EPITOPE VACCINE DESIGN FOR VARIANT 2 STRAINS CIRCULATING IN IRAQ AND THE MIDDLE EAST
HTML Full TextEPITOPE VACCINE DESIGN FOR VARIANT 2 STRAINS CIRCULATING IN IRAQ AND THE MIDDLE EAST
Zahra M. Al-Khafaji * 1 and Aaisha B. Mahmood 2
Institute of Genetic Engineering and Biotechnology for Postgraduate Studies 1, University of Baghdad, Iraq.
Ministry of Agriculture 2, Veterinary Directorate, Baghdad Veterinary Hospital, Al-Dora Hospital, Iraq.
ABSTRACT: Infectious bronchitis virus causes infectious bronchitis in chickens. Variant 2 is a virulent strain circulating in the Middle East, Iraq is one of them, which harbor the strain at high rate causes a severe economic loos. Sequences of variable S1 glycoprotein were collected, consensus sequence derived and used in computational epitope vaccine design. The results gave one B cell epitope “DFMYGSYHPKCDFRPETIN” with very high antigenic score. T cell (CTL) epitope prediction produced four epitopes “QTQTAQSGY, FNFSFLSSF, FSFLSSFVY, NSLSVSLAY” with desirable criteria and react with many MHC I alleles, and docked with BF2*21:01 and BF2.0401 chicken MHC I molecules. T helper cell epitopes prediction gave eight epitopes “GYYNFNFSFLSSFVY, KFIVYRETSVNTTLV, LTNFTFTNVSNALPN, TG GVNTINIYQTQTA, TINIYQTQTAQSGYY, YNFNFSFLSSFVYKQ, NNGL WFNSLSVSLAY, NGLWFNSLSVSLAYG” reacting with many MHC II alleles. These epitopes can be used for preparation of vaccine to be investigated in wet lab experiments.
Keywords: |
Epitopes, Vaccine, Iraq, Middle East, Infectious bronchitis virus
INTRODUCTION: Infectious bronchitis is contiguous disease caused by Infectious Bronchitis Virus (IBV). Gallus gallus family and Pheasants (Phasianus spp) considered as natural hosts for the IBV. It is evident that IBV has become endemic worldwide 1, 2. There is no unifying nomenclature for IBV genotypes, and the names based primarily on geographic areas, but recently a method to define IBV strains was but forward depending on complete sequence of (S1) spike glycoprotein gene 3, 4. The virus belongs to Corona virus group with high changeable feature due to many reasons, among them it’s large genome and replication strategy.
Viral genetic mutations and recombination events give rise to district IBV genotypes, serotypes and pathotypes 1, 3, 5, the high frequency of appearing new IBV variants is distinguished characteristic of this virus among other Corona viruses 6. The virus has many structural proteins include spike glycoprotein; S1 plays a major role in viral attachment, diversity and antibody neutralization.
Mutations and recombination take place in both structural and non-structural proteins, and most of them have been detected in S1 gene, this variation about 20-25% and could be up to 50%, this affects the cross-protection toward virus strains 1, 3, the variations in S1 glycoprotein are used in determination of new viral genotypes and possibly the antiviral response 1, 4. S1 subunit located outside the virus contains about three hypervariable regions (HVRs) and is the most potential target for vaccine design, because of their ability to induce a fast and longer-term immune response than other protein as it mediates virus entry and is a primary determinant of cell tropism and pathogenesis 5, 7, 8, 9, therefore gained much popularity for researches 10, 11, 12. In such situation of high emergence of new variants causing antigenic drift and low cross- protection between serotypes, and outbreaks of disease can occur even in vaccinated flocks 13, 14.
In Iraq IBV was detected in all Governorates in the North, Middle and South at very high rates 15, 16, 17, 18. IBV variant 2 genotype, which showed extensive tissue tropism and implicated in kidney pathology 19 reported frequently in Iraq especially this decade 1, 16, 17, 20. This variant is a major virus variant circulating in the Middle East countries and North Africa 1, 6, 16, 21-27. The dissemination among the Middle East countries was attributed to movement of wild birds and intensive trade and uncontrolled movement of inhabitants and animal trade through the borders 16. Variant 2 doses not respond to vaccines currently in use, challenge studies revealed that H120 vaccine provides poor protection 1, 28.
Vaccination is the most important method for controlling infectious bronchitis, and the genetic variation in the envelope and especially S1 is one of the main hurdles in design vaccine 1, 29. Epitopes have become desirable candidates for vaccine design owing to their comparatively easy production, construction and chemical stability, in addition to the absence of infectious potential 30, and away from changes by mutations and recombination.
Epitope prediction of immunogens using Bioinformatics approaches and prediction tools reduces both the number of validation experiments and time for epitope detection 31. The branch of Bioinformatics, namely Vaccinomics has been used to address the development of new vaccines 14, this approach is already validated in scientific community 32, 33, 34 as Bioinformatics becomes the central pillar of modern life science researches 35.
The aim of this study which carried out using Immunoinfocrmatics is to design vaccine against variant 2 which causes a large loss in economy of poultry industry in Iraq. As the designed vaccine should be ideal when provoke both humoral and cellular responses, both B cell and T cell epitopes (Cytotoxic T cell, and Helper T cell) were designed in order to cope with antigenic drift of IBV.
