Naturally processed HLA class II peptides reveal highly conserved immunogenic flanking region sequence preferences that reflect antigen processing rather than peptide-MHC interactions

A targeted single mutation in influenza A virus universal epitope transforms immunogenicity and protective immunity via CD4+ T cell activation

CD4+ T cells are central to adaptive immunity. Their role in cross-protection in viral infections such as influenza and severe acute respiratory syndrome (SARS) is well documented; however, molecular rules governing T cell receptor (TCR) engagement of peptide-human leukocyte antigen (pHLA) class II are less understood. Here, we exploit an aspect of HLA class II presentation, the peptide-flanking residues (PFRs), to "tune" CD4+ T cell responses within an in vivo model system of influenza. Using a recombinant virus containing targeted substitutions at immunodominant HLA-DR1 epitopes, we demonstrate limited weight loss and improved clinical scores after heterosubtypic re-challenge. We observe enhanced protection linked to lung-derived influenza-specific CD4+ and CD8+ T cells prior to re-infection. Structural analysis of the ternary TCR:pHLA complex identifies that flanking amino acids influence side chains in the core 9-mer peptide, increasing TCR affinity. Augmentation of CD4+ T cell immunity is achievable with a single mutation, representing a strategy to enhance adaptive immunity that is decoupled from vaccine modality.

MHCII-peptide presentation: an assessment of the state-of-the-art prediction methods

Major histocompatibility complex Class II (MHCII) proteins initiate and regulate immune responses by presentation of antigenic peptides to CD4+ T-cells and self-restriction. The interactions between MHCII and peptides determine the specificity of the immune response and are crucial in immunotherapy and cancer vaccine design. With the ever-increasing amount of MHCII-peptide binding data available, many computational approaches have been developed for MHCII-peptide interaction prediction over the last decade. There is thus an urgent need to provide an up-to-date overview and assessment of these newly developed computational methods. To benchmark the prediction performance of these methods, we constructed an independent dataset containing binding and non-binding peptides to 20 human MHCII protein allotypes from the Immune Epitope Database, covering DP, DR and DQ alleles. After collecting 11 known predictors up to January 2022, we evaluated those available through a webserver or standalone packages on this independent dataset. The benchmarking results show that MixMHC2pred and NetMHCIIpan-4.1 achieve the best performance among all predictors. In general, newly developed methods perform better than older ones due to the rapid expansion of data on which they are trained and the development of deep learning algorithms. Our manuscript not only draws a full picture of the state-of-art of MHCII-peptide binding prediction, but also guides researchers in the choice among the different predictors. More importantly, it will inspire biomedical researchers in both academia and industry for the future developments in this field.

Structure-aware deep model for MHC-II peptide binding affinity prediction

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based solutions have yielded promising results on MHC-II molecules in recent years, these methods ignored structure knowledge from each peptide when employing the deep neural network models. Each peptide sequence has its specific combination order, so it is worth considering adding the structural information of the peptide sequence to the deep model training. In this work, we use positional encoding to represent the structural information of peptide sequences and validly combine the positional encoding with existing models by different strategies. Experiments on three datasets show that the introduction of position-coding information can further improve the performance built upon the existing model. The idea of introducing positional encoding to this field can provide important reference significance for the optimization of the deep network structure in the future.

Preclinical risk assessment strategy to mitigate the T-cell dependent immunogenicity of protein biotherapeutics: State of the art, challenges and future perspectives

Protein therapeutics hold a prominent role and have brought significant diversity in efficacious medicinal products. Not just monoclonal antibodies and different antibody formats (pegylated antigen-binding fragments, bispecifics, antibody-drug conjugates, single chain variable fragments, nanobodies, dia-, tria- and tetrabodies), but also purified blood products, growth factors, recombinant cytokines, enzyme replacement factors, fusion proteins are all good instances of therapeutic proteins that have been developed in the past decades and approved for their value in oncology, immune-oncology, and autoimmune diseases discovery programs. Although there was an ingrained belief that fully humanized proteins were expected to have limited immunogenicity, adverse effects associated with immune responses to biological therapies raised some concern in biotech companies. Consequently, drug developers are designing strategies to assess potential immune responses to protein therapeutics during both the preclinical and clinical phases of development. Despite the many factors that can contribute to protein immunogenicity, T cell- (thymus-) dependent (Td) immunogenicity seems to play a crucial role in the development of anti-drug antibodies (ADAs) to biologics. A broad range of methodologies to predict and rationally assess Td immune responses to protein drugs has been developed. This review aims to briefly summarize the preclinical immunogenicity risk assessment strategy to mitigate the risk of potential immunogenic candidates coming towards clinical phases, discussing the advantages and limitations of these technologies, and suggesting a rational approach for assessing and mitigating Td immunogenicity.

A cell-free antigen processing system informs HIV-1 epitope selection and vaccine design

Distinct CD4+ T cell epitopes have been associated with spontaneous control of HIV-1 replication, but analysis of antigen-dependent factors that influence epitope selection is lacking. To examine these factors, we used a cell-free antigen processing system that incorporates soluble HLA-DR (DR1), HLA-DM (DM), cathepsins, and full-length protein antigens for epitope identification by LC-MS/MS. HIV-1 Gag, Pol, Env, Vif, Tat, Rev, and Nef were examined using this system. We identified 35 novel epitopes, including glycopeptides. Epitopes from smaller HIV-1 proteins mapped to regions of low protein stability and higher solvent accessibility. HIV-1 antigens associated with limited CD4+ T cell responses were processed efficiently, while some protective epitopes were inefficiently processed. 55% of epitopes obtained from cell-free processing induced memory CD4+ T cell responses in HIV-1+ donors, including eight of 19 novel epitopes tested. Thus, an in vitro processing system utilizing the components of Class II processing reveals factors influencing epitope selection of HIV-1 and represents an approach to understanding epitope selection from non-HIV-1 antigens.

Live Cell Imaging by Förster Resonance Energy Transfer Fluorescence to Study Trafficking of PLGA Nanoparticles and the Release of a Loaded Peptide in Dendritic Cells

Our previous study demonstrated that a selected β-lactoglobulin-derived peptide (BLG-Pep) loaded in poly(lactic-co-glycolic acid) (PLGA) nanoparticles protected mice against cow's milk allergy development. However, the mechanism(s) responsible for the interaction of the peptide-loaded PLGA nanoparticles with dendritic cells (DCs) and their intracellular fate was/were elusive. Förster resonance energy transfer (FRET), a distance-dependent non-radioactive energy transfer process mediated from a donor to an acceptor fluorochrome, was used to investigate these processes. The ratio of the donor (Cyanine-3)-conjugated peptide and acceptor (Cyanine-5) labeled PLGA nanocarrier was fine-tuned for optimal (87%) FRET efficiency. The colloidal stability and FRET emission of prepared NPs were maintained upon 144 h incubation in PBS buffer and 6 h incubation in biorelevant simulated gastric fluid at 37 °C. A total of 73% of Pep-Cy3 NP was internalized by DCs as quantified using flow cytometry and confirmed using confocal fluorescence microscopy. By real-time monitoring of the change in the FRET signal of the internalized peptide-loaded nanoparticles, we observed prolonged retention (for 96 h) of the nanoparticles-encapsulated peptide as compared to 24 h retention of the free peptide in the DCs. The prolonged retention and intracellular antigen release of the BLG-Pep loaded in PLGA nanoparticles in murine DCs might facilitate antigen-specific tolerance induction.

