Immuno-informatics: Mining genomes for vaccine components

In silico designing and characterization of outer membrane protein K (OmpK) from Vibrio anguillarum and its expression in Nicotiana tabacum for the development of a plant-based vaccine against fish vibriosis

Vibriosis is caused by Vibrio anguillarum in various species of aquaculture. A novel, secure, and stable vaccine is needed to eradicate vibriosis. Here, for reverse vaccinology and plant-based expression, the outer membrane protein K (OmpK) of V. anguillarum was chosen due to its conserved nature in all Vibrio species. OmpK, an ideal vaccine candidate against vibriosis, demonstrated immunogenic, non-allergic, and non-toxic behavior by using various bioinformatics tools. Docking showed the interaction of the OmpK model with TLR-5. In comparison to costly platforms, plants can be used as alternative and economic bio-factories to produce vaccine antigens. We expressed OmpK antigen in Nicotiana tabacum using Agrobacterium-mediated transformation. The expression vector was constructed using Gateway® cloning. Transgene integration was verified by polymerase chain reaction (PCR), and the copy number via qRT-PCR, which showed two copies of transgenes. Western blotting detected monomeric form of OmpK protein. The total soluble protein (TSP) fraction of OmpK was equivalent to 0.38% as detected by ELISA. Mice and fish were immunized with plant-derived OmpK antigen, which showed a significantly high level of anti-OmpK antibodies. The present study is the first report of OmpK antigen expression in higher plants for the potential use as vaccine in aquaculture against vibriosis, which could provide protection against multiple Vibrio species due to the conserved nature OmpK antigen.

Designing a multi-epitope vaccine to control porcine epidemic diarrhea virus infection using immunoinformatics approaches

Porcine epidemic diarrhea virus (PEDV), a continuously evolving pathogen, causes severe diarrhea in piglets with high mortality rates. However, current vaccines cannot provide complete protection against PEDV, so vaccine development is still necessary and urgent. Here, with the help of immunoinformatics approaches, we attempted to design a multi-epitope vaccine named rPMEV to prevent and control PEDV infection. The epitopes of rPMEV were constructed by 9 cytotoxic T lymphocyte epitopes (CTLs), 11 helper T lymphocyte epitopes (HTLs), 6 linear B cell epitopes (LBEs), and 4 conformational B cell epitopes (CBEs) based on the S proteins from the four representative PEDV G2 strains. To enhance immunogenicity, porcine β-defensin-2 (PBD-2) was adjoined to the N-terminal of the vaccine as an adjuvant. All of the epitopes and PBD-2 were joined by corresponding linkers and recombined into the multivalent vaccine, which is stable, antigenic, and non-allergenic. Furthermore, we adopted molecular docking and molecular dynamics simulation methods to analyze the interaction of rPMEV with the Toll-like receptor 4 (TLR4): a stable interaction between them created by 13 hydrogen bonds. In addition, the results of the immune simulation showed that rPMEV could stimulate both cellular and humoral immune responses. Finally, to raise the expression efficiency, the sequence of the vaccine protein was cloned into the pET28a (+) vector after the codon optimization. These studies indicate that the designed multi-epitope vaccine has a potential protective effect, providing a theoretical basis for further confirmation of its protective effect against PEDV infection in vitro and in vivo studies.

Development and Evaluation of Recombinant B-Cell Multi-Epitopes of PDHA1 and GAPDH as Subunit Vaccines against Streptococcus iniae Infection in Flounder (Paralichthys olivaceus)

Streptococcus iniae is a severe Gram-positive pathogen that can infect a wide range of freshwater and marine fish species. In continuation of our earlier studies on the development of S. iniae vaccine candidates, pyruvate dehydrogenase E1 subunit alpha (PDHA1) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were highly efficacious in protecting flounder (Paralichthys olivaceus) against S. iniae. In the present study, to investigate the potential of multi-epitope vaccination strategy to prevent flounder against S. iniae infection, the liner B-cell epitopes of PDHA1 and GAPDH proteins were predicted using a bioinformatics approach and were identified by immunoassay, and recombinant B-cell multi-epitopes of PDHA1 and GAPDH (rMEPIP and rMEPIG) containing immunodominant epitope-concentrated domains were expressed in Escherichia coli BL21 (DE3) and were used as a subunit vaccine to immunize healthy flounder, while recombinant PDHA1 (rPDHA1), GAPDH (rGAPDH) and formalin-inactivated S. iniae (FKC) served as controls. Then, the immunoprotection efficacy of rMEPIP and rMEPIG was evaluated by determining the percentages of CD4-1+, CD4-2+, CD8β+ T lymphocytes and surface-IgM-positive (sIgM+) lymphocytes in peripheral blood leucocytes (PBLs), spleen leucocytes (SPLs) and head kidney leucocytes (HKLs), as well as total IgM, specific IgM, and relative percentage survival (RPS) post immunization, respectively. It was found that fish immunized with rPDHA1, rGAPDH, rMEPIP, rMEPIG and FKC showed significant increases in sIgM+, CD4-1+, CD4-2+, and CD8β+ lymphocytes and production of total IgM and specific IgM against S. iniae or recombinant proteins rPDHA1 and rGAPDH, which indicated the activation of humoral and cellular immune responses after vaccination. Moreover, RPS rate of the multi-epitope vaccine rMEPIP and rMEPIG groups reached 74.07% and 77.78%, higher than that of rPDHA1 and rGAPDH (62.96% and 66.67%) and KFC (48.15%). These results demonstrated that B-cell multi-epitope protein vaccination, rMEPIP and rMEPIG, could give a better protective effect against S. iniae infection, which provided a promising strategy to design the efficient vaccine in teleost fish.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV)

OBJECTIVES

The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options.

METHODS

In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2.

RESULTS

The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine.

CONCLUSION

If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

<i>In silico</i> Research at the Stages of Designing Modern Means for Prevention of Plague (by the Example of Subunit Vaccines)

The purpose of this review was to analyze the findings of domestic and foreign researchers on the development of modern drugs for the specific prevention of plague and to illustrate the possibilities of using bioinformatics analysis at the design stages to create an effective and safe vaccine. Work on the creation of an effective new-generation plague vaccine is hampered by several factors associated primarily with the presence of mechanisms of evasion from the immune system of the macroorganism, as well as a large number of pathogenicity determinants in the plague agent. Due to the development of approaches that are based on in silico studies, there is a progressive development of vaccine technologies oriented primarily to the use of the most important immunogens of the plague microbe (F1 and V antigen). Studies aimed at improving the antigenic properties of F1 and LcrV, as well as work on bioinformatic search and analysis of additional promising components to be included in the composition of subunit vaccines are considered as topical applications of bioinformatics data analysis in developing the tools for enhancing the effectiveness of protection through vaccination with subunit preparations.

Bioinformatics-based SARS-CoV-2 epitopes design and the impact of Spike protein mutants on epitope humoral immunities

Background

Epitope selection is the key to peptide vaccines development. Bioinformatics tools can efficiently improve the screening of antigenic epitopes and help to choose the right ones.

Objective

To predict, synthesize and testify peptide epitopes at spike protein, assess the effect of mutations on epitope humoral immunity, thus provide clues for the design and development of epitope peptide vaccines against SARS-CoV-2.

