Immunoinformatics analysis of antigenic epitopes and designing of a multi-epitope peptide vaccine from putative nitro-reductases of Mycobacterium tuberculosis DosR

Goals and strategies in vaccine development against tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), continues to be a major health problem globally. The emergence of multi-drug-resistant TB and extensively drug-resistant TB has become a severe threat to TB control programs. Currently, the Bacille Calmette-Guerin (BCG) vaccine protects a child from disease dissemination efficiently, but its efficiency wanes in adults. Despite all the limitations of BCG and accelerated TB vaccine research, BCG remains the only approved vaccine available for TB. Anti-TB drug treatment has been successful in combating the disease, but it has various side effects and requires an extended drug treatment period. So, vaccination is the finest outlook that can surpass the above-mentioned limitations. Several vaccine candidates are in the pipeline, and the hope for a potential candidate to either boost the BCG vaccine or replace BCG is underway. This review discusses different approaches to TB vaccine development. It summarizes all the challenges and limitations in vaccine development, and its preclinical and clinical trials. Additionally, DNA vaccines and their vaccination techniques are also discussed. Furthermore, the immunoinformatics approach and nanomaterial-based vaccine delivery with practical and productive endpoints are also discussed. Lastly, the potential prospects are also suggested for further studies, which would help bring positive outcomes.

In-silico development of a novel TLR2-mediating multi-epitope vaccine against Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), still remains one of the leading causes of mortality worldwide. The elusive nature of this pathogen and its ability to develop drug resistance makes it a serious threat to global health. BCG, the only preventive vaccine for TB, has a limited efficacy and provides partial protection against the disease. A new effective recombinant vaccine capable of producing a stronger and more comprehensive immune response is required to address this global threat. In the present study, we adopted an in-silico approach to develop a multi-epitope vaccine by screening 198 "regulatory proteins" of Mtb H37Rv strain. Epitopes generated from these proteins were screened on the basis of antigenicity, cytokine profile, allergenicity, toxicity, conservancy and population coverage. Selected epitopes were docked with predominant MHC alleles that were used to develop a vaccine construct using suitable linkers and adjuvant. The construct was subjected to homology modelling, tertiary structure validation and refinement and was eventually docked with Toll-like receptor 2 receptor. Molecular dynamic simulation studies revealed stable interactions between the vaccine construct and TLR-2 receptor. The construct also displayed a high probability to elicit a protective immune response involving both humoral and cell-mediated components. In conclusion, the findings suggest that the constructed vaccine has the potential to induce a robust immune response against Mtb. However, further in-vitro and in-vivo studies are required to assess the safety, efficacy, and long-term protective effects of the vaccine construct.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00322-8.

Functions of nitroreductases in mycobacterial physiology and drug susceptibility

Tuberculosis is a respiratory infection that is caused by members of the Mycobacterium tuberculosis complex, with M. tuberculosis (Mtb) being the predominant cause of the disease in humans. The approval of pretomanid and delamanid, two nitroimidazole-based compounds, for the treatment of tuberculosis encourages the development of more nitro-containing drugs that target Mtb. Similar to the nitroimidazoles, many antimycobacterial nitro-containing scaffolds are prodrugs that require reductive activation into metabolites that inhibit the growth of the pathogen. This reductive activation is mediated by mycobacterial nitroreductases, leading to the hypothesis that these nitroreductases contribute to the specificity of the nitro prodrugs for mycobacteria. In addition to their prodrug-activating activities, these nitroreductases have different native activities that support the growth of the bacteria. This review summarizes the activities of different mycobacterial nitroreductases with respect to their activation of different nitro prodrugs and highlights their physiological functions in the bacteria.

Respiratory tract infections: an update on the complexity of bacterial diversity, therapeutic interventions and breakthroughs

Respiratory tract infections (RTIs) have a significant impact on global health, especially among children and the elderly. The key bacterial pathogens Streptococcus pneumoniae, Haemophilus influenzae, Klebsiella pneumoniae, Staphylococcus aureus and non-fermenting Gram Negative bacteria such as Acinetobacter baumannii and Pseudomonas aeruginosa are most commonly associated with RTIs. These bacterial pathogens have evolved a diverse array of resistance mechanisms through horizontal gene transfer, often mediated by mobile genetic elements and environmental acquisition. Treatment failures are primarily due to antimicrobial resistance and inadequate bacterial engagement, which necessitates the development of alternative treatment strategies. To overcome this, our review mainly focuses on different virulence mechanisms and their resulting pathogenicity, highlighting different therapeutic interventions to combat resistance. To prevent the antimicrobial resistance crisis, we also focused on leveraging the application of artificial intelligence and machine learning to manage RTIs. Integrative approaches combining mechanistic insights are crucial for addressing the global challenge of antimicrobial resistance in respiratory infections.

