Immunoinformatics comes of age

Two MP2CL5 Antigen Vaccines from Naegleria fowleri Stimulate the Immune Response against Meningitis in the BALB/c Model

Naegleria fowleri is an etiological agent that generates primary amoebic meningoencephalitis; unfortunately, no effective treatment or vaccine is available. The objective of this work was to determine the immunoprotective response of two vaccine antigens, as follows: (i) the polypeptide band of 19 kDa or (ii) a predicted immunogenic peptide from the membrane protein MP2CL5 (Smp145). Both antigens were administered intranasally in mice using cholera toxin (CT) as an adjuvant. The survival rate and immune response of immunized mice with both antigens and challenged with N. fowleri trophozoites were measured in the nose-associated lymphoid tissue (NALT) and nasal passages (NPs) by flow cytometry and enzyme-linked immunosorbent assay (ELISA). We also determined the immunolocalization of both antigens in N. fowleri trophozoites by confocal microscopy. Immunization with the polypeptide band of 19 kDa alone or coadministered with CT was able to confer 80% and 100% of protection, respectively. The immunization with both antigens (alone or coadministered with CT) showed an increase in T and B lymphocytes. In addition, there was an increase in the expression of integrin α4β1 and IgA in the nasal cavity of protected mice, and the IgA, IgG, and IgM levels were increased in serum and nasal washes. The immunolocalization of both antigens in N. fowleri trophozoites was observed in the plasma membrane, specifically in pseudopod-like structures. The MP2CL5 antigens evaluated in this work were capable of conferring protection which would lead us to consider them as potential candidates for vaccines against meningitis caused by N. fowleri.

Research progress on the allergic mechanism, molecular properties, and immune cross-reactivity of the egg allergen Gal d 5

Eggs and their products are commonly consumed in food products worldwide, and in addition to dietary consumption, egg components are widely used in the food industry for their antimicrobial, cooking, and other functional properties. Globally, eggs are the second most common allergenic food after milk. However, current research on egg allergy primarily focuses on egg white allergens, while research on egg yolk allergens is not comprehensive enough. Therefore, summarizing and analyzing the important allergen α-livetin in egg yolk is significant in elucidating the mechanism of egg allergy and exploring effective desensitization methods. This paper discusses the incidence, underlying mechanism, and clinical symptoms of egg allergy. This article provides a comprehensive summary and analysis of the current research status concerning the molecular structural properties, epitopes, and immune cross-reactivity of the egg yolk allergen, Gal d 5. Additionally, it examines the effects of various processing methods on egg allergens. The article also offers suggestions and outlines potential future research directions and ideas in this field.

Diversity and evolution of computationally predicted T cell epitopes against human respiratory syncytial virus

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory infection. Despite more than 60 years of research, there is no licensed vaccine. While B cell response is a major focus for vaccine design, the T cell epitope profile of RSV is also important for vaccine development. Here, we computationally predicted putative T cell epitopes in the Fusion protein (F) and Glycoprotein (G) of RSV wild circulating strains by predicting Major Histocompatibility Complex (MHC) class I and class II binding affinity. We limited our inferences to conserved epitopes in both F and G proteins that have been experimentally validated. We applied multidimensional scaling (MDS) to construct T cell epitope landscapes to investigate the diversity and evolution of T cell profiles across different RSV strains. We find the RSV strains are clustered into three RSV-A groups and two RSV-B groups on this T epitope landscape. These clusters represent divergent RSV strains with potentially different immunogenic profiles. In addition, our results show a greater proportion of F protein T cell epitope content conservation among recent epidemic strains, whereas the G protein T cell epitope content was decreased. Importantly, our results suggest that RSV-A and RSV-B have different patterns of epitope drift and replacement and that RSV-B vaccines may need more frequent updates. Our study provides a novel framework to study RSV T cell epitope evolution. Understanding the patterns of T cell epitope conservation and change may be valuable for vaccine design and assessment.

Molecular Mimicry Analyses Unveiled the Human Herpes Simplex and Poxvirus Epitopes as Possible Candidates to Incite Autoimmunity

Clinical epidemiological studies have reported that viral infections cause autoimmune pathology in humans. Host-pathogen protein sequences and structure-based molecular mimicry cause autoreactive T cells to cross-activate. The aim of the current study was to implement immunoinformatics approaches to infer sequence- and structure-based molecular mimicry between viral and human proteomic datasets. The protein sequences of all the so far known human-infecting viruses were obtained from the VIPR database, and complete human proteome data were retrieved from the NCBI repository. Based on a predefined, stringent threshold of comparative sequence analyses, 24 viral proteins were identified with significant sequence similarity to human proteins. PathDIP identified the enrichment of these homologous proteins in nine metabolic pathways with a p-value < 0.0001. Several viral and human mimic epitopes from these homologous proteins were predicted as strong binders of human HLA alleles, with IC50 < 50 nM. Downstream molecular docking analyses identified that lead virus-human homologous epitopes feasibly interact with HLA and TLR4 types of immune receptors. The vast majority of these top-hit homolog epitopic peptides belong to the herpes simplex and poxvirus families. These lead epitope biological sequences and 3D structural-based molecular mimicry may be promising for interpreting herpes simplex virus and poxvirus infection-mediated autoimmune disorders in humans.

Identification and Characterization of Antigenic Properties of Schistosoma japonicum Heat Shock Protein 90α Derived Peptides

It is known that schistosome-derived antigens induce innate and adaptive immune responses that are essential for the formation of hepatic immunopathology. Here, we screened and synthesized four peptides derived from Schistosoma japonicum (S. japonicum) heat shock protein 90α (Sjp90α-1, -2, -3, and -4), which is widely expressed in adults and eggs of the genus S. japonicum and induces remarkable immune reactions. To define the antigenicity of these peptides, we stimulated splenocytes with peptides, and the results showed that only the Sjp90α-1 peptide could predominately induce the activation of dendritic cells (DCs) and macrophages as well as alter the proportion of follicular helper T (Tfh) cells. Next, CD4⁺ T cells were purified and cocultured with mouse bone-marrow-derived DCs (BMDCs) with or without Sjp90α-1 peptide stimulation in vitro, and the results showed that Sjp90α-1-stimulated BMDCs can significantly induce CD4⁺ T-cell differentiation into Tfh cells, while the direct stimulation of CD4⁺ T cells with Sjp90α-1 did not induce Tfh cells, indicating that the Sjp90α-1 peptide promotes Tfh cell differentiation depending on the presence of DCs. Furthermore, we selected and prepared an Sjp90α-1-peptide-based antibody and illustrated that it has excellent reactivity with the immunizing peptide and detects a single band of 29 kDa corresponding to the Sjp90α protein. The immunolocalization results showed that the protein recognized by this Sjp90α-1-peptide-based antibody is present in the mature eggs and the tegument of adults, implying that the parasite-derived peptide has a potential interaction with the host immune system. Finally, we evaluated antipeptide IgG antibodies and revealed a significantly higher level of anti-Sjp90α-1 peptide IgG antibodies in mice 3 weeks after S. japonicum infection. In conclusion, we illustrate that these synthetic peptides warrant further investigation by evaluating their antigen-specific immune response and their ability to efficiently induce Tfh cells. Moreover, they may constitute a potentially helpful method for the laboratory diagnosis of schistosomiasis japonica.

