A novel design of a multi-antigenic, multistage and multi-epitope vaccine against Helicobacter pylori: An in silico approach

In silico designing of novel epitope-based peptide vaccines against HIV-1

The HIV-1 virus has been regarded as a catastrophe for human well-being. The global incidence of HIV-1-infected individuals is increasing. Hence, development of effective immunostimulatory molecules has recently attracted an increasing attention in the field of vaccine design against HIV-1 infection. In this study, we explored the impacts of CD40L and IFN-γ as immunostimulatory adjuvants for our candidate HIV-1 Nef vaccine in human and mouse using immunoinformatics analyses. Overall, 18 IFN-γ-based vaccine constructs (9 constructs in human and 9 constructs in mouse), and 18 CD40L-based vaccine constructs (9 constructs in human and 9 constructs in mouse) were designed. To find immunogenic epitopes, important characteristics of each component (e.g., MHC-I and MHC-II binding, and peptide-MHC-I/MHC-II molecular docking) were determined. Then, the selected epitopes were applied to create multiepitope constructs. Finally, the physicochemical properties, linear and discontinuous B cell epitopes, and molecular interaction between the 3D structure of each construct and CD40, IFN-γ receptor or toll-like receptors (TLRs) were predicted. Our data showed that the full-length CD40L and IFN-γ linked to the N-terminal region of Nef were capable of inducing more effective immune response than multiepitope vaccine constructs. Moreover, molecular docking of the non-allergenic full-length- and epitope-based CD40L and IFN-γ constructs to their cognate receptors, CD40 and IFN-γ receptors, and TLRs 4 and 5 in mouse were more potent than in human. Generally, these findings suggest that the full forms of these adjuvants could be more efficient for improvement of HIV-1 Nef vaccine candidate compared to the designed multiepitope-based constructs.

Multi-epitope vaccine design using in silico analysis of glycoprotein and nucleocapsid of NIPAH virus

According to the 2018 WHO R&D Blueprint, Nipah virus (NiV) is a priority disease, and the development of a vaccine against NiV is strongly encouraged. According to criteria used to categorize zoonotic diseases, NiV is a stage III disease that can spread to people and cause unpredictable outbreaks. Since 2001, the NiV virus has caused annual outbreaks in Bangladesh, while in India it has caused occasional outbreaks. According to estimates, the mortality rate for infected individuals ranges from 70 to 91%. Using immunoinformatic approaches to anticipate the epitopes of the MHC-I, MHC-II, and B-cells, they were predicted using the NiV glycoprotein and nucleocapsid protein. The selected epitopes were used to develop a multi-epitope vaccine construct connected with linkers and adjuvants in order to improve immune responses to the vaccine construct. The 3D structure of the engineered vaccine was anticipated, optimized, and confirmed using a variety of computer simulation techniques so that its stability could be assessed. According to the immunological simulation tests, it was found that the vaccination elicits a targeted immune response against the NiV. Docking with TLR-3, 7, and 8 revealed that vaccine candidates had high binding affinities and low binding energies. Finally, molecular dynamic analysis confirms the stability of the new vaccine. Codon optimization and in silico cloning showed that the proposed vaccine was expressed to a high degree in Escherichia coli. The study will help in identifying a potential epitope for a vaccine candidate against NiV. The developed multi-epitope vaccine construct has a lot of potential, but they still need to be verified by in vitro & in vivo studies.

Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection

Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.

Construction of an aerolysin-based multi-epitope vaccine against Aeromonas hydrophila: an in silico machine learning and artificial intelligence-supported approach

Aeromonas hydrophila, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhibited resistance to numerous commercial antibiotics, and no vaccine has yet been developed. Aiming to combat the alarmingly high infection rate, this study utilizes in silico techniques to design a multi-epitope vaccine (MEV) candidate against this bacterium based on its aerolysin toxin, which is the most toxic and highly conserved virulence factor among the Aeromonas species. After retrieval, aerolysin was processed for B-cell and T-cell epitope mapping. Once filtered for toxicity, antigenicity, allergenicity, and solubility, the chosen epitopes were combined with an adjuvant and specific linkers to create a vaccine construct. These linkers and the adjuvant enhance the MEV's ability to elicit robust immune responses. Analyses of the predicted and improved vaccine structure revealed that 75.5%, 19.8%, and 1.3% of its amino acids occupy the most favored, additional allowed, and generously allowed regions, respectively, while its ERRAT score reached nearly 70%. Docking simulations showed the MEV exhibiting the highest interaction and binding energies (-1,023.4 kcal/mol, -923.2 kcal/mol, and -988.3 kcal/mol) with TLR-4, MHC-I, and MHC-II receptors. Further molecular dynamics simulations demonstrated the docked complexes' remarkable stability and maximum interactions, i.e., uniform RMSD, fluctuated RMSF, and lowest binding net energy. In silico models also predict the vaccine will stimulate a variety of immunological pathways following administration. These analyses suggest the vaccine's efficacy in inducing robust immune responses against A. hydrophila. With high solubility and no predicted allergic responses or toxicity, it appears safe for administration in both healthy and A. hydrophila-infected individuals.

Embedding of exogenous B cell epitopes on the surface of UreB structure generates a broadly reactive antibody response against Helicobacter pylori

Since Helicobacter pylori (H. pylori) resistance to antibiotic regimens has increased, vaccination is becoming an increasingly important alternative therapy to control H. pylori infection. UreB, FlaA, AlpB, SabA, and HpaA proteins of H. pylori were previously proved to be used as candidate vaccine antigens. Here, we developed an engineered antigen based on a recombinant chimeric protein containing a structural scaffold from UreB and B cell epitopes from FlaA, AlpB, SabA, and HpaA. The multi-epitope chimeric antigen, named MECU, could generate a broadly reactive antibody response including antigen-specific antibodies and neutralising antibodies against H. pylori urease and adhesins. Moreover, therapeutic immunisation with MECU could reduce H. pylori colonisation in the stomach and protect the stomach in BALB/c mice. This study not only provides promising immunotherapy to control H. pylori infection but also offers a reference for antigen engineering against other pathogens.

Immunoinformatics Approach to Design a Chimeric CD70-Peptide Vaccine against Renal Cell Carcinoma

Renal cell carcinoma (RCC) accounts for the majority of cancer-related deaths worldwide. Overexpression of CD70 has been linked to advanced stages of RCC. Therefore, this study aims to develop a multiepitope vaccine targeting the overexpressed CD70 using immunoinformatics techniques. In this investigation, in silico multiepitope vaccines were constructed by linking specific CD70 protein epitopes for helper T lymphocytes and CD8+ T lymphocytes. To enhance immunogenicity, sequences of cell-penetrating peptide (CPP), penetratin (pAntp), along with the entire sequence of tumor necrosis factor-α (TNF-α), were attached to the N-terminal and C-terminal of the CD70 epitopes. Computational assessments were performed on these chimeric vaccines for antigenicity, allergenicity, peptide toxicity, population coverage, and physicochemical properties. Furthermore, refined 3D constructs were subjected to a range of analyses, encompassing structural B-cell epitope prediction and molecular docking. The chosen vaccine construct underwent diverse assessments such as molecular dynamics simulation, immune response simulation, and in silico cloning. All vaccines comprised antigenic, nontoxic, and nonallergenic epitopes, ensuring extensive global population coverage. The vaccine constructs demonstrated favorable physicochemical characteristics. The binding affinity of chimeric vaccines to the TNF receptor remained relatively stable, influenced by the alignment of vaccine components. Molecular docking and dynamics analyses predicted stable interactions between CD70-CPP-TNF and the TNF receptor, indicating potential efficacy. In silico codon optimization and cloning of the vaccine nucleic acid sequence were accomplished using the pET28a plasmid. Furthermore, this vaccine displayed the capacity to modulate humoral and cellular immune responses. Overall, the results suggest therapeutic potential for the chimeric CD70-CPP-TNF vaccine against RCC. However, validation through in vitro and in vivo experiments is necessary. This trial is registered with NCT04696731 and NCT04046445.