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.

A comprehensive approach to developing a multi-epitope vaccine against Mycobacterium tuberculosis: from in silico design to in vitro immunization evaluation

Introduction

The Bacillus Calmette-Guérin (BCG) vaccine, currently used against tuberculosis (TB), exhibits inconsistent efficacy, highlighting the need for more potent TB vaccines.

Materials and methods

In this study, we employed reverse vaccinology techniques to develop a promising multi-epitope vaccine (MEV) candidate, called PP13138R, for TB prevention. PP13138R comprises 34 epitopes, including B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes. Using bioinformatics and immunoinformatics tools, we assessed the physicochemical properties, structural features, and immunological characteristics of PP13138R.

Results

The vaccine candidate demonstrated excellent antigenicity, immunogenicity, and solubility without any signs of toxicity or sensitization. In silico analyses revealed that PP13138R interacts strongly with Toll-like receptor 2 and 4, stimulating innate and adaptive immune cells to produce abundant antigen-specific antibodies and cytokines. In vitro experiments further supported the efficacy of PP13138R by significantly increasing the population of IFN-γ+ T lymphocytes and the production of IFN-γ, TNF-α, IL-6, and IL-10 cytokines in active tuberculosis patients, latent tuberculosis infection individuals, and healthy controls, revealing the immunological characteristics and compare the immune responses elicited by the PP13138R vaccine across different stages of Mycobacterium tuberculosis infection.

Conclusion

These findings highlight the potential of PP13138R as a promising MEV candidate, characterized by favorable antigenicity, immunogenicity, and solubility, without any toxicity or sensitization.

In silico design of a promiscuous chimeric multi-epitope vaccine against Mycobacterium tuberculosis

Tuberculosis (TB) is a global health threat, killing approximately 1.5 million people each year. The eradication of Mycobacterium tuberculosis, the main causative agent of TB, is increasingly challenging due to the emergence of extensive drug-resistant strains. Vaccination is considered an effective way to protect the host from pathogens, but the only clinically approved TB vaccine, Bacillus Calmette-Guérin (BCG), has limited protection in adults. Multi-epitope vaccines have been found to enhance immunity to diseases by selectively combining epitopes from several candidate proteins. This study aimed to design a multi-epitope vaccine against TB using an immuno-informatics approach. Through functional enrichment, we identified eight proteins secreted by M. tuberculosis that are either required for pathogenesis, secreted into extracellular space, or both. We then analyzed the epitopes of these proteins and selected 16 helper T lymphocyte epitopes with interferon-γ inducing activity, 15 cytotoxic T lymphocyte epitopes, and 10 linear B-cell epitopes, and conjugated them with adjuvant and Pan HLA DR-binding epitope (PADRE) using appropriate linkers. Moreover, we predicted the tertiary structure of this vaccine, its potential interaction with Toll-Like Receptor-4 (TLR4), and the immune response it might elicit. The results showed that this vaccine had a strong affinity for TLR4, which could significantly stimulate CD4⁺ and CD8⁺ cells to secrete immune factors and B lymphocytes to secrete immunoglobulins, so as to obtain good humoral and cellular immunity. Overall, this multi-epitope protein was predicted to be stable, safe, highly antigenic, and highly immunogenic, which has the potential to serve as a global vaccine against TB.

Bioinformatics analysis and consistency verification of a novel tuberculosis vaccine candidate HP13138PB

Background

With the increasing incidence of tuberculosis (TB) and the shortcomings of existing TB vaccines to prevent TB in adults, new TB vaccines need to be developed to address the complex TB epidemic.

Method

The dominant epitopes were screened from antigens to construct a novel epitope vaccine termed HP13138PB. The immune properties, structure, and function of HP13138PB were predicted and analyzed with bioinformatics and immunoinformatics. Then, the immune responses induced by the HP13138PB were confirmed by enzyme-linked immunospot assay (ELISPOT) and Th1/Th2/Th17 multi-cytokine detection kit.

