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Discrimination of influenza A virus subtypes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry
被引:0
|作者:
Han, Guobin
[1
,2
]
Liu, Lukuan
[1
,3
]
Sui, Zhigang
[1
]
Zhou, Wen
[1
,4
]
Jiang, Bo
[1
]
Yang, Kaiguang
[1
,5
]
Zhang, Lihua
[1
,5
]
Liang, Zhen
[1
]
Zhang, Yukui
[1
]
机构:
[1] Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China
[2] Fudan Univ, Dept Chem, Shanghai 200000, Peoples R China
[3] Dalian Med Univ, Affiliated Hosp 1, Stem Cell Clin Res Ctr, Dalian 116011, Peoples R China
[4] Univ Chinese Acad Sci, Beijing 100039, Peoples R China
[5] Chinese Acad Sci, Dalian Inst Chem Phys, Dalian 116023, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Influenza A virus;
MALDI-TOF MS;
Virus database;
Virus genotyping;
REVERSE TRANSCRIPTION PCR;
IDENTIFICATION;
D O I:
10.1016/j.ijms.2022.116979
中图分类号:
O64 [物理化学(理论化学)、化学物理学];
O56 [分子物理学、原子物理学];
学科分类号:
070203 ;
070304 ;
081704 ;
1406 ;
摘要:
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 distin-guished. More importantly, this strategy provides an alternative method for identifying and dis-tinguishing other viruses with high variability characteristics, such as SARS-CoV-2, which could be helpful for implementing public health strategies to counter pandemics.(c) 2022 Elsevier B.V. All rights reserved.
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