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Discrimination of influenza A virus subtypes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
- Source :
-
International Journal of Mass Spectrometry . Feb2023, Vol. 484, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
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Abstract
- Influenza is a contagious respiratory illness caused by influenza viruses which possess the enormous threat to older people and young children. Rapid and precise discrimination of virus subtypes are quite crucial for the early therapy, prophylaxis and the prevention of epidemic outbreaks. Herein, a universal strategy, with influenza A virus (IAV) as a model, is proposed for the discrimination of virus subtypes based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Reference library based on nine IAVs subtypes (i.e., H1N1, H3N2, H4N8, H5N8, H6N6, H7N7, H9N2, H10N8, and H11N8) was set up for matching various IAVs subtypes. The simulative test spectra from IAVs showed that the corresponding IAVs subtypes could be distinguished in 90 min, accurately. Furthermore, the principal component analysis results also show that nine virus subtypes can be reliably distinguished. More importantly, this strategy provides an alternative method for identifying and distinguishing other viruses with high variability characteristics, such as SARS-CoV-2, which could be helpful for implementing public health strategies to counter pandemics. A MALDI-TOF MS based universal strategy for the discrimination of virus subtypes was developed, which possess the advantages of speed and high-accuracy. [Display omitted] • A home-made identification database of influenza A virus subtypes was set up. • The discrimination of influenza A virus subtypes could be finished within 90 min. • The influenza A virus subtypes could be distinguished with high accuracy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13873806
- Volume :
- 484
- Database :
- Academic Search Index
- Journal :
- International Journal of Mass Spectrometry
- Publication Type :
- Academic Journal
- Accession number :
- 161059799
- Full Text :
- https://doi.org/10.1016/j.ijms.2022.116979