Spatiotemporal variations and ecological risks of typical antibiotics in rivers inflowing into Taihu Lake, China.

Antibiotics have become a global public concern due to the widespread presence of antibiotic-resistant bacteria and genes. This study investigated the spatial and seasonal variation of conventional water quality parameters and 10 selected antibiotics in rivers inflowing into Taihu Lake. The results showed that total nitrogen, as a pollution driver factor, varied with the seasons, and higher concentrations of pollutants were generally found in the dry season compared with the wet season. For antibiotics, seven of them were detected in surface waters (n = 66) with detection frequencies (DFs) of 1.52-100% and eight antibiotics with DFs of 2.56-100% in sediments (n = 39). Sulfamethoxazole (SMZ, median: 1.47 ng/L), trimethoprim (TMP, median: 0.35 ng/L), and roxithromycin (ROX, median: 0.47 ng/L) with 100% DFs followed by erythromycin (ERY, median: 0.56 ng/L) with a DF of 90.91% accounted for a median percentage of 44.54%, 9.08%, 20.42%, and 13.16% of the ΣABs concentrations in surface waters. In contrast, enrofloxacin (ENR, median: 0.54 ng/g) and ROX (median: 0.29 ng/g) with 100% DFs accounted for a median percentage of 58.21% and 31.71% of the ΣABs concentrations in sediments. Antibiotics in surface waters were mainly related to T, DO, TN and NH3-N, but were mainly related to T, pH and TN for antibiotics in sediments. Furthermore, most of the detected antibiotics showed higher concentrations and more species of antibiotics in winter than in summer or autumn. Similarly, the ecological risk values of antibiotics showed higher in winter than in the other two seasons, whereas the overall risk levels were considered acceptable.

Fine particulate matter as a key factor promoting the spread of antibiotics in river network.

The extensive utilization of antibiotics has resulted in their frequent detection, contributing to an increased abundance of antibiotic resistance genes in rivers and posing a significant threat to environmental health. Particulate matter plays a crucial role as the primary carrier of various pollutants in river ecosystem. Its physicochemical properties and processes of sedimentation and re-suspension can influence the migration and transformation of antibiotics, yet the mechanisms of this impact remain unclear. In this study, we investigated the distribution characteristics at the micro-scale of particles in the upstream plain river network of the Taihu basin and the adsorption behaviors of antibiotics in particulate matter. The results revealed that particles were predominantly in the size range of 30 to 150 µm in the river network and highest total antibiotic concentrations in 0 to 10 µm particle size fractions. Adsorption experiments also confirmed that the smaller the suspended particle size, the stronger the adsorption capacity for antibiotics. Spatially, both the average particle size and total antibiotic concentrations were lower downstream than upstream. The distribution mechanism of antibiotic in river network sediments was significantly influenced by frequent resuspension and settling of fine particles with a stronger capacity to adsorb antibiotics under hydrodynamic conditions. This ultimately facilitated the release of antibiotics from sediment into the water, resulting in lower antibiotic concentrations in downstream sediments relative to upstream These findings suggest that fine particles serve as the primary carriers of antibiotics, and their sorting and transport processes can significantly influence the distribution of antibiotics in water-sediment systems. This study enhances our understanding of the migration mechanisms of antibiotics in river networks and will prove beneficial for the development of management strategies aimed at controlling antibiotic dissemination.

Environmental filtering dominated the antibiotic resistome assembly in river networks.

River networks play important roles in dissemination of antibiotic resistance genes (ARGs). The occurrence, diversity, and abundance of ARGs in river networks have been widely investigated. However, the assembly processes that shaped ARGs profiles across space and time are largely unknown. Here, the dynamics of ARGs profiles in river networks (Taihu Basin) were revealed by high-throughput quantitative PCR followed by multiple statistical analyses to assess the underlying ecological processes. The results revealed clear variations for ARGs profiles across wet, normal, and dry seasons. Meanwhile, a significant negative correlation (p < 0.01) was observed between the similarity of ARGs profiles and geographic distance, indicating ARGs profiles exhibited distance-decay patterns. Null model analysis showed that ARGs profiles were mainly assembled via deterministic processes. Redundancy analysis followed by hierarchical partitioning revealed that environmental attributes (mainly pH and temperature) were the major factors affecting the dynamics of ARGs profiles. Together, these results indicated that environmental filtering was the dominant ecological process that shaped ARGs profiles. This study enhances our understanding how the antibiotic resistome is assembled in river networks and will be beneficial for the development of management strategies to control ARGs dissemination.

Similar geographic patterns but distinct assembly processes of abundant and rare bacterioplankton communities in river networks of the Taihu Basin.

Bacterioplankton play an important role in the biogeochemical cycling in rivers. The dynamics of hydrologic conditions in rivers were believed to affect geographic pattern and assembly process of these microorganisms, which have not been widely investigated. In this study, the geographic pattern and assembly process of bacterioplankton community in river networks of the Taihu Basin were systematically explored using amplicon sequencing of the 16S rRNA gene. The results showed that the diversity, structure,  and taxonomic composition of bacterioplankton community all exhibited significant temporal variation during wet, normal, and dry seasons (p<0.01). The neutral community model and null model were applied to reveal the assembly process of bacterioplankton community. The stochastic process and deterministic process both shaped the bacterioplankton community with greater influence of deterministic process. In addition, the abundant and rare bacterioplankton communities were comparatively analyzed. The abundant and rare bacterioplankton communities exhibited similar temporal dynamics (principal coordinates analysis) and spatial variations (distance-decay relationship), indicating similar geographic patterns. Meanwhile, distinct assembly processes were observed for the abundant and rare bacterioplankton communities. Stochastic process (dispersal limitation) shaped the abundant bacterioplankton community while deterministic process (heterogeneous selection) dominated the assembly process of rare bacterioplankton community. Mantel test, redundancy analysis, and correlation analysis together indicated that pH and dissolved oxygen were the major environmental attributes that affected thestructure and assembly process of bacterioplankton community. These results expanded our understanding of the geographic pattern, assembly process, and driving factors of bacterioplankton community in river networks and provided clues for the underlying mechanisms.