Identification of Novel Potential Vaccine Candidates against Tuberculosis Based on Reverse Vaccinology

Selection of vaccine candidates against Pseudomonas koreensis using reverse vaccinology and a preliminary efficacy trial in Empurau (Tor tambroides)

This study marks the first utilization of reverse vaccinology to develop recombinant subunit vaccines against Pseudomonas koreensis infection in Empurau (Tor tambroides). The proteome (5538 proteins) was screened against various filters to prioritize proteins based on features that are associated with virulence, subcellular localization, transmembrane helical structure, antigenicity, essentiality, non-homology with the host proteome, molecular weight, and stability, which led to the identification of eight potential vaccine candidates. These potential vaccine candidates were cloned and expressed, with six achieving successful expression and purification. The antigens were formulated into two distinct vaccine mixtures, Vac A and Vac B, and their protective efficacy was assessed through in vivo challenge experiments. Vac A and Vac B demonstrated high protective efficacies of 100 % and 81.2 %, respectively. Histological analyses revealed reduced tissue damage in vaccinated fish after experimental infection, with Vac A showing no adverse effects, whereas Vac B exhibited mild degenerative changes. Quantitative real-time PCR results showed a significant upregulation of TNF-α and downregulation of IL-1β in the kidneys, spleen, gills, and intestine in both Vac A- and Vac B-immunized fish after challenged with P. koreensis. Additionally, IL-8 exhibits tissue-specific differential expression, with significant upregulation in the kidney, gills, and intestine, and downregulation in the spleen, particularly notable in Vac A-immunized fish. The research underscores the effectiveness of the reverse vaccinology approach in fish and demonstrates the promising potential of Vac A and Vac B as recombinant subunit vaccines.

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.

Proteomic profiling of membrane vesicles from Mycobacterium avium subsp. paratuberculosis: Navigating towards an insilico design of a multi-epitope vaccine targeting membrane vesicle proteins

Bacteria typically produce membrane vesicles (MVs) at varying levels depending on the surrounding environments. Gram-negative bacterial outer membrane vesicles (OMVs) have been extensively studied for over 30 years, but MVs from Gram-positive bacteria only recently have been a focus of research. In the present study, we isolated MVs from Mycobacterium avium subsp. paratuberculosis (MAP) and analyzed their protein composition using LC-MS/MS. A total of 316 overlapping proteins from two independent preparations were identified in our study, and topology prediction showed these cargo proteins have different subcellular localization patterns. When MVs were administered to bovine-derived macrophages, significant up-regulation of pro-inflammatory cytokines was observed via qRT-PCR. Proteome functional annotation revealed that many of these proteins are involved in the cellular protein metabolic process, tRNA aminoacylation, and ATP synthesis. Secretory proteins with high antigenicity and adhesion capability were mapped for B-cell and T-cell epitopes. Antigenic, Immunogenic and IFN-γ inducing B-cell, MHC-I, and MHC-II epitopes were stitched together through linkers to form multi-epitope vaccine (MEV) construct against MAP. Strong binding energy was observed during the docking of the 3D structure of the MEV with the bovine TLR2, suggesting that the putative MEV may be a promising vaccine candidate against MAP. However, in vitro and in vivo analysis is required to prove the immunogenic concept of the MEV which we will follow in our future studies. SIGNIFICANCE: Johne's disease is a chronic infection caused by Mycobacterium avium subsp. paratuberculosis that has a potential link to Crohn's disease in humans. The disease is characterized by persistent diarrhea and enteritis, resulting in significant economic losses due to reduced milk yield and premature culling of infected animals. The dairy industry in the United States alone experiences losses of approximately USD 250 million due to Johne's disease. The current vaccine against Johne's disease is limited by several factors, including variable efficacy, limited duration of protection, interference with diagnostic tests, inability to prevent infection, and logistical and cost-related challenges. Nevertheless, a multiepitope vaccine design approach targeting M. avium subsp. paratuberculosis has the potential to overcome these challenges and offer improved protection against Johne's disease.

Advances in protein subunit vaccines against tuberculosis

Tuberculosis (TB), also known as the "White Plague", is caused by Mycobacterium tuberculosis (Mtb). Before the COVID-19 epidemic, TB had the highest mortality rate of any single infectious disease. Vaccination is considered one of the most effective strategies for controlling TB. Despite the limitations of the Bacille Calmette-Guérin (BCG) vaccine in terms of protection against TB among adults, it is currently the only licensed TB vaccine. Recently, with the evolution of bioinformatics and structural biology techniques to screen and optimize protective antigens of Mtb, the tremendous potential of protein subunit vaccines is being exploited. Multistage subunit vaccines obtained by fusing immunodominant antigens from different stages of TB infection are being used both to prevent and to treat TB. Additionally, the development of novel adjuvants is compensating for weaknesses of immunogenicity, which is conducive to the flourishing of subunit vaccines. With advances in the development of animal models, preclinical vaccine protection assessments are becoming increasingly accurate. This review summarizes progress in the research of protein subunit TB vaccines during the past decades to facilitate the further optimization of protein subunit vaccines that may eradicate TB.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Design of a multi-epitope vaccine against six Nocardia species based on reverse vaccinology combined with immunoinformatics

Background

Nocardia genus, a complex group of species classified to be aerobic actinomycete, can lead to severe concurrent infection as well as disseminated infection, typically in immunocompromised patients. With the expansion of the susceptible population, the incidence of Nocardia has been gradually growing, accompanied by increased resistance of the pathogen to existing therapeutics. However, there is no effective vaccine against this pathogen yet. In this study, a multi-epitope vaccine was designed against the Nocardia infection using reverse vaccinology combined with immunoinformatics approaches.

