In silico identification of novel protective VSG antigens expressed by Trypanosoma brucei and an effort for designing a highly immunogenic DNA vaccine using IL-12 as adjuvant

Advancement in the development of DNA vaccines against Trypanosoma brucei and future perspective

Trypanosomes are the extracellular protozoan parasites that cause human African trypanosomiasis disease in humans and nagana disease in animals. Tsetse flies act as a vector for the transmission of the disease in African countries. Animals infected with these parasites become useless or workless, and if not treated, disease can be fatal. There are many side effects associated with old treatments and some of them result in death in 5% of cases. There is a major surface glycoprotein in the parasite known as variant surface glycoprotein. The immune system of the host develops antibodies against this antigen but due to antigenic variation, parasites evade the immune response. Currently, no vaccine is available that provides complete protection. In murine models, only partial protection was observed using certain antigens. In order to develop vaccines against trypanosomes, molecular biology and immunology tools have been used. Immunization is the sole method for the control of disease because the eradication of the vector from endemic areas is an impossible task. Genetic vaccines can carry multiple genes encoding different antigens of the same parasite or different parasites. DNA immunization induces the activation of both cellular immune response and humoral immune response along with the generation of memory. This review highlights the importance of DNA vaccines and advances in the development of DNA vaccines against T. brucei.

Genome-wide scan for potential CD4+ T-cell vaccine candidates in Candida auris by exploiting reverse vaccinology and evolutionary information

Candida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary information with reverse vaccinology approach to identify novel epitopes for vaccine design that could elicit CD4+ T-cell responses against C. auris. To this end, we extensively scanned the family of proteins encoded by C. auris genome. In addition, a pathogen may acquire substitutions in epitopes over a period of time which could cause its escape from the immune response thus rendering the vaccine ineffective. To lower this possibility in our design, we eliminated all rapidly evolving genes of C. auris with positive selection. We further employed highly conserved regions of multiple C. auris strains and identified two immunogenic and antigenic T-cell epitopes that could generate the most effective immune response against C. auris. The antigenicity scores of our predicted vaccine candidates were calculated as 0.85 and 1.88 where 0.5 is the threshold for prediction of fungal antigenic sequences. Based on our results, we conclude that our vaccine candidates have the potential to be successfully employed for the treatment of C. auris infection. However, in vivo experiments are imperative to further demonstrate the efficacy of our design.

Trypanosoma evansi RoTat 1.2 variant surface antigen mimotopes selected by panning of the random peptide phage-display library against monoclonal antibodies

Mimotope peptides of native antigens are valuable for diverse applications such as diagnostics, therapeutics and modern vaccine design. Here, we report for the first time the selection and identification of peptide mimotopes of Trypanosoma evansi RoTat 1.2 variant surface glycoprotein (VSG) for their potential uses in surra diagnostics and multi-epitope vaccine research. First, we produced the mouse monoclonal antibodies (mAbs), designated as 2E11 (IgG1) and 1C2 (IgG1), against the antigens in T. evansi RoTat 1.2 lysates. We then used 2E11 mAb to immunoprecipitate the target antigen. The immunoprecipitated antigen was then identified to be the VSG by mass spectrometry. Both 2E11 and 1C2 mAbs reacted with the VSG in immunoblots. The surface plasmon resonance immunosensors developed with both the mAbs detected VSG in the parasite lysates as well as in the rodent sera. Further, the mAbs were biotinylated and used in three rounds of panning to select peptide mimotopes from the random peptide phage display library (PhD-12; New England Biolabs, USA). The phage clones selected against each mAb were amplified and tested by phage capture ELISA for specificity. The peptide coding regions of the selected phages were sequenced and the protein blast search of the deduced amino acid sequences was performed by accessing the non-redundant protein database at https://blast.ncbi.nlm.nih.gov/. The conformational B epitope prediction of the selected mimotope sequences was done by using 3D Pepitope algorithms accessed at: http://pepitope.tau.ac.il/. The potential applications of the selected mimotopes in surra diagnostics and research are being explored.

Immuno-Informatics Based Peptides: An Approach for Vaccine Development Against Outer Membrane Proteins of Pseudomonas Genus

Pseudomonas genus is among the top nosocomial pathogens known to date. Being highly opportunistic, members of pseudomonas genus are most commonly connected with nosocomial infections of urinary tract and ventilator-associated pneumonia. Nevertheless, vaccine development for this pathogenic genus is slow because of no information regarding immunity correlated functional mechanism. In this present work, an immunoinformatics pipeline is used for vaccine development based on epitope-based peptide design, which can result in crucial immune response against outer membrane proteins of pseudomonas genus. A total of 127 outer membrane proteins were analysed, studied and out of them three sequences were obtained to be the producer of non-allergic, highly antigenic T-cell and B-cell epitopes which show good binding affinity towards class II HLA molecules. After performing rigorous screening utilizing docking, simulation, modelling techniques, we had one nonameric peptide (WLLATGIFL)as a good vaccine candidate. The predicted epitopes needs to be further validated for its apt use as vaccine. This work paves a new way with extensive therapeutic application against Pseudomonas genus and their associated diseases.

Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

A common conserved peptide harboring predicted T and B cell epitopes in domain III of envelope protein of Japanese Encephalitis Virus and West Nile Virus for potential use in epitope based vaccines

Japanese encephalitis virus (JEV) and West Nile virus (WNV) are two major mosquito borne flaviviruses belonging to same serocomplex. JEV is transmitted by Culex mosquitoes and the reservoir host for the virus is pigs and/or water birds. WNV is also transmitted by Culex mosquitoes and reservoir host in this case is birds. It can also be transmitted through contact with other infected animals, their blood, or other tissues. The envelope protein of these viruses is the major source of epitopes and provides protective immunity. Bioinformatics tools were used to identify conserved epitopes in the envelope protein of these viruses. A conserved peptide "TPVGRLVTVNPFV" present in both the viruses containing predicted T and B cell epitopes was found. The model of one of the predicted epitope was generated and upon docking it bound in the groove of HLA-A0201 Class I MHC molecule. Further, it was amenable to proteasomal cleavage enhancing its chances of processing by cytosolic pathway. The peptide was found to be non toxic, non allergenic and stable in mammalian cells based on database search. The population coverage was pan world and nearly 70% identity of the peptide was found in the Zika virus envelope protein. The peptide was located in the domain III of envelope protein which is the exposed domain therefore B cell receptors may recognize this peptide easily. The conserved peptide containing T and B cell epitopes can have future application for designing epitope based vaccines for both JEV and WNV.

Designing of an epitope-based peptide vaccine against walking pneumonia: an immunoinformatics approach

Mycoplasma pneumoniae is a substantial respiratory pathogen that develops not only pneumonia but also other respiratory diseases, which mimic viral respiratory syndromes. Nevertheless, vaccine development for this pathogen delays behind as immunity correlated with protection is now predominantly unknown. In the present study, an immunoinformatics pipeline is utilized for epitope-based peptide vaccine design, which can trigger a critical immune response against M. pneumoniae. A total of 105 T-cell epitopes from 12 membrane associated proteins and 7 T-cell epitopes from 5 cytadherence proteins of M. pneumoniae were obtained and validated. Thus, 18 peptides with 9-mer core sequence were identified as best T-cell epitopes by considering the number of residues with > 75% in favored region. Further, the crucial screening studies predicted three peptides with good binding affinity towards HLA molecules as best T-cell and B-cell epitopes. Based on this result, visualization, and dynamic simulation for the three epitopes (WIHGLILLF, VILLFLLLF, and LLAWMLVLF) were assessed. The predicted epitopes needs to be further validated for their adept use as vaccine. Collectively, the study opens up a new horizon with extensive therapeutic application against M. pneumoniae and its associated diseases.

In silico prediction of cancer immunogens: current state of the art

Cancer kills 8 million annually worldwide. Although survival rates in prevalent cancers continue to increase, many cancers have no effective treatment, prompting the search for new and improved protocols. Immunotherapy is a new and exciting addition to the anti-cancer arsenal. The successful and accurate identification of aberrant host proteins acting as antigens for vaccination and immunotherapy is a key aspiration for both experimental and computational research. Here we describe key elements of in silico prediction, including databases of cancer antigens and bleeding-edge methodology for their prediction. We also highlight the role dendritic cell vaccines can play and how they can act as delivery mechanisms for epitope ensemble vaccines. Immunoinformatics can help streamline the discovery and utility of Cancer Immunogens.

A Poly(Lactic-co-Glycolic) Acid Nanovaccine Based on Chimeric Peptides from Different Leishmania infantum Proteins Induces Dendritic Cells Maturation and Promotes Peptide-Specific IFNγ-Producing CD8+ T Cells Essential for the Protection against Experimental Visceral Leishmaniasis

