The pockets guide to HLA class I molecules

Characteristics of Norovirus capsid protein-specific CD8+ T-Cell responses in previously infected individuals

Norovirus (NV) infection causes acute gastroenteritis in children and adults. Upon infection with NV, specific CD8+ T cells, which play an important role in anti-infective immunity, are activated in the host. Owing to the NV's wide genotypic variability, it is challenging to develop vaccines with cross-protective abilities against infection. To aid effective vaccine development, we examined specific CD8+ T-cell responses towards viral-structural protein (VP) epitopes, which enable binding to host susceptibility receptors. We isolated peripheral blood mononuclear cells from 196 participants to screen and identify predominant core peptides towards NV main and small envelope proteins using ex vivo and in vitro intracellular cytokine staining assays. Human leukocyte antigen (HLA) restriction characteristics were detected using next-generation sequencing. Three conservative immunodominant VP-derived CD8+ T-cell epitopes, VP294-102 (TDAARGAIN), VP2153-161 (RGPSNKSSN), and VP1141-148 (FPHIIVDV), were identified and restrictively presented by HLA-Cw * 0102, HLA-Cw * 0702, and HLA-A *1101 alleles, separately. Our findings provide useful insights into the development of future vaccines and treatments for NV infection.

Interplay between vertebrate adaptive immunity and bacterial infectivity genes: Bank vole MHC versus Borrelia afzelii OspC

Coevolution of parasites with their hosts may lead to balancing selection on genes involved in determining the specificity of host-parasite interactions, but examples of such specific interactions in wild vertebrates are scarce. Here, we investigated whether the polymorphic outer surface protein C (OspC), used by the Lyme disease agent, Borrelia afzelii, to manipulate vertebrate host innate immunity, interacts with polymorphic major histocompatibility genes (MHC), while concurrently eliciting a strong antibody response, in one of its main hosts in Europe, the bank vole. We found signals of balancing selection acting on OspC, resulting in little differentiation in OspC variant frequencies between years. Neither MHC alleles nor their inferred functional groupings (supertypes) significantly predicted the specificity of infection with strains carrying different OspC variants. However, we found that MHC alleles, but not supertypes, significantly predicted the level of IgG antibodies against two common OspC variants among seropositive individuals. Our results thus indicate that MHC alleles differ in their ability to induce antibody responses against specific OspC variants, which may contribute to selection of OspC polymorphism by the vole immune system.

CryoEM structure of an MHC-I/TAPBPR peptide bound intermediate reveals the mechanism of antigen proofreading

Class I major histocompatibility complex (MHC-I) proteins play a pivotal role in adaptive immunity by displaying epitopic peptides to CD8+ T cells. The chaperones tapasin and TAPBPR promote the selection of immunogenic antigens from a large pool of intracellular peptides. Interactions of chaperoned MHC-I molecules with incoming peptides are transient in nature, and as a result, the precise antigen proofreading mechanism remains elusive. Here, we leverage a high-fidelity TAPBPR variant and conformationally stabilized MHC-I, to determine the solution structure of the human antigen editing complex bound to a peptide decoy by cryogenic electron microscopy (cryo-EM) at an average resolution of 3.0 Å. Antigen proofreading is mediated by transient interactions formed between the nascent peptide binding groove with the P2/P3 peptide anchors, where conserved MHC-I residues stabilize incoming peptides through backbone-focused contacts. Finally, using our high-fidelity chaperone, we demonstrate robust peptide exchange on the cell surface across multiple clinically relevant human MHC-I allomorphs. Our work has important ramifications for understanding the selection of immunogenic epitopes for T cell screening and vaccine design applications.

A structure-guided approach to predict MHC-I restriction of T cell receptors for public antigens

Peptides presented by class I major histocompatibility complex (MHC-I) proteins provide biomarkers for therapeutic targeting using T cell receptors (TCRs), TCR-mimicking antibodies (TMAs), or other engineered protein binders. Despite the extreme sequence diversity of the Human Leucocyte Antigen (HLA, the human MHC), a given TCR or TMA is restricted to recognize epitopic peptides in the context of a limited set of different HLA allotypes. Here, guided by our analysis of 96 TCR:pHLA complex structures in the Protein Data Bank (PDB), we identify TCR contact residues and classify 148 common HLA allotypes into T-cell cross-reactivity groups (T-CREGs) on the basis of their interaction surface features. Insights from our work have actionable value for resolving MHC-I restriction of TCRs, guiding therapeutic expansion of existing therapies, and informing the selection of peptide targets for forthcoming immunotherapy modalities.

A journey to your self: The vague definition of immune self and its practical implications

The identification of immunogenic peptides has become essential in an increasing number of fields in immunology, ranging from tumor immunotherapy to vaccine development. The nature of the adaptive immune response is shaped by the similarity between foreign and self-protein sequences, a concept extensively applied in numerous studies. Can we precisely define the degree of similarity to self? Furthermore, do we accurately define immune self? In the current work, we aim to unravel the conceptual and mechanistic vagueness hindering the assessment of self-similarity. Accordingly, we demonstrate the remarkably low consistency among commonly employed measures and highlight potential avenues for future research.

Identification of an HLA-A*11:01-restricted neoepitope of mutant PIK3CA and its specific T cell receptors for cancer immunotherapy targeting hotspot driver mutations

Hotspot driver mutations presented by human leukocyte antigens might be recognized by anti-tumor T cells. Based on their advantages of tumor-specificity and immunogenicity, neoantigens derived from hotspot mutations, such as PIK3CAH1047L, may serve as emerging targets for cancer immunotherapies. NetMHCpan V4.1 was utilized for predicting neoepitopes of PIK3CA hotspot mutation. Using in vitro stimulation, antigen-specific T cells targeting the HLA-A*11:01-restricted PIK3CA mutation were isolated from healthy donor-derived peripheral blood mononuclear cells. T cell receptors (TCRs) were cloned using single-cell PCR and sequencing. Their functionality was assessed through T cell activation markers, cytokine production and cytotoxic response to cancer cell lines pulsed with peptides or transduced genes of mutant PIK3CA. Immunogenic mutant antigens from PIK3CA and their corresponding CD8+ T cells were identified. These PIK3CA mutation-specific CD8+ T cells were subsequently enriched, and their TCRs were isolated. The TCR clones exhibited mutation-specific and HLA-restricted reactivity, demonstrating varying degrees of functional avidity. Identified TCR genes were transferred into CD8+ Jurkat cells and primary T cells deficient of endogenous TCRs. TCR-expressing cells demonstrated specific recognition and reactivity against the PIK3CAH1047L peptide presented by HLA-A*11:01-expressing K562 cells. Furthermore, mutation-specific TCR-T cells demonstrated an elevation in cytokine production and profound cytotoxic effects against HLA-A*11:01+ malignant cell lines harboring PIK3CAH1047L. Our data demonstrate the immunogenicity of an HLA-A*11:01-restricted PIK3CA hotspot mutation and its targeting therapeutic potential, together with promising candidates of TCR-T cell therapy.

