The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection

Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation

T cell alloreactivity against minor histocompatibility antigens (mHAgs)-polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms-is at the core of the therapeutic effect of allogeneic hematopoietic cell transplantation (allo-HCT). Despite the crucial role of mHAgs in graft-versus-leukemia (GvL) and graft-versus-host disease (GvHD) reactions, it remains challenging to consistently link patient-specific mHAg repertoires to clinical outcomes. Here we devise an analytic framework to systematically identify mHAgs, including their detection on HLA class I ligandomes and functional verification of their immunogenicity. The method relies on the integration of polymorphism detection by whole-exome sequencing of germline DNA from D-R pairs with organ-specific transcriptional- and proteome-level expression. Application of this pipeline to 220 HLA-matched allo-HCT D-R pairs demonstrated that total and organ-specific mHAg load could independently predict the occurrence of acute GvHD and chronic pulmonary GvHD, respectively, and defined promising GvL targets, confirmed in a validation cohort of 58 D-R pairs, for the prevention or treatment of post-transplant disease recurrence.

copepodTCR: Identification of Antigen-Specific T Cell Receptors with combinatorial peptide pooling

T cell receptor (TCR) repertoire diversity enables the orchestration of antigen-specific immune responses against the vast space of possible pathogens. Identifying TCR/antigen binding pairs from the large TCR repertoire and antigen space is crucial for biomedical research. Here, we introduce copepodTCR, an open-access tool for the design and interpretation of high-throughput experimental assays to determine TCR specificity. copepodTCR implements a combinatorial peptide pooling scheme for efficient experimental testing of T cell responses against large overlapping peptide libraries, useful for "deorphaning" TCRs of unknown specificity. The scheme detects experimental errors and, coupled with a hierarchical Bayesian model for unbiased results interpretation, identifies the response-eliciting peptide for a TCR of interest out of hundreds of peptides tested using a simple experimental set-up. We experimentally validated our approach on a library of 253 overlapping peptides covering the SARS-CoV-2 spike protein. We provide experimental guides for efficient design of larger screens covering thousands of peptides which will be crucial for the identification of antigen-specific T cells and their targets from limited clinical material.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

CD4+ T-Cell Epitope Prediction by Combined Analysis of Antigen Conformational Flexibility and Peptide-MHCII Binding Affinity

Antigen processing in the class II MHC pathway depends on conventional proteolytic enzymes, potentially acting on antigens in native-like conformational states. CD4+ epitope dominance arises from a competition among antigen folding, proteolysis, and MHCII binding. Protease-sensitive sites, linear antibody epitopes, and CD4+ T-cell epitopes were mapped in plague vaccine candidate F1-V to evaluate the various contributions to CD4+ epitope dominance. Using X-ray crystal structures, antigen processing likelihood (APL) predicts CD4+ epitopes with significant accuracy for F1-V without considering peptide-MHCII binding affinity. We also show that APL achieves excellent performance over two benchmark antigen sets. The profiles of conformational flexibility derived from the X-ray crystal structures of the F1-V proteins, Caf1 and LcrV, were similar to the biochemical profiles of linear antibody epitope reactivity and protease sensitivity, suggesting that the role of structure in proteolysis was captured by the analysis of the crystal structures. The patterns of CD4+ T-cell epitope dominance in C57BL/6, CBA, and BALB/c mice were compared to epitope predictions based on APL, MHCII binding, or both. For a sample of 13 diverse antigens, the accuracy of epitope prediction by the combination of APL and I-A^b-MHCII-peptide affinity reached 36%. When MHCII allele specificity was also diverse, such as in human immunity, prediction of dominant epitopes by APL alone reached 42% when using a stringent scoring threshold. Because dominant CD4+ epitopes tend to occur in conformationally stable antigen domains, crystal structures typically are available for analysis by APL, and thus, the requirement for a crystal structure is not a severe limitation.

Antitumor Peptide-Based Vaccine in the Limelight

The success of the immune checkpoint blockade has provided a proof of concept that immune cells are capable of attacking tumors in the clinic. However, clinical benefit is only observed in less than 20% of the patients due to the non-specific activation of immune cells by the immune checkpoint blockade. Developing tumor-specific immune responses is a challenging task that can be achieved by targeting tumor antigens to generate tumor-specific T-cell responses. The recent advancements in peptide-based immunotherapy have encouraged clinicians and patients who are struggling with cancer that is otherwise non-treatable with current therapeutics. By selecting appropriate epitopes from tumor antigens with suitable adjuvants, peptides can elicit robust antitumor responses in both mice and humans. Although recent experimental data and clinical trials suggest the potency of tumor reduction by peptide-based vaccines, earlier clinical trials based on the inadequate hypothesis have misled that peptide vaccines are not efficient in eliminating tumor cells. In this review, we highlighted the recent evidence that supports the rationale of peptide-based antitumor vaccines. We also discussed the strategies to select the optimal epitope for vaccines and the mechanism of how adjuvants increase the efficacy of this promising approach to treat cancer.

Identification of Immunogenic MHC Class II Human HER3 Peptides that Mediate Anti-HER3 CD4+ Th1 Responses and Potential Use as a Cancer Vaccine

The HER3/ERBB3 receptor is an oncogenic receptor tyrosine kinase that forms heterodimers with EGFR family members and is overexpressed in numerous cancers. HER3 overexpression associates with reduced survival and acquired resistance to targeted therapies, making it a potential therapeutic target in multiple cancer types. Here, we report on immunogenic, promiscuous MHC class II-binding HER3 peptides, which can generate HER3-specific CD4⁺ Th1 antitumor immune responses. Using an overlapping peptide screening methodology, we identified nine MHC class II-binding HER3 epitopes that elicited specific Th1 immune response in both healthy donors and breast cancer patients. Most of these peptides were not identified by current binding algorithms. Homology assessment of amino acid sequence BLAST showed >90% sequence similarity between human and murine HER3/ERBB3 peptide sequences. HER3 peptide-pulsed dendritic cell vaccination resulted in anti-HER3 CD4⁺ Th1 responses that prevented tumor development, significantly delayed tumor growth in prevention models, and caused regression in multiple therapeutic models of HER3-expressing murine tumors, including mammary carcinoma and melanoma. Tumors were robustly infiltrated with CD4⁺ T cells, suggesting their key role in tumor rejection. Our data demonstrate that class II HER3 promiscuous peptides are effective at inducing HER3-specific CD4⁺ Th1 responses and suggest their applicability in immunotherapies for human HER3-overexpressing tumors.

