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Novel Multi Epitopes Vaccine Candidates against Vesicular Stomatitis Virus through Reverse Vaccinology

Walla Hasab Elrasoul Makki, Yassir A. Almofti*, Khoubieb Ali Abd-elrahman, Sanaa Bashir

Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum- Sudan

Abstract: Vesicular stomatitis (VS) is a disease of horses, cattle and swine caused by vesicular stomatitis virus (VSV). The virus belongs to the genus Vesiculovirus of the family Rhabdoviridae. The disease has no treatment or vaccine. Therefore the aim of this study was to design multi-epitopes vaccine against vesicular stomatitis New Jersey virus using peptides of the glycoprotein to stimulate protective immune response. A total of 46 sequences of the Glycoprotein of VSV were retrieved from NCBI database. Sequences were aligned to determine the conservancy and to predict epitopes using IEDB analysis resource. Six epitopes were predicted as promising B cell epitopes since they fulfilled the criteria of surface accessibility, antigenicity and proposed as most probable B cell epitope. These epitopes were ₃₉₃₋VLKTKQGYK₋₄₀₁, ₁₄₇₋PHSVKVDEY₋₁₅₅, ₄₅₄₋SKNPVEL₋₄₆₀, ₂₄₀₋CRKPGYKL₋₂₄₇, ₄₂₇₋HPHIE₋₄₃₁ and ₅₀₅₋PIYKS₋₅₀₉. For T cell; four epitopes ₈₆₋FRWYGPKYI₋₉₄, ₁₈₄₋FTSSDGESV₋₁₉₂, ₁₈₉₋GESVCSQLF₋₁₉₇ and ₁₀₈₋CLEAIKAYK-116 were proposed as MHC-I epitopes since they interacted with the highest numbers of alleles and with high binding affinity. For MHC-II four epitopes namely ₂₄₁LKNDLWFQI₂₅₅, ₈₆FRWYGPKYI₉₄, ₁₈₄FTSSDGESV₁₉₂, and ₁₈IEIVFPQHT26 were proposed as peptide vaccine since they interacted with high affinity to MHC-II alleles. It is noteworthy the epitopes ₈₆₋FRWYGPKYI₋₉₄, ₁₈₄₋FTSSDGESV-192 were found interacting with both MHC-I and MHC-II. Thus they further used for docking with the equine haplotype molecules (ELA-A3) where they demonstrated lowest binding energy to the equine MHC class I molecule haplotype. To our knowledge there is no epitope based vaccine for the Vesicular stomatitis New Jersey Virus (VSV-NJ) via reverse vaccinology. In this study, twelve epitopes were proposed eliciting both humeral and cell mediated immunity and predicted to act as a promising peptide vaccine against VSV. Clinical trial is required to proof these epitopes as an efficient vaccine against vesicular stomatitis virus.

Keywords: Vesicular stomatitis Virus (VSV), Epitope, Peptide vaccine, Immune epitope database (IEDB), NCBI

Received September 05, 2019; Revised October 06, 2019; Accepted October 18, 2019

Citation: Walla Hasab Elrasoul Makki, Yassir A. Almofti, Khoubieb Ali Abd-elrahman, Sanaa Bashir, Novel Multi Epitopes Vaccine Candidates against Vesicular Stomatitis Virus through Reverse Vaccinology. American Journal of Infectious Diseases and Microbiology, 7 (1). 43-56. January 2019. doi:10.12691/ajidm-7-1-6

1. Introduction

Vesicular stomatitis (VS) is a disease of horses, cattle, and swine caused by vesicular stomatitis virus (VSV). The virus belongs to the genus Vesiculovirus of the family Rhabdoviridae [1,2]. The disease is transmitted by black flies (Simulium spp.), sand flies (Lutzomyia spp.) and biting midges (Culicoides spp.) [3,4]. Clinically the affected animals showed typical vesicular lesions on muzzle, tongue, lips, or coronary band and teats [5,6]. The VS is classified as A-list infectious disease of the Office International des Epizooties (OIE) with economically important contagious disease of livestock [7,8]. The disease is endemic in Central America and northern regions of South America. Recently outbreaks were reported between 2004- 2006 and the infected horses reached up to 78% and 68% in cattle [9,10].