Experimental Data on PIRCHE and T-Cell Reactivity: HLA-DPB1-Derived Peptides Identified by PIRCHE-I Show Binding to HLA-A*02:01 in vitro and T-Cell Activation in vivo

Introduction

Human leukocyte antigen (HLA)-DPB1 mismatches during hematopoietic stem cell transplantation (HSCT) with an unrelated donor result in an increased risk for the development of graft-versus-host disease (GvHD). The number of CD8+ T-cell epitopes available for indirect allorecognition as predicted by the PIRCHE algorithm has been shown to be associated with GvHD development. As a proof of principle, PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro and in vivo.

Methods

PIRCHE-I analysis was performed to identify HLA-DPB1-derived peptides that could theoretically bind to HLA-A*02:01. PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro by investigating binding affinities of HLA-DPB1-derived peptides to the HLA-A*02:01 in a competition-based binding assay. To investigate the capacity of HLA-DPB1-derived peptides to elicit a T-cell response in vivo, mice were immunized with these peptides. T-cell alloreactivity was subsequently evaluated using an interferon-gamma ELISpot assay.

Results

The PIRCHE-I algorithm identified five HLA-DPB1-derived peptides (RMCRHNYEL, YIYNREEFV, YIYNREELV, YIYNREEYA, and YIYNRQEYA) to be presented by HLA-A*02:01. Binding of these peptides to HLA-A*02:01 was confirmed in a competition-based peptide binding assay, all showing an IC50 value of 21 μm or lower. The peptides elicited an interferon-gamma response in vivo.

Conclusion

Our results indicate that the PIRCHE-I algorithm can identify potential immunogenic HLA-DPB1-derived peptides present in recipients of an HLA-DPB1-mismatched donor. These combined in vitro and in vivo observations strengthen the validity of the PIRCHE-I algorithm to identify HLA-DPB1 mismatch-related GvHD development upon HSCT.

Dynamic allostery in the peptide/MHC complex enables TCR neoantigen selectivity

The inherent cross-reactivity of the T cell receptor (TCR) is balanced by high specificity, which often manifests in confounding ways not easily interpretable from static structures. We show here that TCR discrimination between an HLA-A*03:01 (HLA-A3)-restricted public neoantigen derived from mutant PIK3CA and its wild-type (WT) counterpart emerges from motions within the HLA binding groove that vary with the identity of the peptide's first primary anchor. The motions form a dynamic gate that in the complex with the WT peptide impedes a large conformational change required for TCR binding. The more rigid neoantigen is insusceptible to this limiting dynamic, and with the gate open, is able to transit its central tryptophan residue underneath the peptide backbone to the contralateral side of the HLA-A3 peptide binding groove, facilitating TCR binding. Our findings reveal a novel mechanism driving TCR specificity for a cancer neoantigen that is rooted in the dynamic and allosteric nature of peptide/MHC-I complexes, with implications for resolving long-standing and often confounding questions about the determinants of T cell specificity.

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.

Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?

T cells are essential immune cells responsible for identifying and eliminating pathogens. Through interactions between their T-cell antigen receptors (TCRs) and antigens presented by major histocompatibility complex molecules (MHCs) or MHC-like molecules, T cells discriminate foreign and self peptides. Determining the fundamental principles that govern these interactions has important implications in numerous medical contexts. However, reconstructing a map between T cells and their antagonist antigens remains an open challenge for the field of immunology, and success of in silico reconstructions of this relationship has remained incremental. In this Perspective, we discuss the role that new state-of-the-art deep-learning models for predicting protein structure may play in resolving some of the unanswered questions the field faces linking TCR and peptide-MHC properties to T-cell specificity. We provide a comprehensive overview of structural databases and the evolution of predictive models, and highlight the breakthrough AlphaFold provided the field.

HLA peptide-binding pocket diversity modulates immunological complications after cord blood transplant in acute leukaemia

Pocket motifs and their amino acid positions of HLA molecules are known to govern antigen presentation to effector cells. Our objective was to analyse their influence on the risk of graft-versus-host disease (GVHD) and relapse after umbilical cord blood transplant (UCBT). The transplant characteristics of 849 patients with acute leukaemia were obtained from the Eurocord/EBMT database. Higher acute (a) GVHD was associated with homozygosity of UCB HLA-C amino acid positions 77 and 80 (NN/KK) (p = 0.008). Severe aGVHD was associated with HLA-A pocket B YSAVMENVHY motif (p = 0.002) and NN and RR genotypes of the HLA-C amino acid positions 77 and 156 (p = 0.006 and p = 0.002). Such risk was also increased in case of recipient and UCB mismatches in P4 (p < 0.0001) and P9 (p = 0.003) pockets of HLA-DQB1 alleles. For chronic GVHD, the pocket B YYAVMEISNY motif of the HLA-B*15:01 allele and the absence of mismatch between recipient and UCB in the P6 pocket of HLA-DRB1 were associated with a lower risk (p = 0.0007 and p = 0.0004). In relapse, both UCB pocket B YFAVMENVHY belonging to HLA-A*32:01 and recipient pocket B YDSVGENYQY motif of the HLA-C*07:01 allele were associated with higher risk (p = 0.0026 and p = 0.015). We provide clues on HLA-mediated cellular interactions and their role in the development of GVHD and relapse.

The impact of SARS-CoV-2 spike mutation on peptide presentation is HLA allomorph-specific

CD8+ T cells are crucial for viral elimination and recovery from viral infection. Nonetheless, the current understanding of the T cell response to SARS-CoV-2 at the antigen level remains limited. The Spike protein is an external structural protein that is prone to mutations, threatening the efficacy of current vaccines. Therefore, we have characterised the immune response towards the immunogenic Spike-derived peptide (S976-984, VLNDILSRL), restricted to the HLA-A*02:01 molecule, which is mutated in both Alpha (S982A) and Omicron BA.1 (L981F) variants of concern. We determined that the mutation in the Alpha variant (S982A) impacted both the stability and conformation of the peptide, bound to HLA-A*02:01, in comparison to the original S976-984. We identified a longer and overlapping immunogenic peptide (S975-984, SVLNDILSRL) that could be presented by HLA-A*02:01, HLA-A*11:01 and HLA-B*13:01 allomorphs. We showed that S975-specific CD8+ T cells were weakly cross-reactive to the mutant peptides despite their similar conformations when presented by HLA-A*11:01. Altogether, our results show that the impact of SARS-CoV-2 mutations on peptide presentation is HLA allomorph-specific, and that post vaccination there are T cells able to react and cross-react towards the variant of concern peptides.

