Article Versions
Export Article
Cite this article
  • Normal Style
  • MLA Style
  • APA Style
  • Chicago Style
Research Article
Open Access Peer-reviewed

Multi Epitope Peptide Vaccine against Human Parvovirus B19 Using Immuno-Informatics Approaches

Nisreen Osman Mohammed, Khoubieb Ali Abd-elrahman, Yassir A. Almofti
American Journal of Microbiological Research. 2018, 6(4), 140-164. DOI: 10.12691/ajmr-6-4-3
Received June 15, 2019; Revised August 02, 2018; Accepted August 14, 2018

Abstract

Introduction: Human parvovirus B19 (B19V) is small non-enveloped, single-stranded DNA virus belong to genus Erythrovirus. B19V can cause erythema infectiosum (fifth disease), oligoarthritis, hydrops fetalis and a plastic crisis in patients with sickle cell anemia. A variety of vaccine strategies have been employed targeting immune responses. However their results were controversy with a limiting in availability of viral antigen. Since B19V replicates predominantly in erythroid progenitor cells of human bone marrow, this makes a peptide-based vaccines a promising strategy for development of vaccine against B19V with less allergenic and reactogenic responses. The aim of the present study was to design an efficient multi-epitope vaccine for human B19 virus using VP1 glycoprotein. Material and method: Thirty six sequences of VP1 glycoprotein were retrieved from NCBI database in December 2017 and aligned to determine the conservancy between the retrieved strains. The IEDB different analysis resources were used to predict epitopes that could act as promising peptides vaccine against parvovirus B19. The predicted epitopes were further assessed for population coverage against the whole world population. Results: The epitopes 214-PEVP-217, 675-GLHQPPP-681 and 554-SLRPGPVSQPYH-565 were found to be the most potential epitopes against B cells. For the T cell three epitopes namely 155-FRYSQLAKL-163, 302-CTISPIMGY-310 and 316-YLDFNALNL-324 showed high affinity to MHC-I alleles. The epitopes (core) 155-FRYSQLAKL-163, 438-FYVLEHSSF-446 and 404-WVYFPPQYA-412 showed high affinity to interact with MHC-II alleles. 155-FRYSQLAKL-163 and 438-FYVLEHSSF-446 showed high coverage for whole world population with percentage of 99.73% and 94.85% respectively. Conclusion: This study proposed eight epitopes for B and T cells that could be a powerful multi epitope vaccine against B19V. Particular concern directed towards the epitope 155-FRYSQLAKL-163 which demonstrated merits by reacting efficiently with both MHC-I and MHC-II alleles. Clinical trial is required to proof the efficacy of these epitopes as promising candidate vaccine against parvovirus B19.

1. Introduction

Human parvovirus B19 (B19V) is a small, non-enveloped, single-stranded DNA virus, belongs to the genus Erythrovirus. The genus belongs to large family of Parvoviridae in which the word (parvum) means small. The family formed small capsids about 25 nm in diameter 1, 2. The first discovery of B19V was in 1975 and around 1980s scientist linked the B19V infection to certain disease like a plastic crisis and fifth disease (erythema infectiosum) 1, 3, 4. B19V causes aplastic crisis in patients with shortened red cell survival due to induction of apoptosis in infected erythroid progenitors. Erythema infectiosum also known as slapped cheek (fifth disease). It can also causes oligoarthritis and hydrops fetalis or intrauterine death in infected fetuses 3, 4. The prevalence of B19V is highly common among children with sickle cell anemia and it leads to deaths due to acute and chronic anemia’s (crisis episodes). Moreover the prevalence of B19V among pregnant women remains as a major cause of high maternal mortality especially in Sudan. 5, 6, 7

Parvovirus B19 is transmitted by respiratory aerosol spread from individuals with acute infection, blood products and vertical transmission from mother to fetus. The majority of infections occur during childhood and the risk being greatest in the first two trimesters of pregnancy 1. Regional epidemics occur during late winter and spring due to absence of a lipid envelope in the virus and their genomic stability which makes virus notoriously resistant to heat inactivation and solvent detergents 1, 8, 9, 10. This demonstrated seasonal variation in outbreak of the virus throughout the year and high prevalence among children and compromised and pregnant women 4, 11, 12.

The parvovirus B19 genome consists of a single stranded linear molecule of 5596 nucleotides, composed of an internal coding sequence of 4830 nucleotides flanked by terminal repeat sequences of 383 nucleotides each. B19V contains two structural proteins, viral protein 1(VP1) and viral protein 2 (VP2). VP1differs from VP2 only in an N-terminal “unique region” composed of 227 additional amino acids which are mostly located outside the virion 1, 2, 13. VP1 contains many linear epitopes recognized by neutralizing antibodies and accessible to antibody. This binding makes VP1 most fit capsid protein for designing a vaccine 1, 14.

