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

In silico design of Mycobacterium tuberculosis multi-epitope adhesin protein vaccines

Mycobacterium tuberculosis (Mtb) adhesin proteins are promising candidates for subunit vaccine design. Multi-epitope Mtb vaccine and diagnostic candidates were designed using immunoinformatic tools. The antigenic potential of 26 adhesin proteins were determined using VaxiJen 2.0. The truncated heat shock protein 70 (tnHSP70), 19 kDa antigen lipoprotein (lpqH), Mtb curli pili (MTP), and Phosphate transport protein S1 (PstS1) were selected based on the number of known epitopes on the Immune Epitope Database (IEDB). B- and T-cell epitopes were identified using BepiPred2.0, ABCpred, SVMTriP, and IEDB, respectively. Population coverage was analysed using prominent South African specific alleles on the IEDB. The allergenicity, physicochemical characteristics and tertiary structure of the tri-fusion proteins were determined. The in silico immune simulation was performed using C-ImmSim. Three truncated sequences, with predicted B and T cell epitopes, and without allergenicity or signal peptides were linked by three glycine-serine residues, resulting in the stable, hydrophilic molecules, tnlpqH-tnPstS1-tnHSP70 (64,86 kDa) and tnMTP-tnPstS1-tnHSP70 (63,96 kDa). Restriction endonuclease recognition sequences incorporated at the N- and C-terminal ends of each construct, facilitated virtual cloning using Snapgene, into pGEX6P-1, resulting in novel, highly immunogenic vaccine candidates (0,912-0,985). Future studies will involve the cloning, recombinant protein expression and purification of these constructs for downstream applications.

Development of innovative multi-epitope mRNA vaccine against central nervous system tuberculosis using in silico approaches

Tuberculosis(TB) of the Central nervous system (CNS) is a rare and highly destructive disease. The emergence of drug resistance has increased treatment difficulty, leaving the Bacillus Calmette-Guérin (BCG) vaccine as the only licensed preventative immunization available. This study focused on identifying the epitopes of PknD (Rv0931c) and Rv0986 from Mycobacterium tuberculosis(Mtb) strain H37Rv using an in silico method. The goal was to develop a therapeutic mRNA vaccine for preventing CNS TB. The vaccine was designed to be non-allergenic, non-toxic, and highly antigenic. Codon optimization was performed to ensure effective translation in the human host. Additionally, the secondary and tertiary structures of the vaccine were predicted, and molecular docking with TLR-4 was carried out. A molecular dynamics simulation confirmed the stability of the complex. The results indicate that the vaccine structure shows effectiveness. Overall, the constructed vaccine exhibits ideal physicochemical properties, immune response, and stability, laying a theoretical foundation for future laboratory experiments.

Discovering peptides and computational investigations of a multiepitope vaccine target Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is the causative agent of tuberculosis (TB), a prevalent airborne infectious disease. Despite the availability of the Bacille Calmette-Guerin vaccine, its global efficacy remains modest, and tuberculosis persists as a significant global public health threat. Addressing this challenge and advancing towards the End MTB Strategy, we developed a multiepitope vaccine (MEV) based on immunoinformatics and computational approaches. Immunoinformatics screening of MBT protein identified immune-dominant epitopes based on Major Histocompatibility Complex (MHC) allele binding, immunogenicity, antigenicity, allergenicity, toxicity, and cytokine inducibility. Selected epitopes were integrated into an MEV construct with adjuvant and linkers, forming a fully immunogenic vaccine candidate. Comprehensive analyses encompassed the evaluation of immunological and physicochemical properties, determination of tertiary structure, molecular docking with Toll-Like Receptors (TLR), molecular dynamics (MD) simulations for all atoms, and immune simulations. Our MEV comprises 534 amino acids, featuring 6 cytotoxic T lymphocyte, 8 helper T lymphocyte, and 7 linear B lymphocyte epitopes, demonstrating high antigenicity and stability. Notably, molecular docking studies and triplicate MD simulations revealed enhanced interactions and stability of MEV with the TLR4 complex compared to TLR2. In addition, the immune simulation indicated the capacity to effectively induce elevated levels of antibodies and cytokines, emphasizing the vaccine's robust immunogenic response. This study presents a promising MEV against TB, exhibiting favorable immunological and physicochemical attributes. The findings provide theoretical support for TB vaccine development. Our study aligns with the global initiative of the End MTB Strategy, emphasizing its potential impact on addressing persistent challenges in TB control.

Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

Bioinformatics-Driven mRNA-Based Vaccine Design for Controlling Tinea Cruris Induced by Trichophyton rubrum

Tinea cruris, a dermatophyte fungal infection predominantly caused by Trichophyton rubrum and Epidermophyton floccosum, primarily affects the groin, pubic region, and adjacent thigh. Its recurrence is frequent, attributable to repeated fungal infections in susceptible individuals, especially those with onychomycosis or tinea pedis, which act as reservoirs for dermatophytes. Given the persistent nature of tinea cruris, vaccination emerges as a promising strategy for fungal infection management, offering targeted, durable protection against various fungal species. Vaccines stimulate both humoral and cell-mediated immunity and are administered prophylactically to prevent infections while minimizing the risk of antifungal resistance development. Developing fungal vaccines is challenging due to the thick fungal cell wall, similarities between fungal and human cells, antigenic variation, and evolutionary resemblance to animals, complicating non-toxic target identification and T-cell response variability. No prior research has shown an mRNA vaccine for T. rubrum. Hence, this study proposes a novel mRNA-based vaccine for tinea cruris, potentially offering long-term immunity and reducing reliance on antifungal medications. This study explores the complete proteome of T. rubrum, identifying potential protein candidates for vaccine development through reverse vaccinology. Immunogenic epitopes from these candidates were mapped and integrated into multitope vaccines and reverse translated to construct mRNA vaccines. Then, the mRNA was translated and computationally assessed for physicochemical, chemical, and immunological attributes. Notably, 1,3-beta-glucanosyltransferase, CFEM domain-containing protein, cell wall galactomannoprotein, and LysM domain-containing protein emerged as promising vaccine targets. Antigenic, immunogenic, non-toxic, and non-allergenic cytotoxic T lymphocyte, helper T lymphocyte, and B lymphocyte epitopes were selected and linked with appropriate linkers and Toll-like receptor (TLR) agonist adjuvants to formulate vaccine candidates targeting T. rubrum. The protein-based vaccines underwent reverse translation to construct the mRNA vaccines, which, after inoculation, were translated again by host ribosomes to work as potential components for triggering the immune response. After that, molecular docking, normal mode analysis, and molecular dynamic simulation confirmed strong binding affinities and stable complexes between vaccines and TLR receptors. Furthermore, immune simulations of vaccines with and without adjuvant demonstrated activation of immune responses, evidenced by elevated levels of IgG1, IgG2, IgM antibodies, cytokines, and interleukins. There was no significant change in antibody production between vaccines with and without adjuvants, but adjuvants are crucial for activating the innate immune response via TLRs. Although mRNA vaccines hold promise against fungal infections, further research is essential to assess their safety and efficacy. Experimental validation is crucial for evaluating their immunogenicity, effectiveness, and safety.

Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis

Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

An mRNA vaccine for pancreatic cancer designed by applying in silico immunoinformatics and reverse vaccinology approaches

Pancreatic ductal adenocarcinoma is the most prevalent pancreatic cancer, which is considered a significant global health concern. Chemotherapy and surgery are the mainstays of current pancreatic cancer treatments; however, a few cases are suitable for surgery, and most of the cases will experience recurrent episodes. Compared to DNA or peptide vaccines, mRNA vaccines for pancreatic cancer have more promise because of their delivery, enhanced immune responses, and lower proneness to mutation. We constructed an mRNA vaccine by analyzing S100 family proteins, which are all major activators of receptors for advanced glycation end products. We applied immunoinformatic approaches, including physicochemical properties analysis, structural prediction and validation, molecular docking study, in silico cloning, and immune simulations. The designed mRNA vaccine was estimated to have a molecular weight of 165023.50 Da and was highly soluble (grand average of hydropathicity of -0.440). In the structural assessment, the vaccine seemed to be a well-stable and functioning protein (Z score of -8.94). Also, the docking analysis suggested that the vaccine had a high affinity for TLR-2 and TLR-4 receptors. Additionally, the molecular mechanics with generalized Born and surface area solvation analysis of the "Vaccine-TLR-2" (-141.07 kcal/mol) and "Vaccine-TLR-4" (-271.72 kcal/mol) complexes also suggests a strong binding affinity for the receptors. Codon optimization also provided a high expression level with a GC content of 47.04% and a codon adaptation index score 1.0. The appearance of memory B-cells and T-cells was also observed over a while, with an increased level of helper T-cells and immunoglobulins (IgM and IgG). Moreover, the minimum free energy of the mRNA vaccine was predicted at -1760.00 kcal/mol, indicating the stability of the vaccine following its entry, transcription, and expression. This hypothetical vaccine offers a groundbreaking tool for future research and therapeutic development of pancreatic cancer.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