The electrostatic landscape of MHC-peptide binding revealed using inception networks

Predictive modeling of macromolecular recognition and protein-protein complementarity represents one of the cornerstones of biophysical sciences. However, such models are often hindered by the combinatorial complexity of interactions at the molecular interfaces. Exemplary of this problem is peptide presentation by the highly polymorphic major histocompatibility complex class I (MHC-I) molecule, a principal component of immune recognition. We developed human leukocyte antigen (HLA)-Inception, a deep biophysical convolutional neural network, which integrates molecular electrostatics to capture non-bonded interactions for predicting peptide binding motifs across 5,821 MHC-I alleles. These predictions of generated motifs correlate strongly with experimental peptide binding and presentation data. Beyond molecular interactions, the study demonstrates the application of predicted motifs in analyzing MHC-I allele associations with HIV disease progression and patient response to immune checkpoint inhibitors. A record of this paper's transparent peer review process is included in the supplemental information.

HLA binding-groove motifs are associated with myocarditis induction after Pfizer-BioNTech BNT162b2 vaccination

BACKGROUND AND AIMS

We found a higher incidence of myocarditis in young males who had received at least two Pfizer-BioNTech BNT162b2 vaccinations. The human leukocyte antigens (HLA) are known to play an important role in infectious and autoinflammatory diseases. We hypothesized that certain HLA alleles might be associated with vaccination-induced myocarditis.

METHODS

HLA typing was performed using next-generation sequencing technology with the Illumina Iseq100 platform. HLA class I and II loci were genotyped in 29 patients with post-vaccination myocarditis and compared with HLA data from 300 healthy controls.

RESULTS

We demonstrate that the DRB1*14:01, DRB1*15:03 alleles and the motifs in HLA-A - Leu62 and Gln63, which are part of binding pocket B and HLA-DR Tyr47, His60, Arg70 and Glu74, which are part of binding pockets P4, P7 and P9, were significantly associated with disease susceptibility.

CONCLUSIONS

Our findings suggest that immunogenetic fingerprints in HLA peptide-binding grooves may affect the presentation of peptides derived from the Pfizer-BioNTech BNT162b2 vaccination to T cells and induce an inflammatory process that results in myocarditis.

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor-specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the "dark matter" of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine-learning-supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.

APE-Gen2.0: Expanding Rapid Class I Peptide-Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries

The recognition of peptides bound to class I major histocompatibility complex (MHC-I) receptors by T-cell receptors (TCRs) is a determinant of triggering the adaptive immune response. While the exact molecular features that drive the TCR recognition are still unknown, studies have suggested that the geometry of the joint peptide-MHC (pMHC) structure plays an important role. As such, there is a definite need for methods and tools that accurately predict the structure of the peptide bound to the MHC-I receptor. In the past few years, many pMHC structural modeling tools have emerged that provide high-quality modeled structures in the general case. However, there are numerous instances of non-canonical cases in the immunopeptidome that the majority of pMHC modeling tools do not attend to, most notably, peptides that exhibit non-standard amino acids and post-translational modifications (PTMs) or peptides that assume non-canonical geometries in the MHC binding cleft. Such chemical and structural properties have been shown to be present in neoantigens; therefore, accurate structural modeling of these instances can be vital for cancer immunotherapy. To this end, we have developed APE-Gen2.0, a tool that improves upon its predecessor and other pMHC modeling tools, both in terms of modeling accuracy and the available modeling range of non-canonical peptide cases. Some of the improvements include (i) the ability to model peptides that have different types of PTMs such as phosphorylation, nitration, and citrullination; (ii) a new and improved anchor identification routine in order to identify and model peptides that exhibit a non-canonical anchor conformation; and (iii) a web server that provides a platform for easy and accessible pMHC modeling. We further show that structures predicted by APE-Gen2.0 can be used to assess the effects that PTMs have in binding affinity in a more accurate manner than just using solely the sequence of the peptide. APE-Gen2.0 is freely available at https://apegen.kavrakilab.org.

Gemcitabine Modulates HLA-I Regulation to Improve Tumor Antigen Presentation by Pancreatic Cancer Cells

Pancreatic cancer is a lethal disease, harboring a five-year overall survival rate of only 13%. Current treatment approaches thus require modulation, with attention shifting towards liberating the stalled efficacy of immunotherapies. Select chemotherapy drugs which possess inherent immune-modifying behaviors could revitalize immune activity against pancreatic tumors and potentiate immunotherapeutic success. In this study, we characterized the influence of gemcitabine, a chemotherapy drug approved for the treatment of pancreatic cancer, on tumor antigen presentation by human leukocyte antigen class I (HLA-I). Gemcitabine increased pancreatic cancer cells' HLA-I mRNA transcripts, total protein, surface expression, and surface stability. Temperature-dependent assay results indicated that the increased HLA-I stability may be due to reduced binding of low affinity peptides. Mass spectrometry analysis confirmed changes in the HLA-I-presented peptide pool post-treatment, and computational predictions suggested improved affinity and immunogenicity of peptides displayed solely by gemcitabine-treated cells. Most of the gemcitabine-exclusive peptides were derived from unique source proteins, with a notable overrepresentation of translation-related proteins. Gemcitabine also increased expression of select immunoproteasome subunits, providing a plausible mechanism for its modulation of the HLA-I-bound peptidome. Our work supports continued investigation of immunotherapies, including peptide-based vaccines, to be used with gemcitabine as new combination treatment modalities for pancreatic cancer.

Building trust in deep learning-based immune response predictors with interpretable explanations

The ability to predict whether a peptide will get presented on Major Histocompatibility Complex (MHC) class I molecules has profound implications in designing vaccines. Numerous deep learning-based predictors for peptide presentation on MHC class I molecules exist with high levels of accuracy. However, these MHC class I predictors are treated as black-box functions, providing little insight into their decision making. To build turst in these predictors, it is crucial to understand the rationale behind their decisions with human-interpretable explanations. We present MHCXAI, eXplainable AI (XAI) techniques to help interpret the outputs from MHC class I predictors in terms of input peptide features. In our experiments, we explain the outputs of four state-of-the-art MHC class I predictors over a large dataset of peptides and MHC alleles. Additionally, we evaluate the reliability of the explanations by comparing against ground truth and checking their robustness. MHCXAI seeks to increase understanding of deep learning-based predictors in the immune response domain and build trust with validated explanations.

