ArticleThe Journal of antimicrobial chemotherapy2020
Evaluation of a fully automated bioinformatics tool to predict antibiotic resistance from MRSA genomes.
Article in The Journal of antimicrobial chemotherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- The mutational landscape of Staphylococcus aureus during colonisation.Nature communications · 2025Article
- Evaluation of nationwide analysis surveillance for methicillin-resistantMicrobial genomics · 2025Article
- Evaluating the impact of genomic epidemiology of methicillin-resistantMicrobial genomics · 2024Article
- Benchmarking of two bioinformatic workflows for the analysis of whole-genome sequenced Staphylococcus aureus collected from patients with suspected sepsis.BMC infectious diseases · 2023Observational
- Article
- Antibiotic resistance profiles and population structure of disease-associatedMicrobiology (Reading, England) · 2021Article
- A common protocol for the simultaneous processing of multiple clinically relevant bacterial species for whole genome sequencing.Scientific reports · 2021Article
- Staphylococcus aureus whole genome sequence-based susceptibility and resistance prediction using a clinically amenable workflow.Diagnostic microbiology and infectious disease · 2020Article
- Cross-border spread ofEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2020Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesThe genetic prediction of phenotypic antibiotic resistance based on analysis of WGS data is becoming increasingly feasible, but a major barrier to its introduction into routine use is the lack of fully automated interpretation tools. Here, we report the findings of a large evaluation of the Next Gen Diagnostics (NGD) automated bioinformatics analysis tool to predict the phenotypic resistance of MRSA.
methodsMRSA-positive patients were identified in a clinical microbiology laboratory in England between January and November 2018. One MRSA isolate per patient together with all blood culture isolates (total n = 778) were sequenced on the Illumina MiniSeq instrument in batches of 21 clinical MRSA isolates and three controls.
resultsThe NGD system activated post-sequencing and processed the sequences to determine susceptible/resistant predictions for 11 antibiotics, taking around 11 minutes to analyse 24 isolates sequenced on a single sequencing run. NGD results were compared with phenotypic susceptibility testing performed by the clinical laboratory using the disc diffusion method and EUCAST breakpoints. Following retesting of discrepant results, concordance between phenotypic results and NGD genetic predictions was 99.69%. Further investigation of 22 isolate genomes associated with persistent discrepancies revealed a range of reasons in 12 cases, but no cause could be found for the remainder. Genetic predictions generated by the NGD tool were compared with predictions generated by an independent research-based informatics approach, which demonstrated an overall concordance between the two methods of 99.97%.
conclusionsWe conclude that the NGD system provides rapid and accurate prediction of the antibiotic susceptibility of MRSA.
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