MATERIALS AND METHODS: Number of databases and software were used in this study:
NCBI / Protein, used to retrieve protein sequences.
https://www.ncbi.nlm.nih.gov/protein/
MEGA v.7 software: used for alignment and estimation of phylogeny 36.
http://69.36.184.213/mega.php
BioEdit: used for alignment 37.
http://www.mbio.ncsu.edu/BioEdit/bioedit.html
ExPASyProtParam tool: used for protein characterization.
https://web.expasy.org/protparam/
RAMPAGE software: used for estimation of protein Ramachandran plot.
http://mordred.bioc.cam.ac.uk/~rapper/rampage.php
Phyer2: used for protein modelling 38.
http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index
PEP-FOLD 3: used for prediction of short peptide 3D structure 39.
http://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::PEP-FOLD3
VaxiJen v2.0 software for prediction of antigenicity
http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html
IEDB Database: used for prediction of B- cell and T- cell epitopes and their characters 40.
http://www.iedb.org/
PyRx virtual screening Tool version 8: used for docking studies 41, 42.
https://pyrx.sourceforge.io/downloads
PyMol: used for vitalization 43.
https://pymol.org/2/
PDB database : used to retrieve pdb format of some proteins 44.
Multalin used for consensus sequence estimation 45.
http://multalin.toulouse.inra.fr/multalin/
RESULTS AND DISCUSSION: Vaccine is one of the most effective immunological intervention to control IBV infections 46, based on the pathogen used vaccine formulations might contain several proteins, some of them are unnecessary for induction of protective immunity 47, on the other hand vaccine should induce humoral and cellular immune response, i.e., triggers both B cells and T cells selectively 46. For IBV spike protein (S1) is pairing with the cell receptors which is the key for infection and tropism, and to infect new host, it must adapt to the receptor of the new host either by mutations or recombination with other Corona viruses infecting the new host 5.
Sequence Retrieval: Sequences for S1 glyco-protein of the Middle East were collected from NCBI / GenBank database when have a clear declaration as variant 2, the proteins collected in FASTA format, using date of deposition in the database and the country, these sequences were aligned using ClustalW incorporated in MEGA package v7.0 and Neighbor Joining method for phylogenic tree was estimated, shown in Fig. 1.
FIG. 1: PHYLOGENIC RELATION SHIP AMONG VARIANT 2 STRAINS CIRCULATING IN THE MIDDLE EAST
FIG. 2: SIMILARITY AMONG VARIANT 2 STRAINS vs. IRAQI STRAINS
The degree of similarity was estimated using BLAST (for 2 sequences), this is shown in Fig. 2.
The results indicate an absolute similarity of Iraqi strains with some strains from Iran, and high similarity with the Israeli strains, these results were expected as Iraq and Iran considered open trade market, in addition, it has been noted that only few amino acids substitutions resulting in 2% sequence divergence and can alter the serotypes and determining the pathogenic types 48, these changes of S1 subunit may be responsible for immune escape 49.
The retrieved sequences were subjected to VxiJen v2.0 to estimate the antigenic score as shown in Table 1.
TABLE 1: ANTIGENIC SCORE FOR VARIANT 2 STRAINS OF THE MIDDLE EAST
Strain | Antigenic score |
RW78057/2017/Iran | 0.9362 |
ART85685/2017/Iran | 0.9187 |
ART85682/2017/Iran | 0.9187 |
ART85681/2017/Iran | 0.9187 |
ARW78059/2017/Iran | 0.9054 |
ART85688/2017/Iran | 0.9012 |
ARW78062/2017/Iran | 0.8932 |
ART85680/2017/Iran | 0.8872 |
AKH60832/2015/Iran | 0.8723 |
ART85686/2017/Iran | 0.8652 |
AKH60833/2015/Iran | 0.8558 |
AKH60831/2015/Iran | 0.8558 |
AKH60830/2015/Iran | 0.8558 |
AKH60829/2015/Iran | 0.8558 |
ALQ11049/2016/Iraq | 0.8552 |
AKH60827/2015/Iran | 0.8460 |
ART85683/2017/Iran | 0.8458 |
ALQ11044/2016/Iraq | 0.8372 |
AKH60828/2015/Iran | 0.8170 |
AKR04372/2015/Egypt | 0.6897 |
AKR04371/2015/Egypt | 0.5925 |
ACE88706/2016/Israel | 0.5850 |
ACE88706.2/2012/Israel | 0.5850 |
AFM45044/2012/Israel | 0.5825 |
AKR04373/2015/Egypt | 0.5730 |
AAD19891.1/2016/Israel | 0.5714 |
AFM45043.1/2012/Israel | 0.5709 |
ACT64163/2016/Iraq | 0.5495 |
The results revealed that all of them are antigenic as they exceed the threshold set (0.4).
Selected sequence was chosen from the variable regions, as the most variable region was found in HVR2 1, 16, 50, 51, the selected region in this study shown in Fig. 3.
FIG. 3: THE SEGMENT OF S1 GLYCOPROTEIN SELECTED FOR STUDY
The sequence occupied the position 244-358 according to M41 strain (classical strain) numbering. From these sequences a consensus sequence was chosen using MutliAlin software and named selected protein in the rest of this study and used for further studies i.e., to predict B cell and T cell epitopes. The characterization of selected protein showed in Table 2.