Till 1993 no human B19V vaccine is available. The development of such vaccine has been hampered by the limited availability of viral antigen since B19V replicates predominantly in Erythroid progenitor cells in human bone marrow. Moreover there is no convenient in vitro culture system available for routinely propagating large amounts of virus. However recently a recombinant design vaccine was established and their efficacy was controversial 15, 16, 17.

In this report we attempted to design a vaccine for human B19 virus using VP1 glycoprotein as an immunogen to invigorate protective immune response using immunoinformatics tools. The insilico prediction of epitopes for appropriate protein residues would help in production of peptide vaccine with intense immunogenic and insignificant allergenic impact that opposed to antibody creation that relies on biochemical examinations. The traditional vaccines can be costly, time consuming and not generally work. Moreover formulation of attenuated or inactivated form of microorganism contains a hundred of unnecessary proteins that induced immunity, allergenic or reactogenic responses 18, 19, 20.

2. Material and Methods

2.1. Protein Sequence Retrieval

A total of 36 strains of VP1 glycoprotein were retrieved from NCBI (https://www.ncbi.nlm.nih.gov/protein?term=Human+parvovirus+B19+VP1) in Dec 2017 from different parts of the word. The retrieved strains and their accession numbers were depicted in Table 1.

2.2. Phylogenetic Analysis

The retrieved sequences were subjected to phylogenetic analysis to determine the common ancestor of each strain using different tools from (https://www.phylogeny.fr) 21.

2.3. Determination of VP1 Conserved Regions

The retrieved sequences of VP1 strains were aligned to obtain conserved regions using multiple sequence alignment (MSA). Sequences were aligned with aid of the ClustalW as implemented in the BioEdit program, version 7.2.5 22.

2.4. Epitopes Prediction

To detect the candidate epitopes from VP1 of Parvo virus B19, for B-lymphocytes and T-lymphocytes, several analysis prediction tools from Immune Epitope Database (IEDB) (https://www.iedb.org/) 22, 23 were used.


2.4.1. B-cell Epitope Prediction

B cell epitope is the portion of an immunogen which interacts with B lymphocytes. B-lymphocytes upon exposure differentiated into plasma cells and memory cells. Thus B cells epitopes are shown to being accessible and antigenic 24. Accordingly the classical propensity scale methods and hidden Markov model programmed software were used for the following aspects:


2.4.1.1. Prediction of Linear B-cell Epitopes

BepiPred from immune epitope database (https://toolsiedb.ofg/bcell/) 25 was used as a linear B-cell epitopes prediction from the conserved region of VP1 glycoprotein with a default threshold value of 0.5.


2.4.1.2. Prediction of surface accessibility:-

Emini surface accessibility prediction tool of the immune epitope database (IEDB) was used (https://tools.immuneepitope.org/tools/bcell/iedb) 26. The surface accessible epitopes were predicted from the conserved region of VP1 glycoprotein with default threshold value 1.000.


2.4.1.3. Prediction of Epitopes Antigenicity

The kolaskar and tongaonker antigenicity method was used to determine the antigenic sites with a default threshold value of 1.025 (https://tools.immuneepitope.org/bcell/) 27.


2.4.2. T-cell Epitopes Prediction
2.4.2.1. MHC Class I Binding Predictions

Analysis of peptide binding to MHC class I molecules was assessed by the IEDB MHC-I prediction tool at (https://tools.iedb.org/mhci/n). MHC-I peptide complex presentation to T-lymphocytes underwent several steps. For instance the attachment of cleaved peptides to MHC-1 molecules was predicted by Artificial Neural Network (ANN) 28, 29, 30. Also all epitopes lengths were set as 9 mers. Besides, all the conserved epitopes that bind to alleles at score equal to or less than 100 half-maximal inhibitory concentrations (IC-50) were selected for further analysis 31.


2.4.2.2. MHC Class II Binding Predictions

Analysis of peptide binding to MHC class II molecules was assessed by the IEDB MHC II prediction tool at (https://tools.immuneepitope.org/mhcii/) 32, 33. For MHC-II binding prediction, human allele references set were used. MHC class II groove has the ability to bind peptides with different lengths. Therefore for the analysis, the NN-align as prediction method from IEDB MHC-II prediction tool were used. It allows for identification of the MHC class II binding core and epitopes binding affinity All conserved epitopes that bind to many alleles at score equal or less than 500 half-maximal inhibitory concentrations (IC-50) were selected for further analysis.

2.5. Population Coverage Calculation

For the calculation of the population coverage for all potential MHC-I and II epitopes bindings, the IEDB tools (https://tools.iedb.org/tools/population/iedb_input) 34 was used. The VP1 glycoprotein of B19V was assessed for population coverage against the whole world with selected MHC-I and MHC-II interacted alleles.