Designing a conjugate vaccine targeting Klebsiella pneumoniae ST258 and ST11

Klebsiella pneumoniae (K. pneumoniae) is a common bacterium that can cause iatrogenic infection. Recently, the rise of antibiotic resistance among K. pneumoniae strains is one key factor associated with antibiotic treatment failure. Hencefore, there is an urgent need for effective K. pneumoniae vaccines. This study aimed to design a multi-epitope vaccine (MEV) candidate against K. pneumonia by utilizing an immunoinformatics method. In this study, we obtained 15 cytotoxic T lymphocyte epitopes, 10 helper T lymphocyte epitopes, 6 linear B-cell epitopes, and 2 conformational B-cell epitopes for further research. Then, we designed a multi-epitope vaccine composed of a total of 743 amino acids, containing the epitopes linked by GPGPG flexible links and an EAAAK linker to the Cholera Toxin Subunit B coadjuvant. The observed properties of the MEV, including non-allergenicity, high antigenicity, and hydrophilicity, are noteworthy. The improvements in the tertiary structure through structural refinement and disulfide bonding, coupled with promising molecular interactions revealed by molecular dynamics simulations with TLR4, position the MEV as a strong candidate for further investigation against K. pneumoniae.

Antigen identification strategies and preclinical evaluation models for advancing tuberculosis vaccine development

In its myriad devastating forms, Tuberculosis (TB) has existed for centuries, and humanity is still affected by it. Mycobacterium tuberculosis (M. tuberculosis), the causative agent of TB, was the foremost killer among infectious agents until the COVID-19 pandemic. One of the key healthcare strategies available to reduce the risk of TB is immunization with bacilli Calmette-Guerin (BCG). Although BCG has been widely used to protect against TB, reports show that BCG confers highly variable efficacy (0-80%) against adult pulmonary TB. Unwavering efforts have been made over the past 20 years to develop and evaluate new TB vaccine candidates. The failure of conventional preclinical animal models to fully recapitulate human response to TB, as also seen for the failure of MVA85A in clinical trials, signifies the need to develop better preclinical models for TB vaccine evaluation. In the present review article, we outline various approaches used to identify protective mycobacterial antigens and recent advancements in preclinical models for assessing the efficacy of candidate TB vaccines.

Whole proteome analysis of MDR Klebsiella pneumoniae to identify mRNA and multiple epitope based vaccine targets against emerging nosocomial and lungs associated infections

Klebsiella pneumonia is a Gram negative facultative anaerobic bacterium involved in various community-acquired pneumonia, nosocomial and lungs associated infections. Frequent usage of several antibiotics and acquired resistance mechanisms has made this bacterium multi-drug resistance (MDR), complicating the treatment of patients. To avoid the spread of this bacterium, there is an urgent need to develop a vaccine based on immuno-informatics approaches that is more efficient than conventional method of vaccine prediction or development. Initially, the complete proteomic sequence of K. pneumonia was picked over for specific and prospective vaccine targets. From the annotation of the whole proteome, eight immunogenic proteins were selected, and these shortlisted proteins were interpreted for CTL, B-cells, and HTL epitopes prediction, to construct mRNA and multi-epitope vaccines. The Antigenicity, allergenicity and toxicity analysis validate the vaccine's design, and its molecular docking was done with immuno-receptor the TLR-3. The docking interaction showed a stronger binding affinity with a minimum energy of -1153.2 kcal/mol and established 23 hydrogen bonds, 3 salt bridges, 1 disulfide bond, and 340 non-binding contacts. Further validation was done using In-silico cloning which shows the highest CAI score of 0.98 with higher GC contents of 72.25% which represents a vaccine construct with a high value of expression in E. coli. Immune Simulation shows that the antibodies (IgM, IgG1, and IgG2) production exceeded 650,000 in 2 to 3 days but the response was completely neutralized in the 5th day. In conclusion, the study provides the effective, safe and stable vaccine construct against Klebsiella pneumonia, which further needs in vitro and in vivo validations.Communicated by Ramaswamy H. Sarma.

