Transmission mechanism of antibiotic resistance genes and their differences between water and sediment in the Weihe River Basin

Antibiotic resistance genes (ARGs) are emerging microbial pollutants that are regulated by many factors and pose potential threats to aquatic environments. In this study, we used network analysis, correlation analysis, and constructed models based on metagenomic sequencing results to explore the spatial patterns, impact mechanisms, transmission risks and differences in ARGs in the water and sediment of the Weihe River Basin. The findings revealed notable disparities in ARGs, mobile genetic elements (MGEs), and bacterial communities. In the sediment, the abundance of ARGs was considerably greater than that in water. Moreover, the percentage of ARGs shared by the two components reached a value of 85.8%. Through network analysis, it was determined that the presence of 16 MGEs and 20 bacterial phyla was strongly associated with ARGs (R2>0.7, P<0.05). The Mantel test showed that abiotic factors including DO, pH, nutrients, and heavy metals played important roles in the distribution of ARGs (P<0.05). A structural equation model revealed that the key factors influencing the distribution of ARGs in water were bacterial diversity and environmental parameters (standardized effects of -0.730 and -0.667), and those in sediment were bacterial diversity and MGEs (standardized effects of -0.751 and 0.851). Neutral modeling indicated that deterministic processes played an important role in the assembly of ARGs in the water of the Weihe River Basin, and stochastic processes were dominant in the sediment. There was a highly significant positive linear correlation between ARGs and pathogens, and there was more complex co-occurrence in the water than in the sediment (R2>0.9, P<0.05), with stronger migration and transmission occurring. Exploring ARGs in large-scale watersheds is immensely important for elucidating their traits and transmission mechanisms and consequently paving the way for the formulation of efficient strategies to mitigate resistance threats.