RESUMO
BACKGROUND: Wastewater-based monitoring represents a useful tool for antibiotic resistance surveillance. AIM: To investigate the prevalence and abundance of antibiotic resistance genes (ARGs) in hospital wastewater over time. METHODS: Wastewater from two hospitals in Finland (HUS1 and HUS2) was monitored weekly for nine weeks (weeks 25-33) in summer 2020. A high-throughput real-time polymerization chain reaction (HT-qPCR) system was used to detect and quantify 216 ARGs and genes associated with mobile genetic elements (MGEs), integrons, and bacteria causing hospital-acquired infections (HAIs), as well as the 16S rRNA gene. Data from HT-qPCR were analysed and visualized using a novel digital platform, ResistApp. Eight carbapenem resistance genes (blaGES, blaKPC, blaVIM, blaNDM, blaCMY, blaMOX, blaOXA48, and blaOXA51) and three genes associated with bacteria causing HAIs (Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa) were studied. FINDINGS: There was a significantly higher number of ARGs at both hospitals in weeks 27-30 (174-191 genes) compared to other sampling weeks (151-171 genes). Our analyses also indicated that the two hospitals, which used different amounts of antibiotics, had significantly different resistance gene profiles. Carbapenem resistance genes were more prevalent and abundant in HUS1 than HUS2. Across both hospitals, blaGES and blaVIM were the most prevalent and abundant. There was also a strong positive association between blaKPC and K. pneumoniae in HUS1 wastewater. CONCLUSION: Routine wastewater-based monitoring using ResistApp can provide valuable information on the prevalence and abundance of ARGs in hospitals. This helps hospitals understand the spread of antibiotic resistance in hospitals and identify potential areas for intervention.