Vesicular stomatitis virus (VSV) contains two main serotypes; New Jersey and Indiana vesicular stomatitis. The former serotype account for more than 80% of the clinical cases reported in endemic areas [11,12]. VSV is negative-sense single-stranded genome encodes five structural proteins, nucleoprotein (N), Phosphproteins (P), matrix protein (M), glycoprotein (G), and polymerase (L) [13]. Glycoprotein was used as a vaccine vector and it has been shown to be the main antigenic target for immune response to the virus [14,15,16,17].

Vaccination is usually considered to be the most effective method of preventing infectious diseases. The only vaccine available for the control of VS is an inactivated preparation. This vaccine showed no successful results [18,19]. Efforts to create live attenuated vaccines, subunit- or DNA mediated vaccines against VSV was initiated but have limited success [20,21]. At present there is no satisfactory vaccine against VSV infection. Therefore successful approaches for vaccine design against vesicular stomatitis virus are highly required. Epitope-based vaccines can be constructed for B-cell to predict epitopes that mainly induce antibody production and the T-cell epitopes that induce cellular response and cytokine secretion as cytotoxic T-cells. The advantages of epitope-based vaccines; it focused on the immune response, enhancing immunity and avoiding undesirable epitopes and reducing costs. The peptide vaccines have been developed for many infectious diseases [22,23,24,25,26,27,28,29,30,31]. Therefore the aim of this study was to design a peptide vaccine against vesicular stomatitis New Jersey virus using peptides of its glycoprotein as an immunogen to stimulate protective immune response.

2. Materials and Methods

2.1. Retrieval of Protein Sequences

A total of 46 Glycoprotein sequences of New Jersey Vesicular stomatitis virus were retrieved from National Center for Biotechnology Information database (NCBI) (https://www.ncbi.nlm.nih.gov/protein/) in 19th September 2017. Most of these sequences were from USA. The retrieved sequences and their accession numbers as well as the date and the region of collection were listed in Table 1.

2.2. Phylogenetic Evolution

Phylogenetic tree of the retrieved sequences of the capsid proteins of HEV was created using MEGA7.0.26 (7170509) software [32]. The protein tree was constructed using maximum likelihood parameter in the software.

2.3. Determination of Conserved Regions

Multiple sequence alignment was used to obtain conserved regions in the retrieved sequences using Clustal-W as applied in the Bio-Edit program (version 7.2.5.0) [33]. Candidate epitopes were analyzed by different prediction tools at the Immune Epitope Database IEDB analysis resource (http://www.iedb.org/).

2.4. B-cell Epitope Prediction

B-cell epitopes were characterized by their antigenicity, hydrophilicity, surface accessibility and flexibility. Hence, the reference sequence of glycoprotein was analyzed by several B-cell prediction tools. BepiPred linear epitope prediction tools was used to predict linear epitopes [34,35], Emini surface accessibility prediction tool was used to predict surface epitopes [36], and kolaskar and tongaonker antigenicity tool was used to predict antigenic epitopes [37].

Table 1. Retrieved virus strains, their accession numbers and their area of collection

2.5. T-Cell Epitope Prediction

T cell epitopes were predicted by tools available in Immune Epitope Database (IEDB) (tools.immuneepitope.org) which provides on Major Histocompatibility Complex (MHC) binding predictions. It is noteworthy in this study the human alleles in the IEDB were used to predict the MHC-1 and MHC-11 binding epitopes.

2.5.1. MHC Class I Binding Predictions

MHC I prediction tool has been used to analyze the preferential binding of Glycoprotein to MHC class I molecule. A different method for MHC-1 binding prediction was available in the Immune Epitope Database (IEDB). The artificial neural network (ANN) was used to calculate IC50 values of peptide binding to MHC-1 molecules and calculation of the HLA alleles [38,39]. Before prediction, all peptides length was set to 9 amino acids [30]. The alleles having binding affinity IC50 equal to or less than 300 nM were suggested as candidate epitopes.