A multi-epitope subunit vaccine based on CU/ZN-SOD, OMP31 and BP26 against Brucella melitensis infection in BALB/C mice

Brucellosis, a zoonosis caused by Brucella, is highly detrimental to both humans and animals. Most existing vaccines are live attenuated vaccines with safety flaws for people and animals. Therefore, it is advantageous to design a multi-epitope subunit vaccine (MEV) to prevent Brucella infection. To this end, we applied a reverse vaccinology approach. Six cytotoxic T cell (CTL) epitopes, seven T helper cell (HTL) epitopes, and four linear B cell epitopes from CU/ZN-SOD, Omp31, and BP26 were obtained. We linked the CTL, HTL, B-cell epitopes, the appropriate CTB molecular adjuvant, and the universal T helper lymphocyte epitope, PADRE, with linkers AAY, GPPGG, and KK, respectively. This yielded a 412-amino acid MEV construct, which we named MEVcob. The immunogenicity, stability, safety, and feasibility of the construct were evaluated by bioinformatics tools (including the AlphaFold2 prediction tool, the AlphaFold2 tool, NetMHC-I pan 4.0 server, IEDB MHC-I server, ABCpred service, and C-ImmSim server); the physicochemical properties, secondary and tertiary structures, and binding ability of MEVocb to toll-like receptor 4 (TLR4) was analyzed. Then, codon adaptation and computer cloning studies were performed. MEVocb is highly immunogenic in immunostimulation experiments, The proteins translated by these sequences were relatively stable, exhibiting a high antigenic index. Furthermore, mouse experiments confirmed that the MEVocb construct could raise IFN-γ, IgG, IgG2a, IgG1, IL-2, TNF-α levels in mice, indicating that induced a specific humoral and cellular immune response in BALB/c mice. This vaccine induced a statistically significant level of protection in BALB/c mice when challenged with Brucella melitensis 043 in Xinjiang. Briefly, we utilized immunoinformatic tools to design a novel multi-epitope subunit candidate vaccine against Brucella. This vaccine aims to induce host immune responses and confer specific protective effects. The study results offer a theoretical foundation for the development of a novel Brucella subunit vaccine.

Development and immunological evaluation of an mRNA-based vaccine targeting Naegleria fowleri for the treatment of primary amoebic meningoencephalitis

More than 95% of patients fall victim to primary amoebic meningoencephalitis (PAM), a fatal disease attacking the central nervous system. Naegleria fowleri, a brain-eating microorganism, is PAM's most well-known pathogenic ameboflagellate. Despite the use of antibiotics, the fatality rate continues to rise as no clinical trials have been conducted against this disease. To address this, we mined the UniProt database for pathogenic proteins and selected assumed epitopes to create an mRNA-based vaccine. We identified thirty B-cell and T-cell epitopes for the vaccine candidate. These epitopes, secretion boosters, subcellular trafficking structures, and linkers were used to construct the vaccine candidate. Through predictive modeling and confirmation via the Ramachandran plot (with a quality factor of 92.22), we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: 0.394, instability index: 38.99, antigenicity: 0.8). The theoretical model of immunological simulations indicated favorable responses from both innate and adaptive immune cells, with memory cells expected to remain active for up to 350 days post-vaccination, while the antigen was eliminated from the body within 24 h. Notably, strong interactions were observed between the vaccine construct and TLR-4 (- 11.9 kcal/mol) and TLR-3 (- 18.2 kcal/mol).

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.

Design of a novel multi-epitopes vaccine against Escherichia fergusonii: a pan-proteome based in- silico approach

Escherichia fergusonii a gram-negative rod-shaped bacterium in the Enterobacteriaceae family, infect humans, causing serious illnesses such as urinary tract infection, cystitis, biliary tract infection, pneumonia, meningitis, hemolytic uremic syndrome, and death. Initially treatable with penicillin, antibiotic misuse led to evolving resistance, including resistance to colistin, a last-resort drug. With no licensed vaccine, the study aimed to design a multi-epitope vaccine against E. fergusonii. The study started with the retrieval of the complete proteome of all known strains and proceeded to filter the surface exposed virulent proteins. Seventeen virulent proteins (4 extracellular, 4 outer membranes, 9 periplasmic) with desirable physicochemical properties were identified from the complete proteome of known strains. Further, these proteins were processed for B-cell and T-cell epitope mapping. Obtained epitopes were evaluated for antigenicity, allergenicity, solubility, MHC-binding, and toxicity and the filtered epitopes were fused by specific linkers and an adjuvant into a vaccine construct. Structure of the vaccine candidate was predicted and refined resulting in 78.1% amino acids in allowed regions and VERIFY3D score of 81%. Vaccine construct was docked with TLR-4, MHC-I, and MHC-II, showing binding energies of -1040.8 kcal/mol, -871.4 kcal/mol, and -1154.6 kcal/mol and maximum interactions. Further, molecular dynamic simulation of the docked complexes was carried out resulting in a significant stable nature of the docked complexes (high B-factor and deformability values, lower Eigen and high variance values) in terms of intermolecular binding conformation and interactions. The vaccine was also reported to stimulate a variety of immunological pathways after administration. In short, the designed vaccine revealed promising predictions about its immune protective potential against E. fergusonii infections however experimental validation is needed to validate the results.

Design of a multi-epitope vaccine against brucellosis fused to IgG-fc by an immunoinformatics approach

Introduction

Brucella, a type of intracellular Gram-negative bacterium, has unique features and acts as a zoonotic pathogen. It can lead to abortion and infertility in animals. Eliminating brucellosis becomes very challenging once it spreads among both humans and animals, putting a heavy burden on livestock and people worldwide. Given the increasing spread of brucellosis, it is crucial to develop improved vaccines for susceptible animals to reduce the disease's impact.

Methods

In this study, we effectively used an immunoinformatics approach with advanced computer software to carefully identify and analyze important antigenic parts of Brucella abortus. Subsequently, we skillfully designed chimeric peptides to enhance the vaccine's strength and effectiveness. We used computer programs to find four important parts of the Brucella bacteria that our immune system recognizes. Then, we carefully looked for eight parts that are recognized by a type of white blood cell called cytotoxic T cells, six parts recognized by T helper cells, and four parts recognized by B cells. We connected these parts together using a special link, creating a strong new vaccine. To make the vaccine even better, we added some extra parts called molecular adjuvants. These included something called human β-defensins 3 (hBD-3) that we found in a database, and another part that helps the immune system called PADRE. We attached these extra parts to the beginning of the vaccine. In a new and clever way, we made the vaccine even stronger by attaching a part from a mouse's immune system to the end of it. This created a new kind of vaccine called MEV-Fc. We used advanced computer methods to study how well the MEV-Fc vaccine interacts with certain receptors in the body (TLR-2 and TLR-4).