Methods

First, the proteomes of 6 Nocardia subspecies Nocardia subspecies (Nocardia farcinica, Nocardia cyriacigeorgica, Nocardia abscessus, Nocardia otitidiscaviarum, Nocardia brasiliensis and Nocardia nova) were download NCBI (National Center for Biotechnology Information) database on May 1st, 2022 for the target proteins selection. The essential, virulent-associated or resistant-associated, surface-exposed, antigenic, non-toxic, and non-homologous with the human proteome proteins were selected for epitope identification. The shortlisted T-cell and B-cell epitopes were fused with appropriate adjuvants and linkers to construct vaccines. The physicochemical properties of the designed vaccine were predicted using multiple online servers. The Molecular docking and molecular dynamics (MD) simulation were performed to understand the binding pattern and binding stability between the vaccine candidate and Toll-like receptors (TLRs). The immunogenicity of the designed vaccines was evaluated via immune simulation.

Results

3 proteins that are essential, virulent-associated or resistant-associated, surface-exposed, antigenic, non-toxic, and non-homologous with the human proteome were selected from 218 complete proteome sequences of the 6 Nocardia subspecies epitope identification. After screening, only 4 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes that were antigenic, non-allergenic, and non-toxic were included in the final vaccine construct. The results of molecular docking and MD simulation showed that the vaccine candidate has a strong affinity for TLR2 and TLR4 of the host and the vaccine-TLR complexes were dynamically stable in the natural environment. The results of the immune simulation indicated that the designed vaccine had the potential to induce strong protective immune responses in the host. The codon optimization and cloned analysis showed that the vaccine was available for mass production.

Conclusion

The designed vaccine has the potential to stimulate long-lasting immunity in the host, but further studies are required to validate its safety and efficacy.

In silico prediction and expression analysis of vaccine candidate genes of Campylobacter jejuni

Campylobacter jejuni (C. jejuni) is the most common food-borne pathogen that causes human gastroenteritis in the United States. Consumption of contaminated poultry products is considered as the major source of human Campylobacter infection. An effective vaccine would be a promising alternative to antibiotic supplements to curb C. jejuni colonization in poultry gastrointestinal (GI) tract. However, the genetic diversity among the C. jejuni isolates makes vaccine production more challenging. Despite many attempts, an effective Campylobacter vaccine is not yet available. This study aimed to identify suitable candidates to develop a subunit vaccine against C. jejuni, which could reduce colonization in the GI tract of the poultry. In the current study, 4 C. jejuni strains were isolated from retail chicken meat and poultry litter samples and their genomes were sequenced utilizing next-generation sequencing technology. The genomic sequences of C. jejuni strains were screened to identify potential antigens utilizing the reverse vaccinology approach. In silico genome analysis predicted 3 conserved potential vaccine candidates (phospholipase A [PldA], TonB dependent vitamin B12 transporter [BtuB], and cytolethal distending toxin subunit B [CdtB]) suitable for the development of a vaccine. Furthermore, the expression of predicted genes during host-pathogen interaction was analyzed by an infection study using an avian macrophage-like immortalized cell line (HD11). The HD11 was infected with C. jejuni strains, and the RT-qPCR assay was performed to determine the expression of the predicted genes. The expression difference was analyzed using ΔΔCt methods. The results indicate that all 3 predicted genes, PldA, BtuB, and CdtB, were upregulated in 4 tested C. jejuni strains irrespective of their sources of isolation. In conclusion, in silico prediction and gene expression analysis during host-pathogen interactions identified 3 potential vaccine candidates for C. jejuni.

In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches

Non-typhoidal Salmonella (NTS) is one of the leading bacterial causes of many invasive human infections with a high antibiotic resistance profile. With this concern, the current study aimed to design an effective epitope-based peptide vaccine against NTS species as a successive and substitutive protective measure of invasive NTS disease. To design rationally, the current study considered a comprehensive in silico workflow combination of both immunoinformatics and molecular modeling approaches, including molecular docking and molecular dynamics (MD) simulation. We identified the two most promising T cell epitopes KVLYGIFAI and YGIFAITAL, and three B cell epitopes AAPVQVGEAAGS, TGGGDGSNT, and TGGGDGSNTGTTTT, in the outer membrane of NTS. Using these epitopes, a multiepitope vaccine was subsequently constructed along with appropriate adjuvant and linkers, which showed a good binding affinity and stability with toll-like receptor 2 (TLR2) in both molecular docking and MD simulation. Furthermore, in silico immune simulation described a strong immune response with a high number of antibodies, interferon-γ, and activated B and T cells. This study collectively suggests that predicted vaccine constructs could be considered potential vaccine candidates against common NTS species.Communicated by Ramaswamy H. Sarma.

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.

Structural and Functional Annotation and Molecular Docking Analysis of a Hypothetical Protein from Neisseria gonorrhoeae: An In-Silico Approach

Background

Worldwide, Neisseria gonorrhoeae-related sexually transmitted infections (STIs) continue to be of significant public health concern. This obligate-human pathogen has developed a number of defenses against both innate and adaptive immune responses during infection, some of which are mediated by the pathogen's proteins. Hence, the uncharacterized proteins of N. gonorrhoeae can be annotated to get insight into the unique functions of this organism related to its pathogenicity and to find a more efficient therapeutic target.

Methods

In this study, a hypothetical protein (HP) of N. gonorrhoeae was chosen for analysis and an in-silico approach was used to explore various properties such as physicochemical characteristics, subcellular localization, secondary structure, 3D structures, and functional annotation of that HP. Finally, a molecular docking analysis was performed to design an epitope-based vaccine against that HP.