Visceral leishmaniasis, caused by Leishmania (L.) donovani and L. infantum protozoan parasites, can provoke overwhelming and protracted epidemics, with high case-fatality rates. An effective vaccine against the disease must rely on the generation of a strong and long-lasting T cell immunity, mediated by CD4⁺ T_H1 and CD8⁺ T cells. Multi-epitope peptide-based vaccine development is manifesting as the new era of vaccination strategies against Leishmania infection. In this study, we designed chimeric peptides containing HLA-restricted epitopes from three immunogenic L. infantum proteins (cysteine peptidase A, histone H1, and kinetoplastid membrane protein 11), in order to be encapsulated in poly(lactic-co-glycolic) acid nanoparticles with or without the adjuvant monophosphoryl lipid A (MPLA) or surface modification with an octapeptide targeting the tumor necrosis factor receptor II. We aimed to construct differentially functionalized peptide-based nanovaccine candidates and investigate their capacity to stimulate the immunomodulatory properties of dendritic cells (DCs), which are critical regulators of adaptive immunity generated upon vaccination. According to our results, DCs stimulation with the peptide-based nanovaccine candidates with MPLA incorporation or surface modification induced an enhanced maturation profile with prominent IL-12 production, promoting allogeneic T cell proliferation and intracellular production of IFNγ by CD4⁺ and CD8⁺ T cell subsets. In addition, DCs stimulated with the peptide-based nanovaccine candidate with MPLA incorporation exhibited a robust transcriptional activation, characterized by upregulated genes indicative of vaccine-driven DCs differentiation toward type 1 phenotype. Immunization of HLA A2.1 transgenic mice with this peptide-based nanovaccine candidate induced peptide-specific IFNγ-producing CD8⁺ T cells and conferred significant protection against L. infantum infection. Concluding, our findings supported that encapsulation of more than one chimeric multi-epitope peptides from different immunogenic L. infantum proteins in a proper biocompatible delivery system with the right adjuvant is considered as an improved promising approach for the development of a vaccine against VL.

Sequence-based approach for rapid identification of cross-clade CD8+ T-cell vaccine candidates from all high-risk HPV strains

Human papilloma virus (HPV) is the primary etiological agent responsible for cervical cancer in women. Although in total 16 high-risk HPV strains have been identified so far. Currently available commercial vaccines are designed by targeting mainly HPV16 and HPV18 viral strains as these are the most common strains associated with cervical cancer. Because of the high level of antigenic specificity of HPV capsid antigens, the currently available vaccines are not suitable to provide cross-protection from all other high-risk HPV strains. Due to increasing reports of cervical cancer cases from other HPV high-risk strains other than HPV16 and 18, it is crucial to design vaccine that generate reasonable CD8+ T-cell responses for possibly all the high-risk strains. With this aim, we have developed a computational workflow to identify conserved cross-clade CD8+ T-cell HPV vaccine candidates by considering E1, E2, E6 and E7 proteins from all the high-risk HPV strains. We have identified a set of 14 immunogenic conserved peptide fragments that are supposed to provide protection against infection from any of the high-risk HPV strains across globe.

Loss in CD4 T-cell responses to multiple epitopes in influenza due to expression of one additional MHC class II molecule in the host

An understanding of factors controlling CD4 T-cell immunodominance is needed to pursue CD4 T-cell epitope-driven vaccine design, yet our understanding of this in humans is limited by the complexity of potential MHC class II molecule expression. In the studies described here, we took advantage of genetically restricted, well-defined mouse strains to better understand the effect of increasing MHC class II molecule diversity on the CD4 T-cell repertoire and the resulting anti-influenza immunodominance hierarchy. Interferon-γ ELISPOT assays were implemented to directly quantify CD4 T-cell responses to I-A(b) and I-A(s) restricted peptide epitopes following primary influenza virus infection in parental and F(1) hybrid strains. We found striking and asymmetric declines in the magnitude of many peptide-specific responses in F(1) animals. These declines could not be accounted for by the lower surface density of MHC class II on the cell or by antigen-presenting cells failing to stimulate T cells with lower avidity T-cell receptors. Given the large diversity of MHC class II expressed in humans, these findings have important implications for the rational design of peptide-based vaccines that are based on the premise that CD4 T-cell epitope specificity can be predicted by a simple cataloguing of an individual's MHC class II genotype.

Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 < 50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection

The ability to track CD4 T cells elicited in response to pathogen infection or vaccination is critical because of the role these cells play in protective immunity. Coupled with advances in genome sequencing of pathogenic organisms, there is considerable appeal for implementation of computer-based algorithms to predict peptides that bind to the class II molecules, forming the complex recognized by CD4 T cells. Despite recent progress in this area, there is a paucity of data regarding the success of these algorithms in identifying actual pathogen-derived epitopes. In this study, we sought to rigorously evaluate the performance of multiple Web-available algorithms by comparing their predictions with our results--obtained by purely empirical methods for epitope discovery in influenza that used overlapping peptides and cytokine ELISPOTs--for three independent class II molecules. We analyzed the data in different ways, trying to anticipate how an investigator might use these computational tools for epitope discovery. We come to the conclusion that currently available algorithms can indeed facilitate epitope discovery, but all shared a high degree of false-positive and false-negative predictions. Therefore, efficiencies were low. We also found dramatic disparities among algorithms and between predicted IC(50) values and true dissociation rates of peptide-MHC class II complexes. We suggest that improved success of predictive algorithms will depend less on changes in computational methods or increased data sets and more on changes in parameters used to "train" the algorithms that factor in elements of T cell repertoire and peptide acquisition by class II molecules.