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巴西里约热内卢饮用水供应系统微生物群落的移动耐药性和抗微生物残留

发布者:抗性基因网 时间:2023-06-07 浏览量:175

摘要
      由于抗生素和其他污染物的过度使用,抗生素耐药性基因在环境中广泛存在,对人类和动物健康构成威胁。在这项研究中,我们评估了为巴西里约热内卢市提供饮用水的两个重要流域,即Guandu和São João的抗菌药物残留、细菌多样性和ARGs。此外,还从里约热内卢州的三个不同城市采集了自来水样本,其中包括里约热内卢市的大都市地区。在所有样本的未经处理的水和饮用水中均发现了克拉霉素、磺胺甲恶唑和阿奇霉素。在Guandu和São João流域观察到更丰富的变形菌,大多数序列属于伽马变形菌类。以质粒组为重点的宏基因组学方法揭示了4881个(关渡)、3705个(圣若昂)和3385个(饮用水)ARG,主要与外排系统有关。在两个流域和饮用水中检测到编码金属β-内酰胺酶的基因(blaAIM、blaGIM、blaIMP和blaVIM)。此外,我们首次在巴西证明了粘菌素抗性基因mcr-3和mcr-4(均为流域)以及mcr-9(饮用水和官渡)的存在。我们的数据强调了采取措施减少抗生素和其他污染物处置的重要性,这些污染物能够促进微生物耐药性在水生环境中的发生和传播,并预测可能对人类健康产生的负面影响。
Abstract
Antibiotic resistance genes (ARGs) are widespread in the environment due to the overuse of antibiotics and other pollutants, posing a threat to human and animal health. In this study, we evaluated antimicrobial residues, bacterial diversity and ARGs in two important watersheds, Guandu and São João, that supply drinking water to Rio de Janeiro city, Brazil. In addition, tap water samples were collected from three different cities in Rio de Janeiro State, including the metropolitan area of Rio de Janeiro city. Clarithromycin, sulfamethoxazole and azithromycin were found in untreated water and drinking water in all samples. A greater abundance of Proteobacteria was observed in Guandu and São João watersheds, with most of the sequences belonging to the Gammaproteobacteria class. A plasmidome-focused metagenomics approach revealed 4881 (Guandu), 3705 (São João) and 3385 (drinking water) ARGs mainly associated with efflux systems. The genes encoding metallo-β-lactamase enzymes (blaAIM, blaGIM, blaIMP, and blaVIM) were detected in the two watersheds and in drinking water samples. Moreover, we demonstrated the presence of the colistin resistance genes mcr-3 and mcr-4 (both watersheds) and mcr-9 (drinking water and Guandu) for the first time in Brazil. Our data emphasize the importance of introducing measures to reduce the disposal of antibiotics and other pollutants capable of promoting the occurrence and spread of the microbial resistome on aquatic environments and predicting possible negative impacts on human health.

https://www.nature.com/articles/s41598-022-21040-7