HLA peptide length preferences control CD8+ T cell responses

Characterisation of novel influenza-derived HLA-B*18:01-restricted epitopes

Objectives

Seasonal influenza viruses cause roughly 650 000 deaths annually despite available vaccines. CD8+ T cells typically recognise influenza-derived peptides from internal structural and non-structural influenza proteins and are an attractive avenue for future vaccine design as they could reduce the severity of disease following infection with diverse influenza strains. CD8+ T cells recognise peptides presented by the highly polymorphic Human Leukocyte Antigens class I molecules (HLA-I). Each HLA-I variant has distinct peptide binding preferences, representing a significant obstacle for designing vaccines that elicit CD8+ T cell responses across broad populations. Consequently, the rational design of a CD8+ T cell-mediated vaccine would require the identification of highly immunogenic peptides restricted to a range of different HLA molecules.

Methods

Here, we assessed the immunogenicity of six recently published novel influenza-derived peptides identified by mass-spectrometry and predicted to bind to the prevalent HLA-B*18:01 molecule.

Results

Using CD8+ T cell activation assays and protein biochemistry, we showed that 3/6 of the novel peptides were immunogenic in several HLA-B*18:01+ individuals and confirmed their HLA-B*18:01 restriction. We subsequently compared CD8+ T cell responses towards the previously identified highly immunogenic HLA-B*18:01-restricted NP219 peptide. Using X-ray crystallography, we solved the first crystal structures of HLA-B*18:01 presenting immunogenic influenza-derived peptides. Finally, we dissected the first TCR repertoires specific for HLA-B*18:01 restricted pathogen-derived peptides, identifying private and restricted repertoires against each of the four peptides.

Conclusion

Overall the characterisation of these novel immunogenic peptides provides additional HLA-B*18:01-restricted vaccine targets derived from the Matrix protein 1 and potentially the non-structural protein and the RNA polymerase catalytic subunit of influenza viruses.

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan's predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.

MHC-Fine: Fine-tuned AlphaFold for Precise MHC-Peptide Complex Prediction

The precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold's capabilities by fine-tuning it with a specialized dataset comprised by exclusively high-resolution MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold's original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of MHC-peptide interaction prediction. A comparative analysis was conducted against the homology-modeling-based method Pandora [13], as well as the AlphaFold multimer model [8]. Our results demonstrate that our fine-tuned model outperforms both in terms of RMSD (median value is 0.65 Å) but also provides enhanced predicted lDDT scores, offering a more reliable assessment of the predicted structures. These advances have substantial implications for computational immunology, potentially accelerating the development of novel therapeutics and vaccines by providing a more precise computational lens through which to view MHC-peptide interactions.

Identification of T-Cell Epitopes Using a Combined In-Silico and Experimental Approach in a Mouse Model for SARS-CoV-2

Following viral infection, T-cells are crucial for an effective immune response to intracellular pathogens, including respiratory viruses. During the COVID-19 pandemic, diverse assays were required in pre-clinical trials to evaluate the immune response following vaccination against SARS-CoV-2 and assess the response following exposure to the virus. To assess the nature and potency of the cellular response to infection or vaccination, a reliable and specific activity assay was needed. A cellular activity assay based on the presentation of short peptides (epitopes) allows the identification of T cell epitopes displayed on different alleles of the MHC, shedding light on the strength of the immune response towards antigens and aiding in antigen design for vaccination. In this report, we describe two approaches for scanning T cell epitopes on the surface glycoprotein of the SARS-CoV-2 (spike), which is utilized for attachment and entry and serves as an antigen in many vaccine candidates. We demonstrate that epitope scanning is feasible using peptide libraries or computational scanning combined with a cellular activity assay. Our scans identified four CD8 T cell epitopes, including one novel undescribed epitope. These epitopes enabled us to establish a reliable T-cell response assay, which was examined and used in various experimental mouse models for SARS-CoV-2 infection and vaccination. These approaches could potentially aid in future antigen design for vaccination and establish cellular activity assays against uncharacterized antigens of emerging pathogens.

Identification and Mitigation of Defensins in the Immunopurification of Peptide MHC-I Antigens from Lung Tissue

The class I major histocompatibility (MHC-I) complex is a set of diverse cell surface receptors encoded by the human leukocyte antigen gene complex. These receptors present intracellular antigens to cytotoxic T cells providing information on the state and health of cells. Changes in the immunopeptidome during cancer may provide novel targets for therapeutic intervention. To understand how the tumor immunopeptidome is altered, we developed a mass spectrometry (MS) based platform for isolating and identifying MHC-I peptide antigens in lung tumors. In the course of our work, we encountered several large unknown peptide contaminants which had not been previously reported. To understand the source of these major contaminants, we isolated them using offline fractionation and identified them by liquid chromatography-tandem mass spectrometry (LC-MS/MS) as members of the host defense protein family known as the defensins. To mitigate their detrimental effects, we modified our "Original" data-dependent acquisition (DDA) MS method to narrowly target the MHC-I peptides based on their physical properties including charge state and molecular weight ("z state" DDA), evaluated field asymmetric ion mobility spectrometry to attempt gas-phase separation prior to MS analysis, and developed an immunodepletion approach using defensin specific antibodies. This modified approach improves peptide identification and reduces the impact of defensin contamination in lung tissue samples.

Peptidomes and Structures Illustrate How SLA-I Micropolymorphism Influences the Preference of Binding Peptide Length

Polymorphisms can affect MHC-I binding peptide length preferences, but the mechanism remains unclear. Using a random peptide library combined with LC-MS/MS and de novo sequencing (RPLD-MS) technique, we found that two swine MHC-I molecules with high sequence homology, SLA-1*04:01 and SLA-1*13:01, had significant differences in length preference of the binding peptides. Compared with SLA-1*04:01, SLA-1*13:01 binds fewer short peptides with 8-10 amino acids, but more long peptides. A dodecapeptide peptide (RW12) can bind to both SLA-1*04:01 and SLA-1*13:01, but their crystal structures indicate that the binding modes are significantly different: the entirety of RW12 is embedded in the peptide binding groove of SLA-1*04:01, but it obviously protrudes from the peptide binding groove of SLA-1*13:01. The structural comparative analysis showed that only five differential amino acids of SLA-1*13:01 and SLA-1*04:01 were involved in the binding of RW12, and they determine the different ways of long peptides binding, which makes SLA-1*04:01 more restrictive on long peptides than SLA-1*13:01, and thus binds fewer long peptides. In addition, we found that the N terminus of RW12 extends from the groove of SLA-1*13:01, which is similar to the case previously found in SLA-1*04:01. However, this unusual peptide binding does not affect their preferences of binding peptide length. Our study will be helpful to understand the effect of polymorphisms on the length distribution of MHC-I binding peptides, and to screen SLA-I-restricted epitopes of different lengths and to design effective epitope vaccines.

