Differential Diagnosis for Highly Pathogenic Avian Influenza Virus Using Nanoparticles Expressing Chemiluminescence
Highly pathogenic avian influenza (HPAI) virus is a causative agent of systemic disease in poultry, characterized by high mortality. Rapid diagnosis is crucial for the control of HPAI. In this study, we aimed to develop a differential diagnostic method that can distinguish HPAI from low pathogenic a...
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Veröffentlicht in: | Viruses 2021-06, Vol.13 (7), p.1274, Article 1274 |
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Sprache: | eng |
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Zusammenfassung: | Highly pathogenic avian influenza (HPAI) virus is a causative agent of systemic disease in poultry, characterized by high mortality. Rapid diagnosis is crucial for the control of HPAI. In this study, we aimed to develop a differential diagnostic method that can distinguish HPAI from low pathogenic avian influenza (LPAI) viruses using dual split proteins (DSPs). DSPs are chimeras of an enzymatic split, Renilla luciferase (RL), and a non-enzymatic split green fluorescent protein (GFP). Nanoparticles expressing DSPs, sialic acid, and/or transmembrane serine protease 2 (TMPRSS2) were generated, and RL activity was determined in the presence of HPAI or LPAI pseudotyped viruses. The RL activity of nanoparticles containing both DSPs was approximately 2 x 10(6) RLU, indicating that DSPs can be successfully incorporated into nanoparticles. The RL activity of nanoparticles containing half of the DSPs was around 5 x 10(1) RLU. When nanoparticles containing half of the DSPs were incubated with HPAI pseudotyped viruses at low pH, RL activity was increased up to 1 x 10(3) RLU. However, LPAI pseudotyped viruses produced RL activity only in the presence of proteases (trypsin or TMPRSS2), and the average RL activity was around 7 x 10(2) RLU. We confirmed that nanoparticle fusion assay also diagnoses authentic viruses with specificity of 100% and sensitivity of 91.67%. The data indicated that the developed method distinguished HPAI and LPAI, and suggested that the diagnosis using DSPs could be used for the development of differential diagnostic kits for HPAI after further optimization. |
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ISSN: | 1999-4915 1999-4915 |
DOI: | 10.3390/v13071274 |