Application of pharmacogenomics to vaccines

In silico prediction of CD8+ and CD4+ T cell epitopes in Leishmania major proteome: Using immunoinformatics

The leishmaniases are NDTs (neglected tropical diseases) that affect people all over the world. They are brought on by protozoans from the genus Leishmania and disseminated by phlebotomine flies that are afflicted with the disease. The best option to manage and lower the incidence of these diseases has been thought by the creation of a safe and effective vaccination. This research used an in silico based mining approach to look for high potential epitopes that might bind to MHC Class I and MHC Class II molecules (mainly; HLA-A*02:01 & HLA-DRB1*03:01) from human population in order to promote vaccine development. Based on the presence of signal peptides, GPI anchors, antigenicity predictions, and a subtractive proteomic technique, we have screened 17 putative antigenic proteins from the 8083 total proteins of L. major. After that thorough immunogenic epitope prediction were done using IEDB-AR tools. We isolated five immunogenic epitopes (three 9-mer & two 15-mer) from five antigenic proteins through docking and MD simulation analysis. Finally, these five anticipated epitopes, viz., TLPEIPVNV, ELMAPVFGL, TLAAAVALL, NSINIRLDGVTSAGF and NVPLVVDASSLFRVA have considerably stronger binding potential with their respective alleles and may trigger immunological responses. The goal of this work was to identify MHC restricted epitopes for CD8+ and CD4+ T cells activation using immunoinformatics in order to identify potential vaccine candidates against L. major parasites.

Inferring B-cell derived T-cell receptor induced multi-epitope-based vaccine candidate against enterovirus 71: a reverse vaccinology approach

Purpose

Enterovirus 71, a pathogen that causes hand-foot and mouth disease (HFMD) is currently regarded as an increasing neurotropic virus in Asia and can cause severe complications in pediatric patients with blister-like sores or rashes on the hand, feet, and mouth. Notwithstanding the significant burden of the disease, no authorized vaccine is available. Previously identified attenuated and inactivated vaccines are worthless over time owing to changes in the viral genome.

Materials and Methods

A novel vaccine construct using B-cell derived T-cell epitopes from the virulent polyprotein found the induction of possible immune response. In order to boost the immune system, a beta-defensin 1 preproprotein adjuvant with EAAAK linker was added at the N-terminal end of the vaccine sequence.

Results

The immunogenicity of the designed, refined, and verified prospective three-dimensional-structure of the multi-epitope vaccine was found to be quite high, exhibiting non-allergenic and antigenic properties. The vaccine candidates bound to toll-like receptor 3 in a molecular docking analysis, and the efficacy of the potential vaccine to generate a strong immune response was assessed through in silico immunological simulation.

Conclusion

Computational analysis has shown that the proposed multi-epitope vaccine is possibly safe for use in humans and can elicit an immune response.

Vaccinomics: Paving the Way for Personalized Immunization

Vaccines are one of the most important medical advancements in human history. They have been successfully used to control and limit the spread of many of the lethal diseases that have plagued us, such as smallpox and polio. Previous vaccine design methodologies were based on the model of "isolate-inactivateinject", which amounts to giving the same vaccine dose to everyone susceptible to infection. In recent years, the importance of how the host genetic background alters vaccine response necessitated the introduction of vaccinomics, which is aimed at studying the variability of vaccine efficacy by associating genetic variability and immune response to vaccination. Despite the rapid developments in variant screening, data obtained from association studies is often inconclusive and cannot be used to guide the new generation of vaccines. This review aims to compile the polymorphisms in HLA and immune system genes and examine the link with their immune response to vaccination. The compiled data can be used to guide the development of new strategies for vaccination for vulnerable groups. Overall, the highly polymorphic HLA locus had the highest correlation with vaccine response variability for most of the studied vaccines, and it was linked to variation in multiple stages of the immune response to the vaccines for both humoral and cellular immunity. Designing new vaccine technologies and immunization regiments to accommodate for this variability is an important step for reaching a vaccinomics-based approach to vaccination.

Genomic annotation for vaccine target identification and immunoinformatics-guided multi-epitope-based vaccine design against Songling virus through screening its whole genome encoded proteins

Songling virus (SGLV), a newly discovered tick-borne orthonairovirus, was recently identified in human spleen tissue. It exhibits cytopathic effects in human hepatoma cells and is associated with clinical symptoms including headache, fever, depression, fatigue, and dizziness, but no treatments or vaccines exist for this pathogenic virus. In the current study, immunoinformatics techniques were employed to identify potential vaccine targets within SGLV by comprehensively analyzing SGLV proteins. Four proteins were chosen based on specific thresholds to identify B-cell and T-cell epitopes, validated through IFN-γ epitopes. Six overlap MHC-I, MHC-II, and B cell epitopes were chosen to design a comprehensive vaccine candidate, ensuring 100% global coverage. These structures were paired with different adjuvants for broader protection against international strains. Vaccine constructions' 3D models were high-quality and validated by structural analysis. After molecular docking, SGLV-V4 was selected for further research due to its lowest binding energy (-66.26 kcal/mol) and its suitable immunological and physiochemical properties. The vaccine gene is expressed significantly in E. coli bacteria through in silico cloning. Immunological research and MD simulations supported its molecular stability and robust immune response within the host cell. These findings can potentially be used in designing safer and more effective experimental SGLV-V4 vaccines.

Design of a multi-epitope-based vaccine consisted of immunodominant epitopes of structural proteins of SARS-CoV-2 using immunoinformatics approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown rapid global spread and has resulted in a significant death toll worldwide. In this study, we aimed to design a multi-epitope vaccine against SARS-CoV-2 based on structural proteins S, M, N, and E. We identified B- and T-cell epitopes and then the antigenicity, toxicity, allergenicity, and similarity of predicted epitopes were analyzed. T-cell epitopes were docked with corresponding HLA alleles. Consequently, the selected T- and B-cell epitopes were included in the final construct. All selected epitopes were connected with different linkers and flagellin and pan-HLA DR binding epitopes (PADRE) as an adjuvant were used in the vaccine construct. Furthermore, molecular docking was used to evaluate the complex between the final vaccine construct and two alleles, HLA-A*02:01 and HLA-DRB1*01:01. Finally, codons were optimized for in silico cloning into pET28a(+) vector using SnapGene. The final vaccine construct comprised 11 CTL, HTL, and B-cell epitopes corresponding to 394 amino acid residues. In silico evaluation showed that the designed vaccine might potentially promote an immune response. Further in vivo preclinical and clinical testing is required to determine the safety and efficacy of the designed vaccine.