Ranking Peptide Binders by Affinity with AlphaFold

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.

Evaluating complete surface-associated and secretory proteome of Leishmania donovani for discovering novel vaccines and diagnostic targets

The protozoa Leishmania donovani causes visceral leishmaniasis (kala-azar), the third most common vector-borne disease. The visceral organs, particularly the spleen, liver, and bone marrow, are affected by the disease. The lack of effective treatment regimens makes curing and eradicating the disease difficult. The availability of complete L. donovani genome/proteome data allows for the development of specific and efficient vaccine candidates using the reverse vaccinology method, while utilizing the unique sequential and structural features of potential antigenic proteins to induce protective T cell and B cell responses. Such shortlisted candidates may then be tested quickly for their efficacy in the laboratory and later in clinical settings. These antigens will also be useful for designing antigen-based next-generation sero-diagnostic assays. L. donovani's cell surface-associated proteins and secretory proteins are among the first interacting entities to be exposed to the host immune machinery. As a result, potential antigenic epitope peptides derived from these proteins could serve as competent vaccine components. We used a stepwise filtering-based in silico approach to identify the entire surface-associated and secretory proteome of L. donovani, which may provide rationally selected most exposed antigenic proteins. Our study identified 12 glycosylphosphatidylinositol-anchored proteins, 45 transmembrane helix-containing proteins, and 73 secretory proteins as potent antigens unique to L. donovani. In addition, we used immunoinformatics to identify B and T cell epitopes in them. Out of the shortlisted surface-associated and secretory proteome, 66 protein targets were found to have the most potential overlapping B cell and T cell epitopes (linear and conformational; MHC class I and MHC class II).

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Challenges targeting cancer neoantigens in 2021: a systematic literature review

Introduction: Cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction algorithms, and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. Unfortunately, results from preclinical studies and early phase clinical trials highlight important challenges to the successful clinical translation of neoantigen cancer vaccines.Areas covered: In this review, we provide an overview of current strategies for the identification and prioritization of cancer neoantigens with a particular emphasis on the two most common strategies used for neoantigen identification: (1) direct identification of peptide ligands eluted from peptide-MHC complexes, and (2) next-generation sequencing combined with neoantigen prediction algorithms. We highlight the limitations of current neoantigen prediction pipelines, and discuss broader challenges associated with cancer neoantigen vaccines including tumor purity/heterogeneity and the immunosuppressive tumor microenvironment.Expert opinion: Despite current limitations, neoantigen prediction is likely to improve rapidly based on advances in sequencing, machine learning, and information sharing. The successful development of robust cancer neoantigen prediction strategies is likely to have a significant impact, with the potential to facilitate cancer neoantigen vaccine design.

HLA-DRB1 molecules and the presentation of anchor peptides from RhD, RhCE, and KEL proteins

BACKGROUND

Antigens from the Rh and Kell systems are recognized as the most immunogenic in clinical practice. This study evaluated the possible molecular mechanisms involved in the interaction of antigenic peptides with the DRB1 molecules, which help to explain the high frequency of anti-K and association of D + C antibodies in transfusion and incompatible pregnancy.

STUDY DESIGN AND METHODS

We included 201 patients with antibodies against antigens from the Rh and Kell systems and compare them with 174,015 controls. HLA-DRB1 genotyping and in silico analysis were performed. The NetMHCIIpan software was used to identify RhD-, RhCE-, and KEL-derived anchor peptides that bind to DRB1 molecules.

RESULTS

HLA-DRB1*15 is associated with an increased risk of D, C, E, and K alloimmunization, while the HLA-DRB1*01 and *12 alleles are overrepresented in patients with anti-C and anti-D, respectively. In silico analysis showed that three polymorphic points (60I, 68S, and 103S) common to C and D antigens can be presented by several DRB1 molecules, including DRB1*15:01. The DRB1*09:01 molecule, although not showing statistical significance, was able to interact strongly with almost all five anchor peptides from the sequence containing the polymorphic determinants of E antigen, except 217-WMFWPSVNS-225.

CONCLUSION

The DRB1*15 molecule has specific physicochemical characteristics in residues 11P and 13R in the P4 pocket that can favor the response to various antigenic peptides. Anti-K alloimmunization is unrestricted for interaction with specific DRB1 molecules, which suggests that almost all individuals in our population have DRB1 molecules capable of binding to KEL-derived anchor peptides and produce anti-K when stimulated.

Definition of Naturally Processed Peptides Reveals Convergent Presentation of Autoantigenic Topoisomerase I Epitopes in Scleroderma

OBJECTIVE

Autoimmune responses to DNA topoisomerase I (topo I) are found in a subset of scleroderma patients who are at high risk for interstitial lung disease (ILD) and mortality. Anti-topo I antibodies (ATAs) are associated with specific HLA-DRB1 alleles, and the frequency of HLA-DR-restricted topo I-specific CD4+ T cells is associated with the presence, severity, and progression of ILD. Although this strongly implicates the presentation of topo I peptides by HLA-DR in scleroderma pathogenesis, the processing and presentation of topo I has not been studied.

METHODS

We developed a natural antigen processing assay (NAPA) to identify putative CD4+ T cell epitopes of topo I presented by monocyte-derived dendritic cells (mo-DCs) from 6 ATA-positive patients with scleroderma. Mo-DCs were pulsed with topo I protein, HLA-DR-peptide complexes were isolated, and eluted peptides were analyzed by mass spectrometry. We then examined the ability of these naturally presented peptides to induce CD4+ T cell activation in 11 ATA-positive and 11 ATA-negative scleroderma patients.

RESULTS

We found that a common set of 10 topo I epitopes was presented by Mo-DCs from scleroderma patients with diverse HLA-DR variants. Sequence analysis revealed shared peptide-binding motifs within the HLA-DRβ chains of ATA-positive patients and a subset of topo I epitopes with distinct sets of anchor residues capable of binding to multiple different HLA-DR variants. The NAPA-derived epitopes elicited robust CD4+ T cell responses in 73% of ATA-positive patients (8 of 11), and the number of epitopes recognized correlated with ILD severity (P = 0.025).

CONCLUSION

These findings mechanistically implicate the presentation of a convergent set of topo I epitopes in the development of scleroderma.