Results

This study has identified the potential role of the chosen HP of N. gonorrhoeae in plasmid transfer, cell cycle control, cell division, and chromosome partitioning. Acidic nature, thermal stability, cytoplasmic localization of the protein, and some of its other physicochemical properties have also been identified through this study. Molecular docking analysis has demonstrated that one of the T cell epitopes of the protein has a significant binding affinity with the human leukocyte antigen HLA-B∗15 : 01.

Conclusions

The in-silico characterization of this protein will help us understand molecular mechanism of action of N. gonorrhoeae and get an insight into novel therapeutic identification processes. This research will, therefore, enhance our knowledge to find new medications to tackle this potential threat to humankind.

Identification and construction of a multi-epitopes vaccine design against Klebsiella aerogenes: molecular modeling study

A rapid rise in antibiotic resistance by bacterial pathogens is due to these pathogens adaptation to the changing environmental conditions. Antibiotic resistance infections can be reduced by a number of ways such as development of safe and effective vaccine. Klebsiella aerogene is a gram-negative, rod-shaped bacterium resistant to a variety of antibiotics and no commercial vaccine is available against the pathogen. Identifying antigens that can be easily evaluated experimentally would be crucial to successfully vaccine development. Reverse vaccinology (RV) was used to identify vaccine candidates based on complete pathogen proteomic information. The fully sequenced proteomes include 44,115 total proteins of which 43,316 are redundant and 799 are non-redundant. Subcellular localization showed that only 1 protein in extracellular matrix, 7 were found in outer-membrane proteins, and 27 in the periplasm space. A total of 3 proteins were found virulent. Next in the B-cell-derived T-cell epitopes mapping phase, the 3 proteins (Fe2^+- enterobactin, ABC transporter substrate-binding protein, and fimbriae biogenesis outer membrane usher protein) were tested positive for antigenicity, toxicity, and solubility. GPGPG linkers were used to prepare a vaccine construct composed of 7 epitopes and an adjuvant of toxin B subunit (CTBS). Molecular docking of vaccine construct with major histocompatibility-I (MHC-I), major histocompatibility-II (MHC-II), and Toll-like receptor 4 (TLR4) revealed vaccine robust interactions and stable binding pose to the receptors. By using molecular dynamics simulations, the vaccine-receptors complexes unveiled stable dynamics and uniform root mean square deviation (rmsd). Further, binding energies of complex were computed that again depicted strong intermolecular bindings and formation of stable conformation.

Towards Reverse Vaccinology for Bovine TB: High Throughput Expression of Full Length Recombinant Mycobacterium bovis Proteins

Bovine tuberculosis caused by Mycobacterium bovis, is a significant global pathogen causing economic loss in livestock and zoonotic TB in man. Several vaccine approaches are in development including reverse vaccinology which uses an unbiased approach to select open reading frames (ORF) of potential vaccine candidates, produce them as recombinant proteins and assesses their immunogenicity by direct immunization. To provide feasibility data for this approach we have cloned and expressed 123 ORFs from the M. bovis genome, using a mixture of E. coli and insect cell expression. We used a concatenated open reading frames design to reduce the number of clones required and single chain fusion proteins for protein pairs known to interact, such as the members of the PPE-PE family. Over 60% of clones showed soluble expression in one or the other host and most allowed rapid purification of the tagged bTB protein from the host cell background. The catalogue of recombinant proteins represents a resource that may be suitable for test immunisations in the development of an effective bTB vaccine.

Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants

The genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel epitopes were identified as immunogenic triggering immune responses and no toxic after investigation with in silico tools. Furthermore, we found these peptide vaccine candidates showed a significant binding affinity for MHC I and MHC II alleles in molecular docking investigations. We consider them to be promising targets for developing peptide-based vaccines against SARS-CoV-2. Subsequently, we designed two efficient multi-epitopes vaccines against the SARS-CoV-2, the first one based on potent MHC class I and class II T-cell epitopes of S (FPNITNLCPF-NYNYLYRLFR-MFVFLVLLPLVSSQC), M (MWLSYFIASF-GLMWLSYFIASFRLF), E (LTALRLCAY-LLFLAFVVFLLVTLA), and N (SPRWYFYYL-AQFAPSASAFFGMSR). The second candidate is the result of the tailoring of the first designed vaccine according to three classes of SARS-CoV-2 variants. Molecular docking showed that the protein-protein binding interactions between the vaccines construct and TLR2-TLR4 immune receptors are stable complexes. These findings confirmed that the final multi-epitope vaccine could be easily adapted to new viral variants. Our study offers a shortlist of promising epitopes that can accelerate the development of an effective and safe vaccine against the virus and its adaptation to new variants.Communicated by Ramaswamy H. Sarma.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

A Systematic Immuno-Informatic Approach to Design a Multiepitope-Based Vaccine Against Emerging Multiple Drug Resistant Serratia marcescens