How to manage drug-virus interplay underlying skin eruptions in children

The majority of viral rashes occurring during an antibiotic therapy are considered as a drug hypersensitivity reaction (DHR). Differentiating a viral rash versus a DHR is difficult or even impossible. In delayed DHRs the interplay between viruses and drugs is summarized according to the recent literature. The question is if the same reaction will again occur in case of drug re-exposure in absence of the concomitant viral infection because of persistent immune reactivity. Epstein Barr Virus (EBV) and Human Herpes virus 6 (HHV-6) models are analyzed in case of maculopapular exanthemas (MPEs) and drug reaction with eosinophilia and systemic symptoms (DRESS) over a course of drug therapy. MPEs are the most common skin manifestation during a viral infection and a concomitant drug therapy. In type IVb reactions to drugs a hapten/pro-hapten mechanism and a pharmacological interaction (p-i mechanism) are described as the 2 major ways to make T cells response functional. Rarely the altered repertoire model is involved. The Human Leukocyte Antigen (HLA) predisposition is an additional essential factor that can facilitate DHR. In MPEs rarely a DHR is confirmed by allergy testing. Severity and duration of MPEs, the presence of eosinophilia and systemic symptoms make more reliable the persistent nature of the reaction. Research on this topic is needed in order to provide the clinicians with instruments to decide when to suspect future reactions upon drug re-exposure even in the absence of a viral infection, because those patients should be investigated by a complete drug allergy work up.

Diverse cytomegalovirus US11 antagonism and MHC-A evasion strategies reveal a tit-for-tat coevolutionary arms race in hominids

Recurrent, ancient arms races between viruses and hosts have shaped both host immunological defense strategies as well as viral countermeasures. One such battle is waged by the glycoprotein US11 encoded by the persisting human cytomegalovirus. US11 mediates degradation of major histocompatibility class I (MHC-I) molecules to prevent CD8+ T-cell activation. Here, we studied the consequences of the arms race between US11 and primate MHC-A proteins, leading us to uncover a tit-for-tat coevolution and its impact on MHC-A diversification. We found that US11 spurred MHC-A adaptation to evade viral antagonism: In an ancestor of great apes, the MHC-A A2 lineage acquired a Pro184Ala mutation, which confers resistance against the ancestral US11 targeting strategy. In response, US11 deployed a unique low-complexity region (LCR), which exploits the MHC-I peptide loading complex to target the MHC-A2 peptide-binding groove. In addition, the global spread of the human HLA-A*02 allelic family prompted US11 to employ a superior LCR strategy with an optimally fitting peptide mimetic that specifically antagonizes HLA-A*02. Thus, despite cytomegaloviruses low pathogenic potential, the increasing commitment of US11 to MHC-A has significantly promoted diversification of MHC-A in hominids.

Molecular insights into the HLA-B35 molecules' classification associated with HIV control

Human leukocyte antigen (HLA) class I molecules have been shown to influence the immune response to HIV infection and acquired immunodeficiency syndrome progression. Polymorphisms within the HLA-B35 molecules divide the family into two groups, namely, Px and PY. The Px group is associated with deleterious effects and accelerated disease progression in HIV+ patients, whereas the PY group is not. The classification is based on the preferential binding of a tyrosine at the C-terminal part of the peptide in the PY group, and a nontyrosine residue in the Px group. However, there is a lack of knowledge on the molecular differences between the two groups. Here, we have investigated three HLA-B35 molecules, namely, HLA-B*35:01 (PY), HLA-B*35:03 (Px) and HLA-B*35:05 (unclassified). We selected an HIV-derived peptide, NY9, and demonstrated that it can trigger a polyfunctional CD8+ T-cell response in HLA-B*35:01+ /HIV+ patients. We determined that in the complex with the NY9 peptide, the PY molecule was more stable than the Px molecule. We solved the crystal structures of the three HLA molecules in complex with the NY9 peptide, and structural similarities with HLA-B*35:01 would classify the HLA-B*35:05 within the PY group. Interestingly, we found that HLA-B*35:05 can also bind a small molecule in its cleft, suggesting that small drugs could bind as well.

Genetic Diversity and Sequence Conservation of Peptide-Binding Regions of MHC Class I Genes in Pig, Cattle, Chimpanzee, and Human

Comparative analyses of MHC gene diversity and evolution across different species could offer valuable insights into the evolution of MHC genes. Intra- and inter-species sequence diversity and conservation of 12 classical major histocompatibility complex (MHC) class I genes from cattle, chimpanzees, pigs, and humans was analyzed using 20 representative allelic groups for each gene. The combined analysis of paralogous loci for each species revealed that intra-locus amino-acid sequence variations in the peptide-binding region (PBR) of MHC I genes did not differ significantly between species, ranging from 8.44% for SLA to 10.75% for BoLA class I genes. In contrast, intraspecies differences in the non-PBRs of these paralogous genes were more pronounced, varying from 4.59% for SLA to 16.89% for HLA. Interestingly, the Shannon diversity index and rate of nonsynonymous substitutions for PBR were significantly higher in SLA and BoLA than those in Patr and HLA. Analysis of peptide-binding pockets across all analyzed MHC class I genes of the four species indicated that pockets A and E showed the lowest and highest diversity, respectively. The estimated divergence times suggest that primate and artiodactyl MHC class I genes diverged 60.41 Mya, and BoLA and SLA genes diverged 35.34 Mya. These results offer new insights into the conservation and diversity of MHC class I genes in various mammalian species.

Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

Conserved biophysical compatibility among the highly variable germline-encoded regions shapes TCR-MHC interactions

T cells are critically important components of the adaptive immune system primarily responsible for identifying and responding to pathogenic challenges. This recognition of pathogens is driven by the interaction between membrane-bound T cell receptors (TCRs) and antigenic peptides presented on major histocompatibility complex (MHC) molecules. The formation of the TCR-peptide-MHC complex (TCR-pMHC) involves interactions among germline-encoded and hypervariable amino acids. Germline-encoded and hypervariable regions can form contacts critical for complex formation, but only interactions between germline-encoded contacts are likely to be shared across many of all the possible productive TCR-pMHC complexes. Despite this, experimental investigation of these interactions have focused on only a small fraction of the possible interaction space. To address this, we analyzed every possible germline-encoded TCR-MHC contact in humans, thereby generating the first comprehensive characterization of these largely antigen-independent interactions. Our computational analysis suggests that germline-encoded TCR-MHC interactions that are conserved at the sequence level are rare due to the high amino acid diversity of the TCR CDR1 and CDR2 loops, and that such conservation is unlikely to dominate the dynamic protein-protein binding interface. Instead, we propose that binding properties such as the docking orientation are defined by regions of biophysical compatibility between these loops and the MHC surface.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.