Role of ultraviolet mutational signature versus tumor mutation burden in predicting response to immunotherapy

Hydrophobic neoantigens are more immunogenic because they are better presented by the major histocompatibility complex and better recognized by T cells. Tumor cells can evade the immune response by expressing checkpoints such as programmed death ligand 1. Checkpoint blockade reactivates immune recognition and can be effective in diseases such as melanoma, which harbors a high tumor mutational burden (TMB). Cancers presenting low or intermediate TMB can also respond to checkpoint blockade, albeit less frequently, suggesting the need for biological markers predicting response. We calculated the hydrophobicity of neopeptides produced by probabilistic in silico simulation of the genomic UV exposure mutational signature. We also computed the hydrophobicity of potential neopeptides and extent of UV exposure based on the UV mutational signature enrichment (UVMSE) score in The Cancer Genome Atlas (TCGA; N = 3543 tumors), and in our cohort of 151 immunotherapy‐treated patients. In silico simulation showed that UV exposure significantly increased hydrophobicity of neopeptides, especially over multiple mutagenic cycles. There was also a strong correlation (R² = 0.953) between weighted UVMSE and hydrophobicity of neopeptides in TCGA melanoma patients. Importantly, UVMSE was able to predict better response (P = 0.0026), progression‐free survival (P = 0.036), and overall survival (P = 0.052) after immunotherapy in patients with low/intermediate TMB, but not in patients with high TMB. We show that higher UVMSE scores could be a useful predictor of better immunotherapy outcome, especially in patients with low/intermediate TMB, likely due to increased hydrophobicity (and hence immunogenicity) of neopeptides.

Comparative Analysis of T-Cell Responses to Aquaporin-4 and Myelin Oligodendrocyte Glycoprotein in Inflammatory Demyelinating Central Nervous System Diseases

Autoantibodies against aquaporin-4 (AQP4-Ab) and myelin oligodendrocyte glycoprotein (MOG-Ab) are associated with rare central nervous system inflammatory demyelinating diseases like neuromyelitis optica spectrum disorders (NMOSD). Previous studies have shown that not only antibodies, but also autoreactive T-cell responses against AQP4 are present in NMOSD. However, no study has yet analyzed the presence of MOG reactive T-cells in patients with MOG antibodies. Therefore, we compared AQP4 and MOG specific peripheral T-cell response in individuals with AQP4-Ab (n = 8), MOG-Ab (n = 10), multiple sclerosis (MS, n = 8), and healthy controls (HC, n = 14). Peripheral blood mononuclear cell cultures were stimulated with eight AQP4 and nine MOG peptides selected from previous studies and a tetanus toxoid peptide mix as a positive control. Antigen-specific T-cell responses were assessed using the carboxyfluorescein diacetate succinimidyl ester proliferation assay and the detection of granulocyte macrophage colony-stimulating factor (GM-CSF), interferon (IFN)-ɤ and interleukin (IL)-4, IL-6, and IL-17A in cell culture supernatants. Additionally, human leukocyte antigen (HLA)-DQ and HLA-DR genotyping of all participants was performed. We classified a T-cell response as positive if proliferation (measured by a cell division index ≥3) was confirmed by the secretion of at least one cytokine. Reactivity against AQP4 peptides was observed in many groups, but the T-cell response against AQP4 p156-170 was present only in patients with AQP4-Ab (4/8, 50%) and absent in patients with MOG-Ab, MS and HC (corrected p = 0.02). This AQP4 p156-170 peptide specific T-cell response was significantly increased in participants with AQP4-Ab compared to those without [Odds ratio (OR) = 59.00, 95% confidence interval-CI 2.70–1,290.86]. Moreover, T-cell responses against at least one AQP4 peptide were also more frequent in participants with AQP4-Ab (OR = 11.45, 95% CI 1.24–106.05). We did not observe any significant differences for the other AQP4 peptides or any MOG peptide. AQP4-Ab were associated with HLA DQB1^*02 (OR = 5.71, 95% CI 1.09–30.07), DRB1^*01 (OR = 9.33, 95% CI 1.50–58.02) and DRB1^*03 (OR = 6.75, 95% CI = 1.19–38.41). Furthermore, HLA DRB1^*01 was also associated with the presence of AQP4 p156-170 reactive T-cells (OR = 31.67, 95% CI 1.30–772.98). To summarize, our findings suggest a role of AQP4-specific, but not MOG-specific T-cells, in NMOSD.

Improved Prediction of MHC II Antigen Presentation through Integration and Motif Deconvolution of Mass Spectrometry MHC Eluted Ligand Data

Major histocompatibility complex II (MHC II) molecules play a vital role in the onset and control of cellular immunity. In a highly selective process, MHC II presents peptides derived from exogenous antigens on the surface of antigen-presenting cells for T cell scrutiny. Understanding the rules defining this presentation holds critical insights into the regulation and potential manipulation of the cellular immune system. Here, we apply the NNAlign_MA machine learning framework to analyze and integrate large-scale eluted MHC II ligand mass spectrometry (MS) data sets to advance prediction of CD4+ epitopes. NNAlign_MA allows integration of mixed data types, handling ligands with multiple potential allele annotations, encoding of ligand context, leveraging information between data sets, and has pan-specific power allowing accurate predictions outside the set of molecules included in the training data. Applying this framework, we identified accurate binding motifs of more than 50 MHC class II molecules described by MS data, particularly expanding coverage for DP and DQ beyond that obtained using current MS motif deconvolution techniques. Furthermore, in large-scale benchmarking, the final model termed NetMHCIIpan-4.0 demonstrated improved performance beyond current state-of-the-art predictors for ligand and CD4+ T cell epitope prediction. These results suggest that NNAlign_MA and NetMHCIIpan-4.0 are powerful tools for analysis of immunopeptidome MS data, prediction of T cell epitopes, and development of personalized immunotherapies.

In silico design of a T-cell epitope vaccine candidate for parasitic helminth infection

Trichuris trichiura is a parasite that infects 500 million people worldwide, leading to colitis, growth retardation and Trichuris dysentery syndrome. There are no licensed vaccines available to prevent Trichuris infection and current treatments are of limited efficacy. Trichuris infections are linked to poverty, reducing children's educational performance and the economic productivity of adults. We employed a systematic, multi-stage process to identify a candidate vaccine against trichuriasis based on the incorporation of selected T-cell epitopes into virus-like particles. We conducted a systematic review to identify the most appropriate in silico prediction tools to predict histocompatibility complex class II (MHC-II) molecule T-cell epitopes. These tools were used to identify candidate MHC-II epitopes from predicted ORFs in the Trichuris genome, selected using inclusion and exclusion criteria. Selected epitopes were incorporated into Hepatitis B core antigen virus-like particles (VLPs). Bone marrow-derived dendritic cells and bone marrow-derived macrophages responded in vitro to VLPs irrespective of whether the VLP also included T-cell epitopes. The VLPs were internalized and co-localized in the antigen presenting cell lysosomes. Upon challenge infection, mice vaccinated with the VLPs+T-cell epitopes showed a significantly reduced worm burden, and mounted Trichuris-specific IgM and IgG2c antibody responses. The protection of mice by VLPs+T-cell epitopes was characterised by the production of mesenteric lymph node (MLN)-derived Th2 cytokines and goblet cell hyperplasia. Collectively our data establishes that a combination of in silico genome-based CD4+ T-cell epitope prediction, combined with VLP delivery, offers a promising pipeline for the development of an effective, safe and affordable helminth vaccine.

