Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding

A comprehensive in silico analysis for identification of therapeutic epitopes in HPV16, 18, 31 and 45 oncoproteins

Human papillomaviruses (HPVs) are a group of circular double-stranded DNA viruses, showing severe tropism to mucosal tissues. A subset of HPVs, especially HPV16 and 18, are the primary etiological cause for several epithelial cell malignancies, causing about 5.2% of all cancers worldwide. Due to the high prevalence and mortality, HPV-associated cancers have remained as a significant health problem in human society, making an urgent need to develop an effective therapeutic vaccine against them. Achieving this goal is primarily dependent on the identification of efficient tumor-associated epitopes, inducing a robust cell-mediated immune response. Previous information has shown that E5, E6, and E7 early proteins are responsible for the induction and maintenance of HPV-associated cancers. Therefore, the prediction of major histocompatibility complex (MHC) class I T cell epitopes of HPV16, 18, 31 and 45 oncoproteins was targeted in this study. For this purpose, a two-step plan was designed to identify the most probable CD8+ T cell epitopes. In the first step, MHC-I and II binding, MHC-I processing, MHC-I population coverage and MHC-I immunogenicity prediction analyses, and in the second step, MHC-I and II protein-peptide docking, epitope conservation, and cross-reactivity with host antigens’ analyses were carried out successively by different tools. Finally, we introduced five probable CD8+ T cell epitopes for each oncoprotein of the HPV genotypes (60 epitopes in total), which obtained better scores by an integrated approach. These predicted epitopes are valuable candidates for in vitro or in vivo therapeutic vaccine studies against the HPV-associated cancers. Additionally, this two-step plan that each step includes several analyses to find appropriate epitopes provides a rational basis for DNA- or peptide-based vaccine development.

Neoantigenic Potential of Complex Chromosomal Rearrangements in Mesothelioma

INTRODUCTION

Malignant pleural mesothelioma is a disease primarily associated with exposure to the carcinogen asbestos. Whereas other carcinogen-related tumors are associated with a high tumor mutation burden, mesothelioma is not. We sought to resolve this discrepancy.

METHODS

We used mate-pair (n = 22), RNA (n = 28), and T cell receptor sequencing along with in silico predictions and immunologic assays to understand how structural variants of chromosomes affect the transcriptome.

RESULTS

We observed that inter- or intrachromosomal rearrangements were present in every specimen and were frequently in a pattern of chromoanagenesis such as chromoplexy or chromothripsis. Transcription of rearrangement-related junctions was predicted to result in many potential neoantigens, some of which were proven to bind patient-specific major histocompatibility complex molecules and to expand intratumoral T cell clones. T cells responsive to these predicted neoantigens were also present in a patient's circulating T cell repertoire. Analysis of genomic array data from the mesothelioma cohort in The Cancer Genome Atlas suggested that multiple chromothriptic-like events negatively impact survival.

CONCLUSIONS

Our findings represent the discovery of potential neoantigen expression driven by structural chromosomal rearrangements. These results may have implications for the development of novel immunotherapeutic strategies and the selection of patients to receive immunotherapies.

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

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

Predicting T cell recognition of MHC class I restricted neoepitopes

Epitopes that arise from a somatic mutation, also called neoepitopes, are now known to play a key role in cancer immunology and immunotherapy. Recent advances in high-throughput sequencing have made it possible to identify all mutations and thereby all potential neoepitope candidates in an individual cancer. However, most of these neoepitope candidates are not recognized by T cells of cancer patients when tested in vivo or in vitro, meaning they are not immunogenic. Especially in patients with a high mutational load, usually hundreds of potential neoepitopes are detected, highlighting the need to further narrow down this candidate list. In our study, we assembled a dataset of known, naturally processed, immunogenic neoepitopes to dissect the properties that make these neoepitopes immunogenic. The tools to use and thresholds to apply for prioritizing neoepitopes have so far been largely based on experience with epitope identification in other settings such as infectious disease and allergy. Here, we performed a detailed analysis on our dataset of curated immunogenic neoepitopes to establish the appropriate tools and thresholds in the cancer setting. To this end, we evaluated different predictors for parameters that play a role in a neoepitope's immunogenicity and suggest that using binding predictions and length-rescaling yields the best performance in discriminating immunogenic neoepitopes from a background set of mutated peptides. We furthermore show that almost all neoepitopes had strong predicted binding affinities (as expected), but more surprisingly, the corresponding non-mutated peptides had nearly as high affinities. Our results provide a rational basis for parameters in neoepitope filtering approaches that are being commonly used. Abbreviations: SNV: single nucleotide variant; nsSNV: nonsynonymous single nucleotide variant; ROC: receiver operating characteristic; AUC: area under ROC curve; HLA: human leukocyte antigen; MHC: major histocompatibility complex; PD-1: Programmed cell death protein 1; PD-L1 or CTLA-4: cytotoxic T-lymphocyte associated protein 4.

Identifying neoantigens for use in immunotherapy

This review focuses on the types of cancer antigens that can be recognised by the immune system and form due to alterations in the cancer genome, including cancer testis, overexpressed and neoantigens. Specifically, neoantigens can form when cancer cell-specific mutations occur that result in alterations of the protein from ‘self’. This type of antigen can result in an immune response sufficient to clear tumour cells when activated. Furthermore, studies have reported that the likelihood of successful immunotherapeutic targeting of cancer by many different methods was reliant on immune response to neoantigens. The recent resurgence of interest in the immune response to tumour cells, in conjunction with technological advances, has resulted in a large increase in the predicted, identified and functionally confirmed neoantigens. This growth in identified neoantigen sequences has increased the contents of training sets for algorithms, which in turn improves the prediction of which genetic mutations may form neoantigens. Additionally, algorithms predicting how proteins will be processed into peptide epitopes by the proteasome and which peptides bind to the transporter complex are also improving with this research. Now that large screens of all the tumour-specific protein altering mutations are possible, the emerging data from assessment of the immunogenicity of neoantigens suggest that only a minority of variants will form targetable epitopes. The potential for immunotherapeutic targeting of neoantigens will therefore be greater in cancers with a higher frequency of protein altering somatic variants. There is considerable potential in the use of neoantigens to treat patients, either alone or in combination with other immunotherapies and with continued advancements, these potentials will be realised.

Determination of a Predictive Cleavage Motif for Eluted Major Histocompatibility Complex Class II Ligands

CD4⁺ T cells have a major role in regulating immune responses. They are activated by recognition of peptides mostly generated from exogenous antigens through the major histocompatibility complex (MHC) class II pathway. Identification of epitopes is important and computational prediction of epitopes is used widely to save time and resources. Although there are algorithms to predict binding affinity of peptides to MHC II molecules, no accurate methods exist to predict which ligands are generated as a result of natural antigen processing. We utilized a dataset of around 14,000 naturally processed ligands identified by mass spectrometry of peptides eluted from MHC class II expressing cells to investigate the existence of sequence signatures potentially related to the cleavage mechanisms that liberate the presented peptides from their source antigens. This analysis revealed preferred amino acids surrounding both N- and C-terminuses of ligands, indicating sequence-specific cleavage preferences. We used these cleavage motifs to develop a method for predicting naturally processed MHC II ligands, and validated that it had predictive power to identify ligands from independent studies. We further confirmed that prediction of ligands based on cleavage motifs could be combined with predictions of MHC binding, and that the combined prediction had superior performance. However, when attempting to predict CD4⁺ T cell epitopes, either alone or in combination with MHC binding predictions, predictions based on the cleavage motifs did not show predictive power. Given that peptides identified as epitopes based on CD4⁺ T cell reactivity typically do not have well-defined termini, it is possible that motifs are present but outside of the mapped epitope. Our attempts to take that into account computationally did not show any sign of an increased presence of cleavage motifs around well-characterized CD4⁺ T cell epitopes. While it is possible that our attempts to translate the cleavage motifs in MHC II ligand elution data into T cell epitope predictions were suboptimal, other possible explanations are that the cleavage signal is too diluted to be detected, or that elution data are enriched for ligands generated through an antigen processing and presentation pathway that is less frequently utilized for T cell epitopes.

