Spatiotemporal profiles and underlying mechanisms of the antibiotic resistome in two water-diversion lakes

Human-induced interventions have altered the local characteristics of the lake ecosystems through changes in hydraulic exchange, which in turn impacts the ecological processes of antibiotic resistance genes (ARGs) in the lakes. However, the current understanding of the spatiotemporal patterns and driving factors of ARGs in water-diversion lakes is still seriously insufficient. In the present study, we investigated antibiotic resistome in the main regulation and storage hubs, namely Nansi Lake and Dongping Lake, of the eastern part of the South-to-North Water Diversion project in Shandong Province (China) using a metagenomic-based approach. A total of 653 ARG subtypes belonging to 25 ARG types were detected with a total abundance of 0.125–0.390 copies/cell, with the dominance of bacitracin, multidrug, and macrolide-lincosamide streptogramin resistance genes. The ARG compositions were sensitive to seasonal variation and also interfered by artificial regulation structures along the way. Human pathogenic bacteria such as Acinetobacter calcoaceticus, Acinetobacter lwoffii, Klebsiella pneumoniae, along with the multidrug resistance genes they carried, were the focus of risk control in the two studied lakes, especially in summer. Plasmids were the key mobile genetic elements (MGEs) driving the horizontal gene transfer of ARGs, especially multidrug and sulfonamide resistance genes. The null model revealed that stochastic process was the main driver of ecological drift for ARGs in the lakes. The partial least squares structural equation model further determined that seasonal changes of pH and temperature drove a shift in the bacterial community, which in turn shaped the profile of ARGs by altering the composition of MGEs, antibacterial biocide- and metal-resistance genes (BMGs), and virulence factor genes (VFGs). Our results highlighted the importance of seasonal factors in determining the water transfer period. These findings can aid in a deeper understanding of the spatiotemporal variations of ARGs in lakes and their driving factors, offering a scientific basis for antibiotic resistance management.