Metagenomic analysis of urban wastewater resistome and mobilome: A support for antimicrobial resistance surveillance in an endemic country
2021
Rodríguez, Erika A. | Ramirez, Diego | Balcázar, José L. | Jiménez, J Natalia
In developing countries, where high levels of antimicrobial resistance are observed in hospitals, the surveillance of this phenomenon in wastewater treatment plants (WWTPs) and the environment is very limited, especially using cutting-edge culture-independent methods. In this study, the composition of bacterial communities, the resistome and mobilome (the pool of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs), respectively) at a WWTP were determined using shotgun metagenomics and culture-based approaches. Wastewater samples were collected at four sampling points of a WWTP in Antioquia, Colombia. A total of 24 metagenomes were analyzed. Specifically, there were marked differences in bacterial community composition, resistome, and mobilome, according to the WWTP sampling points. Bacterial families of clinical importance such as Moraxellaceae, Aeromonadaceae, and Enterobacteriaceae were mainly detected in the WWTP influent and effluent samples. Genes encoding resistance to macrolide-lincosamide-streptogramin, β-lactams, and those conferring multidrug resistance (e.g., acrB, adeG, and mexD) were the most abundant. Moreover, some clinically important ARGs such as blaKPC₋₂ and blaCTX₋M, and others not reported locally, such as blaTEM₋₁₉₆, blaGES₋₂₃, blaOXA₋₁₀, mcr-3, and mcr-5 were frequently detected. Co-occurrence network analyses indicated a significant association of ARGs such as blaOXA₋₅₈ and blaKPC genes with Aeromonadaceae and Enterobacteriaceae. Among the markers of MGEs, intI1 and ISCR8 were the most frequently detected. Altogether, this work reveals the importance of shotgun metagenomics and culture-based approaches in antimicrobial resistance studies. The findings also support that WWTPs are hotspots for antimicrobial resistance, whose analysis constitutes a powerful tool to predict the impact of antimicrobial resistance in a population.
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