HIV vaccine development by computer assisted design: the GAIA vaccine

The Question of HIV Vaccine: Why Is a Solution Not Yet Available?

Ever since its discovery, human immunodeficiency virus type 1 (HIV-1) infection has remained a significant public health concern. The number of HIV-1 seropositive individuals currently stands at 40.1 million, yet definitive treatment for the virus is still unavailable on the market. Vaccination has proven to be a potent tool in combating infectious diseases, as evidenced by its success against other pathogens. However, despite ongoing efforts and research, the unique viral characteristics have prevented the development of an effective anti-HIV-1 vaccine. In this review, we aim to provide an historical overview of the various approaches attempted to create an effective anti-HIV-1 vaccine. Our objective is to explore the reasons why specific methods have failed to induce a protective immune response and to analyze the different modalities of immunogen presentation. This trial is registered with NCT05414786, NCT05471076, NCT04224701, and NCT01937455.

An Overview of Current Uses and Future Opportunities for Computer-Assisted Design of Vaccines for Neglected Tropical Diseases

Neglected tropical diseases are infectious diseases that impose high morbidity and mortality rates over 1.5 billion people worldwide. Originally restricted to tropical and subtropical regions, changing climate conditions have increased their potential to emerge elsewhere. Control of their impact suffers from shortages like poor epidemiological surveillance or irregular drug distribution, and some NTDs still lack of appropriate diagnostics and/or efficient therapeutics. For these, availability of vaccines to prevent new infections, or the worsening of those already established, would mean a major breakthrough. However, only dengue and rabies count with approved vaccines at present. Herein, we review the state-of-the-art of vaccination strategies for NTDs, setting the focus on third generation vaccines and the concept of reverse vaccinology. Its capability to address pathogens´ biological complexity, likely contributing to save developmental costs is discussed. The use of computational tools is a fundamental aid to analyze increasingly large datasets aimed at designing vaccine candidates with the highest, possibly, opportunities to succeed. Ultimately, we identify and analyze those studies that took an in silico approach to find vaccine candidates, and experimentally assessed their immunogenicity and/or protection capabilities.

Better Epitope Discovery, Precision Immune Engineering, and Accelerated Vaccine Design Using Immunoinformatics Tools

Computational vaccinology includes epitope mapping, antigen selection, and immunogen design using computational tools. Tools that facilitate the in silico prediction of immune response to biothreats, emerging infectious diseases, and cancers can accelerate the design of novel and next generation vaccines and their delivery to the clinic. Over the past 20 years, vaccinologists, bioinformatics experts, and advanced programmers based in Providence, Rhode Island, USA have advanced the development of an integrated toolkit for vaccine design called iVAX, that is secure and user-accessible by internet. This integrated set of immunoinformatic tools comprises algorithms for scoring and triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, re-engineering or eliminating regulatory T cell epitopes, and re-designing antigens to induce immunogenicity and protection against disease for humans and livestock. Commercial and academic applications of iVAX have included identifying immunogenic T cell epitopes in the development of a T-cell based human multi-epitope Q fever vaccine, designing novel influenza vaccines, identifying cross-conserved T cell epitopes for a malaria vaccine, and analyzing immune responses in clinical vaccine studies. Animal vaccine applications to date have included viral infections of pigs such as swine influenza A, PCV2, and African Swine Fever. “Rapid-Fire” applications for biodefense have included a demonstration project for Lassa Fever and Q fever. As recent infectious disease outbreaks underscore the significance of vaccine-driven preparedness, the integrated set of tools available on the iVAX toolkit stand ready to help vaccine developers deliver genome-derived, epitope-driven vaccines.

Immunoinformatics and Vaccine Development: An Overview

The use of vaccines have resulted in a remarkable improvement in global health. It has saved several lives, reduced treatment costs and raised the quality of animal and human lives. Current traditional vaccines came empirically with either vague or completely no knowledge of how they modulate our immune system. Even at the face of potential vaccine design advance, immune-related concerns (as seen with specific vulnerable populations, cases of emerging/re-emerging infectious disease, pathogens with complex lifecycle and antigenic variability, need for personalized vaccinations, and concerns for vaccines' immunological safety -specifically vaccine likelihood to trigger non-antigen-specific responses that may cause autoimmunity and vaccine allergy) are being raised. And these concerns have driven immunologists toward research for a better approach to vaccine design that will consider these challenges. Currently, immunoinformatics has paved the way for a better understanding of some infectious disease pathogenesis, diagnosis, immune system response and computational vaccinology. The importance of this immunoinformatics in the study of infectious diseases is diverse in terms of computational approaches used, but is united by common qualities related to host–pathogen relationship. Bioinformatics methods are also used to assign functions to uncharacterized genes which can be targeted as a candidate in vaccine design and can be a better approach toward the inclusion of women that are pregnant into vaccine trials and programs. The essence of this review is to give insight into the need to focus on novel computational, experimental and computation-driven experimental approaches for studying of host–pathogen interactions and thus making a case for its use in vaccine development.

Highly conserved influenza T cell epitopes induce broadly protective immunity

Influenza world-wide causes significant morbidity and mortality annually, and more severe pandemics when novel strains evolve to which humans are immunologically naïve. Because of the high viral mutation rate, new vaccines must be generated based on the prevalence of circulating strains every year. New approaches to induce more broadly protective immunity are urgently needed. Previous research has demonstrated that influenza-specific T cells can provide broadly heterotypic protective immunity in both mice and humans, supporting the rationale for developing a T cell-targeted universal influenza vaccine. We used state-of-the art immunoinformatic tools to identify putative pan-HLA-DR and HLA-A2 supertype-restricted T cell epitopes highly conserved among > 50 widely diverse influenza A strains (representing hemagglutinin types 1, 2, 3, 5, 7 and 9). We found influenza peptides that are highly conserved across influenza subtypes that were also predicted to be class I epitopes restricted by HLA-A2. These peptides were found to be immunoreactive in HLA-A2 positive but not HLA-A2 negative individuals. Class II-restricted T cell epitopes that were highly conserved across influenza subtypes were identified. Human CD4⁺ T cells were reactive with these conserved CD4 epitopes, and epitope expanded T cells were responsive to both H1N1 and H3N2 viruses. Dendritic cell vaccines pulsed with conserved epitopes and DNA vaccines encoding these epitopes were developed and tested in HLA transgenic mice. These vaccines were highly immunogenic, and more importantly, vaccine-induced immunity was protective against both H1N1 and H3N2 influenza challenges. These results demonstrate proof-of-principle that conserved T cell epitopes expressed by widely diverse influenza strains can induce broadly protective, heterotypic influenza immunity, providing strong support for further development of universally relevant multi-epitope T cell-targeting influenza vaccines.