Serratia marcescens is now an important opportunistic pathogen that can cause serious infections in hospitalized or immunocompromised patients. Here, we used extensive bioinformatic analyses based on reverse vaccinology and subtractive proteomics-based approach to predict potential vaccine candidates against S. marcescens. We analyzed the complete proteome sequence of 49 isolate of Serratia marcescens and identified 5 that were conserved proteins, non-homologous from human and gut flora, extracellular or exported to the outer membrane, and antigenic. The identified proteins were used to select 5 CTL, 12 HTL, and 12 BCL epitopes antigenic, non-allergenic, conserved, hydrophilic, and non-toxic. In addition, HTL epitopes were able to induce interferon-gamma immune response. The selected peptides were used to design 4 multi-epitope vaccines constructs (SMV1, SMV2, SMV3 and SMV4) with immune-modulating adjuvants, PADRE sequence, and linkers. Peptide cleavage analysis showed that antigen vaccines are processed and presented via of MHC class molecule. Several physiochemical and immunological analyses revealed that all multiepitope vaccines were non-allergenic, stable, hydrophilic, and soluble and induced the immunity with high antigenicity. The secondary structure analysis revealed the designed vaccines contain mainly coil structure and alpha helix structures. 3D analyses showed high-quality structure. Molecular docking analyses revealed SMV4 as the best vaccine construct among the four constructed vaccines, demonstrating high affinity with the immune receptor. Molecular dynamics simulation confirmed the low deformability and stability of the vaccine candidate. Discontinuous epitope residues analyses of SMV4 revealed that they are flexible and can interact with antibodies. In silico immune simulation indicated that the designed SMV4 vaccine triggers an effective immune response. In silico codon optimization and cloning in expression vector indicate that SMV4 vaccine can be efficiently expressed in E. coli system. Overall, we showed that SMV4 multi-epitope vaccine successfully elicited antigen-specific humoral and cellular immune responses and may be a potential vaccine candidate against S. marcescens. Further experimental validations could confirm its exact efficacy, the safety and immunogenicity profile. Our findings bring a valuable addition to the development of new strategies to prevent and control the spread of multidrug-resistant Gram-negative bacteria with high clinical relevance.

Putative antigenic proteins identified by comparative and subtractive reverse vaccinology in necrotic enteritis-causing Clostridium perfringens isolated from broiler chickens

BACKGROUND

Avian necrotic enteritis (NE) caused by Clostridium perfringens is a disease with a major economic impact, generating losses estimated to 6 billion of dollars annually for the poultry industry worldwide. The incidence of the disease is particularly on the rise in broiler chicken flocks eliminating the preventive use of antibiotics. To date, no alternative allows for the efficient prevention of NE and a control of the disease using a vaccinal strategy would be mostly prized. For this purpose, comparative and subtractive reverse vaccinology identifying putative immunogenic bacterial surface proteins is one of the most promising approaches.

RESULTS

A comparative genomic study was performed on 16 C. perfringens strains isolated from healthy broiler chickens and from broilers affected with necrotic enteritis. Results showed that the analyzed genomes were composed of 155,700 distinct proteins from which 13% were identified as extracellular, 65% as cytoplasmic and 22% as part of the bacterial membrane. The evaluation of the immunogenicity of these proteins was determined using the prediction software VaxiJen®.

CONCLUSIONS

For the most part, proteins with the highest scores were associated with an extracellular localisation. For all the proteins analyzed, the combination of both the immunogenicity score and the localisation prediction led to the selection of 12 candidate proteins that were mostly annotated as hypothetical proteins. We describe 6 potential candidates of higher interest due to their antigenic potential, their extracellular localisation, and their possible role in virulence of C. perfringens.

Identification of vaccine targets in pathogens and design of a vaccine using computational approaches

Antigen identification is an important step in the vaccine development process. Computational approaches including deep learning systems can play an important role in the identification of vaccine targets using genomic and proteomic information. Here, we present a new computational system to discover and analyse novel vaccine targets leading to the design of a multi-epitope subunit vaccine candidate. The system incorporates reverse vaccinology and immuno-informatics tools to screen genomic and proteomic datasets of several pathogens such as Trypanosoma cruzi, Plasmodium falciparum, and Vibrio cholerae to identify potential vaccine candidates (PVC). Further, as a case study, we performed a detailed analysis of the genomic and proteomic dataset of T. cruzi (CL Brenner and Y strain) to shortlist eight proteins as possible vaccine antigen candidates using properties such as secretory/surface-exposed nature, low transmembrane helix (< 2), essentiality, virulence, antigenic, and non-homology with host/gut flora proteins. Subsequently, highly antigenic and immunogenic MHC class I, MHC class II and B cell epitopes were extracted from top-ranking vaccine targets. The designed vaccine construct containing 24 epitopes, 3 adjuvants, and 4 linkers was analysed for its physicochemical properties using different tools, including docking analysis. Immunological simulation studies suggested significant levels of T-helper, T-cytotoxic cells, and IgG1 will be elicited upon administration of such a putative multi-epitope vaccine construct. The vaccine construct is predicted to be soluble, stable, non-allergenic, non-toxic, and to offer cross-protection against related Trypanosoma species and strains. Further, studies are required to validate safety and immunogenicity of the vaccine.

Introduction of novel putative immunogenic targets against Proteus mirabilis using a reverse vaccinology approach

Multi-drug resistance of Proteus mirabilis, a frequent cause of catheter-associated urinary tract infections, renders ineffective treatment. Therefore, new advanced strategies are needed to overcome it. In the meantime, vaccination may be the most effective and promising method. In this study antigenicity, allergenicity, subcellular localization, human homology, B-cell epitopes and MHC-II binding sites, conserved domains and protein-protein interactions were predicted using different reverse vaccinology methods and bioinformatics databases to find new putative immunogenic targets against P. mirabilis. Finally, 5 putative immunogenic targets against P. mirabilis were identified. Considering all criteria, QKQ94350.1 (Cell envelope opacity-associated protein A), QKQ94681.1 (Porin), QKQ95001.1 (TonB-dependent hemoglobin/ transferrin/ lactoferrin family receptor), QKQ95221.1 (AsmA) and QKQ94335.1 (N-acetylmuramoyl-L-alanine amidase) are excellent putative immunogenic targets. Finally, a multi-epitope vaccine was designed using the conserved linear epitopes of two OMPs (QKQ94681.1 and QKQ95001.1) and N-acetylmuramoyl-L-alanine amidase (QKQ94335.1), which have promising properties for immunization. These findings can simplify the development of efficient vaccines against P. mirabilis.

