High-Throughput Profiling of the Antibiotic Resistance Gene Transmission in Aquaculture Systems

Abstract

Enunciatively, antibiotic resistance genes (ARGs) have attracted global attention because of their pronounced dangers on human health or ecosystems. The bacterial community (BC) and ARG profile transmission of the fish/water samples were analyzed under high-throughput (HT)-qPCR. ARGs from different fish samples and different ponds varied significantly. In the same pond type, the ARGs in water outnumbered the ARGs in fish based on 16S rRNA gene copies with significant differences, although their genetic structures were similar based on shared characteristics. The highest ARG removal efficiencies of the five pond types rated 98.08–75.6% for top 6 antibiotics (fluoroquinolone > glycopeptide > tetracycline > aminoglycoside > macrolide–lincosamide–streptogramin B > rifamycin). Majority (33) of shared ARGs were discovered in water, although 14 featured in fish and 7 in both mediums. Fusobacteria (0.5–61%), Bacteroidetes (11–57%), and Proteobacteria (15–53%) dominated other phyla. Spirochaetes, Epsilonbacteraeota, aad7, and mefA demonstrated stronger potential to change ARG structures. Shared ARG redundancy correlation analyses revealed tighter relationships among Bacteroidetes, Spirochaetes, and Epsilonbacteraeota, which probably favored ARG partitioning. Although 28.07% variations were unexplainable, mobile genetic elements + BC predominantly influenced 35.50% ARG structural changes while transposase resistance genes, and BC contributed 10.90% and 25.44%, respectively. Analyzed ARGs of the entire aquaculture systems demonstrated significant differential characteristics (numbers, relative abundances, and structural distributions) (p < 0.05). The fish and water ARGs detected in this study constitute indicators for tracing ARG contamination in large-scale environments where antibiotics usage is ubiquitous. The findings imply that the entire aquaculture system understudied are hotspots for advanced antibiotic resistome analyses.