The proliferation of antibiotic resistance genes (ARGs) and microbial communities in industrial wastewater treatment plant treating N,N-dimethylformamide (DMF) by AAO process

Abstract

The excessive use of antibiotics has resulted in the contamination of the environment with antibiotic resistance genes (ARGs), posing a significant threat to public health. Wastewater treatment plants (WWTPs) are known to be reservoirs of ARGs and considered to be hotspots for horizontal gene transfer (HGT) between bacterial communities. However, most studies focused on the distribution and dissemination of ARGs in hospital and urban WWTPs, and little is known about their fate in industrial WWTPs. In this study, collected the 15 wastewater samples containing N,N-dimethylformamide (DMF) from five stages of the anaerobic anoxic aerobic (AAO) process in an industrial WWTPs. The findings revealed a stepwise decrease in DMF and chemical oxygen demand (COD) content with the progression of treatment. However, the number and abundances of ARGs increase in the effluents of biological treatments. Furthermore, the residues of DMF and the treatment process altered the structure of the bacterial community. The correlation analysis indicated that the shift in bacterial community structures might be the main driver for the dynamics change of ARGs. Interestingly, observed that the AAO process may acted as a microbial source and increased the total abundance of ARGs instead of attenuating it. Additionally, found that non-pathogenic bacteria had higher ARGs abundance than pathogenic bacteria in effluents. The study provides insights into the microbial community structure and the mechanisms that drive the variation in ARGs abundance in industrial WWTPs.

Fig 1. The change among the different treatment in WWTPs.

(A) Dynamic changes of the content of DMF and (B) COD; (C) Correlation analysis of DMF and COD; (D) The abundance of 16S rRNA; Influent wastewater, IN; Anaerobic process wastewater, AP; Anoxic process wastewater, ANP; Aerobic process wastewater, AEP; Effluent wastewater, EF.

Fig 2. The abundance of ARGs in WWTPs.

(A) PCA analysis between different samples in WWTPs. (B) the relative abundance of ARGs in WWTPs; (C) the absolute abundance of ARGs in WWTPs; (D) Chord diagram analysis between the sample and ARG subtype; (E) the mechanisms of ARGs variation in WWTPs.

Fig 3. The ARGs changed along the WWTPs process.

(A) venn diagrams analysis between the samples. (B) 53 share genes changed between samples; (C) 18 new generated ARGs changed between samples.

Fig 4. Changes of bacterial community.

(A) PCA analysis between samples base on the OTUs; (B) the structure of bacterial between samples; (C) the variation of bacterial at phylum level between samples. (D) the variation of pathogen at species level between samples.

Fig 5. The correlation between ARG and their host bacteria.

(A) the analysis base on Spearman’s correlation between ARGs and their host; network analysis revealing the correlations among the fates of ARGs, MGEs, DMF and bacterial in influent (B) and effluent (C).