An integrated multi-pronged reverse vaccinology and biophysical approaches for identification of potential vaccine candidates against Nipah virus

Nipah virus, a paramyxovirus linked to Hendra virus that first appeared in Malaysia and is the etiological agent of viral lethal encephalitis, has emerged as a strong threat to the health community in recent decades. Viral infections are seriously affecting global health. Since there are now no efficient therapeutic options, it will take considerable effort to develop appropriate therapeutic management for the Nipah virus. The main purpose of this study was to design a messenger RNA-based multi-epitope vaccine construct against Nipah virus. This purpose was achieved through multiple immunogenic epitopes prediction using Nipah virus antigenic protein using the immune epitope database and analysis resource (IEDB) followed by the vaccine construction and processing. As in multi-epitopes vaccine construction we selected immunogenic potential fragments of viral proteins, therefore in host immune stimulation we observed proper immune responses toward a multi-epitopes vaccine. In this study, the Nipah virus V protein was used to identify immunodominant epitopes utilizing several reverse vaccinology, immunoinformatics and biophysical methods. The potential antigenic predicted epitopes were further analyzed for immunoinformatics analysis and only selected probable antigenic and non-toxic epitopes were used in designing a multi-epitope mRNA based in silico vaccine against the target pathogen. In vaccine designing a total number of 03B cell epitopes, 09 Cytotoxic T lymphocytes (CTLs) and 01 Helper T lymphocytes (HTL) were prioritized as a good vaccine candidate. In the vaccine construction phase, the selected epitopes were linked together using EAAAK, GPGPG, KK, and AAY linkers, and B-defensin (adjuvant), and MITD sequences were also added to the vaccine construct to increase the potency. After vaccine construction, the physiochemical properties of the vaccine construct were evaluated which predicted that the vaccine construct comprises 320 amino acids with 34.29 kDa (kDa) molecular weight. The instability index was 36.55 proving its stability with the aliphatic index of 82.88. Furthermore, 9.0 theoretical pI and -0.317, GRAVY (Grand Average of Hydropathy) values were predicted in physicochemical properties analysis. A solubility check was applied against the vaccine construct depicting that the vaccine construct is soluble with its calculated value of 0.6. Additionally, after prediction the 3D structure was modeled and refined for docking analysis, the refined 3D structure of the vaccine candidate was further checked for binding affinity with immune cell receptors through docking analysis, in the docking analysis we observed that the vaccine construct has a good binding affinity with immune cells receptor and can induce a proper immune response in host cells. As we predicted effective binding of the designed vaccine construct, hence it can further facilitate the development of vaccine formulation against the Nipah virus. Additionally, molecular dynamic simulation was done using the AMBER v20 package for analysis of the dynamic behaviour of the docked complexes and we observed proper binding stability of the vaccine with target receptor. In C-immune simulation, different humoral and cellular antibody titer was observed in response to the vaccine. Overall using bioinformatics, immunoinformatics, and biophysical approaches we observed that this mRNA base epitopes vaccine construct could facilitate the proof of concept for the formation of the experimental base vaccine against the Nipah virus, as the in silico predictions indicated that the vaccine is highly promising in terms of developing protective immunity. However experimental validation is required to disclose the real immune-protective efficacy of the vaccine.

