In multivariate analysis controlled by the inverse probability of treatment weighting by PS, receiving ≥5 days of piperacillin/tazobactam in the last month as the last antibiotic regimen prior to CDI was independently associated with a lower risk of recurrence [adjusted OR (AOR) 0.13; 95% CI: 0.06–0.29; P < 0.0001] whereas exposure for ≥5 days to cephalosporins (versus piperacillin/tazobactam) was associated with an increased risk (AOR 10.9; 95% CI: 4.4–27.1; P < 0.0001). Conclusions Recent use of piperacillin/tazobactam might be associated with a lower risk of CDI recurrence, while recent use of cephalosporins might promote an increased risk. These findings should be considered when treating hospitalized patients.

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Section: Discussionmentioning

confidence: 49%

Role of previous systemic antibiotic therapy on the probability of recurrence after an initial episode of Clostridioides difficile infection treated with vancomycin

Merchante

Herrero

Valverde-Fredet

et al. 2023

JAC-Antimicrobial Resistance

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“…Previous studies have illustrated that Enterococcus , particularly vancomycin-resistant Enterococcus (VRE), can easily outcompete other bacteria due to their tolerance to starvation and antibiotic pressure [ 36 , 37 ]. Enterococcus is also known to reconstitute the metabolic environment in the gut through the arginine deiminase pathway, which supports the growth of several pathogens, such as Escherichia coli and Clostridioides difficile , leading to a possible secondary infection [ 38 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

Altered intestinal microbiome and metabolome correspond to the clinical outcome of sepsis

et al. 2023

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Background The gut microbiome plays a pivotal role in the progression of sepsis. However, the specific mechanism of gut microbiota and its metabolites involved in the process of sepsis remains elusive, which limits its translational application. Method In this study, we used a combination of the microbiome and untargeted metabolomics to analyze stool samples from patients with sepsis enrolled at admission, then microbiota, metabolites, and potential signaling pathways that might play important roles in disease outcome were screened out. Finally, the above results were validated by the microbiome and transcriptomics analysis in an animal model of sepsis. Results Patients with sepsis showed destruction of symbiotic flora and elevated abundance of Enterococcus, which were validated in animal experiments. Additionally, patients with a high burden of Bacteroides, especially B. vulgatus, had higher Acute Physiology and Chronic Health Evaluation II scores and longer stays in the intensive care unit. The intestinal transcriptome in CLP rats illustrated that Enterococcus and Bacteroides had divergent profiles of correlation with differentially expressed genes, indicating distinctly different roles for these bacteria in sepsis. Furthermore, patients with sepsis exhibited disturbances in gut amino acid metabolism compared with healthy controls; namely, tryptophan metabolism was tightly related to an altered microbiota and the severity of sepsis. Conclusion Alterations in microbial and metabolic features in the gut corresponded with the progression of sepsis. Our findings may help to predict the clinical outcome of patients in the early stage of sepsis and provide a translational basis for exploring new therapies.

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“…For example, GIMME and its extensions have been used for the reconstruction of context-specific Escherichia coli and human cell models [ 38 ], for the extraction of cancer-specific GEMs [ 61 ], in the analysis of metabolic immunomodulators of macrophage activation [ 44 ], and in the analysis of Salmonella Typhimurium metabolism in different media [ 45 ]. Applications of RIPTiDE include the prediction of metabolic patterns of Escherichia coli [ 46 ] and the reconstruction of Clostridioides difficile cells in infection and in in vitro settings [ 62 ].…”

Section: Algorithms and Tools For Reconstruction Of Context-specific ...mentioning

confidence: 99%

Context-Specific Genome-Scale Metabolic Modelling and Its Application to the Analysis of COVID-19 Metabolic Signatures

Moškon

Režen

2023

Metabolites

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Genome-scale metabolic models (GEMs) have found numerous applications in different domains, ranging from biotechnology to systems medicine. Herein, we overview the most popular algorithms for the automated reconstruction of context-specific GEMs using high-throughput experimental data. Moreover, we describe different datasets applied in the process, and protocols that can be used to further automate the model reconstruction and validation. Finally, we describe recent COVID-19 applications of context-specific GEMs, focusing on the analysis of metabolic implications, identification of biomarkers and potential drug targets.

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Enterococci enhance Clostridioides difficile pathogenesis

Cited by 99 publications

References 59 publications

Role of previous systemic antibiotic therapy on the probability of recurrence after an initial episode of Clostridioides difficile infection treated with vancomycin

Role of previous systemic antibiotic therapy on the probability of recurrence after an initial episode of Clostridioides difficile infection treated with vancomycin

Altered intestinal microbiome and metabolome correspond to the clinical outcome of sepsis

Context-Specific Genome-Scale Metabolic Modelling and Its Application to the Analysis of COVID-19 Metabolic Signatures

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