Development of a method based on surface enhanced laser desorption and ionization time of flight mass spectrometry for rapid identification of Klebsiella pneumoniae

被引：4

作者：

Xiao, Daiwen ^{[1
,2
]}

Yang, Yongchang ^{[1
,2
]}

Liu, Hua ^{[1
,2
]}

Yu, Hua ^{[1
,2
]}

Yan, Yingjun ^{[1
,2
]}

Huang, Wenfang ^{[1
,2
]}

Jiang, Wei ^{[1
,2
]}

Liao, Weijin ^{[1
,2
]}

Hu, Qi ^{[3
]}

Huang, Bo ^{[3
]}

机构：

[1] Sichuan Acad Med Sci, Clin Lab Dept, Chengdu 610072, Peoples R China

[2] Sichuan Prov Peoples Hosp, Chengdu 610072, Peoples R China

[3] Chongqing Med Univ, Dept Lab Med, Chongqing 400016, Peoples R China

来源：

JOURNAL OF MICROBIOLOGY | 2009年 / 47卷 / 05期

关键词：

identification; K; pneumoniae; SELDI-TOF MS; ARTIFICIAL NEURAL-NETWORKS; MALDI-TOF MS; CLASSIFICATION; BIOMARKERS; BACTERIA; STRAINS; LAVAGE; LEVEL; GENE; DNAJ;

D O I：

10.1007/s12275-009-0092-z

中图分类号：

Q93 [微生物学];

学科分类号：

071005 ; 100705 ;

摘要：

A method based on surface enhanced laser desorption and ionization time of flight mass spectrometry (SELDI-TOF MS) was developed for the rapid identification of Klebsiella pneumoniae by directly applying bacterial colonies without further protein extraction. A total of 40 K. pneumoniae and 114 other related microorganisms isolated clinically were analyzed by SELDI-TOF MS. An identification model for K. pneumoniae was established by artificial neural networks (ANNs) with classification accuracy of 100%. The model was blindly tested with 43 K. pneumoniae and 53 control bacteria again. The results showed that the model was successful with accuracy of 96.9%, sensitivity of 100% and specificity of 943%. This strategy is potential for rapid identification of K. pneumoniae.

引用

页码：646 / 650

页数：5

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