Development of innovative multi-epitope mRNA vaccine against Pseudomonas aeruginosa using in silico approaches

The rising issue of antibiotic resistance has made treating Pseudomonas aeruginosa infections increasingly challenging. Therefore, vaccines have emerged as a viable alternative to antibiotics for preventing P. aeruginosa infections in susceptible individuals. With its superior accuracy, high efficiency in stimulating cellular and humoral immune responses, and low cost, mRNA vaccine technology is quickly replacing traditional methods. This study aimed to design a novel mRNA vaccine by using in silico approaches against P. aeruginosa. The research team identified five surface and antigenic proteins and selected their appropriate epitopes with immunoinformatic tools. These epitopes were then examined for toxicity, allergenicity and homology. The researchers also checked their presentation and identification by major histocompatibility complex cells and other immune cells through valuable tools like molecular docking. They subsequently modeled a multi-epitope protein and optimized it. The mRNA was analyzed in terms of structure and stability, after which the immune system's response against the new vaccine was simulated. The results indicated that the designed mRNA construct could be an effective and promising vaccine that requires laboratory and clinical trials.

Computational design and evaluation of mRNA- and protein-based conjugate vaccines for influenza A and SARS-CoV-2 viruses

BACKGROUND

Israel confirmed the first case of "flurona"-a co-infection of seasonal flu (IAV) and SARS-CoV-2 in an unvaccinated pregnant woman. This twindemic has been confirmed in multiple countries and underscores the importance of managing respiratory viral illnesses.

RESULTS

The novel conjugate vaccine was designed by joining four hemagglutinin, three neuraminidase, and four S protein of B-cell epitopes, two hemagglutinin, three neuraminidase, and four S proteins of MHC-I epitopes, and three hemagglutinin, nine neuraminidase, and five S proteins of MHC-II epitopes with linkers and adjuvants. The constructed conjugate vaccine was found stable, non-toxic, non-allergic, and antigenic with 0.6466 scores. The vaccine contained 14.87% alpha helix, 29.85% extended strand, 9.64% beta-turn, and 45.64% random coil, which was modeled to a 3D structure with 94.7% residues in the most favored region of the Ramachandran plot and Z-score of -3.33. The molecular docking of the vaccine with TLR3 represented -1513.9 kcal/mol of binding energy with 39 hydrogen bonds and 514 non-bonded contacts, and 1.582925e-07 of eigenvalue complex. Immune stimulation prediction showed the conjugate vaccine could activate T and B lymphocytes to produce high levels of Th1 cytokines and antibodies.

CONCLUSION

The in silico-designed vaccine against IAV and SARS-CoV-2 showed good population coverage and immune response with predicted T- and B-cell epitopes, favorable molecular docking, Ramachandran plot results, and good protein expression. It fulfilled safety criteria, indicating potential for preclinical studies and experimental clinical trials.

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.

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.

In silico designing and immunoinformatics analysis of a novel peptide vaccine against metallo-beta-lactamase (VIM and IMP) variants

The rapid spread of acquired metallo-beta-lactamases (MBLs) among gram negative pathogens is becoming a global concern. Improper use of broad-spectrum antibiotics can trigger the colonization and spread of resistant strains which lead to increased mortality and significant economic loss. In the present study, diverse immunoinformatic approaches are applied to design a potential epitope-based vaccine against VIM and IMP MBLs. The amino acid sequences of VIM and IMP variants were retrieved from the GenBank database. ABCpred and BCPred online Web servers were used to analyze linear B cell epitopes, while IEDB was used to determine the dominant T cell epitopes. Sequence validation, allergenicity, toxicity and physiochemical analysis were performed using web servers. Seven sequences were identified for linear B cell dominant epitopes and 4 sequences were considered as dominant CD4+ T cell epitopes, and the predicted epitopes were joined by KK and GPGPG linkers. Stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. Molecular docking showed that the designed vaccine exhibited sustainable and strong binding interactions with Toll-like receptor 4 (TLR4). Finally, codon adaptation and in silico cloning studies were performed to design an effective vaccine production strategy. Immune simulation significantly provided high levels of immunoglobulins, T helper cells, T-cytotoxic cells and INF-γ. Even though the introduced vaccine candidate demonstrates a very potent immunogenic potential, but wet-lab validation is required to further assessment of the effectiveness of this proposed vaccine candidate.

