Epitope-based Vaccine Design Research Articles

Computational design of a chimeric epitope-based vaccine to protect against Staphylococcus aureus infections

• S. aureus is increasingly resistant to different antibiotics. • Urgent need to develop a new preventive strategy against pathogenic S. aureus. • Designing an epitope-based vaccine from five antigens using immunoinformatics tools. • Insertion of TLR2 agonist as an adjuvant in the vaccine construct. • The ability of the designed vaccine to induce both cellular and humoral immunity.

In silico T-cell and B-cell Epitope Based Vaccine Design Against Alphavirus Strain of Chikungunya.

Chikungunya an arbovirus, is transmitted to humans by the bite of Aedes mosquito. The virus occurrences have been reported in Southeast Asian countries including Pakistan. Its symptoms include typical febrile illness and arthralgic syndrome. The virus has not decisively proved to be life-threatening. The attempt was to design T-cell and B-cell epitope-based vaccine for Chikungunya. The proteome of chikungunya was retrieved, antigenic proteins were identified and T-cell epitopes and B-cell epitopes were predicted. Interacting HLA alleles were also identified. The final analysis was done to confirm that predicted T-cell epitopes and B-cell epitopes can be used as a vaccine. About 32 T-cell epitopes and a 10mer B-cell epitope were identified. Both T-cell and Bcell epitopes demonstrated strong interactions with HLA alleles. The predicted T-cell and B-cell epitopes were docked with respective HLA alleles. The docking analysis showed that the predicted respective epitopes best fit into the binding pockets of the alleles. On the basis of this computational analysis, it is suggested that these predicted epitopes can be used as a remedy against Alphavirus strain of chikungunya. Further laboratory experiments can be conducted to determine the efficacy and stability of this work.

In Silico screening of T-cell and B-cell Epitopes of Rotavirus VP7 and VP4 proteins for Effective Vaccine Design

Rotavirus is one of the deadliest causative agents of childhood diarrhea which causes half a million child death across the globe, mostly in developing countries. However, effective vaccine strategies against rotavirus are yet to be established to prevent these unwanted premature deaths. In this regard, in silico vaccine design for rotavirus could be a promising alternative for developing countries due to its efficiency in shortening valuable time and cost. The present study described an epitope-based peptide vaccine design against rotavirus, using a combination of T-cell and B-cell epitope predictions and molecular docking approach. To perform this, sequences of rotavirus VP7 and VP4 proteins were retrieved from the NCBI database and subjected to different bioinformatics tools to predict most immunogenic T-cell and B-cell epitopes. From the identified epitopes, the sequence VMSKRSRSL of VP7 and TQFTDFVSL of VP4 was identified as the most potential epitopes based on their antigenicity, conservancy and interaction with major histocompatability complex I (MHC-I) alleles. Moreover, the peptide VMSKRSRSL interacted with human leukocyte antigen, HLA-B*08:01 and TQFTDFVSL interacted with HLA-A*02:06 with considerable binding energy and affinity score. Combined population coverage for our identified epitopes was found 70.53% and 45.64% for world population and South Asian population respectively. All these results suggest that, the epitopes identified in this study could be a very good vaccine candidate for the strains of rotavirus circulating in Bangladesh. However, as this study is completely dependent on computational prediction algorithms, further in vivo screening is required to come up in a precise conclusion about these epitopes for effective rotavirus vaccination.
 Bangladesh J Microbiol, Volume 35 Number 1 June 2018, pp 45-55

Application of built-in adjuvants for epitope-based vaccines.

Several studies have shown that epitope vaccines exhibit substantial advantages over conventional vaccines. However, epitope vaccines are associated with limited immunity, which can be overcome by conjugating antigenic epitopes with built-in adjuvants (e.g., some carrier proteins or new biomaterials) with special properties, including immunologic specificity, good biosecurity and biocompatibility, and the ability to vastly improve the immune response of epitope vaccines. When designing epitope vaccines, the following types of built-in adjuvants are typically considered: (1) pattern recognition receptor ligands (i.e., toll-like receptors); (2) virus-like particle carrier platforms; (3) bacterial toxin proteins; and (4) novel potential delivery systems (e.g., self-assembled peptide nanoparticles, lipid core peptides, and polymeric or inorganic nanoparticles). This review primarily discusses the current and prospective applications of these built-in adjuvants (i.e., biological carriers) to provide some references for the future design of epitope-based vaccines.