HLA-directed bioinformatics approach for genome-wide mapping of dengue CTL epitopes

Aim: In silico approach was used to predict cytotoxic T lymphocyte (CTL) epitopes from the proteome of all four dengue serotypes. Methods: The immune epitope database analysis resource was used to analyze the CTL epitopes of dengue serotypes. The prediction of epitopes was done against nine high frequency HLA class I alleles occurring worldwide. Results: A total of 2784 epitopes were predicted from all four dengue virus proteomes. Immune epitope database analysis resource tool predicted 202 epitopes as positive for immunogenecity. A total of 39 of 257 consensus epitopes predicted were present in all four serotypes. This study identified nine new class I-restricted epitopes. Conclusion: Mapping of these potentially immunogenic dengue epitopes paves the way for future investigation of their utility as vaccine candidates to prevent or treat dengue virus infections.

HLA based selection of epitopes offers a potential window of opportunity for vaccine design against HIV

The pace of progression to AIDS after HIV infection varies from individual to individual. While some individuals develop AIDS quickly, others are protected from the onset of disease for more than a decade (elite controllers and long term non-progressors). The mechanisms of protection are not yet clearly understood, though various factors including host genetics, immune components and virus attenuation have been elucidated partly. The influence of HLA alleles on HIV-1 infection and disease outcome has been studied extensively. Several HLA alleles are known to be associated with resistance to infection or delayed progression to AIDS after infection. Similarly, certain HLA alleles are reported to be associated with rapid progression to disease. Since HLA alleles influence the outcome of HIV infection differentially, selection of epitopes specifically recognized by protective alleles could serve asa rational means for HIV vaccine design. In this review article, we discuss existing knowledge on HLA alleles and their association with resistance/susceptibility to HIV and its relevance to vaccine design.

An Approach for a Synthetic CTL Vaccine Design against Zika Flavivirus Using Class I and Class II Epitopes Identified by Computer Modeling

The threat posed by severe congenital abnormalities related to Zika virus (ZKV) infection during pregnancy has turned development of a ZKV vaccine into an emergency. Recent work suggests that the cytotoxic T lymphocyte (CTL) response to infection is an important defense mechanism in response to ZKV. Here, we develop the rationale and strategy for a new approach to developing cytotoxic T lymphocyte (CTL) vaccines for ZKV flavivirus infection. The proposed approach is based on recent studies using a protein structure computer model for HIV epitope selection designed to select epitopes for CTL attack optimized for viruses that exhibit antigenic drift. Because naturally processed and presented human ZKV T cell epitopes have not yet been described, we identified predicted class I peptide sequences on ZKV matching previously identified DNV (Dengue) class I epitopes and by using a Major Histocompatibility Complex (MHC) binding prediction tool. A subset of those met the criteria for optimal CD8+ attack based on physical chemistry parameters determined by analysis of the ZKV protein structure encoded in open source Protein Data File (PDB) format files. We also identified candidate ZKV epitopes predicted to bind promiscuously to multiple HLA class II molecules that could provide help to the CTL responses. This work suggests that a CTL vaccine for ZKV may be possible even if ZKV exhibits significant antigenic drift. We have previously described a microsphere-based CTL vaccine platform capable of eliciting an immune response for class I epitopes in mice and are currently working toward in vivo testing of class I and class II epitope delivery directed against ZKV epitopes using the same microsphere-based vaccine.

An immunoinformatics-derived DNA vaccine encoding human class II T cell epitopes of Ebola virus, Sudan virus, and Venezuelan equine encephalitis virus is immunogenic in HLA transgenic mice

Immunoinformatics tools were used to predict human leukocyte antigen (HLA) class II-restricted T cell epitopes within the envelope glycoproteins and nucleocapsid proteins of Ebola virus (EBOV) and Sudan virus (SUDV) and the structural proteins of Venezuelan equine encephalitis virus (VEEV). Selected epitopes were tested for binding to soluble HLA molecules representing 5 class II alleles (DRB1*0101, DRB1*0301, DRB1*0401, DRB1*0701, and DRB1*1501). All but one of the 25 tested peptides bound to at least one of the DRB1 alleles, and 4 of the peptides bound at least moderately or weakly to all 5 DRB1 alleles. Additional algorithms were used to design a single "string-of-beads" expression construct with 44 selected epitopes arranged to avoid creation of spurious junctional epitopes. Seventeen of these 44 predicted epitopes were conserved between the major histocompatibility complex (MHC) of humans and mice, allowing initial testing in mice. BALB/c mice vaccinated with the multi-epitope construct developed statistically significant cellular immune responses to EBOV, SUDV, and VEEV peptides as measured by interferon (IFN)-γ ELISpot assays. Significant levels of antibodies to VEEV, but not EBOV, were also detected in vaccinated BALB/c mice. To assess immunogenicity in the context of a human MHC, HLA-DR3 transgenic mice were vaccinated with the multi-epitope construct and boosted with a mixture of the 25 peptides used in the binding assays. The vaccinated HLA-DR3 mice developed significant cellular immune responses to 4 of the 25 (16%) tested individual class II peptides as measured by IFN-γ ELISpot assays. In addition, these mice developed antibodies against EBOV and VEEV as measured by ELISA. While a low but significant level of protection was observed in vaccinated transgenic mice after aerosol exposure to VEEV, no protection was observed after intraperitoneal challenge with mouse-adapted EBOV. These studies provide proof of concept for the use of an informatics approach to design a multi-agent, multi-epitope immunogen and provide a basis for further testing aimed at focusing immune responses toward desired protective T cell epitopes.