Clinical manifestations and immune response to tuberculosis

Tuberculosis is a far-reaching, high-impact disease. It is among the top ten causes of death worldwide caused by a single infectious agent; 1.6 million tuberculosis-related deaths were reported in 2021 and it has been estimated that a third of the world's population are carriers of the tuberculosis bacillus but do not develop active disease. Several authors have attributed this to hosts' differential immune response in which cellular and humoral components are involved, along with cytokines and chemokines. Ascertaining the relationship between TB development's clinical manifestations and an immune response should increase understanding of tuberculosis pathophysiological and immunological mechanisms and correlating such material with protection against Mycobacterium tuberculosis. Tuberculosis continues to be a major public health problem globally. Mortality rates have not decreased significantly; rather, they are increasing. This review has thus been aimed at deepening knowledge regarding tuberculosis by examining published material related to an immune response against Mycobacterium tuberculosis, mycobacterial evasion mechanisms regarding such response and the relationship between pulmonary and extrapulmonary clinical manifestations induced by this bacterium which are related to inflammation associated with tuberculosis dissemination through different routes.

Vaccines against Tuberculosis: Where Are We Now?

Tuberculosis (TB) is among the top 10 leading causes of death in low-income countries. Statistically, TB kills more than 30,000 people each week and leads to more deaths than any other infectious disease, such as acquired immunodeficiency syndrome (AIDS) and malaria. TB treatment is largely dependent on BCG vaccination and impacted by the inefficacy of drugs, absence of advanced vaccines, misdiagnosis improper treatment, and social stigma. The BCG vaccine provides partial effectiveness in demographically distinct populations and the prevalence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB incidences demands the design of novel TB vaccines. Various strategies have been employed to design vaccines against TB, such as: (a) The protein subunit vaccine; (b) The viral vector vaccine; (c) The inactivation of whole-cell vaccine, using related mycobacteria, (d) Recombinant BCG (rBCG) expressing Mycobacterium tuberculosis (M.tb) protein or some non-essential gene deleted BCG. There are, approximately, 19 vaccine candidates in different phases of clinical trials. In this article, we review the development of TB vaccines, their status and potential in the treatment of TB. Heterologous immune responses generated by advanced vaccines will contribute to long-lasting immunity and might protect us from both drug-sensitive and drug-resistant TB. Therefore, advanced vaccine candidates need to be identified and developed to boost the human immune system against TB.

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5′, 3′ UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

A study on the design of an in silico self-amplifying mRNA vaccine against Nipah virus using immunoinformatics

The scientific community continues to be impressed with RNA-based vaccines with great efficacy, quick synthesis and speed-to-market. The traditional vaccine may require large doses or repeat injections to achieve an expression for protection against the virus; the self-amplifying mRNA vaccine addresses this limitation. Therefore, a thorough examination of the most antigenic component of the Nipah virus was carried out to design the coding sequence of an antigen, which will provoke a virus-specific immune response. After that, we predicted and evaluated epitopes from NiV G-protein. We employed 8 HTL, 2 CTL and 3 B-cell epitopes. The study of structural compatibility was done by performing docking between HLA alleles and epitopes to get insights into the immune response of epitopes. The entire peptide coding sequence of an antigen was linked using a linker to design the structure of the vaccine. Physicochemical parameters of the designed vaccine constructs were assessed using a protparam server. Later, the vaccine sequence was converted into cDNA. We inserted a gene-expressing replicase at the start of a coding sequence for self-amplification. Next, to formulate the final version of vaccine signal sequences were added. Based on these findings, this mRNA vaccine appears to be a promising option against the Nipah virus.Communicated by Ramaswamy H. Sarma.

mRNA vaccines: a new opportunity for malaria, tuberculosis and HIV

The success of the first licensed mRNA-based vaccines against COVID-19 has created a widespread interest on mRNA technology for vaccinology. As expected, the number of mRNA vaccines in preclinical and clinical development increased exponentially since 2020, including numerous improvements in mRNA formulation design, delivery methods and manufacturing processes. However, the technology faces challenges such as the cost of raw materials, the lack of standardization, and delivery optimization. MRNA technology may provide a solution to some of the emerging infectious diseases as well as the deadliest hard-to-treat infectious diseases malaria, tuberculosis, and human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), for which an effective vaccine, easily deployable to endemic areas is urgently needed. In this review, we discuss the functional structure, design, manufacturing processes and delivery methods of mRNA vaccines. We provide an up-to-date overview of the preclinical and clinical development of mRNA vaccines against infectious diseases, and discuss the immunogenicity, efficacy and correlates of protection of mRNA vaccines, with particular focus on research and development of mRNA vaccines against malaria, tuberculosis and HIV.

