Further progress on defining highly conserved immunogenic epitopes for a global HIV vaccine: HLA-A3-restricted GAIA vaccine epitopes

An overview of in silico vaccine design against different pathogens and cancer

INTRODUCTION

Due to overcome the hardness of the vaccine design, computational vaccinology is emerging widely. Prediction of T cell and B cell epitopes, antigen processing analysis, antigenicity analysis, population coverage, conservancy analysis, allergenicity assessment, toxicity prediction, and protein-peptide docking are important steps in the process of designing and developing potent vaccines against various viruses and cancers. In order to perform all of the analyses, several bioinformatics tools and online web servers have been developed. Scientists must take the decision to apply more suitable and precise servers for each part based on their accuracy.

AREAS COVERED

In this review, a wide-range list of different bioinformatics tools and online web servers has been provided. Moreover, some studies were proposed to show the importance of various bioinformatics tools for predicting and developing efficient vaccines against different pathogens including viruses, bacteria, parasites, and fungi as well as cancer.

EXPERT OPINION

Immunoinformatics is the best way to find potential vaccine candidates against different pathogens. Thus, the selection of the most accurate tools is necessary to predict and develop potent preventive and therapeutic vaccines. To further evaluation of the computational and in silico vaccine design, in vitro/in vivo analyses are required to develop vaccine candidates.

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.

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.

Hit-and-run, hit-and-stay, and commensal bacteria present different peptide content when viewed from the perspective of the T cell

Different types of bacteria face different pressures from the immune system, with those that persist ("hit-and-stay") potentially having to adapt more in order to escape than those prone to short-lived infection ("hit-and-run"), and with commensal bacteria potentially different from both due to additional physical mechanisms for avoiding immune detection. The Janus Immunogenicity Score (JIS) was recently developed to assess the likelihood of T cell recognition of an antigen, using an analysis that considers both binding of a peptide within the antigen by major histocompatability complex (MHC) and recognition of the peptide:MHC complex by cognate T cell receptor (TCR). This score was shown to be predictive of T effector vs. T regulatory or null responses in experimental data, as well as to distinguish viruses representative of the hit-and-stay vs. hit-and-run phenotypes. Here, JIS-based analyses were conducted in order to characterize the extent to which the pressure to avoid T cell recognition is manifested in genomic differences among representative hit-and-run, hit-and-stay, and commensal bacteria. Overall, extracellular proteins were found to have different JIS profiles from cytoplasmic ones. Contrasting the bacterial groups, extracellular proteins were shown to be quite different across the groups, much more so than intracellular proteins. The differences were evident even at the level of corresponding peptides in homologous protein pairs from hit-and-run and hit-and-stay bacteria. The multi-level analysis of patterns of immunogenicity across different groups of bacteria provides a new way to approach questions of bacterial immune camouflage or escape, as well as to approach the selection and optimization of candidates for vaccine design.

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.

Comparative genomics and immunoinformatics approach for the identification of vaccine candidates for enterohemorrhagic Escherichia coli O157:H7

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 strains are major human food-borne pathogens, responsible for bloody diarrhea and hemolytic-uremic syndrome worldwide. Thus far, there is no vaccine for humans against EHEC infections. In this study, a comparative genomics analysis was performed to identify EHEC-specific antigens useful as potential vaccines. The genes present in both EHEC EDL933 and Sakai strains but absent in nonpathogenic E. coli K-12 and HS strains were subjected to an in silico analysis to identify secreted or surface-expressed proteins. We obtained a total of 65 gene-encoding protein candidates, which were subjected to immunoinformatics analysis. Our criteria of selection aided in categorizing the candidates as high, medium, and low priority. Three members of each group were randomly selected and cloned into pVAX-1. Candidates were pooled accordingly to their priority group and tested for immunogenicity against EHEC O157:H7 using a murine model of gastrointestinal infection. The high-priority (HP) pool, containing genes encoding a Lom-like protein (pVAX-31), a putative pilin subunit (pVAX-12), and a fragment of the type III secretion structural protein EscC (pVAX-56.2), was able to induce the production of EHEC IgG and sIgA in sera and feces. HP candidate-immunized mice displayed elevated levels of Th2 cytokines and diminished cecum colonization after wild-type challenge. Individually tested HP vaccine candidates showed that pVAX-12 and pVAX-56.2 significantly induced Th2 cytokines and production of fecal EHEC sIgA, with pVAX-56.2 reducing EHEC cecum colonization. We describe here a bioinformatics approach able to identify novel vaccine candidates potentially useful for preventing EHEC O157:H7 infections.