Methods

Bioinformatics servers and immunological tools were used to identify the helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes on the S protein of SARS-CoV-2. Physicochemical properties of candidate epitopes were analyzed using IEDB, VaxiJen, and AllerTOP online software. Three candidate epitopes were synthesized and their antigenic responses were evaluated by binding antibody detection.

Results

A total of 20 antigenic, non-toxic and non-allergenic candidate epitopes were identified from 1502 epitopes, including 6 helper T-cell epitopes, 13 cytotoxic T-cell epitopes, and 1 linear B cell epitope. After immunization with antigen containing candidate epitopes S_206-221, S_403-425, and S_1157-1170 in rabbits, the binding titers of serum antibody to the corresponding peptide, S protein, receptor-binding domain protein were (415044, 2582, 209.3), (852819, 45238, 457767) and (357897, 10528, 13.79), respectively. The binding titers to Omicron S protein were 642, 12,878 and 7750, respectively, showing that N211L, DEL212 and K417N mutations cause the reduction of the antibody binding activity.

Conclusions

Bioinformatic methods are effective in peptide epitopes design. Certain mutations of the Omicron would lead to the loss of antibody affinity to Omicron S protein.

An Update on "Reverse Vaccinology": The Pathway from Genomes and Epitope Predictions to Tailored, Recombinant Vaccines

In this chapter, we review the computational approaches that have led to a new generation of vaccines in recent years. There are many alternative routes to develop vaccines based on the concept of reverse vaccinology. They all follow the same basic principles-mining available genome and proteome information for antigen candidates, and recombinantly expressing them for vaccine production. Some of the same principles have been used successfully for cancer therapy approaches. In this review, we focus on infectious diseases, describing the general workflow from bioinformatic predictions of antigens and epitopes down to examples where such predictions have been used successfully for vaccine development.

Chikungunya Virus Vaccine Development: Through Computational Proteome Exploration for Finding of HLA and cTAP Binding Novel Epitopes as Vaccine Candidates

Chikungunya virus is a major arbovirus of great public health concern in the whole world, but no vaccine is yet available, still advance therapeutic treatment and effective vaccines are in progress. The present multistep screening and structural binding analysis with CHIKV proteome exploration can be crucial in the development phase of CHIKV epitope based vaccine. The approach employed in two phases (i) Sequence based screening of peptides through propred and IEDB Server (ii) Structure based study through autodocking and NAMD VMD simulation analysis. Among all 29 extracted peptides, only two peptides ²LLANTTFPC¹⁰ of protein E3 and ⁹⁸VNSVAIPLL¹⁰⁶ of protein nsP3 were observed most prominent over all consider parameters such as peptide conserve nature, supertype population coverage, TAP binding, docking and simulation study. During docking interaction study, the best peptide and allele docked complexes such as ²LLANTTFPC¹⁰–B*0702 allele and ⁹⁸VNSVAIPLL¹⁰⁶–A*0301 allele exhibited best binding energy of − 3.13 kcal/mol and − 3.19 kcal/mol, respectively, with stable bonding patterns and their motion during NAMD simulation which confirm conserve peptide and allele stable interaction. The current study also exhibited the good docking interaction of both peptides ²LLANTTFPC¹⁰ and ⁹⁸VNSVAIPLL¹⁰⁶ with c TAP1 protein (1jj7 -PDB ID) cavity which confirm as a channel passageway to peptide transport through the cytoplasm to lumen of ER during antigen processing and presentation. Overall, this multistep screening and crosscheck structural binding analysis with an exploration of the complete proteome of CHIKV can be a novel step in the development of CHIKV epitope based vaccine as well as diagnostic development with aspect of time, cost and side effects.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Neoantigen-based personalized cancer vaccines: the emergence of precision cancer immunotherapy

INTRODUCTION

The field of cancer therapy has undergone a major transformation in less than a decade due to the introduction of checkpoint inhibitors, the advent of next generation sequencing and the discovery of neoantigens. The key observation that the breadth of each patient's immune response to the unique mutations or neoantigens present in their tumor is directly related to their survival has led oncologists to focus on driving immune responses to neoantigens through vaccination. Oncology has entered the era of precision immunotherapy, and cancer vaccine development is undergoing a paradigm shift.

AREAS COVERED

Neoantigens are short peptide sequences found in tumors, but not noncancerous tissues, the vast majority of which are unique to each patient. In addition to providing a description of the distinguishing features of neoantigen discovery platforms, this review will address cross-cutting personalized cancer vaccine design themes and developmental stumbling blocks.

EXPERT OPINION

Immunoinformatic pipelines that can rapidly scan cancer genomes and identify 'the best' neoantigens are in high demand. Despite the need for such tools, immunoinformatic methods for identifying neoepitopes in cancer genomes are diverse and have not been well-validated. Validation of 'personalized vaccine design pipelines' will bring about a revolution in neoantigen-based vaccine design and delivery.

Tracking the pipeline: immunoinformatics and the COVID-19 vaccine design

With the onset of the COVID-19 pandemic, the amount of data on genomic and proteomic sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stored in various databases has exponentially grown. A large volume of these data has led to the production of equally immense sets of immunological data, which require rigorous computational approaches to sort through and make sense of. Immunoinformatics has emerged in the recent decades as a field capable of offering this approach by bridging experimental and theoretical immunology with state-of-the-art computational tools. Here, we discuss how immunoinformatics can assist in the development of high-performance vaccines and drug discovery needed to curb the spread of SARS-CoV-2. Immunoinformatics can provide a set of computational tools to extract meaningful connections from the large sets of COVID-19 patient data, which can be implemented in the design of effective vaccines. With this in mind, we represent a pipeline to identify the role of immunoinformatics in COVID-19 treatment and vaccine development. In this process, a number of free databases of protein sequences, structures and mutations are introduced, along with docking web servers for assessing the interaction between antibodies and the SARS-CoV-2 spike protein segments as most commonly considered antigens in vaccine design.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Mining the Mycobacterium tuberculosis proteome for identification of potential T-cell epitope based vaccine candidates

Identification of protective antigens for designing a high-efficacy tuberculosis vaccine is the need of the hour. Till date only 7% of the Mycobacterium tuberculosis proteome has been explored for discovering antigens capable of activating T-cell responses. Therefore, it becomes crucial to screen the remaining Mycobacterium tuberculosis proteome for more immunodominant T-cell epitopes. An extensive knowledge of the epitopes recognized by our immune system can aid this process of finding potential T cell antigens for development of a better TB vaccine. In the present in-silico study, 237 proteins belonging to the 'virulence, detoxification, and adaptation' category of Mycobacterium tuberculosis proteome were targeted for T-cell epitope screening. 50825 MHC Class I and 49357 MHC Class II epitopes were generated using NetMHC3.4 and IEDB servers respectively and tested for their antigenicity and cytokine stimulation. The highest antigenic epitopes were analyzed for their world population coverage and epitope conservancy. Molecular docking and molecular dynamics simulation studies were performed to corroborate the binding affinities and structural stability of the peptide-MHC complexes. We predicted a total of 3 MHC Class I (ILLKMCWPA, FAVGMNVYV, and SLAGNSAKV) and 7 MHC Class II (DLTIGFFLHIPFPPV, RPDLTIGFFLHIPFP, LTIGFFLHIPFPPVE, VLVFALVVALVYLQF, LVFALVVALVYLQFR, PNLVAARFIQLTPVY, and LVLVFALVVALVYLQ) epitopes that can be promising vaccine candidates. These predicted epitopes belong to 6 distinct proteins: Rv0169 (mce1a), Rv3490 (ostA), Rv3496 (mce4D), Rv1085c, Rv0563 (HtpX), Rv3497c (mce4C). All these proteins are expressed at different stages in the life cycle of Mycobacterium tuberculosis and thus, the predicted epitopes could be employed as candidates for designing a multistage-multiepitopic vaccine.

