Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is one of the major pathogens responsible for nosocomial infections. The presence of MRSA in a hospital is detrimental to patients and to hospital management. Thus, rapid identification of MRSA is needed. Here, we report on a prospective method to rapidly discriminate of MSSA from MRSA using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and support vector machine (SVM) analysis in 160 clinical isolates of S. aureus. The predictive model was tested using 100 S. aureus isolates (50 MSSA and 50 MRSA). The identification rates were 90.0% for MSSA and 87.5% for MRSA in a 10-fold cross-validation SVM. In blind test sets, 60 S. aureus isolates (30 MSSA and 30 MRSA) were correctly classified, with identification rates of 93.3% for MSSA and 86.7% for MRSA. The method proposed in this study using the predictive model enables detection of one colony in 5 minutes, and thus is useful at clinical sites at which rapid discrimination of MRSA from MSSA is required.
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