Towards the knowledge-based design of universal influenza epitope ensemble vaccines

MOTIVATION

Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes.

RESULTS

To exemplify our approach we designed two epitope ensemble vaccines comprising highly conserved and experimentally verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96 and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97 and 88% coverage of observed subtypes.

AVAILABILITY AND IMPLEMENTATION

http://imed.med.ucm.es/Tools/episopt.html CONTACT: d.r.flower@aston.ac.uk.

In Vivo Validation of Predicted and Conserved T Cell Epitopes in a Swine Influenza Model

Swine influenza is a highly contagious respiratory viral infection in pigs that is responsible for significant financial losses to pig farmers annually. Current measures to protect herds from infection include: inactivated whole-virus vaccines, subunit vaccines, and alpha replicon-based vaccines. As is true for influenza vaccines for humans, these strategies do not provide broad protection against the diverse strains of influenza A virus (IAV) currently circulating in U.S. swine. Improved approaches to developing swine influenza vaccines are needed. Here, we used immunoinformatics tools to identify class I and II T cell epitopes highly conserved in seven representative strains of IAV in U.S. swine and predicted to bind to Swine Leukocyte Antigen (SLA) alleles prevalent in commercial swine. Epitope-specific interferon-gamma (IFNγ) recall responses to pooled peptides and whole virus were detected in pigs immunized with multi-epitope plasmid DNA vaccines encoding strings of class I and II putative epitopes. In a retrospective analysis of the IFNγ responses to individual peptides compared to predictions specific to the SLA alleles of cohort pigs, we evaluated the predictive performance of PigMatrix and demonstrated its ability to distinguish non-immunogenic from immunogenic peptides and to identify promiscuous class II epitopes. Overall, this study confirms the capacity of PigMatrix to predict immunogenic T cell epitopes and demonstrate its potential for use in the design of epitope-driven vaccines for swine. Additional studies that match the SLA haplotype of animals with the study epitopes will be required to evaluate the degree of immune protection conferred by epitope-driven DNA vaccines in pigs.

iVAX: An integrated toolkit for the selection and optimization of antigens and the design of epitope-driven vaccines

Computational vaccine design, also known as computational vaccinology, encompasses epitope mapping, antigen selection and immunogen design using computational tools. The iVAX toolkit is an integrated set of tools that has been in development since 1998 by De Groot and Martin. It comprises a suite of immunoinformatics algorithms for triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, eliminating regulatory T cell epitopes, and optimizing antigens for immunogenicity and protection against disease. iVAX has been applied to vaccine development programs for emerging infectious diseases, cancer antigens and biodefense targets. Several iVAX vaccine design projects have had success in pre-clinical studies in animal models and are progressing toward clinical studies. The toolkit now incorporates a range of immunoinformatics tools for infectious disease and cancer immunotherapy vaccine design. This article will provide a guide to the iVAX approach to computational vaccinology.

A computational method for identification of vaccine targets from protein regions of conserved human leukocyte antigen binding

Background

Computational methods for T cell-based vaccine target discovery focus on selection of highly conserved peptides identified across pathogen variants, followed by prediction of their binding of human leukocyte antigen molecules. However, experimental studies have shown that T cells often target diverse regions in highly variable viral pathogens and this diversity may need to be addressed through redefinition of suitable peptide targets.

Methods

We have developed a method for antigen assessment and target selection for polyvalent vaccines, with which we identified immune epitopes from variable regions, where all variants bind HLA. These regions, although variable, can thus be considered stable in terms of HLA binding and represent valuable vaccine targets.

Results

We applied this method to predict CD8⁺ T-cell targets in influenza A H7N9 hemagglutinin and significantly increased the number of potential vaccine targets compared to the number of targets discovered using the traditional approach where low-frequency peptides are excluded.

Conclusions

We developed a webserver with an intuitive visualization scheme for summarizing the T cell-based antigenic potential of any given protein or proteome using human leukocyte antigen binding predictions and made a web-accessible software implementation freely available at http://met-hilab.cbs.dtu.dk/blockcons/.

Computer-aided design of T-cell epitope-based vaccines: addressing population coverage

Epitope-based vaccines (EVs) make use of short antigen-derived peptides corresponding to immune epitopes, which are administered to trigger a protective humoral and/or cellular immune response. EVs potentially allow for precise control over the immune response activation by focusing on the most relevant - immunogenic and conserved - antigen regions. Experimental screening of large sets of peptides is time-consuming and costly; therefore, in silico methods that facilitate T-cell epitope mapping of protein antigens are paramount for EV development. The prediction of T-cell epitopes focuses on the peptide presentation process by proteins encoded by the major histocompatibility complex (MHC). Because different MHCs have different specificities and T-cell epitope repertoires, individuals are likely to respond to a different set of peptides from a given pathogen in genetically heterogeneous human populations. In addition, protective immune responses are only expected if T-cell epitopes are restricted by MHC proteins expressed at high frequencies in the target population. Therefore, without careful consideration of the specificity and prevalence of the MHC proteins, EVs could fail to adequately cover the target population. This article reviews state-of-the-art algorithms and computational tools to guide EV design through all the stages of the process: epitope prediction, epitope selection and vaccine assembly, while optimizing vaccine immunogenicity and coping with genetic variation in humans and pathogens.

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.

