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Matrix-Assisted Laser Desorption Ionization: Time of Flight Mass Spectrometry-Identified Models for Detection of ESBL-Producing Bacterial Strains

BACKGROUND: The increase in the amount of extended spectrum beta-lactamases (ESBL)-producing gram-negative bacteria is seriously threatening human health in recent years. Therefore, it is necessary to develop a rapid and reliable method for identification of ESBLs. The purpose of this study was to e...

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Detalles Bibliográficos
Autores principales: Li, Bo, Guo, Tongsheng, Qu, Fen, Li, Boan, Wang, Haibin, Sun, Zhiqiang, Li, Xiaohan, Gao, Zhiqiang, Bao, Chunmei, Zhang, Chenglong, Li, Xiaoxi, Mao, Yuanli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4242706/
https://www.ncbi.nlm.nih.gov/pubmed/25390932
http://dx.doi.org/10.12659/MSMBR.892670
Descripción
Sumario:BACKGROUND: The increase in the amount of extended spectrum beta-lactamases (ESBL)-producing gram-negative bacteria is seriously threatening human health in recent years. Therefore, it is necessary to develop a rapid and reliable method for identification of ESBLs. The purpose of this study was to establish a novel method to discriminate between ESBL-producing and non- ESBL-producing bacteria by using the matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) technique. MATERIAL/METHODS: We detected hydrolyzed production of cefotaxime after incubation with 69 gram-negative bacteria by using MALDI-TOF-MS. Then we established genetic algorithm (GA), supervised neural networks (SNN), and quick classifier (QC) models using several peaks to identify ESBL-producing strains. To confirm the clinical applicability of the models established, a blinded validation test was performed in 34 clinical isolated strains. RESULTS: Using ClinPro Tools software, we identified 4 peaks (456 Da, 396 Da, 370 Da, and 371 Da) in mass spectra of cefotaxime solution that have high enough specificity to discriminate ESBL-producing from non- ESBL-producing strains. Recognition capability of models established were 97.5% (GA), 92.5% (SNN), and 92.5% (QC), and cross validation rates were 90.15% (GA), 97.62 (SNN), and 97.62% (QC). The accuracy rates of the blinded validation test were 82.4% (GA), 88.2% (SNN), and 82.4% (QC). CONCLUSIONS: Our results demonstrate that identification of ESBLs strains by MALDI-TOF-MS has potential clinical value and could be widely used in the future as a routine test in clinical microbiology laboratories.