An epidemiological and molecular study regarding the spread of vancomycin-resistant Enterococcus faecium in a teaching hospital in Bogotá, Colombia 2016.

BACKGROUND: Enterococcus faecium is ranked worldwide as one of the top ten pathogens identified in healthcare-associated infections (HAI) and is classified as one of the high priority pathogens for research and development of new antibiotics worldwide. Due to molecular biology techniques' higher costs, the approach for identifying and controlling infectious diseases in developing countries has been based on clinical and epidemiological perspectives. Nevertheless, after an abrupt vancomycin-resistant Enterococcus faecium dissemination in the Méderi teaching hospital, ending up in an outbreak, further measures needed to be taken into consideration. The present study describes the vancomycin-resistant Enterococcus faecium pattern within Colombian's largest installed-bed capacity hospital in 2016. METHODS: Thirty-three vancomycin-resistant Enterococcus faecium isolates were recovered during a 5-month period in 2016. Multilocus variable-number tandem-repeat analysis was used for molecular typing to determine clonality amongst strains. A modified time-place-sequence algorithm was used to trace VREfm spread patterns during the outbreak period and estimate transmission routes. RESULTS: Four clonal profiles were identified. Chronological clonal profile follow-up suggested a transitional spread from profile "A" to profile "B", returning to a higher prevalence of "A" by the end of the study. Antibiotic susceptibility indicated high-level vancomycin-resistance in most isolates frequently matching vanA gene identification. DISCUSSION: Transmission analysis suggested cross-contamination via healthcare workers. Despite epidemiological control of the outbreak, post-outbreak isolates were still being identified as having outbreak-related clonal profile (A), indicating reduction but not eradication of this clonality. This study supports the use of combined molecular and epidemiological strategies in an approach to controlling infectious diseases. It contributes towards a more accurate evaluation of the effectiveness of the epidemiological measures taken regarding outbreak control and estimates the main cause related to the spread of this microorganism.

Detection of hidden antibiotic resistance through real-time genomics.

Real-time genomics through nanopore sequencing holds the promise of fast antibiotic resistance prediction directly in the clinical setting. However, concerns about the accuracy of genomics-based resistance predictions persist, particularly when compared to traditional, clinically established diagnostic methods. Here, we leverage the case of a multi-drug resistant Klebsiella pneumoniae infection to demonstrate how real-time genomics can enhance the accuracy of antibiotic resistance profiling in complex infection scenarios. Our results show that unlike established diagnostics, nanopore sequencing data analysis can accurately detect low-abundance plasmid-mediated resistance, which often remains undetected by conventional methods. This capability has direct implications for clinical practice, where such "hidden" resistance profiles can critically influence treatment decisions. Consequently, the rapid, in situ application of real-time genomics holds significant promise for improving clinical decision-making and patient outcomes.