title: Rapid Detection of Vancomycin-Intermediate Staphylococcus aureus by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.
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.
authors.affiliation: Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA Department of Anatomic Pathology, University of Washington, Seattle, Washington, USA.
authors.forename: Cheryl A
authors.initials: CA
authors.lastname: Mather
authors.affiliation: Department of Pharmacy, University of Washington School of Pharmacy, Seattle, Washington, USA.
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Werth
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
authors.forename: Shobini
authors.initials: S
authors.lastname: Sivagnanam
authors.affiliation: Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
authors.forename: Dhruba J
authors.initials: DJ
authors.lastname: SenGupta
authors.affiliation: Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA butlerwu@usc.edu.
authors.forename: Susan M
authors.initials: SM
authors.lastname: Butler-Wu
mesh_terms: D006801:Humans; D000069550:Machine Learning; D008826:Microbial Sensitivity Tests / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D013211:Staphylococcus aureus / Q000737:chemistry* / Q000145:classification* / Q000187:drug effects / Q000302:isolation & purification; D013997:Time Factors; D020713:Vancomycin Resistance