Identification of epitope-based peptide vaccine candidates against enterotoxigenic Escherichia coli: a comparative genomics and immunoinformatics approach

The electrostatic landscape of MHC-peptide binding revealed using inception networks

Predictive modeling of macromolecular recognition and protein-protein complementarity represents one of the cornerstones of biophysical sciences. However, such models are often hindered by the combinatorial complexity of interactions at the molecular interfaces. Exemplary of this problem is peptide presentation by the highly polymorphic major histocompatibility complex class I (MHC-I) molecule, a principal component of immune recognition. We developed human leukocyte antigen (HLA)-Inception, a deep biophysical convolutional neural network, which integrates molecular electrostatics to capture non-bonded interactions for predicting peptide binding motifs across 5,821 MHC-I alleles. These predictions of generated motifs correlate strongly with experimental peptide binding and presentation data. Beyond molecular interactions, the study demonstrates the application of predicted motifs in analyzing MHC-I allele associations with HIV disease progression and patient response to immune checkpoint inhibitors. A record of this paper's transparent peer review process is included in the supplemental information.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Development of a novel squalene/α-tocopherol-based self-emulsified nanoemulsion incorporating Leishmania peptides for induction of antigen-specific immune responses

Vaccination has emerged as the most effective strategy to confront infectious diseases, among which is leishmaniasis, that threat public health. Despite laborious efforts there is still no vaccine for humans to confront leishmaniasis. Multi-epitope protein/peptide vaccines present a number of advantages, however their use along with appropriate adjuvants that may also act as antigen carriers is considered essential to overcome subunit vaccines' low immunogenicity. In the present study, a stable self-emulsified nanoemulsion was developed and double-adjuvanted with squalene and α-tocopherol. The prepared nanoemulsion droplets exhibited low cytotoxicity in a certain range of concentrations, while they were efficiently taken up by macrophages and dendritic cells in vitro as well as in vivo in secondary lymphoid organs. To further characterize nanoformulation's potent antigen delivery capability, three multi-epitope Leishmania peptides were incorporated into the nanoemulsion. Peptide encapsulation resulted in dendritic cells' functional differentiation characterized by elevated levels of maturation markers and intracellular cytokine production. Intramuscular administration of the nanoemulsion incorporating Leishmania peptides induced antigen-specific spleen cell proliferation as well as elicitation of CD4+ central memory cells, supporting the potential of the developed nanoformulation to successfully act also as an antigen delivery vehicle and thus encouraging further preclinical studies on its vaccine candidate potency.

Leveraging immunoinformatics for developing a multi-epitope subunit vaccine against Helicobacter pylori and Fusobacterium nucleatum

Gastric ulcers caused by Helicobacter pylori and Fusobacterium nucleatum remain a significant global health concern without an established vaccine. In this study, we utilized immunoinformatics methods to design a multi-epitope vaccine targeting these pathogens. Outer membrane proteins from H. pylori and F. nucleatum were scrutinized to identify high antigenic T-cell and B-cell epitopes. The resulting vaccine comprised carefully analyzed and evaluated epitopes, including cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocytes epitopes. This vaccine exhibited notable antigenicity, suitable immunogenicity, and demonstrated non-allergenicity and non-toxicity. It displayed favorable physiochemical characteristics and high solubility. In interaction studies, the vaccine exhibited robust binding to toll-like receptor 4 (TLR4). Molecular dynamic simulations revealed cohesive structural integrity and stable attachment. Codon adaptation utilizing Escherichia coli K12 host yielded a vaccine with elevated Codon Adaptation Index (CAI) and optimal GC content. In silico cloning into the pET28+(a) vector demonstrated efficient expression. Immune simulations indicated the vaccine's ability to initiate immune responses in humans, mirroring real-life scenarios. Based on these comprehensive findings, we propose that our developed vaccine has the potential to confer robust immunity against H. pylori and F. nucleatum infections.Communicated by Ramaswamy H. Sarma.

In silico and immunoinformatics based multiepitope subunit vaccine design for protection against visceral leishmaniasis

Visceral leishmaniasis (VL) is a vector-borne neglected tropical protozoan disease with high fatality and no certified vaccine. Conventional vaccine preparation is challenging and tedious. Here in this work, we created a global multiepitope subunit vaccination against VL utilizing innovative immunoinformatics technique based on the extensively conserved epitopic regions of the PrimPol protein of Leishmania donovani consisting of four subunits which were analyzed and studied, out of which DNA primase large subunit and DNA polymerase α subunit B were evaluated as antigens by Vaxijen 2.0. The multiepitope vaccine design includes a single adjuvant β-defensins, eight CTL epitopes, eight HTL epitopes, seven linear BCL epitopes and one discontinuous BCL epitope to induce innate, cellular and humoral immune responses against VL. The Expasy ProtParam tool characterized the physiochemical parameters of the vaccine. At the same time, SOLpro evaluated our vaccine constructs to be soluble upon expression. We also modeled the stable tertiary structure of our vaccine construct through Robetta modeling for molecular docking studies with toll-like receptor proteins through HADDOCK 2.4. Simulations based on molecular dynamics revealed an intact vaccine and TLR8 complex, supporting our vaccine design's immunogenicity. Also, the immune simulation of our vaccine by the C-ImmSim server demonstrated the potency of the multiepitope vaccine construct to induce proper immune response for host defense. Codon optimization and in silico cloning of our vaccine further assured high expression. The outcomes of our study on multiepitope vaccine design significantly produced a potential candidate against VL and can potentially eradicate the disease in the future after clinical investigations.Communicated by Ramaswamy H. Sarma.