Results

In the end, Immunosimulation predictions showed that the MEV-Fc vaccine can make the immune system respond strongly, both in terms of cells and antibodies.

Discussion

In summary, our results provide novel insights for the development of Brucella vaccines. Although further laboratory experiments are required to assess its protective effect.

In silico analysis of the conserved surface-exposed epitopes to design novel multiepitope peptide vaccine for all variants of the SARS-CoV-2

Recently the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pervasive threat to generic health. The SARS-CoV-2 spike (S) glycoprotein plays a fundamental role in binds and fusion to the angiotensin-converting enzyme 2 (ACE2). The multi-epitope peptide vaccines would be able to elicit both long-lasting humoral and cellular immune responses, resulting the eliminating SARS-CoV-2 infections as asymptomatic patients are in large numbers. Recently, the omicron variant of the SARS-CoV-2 became a variant of concern that contained just 15-point mutations in the receptor-binding domain of the spike protein. In order to eliminate new evidence on coronavirus variants of concern detected through epidemic intelligence, the conserved epitopes of the receptor-binding domain (RBD) and spike cleavage site is the most probable target for vaccine development to inducing binds and fusion inhibitors neutralizing antibodies respectively. In this study, we utilized bioinformatics tools for identifying and analyzing the spike (S) glycoprotein sequence, e.g. the prediction of the potential linear B-cell epitopes, B-cell multi‑epitope design, secondary and tertiary structures, physicochemical properties, solubility, antigenicity, allergenicity, the molecular docking and molecular dynamics simulation for the promising vaccine candidate against all variant of concern of SARS-CoV-2. Among the epitopes of the RBD region are surface-exposed epitopes SVYAWNRKRISNCV and ATRFASVYAWNRKR as the conserved sequences in all variants of concern can be a good candidate to induce an immune response.Communicated by Ramaswamy H. Sarma.

Design of multi-epitope vaccine candidate against Brucella type IV secretion system (T4SS)

Brucellosis is a common zoonosis, which is caused by Brucella infection, and Brucella often infects livestock, leading to abortion and infertility. At present, human brucellosis remains one of the major public health problems in China. According to previous research, most areas in northwest China, including Xinjiang, Tibet, and other regions, are severely affected by Brucella. Although there are vaccines against animal Brucellosis, the effect is often poor. In addition, there is no corresponding vaccine for human Brucellosis infection. Therefore, a new strategy for early prevention and treatment of Brucella is needed. A multi-epitope vaccine should be developed. In this study, we identified the antigenic epitopes of the Brucella type IV secretion system VirB8 and Virb10 using an immunoinformatics approach, and screened out 2 cytotoxic T lymphocyte (CTL) epitopes, 9 helper T lymphocyte (HTL) epitopes, 6 linear B cell epitopes, and 6 conformational B cell epitopes. These advantageous epitopes are spliced together through different linkers to construct a multi-epitope vaccine. The silico tests showed that the multi-epitope vaccine was non-allergenic and had a strong interaction with TLR4 molecular docking. In immune simulation results, the vaccine construct may be useful in helping brucellosis patients to initiate cellular and humoral immunity. Overall, our findings indicated that the multi-epitope vaccine construct has a high-quality structure and suitable characteristics, which may provide a theoretical basis for the development of a Brucella vaccine.

Integrated immunoinformatics and subtractive proteomics approach for multi-epitope vaccine designing to combat S. pneumoniae TIGR4

Streptococcus pneumoniae is one of the major precarious pathogens accountable for over 1.2 million fatalities annually. The key drivers for pneumococcal vaccine development involve high morbidity and mortality in over one million cases, especially in very young children and the elderly. In this study, immunoinformatics was integrated with subtractive proteomics to find antigenic proteins for designing a multi-epitope vaccine against S. pneumoniae. As prospective vaccine targets, the developed pipeline identified two antigenic proteins, i.e., penicillin-binding protein and ATP synthase subunit. Several immunoinformatics and bioinformatics resources were used to forecast T- and B-cell epitopes from specific proteins. By employing a mixture of five cytotoxic T-cell lymphocytes, six helper T-cell lymphocytes, and seven linear B-cell lymphocyte epitopes, a 392 amino acid-long vaccine was designed. To enhance immune responses, the designed vaccine was coupled with a cholera enterotoxin subunit B adjuvant. The designed vaccine was highly antigenic, non-allergenic, and stable for human usage. The stability of the vaccine with toll-like receptor-4 was evaluated by molecular docking and molecular dynamic simulation. In addition, immunological simulation was performed to test its real-world potency. The vaccine codon was then cloned in silico. Overall, this study paves the way for the development of a multi-epitope S. pneumoniae vaccine under laboratory conditions. Furthermore, the current findings warrant for the experimental validation of the final multi-epitope vaccine construct to demonstrate its immunological reinforcing capability and clinical applicability.

Design of a Multi-Epitope Vaccine against Tuberculosis from Mycobacterium tuberculosis PE_PGRS49 and PE_PGRS56 Proteins by Reverse Vaccinology

Tuberculosis is a disease caused by Mycobacterium tuberculosis, representing the second leading cause of death by an infectious agent worldwide. The available vaccine against this disease has insufficient coverage and variable efficacy, accounting for a high number of cases worldwide. In fact, an estimated third of the world's population has a latent infection. Therefore, developing new vaccines is crucial to preventing it. In this study, the highly antigenic PE_PGRS49 and PE_PGRS56 proteins were analyzed. These proteins were used for predicting T- and B-cell epitopes and for human leukocyte antigen (HLA) protein binding efficiency. Epitopes GGAGGNGSLSS, FAGAGGQGGLGG, GIGGGTQSATGLG (PE_PGRS49), and GTGWNGGKGDTG (PE_PGRS56) were selected based on their best physicochemical, antigenic, non-allergenic, and non-toxic properties and coupled to HLA I and HLA II structures for in silico assays. A construct with an adjuvant (RS09) plus each epitope joined by GPGPG linkers was designed, and the stability of the HLA-coupled construct was further evaluated by molecular dynamics simulations. Although experimental and in vivo studies are still necessary to ensure its protective effect against the disease, this study shows that the vaccine construct is dynamically stable and potentially effective against tuberculosis.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

In silico design of a novel peptide-based vaccine against the ubiquitous apicomplexan Toxoplasma gondii using surface antigens

Human toxoplasmosis is a global public health concern and a commercial vaccine is still lacking. The present in silico study was done to design a novel vaccine candidate using tachyzoite-specific SAG1-realted sequence (SRS) proteins. Overlapping B-cell and strictly-chosen human MHC-I binding epitopes were predicted and connected together using appropriate spacers. Moreover, a TLR4 agonist, human high mobility group box protein 1 (HMGB1), and His-tag were added to the N- and C-terminus of the vaccine sequence. The final vaccine had 442 residues and a molecular weight of 47.71 kDa. Physico-chemical evaluation showed a soluble, highly antigenic and non-allergen protein, with coils and helices as secondary structures. The vaccine 3D model was predicted by ITASSER server, subsequently refined and was shown to possess significant interactions with human TLR4. As well, potent stimulation of cellular and humoral immunity was demonstrated upon chimeric vaccine injection. Finally, the outputs showed that this vaccine model possesses top antigenicity, which could provoke significant cell-mediated immune profile including IFN-γ, and can be utilized towards prophylactic purposes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00140-w.

