Optimized Expression, Purification, and Rapid Detection of Recombinant Influenza Nucleoproteins Expressed in Sf9 Insect Cells
- Authors
- Yoon, Sung-Jin; Park, Young-Jun; Kim, Hyun Ju; Jang, Jinwoo; Lee, Sang Jun; Koo, Sunwoo; Lee, Moo-Seung
- Issue Date
- Oct-2018
- Publisher
- KOREAN SOC MICROBIOLOGY & BIOTECHNOLOGY
- Keywords
- Influenza; rapid detection test; influenza nucleoprotein; Sf9 cells
- Citation
- JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY, v.28, no.10, pp 1683 - 1690
- Pages
- 8
- Journal Title
- JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY
- Volume
- 28
- Number
- 10
- Start Page
- 1683
- End Page
- 1690
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/746
- DOI
- 10.4014/jmb.1805.05053
- ISSN
- 1017-7825
1738-8872
- Abstract
- Accurate and rapid diagnosis of influenza infection is essential to enable early antiviral treatment and reduce the mortality associated with seasonal and epidemic infections. Immunochromatography is one of the most common methods used for the diagnosis of seasonal human influenza; however, it is less effective in diagnosing pandemic influenza virus. Currently, rapid diagnostic kits for pandemic influenza virus rely on the detection of nucleoprotein (NP) or hemagglutinin (HA). NP detection shows higher specificity and is more sensitive than HA detection. In this study, we time-dependently screened expression conditions, and herein report optimal conditions for the expression of recombinant nucleoprotein (rNP), which was 48 h after infection. In addition, we report the use of the expressed rNP in a rapid influenza diagnostic test (SGT i-flex Influenza A&B Test). We constructed expression vectors that synthesized rNP (antigen) of influenza A and B in insect cells (Sf9 cells), employed the purified rNP to the immunoassay test kit, and clearly distinguished NPs of influenza A and influenza B using this rapid influenza diagnostic kit. This approach may improve the development of rapid test kits for influenza using NP.
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Collections - College of Biotechnology & Natural Resource > Department of Systems Biotechnology > 1. Journal Articles
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