ARGs-OAP v3.0: Antibiotic-resistance gene database curation and analysis pipeline optimization

Xiaole YIN, Xiawan ZHENG, Liguan LI, An-Ni ZHANG, Xiao-Tao JIANG, Tong ZHANG

Research output: Contribution to journalArticlespeer-review

12 Citations (Scopus)

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 ARGs online analysis pipeline (ARGs-OAP) has made significant improvements to both the reference database—the structured ARG (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.

Original languageEnglish
Pages (from-to)234-241
JournalEngineering
Volume27
DOIs
Publication statusPublished - Aug 2023

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