2.6. Homology Modeling

Raptor X protein structure prediction server (https://raptorx.uchicago.edu/StructurePrediction/predict/) was used for creation the 3D structure of the VP1 glycoprotein of B19 virus. The reference sequence [AAV35057.1] was used as an input and Chimera 1.8 was used as a tool to visualize the selected epitopes belonging to B cell and T cell (MHC-I and MHC-II). Homology modeling was used for visualization of the surface accessibility of the B lymphocytes predicted candidate epitopes as well as for visualization of all predicted T cell epitopes in the structural level.

3. Results

3.1. Phylogenetic Evolution of the Retrieved Strains

All retrieved strains were representing in phylogenic tree Figure 1. From the figure the Germany and Japan strains share common ancestor. Also Ghana, Brazil and United Kingdom shared common ancestor. Also in another site USA, Japan, China, Korea, German, United Kingdom and Belgium shared common ancestor.

3.2. Alignment

Multiple sequence alignment was represented in Figure 2. Sequence alignment showed that some regions were mutated region, and dots show the conservancy between different retrieved sequences of the strains.

3.3. Prediction of B-cell Epitope

The reference sequence of the viral protein (VP1) was subjected to Bepipred linear epitope, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity methods in IEDB to predict the likelihood of specific regions in the protein that bind to B cell receptor, being in the surface and immunogenic respectively. The thresholds of Bepipred linear epitope, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity were shown in Figure 3. For Bepipred linear epitope prediction method, the average binding score of viral protein to B cell was 0.5. Fifty two epitopes were predicted as a linear epitopes and only 23 epitopes were conserved regions. Emini surface accessibility provided only thirteen epitopes that were potentially predicted on surface by passing the default threshold 1.000. Kolaskar and Tongaonkar antigenicity provided only eight epitopes that gave score above the default threshold 1.025. All the epitopes predicted by these different tools against B cell were provided in Table 2. Accordingly three conserved epitopes were successfully predicted to elicit the B cell lymphocytes since they were conserved among all retrieved strains, got higher score values in Emini surface accessibility and Kolaskar and Tongaonkar antigenicity prediction methods. These three epitopes were 214-PEVP-217, 675-GLHQPPP-681 and 554-SLRPGPVSQPYH-565. The three dimension structural (3D) level of these epitopes was shown in Figure 4.

3.4. T lymphocytes Epitopes Binding Prediction
3.4.1. MHC-I Binding Predictions

The reference structural protein (VP1) was analyzed using IEDB MHC-1 binding prediction tool to predict T cell epitopes interacting with different types of MHC-I alleles. Thirty three conserved peptides were predicted to interact with different MHC-1 alleles. The peptide 155-FRYSQLAKL-163 had higher affinity to interact with 6 alleles, followed by 302-CTISPIMGY-310 that interacted with four alleles and 316-YLDFNALNL-324 that interacted with only two alleles as shown in Table 3. These three epitopes and their positions in structural level of VP1 were shown in Figure 5. The thirty three conserved peptides and their interaction with different MHC-1 alleles were supplemented in an extra sheet 1.


3.4.2. MHC-П Binding Predictions

Seventy nine (79) conserved epitopes were predict from reference viral protein (VP1) which have ability to interact with MHC-II alleles. As shown in Table 4, three peptides (core) 155-FRYSQLAKL-163, 438-FYVLEHSSF-446 and 404-WVYFPPQYA-412 demonstrated higher affinity to interact with MHC-П alleles. The three dimensional structural level (3D) of these epitopes within VP 1 protein was shown in Figure 6. The other core epitopes and their corresponding alleles that interacted with MHC-П were supplemented in an extra sheet- 2.

3.5. Analysis of the Population Coverage

As shown in Table 5 two epitopes, 155-FRYSQLAKL-163 and 316-YLDFNALNL-324, interacted with most frequent MHC-I alleles and they demonstrated population coverage against the whole world 56.26% and 43.86% respectively. Two epitopes, 155-FRYSQLAKL-163 and 438-FYVLEHSSF-446, demonstrated population coverage against the whole world 99.37% and 94.85% respectively against MHC-II. Interestingly the epitope 155-FRYSQLAKL-163 was shown to interact with both MHC-I and MHC-II alleles. As shown in Table 6 the overall epitope sets for the predicted epitopes against MHC-I and MHC-II alleles was 99.44%.