Predicting Antigen Presentation-What Could We Learn From a Million Peptides?

Antigen presentation lies at the heart of immune recognition of infected or malignant cells. For this reason, important efforts have been made to predict which peptides are more likely to bind and be presented by the human leukocyte antigen (HLA) complex at the surface of cells. These predictions have become even more important with the advent of next-generation sequencing technologies that enable researchers and clinicians to rapidly determine the sequences of pathogens (and their multiple variants) or identify non-synonymous genetic alterations in cancer cells. Here, we review recent advances in predicting HLA binding and antigen presentation in human cells. We argue that the very large amount of high-quality mass spectrometry data of eluted (mainly self) HLA ligands generated in the last few years provides unprecedented opportunities to improve our ability to predict antigen presentation and learn new properties of HLA molecules, as demonstrated in many recent studies of naturally presented HLA-I ligands. Although major challenges still lie on the road toward the ultimate goal of predicting immunogenicity, these experimental and computational developments will facilitate screening of putative epitopes, which may eventually help decipher the rules governing T cell recognition.

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.

Pathway based therapeutic targets identification and development of an interactive database CampyNIBase of Campylobacter jejuni RM1221 through non-redundant protein dataset

The bacterial species Campylobacter jejuni RM1221 (CjR) is the primary cause of campylobacteriosis which poses a global threat for human health. Over the years the efficacy of antibiotic treatment is becoming more fruitless due to the development of multiple drug resistant strains. Therefore, identification of new drug targets is a valuable tool for the development of new treatments for affected patients and can be obtained by targeting essential protein(s) of CjR. We conducted this in silico study in order to identify therapeutic targets by subtractive CjR proteome analysis. The most important proteins of the CjR proteome, which includes chokepoint enzymes, plasmid, virulence and antibiotic resistant proteins were annotated and subjected to subtractive analyses to filter out the CjR essential proteins from duplicate or human homologous proteins. Through the subtractive and characterization analysis we have identified 38 eligible therapeutic targets including 1 potential vaccine target. Also, 12 potential targets were found in interactive network, 5 targets to be dealt with FDA approved drugs and one pathway as potential pathway based drug target. In addition, a comprehensive database 'CampyNIBase' has also been developed. Besides the results of this study, the database is enriched with other information such as 3D models of the identified targets, experimental structures and Expressed Sequence Tag (EST) sequences. This study, including the database might be exploited for future research and the identification of effective therapeutics against campylobacteriosis. URL: (http://nib.portal.gov.bd/site/page/4516e965-8935-4129-8c3f-df95e754c562#Banner).

Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes

Recent advances in proteomics and mass-spectrometry have widely expanded the detectable peptide repertoire presented by major histocompatibility complex (MHC) molecules on the cell surface, collectively known as the immunopeptidome. Finely characterizing the immunopeptidome brings about important basic insights into the mechanisms of antigen presentation, but can also reveal promising targets for vaccine development and cancer immunotherapy. This report describes a number of practical and efficient approaches to analyze immunopeptidomics data, discussing the identification of meaningful sequence motifs in various scenarios and considering current limitations. Guidelines are provided for the filtering of false hits and contaminants, and to address the problem of motif deconvolution in cell lines expressing multiple MHC alleles, both for the MHC class I and class II systems. Finally, it is demonstrated how machine learning can be readily employed by non-expert users to generate accurate prediction models directly from mass-spectrometry eluted ligand data sets.

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.

Bioinformatics Tools for the Prediction of T-Cell Epitopes

T-cell responses are activated by specific peptides, called epitopes, presented on the cell surface by MHC molecules. Binding of peptides to the MHC is the most selective step in T-cell antigen presentation and therefore an essential factor in the selection of potential epitopes. Several in-vitro methods have been developed for the determination of peptide binding to MHC molecules, but these are all costly and time-consuming. In consequence, significant effort has been dedicated to the development of in-silico methods to model this event. Here, we describe two such tools, NetMHCcons and NetMHCIIpan, for the prediction of peptide binding to MHC class I and class II molecules, respectively, involved in the activation pathways of CD8+ and CD4+ T cells.

Designing of CD8+ and CD8+-overlapped CD4+ epitope vaccine by targeting late and early proteins of human papillomavirus

BACKGROUND AND AIM

Human papillomavirus (HPV) is an oncogenic agent that causes over 90% of cases of cervical cancer in the world. Currently available prophylactic vaccines are type specific and have less therapeutic efficiency. Therefore, we aimed to predict the potential species-specific and therapeutic epitopes from the protein sequences of HPV45 by using different immunoinformatics tools.

METHODS

Initially, we determined the antigenic potential of late (L1 and L2) and early (E1, E2, E4, E5, E6, and E7) proteins. Then, major histocompatibility complex class I-restricted CD8⁺ T-cell epitopes were selected based on their immunogenicity. In addition, epitope conservancy, population coverage (PC), and target receptor-binding affinity of the immunogenic epitopes were determined. Moreover, we predicted the possible CD8⁺, nested interferon gamma (IFN-γ)-producing CD4⁺, and linear B-cell epitopes. Further, antigenicity, allergenicity, immunogenicity, and system biology-based virtual pathway associated with cervical cancer were predicted to confirm the therapeutic efficiency of overlapped epitopes.

RESULTS

Twenty-seven immunogenic epitopes were found to exhibit cross-protection (≥55%) against the 15 high-risk HPV strains (16, 18, 31, 33, 35, 39, 51, 52, 56, 58, 59, 68, 69, 73, and 82). The highest PC was observed in Europe (96.30%), North America (93.98%), West Indies (90.34%), North Africa (90.14%), and East Asia (89.47%). Binding affinities of 79 docked complexes observed as global energy ranged from -10.80 to -86.71 kcal/mol. In addition, CD8⁺ epitope-overlapped segments in CD4⁺ and B-cell epitopes demonstrated that immunogenicity and IFN-γ-producing efficiency ranged from 0.0483 to 0.5941 and 0.046 to 18, respectively. Further, time core simulation revealed the overlapped epitopes involved in pRb, p53, COX-2, NF-X1, and HPV45 infection signaling pathways.

CONCLUSION

Even though the results of this study need to be confirmed by further experimental peptide sensitization studies, the findings on immunogenic and IFN-γ-producing CD8⁺ and overlapped epitopes provide new insights into HPV vaccine development.

