BACKGROUND 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. RESULTS 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. CONCLUSIONS 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.

中文翻译：

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全球海洋抗性组揭示：探索 TARA 海洋样本中抗生素抗性基因的丰度和分布。


背景技术临床环境中抗生素耐药性（AR）的上升引起了人们的高度关注。因此，了解 AR 机制、进化和全球分布是患者生存的首要任务。尽管人们努力阐明临床菌株中的 AR 机制，但对其在环境微生物中的流行和进化知之甚少。我们使用 TARA Oceans 项目的 293 个宏基因组样本，利用机器学习工具检测和量化环境抗生素抗性基因 (ARG)。结果 经过人工管理 ARG 后，显示了它们在全球海洋中的丰度和分布。此外，还显示了质粒水平 ARG 转移的潜力及其与环境和地理参数的相关性。总共 99,205 个环境开放阅读框 (ORF) 被归类为 560 种不同的 ARG 中的一种，这些 ARG 赋予 26 种抗生素耐药性。我们在假定的质粒序列中发现了 24,567 个 ORF，这表明可移动遗传元件在环境 ARG 传播动态中的重要性。此外，还发现了 4,804 个具有 >=2 个假定 ARG 的重叠群，其中包括 2 个具有 5 个不同 ARG 的类质粒重叠群，这凸显了自然海洋环境中潜在存在的多重耐药微生物。最后，我们鉴定了对一些最相关的临床抗生素具有抗性的 ARG，揭示了 15 个 ARG 的存在，类似于极地生物群落中高丰度的动员粘菌素抗性基因 (mcr)。其中，5 种属于冷杆菌属，该属包括机会性人类病原体。结论 这项研究揭示了全球海洋宏基因组中 ARG 的多样性和丰度。 我们的结果可以在 Zenodo 上以 MySQL 数据库转储格式获得，以及用于分析的所有代码，包括 Github 上提供的 Jupyter Notebook js。我们还开发了一个用于数据可视化的仪表板 Web 应用程序 (http://www.resistomedb.com)。