An integrated approach to the characterization of immune repertoires using AIMS: An Automated Immune Molecule Separator

The adaptive immune system employs an array of receptors designed to respond with high specificity to pathogens or molecular aberrations faced by the host organism. Binding of these receptors to molecular fragments-collectively referred to as antigens-initiates immune responses. These antigenic targets are recognized in their native state on the surfaces of pathogens by antibodies, whereas T cell receptors (TCR) recognize processed antigens as short peptides, presented on major histocompatibility complex (MHC) molecules. Recent research has led to a wealth of immune repertoire data that are key to interrogating the nature of these molecular interactions. However, existing tools for the analysis of these large datasets typically focus on molecular sets of a single type, forcing researchers to separately analyze strongly coupled sequences of interacting molecules. Here, we introduce a software package for the integrated analysis of immune repertoire data, capable of identifying distinct biophysical differences in isolated TCR, MHC, peptide, antibody, and antigen sequence data. This integrated analytical approach allows for direct comparisons across immune repertoire subsets and provides a starting point for the identification of key interaction hotspots in complementary receptor-antigen pairs. The software (AIMS-Automated Immune Molecule Separator) is freely available as an open access package in GUI or command-line form.

A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity

Antigen immunogenicity and the specificity of binding of T-cell receptors to antigens are key properties underlying effective immune responses. Here we propose diffRBM, an approach based on transfer learning and Restricted Boltzmann Machines, to build sequence-based predictive models of these properties. DiffRBM is designed to learn the distinctive patterns in amino-acid composition that, on the one hand, underlie the antigen's probability of triggering a response, and on the other hand the T-cell receptor's ability to bind to a given antigen. We show that the patterns learnt by diffRBM allow us to predict putative contact sites of the antigen-receptor complex. We also discriminate immunogenic and non-immunogenic antigens, antigen-specific and generic receptors, reaching performances that compare favorably to existing sequence-based predictors of antigen immunogenicity and T-cell receptor specificity.

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling

Introduction

Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.

Methods

In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).

Results

We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.

Discussion

This integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction

MOTIVATION

Computationally predicting major histocompatibility complex class I (MHC-I) peptide binding affinity is an important problem in immunological bioinformatics, which is also crucial for the identification of neoantigens for personalized therapeutic cancer vaccines. Recent cutting-edge deep learning-based methods for this problem cannot achieve satisfactory performance, especially for non-9-mer peptides. This is because such methods generate the input by simply concatenating the two given sequences: a peptide and (the pseudo sequence of) an MHC class I molecule, which cannot precisely capture the anchor positions of the MHC binding motif for the peptides with variable lengths. We thus developed an anchor position-aware and high-performance deep model, DeepMHCI, with a position-wise gated layer and a residual binding interaction convolution layer. This allows the model to control the information flow in peptides to be aware of anchor positions and model the interactions between peptides and the MHC pseudo (binding) sequence directly with multiple convolutional kernels.

RESULTS

The performance of DeepMHCI has been thoroughly validated by extensive experiments on four benchmark datasets under various settings, such as 5-fold cross-validation, validation with the independent testing set, external HPV vaccine identification, and external CD8+ epitope identification. Experimental results with visualization of binding motifs demonstrate that DeepMHCI outperformed all competing methods, especially on non-9-mer peptides binding prediction.

AVAILABILITY AND IMPLEMENTATION

DeepMHCI is publicly available at https://github.com/ZhuLab-Fudan/DeepMHCI.

Prognostic and Clinical Significance of Human Leukocyte Antigen Class I Expression in Breast Cancer: A Meta-Analysis

BACKGROUND

The value of human leukocyte antigen (HLA; also known as major histocompatibility complex) class I expression for the prediction of breast cancer survival outcomes remains unclear. We conducted a meta-analysis to explore the prognostic significance of this expression.

MATERIALS AND METHODS

We searched electronic databases to identify reports on associations of HLA class I protein or mRNA expression with survival outcomes and clinicopathological factors in the breast cancer context. Pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were used to conduct a quantitative meta-analysis.

RESULTS

The sample comprised eight studies involving 3590 patients. Only the classical HLA class Ia (HLA-ABC) molecules studies were included in this meta-analysis. Elevated HLA class I protein expression was found to be significantly related to better disease-free survival (DFS) (HR 0.58, 95% CI 0.35-0.95, P = 0.03), particularly among patients with triple-negative breast cancer (TNBC) (HR 0.31, 95% CI 0.18-0.52, P < 0.001), but not to overall survival. It was also associated with estrogen receptor (ER) negativity (OR 1.71, 95% CI 1.24-2.35, P = 0.001), progesterone receptor (PR) negativity (OR 1.49, 95% CI 1.22-1.81, P < 0.001), human epidermal growth factor receptor 2 (HER2) positivity (OR 1.51, 95% CI 1.18-1.94, P = 0.001), TNBC (OR 1.68, 95% CI 1.15-2.45, P < 0.01), high Ki-67 indices (OR 2.06, 95% CI 1.62-2.61, P < 0.001), and high nuclear grades (OR 2.67, 95% CI 2.17-3.29, P < 0.001).

CONCLUSION

This meta-analysis demonstrated that enhanced HLA class I protein expression is significantly associated with the better DFS of patients with breast cancer, especially TNBC, as well as with ER and PR negativity, HER2 positivity, TNBC, and high Ki-67 indices and nuclear grades. The immune target HLA class I may serve as a prognostic indicator for breast cancer.

ERAP1 and ERAP2 Haplotypes Influence Suboptimal HLA-B*27:05-Restricted Anti-Viral CD8+ T Cell Responses Cross-Reactive to Self-Epitopes

The human leukocyte antigen (HLA)-B*27 family of alleles is strongly associated with ankylosing spondylitis (AS), a chronic inflammatory disorder affecting the axial and peripheral joints, yet some HLA-B*27 variants not associated with AS have been shown. Since no major differences in the ligandome of associated compared to not-associated alleles have emerged, a plausible hypothesis is that the quantity rather than the quality of the presented epitopes makes the difference. In addition, the Endoplasmic Reticulum AminoPeptidases (ERAPs) 1 and 2, playing a crucial role in shaping the HLA class I epitopes, act as strong AS susceptibility factors, suggesting that an altered peptidome might be responsible for the activation of pathogenic CD8+ T cells. In this context, we have previously singled out a B*27:05-restricted CD8+ T cell response against pEBNA3A (RPPIFIRRL), an EBV peptide lacking the B*27 classic binding motif. Here, we show that a specific ERAP1/2 haplotype negatively correlates with such response in B*27:05 subjects. Moreover, we prove that the B*27:05 allele successfully presents peptides with the same suboptimal N-terminal RP motif, including the self-peptide, pDYNEIN (RPPIFGDFL). Overall, this study underscores the cooperation between the HLA-B*27 and ERAP1/2 allelic variants in defining CD8+ T cell reactivity to suboptimal viral and self-B*27 peptides and prompts further investigation of the B*27:05 peptidome composition.