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate antigens known as epitopes. There is great interest in identifying epitopes in antigens for a number of practical reasons, including understanding disease etiology, immune monitoring, developing diagnosis assays, and designing epitope-based vaccines. Epitope identification is costly and time-consuming as it requires experimental screening of large arrays of potential epitope candidates. Fortunately, researchers have developed in silico prediction methods that dramatically reduce the burden associated with epitope mapping by decreasing the list of potential epitope candidates for experimental testing. Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.

Informatics for cancer immunotherapy

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.

In Silico Validation of D7 Salivary Protein-derived B- and T-cell Epitopes of Aedes aegypti as Potential Vaccine to Prevent Transmission of Flaviviruses and Togaviruses to Humans

Mosquito (Aedes aegyptii) salivary proteins play a crucial role in facilitating viral transmission from vector-to-host due to their role in facilitating the "blood meal" of the vector. Three main proteins, D7, aegyptin and Sialokinin play a role in this process. Using in-silico programs, we identified B- and T-cell epitopes in the mosquito salivary proteins D7 long and short form. T-cell epitopes with high affinity to the most prevalent HLA MHC class-I supertypes among different population groups was chosen. It is our postulate that these epitopes could be successful in eliciting B and T cell responses, which would decrease the vector blood meal efficiency and hence protect against host infection by certain viruses. These include causative agents like Dengue viruses, Chikungunya virus, Zika and Yellow fever viruses. These viruses are of major public health importance in several countries in the Americas, Asia and Africa. Experimental evidence exists in previously published literature showing the protective effect of antibodies to certain salivary proteins in susceptible hosts. A novel approach of immunizing humans against the vector proteins to reduce transmission of viruses is now under investigation in several laboratories. We have identified the following two B cell epitopes LAALHVTAAPLWDAKDPEQF one from D7L and the other TSEYPDRQNQIEELNKLCKN from D7S. Likewise, two T cell epitopes MTSKNELDV one from D7L and the other YILCKASAF from D7S with affinity to the predominant MHC class-I supertypes were identified towards evaluation as potential vaccine.

Host genotype and time dependent antigen presentation of viral peptides: predictions from theory

The rate of progression of HIV infected individuals to AIDS is known to vary with the genotype of the host, and is linked to their allele of human leukocyte antigen (HLA) proteins, which present protein degradation products at the cell surface to circulating T-cells. HLA alleles are associated with Gag-specific T-cell responses that are protective against progression of the disease. While Pol is the most conserved HIV sequence, its association with immune control is not as strong. To gain a more thorough quantitative understanding of the factors that contribute to immunodominance, we have constructed a model of the recognition of HIV infection by the MHC class I pathway. Our model predicts surface presentation of HIV peptides over time, demonstrates the importance of viral protein kinetics, and provides evidence of the importance of Gag peptides in the long-term control of HIV infection. Furthermore, short-term dynamics are also predicted, with simulation of virion-derived peptides suggesting that efficient processing of Gag can lead to a 50% probability of presentation within 3 hours post-infection, as observed experimentally. In conjunction with epitope prediction algorithms, this modelling approach could be used to refine experimental targets for potential T-cell vaccines, both for HIV and other viruses.

Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes

T cell specificity emerges from a myriad of processes, ranging from the biological pathways that control T cell signaling to the structural and physical mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and physical studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophysical principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunology.

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data

Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes.

Immunodominance of Adenovirus-Derived CD8+ T Cell Epitopes Interferes with the Induction of Transgene-Specific Immunity in Adenovirus-Based Immunization

Adenovirus (Ad)-based immunization is a popular approach in vaccine development, and Ad-based vectors are renowned for their potential to induce strong CD8⁺ T cell responses to the encoded transgene. Surprisingly, we previously found in the mouse Friend retrovirus (FV) model that Ad-based immunization did not induce CD8⁺ T cell responses to the FV Leader-Gag-derived immunodominant epitope GagL_85-93 We show now that induction of GagL_85-93-specific CD8⁺ T cells was highly effective when leader-Gag was delivered by plasmid DNA immunization, implying a role for Ad-derived epitopes in mediating unresponsiveness. By immunizing with DNA constructs encoding strings of GagL_85-93 and the two Ad-derived epitopes DNA-binding protein_418-426 (DBP_418-426) and hexon_486-494, we confirmed that Ad epitopes prevent induction of GagL_85-93-specific CD8⁺ T cells. Interestingly, while DBP_418-426 did not interfere with GagL_85-93-specific CD8⁺ T cell induction, the H-2D^d-restricted hexon_486-494 suppressed the CD8⁺ T cell response to the H-2D^b-restricted GagL_85-93 strongly in H-2^b/d mice but not in H-2^b/b mice. This finding indicates that competition occurs at the level of responding CD8⁺ T cells, and we could indeed demonstrate that coimmunization with an interleukin 2 (IL-2)-encoding plasmid restored GagL_85-93-specific CD8⁺ T cell responses to epitope strings in the presence of hexon_486-494 IL-2 codelivery did not restore GagL_85-93 responsiveness in Ad-based immunization, however, likely due to the presence of further epitopes in the Ad vector. Our findings show that seemingly immunodominant transgene epitopes can be dominated by Ad-derived epitopes. These findings underline the importance of thorough characterization of vaccine vectors, and modifications of vectors or immunogens may be required to prevent impaired transgene-specific immune responses.IMPORTANCE Ad-based vectors are widely used in experimental preclinical and clinical immunization studies against numerous infectious agents, such as human immunodeficiency virus, Ebola virus, Plasmodium falciparum, or Mycobacterium tuberculosis Preexisting immunity to Ad-based vectors is widely recognized as a hindrance to the widespread use of Ad-based vectors for immunizations in humans; however, our data show that an immune response to Ad-derived T cell epitopes can also result in loss or impairment of transgene-specific immune responses in prenaive vaccinees due to immune competition. Our results highlight that seemingly immunodominant epitopes may be affected by dominance of vector-derived epitopes, and modifications of the vector design or the immunogens employed in immunization may lead to more effective vaccines.

The Role of Multiscale Protein Dynamics in Antigen Presentation and T Lymphocyte Recognition

T lymphocytes are stimulated when they recognize short peptides bound to class I proteins of the major histocompatibility complex (MHC) protein, as peptide-MHC complexes. Due to the diversity in T-cell receptor (TCR) molecules together with both the peptides and MHC proteins they bind to, it has been difficult to design vaccines and treatments based on these interactions. Machine learning has made some progress in trying to predict the immunogenicity of peptide sequences in the context of specific MHC class I alleles but, as such approaches cannot integrate temporal information and lack explanatory power, their scope will always be limited. Here, we advocate a mechanistic description of antigen presentation and TCR activation which is explanatory, predictive, and quantitative, drawing on modeling approaches that collectively span several length and time scales, being capable of furnishing reliable biological descriptions that are difficult for experimentalists to provide. It is a form of multiscale systems biology. We propose the use of chemical rate equations to describe the time evolution of the foreign and host proteins to explain how the original proteins end up being presented on the cell surface as peptide fragments, while we invoke molecular dynamics to describe the key binding processes on the molecular level, including those of peptide-MHC complexes with TCRs which lie at the heart of the immune response. On each level, complementary methods based on machine learning are available, and we discuss the relationship between these divergent approaches. The pursuit of predictive mechanistic modeling approaches requires experimentalists to adapt their work so as to acquire, store, and expose data that can be used to verify and validate such models.