Potent neutralization activity against type O foot-and-mouth disease virus elicited by a conserved type O neutralizing epitope displayed on bovine parvovirus virus-like particles.

In this study, ten sites on the N terminus and different surface variable regions (VRs) of the bovine parvovirus (BPV) VP2 capsid protein were selected according to an alignment of its sequence with that of the BPV-1 strain HADEN for insertion of the type O foot-and-mouth disease virus (FMDV) conserved neutralizing epitope 8E8. Ten epitope-chimeric BPV VP2 capsid proteins carrying the 8E8 epitope were expressed in Sf9 cells, and electron micrographs demonstrated that these fusion proteins self-assembled into virus-like particles (VLPs) with properties similar to those of natural BPV virions. Immunofluorescence assay (IFA) and Western blot analysis demonstrated that each of the ten epitope-chimeric VLPs reacted with both anti-BPV serum and anti-type O FMDV mAb 8E8. These results indicated that insertions of the 8E8 epitope at these sites on the BPV VP2 protein did not interfere with the immunoreactivity of VP2 or VLP formation, and that the exogenous epitope 8E8 was correctly expressed in BPV VLPs. In addition, anti-BPV IgG antibodies were induced in mice by intramuscular inoculation with each of the ten chimeric VLPs, indicating that the immunogenicity of the chimeric VLPs was not disrupted. Importantly, potent anti-FMDV viral neutralizing (VN) antibodies, which exhibited the highest titre of 1 : 176, were induced by two chimeric VLPs, rBPV-VLP-8E8(391) and rBPV-VLP-8E8(395), in which the 8E8 epitope was inserted into positions 391/392 and 395/396, respectively, in the VR VIII of BPV VP2. Our results demonstrated that the 391/392 and 395/396 positions in the VR VIII of the BPV VP2 protein can effectively display a foreign epitope, making this an attractive approach for the design of nanoparticle-vectored and epitope-based vaccines.

Designing of an epitope-based peptide vaccine against walking pneumonia: an immunoinformatics approach

Mycoplasma pneumoniae is a substantial respiratory pathogen that develops not only pneumonia but also other respiratory diseases, which mimic viral respiratory syndromes. Nevertheless, vaccine development for this pathogen delays behind as immunity correlated with protection is now predominantly unknown. In the present study, an immunoinformatics pipeline is utilized for epitope-based peptide vaccine design, which can trigger a critical immune response against M. pneumoniae. A total of 105T-cell epitopes from 12 membrane associated proteins and 7T-cell epitopes from 5 cytadherence proteins of M. pneumoniae were obtained and validated. Thus, 18 peptides with 9-mer core sequence were identified as best T-cell epitopes by considering the number of residues with > 75% in favored region. Further, the crucial screening studies predicted three peptides with good binding affinity towards HLA molecules as best T-cell and B-cell epitopes. Based on this result, visualization, and dynamic simulation for the three epitopes (WIHGLILLF, VILLFLLLF, and LLAWMLVLF) were assessed. The predicted epitopes needs to be further validated for their adept use as vaccine. Collectively, the study opens up a new horizon with extensive therapeutic application against M. pneumoniae and its associated diseases.

Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV).

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide 'ELRSELIGY' of phosphoprotein and 'YPLLWSFAM' of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.

Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus.