Immune Complex Formation Is Associated With Loss of Tolerance and an Antibody Response to Both Drug and Target

AMG 966 is a bi-specific, heteroimmunoglobulin molecule that binds both tumor necrosis factor alpha (TNFα) and TNF-like ligand 1A (TL1A). In a first-in-human clinical study in healthy volunteers, AMG 966 elicited anti-drug antibodies (ADA) in 53 of 54 subjects (98.1%), despite a paucity of T cell epitopes observed in T cell assays. ADA were neutralizing and bound to all domains of AMG 966. Development of ADA correlated with loss of exposure. In vitro studies demonstrated that at certain drug-to-target ratios, AMG 966 forms large immune complexes with TNFα and TL1A, partially restoring the ability of the aglycosylated Fc domain to bind FcγRIa and FcγRIIa, leading to the formation of ADA. In addition to ADA against AMG 966, antibodies to endogenous TNFα were also detected in the sera of subjects dosed with AMG 966. This suggests that the formation of immune complexes between a therapeutic and target can cause loss of tolerance and elicit an antibody response against the target.

Detection of IFNγ-Secreting CD4+ and CD8+ Memory T Cells in COVID-19 Convalescents after Stimulation of Peripheral Blood Mononuclear Cells with Live SARS-CoV-2

Background: New coronavirus SARS-CoV-2, a causative agent of the COVID-19 pandemic, has been circulating among humans since November 2019. Multiple studies have assessed the qualitative and quantitative characteristics of virus-specific immunity in COVID-19 convalescents, however, some aspects of the development of memory T-cell responses after natural SARS-CoV-2 infection remain uncovered. Methods: In most of published studies T-cell immunity to the new coronavirus is assessed using peptides corresponding to SARS-CoV-1 or SARS-CoV-2 T-cell epitopes, or with peptide pools covering various parts of the viral proteins. Here, we determined the level of CD4⁺ and CD8⁺ memory T-cell responses in COVID-19 convalescents by stimulating PBMCs collected 1 to 6 months after recovery with sucrose gradient-purified live SARS-CoV-2. IFNγ production by the central and effector memory helper and cytotoxic T cells was assessed by intracellular cytokine staining assay and flow cytometry. Results: Stimulation of PBMCs with live SARS-CoV-2 revealed IFNγ-producing T-helper effector memory cells with CD4⁺CD45RA⁻CCR7⁻ phenotype, which persisted in circulation for up to 6 month after COVID-19. In contrast, SARS-CoV-2-specific IFNγ-secreting cytotoxic effector memory T cells were found at significant levels only shortly after the disease, but rapidly decreased over time. Conclusion: The stimulation of immune cells with live SARS-CoV-2 revealed a rapid decline in the pool of effector memory CD8⁺, but not CD4⁺, T cells after recovery from COVID-19. These data provide additional information on the development and persistence of cellular immune responses after natural infection, and can inform further development of T cell-based SARS-CoV-2 vaccines.

Bioinformatic HLA Studies in the Context of SARS-CoV-2 Pandemic and Review on Association of HLA Alleles with Preexisting Medical Conditions

After the announcement of a new coronavirus in China in December 2019, which was then called SARS-CoV-2, this virus changed to a global concern and it was then declared as a pandemic by WHO. Human leukocyte antigen (HLA) alleles, which are one of the most polymorphic genes, play a pivotal role in both resistance and vulnerability of the body against viruses and other infections as well as chronic diseases. The association between HLA alleles and preexisting medical conditions such as cardiovascular diseases and diabetes mellitus is reported in various studies. In this review, we focused on the bioinformatic HLA studies to summarize the HLA alleles which responded to SARS-CoV-2 peptides and have been used to design vaccines. We also reviewed HLA alleles that are associated with comorbidities and might be related to the high mortality rate among COVID-19 patients. Since both genes and patients' medical conditions play a key role in both severity of the disease and the mortality rate in COVID-19 patients, a better understanding of the connection between HLA alleles and SARS-CoV-2 can provide a wider perspective on the behavior of the virus. Such understanding can help scientists, especially in terms of protecting healthcare workers and designing effective vaccines.

epitopepredict: a tool for integrated MHC binding prediction

A key step in the cellular adaptive immune response is the presentation of antigens to T cells. Computational prediction of T cell epitopes has many applications in vaccine design and immuno-diagnostics. This is the basis of immunoinformatics, which allows in silico screening of peptides before experiments are performed. With the availability of whole genomes for many microbial species it is now feasible to computationally screen whole proteomes for candidate peptides. epitopepredict is a programmatic framework and command line tool designed to aid this process. It provides access to multiple binding prediction algorithms under a single interface and scales for whole genomes using multiple target MHC alleles. A web interface is provided to assist visualization and filtering of the results. The software is freely available under an open-source license from https://github.com/dmnfarrell/epitopepredict.

Comparison of HLA ligand elution data and binding predictions reveals varying prediction performance for the multiple motifs recognized by HLA-DQ2.5

Binding prediction tools are commonly used to identify peptides presented on MHC class II molecules. Recently, a wealth of data in the form of naturally eluted ligands has become available and discrepancies between ligand elution data and binding predictions have been reported. Quantitative metrics for such comparisons are currently lacking. In this study, we assessed how efficiently MHC class II binding predictions can identify naturally eluted peptides, and investigated instances with discrepancies between the two methods in detail. We found that, in general, MHC class II eluted ligands are predicted to bind to their reported restriction element with high affinity. But, for several studies reporting an increased number of ligands that were not predicted to bind, we found that the reported MHC restriction was ambiguous. Additional analyses determined that most of the ligands predicted to not bind, are predicted to bind other co‐expressed MHC class II molecules. For selected alleles, we addressed discrepancies between elution data and binding predictions by experimental measurements and found that predicted and measured affinities correlate well. For DQA1*05:01/DQB1*02:01 (DQ2.5) however, binding predictions did miss several peptides that were determined experimentally to be binders. For these peptides and several known DQ2.5 binders, we determined key residues for conferring DQ2.5 binding capacity, which revealed that DQ2.5 utilizes two different binding motifs, of which only one is predicted effectively. These findings have important implications for the interpretation of ligand elution data and for the improvement of MHC class II binding predictions.

Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins

Immunogenicity risk assessment is a critical element in protein drug development. Currently, the risk assessment is most often performed using MHC-associated peptide proteomics (MAPPs) and/or T-cell activation assays. However, this is a highly costly procedure that encompasses limited sensitivity imposed by sample sizes, the MHC repertoire of the tested donor cohort and the experimental procedures applied. Recent work has suggested that these techniques could be complemented by accurate, high-throughput and cost-effective prediction of in silico models. However, this work covered a very limited set of therapeutic proteins and eluted ligand (EL) data. Here, we resolved these limitations by showcasing, in a broader setting, the versatility of in silico models for assessment of protein drug immunogenicity. A method for prediction of MHC class II antigen presentation was developed on the hereto largest available mass spectrometry (MS) HLA-DR EL data set. Using independent test sets, the performance of the method for prediction of HLA-DR antigen presentation hotspots was benchmarked. In particular, the method was showcased on a set of protein sequences including four therapeutic proteins and demonstrated to accurately predict the experimental MS hotspot regions at a significantly lower false-positive rate compared with other methods. This gain in performance was particularly pronounced when compared to the NetMHCIIpan-3.2 method trained on binding affinity data. These results suggest that in silico methods trained on MS HLA EL data can effectively and accurately be used to complement MAPPs assays for the risk assessment of protein drugs.