TABLE 2: CHARACTERS OF SELECTED PROTEIN USED IN THIS INVESTIGATION (FYPFTNISLVKEK FIVYRETSVNTTLVLTNFTFTNVSNALPNTGGVNTI IYQTQTAQSGYYNFNFSFLSSFVYKQSDFMYGSYHPKCDFRPETINNGLWFNSLSVSLAYGPLQ)
Character | Value |
Formula | C604H881N145O176S2 |
Number of amino acids | 114 |
Molecular weight | 13053.63 |
No. of Negatively charged residues (Asp+Glu) | 5 |
No. of Positively charged residues (Arg+Lys) | 6 |
Isoelectric point (PI) | 8.03 |
Instability index | 32.18 |
Aliphatic index | 70.88 |
Grand average of hydropathicity (GRAVY) | -0.137 |
Table 2 Expasy characters |
The results showed that the protein is positively charged as the residues (Arg + Lys) more than the negatively charged residues (Arg + Glu), the isoelectric point (8.04), i.e., slightly basic demonstrating that the protein is nonallergenic 52, the GRAVY hydropathicity with negative value (-0.137) indicates that the protein is hydrophilic, other characters point to be stable with aliphatic nature. The antigenic score of selected protein is high (0.9041), Ramachandran plot was carried out to indicate the feasibility or fitness of the protein as shown in Fig. 4.
FIG. 4: RAMACHANDRAN PLOT OF SELECTED PROTEIN
These results indicate that 87% of the residues are in the allowed region. 3D structure of the protein was estimated using Phyer 2 software Fig. 5, it appears with rich loops and β-turn structures.
FIG. 5: 3D STRUCTURE OF PROTEIN ESTIMATED BY USING PHYER 2 SERVER
Epitope Predictions: Epitope is an amino acids stretch binds to antibody , located on the surface of the antigen 46, interestingly S1 protein of IBV (about 520 amino acids) contains different immune epitopes responsible for both antibodies and induction of cell based immunity responses (CTL and Helper cells), thus playing as viral antigenic determinants 54. In this neutralizing antibodies are important in removing freely circulating IBV, whereas CTL response is crucial for control and clearance of virus infected cells 55. To achieve this, stimulation of both humoral (B cells) and CMI (Cytotoxic and Helper cells) is considered very essential for any candidate vaccine 56.
B Cell Epitopes: Continuous / linear epitope was predicted using the selected protein sequence and IEDB / BepiPred, The results gave three candidate epitope shown in Fig 6.
Position | Sequence | Length | Antigenic score |
20-23 | TSVN | 4 | |
34-49 | TNVSNALPNTGGVNTI | 16 | 0.2662 |
51-62 | IYQTQTAQSGYY | 12 | 0.5945 |
78-96 | DFMYGSYHPKCDFRPETIN | 19 | 1.4289 |
FIG. 6: PREDICTED B CELL EPITOPES IN THE SELECTED PROTEIN
FIG. 7: CHARACTERS OF SELECTED B CELL EPITOPE, THE POSITION IN β-TURN
FIG. 8: PARKER HYDROPHILICITY PREDICTION OF B CELL EPITOPES
Only epitopes present on the outer surface were chosen, the results showed only one epitope is suitable, this at the position 78-96, with antigenicity score 1.4289 (VaxiJen at cut off value 0.4). The epitope belongs to β-turn of the protein Fig. 7A, B. As the B cell epitope on the surface, it exhibits a hydrophilic nature as shown in Fig. 8.
T Cell Epitopes: Since the immune response of T cells is long-lasting compared to B cells, where the antigen can easily escape the antibody memory response 47, the T cell epitopes were predicted. CTL epitopes were predicted using IEDB / TepiTool, attached to all alleles of MHC I (HLA-A, -B, -C) available in the database, lots of epitopes resulted, these were subjected to filtration, mainly using proteasomal and TAP scores to distinguish the epitope from nonepitope 57, 58, percentile less than 1 and binding affinity less than 200 nm, only four epitopes are satisfied the restriction parameters, and are able to attach to many HLA alleles, Table 3.
TABLE 3: PROTEASOME SCORE AND TAP SCORE OF SELECTED T CELL EPITOPE AND THE ALLELES INTACT WITH THEM
Position | Sequence | Proteasome Score | TAP Score | Alleles |
53-61 | QTQTAQSGY | 1.29 | 1.23 | HLAA*01:01,HLAA*02:01,HLAA*03:01
HLAA*11:01,HLAA*23:01,HLAA*24:02 HLAA*25:01,HLAA*26:01,HLAA*30:01 HLAA*31:01 HLAB*0:01,HLAB*07:02,HLAB*08:01 HLAB*13:01,HLAB*14:02,HLAB*15:01 HLAB*15:02,HLAB*15:25,HLAB*35:01 HLAB*35:03,HLAB*37:01,HLAB*38:23 HLAB*44:02,HLAB*46:01,HLAB*48:01 HLAB*49:01,HLAB*51:01,HLAB*52:01 HLAB*55:01,HLAB*56:01,HLAB*58:01 HLAC*01:02,HLAC*02:09,HLAC*03:04 HLAC*04:01,HLAC*06:02,HLAC*07:04 HLAC*12:02,HLAC*12:03,HLAC*14:02 HLAC*15:02,HLAC*16:01,HLAC*17:01 |