Advancements in the development of nucleic acid vaccines for syphilis prevention and control

Syphilis, a chronic systemic sexually transmitted disease, is caused by the bacterium Treponema pallidum (T. pallidum). Currently, syphilis remains a widespread infectious disease with significant disease burden in many countries. Despite the absence of identified penicillin-resistant strains, challenges in syphilis treatment persist due to penicillin allergies, supply issues, and the emergence of macrolide-resistant strains. Vaccines represent the most cost-effective strategy to prevent and control the syphilis epidemic. In light of the ongoing global coronavirus disease 2019 (COVID-19) pandemic, nucleic acid vaccines have gained prominence in the field of vaccine research and development, owing to their superior efficiency compared to traditional vaccines. This review summarizes the current state of the syphilis epidemic and the preliminary findings in T. pallidum nucleic acid vaccine research, discusses the challenges associated with the development of T. pallidum nucleic acid vaccines, and proposes strategies and measures for future T. pallidum vaccine development.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

Integration of the Microbiome, Metabolome and Transcriptome Reveals Escherichia coli F17 Susceptibility of Sheep

Escherichia coli (E. coli) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of E. coli F17-antagonism (AN) and -sensitive (SE) lambs; however, the biological mechanism underlying E. coli F17 infection has not been fully elucidated. Therefore, the present study first analyzed the metabolite data obtained with UHPLC-MS/MS. A total of 1957 metabolites were profiled in the present study, and 11 differential metabolites were identified between E. coli F17 AN and SE lambs (i.e., FAHFAs and propionylcarnitine). Functional enrichment analyses showed that most of the identified metabolites were related to the lipid metabolism. Then, we presented a machine-learning approach (Random Forest) to integrate the microbiome, metabolome and transcriptome data, which identified subsets of potential biomarkers for E. coli F17 infection (i.e., GlcADG 18:0-18:2, ethylmalonic acid and FBLIM1); furthermore, the PCCs were calculated and the interaction network was constructed to gain insight into the crosstalk between the genes, metabolites and bacteria in E. coli F17 AN/SE lambs. By combing classic statistical approaches and a machine-learning approach, our results revealed subsets of metabolites, genes and bacteria that could be potentially developed as candidate biomarkers for E. coli F17 infection in lambs.

Evaluation of immunomodulatory potential of recombinant histidyl-tRNA synthetase (rLdHisRS) protein of Leishmania donovani as a vaccine candidate against visceral leishmaniasis

Visceral leishmaniasis is neglected tropical protozoan disease caused by Leishmania donovani and are associated with high fatality rate in developing countries since prophylactic vaccines are not available. In the present study, we evaluated the immunomodulatory potential of L. donovani histidyl-tRNA synthetase (LdHisRS) and predicted the epitopes using immunoinformatic tools. Histidyl-tRNA synthetase (HisRS) is a class IIa aminoacyl t-RNA synthetase enzyme (aaRS) required for histidine incorporation into proteins during protein synthesis. The recombinant LdHisRS protein (rLdHisRS) was expressed in E coli BL-21cells, and its immunomodulatory role was assessed in J774A.1 murine macrophage and in BALB/c mice, respectively. LdHisRS specifically stimulated and triggered enhance cell proliferation, nitric oxide release and IFN-γ (70%; P < 0.001), and IL-12 (55.37%; P < 0.05) cytokine release in vitro, whereas BALB/c mice immunized with rLdHisRS show higher NO release (80.95%; P<0.001), higher levels of Th1 cytokines IFN-γ (14%; P < 0.05), TNF-α (34.93%; P < 0.001), and IL-12 (28.49%; P < 0.001) and robust IgG (p<0.001) and IgG2a (p<0.001) production. We also identified 20 Helper T-lymphocytes (HTLs), 30 cytotoxic T lymphocytes (CTLs), and 18 B-cell epitopes from HisRS protein of L. donovani. All these epitopes can be further used to make a multiepitope vaccine against L. donovani.

Designing a Next-Generation Multiepitope-Based Vaccine against Staphylococcus aureus Using Reverse Vaccinology Approaches

Staphylococcus aureus is a human bacterial pathogen that can cause a wide range of symptoms. As virulent and multi-drug-resistant strains of S. aureus have evolved, invasive S. aureus infections in hospitals and the community have become one of the leading causes of mortality and morbidity. The development of novel techniques is therefore necessary to overcome this bacterial infection. Vaccines are an appropriate alternative in this context to control infections. In this study, the collagen-binding protein (CnBP) from S. aureus was chosen as the target antigen, and a series of computational methods were used to find epitopes that may be used in vaccine development in a systematic way. The epitopes were passed through a filtering pipeline that included antigenicity, toxicity, allergenicity, and cytokine inducibility testing, with the objective of identifying epitopes capable of eliciting both T and B cell-mediated immune responses. To improve vaccine immunogenicity, the final epitopes and phenol-soluble modulin α4 adjuvant were fused together using appropriate linkers; as a consequence, a multiepitope vaccine was developed. The chosen T cell epitope ensemble is expected to cover 99.14% of the global human population. Furthermore, docking and dynamics simulations were used to examine the vaccine's interaction with the Toll-like receptor 2 (TLR2), revealing great affinity, consistency, and stability between the two. Overall, the data indicate that the vaccine candidate may be extremely successful, and it will need to be evaluated in experimental systems to confirm its efficiency.

Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework

Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Immunoinformatics Approach to Design a Multi-Epitope Nanovaccine against Leishmania Parasite: Elicitation of Cellular Immune Responses

Leishmaniasis is a vector-borne disease caused by an intracellular parasite of the genus Leishmania with different clinical manifestations that affect millions of people worldwide, while the visceral form may be fatal if left untreated. Since the available chemotherapeutic agents are not satisfactory, vaccination emerges as the most promising strategy for confronting leishmaniasis. In the present study, a reverse vaccinology approach was adopted to design a pipeline starting from proteome analysis of three different Leishmania species and ending with the selection of a pool of MHCI- and MHCII-binding epitopes. Epitopes from five parasite proteins were retrieved and fused to construct a multi-epitope chimeric protein, named LeishChim. Immunoinformatics analyses indicated that LeishChim was a stable, non-allergenic and immunogenic protein that could bind strongly onto MHCI and MHCII molecules, suggesting it as a potentially safe and effective vaccine candidate. Preclinical evaluation validated the in silico prediction, since the LeishChim protein, encapsulated simultaneously with monophosphoryl lipid A (MPLA) into poly(D,L-lactide-co-glycolide) (PLGA) nanoparticles, elicited specific cellular immune responses when administered to BALB/c mice. These were characterized by the development of memory CD4⁺ T cells, as well as IFNγ- and TNFα-producing CD4⁺ and CD8⁺ T cells, supporting the potential of LeishChim as a vaccine candidate.