T Cell Epitope Predictions

Throughout the body, T cells monitor MHC-bound ligands expressed on the surface of essentially all cell types. MHC ligands that trigger a T cell immune response are referred to as T cell epitopes. Identifying such epitopes enables tracking, phenotyping, and stimulating T cells involved in immune responses in infectious disease, allergy, autoimmunity, transplantation, and cancer. The specific T cell epitopes recognized in an individual are determined by genetic factors such as the MHC molecules the individual expresses, in parallel to the individual's environmental exposure history. The complexity and importance of T cell epitope mapping have motivated the development of computational approaches that predict what T cell epitopes are likely to be recognized in a given individual or in a broader population. Such predictions guide experimental epitope mapping studies and enable computational analysis of the immunogenic potential of a given protein sequence region.

CD4 T Cell Determinants in West Nile Virus Disease and Asymptomatic Infection

West Nile (WN) virus infection of humans is frequently asymptomatic, but can also lead to WN fever or neuroinvasive disease. CD4 T cells and B cells are critical in the defense against WN virus, and neutralizing antibodies, which are directed against the viral glycoprotein E, are an accepted correlate of protection. For the efficient production of these antibodies, B cells interact directly with CD4 helper T cells that recognize peptides from E or the two other structural proteins (capsid-C and membrane-prM/M) of the virus. However, the specific protein sites yielding such helper epitopes remain unknown. Here, we explored the CD4 T cell response in humans after WN virus infection using a comprehensive library of overlapping peptides covering all three structural proteins. By measuring T cell responses in 29 individuals with either WN virus disease or asymptomatic infection, we showed that CD4 T cells focus on peptides in specific structural elements of C and at the exposed surface of the pre- and postfusion forms of the E protein. Our data indicate that these immunodominant epitopes are recognized in the context of multiple different HLA molecules. Furthermore, we observed that immunodominant antigen regions are structurally conserved and similarly targeted in other mosquito-borne flaviviruses, including dengue, yellow fever, and Zika viruses. Together, these findings indicate a strong impact of virion protein structure on epitope selection and antigenicity, which is an important issue to consider in future vaccine design.

Peptide Epitope Hot Spots of CD4 T Cell Recognition Within Influenza Hemagglutinin During the Primary Response to Infection

Antibodies specific for the hemagglutinin (HA) protein of influenza virus are critical for protective immunity to infection. Our studies show that CD4 T cells specific for epitopes derived from HA are the most effective in providing help for the HA-specific B cell responses to infection and vaccination. In this study, we asked whether HA epitopes recognized by CD4 T cells in the primary response to infection are equally distributed across the HA protein or if certain segments are enriched in CD4 T cell epitopes. Mice that collectively expressed eight alternative MHC (Major Histocompatibility Complex) class II molecules, that would each have different peptide binding specificities, were infected with an H1N1 influenza virus. CD4 T cell peptide epitope specificities were identified by cytokine EliSpots. These studies revealed that the HA-specific CD4 T cell epitopes cluster in two distinct regions of HA and that some segments of HA are completely devoid of CD4 T cell epitopes. When located on the HA structure, it appears that the regions that most poorly recruit CD4 T cells are sequestered within the interior of the HA trimer, perhaps inaccessible to the proteolytic machinery inside the endosomal compartments of antigen presenting cells.

Influenza and sudden unexpected death: the possible role of peptide cross-reactivity

This study investigates the hypothesis that cross-reactions may occur between human cardiac proteins and influenza antigens, thus possibly representing the molecular mechanism underlying influenzaassociated sudden unexpected death (SUD). Using titin protein as a research model, data were obtained on (1) the occurrence of the titin octapeptide AELLVLLE or its mimic AELLVALE in influenza A virus hemagglutinin (HA) sequences; (2) the immunological potential of AELLVLLE and its mimic AELLVALE; (3) the possible role of the flanking amino acid aa) context of the two octapeptide determinants in eliciting cross-reactivity between the human cardiac titin protein and HA antigens.

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.

Computational prediction of vaccine potential epitopes and 3-dimensional structure of XAGE-1b for non-small cell lung cancer immunotherapy

BACKGROUND

XAGE-1b is shown to be overexpressed in lung adenocarcinoma and to be a strong immunogenic antigen among non-small cell lung cancer (NSCLC) patients. However, 3D structure of XAGE-1b is not available and its confirmation has not been solved yet.

METHODS

Multiple sequence alignment was run to select the most reliable templates. Homology modeling technique was performed using computer-based tool to generate 3-dimensional structure models, eight models were generated and assessed on basis of local and global quality. Immune Epitope Database (IEDB) tools were then used to determine potential B-Cell epitopes while NetMHCpan algorithms were used to enhance the determination for potential epitopes of both Cytotoxic T-lymphocytes and T-helper cells.

RESULTS

Computational prediction was performed for B-Cell epitopes, prediction results generated; 3 linear epitopes where XAGE-1b (13-21) possessed the best score of 0.67, 5 discontinuous epitopes where XAGE-1b (40-52) possessed the best score of 0.67 based on the predicted model of the finest quality. For a potential vaccine design, computational prediction yielded potential Human Leukocyte Antigen (HLA) class I epitopes including HLA-B*08:01-restricted XAGE-1b (3-11) epitope which was the best with 0.2 percentile rank. Regarding HLA Class II epitopes, HLA-DRB1*12:01-restricted XAGE-1b (25-33) was the most antigenic epitope with 5.91 IC50 value. IC50 values were compared with experimental values and population coverage percentages of epitopes were computed.

CONCLUSIONS

This study predicted a model of XAGE-1b tertiary structure which could explain its antigenic function and facilitate usage of predicted peptides for experimental validation towards designing immunotherapies against NSCLC.