Bioinformatics and immunoinformatics approach to develop potent multi-peptide vaccine for coxsackievirus B3 capable of eliciting cellular and humoral immune response

Coxsackievirus B3 (CVB3) is a viral pathogen of various human disorders with no effective preventative interventions. Herein, we aimed to design a chimeric vaccine construct for CVB3 using reverse vaccinology and immunoinformatics approaches by screening the whole viral polyprotein sequence. Firstly, screening and mapping of viral polyprotein to predict 21 immunodominant epitopes (B-cell, CD8+ and CD4+ T-cell epitopes), fused with an adjuvant (Resuscitation-promoting factor), appropriate linkers, HIV-TAT peptide, Pan DR epitope, and 6His-tag to assemble a multi-epitope vaccine construct. The chimeric construct is predicted as probable antigen, non-allergen, stable, possess encouraging physicochemical features, and indicates a broader population coverage (98 %). The tertiary structure of the constructed vaccine was predicted and refined, and its interaction with the Toll-like receptor 4 (TLR4) was investigated through molecular docking and dynamics simulation. Computational cloning of the construct was carried out in pET28a (+) plasmid to guarantee the higher expression of the vaccine protein. Lastly, in silico immune simulation foreseen that humoral and cellular immune responses would be elicited in response to the administration of such a potent chimeric construct. Thus, the design constructed could vaccinate against CVB3 infection and various CVB serotypes. However, further in vitro/in vivo research must assess its safety and effectiveness.

Employing an immunoinformatics approach revealed potent multi-epitope based subunit vaccine for lymphocytic choriomeningitis virus

BACKGROUND

Lymphocytic choriomeningitis virus (LCMV) infects many individuals worldwide and causes severe infection in the immunosuppressant recipient, spontaneous abortion, and congenital disabilities in infants.

OBJECTIVES

There is no specific vaccine or therapeutics available to protect against LCMV infection; thus, there is a need to design a potential vaccine to combat the virus by developing immunity in the population. Herein, we attempted to design a potent multi-epitope vaccine for LCMV using immunoinformatics methods.

METHODS

The whole proteome of the virus was screened and mapped to extract immunodominant B-cell and T-cell epitopes which were fused with appropriate linkers (EAAAK, GGGS, AAY, GPGPG, and AAY), PADRE sequence (13aa) and an adjuvant (50 S ribosomal protein L7/L12) to formulate a multi-epitope vaccine ensemble. Codon adaptation and in silico cloning of the constructed vaccine were carried out using bioinformatics tools. The secondary and tertiary structure of the vaccine construct was predicted and refined. The physicochemical profile of the designed vaccine was analyzed, and the multi-epitope vaccine's potential to bind Toll-like receptors (TLR2 and TLR4) was evaluated through molecular docking and molecular dynamics simulations. Computational immune simulation of the designed vaccine antigen was performed using the C-ImmSim server.

RESULTS

The designed multi-epitope-based vaccine (613 aa) comprised 26 immunodominant (six B-cell, nine cytotoxic T lymphocytes, and 11 helper T lymphocytes) epitopes and is predicted antigenic, non-toxic, non-allergen, soluble, and topographically accessible with a suitable physicochemical profile. The designed vaccine is expected to cover a broad worldwide population (96.35 %) and stimulate a robust adaptive immune response against the virus upon administration. In silico cloning of the constructed vaccine in PET28a (+) vector ensured its optimal expression in the Escherichia coli system. Molecular docking, molecular dynamics simulation, and binding free energy estimation collectively support the stability and energetically favourable interaction of the modeled vaccine-TLR2/4 complexes.

CONCLUSION

The designed multi-epitope vaccine in the present study could serve as a potential vaccine candidate to protect against LMCV infection; however, the experimental validation and safety testing of the vaccine is warranted to validate the study's outcomes.

Developing a multiepitope vaccine for the prevention of SARS-CoV-2 and monkeypox virus co-infection: A reverse vaccinology analysis

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and monkeypox virus (MPXV) severely threaten human health; however, currently, no vaccine can prevent a co-infection with both viruses.

METHODS

Five antigens were selected to predict dominant T and B cell epitopes screened for immunogenicity, antigenicity, toxicity, and sensitization. After screening, all antigens joined in the construction of a novel multiepitope vaccine. The physicochemical and immunological characteristics, and secondary and tertiary structures of the vaccine were predicted and analyzed using bio- and immunoinformatics. Finally, codon optimization and cloning in-silico were performed.

RESULTS

A new multiepitope vaccine, named S7M8, was constructed based on four helper T lymphocyte (HTL) epitopes, six cytotoxic T lymphocyte (CTL) epitopes, five B cell epitopes, as well as Toll-like receptor (TLR) agonists. The antigenicity and immunogenicity scores of the S7M8 vaccine were 0.907374 and 0.6552, respectively. The S7M8 vaccine was comprised of 26.96% α-helices, the optimized Z-value of the tertiary structure was -5.92, and the favored area after majorization in the Ramachandran plot was 84.54%. Molecular docking showed that the S7M8 vaccine could tightly bind to TLR2 (-1100.6 kcal/mol) and TLR4 (-950.3 kcal/mol). In addition, the immune stimulation prediction indicated that the S7M8 vaccine could activate T and B lymphocytes to produce high levels of Th1 cytokines and antibodies.

CONCLUSION

S7M8 is a promising biomarker with good antigenicity, immunogenicity, non-toxicity, and non-sensitization. The S7M8 vaccine can trigger significantly high levels of Th1 cytokines and antibodies and may be a potentially powerful tool in preventing SARS-CoV-2 and MPXV.

CD171 Multi-epitope peptide design based on immuno-informatics approach as a cancer vaccine candidate for glioblastoma

Glioblastoma (GB) is a common primary malignancy of the central nervous system, and one of the highly lethal brain tumors. GB cells can promote therapeutic resistance and tumor angiogenesis. The CD171 is an adhesion molecule in neuronal cells that is expressed in glioma cells as a regulator of brain development during the embryonic period. CD171 is one of the immunoglobulin-like CAMs (cell adhesion molecules) families that can be associated with prognosis in a variety of human tumors. The multi-epitope peptide vaccines are based on synthetic peptides with a combination of both B-cell epitopes and T-cell epitopes, which can induce specific humoral or cellular immune responses. Moreover, Cholera toxin subunit B (CTB), a novel TLR agonist was utilized in the final construct to polarize CD4+ T cells toward T-helper 1 to induce strong cytotoxic T lymphocytes (CTL) responses. In the present study, several immune-informatics tools were used for analyzing the CD171 sequence and studying the important characteristics of a designed vaccine. The results included molecular docking, molecular dynamics simulation, immune response simulation, prediction and validation of the secondary and tertiary structure, physicochemical properties, solubility, conservancy, toxicity as well as antigenicity and allergenicity of the promising candidate for a vaccine against CD171. The immuno-informatic analyze suggested 12 predicted multi-epitope peptides, whose construction consists of 582 residues long. Therewith, cloning adaptation of the designed vaccine was performed, and eventually sequence was inserted into pET30a (+) vector for the application of the anti-glioblastoma vaccine development.Communicated by Ramaswamy H. Sarma.

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.

