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Bo Li, Tongsheng Guo, Fen Qu, Boan Li, Haibin Wang, Zhiqiang Sun, Xiaohan Li, Zhiqiang Gao, Chunmei Bao, Chenglong Zhang, Xiaoxi Li, Yuanli Mao
(Graduate Student Team, Chinese PLA Postgraduate Medical School, Beijing, China (mainland))
Med Sci Monit Basic Res 2014; 20:176-183
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 and 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.