Time for T? Immunoinformatics addresses vaccine design for neglected tropical and emerging infectious diseases

Vaccines have been invaluable for global health, saving lives and reducing healthcare costs, while also raising the quality of human life. However, newly emerging infectious diseases (EID) and more well-established tropical disease pathogens present complex challenges to vaccine developers; in particular, neglected tropical diseases, which are most prevalent among the world's poorest, include many pathogens with large sizes, multistage life cycles and a variety of nonhuman vectors. EID such as MERS-CoV and H7N9 are highly pathogenic for humans. For many of these pathogens, while their genomes are available, immune correlates of protection are currently unknown. These complexities make developing vaccines for EID and neglected tropical diseases all the more difficult. In this review, we describe the implementation of an immunoinformatics-driven approach to systematically search for key determinants of immunity in newly available genome sequence data and design vaccines. This approach holds promise for the development of 21st century vaccines, improving human health everywhere.

Dendritic cell-mediated, DNA-based vaccination against hepatitis C induces the multi-epitope-specific response of humanized, HLA transgenic mice

Hepatitis C virus (HCV) is the etiologic agent of chronic liver disease, hepatitis C. Spontaneous resolution of viral infection is associated with vigorous HLA class I- and class II-restricted T cell responses to multiple viral epitopes. Unfortunately, only 20% of patients clear infection spontaneously, most develop chronic disease and require therapy. The response to chemotherapy varies, however; therapeutic vaccination offers an additional treatment strategy. To date, therapeutic vaccines have demonstrated only limited success. Vector-mediated vaccination with multi-epitope-expressing DNA constructs alone or in combination with chemotherapy offers an additional treatment approach. Gene sequences encoding validated HLA-A2- and HLA-DRB1-restricted epitopes were synthesized and cloned into an expression vector. Dendritic cells (DCs) derived from humanized, HLA-A2/DRB1 transgenic (donor) mice were transfected with these multi-epitope-expressing DNA constructs. Recipient HLA-A2/DRB1 mice were vaccinated s.c. with transfected DCs; control mice received non-transfected DCs. Peptide-specific IFN-γ production by splenic T cells obtained at 5 weeks post-immunization was quantified by ELISpot assay; additionally, the production of IL-4, IL-10 and TNF-α were quantified by cytokine bead array. Splenocytes derived from vaccinated HLA-A2/DRB1 transgenic mice exhibited peptide-specific cytokine production to the vast majority of the vaccine-encoded HLA class I- and class II-restricted T cell epitopes. A multi-epitope-based HCV vaccine that targets DCs offers an effective approach to inducing a broad immune response and viral clearance in chronic, HCV-infected patients.

Immunization with cross-conserved H1N1 influenza CD4+ T-cell epitopes lowers viral burden in HLA DR3 transgenic mice

The emergence of the pandemic H1N1 strain of influenza in 2009 was associated with a unique w-shaped age-related susceptibility curve, with higher incidence of morbidity and mortality among young persons and lower incidence among older persons, also observed during the 1918 influenza pandemic. Pre-existing H1N1 antibodies were not cross-reactive with the prior seasonal vaccine, forcing influenza experts to scramble to develop a new vaccine specific for the pandemic virus. We hypothesized that response to T-cell epitopes that are cross-conserved between pandemic H1N1 and the 2008 seasonal influenza vaccine strains might have contributed to partial protection from clinical illness among older adults, despite the lack of cross-reactive humoral immunity. Using immunoinformatics tools, we previously identified hemagglutinin and neuraminidase epitopes that were highly conserved between seasonal and pandemic H1N1. Here, we validated predicted CD4(+) T-cell epitopes for their ability to bind HLA and to stimulate interferon-γ production in peripheral blood mononuclear cells from a cohort of donors presenting with influenza-like illness during the 2009 pandemic and a separate cohort immunized with trivalent influenza vaccine in 2011. A limited-epitope heterologous DNA-prime/peptide-boost vaccine composed of these sequences stimulated immune responses and lowered lung viral loads in HLA DR3 transgenic mice challenged with pandemic 2009 H1N1 influenza. Cross-priming with conserved influenza T-cell epitopes such as these may be critically important to T cell-mediated protection against pandemic H1N1 in the absence of cross-protective antibodies.

Making vaccines "on demand": a potential solution for emerging pathogens and biodefense?

The integrated US Public Health Emergency Medical Countermeasures Enterprise (PHEMCE) has made great strides in strategic preparedness and response capabilities. There have been numerous advances in planning, biothreat countermeasure development, licensure, manufacturing, stockpiling and deployment. Increased biodefense surveillance capability has dramatically improved, while new tools and increased awareness have fostered rapid identification of new potential public health pathogens. Unfortunately, structural delays in vaccine design, development, manufacture, clinical testing and licensure processes remain significant obstacles to an effective national biodefense rapid response capability. This is particularly true for the very real threat of “novel pathogens” such as the avian-origin influenzas H7N9 and H5N1, and new coronaviruses such as hCoV-EMC. Conventional approaches to vaccine development, production, clinical testing and licensure are incompatible with the prompt deployment needed for an effective public health response. An alternative approach, proposed here, is to apply computational vaccine design tools and rapid production technologies that now make it possible to engineer vaccines for novel emerging pathogen and WMD biowarfare agent countermeasures in record time. These new tools have the potential to significantly reduce the time needed to design string-of-epitope vaccines for previously unknown pathogens. The design process—from genome to gene sequence, ready to insert in a DNA plasmid—can now be accomplished in less than 24 h. While these vaccines are by no means “standard,” the need for innovation in the vaccine design and production process is great. Should such vaccines be developed, their 60-d start-to-finish timeline would represent a 2-fold faster response than the current standard.