Multi epitope vaccine candidate design against Streptococcus pneumonia

Streptococcus pneumonia, the causative agent of sepsis, meningitis and pneumonia, is held responsible for causing invasive diseases predominantly in children along with adults from both developing and developed countries. The available vaccines coverage in the context of different serotypes is limited and emergence of non-vaccine serotypes could further emerge as a threat in future. Advanced immunoinformatics tools have been used for developing a multi epitope subunit vaccine. In the current study we have subjected these four surface antigenic proteins Ply, PsaA, PspA and PspK to construct vaccine designs. We have predicted different B-cell and T-cell epitopes by using NetCTL 1.2, IEDB (Immune Epitope Databases) and ABCpred. An adjuvant (griselimycin) has been added to the vaccine construct sequence in order to improve its immunogenicity. The vaccine construct has been evaluated for its antigenicity, allergenicity, toxicity and different physio-chemical properties. The bioinformatic tools have been used for prediction, refinement and validation of the 3 D structure. Further, the vaccine structure has been docked with a toll-like receptor (TLR-4) by ClusPro 2.0. In conclusion, the proposed multi-epitope vaccine designs could potentially activate both humoral and cellular immune responses and has a potential to be a vaccine candidate against S.pneumoniae, and requires experimental validation for ensuring immunogenicity and safety profile.Communicated by Ramaswamy H. Sarma.

Current Update on Rotavirus in-Silico Multiepitope Vaccine Design

Rotavirus gastroenteritis is one of the leading causes of pediatric morbidity and mortality worldwide in infants and under-five populations. The World Health Organization (WHO) recommended global incorporation of the rotavirus vaccine in national immunization programs to alleviate the burden of the disease. Implementation of the rotavirus vaccination in certain regions of the world brought about a significant and consistent reduction of rotavirus-associated hospitalizations. However, the efficacy of licensed vaccines remains suboptimal in low-income countries where the incidences of rotavirus gastroenteritis continue to happen unabated. The problem of low efficacy of currently licensed oral rotavirus vaccines in low-income countries necessitates continuous exploration, design, and development of new rotavirus vaccines. Traditional vaccine development is a complex, expensive, labor-intensive, and time-consuming process. Reverse vaccinology essentially utilizes the genome and proteome information on pathogens and has opened new avenues for in-silico multiepitope vaccine design for a plethora of pathogens, promising time reduction in the complete vaccine development pipeline by complementing the traditional vaccinology approach. A substantial number of reviews on licensed rotavirus vaccines and those under evaluation are already available in the literature. However, a collective account of rotavirus in-silico vaccines is lacking in the literature, and such an account may further fuel the interest of researchers to use reverse vaccinology to expedite the vaccine development process. Therefore, the main focus of this review is to summarize the research endeavors undertaken for the design and development of rotavirus vaccines by the reverse vaccinology approach utilizing the tools of immunoinformatics.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

In silico screening and epitope mapping of leptospiral outer membrane protein-Lsa46

Leptospirosis is one of the neglected diseases caused by the spirochete, Leptospira interrogans. Leptospiral surface adhesion (Lsa) proteins are surface exposed outer membrane proteins present in the pathogen. It acts as laminin and plasminogen binding proteins which enable them to infect host cells. The major target for the development of vaccine in the current era focuses on surface exposed outer membrane proteins, as they can induce strong and fast immune response in hosts. Therefore, the present study mapped the potential epitopes of the Leptospiral outer membrane proteins, mainly the surface adhesion proteins. Protein sequence analysis of Lsa proteins was done by in silico methods. The primary protein sequence analysis revealed Lsa46 as a suitable target which can be a potent Leptospiral vaccine candidate. Its structure was modelled by threading based method in I-TASSER server and validated by Ramachandran plot. The predicted epitope's interactions with human IgG, IgM(Fab) and T-cell receptor TCR(αβ) were performed by molecular docking studies using Biovia Discovery studio 2018. One of the predicted B-cell epitopes and the IgG showed desirable binding interactions, while four of the predicted B-cell epitopes and T-cell epitopes showed desirable binding interactions with IgM and TCR respectively. The molecular dynamic simulation studies carried out with the molecular docked complexes gave minimized energies indicating stable interactions. The structural analysis of the entire simulated complex showed a stable nature except for one of the Epitope-IgM complex. Further the binding free energy calculation of eight receptor-ligand complex predicted them energetically stable. The results of the study help in elucidating the structural and functional characterization of Lsa46 for epitope-based vaccine design.Communicated by Ramaswamy H. Sarma.

In silico design and evaluation of a novel mRNA vaccine against BK virus: a reverse vaccinology approach

Human polyomavirus type 1, or BK virus (BKV), is a ubiquitous pathogen belonging to the polyomaviridae family mostly known for causing BKV-associated nephropathy (BKVN) and allograft rejection in kidney transplant recipients (KTRs) following the immunosuppression regimens recommended in these patients. Reduction of the immunosuppression level and anti-viral agents are the usual approaches for BKV clearance, which have not met a desired outcome yet. There are also debating matters such as the effect of this pathogen on emerging various comorbidities and the related malignancies in the human population. In this study, a reverse vaccinology approach was implemented to design a mRNA vaccine against BKV by identifying the most antigenic proteins of this pathogen. Potential immunogenic T and B lymphocyte epitopes were predicted through various immunoinformatic tools. The final epitopes were selected according to antigenicity, toxicity, allergenicity, and cytokine inducibility scores. According to the obtained results, the designed vaccine was antigenic, neutral at the physiological pH, non-toxic, and non-allergenic with a world population coverage of 93.77%. Since the mRNA codon optimization ensures the efficient expression of the vaccine in a host cell, evaluation of different parameters showed our designed mRNA vaccine has a stable structure. Moreover, it had strong interactions with toll-like receptor 4 (TLR4) according to the molecular dynamic simulation studies. The in silico immune simulation analyses revealed an overall increase in the immune responses following repeated exposure to the designed vaccine. Based on our findings, the vaccine candidate is ready to be tested as a promising novel mRNA therapeutic vaccine against BKV.

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.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

Identification of potential candidate vaccines against Mycobacterium ulcerans based on the major facilitator superfamily transporter protein

Buruli ulcer is a neglected tropical disease that is characterized by non-fatal lesion development. The causative agent is Mycobacterium ulcerans (M. ulcerans). There are no known vectors or transmission methods, preventing the development of control methods. There are effective diagnostic techniques and treatment routines; however, several socioeconomic factors may limit patients' abilities to receive these treatments. The Bacillus Calmette-Guérin vaccine developed against tuberculosis has shown limited efficacy, and no conventionally designed vaccines have passed clinical trials. This study aimed to generate a multi-epitope vaccine against M. ulcerans from the major facilitator superfamily transporter protein using an immunoinformatics approach. Twelve M. ulcerans genome assemblies were analyzed, resulting in the identification of 11 CD8+ and 7 CD4+ T-cell epitopes and 2 B-cell epitopes. These conserved epitopes were computationally predicted to be antigenic, immunogenic, non-allergenic, and non-toxic. The CD4+ T-cell epitopes were capable of inducing interferon-gamma and interleukin-4. They successfully bound to their respective human leukocyte antigens alleles in in silico docking studies. The expected global population coverage of the T-cell epitopes and their restricted human leukocyte antigens alleles was 99.90%. The population coverage of endemic regions ranged from 99.99% (Papua New Guinea) to 21.81% (Liberia). Two vaccine constructs were generated using the Toll-like receptors 2 and 4 agonists, LprG and RpfE, respectively. Both constructs were antigenic, non-allergenic, non-toxic, thermostable, basic, and hydrophilic. The DNA sequences of the vaccine constructs underwent optimization and were successfully in-silico cloned with the pET-28a(+) plasmid. The vaccine constructs were successfully docked to their respective toll-like receptors. Molecular dynamics simulations were carried out to analyze the binding interactions within the complex. The generated binding energies indicate the stability of both complexes. The constructs generated in this study display severable favorable properties, with construct one displaying a greater range of favorable properties. However, further analysis and laboratory validation are required.