Perpetual complexity: predicting human CD8+ T-cell responses to pathogenic peptides

The accurate prediction of human CD8⁺ T-cell epitopes has great potential clinical and translational implications in the context of infection, cancer and autoimmunity. Prediction algorithms have traditionally focused on calculated peptide affinity for the binding groove of MHC-I. However, over the years it has become increasingly clear that the ultimate T-cell recognition of MHC-I-bound peptides is governed by many contributing factors within the complex antigen presentation pathway. Recent advances in next-generation sequencing and immunnopeptidomics have increased the precision of HLA-I sub-allele classification, and have led to the discovery of peptide processing events and individual allele-specific binding preferences. Here, we review some of the discoveries that initiated the development of peptide prediction algorithms, and outline some of the current available online tools for CD8⁺ T-cell epitope prediction.

Protein structure shapes immunodominance in the CD4 T cell response to yellow fever vaccination

The live attenuated yellow fever (YF) vaccine is a highly effective human vaccine and induces long-term protective neutralizing antibodies directed against the viral envelope protein E. The generation of such antibodies requires the help of CD4 T cells which recognize peptides derived from proteins in virus particles internalized and processed by E-specific B cells. The CD4 T helper cell response is restricted to few immunodominant epitopes, but the mechanisms of their selection are largely unknown. Here, we report that CD4 T cell responses elicited by the YF-17D vaccine are focused to hotspots of two helices of the viral capsid protein and to exposed strands and loops of E. We found that the locations of immunodominant epitopes within three-dimensional protein structures exhibit a high degree of overlap between YF virus and the structurally homologous flavivirus tick-borne encephalitis virus, although amino acid sequence identity of the epitope regions is only 15-45%. The restriction of epitopes to exposed E protein surfaces and their strikingly similar positioning within proteins of distantly related flaviviruses are consistent with a strong influence of protein structure that shapes CD4 T cell responses and provide leads for a rational design of immunogens for vaccination.

Profiling the Targets of Protective CD8+ T Cell Responses to Infection

T cells are critical effectors of host immunity that target intracellular pathogens, such as the causative agents of HIV, tuberculosis, and malaria. The development of vaccines that induce effective cell-mediated immunity against such pathogens has proved challenging; for tuberculosis and malaria, many of the antigens targeted by protective T cells are not known. Here, we report a novel approach for screening large numbers of antigens as potential targets of T cells. Malaria provides an excellent model to test this antigen discovery platform because T cells are critical mediators of protection following immunization with live sporozoite vaccines and the specific antigen targets are unknown. We generated an adenovirus array by cloning 312 highly expressed pre-erythrocytic Plasmodium yoelii antigens into adenovirus vectors using high-throughput methodologies. The array was screened to identify antigen-specific CD8⁺ T cells induced by a live sporozoite vaccine regimen known to provide high levels of sterile protection mediated by CD8⁺ T cells. We identified 69 antigens that were targeted by CD8⁺ T cells induced by this vaccine regimen. The antigen that recalled the highest frequency of CD8⁺ T cells, PY02605, induced protective responses in mice, demonstrating proof of principle for this approach in identifying antigens for vaccine development.

CD11a and CD49d enhance the detection of antigen-specific T cells following human vaccination

BACKGROUND

Determining the efficacy of human vaccines that induce antigen-specific protective CD4 T cell responses against pathogens can be particularly challenging to evaluate. Surface expression of CD11a and CD49d has been shown to identify antigen-specific CD4 T cells against viral pathogens in mice. We hypothesized that CD11a and CD49d would also serve as markers of human antigen-specific T cells responding to vaccination.

METHODS

A phase I vaccine trial enabled us to evaluate a novel gating strategy based on surface expression of CD11a and CD49d as a means of detecting antigen-specific, cytokine producing CD4 and CD8 T cells induced after vaccination of naïve individuals against leishmaniasis. Three study groups received LEISH-F3 recombinant protein combined with either squalene oil-in-water emulsion (SE) alone, SE with the synthetic TLR-4 ligand glucopyranosyl lipid adjuvant (GLA-SE), or SE with Salmonella minnesota-derived monophosphoryl lipid A (MPL-SE). Individuals were given 3 vaccine doses, on days 0, 28 and 168.

RESULTS

Starting after the first vaccine dose, the frequency of both CD11a^hiCD49d⁺ CD4 and CD11a^hiCD49d⁺ CD8 T cells significantly increased over time throughout the 24-week trial. To confirm the role of CD11a^hiCD49d⁺ expression in the identification of the antigen-specific T cells, cytokine production was measured following LEISH-F3 stimulation. All of the IFN-γ, TNF-α, and IL-2 producing cells were found within the CD11a^hiCD49d⁺ population.

CONCLUSIONS

Our results suggest that the change in the frequency of CD11a^hiCD49d⁺ T cells can be used to track antigen-specific CD4 and CD8 T cell responses following T cell-targeted vaccination.

Mycobacterium tuberculosis Complex Exhibits Lineage-Specific Variations Affecting Protein Ductility and Epitope Recognition

The advent of whole-genome sequencing has provided an unprecedented detail about the evolution and genetic significance of species-specific variations across the whole Mycobacterium tuberculosis Complex. However, little attention has been focused on understanding the functional roles of these variations in the protein coding sequences. In this work, we compare the coding sequences from 74 sequenced mycobacterial species including M. africanum, M. bovis, M. canettii, M. caprae, M. orygis, and M. tuberculosis. Results show that albeit protein variations affect all functional classes, those proteins involved in lipid and intermediary metabolism and respiration have accumulated mutations during evolution. To understand the impact of these mutations on protein functionality, we explored their implications on protein ductility/disorder, a yet unexplored feature of mycobacterial proteomes. In agreement with previous studies, we found that a Gly71Ile substitution in the PhoPR virulence system severely affects the ductility of its nearby region in M. africanum and animal-adapted species. In the same line of evidence, the SmtB transcriptional regulator shows amino acid variations specific to the Beijing lineage, which affects the flexibility of the N-terminal trans-activation domain. Furthermore, despite the fact that MTBC epitopes are evolutionary hyperconserved, we identify strain- and lineage-specific amino acid mutations affecting previously known T-cell epitopes such as EsxH and FbpA (Ag85A). Interestingly, in silico studies reveal that these variations result in differential interaction of epitopes with the main HLA haplogroups.

Broad-Based CD4+ T Cell Responses to Influenza A Virus in a Healthy Individual Who Lacks Typical Immunodominance Hierarchy

Influenza A virus (IAV) infection is a significant cause of morbidity and mortality worldwide. CD4⁺ T cell responses have been shown to be important for influenza protection in mouse models and in human volunteers. IAV antigen-specific CD4⁺ T cell responses were found to focus on matrix 1 (M1) and nucleoprotein (NP) at the protein antigen level. At the epitope level, only several epitopes within M1 and NP were recognized by CD4⁺ T cells. And the epitope-specific CD4⁺ T cell responses showed a typical immunodominance hierarchy in most of the healthy individuals studied. In this study, we reported one case of atypical immunodominance hierarchy of CD4⁺ T cell responses to IAV. M1 and NP were still the immunodominant targets of CD4⁺ T cell responses. However, CD4⁺ T cell responses specific to 11 epitopes derived from M1 and NP were detected and showed no significant immunodominance hierarchy. Such an atypical pattern is likely determined by the individual's HLA alleles. These findings will help us better understand the anti-IAV immunity as a whole and improve future vaccines against IAV.