Computational identification of significant immunogenic epitopes of the putative outer membrane proteins from Mycobacterium tuberculosis

Novel vaccines are required to effectively combat the epidemic spread of tuberculosis. Using in silico approaches, this study focuses on prediction of potential B cell and T cell binding immunogenic epitopes for 30 putative outer membrane proteins of Mtb. Among these, certain immunodominant epitopes of Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c were found, which are capable of binding B-cell and a maximum number of MHC alleles. The selected immunodominant epitopes were screened for their allergenic and antigenic properties, their percentage identity against the human proteome and their structural properties. Further, the binding efficacy of the immunodominant epitopes of Rv0295c and Rv1006 with HLA-DRB1*04:01 was analyzed using molecular docking and molecular dynamics studies. Hence, the in silico-derived immunogenic peptides (epitopes) could potentially be used for the design of subunit vaccines against tuberculosis.

Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2

BACKGROUND

In order to obtain antibodies that recognize natural proteins, it is possible to predict the antigenic determinants of natural proteins, which are eventually embodied as polypeptides. The polypeptides can be coupled with corresponding vectors to stimulate the immune system to produce corresponding antibodies, which is also a simple and effective vaccine development method. The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine.

METHODS

The analyses were related to epitopes on 3 proteins, including spike (S), envelope (E) and membrane (M) proteins, which are located on the lipid envelope of the SARS-CoV-2. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed, the sequences of the whole genome of SARS-CoV-2 were obtained from the GISAID.

RESULTS

7 epitopes were predicted, including 6 linear epitopes and 1 conformational epitope. One of the linear and one of the conformational consist of identical sequence, but represent different forms of epitopes. It is worth mentioning that all 6 identified epitopes were conserved in nearly 3500 SARS-CoV-2 genomes, showing that it is helpful to obtain stable and long-acting epitopes under the condition of high frequency of amino acid mutation, which deserved further study at the experiment level.

CONCLUSION

The findings would facilitate the vaccine development, had the potential to be directly applied on the prevention in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus.

Immuno-informatics-based identification of novel potential B cell and T cell epitopes to fight Zika virus infections

BACKGROUND

Globally, the recent outbreak of Zika virus (ZIKV) in Brazil, Asia Pacific, and other countries highlighted the unmet medical needs. Currently, there are neither effective vaccines nor therapeutics available to prevent or treat ZIKV infection.

OBJECTIVE

In this study, we aimed to design an epitope-based vaccine for ZIKV using an in silico approach to predict and analyze B- and T-cell epitopes.

METHODS

The prediction of the most antigenic epitopes has targeted the capsid and the envelope proteins as well as nonstructural proteins NS5 and NS3 using immune-informatics tools PROTPARAM, CFSSP, PSIPRED, and Vaxijen v2.0. B and T-cell epitopes were predicted using ABCpred, IEDB, TepiTool, and their toxicity were evaluated using ToxinPred. The 3-dimensional epitope structures were generated by PEP-FOLD. Energy minimization was performed using Swiss-Pdb Viewer, and molecular docking was conducted using PatchDock and FireDock server.

RESULTS

As a result, we predicted 307 epitopes of MHCI (major histocompatibility complex class I) and 102 epitopes of MHCII (major histocompatibility complex class II). Based on immunogenicity and antigenicity scores, we identified the four most antigenic MHC I epitopes: MVLAILAFLR (HLA-A*68 :01), ETLHGTVTV (HLA-A*68 :02), DENHPYRTW (HLA-B*44 :02),QEGVFHTMW (HLA-B*44 :03) and TASGRVIEEW (HLA-B*58:01), and MHC II epitopes: IIKKFKKDLAAMLRI (HLA-DRB3*02 :02), ENSKMMLELDPPFGD (HLA-DRB3*01:01), HAETWFFDENHPYRT (HLA-DRB3*01:01), TDGVYRVMTRRLLGS (HLA-DRB1*11 :01), and DGCWYGMEIRPRKEP (HLA-DRB5*01:01).

CONCLUSION

This study provides novel potential B cell and T cell epitopes to fight Zika virus infections and may prompt further development of vaccines against ZIKV and other emerging infectious diseases. However, further investigations for protective immune response by in vitro and in vivo studies to ratify the immunogenicity, safety of the predicted structure, and ultimately the vaccine properties to prevent ZIKV infections are warranted.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

Identification of the linear immunodominant epitopes in the β subunit of β-conglycinin and preparation of epitope antibodies

β-conglycinin is one of the major allergens in soybean protein. The purpose of this study was to predict and to identify the major linear epitopes of the β subunit of β-conglycinin. Potential linear epitopes were predicted and confirmed by three immunoinformatics tools combined with the Immune Epitope Database (IEDB). Ten potential epitope peptides were synthesized by Fmoc (9-fluorenylmethoxycarbonyl) solid phase peptide synthesis and were validated by the indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) using sera from soybean allergic patients. Polyclonal antibodies, which were prepared by immunizing rabbits with synthesized peptides, were used to confirm their binding ability with β-conglycinin through western blot and dot blot assays. The results showed that 10 peptides were screened as the main epitopes for the β subunit of β-conglycinin. All 10 peptides (P1-P10) presented IgG binding activity, and P2 and P6 were also validated as IgE binding peptides. Moreover, the results of dot blot showed that P5 and P8 might be located inside the protein molecule. Western blot indicated that most of polyclonal antibodies were bound effectively to the β subunit of β-conglycinin. In addition, few polyclonal antibodies exhibited an immune cross-reaction with the α and α' subunits.

Designing of precise vaccine construct against visceral leishmaniasis through predicted epitope ensemble: A contemporary approach

Visceral leishmaniasis (VL) caused by Leishmania donovani is a fatal parasitic disease affecting primarily the poor population in endemic countries. Increasing number of deaths as well as resistant to existing drugs necessitates the development of an effective vaccine for successful treatment of VL. The present study employed a combinatorial approach for designing monomer vaccine construct against L. donovani by applying forecasted B- and T- cell epitopes from 4 genome derived antigenic proteins having secretory signal peptides and glycophosphatidylinositol (GPI) anchors with ≤ 1 transmembrane helix. The forecasted population coverage of chosen T cell epitope ensemble (combined HLA class I and II) cover 99.14 % of world-wide human population. The predicted 3D structure of vaccine constructs (VC1/VC2) were modeled using homology modeling approach and docked to innate immune receptors TLR-2 and TLR-4 with respective docking energies -1231.4/-910.3 and -1119.4/-1476 kcal/mol. Overall, the aforementioned designed vaccine constructs were found appropriate for including in self-assembly protein nanoparticles (SAPN) for further study in developing cutting-edge precision vaccine against VL in short duration with cost-effective manner.

