Mass Spectrometry-Based System for Identifying and Typing Norovirus Major Capsid Protein VP1
Norovirus-associated diseases are the most common foodborne illnesses worldwide. Polymerase chain reaction-based methods are the primary diagnostics for clinical samples; however, the high mutation rate of norovirus makes viral amplification and genotyping challenging. Technological advances in mass...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/8dfc6420a92b4e24989c7a6b0d16b9f9 |
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| Sumario: | Norovirus-associated diseases are the most common foodborne illnesses worldwide. Polymerase chain reaction-based methods are the primary diagnostics for clinical samples; however, the high mutation rate of norovirus makes viral amplification and genotyping challenging. Technological advances in mass spectrometry (MS) make it a promising tool for identifying disease markers. Besides, the superior sensitivity of MS and proteomic approaches may enable the detection of all variants. Thus, this study aimed to establish an MS-based system for identifying and typing norovirus. We constructed three plasmids containing the major capsid protein VP1 of the norovirus GII.4 2006b, 2006a, and 2009a strains to produce virus-like particles for use as standards. Digested peptide signals were collected using a nano-flow ultra-performance liquid chromatography mass spectrometry (nano-UPLC/MS<sup>E</sup>) system, and analyzed by ProteinLynx Global SERVER and TREE-PUZZLE software. Results revealed that the LC/MS<sup>E</sup> system had an excellent coverage rate: the system detected more than 94% of amino acids of 3.61 femtomole norovirus VP1 structural protein. In the likelihood-mapping analysis, the proportions of unresolved quartets were 2.9% and 4.9% in the VP1 and S domains, respectively, which is superior to the 15.1% unresolved quartets in current PCR-based methodology. In summary, the use of LC/MS<sup>E</sup> may efficiently monitor genotypes, and sensitively detect structural and functional mutations of noroviruses. |
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