Rapid and High-throughput Identification of Recombinant Bacteria with Mass Spectrometry Assay

Objective To construct a rapid and high-throughput assay for identifying recombinant bacteria based on mass spectrometry. Methods Matrix assisted laser desorption ionization time-of-flight mass spectrometry （MALDI-TOF MS） techniques were used to identify 12 recombinant proteins （10 of Yersinia pesti...

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Published inBiomedical and environmental sciences Vol. 27; no. 4; pp. 250 - 258
Main Authors XIAO, Di, TAO, Xiao Xia, WANG, Peng, LIU, Guo Dong, GONG, Ya Nan, ZHANG, Hui Fang, WANG, Hai Bin, ZHANG, Jian Zhong
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.04.2014
Subjects
Bacterial Proteins - analysis
ClinProTools
Cloning, Molecular
Escherichia coli
MALDI-TOF
MALDI-TOF MS
Mass Spectrometry
Organisms, Genetically Modified
Peptide Mapping
Rapid identification
Recombinant bacteria
Recombinant Proteins - analysis
Specific peaks
分类模型
测定法
质谱法
重组菌
鉴定
高通量
鼠疫耶尔森氏菌
MALDI-TOF MS
Specific peaks
Rapid identification
Recombinant bacteria
ClinProTools
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Summary:Objective To construct a rapid and high-throughput assay for identifying recombinant bacteria based on mass spectrometry. Methods Matrix assisted laser desorption ionization time-of-flight mass spectrometry （MALDI-TOF MS） techniques were used to identify 12 recombinant proteins （10 of Yersinia pestis, 1 of Campylobacter jejuni and 1 of Helicobacter pylori）. A classification model for the various phase of recombinant bacteria was established, optimized and validated, using MALDI-TOF MS-CIinProTools system. The differences in the peptide mass spectra were analyzed by using Biotyper and FIexAnalysis softwares. Results Models of GA, SNN, and QC were established. After optimizing the parameters, the GA recognition model showed good classification capabilities： RC=100%, mean CVA=98.7% （the CVA was 96.4% in phase 1, 100% in phase 2, 98.4% in phase 3, and 100% in phase 4, respectively） and PPV=95}. This model can be used to classify the bacteria and their recombinant, which only requires 3.7x103 cells for analysis. The total time needed is only 10 min from protein extraction to reporting the result for one sample. Furthermore, this assay can automatically detect and test 96 samples concurrently. A total of 48 specific peaks （9, 16, 9, and 14 for the four stages, respectively） was found in the various phase of recombinant bacteria. Conclusion MALDI-TOF MS can be used as a fast, accurate, and high-throughput method to identify recombinant bacteria, which provide a new ideas not only for recombinant bacteria but also for the identification of mutant strains and bioterrorism pathogens.
Bibliography:XIAO Di, TAO Xiao Xia, WANG Peng, LIU Guo Dong, GONG Ya Nan, ZHANG Hui Fang, WANG Hai Bin, and ZHANG Jian Zhong（1. State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; 2. Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou 310003, Zhejiang, China; 3. Provincial Key Laboratory for Plague Control and Prevention, Yunnan Provincial Institute for Endemic Diseases Control and Prevention, Dali 671000, Yunnan, China; 4. Beijing Municipal Center for Disease Control and Prevention, Beijing 102206, China; 5. Chaoyang District Center for Disease Control and Prevention, Beijing 100021, China）
11-2816/Q
Recombinant bacteria; MALDI-TOF MS; ClinProTools; Rapid identification; Specific peaks
Objective To construct a rapid and high-throughput assay for identifying recombinant bacteria based on mass spectrometry. Methods Matrix assisted laser desorption ionization time-of-flight mass spectrometry （MALDI-TOF MS） techniques were used to identify 12 recombinant proteins （10 of Yersinia pestis, 1 of Campylobacter jejuni and 1 of Helicobacter pylori）. A classification model for the various phase of recombinant bacteria was established, optimized and validated, using MALDI-TOF MS-CIinProTools system. The differences in the peptide mass spectra were analyzed by using Biotyper and FIexAnalysis softwares. Results Models of GA, SNN, and QC were established. After optimizing the parameters, the GA recognition model showed good classification capabilities： RC=100%, mean CVA=98.7% （the CVA was 96.4% in phase 1, 100% in phase 2, 98.4% in phase 3, and 100% in phase 4, respectively） and PPV=95}. This model can be used to classify the bacteria and their recombinant, which only requires 3.7x103 cells for analysis. The total time needed is only 10 min from protein extraction to reporting the result for one sample. Furthermore, this assay can automatically detect and test 96 samples concurrently. A total of 48 specific peaks （9, 16, 9, and 14 for the four stages, respectively） was found in the various phase of recombinant bacteria. Conclusion MALDI-TOF MS can be used as a fast, accurate, and high-throughput method to identify recombinant bacteria, which provide a new ideas not only for recombinant bacteria but also for the identification of mutant strains and bioterrorism pathogens.
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0895-3988
2214-0190
DOI:10.3967/bes2014.048