64-72 | FNFSFLSSF | 1.12 | 1.10 | HLAA*01:01,HLAA*02:01,HLAA*03:01
HLAA*11:01,HLAA*23:01,HLAA*24:02 HLAA*25:01,HLAA*26:01,HLAA*29:02 HLAA*30:01,HLAA*31:01,HLAA*32:01 HLAA*33:03,HLAA*74:01 HLAB*07:02,HLAB*08:01,HLAB*13:01 HLAB*14:02,HLAB*15:02,HLAB*35:01 HLAB*37:01,HLAB*38:23,HLAB*40:01 HLAB*44:02,HLAB*46:01,HLAB*48:01 HLAB*49:01,HLAB*51:01,HLAB*52:01 HLAB*55:01,HLAB*56:01,HLAB*58:01 HLAC*02:09,HLAC*04:01,HLAC*06:02 HLAC*07:04,HLAC*12:02,HLAC*12:03 HLAC*14:02,HLAC*14:02,HLAC*15:02 HLAC*16:01,HLAC*17:01,HLAC*3:04 |
66-74 | FSFLSSFVY | 1.44 | 1.36 | HLAA*01:01,HLAA*02:01,HLAA*03:01
HLAA*23:01,HLAA*24:02,HLAA*26:01 HLAA*29:02,HLAA*30:01,HLAA*30:02 HLAA*31:01,HLAA*32:01,HLAA*32:01 HLAA*33:03,HLAA*68:02,HLAA*74:01 HLAB*07:02,HLAB*08:01,HLAB*13:01 HLAB*14:02,HLAB*15:01,HLAB*15:02 HLAB*15:25,HLAB*35:01,HLAB*35:03 HLAB*37:01,HLAB*38:23,HLAB*40:01 HLAB*44:02,HLAB*46:01,HLAB*48:01 HLAB*49:01,HLAB*51:01,HLAB*52:01 HLAB*55:01,HLAB*56:01,HLAB*58:01 HLAC*01:02,HLAC*02:09,HLAC*03:04 HLAC*04:01,HLAC*06:02,HLAC*07:04 HLAC*12:02,HLAC*12:03,HLAC*14:02 HLAC*16:01,HLAC*17:01 |
102-110 | NSLSVSLAY | 1.39 | 1.27 | HLAA*01:01,HLAA*02:01,HLAA*03:01
HLAA*11:01,HLAA*23:01,HLAA*24:02 HLAA*25:01,HLAA*26:01,HLAA*29:02 HLAA*30:01,HLAA*30:02,HLAA*31:01 HLAA*32:01,HLAA*33:03,HLAA*68:02 HLAA*74:01,HLAB*07:02 HLAB*08:01,HLAB*13:01,HLAB*14:02 HLAB*15:01,HLAB*15:02,HLAB*15:25 HLAB*35:01,HLAB*35:03,HLAB*37:01 HLAB*38:23,HLAB*40:01,HLAB*44:02 HLAB*48:01,HLAB*49:01,HLAB*51:01 HLAB*51:01,HLAB*52:01,HLAB*55:01 HLAB*56:01,HLAB*58:01 HLAC*01:02,HLAC*02:09,HLAC*03:04 HLAC*04:01,HLAC*06:02,HLAC*07:04 HLAC*12:02,HLAC*12:03,HLAC*14:02 HLAC*15:02,HLAC*16:01,HLAC*17:01 |
Cell responses of cytotoxic (CD8) and helper cells (CD4) play a major role in antiviral immunity (as mentioned previously), so designing of vaccines provoking T cell is much promising 47, and investigation of binding affinity of antigenic epitope to MHC molecules is the goal for predicting epitopes 30 as the processing and presentation of MHC I of antigen is a key mechanism in surveilling and recognizing viral particles by immune system of the infected cells 53, on the other hand, epitope has high binding affinity to several alleles tends to be potential candidate for epitope based vaccine design , and this verified by the selected epitopes mentioned above. T helper cell (CD4) epitopes were predicted as well using IEDB / TepiTool, with percentile less than 1, and binding affinity less than 200nM, and all MHC II alleles (HLA-DR, -DP, -DQ) available in the database, 8 epitopes with 15mer were resulted, all of them have antigenic score above the VaxiJen threshold (0.4), these are shown in Table 4.
TABLE 4: EPITOPES FOR T HELPER CELLS AND THE REACTING HLAs MOLECULES
Position | Sequence | Alleles |
60-74 | GYYNFNFSFLSSFVY | HLA-DPA1*01/DPB1*04:01, HLA-DPA1*01:03/DPB1*02:01, HLA-DPA1*02:01/DPB1*01:01, HLA-DRB1*11:14,HLA-DRB1*11:20,HLA-DRB1*11:14,HLA-DRB1*11:20 |
13-27 | KFIVYRETSVNTTLV | HLA-DRB1*15:06,HLA-DRB1*04:02,HLA-DRB1*08:01,HLA-DRB1*08:04,HLA-DRB1*08:06,HLA-DRB1*08:13,HLA-DRB1*08:17 |
28-42 | LTNFTFTNVSNALPN | HLA-DRB1*04:03, HLA-DRB1*04:04, HLA-DRB1*04:06,
HLA-DRB1*04:07, HLA-DRB1*04:09, HLA-DRB1*04:14, HLA-DRB1*04:16, HLA-DRB1*04:17 HLA-DRB1*04:19,HLA-DRB1*04:45,HLA-DRB1*04:46,HLA-DRB1*04:47,HLA-DRB1*04:48,HLA-DRB1*04:49,HLA-DRB1*04:50,HLA-DRB1*04:52,HLA-DRB1*04:56,HLA-DRB1*04:57,HLA-DRB1*04:60 |
43-57 | TGGVNTINIYQTQTA | HLA-DRB1*04:02, HLA-DRB1*04:08,HLA-DRB1*04:23,HLA-DRB1*08:02,HLA-DRB1*08:04,HLA-DRB1*08:06,HLA-DRB1*08:13
HLA-DRB1*11:02,HLA-DRB1*11:21,HLA-DRB1*11:02,HLA-DRB1*11:21,HLA-DRB1*15:06 |
48-62 | TINIYQTQTAQSGYY | HLA-DRB1*04:02,HLA-DRB1*04:08,HLA-DRB1*04:21,HLA-DRB1*04:23,HLA-DRB1*08:02,HLA-DRB1*08:04,HLA-DRB1*08:06,HLA-DRB1*08:13,HLA-DRB1*11:02,HLA-DRB1*11:21,HLA-DRB1*11:02,HLA-DRB1*11:21 |