Design of a Chimeric Multi-Epitope Vaccine (CMEV) against Both Leishmania martiniquensis and Leishmania orientalis Parasites Using Immunoinformatic Approaches

Leishmaniasis is a parasitic disease caused by protozoan flagellates of the genus Leishmania. Recently, Leishmania martiniquensis and Leishmania orientalis, emerging species of Leishmania, were isolated from patients in Thailand. Development of the vaccine is demanded; however, genetic differences between the two species make it difficult to design a vaccine that is effective for both species. In this study, we applied immuno-informatic approaches to design a chimeric multi-epitope vaccine (CMEV) against both L. martiniquensis and L. orientalis. We identified seven helper T lymphocyte (HTL) epitopes, sixteen cytotoxic T lymphocyte (CTL) epitopes, and eleven B-cell epitopes from sixteen conserved antigenic proteins found in both species. All these epitopes were joined together, and to further enhance immunogenicity, protein and peptides adjuvant were also added at the N-terminal of the molecule by using specific linkers. The candidate CMEV was subsequently analyzed from the perspectives of the antigenicity, allergenicity, and physiochemical properties. The interaction of the designed multi-epitope vaccine and immune receptor (TLR4) of the host were evaluated based on molecular dockings of the predicted 3D structures. Finally, in silico cloning was performed to construct the expression vaccine vector. Docking analysis showed that the vaccine/TLR4 complex took a stable form. Based on the predicted immunogenicity, physicochemical, and structural properties in silico, the vaccine candidate was expected to be appropriately expressed in bacterial expression systems and show the potential to induce a host immune response. This study proposes the experimental validation of the efficacy of the candidate vaccine construct against the two Leishmania.

Vaccinomics to Design a Multiepitope Vaccine against Legionella pneumophila

Legionella pneumophila is found in the natural aquatic environment and can resist a wide range of environmental conditions. There are around fifty species of Legionella, at least twenty-four of which are directly linked to infections in humans. L. pneumophila is the cause of Legionnaires' disease, a potentially lethal form of pneumonia. By blocking phagosome-lysosome fusion, L. pneumophila lives and proliferates inside macrophages. For this disease, there is presently no authorized multiepitope vaccine available. For the multi-epitope-based vaccine (MEBV), the best antigenic candidates were identified using immunoinformatics and subtractive proteomic techniques. Several immunoinformatics methods were utilized to predict B and T cell epitopes from vaccine candidate proteins. To construct an in silico vaccine, epitopes (07 CTL, 03 HTL, and 07 LBL) were carefully selected and docked with MHC molecules (MHC-I and MHC-II) and human TLR4 molecules. To increase the immunological response, the vaccine was combined with a 50S ribosomal adjuvant. To maximize vaccine protein expression, MEBV was cloned and reverse-translated in Escherichia coli. To prove the MEBV's efficacy, more experimental validation is required. After its development, the resulting vaccine is greatly hoped to aid in the prevention of L. pneumophila infections.

An overview of progress from empirical to rational design in modern vaccine development, with an emphasis on computational tools and immunoinformatics approaches

Vaccination remains the most effective strategy for preventing and controlling infectious diseases. Numerous conventional vaccines, especially live attenuated, inactivated (killed) microorganisms and subunit vaccines, lead to an effective induction of protective immune responses, mainly antibody-mediated responses against pathogens. However, it has become known that a wide range of highly dangerous pathogens are uncontrollable via conventional vaccination strategies. Recent advances in molecular biology, immunology, genetics, biochemistry, and bioinformatics have provided new prospects for vaccine development. As a result of these advances, several new strategies for vaccine design, development, and production have appeared. These strategies show advantages over conventional vaccines. In this review, we discuss some of the major novel approaches, including recombinant protein vaccines, live recombinant viral and bacterial vectors, DNA and RNA vaccines, reverse vaccinology and reverse genetics approaches. Moreover, we have described the recent progresses on computational tools and immunoinformatics approaches for identifying, designing, and developing new candidate vaccines.

Combinatorial in silico and in vivo evaluation of immune response elicitation by the affibody ZHER2

Due to the high affinity for binding to target molecules and also other unique attributes, affibodies have a great potential to be used in immunotherapeutic and diagnostic approaches. However, the possibility of undesirable immune response is still a great concern. In the current study, we investigated the possible antigenicity, allergenicity and cytotoxicity of the HER2-targeting affibody Z_HER2. The binding affinity of potential epitopes of the affibody to murine major histocompatibility complex (MHC) molecules was investigated by immunoinformatics tools and docking approaches. The possible interaction of Z_HER2 with human leukocyte antigens HLA-DP, HLA-DM, HLA-DQ and HLA-DR was also studied by protein-protein docking. Additionally, the synthesized affibody gene was expressed and the protein was purified for boosted immunization of Balb/c mice. Induced secretion of IFN-γ, IL-2, IL-4 and IL-10, and total serum IgG were assessed in the immunized mice. Furthermore, MTT cell viability test was performed to evaluate the cytotoxicity of Z_HER2 in splenocytes of the treated mice. In silico analyses showed the possible induction of the immune response by Z_HER2. While the affibody could elicit the secretion of cellular immune cytokines, it could not induce a significant humoral response in the treated mice and did not show any cytotoxic effects on the exposed splenocytes. These findings explain the practicability of Z_HER2 for therapeutic and in vivo diagnostic usages, though its ubiquitous application may need more studies.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Immunoinformatics aided design of peptide-based vaccines against ebolaviruses

Ebolaviruses are at the forefront of emerging viruses and present a very perceptible threat to global peace and harmony. In the last decade, Ebola virus disease has claimed more than 90% of total lives since its inception in 1976. Owing to multiple host immune evasion methods employed by the virus and the limitations of traditional vaccine development approaches, finding a globally effective and reliable counter measure against Ebola virus remains a challenge. Highly conserved peptide fragments belonging to critical viral proteins and containing multiple epitopes which have the capacity to interact with a wide array of HLA molecules present a viable solution. Immunoinformatics or computational immunology enables rapid screening and shortlisting of plausible epitopes with a high immunogenic potential, thus, supporting expeditious elucidation of efficacious vaccine candidates. In light of above facts, we describe a computational methodology in this chapter for identification of potent peptide vaccine candidates against human infecting viruses. By applying this stringent methodology, we were able to identify multiple, immunogenic ebolavirus peptide fragments which, after verification in animal models, might be considered as part of future synthetic Ebola vaccine.

Structural and molecular analyses of functional epitopes and escape mutants in Japanese encephalitis virus envelope protein domain III

The Japanese encephalitis virus (JEV) is one of the vector borne causes of encephalitis found in southeastern Asia. This positive single-stranded RNA virus is a member of the Flaviviridae family, which notably includes dengue, tick-borne, West Nile, Zika as well as yellow fever, and transmits to humans by infected mosquitos. The main site of interactions for antibodies against this virus is the envelope protein domain III (ED3). The present report investigates the time-dependent structural and conformational changes of JEV ED3 functional epitopes and escape mutants by computer simulations. The results indicate the presence of significant structural differences between the functional epitopes and the escape mutants. Mutation-induced structural/conformational instabilities of this type can decrease the antibody neutralization activity. Among the different escape mutants studied here, Ser40Lys/Asp41Arg appear to be most unstable, while Ser40Glu/Asp41Leu exhibit the lowest structural variations. The highest level of escape mutation observed in Ser40Lys is linked to the relatively higher values of root mean square deviation/fluctuation found in the molecular dynamics simulation of this protein. Secondary-structure deviations and depletion of H bonding are other contributing factors to the protein’s increased instability. Overall, the proteins with residue 41 mutations are found to be structurally more ordered than those with residue 40 mutations. The detailed time-based structural assessment of the mutant epitopes described here may contribute to the development of novel vaccines and antiviral drugs necessary to defend against future outbreaks of JEV escape mutants.

