Investigation of the Prevalence of Antibiotic Resistance Genes According to the Wastewater Treatment Scale Using Metagenomic Analysis

Abstract

Although extensive efforts have been made to investigate the dynamics of the occurrence and abundance of antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs), understanding the acquisition of antibiotic resistance based on the WWTP scale and the potential effects on WWTPs is of relatively less interest. In this study, metagenomic analysis was carried out to investigate whether the WWTP scale could be affected by the prevalence and persistence of ARGs and mobile genetic elements (MGEs). As a result, 152 ARG subtypes were identified in small-scale WWTP samples, while 234 ARG subtypes were identified in large-scale WWTP samples. Among the detectable ARGs, multidrug, MLS (macrolide-lincosamide-streptogramin), sulfonamide, and tetracycline resistance genes had the highest abundance, and large and small WWTPs had similar composition characteristics of ARGs. In MGE analysis, plasmids and integrons were 1.5-2.0-fold more abundant in large-scale WWTPs than in small-scale WWTPs. The profile of bacteria at the phylum level showed that Proteobacteria and Actinobacteria were the most dominant bacteria, representing approximately 70% across large- and small-scale WWTPs. Overall, the results of this study elucidate the different abundances and dissemination of ARGs between large- and small-scale WWTPs, which facilitates the development of next-generation engineered wastewater treatment systems.

Keywords: antibiotic resistance gene; metagenomics; mobile genetic elements; wastewater treatment plant; wastewater treatment scale.

Figure 1

Relative abundance of antibiotic resistance gene (ARG) types in the small (A, B) and large (C, D) WWTP samples. A1, B1, and C1 indicate influent samples, A2, B2, and C2 indicate activated sludge samples, and A3, B3, C3 indicate effluent samples.

Figure 2

Heatmap of the relative abundance of ARG subtypes (top 50 most abundant) in the small (A, B) and large (C, D) WWTP samples. A1, B1, and C1 indicate influent samples, A2, B2, and C2 indicate activated sludge samples, and A3, B3, C3 indicate effluent samples.

Figure 3

Nonmetric multidimensional scaling (NMDS) of ARG distribution patterns between small (A, B) and large (C, D) WWTP samples. A1, B1, and C1 indicate influent samples, A2, B2, and C2 indicate activated sludge samples, and A3, B3, C3 indicate effluent samples. Stress is a nonnegative number, representing the credibility of the cluster results. A stress value <0.3 indicates high confidence. Blue arrows indicate significant positive correlation parameters (r > 0.6, p < 0.05).

Figure 4

Relative abundance and taxonomic identification of bacteria at the phylum (A) and genus levels (B) in the small (A, B) and large (C, D) WWTP samples. A1, B1, and C1 indicate influent samples, A2, B2, and C2 indicate activated sludge samples, and A3, B3, C3 indicate effluent samples. Samples with a relative abundance <1% were classified as “others”.

Figure 5

Relative abundance of mobile genetic elements, including plasmids and integrons, in the small (A, B) and large (C, D) WWTP samples. A1, B1, and C1 indicate influent samples, A2, B2, and C2 indicate activated sludge samples, and A3, B3, C3 indicate effluent samples.