Pena Irene, Pena-Vina Eduardo, Rodriguez-Avial Iciar, Picazo Juan J, Gómez-González Álvaro, Culebras Esther
Servicio de Microbiología, Complejo Hospitalario Universitario de Vigo (CHUVI), Vigo, Spain.
Alisio Computing GmbH, Kaiserslautern, Germany.
Enferm Infecc Microbiol Clin (Engl Ed). 2020 Dec 15. doi: 10.1016/j.eimc.2020.10.018.
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).
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.
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.
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.
快速鉴定和检测产碳青霉烯酶肺炎克雷伯菌（CPKP）分离株对于确定疫情爆发以及限制其传播至关重要。目前用于此目的的参考方法是多位点序列分型（MLST），该方法既费力又昂贵。因此，替代分型方法如基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）正受到关注。
本研究旨在分析MALDI-TOF MS作为一种分型方法，使用44株经MLST充分鉴定的CPKP分离株。分离出这些病原体的最常见样本类型是皮肤和软组织（32%）以及尿液（29%）。一半的CPKP分离株来自住院患者。采用两种方法分析通过MALDI-TOF MS获得的质谱峰数据。第一种方法使用获得的所有峰，第二种方法使用选择的21个特征峰。
选择21个特征峰对ST11和ST101显示出更大鉴别力。主成分分析（PCA）表明该数据集可以通过线性分类器有效分组。在检查其基于MALDI-TOF MS信息对细菌菌株进行分类的能力后，为此选择了支持向量机（SVM）。
SVM能够高精度地区分ST11和ST101。总之，我们的结果表明MALDI-TOF MS是一种用于CPKP分离株分型的有前景的替代技术。