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.

Universal H1N1 influenza vaccine development: identification of consensus class II hemagglutinin and neuraminidase epitopes derived from strains circulating between 1980 and 2011

Immune responses to cross-conserved T cell epitopes in novel H1N1 influenza may explain reports of diminished influenza-like illnesses and confirmed infection among older adults, in the absence of cross-reactive humoral immunity, during the 2009 pandemic. These cross-conserved epitopes may prove useful for the development of a universal H1N1 influenza vaccine, therefore, we set out to identify and characterize cross-conserved H1N1 T cell epitopes. An immunoinformatic analysis was conducted using all available pandemic and pre-pandemic HA-H1 and NA-N1 sequences dating back to 1980. Using an approach that balances potential for immunogenicity with conservation, we derived 13 HA and four NA immunogenic consensus sequences (ICS) from a comprehensive analysis of 5,738 HA-H1 and 5,396 NA-N1 sequences. These epitopes were selected because their combined epitope content is representative of greater than 84% of pre-pandemic and pandemic H1N1 influenza strains, their predicted immunogenicity (EpiMatrix) scores were greater than or equal to the 95th percentile of all comparable epitopes, and they were also predicted to be presented by more than four HLA class II archetypal alleles. We confirmed the ability of these peptides to bind in HLA binding assays and to stimulate interferon-γ production in human peripheral blood mononuclear cell cultures. These studies support the selection of the ICS as components of potential group-common H1N1 vaccine candidates and the application of this universal influenza vaccine development approach to other influenza subtypes.

Vaccinomics, adversomics, and the immune response network theory: individualized vaccinology in the 21st century

Vaccines, like drugs and medical procedures, are increasingly amenable to individualization or personalization, often based on novel data resulting from high throughput "omics" technologies. As a result of these technologies, 21st century vaccinology will increasingly see the abandonment of a "one size fits all" approach to vaccine dosing and delivery, as well as the abandonment of the empiric "isolate-inactivate-inject" paradigm for vaccine development. In this review, we discuss the immune response network theory and its application to the new field of vaccinomics and adversomics, and illustrate how vaccinomics can lead to new vaccine candidates, new understandings of how vaccines stimulate immune responses, new biomarkers for vaccine response, and facilitate the understanding of what genetic and other factors might be responsible for rare side effects due to vaccines. Perhaps most exciting will be the ability, at a systems biology level, to integrate increasingly complex high throughput data into descriptive and predictive equations for immune responses to vaccines. Herein, we discuss the above with a view toward the future of vaccinology.

Structure-based redesign of proteins for minimal T-cell epitope content

The protein universe displays a wealth of therapeutically relevant activities, but T-cell driven immune responses to non-"self" biological agents present a major impediment to harnessing the full diversity of these molecular functions. Mutagenic T-cell epitope deletion seeks to mitigate the immune response, but can typically address only a small number of epitopes. Here, we pursue a "bottom-up" approach that redesigns an entire protein to remain native-like but contain few if any immunogenic epitopes. We do so by extending the Rosetta flexible-backbone protein design software with an epitope scoring mechanism and appropriate constraints. The method is benchmarked with a diverse panel of proteins and applied to three targets of therapeutic interest. We show that the deimmunized designs indeed have minimal predicted epitope content and are native-like in terms of various quality measures, and moreover that they display levels of native sequence recovery comparable to those of non-deimmunized designs.

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.