Discrimination Between Human Leukocyte Antigen Class I-Bound and Co-Purified HIV-Derived Peptides in Immunopeptidomics Workflows

Immunopeptidomics mapping of Listeria monocytogenes T cell epitopes in mice

Listeria monocytogenes is a foodborne intracellular bacterial model pathogen. Protective immunity against Listeria depends on an effective CD8+ T cell response, but very few T cell epitopes are known in mice as a common animal infection model for listeriosis. To identify epitopes we screened for Listeria immunopeptides presented in the spleen of infected mice by mass spectrometry-based immunopeptidomics. We mapped more than 6,000 mouse self-peptides presented on MHC Class I molecules, including 12 high confident Listeria peptides from 12 different bacterial proteins. Bacterial immunopeptides with confirmed fragmentation spectra were further tested for their potential to activate CD8+ T cells, revealing VTYNYINI from the putative cell wall surface anchor family protein LMON_0576 as a novel bona fide peptide epitope. The epitope showed high biological potency in a prime boost model and can be used as a research tool to probe CD8+ T cell responses in mouse models of Listeria infection. Together, our results demonstrate the power of immunopeptidomics for bacterial antigen identification.

MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer

Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.

Cryptic MHC-E epitope from influenza elicits a potent cytolytic T cell response

The extent to which unconventional forms of antigen presentation drive T cell immunity is unknown. By convention, CD8 T cells recognize viral peptides, or epitopes, in association with classical major histocompatibility complex (MHC) class I, or MHC-Ia, but immune surveillance can, in some cases, be directed against peptides presented by nonclassical MHC-Ib, in particular the MHC-E proteins (Qa-1 in mice and HLA-E in humans); however, the overall importance of nonclassical responses in antiviral immunity remains unclear. Similarly uncertain is the importance of 'cryptic' viral epitopes, defined as those undetectable by conventional mapping techniques. Here we used an immunopeptidomic approach to search for unconventional epitopes that drive T cell responses in mice infected with influenza virus A/Puerto Rico/8/1934. We identified a nine amino acid epitope, termed M-SL9, that drives a co-immunodominant, cytolytic CD8 T cell response that is unconventional in two major ways: first, it is presented by Qa-1, and second, it has a cryptic origin, mapping to an unannotated alternative reading frame product of the influenza matrix gene segment. Presentation and immunogenicity of M-SL9 are dependent on the second AUG codon of the positive sense matrix RNA segment, suggesting translation initiation by leaky ribosomal scanning. During influenza virus A/Puerto Rico/8/1934 infection, M-SL9-specific T cells exhibit a low level of egress from the lungs and strong differentiation into tissue-resident memory cells. Importantly, we show that M-SL9/Qa-1-specific T cells can be strongly induced by messenger RNA vaccination and that they can mediate antigen-specific cytolysis in vivo. Our results demonstrate that noncanonical translation products can account for an important fraction of the T cell repertoire and add to a growing body of evidence that MHC-E-restricted T cells could have substantial therapeutic value.

Expanding the MAPPs Assay to Accommodate MHC-II Pan Receptors for Improved Predictability of Potential T Cell Epitopes

A critical step in the immunogenicity cascade is attributed to human leukocyte antigen (HLA) II presentation triggering T cell immune responses. The liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based major histocompatibility complex (MHC) II-associated peptide proteomics (MAPPs) assay is implemented during preclinical risk assessments to identify biotherapeutic-derived T cell epitopes. Although studies indicate that HLA-DP and HLA-DQ alleles are linked to immunogenicity, most MAPPs studies are restricted to using HLA-DR as the dominant HLA II genotype due to the lack of well-characterized immunoprecipitating antibodies. Here, we address this issue by testing various commercially available clones of MHC-II pan (CR3/43, WR18, and Tü39), HLA-DP (B7/21), and HLA-DQ (SPV-L3 and 1a3) antibodies in the MAPPs assay, and characterizing identified peptides according to binding specificity. Our results reveal that HLA II receptor-precipitating reagents with similar reported specificities differ based on clonality and that MHC-II pan antibodies do not entirely exhibit pan-specific tendencies. Since no individual antibody clone is able to recover the complete HLA II peptide repertoire, we recommend a mixed strategy of clones L243, WR18, and SPV-L3 in a single immunoprecipitation step for more robust compound-specific peptide detection. Ultimately, our optimized MAPPs strategy improves the predictability and additional identification of T cell epitopes in immunogenicity risk assessments.