Mechanistic diversity in MHC class I antigen recognition

Throughout its evolution, the human immune system has developed a plethora of strategies to diversify the antigenic peptide sequences that can be targeted by the CD8+ T cell response against pathogens and aberrations of self. Here we provide a general overview of the mechanisms that lead to the diversity of antigens presented by MHC class I complexes and their recognition by CD8+ T cells, together with a more detailed analysis of recent progress in two important areas that are highly controversial: the prevalence and immunological relevance of unconventional antigen peptides; and cross-recognition of antigenic peptides by the T cell receptors of CD8+ T cells.

Broad-Based Influenza-Specific CD8+ T Cell Response without the Typical Immunodominance Hierarchy and Its Potential Implication

Syngeneic murine systems have pre-fixed MHC, making them an imperfect model for investigating the impact of MHC polymorphism on immunodominance in influenza A virus (IAV) infections. To date, there are few studies focusing on MHC allelic differences and its impact on immunodominance even though it is well documented that an individual’s HLA plays a significant role in determining immunodominance hierarchy. Here, we describe a broad-based CD8⁺ T cell response in a healthy individual to IAV infection rather than a typical immunodominance hierarchy. We used a systematic antigen screen approach combined with epitope prediction to study such a broad CD8⁺ T cell response to IAV infection. We show CD8⁺ T cell responses to nine IAV proteins and identify their minimal epitope sequences. These epitopes are restricted to HLA-B*44:03, HLA-A*24:02 and HLA-A*33:03 and seven out of the nine epitopes are novel (NP_319–330^# (known and demonstrated minimal epitope positions are subscripted; otherwise, amino acid positions are shown as normal text (for example NP 319–330 or NP 313–330)), M1_124–134, M2_7–15, NA_337–346, PB2_39–49, HA_445–453 and NS1_195–203). Additionally, most of these novel epitopes are highly conserved among H1N1 and H3N2 strains that circulated in Australia and other parts of the world.

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Genetic Bias, Diversity Indices, Physiochemical Properties and CDR3 Motifs Divide Auto-Reactive from Allo-Reactive T-Cell Repertoires

The distinct properties of allo-reactive T-cell repertoires are not well understood. To investigate whether auto-reactive and allo-reactive T-cell repertoires encoded distinct properties, we used dextramer enumeration, enrichment, single-cell T-cell receptor (TCR) sequencing and multiparameter analysis. We found auto-reactive and allo-reactive T-cells differed in mean ex vivo frequency which was antigen dependent. Allo-reactive T-cells showed clear differences in TCR architecture, with enriched usage of specific T-cell receptor variable (TRBJ) genes and broader use of T-cell receptor variable joining (TRBJ) genes. Auto-reactive T-cell repertoires exhibited complementary determining regions three (CDR3) lengths using a Gaussian distribution whereas allo-reactive T-cell repertoires exhibited distorted patterns in CDR3 length. CDR3 loops from allo-reactive T-cells showed distinct physical-chemical properties, tending to encode loops that were more acidic in charge. Allo-reactive T-cell repertoires differed in diversity metrics, tending to show increased overall diversity and increased homogeneity between repertoires. Motif analysis of CDR3 loops showed allo-reactive T-cell repertoires differed in motif preference which included broader motif use. Collectively, these data conclude that allo-reactive T-cell repertoires are indeed different to auto-reactive repertoires and provide tangible metrics for further investigations and validation. Given that the antigens studied here are overexpressed on multiple cancers and that allo-reactive TCRs often show increased ligand affinity, this new TCR bank also has translational potential for adoptive cell therapy, soluble TCR-based therapy and rational TCR design.

Potential CD8+ T Cell Cross-Reactivity Against SARS-CoV-2 Conferred by Other Coronavirus Strains

While individuals infected with coronavirus disease 2019 (COVID-19) manifested a broad range in susceptibility and severity to the disease, the pre-existing immune memory to related pathogens cross-reactive against SARS-CoV-2 can influence the disease outcome in COVID-19. Here, we investigated the potential extent of T cell cross-reactivity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be conferred by other coronaviruses and influenza virus, and generated an in silico map of public and private CD8+ T cell epitopes between coronaviruses. We observed 794 predicted SARS-CoV-2 epitopes of which 52% were private and 48% were public. Ninety-nine percent of the public epitopes were shared with SARS-CoV and 5.4% were shared with either one of four common coronaviruses, 229E, HKU1, NL63, and OC43. Moreover, to assess the potential risk of self-reactivity and/or diminished T cell response for peptides identical or highly similar to the host, we identified predicted epitopes with high sequence similarity with human proteome. Lastly, we compared predicted epitopes from coronaviruses with epitopes from influenza virus deposited in IEDB, and found only a small number of peptides with limited potential for cross-reactivity between the two virus families. We believe our comprehensive in silico profile of private and public epitopes across coronaviruses would facilitate design of vaccines, and provide insights into the presence of pre-existing coronavirus-specific memory CD8+ T cells that may influence immune responses against SARS-CoV-2.

HIV-1 induced changes in HLA-C*03 : 04-presented peptide repertoires lead to reduced engagement of inhibitory natural killer cell receptors

OBJECTIVE

Viral infections influence intracellular peptide repertoires available for presentation by HLA-I. Alterations in HLA-I/peptide complexes can modulate binding of killer immunoglobuline-like receptors (KIRs) and thereby the function of natural killer (NK) cells. Although multiple studies have provided evidence that HLA-I/KIR interactions play a role in HIV-1 disease progression, the consequence of HIV-1 infection for HLA-I/KIR interactions remain largely unknown.

DESIGN

We determined changes in HLA-I presented peptides resulting from HIV-1-infection of primary human CD4 T cells and assessed the impact of changes in peptide repertoires on HLA-I/KIR interactions.