62-76 | YNFNFSFLSSFVYKQ | HLA-DRB1*03:05,HLA-DRB1*15:01,HLA-DRB1*15:08,HLA-DRB1*15:11,HLA-DRB1*15:14,HLA-DRB1*15:15,HLA-DRB1*15:19,HLA-DRB1*15:26,HLA-DRB1*15:29,HLA-DRB1*15:30,HLA-DRB1*15:31,HLA-DRB1*15:38,HLA-DRB1*15:39,HLA-DRB1*15:44,HLA-DRB1*15:47 |
96-110 | NNGLWFNSLSVSLAY | HLA-DRB1*04:01,HLA-DRB1*04:03,HLA-DRB1*04:05,HLA-DRB1*04:44,HLA-DRB1*04:45,HLA-DRB1*04:46,HLA-DRB1*04:47,HLA-DRB1*04:48,HLA-DRB1*04:49,HLA-DRB1*04:50,HLA-DRB1*04:51,HLA-DRB1*04:52,HLA-DRB1*04:54,HLA-DRB1*04:57,HLA-DRB1*04:60,HLA-DRB1*04:61,HLA-DRB1*04:44,HLA-DRB1*08:13 |
97-111 | NGLWFNSLSVSLAYG | HLA-DRB1*01:01,HLA-DRB1*01:13,HLA-DRB1*01:14,HLA-DRB1*01:17,HLA-DRB1*04:06,HLA-DRB1*04:07,HLA-DRB1*04:08,HLA-DRB1*04:09,HLA-DRB1*04:16,HLA-DRB1*04:17,HLA-DRB1*04:19,HLA-DRB1*01:21,HLA-DRB1*01:24,HLA-DRB1*01:29,HLA-DRB1*09:01,HLA-DRB1*10:01,HLA-DRB1*10:03,HLA-DRB1*09:01,HLA-DRB1*10:01,HLA-DRB1*10:03,HLA-DRB1*14:10 |
All the epitopes were BLASTed using NCBI/ BLAST and were found to for spike protein of IBV, in addition their allergenicity were also estimated and found in agreement with FAO/WHO regulations.
Docking Studies: Molecular docking is a key tool in structural molecular biology and computer -assisted drug design, and binding of immunogenic epitopes to MHC molecules makes reliable predictions of epitopes that minimizes the experimental efforts needed to identify new epitopes to be used in vaccine design 35, at the same time little information about MHC alleles in poultry are available 59, while MHCs of several organisms are supported by tools of IEDB, chicken not among them, and there is no database or software available to calculate the binding affinity of epitope with specific chicken MHC I or MHCII alleles 47, but the attitude used by researchers is to use human MHC molecules (HLAs) at the computational stages, and this confirmed by molecular docking with known chicken MHC molecules, This depending on facts that several studies suggest similarity between HLA alleles and chicken MHC 60-63, and since the MHC molecules are among the most polymorphic proteins in higher vertebrates, and there are more than 6000 alleles for MHC I and MHC II, this necessities developing of Bioinformatics tools to deal with 30.
MHC I alleles (HLA-A, -B, -C) were chosen instead of B-F chicken alleles at a computational prediction stage, since B-F molecules have been structurally and functionally linked to mammalian MHC I and involved in antigen presentation to CD8 T lymphocytes 64. Among, the B-F molecules BF2*21:01 is predominantly expressed and exhibits a promiscuous peptide binding affinity, so it performs a uniqueness in flexibility for binding different peptides 63, the other MHC I allele BF2.0401, is positively charged molecule and practically can bind a variety of epitope peptides 65.
All the predicted epitopes were subjected to PEP-FOLD 3.0 web-based servers for 3D structure conversion in order to analyze the interactions with HLA molecules. The epitopes of Table 3 were docked with BF2*21:01 (pdb ID 3bev) and BF2.0401 (pdb ID 4g42) using PyRx Virtual Screening Tool version 8, the Grid extended to cover the protein molecule, epitope used as ligand, the parameters for docking each epitope shown in Table 5.
TABLE 5: THE PARAMETERS USED FOR DOCKING PROCESS
Position | Sequence | Δ G kal/mol | RMSD value |
3bev | |||
53-61 | QTQTAQSGY | -8.3 | 0 |
64-72 | FNFSFLSSF | -8.1 | 0 |
66-74 | FSFLSSFVY | -9.2 | 0 |
102-110 | NSLSVSLAY | -7.2 | 0 |
4g42 | |||
53-61 | QTQTAQSGY | -8.9 | 0 |
64-72 | FNFSFLSSF | -8.8 | 0 |
66-74 | FSFLSSFVY | -8.9 | 0 |
102-110 | NSLSVSLAY | -8.0 | 0 |
Visualization shown in Fig. 9A for 3bev allele and Fig. 9B for 4g42 allele.
The 3D structure of chicken B-L (MHC II molecules) and human HLA-DR1 are similar at 66%, the former has more polymorphic sites, probably to compensate responding to wide varieties of pathogens in chickens 61. In addition MHC II binding groove is open from both ends unlike MHC I binding groove which is closed, therefore longer peptides (more than 15mer) can fit in this groove 35, this variability in binding makes prediction / docking difficult and less accurate 35, and since there is no pdb structure for chicken MHC II molecules available, this docking was unable to perform.