Computational discovery and ex-vivo validation study of novel antigenic vaccine candidates against tuberculosis

Tuberculosis (TB) is a complex infectious bacterial disease, which has evolved with highly successful mechanisms to interfere with host defenses and existing classes of antibiotics to resist eradication. The single obtainable TB vaccine, Bacille Calmette-Guerin (BCG) has failed to provide regular defense for respiratory TB in adults. In this study, a bioinformatics and immunoinformatics approach was applied on Mycobacterium tuberculosis (Mtb) H37Rv proteomes to discover the potential subunit vaccine candidates that elicit both tuberculosis-specific T-cells and B-cell immune response. A total of 4049 proteins of MtbH37RvMtbH37Rv were retrieved and subjected to in silico sequence-based analysis. Finally, five (P9WL69 (Rv2599), P9WIG1 (Rv0747), P9WLQ1 (Rv1987), O53608 (Rv0063), O06624 (Rv1566c)) novel putative proteins were selected. Among the five putative antigenic vaccine candidates, P9WL69 protein was selected for the ex-vivo validation study. The P9WL69 protein encoding gene was amplified and cloned on pET21b vector. The success of the recombinant clone (pET21b-RV2599) was confirmed by colony PCR, insert release test and sequencing. Furthermore, the identified epitopes of the P9WL69 protein were considered for in silico docking and molecular dynamics simulation study using Toll-like Receptors (TLRs) (TLR-2, TLR-4, TLR-9), Mannose receptor, and Myeloid differentiation 88 (MYD88) to understand their binding affinity towards the development of immunogenic vaccines against tuberculosis.

Immunization with SP_1992 (DiiA) Protein of Streptococcus pneumoniae Reduces Nasopharyngeal Colonization and Protects against Invasive Disease in Mice

Knowledge-based vaccinology can reveal uncharacterized antigen candidates for a new generation of protein-based anti-pneumococcal vaccines. DiiA, encoded by the sp_1992 locus, is a surface protein containing either one or two repeats of a 37mer N-terminal motif that exhibits low interstrain variability. DiiA belongs to the core proteome, contains several conserved B-cell epitopes, and is associated with colonization and pathogenesis. Immunization with DiiA protein via the intraperitoneal route induced a strong IgG response, including different IgG subtypes. Vaccination with DiiA increased bacterial clearance and induced protection against sepsis, conferring 70% increased survival at 48 h post-infection when compared to the adjuvant control. The immunogenic response and survival rates in mice immunized with a truncated DiiA version lacking 119 N-terminal residues were remarkably lower, confirming the relevance of the repeat zone in the immunoprotection by DiiA. Intranasal immunization of mice with the entire recombinant protein elicited mucosal IgG and IgA responses that reduced bacterial colonization of the nasopharynx, confirming that this protein might be a vaccine candidate for reducing the carrier rate. DiiA constitutes an example of how functionally unannotated proteins may still represent promising candidates that can be used in prophylactic strategies against the pneumococcal carrier state and invasive disease.

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

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

Prioritization of potential drug targets and antigenic vaccine candidates against Klebsiella aerogenes using the computational subtractive proteome-driven approach

Klebsiella aerogenes is a multidrug-resistant Gram-negative bacterium that causes nosocomial infections. The organism showed resistance to most of the conventional antibiotics available. Because of the high resistance of the species, the treatment of K. aerogenes is difficult. These species are resistant to third-generation cephalosporins due to the production of chromosomal beta-lactams with cephalosporin activity. The lack of better treatment and the development of therapeutic resistance in hospitals hinders better/new broad-spectrum-based treatment against this pathogen. This study identifies potential drug targets/vaccine candidates through a computational subtractive proteome-driven approach. This method is used to predict proteins that are not homologous to humans and human symbiotic intestinal flora. The resultant proteome of K. aerogenes was further searched for proteins, which are essential, virulent, and determinants of antibiotic/drug resistance. Subsequently, their druggability properties were also studied. The data set was reduced based on its presence in the pathogen-specific metabolic pathways. The subtractive proteome analysis predicted 13 proteins as potential drug targets for K. aerogenes. Furthermore, these target proteins were annotated based on their spectrum of activity, cellular localization, and antigenicity properties, which ensured that they are potent candidates for broad-spectrum antibiotic and vaccine design. The results open up new opportunities for designing and manufacturing powerful antigenic vaccines against K. aerogenes and the detection and release of new and active drugs against K. aerogenes without altering the gut microbiome.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00068-9.

Strongyloides stercoralis proteome: A reverse approach to the identification of potential immunogenic candidates

Strongyloides stercoralis is a parasite widely distributed in the tropical and subtropical areas in the world. Its treatment and diagnosis have a limitation as many other parasitic diseases. Nowadays, there is a great interest in designing an efficient epitope for vaccines or diagnostic. In this study, a bioinformatics-based screening approach has been incorporated in order to explore potential immunogens in the S. stercoralis proteome. Bioinformatic tools were used to predict diagnostic and vaccinology approaches. 12.851 cell immunology proteins from Uniprot were analyzed. Thirty-four immunogenic candidates were identified, they had higher antigenic activity, less than 2 α-helices, non-allergen activity and they do not have homology with host proteins, all of them have ortholog protein with Strongyloides ratti. Some of them presented a good binding with immunological cell (T and B cell). These proteins could be a good alternative as a candidate for the design of the novel vaccines or diagnostic tests of strongyloides stercoralis.

Recent progress in the design of DNA vaccines against tuberculosis

Current tuberculosis (TB) vaccines have some disadvantages and many efforts have been undertaken to produce effective TB vaccines. As a result of their advantages, DNA vaccines are promising future vaccine candidates. This review focuses on the design and delivery of novel DNA-based vaccines against TB.