ImmunoNodes - graphical development of complex immunoinformatics workflows

Background

Immunoinformatics has become a crucial part in biomedical research. Yet many immunoinformatics tools have command line interfaces only and can be difficult to install. Web-based immunoinformatics tools, on the other hand, are difficult to integrate with other tools, which is typically required for the complex analysis and prediction pipelines required for advanced applications.

Result

We present ImmunoNodes, an immunoinformatics toolbox that is fully integrated into the visual workflow environment KNIME. By dragging and dropping tools and connecting them to indicate the data flow through the pipeline, it is possible to construct very complex workflows without the need for coding.

Conclusion

ImmunoNodes allows users to build complex workflows with an easy to use and intuitive interface with a few clicks on any desktop computer.

Characterizing neoantigens for personalized cancer immunotherapy

Somatic mutations can generate neoantigens that are presented on MHC molecules and drive effective T cells responses against cancer. Mutation load in cancer patients predicts response to immune checkpoint blockade therapy. Additionally, vaccination targeting neoantigens controls established tumor growth in preclinical models. These recent findings led to a renewed interest in the field of cancer vaccines and the development of antigen-targeted cancer immunotherapies. However, targeting neoantigens is challenging, as most mutations are unique to each cancer patient. In addition, only a small fraction of the mutations are immunogenic and therefore their accurate prediction is critical. In this review, we discuss the properties of neoantigens that influence their immunogenicity, along with questions that remain to be addressed in order to improve prediction algorithms.

In silico-based vaccine design against Ebola virus glycoprotein

Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.

The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design

The task of epitope discovery and vaccine design is increasingly reliant on bioinformatics analytic tools and access to depositories of curated data relevant to immune reactions and specific pathogens. The Immune Epitope Database and Analysis Resource (IEDB) was indeed created to assist biomedical researchers in the development of new vaccines, diagnostics, and therapeutics. The Analysis Resource is freely available to all researchers and provides access to a variety of epitope analysis and prediction tools. The tools include validated and benchmarked methods to predict MHC class I and class II binding. The predictions from these tools can be combined with tools predicting antigen processing, TCR recognition, and B cell epitope prediction. In addition, the resource contains a variety of secondary analysis tools that allow the researcher to calculate epitope conservation, population coverage, and other relevant analytic variables. The researcher involved in vaccine design and epitope discovery will also be interested in accessing experimental published data, relevant to the specific indication of interest. The database component of the IEDB contains a vast amount of experimentally derived epitope data that can be queried through a flexible user interface. The IEDB is linked to other pathogen-specific and immunological database resources.

Genomic analysis of 63,220 tumors reveals insights into tumor uniqueness and targeted cancer immunotherapy strategies

Background

The integration of genomics with immunotherapy has potential value for cancer vaccine development. Given the clinical successes of immune checkpoint modulators, interest in cancer vaccines as therapeutic options has been revived. Current data suggest that each tumor contains a unique set of mutations (mutanome), thus requiring the creation of individualized cancer vaccines. However, rigorous analysis of non-individualized cancer immunotherapy approaches across multiple cancer types and in the context of known driver alterations has yet to be reported. We therefore set out to determine the feasibility of a generalizable cancer vaccine strategy based on targeting multiple neoantigens in an HLA-A/B subtype-directed manner.

Methods

A cancer gene-focused, hybrid capture-based genomic analysis was performed on 63,220 unique tumors. Neoantigens were predicted using a combined peptide processing and MHC-I binding prediction tool (IEDB) for all recurrent (>10 tumors) missense alterations and non-frameshift indels for the two most common HLA-A/B subtypes in North American/European populations.

Results

Despite being overwhelmingly unique overall, many mutanomes (~45%) contain at least one mutation from a set of ten mutations chosen to maximize the number of unique tumors. This held true for tumors driven by KRAS G12C (n = 1799), PIK3CA E545K (n = 1713), or EGFR L858R (n = 478) alterations, which define distinct sample subsets. We therefore hypothesized that sets of carefully selected mutations/neoantigens may allow the development of broadly applicable semi-universal cancer vaccines. To test the feasibility of such an approach, antigen processing and MHC-I binding prediction was applied for HLA subtypes A*01:01/B*08:01 and A*02:01/B*44:02. In tumors with a specific HLA type, 0.7 and 2.5% harbored at least one of a set of ten neoantigens predicted to bind to each subtype, respectively. In comparison, KRAS G12C-driven tumors produced similar results (0.8 and 2.6% for each HLA subtype, respectively), indicating that neoantigen targets still remain highly diverse even within the context of major driver mutations.

Conclusions

This “best case scenario” analysis of a large tumor set across multiple cancer types and in the context of driver alterations reveals that semi-universal, HLA-specific cancer vaccine strategies will be relevant to only a small subset of the general population. Similar analysis of whole exome/genome sequencing, although not currently feasible at scale in a clinical setting, will likely uncover further diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0408-2) contains supplementary material, which is available to authorized users.

Unconventional Peptide Presentation by Major Histocompatibility Complex (MHC) Class I Allele HLA-A*02:01: BREAKING CONFINEMENT

Peptide antigen presentation by major histocompatibility complex (MHC) class I proteins initiates CD8⁺ T cell-mediated immunity against pathogens and cancers. MHC I molecules typically bind peptides with 9 amino acids in length with both ends tucked inside the major A and F binding pockets. It has been known for a while that longer peptides can also bind by either bulging out of the groove in the middle of the peptide or by binding in a zigzag fashion inside the groove. In a recent study, we identified an alternative binding conformation of naturally occurring peptides from Toxoplasma gondii bound by HLA-A*02:01. These peptides were extended at the C terminus (PΩ) and contained charged amino acids not more than 3 residues after the anchor amino acid at PΩ, which enabled them to open the F pocket and expose their C-terminal extension into the solvent. Here, we show that the mechanism of F pocket opening is dictated by the charge of the first charged amino acid found within the extension. Although positively charged amino acids result in the Tyr-84 swing, amino acids that are negatively charged induce a not previously described Lys-146 lift. Furthermore, we demonstrate that the peptides with alternative binding modes have properties that fit very poorly to the conventional MHC class I pathway and suggest they are presented via alternative means, potentially including cross-presentation via the MHC class II pathway.

Peptide Processing Is Critical for T-Cell Memory Inflation and May Be Optimized to Improve Immune Protection by CMV-Based Vaccine Vectors

Cytomegalovirus (CMV) elicits long-term T-cell immunity of unparalleled strength, which has allowed the development of highly protective CMV-based vaccine vectors. Counterintuitively, experimental vaccines encoding a single MHC-I restricted epitope offered better immune protection than those expressing entire proteins, including the same epitope. To clarify this conundrum, we generated recombinant murine CMVs (MCMVs) encoding well-characterized MHC-I epitopes at different positions within viral genes and observed strong immune responses and protection against viruses and tumor growth when the epitopes were expressed at the protein C-terminus. We used the M45-encoded conventional epitope HGIRNASFI to dissect this phenomenon at the molecular level. A recombinant MCMV expressing HGIRNASFI on the C-terminus of M45, in contrast to wild-type MCMV, enabled peptide processing by the constitutive proteasome, direct antigen presentation, and an inflation of antigen-specific effector memory cells. Consequently, our results indicate that constitutive proteasome processing of antigenic epitopes in latently infected cells is required for robust inflationary responses. This insight allows utilizing the epitope positioning in the design of CMV-based vectors as a novel strategy for enhancing their efficacy.