Rational design of a novel multi-epitope peptide-based vaccine against Onchocerca volvulus using transmembrane proteins

Almost a decade ago, it was recognized that the global elimination of onchocerciasis by 2030 will not be feasible without, at least, an effective prophylactic and/or therapeutic vaccine to complement chemotherapy and vector control strategies. Recent advances in computational immunology (immunoinformatics) have seen the design of novel multi-epitope onchocerciasis vaccine candidates which are however yet to be evaluated in clinical settings. Still, continued research to increase the pool of vaccine candidates, and therefore the chance of success in a clinical trial remains imperative. Here, we designed a multi-epitope vaccine candidate by assembling peptides from 14 O. volvulus (Ov) proteins using an immunoinformatics approach. An initial 126 Ov proteins, retrieved from the Wormbase database, and at least 90% similar to orthologs in related nematode species of economic importance, were screened for localization, presence of transmembrane domain, and antigenicity using different web servers. From the 14 proteins retained after the screening, 26 MHC-1 and MHC-II (T-cell) epitopes, and linear B-lymphocytes epitopes were predicted and merged using suitable linkers. The Mycobacterium tuberculosis Resuscitation-promoting factor E (RPFE_MYCTU), which is an agonist of TLR4, was then added to the N-terminal of the vaccine candidate as a built-in adjuvant. Immune simulation analyses predicted strong B-cell and IFN-γ based immune responses which are necessary for protection against O. volvulus infection. Protein-protein docking and molecular dynamic simulation predicted stable interactions between the 3D structure of the vaccine candidate and human TLR4. These results show that the designed vaccine candidate has the potential to stimulate both humoral and cellular immune responses and should therefore be subject to further laboratory investigation.

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 novel chimeric multi-epitope vaccine against Burkholderia pseudomallei, a causative agent of melioidosis

Burkholderia pseudomallei, a gram-negative soil-dwelling bacterium, is primarily considered a causative agent of melioidosis infection in both animals and humans. Despite the severity of the disease, there is currently no licensed vaccine on the market. The development of an effective vaccine against B. pseudomallei could help prevent the spread of infection. The purpose of this study was to develop a multi-epitope-based vaccine against B. pseudomallei using advanced bacterial pan-genome analysis. A total of four proteins were prioritized for epitope prediction by using multiple subtractive proteomics filters. Following that, a multi-epitopes based chimeric vaccine construct was modeled and joined with an adjuvant to improve the potency of the designed vaccine construct. The structure of the construct was predicted and analyzed for flexibility. A population coverage analysis was performed to evaluate the broad-spectrum applicability of B. pseudomallei. The computed combined world population coverage was 99.74%. Molecular docking analysis was applied further to evaluate the binding efficacy of the designed vaccine construct with the human toll-like receptors-5 (TLR-5). Furthermore, the dynamic behavior and stability of the docked complexes were investigated using molecular dynamics simulation, and the binding free energy determined for Vaccine-TLR-5 was delta total -168.3588. The docking result revealed that the vaccine construct may elicit a suitable immunological response within the host body. Hence, we believe that the designed in-silico vaccine could be helpful for experimentalists in the formulation of a highly effective vaccine for B. pseudomallei.

Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches

Background

Bovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses.

Methods

Following a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction.

Results

Our vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor.

Conclusions

The proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03181-w.

A subtractive proteomics and immunoinformatics approach towards designing a potential multi-epitope vaccine against pathogenic Listeriamonocytogenes

Listeria monocytogenes is the causative agent of listeriosis, which is dangerous for pregnant women, the elderly or individuals with a weakened immune system. Individuals with leukaemia, cancer, HIV/AIDS, kidney transplant and steroid therapy suffer from immunological damage are menaced. World Health Organization (WHO) reports that human listeriosis has a high mortality rate of 20-30% every year. To date, no vaccine is available to treat listeriosis. Thereby, it is high time to design novel vaccines against L. monocytogenes. Here, we present computational approaches to design an antigenic, stable and safe vaccine against the L. monocytogenes that could help to control the infections associated with the pathogen. Three vital pathogenic proteins of L. monocytogenes, such as Listeriolysin O (LLO), Phosphatidylinositol-specific phospholipase C (PI-PLC), and Actin polymerization protein (ActA), were selected using a subtractive proteomics approach to design the multi-epitope vaccine (MEV). A total of 5 Cytotoxic T-lymphocyte (CTL) and 9 Helper T-lymphocyte (HTL) epitopes were predicted from these selected proteins. To design the multi-epitope vaccine (MEV) from the selected proteins, CTL epitopes were joined with the AAY linker, and HTL epitopes were joined with the GPGPG linker. Additionally, a human β-defensin-3 (hBD-3) adjuvant was added to the N-terminal side of the final MEV construct to increase the immune response to the vaccine. The final MEV was predicted to be antigenic, non-allergen and non-toxic in nature. Physicochemical property analysis suggested that the MEV construct is stable and could be easily purified through the E. coli expression system. This in-silico study showed that MEV has a robust binding interaction with Toll-like receptor 2 (TLR2), a key player in the innate immune system. Current subtractive proteomics and immunoinformatics study provides a background for designing a suitable, safe and effective vaccine against pathogenic L. monocytogenes.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Pan-Genome-Assisted Computational Design of a Multi-Epitopes-Based Vaccine Candidate against Helicobacter cinaedi

Helicobacter cinaedi is a Gram-negative bacterium from the family Helicobacteraceae and genus Helicobacter. The pathogen is a causative agent of gastroenteritis, cellulitis, and bacteremia. The increasing antibiotic resistance pattern of the pathogen prompts the efforts to develop a vaccine to prevent dissemination of the bacteria and stop the spread of antibiotic resistance (AR) determinants. Herein, a pan-genome analysis of the pathogen strains was performed to shed light on its core genome and its exploration for potential vaccine targets. In total, four vaccine candidates (TonB dependent receptor, flagellar hook protein FlgE, Hcp family type VI secretion system effector, flagellar motor protein MotB) were identified as promising vaccine candidates and subsequently subjected to an epitopes' mapping phase. These vaccine candidates are part of the pathogen core genome: they are essential, localized at the pathogen surface, and are antigenic. Immunoinformatics was further applied on the selected vaccine proteins to predict potential antigenic, non-allergic, non-toxic, virulent, and DRB*0101 epitopes. The selected epitopes were then fused using linkers to structure a multi-epitopes' vaccine construct. Molecular docking simulations were conducted to determine a designed vaccine binding stability with TLR5 innate immune receptor. Further, binding free energy by MMGB/PBSA and WaterSwap was employed to examine atomic level interaction energies. The designed vaccine also stimulated strong humoral and cellular immune responses as well as interferon and cytokines' production. In a nutshell, the designed vaccine is promising in terms of immune responses' stimulation and could be an ideal candidate for experimental analysis due to favorable physicochemical properties.