METHODS

Liquid chromatography-coupled tandem mass spectrometry to identify HLA-I presented peptides, cell-based in-vitro assays to evaluate functional consequences of alterations in immunopeptidome and atomistic molecular dynamics simulations to confirm experimental data.

RESULTS

A total of 583 peptides exclusively presented on HIV-1-infected cells were identified, of which only 0.2% represented HIV-1 derived peptides. Focusing on HLA-C*03 : 04/KIR2DL3 interactions, we observed that HLA-C*03 : 04-presented peptides derived from noninfected CD4 T cells mediated stronger binding of inhibitory KIR2DL3 than peptides derived from HIV-1-infected cells. Furthermore, the most abundant peptide presented by HLA-C*03 : 04 on noninfected CD4 T cells (VIYPARISL) mediated the strongest KIR2DL3-binding, while the most abundant peptide presented on HIV-1-infected cells (YAIQATETL) did not mediate KIR2DL3-binding. Molecular dynamics simulations of HLA-C*03 : 04/KIR2DL3 interactions in the context of these two peptides revealed that VIYPARISL significantly enhanced the HLA-C*03 : 04/peptide contact area to KIR2DL3 compared with YAIQATETL.

CONCLUSION

These data demonstrate that HIV-1 infection-induced changes in HLA-I-presented peptides can reduce engagement of inhibitory KIRs, providing a mechanism for enhanced activation of NK cells by virus-infected cells.

Cross-Reactive Donor-Specific CD8+ Tregs Efficiently Prevent Transplant Rejection

To reduce the use of non-specific immunosuppressive drugs detrimental to transplant patient health, therapies in development aim to achieve antigen-specific tolerance by promoting antigen-specific regulatory T cells (Tregs). However, identification of the natural antigens recognized by Tregs and the contribution of their dominance in transplantation has been challenging. We identify epitopes derived from distinct major histocompatibility complex (MHC) class II molecules, sharing a 7-amino acid consensus sequence positioned in a central mobile section in complex with MHC class I, recognized by cross-reactive CD8⁺ Tregs, enriched in the graft. Antigen-specific CD8⁺ Tregs can be induced in vivo with a 16-amino acid-long peptide to trigger transplant tolerance. Peptides derived from human HLA class II molecules, harboring the rat consensus sequence, also activate and expand human CD8⁺ Tregs, suggesting its potential in human transplantation. Altogether, this work should facilitate the development of therapies with peptide epitopes for transplantation and improve our understanding of CD8⁺ Treg recognition.

Overlapping Peptides Elicit Distinct CD8+ T Cell Responses following Influenza A Virus Infection

The presentation of pathogen-derived peptides on MHC class I molecules is essential for the initiation of adaptive CD8⁺ T cell immunity, which in turn is critical for effective control of many significant human infections. The identification of immunogenic pathogen-derived epitopes and a detailed understanding of how they are recognized by TCRs is essential for the design of effective T cell-based vaccines. In this study, we have characterized the T cell recognition and immune responses in mice to two naturally presented influenza A virus-derived peptides previously identified from virally infected cells via mass spectrometry. These neuraminidase-derived peptides, NA_181-190 (SGPDNGAVAV) and NA_181-191 (SGPDNGAVAVL), are completely overlapping with the exception of a 1 aa extension at the C terminus of the longer peptide. This minor peptidic difference results in the induction of two completely independent and non-cross-reactive T cell populations that show distinct functional characteristics after influenza A virus infection of B6 mice. We show that the unique TCR reactivity to the overlapping peptides is present in the naive repertoire prior to immune expansion in B6 mice. Moreover, we provide a structural explanation underlying the distinct CD8⁺ T cell reactivities, which reinforces the concept that peptide length is a key determinant of Ag specificity in CD8⁺ T cell responses.

Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions

We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations for SARS-CoV-2. Our approach optimizes the presentation likelihood of a diverse set of vaccine peptides conditioned on a target human-population HLA haplotype distribution and expected epitope drift. Our proposed SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA average hits per person (≥ 1 peptide: 99.91%) with all vaccine peptides perfectly conserved across 4,690 geographically sampled SARS-CoV-2 genomes. Our proposed MHC class II vaccine formulations provide 97.21% predicted coverage with at least five vaccine peptide-HLA average hits per person with all peptides having an observed mutation probability of ≤ 0.001. We provide an open-source implementation of our design methods (OptiVax), vaccine evaluation tool (EvalVax), as well as the data used in our design efforts here: https://github.com/gifford-lab/optivax.

Robust computational design and evaluation of peptide vaccines for cellular immunity with application to SARS-CoV-2

We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations, and we find for SARS-CoV-2 that it provides superior predicted display of viral epitopes by MHC class I and MHC class II molecules over populations when compared to other candidate vaccines. Our method is robust to idiosyncratic errors in the prediction of MHC peptide display and considers target population HLA haplotype frequencies during optimization. To minimize clinical development time our methods validate vaccines with multiple peptide presentation algorithms to increase the probability that a vaccine will be effective. We optimize an objective function that is based on the presentation likelihood of a diverse set of vaccine peptides conditioned on a target population HLA haplotype distribution and expected epitope drift. We produce separate peptide formulations for MHC class I loci (HLA-A, HLA-B, and HLA-C) and class II loci (HLA-DP, HLA-DQ, and HLA-DR) to permit signal sequence based cell compartment targeting using nucleic acid based vaccine platforms. Our SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA hits on average in an individual (≥ 1 peptide 99.91%) with all vaccine peptides perfectly conserved across 4,690 geographically sampled SARS-CoV-2 genomes. Our MHC class II vaccine formulations provide 90.17% predicted coverage with at least five vaccine peptide-HLA hits on average in an individual with all peptides having observed mutation probability ≤ 0.001. We evaluate 29 previously published peptide vaccine designs with our evaluation tool with the requirement of having at least five vaccine peptide-HLA hits per individual, and they have a predicted maximum of 58.51% MHC class I coverage and 71.65% MHC class II coverage given haplotype based analysis. We provide an open source implementation of our design methods (OptiVax), vaccine evaluation tool (EvalVax), as well as the data used in our design efforts.