Immunoinformatics based design and prediction of proteome-wide killer cell epitopes of Leishmania donovani: Potential application in vaccine development

Despite several extensive and exhaustive efforts, search for potential therapy against leishmaniasis has not made much progress. In the present work, we have employed mining strategy to screen Leishmania donovani proteome for identification of promising vaccine candidate. We have screened 21 potential antigenic proteins from 7960 total protein of L. donovani, based on the presence of signal peptide, GPI anchor, antigenicity prediction and substractive proteomic approach. Secondly, we have also performed comprehensive immunogenic epitope prediction from the screened 21 proteins, using IEDB-AR tools. Out of the 21 antigenic proteins, we obtained 11 immunogenic epitopes from 9 proteins. The final results revealed that four predicted epitopes namely; YPAFAALVF, VAVAATVAY, AAAPTEAAL and MYPLVAVVF, have significantly better binding potential with respective alleles and could elicits immune responses. Docking analysis using PATCHDOCK server and molecular dynamic simulation using GROMACS revealed the potential of the sequences as immunogenic epitopes. In silico studies also suggested that the epitopes occupied almost same binding cleft with the respective alleles, when compared with the reference peptides. It is also suggested from the molecular dynamic simulation data that the peptides were intact in the pocket for longer periods of time. Our study was designed to select MHC class I restricted epitopes for the activation of CD8 T cells using immunoinformatics for the prediction of probable vaccine candidate against L. donovani parasites. Communicated by Ramaswamy H. Sarma.

A candidate multi-epitope vaccine against Lumpy skin disease

Lumpy skin disease (LSD) is a fulminant infectious disease that mostly affects cattle and causes considerable economic loss throughout the globe. This study was conducted to develop a new multi-epitope-based vaccine against LSD that can elicit immunological responses using an in silico reverse vaccinology approach. Initially, three antigenic proteins, protein E5, E3 ubiquitin-protein ligase LAP and 62 kDa protein, were manipulated to recognize potential T-cell and B-cell epitopes. To identify superior epitopes, a variety of bioinformatic techniques including antigenicity testing, transmembrane topology screening, allergenicity assessment, conservancy analysis, and toxicity evaluation were used. Finally, three new subunit vaccines (construct V1, V2 and V3) were developed employing the most effective epitopes, suitable adjuvants, pan HLA DR-binding epitope (PADRE) and linkers. Then, based on the antigenicity, solubility, and validation score of the 3D structures, construct V2 was chosen as one of the best candidate vaccines. The results of the molecular dynamic simulation and disulphide engineering indicated that the vaccine (construct V2) was stable. Additionally, the immunological simulation findings supported the vaccine candidate's ability to trigger humoral and cellular immune responses. Further validation of the proposed vaccine candidate may necessitate additional in vitro and in vivo investigations.

2022 AAHA Canine Vaccination Guidelines

These guidelines are an update and extension of previous AAHA peer-reviewed canine vaccination guidelines published in 2017. Vaccination is a cornerstone of canine preventive healthcare and one of the most cost-effective ways of maintaining a dog's health, longevity, and quality of life. Canine vaccination also serves a public health function by forming a barrier against several zoonotic diseases affecting dogs and humans. Canine vaccines are broadly categorized as containing core and noncore immunizing antigens, with administration recommendations based on assessment of individual patient risk factors. The guidelines include a comprehensive table listing canine core and noncore vaccines and a recommended vaccination and revaccination schedule for each vaccine. The guidelines explain the relevance of different vaccine formulations, including those containing modified-live virus, inactivated, and recombinant immunizing agents. Factors that potentially affect vaccine efficacy are addressed, including the patient's prevaccination immune status and vaccine duration of immunity. Because animal shelters are one of the most challenging environments for prevention and control of infectious diseases, the guidelines also provide recommendations for vaccination of dogs presented at or housed in animal shelters, including the appropriate response to an infectious disease outbreak in the shelter setting. The guidelines explain how practitioners can interpret a patient's serological status, including maternally derived antibody titers, as indicators of immune status and suitability for vaccination. Other topics covered include factors associated with postvaccination adverse events, vaccine storage and handling to preserve product efficacy, interpreting product labeling to ensure proper vaccine use, and using client education and healthcare team training to raise awareness of the importance of vaccinations.

Proteome Exploration of Legionella pneumophila To Identify Novel Therapeutics: a Hierarchical Subtractive Genomics and Reverse Vaccinology Approach

Legionella pneumophila is a human pathogen distributed worldwide, causing Legionnaires’ disease (LD), a severe form of pneumonia and respiratory tract infection. L. pneumophila is emerging as an antibiotic-resistant strain, and controlling LD is now difficult. Hence, developing novel drugs and vaccines against L. pneumophila is a major research priority.

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.

Immunoinformatics and reverse vaccinomic approaches for effective design

The emergence of mutagenic strains of severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) worst hit the world which already suffered from the Coronavirus disease-2019 (COVID-19) pandemic for 2 years. Due to recent advances in vaccinomics, many vaccine candidates are available but their efficacy against a mutant version of SARS-CoV-2 has remained uncertain. The immune-informatics-based reverse vaccinomic approaches have shown promising investigations recently for the development of cost-effective vaccinomics candidates in a very short period of time. The strategic vaccine development of selected epitopes using artificial intelligence for both B- and T-cells is a very crucial step in this process. This approach provides a highly effective and immunogenic vaccine that offers immunological safety against autoimmunity and other adverse effects over ethnicities, pregnant women, and vulnerable age groups. Several researchers have developed effective vaccine candidates using computational vaccinology and the immune-informatics approach. In this process, a unique peptide sequence of viral proteins such as Nucleocapsid, spike, envelope protein was identified by various in silico tools which are acting as immunological epitopes against TLRs, T-cells, and B-cells. While the conventional immunological vaccine studies take years for vaccine candidature, the immunoinformatics approach is a time-efficient way for the next generation research to study host-pathogen interactions and vaccine development. It is also cost-effective and leads to a better understanding of disease pathogenesis, diagnosis, and immunological response. Owing to the advantage of immunoinformatics-based vaccine approaches the present chapter aimed to discuss vaccine development using immunoinformatics approaches. Besides, the current challenges and future aspects have also been discussed herewith.

