The comprehensive antibiotic resistance database - PubMed (original) (raw)

. 2013 Jul;57(7):3348-57.

doi: 10.1128/AAC.00419-13. Epub 2013 May 6.

Nicholas Waglechner, Fazmin Nizam, Austin Yan, Marisa A Azad, Alison J Baylay, Kirandeep Bhullar, Marc J Canova, Gianfranco De Pascale, Linda Ejim, Lindsay Kalan, Andrew M King, Kalinka Koteva, Mariya Morar, Michael R Mulvey, Jonathan S O'Brien, Andrew C Pawlowski, Laura J V Piddock, Peter Spanogiannopoulos, Arlene D Sutherland, Irene Tang, Patricia L Taylor, Maulik Thaker, Wenliang Wang, Marie Yan, Tennison Yu, Gerard D Wright

Affiliations

The comprehensive antibiotic resistance database

Andrew G McArthur et al. Antimicrob Agents Chemother. 2013 Jul.

Abstract

The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.

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Figures

Fig 1

Fig 1

Presentation of the Staphylococcus aureus blaZ ß-lactamase gene in the CARD. (A) The gene's Web page in the CARD, providing annotation, accession, source information, ontological classification (SO, ARO, GO), and associated molecular features (mRNA, polypeptide, coding sequence [CDS]). (B) Dynamic browsing and analysis of the blaZ gene using the Web-based genome visualization and analysis tool GBrowse.

Fig 2

Fig 2

Classification of aminocoumarin-resistant gyrase B in the Antibiotic Resistance Ontology (ARO), illustrating the use of ontological relationships to describe knowledge about the gene (see Table 3). The is_a relationships are depicted by solid arrows labeled with “i” and generally denote classification hierarchies within the major branches of the ARO (mechanism, determinant, antibiotic, target), while dashed arrows labeled with “p” reflect part_of relationships between genes and mechanisms. Dashed arrows labeled with “d” depict derived_from relationships between antibiotic-sensitive precursors and antibiotic-resistant forms of the gene, while those labeled with “t” reflect targeted_by relationships between antibiotic-sensitive forms and antibiotic molecules. Dashed arrows labeled with “r” depict confers_resistance relationships between antibiotic resistance genes and antibiotic molecules. Asterisks denote a derived_from relationship between antibiotic-resistant and -sensitive DNA topoisomerase subunits.

Fig 3

Fig 3

Organization of aminoglycoside antibiotics (blue), their target (green), and aminoglycoside resistance genes (red) in the CARD's Antibiotic Resistance Ontology, illustrating the diversity of genes providing resistance to single or multiple aminoglycosides. Nodes represent ontology terms, while edges represent relationships between ontology terms.

Fig 4

Fig 4

An ontology term Web page for tetracycline resistance gene tetX (ARO:3000205) in the CARD, providing descriptive, ontological classification, sequence, protein structure, publication, taxonomic distribution, and bioinformatics data/model information. By providing an ontology-centered interface, the CARD offers a clearinghouse of information on antibiotic resistance genes, mechanisms, drugs, etc. The left column reflects ontological cross-referencing (see Materials and Methods).

Fig 5

Fig 5

Analysis of the whole genome of Acinetobacter baumannii strain TCDC-AB0715 by the Resistance Gene Identifier (RGI). The A. baumannii strain TCDC-AB0715 is a clinical isolate with resistance to carbapenems, fluoroquinolones, and cephalosporins (26). (A) “Resistance wheel” for A. baumannii strain TCDC-AB0715, predicting resistance to a broad range of antibiotic classes. (B) Details screen of orf0_267, illustrating detection of the aminoglycoside nucleotidyltransferase ANT(3″). (C) Open reading frame (ORF) map of a region of the A. baumannii strain TCDC-AB0715 chromosome, with prediction of β-lactamases TEM-1 and TEM-33 (light blue), aminoglycoside phosphotransferases, nucleotidyltransferases, and acetyltransferases (pink), chloramphenicol acetyltransferase (bright green), sulfonamide-resistant dihydropteroate synthase sul1 (dark green), tetracycline efflux pump tetB (dark pink), and genes implicated in general efflux (dark blue). ORFs unrelated to antibiotic resistance are presented in gray, while non-protein-coding regions are presented in black. The resistance genes identified are consistent with the reported resistance phenotype (26).

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