Rapid Detection of Vancomycin-Intermediate Staphylococcus aureus by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

利用基质辅助激光解吸电离飞行时间质谱法快速检测万古霉素中介金黄色葡萄球菌

阅读:1

Abstract

Vancomycin is the standard of care for the treatment of invasive methicillin-resistantStaphylococcus aureus(MRSA) infections. Infections with vancomycin-nonsusceptible MRSA, including vancomycin-intermediateS. aureus(VISA) and heterogeneous VISA (hVISA), are clinically challenging and are associated with poor patient outcomes. The identification of VISA in the clinical laboratory depends on standard susceptibility testing, which takes at least 24 h to complete after isolate subculture, whereas hVISA is not routinely detected in clinical labs. We therefore sought to determine whether VISA and hVISA can be differentiated from vancomycin-susceptibleS. aureus(VSSA) using the spectra produced by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Strains of MRSA were characterized for vancomycin susceptibility phenotype by broth microdilution and modified population analysis. We tested 21 VISA, 21 hVISA, and 38 VSSA isolates by MALDI-TOF MS. Susceptibility phenotypes were separated by using a support vector machine (SVM) machine learning algorithm. The resulting model was validated by leave-one-out cross validation. Models were developed and validated by using spectral profiles generated under various subculture conditions, as well as with and without hVISA strains. Using SVM, we correctly identified 100% of the VISA and 97% of the VSSA isolates with an overall classification accuracy of 98%. Addition of hVISA to the model resulted in 76% hVISA identification, 100% VISA identification, and 89% VSSA identification, for an overall classification accuracy of 89%. We conclude that VISA/hVISA and VSSA isolates are separable by MALDI-TOF MS with SVM analysis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。