A large peptidome dataset improves HLA class I epitope prediction across most of the human population

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

ERAP1 enzyme-mediated trimming and structural analyses of MHC I-bound precursor peptides yield novel insights into antigen processing and presentation

Endoplasmic reticulum aminopeptidase 1 (ERAP1) and ERAP2 critically shape the major histocompatibility complex I (MHC I) immunopeptidome. The ERAPs remove N-terminal residues from antigenic precursor peptides and generate optimal-length peptides (i.e. 8-10-mers) to fit into the MHC class I groove. It is therefore intriguing that MHC class I molecules can present N-terminally extended peptides on the cell surface that can elicit CD8+ T-cell responses. This observation likely reflects gaps in our understanding of how antigens are processed by the ERAP enzymes. To better understand ERAPs' function in antigen processing, here we generated a nested set of N-terminally extended 10-20-mer peptides (RA) _n AAKKKYCL covalently bound to the human leukocyte antigen (HLA)-B*0801. We used X-ray crystallography, thermostability assessments, and an ERAP1-trimming assay to characterize these complexes. The X-ray structures determined at 1.40-1.65 Å resolutions revealed that the residue extensions (RA) _n unexpectedly protrude out of the A pocket of HLA-B*0801, whereas the AAKKKYCL core of all peptides adopts similar, bound conformations. HLA-B*0801 residue 62 was critical to open the A pocket. We also show that HLA-B*0801 and antigenic precursor peptides form stable complexes. Finally, ERAP1-mediated trimming of the MHC I-bound peptides required a minimal length of 14 amino acids. We propose a mechanistic model explaining how ERAP1-mediated trimming of MHC I-bound peptides in cells can generate peptides of canonical as well as noncanonical lengths that still serve as stable MHC I ligands. Our results provide a framework to better understand how the ERAP enzymes influence the MHC I immunopeptidome.

Peptide-Major Histocompatibility Complex Class I Binding Prediction Based on Deep Learning With Novel Feature

Peptide-based vaccine development needs accurate prediction of the binding affinity between major histocompatibility complex I (MHC I) proteins and their peptide ligands. Nowadays more and more machine learning methods have been developed to predict binding affinity and some of them have become the popular tools. However most of them are designed by the shallow neural networks. Bengio said that deep neural networks can learn better fits with less data than shallow neural networks. In our case, some of the alleles only have dozens of peptide data. In addition, we transform each peptide into a characteristic matrix and input it into the model. As we know when dealing with the problem that the input is a matrix, convolutional neural network (CNN) can find the most critical features by itself. Obviously, compared with the traditional neural network model, CNN is more suitable for predicting binding affinity. Different from the previous studies which are based on blocks substitution matrix (BLOSUM), we used novel feature to do the prediction. Since we consider that the order of the sequence, hydropathy index, polarity and the length of the peptide could affect the binding affinity and the properties of these amino acids are key factors for their binding to MHC, we extracted these information from each peptide. In order to make full use of the data we have obtained, we have integrated different lengths of peptides into 15mer based on the binding mode of peptide to MHC I. In order to demonstrate that our method is reliable to predict peptide-MHC binding, we compared our method with several popular methods. The experiments show the superiority of our method.

Application of mass spectrometry-based MHC immunopeptidome profiling in neoantigen identification for tumor immunotherapy

One of the challenges for cancer vaccine and adoptive T-cell-based immunotherapy is to identify the major histocompatibility complex (MHC)-associated non-self neoantigens recognized by T cells. T cell epitope in silico prediction algorithms have been widely used for neoantigen prediction; nonetheless, this platform lacks the experimental evidence of directly identification of the presented epitopes on cell surface. Currently, mass spectrometry (MS)-based proteomics is an advanced analytical technology for large-scale peptide sequencing, which has become a powerful tool for directly profiling the immunopeptidome presented by MHC molecules. Integrating with next-generation sequencing, proteogenomic analysis provides the "gold standard" for neoantigen identification at protein level. This method discovers the tumor-specific neoantigens derived from somatic mutations, proteasome splicing, noncoding RNA, and post-translational modified antigens. Herein, we review basis of antigen processing and presentation, tumor antigen classification, existing approaches for neoantigen discovery, quantitative proteomics, epitope prediction programs, and advantages and drawbacks of proteomics workflow for MHC immunopeptidome profiling. Furthermore, we summarize 40 recently published reports addressing the fundamental theory, breakthrough and most advanced updates for the mass spectrometry-based neoantigen discovery for cancer immunotherapy.

Quantification of epitope abundance reveals the effect of direct and cross-presentation on influenza CTL responses

The magnitude of T cell responses to infection is a function of the naïve T cell repertoire combined with the context and duration of antigen presentation. Using mass spectrometry, we identify and quantify 21 class 1 MHC-restricted influenza A virus (IAV)-peptides following either direct or cross-presentation. All these peptides, including seven novel epitopes, elicit T cell responses in infected C57BL/6 mice. Directly presented IAV epitopes maintain their relative abundance across distinct cell types and reveal a broad range of epitope abundances. In contrast, cross-presented epitopes are more uniform in abundance. We observe a clear disparity in the abundance of the two key immunodominant IAV antigens, wherein direct infection drives optimal nucleoprotein (NP)_366–374 presentation, while cross-presentation is optimal for acid polymerase (PA)_224–233 presentation. The study demonstrates how assessment of epitope abundance in both modes of antigen presentation is necessary to fully understand the immunogenicity and response magnitude to T cell epitopes.

CTL responses are critical in protection against pathogens. Here, using mass spectrometry and flow cytometry, the authors characterize the kinetics of influenza A virus class I MHC epitopes cross-presented in professional antigen presenting cells and identify new epitopes that elicit T cell responses in infected mice.

Intracellular Peptides in Cell Biology and Pharmacology

Intracellular peptides are produced by proteasomes following degradation of nuclear, cytosolic, and mitochondrial proteins, and can be further processed by additional peptidases generating a larger pool of peptides within cells. Thousands of intracellular peptides have been sequenced in plants, yeast, zebrafish, rodents, and in human cells and tissues. Relative levels of intracellular peptides undergo changes in human diseases and also when cells are stimulated, corroborating their biological function. However, only a few intracellular peptides have been pharmacologically characterized and their biological significance and mechanism of action remains elusive. Here, some historical and general aspects on intracellular peptides' biology and pharmacology are presented. Hemopressin and Pep19 are examples of intracellular peptides pharmacologically characterized as inverse agonists to cannabinoid type 1 G-protein coupled receptors (CB1R), and hemopressin fragment NFKF is shown herein to attenuate the symptoms of pilocarpine-induced epileptic seizures. Intracellular peptides EL28 (derived from proteasome 26S protease regulatory subunit 4; Rpt2), PepH (derived from Histone H2B type 1-H), and Pep5 (derived from G1/S-specific cyclin D2) are examples of peptides that function intracellularly. Intracellular peptides are suggested as biological functional molecules, and are also promising prototypes for new drug development.