Human leukocyte antigen (HLA) class II peptide flanking residues tune the immunogenicity of a human tumor-derived epitope

CD4+ T-cells recognize peptide antigens, in the context of human leukocyte antigen (HLA) class II molecules (HLA-II), which through peptide-flanking residues (PFRs) can extend beyond the limits of the HLA binding. The role of the PFRs during antigen recognition is not fully understood; however, recent studies have indicated that these regions can influence T-cell receptor (TCR) affinity and pHLA-II stability. Here, using various biochemical approaches including peptide sensitivity ELISA and ELISpot assays, peptide-binding assays and HLA-II tetramer staining, we focused on CD4+ T-cell responses against a tumor antigen, 5T4 oncofetal trophoblast glycoprotein (5T4), which have been associated with improved control of colorectal cancer. Despite their weak TCR-binding affinity, we found that anti-5T4 CD4+ T-cells are polyfunctional and that their PFRs are essential for TCR recognition of the core bound nonamer. The high-resolution (1.95 Å) crystal structure of HLA-DR1 presenting the immunodominant 20-mer peptide 5T4111-130, combined with molecular dynamic simulations, revealed how PFRs explore the HLA-proximal space to contribute to antigen reactivity. These findings advance our understanding of what constitutes an HLA-II epitope and indicate that PFRs can tune weak affinity TCR-pHLA-II interactions.

Ligandomes obtained from different HLA-class II-molecules are homologous for N- and C-terminal residues outside the peptide-binding cleft

Human CD4+ T lymphocytes play an important role in inducing potent immune responses. T cells are activated and stimulated by peptides presented in human leucocyte antigen (HLA)-class II molecules. These HLA-class II molecules typically present peptides of between 12 and 20 amino acids in length. The region that interacts with the HLA molecule, designated as the peptide-binding core, is highly conserved in the residues which anchor the peptide to the molecule. In addition, as these peptides are the product of proteolytic cleavages, certain conserved residues may be expected at the N- and C-termini outside the binding core. To study whether similar conserved residues are present in different cell types, potentially harbouring different proteolytic enzymes, the ligandomes of HLA-DRB1*03:01/HLA-DRB > 1 derived from two different cell types (dendritic cells and EBV-transformed B cells) were identified with mass spectrometry and the binding core and N- and C-terminal residues of a total of 16,568 peptides were analysed using the frequencies of the amino acids in the human proteome. Similar binding motifs were found as well as comparable conservations in the N- and C-terminal residues. Furthermore, the terminal conservations of these ligandomes were compared to the N- and C-terminal conservations of the ligandome acquired from dendritic cells homozygous for HLA-DRB1*04:01. Again, comparable conservations were evident with only minor differences. Taken together, these data show that there are conservations in the terminal residues of peptides, presumably the result of the activity of proteases involved in antigen processing.

Myelin oligodendrocyte glycoprotein revisited-sensitive detection of MOG-specific T-cells in multiple sclerosis

Autoreactive CD4+ T-cells are believed to be a main driver of multiple sclerosis (MS). Myelin oligodendrocyte glycoprotein (MOG) is considered an autoantigen, yet doubted in recent years. The reason is in part due to low frequency and titers of MOG autoantibodies and the challenge to detect MOG-specific T-cells. In this study we aimed to analyze T-cell reactivity and frequency utilizing a novel method for detection of antigen-specific T-cells with bead-bound MOG as stimulant. Peripheral blood mononuclear cells (PBMCs) from natalizumab treated persons with MS (n = 52) and healthy controls (HCs) (n = 24) were analyzed by IFNγ/IL-22/IL-17A FluoroSpot. A higher number of IFNγ (P = 0.001), IL-22 (P = 0.003), IL-17A (P < 0.0001) as well as double and triple cytokine producing MOG-specific T-cells were detected in persons with MS compared to HCs. Of the patients, 46.2-59.6% displayed MOG-reactivity. Depletion of CD4+ T-cells or monocytes or blocking HLA-DR completely eliminated the MOG specific response. Anti-MOG antibodies did not correlate with T-cell MOG-responses. In conclusion, we present a sensitive method to detect circulating autoreactive CD4+ T-cells producing IFNγ, IL-22 or IL-17A using MOG as a model antigen. Further, we demonstrate that MOG-specific T-cells are present in approximately half of persons with MS.

Footprints of antigen processing boost MHC class II natural ligand predictions

Background

Major histocompatibility complex class II (MHC-II) molecules present peptide fragments to T cells for immune recognition. Current predictors for peptide to MHC-II binding are trained on binding affinity data, generated in vitro and therefore lacking information about antigen processing.

Methods

We generate prediction models of peptide to MHC-II binding trained with naturally eluted ligands derived from mass spectrometry in addition to peptide binding affinity data sets.

Results

We show that integrated prediction models incorporate identifiable rules of antigen processing. In fact, we observed detectable signals of protease cleavage at defined positions of the ligands. We also hypothesize a role of the length of the terminal ligand protrusions for trimming the peptide to the MHC presented ligand.

Conclusions

The results of integrating binding affinity and eluted ligand data in a combined model demonstrate improved performance for the prediction of MHC-II ligands and T cell epitopes and foreshadow a new generation of improved peptide to MHC-II prediction tools accounting for the plurality of factors that determine natural presentation of antigens.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0594-6) contains supplementary material, which is available to authorized users.

Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation

Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation.

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.

Quantification of HLA-DM-Dependent Major Histocompatibility Complex of Class II Immunopeptidomes by the Peptide Landscape Antigenic Epitope Alignment Utility

The major histocompatibility complex of class II (MHCII) immunopeptidome represents the repertoire of antigenic peptides with the potential to activate CD4⁺ T cells. An understanding of how the relative abundance of specific antigenic epitopes affects the outcome of T cell responses is an important aspect of adaptive immunity and offers a venue to more rationally tailor T cell activation in the context of disease. Recent advances in mass spectrometric instrumentation, computational power, labeling strategies, and software analysis have enabled an increasing number of stratified studies on HLA ligandomes, in the context of both basic and translational research. A key challenge in the case of MHCII immunopeptidomes, often determined for different samples at distinct conditions, is to derive quantitative information on consensus epitopes from antigenic peptides of variable lengths. Here, we present the design and benchmarking of a new algorithm [peptide landscape antigenic epitope alignment utility (PLAtEAU)] allowing the identification and label-free quantification (LFQ) of shared consensus epitopes arising from series of nested peptides. The algorithm simplifies the complexity of the dataset while allowing the identification of nested peptides within relatively short segments of protein sequences. Moreover, we apply this algorithm to the comparison of the ligandomes of cell lines with two different expression levels of the peptide-exchange catalyst HLA-DM. Direct comparison of LFQ intensities determined at the peptide level is inconclusive, as most of the peptides are not significantly enriched due to poor sampling. Applying the PLAtEAU algorithm for grouping of the peptides into consensus epitopes shows that more than half of the total number of epitopes is preferentially and significantly enriched for each condition. This simplification and deconvolution of the complex and ambiguous peptide-level dataset highlights the value of the PLAtEAU algorithm in facilitating robust and accessible quantitative analysis of immunopeptidomes across cellular contexts. In silico analysis of the peptides enriched for each HLA-DM expression conditions suggests a higher affinity of the pool of peptides isolated from the high DM expression samples. Interestingly, our analysis reveals that while for certain autoimmune-relevant epitopes their presentation increases upon DM expression others are clearly edited out from the peptidome.

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.

