Designing of Multi-Epitope Peptide Vaccine Based on Outer Membrane Proteins OmpF, OmpC, and PgtE of Salmonella enterica Typhi

1. Introduction

Salmonella enterica is a gram-negative bacterium that causes salmonellosis and belongs to the Enterobacteriaceae family. S. enterica is a flagellating bacillus that causes gastrointestinal disease in humans and animals ( 1 ). There are six subspecies of S. enterica, which are: Enterica, Arizonae, Diarizonae, Salamae, Indica, and Houtenae ( 2 - 4 ). There are over 2600 Salmonella enterica serovars, and the most important serovars of S. enterica are Salmonella Typhi and Salmonella Typhimurium ( 5 ). Salmonella Typhi causes typhoid fever with typical symptoms, such as persistent fever, chills, and abdominal pain, killing many people each year. Salmonella is transmitted through feces and spread through contaminated water and food ( 6 ). An estimated 11 to 21 million cases of typhoid fever and approximately 128000 to 161000 deaths worldwide each year ( 7 ). Antimicrobial resistance of pathogenic intestinal bacteria is one of the global health problems today. Multiresistance of S. Typhi to ampicillin, chloramphenicol, and cotrimoxazole has been reported ( 8 - 10 ).

In recent years, various approaches have been taken to develop vaccines against Salmonella Typhi. This vaccine contains injectable Ty21a and Vi, which are moderately effective (50-80% protection) ( 11 ). Despite the fact that vaccines against typhoid fever are commonly administered, it is important to consider the immune mechanisms for enteric infections ( 12 ).

In recent years, immunoinformatics has been well established and applied to vaccine information of various microorganisms ( 13 ). Data based on the genomes of microorganisms can help predict the epitopes that can interact with the host immune system. However, mapping epitopes in immunogenic proteins is critical for peptide vaccine development. In S. Typhi, the immune potential of outer membrane proteins (Omps) has been studied ( 14 ). They are good candidates for the development of multi-epitope vaccines against Salmonella Typhi. The studies revealed that the epitopes can bind to human leukocyte antigen alleles (HLA) and major histocompatibility complex (MHC) class I and class II proteins, which play a central role in the immune system and are recognized by cytotoxic CD8⁺ T-cells and CD4⁺ T-cells, respectively ( 15 ). CD4⁺ and CD8⁺ epitopes are used for vaccine models that target a variety of pathogens ( 16 ). Vaccines based on multiple epitopes are cheaper, safe, time-saving, stable, highly specific, and bind to multi-epitope alleles simultaneously compared with vaccines produced in a conventional manner ( 17 ). Therefore, the goal was to develop an effective multiepitope vaccine against the bacterium S. Typhi. The vaccine was developed from the antigens OmpC, OmpF, and PgtE. Finally the docking of the ligand to a receptor (TLR4) was analyzed. Stability energy and electron surface map analysis was performed for a refined vaccine with TLR4 receptor.

2. Methods and Materials

2.1. Finding the protein retrieval

The sequence of OmpF (Uni-prot Accession no Q56113), OmpC (Uni-prot Accession no P0A264), and PgtE (Uni-prot Accession no P06185) from S. Typhi was retrieved from http://www.uniprot.org. The sequence obtained was stored in a text-based format known as FASTA.

2.2. Prediction of sequence-based CD8+ epitopes

The IEDB Analysis Resource tool was used to predict MHC-I alleles (http://tools.iedb.org/mhci), and a threshold of 0.5 was used to identify nine mer-amino acids. This software is freely available on the public website. This web server predicts epitopes in proteins based on accessibility, flexibility, antigenicity, and hydrophobicity.

2.3. Prediction of sequence-based CD4+ epitopes

IEDB (http://tools.iedb.org/mhcii/) was used to predict nine mer-linear CD4⁺ alleles. For this tool, the criterion for selecting candidate epitopes is a p-value greater than 0.5.

