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Infective/bacterial endocarditis is a rare but life-threatening disease with a hospital mortality rate of 22.7% and a 1-year mortality rate of 40%. Therefore, continued research efforts to develop efficient anti-infective implant materials are of the utmost importance. Equally important is the development of test systems that allow the performance of new materials to be comprehensively evaluated. In this study, a novel antibacterial coating based on dalbavancin was tested in comparison to rifampicin/minocycline, and the suitability of a recently developed mouse tail vein model for testing the implant coatings was validated. Small polymeric stent grafts coated with a poly-L-lactic acid (PLLA) layer and incorporated antibiotics were colonized with Staphylococcus (S.) aureus before implantation into the tail vein of mice. The main assessment criteria were the hematogenous spread of the bacteria and the local tissue reaction to the contaminated implant. For this purpose, colony-forming units (CFU) in the blood, spleen and kidneys were determined. Tail cross sections were prepared for histological analysis, and plasma cytokine levels and expression values of inflammation-associated genes were examined. Both antibiotic coatings performed excellently, preventing the onset of infection. The present study expands the range of available methods for testing the anti-infectivity of cardiovascular implants, and the spectrum of agents for effective surface coating.
The anaerobic, gastrointestinal pathogen Clostridioides difficile can cause severe forms of enterocolitis which is mainly mediated by the toxins it produces. The RNA polymerase inhibitor Fidaxomicin is the current gold standard for the therapy of C. difficile infections due to several beneficial features including its ability to suppress toxin synthesis in C. difficile. In contrast to the Rifamycins, Fidaxomicin binds to the RNA polymerase switch region, which is also the binding site for Myxopyronin B. Here, serial broth dilution assays were performed to test the susceptibility of C. difficile and other anaerobes to Myxopyronin B, proving that the natural product is considerably active against C. difficile and that there is no cross-resistance between Fidaxomicin and Myxopyronin B in a Fidaxomicin-resistant C. difficile strain. Moreover, mass spectrometry analysis indicated that Myxopyronin B is able to suppress early phase toxin synthesis in C. difficile to the same degree as Fidaxomicin. Conclusively, Myxopyronin B is proposed as a new lead structure for the design of novel antibiotics for the therapy of C. difficile infections.
Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.