Generation of novel complete HLA class I monoallelic cell lines used in an MHC stabilization assay for neoantigen evaluation

Immunogenic neoantigens derived from somatic mutations in cancer have been identified through clinical studies with the cloning of tumor-infiltrating T cells, and cancer driver gene mutation-derived epitopes have been reported; however, these are rare. At present, the validation of epitopes predicted in silico is difficult as human T-cell clonal diversity cannot be reproduced in vitro or in experimental animal models. To confirm the epitope peptides presented by human leukocyte antigen (HLA) class I molecules predicted in silico, biochemical methods such as major histocompatibility complex (MHC) stabilization assays and mass spectrometry-mediated identification have been developed based on HLA-A*02:01 monoallelic T2 cells and HLA-C*01:02 monoallelic LCL721.221 cells. Therefore, in the present study, to prevent confusion due to peptide cross-presentation among HLA molecules, HLA class I monoallelic B-cell clones were generated from the TISI cell line by knocking out HLA-ABC and TAP2, and knocking in HLA alleles. To explore cancer driver mutations as potential targets for immunotherapy, exome sequencing data from 5,143 patients with cancer enrolled in a comprehensive genome analysis project at the Shizuoka Cancer Center were used to identify somatic amino acid substituted mutations and the 50 most frequent mutations in five genes, TP53, EGFR, PIK3CA, KRAS and BRAF, were identified. Using NetMHC4.1, the present study predicted whether epitopes derived from these mutations are presented on major HLA-ABC alleles in Japanese individuals and synthesized 138 peptides for MHC stabilization assays. The authors also attempted to examine the candidate epitopes at physiological temperatures by using antibody clone G46-2.6, which can detect HLA-ABC, independent of β2-microglobulin association. In the assays, although the peptide-induced HLA expression levels were associated with the predicted affinities, the respective HLA alleles exhibited varying degrees of responsiveness, and unexpectedly, p53-mutant epitopes with predicted weak affinities exhibited strong responses. These results suggested that MHC stabilization assays using completely monoallelic HLA-expressing B-cell lines are useful for evaluating the presentation of neoantigen epitopes.

HLA class I signal peptide polymorphism determines the level of CD94/NKG2-HLA-E-mediated regulation of effector cell responses

Human leukocyte antigen (HLA)-E binds epitopes derived from HLA-A, HLA-B, HLA-C and HLA-G signal peptides (SPs) and serves as a ligand for CD94/NKG2A and CD94/NKG2C receptors expressed on natural killer and T cell subsets. We show that among 16 common classical HLA class I SP variants, only 6 can be efficiently processed to generate epitopes that enable CD94/NKG2 engagement, which we term 'functional SPs'. The single functional HLA-B SP, known as HLA-B/-21M, induced high HLA-E expression, but conferred the lowest receptor recognition. Consequently, HLA-B/-21M SP competes with other SPs for providing epitope to HLA-E and reduces overall recognition of target cells by CD94/NKG2A, calling for reassessment of previous disease models involving HLA-B/-21M. Genetic population data indicate a positive correlation between frequencies of functional SPs in humans and corresponding cytomegalovirus mimics, suggesting a means for viral escape from host responses. The systematic, quantitative approach described herein will facilitate development of prediction algorithms for accurately measuring the impact of CD94/NKG2-HLA-E interactions in disease resistance/susceptibility.

Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.