4. Discussion

Recently there have been considerable efforts toward developing a synthetic peptide vaccines which include B and T cell epitopes that could potentially lead to improved vaccination against parvovirus B19 35, 36, 37. Many recombinants B19 parvovirus capsids of various structural protein compositions like VP1 & VP2 were evaluated as vaccine. Other studies used virus-like particles (VLPs) by mix VP1 and VP2 with specific ratio which gives antibody levels similar to those elicited by infection but it caused significant reactogenicity like headache, fever, gastrointestinal related distress and fatigue 37, 38.

To our knowledge, there is no peptide prediction has been conducted specifically for B19V with a good immune response and less immunological side effect. In this study we determine a 100% conserved regions which are then investigated to predict the highly potential immunogenic epitopes for both B and T cells using VP1 capsid protein. VP1 has been proposed from different study as a good candidate protein for vaccine against B19V 2, 38. Our results revealed that all the proposed epitopes for B cell were above threshold scores in Bepipred linear epitope, Emini surface accessibility and Kolaskar and Tongaonkar antigenicity using prediction methods in IEDB. One of the promising predicted epitopes was 214-PEVP-217. This tetra peptide probably activating humeral immune response as it is part of VP1 capsid protein. 39

Since the immune response of T cell is long lasting response comparing with B cell, where the antigen can easily escape the antibody memory response and considering that CD8+T and CD4+T cell responses play a major role in antiviral immunity 40. Many peptides were proposed by this study that binds to MHC-I molecules (Table 3). All the proposed epitopes were interacted with MHC-I exceeding the thresholds. Moreover the epitope 155-FRYSQLAKL-163 binds to six alleles with worldwide population coverage 56.26% to MHC-I alleles. This finding is not consistent with another study which proposed a single HLAB 35-restricted peptide (QPTRVDQKM) to stimulate immunity 41 however this study recommended further mapping down to the epitopes restricted to MHC-I 41.

For MHC-II (CD4+) three peptides were proposed (438-FYVLEHSSF-446, 404-WVYFPPQYA-412 and 155-FRYSQLAKL-163) that they bound successfully to many HLA alleles of MHC-II (Table 4). These peptides were above proposed thresholds as well as they have higher population coverage. One of the most promising and interested finding of this study was that the epitope 155-FRYSQLAKL-163 was shared in both MHC-I & II as well as it has population coverage of 99.73%.

5. Conclusion

Parvo virus (B19V) has high prevalence among children and due to it is vertical transmission from mother to fetus which lead to fetal loss, developing of a vaccine with less immunological side effect remains a challenging issue. In this study we proposed many peptides that could be a powerful multi epitopes vaccine against B19V especially the peptide 155-FRYSQLAKL-163 which interacted against both MHC-I & II. To determine the efficacy of these proposed epitopes clinical trials is required.

Acknowledgments

We are grateful to Dr:Ahmed Hamdi Abu-haraz, Africa city of Technology, Khartoum, Sudan for his excellent editing of manuscript. Thanks to our colleagues in University of Bahri for their help and support.

Competing Interest

The authors declare that they have no competing interest.

Funding

This study received no specific grant from any funding agency in the public, commercial, or private sectors.

References

[1]  Young NS, Brown KE. Parvovirus B19. New England Journal of Medicine. 2004; 350(6): 586-97.
In article      View Article  PubMed
 
[2]  Kerr JR. The role of parvovirus B19 in the pathogenesis of autoimmunity and autoimmune disease. Journal of clinical pathology. 2016; 69(4): 279-91.
In article      View Article  PubMed
 
[3]  Servant-Delmas A, Morinet F. Update of the human parvovirus B19 biology. Transfusion Clinique et Biologique. 2016; 23(1): 5-12.
In article      View Article  PubMed
 
[4]  Suzuki M, Yoto Y, Ishikawa A, Tsutsumi H. Analysis of nucleotide sequences of human parvovirus B19 genome reveals two different modes of evolution, a gradual alteration and a sudden replacement: a retrospective study in Sapporo, Japan, from 1980 to 2008. Journal of virology. 2009; 83(21):10975-80.
In article      View Article  PubMed
 
[5]  Smith-Whitley K, Zhao H, Hodinka RL, Kwiatkowski J, Cecil R, Cecil T, et al. Epidemiology of human parvovirus B19 in children with sickle cell disease. Blood. 2004; 103(2): 422-7.
In article      View Article  PubMed
 
[6]  Gasim GI, Eltayeb R, Elhassan EM, Haggaz AD, Rayis DA, Adam I. Human parvovirus B19 and low hemoglobin levels in pregnant Sudanese women. International Journal of Gynecology & Obstetrics. 2016; 132(3): 318-20.
In article      View Article  PubMed
 
[7]  de Jong EP, de Haan TR, Kroes AC, Beersma MF, Oepkes D, Walther FJ. Parvovirus B19 infection in pregnancy. Journal of clinical virology. 2006; 36(1): 1-7.
In article      View Article  PubMed
 
