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Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development.

ABSTRACT: High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that of T-cell epitopes. Furthermore, the motifs of linear B-cell epitopes in different pathogens are quite different (e. g. HCV and hepatitis B virus). To cope with this challenge, this work aims to propose an HCV-customized sequence-based prediction method to identify B-cell epitopes of HCV.This work establishes an experimentally verified dataset comprising the B-cell response of HCV dataset consisting of 774 linear B-cell epitopes and 774 non B-cell epitopes from the Immune Epitope Database. An interpretable rule mining system of B-cell epitopes (IRMS-BE) is proposed to select informative physicochemical properties (PCPs) and then extracts several if-then rule-based knowledge for identifying B-cell epitopes. A web server Bcell-HCV was implemented using an SVM with the 34 informative PCPs, which achieved a training accuracy of 79.7% and test accuracy of 70.7% better than the SVM-based methods for identifying B-cell epitopes of HCV and the two general-purpose methods. This work performs advanced analysis of the 34 informative properties, and the results indicate that the most effective property is the alpha-helix structure of epitopes, which influences the connection between host cells and the E2 proteins of HCV. Furthermore, 12 interpretable rules are acquired from top-five PCPs and achieve a sensitivity of 75.6% and specificity of 71.3%. Finally, a conserved promising vaccine candidate, PDREMVLYQE, is identified for inclusion in a vaccine against HCV.This work proposes an interpretable rule mining system IRMS-BE for extracting interpretable rules using informative physicochemical properties and a web server Bcell-HCV for predicting linear B-cell epitopes of HCV. IRMS-BE may also apply to predict B-cell epitopes for other viruses, which benefits the improvement of vaccines development of these viruses without significant modification. Bcell-HCV is useful for identifying B-cell epitopes of HCV antigen to help vaccine development, which is available at http://e045.life.nctu.edu.tw/BcellHCV.

SUBMITTER: Huang WL

PROVIDER: S-EPMC4682406 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development.

Huang Wen-Lin WL Tsai Ming-Ju MJ Hsu Kai-Ti KT Wang Jyun-Rong JR Chen Yi-Hsiung YH Ho Shinn-Ying SY

BMC medical genomics 20151209

<h4>Background</h4>High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that ...[more]

PMID: 26680271

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Project description:Hepatitis E virus (HEV) causes liver disease in humans and is thought to be a zoonotic infection, with domestic animals, including swine and rabbits, being a reservoir. One of the proteins encoded by the virus is the capsid protein. This is likely the major immune-dominant protein and a target for vaccination. Four monoclonal antibodies (MAbs), three novel, 1E4, 2C7, and 2G9, and one previously characterized, 1B5, were evaluated for binding to the capsid protein from genotype 4 swine HEV. The results indicated that 625DFCP628, 458PSRPF462, and 407EPTV410 peptides on the capsid protein comprised minimal amino acid sequence motifs recognized by 1E4, 2C7, and 2G9, respectively. The data suggested that 2C7 and 2G9 epitopes were partially exposed on the surface of the capsid protein. Truncated genotype 4 swine HEV capsid protein (sp239, amino acids 368 to 606) can exist in multimeric forms. Preincubation of swine HEV with 2C7, 2G9, or 1B5 before addition to HepG2 cells partially blocked sp239 cell binding and inhibited swine HEV infection. The study indicated that 2C7, 2G9, and 1B5 partially blocked swine HEV infection of rabbits better than 1E4 or normal mouse IgG. The cross-reactivity of antibodies suggested that capsid epitopes recognized by 2C7 and 2G9 are common to HEV strains infecting most host species. Collectively, MAbs 2C7, 2G9, and 1B5 were shown to recognize three novel linear neutralizing B-cell epitopes of genotype 4 HEV capsid protein. These results enhance understanding of HEV capsid protein structure to guide vaccine and antiviral design.IMPORTANCE Genotype 3 and 4 HEVs are zoonotic viruses. Here, genotype 4 HEV was studied due to its prevalence in human populations and pig herds in China. To improve HEV disease diagnosis and prevention, a better understanding of the antigenic structure and neutralizing epitopes of HEV capsid protein are needed. In this study, the locations of three novel linear B-cell recognition epitopes within genotype 4 swine HEV capsid protein were characterized. Moreover, the neutralizing abilities of three MAbs specific for this protein, 2C7, 2G9, and 1B5, were studied in vitro and in vivo Collectively, these findings reveal structural details of genotype 4 HEV capsid protein and should facilitate development of applications for the design of vaccines and antiviral drugs for broader prevention, detection, and treatment of HEV infection of diverse human and animal hosts.

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Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development.

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Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development.

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