Predicting Immunogenicity Risk in Biopharmaceuticals

The assessment of immunogenicity of biopharmaceuticals is a crucial step in the process of their development. Immunogenicity is related to the activation of adaptive immunity. The complexity of the immune system manifests through numerous different mechanisms, which allows the use of different approaches for predicting the immunogenicity of biopharmaceuticals. The direct experimental approaches are sometimes expensive and time consuming, or their results need to be confirmed. In this case, computational methods for immunogenicity prediction appear as an appropriate complement in the process of drug design. In this review, we analyze the use of various In silico methods and approaches for immunogenicity prediction of biomolecules: sequence alignment algorithms, predicting subcellular localization, searching for major histocompatibility complex (MHC) binding motifs, predicting T and B cell epitopes based on machine learning algorithms, molecular docking, and molecular dynamics simulations. Computational tools for antigenicity and allergenicity prediction also are considered.

Immunoinformatics Approach for the Identification and Characterization of T Cell and B Cell Epitopes towards the Peptide-Based Vaccine against SARS-CoV-2

Presently, immunoinformatics is playing a significant role in epitope identification and vaccine designing for various critical diseases. Using immunoinformatics, several scientists are trying to identify and characterize T cell and B cell epitopes as well as design peptide-based vaccine against SARS-CoV-2. In this review article, we have tried to discuss the importance in adaptive immunity and its significance for designing the SARS-CoV-2 vaccine. Moreover, we have attempted to illustrate several significant key points for utilizing immunoinformatics for vaccine designing, such as the criteria for selection and identification of epitopes, T cell epitope, and B cell epitope prediction and different emerging tools/databases for immunoinformatics. In the current scenario, a few immunoinformatics studies have been performed for various infectious pathogens and related diseases. Thus, we have also summarized and included these current immunoinformatics studies in this review article. Finally, we have discussed about the probable T cell and B cell epitopes and their identification and characterization for vaccine designing against SARS-CoV-2.

Yersinia pestis Antigen F1 but Not LcrV Induced Humoral and Cellular Immune Responses in Humans Immunized with Live Plague Vaccine-Comparison of Immunoinformatic and Immunological Approaches

The recent progress in immunoinformatics provided the basis for an accelerated development of target-specific peptide vaccines as an alternative to the traditional vaccine concept. However, there is still limited information on whether the in silico predicted immunoreactive epitopes correspond to those obtained from the actual experiments. Here, humoral and cellular immune responses to two major Yersinia pestis protective antigens, F1 and LcrV, were studied in human donors immunized with the live plague vaccine (LPV) based on the attenuated Y. pestis strain EV line NIIEG. The F1 antigen provided modest specific cellular (mixed T helper 1 (Th1)/Th2 type) and humoral immune responses in vaccinees irrespective of the amount of annual vaccinations and duration of the post-vaccination period. The probing of the F1 overlapping peptide library with the F1-positive sera revealed the presence of seven linear B cell epitopes, which were all also predicted by in silico assay. The immunoinformatics study evaluated their antigenicity, toxicity, and allergenic properties. The epitope TSQDGNNH was mostly recognized by the sera from recently vaccinated donors rather than antibodies from those immunized decades ago, suggesting the usefulness of this peptide for differentiation between recent and long-term vaccinations. The in silico analysis predicted nine linear LcrV-specific B-cell epitopes; however, weak antibody and cellular immune responses prevented their experimental evaluation, indicating that LcrV is a poor marker of successful vaccination. No specific Th17 immune response to either F1 or LcrV was detected, and there were no detectable serum levels of F1-specific immunoglobulin A (IgA) in vaccinees. Overall, the general approach validated in the LPV model could be valuable for the rational design of vaccines against other neglected and novel emerging infections with high pandemic potency.

Computational Immune Proteomics Approach to Target COVID-19

Progress of the omics platforms widens their application to diverse fields, including immunology. This enables a deeper level of knowledge and the provision of a huge amount of data for which management and fruitful integration with the past evidence requires a steadily growing computational effort. In light of this, immunoinformatics emerges as a new discipline placed in between the traditional lab-based investigations and the computational analysis of the biological data. Immunoinformatics make use of tailored bioinformatics tools and data repositories to facilitate the analysis of data from a plurality of disciplines and help drive novel research hypotheses and in silico screening investigations in a fast, reliable, and cost-effective manner. Such computational immunoproteomics studies may as well prepare and guide lab-based investigations, representing valuable technology for the investigation of novel pathogens, to tentatively evaluate specificity of diagnostic products, to forecast on potential adverse effects of vaccines and to reduce the use of animal models. The present manuscript provides an overview of the COVID-19 pandemic and reviews the state of the art of the omics technologies employed in fighting SARS-CoV-2 infections. A comprehensive description of the immunoinformatics approaches and its potential role in contrasting COVID-19 pandemics is provided.

Computational perspectives revealed prospective vaccine candidates from five structural proteins of novel SARS corona virus 2019 (SARS-CoV-2)

Background

The present pandemic COVID-19 is caused by SARS-CoV-2, a single-stranded positive-sense RNA virus from the Coronaviridae family. Due to a lack of antiviral drugs, vaccines against the virus are urgently required.

Methods

In this study, validated computational approaches were used to identify peptide-based epitopes from six structural proteins having antigenic properties. The Net-CTL 1.2 tool was used for the prediction of CD8⁺ T-cell epitopes, while the robust tools Bepi-Pred 2 and LBtope was employed for the identification of linear B-cell epitopes. Docking studies of the identified epitopes were performed using HADDOCK 2.4 and the structures were visualized by Discovery Studio and LigPlot⁺. Antigenicity, immunogenicity, conservancy, population coverage and allergenicity of the predicted epitopes were determined by the bioinformatics tools like VaxiJen v2.0 server, the Immune Epitope Database tools and AllerTOP v.2.0, AllergenFP 1.0 and ElliPro.

Results

The predicted T cell and linear B-cell epitopes were considered as prime vaccine targets in case they passed the requisite parameters like antigenicity, immunogenicity, conservancy, non-allergenicity and broad range of population coverage. Among the predicted CD8+ T cell epitopes, potential vaccine targets from surface glycoprotein were; YQPYRVVVL, PYRVVVLSF, GVYFASTEK, QLTPTWRVY, and those from ORF3a protein were LKKRWQLAL, HVTFFIYNK. Similarly, RFLYIIKLI, LTWICLLQF from membrane protein and three epitopes viz; SPRWYFYYL, TWLTYTGAI, KTFPPTEPK from nucleocapsid phosphoprotein were the superior vaccine targets observed in our study. The negative values of HADDOCK and Z scores obtained for the best cluster indicated the potential of the epitopes as suitable vaccine candidates. Analysis of the 3D and 2D interaction diagrams of best cluster produced by HADDOCK 2.4 displayed the binding interaction of leading T cell epitopes within the MHC-1 peptide binding clefts. On the other hand, among linear B cell epitopes the majority of potential vaccine targets were from nucleocapsid protein, viz; ⁵⁹⁻HGKEDLKFPRGQGVPINTNSSPDDQIGYYRRATRRIRGGDGKMKDLS⁻¹⁰⁵, ²²⁷⁻LNQLE SKMSGKGQQQQGQTVTKKSAAEASKKPRQKRTATK⁻²⁶⁶, ³⁻DNGPQNQRNAPRITFGGP⁻²⁰, ²⁹⁻GERSGARSKQRRPQGL⁻⁴⁵. Two other prime vaccine targets, ³⁷⁰⁻NSASFSTFKCYGVSPTKLNDLCFTNV⁻³⁹⁵ and ²⁶⁰⁻AGAAAYYVGYLQPRT⁻²⁷⁴ were identified in the spike protein. The potential B-cell conformational epitopes were predicted on the basis of a higher protrusion index indicating greater solvent accessibility. These conformational epitopes were of various lengths and belonged to spike, ORF3a, membrane and nucleocapsid proteins.