Oropouche virus (OROV) is an emerging pathogen which causes Oropouche fever and meningitis in humans. Several outbreaks of OROV in South America, especially in Brazil, have changed its status as an emerging disease, but no vaccine or specific drug target is available yet. Our approach was to identify the epitope-based vaccine candidates as well as the ligand-binding pockets through the use of immunoinformatics. In this report, we identified both T-cell and B-cell epitopes of the most antigenic OROV polyprotein with the potential to induce both humoral and cell-mediated immunity. Eighteen highly antigenic and immunogenic CD8+ T-cell epitopes were identified, including three 100% conserved epitopes (TSSWGCEEY, CSMCGLIHY, and LAIDTGCLY) as the potential vaccine candidates. The selected epitopes showed 95.77% coverage for the mixed Brazilian population. The docking simulation ensured the binding interaction with high affinity. A total of five highly conserved and nontoxic linear B-cell epitopes “NQKIDLSQL,” “HPLSTSQIGDRC,” “SHCNLEFTAITADKIMSL,” “PEKIPAKEGWLTFSKEHTSSW,” and “HHYKPTKNLPHVVPRYH” were selected as potential vaccine candidates. The predicted eight conformational B-cell epitopes represent the accessibility for the entered virus. In the posttherapeutic strategy, ten ligand-binding pockets were identified for effective inhibitor design against emerging OROV infection. Collectively, this research provides novel candidates for epitope-based peptide vaccine design against OROV.

Trans-Allelic Model for Prediction of Peptide:MHC-II Interactions.

Major histocompatibility complex class two (MHC-II) molecules are trans-membrane proteins and key components of the cellular immune system. Upon recognition of foreign peptides expressed on the MHC-II binding groove, CD4+ T cells mount an immune response against invading pathogens. Therefore, mechanistic identification and knowledge of physicochemical features that govern interactions between peptides and MHC-II molecules is useful for the design of effective epitope-based vaccines, as well as for understanding of immune responses. In this article, we present a comprehensive trans-allelic prediction model, a generalized version of our previous biophysical model, that can predict peptide interactions for all three human MHC-II loci (HLA-DR, HLA-DP, and HLA-DQ), using both peptide sequence data and structural information of MHC-II molecules. The advantage of this approach over other machine learning models is that it offers a simple and plausible physical explanation for peptide–MHC-II interactions. We train the model using a benchmark experimental dataset and measure its predictive performance using novel data. Despite its relative simplicity, we find that the model has comparable performance to the state-of-the-art method, the NetMHCIIpan method. Focusing on the physical basis of peptide–MHC binding, we find support for previous theoretical predictions about the contributions of certain binding pockets to the binding energy. In addition, we find that binding pocket P5 of HLA-DP, which was not previously considered as a primary anchor, does make strong contribution to the binding energy. Together, the results indicate that our model can serve as a useful complement to alternative approaches to predicting peptide–MHC interactions.

Epitope-based vaccine design yields fusion peptide-directed antibodies that neutralize diverse strains of HIV-1.

A central goal of HIV-1-vaccine research is the elicitation of antibodies capable of neutralizing diverse primary isolates of HIV-1. Here we show that focusing the immune response to exposed N-terminal residues of the fusion peptide, a critical component of the viral entry machinery and the epitope of antibodies elicited by HIV-1 infection, through immunization with fusion peptide-coupled carriers and prefusion-stabilized envelope trimers, induces cross-clade neutralizing responses. In mice, these immunogens elicited monoclonal antibodies capable of neutralizing up to 31% of a cross-clade panel of 208 HIV-1 strains. Crystal and cryo-electron microscopy structures of these antibodies revealed fusion peptide-conformational diversity as a molecular explanation for the cross-clade neutralization. Immunization of guinea pigs and rhesus macaques induced similarly broad fusion peptide-directed neutralizing responses suggesting translatability. The N terminus of the HIV-1-fusion peptide is thus a promising target of vaccine efforts aimed at eliciting broadly neutralizing antibodies.

Broadly neutralizing antibodies from human survivors target a conserved site in the Ebola virus glycoprotein HR2-MPER region.