Vaccinomics: a future avenue for vaccine development against emerging pathogens

INTRODUCTION

Vaccines are a major achievement in medical sciences, but the development of more effective vaccines against infectious diseases is essential for prevention and control of emerging pathogens worldwide. The application of omics technologies has advanced vaccinology through the characterization of host-vector-pathogen molecular interactions and the identification of candidate protective antigens. However, major challenges such as host immunity, pathogen and environmental factors, vaccine efficacy and safety need to be addressed. Vaccinomics provides a platform to address these challenges and improve vaccine efficacy and safety.

AREAS COVERED

In this review, we summarize current information on vaccinomics and propose quantum vaccinomics approaches to further advance vaccine development through the identification and combination of antigen protective epitopes, the immunological quantum. The COVID-19 pandemic caused by SARS-CoV-2 is an example of emerging infectious diseases with global impact on human health.

EXPERT OPINION

Vaccines are required for the effective and environmentally sustainable intervention for the control of emerging infectious diseases worldwide. Recent advances in vaccinomics provide a platform to address challenges in improving vaccine efficacy and implementation. As proposed here, quantum vaccinomics will contribute to vaccine development, efficacy, and safety by facilitating antigen combinations to target pathogen infection and transmission in emerging infectious diseases.

In Silico Prediction of a Multitope Vaccine against Moraxella catarrhalis: Reverse Vaccinology and Immunoinformatics

Moraxella catarrhalis (M. catarrhalis) is a Gram-negative bacterium that can cause serious respiratory tract infections and middle ear infections in children and adults. M. catarrhalis has demonstrated an increasing rate of antibiotic resistance in the last few years, thus development of an effective vaccine is a major health priority. We report here a novel designed multitope vaccine based on the mapped epitopes of the vaccine candidates filtered out of the whole proteome of M. catarrhalis. After analysis of 1615 proteins using a reverse vaccinology approach, only two proteins (outer membrane protein assembly factor BamA and LPS assembly protein LptD) were nominated as potential vaccine candidates. These proteins were found to be essential, outer membrane, virulent and non-human homologs with appropriate molecular weight and high antigenicity score. For each protein, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell lymphocyte (BCL) epitopes were predicted and confirmed to be highly antigenic and cover conserved regions of the proteins. The mapped epitopes constituted the base of the designed multitope vaccine where suitable linkers were added to conjugate them. Additionally, beta defensin adjuvant and pan-HLA DR-binding epitope (PADRE) peptide were also incorporated into the construct to improve the stimulated immune response. The constructed multitope vaccine was analyzed for its physicochemical, structural and immunological characteristics and it was found to be antigenic, soluble, stable, non-allergenic and have a high affinity to its target receptor. Although the in silico analysis of the current study revealed that the designed multitope vaccine has the ability to trigger a specific immune response against M. catarrhalis, additional translational research is required to confirm the effectiveness of the designed vaccine.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

Vaccines are not one size fits all, just like medications: rotavirus vaccine study

The current global coronavirus disease 2019 pandemic has shown us once again how important vaccination is in controlling and preventing the spread of deadly diseases. Vaccinations are one of the most tried and tested public health measures aimed at the prevention and eventual eradication of various diseases. Many debilitating diseases like polio have been eradicated in countries like India due to effective vaccination strategies. Just like with any other public health initiative, there do exist various challenges for vaccination. Efficacy and correlate of protection studies are crucial in determining which vaccine works best. The rotavirus vaccine (ROTAVAC; Bharat Biotech International Ltd., Hyderabad, India) is one such example where efficacy seen in one geographical and ethnic population is not replicated elsewhere. This has prompted various researchers and pharmaceutical companies to think about customizing vaccines to the individual needs of a particular geographic and ethnic group. In this brief communication, we look at the rotavirus vaccination story and see how it laid down the idea for customized vaccination development and what the future of vaccine development looks like.

Ontology-based Precision Vaccinology for Deep Mechanism Understanding and Precision Vaccine Development

Vaccination is one of the most important innovations in human history. It has also become a hot research area in a new application - the development of new vaccines against non-infectious diseases such as cancers. However, effective and safe vaccines still do not exist for many diseases, and where vaccines exist, their protective immune mechanisms are often unclear. Although licensed vaccines are generally safe, various adverse events, and sometimes severe adverse events, still exist for a small population. Precision medicine tailors medical intervention to the personal characteristics of individual patients or sub-populations of individuals with similar immunity-related characteristics. Precision vaccinology is a new strategy that applies precision medicine to the development, administration, and post-administration analysis of vaccines. Several conditions contribute to make this the right time to embark on the development of precision vaccinology. First, the increased level of research in vaccinology has generated voluminous "big data" repositories of vaccinology data. Secondly, new technologies such as multi-omics and immunoinformatics bring new methods for investigating vaccines and immunology. Finally, the advent of AI and machine learning software now makes possible the marriage of Big Data to the development of new vaccines in ways not possible before. However, something is missing in this marriage, and that is a common language that facilitates the correlation, analysis, and reporting nomenclature for the field of vaccinology. Solving this bioinformatics problem is the domain of applied biomedical ontology. Ontology in the informatics field is human- and machine-interpretable representation of entities and the relations among entities in a specific domain. The Vaccine Ontology (VO) and Ontology of Vaccine Adverse Events (OVAE) have been developed to support the standard representation of vaccines, vaccine components, vaccinations, host responses, and vaccine adverse events. Many other biomedical ontologies have also been developed and can be applied in vaccine research. Here, we review the current status of precision vaccinology and how ontological development will enhance this field, and propose an ontology-based precision vaccinology strategy to support precision vaccine research and development.

