WGS to predict antibiotic MICs for Neisseria gonorrhoeae
| العنوان: | WGS to predict antibiotic MICs for Neisseria gonorrhoeae |
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| المؤلفون: | Eyre, D, De Silva, D, Cole, K, Peters, J, Cole, MJ, Grad, YH, Demczuk, W, Martin, I, Mulvey, MR, Crook, DW, Walker, AS, Peto, T, Paul, J |
| المصدر: | Journal of Antimicrobial Chemotherapy. |
| سنة النشر: | 2017 |
| الوصف: | Background: Tracking the spread of antimicrobial resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. Objectives: We investigate whether whole-genome sequencing, WGS, and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of minimum inhibitory concentrations, MICs, in N. gonorrhoeae. Methods: WGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin, and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross validation. Results: Overall 1785/3380(53%) MIC values were predicted to the nearest doubling dilution, and 3147(93%) within ±1 and 3314(98%) within ±2 doubling-dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error rate (VME, phenotypically resistant, WGS-prediction sensitive) was 21/1577(1.3%, 95%CI 0.8-2.0%), and the major error rate (ME, phenotypically sensitive, WGS-prediction resistant) was 20/1186(1.7%, 1.0-2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all 5 antimicrobials. Conclusions: We demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species. |
| اللغة: | English |
| تدمد: | 1460-2091 0305-7453 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6fc6140be08f4d075ec6bd0cc5055605 http://ora.ox.ac.uk/objects/uuid: |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.dedup.wf.001..6fc6140be08f4d075ec6bd0cc5055605 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14602091 03057453 |
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