Adaptive response of Pseudomonas aeruginosa under serial ciprofloxacin exposure.

Understanding the evolution of antibiotic resistance is important for combating drug-resistant bacteria. In this work, we investigated the adaptive response of Pseudomonas aeruginosa to ciprofloxacin. Ciprofloxacin-susceptible P. aeruginosa ATCC 9027, CIP-E1 (P. aeruginosa ATCC 9027 exposed to ciprofloxacin for 14 days) and CIP-E2 (CIP-E1 cultured in antibiotic-free broth for 10 days) were compared. Phenotypic responses including cell morphology, antibiotic susceptibility, and production of pyoverdine, pyocyanin and rhamnolipid were assessed. Proteomic responses were evaluated using comparative iTRAQ labelling LC-MS/MS to identify differentially expressed proteins (DEPs). Expression of associated genes coding for notable DEPs and their related regulatory genes were checked using quantitative reverse transcriptase PCR. CIP-E1 displayed a heterogeneous morphology, featuring both filamentous cells and cells with reduced length and width. By contrast, although filaments were not present, CIP-E2 still exhibited size reduction. Considering the MIC values, ciprofloxacin-exposed strains developed resistance to fluoroquinolone antibiotics but maintained susceptibility to other antibiotic classes, except for carbapenems. Pyoverdine and pyocyanin production showed insignificant decreases, whereas there was a significant decrease in rhamnolipid production. A total of 1039 proteins were identified, of which approximately 25 % were DEPs. In general, there were more downregulated proteins than upregulated proteins. Noted changes included decreased OprD and PilP, and increased MexEF-OprN, MvaT and Vfr, as well as proteins of ribosome machinery and metabolism clusters. Gene expression analysis confirmed the proteomic data and indicated the downregulation of rpoB and rpoS. In summary, the response to CIP involved approximately a quarter of the proteome, primarily associated with ribosome machinery and metabolic processes. Potential targets for bacterial interference encompassed outer membrane proteins and global regulators, such as MvaT.

The First Report of Candida Auris Infection in Vietnam.

Infection caused by Candida auris ha C. auris s rapidly become a global health threat. C. auris created a significant healthcare burden due to various complicating factors, including misidentification by commercial identification methods, potent antifungal resistance, high mortality rates and the possibility of nosocomial outbreaks through direct contact. In Vietnam, there are currently no clinical reports on C. auris infections. Here, we present four clinical cases of C. auris infections in the Department of Pulmonary Medicine of Cho Ray Hospital in southern Vietnam. Through this report, we aim to highlight the attention to the emergence of C. auris in Vietnam. Further research on C. auris infections is warranted, focusing on newly observed clinical characteristics present in all cases in this report, including hypoalbuminaemia and corticosteroid usage. Moreover, one case of resistance to amphotericin B has been identified, possibly due to prior exposure to this antifungal agent. LEARNING POINTS: Further research on Candida auris infections is warranted, focusing on newly observed clinical features present in all cases in this report, including hypoalbuminaemia and corticosteroid use during hospitalisation.While Candida auris remains susceptible to commonly used antifungal drugs, one case of resistance to amphotericin B has been documented, possibly due to prior exposure to this antifungal agent.

A Web-Based Dynamic Nomogram to Predict the Risk of Methicillin-Resistant Staphylococcal Infection in Patients with Pneumonia.

The aim of this study was to create a dynamic web-based tool to predict the risks of methicillin-resistant Staphylococcus spp. (MRS) infection in patients with pneumonia. We conducted an observational study of patients with pneumonia at Cho Ray Hospital from March 2021 to March 2023. The Bayesian model averaging method and stepwise selection were applied to identify different sets of independent predictors. The final model was internally validated using the bootstrap method. We used receiver operator characteristic (ROC) curve, calibration, and decision curve analyses to assess the nomogram model's predictive performance. Based on the American Thoracic Society, British Thoracic Society recommendations, and our data, we developed a model with significant risk factors, including tracheostomies or endotracheal tubes, skin infections, pleural effusions, and pneumatoceles, and used 0.3 as the optimal cut-off point. ROC curve analysis indicated an area under the curve of 0.7 (0.63-0.77) in the dataset and 0.71 (0.64-0.78) in 1000 bootstrap samples, with sensitivities of 92.39% and 91.11%, respectively. Calibration analysis demonstrated good agreement between the observed and predicted probability curves. When the threshold is above 0.3, we recommend empiric antibiotic therapy for MRS. The web-based dynamic interface also makes our model easier to use.

Age-Dependent Decrease of DNA Hydroxymethylation in Human T Cells.

Hydroxymethylcytosine (hmC) is a natural nucleobase, which is converted from methylcytosine (mC) by tet methylcytosine dioxygenase (TET) family (TET1-3) enzymes. Decrease of genomic hmC is postulated to confer a risk for myeloid-lineage as well as T-cell neoplasms, based on the fact that loss-of-function mutations in the TET2 gene were frequently identified in these diseases. The relationship between hmC and aging remains to be elucidated. Here, we demonstrated that hmC content decreased with age in the peripheral blood T cells of 53 human volunteers. We further identified that the mRNA expression levels of TET1 and TET3 decreased with age, while those of TET2 were not influenced by age. The genomic hmC content was correlated with the mRNA expression level of TET3, but not those of TET1 and TET2. Our study suggests the presence of new epigenetic regulatory mechanisms in aging T cells.