Vaccinomics approach for scheming potential epitope-based peptide vaccine by targeting l-protein of Marburg virus

Marburg virus is one of the world’s most threatening diseases, causing extreme hemorrhagic fever, with a death rate of up to 90%. The Food and Drug Administration (FDA) currently not authorized any treatments or vaccinations for the hindrance and post-exposure of the Marburg virus. In the present study, the vaccinomics methodology was adopted to design a potential novel peptide vaccine against the Marburg virus, targeting RNA-directed RNA polymerase (l). A total of 48 l-proteins from diverse variants of the Marburg virus were collected from the NCBI GenBank server and used to classify the best antigenic protein leading to predict equally T and B-cell epitopes. Initially, the top 26 epitopes were evaluated for the attraction with major histocompatibility complex (MHC) class I and II alleles. Finally, four prospective central epitopes NLSDLTFLI, FRYEFTRHF, YRLRNSTAL, and YRVRNVQTL were carefully chosen. Among these, FRYEFTRHF and YRVRNVQTL peptides showed 100% conservancy. Though YRLRNSTAL showed 95.74% conservancy, it demonstrated the highest combined score as T cell epitope (2.5461) and population coverage of 94.42% among the whole world population. The epitope was found non-allergenic, and docking interactions with human leukocyte antigens (HLAs) also verified. Finally, in vivo analysis of the recommended peptides might contribute to the advancement of an efficient and exclusively prevalent vaccine that would be an active route to impede the virus spreading.

Vaccinomics and Adversomics in the Era of Precision Medicine: A Review Based on HBV, MMR, HPV, and COVID-19 Vaccines

Precision medicine approaches based on pharmacogenomics are now being successfully implemented to enable physicians to predict more efficient treatments and prevention strategies for a given disease based on the genetic background of the patient. This approach has already been proposed for vaccines, but research is lagging behind the needs of society, and precision medicine is far from being implemented here. While vaccinomics concerns the effectiveness of vaccines, adversomics concerns their side effects. This area has great potential to address public concerns about vaccine safety and to promote increased public confidence, higher vaccination rates, and fewer serious adverse events in genetically predisposed individuals. The aim here is to explore the contemporary scientific literature related to the vaccinomic and adversomic aspects of the three most-controversial vaccines: those against hepatitis B, against measles, mumps, and rubella, and against human Papilloma virus. We provide detailed information on the genes that encode human leukocyte antigen, cytokines and their receptors, and transcription factors and regulators associated with the efficacy and safety of the Hepatitis B and Measles, Mumps and Rubella virus vaccines. We also investigate the future prospects of vaccinomics and adversomics of a COVID-19 vaccine, which might represent the fastest development of a vaccine ever.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 disease in China. So far, no vaccine has licensed to protect against infection with COVID-19, therefore an effective COVID-19 vaccine needed. The aim of this study was to predict antigenic peptides of SARS-CoV-2 for designing the COVID-19 vaccine using immunoinformatic analysis. In this study, T and B-cell epitopes of S protein were predicted and screened based on the antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. The epitopes were joined by the appropriate linker. LT-IIc as an adjuvant was attached to the end of the structure. The secondary and 3D structure of the vaccine was predicted. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The proposed vaccine's binding affinity to the HLA-A11:01 and HLA-DRB1_01:01 molecule was evaluated by molecular docking. Using molecular dynamics, the stability of vaccine-HLA complexes was also evaluated. Finally, in silico gene cloning was performed in the pET30a (+) vector. The findings suggest that the current vaccine may be a promising vaccine to prevent SARS-CoV-2 infection.

Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.

Vaccine confidence: the keys to restoring trust

During the 20^th century, the discovery of modern vaccines and ensuing mass vaccination dramatically decreased the incidence of many infectious diseases and in some cases eliminated them. Despite this, we are now witnessing a decrease in vaccine confidence that threatens to reverse the progress made. Considering the different extents of low vaccine confidence in different countries of the world, both developed and developing, we aim to contribute to the discussion of the reasons for this, and to propose some viable scientific solutions to build or help restore vaccine confidence worldwide.

Reverse Vaccinology and Its Applications

The application of the fields of pharmacogenomics and pharmacogenetics to vaccine design, profoundly combined with bioinformatics, has been recently termed "vaccinomics." The enormous amount of information generated by whole genome sequencing projects and the rise of bioinformatics has triggered the birth of a new era of vaccine research and development, leading to a "third generation" of vaccines, which are based on the application of vaccinomics science to vaccinology. The first example of such an approach is reverse vaccinology. Reverse vaccinology reduces the period of vaccine target detection and evaluation to 1-2 years. This approach targets the genomic sequence and predicts those antigens that are most likely to be vaccine candidates. This approach allows not only the identification of all the antigens obtained by the previous methods but also the discovery of new antigens that work on a totally different paradigm. Hence this method helps in the discovery of novel mechanisms of immune intervention. Epitope-based immune-derived vaccines (IDV) are generally considered to be safe when compared to other vectored or attenuated live vaccines. Epitope-based IDV may also provide essential T-cell help for antibody-directed vaccines. Such vaccines may have a significant advantage over earlier vaccine design approaches, as the cautious assortment of the components may diminish.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.

Current perspectives in assessing humoral immunity after measles vaccination

INTRODUCTION

Repeated measles outbreaks in countries with relatively high vaccine coverage are mainly due to failure to vaccinate and importation; however, cases in immunized individuals exist raising questions about suboptimal measles vaccine-induced humoral immunity and/or waning immunity in a low measles-exposure environment.

AREAS COVERED

The plaque reduction neutralization measurement of functional measles-specific antibodies correlates with protection is the gold standard in measles serology, but it does not assess cellular-immune or other parameters that may be associated with durable and/or protective immunity after vaccination. Additional correlates of protection and long-term immunity and new determinants/signatures of vaccine responsiveness such as specific CD46 and IFI44L genetic variants associated with neutralizing antibody titers after measles vaccination are under investigation. Current and future systems biology studies, coupled with new technology/assays and analytical approaches, will lead to an increasingly sophisticated understanding of measles vaccine-induced humoral immunity and will identify 'signatures' of protective and durable immune responses.

EXPERT OPINION

This will translate into the development of highly predictive assays of measles vaccine efficacy, effectiveness, and durability for prospective identification of potential low/non-responders and susceptible individuals who require additional vaccine doses. Such new advances may drive insights into the development of new/improved vaccine formulations and delivery systems.

An Immunopharmacoinformatics Approach in Development of Vaccine and Drug Candidates for West Nile Virus

An outbreak of West Nile Virus (WNV) like the recent Ebola can be more epidemic and fatal to public health throughout the world. WNV possesses utmost threat as no vaccine or drug is currently available for its treatment except mosquito control. The current study applied the combined approach of immunoinformatics and pharmacoinformatics to design potential epitope-based vaccines and drug candidates against WNV. By analyzing the whole proteome of 2994 proteins, the WNV envelope glycoprotein was selected as a therapeutic target based on its highest antigenicity. After proper assessment “KSFLVHREW” and “ITPSAPSYT” were found to be the most potential T and B-cell epitopes, respectively. Besides, we have designed and validated four novel drugs from a known WNV inhibitor, AP30451 by adopting computational approaches. Toxicity assessment and drug score confirmed the effectiveness of these drug candidates. This in silico research might greatly facilitate the wet lab experiments to develop vaccine and drug against WNV.