[8]  Letalef M, Vanham G, Boukef K, Yacoub S, Muylle L, Mertens G. Higher prevalence of parvovirus B19 in Belgian as compared to Tunisian blood donors: differential implications for prevention of transfusional transmission. Transfusion science. 1997; 18(4): 523-30.
In article      View Article
 
[9]  Kelly H, Siebert D, Hammond R, Leydon J, Kiely P, Maskill W. The age-specific prevalence of human parvovirus immunity in Victoria, Australia compared with other parts of the world. Epidemiology and Infection. 2000; 124(03): 449-57.
In article      View Article  PubMed
 
[10]  Anderson LJ. Role of parvovirus B19 in human disease. The Pediatric infectious disease journal. 1987; 6(8): 711-8.
In article      View Article  PubMed
 
[11]  Pillay D, Kibbler C, Griffiths P, Hurt S, Patou G. Parvovirus B19 outbreak in a children's ward. The Lancet. 1992; 339(8785): 107-9.
In article      View Article
 
[12]  Serjeant GR, Mason K, Topley J, Serjeant BE, Pattison JR, Jones SE, et al. Outbreak of aplastic crises in sickle cell anaemia associated with parvovirus-like agent. The Lancet. 1981; 318(8247): 595-7.
In article      View Article
 
[13]  Greulich S, Kindermann I, Schumm J, Perne A, Birkmeier S, Grün S, et al. Predictors of outcome in patients with parvovirus B19 positive endomyocardial biopsy. Clinical Research in Cardiology. 2016; 105(1): 37-52.
In article      View Article  PubMed
 
[14]  Kaufmann B, Simpson AA, Rossmann MG. The structure of human parvovirus B19. Proceedings of the National Academy of Sciences of the United States of America. 2004; 101(32): 11628-33.
In article      View Article  PubMed
 
[15]  Bansal GP, Hatfield JA, Dunn FE, Kramer AA, Brady F, Riggin CH, et al. Candidate recombinant vaccine for human B19 parvovirus. Journal of Infectious Diseases. 1993; 167(5): 1034-44.
In article      View Article  PubMed
 
[16]  Ballou WR, Reed JL, Noble W, Young NS, Koenig S. Safety and immunogenicity of a recombinant parvovirus B19 vaccine formulated with MF59C. 1. Journal of Infectious Diseases. 2003; 187(4): 675-8.
In article      View Article  PubMed
 
[17]  Effio CL, Oelmeier SA, Hubbuch J. High-throughput characterization of virus-like particles by interlaced size-exclusion chromatography. Vaccine. 2016; 34(10): 1259-67.
In article      View Article  PubMed
 
[18]  Li W, Joshi MD, Singhania S, Ramsey KH, Murthy AK. Peptide vaccine: progress and challenges. Vaccines. 2014;2(3):515-36.
In article      View Article  PubMed
 
[19]  Purcell AW, McCluskey J, Rossjohn J. More than one reason to rethink the use of peptides in vaccine design. Nature reviews Drug discovery. 2007;6(5):404-14.
In article      View Article  PubMed
 
[20]  Hoshino Y. Peptide-Based Immunotherapeutics and Vaccines 2015.
In article      View Article
 
[21]  Dereeper A, Guignon V, Blanc G, Audic S, Buffet S, Chevenet F, et al. Phylogeny. fr: robust phylogenetic analysis for the non-specialist. Nucleic acids research. 2008;36(suppl 2):W465-W9.
In article      View Article  PubMed
 
[22]  Chevenet F, Brun C, Bañuls A-L, Jacq B, Christen R. TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC bioinformatics. 2006;7(1):439.
In article      View Article  PubMed
 
[23]  Hall TA, editor BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic acids symposium series; 1999: [London]: Information Retrieval Ltd., c1979-c2000.
In article      View Article
 
[24]  Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, et al. The immune epitope database (IEDB) 3.0. Nucleic acids research. 2015;43(D1):D405-D12.
In article      View Article  PubMed
 
[25]  Hasan MA, Hossain M, Alam J. A computational assay to design an epitope-based Peptide vaccine against Saint Louis encephalitis virus. Bioinformatics and Biology insights. 2013;7:347.
In article      View Article  PubMed
 
[26]  Larsen JE, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes. Immunome research. 2006;2(1):2.
In article      View Article  PubMed
 
[27]  Emini EA, Hughes JV, Perlow D, Boger J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. Journal of virology. 1985; 55(3):836-9.
In article      PubMed  PubMed
 
[28]  Kolaskar A, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS letters. 1990; 276(1-2): 172-4.
In article      View Article
 
[29]  Kim Y, Ponomarenko J, Zhu Z, Tamang D, Wang P, Greenbaum J, et al. Immune epitope database analysis resource. Nucleic acids research. 2012:gks438.
In article      View Article
 