Study of the Binding Pattern of HLA Class I Alleles of Indian Frequency and cTAP Binding Peptide for Chikungunya Vaccine Development

Chikungunya is a mosquito-borne disease, caused by the member of the Togaviridae family belongs to the genus alphavirus, making it a major threat in all developing countries as well as some developed countries. The mosquito acts as a vector for the disease and carries the CHIK-Virus. To date there is no direct treatment available and that demands the development of more effective vaccines. In this study author employed Immune Epitope Database and Analysis Resource, a machine learning-based algorithm principally working on the Artificial Neural Network (ANN) algorithm, also known as (IEDB-ANN) for the prediction and analysis of Epitopes. A total of 173 epitopes were identified on the basis of IC50 values, among them 40 epitopes were found, sharing part with the linear B-cell epitopes and exposed to the cTAP1protein, and out of 40, 6 epitopes were noticed to show interactions with the cTAP with their binding energy ranging from - 3.61 to - 1.22 kcal/mol. The six epitopes identified were exposed to the HLA class I alleles and from this all revealed interaction with the HLA alleles and minimum binding energy that ranges from - 4.12 to - 5.88 kcal/mol. Besides, two T cell epitopes i.e. 145KVFTGVYPE153 and 395STVPVAPPR403 were found most promiscuous candidates. These promiscuous epitopes-HLA complexes were further analyzed by the molecular dynamics simulation to check the stability of the complex. Results obtained from this study suggest that the identified epitopes i.e. and 395 STVPVAPPR 403 , are likely to be capable of passing through the lumen of ER to bind withthe HLA class I allele and provide new insights and potential application in the designing and development of peptide-based vaccine candidate for the treatment of chikungunya.

Bioinformatics analyses of immunogenic T-cell epitopes of LeIF and PpSP15 proteins from Leishmania major and sand fly saliva used as model antigens for the design of a multi-epitope vaccine to control leishmaniasis

Leishmaniasis is caused by protozoan parasites belonging to 20 Leishmania species. This infectious disease is transmitted by bites of infected phlebotomine sandflies, and is widespread in 97 countries throughout the world. No preventive or effective vaccine has been developed yet. In this study, diverse computational methods were integrated to calculate evolutionary divergence, immunogenicity, IFN-γ production, epitope conservancy, and population coverage of protein fusion models of LeIF-SP15 namely SaLeish. Immunogenicity of LeIF of Leishmania species and SP15 of sandfly saliva has not been investigated in-silico in fusion form. A complete set of 9-mer MHC class I and 15-mer MHC class II peptides were identified with a high affinity for the antigenic epitopes of SaLeish inducing specific responses of CD8⁺ and CD4⁺ T cells from BALB/c and human. Our preferred approach was determining truncated fragment of SaLeish rather than a whole length bearing the capacity to trigger specific immune response. Phylogenetic analysis showed that LeIF protein is under balancing selection and is conserved between different Leishmania species. Selected SaLeish model contained 19 and 35 antigenic peptides for MHC class I and II, respectively, with strong binding affinity to both highly frequent HLA-I and HLA-II alleles. Analysis of class I CTL epitopes showed that promiscuous peptides of KSLKADIRK, MSCIPHCKY, LQAGVIVAV, and YQYYGFVAM have greater affinity to interact with HLA-A*01:01, HLA-A*02 (03, 06), HLA-A*30:02, HLA-B*40:01, and HLA-B*52:01 molecules. Population coverage with a range of 78-85% confirmed SaLeish-Model4 as an appropriate vaccine candidate among Persian, South Asia, Europe, and North America population. Also, predicted antigenic epitopes of AKPEIRTFSNVLIKY, TRVQDDLRKLQAGVI, and VALFSATMPEEVLEL corresponding to MHC class II were found to provide strong ability to produce IFNγ toward TH(1)-biased-DTH responses. Findings of the current investigation warrant the future experimental assessment of promising SaLeish prophylaxis vaccine that is capable to enhance both innate and specific cellular immune responses.

Designing a multi-epitope vaccine for cross-protection against Shigella spp: An immunoinformatics and structural vaccinology study

Shigellosis is a severe diarrheal disease with high mortality and morbidity rate. Until now, there is no approved vaccine against the disease. Therefore, the present study was planned to design a novel multi-epitope vaccine against Shigella spp., the causative agents of the disease based on the immunoinformatic tools. For this end, firstly seven conserved antigens of the bacteria, including IpaA, IpaB, IpaC, IpaD, OmpC, OmpF and VirG were selected. Then, linear B-cell epitope mapping of these proteins was carried out and top-ranked and shared epitopes were selected based on antigenicity, allergenicity, stability, toxicity and physicochemical properties for further analysis. In next step, B-cell derived T-cell epitopes were determined and appropriate epitopes were selected for incorporation into the final construct. Moreover, the selected epitopes and two mucosal adjuvants including ctxB and LT-IIc were joined using appropriate linkers. The three dimensional structure of the final construct was modeled and evaluated in term of structural quality and presence of conformational B-cell epitopes. Furthermore, binding affinity of the proposed vaccine to MHC I and II molecules were evaluated through molecular docking method using Hex 8.0. as well as the stability of the vaccine-MHC complexes was monitored by molecular dynamics method using the NAMD graphical user interface embedded in visual molecular dynamics. Finally, to evaluate the immunogenicity of the designed protein, the protein was administered to BALB/c mice and the serum IgG was determined by ELISA. The results indicated that the proposed vaccine has high structural quality and binding affinity to both MHC I and II molecules. Moreover, molecular dynamics studies confirmed that the vaccine-MHC docked complexes were stable during simulation time. Animal study showed that the proposed protein is able to evoke mice's humoral immune response. In sum, the results suggested that the proposed candidate vaccine could be considered as a promising anti-shigellosis vaccine.

Identification of HLA-I restricted epitopes in six vaccine candidates of Leishmania tropica using immunoinformatics and molecular dynamics simulation approaches

In spite of numerous studies on vaccination for various species of Leishmania, research on the development of an effective vaccine for L. tropica is very scarce. In silico epitope prediction is a new way to survey the best vaccine candidates. Here, we predicted the best epitopes of six L. tropica antigens with vaccine capability against this pathogen, using highly frequent HLA-I alleles. Based on the frequent HLA alleles, the protein sequences were screened individually using four different MHC prediction applications, namely SYFPEITHI, ProPredI, BIMAS, and IEDB. Several in silico assays including clustering, human similarity exclusion, epitope conservancy prediction, investigating in experimental records, immunogenicity prediction, and prediction of population coverage were performed to narrow the results and to find the best epitopes. The selected epitopes and their restricted HLA-I alleles were docked and the final epitopes with the lowest binding energy (the highest binding affinity) were chosen. Finally, the stability and the binding properties of the best epitope-HLA-I combinations were analyzed using molecular dynamics simulation studies. We found ten potential peptides with strong binding affinity to highly frequent HLA-I alleles that can be further evaluated as vaccine targets against L. tropica.