2.4. B-cell epitope

B-cells are lymphocytes responsible for humoral immunity and produce antibodies. IEDB software was used to predict and select appropriate linear and continuous B-cell epitopes in the vaccine structure. This web-based software allows prediction and analysis of B-cell epitopes using computational tools.

2.5. Allergenicity, Antigenicity, and immunogenicity

The VaxiJen server (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html) was used to predict the antigenic properties of epitopes. This server determines the antigenicity of the sequence based on the physicochemical properties of the proteins with a cut-off value of 0.5 and independent of the orientation of the protective antigens.

We used the AllerTop server (http://www.ddg-pharmfac.net/AllerTOP) to test the allergenicity of epitopes. The immunogenicity of OmpF, OmpC, and PgtE epitopes was checked at http://tools.iedb.org/immunogenicity. This web server predicts vaccine allergenicity based on key physical and chemical properties of the proteins.

2.6. Physicochemical activities

The ProtParam server (http://web.expasy.org/protparam) is used to study the physicochemical activities. It is used to report the amino acid composition, theoretical pI, molecular weight (MW), instability index, half-life, aliphatic index, and grand average hydropathy (GRAVY) of the construct.

2.7. Design and fusion of Epitopes

Epitopes were arranged as CD4⁺, CD8⁺, and B-cell of OmpF, OmpC, and PgtE, respectively (Fig. 1). Linker sequences of AAY were used in the case of MHC- I, KK for MHC- II, and GPGPG were incorporated into B-cell epitopes. Immunogenic proteins can increase the potency and efficacy of an epitope-based vaccine. For example, HBHA (AN: ZP_07011362.1) from Mycobacterium tuberculosis (N-terminal of the vaccine) was used as an adjuvant that can bind to TLR4 ( 18 ). The EAAAK linker with helical structure was placed on both sides of HBHA to minimize domain interaction ( 19 ).

Figure 1. Designing and fusing of epitopes

2.8. Prediction of secondary structure

PSIPRED tool (http://bioinf.cs.ucl.ac.uk/psipred) was used to predict the secondary structure. Four conformational states (helices, sheets, turns, and coils) of candidate genes were analyzed.

2.9. Modeling and refinement of the tertiary structure

RAPTORX server (http://raptorx.uchicago.edu/StructPredV2/) was used to predict the 3D structure. PyMOL is a comprehensive molecular software used to visualize 3D designs. ProSA is a powerful server (http://prosa.services.came.sbg.ac.at/prosa.php) used to check for possible errors. The predicted 3D structural model was refined using the Galaxyrefine server (https://galaxy.seoklab.org/cgi-bin/submit.cgi?type=REFINE). Ramachandran plot (http://swissmodel.expasy.org/workspace) predicts the structural stereochemical property in PROCHECK software ( 20 ).

2.10. Docking of vaccine (ligand) to TLR4 (receptor)

Ligand-receptor docking is an in-silico method (ClusPro) used to determine the best match and estimate the binding dependence between ligand and receptor. For docking, water molecules and additional binding molecules of the ligand (unsuitable epitopes) were separated from the receptor, polar hydrogen bonds were added to the receptor, and finally the energy of the system was optimized.

2.11. Energy and surface map of a vaccine-TLR4 complex

To confirm the stability of the model structure, the ligand-TLR4 construct and the surface map of the vaccine, a computational analysis was performed using Amber10: EHT/all-atom force field with rigid water molecules at room temperature.

3. Results

In the current study, a total of 18 epitopes with nine mer lengths were obtained from three genes and subjected to vaccine modeling. The immunogenicity score of all MHC- I was retrieved from the IEDB server. The results showed that the range of immunogenicity score of MHC-I epitopes was between -0.008 and -0.2 (Table. 1). To see the MHC-II epitopes, the IEDB tools were used and 9 epitopes of 15 mer length were found. To detect linear B-cell epitopes, the sequences were subjected to the IEDB antigen sequence properties, and 22 epitopes from 9 to 34 mer in length were obtained (Table. 2).