2.5.2. MHC Class II Binding Predictions

Peptide binding analysis of MHC class II molecules was assessed by the IEDB MHCII prediction tool. Certain HLA-DR, HLA-DP, HLA-DQ alleles were analyzed [40,41]. MHCII binding prediction was achieved using NN-align method [42]. All epitopes that bind to many alleles at score equal to or less than 1000 half-maximal inhibitory concentration (IC50) were proposed as MHCII epitopes.

2.6. Homology Modeling

The reference sequence of Glycoprotein of VSV-NJ was used to create the 3D structure by Raptor X server at (http://raptorx.uchicago.edu/Structure Prediction/predict/) and UCSF Chimera (version 1.8) was used to visualize the selected epitopes belonging to the B- cell, MHC I, and MHC II [43].

2.7. Molecular Docking

Pep fold software was used to predict the three dimensional structure of selected peptides [44]. Raptor X was used to predict 3D structure of the MHC class I of Equas Caballus ELA-A3 haplotype (NP_001116853.1). These structures were further prepared for running docking in Patch Dock server [45] and visualized using Chimera 1.8. [43]

3. Results

3.1. Phylogenetic Evolution

Phylogenetic tree demonstrated the evolutionary divergence within the retrieved sequences of the glycoprotein. As shown in Figure 1 retrieved strains showed molecular divergence in their common ancestors.

3.2. Sequences Alignment

Sequence alignment of all retrieved strains was performed using ClustalW that presented by Bioedit software. As shown in Figure 2, the retrieved sequences demonstrated conservancy when sequences were aligned. The conserved regions were recognized by identity of amino acid sequences among the retrieved sequences.

3.3. B-cell Epitope Prediction

As shown in Figure 3, BepiPred linear epitopes prediction, Emini surface accessibility and kolaskar and tongaonker antigenicity tools were used for prediction of B cells epitopes with thresholds of 0.031, 1.000 and 1.035, respectively. According to the criteria of B cell prediction tools; Bepipred linear epitope prediction tools proposed 32 epitopes as a linear epitopes. Emini surface accessibility and Kolaskar and Tongaonkar antigenicity methods proposed 25 and 13 epitopes, respectively. However ten epitopes only has passed the three criteria of B cell prediction tools. Table 2 demonstrated all these epitopes that predicted by the B cell tools. Among these epitopes; six epitopes were proposed as B cell epitopes since they got high scores in the three tools. The 3D structures of these six epitopes in the glycoprotein were provided in Figure 4.

3.4. MHC Class I Binding Predictions

IEDB MHCI epitope prediction tool generated 10 unique binding epitopes from the Glycoprotein having affinity values less or equal 300 nM that bound to highest number of MHCI alleles. These epitopes were demonstrated in Table 3. From these ten epitopes; four epitopes namely ₈₆FRWYGPKYI₉₄, ₁₈₄FTSSDGESV₁₉₂, ₁₈₉₋GESVCSQLF₋₁₉₇ and ₁₀₈₋CLEAIKAYK₋₁₁₆ were proposed as MHC-1 epitopes since they bound to high number of alleles with less IC50 and percentile rank. The 3D structures of these epitopes in the glycoprotein were provided in Figure 5 and Figure 6.