A novel strategy for developing vaccine candidate against Jaagsiekte sheep retrovirus from the envelope and gag proteins: an in-silico approach

BACKGROUND

Sheep pulmonary adenocarcinoma (OPA) is a contagious lung cancer of sheep caused by the Jaagsiekte retrovirus (JSRV). OPA typically has a serious economic impact worldwide. A vaccine has yet to be developed, even though the disease has been globally spread, along with its complications. This study aimed to construct an effective multi-epitopes vaccine against JSRV eliciting B and T lymphocytes using immunoinformatics tools.

RESULTS

The designed vaccine was composed of 499 amino acids. Before the vaccine was computationally validated, all critical parameters were taken into consideration; including antigenicity, allergenicity, toxicity, and stability. The physiochemical properties of the vaccine displayed an isoelectric point of 9.88. According to the Instability Index (II), the vaccine was stable at 28.28. The vaccine scored 56.51 on the aliphatic index and -0.731 on the GRAVY, indicating that the vaccine was hydrophilic. The RaptorX server was used to predict the vaccine's tertiary structure, the GalaxyWEB server refined the structure, and the Ramachandran plot and the ProSA-web server validated the vaccine's tertiary structure. Protein-sol and the SOLPro servers showed the solubility of the vaccine. Moreover, the high mobile regions in the vaccine's structure were reduced and the vaccine's stability was improved by disulfide engineering. Also, the vaccine construct was docked with an ovine MHC-1 allele and showed efficient binding energy. Immune simulation remarkably showed high levels of immunoglobulins, T lymphocytes, and INF-γ secretions. The molecular dynamic simulation provided the stability of the constructed vaccine. Finally, the vaccine was back-transcribed into a DNA sequence and cloned into a pET-30a ( +) vector to affirm the potency of translation and microbial expression.

CONCLUSION

A novel multi-epitopes vaccine construct against JSRV, was formed from B and T lymphocytes epitopes, and was produced with potential protection. This study might help in controlling and eradicating OPA.

Analysis of Foot and Mouth Disease Virus Polyprotein for Multi Peptides Vaccine Design: An In silico Strategy

Foot-and-mouth disease virus (FMDV) is small RNA virus from Picornaviridae family; genus Aphthovirus. FMDV causes maximum levels of infectivity in cattle and harmful socioeconomic effects. The present report attempted to design vaccine candidate from the polyprotein of FMDV to stimulate protective immune response. The IEDB server was used to predict B and T cells epitopes that were linked via GPGPG and YAA linkers, respectively. Mycobacterium tuberculosis 50S ribosomal protein was exploited as an adjuvant and a six histidine-tag sequence was linked to the carboxyl end of the vaccine for purification and identification. The predicted vaccine comprised 313aa and was antigenic and not allergic. Moreover, the vaccine was acidic and showed stability and hydrophilicity. Vaccine secondary and tertiary structures were predicted. The tertiary structure was refined to ameliorate the quality of the global and local structures of the vaccine. Vaccine model validation was performed and the final quality score of the structural model was computed. The validated model was used for molecular docking with bovine (N*01801-BoLA-A11) allele. Docking process in terms of binding free energy score was significant. Vaccine solubility was investigated based on the protein of E. coli and the stability was based on the disulfide bonding to lessen the entropic and mobile points in vaccine. Lastly, the in silico cloning ensured the proper cloning and best translation of the DNA of vaccine in molecular vectors.

Prevalence of antibiotic heteroresistance associated with Helicobacter pylori infection: A systematic review and meta-analysis

BACKGROUND

Heteroresistance is a general term to describe diverse responses to specific antibiotics that can occur due to infection with either multiple bacterial strains or microevolution of a single strain during chronic infection. Due to limited information regarding heteroresistance Helicobacter pylori (H. pylori) infection, the current study was carried out to evaluate the prevalence of this phenomenon.

METHODS

For this study, all potential relevant studies were collected by searching international databases such as ISI Web of Science, PubMed, Scopus, ScienceDirect, ProQuest, Embase, DOAJ, China National Knowledge Infrastructure (CNKI), and Google Scholar. Finally, the frequency of heteroresistance H. pylori infection was measured using the event rate corresponding to 95% confidence intervals.

RESULTS

A total of 26 studies met our criteria; the eligible studies were related to the years 2001-2022. Our results showed that the prevalence of heteroresistance H. pylori strains was 60.1% to clarithromycin, 61.1% to metronidazole, 46.1% to levofloxacin, 3.8% to amoxicillin, and 21.1% to tetracycline. Our literature review also showed discrepancy of antimicrobial susceptibility test in strains isolated from different anatomical sites of the stomach. Heteroresistance H. pylori infection in developing countries is mostly due to infection with multiple H. pylori strains, while in developed countries it is due to microevolution of a single H. pylori strain in response to antibiotic pressure.

CONCLUSIONS

Heteroresistance H. pylori infection interferes with successful therapy and eventually can lead to the treatment failure. If a biopsy is taken from only one gastric site, resistant strains of H. pylori may be underestimated. Considering the role of heteroresistance H. pylori infection in treatment failure, it is very important for gastroenterologists to improve their knowledge about this fact. Regardingly, new guidelines should be developed and designed for the management and treatment of heteroresistance H. pylori infection.

Exploratory Algorithm of a Multi-epitope-based Subunit Vaccine Candidate Against Cryptosporidium hominis: Reverse Vaccinology-Based Immunoinformatic Approach

Cryptosporidiosis is the leading protozoan-induced cause of diarrheal illness in children, and it has been linked to childhood mortality, malnutrition, cognitive development, with retardation of growth. Cryptosporidium hominis, the anthroponotically transmitted species within the Cryptosporidium genus, contributes significantly to the global burden of infection, accounting for the majority of clinical cases in numerous nations, as well as its emergence in the last decade is largely due to detections obtained through noteworthy epidemiologic research. Nevertheless, there is no vaccine available, and the only licensed medication, nitazoxanide, has been demonstrated to have efficacy limitations in a number of patient groups recognized to be at high risk of complications. Therefore, current study delineates the computational vaccine design for Cryptosporidium hominis, the notable pathogen for enteric diarrhea. Firstly, a comprehensive literature search was conducted to identify six proteins based on their toxigenicity, allergenicity, antigenicity, and prediction of transmembrane helices to make up a multi-epitope-based subunit vaccine. Following that, antigenic non-toxic HTL epitope, CTL epitope with B cell epitope were predicted from the selected proteins and construct a vaccine candidate with adding an adjuvant and some linkers with immunologically superior epitopes. Afterwards, the constructed vaccine candidates and TLR2 receptor were put into the ClusPro server for molecular dynamic simulation to know the binding stability of the vaccine-TLR2 complex. Following that, Escherichia coli strain K12 was used as a cloning host for the chosen vaccine construct via the JCat server. As a result of the findings, it was resolute that the proposed chimeric peptide vaccine could improve the immune response to Cryptosporidium hominis.

Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis

The tick-borne bacterium, Borrelia burgdorferi has been implicated in Lyme disease-a deadly infection, formerly confined to North America, but currently widespread across Europe and Asia. Despite the severity of this disease, there is still no human Lyme disease vaccine available. A reliable immunoinformatic approach is urgently needed for designing a therapeutic vaccine against this Gram-negative pathogen. Through this research, we explored the immunodominant proteins of B. burgdorferi and developed a novel and reliable vaccine design with great immunological predictability as well as low contamination and autoimmunity risks. Our initial analysis involved proteome-wide analysis to filter out proteins on the basis of their redundancy, homology to humans, virulence, immunogenicity, and size. Following the selection of proteins, immunoinformatic tools were employed to identify MHC class I & II epitopes and B-cell epitopes, which were subsequently subjected to a rigorous screening procedure. In the final formulation, ten common MHC-I and II epitopes were used together with a suitable adjuvant. We predicted that the final chimeric multi-epitope vaccine could invoke B-cell responses and IFN-gamma-mediated immunity as well as being stable and non-allergenic. The dynamics simulations predicted the stable folding of the designed molecule, after which the molecular docking predicted the stability of the interaction between the potential antigenic epitopes and human immune receptors. Our studies have shown that the designed next-generation vaccine stimulates desirable immune responses, thus potentially providing a viable way to prevent Lyme disease. Nevertheless, further experimental studies in a wet lab are needed in order to validate the results.