The results showed (Table. 3) a total of nine interferon-γ- inducing epitopes (15 mer). A total of five interferon-γ- inducing epitopes were predicted with positive scores and four interferon-γ- generating epitopes were predicted with negative scores

Antigenicity of the construct was indicated by ANTIGENpro for both CD4⁺ and CD8⁺ epitopes (Tables. 4 and 5).

The psipred server at http://bioinf.cs.ucl.ac.uk/psipred is used to display secondary structure. According to the results in Fig. 2 (a). Of the 749 amino acids analyzed, 246 (32.84%) were involved in α-helix formation, 94 (12.55%) in β- strand formation, and 410 (54.73%) were engaged in coil formation.

Figure 2. (a) Secondary structure, (b) Local model quality, (c) Z-score plot of refined model. The best model showed a Z-score of -5.38 (large black spot). Z-scores of all model protein chains (in PDB format) indicated by NMR spectroscopy (dark blue)

ProSAweb was used to predict the quality and errors of the 3D structure of the engineered vaccine. The Z-score of the best refined model was -5.38 (Fig.2 (b, c, and d)).

The Galaxy web server displayed the five models with GDT-HA, MolProbity, RMSD, and Ramachandran plot. Model 3 proved to be the best based on its parameters, including GDT-HA (0.939), MolProbity (2.111), and RMSD (0.468). The clash score of model 3 was 11.5 with a poor Rotamers score of 0.6 and a Rama favored score of 90.5. The Ramachandran diagram of the refined structure of the multi-epitope vaccine shows 39% helix, 9% beta and 51% coil of residues (Fig. 2 (e)).

ProtParam sever was used to check the physiochemical activities of the constructed model. The results showed that the isoelectric point (pI) of all vaccine is 5.00. The constructed vaccine consists of 749 amino acids with a molecular weight of 77981.61. The total number of residues with positive and negative charges was 93 and 72, respectively. The half-life of the vaccine is estimated to be one h in mammalian reticulocytes (in vitro), 30 min in yeast (in vivo), and > 10 h in E. Coli (in vivo). The hydrophobicity of the protein was estimated by a grand average of hydropathicity (GRAVY). GRAVY score of the construct was -0.821. The predicted scaled solubility was 0.582. The instability index of the protein was 16.19. In addition, the aliphatic index was 52.51.

Multi-epitope vaccine and TRL4 docking were performed using ClusPro server. Of the 10 models obtained, the model with the minimum energy value of -965.5 was considered. The best docking of a ligand-receptor is shown in Fig. 3.

Figure 3. Docked complex of ligand-receptor by the ClusPro server. (a): ligand with blue color and receptor (TLR4) with green color, (b): interacting amino acid residues of ligand and receptor, which are labeled in black. Results revealed a probable

To estimate the structural stability of the docked vaccine constructTLR4, some statistical features were analyzed based on the 100-ns trajectory of the molecular dynamics simulation and shown in Fig. 4 (a) and (b). The RMSD of all atoms in the ligand-receptor complex gradually increases with timeand persists until 20 ns. The RMSD curve of all atoms means that the ligand-receptor complex remained mostly stable, and the RMSD value converged within ~0 .1 nm. Moreover, the ∆G of the stable structure is -3.91×10⁴ Kcal mol^-1 with 1.93 RMSD. Van der Waals forces are a general term for the attraction of intermolecular forces between molecules. Fig. 5 (a) shows the Van der Waals surface of the vaccine construct-TLR4 complex. The Van der Waals forces depend on the distance between the atoms or molecules on the surface; the gray color shows that in this complex, the intermolecular forces are weak, resulting from the interactions between uncharged atoms/molecules. Fig. 5 (b) shows the electrostatic surface of the construct-TLR4 complex. The red site conducts the opposite electrostatic force, and the blue color shows the flattering posture of the molecule.