Designing and Expression of Recombinant Chimeric Spike Protein from SARS-CoV-2 in Escherichia coli and Its Immunogenicity Assessment

Since December 2019, the world has been grappling with an ongoing global COVID-19 pandemic. Various virus variants have emerged over the past two years, each posing a greater threat than its predecessors. The recent appearance of the omicron variant (B.1.1.529) has raised significant alarm within the field of epidemiology due to its highly contagious nature and rapid transmission rate. The omicron variant possessed mutations in the key receptor-binding domain (RBD) region, the S region, and these modifications have shown a notable impact on the strain's susceptibility to neutralizing antibodies. Developing safe and efficient vaccines to prevent a future severe acute respiratory outbreak of coronavirus syndrome 2 (SARS-CoV-2) is significant. Viral surface spike proteins are ideal targets for vaccines. This study aimed to find a multi-subunit chimeric vaccine. After conducting bioinformatics analysis, the recombinant spike (RS) protein of SARS-CoV-2 was deliberately designed and subsequently produced using E. coli expression systems. The immunogenicity of RS and neutralizing antibody responses were evaluated on immunized BALB/c mice. There was a significant difference in antibody titers between RS-immunized mice and control groups. The endpoint of the serum antibody titer of mice immunized with our chimeric protein was 2.5 times higher than that of the negative control. The chimeric construct could present multiple antigens simultaneously, influentially affecting immunization. Sera from mice vaccinated by RS could recognize the SARS-CoV-2 virus and neutralize antibodies. Our chimeric peptide could bind to antibodies in the serum of patients infected with different serotypes of the SARS-CoV-2 virus, such as alpha, delta, and omicron variants. The results indicated that the RS protein would be a potential novel antigenic candidate for subunit vaccine development and could be used as a useful alternative to generate diagnostic serological tests for SARS-CoV-2 infection.

Design of a chimeric protein composed of FimH, FyuA and CNF-1 virulence factors from uropathogenic Escherichia coli and evaluation its biological activity and immunogenicity in vitro and in vivo

Urinary tract infections (UTIs) caused by Uropathogenic Escherichia coli (UPEC) are among the most prevalent bacterial infections in humans. Antibiotic resistance among UPEC isolates is increasing, and designing an effective vaccine can prevent or reduce these infections. FimH adhesin, iron scavenger receptor FyuA, and cytotoxic necrotizing factor -1 (CNF-1) are among the most important virulence factors of UPEC strains. Thus, a novel multi-epitope protein composed of FimH, FyuA, and CNF-1 was designed to evaluate its biological activity and immunogenicity in vitro and in vivo, respectively. The final vaccine design had seven domains, including the N-terminal domain of FimH, four domains of FyuA, and two domains of CNF-1, as determined by immunoinformatics analysis. The results of tertiary structure prediction showed that the chimeric protein had a C-score of -0.25 and Z-score of -1.94. Molecular docking indicated that thirty six ligand residues of the chimeric protein interacted with 53 receptor residues of TLR-4 by hydrogen bonds and hydrophobic interactions. Analysis of protein expression by SDS-PAGE showed an approximately 44 kDa band with different concentrations of IPTG which were confirmed by Western blot. According to ELISA results, the level of IL-8 produced by stimulated Ht29 cells with the chimeric protein was significantly higher than the stimulated Ht29 cells with CNF-1 alone and un-stimulated Ht29 cells. Rabbits subcutaneously immunized with the chimeric protein admixed with Freund adjuvant induced higher level of serum IgG on day 14 after the first vaccination than control rabbits. Furthermore, the booster dose of the chimeric protein significantly enhanced the IgG levels as compared to day 14 and also controls. As, the chimeric protein has suitable B-cell epitopes and MHC-I and MHC-II binding epitopes to stimulate humoral and cellular immunity, it could be a promising vaccine candidate against UTIs caused by UPEC. Evaluating the multi-epitope protein in inducing humoral and cellular immune responses, as well as protection, is ongoing in the mice models.

Designing of cytotoxic T lymphocyte-based multi-epitope vaccine against SARS-CoV2: a reverse vaccinology approach

SARS-CoV2 is a single-stranded RNA virus, gaining much attention after it out broke in China in December 2019. The virus rapidly spread to several countries around the world and caused severe respiratory illness to humans. Since the outbreak, researchers around the world have devoted maximum resources and effort to develop a potent vaccine that would offer protection to uninfected individuals against SARS-CoV2. Reverse vaccinology is a relatively new approach that thrives faster in vaccine research. In this study, we constructed Cytotoxic T Lymphocytes (CTL)-based multi-epitope vaccine using hybrid epitope prediction methods. A total of 121 immunogenic CTL epitopes were screened by various sequence-based prediction methods and docked with their respective HLA alleles using the AutoDock Vina v1.1.2. In all, 17 epitopes were selected based on their binding affinity, followed by the construction of multi-epitope vaccine by placing the appropriate linkers between the epitopes and tuberculosis heparin-binding hemagglutinin (HBHA) adjuvant. The final vaccine construct was modeled by the I-TASSER server and the best model was further validated by ERRAT, ProSA, and PROCHECK servers. Furthermore, the molecular interaction of the constructed vaccine with TLR4 was assessed by ClusPro 2.0 and PROtein binDIng enerGY prediction (PRODIGY) server. The immune simulation analysis confirms that the constructed vaccine was capable of inducing long-lasting memory T helper (Th) and CTL responses. Finally, the nucleotide sequence was codon-optimized by the JCAT tool and cloned into the pET21a (+) vector. The current results reveal that the candidate vaccine is capable of provoking robust CTL response against the SARS-CoV2.Communicated by Ramaswamy H. Sarma.