Nowadays, it seems never-ending race with IBV as new variants are continuously emerging in major poultry production countries, and most vaccines are based on B cell immunity which can be escaped, but recently T cell (CD8) immunity generates a strong immune response is practiced 14. On the other hand, many vaccines trails are currently being conducted worldwide , but they fail to reach phase III, this indicates a gap between the early stages trials (phase I and phase II) and the efficacy trail (phase III) 31. And it is well known that the core goal behind all vaccinations is to initiate an immune response in a quicker fashion than the pathogen itself 30.
CONCLUSION: In conclusion peptide (epitope) vaccine is strongly supersedes the conventional vaccines as it design to cover variant virulent mutated strains, which will reduce the recurrent outbreaks in vaccinated flocks and their huge accompanied economical loss to the minimum. In addition epitope vaccine helps in exclusion of suppressive epitopes and exclude the emergence of new variants by mutation of the viral genome and recombination with other viruses. So in this approach it is possible to incorporate several epitope peptides directed against different viruses or multiple virus strains into single delivery system, with view to induce broad and specific immune response in a single administration 55, 66.
FIG. 9A: DOCKING WITH BF2*21:01 (CHICKEN MHC I MOLECULE)
FIG. 9B: DOCKING WITH BF2.0401 (CHICKEN MHC I MOLECULE)
Epitope based vaccine designing is more promising, as the conventional vaccines lies on the response induced by the natural immunogen which are not optimal. In this study the selected protein was used for epitope prediction supposed to work with all strains. And this can be combined with global types to generate universal vaccine. Overlapped epitopes predicted in this study could introduce the possibility of antigen presentation to immune cells via both MHC I (B-F) and MHC II(B-L) pathways.
ACKNOWLEDGEMENT: Nil
CONFLICT OF INTEREST: Nil
REFERENCES:
- Bande F, Arshad S, Rahman Omar A, Hair-Bejo M, Mahmuda A and Nair V: Global distributions and strain diversity of avian infectious bronchitis virus: a review. Animal Health Research Reviews 2017; 18: 70-83.
- Cavanagh D, Davis PJ and Mockett A: Amino acids within hypervariable region 1 of avian Corona virus IBV (Massachusetts serotype) spike glycoprotein are associated with neutralization epitopes. Virus Research 1988; 11: 141-
- Lin S and Chen H: Infectious bronchitis virus variants: molecular analysis and pathogenicity investigation. International Journal of Molecular Sciences 2017; 18: 1-17.
- Valastro V, Holmes E, Britton P, Fusaro A, Jackwood M and Cattoli G: S1 gene-based phylogeny of infectious bronchitis virus: An attempt to harmonize virus classification. Infection, Genetics and Evolution Journal 2016; 39: 349-364.
- Belouzard S, Millet J, Licitra B and Whittaker G: Mechanisms of coronavirus cell entry mediated by the viral spike protein. Viruses 2012; 4: 1011-1033.
- Bochkov YA, Batchenko GV, Shcherbakova LO, Borisov AV and Drygin VV: Molecular epizootiology of avian infectious bronchitis in Russia. Avian Pathology 2006; 35: 379-393.
- Cavanagh D and Davis P: Coronavirus IBV: Removal of spike glycopolypeptide S1 by urea abolishes infectivity and haemagglutination but not attachment to cells. Journal of General Virology 1986; 67: 1443-1448.
- Promkuntod N, Van Eijndhoven R, De Vrieze G, Gröne A and Verheije M: Mapping of the receptor-binding domain and amino acids critical for attachment in the spike protein of avian coronavirus infectious bronchitis virus. Virology 2014; 448: 26-32.
- Casais R, Dove B, Cavanagh D and Britton P: Recombinant avian infectious bronchitis virus expressing a heterologous spike gene demonstrates that the spike protein is a determinant of cell tropism. Journal of Virology 2003; 77: 9084-9089.
- Ma C, Li Y, Wang L, Zhao G, Tao X and Tseng CT: Intranasal vaccination with recombinant receptor-binding domain of MERS-CoV spike protein induces much stronger local mucosal immune responses than subcutaneous immunization: Implication for designing novel mucosal MERS vaccines. Vaccine 2014; 32: 2100-2108.
- Yang ZY1, Kong WP, Huang Y, Roberts A, Murphy BR and Subbarao K: A DNA vaccine induces SARS coronavirus neutralization and protective immunity in mice. Nature 2004 ; 428: 561-564.
- Agnihothram S, Gopal R, Yount BL, Donaldson EF, Menachery VD and Graham RL: Evaluation of serologic and antigenic relationships between Middle Eastern respiratory syndrome coronavirus and other coronaviruses to develop vaccine platforms for the rapid response to emerging coronaviruses. The Journal of Infectious Diseases 2014; 209: 995-1006.
- Cavanagh D: Severe acute respiratory syndrome vaccine development: Experiences of vaccination against avian infectious bronchitis coronavirus. Avian Pathology 2003; 32: 567-582.
- Oany A, Emran AA and Jyoti TP: Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in-silico Drug Design, Development and Therapy 2014; 8: 1139-1149.
- Alazawy A, Abdulhussain S, Nasser A, Albaldawy A, Bande F and Jameel G: Serological survey and molecular detection of infectious bronchitis virus in broiler chickens in Diyala province, Iraq. International Journal of Poultry Science 2017; 16: 88-92.
- Meir R, Rosenblut E, Perl S, Kass N, Ayali G, Hemsani E and Perk S: Identification of a novel nephropathogenic infectious bronchitis virus in Israel. Avian Disease 2004; 48: 635-41.