HLA-F*01:01 presents peptides with N-terminal flexibility and a preferred length of 16 residues

HLA-F belongs to the non-classical HLA-Ib molecules with a marginal polymorphic nature and tissue-restricted distribution. HLA-F is a ligand of the NK cell receptor KIR3DS1, whose activation initiates an antiviral downstream immune response and lead to delayed disease progression of HIV-1. During the time course of HIV infection, the expression of HLA-F is upregulated while its interaction with KIR3DS1 is diminished. Understanding HLA-F peptide selection and presentation is essential to a comprehensive understanding of this dynamic immune response and the molecules function. In this study, we were able to recover stable pHLA-F*01:01 complexes and analyze the characteristics of peptides naturally presented by HLA-F. These HLA-F-restricted peptides exhibit a non-canonical length without a defined N-terminal anchor. The peptide characteristics lead to a unique presentation profile and influence the stability of the protein. Furthermore, we demonstrate that almost all source proteins of HLA-F-restricted peptides are described to interact with HIV proteins. Understanding the balance switch between HLA-Ia and HLA-F expression and peptide selection will support to understand the role of HLA-F in viral pathogenesis.

Broad CD8+ T cell cross-recognition of distinct influenza A strains in humans

Newly-emerged and vaccine-mismatched influenza A viruses (IAVs) result in a rapid global spread of the virus due to minimal antibody-mediated immunity. In that case, established CD8⁺ T-cells can reduce disease severity. However, as mutations occur sporadically within immunogenic IAV-derived T-cell peptides, understanding of T-cell receptor (TCRαβ) cross-reactivity towards IAV variants is needed for a vaccine design. Here, we investigate TCRαβ cross-strain recognition across IAV variants within two immunodominant human IAV-specific CD8⁺ T-cell epitopes, HLA-B*37:01-restricted NP_338-346 (B37-NP₃₃₈) and HLA-A*01:01-restricted NP_44-52 (A1-NP₄₄). We find high abundance of cross-reactive TCRαβ clonotypes recognizing distinct IAV variants. Structures of the wild-type and variant peptides revealed preserved conformation of the bound peptides. Structures of a cross-reactive TCR-HLA-B37-NP₃₃₈ complex suggest that the conserved conformation of the variants underpins TCR cross-reactivity. Overall, cross-reactive CD8⁺ T-cell responses, underpinned by conserved epitope structure, facilitates recognition of distinct IAV variants, thus CD8⁺ T-cell-targeted vaccines could provide protection across different IAV strains.

Mutations within immunological epitope containing regions of influenza A virus can impair the established immune response between influenza strains and could impact rational vaccine design. Here Grant et al. examine the presence, structural impact and cross reactivity of two human immunodominant influenza epitope variants.

Development of a novel clustering tool for linear peptide sequences

Epitopes identified in large-scale screens of overlapping peptides often share significant levels of sequence identity, complicating the analysis of epitope-related data. Clustering algorithms are often used to facilitate these analyses, but available methods are generally insufficient in their capacity to define biologically meaningful epitope clusters in the context of the immune response. To fulfil this need we developed an algorithm that generates epitope clusters based on representative or consensus sequences. This tool allows the user to cluster peptide sequences on the basis of a specified level of identity by selecting among three different method options. These include the 'clique method', in which all members of the cluster must share the same minimal level of identity with each other, and the 'connected graph method', in which all members of a cluster must share a defined level of identity with at least one other member of the cluster. In cases where it is not possible to define a clear consensus sequence with the connected graph method, a third option provides a novel 'cluster-breaking algorithm' for consensus sequence driven sub-clustering. Herein we demonstrate the tool's clustering performance and applicability using (i) a selection of dengue virus epitopes for the 'clique method', (ii) sets of allergen-derived peptides from related species for the 'connected graph method' and (iii) large data sets of eluted ligand, major histocompatibility complex binding and T-cell recognition data captured within the Immune Epitope Database (IEDB) with the newly developed 'cluster-breaking algorithm'. This novel clustering tool is accessible at http://tools.iedb.org/cluster2/.

Divergent T-cell receptor recognition modes of a HLA-I restricted extended tumour-associated peptide

Human leukocyte antigen (HLA)-I molecules generally bind short peptides (8–10 amino acids), although extended HLA-I restricted peptides (>10 amino acids) can be presented to T cells. However, the function of such extended HLA-I epitopes in tumour immunity, and how they would be recognised by T-cell receptors (TCR) remains unclear. Here we show that the structures of two distinct TCRs (TRAV4⁺TRAJ21⁺-TRBV28⁺TRBJ2-3⁺ and TRAV4⁺TRAJ8⁺-TRBV9⁺TRBJ2-1⁺), originating from a polyclonal T-cell repertoire, bind to HLA-B*07:02, presenting a 13-amino-acid-long tumour-associated peptide, NY-ESO-1_60–72. Comparison of the structures reveals that the two TCRs differentially binds NY-ESO-1_60–72–HLA-B*07:02 complex, and induces differing extent of conformational change of the NY-ESO-1_60–72 epitope. Accordingly, polyclonal TCR usage towards an extended HLA-I restricted tumour epitope translates to differing TCR recognition modes, whereby extensive flexibility at the TCR–pHLA-I interface engenders recognition.

Human leukocyte antigen (HLA) presents peptides to activate T cells, but many aspects in the T cell receptor (TCR)/HLA interaction remain unclear. Here the authors show, via structural data, that two TCRs differentially recognize the same tumour peptide/HLA complex and induce contrasting conformation changes of the peptide.

