摘要

       鸭鱼混养是我国南方珠江三角洲地区典型的养殖模式。2014年9月和12月，我们检查了广东省三个养鸭场的土壤、水和沉积物样本。我们测定了3个金属抗性基因16srDNA和23个编码四环素、磺胺类、喹诺酮类、氯霉素和β-内酰胺酶抗性基因的丰度。采用Illumina 16srDNA基因高通量测序法对微生物群落结构进行了定量分析。我们发现抗生素耐药基因普遍存在，其中sul1、sul2、tetA、tetM、aac（6’）-Ib和floR基因最为丰富。铜、锌水平与多种ARG类型显著相关，sul2、floR和tetM被认为是潜在的耐药基因指标。铜水平与sul3、tetT、tetW、qnrB、qnrS、fexB、sul1、sul2、tetM和qnrA的相对丰度显著正相关。锌与sul2、sul3、tetM、tetA、tetT、tetW、qnrA、qnrB、qnrS、aac（6’）-Ib、qepA、blaSHV、cmlA、floR、fexA、cfr和fexB的相对丰度显著相关。不动杆菌、短杆菌和子宫杆菌的水平与金属抗性基因以及qnrB、oqxA、oqxB和blaSHV呈显著正相关（p＞0.8）。鞘氨醇杆菌、黄杆菌、酸热菌和棒状杆菌与四环素抗性基因、磺胺抗性基因、blaTEM、blaCTX和cfr的丰度有显著相关（p＞0.8）。土壤中鞘氨醇杆菌、黄杆菌、酸热菌和棒状杆菌最为丰富，而水样中不动杆菌、短杆菌和子宫杆菌最为丰富。抗药性基因在水产养殖环境中的传播十分广泛，要建立水产养殖环境保护所需的风险评估方法，必须对其来源进行追踪。

        Duck/fish polyculture farming is a typical farming model in the Pearl River delta in southern China. We examined soil, water, and sediment samples from three duck-fish farms in Guangdong Province in September and December 2014. We determined the abundance of three metal resistance genes, 16S rDNA, and 23 antibiotic resistance genes encoding resistance to tetracycline, sulfonamides, quinolones, chloramphenicol, and β-lactamases. Microbial community structure was quantified by Illumina high-throughput sequencing of 16S rDNA genes. We found a prevalence of antibiotic resistance genes and the sul1, sul2, tetA, tetM, aac(6')-Ib, and floR genes were the most abundant. Levels of Cu and Zn were significantly correlated with numerous ARG types and sul2, floR, and tetM were identified as potential antibiotic resistance gene indicators. Cu levels were significantly and positively correlated with the relative abundance of sul3, tetT, tetW, qnrB, qnrS, fexB, sul1, sul2, tetM, and qnrA. Zn was significantly correlated to relative abundance of sul2, sul3, tetM, tetA, tetT, tetW, qnrA, qnrB, qnrS, aac(6')-Ib, qepA, bla_SHV, cmlA, floR, fexA, cfr, and fexB. The levels of Acinetobacter, Brevibacillus, and Wautersiella showed significant positive correlations with metal resistance genes as well as qnrB, oqxA, oqxB, and bla_SHV (p > 0.8). Sphingobacterium, Flavobacterium, Acidothermus, and Corynebacterium had significant correlations with abundance of tetracycline resistance genes, sulfonamide resistance genes, bla_TEM, bla_CTX, and cfr (p > 0.8). Sphingobacterium, Flavobacterium, Acidothermus, and Corynebacterium were most abundant in soil samples while Acinetobacter, Brevibacillus, and Wautersiella were most abundant in water samples. Dissemination of antibiotic resistance genes in aquaculture environments is extensive and tracing their origins is necessary to establish risk assessment methods required for aquatic environmental protection.

        https://link.springer.com/article/10.1007/s11356-018-04065-2