HIV-2 and its role in conglutinated approach towards Acquired Immunodeficiency Syndrome (AIDS) Vaccine Development

Acquired Immunodeficiency Syndrome (AIDS) is one of the most critically acclaimed endemic diseases, caused by two lentiviruses HIV-1 and 2. HIV-2 displays intimate serological and antigenic resemblance to Simian Immunodeficiency Virus (SIV) along with less pathogenicity, lower infectivity and appreciable cross reactivity with HIV-1 antigens. The present era is confronted with the challenge to fabricate a vaccine effective against all clades of both the species of HIV. But vaccine development against HIV-1 has proven highly intricate, moreover the laborious and deficient conventional approaches has slackened the pace regarding the development of new vaccines. These concerns may be tackled with the development of HIV-2 vaccine as a natural control of HIV-1 that has been found in ancestors of HIV-2 i.e. African monkeys, mangabeys and macaques. Thereby, suggesting the notion of cross protection among HIV-2 and HIV-1. Assistance of bioinformatics along with vaccinomics strategy can bring about a quantum leap in this direction for surpassing the bottleneck in conventional approaches. These specifics together can add to our conception that HIV-2 vaccine design by in silico strategy will surely be a constructive approach for HIV-1 targeting.

HIV-1 Vaccine Trials: Evolving Concepts and Designs

An effective prophylactic HIV-1 vaccine is needed to eradicate the HIV/AIDS pandemic but designing such a vaccine is a challenge. Despite many advances in vaccine technology and approaches to generate both humoral and cellular immune responses, major phase-II and -III vaccine trials against HIV/AIDS have resulted in only moderate successes. The modest achievement of the phase-III RV144 prime-boost trial in Thailand re-emphasized the importance of generating robust humoral and cellular responses against HIV. While antibody-directed approaches are being pursued by some groups, others are attempting to develop vaccines targeting cell-mediated immunity, since evidence show CTLs to be important for the control of HIV replication. Phase-I and -IIa multi-epitope vaccine trials have already been conducted with vaccine immunogens consisting of known CTL epitopes conserved across HIV subtypes, but have so far fallen short of inducing robust and consistent anti-HIV CTL responses. The concepts leading to the development of T-cell epitope-based vaccines, the outcomes of related clinical vaccine trials and efforts to enhance the immunogenicity of cell-mediated approaches are summarized in this review. Moreover, we describe a novel approach based on the identification of SIV and FIV antigens which contain conserved HIV-specific T-cell epitopes and represent an alternative method for developing an effective HIV vaccine against global HIV isolates.

Conservation of HIV-1 T cell epitopes across time and clades: validation of immunogenic HLA-A2 epitopes selected for the GAIA HIV vaccine

HIV genomic sequence variability has complicated efforts to generate an effective globally relevant vaccine. Regions of the viral genome conserved in sequence and across time may represent the "Achilles' heel" of HIV. In this study, highly conserved T-cell epitopes were selected using immunoinformatics tools combining HLA-A2 supertype binding predictions with relative global conservation. Analysis performed in 2002 on 10,803 HIV-1 sequences, and again in 2009, on 43,822 sequences, yielded 38 HLA-A2 epitopes. These epitopes were experimentally validated for HLA binding and immunogenicity with PBMCs from HIV-infected patients in Providence, Rhode Island, and/or Bamako, Mali. Thirty-five (92%) stimulated an IFNγ response in PBMCs from at least one subject. Eleven of fourteen peptides (79%) were confirmed as HLA-A2 epitopes in both locations. Validation of these HLA-A2 epitopes conserved across time, clades, and geography supports the hypothesis that such epitopes could provide effective coverage of virus diversity and would be appropriate for inclusion in a globally relevant HIV vaccine.

Immunogenicity and immune modulatory effects of in silico predicted L. donovani candidate peptide vaccines

Visceral leishmaniasis (VL) is a serious parasitic disease for which control measures are limited and drug resistance is increasing. First and second generation vaccine candidates have not been successful. The goal of the present study was to select possibly immunogenic L. donovani donovani GP63 peptides using immunoinformatics tools and to test their immunogenicity in vitro. The amino acid sequence of L. donovani donovani GP63 [GenBank accession: ACT31401] was screened using the EpiMatrix algorithm for putative T cell epitopes that would bind to the most common HLA class II alleles (DRB1*1101 and DRB1*0804) among at-risk populations. Four T cell epitopes were selected from nine potential candidates. Stimulation of whole blood from healthy volunteers using the peptides separately produced mean IFN-γ and IL-4 levels that were not significantly different from negative controls, while the pooled peptides produced a moderate IFN-γ increase in some volunteers. However, mean IL-10 levels were significantly reduced for all individuals compared with controls. The immunogenicity of these epitopes may be harnessed most effectively in a vaccine delivered in combination with immune-modulating adjuvants.

New vaccines needed for pathogens infecting animals and humans: One Health

The field of "One Health" encourages researchers to collaborate across a wide range of disciplines to improve health at the animal-human-ecosystems interface. One Health recognizes the potential of emerging infectious diseases to impact public health and global food security, and the need for a multidisciplinary approach to counteract the effect of these diseases. Vaccinologists are also beginning to engage in research related to One Health, recognizing that preventing transmission of emerging infectious diseases at the animal-human interface is critically important for protecting the world population from epizootics and pandemics. In this synopsis of recent work in the One Health field, we describe some emerging One Health pathogens, discuss the importance of One Health to food safety and biodefense, propose strategies for improving One Health including the development of new vaccines and new vaccine design approaches, and close with a brief discussion of the opportunities and risks related to One Health vaccine research.

Conservation analysis of dengue virus T-cell epitope-based vaccine candidates using Peptide block entropy

Broad coverage of the pathogen population is particularly important when designing CD8+ T-cell epitope vaccines against viral pathogens. Traditional approaches are based on combinations of highly conserved T-cell epitopes. Peptide block entropy analysis is a novel approach for assembling sets of broadly covering antigens. Since T-cell epitopes are recognized as peptides rather than individual residues, this method is based on calculating the information content of blocks of peptides from a multiple sequence alignment of homologous proteins rather than using the information content of individual residues. The block entropy analysis provides broad coverage of variant antigens. We applied the block entropy analysis method to the proteomes of the four serotypes of dengue virus (DENV) and found 1,551 blocks of 9-mer peptides, which cover 99% of available sequences with five or fewer unique peptides. In contrast, the benchmark study by Khan et al. (2008) resulted in 165 conserved 9-mer peptides. Many of the conserved blocks are located consecutively in the proteins. Connecting these blocks resulted in 78 conserved regions. Of the 1551 blocks of 9-mer peptides 110 comprised predicted HLA binder sets. In total, 457 subunit peptides that encompass the diversity of all sequenced DENV strains of which 333 are T-cell epitope candidates.