Figure 1. Evolutionary divergence analysis of capsid protein of the HEV. The retrieved strains showed divergence in their common ancestors

Figure 2. Multiple sequence alignment (MSA) of the retrieved strains using Bioedit software and ClustalW. Dots indicated the conservancy and letters showed the alteration in amino acid

Figure 3. Prediction of B-cell epitopes by different IEDB scales (a- Bepipred linear epitope prediction threshold 0.031, b- Emini surface accessibility threshold 1.000, c- Kolaskar and Tongaonkar antigenicity prediction threshold 1.035). Regions above threshold (red line) are proposed to be a part of B cell epitope while regions below the threshold (red line) were not

Table 2. B cell predicted epitopes. The table demonstrated the predicted conserved epitopes with their surface accessibility score (a) and antigenicity score (b)

Figure 4. Structural positions of the B cell epitopes of glycoprotein of New Jersey Vesicular stomatitis virus. The position of the six epitopes was shown encircled. The figure showed the positions of these epitopes from different sites of view of the same protein

Table 3. List of best epitopes that had binding affinity with the human MHC class I alleles

Table 4. List of the best four epitopes that had binding affinity with the human MHC class II alleles

3.5. MHC class II binding predictions

Peptides binding to MHC class II molecules were evaluating with the IEDB MHC-II prediction tools using human alleles. Several methods were used for analysis of MHC-II epitopes binding grooves. However the NN- align is important for instantaneous identification of the MHC class II binding core epitope. In this study, several core peptides were predicted to interact with considerable number of MHCII alleles. However four epitopes namely ₂₄₁LKNDLWFQI₂₅₅, ₈₆FRWYGPKYI₉₄, ₁₈₄FTSSDGESV₁₉₂, and ₁₈IEIVFPQHT26 demonstrated great binding interaction with 82, 78 and 44 and 39 MHC-II alleles, respectively. These four epitopes and their interacting alleles were provided in Table 4. The epitopes ₈₆FRWYGPKYI₉₄ and ₁₈₄FTSSDGESV₁₉₂ were found interacting in both MHC-I and MHC-II alleles. Thus their positions in the 3D structures of glycoprotein was depicted in Figure 5 while the 3D structures of ₁₈IEIVFPQHT26 and 241LKNDLWFQI₂₅₅ in the glycoprotein were depicted in Figure 6.

3.6 Docking of the Selected Epitopes with MHC Class 1 Alleles

Binding models of the best probable epitopes (₈₆FRWYGPKYI₉₄, ₁₈₄FTSSDGESV₁₉₂, ₁₈₉₋GESVCSQLF₋₁₉₇ and ₁₀₈₋CLEAIKAYK₋₁₁₆) to the equine ELA-A3 molecule was observed using Patch dock. As demonstrated in Table 5 lowest binding energy (kcal/mol) was selected to predict probable CTL epitopes based on the score of global energy and attractive VDW in kcal/mol unit of docked molecules. Docking of ₈₆FRWYGPKYI₉₄ and ₁₈₄FTSSDGESV₁₉₂ with ELA-A3 allele produced -22.07kcal/mol and -70.22kcal/mol global energy respectively. This indicated the strong binding affinity between the ligand and the receptor. Moreover, 189-GESVCSQLF₋₁₉₇ and ₁₀₈₋CLEAIKAYK-116 epitopes demonstrated favorable binding affinity with ELA-A3 allele with -23.72kcal/mol and 1.34kcal/mol global energy, respectively. Generally the docked molecules showed different binding site for ELA-A3 allele (Figure 7 and Figure 8). These results revealed that the docked epitopes could induce the humoral and cellular immunity responses.

Figure 5. Structural position of the two epitopes of glycoprotein of New Jersey Vesicular stomatitis virus that interacted with both MHC-I & MHC-II alleles. Also these two epitopes were docked with equine haplotype molecule

Figure 6. Structural positions of the other two promising T cell epitopes of glycoprotein of New Jersey Vesicular stomatitis virus. The position of the epitopes was shown in dark blue, purple and yellow colors. The figure showed the positions of these epitopes from different sites of view of the same protein

Figure 7. Visualization of the 3D structure of ELA-A3 equine allele (in green color) using chimera visualization tool. The a, b, c and d are the docked epitopes ₈₆FRWYGPKYI₉₄, ₁₈₄FTSSDGESV₁₉₂, ₁₈₉₋GESVCSQLF₋₁₉₇ and ₁₀₈₋CLEAIKAYK₋₁₁₆, respectively, (shown in yellow color) that proposed for CTL for docking with ELA-A3 equine allele