Conclusions

Taken together, eleven T cell epitopes, seven B cell linear epitopes and ten B cell conformational epitopes were identified from five structural proteins of SARS-CoV-2 using advanced computational tools. These potential vaccine candidates may provide important timely directives for an effective vaccine against SARS-CoV-2.

Vaccine candidate designed against carcinoembryonic antigen-related cell adhesion molecules using immunoinformatics tools

Carcinoembryonic antigen-related cell adhesion (CEACAM) molecules belong to a family of membrane glycoproteins that mediate intercellular interactions influencing cellular growth, immune cell activation, apoptosis, and tumor suppression. Several family members (CEACAM1, CEACAM5, and CEACAM6) are highly expressed in cancers, and they share a conserved N-terminal domain that serves as an attractive target for cancer immunotherapy. A multi-epitope vaccine candidate against this conserved domain has been developed using immunoinformatics tools. Specifically, several epitopes predicted to interact with MHC class I and II molecules were linked together with appropriate linkers. The tertiary structure of the vaccine is generated by homology and ab initio modeling. Molecular docking of epitopes to MHC structures have revealed that the lowest energy conformations are the epitopes bound to the antigen-binding groove of the MHC molecules. Subsequent molecular dynamics simulation has confirmed the stability of the binding conformations in solution. The predicted vaccine has relatively high antigenicity and low allergenicity, suggesting that it is an ideal candidate for further refinement and development.Communicated by Ramaswamy H. Sarma.

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach

Background

A new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a “public-health emergency of international concern” due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus, the objective of this study is to design a multiepitope peptide vaccine against COVID-19 using an immunoinformatics approach.

Method

Several techniques facilitating the combination of the immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the envelope protein of 2019-nCoV as a target.

Results

Extensive mutations, insertion, and deletion were discovered with comparative sequencing in the COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively.

Conclusion

The T-cell epitope-based peptide vaccine was designed for COVID-19 using the envelope protein as an immunogenic target. Nevertheless, the proposed vaccine rapidly needs to be validated clinically in order to ensure its safety and immunogenic profile to help stop this epidemic before it leads to devastating global outbreaks.

Preliminary investigation demonstrating the GHITM gene probably involved in apoptosis and growth of the golden apple snail (Pomacea canaliculata)

Background

Growth hormone inducible transmembrane protein (GHITM) is a highly conserved transmembrane protein. This study was conducted to investigate the role of GHITM gene in the apoptosis and growth of the golden apple snail Pomacea canaliculate.

Results

The complete cDNA of this gene was cloned using the rapid amplification of cDNA ends (RACE) method and subjected to bioinformatics analysis. The full-length cDNA was 2242 bp, including an open reading frame of 1021 bp that encoded a protein of 342 amino acid residues. The mRNA expression profiles of GHITM gene in different tissues (liver, kidney, gonad and foot) and different growth phases (6-months old and 2-years old) showed that it was expressed in various tissues and different growth phases. Silencing of the GHITM gene by RNAi (RNA interference) experiments revealed that the GHITM gene possibly plays a role in inhibiting apoptosis through detecting the Caspase (Cysteine-requiring Aspartate Protease)-3 activity. In addition, the aperture width and body whorl length of the snail was significantly affected by RNAi, suggesting that this gene plays a significant role in promoting the growth of the organism.

Conclusions

These results demonstrated that the GHITM gene was involved in apoptosis and growth in golden apple snail.

Pan-Cancer Analysis and Drug Formulation for GPR139 and GPR142

GPR (G protein receptor) 139 and 142 are novel foundling GPCRs (G protein-coupled receptors) in the class "A" of the GPCRs family and are suitable targets for various biological conditions. To engage these targets, validated pharmacophores and 3D QSAR (Quantitative structure-activity relationship) models are widely used because of their direct fingerprinting capability of the target and an overall accuracy. The current work initially analyzes GPR139 and GPR142 for its genomic alteration via tumor samples. Next to that, the pharmacophore is developed to scan the 3D database for such compounds that can lead to potential agonists. As a result, several compounds have been considered, showing satisfactory performance and a strong association with the target. Additionally, it is gripping to know that the obtained compounds were observed to be responsible for triggering pan-cancer. This suggests the possible role of novel GPR139 and GPR142 as the substances for initiating a physiological response to handle the condition incurred as a result of cancer.

Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein

Immunoinformatics is a new critical field with several tools and databases that conduct the eyesight of experimental selection and facilitate analysis of the great amount of immunologic data obtained from experimental researches and helps to design and introducing new hypothesis. Given these visages, immunoinformatics seems to be the way that develop and progress the immunological research. Bioinformatics methods and applications are successfully employed in vaccine informatics to assist different sites of the preclinical, clinical, and post-licensure vaccine enterprises. On the other hand, the progression of molecular biology and immunology caused epitope vaccines have become the focus of research on molecular vaccines. Moreover, reverse vaccinology could improve vaccine production and vaccination protocols by in silico prediction of protein-vaccine candidates from genome sequences. B- and T-cell immune epitopes could be predicted by immunoinformatics algorithms and computational methods to improve the vaccine design, protective immunity analysis, assessment of vaccine safety and efficacy, and immunization modeling. This review aims to discuss the power of computational approaches in vaccine design and their relevance to the development of effective vaccines. Furthermore, the various divisions of this field and available tools in each item are introduced and reviewed.

Contriving a chimeric polyvalent vaccine to prevent infections caused by herpes simplex virus (type-1 and type-2): an exploratory immunoinformatic approach

Herpes simplex virus type 1 (HSV-1) and 2 (HSV-2) cause a variety of infections including oral-facial infections, genital herpes, herpes keratitis, cutaneous infection and so on. To date, FDA-approved licensed HSV vaccine is not available yet. Hence, the study was conducted to identify and characterize an effective epitope based polyvalent vaccine against both types of Herpes Simplex Virus. The selected proteins were retrieved from ViralZone and assessed to design highly antigenic epitopes by binding analyses of the peptides with MHC class-I and class-II molecules, antigenicity screening, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach. The final vaccine was constructed by the combination of top CTL, HTL and BCL epitopes from each protein along with suitable adjuvant and linkers. Physicochemical and secondary structure analysis, disulfide engineering, molecular dynamic simulation and codon adaptation were further employed to develop a unique multi-epitope peptide vaccine. Docking analysis of the refined vaccine structure with different MHC molecules and human immune TLR-2 receptor demonstrated higher interaction. Complexed structure of the modeled vaccine and TLR-2 showed minimal deformability at molecular level. Moreover, translational potency and microbial expression of the modeled vaccine was analyzed with pET28a(+) vector for E. coli strain K12 and the vaccine constructs had no similarity with entire human proteome. The study enabled design of a novel chimeric polyvalent vaccine to confer broad range immunity against both HSV serotypes. However, further wet lab based research using model animals are highly recommended to experimentally validate our findings.Communicated by Ramaswamy H. Sarma.

Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus

Oropouche virus (OROV) is an emerging pathogen which causes Oropouche fever and meningitis in humans. Several outbreaks of OROV in South America, especially in Brazil, have changed its status as an emerging disease, but no vaccine or specific drug target is available yet. Our approach was to identify the epitope-based vaccine candidates as well as the ligand-binding pockets through the use of immunoinformatics. In this report, we identified both T-cell and B-cell epitopes of the most antigenic OROV polyprotein with the potential to induce both humoral and cell-mediated immunity. Eighteen highly antigenic and immunogenic CD8⁺ T-cell epitopes were identified, including three 100% conserved epitopes (TSSWGCEEY, CSMCGLIHY, and LAIDTGCLY) as the potential vaccine candidates. The selected epitopes showed 95.77% coverage for the mixed Brazilian population. The docking simulation ensured the binding interaction with high affinity. A total of five highly conserved and nontoxic linear B-cell epitopes "NQKIDLSQL," "HPLSTSQIGDRC," "SHCNLEFTAITADKIMSL," "PEKIPAKEGWLTFSKEHTSSW," and "HHYKPTKNLPHVVPRYH" were selected as potential vaccine candidates. The predicted eight conformational B-cell epitopes represent the accessibility for the entered virus. In the posttherapeutic strategy, ten ligand-binding pockets were identified for effective inhibitor design against emerging OROV infection. Collectively, this research provides novel candidates for epitope-based peptide vaccine design against OROV.

Computational B-cell epitope identification and production of neutralizing murine antibodies against Atroxlysin-I

Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

Identity and validity of conserved B cell epitopes of filovirus glycoprotein: towards rapid diagnostic testing for Ebola and possibly Marburg virus disease

Background

Ebolavirus and Marburgvirus are genera of the virus family Filoviridae. Filoviruses cause rare but fatal viral hemorrhagic fevers (VHFs) in remote villages of equatorial Africa with potential for regional and international spread. Point-of-care (POC) rapid diagnostic tests (RDTs) are critical for early epidemic detection, reponse and control. There are 2 RDTs for Zaire ebolavirus (EBOV), but not other Ebolavirus spp. or Marburg marburgvirus (MARV). We validate 3 conserved B cell epitopes of filovirus glycoprotein (GP) using ebola virus diseases (EVD) survivor samples, towards devising pan-filovirus RDTs.

Methods

In-silico Immuno-informatics:- (a) multiple and basic local alignments of amino-acid sequences of filovirus (4 Ebolavirus spp. & MARV) Gp1, 2 and epitope prediction and conservation analyses within context of ClusterW, BLAST-P and the immune epitope database analysis resource (IEDB-AR); alongside (b) in-vitro enzyme immuno-assays (EIAs) for SUDV Gp1, 2 antigen and host-specific antibodies (IgM and IgG) among 94 gamma irradiated EVD survivor serum and 9 negative controls.

Results

Linear B cell epitopes were present across the entire length of all Gp1, 2, most lying in the region between amino acids positioned 350 and 500. Three seperate epitopes 97/80_GAFFLYDRLAST, 39_YEAGEWAENCY and 500_CGLRQLANETTQALQLFLRATTELR (designated UG-Filo-Peptide− 1, 2 and 3 respectively) were conserved within all studied filovirus species Gp1, 2. Gp1, 2 host specific IgM levels were comparably low (av. ODs < 0.04 [95% CI: 0.02837 to 0.04033]) among the 9 negative controls and 57 survivor samples analyzed. Host specific IgG levels, on the other hand, were elevated (av. ODs > 1.7525 [95% CI: 0.3010 to 3.1352]) among the 92 survivor samples relative to the 9 negative controls (av. ODs < 0.2.321 [95% CI: -0.7596 to 0.5372]). Filovirus Gp1, 2 antigen was not detected [av. ODs < 0.20] within EVD survivor serum relative to recombinant protein positive controls [av. ODs = 0.50].

Conclusions

These conserved B cell epitopes of filovirus Gp1, 2 and their derivative antibodies are promising for research and development of RDTs for EVD, with potential for extension to detect MVD.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3409-x) contains supplementary material, which is available to authorized users.

A Gene-Based Positive Selection Detection Approach to Identify Vaccine Candidates Using Toxoplasma gondii as a Test Case Protozoan Pathogen

Over the last two decades, various in silico approaches have been developed and refined that attempt to identify protein and/or peptide vaccines candidates from informative signals encoded in protein sequences of a target pathogen. As to date, no signal has been identified that clearly indicates a protein will effectively contribute to a protective immune response in a host. The premise for this study is that proteins under positive selection from the immune system are more likely suitable vaccine candidates than proteins exposed to other selection pressures. Furthermore, our expectation is that protein sequence regions encoding major histocompatibility complexes (MHC) binding peptides will contain consecutive positive selection sites. Using freely available data and bioinformatic tools, we present a high-throughput approach through a pipeline that predicts positive selection sites, protein subcellular locations, and sequence locations of medium to high T-Cell MHC class I binding peptides. Positive selection sites are estimated from a sequence alignment by comparing rates of synonymous (dS) and non-synonymous (dN) substitutions among protein coding sequences of orthologous genes in a phylogeny. The main pipeline output is a list of protein vaccine candidates predicted to be naturally exposed to the immune system and containing sites under positive selection. Candidates are ranked with respect to the number of consecutive sites located on protein sequence regions encoding MHCI-binding peptides. Results are constrained by the reliability of prediction programs and quality of input data. Protein sequences from Toxoplasma gondii ME49 strain (TGME49) were used as a case study. Surface antigen (SAG), dense granules (GRA), microneme (MIC), and rhoptry (ROP) proteins are considered worthy T. gondii candidates. Given 8263 TGME49 protein sequences processed anonymously, the top 10 predicted candidates were all worthy candidates. In particular, the top ten included ROP5 and ROP18, which are T. gondii virulence determinants. The chance of randomly selecting a ROP protein was 0.2% given 8263 sequences. We conclude that the approach described is a valuable addition to other in silico approaches to identify vaccines candidates worthy of laboratory validation and could be adapted for other apicomplexan parasite species (with appropriate data).

In Silico Methods in Antibody Design

Antibody therapies with high efficiency and low toxicity are becoming one of the major approaches in antibody therapeutics. Based on high-throughput sequencing and increasing experimental structures of antibodies/antibody-antigen complexes, computational approaches can predict antibody/antigen structures, engineering the function of antibodies and design antibody-antigen complexes with improved properties. This review summarizes recent progress in the field of in silico design of antibodies, including antibody structure modeling, antibody-antigen complex prediction, antibody stability evaluation, and allosteric effects in antibodies and functions. We listed the cases in which these methods have helped experimental studies to improve the affinities and physicochemical properties of antibodies. We emphasized how the molecular dynamics unveiled the allosteric effects during antibody-antigen recognition and antibody-effector recognition.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs.

Epitopes based drug design for dengue virus envelope protein: A computational approach

Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region "QHGTI" in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset "Chembridge". A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski's rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.