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.

Immunoinformatics Approach to Design Novel Subunit Vaccine against the Epstein-Barr Virus

Epstein-Barr virus (EBV) is a lymphotropic virus responsible for numerous epithelial and lymphoid cell malignancies, including gastric carcinoma, Hodgkin's lymphoma, nasopharyngeal carcinoma, and Burkitt lymphoma. Hundreds of thousands of people worldwide get infected with this virus, and in most cases, this viral infection leads to cancer. Although researchers are trying to develop potential vaccines and drug therapeutics, there is still no effective vaccine to combat this virus. In this study, the immunoinformatics approach was utilized to develop a potential multiepitope subunit vaccine against the two most common subtypes of EBV, targeting three of their virulent envelope glycoproteins. Eleven cytotoxic T lymphocyte (CTL) epitopes, 11 helper T lymphocyte (HTL) epitopes, and 10 B-cell lymphocyte (BCL) epitopes were predicted to be antigenic, nonallergenic, nontoxic, and fully conserved among the two subtypes, and nonhuman homologs were used for constructing the vaccine after much analysis. Later, further validation experiments, including molecular docking with different immune receptors (e.g., Toll-like receptors [TLRs]), molecular dynamics simulation analyses (including root means square deviation [RMSD], root mean square fluctuation [RMSF], radius of gyration [Rg], principal-component analysis [PCA], dynamic cross-correlation [DCC], definition of the secondary structure of proteins [DSSP], and Molecular Mechanics Poisson-Boltzmann Surface Area [MM-PBSA]), and immune simulation analyses generated promising results, ensuring the safe and stable response of the vaccine with specific immune receptors after potential administration within the human body. The vaccine's high binding affinity with TLRs was revealed in the docking study, and a very stable interaction throughout the simulation proved the potential high efficacy of the proposed vaccine. Further, in silico cloning was also conducted to design an efficient mass production strategy for future bulk industrial vaccine production. IMPORTANCE Epstein-Barr virus (EBV) vaccines have been developing for over 30 years, but polyphyletic and therapeutic vaccines have failed to get licensed. Our vaccine surpasses the limitations of many such vaccines and remains very promising, which is crucial because the infection rate is higher than most viral infections, affecting a whopping 90% of the adult population. One of the major identifications covers a holistic analysis of populations worldwide, giving us crucial information about its effectiveness for everyone's unique immunological system. We targeted three glycoproteins that enhance the virulence of the virus to design an epitope-based polyvalent vaccine against two different strains of EBV, type 1 and 2. Our methodology in this study is nonconventional yet swift to show effective results while designing vaccines.

Designing a Multi-Epitope Vaccine against Toxoplasma gondii: An Immunoinformatics Approach

Infection with the intracellular apicomplexan parasite Toxoplasma gondii causes serious clinical outcomes in both human and veterinary settings worldwide. Although approximately one-third of the world’s population is infected with T. gondii, an effective human vaccine for this disease remains unavailable. We aimed to design a potential T. gondii vaccine candidate that consisted of the B- and T-lymphocyte epitopes of three parasite immunogenic antigens. Firstly, the immunodominant epitopes expressed within the ROP2, MIC3, and GRA7 proteins of T. gondii were identified. Subsequently, six B-cell epitopes, five CTL epitopes, and five HTL epitopes were combined to generate a multi-epitope vaccine, and the 50S ribosomal protein L7/L12 was added as an adjuvant to boost the vaccine’s immunogenicity. All these epitopes were found to be antigenic, nonallergenic, nontoxic, and nonhuman homologs. The designed vaccine construct has a molecular weight of 51 kDa, an antigenicity score of 0.6182, and a solubility of 0.903461. Likewise, the candidate vaccine was immunogenic, nonallergenic, and stable. Molecular docking analysis revealed stable interactions between the vaccine construct and the TLR-4 immune receptor. Meanwhile, the stability of the developed vaccine was validated using molecular dynamics simulation. In silico, the vaccine construct was able to trigger primary immune responses. However, further laboratory-based assessments are needed to confirm its efficacy and safety.

Novel In Silico mRNA vaccine design exploiting proteins of M. tuberculosis that modulates host immune responses by inducing epigenetic modifications

Tuberculosis is an airborne infectious disease caused by Mycobacterium tuberculosis. BCG is the only approved vaccine. However, it has limited global efficacy. Pathogens could affect the transcription of host genes, especially the ones related to the immune system, by inducing epigenetic modifications. Many proteins of M. tuberculosis were found to affect the host's epigenome. Nine proteins were exploited in this study to predict epitopes to develop an mRNA vaccine against tuberculosis. Many immunoinformatics tools were employed to construct this vaccine to elicit cellular and humoral immunity. We performed molecular docking between selected epitopes and their corresponding MHC alleles. Thirty epitopes, an adjuvant TLR4 agonist RpfE, constructs for subcellular trafficking, secretion booster, and specific linkers were combined to develop the vaccine. This proposed construct was tested to cover 99.38% of the population. Moreover, it was tested to be effective and safe. An in silico immune simulation of the vaccine was also performed to validate our hypothesis. It also underwent codon optimization to ensure mRNA's efficient translation once it reaches the cytosol of a human host. Furthermore, secondary and tertiary structures of the vaccine peptide were predicted and docked against TLR-4 and TLR-3.Molecular dynamics simulation was performed to validate the stability of the binding complex. It was found that this proposed construction can be a promising vaccine against tuberculosis. Hence, our proposed construct is ready for wet-lab experiments to approve its efficacy.

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.

