An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance

• Published in: Nature communications Vol. 14; no. 1; pp. 60 - 12
• Main Authors: Sherry, Norelle L., Horan, Kristy A., Ballard, Susan A., Gonҫalves da Silva, Anders, Gorrie, Claire L., Schultz, Mark B., Stevens, Kerrie, Valcanis, Mary, Sait, Michelle L., Stinear, Timothy P., Howden, Benjamin P., Seemann, Torsten
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 04-01-2023; Nature Publishing Group; Nature Portfolio
• Subjects: 45/23; 631/326/107; 631/326/22/1434; 631/326/325/2482; 692/699/255/1318; Anti-Bacterial Agents - pharmacology; Antibiotics; Antimicrobial agents; Antimicrobial resistance; Bioinformatics; Computational Biology; Dilution; Drug resistance; Drug Resistance, Bacterial - genetics; Gene sequencing; Genomes; Genomics; Humanities and Social Sciences; Laboratories; Microbial Sensitivity Tests; Microbiology; multidisciplinary; Phenotypes; Public health; Science; Science (multidisciplinary); Surveillance; Whole genome sequencing; Workflow
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-35713-4

Realising the promise of genomics to revolutionise identification and surveillance of antimicrobial resistance (AMR) has been a long-standing challenge in clinical and public health microbiology. Here, we report the creation and validation of
abritAMR
, an ISO-certified bioinformatics platform for genomics-based bacterial AMR gene detection. The
abritAMR
platform utilises NCBI’s
AMRFinderPlus
, as well as additional features that classify AMR determinants into antibiotic classes and provide customised reports. We validate
abritAMR
by comparing with PCR or reference genomes, representing 1500 different bacteria and 415 resistance alleles. In these analyses,
abritAMR
displays 99.9% accuracy, 97.9% sensitivity and 100% specificity. We also compared genomic predictions of phenotype for 864
Salmonella
spp. against agar dilution results, showing 98.9% accuracy. The implementation of
abritAMR
in our institution has resulted in streamlined bioinformatics and reporting pathways, and has been readily updated and re-verified. The
abritAMR
tool and validation datasets are publicly available to assist laboratories everywhere harness the power of AMR genomics in professional practice.
The implementation of genomics for identification and surveillance of antimicrobial resistance (AMR) in clinical laboratories remains challenging. Here, Sherry et al. present a bioinformatics platform for detection of AMR determinants from whole-genome sequencing data, suitable for clinical and public-health microbiology reporting.