Summary paragraphEbola virus (EBOV) in humans causes a severe illness with high mortality rates. Several strategies have been developed in the past to treat EBOV infection, including the antibody cocktail ZMappTM that has been shown to be effective in nonhuman primate models of infection1 and has been used under compassionate-treatment protocols in humans2. ZMappTM is a mixture of three chimerized murine monoclonal antibodies (mAbs)3–6 that target EBOV-specific epitopes on the surface glycoprotein (GP)7,8. However, ZMappTM mAbs do not neutralize other species from the Ebolavirus genus, such as Bundibugyo virus (BDBV), Reston virus (RESTV) or Sudan virus (SUDV). Here we describe three naturally-occurring human cross-neutralizing mAbs, from BDBV survivors, that target an antigenic site in the canonical heptad repeat 2 (HR2) region near the membrane proximal external region (MPER) of GP. The identification of a conserved neutralizing antigenic site in the GP suggests that these mAbs could be used to design universal antibody therapeutics against diverse ebolavirus species. Furthermore, we found that immunization with a peptide comprising the HR2/MPER antigenic site elicits neutralizing antibodies in rabbits. Structural features determined by conserved residues in the antigenic site described here could inform an epitope-based vaccine design against infection caused by diverse ebolavirus species.

Epitope-Based Vaccine Design against the Outer Membrane Glycoprotein of HCMV

Palestine (West Bank and Gaza) has been considered as an important center of plant diversity and speciation in the Mediterranean region. However, several species are threatened by numerous factors including human activities, e.g., conversion of traditional to intensive agriculture, accompanied by deep ploughing and the application of pesticides, overgrazing, and urban development and construction; and global climatic change. In this study, the “rednumber” procedure was applied, with a few modifications, to Palestinian plants and a red list with International Union for Conservation of Nature (IUCN) categories conservation priorities was constructed, as quantified by the red numbers. The same procedure was applied to extinct plants. One hundred and two species that received red numbers of 3 or above were entered in the updated “red list” of the endangered plants. This study also shows a high extinction risk to the Palestinian threatened wild flora, with 76.4% of the threatened species were critically endangered 39.2%, and endangered 3.72% only 19.6% were vulnerable. The Palestinian flora is thus of conservation concern. The study provides an updated national IUCN Red List for a large group of Palestinian plants, and thus offers an overview of the threatened Palestinian flora. This Red List is an important prerequisite towards the recognition of the danger to Palestinian biodiversity hotspots, conservation of threatened species and the raising of public awareness at national and international levels.

Epitope-Based Vaccine Design against the Outer Membrane Glycoprotein of HCMV

Human cytomegalovirus is also known as (HCMV), a human beta-herpesvirus 5 which affects over 80% adults worldwide. HCMV infection is considered one of the most leading causes of morbidity and mortality during congenital infection. It can be lethal for the immunosuppressed, such as HIV-infected individuals and patients having their organ transplanted. Considering the clinical importance of HCMV, in this study we aim to design epitope based peptides to develop a vaccine against HCMV by targeting the envelope glycoprotein B of HCMV. We predicted total 22 epitopes and their variability were analysed. The analysis of population coverage reveals a high percentage of the coverage for the America and Europe with an overall 69.77% population coverage for the world. Finally, we predicted the 3D structure of epitope YAYIYTTYL and its binding profile with the human leukocyte antigen serotype (HLA-A*02:01 and HLA-A*02:03) were analyzed using Auto Dock Vina. Our study will facilitate the epitope-based vaccine designing of HCMV and could have a far-reaching benefit on the drug development for HCMV associated diseases.

Homology modeling and epitope prediction of Der f 33.

Dermatophagoides farinae (Der f), one of the main species of house dust mites, produces more than 30 allergens. A recently identified allergen belonging to the alpha-tubulin protein family, Der f 33, has not been characterized in detail. In this study, we used bioinformatics tools to construct the secondary and tertiary structures and predict the B and T cell epitopes of Der f 33. First, protein attribution, protein patterns, and physicochemical properties were predicted. Then, a reasonable tertiary structure was constructed by homology modeling. In addition, six B cell epitopes (amino acid positions 34–45, 63–67, 103–108, 224–230, 308–316, and 365–377) and four T cell epitopes (positions 178–186, 241–249, 335–343, and 402–410) were predicted. These results established a theoretical basis for further studies and eventual epitope-based vaccine design against Der f 33.