Advancing mRNA technologies for therapies and vaccines: An African context

Synthetic mRNA technologies represent a versatile platform that can be used to develop advanced drug products. The remarkable speed with which vaccine development programs designed and manufactured safe and effective COVID-19 vaccines has rekindled interest in mRNA technology, particularly for future pandemic preparedness. Although recent R&D has focused largely on advancing mRNA vaccines and large-scale manufacturing capabilities, the technology has been used to develop various immunotherapies, gene editing strategies, and protein replacement therapies. Within the mRNA technologies toolbox lie several platforms, design principles, and components that can be adapted to modulate immunogenicity, stability, in situ expression, and delivery. For example, incorporating modified nucleotides into conventional mRNA transcripts can reduce innate immune responses and improve in situ translation. Alternatively, self-amplifying RNA may enhance vaccine-mediated immunity by increasing antigen expression. This review will highlight recent advances in the field of synthetic mRNA therapies and vaccines, and discuss the ongoing global efforts aimed at reducing vaccine inequity by establishing mRNA manufacturing capacity within Africa and other low- and middle-income countries.

Evaluation of the whole proteome to design a novel mRNA-based vaccine against multidrug-resistant Serratia marcescens

Serratia marcescens, a Gram-negative bacterium, is one of the known disease-causing pathogens. It is resistant to ampicillin, macrolides, cephalosporins, cefotaxime, and ceftazidime. The only antibiotic that has been proven to be effective against S. marcescens is gentamicin. By causing epigenetic alterations, bacteria can also become resistant to all antibiotics. Many epigenetically related proteins were studied, and four proteins were selected in this regard for epitope evaluation and their subsequent use in the development of a messenger ribonucleic acid (mRNA) vaccine. A series of immune-informatics tools used to build this mRNA vaccine elicited cellular and humoral immunity. Molecular docking between epitopes and alleles of the major histocompatibility complex (MHC) was performed. The vaccine was developed using 37 epitopes, an adjuvant that is a TLR-4 agonist known as resuscitation-promoting factor E (RpfE), subcellular trafficking structures, secretion boosters, and linkers. This proposed architecture was found to cover 99.6% of the population during testing. During testing, it was proven that it was both effective and safe. To confirm our idea, we performed an in silico immunological simulation of vaccination. The codon was also optimized to ensure that the mRNA reached the cytoplasm of a human host and underwent efficient translation. TLR-4 and TLR-3 were also docked against the secondary and tertiary structures of the vaccine peptide. Furthermore, the vaccine's stability was confirmed by molecular dynamics simulation. In summary, this vaccine construct can be a potential candidate against S. marcescens and is suitable for in vitro analyses to validate its effectiveness.

Designing mRNA- and Peptide-Based Vaccine Construct against Emerging Multidrug-Resistant Citrobacter freundii: A Computational-Based Subtractive Proteomics Approach

Background and Objectives: Citrobacter freundii (C. freundii) is an emerging and opportunistic Gram-negative bacteria of the human gastrointestinal tract associated with nosocomial and severe respiratory tract infections. It has also been associated with pneumonia, bloodstream, and urinary tract infections. Intrinsic and adaptive virulence characteristics of C. freundii have become a significant source of diarrheal infections and food poisoning among immune-compromised patients and newborns. Impulsive usage of antibiotics and these adaptive virulence characteristics has modulated the C. freundii into multidrug-resistant (MDR) bacteria. Conventional approaches are futile against MDR C. freundii. Materials and Methods: The current study exploits the modern computational-based vaccine design approach to treat infections related to MDR C. freundii. A whole proteome of C. freundii (strain: CWH001) was retrieved to screen pathogenic and nonhomologous proteins. Six proteins were shortlisted for the selection of putative epitopes for vaccine construct. Highly antigenic, nonallergen, and nontoxic eleven B-cell, HTL, and TCL epitopes were selected for mRNA- and peptide-based multi-epitope vaccine construct. Secondary and tertiary structures of the multi-epitope vaccine (MEVC) were designed, refined, and validated. Results: Evaluation of population coverage of MHC-I and MHC-II alleles were 72% and 90%, respectively. Docking MEVC with TLR-3 receptor with the binding affinity of 21.46 (kcal/mol) occurred through the mmGBSA process. Further validations include codon optimization with an enhanced CAI value of 0.95 and GC content of about 51%. Immune stimulation and molecular dynamic simulation ensure the antibody production upon antigen interaction with the host and stability of the MEVC construct, respectively. Conclusions: These interpretations propose a new strategy to combat MDR C. freundii. Further, in vivo and in vitro trials of this vaccine will be valuable in combating MDR pathogens.

