Tertiary Wastewater Treatment Processes Can Be a Double-Edged Sword for Water Quality Improvement in View of Mitigating Antimicrobial Resistance and Pathogenicity.
Shuyu JiaXinran GaoYangyang ZhangPeng ShiChen WangQing ZhouLin YeXu-Xiang ZhangPublished in: Environmental science & technology (2022)
Despite the high removal efficiency for chemical pollutants by tertiary wastewater treatment processes (TWTPs), there is no definite conclusion in terms of microbial risk mitigation yet. This study utilized metagenomic approaches to reveal the alterations of antibiotic resistance genes (ARGs), virulence factor genes (VFGs), their co-occurrence, and potential hosts during multiple TWTPs. Results showed that the TWTPs reduced chemical pollutants in wastewater, but the denitrifying biofilter (DB) significantly increased the absolute abundances of selected antibiotic-resistant bacteria and ARGs, and simultaneously elevated the relative abundances of ARGs and VFGs through the enrichment of multidrug resistance and offensive genes, respectively. Moreover, the co-occurrence of ARGs and VFGs (e.g., bac A- tap W, mex F- ade G) was only identified after the DB treatment and all carried by Pseudomonas . Then, the ultraviolet and constructed wetland treatment showed good complementarity for microbial risk reduction through mitigating antibiotic resistance and pathogenicity. Network and binning analyses showed that the shift of key operational taxonomic units affiliating to Pseudomonas and Acinetobacter may contribute to the dynamic changes of ARGs and VFGs during the TWTPs. Overall, this study sheds new light on how the TWTPs affect the antibiotic resistome and VFG profiles and what TWTPs should be selected for microbial risk mitigation.
Keyphrases
- antibiotic resistance genes
- wastewater treatment
- microbial community
- antimicrobial resistance
- biofilm formation
- genome wide
- quality improvement
- climate change
- anaerobic digestion
- pseudomonas aeruginosa
- staphylococcus aureus
- heavy metals
- dna methylation
- single cell
- candida albicans
- combination therapy
- genome wide identification
- replacement therapy
- network analysis