Conserved Binding Regions Provide the Clue for Peptide-Based Vaccine Development: A Chemical Perspective

Synthetic peptides have become invaluable biomedical research and medicinal chemistry tools for studying functional roles, i.e., binding or proteolytic activity, naturally-occurring regions’ immunogenicity in proteins and developing therapeutic agents and vaccines. Synthetic peptides can mimic protein sites; their structure and function can be easily modulated by specific amino acid replacement. They have major advantages, i.e., they are cheap, easily-produced and chemically stable, lack infectious and secondary adverse reactions and can induce immune responses via T- and B-cell epitopes. Our group has previously shown that using synthetic peptides and adopting a functional approach has led to identifying Plasmodium falciparumconserved regions binding to host cells. Conserved high activity binding peptides’ (cHABPs) physicochemical, structural and immunological characteristics have been taken into account for properly modifying and converting them into highly immunogenic, protection-inducing peptides (mHABPs) in the experimental Aotus monkey model. This article describes stereo–electron and topochemical characteristics regarding major histocompatibility complex (MHC)-mHABP-T-cell receptor (TCR) complex formation. Some mHABPs in this complex inducing long-lasting, protective immunity have been named immune protection-inducing protein structures (IMPIPS), forming the subunit components in chemically synthesized vaccines. This manuscript summarizes this particular field and adds our recent findings concerning intramolecular interactions (H-bonds or π-interactions) enabling proper IMPIPS structure as well as the peripheral flanking residues (PFR) to stabilize the MHCII-IMPIPS-TCR interaction, aimed at inducing long-lasting, protective immunological memory.

PixelDB: Protein-peptide complexes annotated with structural conservation of the peptide binding mode

PixelDB, the Peptide Exosite Location Database, compiles 1966 non-redundant, high-resolution structures of protein-peptide complexes filtered to minimize the impact of crystal packing on peptide conformation. The database is organized to facilitate study of structurally conserved versus non-conserved elements of protein-peptide engagement. PixelDB clusters complexes based on the structural similarity of the peptide-binding protein, and by comparing complexes within a cluster highlights examples of domains that engage peptides using more than one binding mode. PixelDB also identifies conserved peptide core structural motifs characteristic of each binding mode. Peptide regions that flank core motifs often make non-structurally conserved interactions with the protein surface in regions we call exosites. Many examples establish that exosite contacts can be important for enhancing protein binding and interaction specificity. PixelDB provides a resource for computational and structural biologists to study, model, and predict core-motif and exosite-contacting peptide interactions. PixelDB is available to the community without restriction in a convenient flat-file format with accompanying visualization tools.

Phenotypic and functional characterization of T cells in white matter lesions of multiple sclerosis patients

T cells are considered pivotal in the pathology of multiple sclerosis (MS), but their function and antigen specificity are unknown. To unravel the role of T cells in MS pathology, we performed a comprehensive analysis on T cells recovered from paired blood, cerebrospinal fluid (CSF), normal-appearing white matter (NAWM) and white matter lesions (WML) from 27 MS patients with advanced disease shortly after death. The differentiation status of T cells in these compartments was determined by ex vivo flow cytometry and immunohistochemistry. T-cell reactivity in short-term T-cell lines (TCL), generated by non-specific stimulation of T cells recovered from the same compartments, was determined by intracellular cytokine flow cytometry. Central memory T cells predominated in CSF and effector memory T cells were enriched in NAWM and WML. WML-derived CD8⁺ T cells represent chronically activated T cells expressing a cytotoxic effector phenotype (CD95L and granzyme B) indicative for local antigenic stimulation (CD137). The same lesions also contained higher CD8⁺ T-cell frequencies expressing co-inhibitory (TIM3 and PD1) and co-stimulatory (ICOS) T-cell receptors, yet no evidence for T-cell senescence (CD57) was observed. The oligoclonal T-cell receptor (TCR) repertoire, particularly among CD8⁺ T cells, correlated between TCL generated from anatomically separated WML of the same MS patient, but not between paired NAWM and WML. Whereas no substantial T-cell reactivity was detected towards seven candidate human MS-associated autoantigens (cMSAg), brisk CD8⁺ T-cell reactivity was detected in multiple WML-derived TCL towards autologous Epstein–Barr virus (EBV) infected B cells (autoBLCL). In one MS patient, the T-cell response towards autoBLCL in paired intra-lesional TCL was dominated by TCRVβ2⁺CD8⁺ T cells, which were localized in the parenchyma of the respective tissues expressing a polarized TCR and CD8 expression suggesting immunological synapse formation in situ. Collectively, the data suggest the involvement of effector memory cytotoxic T cells recognizing antigens expressed by autoBLCL, but not the assayed human cMSAg, in WML of MS patients.

Computational Identification and Characterization of a Promiscuous T-Cell Epitope on the Extracellular Protein 85B of Mycobacterium spp. for Peptide-Based Subunit Vaccine Design

Tuberculosis (TB) is a reemerging disease that remains as a leading cause of morbidity and mortality in humans. To identify and characterize a T-cell epitope suitable for vaccine design, we have utilized the Vaxign server to assess all antigenic proteins of Mycobacterium spp. recorded to date in the Protegen database. We found that the extracellular protein 85B displayed the most robust antigenicity among the proteins identified. Computational tools for identifying T-cell epitopes predicted an epitope, 181-QQFIYAGSLSALLDP-195, that could bind to at least 13 major histocompatibility complexes, revealing the promiscuous nature of the epitope. Molecular docking simulation demonstrated that the epitope could bind to the binding groove of MHC II and MHC I molecules by several hydrogen bonds. Molecular docking analysis further revealed that the epitope had a distinctive binding pattern to all DRB1 and A and B series of MHC molecules and presented almost no polymorphism in its binding site. Moreover, using "Allele Frequency Database," we checked the frequency of HLA alleles in the worldwide population and found a higher frequency of both class I and II HLA alleles in individuals living in TB-endemic regions. Our results indicate that the identified peptide might be a universal candidate to produce an efficient epitope-based vaccine for TB.

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.

A deimmunised form of the ribotoxin, α-sarcin, lacking CD4+ T cell epitopes and its use as an immunotoxin warhead

Fungal ribotoxins that block protein synthesis can be useful warheads in the context of a targeted immunotoxin. α-Sarcin is a small (17 kDa) fungal ribonuclease produced by Aspergillus giganteus that functions by catalytically cleaving a single phosphodiester bond in the sarcin–ricin loop of the large ribosomal subunit, thus making the ribosome unrecognisable to elongation factors and leading to inhibition of protein synthesis. Peptide mapping using an ex vivo human T cell assay determined that α-sarcin contained two T cell epitopes; one in the N-terminal 20 amino acids and the other in the C-terminal 20 amino acids. Various mutations were tested individually within each epitope and then in combination to isolate deimmunised α-sarcin variants that had the desired properties of silencing T cell epitopes and retention of the ability to inhibit protein synthesis (equivalent to wild-type, WT α-sarcin). A deimmunised variant (D9T/Q142T) demonstrated a complete lack of T cell activation in in vitro whole protein human T cell assays using peripheral blood mononuclear cells from donors with diverse HLA allotypes. Generation of an immunotoxin by fusion of the D9T/Q142T variant to a single-chain Fv targeting Her2 demonstrated potent cell killing equivalent to a fusion protein comprising the WT α-sarcin. These results represent the first fungal ribotoxin to be deimmunised with the potential to construct a new generation of deimmunised immunotoxin therapeutics.

Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions

Why do patients suffering from neurodegenerative diseases generate autoantibodies that selectively bind soluble aggregates of amyloidogenic proteins? Presently, molecular basis of interactions between the soluble aggregates and human immune system is unknown. By analyzing sequences of experimentally validated T-cell autoimmune epitopes, aggregating peptides, amyloidogenic proteins and randomly generated peptides, here we report overlapping regions that likely drive aggregation as well as generate autoantibodies against the aggregates. Sequence features, that make short peptides susceptible to aggregation, increase their incidence in human T-cell autoimmune epitopes by 4–6 times. Many epitopes are predicted to be significantly aggregation prone (aggregation propensities ≥10%) and the ones containing experimentally validated aggregating regions are enriched in hydrophobicity by 10–20%. Aggregate morphologies also influence Human Leukocyte Antigen (HLA) - types recognized by the aggregating regions containing epitopes. Most (88%) epitopes that contain amyloid fibril forming regions bind HLA-DR, while majority (63%) of those containing amorphous β-aggregating regions bind HLA-DQ. More than two-thirds (70%) of human amyloidogenic proteins contain overlapping regions that are simultaneously aggregation prone and auto-immunogenic. Such regions help clear soluble aggregates by generating selective autoantibodies against them. This can be harnessed for early diagnosis of proteinopathies and for drug/vaccine design against them.

Alleles of HLA-DRB1*04 Associated with Pulmonary Tuberculosis in Amazon Brazilian Population

Immunogenetic host factors are associated with susceptibility or protection to tuberculosis (TB). Strong associations of HLA class II genes with TB are reported. We analyzed the HLA-DRB1*04 alleles to identify subtypes associated with pulmonary TB and their interaction with risk factors such as alcohol, smoking, and gender in 316 pulmonary TB patients and 306 healthy individuals from the Brazilian Amazon. The HLA-DRB1*04 was prevalent in patients with pulmonary TB (p<0.0001; OR = 2.94; 95% CI = 2.12 to 4.08). Direct nucleotide sequencing of DRB1 exon 2 identified nine subtypes of HLA-DRB1*04. The subtype HLA-DRB1*04:11:01 (p = 0.0019; OR = 2.23; 95% CI = 1.34 to 3.70) was associated with susceptibility to pulmonary TB while DRB1*04:07:01 (p<0.0001; OR = 0.02; 95% CI = 0.001 to 0.33) to protection. Notably, the interaction between alcohol and HLA-DRB1*04:11:01 increased the risk for developing pulmonary TB (p = 0.0001; OR = 51.3; 95% CI = 6.81 to 386). Multibacillary pulmonary TB, the clinical presentation of disease transmission, was strongly associated with interaction to alcohol (p = 0.0026; OR = 11.1; 95% CI = 3.99 to 30.9), HLA-DRB1*04:11:01 (p = 0.0442; OR = 2.01; 95% CI = 1.03 to 3.93) and DRB1*04:92 (p = 0.0112; OR = 8.62; 95% CI = 1.63 to 45.5). These results show that HLA-DRB1*04 are associated with pulmonary TB. Interestingly, three subtypes, DRB1*04:07:01, DRB1*04:11:01 and DRB1*04:92 of the HLA-DRB1*04 could be potential immunogenetic markers that may help to explain mechanisms involved in disease development.

Enhanced Detection of Antigen-Specific CD4+ T Cells Using Altered Peptide Flanking Residue Peptide-MHC Class II Multimers

Fluorochrome-conjugated peptide–MHC (pMHC) class I multimers are staple components of the immunologist’s toolbox, enabling reliable quantification and analysis of Ag-specific CD8⁺ T cells irrespective of functional outputs. In contrast, widespread use of the equivalent pMHC class II (pMHC-II) reagents has been hindered by intrinsically weaker TCR affinities for pMHC-II, a lack of cooperative binding between the TCR and CD4 coreceptor, and a low frequency of Ag-specific CD4⁺ T cell populations in the peripheral blood. In this study, we show that peptide flanking regions, extending beyond the central nonamer core of MHC-II–bound peptides, can enhance TCR–pMHC-II binding and T cell activation without loss of specificity. Consistent with these findings, pMHC-II multimers incorporating peptide flanking residue modifications proved superior for the ex vivo detection, characterization, and manipulation of Ag-specific CD4⁺ T cells, highlighting an unappreciated feature of TCR–pMHC-II interactions.

Intrathecal CD4(+) and CD8(+) T-cell responses to endogenously synthesized candidate disease-associated human autoantigens in multiple sclerosis patients

MS pathology is potentially orchestrated by autoreactive T cells, but the antigens recognized remain unknown. A novel APC/T-cell platform was developed to determine intrathecal CD4(+) and CD8(+) T-cell responses to candidate MS-associated autoantigens (cMSAg) in clinically isolated syndrome (CIS, n = 7) and MS (n = 6) patients. Human cMSAg encoding open reading frames (n = 8) were cloned into an Epstein-Barr virus (EBV)-based vector to express cMSAg at high levels in EBV-transformed B-cells (BLCLs). Human cMSAg cloned were myelin-associated and -oligodendrocyte glycoprotein, myelin basic protein, proteolipid protein, ATP-dependent potassium channel ATP-dependent inwards rectifying potassium channel 4.1, S100 calcium-binding protein B, contactin-2, and neurofascin. Transduced BLCLs were used as autologous APC in functional T-cell assays to determine cMSAg-specific T-cell frequencies in cerebrospinal fluid derived T-cell lines (CSF-TCLs) by intracellular IFN-γ flow cytometry. Whereas all CSF-TCL responded strongly to mitogenic stimulation, no substantial T-cell reactivity to cMSAg was observed. Contrastingly, measles virus fusion protein-specific CD4(+) and CD8(+) T-cell clones, used as control of the APC/T-cell platform, efficiently recognized transduced BLCL expressing their cognate antigen. The inability to detect substantial T-cell reactivity to eight human endogenously synthesized cMSAg in autologous APC do not support their role as prominent intrathecal T-cell target antigens in CIS and MS patients early after onset of disease.

Sequence conservation analysis and in silico human leukocyte antigen-peptide binding predictions for the Mtb72F and M72 tuberculosis candidate vaccine antigens

Background

Requisites for an efficacious tuberculosis (TB) vaccine are a minimal genomic diversity among infectious Mycobacterium tuberculosis strains for the selected antigen, and the capability to induce robust T-cell responses in the majority of human populations. A tool in the identification of putative T-cell epitopes is in silico prediction of major histocompatibility complex (MHC)-peptide binding. Candidate TB vaccine antigen Mtb72F and its successor M72 are recombinant fusion proteins derived from Mtb32A and Mtb39A (encoded by Rv0125 and Rv1196, respectively). Adjuvanted Mtb72F and M72 candidate vaccines were shown to induce CD4⁺ T-cell responses in European, US, African and Asian populations.