Can we predict T cell specificity with digital biology and machine learning?

Recent advances in machine learning and experimental biology have offered breakthrough solutions to problems such as protein structure prediction that were long thought to be intractable. However, despite the pivotal role of the T cell receptor (TCR) in orchestrating cellular immunity in health and disease, computational reconstruction of a reliable map from a TCR to its cognate antigens remains a holy grail of systems immunology. Current data sets are limited to a negligible fraction of the universe of possible TCR-ligand pairs, and performance of state-of-the-art predictive models wanes when applied beyond these known binders. In this Perspective article, we make the case for renewed and coordinated interdisciplinary effort to tackle the problem of predicting TCR-antigen specificity. We set out the general requirements of predictive models of antigen binding, highlight critical challenges and discuss how recent advances in digital biology such as single-cell technology and machine learning may provide possible solutions. Finally, we describe how predicting TCR specificity might contribute to our understanding of the broader puzzle of antigen immunogenicity.

A common allele of HLA is associated with asymptomatic SARS-CoV-2 infection

Studies have demonstrated that at least 20% of individuals infected with SARS-CoV-2 remain asymptomatic1-4. Although most global efforts have focused on severe illness in COVID-19, examining asymptomatic infection provides a unique opportunity to consider early immunological features that promote rapid viral clearance. Here, postulating that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection, we enrolled 29,947 individuals, for whom high-resolution HLA genotyping data were available, in a smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n = 1,428) comprised unvaccinated individuals who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci with disease course and identified a strong association between HLA-B*15:01 and asymptomatic infection, observed in two independent cohorts. Suggesting that this genetic association is due to pre-existing T cell immunity, we show that T cells from pre-pandemic samples from individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF. The majority of the reactive T cells displayed a memory phenotype, were highly polyfunctional and were cross-reactive to a peptide derived from seasonal coronaviruses. The crystal structure of HLA-B*15:01-peptide complexes demonstrates that the peptides NQKLIANQF and NQKLIANAF (from OC43-CoV and HKU1-CoV) share a similar ability to be stabilized and presented by HLA-B*15:01. Finally, we show that the structural similarity of the peptides underpins T cell cross-reactivity of high-affinity public T cell receptors, providing the molecular basis for HLA-B*15:01-mediated pre-existing immunity.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptide/HLA (pHLA, the human MHC) structures has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within a curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these representative backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer peptide/HLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in terms of structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work provide a framework for linking conformational diversity with antigen immunogenicity and receptor cross-reactivity.

Decoupling peptide binding from T cell receptor recognition with engineered chimeric MHC-I molecules

Major Histocompatibility Complex class I (MHC-I) molecules display self, viral or aberrant epitopic peptides to T cell receptors (TCRs), which employ interactions between complementarity-determining regions with both peptide and MHC-I heavy chain 'framework' residues to recognize specific Human Leucocyte Antigens (HLAs). The highly polymorphic nature of the HLA peptide-binding groove suggests a malleability of interactions within a common structural scaffold. Here, using structural data from peptide:MHC-I and pMHC:TCR structures, we first identify residues important for peptide and/or TCR binding. We then outline a fixed-backbone computational design approach for engineering synthetic molecules that combine peptide binding and TCR recognition surfaces from existing HLA allotypes. X-ray crystallography demonstrates that chimeric molecules bridging divergent HLA alleles can bind selected peptide antigens in a specified backbone conformation. Finally, in vitro tetramer staining and biophysical binding experiments using chimeric pMHC-I molecules presenting established antigens further demonstrate the requirement of TCR recognition on interactions with HLA framework residues, as opposed to interactions with peptide-centric Chimeric Antigen Receptors (CARs). Our results underscore a novel, structure-guided platform for developing synthetic HLA molecules with desired properties as screening probes for peptide-centric interactions with TCRs and other therapeutic modalities.

Comparative analysis of the variability of the human leukocyte antigen peptide-binding pockets in patients with acute leukaemia

The association between acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML) and the human leukocyte antigens (HLA) has rarely been studied in terms of diversity of peptide-binding pockets. The objective of this study was to analyse whether motifs of HLA class I and class II peptide-binding pockets and/or their amino acid positions were differentially associated with ALL and AML. We included 849 patients from the Eurocord/European Blood and Marrow Transplant registry. The HLA peptide-binding pockets whose amino acid variability was analysed were B and F for HLA class I, P4, P6, and P9 for HLA-DRB1, and P4 and P9 for HLA-DQB1. The motif RFDRAY in P4 of HLA-DRB1*16:01/02/03/05 alleles and the motif YYVSY in P9 of HLA-DQB1*05:02/04/05 alleles, were statistically associated with ALL (corrected p value [p_c ] = 0.001 and p_c  = 0.035 respectively). The frequency of serine 57 in the P9 of HLA-DQB1 was higher in ALL (odds ratio 2.09, 95% confidence interval: 1.27-3.44; p_c  = 0.037). Our analysis suggests that specific motifs in terms of HLA class II pockets and amino acids might be unique to ALL. The associations identified in this study encourage further investigation oF the role of HLA peptide-binding pockets and their amino acids in immune processes underpinning acute leukaemia and ultimately in immunotherapy settings.

HLA Class I Supertype Classification Based on Structural Similarity

HLA class I proteins, a critical component in adaptive immunity, bind and present intracellular Ags to CD8+ T cells. The extreme polymorphism of HLA genes and associated peptide binding specificities leads to challenges in various endeavors, including neoantigen vaccine development, disease association studies, and HLA typing. Supertype classification, defined by clustering functionally similar HLA alleles, has proven helpful in reducing the complexity of distinguishing alleles. However, determining supertypes via experiments is impractical, and current in silico classification methods exhibit limitations in stability and functional relevance. In this study, by incorporating three-dimensional structures we present a method for classifying HLA class I molecules with improved breadth, accuracy, stability, and flexibility. Critical for these advances is our finding that structural similarity highly correlates with peptide binding specificity. The new classification should be broadly useful in peptide-based vaccine development and HLA-disease association studies.