Defining epitope coverage requirements for T cell-based HIV vaccines: theoretical considerations and practical applications

Background

HIV vaccine development must address the genetic diversity and plasticity of the virus that permits the presentation of diverse genetic forms to the immune system and subsequent escape from immune pressure. Assessment of potential HIV strain coverage by candidate T cell-based vaccines (whether natural sequence or computationally optimized products) is now a critical component in interpreting candidate vaccine suitability.

Methods

We have utilized an N-mer identity algorithm to represent T cell epitopes and explore potential coverage of the global HIV pandemic using natural sequences derived from candidate HIV vaccines. Breadth (the number of T cell epitopes generated) and depth (the variant coverage within a T cell epitope) analyses have been incorporated into the model to explore vaccine coverage requirements in terms of the number of discrete T cell epitopes generated.

Results

We show that when multiple epitope generation by a vaccine product is considered a far more nuanced appraisal of the potential HIV strain coverage of the vaccine product emerges. By considering epitope breadth and depth several important observations were made: (1) epitope breadth requirements to reach particular levels of vaccine coverage, even for natural sequence-based vaccine products is not necessarily an intractable problem for the immune system; (2) increasing the valency (number of T cell epitope variants present) of vaccine products dramatically decreases the epitope requirements to reach particular coverage levels for any epidemic; (3) considering multiple-hit models (more than one exact epitope match with an incoming HIV strain) places a significantly higher requirement upon epitope breadth in order to reach a given level of coverage, to the point where low valency natural sequence based products would not practically be able to generate sufficient epitopes.

Conclusions

When HIV vaccine sequences are compared against datasets of potential incoming viruses important metrics such as the minimum epitope count required to reach a desired level of coverage can be easily calculated. We propose that such analyses can be applied early in the planning stages and during the execution phase of a vaccine trial to explore theoretical and empirical suitability of a vaccine product to a particular epidemic setting.

Universal peptide vaccines - optimal peptide vaccine design based on viral sequence conservation

Rapidly mutating viruses such as the hepatitis C virus (HCV), the human immunodeficiency virus (HIV), or influenza viruses (Flu) call for highly effective universal peptide vaccines, i.e. vaccines that do not only yield broad population coverage but also broad coverage of various viral strains. The efficacy of such vaccines is determined by multiple properties of the epitopes they comprise. Beyond the specific properties of each epitope, properties of the corresponding source antigens are of great importance. If a response is mounted against viral proteins with a low copy number within the cell or against proteins expressed very late, this response may fail to induce lysis of the infected cells before budding can take place. We here propose a novel methodology to optimize the epitope composition and assembly in order to induce maximum protection. In order for a peptide vaccine to yield the best possible universal protection, several conditions should be met: (a) an optimal choice of target antigens, (b) an optimal choice of highly conserved epitopes, (c) maximum coverage of the target population, and (d) the proper ordering of the epitopes in the final vaccine to ensure favorable cleavage. We propose a mathematical formalism for epitope selection and ordering that balances the constraints imposed by these different conditions. Focusing on HCV, HIV, and Flu, we show that not all of the conditions can be satisfied for all viruses. Depending on the virus, different constraints are harder to fulfill: for Flu, the conservation constraint is violated first, while for HIV, it is difficult to focus the response at the optimal target antigens. The proposed methodology can be applied to any virus to assess the feasibility of optimally combining the above-mentioned constraints.

Human immunodeficiency virus (HIV) immunopathogenesis and vaccine development: a review

The development of a safe, effective and globally affordable HIV vaccine offers the best hope for the future control of the HIV-1 pandemic. Since 1987, scores of candidate HIV-1 vaccines have been developed which elicited varying degrees of protective responses in nonhuman primate models, including DNA vaccines, subunit vaccines, live vectored recombinant vaccines and various prime-boost combinations. Four of these candidate vaccines have been tested for efficacy in human volunteers, but, to the exception of the recent RV144 Phase III trial in Thailand, which elicited a modest but statistically significant level of protection against infection, none has shown efficacy in preventing HIV-1 infection or in controlling virus replication and delaying progression of disease in humans. Protection against infection was observed in the RV144 trial, but intensive research is needed to try to understand the protective immune mechanisms at stake. Building-up on the results of the RV144 trial and deciphering what possibly are the immune correlates of protection are the top research priorities of the moment, which will certainly accelerate the development of an highly effective vaccine that could be used in conjunction with other HIV prevention and treatment strategies. This article reviews the state of the art of HIV vaccine development and discusses the formidable scientific challenges met in this endeavor, in the context of a better understanding of the immunopathogenesis of the disease.

Emerging vaccine informatics

Vaccine informatics is an emerging research area that focuses on development and applications of bioinformatics methods that can be used to facilitate every aspect of the preclinical, clinical, and postlicensure vaccine enterprises. Many immunoinformatics algorithms and resources have been developed to predict T- and B-cell immune epitopes for epitope vaccine development and protective immunity analysis. Vaccine protein candidates are predictable in silico from genome sequences using reverse vaccinology. Systematic transcriptomics and proteomics gene expression analyses facilitate rational vaccine design and identification of gene responses that are correlates of protection in vivo. Mathematical simulations have been used to model host-pathogen interactions and improve vaccine production and vaccination protocols. Computational methods have also been used for development of immunization registries or immunization information systems, assessment of vaccine safety and efficacy, and immunization modeling. Computational literature mining and databases effectively process, mine, and store large amounts of vaccine literature and data. Vaccine Ontology (VO) has been initiated to integrate various vaccine data and support automated reasoning.