Experimental cytomegalovirus (CMV) based vaccine vectors have provided highly encouraging results as innovative vaccine formulations against deadly virus infections, such as Ebola or AIDS. Nevertheless, it has remained incompletely understood why CMV is so efficient at stimulating T-lymphocytes, the immune cells that recognize pathogens within infected cells. We have generated an array of CMV mutants expressing the same antigen in different genes or in different parts of the same gene. This allowed us to identify that the immediate environment of the antigen, rather than properties of the antigen itself, crucially determine the immune protection conferred by CMV-based vaccines, implying that optimal immunity depends on the ability of host cells to degrade CMV proteins into peptides, short units that are recognized by T-cells. Detailed analysis revealed that strong and sustained T-cell immunity occurs only when their antigenic targets are processed by a primitive cellular machinery that is present in all cells of the body, rather than by its newly-evolved counterpart, which is present only in specialized antigen-presenting cells. Most importantly, our results provide a simple strategy to develop improved CMV vaccines by positioning the antigenic peptides at the right spot in CMV proteins.

Identification of epitope-based peptide vaccine candidates against enterotoxigenic Escherichia coli: a comparative genomics and immunoinformatics approach

Enterotoxigenic Escherichia coli (ETEC) associated diarrhea remains a global killer with an estimated annual incidence rate of 840 million infections and 3 800 000 deaths worldwide. There are no vaccines available for ETEC and the traditional vaccine development approach is arduous and time consuming. Thus, alternative in silico approaches for epitope prediction have engrossed the interest of researchers to reduce resources and time of vaccine development. Computational approaches are playing a crucial role in fighting against rapidly growing infectious organisms. In this study we employed an integrated comparative genomics and immunoinformatics approach for proteome scale identification of peptide vaccine candidates. The proteins shared between both ETEC E24377A and H10407 strains, but lacking in commensal E. coli SE11, were subjected to immunoinformatics analysis. For a protein pool shared between different pathogenic ETEC strains, we investigated varied physicochemical and immunogenic properties to prioritize potential vaccine candidates. Epitopes were further tested using docking studies to bind in the MHC-I binding cleft. Predicted epitopes provided more than a 95% population coverage in diarrhea endemic regions presented by major MHC-I supertypes, and bind efficiently to a MHC molecule. We conclude by accentuating that the epitopes predicted in this study are believed to accelerate the development of successful vaccines to control or prevent ETEC infections, albeit the results require experimental validation using model organisms. This study underscores that in silico approaches, together with omics data, hold great potential to be utilized for rapid and reliable genome-wide screening for identification of vaccine candidates against devastating infectious diseases.

Breast Cancer Immunology and Immunotherapy: Current Status and Future Perspectives

Cancer immunology has gained renewed interest in the past few years due to emerging findings on mechanisms involved in tumoral immune evasion. Indisputably, immune edition is currently considered a critical hallmark of cancer. Basic research has revealed new targets which can be modulated in the clinical setting with new compounds and strategies. As recent evidence confirms, breast cancer (BC) is a complex and heterogeneous disease in which host immune responses play a substantial role. T-infiltrating lymphocytes measurement is suggested as a powerful new tool necessary to predict early BC evolution, especially in HER2-positive and triple negative subtypes. However, T-infiltrating lymphocytes, genomic platforms, and many other biomarkers in tissue and peripheral blood (e.g., regulatory T cells and myeloid-derived suppressor cells) are not the only factors being evaluated regarding their potential role as prognostic and/or predictive factors. Many ongoing clinical trials are exploring the activity of immune checkpoint modulators in BC treatment, both in the advanced and neoadjuvant setting. Although this field is expanding with exciting new discoveries and promising clinical results-and creating great expectations-there remain many uncertainties yet to be addressed satisfactorily before this long awaited therapeutic promise can come to fruition.

Excavating the surface-associated and secretory proteome of Mycobacterium leprae for identifying vaccines and diagnostic markers relevant immunodominant epitopes

For centuries, Mycobacterium leprae, etiological agent of leprosy, has been afflicting mankind regardless of extensive use of live-attenuated vaccines and antibiotics. Surface-associated and secretory proteins (SASPs) are attractive targets against bacteria. We have integrated biological knowledge with computational approaches and present a proteome-wide identification of SASPs. We also performed computational assignment of immunodominant epitopes as coordinates of prospective antigenic candidates in most important class of SASPs, the outer membrane proteins (OMPs). Exploiting the known protein sequence and structural characteristics shared by the SASPs from bacteria, 17 lipoproteins, 11 secretory and 19 novel OMPs (including 4 essential proteins) were identified in M. leprae As OMPs represent the most exposed antigens on the cell surface, their immunoinformatics analysis showed that the identified 19 OMPs harbor T-cell MHC class I epitopes and class II epitopes against HLA-DR alleles (54), while 15 OMPs present potential T-cell class II epitopes against HLA-DQ alleles (6) and 7 OMPs possess T-cell class II epitopes against HLA-DP alleles (5) of humans. Additionally, 11 M. leprae OMPs were found to have B-cell epitopes and these may be considered as prime candidates for the development of new immunotherapeutics against M. leprae.

Surface proteome mining for identification of potential vaccine candidates against Campylobacter jejuni: an in silico approach

Campylobacter jejuni remains a major cause of human gastroenteritis with estimated annual incidence rate of 450 million infections worldwide. C. jejuni is a major burden to public health in both socioeconomically developing and industrialized nations. Virulence determinants involved in C. jejuni pathogenesis are multifactorial in nature and not yet fully understood. Despite the completion of the first C. jejuni genome project in 2000, there are currently no vaccines in the market against this pathogen. Traditional vaccinology approach is an arduous and time extensive task. Omics techniques coupled with sequencing data have engaged researcher's attention to reduce the time and resources applied in the process of vaccine development. Recently, there has been remarkable increase in development of in silico analysis tools for efficiently mining biological information obscured in the genome. In silico approaches have been crucial for combating infectious diseases by accelerating the pace of vaccine development. This study employed a range of bioinformatics approaches for proteome scale identification of peptide vaccine candidates. Whole proteome of C. jejuni was investigated for varied properties like antigenicity, allergenicity, major histocompatibility class (MHC)-peptide interaction, immune cell processivity, HLA distribution, conservancy, and population coverage. Predicted epitopes were further tested for binding in MHC groove using computational docking studies. The predicted epitopes were conserved; covered more than 80 % of the world population and were presented by MHC-I supertypes. We conclude by underscoring that the epitopes predicted are believed to expedite the development of successful vaccines to control or prevent C. jejuni infections albeit the results need to be experimentally validated.