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.

Integrated computational prediction and experimental validation identifies promiscuous T cell epitopes in the proteome of Mycobacterium bovis

The discovery of novel antigens is an essential requirement in devising new diagnostics or vaccines for use in control programmes against human tuberculosis (TB) and bovine tuberculosis (bTB). Identification of potential epitopes recognised by CD4⁺ T cells requires prediction of peptide binding to MHC class-II, an obligatory prerequisite for T cell recognition. To comprehensively prioritise potential MHC-II-binding epitopes from Mycobacterium bovis, the agent of bTB and zoonotic TB in humans, we integrated three binding prediction methods with the M. bovisproteome using a subset of human HLA alleles to approximate the binding of epitope-containing peptides to the bovine MHC class II molecule BoLA-DRB3. Two parallel strategies were then applied to filter the resulting set of binders: identification of the top-scoring binders or clusters of binders. Our approach was tested experimentally by assessing the capacity of predicted promiscuous peptides to drive interferon-γ secretion from T cells of M. bovis infected cattle. Thus, 376 20-mer peptides, were synthesised (270 predicted epitopes, 94 random peptides with low predictive scores and 12 positive controls of known epitopes). The results of this validation demonstrated significant enrichment (>24 %) of promiscuously recognised peptides predicted in our selection strategies, compared with randomly selected peptides with low prediction scores. Our strategy offers a general approach to the identification of promiscuous epitopes tailored to target populations where there is limited knowledge of MHC allelic diversity.

T-cell recognition is shaped by epitope sequence conservation in the host proteome and microbiome

Several mechanisms exist to avoid or suppress inflammatory T-cell immune responses that could prove harmful to the host due to targeting self-antigens or commensal microbes. We hypothesized that these mechanisms could become evident when comparing the immunogenicity of a peptide from a pathogen or allergen with the conservation of its sequence in the human proteome or the healthy human microbiome. Indeed, performing such comparisons on large sets of validated T-cell epitopes, we found that epitopes that are similar with self-antigens above a certain threshold showed lower immunogenicity, presumably as a result of negative selection of T cells capable of recognizing such peptides. Moreover, we also found a reduced level of immune recognition for epitopes conserved in the commensal microbiome, presumably as a result of peripheral tolerance. These findings indicate that the existence (and potentially the polarization) of T-cell responses to a given epitope is influenced and to some extent predictable based on its similarity to self-antigens and commensal antigens.

Epitope specific T-cell responses against influenza A in a healthy population

Pre-existing human CD4(+) and CD8(+) T-cell-mediated immunity may be a useful correlate of protection against severe influenza disease. Identification and evaluation of common epitopes recognized by T cells with broad cross-reactivity is therefore important to guide universal influenza vaccine development, and to monitor immunological preparedness against pandemics. We have retrieved an optimal combination of MHC class I and class II restricted epitopes from the Immune Epitope Database (www.iedb.org), by defining a fitness score function depending on prevalence, sequence conservancy and HLA super-type coverage. Optimized libraries of CD4(+) and CD8(+) T-cell epitopes were selected from influenza antigens commonly present in seasonal and pandemic influenza strains from 1934 to 2009. These epitope pools were used to characterize human T-cell responses in healthy donors using interferon-γ ELISPOT assays. Upon stimulation, significant CD4(+) and CD8(+) T-cell responses were induced, primarily recognizing epitopes from the conserved viral core proteins. Furthermore, the CD4(+) and CD8(+) T cells were phenotypically characterized regarding functionality, cytotoxic potential and memory phenotype using flow cytometry. Optimized sets of T-cell peptide epitopes may be a useful tool to monitor the efficacy of clinical trials, the immune status of a population to predict immunological preparedness against pandemics, as well as being candidates for universal influenza vaccines.

Identification of Conserved Peptides Comprising Multiple T Cell Epitopes of Matrix 1 Protein in H1N1 Influenza Virus

Cell mediated immune response plays a key role in combating viral infection and thus identification of new vaccine targets manifesting T cell mediated response may serve as an ideal approach for influenza vaccine. The present study involves the application of an immunoinformatics-based consensus approach for epitope prediction (three epitope prediction tools each for CD4+ and CD8+ T cell epitopes) and molecular docking to identify peptide sequences containing T cell epitopes using the conserved sequences from all the Matrix 1 protein sequences of H1N1 virus available until April 2015. Three peptides comprising CD4+ and CD8+ T cell epitopes were obtained, which were not exactly reported in earlier studies. Population coverage study of these multi-epitope peptides revealed that they are capable of inducing a potent immune response belonging to individuals from different populations and ethnicity distributed around the globe. Conservation study with other subtypes of influenza virus infecting humans (H2N2, H5N1, H7N9, and H3N2) revealed that these three peptides were conserved (>90%), with 100% identity in most of these strains. Hence, these peptides can impart immunity against H1N1 as well as other subtypes of influenza virus. A molecular docking study of the predicted peptides with class I and II human leukocyte antigen (HLA) molecules has shown that the majority of them have comparable binding energies to that of native peptides. Hence, these peptides from Matrix 1 protein of H1N1 appear to be promising candidates for universal vaccine design.

Identification of a novel linear epitope on the NS1 protein of avian influenza virus

BACKGROUND

The NS1 protein of avian influenza virus (AIV) is an important virulent factor of AIV. It has been shown to counteract host type I interferon response, to mediate host cell apoptosis, and to regulate the process of protein synthesis. The identification of AIV epitopes on NS1 protein is important for understanding influenza virus pathogenesis.

RESULTS

In this paper, we describe the generation, identification, and epitope mapping of a NS1 protein-specific monoclonal antibody (MAb) D9. First, to induce the production of MAbs, BALB/c mice were immunized with a purified recombinant NS1 expressed in E. coli. The spleen cells from the immunized mice were fused with myeloma cells SP2/0, and through screening via indirect ELISAs, a MAb, named D9, was identified. Western blot assay results showed that MAb D9 reacted strongly with the recombinant NS1. Confocal laser scanning microscopy showed that this MAb also reacts with NS1 expressed in 293T cells that had been transfected with eukaryotic recombinant plasmids. Results from screening a phage display random 7-mer peptide library with MAb D9 demonstrated that it recognizes phages displaying peptides with the consensus peptide WNLNTV--VS, which closely matches the (182)WNDNTVRVS(190) of AIV NS1. Further identification of the displayed epitope was performed with a set of truncated polypeptides expressed as glutathione S-transferase fusion proteins, and the motif (182)WNDNT(186) was defined as the minimal unit of the linear B cell epitope recognized by MAb D9 in western blot assays. Moreover, homology analysis showed that this epitope is a conserved motif among AIV.

