Quorum quenching (QQ)-based strategies are efficient for biofouling control. However, the feasibility of using QQ bacteria in antibiotic-stressed membrane bioreactors (MBRs) remains unknown. In this study, we isolated three novel QQ strains (Bacillus sp. QX01 and QX03, Delftia sp. QX14) from the activated sludge of an actual MBR. They can degrade 11 N-acyl-homoserine lactones (AHLs) with high efficiencies and rates through intracellular QQ pathways involving putative acylases and lactonases. Running two lab-scale MBRs, we found that introducing antibiotics (sulfamethoxazole, azithromycin, and ciprofloxacin, each at 100 μg/L) shortened the fouling cycle by 71.4 %. However, the immobilized inoculation of QX01 into one MBR extended the fouling cycle by 1.5-2.0 times. Quantitative detection revealed that QX01 significantly reduced the concentrations of two AHLs (C4-HSL and C8-HSL), which were positively correlated with the contents of extracellular polymeric substances (EPS) (Pearson's r = 0.62-0.83, P < 0.01). This suggests that QX01 could perform its QQ activity robustly under antibiotic stress, thereby inhibiting EPS production (proteins especially) and biofilm formation. Moreover, QX01 notably altered the succession patterns of both sludge and fouling communities, with more pronounced effects on abundant taxa. Genera associated with AHL synthesis and EPS production, such as Terrimonas and Rhodobacter, were significantly depleted, contributing to the mitigated biofouling. Additionally, QX01 increased the bacterial community diversity (evenness especially), which was inhibited by antibiotics. Overall, we demonstrate that the novel QQ bacteria could be effective for biofouling control in antibiotic-stressed MBRs, though future work is needed to develop practical approaches for prolonging QQ activity.

Coastal sediment cores provide important records of land-based antibiotics' deposition. This study examined sediment cores from the Hangzhou Bay, East China Sea, dating back to 1980–2020 using 210Pbex. The 40-year analysis revealed a mismatch between sediment depth and age. Wastewater treatment facilities have significantly reduced antibiotics discharge into the sea. We identified 27 antibiotics, with enrofloxacin (ERFX) and nadifloxacin (NDFX) exhibiting the highest average concentrations of 84.9 and 83.4 ng/g, respectively. Quinolones (QNs) were prominent, displaying strong co-occurrence and similar distribution patterns shaped by comparable soil-water distribution coefficient (Kd). QNs correlated positively with total antibiotic concentration, serving as indicators. We proposed a multi-dimensional risk assessment of antibiotics, encompassing ecological and antimicrobial resistance (AMR) risks, complementing each other. The assessment revealed antibiotics with distinct risks: sulfacetamide (SCM) and clindamycin (CLIN) exhibited high ecological risks, while ERFX, ciprofloxacin (CFX), norfloxacin (NFX), gatifloxacin (GTFX), moxifloxacin (MXFX), and marbofloxacin (MBFX) presented high AMR risks.

Effective risk assessment and control of environmental antibiotic resistance depend on comprehensive information about antibiotic resistance genes (ARGs) and their microbial hosts. Advances in sequencing technologies and bioinformatics have enabled the identification of ARG hosts using metagenome-assembled contigs and genomes. However, these approaches often suffer from information loss and require extensive computational resources. Here we introduce a bioinformatic strategy that identifies ARG hosts by prescreening ARG-like reads (ALRs) directly from total metagenomic datasets. This ALR-based method offers several advantages: (1) it enables the detection of low-abundance ARG hosts with higher accuracy in complex environments; (2) it establishes a direct relationship between the abundance of ARGs and their hosts; and (3) it reduces computation time by approximately 44–96% compared to strategies relying on assembled contigs and genomes. We applied our ALR-based strategy alongside two traditional methods to investigate a typical human-impacted environment. The results were consistent across all methods, revealing that ARGs are predominantly carried by Gammaproteobacteria and Bacilli, and their distribution patterns may indicate the impact of wastewater discharge on coastal resistome. Our strategy provides rapid and accurate identification of antibiotic-resistant bacteria, offering valuable insights for the high-throughput surveillance of environmental antibiotic resistance. This study further expands our knowledge of ARG-related risk management in future.