Evaluation and Designing of Epitopic-Peptide Vaccine Against Bunyamwera orthobunyavirus Using M-Polyprotein Target Sequences

Bunyamwera orthobunyavirus and its serogroup can cause several diseases in humans, cattle, ruminants, and birds. The viral M-polyprotein helps the virus to enter the host body. Therefore, this protein might serve as a potential vaccine target against Bunyamwera orthobunyavirus. The present study applied the immunoinformatics technique to design an epitopic vaccine component that could protect against Bunyamwera infection. Phylogenetic analysis revealed the presence of conserved patterns of M-polyprotein within the viral serogroup. Three epitopes common for both B-cell and T-cell were identified, i.e., YQPTELTRS, YKAHDKEET, and ILGTGTPKF merged with a specific linker peptide to construct an active vaccine component. The low atomic contact energy value of docking complex between human TLR4 (TLR4/MD2 complex) and vaccine construct confirms the elevated protein–protein binding interaction. Molecular dynamic simulation and normal mode analysis illustrate the docking complex’s stability, especially by the higher Eigenvalue. In silico cloning of the vaccine construct was applied to amplify the desired vaccine component. Structural allocation of both the vaccine and epitopes also show the efficacy of the developed vaccine. Hence, the computational research design outcomes support that the peptide-based vaccine construction is a crucial drive target to limit the infection of Bunyamwera orthobunyavirus to an extent.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.

Combating Childhood Infections in LMICs: evaluating the contribution of Big Data Big data, biomarkers and proteomics: informing childhood diarrhoeal disease management in Low- and Middle-Income Countries

Despite efforts to reduce the global burden of childhood diarrhoea, 50% of all cases globally occur in children under five years in Low–Income and Middle- Income Countries (LMICs) and knowledge gaps remain regarding the aetiological diagnosis, introduction of diarrhoeal vaccines, and the role of environmental enteric dysfunction and severe acute malnutrition. Biomarkers may assist in understanding disease processes, from diagnostics, to management of childhood diarrhoea and the sequelae to vaccine development. Proteomics has the potential to assist in the identification of new biomarkers to understand the processes in the development of childhood diarrhoea and to aid in developing new vaccines. Centralised repositories that enable mining of large data sets to better characterise risk factors, the proteome of both the patient and the different diarrhoeal pathogens, and the environment, could inform patient management and vaccine development, providing a systems biological approach to address the burden of childhood diarrhoea in LMICs.

An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins

Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

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.

Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

An integrative docking and simulation-based approach towards the development of epitope-based vaccine against enterotoxigenic Escherichia coli

Enterotoxigenic E.coli is causing diarrheal illness in children as well as adults with the majority of the cases occurring in developing countries. To reduce the number of cases occurring worldwide, the development of an effectual vaccine against these bacteria can be the only prevention. This conjectural work was performed using modern bioinformatics tools for investigation of proteome of ETEC strain E24377A. Different computational vaccinology approaches were deployed to assess several parameters including antigenicity, allergenicity, stability, localization, molecular weight and toxicity of the predicted epitopes required for good vaccine candidate to elicit immune response against diarrhea. We estimated two known control antigens, epitope ¹⁴¹STLPETTVV¹⁴⁹ of Hepatitis B virus and epitope ²⁶⁵ILRGSVAHK²⁷³ of H1N1 Nucleoprotein in an attempt to corroborate our research work. Furthermore molecular docking was performed to evaluate the interaction between HLA allele and peptide, the peptide QYGGGNSAL and peptide LPYFELRWL were considered to be the most promiscuous T cell epitopes with the highest binding energy value of −2.09 kcal/mol and −1.84 kcal/mol, respectively. In addition, dynamic simulation revealed good stability of the vaccine construct as well as population coverage analysis exhibits the highest population coverage in the regions of East Asia, India, Northeast Asia, South Asia and North America. Therefore, these two epitopes can be further synthesized for wet lab analysis and could be considered as a promising vaccine against diarrhea.

Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the most cryptic pandemic outbreak of the 21st century, has gripped more than 1.8 million people to death and infected almost eighty six million. As it is a new variant of SARS, there is no approved drug or vaccine available against this virus. This study aims to predict some promising cytotoxic T lymphocyte epitopes in the SARS-CoV-2 proteome utilizing immunoinformatic approaches. Firstly, we identified 21 epitopes from 7 different proteins of SARS-CoV-2 inducing immune response and checked for allergenicity and conservancy. Based on these factors, we selected the top three epitopes, namely KAYNVTQAF, ATSRTLSYY, and LTALRLCAY showing functional interactions with the maximum number of MHC alleles and no allergenicity. Secondly, the 3D model of selected epitopes and HLA-A*29:02 were built and Molecular Docking simulation was performed. Most interestingly, the best two epitopes predicted by docking are part of two different structural proteins of SARS-CoV-2, namely Membrane Glycoprotein (ATSRTLSYY) and Nucleocapsid Phosphoprotein (KAYNVTQAF), which are generally target of choice for vaccine designing. Upon Molecular Docking, interactions between selected epitopes and HLA-A*29:02 were further validated by 50 ns Molecular Dynamics (MD) simulation. Analysis of RMSD, Rg, SASA, number of hydrogen bonds, RMSF, MM-PBSA, PCA, and DCCM from MD suggested that ATSRTLSYY is the most stable and promising epitope than KAYNVTQAF epitope. Moreover, we also identified B-cell epitopes for each of the antigenic proteins of SARS CoV-2. Findings of our work will be a good resource for wet lab experiments and will lessen the timeline for vaccine construction.Communicated by Ramaswamy H. Sarma.

Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible countermeasures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for developing potential vaccines; however, most of them are proved to possess negative consequences. Therefore, in this study, immunoinformatics methods were exploited to design a novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog, and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vitro and in vivo studies are required on the predicted vaccine to finally validate its safety and efficacy.