Immunogenicity and Protective Efficacy of T-Cell Epitopes Derived From Potential Th1 Stimulatory Proteins of Leishmania (Leishmania) donovani

Development of a suitable vaccine against visceral leishmaniasis (VL), a fatal parasitic disease, is considered to be vital for maintaining the success of kala-azar control programs. The fact that Leishmania-infected individuals generate life-long immunity offers a viable proposition in this direction. Our prior studies demonstrated that T-helper1 (Th1) type of cellular response was generated by six potential recombinant proteins viz. elongation factor-2 (elF-2), enolase, aldolase, triose phosphate isomerase (TPI), protein disulfide isomerase (PDI) and p45, derived from a soluble antigenic fraction (89.9–97.1 kDa) of Leishmania (Leishmania) donovani promastigote, in treated Leishmania patients and golden hamsters and showed significant prophylactic potential against experimental VL. Moreover, since, it is well-known that our immune system, in general, triggers production of specific protective immunity in response to a small number of amino acids (peptide), this led to the identification of antigenic epitopes of the above-stated proteins utilizing immunoinformatics. Out of thirty-six, three peptides-P-10 (enolase), P-14, and P-15 (TPI) elicited common significant lymphoproliferative as well as Th1-biased cytokine responses both in golden hamsters and human subjects. Further, immunization with these peptides plus BCG offered 75% prophylactic efficacy with boosted cellular immune response in golden hamsters against Leishmania challenge which is indicative of their candidature as potential vaccine candidates.

Deciphering foot-and-mouth disease (FMD) virus-host tropism

The pattern of interactions between foot and mouth disease (FMD) viral protein 1 (VP1) with susceptible and resistant host integrins were deciphered. The putative effect of site-directed mutation on alteration of interaction is illustrated using predicted and validated 3D structures of VP1, mutated VP1 and integrins of Bos taurus, Gallus and Canis. Strong interactions were observed between FMDV-VP1 protein motifs at conserved tripeptide, Arg-Gly-Asp ¹⁴³RGD¹⁴⁵ and at domain ⁶⁷⁶SIPLQ⁶⁸⁰ in alpha-integrin of B. taurus. Notably, in-silico site-directed mutation in FMDV-VP1 protein led to complete loss of interaction between FMD-VP1 protein and B. taurus integrin, which confirmed the active role of arginine-glycine-aspartic acid (RGD) domain. Interestingly, in-vitro analysis demonstrates the persistence of the putative tropism site 'SIPLQ' in different cattle breeds undertaken. Thus, the attempt to decipher the tropism of FMDV at host receptor level interaction might be useful for future FMD control strategies through development of mimetic marker vaccines and/or host receptor manipulations. Communicated by Ramaswamy H. Sarma.

Vaccine Target Discovery

With the rise in novel infectious agents and disease pandemics, a new era of vaccine discovery is necessary. To address this, the new field of immunomics is described, which is synergistically powered by integrating bioinformatics methodologies with technological advances in biology and high-throughput instrumentation. By incorporating biological data from immunology and molecular biology with current genomics and proteomics, immunomics is geared to deliver an insight into immune function, optimal stimulation of immune responses and precise mapping and rational selection of immune targets that cover antigenic diversity. These efforts are expected to contribute towards the development of new generation of vaccines, tailored to both the genetic make-up of the human population and of the pathogen. Vaccine technologies are also being explored for prevention or control of non-communicable diseases.

Design and testing of a highly conserved human rotavirus VP8* immunogenic peptide with potential for vaccine development

Rotavirus infection of young children particularly below five years of age resulting in severe diarhoea, is the cause of a large number of infant deaths all over the world, more so in developing countries like India. Vaccines developed against this infection in the last two decades have shown mixed results with some of them leading to complications. Oral vaccines have not been very effective in India. Significant diversity has been found in circulating virus strains in India. Development of a vaccine against diverse genetic variants of the different strains would go a long way in reducing the incidence of infection in developing countries. Success of such a vaccine would depend to a large extent on the antigenic peptide to be used in antibody production. The non-glycosylated protein VP4 on the surface capsid of the virus is important in rota viral immunogenicity and the major antigenic site(s) responsible for neutralization of the virus via VP4 is in the VP8* subunit of VP4. It is necessary that the peptide should be very specific and a peptide sequence which would stimulate both the T and B immunogenic cells would provide maximum protection against the virus. Advanced computational techniques and existing databases of sequences of the VP4 protein of rotavirus help in identification of such specific sequences. Using an in silico approach we have identified a highly conserved VP8* subunit of the VP4 surface protein of rotavirus which shows both T and B cell processivity and is also non-allergenic. This sub-unit could be used in in vivo models for induction of antibodies.

H1N1 influenza virus epitopes classified by monoclonal antibodies

Epitopes serve an important role in influenza infection. It may be useful to screen universal influenza virus vaccines, analyzing the epitopes of multiple subtypes of the hemagglutinin (HA) protein. A total of 40 monoclonal antibodies (mAbs) previously obtained from flu virus HA antigens (development and characterization of 40 mAbs generated using H1N1 influenza virus split vaccines were previously published) were used to detect and classify mAbs into distinct flu virus sub-categories using the ELISA method. Following this, the common continuous amino acid sequences were identified by multiple sequence alignment analysis with the GenBank database and DNAMAN software, for use in predicting the epitopes of the HA protein. Synthesized peptides of these common sequences were prepared, and used to verify and determine the predicted linear epitopes through localization and distribution analyses. With these methods, nine HA linear epitopes distributed among different strains of influenza virus were identified, which included three from influenza A, four from 2009 H1N1 and seasonal influenza, and two from H1. The present study showed that considering a combination of the antigen-antibody reaction specificity, variation in the influenza virus HA protein and linear epitopes may present a useful approach for designing effective multi-epitope vaccines. Furthermore, the study aimed to clarify the cause and pathogenic mechanism of influenza virus HA-induced flu, and presents a novel idea for identifying the epitopes of other pathogenic microorganisms.

Analysis of viral diversity for vaccine target discovery

BACKGROUND

Viral vaccine target discovery requires understanding the diversity of both the virus and the human immune system. The readily available and rapidly growing pool of viral sequence data in the public domain enable the identification and characterization of immune targets relevant to adaptive immunity. A systematic bioinformatics approach is necessary to facilitate the analysis of such large datasets for selection of potential candidate vaccine targets.

RESULTS

This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis.

CONCLUSION

These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation.