CONCLUSIONS

We identified a conserved linear epitope, WNDNT, on the AIV NS1 protein that is recognized by MAb D9. This MAb and its epitope may facilitate future studies on NS1 function and aid the development of new diagnostic methods for AIV detection.

Current methods of epitope identification for cancer vaccine design

The importance of the immune system in tumor development and progression has been emerging in many cancers. Previous cancer vaccines have not shown long-term clinical benefit possibly because were not designed to avoid eliciting regulatory T-cell responses that inhibit the anti-tumor immune response. This review will examine different methods of identifying epitopes derived from tumor associated antigens suitable for immunization and the steps used to design and validate peptide epitopes to improve efficacy of anti-tumor peptide-based vaccines. Focusing on in silico prediction algorithms, we survey the advantages and disadvantages of current cancer vaccine prediction tools.

Seasonal Influenza Can Poise Hosts for CD4 T-Cell Immunity to H7N9 Avian Influenza

The emergence of avian H7N9 viruses has raised concerns about its pandemic potential and prompted vaccine trials. At present, it is unknown whether there will be sufficient cross-reactive hemagglutinin (HA)-specific CD4 T-cell memory with seasonal influenza to facilitate antibody production to H7 HA. There has also been speculation that H7N9 will have few CD4 T-cell epitopes. In this study, we quantified the potential of seasonal influenza to provide memory CD4 T cells that can cross-reactively recognize H7 HA-derived peptides. These studies have revealed that many humans have substantial H7-reactive CD4 T cells, whereas up to 40% are lacking such reactivity. Correlation studies indicate that CD4 T cells reactive with H7 HA are drawn from reactivity generated from seasonal strains. Overall, our findings suggest that previous exposure of humans to seasonal influenza can poise them to respond to avian H7N9, but this is likely to be uneven across populations.

Development and validation of a broad scheme for prediction of HLA class II restricted T cell epitopes

Computational prediction of HLA class II restricted T cell epitopes has great significance in many immunological studies including vaccine discovery. In recent years, prediction of HLA class II binding has improved significantly but a strategy to globally predict the most dominant epitopes has not been rigorously defined. Using human immunogenicity data associated with sets of 15-mer peptides overlapping by 10 residues spanning over 30 different allergens and bacterial antigens, and HLA class II binding prediction tools from the Immune Epitope Database and Analysis Resource (IEDB), we optimized a strategy to predict the top epitopes recognized by human populations. The most effective strategy was to select peptides based on predicted median binding percentiles for a set of seven DRB1 and DRB3/4/5 alleles. These results were validated with predictions on a blind set of 15 new allergens and bacterial antigens. We found that the top 21% predicted peptides (based on the predicted binding to seven DRB1 and DRB3/4/5 alleles) were required to capture 50% of the immune response. This corresponded to an IEDB consensus percentile rank of 20.0, which could be used as a universal prediction threshold. Utilizing actual binding data (as opposed to predicted binding data) did not appreciably change the efficacy of global predictions, suggesting that the imperfect predictive capacity is not due to poor algorithm performance, but intrinsic limitations of HLA class II epitope prediction schema based on HLA binding in genetically diverse human populations.

Immunodominant CD4+ T-cell responses to influenza A virus in healthy individuals focus on matrix 1 and nucleoprotein

Antigen-specific CD4(+) T cells are essential for effective virus-specific host responses, with recent human challenge studies (in volunteers) establishing their importance for influenza A virus (IAV)-specific immunity. However, while many IAV CD4(+) T cell epitopes have been identified, few are known to stimulate immunodominant CD4(+) T cell responses. Moreover, much remains unclear concerning the major antigen(s) responded to by the human CD4(+) T cells and the extents and magnitudes of these responses. We initiated a systematic screen of immunodominant CD4(+) T cell responses to IAV in healthy individuals. Using in vitro expanded-multispecificity IAV-specific T cell lines and individual IAV protein antigens produced by recombinant vaccinia viruses, we found that the internal matrix protein 1 (M1) and nucleoprotein (NP) were the immunodominant targets of CD4(+) T cell responses. Ten epitopes derived from M1 and NP were definitively characterized. Furthermore, epitope sequence conservation analysis established that immunodominance correlated with an increased frequency of mutations, reflecting the fact that these prominent epitopes are under greater selective pressure. Such evidence that particular CD4(+) T cells are important for protection/recovery is of value for the development of novel IAV vaccines and for our understanding of different profiles of susceptibility to these major pathogens. Importance: Influenza virus causes half a million deaths annually. CD4(+) T cell responses have been shown to be important for protection against influenza and for recovery. CD4(+) T cell responses are also critical for efficient CD8(+) T cell response and antibody response. As immunodominant T cells generally play a more important role, characterizing these immunodominant responses is critical for influenza vaccine development. We show here that the internal matrix protein 1 (M1) and nucleoprotein (NP), rather than the surface proteins reported previously, are the immunodominant targets of CD4(+) T cell responses. Interestingly, these immunodominant epitope regions accumulated many mutations over time, which likely indicates increased immune pressure. These findings have significant implications for the design of T cell-based influenza vaccines.

Sequence diversity in the pe_pgrs genes of Mycobacterium tuberculosis is independent of human T cell recognition

The Mycobacterium tuberculosis genome includes the large family of pe_pgrs genes, whose functions are unknown. Because of precedents in other pathogens in which gene families showing high sequence variation are involved in antigenic variation, a similar role has been proposed for the pe_pgrs genes. However, the impact of immune selection on pe_pgrs genes has not been examined. Here, we sequenced 27 pe_pgrs genes in 94 clinical strains from five phylogenetic lineages of the M. tuberculosis complex (MTBC). We found that pe_pgrs genes were overall more diverse than the remainder of the MTBC genome, but individual members of the family varied widely in their nucleotide diversity and insertion/deletion (indel) content: some were more, and others were much less, diverse than the genome average. Individual pe_pgrs genes also differed in the ratio of nonsynonymous to synonymous mutations, suggesting that different selection pressures act on individual pe_pgrs genes. Using bioinformatic methods, we tested whether sequence diversity in pe_pgrs genes might be selected by human T cell recognition, the major mechanism of adaptive immunity to MTBC. We found that the large majority of predicted human T cell epitopes were confined to the conserved PE domain and experimentally confirmed the antigenicity of this domain in tuberculosis patients. In contrast, despite being genetically diverse, the PGRS domains harbored few predicted T cell epitopes. These results indicate that human T cell recognition is not a significant force driving sequence diversity in pe_pgrs genes, which is consistent with the previously reported conservation of human T cell epitopes in the MTBC.