Big Data's Role in Precision Public Health

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

Vaccinomics Approach for Designing Potential Peptide Vaccine by Targeting Shigella spp. Serine Protease Autotransporter Subfamily Protein SigA

Shigellosis, a bacillary dysentery, is closely associated with diarrhoea in human and causes infection of 165 million people worldwide per year. Casein-degrading serine protease autotransporter of enterobacteriaceae (SPATE) subfamily protein SigA, an outer membrane protein, exerts both cytopathic and enterotoxic effects especially cytopathic to human epithelial cell type-2 (HEp-2) and is shown to be highly immunogenic. In the present study, we have tried to impose the vaccinomics approach for designing a common peptide vaccine candidate against the immunogenic SigA of Shigella spp. At first, 44 SigA proteins from different variants of S. flexneri, S. dysenteriae, S. boydii, and S. sonnei were assessed to find the most antigenic protein. We retrieved 12 peptides based on the highest score for human leukocyte antigen (HLA) supertypes analysed by NetCTL. Initially, these peptides were assessed for the affinity with MHC class I and class II alleles, and four potential core epitopes VTARAGLGY, FHTVTVNTL, HTTWTLTGY, and IELAGTLTL were selected. From these, FHTVTVNTL and IELAGTLTL peptides were shown to have 100% conservancy. Finally, IELAGTLTL was shown to have the highest population coverage (83.86%) among the whole world population. In vivo study of the proposed epitope might contribute to the development of functional and unique widespread vaccine, which might be an operative alleyway to thwart dysentery from the world.

Pharmacogenetics and the treatment of asthma

Heterogeneity defines both the natural history of asthma as well as patient's response to treatment. Pharmacogenomics contribute to understand the genetic basis of drug response and thus to define new therapeutic targets or molecular biomarkers to evaluate treatment effectiveness. This review is initially focused on different genes so far involved in the pharmacological response to asthma treatment. Specific considerations regarding allergic asthma, the pharmacogenetics aspects of polypharmacy and the application of pharmacogenomics in new drugs in asthma will also be addressed. Finally, future perspectives related to epigenetic regulatory elements and the potential impact of systems biology in pharmacogenetics of asthma will be considered.

Prediction of promiscuous T cell epitopes in RNA dependent RNA polymerase of Chikungunya virus

OBJECTIVE

To explore RNA dependent RNA polymerase of Chikungunya virus (CHIKV) and develop T cell based epitopes with high antigenicity and good binding affinity for the human leukocyte antigen (HLA) classes as targets for epitopes based CHIKV vaccine.

METHODS

In this study we downloaded 371 non-structural protein 4 protein sequences of CHIKV belonging to different regions of the world from the US National Institute of Allergy and Infectious Diseases (NIAID) virus pathogen resource database. All the sequences were aligned by using CLUSTALW software and a consensus sequence was developed by using Uni Pro U Gene Software version 1.2.1. Propred I and Propred software were used to predict HLA I and HLA II binding promiscuous epitopes from the consensus sequence of non-structural protein 4 protein. The predicted epitopes were analyzed to determine their antigenicity through Vaxijen server version 2.0. All the HLA I binding epitopes were scanned to determine their immunogenic potential through the Immune Epitope Database (IEDB). All the predicted epitopes of our study were fed to IEDB database to determine whether they had been tested earlier.

RESULTS

Twenty two HLA class II epitopes and eight HLA class I epitopes were predicted. The promiscuous epitopes WMNMEVKII at position 486-494 and VRRLNAVLL at 331-339 were found to bind with 37 and 36 of the 51 HLA class II alleles respectively. Epitope MANRSRYQS at position 58-66 and epitopes YQSRKVENM at positions 64-72 were predicted to bind with 12 and 9 HLA II alleles with antigenicity scores of 0.754 9 and 1.013 0 respectively. Epitope YSPPINVRL was predicted to bind 18 HLA I alleles and its antigenicity score was 1.425 9 and immunogenicity score was 0.173 83. This epitope is very useful in the preparation of a universal vaccine against CHIKV infection.

CONCLUSIONS

Epitopes reported in this study showed promiscuity, antigenicity as well as good binding affinity for the HLA classes. These epitopes will provide the baseline for development of efficacious vaccine for CHIKV.

Effects of interleukin-4 and interleukin-12B gene polymorphisms on hepatitis B virus vaccination

 Approximately 10% of individuals do not respond to hepatitis B virus (HBV) vaccination, i.e. non-responders (NRs). We aimed to investigate the association of interleukin (IL)-4 and IL-12B gene polymorphisms with responsiveness to the HBV vaccine in Korean infants. Among 300 healthy infants (9-12 month), SNPs for the IL-4 gene (rs2243250, rs2070874, and rs2227284) and for the IL-12B gene (rs3213094 and rs17860508) were compared between subgroups in terms of the response to HBV vaccination. The percentages of NRs (< 10 mIU/mL), low-titer responders (LRs, 10-100 mIU/mL), and high-titer responders (HRs, ≥ 100 mIU/mL) were 20.3%, 37.7% and 42.0%, respectively. No SNPs differed in frequency between NRs and responders or between LRs and HRs. We divided the subjects into two groups according to the time interval from the 3rd dose of HBV vaccination to Ab quantification: > 6 months from the 3rd dose (n = 87) and ≤ 6 months from the 3rd dose (n = 213). In the ≤ 6 month subjects, rs2243250C and rs2227284G were significantly frequent in the lower-titer individuals (NRs + LR) than HRs (40.1 vs. 25.9%, p = 0.014 and 45.1 vs. 33.0%, p = 0.018, respectively), and the rs2243250C and rs2227284G frequencies were significantly different among the three subgroups (13.2 vs. 26.9 vs. 25.9%, p = 0.040 and 15.5 vs. 29.6 vs. 33.0%, p = 0.038, respectively). In conclusion, those results suggest that IL-4 gene polymorphisms may play a role in the response to the HBV vaccine in Korean infants.