Analysis of Putative Epitope Candidates of Mycobacterium tuberculosis Against Pakistani Human Leukocyte Antigen Background: An Immunoinformatic Study for the Development of Future Vaccine

Tuberculosis (TB), a chronic disease caused by Mycobacterium tuberculosis (Mtb), is a global health issue across the world. Pakistan ranks fifth among the countries, which are facing, a significantly great number of mortalities and morbidities due to TB. Unfortunately, all previously reported treatments are not successful for the eradication of TB. Here in this study, we report an emerging treatment option for this disease. We have applied immunoinformatics to predict highly conserved B and T-cell epitopes from Mtb, showing significant binding affinities to the frequent HLA alleles in the Pakistani population. A total of ten highly referenced and experimentally validated epitopes were selected from the Immune Epitope Database (IEDB), followed by their conservancy analysis using weblogos. The consensus sequences and variants derived from these sequences were examined, for their binding affinities, with prevalent HLA alleles of Pakistan. Moreover, the antigenic and allergenic natures of these peptides were also evaluated via Vaxijen and AllerTOP, respectively. Consequently, all potentially allergenic and non-antigenic, peptide fragments, were excluded from the analysis. Among all putative epitopes, three CD8 + T-cell epitopes were selected, as ideal vaccine candidates and, population coverage analysis revealed that the combination of these three peptides was covering, 67.28% Pakistani Asian and 57.15% mixed Pakistani populations. Likewise, eleven linear and six conformational or discontinuous B-cell epitopes were also marked as potential vaccine candidates based on their prediction score, non-allergenic nature, and antigenic properties. These epitopes, however, need the final validation via wet-lab studies. After their approval, these epitopes would be effective candidates for the future designing of epitope-based vaccines against Mtb infections in Pakistan.

Immunoinformatics Approach to Design a Novel Epitope-Based Oral Vaccine Against Helicobacter pylori

Helicobacter pylori is an infectious agent that colonizes the gastric mucosa of half of the population worldwide. This bacterium has been recognized as belonging to group 1 carcinogen by the World Health Organization for the role in development of gastritis, peptic ulcers, and cancer. Due to the increase in resistance to antibiotics used in the anti-H. pylori therapy, the development of an effective vaccine is an alternative of great interest, which remains a challenge. Therefore, a rational, strategic, and efficient vaccine design against H. pylori is necessary where the use of the most current bioinformatics tools could help achieve it. In this study, immunoinformatics approach was used to design a novel multiepitope oral vaccine against H. pylori. Our multiepitope vaccine is composed of cholera toxin subunit B (CTB) that is used as a mucosal adjuvant to enhance vaccine immunogenicity for oral immunization. CTB fused to 11 epitopes predicted of pathogenic (UreB170-189, VacA459-478, CagA1103-1122, GGT106-126, NapA30-44, and OipA211-230) and colonization (HpaA33-52, FlaA487-506, FecA437-456, BabA129-149, and SabA540-559) proteins from H. pylori. CKS9 peptide (CKSTHPLSC) targets epithelial microfold cells to enhance vaccine uptake from the gut barrier. All sequences were joined to each other by proper linkers. The vaccine was modeled and validated to achieve a high-quality three-dimensional structure. The vaccine design was evaluated as nonallergenic, antigenic, soluble, and with an appropriate molecular weight and isoelectric point. Our results suggest that our newly designed vaccine could serve as a promising anti-H. pylori vaccine candidate.

Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV)

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide 'ELRSELIGY' of phosphoprotein and 'YPLLWSFAM' of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.

Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the human SKP2 gene

In SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complexes, S-phase kinase 2 (SKP2) is one of the major players of F-box family, that is responsible for the degradation of several important cell regulators and tumor suppressor proteins. Despite of having significant evidence for the role of SKP2 on tumorgenesis, there is a lack of available data regarding the effect of non-synonymous polymorphisms. In this communication, the structural and functional consequences of non-synonymous single nucleotide polymorphisms (nsSNPs) of SKP2 have been reported by employing various computational approaches and molecular dynamics simulation. Initially, several computational tools like SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0 and ConSurf have been implicated in this study to explore the damaging SNPs. In total of 172 nsSNPs, 5 nsSNPs were identified as deleterious and 3 of them were predicted to be decreased the stability of protein. Guided from ConSurf analysis, P101L (rs761253702) and Y346C (rs755010517) were categorized as the highly conserved and functional disrupting mutations. Therefore, these mutations were subjected to three dimensional model building and molecular dynamics simulation study for the detailed structural consequences upon the mutations. The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics. As both these mutations are located in the most functional regions of SKP2 protein, these computational insights might be helpful to consider these nsSNPs for wet-lab confirmatory analysis as well as in rationalizing future population based studies and structure based drug design against SKP2.

Vaccine Target Discovery

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

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

PPE65 of M. tuberculosis regulate pro-inflammatory signalling through LRR domains of Toll like receptor-2

Our understanding of the PE/PPE family of proteins in M. tuberculosis (Mtb) pathogenesis is still evolving and their critical roles in the host immunomodulation are still in the discovery process. Earlier studies from our group have shown that TLR2-LRR domain plays an important role in regulating cytokine signalling by PPE proteins. The importance of TLR2-LRR domain 16-20 in the regulation of PPE17-induced pro-inflammatory signalling has been established recently. However, it is yet to find whether other PPE protein also targets the TLR2-LRR 16-20 domain for induction of pro-inflammatory responses. In the current study, we have explored the structural parameters and possible role of PPE65 in generating pro-inflammatory signalling molecules mediated through IRAK3 downstream of TLR2-LRR domain 16-20. This study conceptualizes the functional characteristics of PPE65 in infection condition and might possibly provide valuable information in exploring this protein as an immunomodulator in Mtb infection.