Design of a multi-epitope subunit vaccine for immune-protection against Leishmania parasite

Visceral Leishmaniasis (VL) is an insect-borne neglected disease caused by the protozoan parasite Leishmania donovani. In the absence of a commercial vaccine against VL, chemotherapy is currently the only option used for the treatment of VL. Vaccination has been considered as the most effective and powerful tool for complete eradication and control of infectious diseases. In this study, we aimed to design a peptide-based vaccine against L. donovani using immuno-bioinformatic tools. We identified 6 HTL, 18 CTL, and 25 B-cell epitopes from three hypothetical membrane proteins of L. donovani. All these epitopes were used to make a vaccine construct along with linkers. An adjuvant was also added at the N-terminal to enhance its immunogenicity. After that, we checked the quality of this vaccine construct and found that it is nontoxic, nonallergic, and thermally stable. A 3D structure of the vaccine construct was also generated by homology modeling to evaluate its interaction with innate immune receptors (TLR). Molecular docking was performed, which confirmed its binding with a toll-like receptor-2 (TLR-2). The stability of vaccine-TLR-2 complex and underlying interactions were evaluated using molecular dynamic simulation. Lastly, we carried out in silico cloning to check the expression of the final designed vaccine. The designed vaccine construct needs further experimental and clinical investigations to develop it as a safe and effective vaccine against VL infection.

In silico analysis and in vivo assessment of a novel epitope-based vaccine candidate against uropathogenic Escherichia coli

Uropathogenic Escherichia coli (UPEC) are common pathogens in urinary tract infections (UTIs), which show resistance to antibiotics. Therefore, there is a need for a vaccine to reduce susceptibility to the infection. In the present study, bioinformatics approaches were employed to predict the best B and T-cell epitopes of UPEC virulence proteins to develop a multiepitope vaccine candidate against UPEC. Then, the efficacy of the candidate was studied with and without Freund adjuvant. Using bioinformatics methods, 3 epitope-rich domains of IutA and FimH antigens were selected to construct the fusion. Molecular docking and Molecular dynamics (MD) simulation were employed to investigate in silico interaction between designed vaccine and Toll-like receptor 4 (TLR4). Our results showed that the levels of IgG and IgA antibodies were improved in the serum and mucosal samples of the vaccinated mice, and the IgG responses were maintained for at least 6 months. The fusion protein was also able to enhance the level of cytokines IFN.γ (Th1), IL.4 (Th2), and IL.17. In challenge experiments, all vaccine combinations showed high potency in the protection of the urinary tract even after 6 months post first injection. The present study indicates that the designed candidate is able to evoke strong protective responses which warrant further studies.

Immunoinformatics and Epitope Prediction

With advancements in sequencing technologies, vast amount of experimental data has accumulated. Due to rapid progress in the development of bioinformatics tools and the accumulation of data, immunoinformatics or computational immunology emerged as a special branch of bioinformatics which utilizes bioinformatics approaches for understanding and interpreting immunological data. One extensively studied aspect of applied immunology involves using available databases and tools for prediction of B- and T-cell epitopes. B and T cells comprise two arms of adaptive immunity.This chapter first reviews the methodology we used for computational identification of B- and T-cell epitopes against enterotoxigenic Escherichia coli (ETEC). Then we discuss other databases of epitopes and analysis tools for T-cell and B-cell epitope prediction and vaccine design. The predicted peptides were analyzed for conservation and population coverage. HLA distribution analysis for predicted epitopes identified efficient MHC binders. Epitopes were further tested using computational docking studies to bind in MHC-I molecule cleft. The predicted epitopes were conserved and covered more than 80% of the world population.

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.

Development of a conserved chimeric vaccine based on helper T-cell and CTL epitopes for induction of strong immune response against Schistosoma mansoni using immunoinformatics approaches

Currently, three recombinant antigens based vaccines are under clinical trials against Schistosomiasis, but there is no vaccine available for prophylaxis or therapeutic. This study was conducted to construct a multi-epitope based vaccine against Schistosoma mansoni via utilizing Sm14, Sm21.7, Sm23, Sm29, Smp80, Sm-CB and SM-TSP-2 antigens. Helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL) and IFN-γ epitopes were predicted. Furthermore, Pan HLA DR-binding epitope was added to the vaccine. Moreover, 50S ribosomal protein L7/L12 of Mycobacterium tuberculosis as a novel TLR4 agonist was applied. The TAT peptide was added to the vaccine to augment intracellular delivery. The selected epitopes were linked together through appropriate linkers and chimeric vaccine was constructed with 617 amino acids with molecular weight of 65.43 kDa. Physico-chemical properties revealed a soluble protein with antigenic and non-allergic properties. Further analyses validated the stability of the construct that was able to interact with TLR4. Immunoinformatics analysis demonstrated the strong potential of constructed vaccine to stimulate T and B-cell mediated immune responses. In summary, obtained data indicated that the proposed vaccine can properly induce both T and B cells immune responses and could possibly be utilized for prophylactic or therapeutic aims in response to infection caused by S. mansoni.

Development a multi-epitope driven subunit vaccine for immune response reinforcement against Serogroup B of Neisseria meningitidis using comprehensive immunoinformatics approaches

Serogroup B of Neisseria meningitidis is the main cause of mortality due to meningococcal meningitis. Despite of many investigations, there is still no effective vaccine to prevent this serious infection. Therefore, this study was conducted to design a multi-epitope based vaccine through immunoinformatics approaches. The T CD4⁺ and TCD8⁺ cells along with IFN-γ inducing epitopes were selected from TspA, FHbp, NspA, TbpB, PilQ and NspA antigens form serogroup B of Neisseria meningitidis. Furthermore, to induce strong helper T lymphocytes (HTLs) responses, Pan HLA DR-binding epitope (PADRE) was used. In addition, loop 5 and 7 of the PorB as a TLR2 agonist were added to the vaccine construct. Physico-chemical properties, secondary and tertiary structures of the proposed construct were assessed. Finally, homology modeling, refinement and molecular docking were carried out to evaluated the construct tertiary structure and protein-protein interaction, respectively. By fusing the CTL, HTL and IFN-γ predicted epitopes along with suitable adjuvant and linkers, a multi-epitope vaccine was constructed with a TAT sequence of HIV at the N-terminal. Immunoinformatics analyses confirmed a soluble and non-allergic protein with a molecular weight of 62.5 kDa and high antigenicity. Furthermore, the stability of the multi-epitope construct was established and showed strong potential to generate humoral and cell-mediated immune responses. In addition, through molecular docking and dynamic simulation, the microscopic interaction between the vaccine construct and TLR-2 were verified. In summary, immunoinformatics analysis demonstrated that the constructed multi-epitope vaccine had a strong potential of T and B-cell stimulation and it could possibly be used for prophylactic or therapeutic aims to protect against serogroup B of N. meningitidis.