Discovery of T-cell Driven Subunit Vaccines from Zika Virus Genome: An Immunoinformatics Approach

The recent outbreaks of Zika virus and the absence of a specific therapy have necessitated to identify T-cell-stimulating antigenic peptides as potential subunit vaccine candidates. The translated ssRNA (+) genome of Zika virus was explored in EMBOSS antigenic and VaxiJen to predict 63 peptides as potential antigens. Three MHC-II binding peptide prediction tools, viz. NetMHCIIpan, PREDIVAC and immune epitope database (IEDB) were employed in consensus on 63 antigenic peptides to propose 14 T-helper cell epitopes. Similarly, analysis on 63 antigenic peptides through NetMHC, NetCTL and IEDB MHC-I binding peptide prediction tool led to identification of 14 CTL epitopes. Seven T-cell epitopes, C:44-66, M:135-149, NS2A:124-144, NS3:421-453, NS3:540-554, NS4B:90-134 and NS4B:171-188, are observed to share overlapping MHC-I and MHC-II binding motifs and hence, are being proposed to constitute minimum T-cell antigens to elicit protective T-cell immune response against Zika. Three of them, C:44-66, NS3:421-453 and NS3:540-554 are identified to be conserved across all the selected strains of Zika virus. Moreover, the 21 T-cell epitopes are non-self to humans and exhibited good coverage in variable populations of 14 geographical locations. Therefore, 21 T-cell epitopes are proposed as potential subunit vaccines against Zika virus.

Preparation of monoclonal antibodies against gamma-type phospholipase A2 inhibitors and immunodetection of these proteins in snake blood

Background

The gamma-type phospholipase A₂ inhibitor (PLIγ) is a natural protein commonly found in snake serum, which can neutralize pathophysiological effects of snake venom phospholipases A₂. Therefore, this protein is a potential candidate to the development of a novel antivenom. To the best of our knowledge, there is no antibody currently available for PLIγ identification and characterization.

Methods

Bioinformatics prediction of epitope using DNAStar software was performed based on the sequence of Sinonatrix annularis PLIγ (SaPLIγ). The best epitope ¹⁵¹CPVLRLSNRTHEANRNDLIKVA¹⁷² was chosen and synthesized, and then conjugated to keyhole limpet hemocyanin and bovine serum albumin for use as an immunogen and plate-coating antigen, respectively.

Results

Eighteen IgG anti-PLIγ mAb hybridoma cell strains were obtained, and all the mAbs had positive interaction with recombinant His6-PLIγ and natural SaPLIγ. Moreover, the mAb from 10E9 strain was also successfully used for the immunodetection of other snake serum PLIγs. cDNA sequence alignment of those PLIγs from different snake species showed that their epitope segments were highly homologous.

Conclusions

The successful preparation of anti-PLIγmAb is significant for further investigation on the relationship between the structure and function of PLIγs, as well as the interaction between PLIγs and PLA₂s.

A Poly(Lactic-co-Glycolic) Acid Nanovaccine Based on Chimeric Peptides from Different Leishmania infantum Proteins Induces Dendritic Cells Maturation and Promotes Peptide-Specific IFNγ-Producing CD8+ T Cells Essential for the Protection against Experimental Visceral Leishmaniasis

Visceral leishmaniasis, caused by Leishmania (L.) donovani and L. infantum protozoan parasites, can provoke overwhelming and protracted epidemics, with high case-fatality rates. An effective vaccine against the disease must rely on the generation of a strong and long-lasting T cell immunity, mediated by CD4⁺ T_H1 and CD8⁺ T cells. Multi-epitope peptide-based vaccine development is manifesting as the new era of vaccination strategies against Leishmania infection. In this study, we designed chimeric peptides containing HLA-restricted epitopes from three immunogenic L. infantum proteins (cysteine peptidase A, histone H1, and kinetoplastid membrane protein 11), in order to be encapsulated in poly(lactic-co-glycolic) acid nanoparticles with or without the adjuvant monophosphoryl lipid A (MPLA) or surface modification with an octapeptide targeting the tumor necrosis factor receptor II. We aimed to construct differentially functionalized peptide-based nanovaccine candidates and investigate their capacity to stimulate the immunomodulatory properties of dendritic cells (DCs), which are critical regulators of adaptive immunity generated upon vaccination. According to our results, DCs stimulation with the peptide-based nanovaccine candidates with MPLA incorporation or surface modification induced an enhanced maturation profile with prominent IL-12 production, promoting allogeneic T cell proliferation and intracellular production of IFNγ by CD4⁺ and CD8⁺ T cell subsets. In addition, DCs stimulated with the peptide-based nanovaccine candidate with MPLA incorporation exhibited a robust transcriptional activation, characterized by upregulated genes indicative of vaccine-driven DCs differentiation toward type 1 phenotype. Immunization of HLA A2.1 transgenic mice with this peptide-based nanovaccine candidate induced peptide-specific IFNγ-producing CD8⁺ T cells and conferred significant protection against L. infantum infection. Concluding, our findings supported that encapsulation of more than one chimeric multi-epitope peptides from different immunogenic L. infantum proteins in a proper biocompatible delivery system with the right adjuvant is considered as an improved promising approach for the development of a vaccine against VL.

Leishmania donovani Nucleoside Hydrolase (NH36) Domains Induce T-Cell Cytokine Responses in Human Visceral Leishmaniasis

Development of immunoprotection against visceral leishmaniasis (VL) focused on the identification of antigens capable of inducing a Th1 immune response. Alternatively, antigens targeting the CD8 and T-regulatory responses are also relevant in VL pathogenesis and worthy of being included in a preventive human vaccine. We assessed in active and cured patients and VL asymptomatic subjects the clinical signs and cytokine responses to the Leishmania donovani nucleoside hydrolase NH36 antigen and its N-(F1), central (F2) and C-terminal (F3) domains. As markers of VL resistance, the F2 induced the highest levels of IFN-γ, IL-1β, and TNF-α and, together with F1, the strongest secretion of IL-17, IL-6, and IL-10 in DTH+ and cured subjects. F2 also promoted the highest frequencies of CD3+CD4+IL-2+TNF-α-IFN-γ-, CD3+CD4+IL-2+TNF-α+IFN-γ-, CD3+CD4+IL-2+TNF-α-IFN-γ+, and CD3+CD4+IL-2+TNF-α+IFN-γ+ T cells in cured and asymptomatic subjects. Consistent with this, the IFN-γ increase was correlated with decreased spleen (R = -0.428, P = 0.05) and liver sizes (R = -0.428, P = 0.05) and with increased hematocrit counts (R = 0.532, P = 0.015) in response to F1 domain, and with increased hematocrit (R = 0.512, P 0.02) and hemoglobin counts (R = 0.434, P = 0.05) in response to F2. Additionally, IL-17 increases were associated with decreased spleen and liver sizes in response to F1 (R = -0.595, P = 0.005) and F2 (R = -0.462, P = 0.04). Conversely, F1 and F3 increased the CD3+CD8+IL-2+TNF-α-IFN-γ-, CD3+CD8+IL-2+TNF-α+IFN-γ-, and CD3+CD8+IL-2+TNF-α+IFN-γ+ T cell frequencies of VL patients correlated with increased spleen and liver sizes and decreased hemoglobin and hematocrit values. Therefore, cure and acquired resistance to VL correlate with the CD4+-Th1 and Th-17 T-cell responses to F2 and F1 domains. Clinical VL outcomes, by contrast, correlate with CD8+ T-cell responses against F3 and F1, potentially involved in control of the early infection. The in silico-predicted NH36 epitopes are conserved and bind to many HL-DR and HLA and B allotypes. No human vaccine against Leishmania is available thus far. In this investigation, we identified the NH36 domains and epitopes that induce CD4+ and CD8+ T cell responses, which could be used to potentiate a human universal T-epitope vaccine against leishmaniasis.