Hepatitis B and Hepatitis D Viruses: A Comprehensive Update with an Immunological Focus

Hepatitis B virus (HBV) and hepatitis delta virus (HDV) are highly prevalent viruses estimated to infect approximately 300 million people and 12-72 million people worldwide, respectively. HDV requires the HBV envelope to establish a successful infection. Concurrent infection with HBV and HDV can result in more severe disease outcomes than infection with HBV alone. These viruses can cause significant hepatic disease, including cirrhosis, fulminant hepatitis, and hepatocellular carcinoma, and represent a significant cause of global mortality. Therefore, a thorough understanding of these viruses and the immune response they generate is essential to enhance disease management. This review includes an overview of the HBV and HDV viruses, including life cycle, structure, natural course of infection, and histopathology. A discussion of the interplay between HDV RNA and HBV DNA during chronic infection is also included. It then discusses characteristics of the immune response with a focus on reactions to the antigenic hepatitis B surface antigen, including small, middle, and large surface antigens. This paper also reviews characteristics of the immune response to the hepatitis D antigen (including small and large antigens), the only protein expressed by hepatitis D. Lastly, we conclude with a discussion of recent therapeutic advances pertaining to these viruses.

Human T cells recognize HLA-DP-bound peptides in two orientations

Human leukocyte antigen (HLA) molecules present small peptide antigens to T cells, thereby allowing them to recognize pathogen-infected and cancer cells. A central dogma over the last 50+ y is that peptide binding to HLA molecules is mediated by the docking of side chains of particular amino acids in the peptide into pockets in the HLA molecules in a conserved N- to C-terminal orientation. Whether peptides can be presented in a reversed C- to N-terminal orientation remains unclear. Here, we performed large-scale identification of peptides bound to HLA-DP molecules and observed that in addition to peptide binding in an N- to C-terminal orientation, in 9 out of 14 HLA-DP allotypes, reverse motifs are found, compatible with C- to N-terminal peptide binding. Moreover, we isolated high-avidity human cytomegalovirus (CMV)-specific HLA-DP-restricted CD4⁺ T cells from the memory repertoire of healthy donors and demonstrate that such T cells recognized CMV-derived peptides bound to HLA-DPB1*01:01 or *05:01 in a reverse C- to N-terminal manner. Finally, we obtained a high-resolution HLA-DPB1*01:01-CMVpp65_(142-158) peptide crystal structure, which is the molecular basis for C- to N-terminal peptide binding to HLA-DP. Our results point to unique features of HLA-DP molecules that substantially broaden the HLA class II bound peptide repertoire to combat pathogens and eliminate cancer cells.

The Gallus gallus RJF reference genome reveals an MHCY haplotype organized in gene blocks that contain 107 loci including 45 specialized, polymorphic MHC class I loci, 41 C-type lectin-like loci, and other loci amid hundreds of transposable elements

MHCY is a second major histocompatibility complex-like gene region in chickens originally identified by the presence of major histocompatibility complex class I-like and class II-like gene sequences. Up to now, the MHCY gene region has been poorly represented in genomic sequence data. A high density of repetitive sequence and multiple members of several gene families prevented the accurate assembly of short-read sequence data for MHCY. Identified here by single-molecule real-time sequencing sequencing of BAC clones for the Gallus gallus Red Jungle Fowl reference genome are 107 MHCY region genes (45 major histocompatibility complex class I-like, 41 c-type-lectin-like, 8 major histocompatibility complex class IIβ, 8 LENG9-like, 4 zinc finger protein loci, and a single only zinc finger-like locus) located amid hundreds of retroelements within 4 contigs representing the region. Sequences obtained for nearby ribosomal RNA genes have allowed MHCY to be precisely mapped with respect to the nucleolar organizer region. Gene sequences provide insights into the unusual structure of the MHCY class I molecules. The MHCY class I loci are polymorphic and group into 22 types based on predicted amino acid sequences. Some MHCY class I loci are full-length major histocompatibility complex class I genes. Others with altered gene structure are considered gene candidates. The amino acid side chains at many of the polymorphic positions in MHCY class I are directed away rather than into the antigen-binding groove as is typical of peptide-binding major histocompatibility complex class I molecules. Identical and nearly identical blocks of genomic sequence contribute to the observed multiplicity of identical MHCY genes and the large size (&gt;639 kb) of the Red Jungle Fowl MHCY haplotype. Multiple points of hybridization observed in fluorescence in situ hybridization suggest that the Red Jungle Fowl MHCY haplotype is made up of linked, but physically separated genomic segments. The unusual gene content, the evidence of highly similar duplicated segments, and additional evidence of variation in haplotype size distinguish polymorphic MHCY from classical polymorphic major histocompatibility complex regions.

Homologous peptides derived from influenza A, B and C viruses induce variable CD8+ T cell responses with cross-reactive potential

Objective

Influenza A, B and C viruses (IAV, IBV and ICV, respectively) circulate globally, infecting humans and causing widespread morbidity and mortality. Here, we investigate the T cell response towards an immunodominant IAV epitope, NP_265‐273, and its IBV and ICV homologues, presented by HLA‐A*03:01 molecule expressed in ~ 4% of the global population (~ 300 million people).

Methods

We assessed the magnitude (tetramer staining) and quality of the CD8⁺ T cell response (intracellular cytokine staining) towards NP_265‐IAV and described the T cell receptor (TCR) repertoire used to recognise this immunodominant epitope. We next assessed the immunogenicity of NP_265‐IAV homologue peptides from IBV and ICV and the ability of CD8⁺ T cells to cross‐react towards these homologous peptides. Furthermore, we determined the structures of NP_265‐IAV and NP_323‐IBV peptides in complex with HLA‐A*03:01 by X‐ray crystallography.

Results

Our study provides a detailed characterisation of the CD8⁺ T cell response towards NP_265‐IAV and its IBV and ICV homologues. The data revealed a diverse repertoire for NP_265‐IAV that is associated with superior anti‐viral protection. Evidence of cross‐reactivity between the three different influenza virus strain‐derived epitopes was observed, indicating the discovery of a potential vaccination target that is broad enough to cover all three influenza strains.

Conclusion

We show that while there is a potential to cross‐protect against distinct influenza virus lineages, the T cell response was stronger against the IAV peptide than IBV or ICV, which is an important consideration when choosing targets for future vaccine design.