BPSL1626: Reverse and Structural Vaccinology Reveal a Novel Candidate for Vaccine Design against Burkholderia pseudomallei

Due to significant advances in computational biology, protein prediction, together with antigen and epitope design, have rapidly moved from conventional methods, based on experimental approaches, to in silico-based bioinformatics methods. In this context, we report a reverse vaccinology study that identified a panel of 104 candidate antigens from the Gram-negative bacterial pathogen Burkholderia pseudomallei, which is responsible for the disease melioidosis. B. pseudomallei can cause fatal sepsis in endemic populations in the tropical regions of the world and treatment with antibiotics is mostly ineffective. With the aim of identifying potential vaccine candidates, we report the experimental validation of predicted antigen and type I fimbrial subunit, BPSL1626, which we show is able to recognize and bind human antibodies from the sera of Burkholderia infected patients and to stimulate T-lymphocytes in vitro. The prerequisite for a melioidosis vaccine, in fact, is that both antibody- and cell-mediated immune responses must be triggered. In order to reveal potential antigenic regions of the protein that may aid immunogen re-design, we also report the crystal structure of BPSL1626 at 1.9 Å resolution on which structure-based epitope predictions were based. Overall, our data suggest that BPSL1626 and three epitope regions here-identified can represent viable candidates as potential antigenic molecules.

Advanced In Silico Tools for Designing of Antigenic Epitope as Potential Vaccine Candidates Against Coronavirus

Vaccines are the most economical and potent substitute of available medicines to cure various bacterial and viral diseases. Earlier, killed or attenuated pathogens were employed for vaccine development. But in present era, the peptide vaccines are in much trend and are favoured over whole vaccines because of their superiority over conventional vaccines. These vaccines are either based on single proteins or on synthetic peptides including several B-cell and T-cell epitopes. However, the overall mechanism of action remains the same and works by prompting the immune system to activate the specific B-cell- and T-cell-mediated responses against the pathogen. Rino Rappuoli and others have contributed in this field by plotting the design of the most potent and fully computational approach for discovery of potential vaccine candidates which is popular as reverse vaccinology. This is quite an unambiguous advance for vaccine evolution where one begins with the genome information of the pathogen and ends up with the list of certain epitopes after application of multiple bioinformatics tools. This book chapter is an effort to bring this approach of reverse vaccinology into notice of readers using example of coronavirus.

Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach

Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

A novel B- and helper T-cell epitopes-based prophylactic vaccine against Echinococcus granulosus

Introduction: In this study, we targeted the worm stage of Echinococcus granulosus to design a novel multi-epitope B- and helper T-cell based vaccine construct for immunization of dogs against this multi-host parasite.

Methods: The vaccine was designed based on the local Eg14-3-3 antigen (Ag). DNA samples were extracted from the protoscoleces of the infected sheep’s liver, and then subjected to the polymerase chain reaction (PCR) with 14-3-3 specific forward and reverse primers. For the vaccine designing, several in silico steps were undertaken. Three-dimensional (3D) structure of the local Eg14-3-3 Ag was modeled by EasyModeller software. The protein modeling accuracy was then analyzed via various validation assays. Potential transmembrane helix, signal peptide, post-translational modifications and allergenicity of Eg14-3-3 were evaluated as the preliminary measures of B-cell epitopes (BEs ) prediction. Having used many web-servers, a well-designed process was carried out for improved prediction of BEs. High ranked linear and conformational BEs were utilized for engineering the final vaccine construct. Possible T-helper epitopes (TEs) were identified by the molecular docking between 13-mer fragments of the Eg14-3-3 Ag and two high frequent dog class II MHC alleles (i.e., DLA-DRB1*01101 and DRB1*01501). The epitopes coverage was evaluated by Shannon’s variability plot.

Results: The final designed construct was analyzed based on different physicochemical properties, which was then codon optimized for high-level expression in Escherichia coli k12. This minigene construct is the first dog-specific epitopic vaccine construct that is established based on TEs with high-binding affinity to canine MHC alleles.

Conclusion: This in silico study is the first part of a multi-antigenic vaccine designing work that represents as a novel dog-specific vaccine against E. granulosus. Here, we present key data on the step-by-step methodologies used for designing this de novo vaccine, which is under comprehensive in vivo investigations.

Novel in silico tools for designing peptide-based subunit vaccines and immunotherapeutics

The conventional approach for designing vaccine against a particular disease involves stimulation of the immune system using the whole pathogen responsible for the disease. In the post-genomic era, a major challenge is to identify antigenic regions or epitopes that can stimulate different arms of the immune system. In the past two decades, numerous methods and databases have been developed for designing vaccine or immunotherapy against various pathogen-causing diseases. This review describes various computational resources important for designing subunit vaccines or epitope-based immunotherapy. First, different immunological databases are described that maintain epitopes, antigens and vaccine targets. This is followed by in silico tools used for predicting linear and conformational B-cell epitopes required for activating humoral immunity. Finally, information on T-cell epitope prediction methods is provided that includes indirect methods like prediction of Major Histocompatibility Complex and transporter-associated protein binders. Different studies for validating the predicted epitopes are also examined critically. This review enlists novel in silico resources and tools available for predicting humoral and cell-mediated immune potential. These predicted epitopes could be used for designing epitope-based vaccines or immunotherapy as they may activate the adaptive immunity. Authors emphasized the need to develop tools for the prediction of adjuvants to activate innate and adaptive immune system simultaneously. In addition, attention has also been given to novel prediction methods to predict general therapeutic properties of peptides like half-life, cytotoxicity and immune toxicity.

