School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, P. R. China.
Suzhou Precision Biotech Co., Ltd, Suzhou 215000, P. R. China.
Environ Sci Technol. 2023 Mar 28;57(12):4971-4983. doi: 10.1021/acs.est.2c08766. Epub 2023 Mar 17.
infection is the main cause of diarrhea in humans worldwide. The emergence of antimicrobial resistance (AMR) of is a growing public health threat worldwide, while large-scale studies monitoring the longitudinal AMR trends of isolates remain scarce. Here, the AMR gene (ARG) profiles of 717 isolates from 1920 to 2020 worldwide were determined. The results showed that the average number of ARGs in isolates has increased significantly, from 19.2 ± 2.4 before 1970 to 29.6 ± 5.3 after 2010. In addition, mobile genetic elements were important contributors to ARGs in isolates. The results of the structural equation model showed that the human development index drove the consumption of antibiotics and indirectly promoted the antibiotic resistance. Finally, a machine learning algorithm was used to predict the antibiotic resistance risk of global terrestrial isolates and successfully map the antibiotic resistance threats in global land habitats with over 80% accuracy. Collectively, this study monitored the longitudinal AMR trends, quantitatively surveilled the health risk of AMR, and provided a theoretical basis for mitigating the threat of antibiotic resistance.
感染是全球人类腹泻的主要原因。抗生素耐药性（AMR）的出现是全球日益严重的公共卫生威胁，而监测分离株纵向 AMR 趋势的大规模研究仍然很少。在这里，我们确定了来自全球 1920 年至 2020 年的 717 株 分离株的 AMR 基因（ARG）图谱。结果表明，分离株中的 ARG 数量平均显著增加，从 1970 年以前的 19.2 ± 2.4 增加到 2010 年以后的 29.6 ± 5.3。此外，移动遗传元件是 分离株中 ARGs 的重要贡献者。结构方程模型的结果表明，人类发展指数驱动了抗生素的消费，并间接地促进了抗生素耐药性。最后，使用机器学习算法预测了全球陆地 分离株的抗生素耐药性风险，并成功地以超过 80%的准确率绘制了全球陆地生境中的抗生素耐药性威胁图。总的来说，本研究监测了纵向 AMR 趋势，定量监测了 AMR 的健康风险，并为减轻抗生素耐药性威胁提供了理论依据。