Vaccine development for enteric bacterial pathogens: Where do we stand?

Gut infections triggered by pathogenic bacteria lead to most frequently occurring diarrhea in humans accounting for million deaths annually. Currently, only a few licensed vaccines are available against these pathogens for mostly travelers moving to diarrheal endemic areas. Besides commercialized vaccines, there are many formulations that are either under clinical or pre-clinical stages of development and despite several efforts to improve safety, immunogenicity and efficacy, none of them can confer long-term protective immunity, for which repeated booster doses are always recommended. Further in many countries, financial, social and political constraints have jeopardized vaccine development program against these pathogens that enforce us to gather knowledge on safety, tolerability, immunogenicity and protective efficacy regarding the same. In this review, we analyze safety and efficacy issues of vaccines against five major gut bacteria causing enteric infections. The article also simultaneously describes several barriers for vaccine development and further discusses possible strategies to enhance immunogenicity and efficacy.

Genome wide characterization of enterotoxigenic Escherichia coli serogroup O6 isolates from multiple outbreaks and sporadic infections from 1975-2016

Enterotoxigenic Escherichia coli (ETEC) are an important cause of diarrhea globally, particularly among children under the age of five in developing countries. ETEC O6 is the most common ETEC serogroup, yet the genome wide population structure of isolates of this serogroup is yet to be determined. In this study, we have characterized 40 ETEC O6 isolates collected between 1975–2016 by whole genome sequencing (WGS) and by phenotypic antimicrobial susceptibility testing. To determine the relatedness of isolates, we evaluated two methods—whole genome high-quality single nucleotide polymorphism (whole genome-hqSNP) and core genome SNP analyses using Lyve-SET and Parsnp respectively. All isolates were tested for antimicrobial susceptibility using a panel of 14 antibiotics. ResFinder 2.1 and a custom quinolone resistance determinants workflow were used for resistance determinant detection. VirulenceFinder 1.5 was used for prediction of the virulence genes. Thirty-seven isolates clustered into three major clades (I, II, III) by whole genome-hqSNP and core genome SNP analyses, while three isolates included in the whole genome-hqSNP analysis only did not cluster with clades I-III by both analyses and formed a distantly related outgroup, designated clade IV. Median number of pairwise whole genome-hqSNPs in clonal ETEC O6 outbreaks ranged from 0 to 5. Of the 40 isolates tested for antimicrobial susceptibility, 18 isolates were pansusceptible. Twenty-two isolates were resistant to at least one antibiotic, nine of which were multidrug resistant. Phenotypic antimicrobial resistance (AR) correlated with AR determinants in 22 isolates. Thirty-two isolates harbored both enterotoxin virulence genes while the remaining 8 isolates had only one of the two virulence genes. In summary, whole genome-hqSNP and core genome SNP analyses from this study revealed similar evolutionary relationships and an overall diversity of ETEC O6 isolates independent of time of isolation. Less than 5 pairwise hqSNPs between ETEC O6 isolates is circumstantially indicative of an outbreak cluster. Findings from this study will be a basis for quicker outbreak detection and control by efficient subtyping by WGS.

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Human papillomavirus (HPV) induced cervical cancer is the second most common cause of death, after breast cancer, in females. Three prophylactic vaccines by Merck Sharp & Dohme (MSD) and GlaxoSmithKline (GSK) have been confirmed to prevent high-risk HPV strains but these vaccines have been shown to be effective only in girls who have not been exposed to HPV previously. The constitutively expressed HPV oncoproteins E6 and E7 are usually used as target antigens for HPV therapeutic vaccines. These early (E) proteins are involved, for example, in maintaining the malignant phenotype of the cells. In this study, we predicted antigenic peptides of HPV types 16 and 18, encoded by E6 and E7 genes, using an immunoinformatics approach. To further evaluate the immunogenic potential of the predicted peptides, we studied their ability to bind to class I major histocompatibility complex (MHC-I) molecules in a computational docking study that was supported by molecular dynamics (MD) simulations and estimation of the free energies of binding of the peptides at the MHC-I binding cleft. Some of the predicted peptides exhibited comparable binding free energies and/or pattern of binding to experimentally verified MHC-I-binding epitopes that we used as references in MD simulations. Such peptides with good predicted affinity may serve as candidate epitopes for the development of therapeutic HPV peptide vaccines.

Preparation of porcine enterotoxigenic Escherichia coli (ETEC) ghosts and immunogenic analysis in a mouse model

Enterotoxignenic Escherichia coli (ETEC)-associated colibacillosis causes high levels of morbidity and mortality in neonatal piglets. Vaccination is among effective strategy to fight against ETEC-related diseases. Bacterial ghosts (BGs) are empty bacterial envelopes, which substain subtle antigenic comformation in bacterial outer membrane. In this study, a BG vaccine was generated using porcine ETEC isolated strain DQ061 and evaluated its safety and immunogenicity in a mouse model. The recombinant bacteria were constructed by transformation of lysis plasmid pHH43 and generation of BGs was conducted in a lysis rate of 99.93% by incubation of the recombinant bacteria at 42 °C for 2 h. Mice were immunized subcutaneously twice in 2-week intervals with BGs, BGs emulsified with ISA 206 adjuvant, or formalin-inactivated ETEC vaccine after safety test. Mice with either of two BG vaccines developed higher titer of antibodies, secreted higher titer of interleukin 4, gamma interferon and alpha tumor necrosis factor after 2 doses than those with formalin-inactivated ETEC vaccine or those with adjuvant placebo (P < 0.01). The quantity of CD4⁺ and CD8⁺ T lymphocyte in spleen was higher in both BG groups than that in the inactivated vaccine group or adjuvant group 2 weeks post boost immunization (P < 0.05). The vaccinated mice were challenged intraperitoneally with 10 × LD₅₀ dose of DQ061. Mice with the BGs plus adjuvant were completely protected against challenge, compared to 60% protection of mice with the inactivated vaccine. Mice exhibited decreased tissue lesion and reduced bacterial loads in the BGs groups by comparison with those with the inactivated vaccine or adjuvant only. Our results validated that the ETEC BGs bear high safety and immunogenicity in a mouse model, suggesting a potential of further evaluation in a pig model.