Figure 4. (a) Difference of ∆G of docking pose of vaccine with TRL4, and (b) RMSD structural stability analysis of vaccine with TRL4

Figure 5. Van der Waals, (a) and electrostatic (b) maps for a vaccine with TRL4

4. Discussion

Classical strategies are used for the development of most human vaccines ( 21 ). Because of its time-consuming and costly approach, reverse vaccinology, which includes genomic information, could predict antigenic proteins that elicit an immune response ( 22 ). Multi-epitope vaccines are planned for various bacteria and parasites ( 23 ). In the present study, the predicted epitopes were joined by different linkers (AAY, KK, and GPGPG) as cleavage sites. These linkers were used to increase protein stability ( 24 ). In the present study, the EAAAK linkers were used before and after the adjuvant. The EAAAK linkers are defined as rigid linkers that can separate and reduce the interaction between vaccine domains and increase the thermal stability of chimeric proteins ( 25 ). The dilysine linker (KK) has been used in multi-epitopes as a suitable linker for cathepsin B, enhancing T-cell antigen presentation and increasing immunogenicity ( 26 ). AAY linkers are efficiently cleaved in cells, reducing cross-linking, to improve multi-epitope vaccines ( 27 , 28 ). GPGPG linkers have been used for B-cell cross-linking ( 29 ). In addition, the GPGPG linker can elicit a helper T lymphocyte (HTL) response and abrogate the immunogenicity of the compound and restore immunogenicity ( 30 ).

The antigenic proteins of Salmonella Typhi were extracted from the NCBI protein database based on the FASTA format of their genes. Cytotoxic Tlymphocytes are CD8⁺ T-cell responses to cells with intracellular viral, bacterial, or protozoal infections. In the current study, lower percentile ranks were chosen because of the highest immunogenic properties of the epitopes (Table. 1). Epitopes identified by their corresponding receptors (B-cells) play an important role in vaccine modeling. Thus, 22 epitopes ranging from 9 to 34 mer in length were obtained. Antigenicity is the ability of an antigen to bind with specific antibodies and elicit an immunological response that includes allergenicity and immunogenicity. ANTIGENpro indicated a high probability of antigenicity for both CD4⁺ and CD8⁺ epitopes. Allergenic vaccines can induce sensitization and allergic reactions associated with the IgE antibody response, so the multi-epitope should be free of allergenicity.

The secondary structure of the construct showed the formation of α-helix, β-strands, and coil. In addition, the 3D structure of the vaccine was displayed using Raptrox and refined using GalaxyRefine server. The 3D structure of the engineered vaccine was within the range of native proteins with similar sizes. The Galaxy web server showed that model 3 was the best based on its parameters, including GDT-HA, MolProbity, and RMSD. The clash score of the best model showed a poor rotamer score.

In the current study, the isoelectric point of the vaccine indicates the basic behavior of the protein. ProtParam sever indicates the basic behavior of the protein with positive and negative charges. GRAVY score of the construct indicates that the molecule is hydrophilic. The instability index of the protein indicated a stable molecule.

The results showed that the RMSD of all atoms in the ligand-receptor complex increased with time. The RMSD diagram showed that the ligand-receptor complex remained mostly stable. Van der Waals forces are weak and arise from the interactions between uncharged atoms/molecules.

Conclusion: Salmonella Typhi causes typhoid fever and death of many people every year. The resistance of S. Typhi to many antibiotics, suggesting that it is extremely dangerous to living organisms. Since a polyepitope vaccine based on immunogenic outer membrane proteins of S. Typhi, was developed in the present study, the results of in-silico analyses indicate that the constructed vaccine can be used to control typhoid fever and needs further investigation.

Authors’ Contribution

Fereshteh Ezzati Ghadi: Supervision, Writing, Revision, Investigation,

Zahra Roudbari: Writing, Methodology, Revision,

Razieh Razavi: Writing, Methodology, Visualization

Ethics

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

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