ARGs-OSP

ARGs-OSP maps the distribution and mobility of antibiotic resistance genes (ARGs) across bacterial genomes, plasmids, integrons, and metagenomes to support comparative ecological and clinical analyses.


Key Features:

  • Extensive Database: Profiles are derived from a dataset comprising 55,000 bacterial genomes, 16,000 plasmid sequences, 3,000 integron sequences, and 850 metagenomes for comparative ARG analyses.
  • Standardized Analysis Pipeline: Employs a standardized pipeline to ensure consistent and reliable cross-sample comparisons.
  • Focus on Mobile ARGs: Identifies mobile ARGs and reports that over 80% of known ARGs are not associated with plasmids or integrons, with examples including tetracycline and beta-lactam resistance genes such as tetA, tetM, and class A beta-lactamase.
  • Integration with Global Data: Integrates data from human-associated and non-human-associated habitats to characterize environmental reservoirs of ARGs.
  • Correlation Analysis: Performs correlation analyses between ARG abundance and class 1 integrases (intI1), revealing poor linear correlation across habitats and no significant correlation with anthropogenic factors.

Scientific Applications:

  • Risk Assessment: Provides detailed ARG distribution profiles to inform environmental and public health risk assessments of antibiotic resistance.
  • Evolutionary Studies: Enables investigation of the evolutionary dynamics and dissemination of ARGs across bacterial taxa and mobile genetic elements.
  • Clinical Relevance: Identifies clinically relevant mobile ARGs to support understanding of resistance mechanisms in pathogens.

Methodology:

Metagenomic analysis combined with a standardized analysis pipeline to generate consistent ARG distribution profiles from genomic, plasmid, integron, and metagenomic datasets.

Topics

Details

Tool Type:
web application
Programming Languages:
Python, R
Added:
1/18/2021
Last Updated:
1/28/2021

Operations

Publications

Zhang AN, Hou C, Negi M, Li L, Zhang T. Online searching platform for the antibiotic resistome in bacterial tree of life and global habitats. FEMS Microbiology Ecology. 2020;96(7). doi:10.1093/femsec/fiaa107. PMID:32472933.

PMID: 32472933
Funding: - National Key R&D Program of China: 2018YFC0310600 - Hong Kong Theme-based Research Scheme: T21-711/16-R

Links