A Chimera Containing CD4+ and CD8+ T-Cell Epitopes of the Leishmania donovani Nucleoside Hydrolase (NH36) Optimizes Cross-Protection against Leishmania amazonesis Infection

The Leishmania donovani nucleoside hydrolase (NH36) and NH A34480 of Leishmania amazonensis share 93% of sequence identity. In mice, the NH36 induced protection against visceral leishmaniasis is mediated by a CD4+ T cell response against its C-terminal domain (F3). Besides this CD4+ Th1 response, prevention and cure of L. amazonensis infection require also additional CD8+ and regulatory T-cell responses to the NH36 N-terminal (F1 domain). We investigated if mice vaccination with F1 and F3 domains cloned in tandem, in a recombinant chimera, with saponin, optimizes the vaccine efficacy against L. amazonensis infection above the levels promoted by the two admixed domains or by each domain independently. The chimera induced the highest IgA, IgG, and IgG2a anti-NH36 antibody, IDR, IFN-γ, and IL-10 responses, while TNF-α was more secreted by mice vaccinated with F3 or all F3-contaning vaccines. Additionally, the chimera and the F1 vaccine also induced the highest proportions of CD4+ and CD8+ T cells secreting IL-2, TNF-α, or IFN-γ alone, TNF-α in combination with IL-2 or IFN-γ, and of CD4+ multifunctional cells secreting IL-2, TNF-α, and IFN-γ. Correlating with the immunological results, the strongest reductions of skin lesions sizes were determined by the admixed domains (80%) and by the chimera (84%), which also promoted the most pronounced and significant reduction of the parasite load (99.8%). Thus, the epitope presentation in a recombinant chimera optimizes immunogenicity and efficacy above the levels induced by the independent or admixed F1 and F3 domains. The multiparameter analysis disclosed that the Th1-CD4+ T helper response induced by the chimera is mainly directed against its FRYPRPKHCHTQVA epitope. Additionally, the YPPEFKTKL epitope of F1 induced the second most important CD4+ T cell response, and, followed by the DVAGIVGVPVAAGCT, FMLQILDFYTKVYE, and ELLAITTVVGNQ sequences, also the most potent CD8+ T cell responses and IL-10 secretion. Remarkably, the YPPEFKTKL epitope shows high amino acid identity with a multipotent PADRE sequence and stimulates simultaneously the CD4+, CD8+ T cell, and a probable T regulatory response. With this approach, we advanced in the design of a NH36 polytope vaccine capable of inducing cross-protection to cutaneous leishmaniasis.

In silico CD4+, CD8+ T-cell and B-cell immunity associated immunogenic epitope prediction and HLA distribution analysis of Zika virus

Zika virus (ZIKV) is a mosquito-borne flavivirus distributed all over Africa, South America and Asia. The infection with the virus may cause acute febrile sickness that clinically resembles dengue fever, yet there is no vaccine, no satisfactory treatment, and no means of evaluating the risk of the disease or prognosis in the infected people. In the present study, the efficacy of the host's immune response in reducing the risk of infectious diseases was taken into account to carry out immuno-informatics driven epitope screening strategy of vaccine candidates against ZIKV. In this study, HLA distribution analysis was done to ensure the coverage of the vast majority of the population. Systematic screening of effective dominant immunogens was done with the help of Immune Epitope & ABCPred databases. The outcomes suggested that the predicted epitopes may be protective immunogens with highly conserved sequences and bear potential to induce both protective neutralizing antibodies, T & B cell responses. A total of 25 CD4+ and 16 CD8+ peptides were screened for T-cell mediated immunity. The predicted epitope "TGLDFSDLYYLTMNNKHWLV" was selected as a highly immunogenic epitope for humoral immunity. These peptides were further screened as non-toxic, immunogenic and non-mutated residues of envelop viral protein. The predicted epitope could work as suitable candidate(s) for peptide based vaccine development. Further, experimental validation of these epitopes is warranted to ensure the potential of B- and T-cells stimulation for their efficient use as vaccine candidates, and as diagnostic agents against ZIKV.

Dimeric and Trimeric Fusion Proteins Generated with Fimbrial Adhesins of Uropathogenic Escherichia coli

Urinary tract infections (UTIs) are associated with high rates of morbidity and mortality worldwide, and uropathogenic Escherichia coli (UPEC) is the main etiologic agent. Fimbriae assembled on the bacterial surface are essential for adhesion to the urinary tract epithelium. In this study, the FimH, CsgA, and PapG adhesins were fused to generate biomolecules for use as potential target vaccines against UTIs. The fusion protein design was generated using bioinformatics tools, and template fusion gene sequences were synthesized by GenScript in the following order fimH-csgA-papG-fimH-csgA (fcpfc) linked to the nucleotide sequence encoding the [EAAAK]₅ peptide. Monomeric (fimH, csgA, and papG), dimeric (fimH-csgA), and trimeric (fimH-csgA-papG) genes were cloned into the pLATE31 expression vector and generated products of 1040, 539, 1139, 1442, and 2444 bp, respectively. Fusion protein expression in BL21 E. coli was induced with 1 mM IPTG, and His-tagged proteins were purified under denaturing conditions and refolded by dialysis using C-buffer. Coomassie blue-stained SDS-PAGE gels and Western blot analysis revealed bands of 29.5, 11.9, 33.9, 44.9, and 82.1 kDa, corresponding to FimH, CsgA, PapG, FC, and FCP proteins, respectively. Mass spectrometry analysis by MALDI-TOF/TOF revealed specific peptides that confirmed the fusion protein structures. Dynamic light scattering analysis revealed the polydispersed state of the fusion proteins. FimH, CsgA, and PapG stimulated the release of 372–398 pg/mL IL-6; interestingly, FC and FCP stimulated the release of 464.79 pg/mL (p ≤ 0.018) and 521.24 pg/mL (p ≤ 0.002) IL-6, respectively. In addition, FC and FCP stimulated the release of 398.52 pg/mL (p ≤ 0.001) and 450.40 pg/mL (p ≤ 0.002) IL-8, respectively. High levels of IgA and IgG antibodies in human sera reacted against the fusion proteins, and under identical conditions, low levels of IgA and IgG antibodies were detected in human urine. Rabbit polyclonal antibodies generated against FimH, CsgA, PapG, FC, and FCP blocked the adhesion of E. coli strain CFT073 to HTB5 bladder cells. In conclusion, the FC and FCP proteins were highly stable, demonstrated antigenic properties, and induced cytokine release (IL-6 and IL-8); furthermore, antibodies generated against these proteins showed protection against bacterial adhesion.

