Abstract
Objectives: The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly available web-based AMR databases, whole-genome sequencing (WGS) offers the capacity for rapid detection of AMR genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility test results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) clinical isolates using publicly available tools and databases. Methods: Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. The AMR gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between the WGS-predicted resistance profile and phenotypic susceptibility as well as the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for each antibiotic/organism combination, using the phenotypic results as gold standard. Results: Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3%, with a sensitivity, specificity, PPV and NPV of 98.7% (95% CI 97.2–99.5%), 99.6% (95% CI 98.8–99.9%), 99.3% (95% CI 98.0–99.8%) and 99.2% (95% CI 98.3–99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4%, sensitivity to 99.3% (95% CI 98.2–99.8%) and NPV to 99.4% (95% CI 98.4–99.8%). Conclusion: WGS can be used as a reliable predicator of phenotypic resistance both for MRSA and VRE using readily available online tools.
| Original language | English |
|---|---|
| Pages (from-to) | 136-143 |
| Number of pages | 8 |
| Journal | Journal of Global Antimicrobial Resistance |
| Volume | 19 |
| DOIs | |
| Publication status | Published - 12-2019 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Microbiology
- Immunology and Allergy
- Immunology
- Microbiology (medical)
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