Copper is one of the most abundant heavy metals present in swine manure. In this study, a laboratory-scale aerobic composting system was amended with Cu at three levels (0, 200, and 2000 mg kg-1, i.e., control, Cu200, and Cu2000 treatments, respectively) to determine its effect on the fate of copper resistance genes [copper resistance genes (CRGs): pcoA, cusA, copA, and tcrB], antibiotic resistance genes [antibiotic resistance genes (ARGs): erm(A) and erm(B)], and intl1. The results showed that the absolute abundances of pcoA, tcrB, erm(A), erm(B), and intl1 were reduced, whereas those of copA and cusA increased after swine manure composting. Redundancy analysis showed that temperature significantly affected the variations in CRGs, ARGs, and intl1. The decreases in CRGs, ARGs, and intI1 were positively correlated with the exchangeable Cu levels. The bacterial community could be grouped according to the composting time under different treatments, where the high concentration of copper had a more persistent effect on the bacterial community. Network analysis determined that the co-occurrence of CRGs, ARGs, and intI1, and the bacterial community were the main contributors to the changes in CRGs, ARG, and intl1. Thus, temperature, copper, and changes in the bacterial community composition had important effects on the variations in CRGs, ARGs, and intl1 during manure composting in the presence of added copper.

The spread of antibiotic resistance genes in river systems is an emerging environmental issue due to their potential threat to aquatic ecosystems and public health. In this study, we used droplet digital polymerase chain reaction (ddPCR) to evaluate pollution with clinically relevant antibiotic resistance genes (ARGs) at 13 monitoring sites along the main stream of the Weihe River in China. Six clinically relevant ARGs and a class I integron-integrase (intI1) gene were analyzed using ddPCR, and the bacterial community was evaluated based on the bacterial 16S rRNA V3–V4 regions using MiSeq sequencing. The results indicated Proteobacteria, Actinobacteria, Cyanobacteria, and Bacteroidetes as the dominant phyla in the water samples from the Weihe River. Higher abundances of blaTEM, strB, aadA, and intI1 genes (103 to 105 copies/mL) were detected in the surface water samples compared with the relatively low abundances of strA, mecA, and vanA genes (0–1.94 copies/mL). Eight bacterial genera were identified as possible hosts of the intI1 gene and three ARGs (strA, strB, and aadA) based on network analysis. The results suggested that the bacterial community structure and horizontal gene transfer were associated with the variations in ARGs.

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