Table 5. The binding energy and Attractive VDW scores for the proposed epitopes with ELA-A3 equine allele using PatchDock server

Figure 8. Visualization of PatchDock Molecular docking of MHCI proposed epitopes and ELA-A3 equine allele receptors using UCSF-Chimera visualization tool. Receptors (ELA-A3 allele) represented by rounded ribbon structure green colour while CTL epitopes represent by yellow and red colors

4. Discussion

Vesicular stomatitis (VS) is contagious disease caused by Vesicular stomatitis virus (VSV) often causes a mortality rate exceeding 90% in horse. Vaccination is effective method of preventing Vesicular stomatitis (VS) such as inactivated preparation vaccine, live attenuated vaccine, and DNA mediated vaccine. But all these vaccine available have not performed successfully. Therefore, in this study we aim to predict peptide vaccine for the Vesicular stomatitis New Jersey virus of its glycoprotein as an immunogen to stimulate protective immune response. Peptide- based vaccine has good desirable immune response and a minimal immunological side effect. There are many peptide vaccines under development of designing vaccine and therapeutic for most infectious diseases such as influenza virus, cancer, Ebola virus, and other [46,47,48,49,50].

In this study the selected peptides that could be recognized by B cell and T cell epitope. For B cell epitope prediction; eight epitopes PKYI, VLKTKQGYK, PHSVKVDEY, SKNPVEL, CRKPGYKL, HPHIE, PIYKS, and DLPH got scores above the threshold of Emini and antigenicity, therefore that capable of inducing the desired immune response as B cell epitope. For MHC I and II binding prediction used human alleles in IEDB T-cell prediction tools since it showed similarity, because haven’t entered equine alleles as data [40,51,52].

There were two epitopes “FRWYGPKYI, FTSSDGESV” interacted with the highest numbers of MHC class I alleles and have high binging affinity and the lowest binding energy to equine MHC class I molecule (ELA-A3) haplotype in the structural level. FRWYGPKYI epitope was found to bind 5 MHCI Alleles; HLA-B*27:05, HLA-C*06:02, HLA-C*07:01, HLA-C*07:02, HLA-C*12:03 and FTSSDGESV epitope was found to bind 4 MHC II Alleles HLA-A*02:06, HLA-A*68:02, HLA-C*03:03, HLA-C*12:03. While in MHC II prediction, five most potential epitopes were chosen on the basis of highest number of MHC II alleles “IEIVFPQHT, FRWYGPKYI, FTSSDGESV, LKNDLWFQI, and LISDVERIL. This study proposed an interesting T cell epitope (FRWYGPKYI, FTSSDGESV) that have very strong binding affinity to both MHC1 and MHC11 alleles. So this epitope based vaccine would be able to elicit both humeral and cell mediated immunity. To our knowledge there is no epitope based vaccine for the Vesicular stomatitis New Jersey Virus (VSV-NJ) using immunoinformatics approach.

5. Conclusion

This study predicted novel B-cells and T-cell epitopes from the glycoprotein of Vesicular stomatitis New Jersey Virus strains. The proposed epitopes showed conservancy rates and demonstrated potentiality as based peptide vaccine for application in the control of Vesicular stomatitis New Jersey Virus infection. The use of such vaccines will likely reduce the challenges associated with live attenuated vaccines and allow broad coverage of the target Vesicular stomatitis New Jersey Virus strains. Accordingly Immunoinformatic techniques focused on immune response would avoid undesirable epitopes and reducing costs for designing of new vaccines and therapies.

Acknowledgments

Authors would like to thank the staff members of College of Veterinary Medicine, University of Bahri, Sudan for their cooperation and support.

Data Availability

The [glycoprotein of the retrieved strains was from the NCBI. Also analysis of the epitopes was in IEDB] data used to support the findings of this study are included within the article.

Conflict of Interests

The authors declared that they have no conflict of interests regarding the publication of this paper.

Funding

No funding was received

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