Gemcitabine alters the proteasome composition and immunopeptidome of tumour cells

The antigenic makeup of tumour cells can have a profound effect on the progression of cancer and success of immunotherapies. Therefore, one strategy to improve the efficacy of cancer treatments is to augment the antigens displayed by tumours. The present study explores how the recognition of tumour cells may be altered by non-cytotoxic concentrations of gemcitabine (GEM). Testing a panel of chemotherapeutics in human cancer cell lines in vitro, it was found that GEM increased surface expression of HLA-A,B,C and that underlying this were specific increases in β-2-microglobulin and immunoproteasome subunit proteins. Furthermore, the peptide antigen repertoire displayed on HLA class I was altered, revealing a number of novel antigens, many of which that were derived from proteins involved in the DNA-damage response. Changes in the nature of the peptide antigens eluted from HLA-A,B,C after GEM treatment consisted of amino acid anchor-residue modifications and changes in peptide length which rendered peptides likely to favour alternative HLA-alleles and increased their predicted immunogenicity. Signalling through the MAPK/ERK and NFκB/RelB pathways was associated with these changes. These data may explain observations made in previous in vivo studies, advise as to which antigens should be used in future vaccination protocols and reinforce the idea that chemotherapy and immunotherapy could be used in combination.

Association of the HLA-B alleles with carbamazepine-induced Stevens-Johnson syndrome/toxic epidermal necrolysis in the Javanese and Sundanese population of Indonesia: the important role of the HLA-B75 serotype

Carbamazepine (CBZ) is a common cause of life-threatening cutaneous adverse drug reactions such as Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Previous studies have reported a strong association between the HLA genotype and CBZ-induced SJS/TEN. We investigated the association between the HLA genotype and CBZ-induced SJS/TEN in Javanese and Sundanese patients in Indonesia. Nine unrelated patients with CBZ-induced SJS/TEN and 236 healthy Javanese and Sundanese controls were genotyped for HLA-B and their allele frequencies were compared. The HLA-B*15:02 allele was found in 66.7% of the patients with CBZ-induced SJS/TEN, but only in 29.4% of tolerant control (p = 0.029; odds ratio [OR]: 6.5; 95% CI: 1.2-33.57) and 22.9% of healthy controls (p = 0.0021; OR: 6.78; 95% CI: 1.96-23.38). These findings support the involvement of HLA-B*15:02 in CBZ-induced SJS/TEN reported in other Asian populations. Interestingly, we also observed the presence of the HLA-B*15:21 allele. HLA-B*15:02 and HLA-B*15:21 are members of the HLA-B75 serotype, for which a greater frequency was observed in CBZ-induced SJS/TEN (vs tolerant control [p = 0.0078; OR: 12; 95% CI: 1.90-75.72] and vs normal control [p = 0.0018; OR: 8.56; 95% CI: 1.83-40]). Our findings suggest that screening for the HLA-B75 serotype can predict the risk of CBZ-induced SJS/TEN more accurately than screening for a specific allele.

Molecular challenges imposed by MHC-I restricted long epitopes on T cell immunity

It has widely been accepted that major histocompatibility complex class I molecules (MHC-I) are limited to binding small peptides of 8-10 residues in length. However, this consensus has recently been challenged with the identification of longer peptides (≥11 residues) that can also elicit cytotoxic CD8+ T cell responses. Indeed, a growing number of studies demonstrate that these non-canonical epitopes are important targets for the immune system. As long epitopes represent up to 10% of the peptide repertoire bound to MHC-I molecules, here we review their impact on antigen presentation by MHC-I, TCR recognition, and T cell immunity.

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field.

Human Leukocyte Antigen (HLA) Peptides Derived from Tumor Antigens Induced by Inhibition of DNA Methylation for Development of Drug-facilitated Immunotherapy

Treatment of cancer cells with anticancer drugs often fails to achieve complete remission. Yet, such drug treatments may induce alteration in the tumor's gene expression patterns, including those of Cancer/Testis Antigens (CTA). The degradation products of such antigens can be presented as HLA peptides on the surface of the tumor cells and be developed into anticancer immunotherapeutics. For example, the DNA methyl transferase inhibitor, 5-aza-2'-deoxycytidine (Decitabine) has limited antitumor efficacy, yet it induces the expression of many genes, including CTAs that are normally silenced in the healthy adult tissues. In this study, the presentation of many new HLA peptides derived from CTAs and induced by Decitabine was demonstrated in three human Glioblastoma cell lines. Such presentation of CTA-derived HLA peptides can be exploited for development of new treatment modalities, combining drug treatment with anti-CTA targeted immunotherapy. The Decitabine-induced HLA peptidomes include many CTAs that are not normally detected in healthy tissues or in cancer cells, unless treated with the drug. In addition, the study included large-scale analyses of the simultaneous effects of Decitabine on the transcriptomes, proteomes and HLA peptidomes of the human Glioblastoma cells. It demonstrates the poor correlations between these three levels of gene expression, both in their total levels and in their response to the drug. The proteomics and HLA peptidomics data are available via ProteomeXchange with identifier PXD003790 and the transcriptomics data are available via GEO with identifier GSE80137.

Deciphering the clinical relevance of allo-human leukocyte antigen cross-reactivity in mediating alloimmunity following transplantation

PURPOSE OF REVIEW

Despite a growing awareness regarding the potential of cross-reactive virus-specific memory T cells to mediate alloimmunity, there has been limited clinical evaluation on allograft immunopathology. This review will explore published models of human T-cell cross-reactivity and discuss criteria required to drive this mechanism as a contributing cause of allograft dysfunction in transplantation.

RECENT FINDINGS

Published models of human allogeneic (allo)-human leukocyte antigen (HLA) cross-reactivity have enabled dissection of the cross-reactive T cell receptor/peptide/major histocompatibility complex (TCR/peptide/MHC) interaction. In many of the models, the cross-reactive T cells express a unique TCR, although the relevance of a public cross-reactive TCR repertoire has yet to be determined. Equally, allopeptide identity, a vital component driving cross-recognition, remains unknown in the majority of models thereby prompting further characterization utilizing novel technologies. Although clinical studies examining the presence and impact of specific cross-reactive virus-specific T cells have been minimally explored, the existing data suggest that there may be a marginal set of requirements that need to be satisfied before the potentially damaging effects of allo-HLA cross-reactivity can be realized.

SUMMARY

Our understanding of allo-HLA cross-reactivity continues to evolve as improved technology and novel strategies allow us to better question the contribution of allo-HLA cross-reactivity in clinically relevant allograft dysfunction.

NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets

Background

Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells.

Results

Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining information across both multiple MHC molecules and peptide lengths. This pan-allele/pan-length algorithm significantly outperforms state-of-the-art methods, and captures differences in the length profile of binders to different MHC molecules leading to increased accuracy for ligand identification. Using this model, we demonstrate that percentile ranks in contrast to affinity-based thresholds are optimal for ligand identification due to uniform sampling of the MHC space.