mRNA Vaccine Designing Using Chikungunya Virus E Glycoprotein through Immunoinformatics-Guided Approaches

Chikungunya virus is an alphavirus transmitted by mosquitos that develops into chikungunya fever and joint pain in humans. This virus’ name originated from a Makonde term used to describe an illness that changes the joints and refers to the posture of afflicted patients who are affected by excruciating joint pain. There is currently no commercially available drug or vaccine for chikungunya virus infection and the treatment is performed by symptom reduction. Herein, we have developed a computationally constructed mRNA vaccine construct featuring envelope glycoprotein as the target molecule to aid in the treatment process. We have utilized the reverse vaccinology approach to determine epitopes that would generate adaptive immune reactions. The resulting T and B lymphocytes epitopes were screened by various immunoinformatic tools and a peptide vaccine construct was designed. It was validated by proceeding to docking and MD simulation studies. The following design was then back-translated in nucleotide sequence and codons were optimized according to the expression host system (H. sapiens). Various sequences, including 3′ and 5′ UTR regions, Kozak sequence, poly (A) tail, etc., were introduced into the sequence for the construction of the final mRNA vaccine construct. The secondary structure was generated for validation of the mRNA vaccine construct sequence. Additionally, in silico cloning was also performed to design a vector for proceeding towards in vitro experimentation. The proposed designed vaccine construct may proceed with experimental testing for further efficacy verification and the final development of a vaccine against chikungunya virus infection.

Regulation of Host Immune Response against Enterobacter cloacae Proteins via Computational mRNA Vaccine Design through Transcriptional Modification

Enterobacter cloacae is mainly responsible for sepsis, urethritis, and respiratory tract infections. These bacteria may affect the transcription of the host and particularly their immune system by producing changes in their epigenetics. In the present study, four proteins of Enterobacter cloacae were used to predict the epitopes for the construction of an mRNA vaccine against Enterobacter cloacae infections. In order to generate cellular and humoral responses, various immunoinformatic-based approaches were used for developing the vaccine. The molecular docking analysis was performed for predicting the interaction among the chosen epitopes and corresponding MHC alleles. The vaccine was developed by combining epitopes (thirty-three total), which include the adjuvant Toll-like receptor-4 (TLR4). The constructed vaccine was analyzed and predicted to cover 99.2% of the global population. Additionally, in silico immunological modeling of the vaccination was also carried out. When it enters the cytoplasm of the human (host), the codon is optimized to generate the translated mRNA efficiently. Moreover, the peptide structures were analyzed and docked with TLR-3 and TLR-4. A dynamic simulation predicted the stability of the binding complex. The assumed construct was considered to be a potential candidate for a vaccine against Enterobacter cloacae infections. Hence, the proposed construct is suitable for in vitro analyses to validate its effectiveness.

Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter

A growing amount of information about the different types, functions, and roles played by non-coding RNAs (ncRNAs) is becoming available, as more and more research is done. ncRNAs have been identified as potential therapeutic targets in the treatment of tuberculosis (TB), because they may be essential regulators of the gene network. ncRNA profiling and sequencing has recently revealed significant dysregulation in tuberculosis, primarily due to aberrant processes of ncRNA synthesis, including amplification, deletion, improper epigenetic regulation, or abnormal transcription. Despite the fact that ncRNAs may have a role in TB characteristics, the detailed mechanisms behind these occurrences are still unknown. The dark matter of the genome can only be explored through the development of cutting-edge bioinformatics and molecular technologies. In this review, ncRNAs' synthesis and functions are discussed in detail, with an emphasis on the potential role of ncRNAs in tuberculosis. We also focus on current platforms, experimental strategies, and computational analyses to explore ncRNAs in TB. Finally, a viewpoint is presented on the key challenges and novel techniques for the future and for a wide-ranging therapeutic application of ncRNAs.