A Note on Ongoing Revisions of the Antibiotic Resistance Ontology
The Comprehensive Antibiotic Resistance Database gratefully acknowledges recent funding from the Genome Canada & Canadian Institutes of Health Research's Bioinformatics & Computational Biology program, allowing integration of the Antibiotic Resistance Ontology (ARO) with the Genomic Epidemiology Ontology, IRIDA platform, and OBO Foundry (see Genome Canada press release). As such, the next two years will be a time of active development for the ARO. Expect significant changes in the ARO between monthly releases as well as occasional incomplete revisions, which may affect downstream analyses.
February 2017 Changes
Use of the part_of relationship now follows canonical usage and is restricted to association of sub-units with their large multi-unit protein complexes
Extensive revisions to the antimicrobial efflux branch of the ARO
Extensive revisions to the rRNA mutations branch of the ARO
New use of the participates_in and has_part relationships in place of formerly incorrect usage of the part_of relationship for association of resistance determinants with their mechanism of action.
April 2017 Changes
Extensive addition of confers_resistance_to_drug relationships for efflux complexes
Drug and mechanism category updates for the Resistance Gene Identifier
May 2017 Changes
Addition of bitscores to detection models, curation of chloramphenicol exporter proteins, ontology changes, JSON file format changes
August 2017 Changes
Removal of redundant intermediate terms relating resistance determinant to drug class, with improved overall classification by Drug Class and Resistance Mechanism
January 2018 Changes
Parallel classification system added to the ARO for organization of RGI results: Drug Class, Resistance Mechanism, AMR Gene Family
Allen HK, et al. 2009. ISME J 3(2): 243-251. Functional metagenomics reveals diverse beta-lactamases in a remote Alaskan soil. (PMID 18843302)
Resistomes
Prevalence of LRA-18 among the sequenced genomes, plasmids, and whole-genome shotgun assemblies available at NCBI or IslandViewer for 414 important pathogens (see methodological details and complete list of analyzed pathogens). Values reflect percentage of genomes, plasmids, genome islands, or whole-genome shotgun assemblies that have at least one hit to the AMR detection model. Default view includes percentages calculated based on Perfect plus Strict RGI hits. Select the checkbox to view percentages based on only Perfect matches to AMR reference sequences curated in CARD (note: this excludes resistance via mutation as references in protein variant models are often wild-type, sensitive sequences).
Model Definition: Protein Homolog Models (PHM) detect protein sequences based on their similarity to a curated reference sequence, using curated BLASTP bitscore cut-offs. Protein Homolog Models apply to all genes that confer resistance through their presence in an organism, such as the presence of a beta-lactamase gene on a plasmid. PHMs include a reference sequence and a bitscore cut-off for detection using BLASTP. A Perfect RGI match is 100% identical to the reference protein sequence along its entire length, a Strict RGI match is not identical but the bit-score of the matched sequence is greater than the curated BLASTP bit-score cutoff, Loose RGI matches have a bit-score less than the curated BLASTP bit-score cut-off.