[30]  Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic acids research. 2008;36(suppl 2):W509-W12.
In article      View Article  PubMed
 
[31]  Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A, et al. Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome research. 2008; 4(1): 2.
In article      View Article  PubMed
 
[32]  Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 2008; 4(4): e1000048.
In article      View Article  PubMed
 
[33]  Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, et al. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC bioinformatics. 2010; 11(1): 568.
In article      View Article  PubMed
 
[34]  Bui H-H, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC bioinformatics. 2006; 7(1): 153.
In article      View Article  PubMed
 
[35]  Tam JP. Synthetic peptide vaccine design: synthesis and properties of a high-density multiple antigenic peptide system. Proceedings of the National Academy of Sciences. 1988; 85(15): 5409-13.
In article      View Article
 
[36]  Arnon R, Horwitz RJ. Synthetic peptides as vaccines. Current opinion in immunology. 1992; 4(4): 449-53.
In article      View Article
 
[37]  van der Burg SH, Bijker MS, Welters MJ, Offringa R, Melief CJ. Improved peptide vaccine strategies, creating synthetic artificial infections to maximize immune efficacy. Advanced drug delivery reviews. 2006; 58(8): 916-30.
In article      View Article  PubMed
 
[38]  Chandramouli S, Medina-Selby A, Coit D, Schaefer M, Spencer T, Brito LA, et al. Generation of a parvovirus B19 vaccine candidate. Vaccine. 2013; 31(37): 3872-8.
In article      View Article  PubMed
 
[39]  Corcoran A, Mahon BP, Doyle S. B cell memory is directed toward conformational epitopes of parvovirus B19 capsid proteins and the unique region of VP1. Journal of Infectious Diseases. 2004; 189(10): 1873-80.
In article      View Article  PubMed
 
[40]  Black M, Trent A, Tirrell M, Olive C. Advances in the design and delivery of peptide subunit vaccines with a focus on toll-like receptor agonists. Expert review of vaccines. 2010; 9(2): 157-73.
In article      View Article  PubMed
 
[41]  Klenerman P, Tolfvenstam T, Price DA, Nixon DF, Broliden K, Oxenius A. T lymphocyte responses against human parvovirus B19: small virus, big response. Pathologie Biologie. 2002; 50(5): 317-25.
In article      View Article
 

Published with license by Science and Education Publishing, Copyright © 2018 Nisreen Osman Mohammed, Khoubieb Ali Abd-elrahman and Yassir A. Almofti

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/

Cite this article:

Normal Style
Nisreen Osman Mohammed, Khoubieb Ali Abd-elrahman, Yassir A. Almofti. Multi Epitope Peptide Vaccine against Human Parvovirus B19 Using Immuno-Informatics Approaches. American Journal of Microbiological Research. Vol. 6, No. 4, 2018, pp 140-164. https://pubs.sciepub.com/ajmr/6/4/3
MLA Style
Mohammed, Nisreen Osman, Khoubieb Ali Abd-elrahman, and Yassir A. Almofti. "Multi Epitope Peptide Vaccine against Human Parvovirus B19 Using Immuno-Informatics Approaches." American Journal of Microbiological Research 6.4 (2018): 140-164.
APA Style
Mohammed, N. O. , Abd-elrahman, K. A. , & Almofti, Y. A. (2018). Multi Epitope Peptide Vaccine against Human Parvovirus B19 Using Immuno-Informatics Approaches. American Journal of Microbiological Research, 6(4), 140-164.
Chicago Style
Mohammed, Nisreen Osman, Khoubieb Ali Abd-elrahman, and Yassir A. Almofti. "Multi Epitope Peptide Vaccine against Human Parvovirus B19 Using Immuno-Informatics Approaches." American Journal of Microbiological Research 6, no. 4 (2018): 140-164.
Share
  • Figure 2. Multiple sequence alignment for a part of the retrieved strains for the most mutated regions. Dots showed the conservancy between the aligned sequences
  • Figure 3. Prediction of B-cell epitopes by different IEDB scales (A- Bepipred linear epitope prediction, B- Emini surface accessibility, C- Kolaskar and Tongaonkar antigenicity prediction). Regions above threshold (red line) are proposed to be a part of B cell epitope while regions below the threshold (red line) are not
  • Figure 4. Position of proposed conserved B cell epitopes in structural level of VP1 protein of parvovirus B19. The three predicted epitopes were shown to interact with B cell and showed conservancy, surface accessibility and antigenicity using IEDB software
  • Table 2. B-cell epitopes prediction, the position of peptides is according to the position of amino acids in the VP1 of the B19V
  • Table 3. List of top epitopes that had binding affinity with MHC-I alleles. The position of peptides is according to position of amino acids in VPI protein of B19 V
  • Table 4. List of top three epitopes that had binding affinity with the MHC Class II alleles .The position of peptides is according to position of amino acids in VPI protein of B19 V
  • Table 5. The population coverage against the whole world for the predicted epitopes. The overall population coverage epitope set for predicted epitopes in MHC-1 was 76.36% and for MHC-11 was 99.44%.
  • Table 6. The population coverage against the whole world for the predicted epitopes against both MHC-1 and MHC-11. The overall population coverage epitope set for predicted epitopes is 99.87%
[1]  Young NS, Brown KE. Parvovirus B19. New England Journal of Medicine. 2004; 350(6): 586-97.
In article      View Article  PubMed
 