Methods

Sequence conservation of Mtb32A, Mtb39A, Mtb72F and M72 among 46 strains (prevalent Mycobacterium strains causing human TB disease, and H37Ra) was assessed by multiple alignments using ClustalX. For Mtb32A, Mtb39A and Mtb72F, 15-mer human leukocyte antigen (HLA)-class II-binding peptides were predicted for 158 DRB1 alleles prevailing in populations with high TB burden, 6 DRB3/4/5, 8 DQ and 6 DP alleles, using NetMHCII-pan-3.0. Results for 3 DRB1 alleles were compared with previously published allele-matched in vitro binding data. Additional analyses were done for M72. Nonameric MHC class I-binding peptides in Mtb72F were predicted for three alleles representative of class I supertypes A02, A03 and B07, using seven prediction algorithms.

Results

Sequence identity among strains was ≥98 % for each protein. Residue changes in Mtb39A comprised primarily single residue or nucleotide insertions and/or deletions in repeat regions, and were observed in 67 % of strains. For Mtb72F, 156 DRB1, 6 DRB3/4/5, 7 DQ and 5 DP alleles were predicted to contain at least one MHC class II-binding peptide, and class I-binding peptides were predicted for each HLA-A/B allele. Comparison of predicted MHC-II-binding peptides with experimental data indicated that the algorithm’s sensitivity and specificity were variable among alleles.

Conclusions

The sequences from which Mtb72F and M72 are derived are highly conserved among representative Mycobacterium strains. Predicted putative T-cell epitopes in M72 and/or Mtb72F covered a wide array of HLA alleles. In silico binding predictions for class I- and II-binding putative epitopes can be complemented with biochemical verification of HLA binding capacity, processing and immunogenicity of the predicted peptides.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-015-0119-7) contains supplementary material, which is available to authorized users.

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

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

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

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.

Immunogenic peptide discovery in cancer genomes

As immunotherapies to treat malignancy continue to diversify along with the tumor types amenable to treatment, it will become very important to predict which treatment is most likely to benefit a given patient. Tumor neoantigens, novel peptides resulting from somatic tumor mutations and recognized by the immune system as foreign, are likely to contribute significantly to the efficacy of immunotherapy. Multiple in silico methods have been developed to predict whether peptides, including tumor neoantigens, will be presented by the major histocompatibility complex (MHC) Class I or Class II, and interact with the T cell receptor (TCR). The methods for neoantigen prediction will be reviewed here, along with the most important examples of their use in the field of oncology.

Prediction of epitope-based peptides for the utility of vaccine development from fusion and glycoprotein of nipah virus using in silico approach

This study aims to design epitope-based peptides for the utility of vaccine development by targeting glycoprotein G and envelope protein F of Nipah virus (NiV) that, respectively, facilitate attachment and fusion of NiV with host cells. Using various databases and tools, immune parameters of conserved sequence(s) from G and F proteins of different isolates of NiV were tested to predict probable epitope(s). Binding analyses of the peptides with MHC class-I and class-II molecules, epitope conservancy, population coverage, and linear B cell epitope prediction were analyzed. Predicted peptides interacted with seven or more MHC alleles and illustrated population coverage of more than 99% and 95%, for G and F proteins, respectively. The predicted class-I nonamers, SLIDTSSTI and EWISIVPNF, superimposed on the putative decameric B cell epitopes, were also identified as core sequences of the most probable class-II 15-mer peptides GPKVSLIDTSSTITI and EWISIVPNFILVRNT. These peptides were further validated for their binding to specific HLA alleles using in silico docking technique. Our in silico analysis suggested that the predicted epitopes, either GPKVSLIDTSSTITI or EWISIVPNFILVRNT, could be a better choice as universal vaccine component against NiV irrespective of different isolates which may elicit both humoral and cell-mediated immunity.

The versatility of the αβ T-cell antigen receptor

The T-cell antigen receptor is a heterodimeric αβ protein (TCR) expressed on the surface of T-lymphocytes, with each chain of the TCR comprising three complementarity-determining regions (CDRs) that collectively form the antigen-binding site. Unlike antibodies, which are closely related proteins that recognize intact protein antigens, TCRs classically bind, via their CDR loops, to peptides (p) that are presented by molecules of the major histocompatibility complex (MHC). This TCR-pMHC interaction is crucially important in cell-mediated immunity, with the specificity in the cellular immune response being attributable to MHC polymorphism, an extensive TCR repertoire and a variable peptide cargo. The ensuing structural and biophysical studies within the TCR-pMHC axis have been highly informative in understanding the fundamental events that underpin protective immunity and dysfunctional T-cell responses that occur during autoimmunity. In addition, TCRs can recognize the CD1 family, a family of MHC-related molecules that instead of presenting peptides are ideally suited to bind lipid-based antigens. Structural studies within the CD1-lipid antigen system are beginning to inform us how lipid antigens are specifically presented by CD1, and how such CD1-lipid antigen complexes are recognized by the TCR. Moreover, it has recently been shown that certain TCRs can bind to vitamin B based metabolites that are bound to an MHC-like molecule termed MR1. Thus, TCRs can recognize peptides, lipids, and small molecule metabolites, and here we review the basic principles underpinning this versatile and fascinating receptor recognition system that is vital to a host's survival.

APL-1, an altered peptide ligand derived from human heat-shock protein 60, selectively induces apoptosis in activated CD4+ CD25+ T cells from peripheral blood of rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic T-cell mediated autoimmune disease that affects primarily the joints. The induction of immune tolerance through antigen-specific therapies for the blockade of pathogenic CD4+ T cells constitutes a current focus of research. In this focus it is attempted to simultaneously activate multiple regulatory mechanisms, such as: apoptosis and regulatory T cells (Tregs). APL-1 is an altered peptide ligand derived from a novel CD4+ T-cell epitope of human heat-shock protein of 60kDa, an autoantigen involved in the pathogenesis of RA. Previously, we have reported that APL-1 induces CD4+ CD25(high)Foxp3+ Tregs in several systems. Here, we investigated the ability of APL-1 in inducing apoptosis in PBMCs from RA patients, who were classified as active or inactive according to their DAS28 score. APL-1 decreased the viability of PBMCs from active but not from inactive patients. DNA fragmentation assays and typical morphological features clearly demonstrated that APL-1 induced apoptosis in these cells. Activated CD4+ CD25+ T cells but not resting CD4+ CD25- T cells were identified as targets of APL-1. Furthermore, CD4+ T-cell responses to APL-1 were found to be dependent on antigen presentation via the HLA-DR molecule. Thus, APL-1 is a regulatory CD4+ T cell epitope which might modulate inflammatory immune responses in PBMCs from RA patients by inducing CD4+ CD25(high)Foxp3+ Tregs and apoptosis in activated CD4+ T cells. These results support further investigation of this candidate drug for the treatment of RA.

T-cell dependent immunogenicity of protein therapeutics: Preclinical assessment and mitigation

Protein therapeutics hold a prominent and rapidly expanding place among medicinal products. Purified blood products, recombinant cytokines, growth factors, enzyme replacement factors, monoclonal antibodies, fusion proteins, and chimeric fusion proteins are all examples of therapeutic proteins that have been developed in the past few decades and approved for use in the treatment of human disease. Despite early belief that the fully human nature of these proteins would represent a significant advantage, adverse effects associated with immune responses to some biologic therapies have become a topic of some concern. As a result, drug developers are devising strategies to assess immune responses to protein therapeutics during both the preclinical and the clinical phases of development. While there are many factors that contribute to protein immunogenicity, T cell- (thymus-) dependent (Td) responses appear to play a critical role in the development of antibody responses to biologic therapeutics. A range of methodologies to predict and measure Td immune responses to protein drugs has been developed. This review will focus on the Td contribution to immunogenicity, summarizing current approaches for the prediction and measurement of T cell-dependent immune responses to protein biologics, discussing the advantages and limitations of these technologies, and suggesting a practical approach for assessing and mitigating Td immunogenicity.