Physicochemical and immunological characterization of chitosan-coated bacteriophage nanoparticles for in vivo mycotoxin modeling

To propose a novel modeling of aflatoxin immunization and surrogate toxin conjugate from AFB1 vaccines, an immunogen based on the mimotope, (i.e. a peptide-displayed phage that mimics aflatoxins epitope without toxin hazards) was designed. The recombinant phage 3P30 was identified by phage display technology and exhibited the ability to bind, dose dependent, specifically to its cognate target − anti-AFB1 antibody. In immunization assay, the phage-displayed mimotope and its peptide chemically synthesized were able to induce specific anti-AFB1 antibodies, indicating the proof of concept for aflatoxin mimicry. Furthermore, the phage 3P30 was homogeneously coated with chitosan, which also provided a tridimensional matrix network for mucosal delivery. After intranasal immunization, chitosan coated phages improved specific immunogenicity compared to the free antigen. It can be concluded that affinity-selected phage may contribute to the rational design of epitope-based vaccines in a prospectus for the control of aflatoxins and possibly other mycotoxins, and that chitosan coating improved the vectorization of the vaccine by the mucosal route.

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design

Background and objectiveT-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. MethodsIn this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. ResultsThe prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95.125% and an AUC of 0.987 on the HLA-DRB1*0101 allele of the Wang benchmark dataset. ConclusionsThe results indicate that the proposed prediction technique “GAPES” is a promising technique that will help researchers and scientists to predict the protein structure and it will assist them in the intelligent design of new epitope-based vaccines.

Epitope-Based Peptide Vaccine Design against Mokola Rabies Virus Glycoprotein G Utilizing In Silico Approaches

Background: Lyssavirus is considered as a neglected, zoonotic and tropical virus. Among all the Lyssavirus species known to exist today, Mokola virus is unique and appears to be exclusive to Africa. This virus is responsible for a meningoencephalomyelitis in mammals therefore; in silico prediction of epitopes of appropriate protein residues is important to produce a peptide vaccine with powerful immunogenic and minimal allergic effect. The aim of this study was to design a vaccine for Mokola virus using its glycoprotein peptides as an immunogen to stimulate protective immune response. Methods and materials: Glycoprotein G Sequences of Mokola was explored from NCBI then the sequences were aligned to obtain conserved regions. The nominees epitopes from Immune Epitope Database were analyzed by different prediction tools for B-cell, T-cell MHC class II and I. Then sequences aligned with the aid of ClustalW implemented in the BioEdit program. Results and conclusions: For Bepipred test of B-cell the total number of conserved epitopes was 85. For Emini surface accessibility prediction, 36 conserved epitopes were passing the default threshold 1.0. In Kolaskar and Tongaonkar antigenicity, 36 conserved epitopes gave score above the default threshold 1.045. However, there are only three epitopes that pass the three tests (LYTIPEK, LAHQK, YPSVPS). The reference glycoprotein strain was analyzed using IEDB MHC-I binding prediction tool to predict T cell epitope. Twenty conserved peptides were predicted to interact with different MHC-I alleles. For MHC-II binding prediction there were 47 conserved epitopes found to interact with MHC-II alleles. The peptides GQILIPEMQ, FRRLSHFRK and FVGYVTTTF had the affinity to bind the highest number of MHC-II alleles. World population coverage for MHC-I most promising 3 peptides FVDLHMPDV, FVGYVTTTF and RLFDGTWVS was 67.42%, while the world population coverage for most promising MHC-II peptides was 99.77%, for the binding to MHC-I and MHC-II, The peptide FVG TTTF world population coverage was 99.31%.