- Mahmood ZH, Sleman RR and Uthman AU: Isolation and molecular characterization of Sul/01/09 avian infectious bronchitis virus, indicates the emergence of a new genotype in the Middle East. Veterinary Microbiology 2011; 150: 21-27.
- Atta R and Allawe A: Isolation and sequencing of field isolates of avian infectious bronchitis virus in Iraq. Journal of Entomology and Zoology Studies 2018; 6: 529-540.
- Ababneh M, Dalab A, Alsaad S and Al-Zghoul1 M: Presence of infectious bronchitis virus strain CK/CH/LDL/97I in the Middle East. ISRN Veterinary Science 2012; 1-6.
- Seger W, GhalyanchiLangeroudi A , Karimi V, Madadgar O Marandi M and Hashemzadeh M: Genotyping of infectious bronchitis viruses from broiler farms in Iraq during 2014-2015. Archives of Virology 2016; 161: 1229-1237.
- Kahya S , Coven F , Temelli S , Eyigor A and Carli K : Presence of IS/1494/06 genotype-related infectious bronchitis virus in breeder and broiler flocks in Turkey. Ankara Üniversitesi Veteriner Fakültesi Dergisi 2013; 60: 27-31.
- Awad F, Baylis M and Ganapathy K: Detection of variant infectious bronchitis viruses in broiler flocks in Libya. International Journal of Veterinary Science and Medicine 2014; 2: 78-82.
- Hussein M, Emara M, Rohaim M, Ganapathy K and Arafa A: Sequence analysis of infectious bronchitis virus IS/1494 like strain isolated from broiler chicken co-infected with Newcastle disease virus in Egypt during 2012. International Journal of Poultry Science 2014; 13: 530-536.
- Hosseini H, Fard MH, Charkhkar S and Morshed R: Epidemiology of avian infectious bronchitis virus genotypes in Iran (2010-2014). Avian Diseases 2015; 59: 431-435.
- Najafi H, Langeroudi AG, Hashemzadeh M, Karimi V, Madadgar O, Ghafouri SA, Maghsoudlo H and Farahani RK: Molecular characterization of infectious bronchitis viruses isolated from broiler chicken farms in Iran, 2014- Archives of Virology 2016; 161: 53-62.
- Callison S, Jackwood M, and Hilt D: Molecular characterization of infectious bronchitis virus isolates foreign to the United States and comparison with United States isolates. Avian Diseases 2001; 45: 492 -499.
- Abdel-Moneim AS, Afifi MA and El-Kady MF: Emergence of a novel genotype of avian infectious bronchitis virus in Egypt. Archives of Virology 2012; 157: 2453-2457.
- Gelb J, Weisman Y, Ladman BS and Meir R: S1gene characteristics and efficacy of vaccination against infectious bronchitis virus field isolates from the United States and Israel (1996 to 2000). Avian Pathology 2005; 34: 194-
- Murrell S, Wu SC and Butler M: Review of dengue virus and the development of a vaccine. Biotechnology Advances 2011; 29: 239-247.
- Patronov A and Doytchinova I: T-cell epitope vaccine design by immunoinformatics. Open Biol 2013; 3: 1-13.
- Raghuwanshi R, Singh M and Shukla V: Immuno-informatic Approaches in Epitope Prediction for Vaccine Designing against Viral infections. Virology and Immunology Journal 2018; 2: 1-5.
- Moise L and De Groot AS: Putting immunoinformatics to the test. Nature Biotechnology 2006; 24: 791-792.
- Tomar N and De R: Immunoinformatics: an integrated scenario. Immunology 2010; 131: 153-168.
- De Groot A, Ardito M, Moise L, Gustafson E, Spero D and Tejada G: Immunogenic consensus sequence T helper epitopes for a pan-burkholderia biodefense vaccine. Immunome Research 2011; 7: e7.
- Srivastava P, Jain R, Dubey S, Bhatnagar S and Ahmad N: Prediction of epitope-based peptides for vaccine development from coat proteins GP2 and VP24 of Ebola virus using immunoinformatics. International Journal of Peptide Research and Therapeutics 2016; 22: 119-133.
- Kumar S, Stecher G and Tamura K: MEGA7 Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Molecular Biology and Evolution 2016; 33: 1870-1874
- Hall T and Carlsbad C: BioEdit an important software for molecular biology. GERF Bulletin of Biosciences 2011; 2: 60-61.
- Kelley L, Mezulis S, Yates C, Wass M and Sternberg M: The Phyre2 web portal for protein modelling, prediction and analysis. Nature Protocols 2015; 10: 845-858.
- Lamiable A, Thévenet P, Rey J, Vavrusa M, Derreumaux P and Tufféry P: PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex. Nucleic Acids Research 2016; 8: W449-454.
- Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD and Cantrell JR: The immune epitope database (IEDB) 3.0. Nucleic Acids Research 2015; 43: D405-D412.
- Dallakyan S and Olson AJ: Small-molecule library screening by docking with PyRx. Methods in Molecular Biology 2015; 1263: 243-250.
- Trott O and Olson AJ: AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry 2010; 31: 455-461.
- Suvannang N, Nantasenamat C Isarankura-Na-Ayudhya C and Prachayasittikul V: Molecular docking of aromatase inhibitors. Molecules 2011; 16: 3597-3617.
- RoseP, Prlić A, Altunkaya A, Bi C, Bradley A and Christie C: The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucleic Acids Research 2017; 45: D271-D281.
