摘要
      令人振奋的是，抗生素耐药性基因（ARGs）因其对人类健康或生态系统的明显危害而引起了全球的关注。在高通量（HT）-qPCR下分析了鱼类/水样本的细菌群落（BC）和ARG图谱传播。来自不同鱼类样本和不同池塘的ARG差异很大。在同一池塘类型中，基于16S rRNA基因拷贝，水中的ARG数量超过了鱼类中的ARG，具有显著差异，尽管它们的遗传结构基于共同特征是相似的。对于前6种抗生素（氟喹诺酮类>糖肽类>四环素类>氨基糖苷类>大环内酯类-林可酰胺类-链脲菌素B类>利福霉素），五种池塘类型的ARG去除率最高，为98.08–75.6%。大多数（33）共有的ARGs是在水中发现的，尽管有14种在鱼类中发现，7种在两种介质中都发现。梭杆菌门（0.5-61%）、拟杆菌门（11-57%）和变形杆菌门（15-53%）在其他门中占主导地位。螺旋体、Epsilonbacteraeota、aad7和mefA表现出更强的改变ARG结构的潜力。
共享ARG冗余相关性分析显示，拟杆菌门、螺旋体门和拟杆菌门之间的关系更为密切，这可能有利于ARG的分配。尽管28.07%的变异是无法解释的，但移动遗传元件+BC主要影响35.50%的ARG结构变化，而转座酶抗性基因和BC分别贡献了10.90%和25.44%。分析表明，整个水产养殖系统的ARGs具有显著的差异特征（数量、相对丰度和结构分布）（p < 0.05）。本研究中检测到的鱼类和水ARG构成了追踪抗生素使用普遍存在的大规模环境中ARG污染的指标。研究结果表明，研究不足的整个水产养殖系统是高级抗生素耐药性分析的热点。
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.

https://www.liebertpub.com/doi/abs/10.1089/ees.2021.0234