Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke - DIfE, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany.
Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller University, Lessingstrasse 8, 07743 Jena, Germany.
Gigascience. 2020 May 1;9(5). doi: 10.1093/gigascience/giaa046.
The rise of antibiotic resistance (AR) in clinical settings is of great concern. Therefore, the understanding of AR mechanisms, evolution, and global distribution is a priority for patient survival. Despite all efforts in the elucidation of AR mechanisms in clinical strains, little is known about its prevalence and evolution in environmental microorganisms. We used 293 metagenomic samples from the TARA Oceans project to detect and quantify environmental antibiotic resistance genes (ARGs) using machine learning tools.
After manual curation of ARGs, their abundance and distribution in the global ocean are presented. Additionally, the potential of horizontal ARG transfer by plasmids and their correlation with environmental and geographical parameters is shown. A total of 99,205 environmental open reading frames (ORFs) were classified as 1 of 560 different ARGs conferring resistance to 26 antibiotic classes. We found 24,567 ORFs in putative plasmid sequences, suggesting the importance of mobile genetic elements in the dynamics of environmental ARG transmission. Moreover, 4,804 contigs with >=2 putative ARGs were found, including 2 plasmid-like contigs with 5 different ARGs, highlighting the potential presence of multi-resistant microorganisms in the natural ocean environment. Finally, we identified ARGs conferring resistance to some of the most relevant clinical antibiotics, revealing the presence of 15 ARGs similar to mobilized colistin resistance genes (mcr) with high abundance on polar biomes. Of these, 5 are assigned to Psychrobacter, a genus including opportunistic human pathogens.
This study uncovers the diversity and abundance of ARGs in the global ocean metagenome. Our results are available on Zenodo in MySQL database dump format, and all the code used for the analyses, including a Jupyter notebook js avaliable on Github. We also developed a dashboard web application (http://www.resistomedb.com) for data visualization.
临床环境中抗生素耐药性（AR）的上升令人担忧。因此，了解 AR 机制、进化和全球分布是患者生存的首要任务。尽管在临床菌株中阐明 AR 机制方面做出了所有努力，但对环境微生物中其流行率和进化的了解甚少。我们使用 TARA 海洋项目的 293 个宏基因组样本，使用机器学习工具来检测和量化环境抗生素抗性基因（ARGs）。
在对 ARGs 进行手动策展后，展示了它们在全球海洋中的丰度和分布。此外，还展示了质粒介导的水平 ARG 转移的潜力及其与环境和地理参数的相关性。总共将 99,205 个环境开放阅读框（ORFs）分类为 1 种 560 种不同的 ARG，赋予 26 种抗生素类别的抗性。我们在假定的质粒序列中发现了 24,567 个 ORFs，这表明移动遗传元件在环境 ARG 传播动力学中的重要性。此外，发现了 4,804 个包含>=2 个假定 ARG 的连续序列，其中包括 2 个具有 5 种不同 ARG 的质粒样连续序列，突出了多耐药微生物在自然海洋环境中存在的可能性。最后，我们鉴定了赋予一些最相关临床抗生素抗性的 ARGs，揭示了高丰度存在于极地生物群系中的 15 种类似于移动多粘菌素抗性基因（mcr）的 ARGs。其中 5 种属于 Psychrobacter，该属包括机会性病原体人类病原体。
本研究揭示了全球海洋宏基因组中 ARG 的多样性和丰度。我们的结果以 MySQL 数据库转储格式在 Zenodo 上可用，所有用于分析的代码，包括在 Github 上提供的 Jupyter 笔记本 js，我们还开发了一个数据可视化的仪表板 Web 应用程序（http://www.resistomedb.com）。