Differences in HIV-specific T cell responses between HIV-exposed and -unexposed HIV-seronegative individuals

HIV-1-specific T lymphocyte responses in individuals exposed to HIV-1 but who remain persistently seronegative (HESNs) have been reported in some but not all previous studies. This study was designed to resolve unequivocally the question of whether HESNs make HIV-1-specific T cell responses. We performed a blind investigation to measure HIV-1-specific T cell responses in both HIV-1-serodiscordant couples and HIV-1-unexposed seronegative controls (HUSNs). We found low-frequency HIV-1-specific T cells in both HESNs and HUSNs but show that the response rates were higher over time in the former (P = 0.01). Furthermore, the magnitudes of the HIV-1-specific T cell responses were significantly higher among responding HESNs than among HUSNs over time (P = 0.002). In both groups, responses were mediated by CD4 T cells. The responses were mapped to single peptides, which often corresponded to epitopes restricted by multiple HLA-DR types that have previously been detected in HIV-1-infected patients. HIV-1-specific T cell responses in HUSNs and some HESNs likely represent cross-reactivity to self or foreign non-HIV-1 antigens. The significantly greater T cell responses in HESNs, including in two who were homozygous for CCR5Δ32, demonstrates that HIV-1-specific T cell responses can be induced or augmented by exposure to HIV-1 without infection.

HelicoVax: epitope-based therapeutic Helicobacter pylori vaccination in a mouse model

Helicobacter pylori is the leading cause of gastritis, peptic ulcer disease and gastric adenocarcinoma and lymphoma in humans. Due to the decreasing efficacy of anti-H. pylori antibiotic therapy in clinical practice, there is renewed interest in the development of anti-H. pylori vaccines. In this study an in silico-based approach was utilized to develop a multi-epitope DNA-prime/peptide-boost immunization strategy using informatics tools. The efficacy of this construct was then assessed as a therapeutic vaccine in a mouse model of gastric cancer induced by chronic H. pylori infection. The multi-epitope vaccine administered intranasally induced a broad immune response as determined by interferon-gamma production in ELISpot assays. This was associated with a significant reduction in H. pylori colonization compared with mice immunized with the same vaccine intramuscularly, given an empty plasmid, or given a whole H. pylori lysate intranasally as the immunogen. Total scores of gastric histological changes were not significantly different among the 4 experimental groups. These results suggest that further development of an epitope-based mucosal vaccine may be beneficial in eradicating H. pylori and reducing the burden of the associated gastric diseases in humans.

Harnessing the power of genomics and immunoinformatics to produce improved vaccines

The role of cellular immunity as a mediator of protection against disease is gaining recognition, particularly with regard to the many pathogens for which we presently lack effective vaccines. As a result, there is an ever-increasing need to understand the T-cell populations induced by vaccination and, therefore, T-cell epitopes responsible for triggering their activation. Although the characterization and harnessing of cellular immunity for vaccine development is an active area of research interest, the field still needs to rigorously define T-cell epitope specificities, above all, on a genomic level. New immunoinformatic epitope mapping tools now make it possible to identify pathogen epitopes and perform comparisons against human and microbial genomic data sets. Such information will help to determine whether adaptive immune responses elicited by a vaccine are both pathogen-specific and protective, but not crossreactive against host or host-associated sequences that could jeopardize self-tolerance and/or human microbiome-host homeostasis. Here, we discuss advances in genomics and vaccine design and their relevance to the development of safer, more effective vaccines.

VennVax, a DNA-prime, peptide-boost multi-T-cell epitope poxvirus vaccine, induces protective immunity against vaccinia infection by T cell response alone

The potential for smallpox to be disseminated in a bioterror attack has prompted development of new, safer smallpox vaccination strategies. We designed and evaluated immunogenicity and efficacy of a T-cell epitope vaccine based on conserved and antigenic vaccinia/variola sequences, identified using bioinformatics and immunological methods. Vaccination in HLA transgenic mice using a DNA-prime/peptide-boost strategy elicited significant T cell responses to multiple epitopes. No antibody response pre-challenge was observed, neither against whole vaccinia antigens nor vaccine epitope peptides. Remarkably, 100% of vaccinated mice survived lethal vaccinia challenge, demonstrating that protective immunity to vaccinia does not require B cell priming.

Models of RNA virus evolution and their roles in vaccine design

Viruses are fast evolving pathogens that continuously adapt to the highly variable environments they live and reproduce in. Strategies devoted to inhibit virus replication and to control their spread among hosts need to cope with these extremely heterogeneous populations and with their potential to avoid medical interventions. Computational techniques such as phylogenetic methods have broadened our picture of viral evolution both in time and space, and mathematical modeling has contributed substantially to our progress in unraveling the dynamics of virus replication, fitness, and virulence. Integration of multiple computational and mathematical approaches with experimental data can help to predict the behavior of viral pathogens and to anticipate their escape dynamics. This piece of information plays a critical role in some aspects of vaccine development, such as viral strain selection for vaccinations or rational attenuation of viruses. Here we review several aspects of viral evolution that can be addressed quantitatively, and we discuss computational methods that have the potential to improve vaccine design.

Reverse vaccinology: developing vaccines in the era of genomics

The sequence of microbial genomes made all potential antigens of each pathogen available for vaccine development. This increased by orders of magnitude potential vaccine targets in bacteria, parasites, and large viruses and revealed virtually all their CD4(+) and CD8(+) T cell epitopes. The genomic information was first used for the development of a vaccine against serogroup B meningococcus, and it is now being used for several other bacterial vaccines. In this review, we will first summarize the impact that genome sequencing has had on vaccine development, and then we will analyze how the genomic information can help further our understanding of immunity to infection or vaccination and lead to the design of better vaccines by diving into the world of T cell immunity.