Conclusions

We have developed a neural network-based machine-learning algorithm leveraging information across multiple receptor specificities and ligand length scales, and demonstrated how this approach significantly improves the accuracy for prediction of peptide binding and identification of MHC ligands. The method is available at www.cbs.dtu.dk/services/NetMHCpan-3.0.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0288-x) contains supplementary material, which is available to authorized users.

Unmasking targets of antitumor immunity via high-throughput antigen profiling

More than three decades of evidence has established that antitumor immune responses, initially shown with IL-2 treatment, can result in complete, durable eradication of malignant disease in metastatic patients. Recent studies have demonstrated that immune checkpoint blockade as well as cellular therapies, including dendritic cell activation of T cells and adoptive T cell transfer, can induce long-lasting responses. To elicit cytolysis of tumor cells, effector T cells rely on tumor expression of target antigens. However, the antigens targeted during antitumor responses are largely unknown. Technological advancements and availability of sequencing data have paved the way for more efficient screening and validation of tumor-associated antigens and neoantigens derived from non-synonymous mutations targeted by T cells under baseline conditions and in the context of immunotherapy.

Evolution and comparative analysis of the bat MHC-I region

Bats are natural hosts to numerous viruses and have ancient origins, having diverged from other eutherian mammals early in evolution. These characteristics place them in an important position to provide insights into the evolution of the mammalian immune system and antiviral immunity. We describe the first detailed partial map of a bat (Pteropus alecto) MHC-I region with comparative analysis of the MHC-I region and genes. The bat MHC-I region is highly condensed, yet relatively conserved in organisation, and is unusual in that MHC-I genes are present within only one of the three highly conserved class I duplication blocks. We hypothesise that MHC-I genes first originated in the β duplication block, and subsequently duplicated in a step-wise manner across the MHC-I region during mammalian evolution. Furthermore, bat MHC-I genes contain unique insertions within their peptide-binding grooves potentially affecting the peptide repertoire presented to T cells, which may have implications for the ability of bats to control infection without overt disease.

The Length Distribution of Class I-Restricted T Cell Epitopes Is Determined by Both Peptide Supply and MHC Allele-Specific Binding Preference

HLA class I-binding predictions are widely used to identify candidate peptide targets of human CD8(+) T cell responses. Many such approaches focus exclusively on a limited range of peptide lengths, typically 9 aa and sometimes 9-10 aa, despite multiple examples of dominant epitopes of other lengths. In this study, we examined whether epitope predictions can be improved by incorporating the natural length distribution of HLA class I ligands. We found that, although different HLA alleles have diverse length-binding preferences, the length profiles of ligands that are naturally presented by these alleles are much more homogeneous. We hypothesized that this is due to a defined length profile of peptides available for HLA binding in the endoplasmic reticulum. Based on this, we created a model of HLA allele-specific ligand length profiles and demonstrate how this model, in combination with HLA-binding predictions, greatly improves comprehensive identification of CD8(+) T cell epitopes.

Gapped sequence alignment using artificial neural networks: application to the MHC class I system

MOTIVATION

Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to peptides of length 8-11 amino acids. On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment.

RESULTS

We show that prediction methods based on alignments that include insertions and deletions have significantly higher performance than methods trained on peptides of single lengths. Also, we illustrate how the location of deletions can aid the interpretation of the modes of binding of the peptide-MHC, as in the case of long peptides bulging out of the MHC groove or protruding at either terminus. Finally, we demonstrate that the method can learn the length profile of different MHC molecules, and quantified the reduction of the experimental effort required to identify potential epitopes using our prediction algorithm.

AVAILABILITY AND IMPLEMENTATION

The NetMHC-4.0 method for the prediction of peptide-MHC class I binding affinity using gapped sequence alignment is publicly available at: http://www.cbs.dtu.dk/services/NetMHC-4.0.

T Cell Cross-Reactivity between a Highly Immunogenic EBV Epitope and a Self-Peptide Naturally Presented by HLA-B*18:01+ Cells

T cell cross-reactivity underpins the molecular mimicry hypothesis in which microbial peptides sharing structural features with host peptides stimulate T cells that cross-react with self-peptides, thereby initiating and/or perpetuating autoimmune disease. EBV represents a potentially important factor in the pathogenesis of several T cell-mediated autoimmune disorders, with molecular mimicry a likely mechanism. In this study, we describe a human self-peptide (DELEIKAY) that is a homolog of a highly immunogenic EBV T cell epitope (SELEIKRY) presented by HLA-B*18:01. This self-peptide was shown to bind stably to HLA-B*18:01, and peptide elution/mass spectrometric studies showed it is naturally presented by this HLA molecule on the surface of human cells. A significant proportion of CD8(+) T cells raised from some healthy individuals against this EBV epitope cross-reacted with the self-peptide. A diverse array of TCRs was expressed by the cross-reactive T cells, with variable functional avidity for the self-peptide, including some T cells that appeared to avoid autoreactivity by a narrow margin, with only 10-fold more of the self-peptide required for equivalent activation as compared with the EBV peptide. Structural studies revealed that the self-peptide-HLA-B*18:01 complex is a structural mimic of the EBV peptide-HLA-B*18:01 complex, and that the strong antiviral T cell response is primarily dependent on the alanine/arginine mismatch at position 7. To our knowledge, this is the first report confirming the natural presentation of a self-peptide cross-recognized in the context of self-HLA by EBV-reactive CD8(+) T cells. These results illustrate how aberrant immune responses and immunopathological diseases could be generated by EBV infection.

Naturally processed non-canonical HLA-A*02:01 presented peptides

Human leukocyte antigen (HLA) class I molecules generally present peptides (p) of 8 to 11 amino acids (aa) in length. Although an increasing number of examples with lengthy (>11 aa) peptides, presented mostly by HLA-B alleles, have been reported. Here we characterize HLA-A*02:01 restricted, in addition to the HLA-B*0702 and HLA-B*4402 restricted, lengthy peptides (>11 aa) arising from the B-cell ligandome. We analyzed a number of 15-mer peptides presented by HLA-A*02:01, and confirmed pHLA-I formation by HLA folding and thermal stability assays. Surprisingly the binding affinity and stability of the 15-mer epitopes in complex with HLA-A*02:01 were comparable with the values observed for canonical length (8 to 11 aa) HLA-A*02:01-restricted peptides. We solved the structures of two 15-mer epitopes in complex with HLA-A*02:01, within which the peptides adopted distinct super-bulged conformations. Moreover, we demonstrate that T-cells can recognize the 15-mer peptides in the context of HLA-A*02:01, indicating that these 15-mer peptides represent immunogenic ligands. Collectively, our data expand our understanding of longer epitopes in the context of HLA-I, highlighting that they are not limited to the HLA-B family, but can bind the ubiquitous HLA-A*02:01 molecule, and play an important role in T-cell immunity.

