Prediction and identification of linear B-cell epitopes in the hemagglutinin of H7N9 avian influenza virus in human / 中华临床感染病杂志
Chinese Journal of Clinical Infectious Diseases
; (6): 336-341,348, 2016.
Article
en Zh
| WPRIM
| ID: wpr-604691
Biblioteca responsable:
WPRO
ABSTRACT
Objective To predict and identify liner B-cell epitopes in the hemagglutinin ( HA) of human-infected avian-origin H7N9 influenza virus and analyze the specificity of H7 subtype.Methods Three serum samples collected at different times from the same patient who was confirmed to be infected with H7N9 influenza virus were provided by Shaoxing People’s Hospital, and one serum sample from healthy person was collected as the control.The extracellular region of HA protein was predicted by TMHMM Sever v.2.0.The potential B-cell epitopes were predicted by DNAStar Lasergene’ s Protean, BcePred and ABCpred tools, and the immunogenicity of the predicted B cell antigen epitopes was assessed by indirect enzyme-linked immunosordent assay ( ELISA ) .H7 subtype specificity was analyzed by comparing HA protein amino acid sequence with H7N9 and H1-H16 subtype influenza virus from Genbank using Clustal X 2.1 software, and Cn3D 4.3.1 software was used to detect the distribution and 3D structure of predicted epitopes on the HA protein of H7N9.Results The potential B-cell epitopes may be located in 172-183, 363-380, 452-472 and 491-506 of extracellular N-terminus of HA protein.ELISA showed that four predicted eptiopes specifically reacted with positive serums from patient.Multi-sequence alignment demonstrated that peptide 172-183 and 363-380 had higher H7 subtype specificity compared with amino acid sequences of other subtypes.Moreover, the predicted linear B-cell epitopes all located on the surface of HA protein according to the 3D structure analysis.Conclusion Four potential B-cell epitopes were identified, in which peptide 172-183 and 363-380 have higher H7 subtype specificity, and may be used in the design of epitope-based vaccines and diagnostics tests.
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Base de datos:
WPRIM
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
Zh
Revista:
Chinese Journal of Clinical Infectious Diseases
Año:
2016
Tipo del documento:
Article