Abstract

Antibiotic resistance is reportedly disseminated from wastewater treatment plants (WWTPs) into aquatic environments. In this study, it was hypothesized that discharge of effluent from WWTPs may influence resistome of the adjacent aquatic environment. Thus, we aimed at investigation of resistome in WWTPs and receiving waters, to observe the dynamics of resistome and to determine the indicators for consistent comparison of contamination level. In this study, twenty-seven samples of upstreams (n = 9), downstreams (n = 9), and effluents (n = 9) samples from nine WWTPs located in the Nakdong and Yeongsan Rivers, South Korea, were collected for four years, and a total of 343 antibiotic resistance genes (ARGs) were quantitatively amplified using SmartChip analysis. The five core ARGs (aadA, aadA2, aadA5, strB, and sul1) were commonly detected in all samples. Three (aadA, aadA2, aadA5) of the five core ARGs were significantly more abundant in the effluent than in the aquatic environment. Interestingly, the water sources of the aquatic environments and effluents could be differentiated based on the abundance of the five core ARGs. The decision-making tree model supported the classification of the two water sources: aquatic environments and effluents. Taken together, considering the ubiquitous presence of the five ARGs with significantly different abundance between water sources, core ARGs including aadA2 are recommended as indicator genes to monitor ARGs contamination by employing quantitative analysis in South Korea. Determination of indicators would help consistently evaluate contamination level by ARGs.

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