A novel in silico minigene vaccine based on CD4+ T-helper and B-cell epitopes of EG95 isolates for vaccination against cystic echinococcosis

EG95 oncospheral antigen plays a crucial role in Echinococcus granulosus pathogenicity. Considering the diversity of antigen among different EG95 isolates, it seems to be an ideal antigen for designing a universal multivalent minigene vaccine, so-called multi-epitope vaccine. This is the first in silico study to design a construct for the development of global EG95-based hydatid vaccine against E. granulosus in intermediate hosts. After antigen sequence selection, the three-dimensional structure of EG95 was modeled and multilaterally validated. The preliminary parameters for B-cell epitope prediction were implemented such as the possible transmembrane helix, signal peptide, post-translational modifications and allergenicity. The high ranked linear and conformational B-cell epitopes derived from several online web-servers (e.g., ElliPro, BepiPred v1.0, BcePred, ABCpred, SVMTrip, IEDB algorithms, SEPPA v2.0 and Discotope v2.0) were utilized for multiple sequence alignment and then for engineering the vaccine construct. T-helper based epitopes were predicted by molecular docking between the high frequent ovar class II allele (Ovar-DRB1*1202) and hexadecamer fragments of the EG95 protein. Having used the immune-informatics tools, we formulated the first EG95-based minigene vaccine based on T-helper epitope with high-binding affinity to the ovar MHC allele. This designed construct was analyzed for different physicochemical properties. It was also codon-optimized for high-level expression in Escherichia coli k12. Taken all, we propose the present in silico vaccine constructs as a promising platform for the generation of broadly protective vaccines for species and genus-specific immunization of the natural hosts of the parasite.

Successes and failures in human tuberculosis vaccine development

INTRODUCTION

Tuberculosis (TB) is an infectious disease caused mainly by Mycobacterium tuberculosis. In 2016, the WHO estimated 10.5 million new cases and 1.8 million deaths, making this disease the leading cause of death by an infectious agent. The current and projected TB situation necessitates the development of new vaccines with improved attributes compared to the traditional BCG method. Areas covered: In this review, the authors describe the most promising candidate vaccines against TB and discuss additional key elements in vaccine development, such as animal models, new adjuvants and immunization routes and new strategies for the identification of candidate vaccines. Expert opinion: At present, around 13 candidate vaccines for TB are in the clinical phase of evaluation; however, there is still no substitute for the BCG vaccine. One major impediment to developing an effective vaccine is our lack of understanding of several of the mechanisms associated with infection and the immune response against TB. However, the recent implementation of an entirely new set of technological advances will facilitate the proposal of new candidates. Finally, development of a new vaccine will require a major coordination of effort in order to achieve its effective administration to the people most in need of it.

The N-terminal domain of Mycobacterium tuberculosis PPE17 (Rv1168c) protein plays a dominant role in inducing antibody responses in active TB patients

The PPE (proline-proline-glutamic acid) proteins of Mycobacterium tuberculosis are characterized by a conserved N-terminal domain of approximately 180 amino acids and variable C-terminal domain. Since last decade, these proteins have gained much importance in the serodiagnosis of tuberculosis (TB) as they act as a source of antigenic variation. We have demonstrated earlier that one of the PPE proteins PPE17 (Rv1168c) induces strong B-cell and T-cell responses in active TB disease and also displays a higher antibody titer compared to immunodominant antigens such as ESAT-6, Hsp60 and PPD. However, the immunodominant domain of PPE17 (N-terminal or C-terminal) was not examined in detail. In the present study, we observed that antibody responses elicited in TB patients were directed mostly towards the N-terminal domain of PPE17 (N-PPE17). The antibody generated against N-PPE17 in TB patients did not significantly cross-react with N-terminal domains of other PPE proteins used in this study. Our data suggest that the N-terminal domain of PPE17 protein is immunodominant and could be used as a better serodiagnostic marker than the full-length PPE17 protein.

Glycolysis-related proteins are broad spectrum vaccine candidates against aquacultural pathogens

Reverse vaccinology (RV) has become a popular method for developing vaccines. Although Edwardsiella tarda is deemed to be an important fish pathogen, so far, no reports have used a genome-based approach to screen vaccine candidates against E. tarda. In the current study, protective antigens of E. tarda were screened using RV. Large-scale cloning, expression and purification of potential candidates were carried out, and their immunoprotective potential was evaluated. A candidate fructose-bisphosphate aldolase (FBA) exhibited broad spectrum protection, as did another glycolysis-related protein glyceraldehyde-3-phosphate dehydrogenase (GAPDH), which we reported previously, indicating the potential of other glycolysis-related proteins of E. tarda as broad spectrum protective antigens. In total, half (5 out 10) of these proteins showed prominent immunoprotective potential. Therefore, we suggest that glycolysis-related proteins are a class of potential broad spectrum protective antigens and that these proteins should be preferentially selected.

In silico-based vaccine design against Ebola virus glycoprotein

Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.

Identification of Novel Vaccine Candidates against Campylobacter through Reverse Vaccinology

Campylobacteriosis is the most prevalent bacterial foodborne gastroenteritis affecting humans in the European Union. Human cases are mainly due to Campylobacter jejuni or Campylobacter coli, and contamination is associated with the handling and/or consumption of poultry meat. In fact, poultry constitutes the bacteria's main reservoir. A promising way of decreasing the incidence of campylobacteriosis in humans would be to decrease avian colonization. Poultry vaccination is of potential for this purpose. However, despite many studies, there is currently no vaccine available on the market to reduce the intestinal Campylobacter load in chickens. It is essential to identify and characterize new vaccine antigens. This study applied the reverse vaccinology approach to detect new vaccine candidates. The main criteria used to select immune proteins were localization, antigenicity, and number of B-epitopes. Fourteen proteins were identified as potential vaccine antigens. In vitro and in vivo experiments now need to be performed to validate the immune and protective power of these newly identified antigens.