Irene Pena1, Eduardo Pena-Vina2, Iciar Rodriguez-Avial3, Juan J Picazo4, Álvaro Gómez-González5, Esther Culebras6. 1. Servicio de Microbiología, Complejo Hospitalario Universitario de Vigo (CHUVI), Vigo, Spain. 2. Alisio Computing GmbH, Kaiserslautern, Germany. 3. Servicio de Microbiología Clínica, Hospital Clínico San Carlos, IdISCC and IML Institutes, Germany. 4. Departamento de Medicina, Facultad de Medicina, Universidad Complutense, Madrid, Spain. 5. BD Integrated Diagnostic Solutions, San Agustín de Guadalix, Madrid, Spain. 6. Servicio de Microbiología Clínica, Hospital Clínico San Carlos, IdISCC and IML Institutes, Germany; Departamento de Medicina, Facultad de Medicina, Universidad Complutense, Madrid, Spain. Electronic address: esther.culebras@salud.madrid.org.
Abstract
INTRODUCTION: The rapid identification and detection of carbapenemase-producing Klebsiella pneumoniae (CPKP) isolates is crucial to ascertain outbreaks, as well as to limit their spread. The current reference method for this purpose is multilocus sequence typing (MLST), which is laborious and expensive. Consequently, alternative typing methods are gaining attention, such as Matrix-Assisted Laser Desorption Ionization-Time Of Flight Mass Spectrometry (MALDI-TOF MS). METHODS: This study sought to analyze MALDI-TOF MS as a typing method using 44 CPKP isolates that were well characterized by MLST. The most common types of samples from which these pathogens were isolated were skin and soft tissues (32%) and urine (29%). Half of the CPKP isolates were from hospitalized patients. Two approaches were followed for the analysis of the mass peak data obtained by MALDI-TOF MS. The first using all peaks obtained and the second using a selection of 21 characteristic peaks. RESULTS: The selection of 21 characteristic peaks showed greater discrimination power for ST11 and ST101. Principal component analysis (PCA) indicated that this dataset could be efficiently grouped with lineal classifiers. A Support Vector Machine (SVM) was chosen for this purpose after checking its capacity to classify bacterial strains on the basis of MALDI-TOF MS information. CONCLUSION: SVM was able to discriminate between ST11 and ST101 with high accuracy. In conclusion, our results reveal MALDI-TOF MS as a promising alternative technique for typing of CPKP isolates.
INTRODUCTION: The rapid identification and detection of carbapenemase-producing Klebsiella pneumoniae (CPKP) isolates is crucial to ascertain outbreaks, as well as to limit their spread. The current reference method for this purpose is multilocus sequence typing (MLST), which is laborious and expensive. Consequently, alternative typing methods are gaining attention, such as Matrix-Assisted Laser Desorption Ionization-Time Of Flight Mass Spectrometry (MALDI-TOF MS). METHODS: This study sought to analyze MALDI-TOF MS as a typing method using 44 CPKP isolates that were well characterized by MLST. The most common types of samples from which these pathogens were isolated were skin and soft tissues (32%) and urine (29%). Half of the CPKP isolates were from hospitalized patients. Two approaches were followed for the analysis of the mass peak data obtained by MALDI-TOF MS. The first using all peaks obtained and the second using a selection of 21 characteristic peaks. RESULTS: The selection of 21 characteristic peaks showed greater discrimination power for ST11 and ST101. Principal component analysis (PCA) indicated that this dataset could be efficiently grouped with lineal classifiers. A Support Vector Machine (SVM) was chosen for this purpose after checking its capacity to classify bacterial strains on the basis of MALDI-TOF MS information. CONCLUSION: SVM was able to discriminate between ST11 and ST101 with high accuracy. In conclusion, our results reveal MALDI-TOF MS as a promising alternative technique for typing of CPKP isolates.