Protective HLA-B57: T cell and natural killer cell recognition in HIV infection

Understanding the basis of the immune determinants controlling disease outcome is critical to provide better care to patients and could be exploited for therapeutics and vaccine design. The discovery of the human immunodeficiency virus (HIV) virus as the causing agent of acquired immunodeficiency syndrome (AIDS) decades ago, led to a tremendous amount of research. Among the findings, it was discovered that some rare HIV+ individuals, called HIV controllers (HICs), had the ability to control the virus and keep a low viral load without the need of treatment. This ability allows HICs to delay or avoid progression to AIDS. HIV control is strongly associated with the expression of human leukocyte antigen (HLA) alleles in HICs. From the HIV protective HLAs described, HLA-B57 is the most frequent in HIC patients. HLA-B57 can present a large range of highly conserved Gag-derived HIV peptides to CD8+ T cells and natural killer (NK) cells, both the focus of this review. So far there are limited differences in the immune response strength, magnitude, or receptor repertoire towards HIV epitopes that could explain viral control in HICs. Interestingly, some studies revealed that during early infection the large breadth of the immune response towards HIV mutants in HLA-B57+ HIC patients, might in turn influence the disease outcome.

Peptide-dependent tuning of major histocompatibility complex motional properties and the consequences for cellular immunity

T cell receptors (TCRs) and other receptors of the immune system recognize peptides presented by class I or class II major histocompatibility complex (MHC) proteins. Although we generally distinguish between the MHC protein and its peptide, at an atomic level the two form a structural composite, which allows peptides to influence MHC properties and vice versa. One consequence is the peptide-dependent tuning of MHC structural dynamics, which contributes to protein structural adaptability and influences how receptors identify and bind targets. Peptide-dependent tuning of MHC protein dynamics can impact processes such as antigenicity, TCR cross-reactivity, and T cell repertoire selection. Motional tuning extends beyond the binding groove, influencing peptide selection and exchange, as well as interactions with other immune receptors. Here, we review recent findings showing how peptides can affect the dynamic and adaptable nature of MHC proteins. We highlight consequences for immunity and demonstrate how MHC proteins have evolved to be highly sensitive dynamic reporters, with broad immunological consequences.

T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles

CD8+ T cells are a pivotal part of the immune response to viruses, playing a key role in disease outcome and providing long-lasting immunity to conserved pathogen epitopes. Understanding CD8+ T cell immunity in humans is complex due to CD8+ T cell restriction by highly polymorphic Human Leukocyte Antigen (HLA) proteins, requiring T cell epitopes to be defined for different HLA allotypes across different ethnicities. Here we evaluate strategies that have been developed to facilitate epitope identification and study immunogenic T cell responses. We describe an immunopeptidomics approach to sequence HLA-bound peptides presented on virus-infected cells by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using antigen presenting cell lines that stably express the HLA alleles characteristic of Indigenous Australians, this approach has been successfully used to comprehensively identify influenza-specific CD8+ T cell epitopes restricted by HLA allotypes predominant in Indigenous Australians, including HLA-A*24:02 and HLA-A*11:01. This is an essential step in ensuring high vaccine coverage and efficacy in Indigenous populations globally, known to be at high risk from influenza disease and other respiratory infections.

Cutting Edge: Unconventional CD8+ T Cell Recognition of a Naturally Occurring HLA-A*02:01-Restricted 20mer Epitope

Unconventional HLA class I-restricted CD8⁺ T cell epitopes, longer than 10 aa, have been implicated to play a role in human immunity against viruses and cancer. T cell recognition of long peptides, centrally bulging from the HLA cleft, has been described previously. Alternatively, long peptides can contain a linear HLA-bound core peptide, with a N- or C-terminal peptide "tail" extending from the HLA peptide binding groove. The role of such a peptide "tail" in CD8⁺ T cell recognition remains unclear. In this study, we identified a 20mer peptide (FLPTPEELGLLGPPRPQVLA [FLP]) derived from the IL-27R subunit α gene restricted to HLA-A*02:01, for which we solved the crystal structure and demonstrated a long C-terminal "tail" extension. FLP-specific T cell clones demonstrated various recognition modes, some T cells recognized the FLP core peptide, while for other T cells the peptide tail was essential for recognition. These results demonstrate a crucial role for a C-terminal peptide tail in immunogenicity.

HLA-A*11:01-restricted CD8+ T cell immunity against influenza A and influenza B viruses in Indigenous and non-Indigenous people

HLA-A*11:01 is one of the most prevalent human leukocyte antigens (HLAs), especially in East Asian and Oceanian populations. It is also highly expressed in Indigenous people who are at high risk of severe influenza disease. As CD8⁺ T cells can provide broadly cross-reactive immunity to distinct influenza strains and subtypes, including influenza A, B and C viruses, understanding CD8⁺ T cell immunity to influenza viruses across prominent HLA types is needed to rationally design a universal influenza vaccine and generate protective immunity especially for high-risk populations. As only a handful of HLA-A*11:01-restricted CD8⁺ T cell epitopes have been described for influenza A viruses (IAVs) and epitopes for influenza B viruses (IBVs) were still unknown, we embarked on an epitope discovery study to define a CD8⁺ T cell landscape for HLA-A*11:01-expressing Indigenous and non-Indigenous Australian people. Using mass-spectrometry, we identified IAV- and IBV-derived peptides presented by HLA-A*11:01 during infection. 79 IAV and 57 IBV peptides were subsequently screened for immunogenicity in vitro with peripheral blood mononuclear cells from HLA-A*11:01-expressing Indigenous and non-Indigenous Australian donors. CD8⁺ T cell immunogenicity screening revealed two immunogenic IAV epitopes (A11/PB2_320-331 and A11/PB2_323-331) and the first HLA-A*11:01-restricted IBV epitopes (A11/M_41-49, A11/NS1_186-195 and A11/NP_511-520). The immunogenic IAV- and IBV-derived peptides were >90% conserved among their respective influenza viruses. Identification of novel immunogenic HLA-A*11:01-restricted CD8⁺ T cell epitopes has implications for understanding how CD8⁺ T cell immunity is generated towards IAVs and IBVs. These findings can inform the development of rationally designed, broadly cross-reactive influenza vaccines to ensure protection from severe influenza disease in HLA-A*11:01-expressing individuals.

Influenza A and influenza B viral infections cause significant morbidity and mortality. Established CD8⁺ T cell immunity directed at conserved viral regions provides protection against influenza viruses, drives rapid recovery, and leads to less severe clinical outcomes. Killer CD8⁺ T cells recognising viral peptides presented by HLA class I glycoproteins can provide broad immunity across distinct influenza strains and subtypes. Using immunopeptidomics, we identified novel CD8⁺ T cell targets for influenza A and influenza B viruses in the context of HLA-A*11:01, an HLA-I allomorph highly prevalent in East Asia and Oceania, including Indigenous populations. Our study provides key insights for T cell-directed vaccines and immunotherapies.