Morbid Sequences Suggest Molecular Mimicry between Microbial Peptides and Self-Antigens: A Possibility of Inciting Autoimmunity

Understanding etiology of autoimmune diseases has been a great challenge for designing drugs and vaccines. The pathophysiology of many autoimmune diseases may be attributed to molecular mimicry provoked by microbes. Molecular mimicry hypothesizes that a sequence homology between foreign and self-peptides leads to cross-activation of autoreactive T cells. Different microbial proteins are implicated in various autoimmune diseases, including multiple sclerosis, human type 1 diabetes, primary biliary cirrhosis and rheumatoid arthritis. It may be imperative to identify the microbial epitopes that initiate the activation of autoreactive T cells. Consequently, in the present study, we employed immunoinformatics tools to delineate homologous antigenic regions between microbes and human proteins at not only the sequence level but at the structural level too. Interestingly, many cross-reactive MHC class II binding epitopes were detected from an array of microbes. Further, these peptides possess a potential to skew immune response toward Th1-like patterns. The present study divulges many microbial target proteins, their putative MHC-binding epitopes, and predicted structures to establish the fact that both sequence and structure are two important aspects for understanding the relationship between molecular mimicry and autoimmune diseases. Such findings may enable us in designing potential immunotherapies to tolerize autoreactive T cells.

The porcine translational research database: a manually curated, genomics and proteomics-based research resource

BACKGROUND

The use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are relevant to human studies and for comparative evaluation with rodent models. Furthermore, they contain a significant number of errors due to their primary reliance on machine-based annotation. To address these deficiencies, a comprehensive literature-based survey was conducted to identify certain selected genes that have demonstrated function in humans, mice or pigs.

RESULTS

The process identified 13,054 candidate human, bovine, mouse or rat genes/proteins used to select potential porcine homologs by searching multiple online sources of porcine gene information. The data in the Porcine Translational Research Database (( http://www.ars.usda.gov/Services/docs.htm?docid=6065 ) is supported by >5800 references, and contains 65 data fields for each entry, including >9700 full length (5' and 3') unambiguous pig sequences, >2400 real time PCR assays and reactivity information on >1700 antibodies. It also contains gene and/or protein expression data for >2200 genes and identifies and corrects 8187 errors (gene duplications artifacts, mis-assemblies, mis-annotations, and incorrect species assignments) for 5337 porcine genes.

CONCLUSIONS

This database is the largest manually curated database for any single veterinary species and is unique among porcine gene databases in regard to linking gene expression to gene function, identifying related gene pathways, and connecting data with other porcine gene databases. This database provides the first comprehensive description of three major Super-families or functionally related groups of proteins (Cluster of Differentiation (CD) Marker genes, Solute Carrier Superfamily, ATP binding Cassette Superfamily), and a comparative description of porcine microRNAs.

Immuno-diagnosis of Mycobacterium tuberculosis in sputum, and reduction of timelines for its positive cultures to within 3 h by pathogen-specific thymidylate kinase expression assays

BACKGROUND

Laboratory diagnosis of Tuberculosis (TB) is traditionally based on microscopy and or culture. Microscopy is however, only sensitive to a specified degree of bacillary load not present in HIV co-infected persons. Traditional cultures of Mycobacterium tuberculosis (M. tb), on the other hand, take weeks to read-thereby delaying the critical decision whether or not, to treat. Although nucleic acids amplification tests (NAATS) applied directly on sputum or cultures can increase the sensitivity for TB diagnosis among those with HIV co-infection as well as reduce time-lines for positive culture detection, they do not replace the need for smear microscopy and culture. We have previously proposed the M. tb DNA-synthetic enzyme thymidylate kinase (aka TMKmt) as an organism-specific growth and proliferation biomarker to reduce time-lines for detection of positive TB cultures. In this study, we explored the secretory levels of TMKmt in M. tb cultures and sputum, towards improving the overall laboratory diagnosis of TB.

METHODS AND RESULTS

Modelling of TMKmt secretion in vitro was done by cloning, expressing and SDS-PAGE/MALDI-TOF detection of purified recombinant TMKmt in E. coli. TMKmt expression profiling in M. tb was done by qRT-PCR assay of related messenger ribonucleic acids (mRNA) and TMKmt antigen detection by Enzyme linked Immuno-absorbent Assay (EIA) among cultures of a pathogenic wild-type Ugandan strain (genotype 1) alongside the H37Rv laboratory strain. Owing to the high-load of pathogen in-culture, direct EIA on limiting dilutions of sputum were done to examine for assay sensitivity. A rise in TMKmt antigen levels was observed at 3 h post-innoculation among in vitro cultures of E. coli. The 1st of several cyclic spikes in TMKmt mRNA and antigen levels were detected at 2.5 h among in vitro cultures of the pathogenic wild-type Ugandan isolate alongside the laboratory M. tb strain. TMKmt antigen was detected up to between 1 × 10-4-1 × 10-5 (containing 10 and 1 CFUs/ml) dilutions of a microscopically designated 1+ (est. Acid Fast Bacillary load of 1 × 105) patient sample.

CONCLUSIONS

Detection of TMKmt expressed mRNA and Ag offers us opportune for instant diagnosis of M. tb in sputum, and reduction of timelines for positive pathogen detection in cultures to within 3 h.

In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity

Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I), a putative heat shock protein (EL PGI II), Spa32 (EL PGI III), IcsB (EL PGI IV) and a hypothetical protein (EL PGI V). These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP) and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

In silico analysis and in vitro evaluation of immunogenic and immunomodulatory properties of promiscuous peptides derived from Leishmania infantum eukaryotic initiation factor

It is generally considered as imperative the ability to control leishmaniasis through the development of a protective vaccine capable of inducing long-lasting and protective cell-mediated immune responses. In this current study, we demonstrated potential epitopes that bind to H2 MHC class I and II molecules by conducting the in silico analysis of Leishmania infantum eukaryotic Initiation Factor (LieIF) protein, using online available algorithms. Moreover, we synthesized five peptides (16-18 amino acids long) which are part of the N-terminal portion of LieIF and contain promising MHC class I and II-restricted epitopes and afterwards, their predicted immunogenicity was evaluated in vitro by monitoring peptide-specific T-cell responses. Additionally, the immunomodulatory properties of these peptides were investigated in vitro by exploring their potential of inducing phenotypic maturation and functional differentiation of murine Bone-Marrow derived Dendritic Cells (BM-DCs). It was revealed by our data that all the synthetic peptides predicted for H2 alleles; present the property of immunogenicity. Among the synthetic peptides which contained T-cell epitopes, the peptide 52-68 aa (LieIF_2) exhibited immunomodulatory properties with the larger potential. LieIF_2-pulsed BM-DCs up-regulated the expression of the co-stimulatory surface molecules CD80 and CD86, as well as the production of the proinflammatory cytokine TNF-α and of the Th1-polarizing cytokines IL-12 and IFN-γ. The aforementioned data suggest that selected parts of LieIF could be used to develop innovative subunit protective vaccines able to induce effective immunity mediated by MHC class I-restricted as well as class II-restricted T-cell responses.

Sero-diagnosis of Active Mycobacterium tuberculosis Disease among HIV Co-infected Persons using Thymidylate Kinase based Antigen and Antibody Capture Enzyme Immuno-Assays

BACKGROUND

Clinical and laboratory diagnosis of Active Tuberculosis (ATB) and latent Mycobacterium Tuberculosis (M. tuberculosis) infections (LTBI) among people living with HIV/AIDS (PLWHA) presents formidable challenges. In the past, WHO issued an advisory against the use of existing TB sero-diagnostics. Emerging evidence, however, points to a precision of TB sero-diagnostics based on secretory rather than structural M. tuberculosis antigens. We hypothesized that secretory levels of M. tuberculosis thymidylate kinase (TMKmt) can Designate ATBI from LTBI and no TB (NTB). Here, we report in-house validation studies of levels of TMKmt antigen (Ag) and host specific TMKmt antibody (Ab) amongst HIV +ve and HIV -ve participants.