[2]  Kerr JR. The role of parvovirus B19 in the pathogenesis of autoimmunity and autoimmune disease. Journal of clinical pathology. 2016; 69(4): 279-91.
In article      View Article  PubMed
 
[3]  Servant-Delmas A, Morinet F. Update of the human parvovirus B19 biology. Transfusion Clinique et Biologique. 2016; 23(1): 5-12.
In article      View Article  PubMed
 
[4]  Suzuki M, Yoto Y, Ishikawa A, Tsutsumi H. Analysis of nucleotide sequences of human parvovirus B19 genome reveals two different modes of evolution, a gradual alteration and a sudden replacement: a retrospective study in Sapporo, Japan, from 1980 to 2008. Journal of virology. 2009; 83(21):10975-80.
In article      View Article  PubMed
 
[5]  Smith-Whitley K, Zhao H, Hodinka RL, Kwiatkowski J, Cecil R, Cecil T, et al. Epidemiology of human parvovirus B19 in children with sickle cell disease. Blood. 2004; 103(2): 422-7.
In article      View Article  PubMed
 
[6]  Gasim GI, Eltayeb R, Elhassan EM, Haggaz AD, Rayis DA, Adam I. Human parvovirus B19 and low hemoglobin levels in pregnant Sudanese women. International Journal of Gynecology & Obstetrics. 2016; 132(3): 318-20.
In article      View Article  PubMed
 
[7]  de Jong EP, de Haan TR, Kroes AC, Beersma MF, Oepkes D, Walther FJ. Parvovirus B19 infection in pregnancy. Journal of clinical virology. 2006; 36(1): 1-7.
In article      View Article  PubMed
 
[8]  Letalef M, Vanham G, Boukef K, Yacoub S, Muylle L, Mertens G. Higher prevalence of parvovirus B19 in Belgian as compared to Tunisian blood donors: differential implications for prevention of transfusional transmission. Transfusion science. 1997; 18(4): 523-30.
In article      View Article
 
[9]  Kelly H, Siebert D, Hammond R, Leydon J, Kiely P, Maskill W. The age-specific prevalence of human parvovirus immunity in Victoria, Australia compared with other parts of the world. Epidemiology and Infection. 2000; 124(03): 449-57.
In article      View Article  PubMed
 
[10]  Anderson LJ. Role of parvovirus B19 in human disease. The Pediatric infectious disease journal. 1987; 6(8): 711-8.
In article      View Article  PubMed
 
[11]  Pillay D, Kibbler C, Griffiths P, Hurt S, Patou G. Parvovirus B19 outbreak in a children's ward. The Lancet. 1992; 339(8785): 107-9.
In article      View Article
 
[12]  Serjeant GR, Mason K, Topley J, Serjeant BE, Pattison JR, Jones SE, et al. Outbreak of aplastic crises in sickle cell anaemia associated with parvovirus-like agent. The Lancet. 1981; 318(8247): 595-7.
In article      View Article
 
[13]  Greulich S, Kindermann I, Schumm J, Perne A, Birkmeier S, Grün S, et al. Predictors of outcome in patients with parvovirus B19 positive endomyocardial biopsy. Clinical Research in Cardiology. 2016; 105(1): 37-52.
In article      View Article  PubMed
 
[14]  Kaufmann B, Simpson AA, Rossmann MG. The structure of human parvovirus B19. Proceedings of the National Academy of Sciences of the United States of America. 2004; 101(32): 11628-33.
In article      View Article  PubMed
 
[15]  Bansal GP, Hatfield JA, Dunn FE, Kramer AA, Brady F, Riggin CH, et al. Candidate recombinant vaccine for human B19 parvovirus. Journal of Infectious Diseases. 1993; 167(5): 1034-44.
In article      View Article  PubMed
 
[16]  Ballou WR, Reed JL, Noble W, Young NS, Koenig S. Safety and immunogenicity of a recombinant parvovirus B19 vaccine formulated with MF59C. 1. Journal of Infectious Diseases. 2003; 187(4): 675-8.
In article      View Article  PubMed
 
