Sulfamethazine

Constructed wetlands (CWs) are increasingly utilized for sulfonamide remediation, yet the ecological drivers governing sulfonamide-degrading bacteria (SDB) remain inadequately characterized. To systematically evaluate how oxygen and nutrient availability interact to shape SDB communities, this study classified CWs into three distinct functional types: high-dissolved-oxygen-high-nutrient (HD-HN), high-dissolved-oxygen-low-nutrient (HD-LN), and low-dissolved-oxygen-high-nutrient (LD-HN) systems. Analysis of medium-to-large CWs in South China demonstrated pervasive SDB colonization (relative abundance: 0.104 %-0.503 %), with comparative analysis across the three CW types revealing that aerobic regimes synergized with elevated nutrient loads fostered stochastic community assembly (R² = 0.813 for HD-HN) and expanded niche breadth of SDB, culminating in functionally robust consortia. The classification framework demonstrated that stochastic processes dominated high-resource environments (HD-HN), starkly contrasting with deterministic selection in oxygen-depleted systems (LD-HN) and nutrient-limited conditions (HD-LN). Co-occurrence network pinpointed SDB as keystone taxa with significantly higher connectivity (average degree >30), facilitating sulfonamide elimination through cross-functional collaboration with non-SDB taxa. Mesocosm experiments validated field observations by replicating key environmental gradients under controlled conditions, achieving >50 % sulfamethazine removal in optimized HD-HN configurations, confirming the generalizability of the identified SDB response patterns. These findings advance predictive frameworks for optimizing CW design through targeted manipulation of oxygen and nutrient regimes to enhance co-contaminant remediation.

Antibiotics frequently co-occur in aquatic environments, yet their combined ecological effects remain insufficiently understood under realistic mixture scenarios. To address this knowledge gap, we established 36 replicated freshwater microcosms and exposed them to two commonly detected antibiotics, sulfamethazine (SMT) and tetracycline (TC), both individually and in combination, at environmentally realistic concentrations over a 28-day period. At the primary producer level, both antibiotics reduced green algal abundance at intermediate and high concentrations alone, whereas their combination exposure did not consistently inhibit growth, suggesting altered ecological effects under mixture exposure. Zooplankton community structure was significantly altered under both individual and mixture treatments, with stimulatory as well as adverse effects observed at different dose levels. Microbial communities responded in a compartment-specific manner. Single-compound exposures significantly shifted community structure in both water column and sediment. In contrast, no significant changes were detected in water-column microbial communities under mixture treatments, suggesting antagonistic interactions between SMT and TC, likely related to their distinct modes of action and compensatory microbial regulation. At the functional level, leaf-litter decomposition was consistently accelerated across multiple treatments, indicating enhanced microbial activity and functional stimulation. Collectively, these findings provide experimental evidence that antibiotic mixtures can exert non-additive effects across trophic levels and ecosystem processes, highlighting the importance of accounting for such interactions in future research and risk assessment frameworks.