METHODS AND RESULTS

Direct TMKmt Ag and host specific IgG Ab detection EIAs were conducted on broadly consented, stored serum (N=281[Ag] vs. 214 [Ab] respective) samples stratified as either HIV +ve or HIV-ve ATB relative to LTBI and No TB. On one hand, UG-peptide 1 and its PAb-based EIAs accurately diagnosed ATB relative to LTBI and NTB among HIV +ve subjects {irrespectively: (a) Ag detection ATB=OD>0.490; 95% CI: 0.7446 to 0.8715 vs. LTBI=OD<0.490; 95% CI 0.4325 to 0.4829 vs. NTB=OD<0.26; 95% CI 0.1675 to 0.2567 and (b) TMKmt specific IgG detection ATB=OD>1.00; 95% CI 1.170 to 1.528 [HIV +ve] and 2.044 to 2.978 [HIV -ve] respectively vs. LTBI=OD<1.00; 95% CI 0.2690 to 0.6396 vs. NTB=OD<; 95% CI 0.1527 to 0.8751}. HIV -ve ATB presented with Ag levels greater than NTB and less than LTBI (i.e. ATB -ve=<0.490 ODs>0.26), but displayed better ant-TMKmt IgG responses (OD>2.00; 95% CI 2.044 to 2.978) relative to HIV +ve ATB (OD<1.600; 95% CI 1.170 to 1.528); suggesting a better control of M. tuberculosis-septicemia. On the other hand, UG-peptide 2 and its PAb-based EIAs did not demonstrate ATB diagnostic potential regardless of HIV sero-status, except towards designating NTB.

CONCLUSIONS

TMKmt Ab and Ag detecting EIAs based on UG-peptide 1 and its derivative PAb can accurately demarcate ATB from LTBI and NTB among HIV +ve subjects.

Personalized Medicine in the Era of Genomics

Personalized medicine is a model that aims at customizing healthcare and tailoring medicine according to an individual`s genetic makeup. It classifies individuals that differ in their susceptibility to a particular disease or response to a particular treatment into subpopulations based on individual's unique genetic and clinical information along with environmental factors. The completion of Human Genome Project and the advent of high-throughput genome analysis tools has helped in building and strengthening this model. There lies a huge potential in the implementation of personalized medicine to significantly improve the clinical outcomes; however, its implementation into clinical practice remains slow and is a matter of concern. This chapter aims at acquainting readers with the underlying concepts and components of personalized medicine supplemented with some disease-based case studies, discussing challenges and recent advancements in the implementation of the model of personalized medicine.

Los Alamos Hepatitis C Virus Sequence and Human Immunology Databases: An Expanding Resource for Antiviral Research

The hepatitis C virus (HCV) resource at Los Alamos (hcv.lanl.gov) provides access to multiple databases: one containing annotated sequences and the other a repository of immunogenic epitopes. They are derived from databases originally developed for HIV research (hiv.lanl.gov). HCV and HIV are RNA viruses with relatively compact genomes (around 10 kb) that are extraordinarily variable, both within and between hosts. This diversity requires methods to track and exclude variants from an individual infection or from epidemiologically related infections, and tools to analyse the variation. The HCV immunology database contains a curated inventory of immunogenic epitopes and information about their interaction with the host immune system, with associated retrieval and analysis tools. This interactive resource provides flexible retrieval tools for sequences, epitopes, clinical information, and metadata, as well as utilities for scientific data analysis, to investigators with internet access and a web browser. This paper describes the types of data and the services that these databases offer, the tools they provide, and their configuration and use. Examples of applications to clonal analysis for drug-resistance mutations are shown.

A statistical approach to determining responses to individual peptides from pooled-peptide ELISpot data

To investigate in detail the effect of infection or vaccination on the human immune system, ELISpot assays are used to simultaneously test the immune response to a large number of peptides of interest. Scientists commonly use "peptide pools", where, instead of an individual peptide, a test well contains a group of peptides. Since the response from a well may be due to any or many of the peptides in the pool, pooled assays usually need to be followed by confirmatory assays of a number of individual peptides. We present a statistical method that enables estimation of individual peptide responses from pool responses using the Expectation Maximization (EM) algorithm for "incomplete data". We demonstrate the accuracy and precision of these estimates in simulation studies of ELISpot plates with 90 pools of 6 or 7 peptides arranged in three dimensions and three Mock wells for the estimation of background. In analysis of real pooled data from 6 subjects in a HIV-1 vaccine trial, where 199 peptides were arranged in 80 pools if size 9 or 10, our estimates were in very good agreement with the results from individual-peptide confirmatory assays. Compared to the classical approach, we could identify almost all the same peptides with high or moderate response, with less than half the number of confirmatory tests. Our method facilitates efficient use of the information available in pooled ELISpot data to avoid or reduce the need for confirmatory testing. We provide an easy-to-use free online application for implementing the method, where on uploading two spreadsheets with the pool design and pool responses, the user obtains the estimates of the individual peptide responses.

Vaccine Design for H5N1 Based on B- and T-cell Epitope Predictions

From 2003 to 2013, Indonesia had the highest number of avian influenza A cases in humans, with 192 cases and 160 fatalities. Avian influenza is caused by influenza virus type A, such as subtype H5N1. This virus has two glycoproteins: hemagglutinin and neuraminidase, which will become the primary target to be neutralized by vaccine. Vaccine is the most effective immunologic intervention. In this study, we use the epitope-based vaccine design from hemagglutinin and neuraminidase of H5N1 Indonesian strain virus by using immunoinformatics approach in order to predict the binding of B-cell and T-cell epitopes (class I and class II human leukocyte antigen [HLA]). BCPREDS was used to predict the B-cell epitope. Propred, Propred I, netMHCpan, and netMHCIIpan were used to predict the T-cell epitope. Two B-cell epitopes of hemagglutinin candidates and one B-cell epitope of neuraminidase candidates were obtained to bind T-cell CD4(+) (class II HLA), and also five T-cell epitope hemagglutinin and four T-cell epitope neuraminidase were obtained to bind T-cell CD8(+) (class I HLA). The visualization of epitopes was done using MOE 2008.10. It shows that the binding affinity of epitope-HLA was based on minimum binding free energy (ΔG binding). Based on this result, visualization, and dynamic simulation, four hemagglutinin epitopes (MEKIVLLLA, CPYLGSPSF, KCQTPMGAI, and IGTSTLNQR) and two neuraminidase epitopes (NPNQKIITI and CYPDAGEIT) were computed as having the best binding affinity from HLA ligand. The results mentioned above are from in silico experiments and need to be validated using wet experiment.

The quantitative prediction of HLA-B*2705 peptide binding affinities using Support Vector Regression to gain insights into its role for the Spondyloarthropathies

Computational methods are increasingly utilised in many immunoinformatics problems such as the prediction of binding affinity of peptides. The peptides could provide valuable insight into the drug design and development such as vaccines. Moreover, they can be used to diagnose diseases. The presence of human class I MHC allele HLA-B*2705 is one of the strong hypothesis that would lead spondyloarthropathies. In this paper, Support Vector Regression is used in order to predict binding affinity of peptides with the aid of experimentally determined peptide-MHC binding affinities of 222 peptides to HLA-B*2705 to get more insight into this problematic disease. The results yield a high correlation coefficient as much as 0.65 and the SVR-based predictive models can be considered as a useful tool in order to predict the binding affinities for newly discovered peptides.