- Corpet F: Multiple sequence alignment with hierarchical clustering. Nucleic Acids Research 1988; 16: 10881-890.
- Tambunan U, Sipahutar F, Parikesit A and Kerami D: Vaccine design for H5N1 based on B- and T-cell epitope predictions. Bioinformatics and Biology Insights 2016; 10: 27-35.
- Badawi M, Fadl Alla A, Alam S, Mohamed W, Osman D and Ali S: Immunoinformatics predication and in silico modeling of epitope-based peptide vaccine against virulent Newcastle disease viruses. American Journal of Infectious Diseases and Microbiology 2016; 4: 61-71.
- Cavanagh D, Elus M and Cook J: Relationship between sequence variation in the S1 spike protein of infectious bronchitis virus and the extent of cross-protection in-vivo. Avian Pathology 1997; 26: 63-74.
- Han Z, Sun C, Yan B, Zhang X, Wang Y and Li C: A 15-year analysis of molecular epidemiology of avian infectious bronchitis coronavirus in China. Infection, Genetics and Evolution Journal 2011; 11: 190-200.
- Koch G, Hartog L, Kant A and van Roozelaar DJ: Antigenic domains on the peplomer protein of avian infectious bronchitis virus: correlation with biological functions. Journal of General Virology 1990; 71: 1929-1935.
- Moore KM, Jackwood MW and Hilt DA: Identification of amino acids involved in a serotype and neutralization specific epitope within the S1 subunit of avian infectious bronchitis virus. Archives of Virology 1997; 142: 2249-2256.
- Singh S Taneja B, Salvi SS and Agrawal A: Physical properties of intact proteins may predict allergenecity or lack thereof. PLoS One 2009; 17:
- Tan L, Liao Y, Fan J, Zhang Y, Mao X and Sun Y: Prediction and identification of novel IBV S1 protein derived CTL epitopes in chicken. Vaccine 2016; 34(3): 380-386.
- Ignjatovic J and Galli L: The S1 glycoprotein but not the N or M proteins of avian infectious bronchitis virus induces protection in vaccinated chickens. Archives of Virology 1994; 138: 117-134.
- Bande F, Arshad S, Bejo M, Kadkhodaei S and Omar A: Prediction and in-silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for Application in Peptide Vaccines. Advances in Bioinformatics 2016; 1-5.
- Guo Z, Wang H, Yang T, Wang X, Lu D, Li Y and Zhang Y: Priming with a DNA vaccine and boosting with an inactivated vaccine enhance the immune response against infectious bronchitis virus. Journal of Virological Methods 2010; 167: 84-89.
- Tenzera S, B. Petersb B, Bulikb D, Schoorc O, Lemme C and Schatza M: Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding. Cellular and Molecular Life Sciences 2005; 62: 1025-1037.
- Peters B, Bulik S, Tampe R, van Endert P and Holzhu¨ tter H : Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors. The Journal of Immunology 2003; 171: 1741-1749.
- Chen F, Pan L, Zhang J, Zhou X, Li J and Yu W: Allele dependent association of chicken MHC class I molecules with the invariant chain. Veterinary Immunology and Immunopathology 2014; 160: 273-280.
- Spike C and Lamont S: Genetic analysis of 3 loci homologous to human G9a: evidence for inkage of a class III gene with the chicken MHC. Animal Genetics 1995; 26: 185-187.
- Chen F, Pan L, Chao W, Dai Y and Yu W: Character of chicken polymorphic Major Histocompatibility Complex Class II alleles of 3 Chinese local breeds. Poultry Science 2012; 91(5): 1097-1104.
- Chappell P, Meziane E, Harrison M, Magiera L, Clemens Hermann C and Mears L: Expression levels of MHC class I molecules are inversely correlated with promiscuity of peptide binding. eLife 2015; 4: e05345
- Koch M, Camp S, Collen T, Avila D, Salomonsen J and Wallny HJ: Structures of an MHC class I molecule from B21 chickens illustrate promiscuous peptide binding. Immunity 2007; 27: 885-899.
- Butter C, Staines K, van Hateren A, Davison F and Kaufman J: Peptide motifs of the single dominantly expressed class I molecule explain the striking MHC-determined response to Rous sarcoma virus in chickens. Proceedings of the National Academy of Sciences 2006; 103: 1434-1439.
- Zhang J, Chen Y, Qi J, Gao F, Liu Y and Liu J: Narrow Groove and Restricted Anchors of MHC Class I Molecule BF2*0401 Plus Peptide Transporter Restriction Can Explain Disease Susceptibility of B4 Chickens. J Immunol 2012; 189: 4478-4487. doi: 10.4049/jimmunol.1200885
- Bande F, Arshad S, Bejo M, Moeini H and Omar A: Progress and challenges toward the development of vaccines against avian infectious bronchitis. Journal of Immunology Research 2015; 1-12.
How to cite this article:
Al-Khafaji ZM and Mahmood AB: Epitope vaccine design for variant 2 strains circulating in Iraq and the Middle East. Int J Pharm Sci & Res 2018; 9(12): 5086-97. doi: 10.13040/IJPSR.0975-8232.9(12).5086-97.
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Article Information
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5086-5097
977
1143
English
IJPSR
Z. M. Al-Khafaji * and A. B. Mahmood
Institute of Genetic Engineering and Biotechnology for Postgraduate Studies, University of Baghdad, Iraq.
zahranasserk@gmail.com
19 April, 2018
07 July, 2018
18 July, 2018
10.13040/IJPSR.0975-8232.9(12).5086-97
01 December, 2018