Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis
Background and Objective. Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Pseudomonas aeruginosa, and Mycobacterium tuberculosis are primary respiratory bacterial pathogens contributing to morbidity and mortal...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Canadian Journal of Infectious Diseases and Medical Microbiology |
| Online Access: | http://dx.doi.org/10.1155/2020/2697230 |
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| _version_ | 1832566334617026560 |
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| author | Liuyang Hu Bing Han Qin Tong Hui xiao Donglin Cao |
| author_facet | Liuyang Hu Bing Han Qin Tong Hui xiao Donglin Cao |
| author_sort | Liuyang Hu |
| collection | DOAJ |
| description | Background and Objective. Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Pseudomonas aeruginosa, and Mycobacterium tuberculosis are primary respiratory bacterial pathogens contributing to morbidity and mortality in developing countries. This study evaluated the diagnostic performance of multiplex real-time PCR with fluorescence melting curve analysis (MCA) assay, which was used to detect eight respiratory bacterial pathogens simultaneously. Methods. A total of 157 sputum specimens were examined by multiplex real-time with fluorescence MCA, and the results were compared with the conventional culture method. Results. Multiplex real-time PCR with fluorescence MCA specifically detected and differentiated eight respiratory bacterial pathogens by different melting curve peaks for each amplification product within 2 hours and exhibited high repeatability. The limit of detection ranged from 64 to 102 CFU/mL in the multiplex PCR system. Multiplex real-time PCR with fluorescence MCA showed a sensitivity greater than 80% and a 100% specificity for each pathogen. The kappa correlation of eight bacteria ranged from 0.89 to 1.00, and the coefficient of variation ranged from 0.05% to 0.80%. Conclusions. Multiplex real-time PCR with fluorescence MCA assay is a sensitive, specific, high-throughput, and cost-effective method to detect multiple bacterial pathogens simultaneously. |
| format | Article |
| id | doaj-art-4d402677e17a42f2963606f538f4ce7d |
| institution | Kabale University |
| issn | 1712-9532 1918-1493 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Canadian Journal of Infectious Diseases and Medical Microbiology |
| spelling | doaj-art-4d402677e17a42f2963606f538f4ce7d2025-02-03T01:04:19ZengWileyCanadian Journal of Infectious Diseases and Medical Microbiology1712-95321918-14932020-01-01202010.1155/2020/26972302697230Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve AnalysisLiuyang Hu0Bing Han1Qin Tong2Hui xiao3Donglin Cao4Department of Laboratory Medicine, Guangdong Second Provincial General Hospital, Guangzhou 510317, ChinaDepartment of Laboratory Medicine, Guangdong Second Provincial General Hospital, Guangzhou 510317, ChinaShenzhen Longhua District Central Hospital, Shenzhen 518110, ChinaGuangzhou Baochuang Biotechnology Co., Ltd., Guangzhou 510336, ChinaDepartment of Laboratory Medicine, Guangdong Second Provincial General Hospital, Guangzhou 510317, ChinaBackground and Objective. Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Pseudomonas aeruginosa, and Mycobacterium tuberculosis are primary respiratory bacterial pathogens contributing to morbidity and mortality in developing countries. This study evaluated the diagnostic performance of multiplex real-time PCR with fluorescence melting curve analysis (MCA) assay, which was used to detect eight respiratory bacterial pathogens simultaneously. Methods. A total of 157 sputum specimens were examined by multiplex real-time with fluorescence MCA, and the results were compared with the conventional culture method. Results. Multiplex real-time PCR with fluorescence MCA specifically detected and differentiated eight respiratory bacterial pathogens by different melting curve peaks for each amplification product within 2 hours and exhibited high repeatability. The limit of detection ranged from 64 to 102 CFU/mL in the multiplex PCR system. Multiplex real-time PCR with fluorescence MCA showed a sensitivity greater than 80% and a 100% specificity for each pathogen. The kappa correlation of eight bacteria ranged from 0.89 to 1.00, and the coefficient of variation ranged from 0.05% to 0.80%. Conclusions. Multiplex real-time PCR with fluorescence MCA assay is a sensitive, specific, high-throughput, and cost-effective method to detect multiple bacterial pathogens simultaneously.http://dx.doi.org/10.1155/2020/2697230 |
| spellingShingle | Liuyang Hu Bing Han Qin Tong Hui xiao Donglin Cao Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis Canadian Journal of Infectious Diseases and Medical Microbiology |
| title | Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis |
| title_full | Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis |
| title_fullStr | Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis |
| title_full_unstemmed | Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis |
| title_short | Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis |
| title_sort | detection of eight respiratory bacterial pathogens based on multiplex real time pcr with fluorescence melting curve analysis |
| url | http://dx.doi.org/10.1155/2020/2697230 |
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