Metagenomic analysis to determine the characteristics of antibiotic resistance genes in typical antibiotic-contaminated sediments

Abstract

Comprehensive studies of the effects of various physical and chemical variables (including heavy metals), antibiotics, and microorganisms in the environment on antibiotic resistance genes are rare. We collected sediment samples from the Shatian Lake aquaculture area and surrounding lakes and rivers located in Shanghai, China. The spatial distribution of sediment ARGs was assessed by metagenomic analysis that revealed 26 ARG types (510 subtypes), dominated by Multidrug, β-lactam, Aminoglycoside, Glycopeptides, Fluoroquinolone, and Tetracyline. Redundancy discriminant analysis indicated that antibiotics (SAs and MLs) in the aqueous environment and sediment along with water TN and TP were the key variables affecting the abundance distribution of total ARGs. However, the main environmental drivers and key influences differed among the different ARGs. For total ARGs, the environmental subtypes affecting their structural composition and distribution characteristics were mainly antibiotic residues. Procrustes analysis showed a significant correlation between ARGs and microbial communities in the sediment in the survey area. Network analysis revealed that most of the target ARGs were significantly and positively correlated with microorganisms, and a small number of ARGs (e.g., rpoB, mdtC, and efpA) were highly significantly and positively correlated with microorganisms (e.g., Knoellia, Tetrasphaera, and Gemmatirosa). Potential hosts for the major ARGs included Actinobacteria, Proteobacteria, and Gemmatimonadetes. Our study provides new insight and a comprehensive assessment of the distribution and abundance of ARGs and the drivers of ARG occurrence and transmission.