Prediction and Conservancy Analysis of Multiepitope Based Peptide Vaccine Against Merkel Cell Polyomavirus: An Immunoinformatics Approach

Merkel cell Polyomavirus is non-enveloped, dsDNA virus belonging to Polyomaviridae family linked to an uncommon aggressive skin malignancy. The poor prognosis and limited understanding of disease pathogenesis warrants innovative treatment. In this current study we aim to predict TB cell immunogenic epitopes from the VP1 protein of all merkel cell polyomavirus strain which will aid in effective epitope based vaccine design using immuoinformatics approaches. We retrieved 423 full-length VP1 protein sequences of merkel cell polyomaviruse virus species from the NCBI database. These sequences were analyzed to determine the conserved region and were used to predict the epitopes using the IEDB immunoinformatics algorithms. For B cell three epitope were predicted as peptide vaccine (QEKTVY, KTVYPK, and QEKTVYP). For T cell the predicted Class-I peptides (SLFSNLMPK, LQMWEAISV and LLVKGGVEV) were found to cover the maximum number of MHC I alleles. The highest scoring Class II MHC binding peptides were (IELYLNPRM, ISSLINVHY and INSLFSNLM). Further experiments will need to be undertaken to confirm the potential of these predicted epitopes in a future efficacious vaccine development.

Aberrant Glycosylation of Anchor-Optimized MUC1 Peptides Can Enhance Antigen Binding Affinity and Reverse Tolerance to Cytotoxic T Lymphocytes.

Cancer vaccines have often failed to live up to their promise, although recent results with checkpoint inhibitors are reviving hopes that they will soon fulfill their promise. Although mutation-specific vaccines are under development, there is still high interest in an off-the-shelf vaccine to a ubiquitous antigen, such as MUC1, which is aberrantly expressed on most solid and many hematological tumors, including more than 90% of breast carcinomas. Clinical trials for MUC1 have shown variable success, likely because of immunological tolerance to a self-antigen and to poor immunogenicity of tandem repeat peptides. We hypothesized that MUC1 peptides could be optimized, relying on heteroclitic optimizations of potential anchor amino acids with and without tumor-specific glycosylation of the peptides. We have identified novel MUC1 class I peptides that bind to HLA-A*0201 molecules with significantly higher affinity and function than the native MUC1 peptides. These peptides elicited CTLs from normal donors, as well as breast cancer patients, which were highly effective in killing MUC1-expressing MCF-7 breast cancer cells. Each peptide elicited lytic responses in greater than 6/8 of normal individuals and 3/3 breast cancer patients. The CTLs generated against the glycosylated-anchor modified peptides cross reacted with the native MUC1 peptide, STAPPVHNV, suggesting these analog peptides may offer substantial improvement in the design of epitope-based vaccines.

Identification and characterization of CD4+ T cell epitopes present in Trichinella spiralis paramyosin

Trichinellosis is a worldwide zoonosis and vaccinating swine with a potent vaccine is a practical approach to prevent Trichinella infections in China. Paramyosin of T. spiralis (Ts-Pmy) was shown in our previous work to be a good vaccine candidate against Trichinella infections. Because CD4+ T cells play a crucial role in effective immunity against T. spiralis infection, identifying CD4+ T cell epitopes of paramyosin is crucial for constructing a chimeric subunit epitope vaccine. Twelve CD4+ T cell epitopes of Ts-Pmy with the highest scores were predicted and synthesized as peptides. Five of the twelve peptides, P2, P3, P4, P5 and P12, induced strong splenocyte proliferation and secretion of the Th2 cytokines IL-4 and IL-5 from rTs-Pmy-immunized mouse splenocytes. To assess the immunogenicity of CD4+ T cell epitopes in vivo, splenocytes from mice immunized with individual peptides were stimulated with the corresponding peptides. P2, P3, P4 and P5 induced strong cell proliferation and secretion of both Th1 (INF-γ, IL-2) and Th2 (IL-4, IL-5) cytokines. The results indicate that the peptides P2, P3, P4 and P5 are immunodominant CD4+ T cell epitopes of Ts-Pmy. This study will facilitate the design of an effective epitope-based multivalent subunit vaccine against Trichinella infections.