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通过基质辅助激光解吸电离飞行时间质谱快速检测K1高毒力肺炎克雷伯菌

Rapid Detection of K1 Hypervirulent Klebsiella pneumoniae by MALDI-TOF MS.

作者信息

Huang Yonglu, Li Jiaping, Gu Danxia, Fang Ying, Chan Edward W, Chen Sheng, Zhang Rong

机构信息

Department of Clinical Microbiology, Second Affiliated Hospital of Zhejiang University Hangzhou, China.

Shenzhen Key Lab for Food Biological Safety Control, Food Safety and Technology Research Center, Hong Kong PolyU Shenzhen Research InstituteShenzhen, China; State Key Lab of Chirosciences, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic UniversityHong Kong, China.

出版信息

Front Microbiol. 2015 Dec 21;6:1435. doi: 10.3389/fmicb.2015.01435. eCollection 2015.

Abstract

Hypervirulent strains of Klebsiella pneumoniae (hvKP) are genetic variants of K. pneumoniae which can cause life-threatening community-acquired infection in healthy individuals. Currently, methods for efficient differentiation between classic K. pneumoniae (cKP) and hvKP strains are not available, often causing delay in diagnosis and treatment of hvKP infections. To address this issue, we devised a Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) approach for rapid identification of K1 hvKP strains. Four standard algorithms, genetic algorithm (GA), support vector machine (SVM), supervised neural network (SNN), and quick classifier (QC), were tested for their power to differentiate between K1 and non-K1 strains, among which SVM was the most reliable algorithm. Analysis of the receiver operating characteristic curves of the interest peaks generated by the SVM model was found to confer highly accurate detection sensitivity and specificity, consistently producing distinguishable profiles for K1 hvKP and non-K1 strains. Of the 43 K. pneumoniae modeling strains tested by this approach, all were correctly identified as K1 hvKP and non-K1 capsule type. Of the 20 non-K1 and 17 K1 hvKP validation isolates, the accuracy of K1 hvKP and non-K1 identification was 94.1 and 90.0%, respectively, according to the SVM model. In summary, the MALDI-TOF MS approach can be applied alongside the conventional genotyping techniques to provide rapid and accurate diagnosis, and hence prompt treatment of infections caused by hvKP.

摘要

高毒力肺炎克雷伯菌(hvKP)菌株是肺炎克雷伯菌的基因变体,可在健康个体中引起危及生命的社区获得性感染。目前,尚无有效区分经典肺炎克雷伯菌(cKP)和hvKP菌株的方法,这常常导致hvKP感染的诊断和治疗延迟。为解决这一问题,我们设计了一种基质辅助激光解吸/电离飞行时间(MALDI-TOF)质谱(MS)方法,用于快速鉴定K1 hvKP菌株。测试了四种标准算法,即遗传算法(GA)、支持向量机(SVM)、监督神经网络(SNN)和快速分类器(QC)区分K1和非K1菌株的能力,其中SVM是最可靠的算法。对SVM模型生成的感兴趣峰进行的受试者工作特征曲线分析显示,其具有高度准确的检测灵敏度和特异性,始终能为K1 hvKP和非K1菌株生成可区分的图谱。用这种方法测试的43株肺炎克雷伯菌建模菌株均被正确鉴定为K1 hvKP和非K1荚膜型。根据SVM模型,在20株非K1和17株K1 hvKP验证分离株中,K1 hvKP和非K1鉴定的准确率分别为94.1%和90.0%。总之,MALDI-TOF MS方法可与传统基因分型技术一起应用,以提供快速准确的诊断,从而及时治疗由hvKP引起的感染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6bd/4685062/85aeb62b9d09/fmicb-06-01435-g0001.jpg

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