Immunomics: a 21st century approach to vaccine development for complex pathogens

Immunomics is a relatively new field of research which integrates the disciplines of immunology, genomics, proteomics, transcriptomics and bioinformatics to characterize the host-pathogen interface. Herein, we discuss how rapid advances in molecular immunology, sophisticated tools and molecular databases are facilitating in-depth exploration of the immunome. In our opinion, an immunomics-based approach presides over traditional antigen and vaccine discovery methods that have proved ineffective for highly complex pathogens such as the causative agents of malaria, tuberculosis and schistosomiasis that have evolved genetic and immunological host-parasite adaptations over time. By using an integrative multidisciplinary approach, immunomics offers enormous potential to advance 21st century antigen discovery and rational vaccine design against complex pathogens such as the Plasmodium parasite.

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.

Reconstitution of CD8 T Cells Protective against Cytomegalovirus in a Mouse Model of Hematopoietic Cell Transplantation: Dynamics and Inessentiality of Epitope Immunodominance

Successful reconstitution of cytomegalovirus (CMV)-specific CD8⁺ T cells by hematopoietic cell transplantation (HCT) gives a favorable prognosis for the control of CMV reactivation and prevention of CMV disease after hematoablative therapy of hematopoietic malignancies. In the transient immunocompromised state after HCT, pre-emptive cytoimmunotherapy with viral epitope-specific effector or memory CD8⁺ T cells is a promising option to speed up antiviral control. Despite high-coding capacity of CMVs and a broad CD8⁺ T-cell response on the population level, which reflects polymorphism in major histocompatibility complex class-I (MHC-I) glycoproteins, the response in terms of quantity of CD8⁺ T cells in any individual is directed against a limited set of CMV-encoded epitopes selected for presentation by the private repertoire of MHC-I molecules. Such epitopes are known as “immunodominant” epitopes (IDEs). Besides host immunogenetics, genetic variance in CMV strains harbored as latent viruses by an individual HCT recipient can also determine the set of IDEs, which complicates a “personalized immunotherapy.” It is, therefore, an important question if IDE-specific CD8⁺ T-cell reconstitution after HCT is critical or dispensable for antiviral control. As viruses with targeted mutations of IDEs cannot be experimentally tested in HCT patients, we employed the well-established mouse model of HCT. Notably, control of murine CMV (mCMV) after HCT was comparably efficient for IDE-deletion mutant mCMV-Δ4IDE and the corresponding IDE-expressing revertant virus mCMV-Δ4IDE-rev. Thus, antigenicity-loss mutations in IDEs do not result in loss-of-function of a polyclonal CD8⁺ T-cell population. Although IDE deletion was not associated with global changes in the response to non-IDE epitopes, the collective of non-IDE-specific CD8⁺ T-cells infiltrates infected tissue and confines infection within nodular inflammatory foci. We conclude from the model, and predict also for human CMV, that there is no need to exclusively aim for IDE-specific immunoreconstitution.

An in silico approach predicted potential therapeutics that can confer protection from maximum pathogenic Hantaviruses

Aim: In silico approach is used to identify most potent epitope and drug against pathogenic Hantavirus against which no approved therapeutics exist. Methods: Nucleocapsid protein sequences were retrieved, aligned and conserved regions were analyzed for the presence of B- and T-cell epitopes, and pockets for potential drugs. Results: T-cell epitope SYLRRTQSM and B-cell epitopes SYLRRTQ and YLRRTQSM appeared to be highly conserved, antigenic, nonallergenic. The T-cell epitope bound to maximum alleles. Thus, SYLRRTQSM would likely elicit both T- and B-cell immunity. High-throughput screening of Traditional Chinese Medicine database by docking technique revealed a potential drug, compound 46547 (1R,11S,15S,18S,20S,21R,22S)-12-oxa-8,17-diazaheptacyclo[15.5.2.0^{1,18}.0^{2,7}.0^{8,22}.0^{11,21}.0^{15,20}]tetracosa-2,4,6-trien-9-one. Conclusion: Our results predict potential therapeutics against multiple strains of pathogenic Hantavirus, but requires validation by in vivo experimentation.

Two highly similar LAEDDTNAQKT and LTDKIGTEI epitopes in G glycoprotein may be useful for effective epitope based vaccine design against pathogenic Henipavirus

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Computational approaches were used to identify epitopes for vaccine development against Henipavirus.

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The strategy combines B-cell epitope prediction, T-cell epitope prediction, docking simulation assay, and cytotoxicity analysis of the G glycoprotein.

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Two potential epitopes were predicted which may be used for the development of peptide vaccines.

Nipah virus and Hendra virus, two members of the genus Henipavirus, are newly emerging zoonotic pathogens which cause acute respiratory illness and severe encephalitis in human. Lack of the effective antiviral therapy endorses the urgency for the development of vaccine against these deadly viruses. In this study, we employed various computational approaches to identify epitopes which has the potential for vaccine development. By analyzing the immune parameters of the conserved sequences of G glycoprotein using various databases and bioinformatics tools, we identified two potential epitopes which may be used as peptide vaccines. Using different B cell epitope prediction servers, four highly similar B cell epitopes were identified. Immunoinformatics analyses revealed that LAEDDTNAQKT is a highly flexible and accessible B-cell epitope to antibody. Highly similar putative CTL epitopes were analyzed for their binding with the HLA-C 12*03 molecule. Docking simulation assay revealed that LTDKIGTEI has significantly lower binding energy, which bolstered its potential as epitope-based vaccine design. Finally, cytotoxicity analysis has also justified their potential as promising epitope-based vaccine candidate. In sum, our computational analysis indicates that either LAEDDTNAQKT or LTDKIGTEI epitope holds a promise for the development of universal vaccine against all kinds of pathogenic Henipavirus. Further in vivo and in vitro studies are necessary to validate the obtained findings.

Designing string-of-beads vaccines with optimal spacers

String-of-beads polypeptides allow convenient delivery of epitope-based vaccines. The success of a polypeptide relies on efficient processing: constituent epitopes need to be recovered while avoiding neo-epitopes from epitope junctions. Spacers between epitopes are employed to ensure this, but spacer selection is non-trivial.

We present a framework to determine optimally the length and sequence of a spacer through multi-objective optimization for human leukocyte antigen class I restricted polypeptides. The method yields string-of-bead vaccines with flexible spacer lengths that increase the predicted epitope recovery rate fivefold while reducing the immunogenicity from neo-epitopes by 44 % compared to designs without spacers.

T-Cell Epitope Discovery for Therapeutic Cancer Vaccines

The success of recent immune checkpoint blockade trials in solid tumors has demonstrated the tremendous potential of immune-mediated treatment strategies for cancer therapy. These immune therapies activate preexisting cytotoxic CD8(+) T cells (CTL) to selectively target and eradicate malignant cells. In vitro models suggest that these therapies may be more effective in combination with priming of CTL using cancer vaccines. CTL-mediated tumor targeting is achieved by its recognition of tumor antigenic epitopes presented on human leukocyte antigen (HLA) class I molecules by tumor cells. Discovering CTL-antigenic epitopes is therefore central to the design of therapeutic T-cell vaccines and immune monitoring of these complex immunotherapies. However, selecting and monitoring T-cell epitopes remains difficult due to the extensive polymorphism of HLA alleles and the presence of confounding non-immunogenic self-peptides. To overcome these challenges, this chapter presents methodologies for the design of CTL-targeted vaccines using selection of target HLA alleles, novel integrated computational strategies to predict HLA-class I CTL epitopes, and epitope validation methods using short-term ex vivo T-cell stimulation. This strategy results in the improved efficiency for selecting antigenic epitopes for CTL-mediated vaccines and for immune monitoring of tumor antigens.