Molecular dynamics simulations to provide insights into epitopes coupled to the soluble and membrane-bound MHC-II complexes

Epitope recognition by major histocompatibility complex II (MHC-II) is essential for the activation of immunological responses to infectious diseases. Several studies have demonstrated that this molecular event takes place in the MHC-II peptide-binding groove constituted by the α and β light chains of the heterodimer. This MHC-II peptide-binding groove has several pockets (P1-P11) involved in peptide recognition and complex stabilization that have been probed through crystallographic experiments and in silico calculations. However, most of these theoretical calculations have been performed without taking into consideration the heavy chains, which could generate misleading information about conformational mobility both in water and in the membrane environment. Therefore, in absence of structural information about the difference in the conformational changes between the peptide-free and peptide-bound states (pMHC-II) when the system is soluble in an aqueous environment or non-covalently bound to a cell membrane, as the physiological environment for MHC-II is. In this study, we explored the mechanistic basis of these MHC-II components using molecular dynamics (MD) simulations in which MHC-II was previously co-crystallized with a small epitope (P₇) or coupled by docking procedures to a large (P₂₂) epitope. These MD simulations were performed at 310 K over 100 ns for the water-soluble (MHC-II_w, MHC-II-P_7w, and MHC-II-P_22w) and 150 ns for the membrane-bound species (MHC-II_m, MHC-II-P_7m, and MHC-II-P_22m). Our results reveal that despite the different epitope sizes and MD simulation environments, both peptides are stabilized primarily by residues lining P1, P4, and P6-7, and similar noncovalent intermolecular energies were observed for the soluble and membrane-bound complexes. However, there were remarkably differences in the conformational mobility and intramolecular energies upon complex formation, causing some differences with respect to how the two peptides are stabilized in the peptide-binding groove.

Re-Directing CD4(+) T Cell Responses with the Flanking Residues of MHC Class II-Bound Peptides: The Core is Not Enough

Recombinant αβ T cell receptors, expressed on T cell membranes, recognize short peptides presented at the cell surface in complex with MHC molecules. There are two main subsets of αβ T cells: CD8(+) T cells that recognize mainly cytosol-derived peptides in the context of MHC class I (pMHC-I), and CD4(+) T cells that recognize peptides usually derived from exogenous proteins presented by MHC class II (pMHC-II). Unlike the more uniform peptide lengths (usually 8-13mers) bound in the MHC-I closed groove, MHC-II presented peptides are of a highly variable length. The bound peptides consist of a core bound 9mer (reflecting the binding motif for the particular MHC-II type) but with variable peptide flanking residues (PFRs) that can extend from both the N- and C-terminus of the MHC-II binding groove. Although pMHC-I and pMHC-II play a virtually identical role during T cell responses (T cell antigen presentation) and are very similar in overall conformation, there exist a number of subtle but important differences that may govern the functional dichotomy observed between CD8(+) and CD4(+) T cells. Here, we provide an overview of the impact of structural differences between pMHC-I and pMHC-II and the molecular interactions with the T cell receptor including the functional importance of MHC-II PFRs. We consider how factors such as anatomical location, inflammatory milieu, and particular types of antigen presenting cell might, in theory, contribute to the quantitative (i.e., pMHC ligand frequency) as well as qualitative (i.e., variable PFR) nature of peptide epitopes, and hence offer a means of control and influence of a CD4(+) T cell response. Lastly, we review our recent findings showing how modifications to MHC-II PFRs can modify CD4(+) T cell antigen recognition. These findings may have novel applications for the development of CD4(+) T cell peptide vaccines and diagnostics.

Using databases and data mining in vaccinology

Throughout time functional immunology has accumulated vast amounts of quantitative and qualitative data relevant to the design and discovery of vaccines. Such data includes, but is not limited to, components of the host and pathogen genome (including antigens and virulence factors), T- and B-cell epitopes and other components of the antigen presentation pathway and allergens. In this review the authors discuss a range of databases that archive such data. Built on such information, increasingly sophisticated data mining techniques have developed that create predictive models of utilitarian value. With special reference to epitope data, the authors discuss the strengths and weaknesses of the available techniques and how they can aid computer-aided vaccine design deliver added value for vaccinology.

Prediction of peptides binding to MHC class I and II alleles by temporal motif mining

BACKGROUND

MHC (Major Histocompatibility Complex) is a key player in the immune response of most vertebrates. The computational prediction of whether a given antigenic peptide will bind to a specific MHC allele is important in the development of vaccines for emerging pathogens, the creation of possibilities for controlling immune response, and for the applications of immunotherapy. One of the problems that make this computational prediction difficult is the detection of the binding core region in peptides, coupled with the presence of bulges and loops causing variations in the total sequence length. Most machine learning methods require the sequences to be of the same length to successfully discover the binding motifs, ignoring the length variance in both motif mining and prediction steps. In order to overcome this limitation, we propose the use of time-based motif mining methods that work position-independently.

RESULTS

The prediction method was tested on a benchmark set of 28 different alleles for MHC class I and 27 different alleles for MHC class II. The obtained results are comparable to the state of the art methods for both MHC classes, surpassing the published results for some alleles. The average prediction AUC values are 0.897 for class I, and 0.858 for class II.

CONCLUSIONS

Temporal motif mining using partial periodic patterns can capture information about the sequences well enough to predict the binding of the peptides and is comparable to state of the art methods in the literature. Unlike neural networks or matrix based predictors, our proposed method does not depend on peptide length and can work with both short and long fragments. This advantage allows better use of the available training data and the prediction of peptides of uncommon lengths.

Flanking residues are central to DO11.10 T cell hybridoma stimulation by ovalbumin 323-339

T cell activation requires formation of a tri-molecular interaction between a major histocompatibility complex (MHC), peptide, and T cell receptor. In a common model system, the ovalbumin epitope 323–339 binds the murine class II MHC, I-A^d, in at least three distinct registers. The DO11.10 T cell recognizes the least stable of these, as determined by peptide-MHC dissociation rates. Using exogenous peptides and peptide insertions into a carrier protein in combination with IL-2 secretion assays, we show that the alternate registers do not competitively inhibit display of the active register four. In contrast, this weakly binding register is stabilized by the presence of n-terminal flanking residues active in MHC binding. The DO11.10 hybridoma is sensitive to the presence of specific wild-type residues extending to at least the P-3 peptide position. Transfer of the P-4 to P-2 flanking residues to a hen egg lysozyme epitope also presented by I-A^d increases the activity of that epitope substantially. These results illustrate the inherent complexity in delineating the interaction of multiple registers based on traditional thermodynamic measurements and demonstrate the potential of flanking residue modification for increasing the activity of weakly bound epitopes. The latter technique represents an alternative to substitution of anchor residues within a weakly bound register, which we show can significantly decrease the activity of the epitope to a responding T cell.