Migration and biotransformation mechanisms of risk-priority antibiotics in wastewater biotreatment: An integrated...

Understanding the fate and transformation of antibiotics is essential for controlling antibiotic pollution in wastewater treatment plants (WWTPs). This study integrated metagenomics, metaproteomics, molecular dynamics (MD) simulations, and pathway analysis to elucidate the behavior of ciprofloxacin (CIP), sulfamethoxazole (SMX), and roxithromycin (ROX) under single- and mixed-antibiotic exposures in an activated sludge system. Fate analysis revealed divergent pathways: SMX was predominantly biodegraded (>70%), whereas CIP and ROX were mainly adsorbed onto sludge, showing poor removal and high effluent residuals (CIP > 50%, ROX > 60%). Under mixed-antibiotic stress, microorganisms favored lower-energy degradation pathways, leading to simplified (skip-step) transformations. MD simulations unveiled that within the extracellular polymeric substances (EPS) matrix, the protein fraction exhibited the strongest binding. Docking and MD simulations on a proteomics-derived interface-associated protein (OmpA) revealed a co-adsorption behavior under mixed-antibiotic exposure, where CIP strongly anchored through multipoint hydrogen bonding/electrostatic interactions and facilitated SMX stabilization in the same pocket via aromatic stacking. Multi-omics analyses revealed a microbial "survival-first" strategy dominated by resistance and repair. Notably, transporter-related stress responses were prominent under mixed stress, and several ABC transporter-associated components (e.g., K02003/K02004 and K02033) were negatively correlated with removal efficiency, coinciding with reduced degradation by key genera such as Micropruina and Ottowia. Under mixed-antibiotic stress, a confluence of reinforced resistance (e.g., Type IV secretion system K03205), altered EPS binding, and skewed energy allocation (e.g., downregulation of cofactor synthesis ko01240) led to incomplete degradation and widespread persistence. This study provides a multiscale theoretical framework for optimizing WWTPs to control antibiotic pollution.