A multi-subunit based, thermodynamically stable model vaccine using combined immunoinformatics and protein structure based approach

Immunizations with the conventional vaccines have failed to effectively inhibit the incidences and further dissemination of the infections. To address it, we have implemented protein structure based strategies to design an efficient multi-epitope subunit vaccine against Mycobacterium avium subsp. paratuberculosis (MAP). Previously reported immunodominant peptide epitope sequences from MAP1611 protein were conjugated together with a stretch of conserved amino acid residues of heparin-binding hemagglutinin, reported as a TLR4 agonist and was employed as an adjuvant to polarize the cellular responses toward host protective Th1 responses. These three types of component peptides were combined with the help of relevant linkers for efficient separation to improve and intensify the antigen processing and presentation. The primary structures of these multi peptides were 3-dimensional homology modeled to yield the final chimeric vaccine. Further, its conformational correctness and stability enhancement was assessed using molecular dynamics (MD) simulations. Finally, disulfide engineering in the most flexible regions of the molecule yielded three potential mutants, Y593C-E610C, Q631C-A634C and a double mutant Q631C-A634C/Y593C-E610C. The double mutant represents thermodynamically most stable version among them. It is potentially highly antigenic, soluble and non-allergen molecule interacting with the TLR receptor expressed on the immune cells. This vaccine contains both T-cell and several B-cell epitopes and an adjuvant which potentially possess protective cellular and humoral immune responses triggering properties. The presented vaccine strategy will be proven a promising pathogen specific candidate with wide therapeutic application against MAP which may be extended to other prevalent infections in future.

Targeting the undruggable: immunotherapy meets personalized oncology in the genomic era

Owing to recent advances in genomic technologies, personalized oncology is poised to fundamentally alter cancer therapy. In this paradigm, the mutational and transcriptional profiles of tumors are assessed, and personalized treatments are designed based on the specific molecular abnormalities relevant to each patient's cancer. To date, such approaches have yielded impressive clinical responses in some patients. However, a major limitation of this strategy has also been revealed: the vast majority of tumor mutations are not targetable by current pharmacological approaches. Immunotherapy offers a promising alternative to exploit tumor mutations as targets for clinical intervention. Mutated proteins can give rise to novel antigens (called neoantigens) that are recognized with high specificity by patient T cells. Indeed, neoantigen-specific T cells have been shown to underlie clinical responses to many standard treatments and immunotherapeutic interventions. Moreover, studies in mouse models targeting neoantigens, and early results from clinical trials, have established proof of concept for personalized immunotherapies targeting next-generation sequencing identified neoantigens. Here, we review basic immunological principles related to T-cell recognition of neoantigens, and we examine recent studies that use genomic data to design personalized immunotherapies. We discuss the opportunities and challenges that lie ahead on the road to improving patient outcomes by incorporating immunotherapy into the paradigm of personalized oncology.

Epitope-based peptide vaccine design and target site depiction against Ebola viruses: an immunoinformatics study

Ebola viruses (EBOVs) have been identified as an emerging threat in recent year as it causes severe haemorrhagic fever in human. Epitope‐based vaccine design for EBOVs remains a top priority because a mere progress has been made in this regard. Another reason is the lack of antiviral drug and licensed vaccine although there is a severe outbreak in Central Africa. In this study, we aimed to design an epitope‐based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites using various immunoinformatics and docking simulation tools. The capacity to induce both humoral and cell‐mediated immunity by T cell and B cell was checked for the selected protein. The peptide region spanning 9 amino acids from 42 to 50 and the sequence TLASIGTAF were found as the most potential B and T cell epitopes, respectively. This peptide could interact with 12 HLAs and showed high population coverage up to 80.99%. Using molecular docking, the epitope was further appraised for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post‐therapeutic strategy, docking study of predicted 3D structure identified suitable therapeutic inhibitor against targeted protein. However, this computational epitope‐based peptide vaccine designing and target site prediction against EBOVs open up a new horizon which may be the prospective way in Ebola viruses research; the results require validation by in vitro and in vivo experiments.

A Leishmania-specific hypothetical protein expressed in both promastigote and amastigote stages of Leishmania infantum employed for the serodiagnosis of, and as a vaccine candidate against, visceral leishmaniasis

BACKGROUND

LiHyV is an antigenic hypothetical protein present in both promastigote and amastigote stages of Leishmania infantum, which was recently identified by an immunoproteomic approach. A recombinant version of this protein (rLiHyV) was evaluated as a diagnostic marker for canine VL (CVL). In addition, the prophylactic efficacy of the rLiHyV protein, and two of its CD8(+) T cell epitopes, has been analyzed in a murine model of visceral leishmaniasis (VL).

METHODS

Initially, the rLiHyV protein was evaluated by an ELISA technique for the serodiagnosis of CVL. Secondly, vaccines composed of the recombinant protein and both chemically synthesized peptides, combined with saponin as an adjuvant; were administered subcutaneously into BALB/c mice. The cellular and humoral responses generated by vaccination were evaluated. In addition, the parasite burden and immune response were studied 10 weeks after L. infantum infection.

RESULTS

The rLiHyV protein was recognized by antibodies of VL dogs. No cross-reactivity was obtained with sera from dogs vaccinated with a Brazilian commercial vaccine, with sera from animals infected with Trypanosoma cruzi, Babesia canis and Ehrlichia canis, or those from non-infected animals living in an endemic area for leishmaniasis. After challenge with L. infantum, spleen cells of BALB/c mice vaccinated with rLiHyV/saponin stimulated with parasite antigens showed a higher production of IFN-γ, IL-12 and GM-CSF, than the same cells obtained from mice vaccinated with the individual peptides, or mice from control (inoculated with saline or saponin) groups. This Th1-type cellular response observed in rLiHyV/saponin vaccinated mice was accompanied by the induction of parasite-specific IgG2a isotype antibodies. Animals immunized with rLiHyV/saponin showed significant reductions in the parasite burden in the liver, spleen, bone marrow and in the lymph nodes draining the paws relative to control mice.

CONCLUSIONS

The present study showed for the first time that the L. infantum LiHyV protein could be considered as a vaccine candidate against L. infantum infection, as well as a diagnostic marker for CVL.