Result

The HP13138PB vaccine consisted of 13 helper T lymphocytes (HTL) epitopes, 13 cytotoxic T lymphocytes (CTL) epitopes, and 8 B-cell epitopes. It was found that the antigenicity, immunogenicity, and solubility index of the HP13138PB vaccine were 0.87, 2.79, and 0.55, respectively. The secondary structure prediction indicated that the HP13138PB vaccine had 31% of α-helix, 11% of β-strand, and 56% of coil. The tertiary structure analysis suggested that the Z-score and the Favored region of the HP13138PB vaccine were -4.47 88.22%, respectively. Furthermore, the binding energies of the HP13138PB to toll-like receptor 2 (TLR2) was -1224.7 kcal/mol. The immunoinformatics and real-world experiments showed that the HP13138PB vaccine could induce an innate and adaptive immune response characterized by significantly higher levels of cytokines such as interferon-gamma (IFN-γ), tumor necrosis factor-α (TNF-α), interleukin-4 (IL-4), and IL-10.

Conclusion

The HP13138PB is a potential vaccine candidate to prevent TB, and this study preliminarily evaluated the ability of the HP13138PB to generate an immune response, providing a precursor target for developing TB vaccines.

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.

Multi-epitope-based vaccine design by exploring antigenic potential among leptospiral lipoproteins using comprehensive immunoinformatics and structure-based approaches

Leptospirosis is a tropical and globally neglected zoonotic disease caused by pathogenic spirochetes, leptospira. Although the disease has been studied for decades, a potent or effective vaccine is not available so far. Efforts are being made to design an efficient vaccine candidate using different approaches. Immunoinformatics approaches have been proven to be promising in terms of time and cost. Here, we used immunoinformatics and structure-based approaches to evaluate antigenic B and T-cell epitopes present on the Leptospiral lipoproteins (LipL). The promiscuous overlapping epitopes (B-cell, T-cell, IFN- γ positive and non-allergens), which can induce humoral, cell-mediated, and innate immunity, were selected to generate a multi-epitope chimeric vaccine. To enhance the vaccine immunogenicity, a TLR agonist was fused to the vaccine with a suitable linker. The chimeric vaccine structure was predicted for molecular docking studies with immune receptors. Moreover, the stability of the vaccine-immune receptor complexes was analyzed by normal mode analysis (NMA). The potency of the vaccine construct was predicted by the immune simulation tool. The study provides additional information towards constructing a peptide-based chimeric vaccine effort against Leptospira. This article is protected by copyright. All rights reserved.

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.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

Immunoinformatics-Based Designing of a Multi-Epitope Chimeric Vaccine From Multi-Domain Outer Surface Antigens of Leptospira

Accurate information on antigenic epitopes within a multi-domain antigen would provide insights into vaccine design and immunotherapy. The multi-domain outer surface Leptospira immunoglobulin-like (Lig) proteins LigA and LigB, consisting of 12–13 homologous bacterial Ig (Big)-like domains, are potential antigens of Leptospira interrogans. Currently, no effective vaccine is available against pathogenic Leptospira. Both the humoral immunity and cell-mediated immunity of the host play critical roles in defending against Leptospira infection. Here, we used immunoinformatics approaches to evaluate antigenic B-cell lymphocyte (BCL) and cytotoxic T-lymphocyte (CTL) epitopes from Lig proteins. Based on certain crucial parameters, potential epitopes that can stimulate both types of adaptive immune responses were selected to design a chimeric vaccine construct. Additionally, an adjuvant, the mycobacterial heparin-binding hemagglutinin adhesin (HBHA), was incorporated into the final multi-epitope vaccine construct with a suitable linker. The final construct was further scored for its antigenicity, allergenicity, and physicochemical parameters. A three-dimensional (3D) modeled construct of the vaccine was implied to interact with Toll-like receptor 4 (TLR4) using molecular docking. The stability of the vaccine construct with TLR4 was predicted with molecular dynamics simulation. Our results demonstrate the application of immunoinformatics and structure biology strategies to develop an epitope-specific chimeric vaccine from multi-domain proteins. The current findings will be useful for future experimental validation to ratify the immunogenicity of the chimera.