[17]  Effio CL, Oelmeier SA, Hubbuch J. High-throughput characterization of virus-like particles by interlaced size-exclusion chromatography. Vaccine. 2016; 34(10): 1259-67.
In article      View Article  PubMed
 
[18]  Li W, Joshi MD, Singhania S, Ramsey KH, Murthy AK. Peptide vaccine: progress and challenges. Vaccines. 2014;2(3):515-36.
In article      View Article  PubMed
 
[19]  Purcell AW, McCluskey J, Rossjohn J. More than one reason to rethink the use of peptides in vaccine design. Nature reviews Drug discovery. 2007;6(5):404-14.
In article      View Article  PubMed
 
[20]  Hoshino Y. Peptide-Based Immunotherapeutics and Vaccines 2015.
In article      View Article
 
[21]  Dereeper A, Guignon V, Blanc G, Audic S, Buffet S, Chevenet F, et al. Phylogeny. fr: robust phylogenetic analysis for the non-specialist. Nucleic acids research. 2008;36(suppl 2):W465-W9.
In article      View Article  PubMed
 
[22]  Chevenet F, Brun C, Bañuls A-L, Jacq B, Christen R. TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC bioinformatics. 2006;7(1):439.
In article      View Article  PubMed
 
[23]  Hall TA, editor BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic acids symposium series; 1999: [London]: Information Retrieval Ltd., c1979-c2000.
In article      View Article
 
[24]  Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, et al. The immune epitope database (IEDB) 3.0. Nucleic acids research. 2015;43(D1):D405-D12.
In article      View Article  PubMed
 
[25]  Hasan MA, Hossain M, Alam J. A computational assay to design an epitope-based Peptide vaccine against Saint Louis encephalitis virus. Bioinformatics and Biology insights. 2013;7:347.
In article      View Article  PubMed
 
[26]  Larsen JE, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes. Immunome research. 2006;2(1):2.
In article      View Article  PubMed
 
[27]  Emini EA, Hughes JV, Perlow D, Boger J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. Journal of virology. 1985; 55(3):836-9.
In article      PubMed  PubMed
 
[28]  Kolaskar A, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS letters. 1990; 276(1-2): 172-4.
In article      View Article
 
[29]  Kim Y, Ponomarenko J, Zhu Z, Tamang D, Wang P, Greenbaum J, et al. Immune epitope database analysis resource. Nucleic acids research. 2012:gks438.
In article      View Article
 
[30]  Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic acids research. 2008;36(suppl 2):W509-W12.
In article      View Article  PubMed
 
[31]  Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A, et al. Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome research. 2008; 4(1): 2.
In article      View Article  PubMed
 
[32]  Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 2008; 4(4): e1000048.
In article      View Article  PubMed
 
[33]  Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, et al. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC bioinformatics. 2010; 11(1): 568.
In article      View Article  PubMed
 
[34]  Bui H-H, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC bioinformatics. 2006; 7(1): 153.
In article      View Article  PubMed
 
[35]  Tam JP. Synthetic peptide vaccine design: synthesis and properties of a high-density multiple antigenic peptide system. Proceedings of the National Academy of Sciences. 1988; 85(15): 5409-13.
In article      View Article
 
[36]  Arnon R, Horwitz RJ. Synthetic peptides as vaccines. Current opinion in immunology. 1992; 4(4): 449-53.
In article      View Article
 
[37]  van der Burg SH, Bijker MS, Welters MJ, Offringa R, Melief CJ. Improved peptide vaccine strategies, creating synthetic artificial infections to maximize immune efficacy. Advanced drug delivery reviews. 2006; 58(8): 916-30.
In article      View Article  PubMed
 
[38]  Chandramouli S, Medina-Selby A, Coit D, Schaefer M, Spencer T, Brito LA, et al. Generation of a parvovirus B19 vaccine candidate. Vaccine. 2013; 31(37): 3872-8.
In article      View Article  PubMed
 
[39]  Corcoran A, Mahon BP, Doyle S. B cell memory is directed toward conformational epitopes of parvovirus B19 capsid proteins and the unique region of VP1. Journal of Infectious Diseases. 2004; 189(10): 1873-80.
In article      View Article  PubMed
 
[40]  Black M, Trent A, Tirrell M, Olive C. Advances in the design and delivery of peptide subunit vaccines with a focus on toll-like receptor agonists. Expert review of vaccines. 2010; 9(2): 157-73.
In article      View Article  PubMed
 
[41]  Klenerman P, Tolfvenstam T, Price DA, Nixon DF, Broliden K, Oxenius A. T lymphocyte responses against human parvovirus B19: small virus, big response. Pathologie Biologie. 2002; 50(5): 317-25.
In article      View Article