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

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

Acyclovir Has Low but Detectable Influence on HLA-B*57:01 Specificity without Inducing Hypersensitivity

Immune mediated adverse drug reactions (IM-ADRs) remain a significant source of patient morbidity that have more recently been shown to be associated with specific class I and/or II human leukocyte antigen (HLA) alleles. Abacavir-induced hypersensitivity syndrome is a CD8⁺ T cell dependent IM-ADR that is exclusively mediated by HLA-B*57:01. We and others have previously shown that abacavir can occupy the floor of the peptide binding groove of HLA-B*57:01 molecules, increasing the affinity of certain self peptides resulting in an altered peptide-binding repertoire. Here, we have identified another drug, acyclovir, which appears to act in a similar fashion. As with abacavir, acyclovir showed a dose dependent increase in affinity for peptides with valine and isoleucine at their C-terminus. In agreement with the binding studies, HLA-B*57:01 peptide-elution studies performed in the presence of acyclovir revealed an increased number of endogenously bound peptides with a C-terminal isoleucine. Accordingly, we have hypothesized that acyclovir acts by the same mechanism as abacavir, although our data also suggest the overall effect is much smaller: the largest changes of peptide affinity for acyclovir were 2-5 fold, whereas for abacavir this effect was as much as 1000-fold. Unlike abacavir, acyclovir is not known to cause IM-ADRs. We conclude that the modest effect of acyclovir on HLA binding affinity in contrast to the large effect of abacavir is insufficient to trigger a hypersensitivity syndrome. We further support this by functional in vitro studies where acyclovir, unlike abacavir, was unable to produce an increase in IFN-γ upon expansion of HLA-B*57:01⁺ PBMCs from healthy donors. Using abacavir and acyclovir as examples we therefore propose an in vitro pre-clinical screening strategy, whereby thresholds can be applied to MHC-peptide binding assays to determine the likelihood that a drug could cause a clinically relevant IM-ADR.

Accurate prediction of immunogenic T-cell epitopes from epitope sequences using the genetic algorithm-based ensemble learning

Background

T-cell epitopes play the important role in T-cell immune response, and they are critical components in the epitope-based vaccine design. Immunogenicity is the ability to trigger an immune response. The accurate prediction of immunogenic T-cell epitopes is significant for designing useful vaccines and understanding the immune system.

Methods

In this paper, we attempt to differentiate immunogenic epitopes from non-immunogenic epitopes based on their primary structures. First of all, we explore a variety of sequence-derived features, and analyze their relationship with epitope immunogenicity. To effectively utilize various features, a genetic algorithm (GA)-based ensemble method is proposed to determine the optimal feature subset and develop the high-accuracy ensemble model. In the GA optimization, a chromosome is to represent a feature subset in the search space. For each feature subset, the selected features are utilized to construct the base predictors, and an ensemble model is developed by taking the average of outputs from base predictors. The objective of GA is to search for the optimal feature subset, which leads to the ensemble model with the best cross validation AUC (area under ROC curve) on the training set.

Results

Two datasets named ‘IMMA2’ and ‘PAAQD’ are adopted as the benchmark datasets. Compared with the state-of-the-art methods POPI, POPISK, PAAQD and our previous method, the GA-based ensemble method produces much better performances, achieving the AUC score of 0.846 on IMMA2 dataset and the AUC score of 0.829 on PAAQD dataset. The statistical analysis demonstrates the performance improvements of GA-based ensemble method are statistically significant.

Conclusions

The proposed method is a promising tool for predicting the immunogenic epitopes. The source codes and datasets are available in S1 File.

Viral evolution in HLA-B27-restricted CTL epitopes in human immunodeficiency virus type 1-infected individuals

The HLA-B27 allele is over-represented among human immunodeficiency virus type 1-infected long-term non-progressors. In these patients, strong CTL responses targeting HLA-B27-restricted viral epitopes have been associated with long-term asymptomatic survival. Indeed, loss of control of viraemia in HLA-B27 patients has been associated with CTL escape at position 264 in the immunodominant KK10 epitope. This CTL escape mutation in the viral Gag protein has been associated with severe viral attenuation and may require the presence of compensatory mutations before emerging. Here, we studied sequence evolution within HLA-B27-restricted CTL epitopes in the viral Gag protein during the course of infection of seven HLA-B27-positive patients. Longitudinal gag sequences obtained at different time points around the time of AIDS diagnosis were obtained and analysed for the presence of mutations in epitopes restricted by HLA-B27, and for potential compensatory mutations. Sequence variations were observed in the HLA-B27-restricted CTL epitopes IK9 and DR11, and the immunodominant KK10 epitope. However, the presence of sequence variations in the HLA-B27-restricted CTL epitopes could not be associated with an increase in viraemia in the majority of the patients studied. Furthermore, we observed low genetic diversity in the gag region of the viral variants throughout the course of infection, which is indicative of low viral replication and corresponds to the low viral load observed in the HLA-B27-positive patients. These data indicated that control of viral replication can be maintained in HLA-B27-positive patients despite the emergence of viral mutations in HLA-B27-restricted epitopes.

TCR contact residue hydrophobicity is a hallmark of immunogenic CD8+ T cell epitopes

Despite the availability of major histocompatibility complex (MHC)-binding peptide prediction algorithms, the development of T-cell vaccines against pathogen and tumor antigens remains challenged by inefficient identification of immunogenic epitopes. CD8(+) T cells must distinguish immunogenic epitopes from nonimmunogenic self peptides to respond effectively against an antigen without endangering the viability of the host. Because this discrimination is fundamental to our understanding of immune recognition and critical for rational vaccine design, we interrogated the biochemical properties of 9,888 MHC class I peptides. We identified a strong bias toward hydrophobic amino acids at T-cell receptor contact residues within immunogenic epitopes of MHC allomorphs, which permitted us to develop and train a hydrophobicity-based artificial neural network (ANN-Hydro) to predict immunogenic epitopes. The immunogenicity model was validated in a blinded in vivo overlapping epitope discovery study of 364 peptides from three HIV-1 Gag protein variants. Applying the ANN-Hydro model on existing peptide-MHC algorithms consistently reduced the number of candidate peptides across multiple antigens and may provide a correlate with immunodominance. Hydrophobicity of TCR contact residues is a hallmark of immunogenic epitopes and marks a step toward eliminating the need for empirical epitope testing for vaccine development.

Proteome-wide B and T cell epitope repertoires in outer membrane proteins of Mycobacterium avium subsp. paratuberculosis have vaccine and diagnostic relevance: a holistic approach

Mycobacterium avium subsp. paratuberculosis (MAP) is an etiological agent of chronic inflammation of the intestine among ruminants and humans. Currently, there are no effective vaccines and sensitive diagnostic tests available for its control and detection. For this, it is of paramount importance to identify the MAP antigens, which may be immunologically recognized by the host immune system. To address this challenge, we performed identification of the immunogenic epitopes in the MAP outer membrane proteins (OMPs). We have previously identified 57 MAP proteins as OMPs [Rana A, Rub A, Akhter Y. 2014. Molecular BioSystems, 10:2329-2337] and have evaluated them for the epitope selection and analysis employing a computational approach. Thirty-five MAP OMPs are reported with nine-mer peptides showing high binding affinity to major histocompatibility complex (MHC) class I molecules and 28 MAP OMPs with 15-mer peptides of high binding affinity for MHC class II molecules. The presence of MHC binding epitopes indicates the potential cell-mediated immune response inducing capacity of these MAP OMPs in infected host. To further investigate the humoral response inducing properties of OMPs of MAP, we report potential B cell epitopes based on the sequences of peptide antigens and their molecular structures. We also report 10 proteins having epitopes for both B and T cells representing potential candidates which may invoke both humoral and cellular immune responses in the host. These findings will greatly accelerate and expedite the formulation of effective and cost-efficient vaccines and diagnostic tests against MAP infection.