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ARGs-OAP v3.0:抗生素耐药性基因数据库的建立和分析管道的优化

发布者:抗性基因网 时间:2023-05-29 浏览量:1609

摘要
      由抗生素耐药性基因(ARGs)编码的抗生素耐药性已经激增,对世界各地的公共健康构成越来越大的威胁。随着技术的进步,特别是在宏基因组测序的普及方面,科学家们已经能够以加速的速度高精度破译不同样本中ARGs的图谱。为了以高通量的方式分析数千个ARG,需要标准化和集成化的管道。广泛使用的抗生素耐药性基因在线分析管道(ARGs-OAP)的新版本(v3.0)对参考数据库、结构化抗生素耐药性基因(SARG)数据库和综合分析管道都做出了重大改进。序列管理增强了严重急性呼吸系统综合征,以提高注释的可靠性,纳入新出现的抗性基因型,并确定严格的机制分类。该数据库以树状结构和字典的形式进行了进一步的在线组织和可视化。它还被划分为用于不同应用场景的子数据库。此外,ARGs OAP还通过调整量化方法、简化工具实现以及使用用户定义的参考数据库的多个功能进行了改进。此外,在线平台现在提供了一个多样化的生物统计分析工作流程,其中包括用于有效解释ARG剖面的可视化包。ARGs OAP v3.0具有改进的数据库和分析管道,将有利于学术界、政府管理层和关于ARGs环境流行率风险评估的咨询。
Abstract
Antibiotic resistance, which is encoded by antibiotic-resistance genes (ARGs), has proliferated to become a growing threat to public health around the world. With technical advances, especially in the popularization of metagenomic sequencing, scientists have gained the ability to decipher the profiles of ARGs in diverse samples with high accuracy at an accelerated speed. To analyze thousands of ARGs in a high-throughput way, standardized and integrated pipelines are needed. The new version (v3.0) of the widely used antibiotic-resistance genes online analysis pipeline (ARGs-OAP) has made significant improvements to both the reference database—the structured antibiotic-resistance gene (SARG) database—and the integrated analysis pipeline. SARG has been enhanced with sequence curation to improve annotation reliability, incorporate emerging resistance genotypes, and determine rigorous mechanism classification. The database has been further organized and visualized online in the format of a tree-like structure with a dictionary. It has also been divided into sub-databases for different application scenarios. In addition, the ARGs-OAP has been improved with adjusted quantification methods, simplified tool implementation, and multiple functions with user-defined reference databases. Moreover, the online platform now provides a diverse biostatistical analysis workflow with visualization packages for the efficient interpretation of ARG profiles. The ARGs-OAP v3.0 with an improved database and analysis pipeline will benefit academia, governmental management, and consultation regarding risk assessment of the environmental prevalence of ARGs.

https://www.sciencedirect.com/science/article/pii/S2095809922008062