Ontology-Based Vaccine Adverse Event Representation and Analysis

Vaccine is the one of the greatest inventions of modern medicine that has contributed most to the relief of human misery and the exciting increase in life expectancy. In 1796, an English country physician, Edward Jenner, discovered that inoculating mankind with cowpox can protect them from smallpox (Riedel S, Edward Jenner and the history of smallpox and vaccination. Proceedings (Baylor University. Medical Center) 18(1):21, 2005). Based on the vaccination worldwide, we finally succeeded in the eradication of smallpox in 1977 (Henderson, Vaccine 29:D7-D9, 2011). Other disabling and lethal diseases, like poliomyelitis and measles, are targeted for eradication (Bonanni, Vaccine 17:S120-S125, 1999).Although vaccine development and administration are tremendously successful and cost-effective practices to human health, no vaccine is 100% safe for everyone because each person reacts to vaccinations differently given different genetic background and health conditions. Although all licensed vaccines are generally safe for the majority of people, vaccinees may still suffer adverse events (AEs) in reaction to various vaccines, some of which can be serious or even fatal (Haber et al., Drug Saf 32(4):309-323, 2009). Hence, the double-edged sword of vaccination remains a concern.To support integrative AE data collection and analysis, it is critical to adopt an AE normalization strategy. In the past decades, different controlled terminologies, including the Medical Dictionary for Regulatory Activities (MedDRA) (Brown EG, Wood L, Wood S, et al., Drug Saf 20(2):109-117, 1999), the Common Terminology Criteria for Adverse Events (CTCAE) (NCI, The Common Terminology Criteria for Adverse Events (CTCAE). Available from: http://evs.nci.nih.gov/ftp1/CTCAE/About.html . Access on 7 Oct 2015), and the World Health Organization (WHO) Adverse Reactions Terminology (WHO-ART) (WHO, The WHO Adverse Reaction Terminology - WHO-ART. Available from: https://www.umc-products.com/graphics/28010.pdf ), have been developed with a specific aim to standardize AE categorization. However, these controlled terminologies have many drawbacks, such as lack of textual definitions, poorly defined hierarchies, and lack of semantic axioms that provide logical relations among terms. A biomedical ontology is a set of consensus-based and computer and human interpretable terms and relations that represent entities in a specific biomedical domain and how they relate each other. To represent and analyze vaccine adverse events (VAEs), our research group has initiated and led the development of a community-based ontology: the Ontology of Adverse Events (OAE) (He et al., J Biomed Semant 5:29, 2014). The OAE has been found to have advantages to overcome the drawbacks of those controlled terminologies (He et al., Curr Pharmacol Rep :1-16. doi:10.1007/s40495-016-0055-0, 2014). By expanding the OAE and the community-based Vaccine Ontology (VO) (He et al., VO: vaccine ontology. In The 1st International Conference on Biomedical Ontology (ICBO-2009). Nature Precedings, Buffalo. http://precedings.nature.com/documents/3552/version/1 ; J Biomed Semant 2(Suppl 2):S8; J Biomed Semant 3(1):17, 2009; Ozgur et al., J Biomed Semant 2(2):S8, 2011; Lin Y, He Y, J Biomed Semant 3(1):17, 2012), we have also developed the Ontology of Vaccine Adverse Events (OVAE) to represent known VAEs associated with licensed vaccines (Marcos E, Zhao B, He Y, J Biomed Semant 4:40, 2013).In this book chapter, we will first introduce the basic information of VAEs, VAE safety surveillance systems, and how to specifically query and analyze VAEs using the US VAE database VAERS (Chen et al., Vaccine 12(10):960-960, 1994). In the second half of the chapter, we will introduce the development and applications of the OAE and OVAE. Throughout this chapter, we will use the influenza vaccine Flublok as the vaccine example to launch the corresponding elaboration (Huber VC, McCullers JA, Curr Opin Mol Ther 10(1):75-85, 2008). Flublok is a recombinant hemagglutinin influenza vaccine indicated for active immunization against disease caused by influenza virus subtypes A and type B. On January 16, 2013, Flublok was approved by the FDA for the prevention of seasonal influenza in people 18 years and older in the USA. Now, more than 3 years later, an exploration of the reported AEs associated with this vaccine is urgently needed.

From ZikV genome to vaccine: in silico approach for the epitope-based peptide vaccine against Zika virus envelope glycoprotein

Zika virus (ZikV) has emerged as a potential threat to human health worldwide. A member of the Flaviviridae, ZikV is transmitted to humans by mosquitoes. It is related to other pathogenic vector-borne flaviviruses including dengue, West Nile and Japanese encephalitis viruses, but produces a comparatively mild disease in humans. As a result of its epidemic outbreak and the lack of potential medication, there is a need for improved vaccine/drugs. Computational techniques will provide further information about this virus. Comparative analysis of ZikV genomes should lead to the identification of the core characteristics that define a virus family, as well as its unique properties, while phylogenetic analysis will show the evolutionary relationships and provide clues about the protein's ancestry. Envelope glycoprotein of ZikV was obtained from a protein database and the most immunogenic epitope for T cells and B cells involved in cell-mediated immunity, whereas B cells are primarily responsible for humoral immunity. We mainly focused on MHC class I potential peptides. YRIMLSVHG, VLIFLSTAV and MMLELDPPF, GLDFSDLYY are the most potent peptides predicted as epitopes for CD4⁺ and CD8⁺ T cells, respectively, whereas MMLELDPPF and GLDFSDLYY had the highest pMHC-I immunogenicity score and these are further tested for interaction against the HLA molecules, using in silico docking techniques to verify the binding cleft epitope. However, this is an introductory approach to design an epitope-based peptide vaccine against ZikV; we hope that this model will be helpful in designing and predicting novel vaccine candidates.

Therapeutics Insight with Inclusive Immunopharmacology Explication of Human Rotavirus A for the Treatment of Diarrhea

Rotavirus is the most common cause of severe infant and childhood diarrhea worldwide, and the morbidity and mortality rate is going to be outnumbered in developing countries like Bangladesh. To mitigate this substantial burden of disease, new therapeutics such as vaccine and drug are swiftly required against rotavirus. The present therapeutics insight study was performed with comprehensive immunoinformatics and pharmacoinformatics approach. T and B-cell epitopes were assessed in the conserved region of outer capsid protein VP4 among the highly reviewed strains from different countries including Bangladesh. The results suggest that epitope SU1 (TLKNLNDNY) could be an ideal candidate among the predicted five epitopes for both T and B-cell epitopes for the development of universal vaccine against rotavirus. This research also suggests five novel drug compounds from medicinal plant Rhizophora mucronata Lamk. for better therapeutics strategies against rotavirus diarrhea based on 3D structure building, pharmacophore, ADMET, and QSAR properties. The exact mode of action between drug compounds and target protein VP4 were revealed by molecular docking analysis. Drug likeness and oral bioavailability further confirmed the effectiveness of the proposed drugs against rotavirus diarrhea. This study might be implemented for experimental validation to facilitate the novel vaccine and drug design.