IMPORTANCE

Recognition of Mycobacterium tuberculosis antigens by T lymphocytes is known to be important for immune protection against tuberculosis, but it is unclear whether human T cell recognition drives antigenic variation in M. tuberculosis. We previously discovered that the known human T cell epitopes in the M. tuberculosis complex are highly conserved, but we hypothesized that undiscovered epitopes with naturally occurring sequence variants might exist. To test this hypothesis, we examined the pe_pgrs genes, a large family of genes that has been proposed to function in immune evasion by M. tuberculosis. We found that the pe_pgrs genes exhibit considerable sequence variation, but the regions containing T cell epitopes and the regions of variation are distinct. These findings confirm that the majority of human T cell epitopes of M. tuberculosis are highly conserved and indicate that selection forces other than T cell recognition drive sequence variation in the pe_pgrs genes.

Nucleoprotein of influenza A virus is a major target of immunodominant CD8+ T-cell responses

Influenza A virus causes annual epidemics and sporadic pandemics, resulting in significant morbidity and mortality worldwide. Vaccines are currently available; however, they induce a non-strain-cross protective humoral immune response directed against the rapidly mutating surface glycoproteins, and thus need to be updated annually. As T cells are directed against more conserved internal influenza proteins, a T-cell-based vaccine has the potential to induce long-lasting and cross-strain protective CD8(+) T-cell immunity, and in that way minimize the severity of influenza infection. However, to rationally design such vaccines, we need to identify immunogenic T-cell regions within the most antigenic viral proteins. In this study, we have used a systematic approach to identify immunodominant peptides in HLA-A2-negative donors. A broad range of CD8(+) T-cell responses were observed and 6/7 donors had an immunodominant response against the relatively conserved internal nucleoprotein (NP). Dissecting the minimal epitope regions within the immunogenic NP led to the identification of six novel immunodominant epitopes, which include a 12-mer and an 8-mer peptides. The majority of immunodominant epitopes was clustered within the carboxyl terminal 2/3 of the NP protein and were highly conserved. We also subjected NP to three common computer algorithms for epitope prediction and found that most of the novel epitopes would not have been predicted. Our study emphasizes the importance of using a systematic approach to identify immunodominant CD8(+) T-cell responses and suggests that the epitope-rich regions within NP present a promising target for the T-cell-mediated multi-strain influenza vaccine.

Identification of cytotoxic T lymphocyte epitopes on swine viruses: multi-epitope design for universal T cell vaccine

Classical swine fever (CSF), foot-and-mouth disease (FMD) and porcine reproductive and respiratory syndrome (PRRS) are the primary diseases affecting the pig industry globally. Vaccine induced CD8⁺ T cell-mediated immune response might be long-lived and cross-serotype and thus deserve further attention. Although large panels of synthetic overlapping peptides spanning the entire length of the polyproteins of a virus facilitate the detection of cytotoxic T lymphocyte (CTL) epitopes, it is an exceedingly costly and cumbersome approach. Alternatively, computational predictions have been proven to be of satisfactory accuracy and are easily performed. Such a method enables the systematic identification of genome-wide CTL epitopes by incorporating epitope prediction tools in analyzing large numbers of viral sequences. In this study, we have implemented an integrated bioinformatics pipeline for the identification of CTL epitopes of swine viruses including the CSF virus (CSFV), FMD virus (FMDV) and PRRS virus (PRRSV) and assembled these epitopes on a web resource to facilitate vaccine design. Identification of epitopes for cross protections to different subtypes of virus are also reported in this study and may be useful for the development of a universal vaccine against such viral infections among the swine population. The CTL epitopes identified in this study have been evaluated in silico and possibly provide more and wider protection in compared to traditional single-reference vaccine design. The web resource is free and open to all users through http://sb.nhri.org.tw/ICES.

HLA-DM and HLA-DO, key regulators of MHC-II processing and presentation

Peptide loading of class II MHC molecules in endosomal compartments is regulated by HLA-DM. HLA-DO modulates HLA-DM function, with consequences for the spectrum of MHC-bound epitopes presented at the cell surface for interaction with T cells. Here, we summarize and discuss recent progress in investigating the molecular mechanisms of action of HLA-DM and HLA-DO and in understanding their roles in immune responses. Key findings are the long-awaited structures of HLA-DM in complex with its class II substrate and with HLA-DO, and observation of a novel phenotype--autoimmunity combined with immunodeficiency--in mice lacking HLA-DO. We also highlight several areas where gaps persist in our knowledge about this pair of proteins and their molecular biology and immunobiology.

CD4 T cell help is limiting and selective during the primary B cell response to influenza virus infection

Influenza virus vaccination strategies are focused upon the elicitation of protective antibody responses through administration of viral protein through either inactivated virions or live attenuated virus. Often overlooked in this strategy is the CD4 T cell response: how it develops into memory, and how it may support future primary B cell responses to heterologous infection. Through the utilization of a peptide-priming regimen, this study describes a strategy for developing CD4 T cell memory with the capacity to robustly expand in the lung-draining lymph node after live influenza virus infection. Not only were frequencies of antigen-specific CD4 T cells enhanced, but these cells also supported an accelerated primary B cell response to influenza virus-derived protein, evidenced by high anti-nucleoprotein (NP) serum antibody titers early, while there is still active viral replication ongoing in the lung. NP-specific antibody-secreting cells and heightened frequencies of germinal center B cells and follicular T helper cells were also readily detectable in the draining lymph node. Surprisingly, a boosted memory CD4 T cell response was not sufficient to provide intermolecular help for antibody responses. Our study demonstrates that CD4 T cell help is selective and limiting to the primary antibody response to influenza virus infection and that preemptive priming of CD4 T cell help can promote effective and rapid conversion of naive B cells to mature antibody-secreting cells.

Dendritic cell-based vaccines: barriers and opportunities

Dendritic cells (DCs) have several characteristics that make them an ideal vehicle for tumor vaccines, and with the first US FDA-approved DC-based vaccine in use for the treatment of prostate cancer, this technology has become a promising new therapeutic option. However, DC-based vaccines face several barriers that have limited their effectiveness in clinical trials. A major barrier includes the activation state of the DC. Both DC lineage and maturation signals must be selected to optimize the antitumor response and overcome immunosuppressive effects of the tumor microenvironment. Another barrier to successful vaccination is the selection of target antigens that will activate both CD8(+) and CD4(+) T cells in a potent, immune-specific manner. Finally, tumor progression and immune dysfunction limit vaccine efficacy in advanced stages, which may make DC-based vaccines more efficacious in treating early-stage disease. This review underscores the scientific basis and advances in the development of DC-based vaccines, focuses on current barriers to success and highlights new research opportunities to address these obstacles.