Immunoinformatics-aided design of a potential multi-epitope peptide vaccine against Leishmania infantum

Visceral leishmaniasis (VL) or kala-azar, the most severe form of the disease, is endemic in more than eighty countries across the world. To date, there is no approved vaccine against VL in the market. Recent advances in reverse vaccinology could be promising approach in designing the efficient vaccine for VL treatment. In this study, an efficient multi-epitope vaccine against Leishmania infantum, the causative agent of VL, was designed using various computational vaccinology methods. Potential immunodominant epitopes were selected from four antigenic proteins, including histone H1, sterol 24-c-methyltransferase (SMT), Leishmania-specific hypothetical protein (LiHy), and Leishmania-specific antigenic protein (LSAP). To enhance vaccine immunogenicity, two resuscitation-promoting factor of Mycobacterium tuberculosis, RpfE and RpfB, were employed as adjuvants. All the aforesaid segments were joined using proper linkers. Homology modeling, followed by refinement and validation was performed to obtain a high-quality 3D structure of designed vaccine. Docking analyses and molecular dynamics (MD) studies indicated vaccine/TLR4 complex was in the stable form during simulation time. In sum, we expect our designed vaccine is able to induce humoral and cellular immune responses against L. infantum, and may be promising medication for VL, after in vitro and in vivo immunological assays.

Immunoinformatics approaches to design a novel multi-epitope subunit vaccine against HIV infection

The end goal of HIV vaccine designing requires novel strategies to elicit a strong humoral and cell-mediated immune response. The emergence of drug resistance and the requirement of next line treatment necessitate the finding of the potential and immunogenic vaccine candidate. This study employed a novel immunoinformatics approach to design multi-epitope subunit vaccine against HIV infection. Here, we designed the subunit vaccine by the combination of CTL, HTL and BCL epitopes along with suitable adjuvant and linkers. Physiochemical characterization of subunit vaccine was assessed to ensure its thermostability, theoretical PI, and amphipathic behavior. In further assessment, subunit vaccine was found to be immunogenic with the capability to generate humoral and cell-mediated immune response. Further, homology modeling and refinement was performed and the refined modeled structure was used for molecular docking with the immune receptor (TLR-3) present on lymphocyte cells. Consequently, molecular dynamics simulation ensured the molecular interaction between TLR-3 and subunit vaccine candidate. Disulfide engineering was performed by placing the cysteine residues in the region of high mobility to enhance the vaccine stability. At last, in silico cloning was performed to warrant the translational efficiency and microbial expression of the designed vaccine.

Excavating chikungunya genome to design B and T cell multi-epitope subunit vaccine using comprehensive immunoinformatics approach to control chikungunya infection

Chikungunya infection has been a cause of countless deaths worldwide. Due to lack of permanent treatment and prevention of this disease, the mortality rate remains very high. Therefore, we followed an immunoinformatics approach for the development of multi-epitope subunit vaccine which is able to elucidate humoral, cell-mediated and innate immune responses inside the host body. Both structural and non-structural proteins of chikungunya virus were utilized for prediction of B-cell and T-cell binding epitopes along with interferon-γ (IFN-γ) inducing epitopes. The vaccine construct is composed of β-defensin as an adjuvant at the N-terminal followed by Cytotoxic T-Lymphocytes (CTL) and Helper T-Lymphocyte (HTL) epitopes. The same vaccine construct was also utilized for the prediction of B-cell binding epitopes and IFN-γ inducing epitopes. This was followed by the 3D model generation, refinement and validation of the vaccine construct. Later on, the interaction of modeled vaccine with the innate immune receptor (TLR-3) was explored by performing molecular docking and molecular dynamics simulation studies. Also to check the efficiency of expression of this vaccine construct in an expression vector, in silico cloning was performed at the final stage of vaccine development. Further, designed multi-epitope subunit vaccine necessitates experimental and clinical investigation to develop as an immunogenic vaccine candidate.

Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches

Helicobacter pylori is the cunning bacterium that can live in the stomachs of many people without any symptoms, but gradually can lead to gastric cancer. Due to various obstacles, which are related to anti-H. pylori antibiotic therapy, recently developing an anti-H. pylori vaccine has attracted more attention. In this study, different immunoinformatics and computational vaccinology approaches were employed to design an efficient multi-epitope oral vaccine against H. pylori. Our multi-epitope vaccine is composed of heat labile enterotoxin IIc B (LT-IIc) that is used as a mucosal adjuvant to enhance vaccine immunogenicity for oral immunization, cartilage oligomeric matrix protein (COMP) to increase vaccine stability in acidic pH of gut, one experimentally protective antigen, OipA, and two hypothetical protective antigens, HP0487 and HP0906, and "CTGKSC" peptide motif that target epithelial microfold cells (M cells) to enhance vaccine uptake from the gut barrier. All the aforesaid segments were joined to each other by proper linkers. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality 3D structure. The resulting high-quality model was applied for conformational B-cell epitopes selection and docking analyses with a toll-like receptor 2 (TLR2). Moreover, molecular dynamics studies demonstrated that the protein-TLR2 docked model was stable during simulation time. We believe that our vaccine candidate can induce mucosal sIgA and IgG antibodies, and Th1/Th2/Th17-mediated protective immunity that are crucial for eradicating H. pylori infection. In sum, the computational results suggest that our newly designed vaccine could serve as a promising anti-H. pylori vaccine candidate.