Multi Epitope-Based Vaccine Design for Protection Against Mycobacterium tuberculosis and SARS-CoV-2 Coinfection

Background

A prophylactic and immunotherapeutic vaccine for Mycobacterium tuberculosis (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection.

Methods

The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike glycoprotein of SARS-CoV-2 for B and T cells. The antigenicity, allergenicity, and several physiochemical properties of the developed multi-epitope vaccination were then evaluated. Additionally, molecular docking and normal mode analysis (NMA) were utilized in evaluating the vaccine’s immunogenicity and complex stability.

Results

Selected proteins and predicted epitopes suggest that the vaccine prediction can be helpful in the protection against both SARS-CoV-2 and MTB coinfection. Through docking molecular and NMA, the vaccine-TLR4 protein interaction was predicted to be efficient with a high level of IgG, T-helper cells, T-cytotoxic cells, andIFN-γ.

Conclusion

This epitope-based vaccine is a potentially attractive tool for SARS-CoV-2 and MTB coinfection vaccine development.

Human Coronavirus Spike Protein Based Multi-Epitope Vaccine against COVID-19 and Potential Future Zoonotic Coronaviruses by Using Immunoinformatic Approaches

Zoonotic coronaviruses (CoV) have emerged twice and have caused severe respiratory diseases in humans. Due to the frequent outbreaks of different human coronaviruses (HCoVs), the development of a pan-HCoV vaccine is of great importance. Various conserved epitopes shared by HCoVs are reported to induce cross-reactive T-cell responses. Therefore, this study aimed to design a multi-epitope vaccine, targeting the HCoV spike protein. Genetic analysis revealed that the spike region is highly conserved among SARS-CoV-2, bat SL-CoV, and SARS-CoV. By employing the immunoinformatic approach, we prioritized 20 MHC I and 10 MHCII conserved epitopes to design a multi-epitope vaccine. This vaccine candidate is anticipated to strongly elicit both humoral and cell-mediated immune responses. These results warrant further development of this vaccine into real-world application.

Design of a Multiepitope Vaccine against Chicken Anemia Virus Disease

Chicken anemia virus (CAV) causes severe clinical and sub-clinical infection in poultry globally and thus leads to economic losses. The drawbacks of the commercially available vaccines against CAV disease signal the need for a novel, safe, and effective vaccine design. In this study, a multiepitope vaccine (MEV) consisting of T-cell and B-cell epitopes from CAV viral proteins (VP1 and VP2) was computationally constructed with the help of linkers and adjuvant. The 3D model of the MEV construct was refined and validated by different online bioinformatics tools. Molecular docking showed stable interaction of the MEV construct with TLR3, and this was confirmed by Molecular Dynamics Simulation. Codon optimization and in silico cloning of the vaccine in pET-28a (+) vector also showed its potential expression in the E. coli K12 system. The immune simulation also indicated the ability of this vaccine to induce an effective immune response against this virus. Although the vaccine in this study was computationally constructed and still requires further in vivo study to confirm its effectiveness, this study marks a very important step towards designing a potential vaccine against CAV disease.

In silico Analysis of Peptide-Based Biomarkers for the Diagnosis and Prevention of Latent Tuberculosis Infection

Background

Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but there are no specific methods for diagnosing and preventing LTBI.

Methods

Dominant T and B cell epitopes predicted from five antigens related to LTBI and Mycobacterium tuberculosis region of difference (LTBI-RD) were used to construct a novel polypeptide molecule (PPM). Then, the physicochemical properties, secondary structure, tertiary structure of the PPM, and its binding ability to toll-like receptor 2 (TLR2) and TLR4 were analyzed by bioinformatics tools. Finally, immune stimulation and expression optimization of the PPM were carried out.

Results

Four helper T lymphocytes (HTL) epitopes, five cytotoxic T lymphocytes (CTL) epitopes, and three B cell epitopes were predicted and screened from five LTBI-RD related antigens. These epitopes were connected in series with linkers and adjuvants to construct a novel PPM termed C543P. The results indicated that antigenicity and immunogenicity scores of the C543P candidate were 0.936399 and 1.36469, respectively. The structural analysis results showed that the C543P candidate had good stability. Its secondary structure contained 43.6% α-helix, the Z-score after tertiary structure optimization was −7.9, and the Ramachandran diagram showed that 88.77% amino acid residues of the C543P candidate were in the allowable region. Furthermore, the C543P candidate showed an excellent affinity to TLR2 (−1091.7kcal/mol) and TLR4 (−1102.7kcal/mol). In addition, we also analyzed the immunological characteristics of the C543P candidate. Immune stimulation prediction showed that the C543P candidate could effectively activate T and B lymphocytes and produce high levels of Th1 cytokines such as IFN-γ and IL-2.

Conclusion

We constructed a novel PPM with acceptable antigenicity, immunogenicity, stability, and ability to induce robust immune responses. This study provides a new diagnostic biomarker or peptides-based vaccine for LTBI diagnosis and prevention.

Insight Into Novel Anti-tuberculosis Vaccines by Using Immunoinformatics Approaches

Tuberculosis (TB), an infectious disease, has been a leading cause of morbidity and mortality for decades. The causative agent of TB is the Mycobacterium tuberculosis (Mtb) which can infects various parts of the body, mainly the lungs in pulmonary TB cases. Mycobacterium bovis Bacillus Calmette–Guerin (BCG) is the only approved vaccine for TB, but its efficiency to combat pulmonary TB is limited. Multidrug-resistant (MDR) TB and extensive drug-resistant (XDR) TB requires the evolution of more potent vaccines. Therefore, this research aims to generate a universal TB subunit vaccine using advanced immunoinformatics techniques. In generating a novel multiepitope subunit vaccine, we selected the conserved and experimentally confirmed antigens Rv0058, Rv0101, and Rv3343. After a rigorous evaluation, the top candidates from predicted Helper T-lymphocytes (HTL), Cytotoxic T-lymphocytes (CTL), and B-cell epitopes were considered potential vaccine candidates. Immunogenicity was enhanced by the addition of an adjuvant to the ultimate construct of the vaccine. B-cell epitopes predictions guaranteed the eventual induction of a humoral response. Thereafter, dynamics simulations and molecular docking validated the vaccine-receptor complex’s stability and high affinity for the immune receptor TLR-3. Also, immune simulations revealed the significantly elevated levels of immunoglobulins such as IgM, cytokines such as interleukin-2, helper T (Th) cells, and cytotoxic T-cell populations. These results agreed with the actual inflammatory response and showed rapid antigen clearance after manifold exposure. Finally, the E. coli K12 strain was confirmed via in-silico cloning for quality expression. Nevertheless, in vivo experiments should be performed to validate the safety of the proposed vaccine and its inherent ability to prevent TB infection.