Title |
Multiplex Reverse Transcription-PCR for Simultaneous Surveillance of Influenza A and B Viruses
|
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Published in |
Journal of Clinical Microbiology, October 2017
|
DOI | 10.1128/jcm.00957-17 |
Pubmed ID | |
Authors |
Bin Zhou, Yi-Mo Deng, John R. Barnes, October M. Sessions, Tsui-Wen Chou, Malania Wilson, Thomas J. Stark, Michelle Volk, Natalie Spirason, Rebecca A. Halpin, Uma Sangumathi Kamaraj, Tao Ding, Timothy B. Stockwell, Mirella Salvatore, Elodie Ghedin, Ian G. Barr, David E. Wentworth |
Abstract |
Influenza A and B viruses are the causative agents of annual influenza epidemics that can be severe; influenza A viruses intermittently cause pandemics. Sequence information from influenza genomes is instrumental in determining mechanisms underpinning antigenic evolution and antiviral resistance. However, due to sequence diversity and the dynamics of influenza evolution, rapid and high-throughput sequencing of influenza viruses remains a challenge. We developed a single-reaction FluA/B Multiplex RT-PCR method that amplifies the most critical genomic segments (HA, NA, and M) of seasonal influenza A and B viruses for next-generation sequencing, regardless of viral types, subtypes, or lineages. Herein we demonstrate that the strategy is highly sensitive and robust. The strategy was validated on thousands of seasonal influenza A and B virus positive specimens using multiple next-generation sequencing platforms. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 46 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 10 | 22% |
Researcher | 6 | 13% |
Student > Ph. D. Student | 4 | 9% |
Student > Bachelor | 4 | 9% |
Student > Doctoral Student | 2 | 4% |
Other | 7 | 15% |
Unknown | 13 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 7 | 15% |
Biochemistry, Genetics and Molecular Biology | 7 | 15% |
Immunology and Microbiology | 5 | 11% |
Veterinary Science and Veterinary Medicine | 4 | 9% |
Medicine and Dentistry | 3 | 7% |
Other | 5 | 11% |
Unknown | 15 | 33% |