T cell epitope clustering in the highly immunogenic BZLF1 antigen of Epstein-Barr virus

Polymorphism in the human leukocyte antigen (HLA) loci ensures that the CD8(+) T cell response to viruses is directed against a diverse range of antigenic epitopes, thereby minimizing the impact of virus escape mutation across the population. The BZLF1 antigen of Epstein-Barr virus is an immunodominant target for CD8(+) T cells, but the response has been characterized only in the context of a limited number of HLA molecules due to incomplete epitope mapping. We have now greatly expanded the number of defined CD8(+) T cell epitopes from BZLF1, allowing the response to be evaluated in a much larger proportion of the population. Some regions of the antigen fail to be recognized by CD8(+) T cells, while others include clusters of overlapping epitopes presented by different HLA molecules. These highly immunogenic regions of BZLF1 include polymorphic sequences, such that up to four overlapping epitopes are impacted by a single amino acid variation common in different regions of the world. This focusing of the immune response to limited regions of the viral protein could be due to sequence similarity to human proteins creating "immune blind spots" through self-tolerance. This study significantly enhances the understanding of the immune response to BZLF1, and the precisely mapped T cell epitopes may be directly exploited in vaccine development and adoptive immunotherapy.

IMPORTANCE

Epstein-Barr virus (EBV) is an important human pathogen, associated with several malignancies, including nasopharyngeal carcinoma and Hodgkin lymphoma. T lymphocytes are critical for virus control, and clinical trials aimed at manipulating this arm of the immune system have demonstrated efficacy in treating these EBV-associated diseases. These trials have utilized information on the precise location of viral epitopes for T cell recognition, for either measuring or enhancing responses. In this study, we have characterized the T cell response to the highly immunogenic BZLF1 antigen of EBV by greatly expanding the number of defined T cell epitopes. An unusual clustering of epitopes was identified, highlighting a small region of BZLF1 that is targeted by the immune response of a high proportion of the world's population. This focusing of the immune response could be utilized in developing vaccines/therapies with wide coverage, or it could potentially be exploited by the virus to escape the immune response.

Soluble HLA technology as a strategy to evaluate the impact of HLA mismatches

HLA class I incompatibilities still remain one of the main barriers for unrelated bone marrow transplantation (BMT); hence the molecular understanding of how to mismatch patients and donors and still have successful clinical outcomes will guide towards the future of unrelated BMT. One way to estimate the magnitude of polymorphisms within the PBR is to determine which peptides can be selected by individual HLA alleles and subsequently presented for recognition by T cells. The features (structure, length, and sequence) of different peptides each confer an individual pHLA landscape and thus directly shape the individual immune response. The elution and sequencing of peptides by mass spectrometric analysis enable determining the bona fide repertoire of presented peptides for a given allele. This is an effective and simple way to compare the functions of allelic variants and make a first assessment of their degree of permissivity. We describe the methodology used for peptide sequencing and the limitations of peptide prediction tools compared to experimental methods. We highlight the altered peptide features that are observed between allelic variants and the need to discover the altered peptide repertoire in situations of "artificial" graft versus host disease (GvHD) that occur in HLA-specific hypersensitive immune responses to drugs.

Cross-reactivity analysis of T cell receptors specific for overlapping HIV-1 Nef epitopes of different lengths

Overlapping peptides of different lengths from a certain immunodominant region can be presented by the same HLA class I molecule and elicit different T cell responses. However, how peptide-length specificity of antigen-specific CD8(+) T lymphocytes influence cross-reactivity profiles of these cells remains elusive. This question is particularly important in the face of highly variable pathogens such as HIV-1. Here, we examined this problem by using HLA-B*35:01-restricted CD8(+) T lymphocytes specific for Nef epitopes, i.e., RY11 (RPQVPLRPMTY), VY8 (VPLRPMTY), and RM9 (RPQVPLRPM), in which VY8 and RM9 were contained entirely within RY11, in combination with a T cell receptor (TCR) reconstruction system as well as HLA-B35 tetramers and a set of a single-variant peptide library. The TCR reactivity toward the peptide-length variants was classified into three types: mutually exclusive specificity toward (1) RY11 or (2) VY8 and (3) cross-recognition toward RM9 and RY11. TCR cross-reactivity toward variant peptides was similar within the same peptide-length reactivity type but was markedly different between the types. Thus, TCRs showing similar peptide-length reactivity have shared peptide recognition footprints and thereby similar weakness to antigenic variations, providing us with further insight into the antiviral vaccine design.

CD8+ T cell responses to lytic EBV infection: late antigen specificities as subdominant components of the total response

EBV elicits primary CD8(+) T cell responses that, by T cell cloning from infectious mononucleosis (IM) patients, appear skewed toward immediate early (IE) and some early (E) lytic cycle proteins, with late (L) proteins rarely targeted. However, L Ag-specific responses have been detected regularly in polyclonal T cell cultures from long-term virus carriers. To resolve this apparent difference between responses to primary and persistent infection, 13 long-term carriers were screened in ex vivo IFN-γ ELISPOT assays using peptides spanning the two IE, six representative E, and seven representative L proteins. This revealed memory CD8 responses to 44 new lytic cycle epitopes that straddle all three protein classes but, in terms of both frequency and size, maintain the IE > E > L hierarchy of immunodominance. Having identified the HLA restriction of 10 (including 7 L) new epitopes using memory CD8(+) T cell clones, we looked in HLA-matched IM patients and found such reactivities but typically at low levels, explaining why they had gone undetected in the original IM clonal screens. Wherever tested, all CD8(+) T cell clones against these novel lytic cycle epitopes recognized lytically infected cells naturally expressing their target Ag. Surprisingly, however, clones against the most frequently recognized L Ag, the BNRF1 tegument protein, also recognized latently infected, growth-transformed cells. We infer that BNRF1 is also a latent Ag that could be targeted in T cell therapy of EBV-driven B-lymphoproliferative disease.