Computational approach for predicting the conserved B-cell epitopes of hemagglutinin H7 subtype influenza virus

An avian-origin influenza H7N9 virus epidemic occurred in China in 2013–2014, in which >422 infected people suffered from pneumonia, respiratory distress syndrome and septic shock. H7N9 viruses belong to the H7 subtype of avian-origin influenza viruses (AIV-H7). Hemagglutinin (HA) is a vital membrane protein of AIV that has an important role in host recognition and infection. The epitopes of HA are significant determinants of the regularity of epidemic and viral mutation and recombination mechanisms. The present study aimed to predict the conserved B-cell epitopes of AIV-H7 HA using a bioinformatics approach, including the three most effective epitope prediction softwares available online: Artificial Neural Network based B-cell Epitope Prediction (ABCpred), B-cell Epitope Prediction (BepiPred) and Linear B-cell Epitope Prediction (LBtope). A total of 24 strains of Euro-Asiatic AIV-H7 that had been associated with a serious poultry pandemic or had infected humans in the past 30 years were selected to identify the conserved regions of HA. Sequences were obtained from the National Center for Biotechnology Information and Global Initiative on Sharing Avian Influenza Data databases. Using a combination of software prediction and sequence comparisons, the conserved epitopes of AIV-H7 were predicted and clarified. A total of five conserved epitopes [amino acids (aa) 37–52, 131–142, 215–234, 465–484 and 487–505] with a suitable length, high antigenicity and minimal variation were predicted and confirmed. Each obtained a score of >0.80 in ABCpred, 60% in LBtope and a level of 0.35 in Bepipred. In addition, a representative amino acid change (glutamine²³⁵-to-leucine²³⁵) in the HA protein of the 2013 AIV-H7N9 was discovered. The strategy adopted in the present study may have profound implications on the rapid diagnosis and control of infectious disease caused by H7N9 viruses, as well as by other virulent viruses, such as the Ebola virus.

In silico proposition to predict cluster of B- and T-cell epitopes for the usefulness of vaccine design from invasive, virulent and membrane associated proteins of C. jejuni

Purpose

Campylobacter jejuni is the one of the leading causes of bacterial diarrheal illness worldwide. This study aims to design specific epitopes for the utility of designing peptide vaccine(s) against C. jejuni by targeting invasive, virulent and membrane associated proteins like FlaA, Cia, CadF, PEB1, PEB3 and MOMP.

Methods

In the present study, various immunoinformatics approaches have been applied to design a potential epitope based vaccine against C. jejuni. The tools include Bepipred, ABCpred, Immune Epitope databse (IEDB) resource portal, Autodock vina etc.

Results

Peptides “EINKN”, “TGSRLN”, “KSNPDI”, “LDENGCE” respectively from FlaA, MOMP, PEB3, CadF proteins were found to be the most potential B cell epitopes while peptides “FRINTNVAA”, “NYFEGNLDM”, “YKYSPKLNF”, “YQDAIGLLV”, “FRNNIVAFV” and “LIMPVFHEL” respectively from Fla, CadF, MOMP, PEB1A, PEB3 and Cia might elicit cell mediated immunity and “IFYTTGSRL” from MOMP protein might elicit both humoral and cell-mediated immunity. All these potential peptidic epitopes showed almost 80–100 % conservancy in different strains of C jejuni with varying proportions of population coverage ranging from 22–60 %. Further authentication of these peptide epitopes as probable vaccine candidate was mediated by their binding to specific HLA alleles using in silico docking technique.

Conclusion

Based on the present study, it could be concluded that these predicted epitopes might be used to design a vaccine against C. jejuni bacteria and thus, could be validated in model hosts to verify their efficacy as vaccine.

Electronic supplementary material

The online version of this article (doi:10.1186/s40203-016-0020-y) contains supplementary material, which is available to authorized users.

iVAX: An integrated toolkit for the selection and optimization of antigens and the design of epitope-driven vaccines

Computational vaccine design, also known as computational vaccinology, encompasses epitope mapping, antigen selection and immunogen design using computational tools. The iVAX toolkit is an integrated set of tools that has been in development since 1998 by De Groot and Martin. It comprises a suite of immunoinformatics algorithms for triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, eliminating regulatory T cell epitopes, and optimizing antigens for immunogenicity and protection against disease. iVAX has been applied to vaccine development programs for emerging infectious diseases, cancer antigens and biodefense targets. Several iVAX vaccine design projects have had success in pre-clinical studies in animal models and are progressing toward clinical studies. The toolkit now incorporates a range of immunoinformatics tools for infectious disease and cancer immunotherapy vaccine design. This article will provide a guide to the iVAX approach to computational vaccinology.

Identification of CD4+ T-cell epitope and investigation of HLA distribution for the immunogenic proteins of Burkholderia pseudomallei using in silico approaches - A key vaccine development strategy for melioidosis

Melioidosis is a serious infectious diseases affecting multi-organ system in humans with high mortality rate. The disease is caused by the bacterium, Burkholderia pseudomallei and it is intrinsically resistant to many antibiotics. Thus, there is an urgent need for protective vaccine against B. pseudomallei; which may reduce morbidity and mortality in endemic areas. The identification of peptides that bind to major histocompatibility complex II class helps in understanding the nature of immune response and identifying T-cell epitopes for the design of new vaccines. Previous studies indicate that, ompA, bipB, fliC and groEL proteins of B. pseudomallei stimulate CD4+ T-cell immune response and act as protective immunogens. However, the data for CD4+ T-cell epitopes of these immunogenic proteins are very limited. Hence, in this present study we attempted to identify CD4+ T-cell epitopes in B. pseudomallei immunogenic proteins using in silico approaches. We did population coverage analysis for these identified epitopic core sequences to identify individuals in endemic areas expected to respond to a given set of these epitopes on the basis of HLA genotype frequencies. We observed that eight epitopic core sequences, two from each immunogenic protein, were associated with the maximum number of HLA-DR binding alleles. These eight peptides are found to be immunogenic in more than 90% of population in endemic areas considered. Thus, these eight peptides containing epitopic core sequences may act as probable vaccine candidates and they may be considered for the development of epitope-based vaccines for melioidosis.

Post-Genomics and Vaccine Improvement for Leishmania

Leishmaniasis is a parasitic disease that primarily affects Asia, Africa, South America, and the Mediterranean basin. Despite extensive efforts to develop an effective prophylactic vaccine, no promising vaccine is available yet. However, recent advancements in computational vaccinology on the one hand and genome sequencing approaches on the other have generated new hopes in vaccine development. Computational genome mining for new vaccine candidates is known as reverse vaccinology and is believed to further extend the current list of Leishmania vaccine candidates. Reverse vaccinology can also reduce the intrinsic risks associated with live attenuated vaccines. Individual epitopes arranged in tandem as polytopes are also a possible outcome of reverse genome mining. Here, we will briefly compare reverse vaccinology with conventional vaccinology in respect to Leishmania vaccine, and we will discuss how it influences the aforementioned topics. We will also introduce new in vivo models that will bridge the gap between human and laboratory animal models in future studies.

Vaccines: A review of immune-based interventions to prevent and treat disease

The enormous gains made in public health during the 20th century, through the prevention and treatment of infectious disease, have contributed to dramatic improvements in the quality and length of the human lifespan. Continued advances in medicine are dependent on addressing several challenges including the increase in existing and new resistance to antibiotics, the decrease in productivity of the research and development (R&D) ecosystem, uncertain regulatory pathways, and an economic environment that rewards innovation for developing therapeutics that involve long cycle times from idea to a product. In this article, we consider important issues pertaining to the development of vaccines with particular emphasis on preclinical requirements, optimal dose selection, design, execution, and reporting of clinical trials for regulatory submission, planning and implementation of post-approval life-cycle programs, and emerging themes in therapeutic vaccines.