A Brief Review of Computer-Assisted Approaches to Rational Design of Peptide Vaccines

The growing incidences of new viral diseases and increasingly frequent viral epidemics have strained therapeutic and preventive measures; the high mutability of viral genes puts additional strains on developmental efforts. Given the high cost and time requirements for new drugs development, vaccines remain as a viable alternative, but there too traditional techniques of live-attenuated or inactivated vaccines have the danger of allergenic reactions and others. Peptide vaccines have, over the last several years, begun to be looked on as more appropriate alternatives, which are economically affordable, require less time for development and hold the promise of multi-valent dosages. The developments in bioinformatics, proteomics, immunogenomics, structural biology and other sciences have spurred the growth of vaccinomics where computer assisted approaches serve to identify suitable peptide targets for eventual development of vaccines. In this mini-review we give a brief overview of some of the recent trends in computer assisted vaccine development with emphasis on the primary selection procedures of probable peptide candidates for vaccine development.

Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research

Compared with controlled terminologies (e.g., MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network (i.e., OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

Variability in Humoral Immunity to Measles Vaccine: New Developments

Despite the existence of an effective measles vaccine, resurgence in measles cases in the USA and across Europe has occurred, including in individuals vaccinated with two doses of the vaccine. Host genetic factors result in inter-individual variation in measles vaccine-induced antibodies, and play a role in vaccine failure. Studies have identified HLA (human leukocyte antigen) and non-HLA genetic influences that individually or jointly contribute to the observed variability in the humoral response to vaccination among healthy individuals. In this exciting era, new high-dimensional approaches and techniques including vaccinomics, systems biology, GWAS, epitope prediction and sophisticated bioinformatics/statistical algorithms provide powerful tools to investigate immune response mechanisms to the measles vaccine. These might predict, on an individual basis, outcomes of acquired immunity post measles vaccination.

Single nucleotide polymorphisms/haplotypes associated with multiple rubella-specific immune response outcomes post-MMR immunization in healthy children

The observed heterogeneity in rubella-specific immune response phenotypes post-MMR vaccination is thought to be explained, in part, by inter-individual genetic variation. In this study, single nucleotide polymorphisms (SNPs) and multiple haplotypes in several candidate genes were analyzed for associations with more than one rubella-specific immune response outcome, including secreted IFN-γ, secreted IL-6, and neutralizing antibody titers. Overall, we identified 23 SNPs in 10 different genes that were significantly associated with at least two rubella-specific immune responses. Of these SNPs, we detected eight in the PVRL3 gene, five in the PVRL1 gene, one in the TRIM22 gene, two in the IL10RB gene, two in the TLR4 gene, and five in other genes (PVR, ADAR, ZFP57, MX1, and BTN2A1/BTN3A3). The PVRL3 gene haplotype GACGGGGGCAGCAAAAAGAAGAGGAAAGAACAA was significantly associated with both higher IFN-γ secretion (t-statistic 4.43, p < 0.0001) and higher neutralizing antibody titers (t-statistic 3.14, p = 0.002). Our results suggest that there is evidence of multigenic associations among identified gene SNPs and that polymorphisms in these candidate genes contribute to the overall observed differences between individuals in response to live rubella virus vaccine. These results will aid our understanding of mechanisms behind rubella-specific immune response to MMR vaccine and influence the development of vaccines in the future.

Highly conserved regions in Ebola virus RNA dependent RNA polymerase may be act as a universal novel peptide vaccine target: a computational approach

Purpose

Ebola virus (EBOV) is such kind of virus which is responsible for 23,825 cases and 9675 deaths worldwide only in 2014 and with an average diseases fatality rate between 25 % and 90 %. Although, medical technology has tried to handle the problems, there is no Food and Drug Administration (FDA)-approved therapeutics or vaccines available for the prevention, post exposure, or treatment of Ebola virus disease (EVD).

Methods

In the present study, we used the immunoinformatics approach to design a potential epitope-based vaccine against the RNA-dependent RNA polymerase-L of EBOV. BioEdit v7.2.3 sequence alignment editor, Jalview v2 and CLC Sequence Viewer v7.0.2 were used for the initial sequence analysis for securing the conservancy from the sequences. Later the Immune Epitope Database and Analysis Resource (IEDB-AR) was used for the identification of T-cell and B-cellepitopes associated with type I and II major histocompatibility complex molecules analysis. Finally, the population coverage analysis was employed.

Results

The core epitope “FRYEFTAPF” was found to be the most potential one, with 100 % conservancy among all the strains of EBOV. It also interacted with both type I and II major histocompatibility complex molecules and is considered as nonallergenic in nature. Finally, with impressive cumulative population coverage of 99.87 % for the both MHC-I and MHC-II class throughout the world population was found for the proposed epitope.

Conclusion

To end, the projected peptide gave us a solid stand to propose for vaccine consideration and that might be experimented for its potency in eliciting immunity through humoral and cell mediated immune responses in vitro and in vivo.

Electronic supplementary material

The online version of this article (doi:10.1186/s40203-015-0011-4) contains supplementary material, which is available to authorized users.

Adversomics: a new paradigm for vaccine safety and design

Despite the enormous population benefits of routine vaccination, vaccine adverse events (AEs) and reactions, whether real or perceived, have posed one of the greatest barriers to vaccine acceptance--and thus to infectious disease prevention--worldwide. A truly integrated clinical, translational, and basic science approach is required to understand the mechanisms behind vaccine AEs, predict them, and then apply this knowledge to new vaccine design approaches that decrease, or avoid, these events. The term 'adversomics' was first introduced in 2009 and refers to the study of vaccine adverse reactions using immunogenomics and systems biology approaches. In this review, we present the current state of adversomics research, review known associations and mechanisms of vaccine AEs/reactions, and outline a plan for the further development of this emerging research field.