A Computational Approach for Designing a Universal Epitope-Based Peptide Vaccine Against Nipah Virus

Nipah virus (NiV) is highly pathogenic single-stranded negative sense RNA virus. It can cause severe encephalitis and respiratory disease in humans. In addition, NiV infects a large range of host including mammals. As a result of its higher zoonotic potential and pathogenicity for human, it has been rated as an alert in recent days. A therapeutic treatment or vaccines has become elusive to fight against this virus. In this study, the attachment (G) and fusion (F) glycoproteins of NiV, responsible for the viral attachment and entry to the host cell, were selected to develop epitope-based vaccine against Nipah virus. Epitopes were identified from the conserved region of G and F protein of NiV. Both B-cell and T-cell immunity were checked to affirm it that these epitopes will be able to induce humoral and cellular immunity. A total of 6 T-cell epitopes and 19 significant HLA-epitope interactions were identified. Eventually it has shown an acceptable percentage in population coverage (46.45 %) and efficient binding with HLA molecule by molecular docking study.

In silico peptide prediction for antibody generation to recognize 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in genetically modified organisms

For the prospective immunorecognition of 5-enolpyruvylshikimate-3-phosphate synthase (CP4-EPSPS) as a biomarker protein expressed by transgenic soybean, an extensive in silico evaluation of the referred protein was performed. The main objective of this study was the selection of a set of peptides that could function as potential immunogens for the production of novel antibodies against CP4-EPSPS protein. For this purpose, the protein was in silico cleaved with trypsin/chymotrypsin and the resultant peptides were extensively analyzed for further selection of the best candidates for antibody production. The analysis enabled the successful proposal of four peptides with potential immunogenicity for their future use as screening biomarkers of genetically modified organisms. To our knowledge, this is the first attempt to select and define potential linear epitopes for the immunization of animals and, subsequently, to generate adequate antibodies for CP4-EPSPS recognition. The present work will be followed by the synthesis of the candidate peptides to be incubated in animals for antibody generation and potential applicability for the development of an immunosensor for CP4-EPSPS detection.

A comprehensive immunoinformatics and target site study revealed the corner-stone toward Chikungunya virus treatment

Recent concerning facts of Chikungunya virus (CHIKV); a Togaviridae family alphavirus has proved this as a worldwide emerging threat which causes Chikungunya fever and devitalizing arthritis. Despite severe outbreaks and lack of antiviral drug, a mere progress has been made regarding to an epitope-based vaccine designed for CHIKV. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites by using various immunoinformatics and docking simulation tools. Initially, whole proteome of CHIKV was retrieved from database and perused to identify the most immunogenic protein. Structural properties of the selected protein were analyzed. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell were checked for the selected protein. The peptide region spanning 9 amino acids from 397 to 405 and the sequence YYYELYPTM were found as the most potential B cell and T cell epitopes respectively. This peptide could interact with as many as 19 HLAs and showed high population coverage ranging from 69.50% to 84.94%. By using in silico docking techniques the epitope was further assessed for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post therapeutic strategy, three dimensional structure was predicted along with validation and verification that resulted in molecular docking study to identify the potential drug binding sites and suitable therapeutic inhibitor against targeted protein. Finally, pharmacophore study was also performed in quest of seeing potent drug activity. However, this computational epitope-based peptide vaccine designing and target site prediction against CHIKV opens up a new horizon which may be the prospective way in Chikungunya virus research; the results require validation by in vitro and in vivo experiments.

Phylodynamic analysis of porcine reproductive and respiratory syndrome virus (PRRSV) in Italy: action of selective pressures and interactions between different clades

Porcine reproductive and respiratory syndrome (PRRS) is the most relevant and challenging infectious disease to affect swine breeding. Despite this, several aspects of the virus' evolution and virus-host interaction are still poorly understood and largely based on knowledge obtained through in vitro or in vivo experimental infections. Due to peculiar experimental conditions, our understanding is often contradictory and difficult to infer with respect to actual field conditions. Our phylodynamic study, based on ORF5 sequences of 141 samples collected in Italy from 1993 to 2012, explores different aspects of PRRSV epidemiology, evolution, and virus-host interaction. Two major clades, belonging to Type 1 subtype 1, were demonstrated to co-circulate while harboring a relevant intra- and inter-clade genetic diversity. Most Recent Common Ancestor (MRCA), evolution rates, and population dynamics were estimated using a serial coalescent-based approach, and different demographic histories were reconstructed for the two clades. Analysis of selective pressure revealed that sites subjected to diversifying selection were mainly located in the region of glycoprotein 5 (GP5) exposed to the host environment. Similarly, the vast majority of strains were highly glycosylated, confirming the proposed protective role of the glycan shield against the humoral immune response. Overall, our study reports both interactions among the viral populations as well as between virus and host, and their relevance in shaping viral evolution: different population dynamics over time seem to reflect a competition between clades. Some evidence argues in favor of the role of immune pressure in affecting GP5 evolution, including frequent changes in the region exposed to the host immune response, and preserving glycosylation profiles that can hamper humoral immunity.

Observation of high recombination occurrence of Porcine Reproductive and Respiratory Syndrome Virus in field condition

Recombination in Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is a well-documented phenomenon. A high recombination frequency has been reported in experimental conditions both in vitro and in vivo, and its role in driving viral evolution has been postulated by several authors. However field evidences are rare, mainly obtained from large-scale sampling and typically represented by single sequences rather than by groups of circulating "recombinant progenies". The present work was aimed to investigate the gray area between experimental studies and large-scale epidemiological investigations. The study was performed on ORF5, ORF7 and concatenated sequences obtained in our laboratory or available in GenBank collected between 2009 and 2012 in northern Italy. Six independent recombinant strains out of 66 concatenated sequences (∼9%) were found, demonstrating a high recombination frequency respect to previous field studies but comparable to in vitro experiments. In silico analysis let speculate that this new strain displayed physicochemical features diverse enough to potentially alter its immunological properties. Taken altogether, the results of our study support previous experimental evidences that depict PRRSV to be extremely prone to recombination. The limited temporal and geographical spread of recombinant strains however states in favor of a limited fitness of the recombinant progeny compared to parental strains and the marginal role of this phenomenon in PRRSV evolution.

An overview of bioinformatics tools for epitope prediction: implications on vaccine development

Exploitation of recombinant DNA and sequencing technologies has led to a new concept in vaccination in which isolated epitopes, capable of stimulating a specific immune response, have been identified and used to achieve advanced vaccine formulations; replacing those constituted by whole pathogen-formulations. In this context, bioinformatics approaches play a critical role on analyzing multiple genomes to select the protective epitopes in silico. It is conceived that cocktails of defined epitopes or chimeric protein arrangements, including the target epitopes, may provide a rationale design capable to elicit convenient humoral or cellular immune responses. This review presents a comprehensive compilation of the most advantageous online immunological software and searchable, in order to facilitate the design and development of vaccines. An outlook on how these tools are supporting vaccine development is presented. HIV and influenza have been taken as examples of promising developments on vaccination against hypervariable viruses. Perspectives in this field are also envisioned.

Comparison of experimental fine-mapping to in silico prediction results of HIV-1 epitopes reveals ongoing need for mapping experiments

Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.