ArticleJournal of clinical microbiology2014
Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing.
Article in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 185 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
185 citing papers in PubMed, 3 syntheses or guidelines pooled it, 346 citations in OpenAlex.
- The global prevalence of fusidic acid resistance in clinical isolates of Staphylococcus aureus: a systematic review and meta-analysis.Antimicrobial resistance and infection control · 2021Pooled it
- Large-scale assessment of antimicrobial resistance marker databases for genetic phenotype prediction: a systematic review.The Journal of antimicrobial chemotherapy · 2020Pooled it
- Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.PLoS computational biology · 2019Pooled it
- Genomic Characterization of Colistin and Fluoroquinolone Resistance in Multidrug-ResistantAntibiotics (Basel, Switzerland) · 2026Article
- Antibiotic-Specific Genotype-Phenotype Concordance and Cross-Database Interoperability in PublicInternational journal of molecular sciences · 2026Article
- Comparative genomics of methicillin-resistant and -susceptibleMicrobiology spectrum · 2026Article
- Integrated Phenotypic and Genomic Characterization of Cefotaxime/Clavulanic Acid Inhibitor-Positive Multidrug-ResistantAnimals : an open access journal from MDPI · 2026Article
- The Brief Case: Adjudication of discrepant genotypic and phenotypic antimicrobial susceptibility testing results in a patient withJournal of clinical microbiology · 2026Review
- Genetic and clinical landscape of methicillin-resistantJAC-antimicrobial resistance · 2026Article
- Comparative genomic analysis ofFrontiers in public health · 2026Article
- Prevalence and whole genome sequencing analysis of Salmonella isolated from a homebred chicken farm in Jiangsu province.Frontiers in veterinary science · 2026Article
- stackPredAMR-a stacked random forest approach improves AMR phenotype prediction for multiple species and antimicrobial agents.Bioinformatics advances · 2026Article
- Comparative Evaluation of Sequencing Technologies for Detecting Antimicrobial Resistance in Bloodstream Infections.Antibiotics (Basel, Switzerland) · 2025Review
- Genomic Insights into Multidrug-resistant Mammaliicoccus sciuri Carrying Novel Staphylococcal Cassette Chromosome mec (SCCmec) Elements and Plasmids from Farm Ruminants on the East Coast of Peninsular Malaysia.Current microbiology · 2025Article
- Review
- Prediction of antimicrobial resistance inMicrobiology spectrum · 2025Article
- Metagenomic Next-Generation Sequencing in Infectious Diseases: Clinical Applications, Translational Challenges, and Future Directions.Diagnostics (Basel, Switzerland) · 2025Review
- Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions forMicrobiology spectrum · 2025Article
- Genomics for antimicrobial resistance-progress and future directions.Antimicrobial agents and chemotherapy · 2025Review
- Proceedings of the Clinical Microbiology Open 2024: artificial intelligence applications in clinical microbiology.Journal of clinical microbiology · 2025Article
125 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
Abstract
Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.