[Proteomics in infectious diseases]

Infectious diseases have a high incidence in the population, causing a major impact on global health. In vitro culture of microorganisms is the first technique applied for infection diagnosis which is laborious and time consuming. In recent decades, efforts have been focused on the applicability of "Omics" sciences, highlighting the progress provided by proteomic techniques in the field of infectious diseases. This review describes the management, processing and analysis of biological samples for proteomic research.

Identification of highly conserved regions in L-segment of Crimean-Congo hemorrhagic fever virus and immunoinformatic prediction about potential novel vaccine

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne zoonotic viral disease with a disease fatality rate between 15% and 70%. Despite the wide range of distribution, the virus (CCHFV) is basically endemic in Africa, Asia, eastern Europe, and the Middle East. Acute febrile illness associated with petechiae, disseminated intravascular coagulation, and multiple-organ failure are the main symptoms of the disease. With all these fatal effects, CCHFV is considered a huge threat as no successful therapeutic approach is currently available for the treatment of this disease. In the present study, we have used the immunoinformatics approach to design a potential epitope-based vaccine against the RNA-dependent RNA polymerase-L of CCHFV. Both the T-cell and B-cell epitopes were assessed, and the epitope "DCSSTPPDR" was found to be the most potential one, with 100% conservancy among all the strains of CCHFV. The epitope was also found to interact with both type I and II major histocompatibility complex molecules and is considered nonallergenic as well. In vivo study of our proposed peptide is advised for novel universal vaccine production, which might be an effective path to prevent CCHF disease.

Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach

Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccine designed for HCoV. In this study, a computational approach was adopted to identify a multiepitope vaccine candidate against this virus that could be suitable to trigger a significant immune response. Sequences of the spike proteins were collected from a protein database and analyzed with an in silico tool, to identify the most immunogenic protein. Both T cell immunity and B cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-mediated immunity. The peptide sequence from 88–94 amino acids and the sequence KSSTGFVYF were found as the most potential B cell and T cell epitopes, respectively. Furthermore, conservancy analysis was also done using in silico tools and showed a conservancy of 64.29% for all epitopes. The peptide sequence could interact with as many as 16 human leukocyte antigens (HLAs) and showed high cumulative population coverage, ranging from 75.68% to 90.73%. The epitope was further tested for binding against the HLA molecules, using in silico docking techniques, to verify the binding cleft epitope interaction. The allergenicity of the epitopes was also evaluated. This computational study of design of an epitope-based peptide vaccine against HCoVs allows us to determine novel peptide antigen targets in spike proteins on intuitive grounds, albeit the preliminary results thereof require validation by in vitro and in vivo experiments.

Ontology-supported research on vaccine efficacy, safety and integrative biological networks

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

HLA genotypes and rubella vaccine immune response: additional evidence

Recent population-based studies have demonstrated the genetic heritability of rubella vaccine response and assessed that the HLA system may explain about 20% of the inter-individual variance in humoral immune response to this vaccine. Our earlier studies compared HLA allelic associations with rubella vaccine-specific antibodies between two smaller cohorts of healthy Rochester, MN, children (346 and 396 subjects) after two doses of rubella-containing vaccine. This study found that specific HLA alleles were consistently associated with rubella-specific antibody titers (B*27:05, DPA1*02:01, and DPB1*04:01 alleles). The current study examined HLA associations in an independent larger cohort of 1012 healthy San Diego, CA, subjects (age 19-40 years) after rubella vaccine in order to replicate our previous findings in the Rochester subjects. Two HLA associations of comparable magnitudes were consistently observed between B*27:05 (median NT50 Rochester cohort 48.9, p=0.067; San Diego cohort 54.8, p=0.047) and DPB1*04:01 (median NT50 Rochester cohort 61.6, p<0.001; San Diego cohort 70.8, p=0.084) alleles and rubella virus-neutralizing antibody titers. Additional HLA alleles resulted in consistent effects on IL-6 production in both cohorts, but did not meet criteria for statistical significance. Our data suggest these HLA alleles play a role in rubella vaccine-induced immunity and provide the basis for future studies that may explain the mechanism(s) by which these HLA polymorphisms affect immune responses to rubella vaccine.

The ontology of genetic susceptibility factors (OGSF) and its application in modeling genetic susceptibility to vaccine adverse events

Background

Due to human variations in genetic susceptibility, vaccination often triggers adverse events in a small population of vaccinees. Based on our previous work on ontological modeling of genetic susceptibility to disease, we developed an Ontology of Genetic Susceptibility Factors (OGSF), a biomedical ontology in the domain of genetic susceptibility and genetic susceptibility factors. The OGSF framework was then applied in the area of vaccine adverse events (VAEs).

Results

OGSF aligns with the Basic Formal Ontology (BFO). OGSF defines ‘genetic susceptibility’ as a subclass of BFO:disposition and has a material basis ‘genetic susceptibility factor’. The ‘genetic susceptibility to pathological bodily process’ is a subclasses of ‘genetic susceptibility’. A VAE is a type of pathological bodily process. OGSF represents different types of genetic susceptibility factors including various susceptibility alleles (e.g., SNP and gene). A general OGSF design pattern was developed to represent genetic susceptibility to VAE and associated genetic susceptibility factors using experimental results in genetic association studies. To test and validate the design pattern, two case studies were populated in OGSF. In the first case study, human gene allele DBR*15:01 is susceptible to influenza vaccine Pandemrix-induced Multiple Sclerosis. The second case study reports genetic susceptibility polymorphisms associated with systemic smallpox VAEs. After the data of the Case Study 2 were represented using OGSF-based axioms, SPARQL was successfully developed to retrieve the susceptibility factors stored in the populated OGSF. A network of data from the Case Study 2 was constructed by using ontology terms and individuals as nodes and ontology relations as edges. Different social network analys is (SNA) methods were then applied to verify core OGSF terms. Interestingly, a SNA hub analysis verified all susceptibility alleles of SNPs and a SNA closeness analysis verified the susceptibility genes in Case Study 2. These results validated the proper OGSF structure identified different ontology aspects with SNA methods.

Conclusions

OGSF provides a verified and robust framework for representing various genetic susceptibility types and genetic susceptibility factors annotated from experimental VAE genetic association studies. The RDF/OWL formulated ontology data can be queried using SPARQL and analyzed using centrality-based network analysis methods.