A novel strategy of epitope design in Neisseria gonorrhoeae

In spite of genome sequences of both human and N. gonorrhoeae in hand, vaccine for gonorrhea is yet not available. Due to availability of several host and pathogen genomes and numerous tools for in silico prediction of effective B-cell and T-cell epitopes; recent trend of vaccine designing has been shifted to peptide or epitope based vaccines that are more specific, safe, and easy to produce. In order to design and develop such a peptide vaccine against the pathogen, we adopted a novel computational approache based on sequence, structure, QSAR, and simulation methods along with fold level analysis to predict potential antigenic B-cell epitope derived T-cell epitopes from four vaccine targets of N. gonorrhoeae previously identified by us [Barh and Kumar (2009) In Silico Biology 9, 1-7]. Four epitopes, one from each protein, have been designed in such a way that each epitope is highly likely to bind maximum number of HLA molecules (comprising of both the MHC-I and II) and interacts with most frequent HLA alleles (A*0201, A*0204, B*2705, DRB1*0101, and DRB1*0401) in human population. Therefore our selected epitopes are highly potential to induce both the B-cell and T-cell mediated immune responses. Of course, these selected epitopes require further experimental validation.

Vaxign: the first web-based vaccine design program for reverse vaccinology and applications for vaccine development

Vaxign is the first web-based vaccine design system that predicts vaccine targets based on genome sequences using the strategy of reverse vaccinology. Predicted features in the Vaxign pipeline include protein subcellular location, transmembrane helices, adhesin probability, conservation to human and/or mouse proteins, sequence exclusion from genome(s) of nonpathogenic strain(s), and epitope binding to MHC class I and class II. The precomputed Vaxign database contains prediction of vaccine targets for >70 genomes. Vaxign also performs dynamic vaccine target prediction based on input sequences. To demonstrate the utility of this program, the vaccine candidates against uropathogenic Escherichia coli (UPEC) were predicted using Vaxign and compared with various experimental studies. Our results indicate that Vaxign is an accurate and efficient vaccine design program.

High throughput T epitope mapping and vaccine development

Mapping of antigenic peptide sequences from proteins of relevant pathogens recognized by T helper (Th) and by cytolytic T lymphocytes (CTL) is crucial for vaccine development. In fact, mapping of T-cell epitopes provides useful information for the design of peptide-based vaccines and of peptide libraries to monitor specific cellular immunity in protected individuals, patients and vaccinees. Nevertheless, epitope mapping is a challenging task. In fact, large panels of overlapping peptides need to be tested with lymphocytes to identify the sequences that induce a T-cell response. Since numerous peptide panels from antigenic proteins are to be screened, lymphocytes available from human subjects are a limiting factor. To overcome this limitation, high throughput (HTP) approaches based on miniaturization and automation of T-cell assays are needed. Here we consider the most recent applications of the HTP approach to T epitope mapping. The alternative or complementary use of in silico prediction and experimental epitope definition is discussed in the context of the recent literature. The currently used methods are described with special reference to the possibility of applying the HTP concept to make epitope mapping an easier procedure in terms of time, workload, reagents, cells and overall cost.

Towards in silico design of epitope-based vaccines

BACKGROUND

Epitope-based vaccines (EVs) make use of immunogenic peptides (epitopes) to trigger an immune response. Due to their manifold advantages, EVs have recently been attracting growing interest. The success of an EV is determined by the choice of epitopes used as a basis. However, the experimental discovery of candidate epitopes is expensive in terms of time and money. Furthermore, for the final choice of epitopes various immunological requirements have to be considered.

METHODS

Numerous in silico approaches exist that can guide the design of EVs. In particular, computational methods for MHC binding prediction have already become standard tools in immunology. Apart from binding prediction and prediction of antigen processing, methods for epitope design and selection have been suggested. We review these in silico approaches for epitope discovery and selection along with their strengths and weaknesses. Finally, we discuss some of the obvious problems in the design of EVs.

CONCLUSION

State-of-the-art in silico approaches to MHC binding prediction yield high accuracies. However, a more thorough understanding of the underlying biological processes and significant amounts of experimental data will be required for the validation and improvement of in silico approaches to the remaining aspects of EV design.

In silico-accelerated identification of conserved and immunogenic variola/vaccinia T-cell epitopes

Epitopes shared by the vaccinia and variola viruses underlie the protective effect of vaccinia immunization against variola infection. We set out to identify a subset of cross-reactive epitopes using bioinformatics and immunological methods. Putative T-cell epitopes were computationally predicted from highly conserved open reading frames from seven complete vaccinia and variola genomes using EpiMatrix. Over 100 epitopes bearing low human sequence homology were selected and assessed in HLA binding assays and in T-cell antigenicity assays using PBMCs isolated from Dryvax-immunized subjects. This experimental validation of computational predictions illustrates the potential for immunoinformatics methods to identify candidate immunogens for a new, safer smallpox vaccine.

OptiTope--a web server for the selection of an optimal set of peptides for epitope-based vaccines

Epitope-based vaccines (EVs) have recently been attracting significant interest. They trigger an immune response by confronting the immune system with immunogenic peptides derived from, e.g. viral- or cancer-related proteins. Binding of these peptides to proteins from the major histocompatibility complex (MHC) is crucial for immune system activation. However, since the MHC is highly polymorphic, different patients typically bind different repertoires of peptides. Furthermore, economical and regulatory issues impose strong limitations on the number of peptides that can be included in an EV. Hence, it is crucial to identify the optimal set of peptides for a vaccine, given constraints such as MHC allele probabilities in the target population, peptide mutation rates and maximum number of selected peptides. OptiTope aims at assisting immunologists in this critical task. With OptiTope, we provide an easy-to-use tool to determine a provably optimal set of epitopes with respect to overall immunogenicity in a specific individual (personalized medicine) or a target population (e.g. a certain ethnic group). OptiTope is available at http://www.epitoolkit.org/optitope.