For many but not for all: how the conformational flexibility of the peptide/MHCII complex shapes epitope selection

The adaptive immune response starts when CD4+ T cells recognize peptide antigens presented by class II molecules of the Major Histocompatibility Complex (MHCII). Two outstanding features of MHCII molecules are their polymorphism and the ability of each allele to bind a large panoply of peptides. The ability of each MHCII molecule to interact with a limited, though broad, range of amino acid sequences, or "permissive specificity" of binding, is the result of structural flexibility. This flexibility has been identified through biochemical and biophysical studies, and molecular dynamic simulations have modeled the conformational rearrangements that the peptide and the MHCII undergo during interaction. Moreover, there is evidence that the structural flexibility of the peptide/MHCII complex correlates with the activity of the "peptide-editing" molecule DM. In light of the impact that these recent findings have on our ability to predict MHCII epitopes, a review of the structural and thermodynamic determinants of peptide binding to MHCII is proposed.

Increase in IFNγ(-)IL-2(+) cells in recent human CD4 T cell responses to 2009 pandemic H1N1 influenza

Human CD4 T cell recall responses to influenza virus are strongly biased towards Type 1 cytokines, producing IFNγ, IL-2 and TNFα. We have now examined the effector phenotypes of CD4 T cells in more detail, particularly focusing on differences between recent versus long-term, multiply-boosted responses. Peptides spanning the proteome of temporally distinct influenza viruses were distributed into pools enriched for cross-reactivity to different influenza strains, and used to stimulate antigen-specific CD4 T cells representing recent or long-term memory. In the general population, peptides unique to the long-circulating influenza A/New Caledonia/20/99 (H1N1) induced Th1-like responses biased toward the expression of IFNγ(+)TNFα(+) CD4 T cells. In contrast, peptide pools enriched for non-cross-reactive peptides of the pandemic influenza A/California/04/09 (H1N1) induced more IFNγ(-)IL-2(+)TNFα(+) T cells, similar to the IFNγ(-)IL-2(+) non-polarized, primed precursor T cells (Thpp) that are a predominant response to protein vaccination. These results were confirmed in a second study that compared samples taken before the 2009 pandemic to samples taken one month after PCR-confirmed A/California/04/09 infection. There were striking increases in influenza-specific TNFα(+), IFNγ(+), and IL-2(+) cells in the post-infection samples. Importantly, peptides enriched for non-cross-reactive A/California/04/09 specificities induced a higher proportion of Thpp-like IFNγ(-)IL-2(+)TNFα(+) CD4 T cells than peptide pools cross-reactive with previous influenza strains, which induced more Th1 (IFNγ(+)TNFα(+)) responses. These IFNγ(-)IL-2(+)TNFα(+) CD4 T cells may be an important target population for vaccination regimens, as these cells are induced upon infection, may have high proliferative potential, and may play a role in providing future effector cells during subsequent infections.

PREDIVAC: CD4+ T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

Background

CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge.

Results

We developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design.

Conclusions

The comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/.

Revealing the role of CD4(+) T cells in viral immunity

Sant and McMichael discuss new advances in detecting CD4⁺ T cells at the right time and place during viral infection.

Protective immunity to chronic and acute viral infection relies on both the innate and adaptive immune response. Although neutralizing antibody production by B cells and cytotoxic activity of CD8⁺ T cells are well-accepted components of the adaptive immune response to viruses, identification of the specific role of CD4⁺ T cells in protection has been more challenging to establish. Delineating the contribution of CD4⁺ T cells has been complicated by their functional heterogeneity, breadth in antigen specificity, transient appearance in circulation, and sequestration in tissue sites of infection. In this minireview, we discuss recent progress in identifying the multiple roles of CD4⁺ T cells in orchestrating and mediating the immune responses against viral pathogens. We highlight several recent reports, including one published in this issue, that have employed comprehensive and sophisticated approaches to provide new evidence for CD4⁺ T cells as direct effectors in antiviral immunity.

Trivalent inactivated influenza vaccines induce broad immunological reactivity to both internal virion components and influenza surface proteins

There are a number of related goals of influenza vaccination, including elicitation of protective antibodies and induction of cellular CD4 and CD8+ T cell responses. Because CD4+ T cell expansion and functionality are influenced by peptide specificity and T cell gene expression can be modified by repeated re-stimulations, it is important to evaluate how frequent influenza vaccinations affect CD4+ T cell dependent functions in protective immunity to influenza. Trivalent influenza vaccines (TIV) have production of neutralizing antibodies to HA as their primary goal and main criteria for efficacy. Accordingly, they are not characterized for any other viral components. In the current study, we evaluated whether other influenza virus proteins were present in commercial TIV at levels sufficient for immunogenicity in vivo. Mice that differed with regard to their expressed class II molecules were used in concert with peptide-stimulated cytokine ELISPOT assays to comprehensively evaluate the CD4+ T cell antigen specificity induced by the TIV. Our studies revealed that NA, NP, M1 and NS1 were present in sufficient quantities in the TIV to prime and boost CD4+ T cells. These results suggest that in humans, the broad CD4+ T cell repertoire induced by live infection is continually boosted and maintained throughout life by regular vaccination with licensed intramuscular split vaccines. The implications raised by our findings on CD4+ T cell functionality in influenza are discussed.

The peptide specificity of the endogenous T follicular helper cell repertoire generated after protein immunization

T follicular helper (Tfh) cells potentiate high-affinity, class-switched antibody responses, the predominant correlate of protection from vaccines. Despite intense interest in understanding both the generation and effector functions of this lineage, little is known about the epitope specificity of Tfh cells generated during polyclonal responses. To date, studies of peptide-specific Tfh cells have relied on either the transfer of TcR transgenic cells or use of peptide∶MHC class II tetramers and antibodies to stain TcR and follow limited peptide specificities. In order to comprehensively evaluate polyclonal responses generated from the natural endogenous TcR repertoire, we developed a sorting strategy to separate Tfh cells from non-Tfh cells and found that their epitope-specific responses could be tracked with cytokine-specific ELISPOT assays. The immunodominance hierarchies of Tfh and non-Tfh cells generated in response to immunization with several unrelated protein antigens were remarkably similar. Additionally, increasing the kinetic stability of peptide-MHC class II complexes enhanced the priming of both Tfh and conventional CD4 T cells. These findings may provide us with a strategy to rationally and selectively modulate epitope-specific Tfh responses. By understanding the parameters that control epitope-specific priming, vaccines may be tailored to enhance or focus Tfh responses to facilitate optimal B cell responses.