The HLA class-II immunopeptidomes of AAV capsids proteins

Introduction

Gene therapies are using Adeno-associated viruses (AAVs) as vectors, but immune responses against the capsids pose challenges to their efficiency and safety. Helper T cell recognition of capsid-derived peptides bound to human leukocyte antigen (HLA) class II molecules is an essential step in the AAV-specific adaptive immunity.

Methods

Using MHC-associated peptide proteomics, we identified the HLA-DR and HLA-DQ immunopeptidomes of the capsid proteins of three different AAV serotypes (AAV2, AAV6, and AAV9) from a panel of healthy donors selected to represent a majority of allele usage.

Results

The identified sequences span the capsids of all serotypes, with AAV2 having the highest peptide count. For all the serotypes, multiple promiscuous peptides were identified and displayed by both HLA-DR and -DQ. However, despite high sequence homology, there were few identical peptides among AAV2, AAV6, and AAV9 immunopeptidomes, and none were promiscuous.

Discussion

Results from this work represent a comprehensive immunopeptidomics research of potential CD4+ T cell epitopes and provide the basis for immunosurveillance efforts for safer and more efficient AAV-based gene therapies.

Immunopeptidomic Analysis of BoLA-I and BoLA-DR Presented Peptides from Theileria parva Infected Cells

The apicomplexan parasite Theileria parva is the causative agent of East Coast fever, usually a fatal disease for cattle, which is prevalent in large areas of eastern, central, and southern Africa. Protective immunity against T. parva is mediated by CD8+ T cells, with CD4+ T-cells thought to be important in facilitating the full maturation and development of the CD8+ T-cell response. T. parva has a large proteome, with >4000 protein-coding genes, making T-cell antigen identification using conventional screening approaches laborious and expensive. To date, only a limited number of T-cell antigens have been described. Novel approaches for identifying candidate antigens for T. parva are required to replace and/or complement those currently employed. In this study, we report on the use of immunopeptidomics to study the repertoire of T. parva peptides presented by both BoLA-I and BoLA-DR molecules on infected cells. The study reports on peptides identified from the analysis of 13 BoLA-I and 6 BoLA-DR datasets covering a range of different BoLA genotypes. This represents the most comprehensive immunopeptidomic dataset available for any eukaryotic pathogen to date. Examination of the immunopeptidome data suggested the presence of a large number of coprecipitated and non-MHC-binding peptides. As part of the work, a pipeline to curate the datasets to remove these peptides was developed and used to generate a final list of 74 BoLA-I and 15 BoLA-DR-presented peptides. Together, the data demonstrated the utility of immunopeptidomics as a method to identify novel T-cell antigens for T. parva and the importance of careful curation and the application of high-quality immunoinformatics to parse the data generated.

Immunopeptidomics-based design of mRNA vaccine formulations against Listeria monocytogenes

Listeria monocytogenes is a foodborne intracellular bacterial pathogen leading to human listeriosis. Despite a high mortality rate and increasing antibiotic resistance no clinically approved vaccine against Listeria is available. Attenuated Listeria strains offer protection and are tested as antitumor vaccine vectors, but would benefit from a better knowledge on immunodominant vector antigens. To identify novel antigens, we screen for Listeria peptides presented on the surface of infected human cell lines by mass spectrometry-based immunopeptidomics. In between more than 15,000 human self-peptides, we detect 68 Listeria immunopeptides from 42 different bacterial proteins, including several known antigens. Peptides presented on different cell lines are often derived from the same bacterial surface proteins, classifying these antigens as potential vaccine candidates. Encoding these highly presented antigens in lipid nanoparticle mRNA vaccine formulations results in specific CD8⁺ T-cell responses and induces protection in vaccination challenge experiments in mice. Our results can serve as a starting point for the development of a clinical mRNA vaccine against Listeria and aid to improve attenuated Listeria vaccines and vectors, demonstrating the power of immunopeptidomics for next-generation bacterial vaccine development.

Impact of Micropolymorphism Outside the Peptide Binding Groove in the Clinically Relevant Allele HLA-C*14 on T Cell Responses in HIV-1 Infection

There is increasing evidence for the importance of human leukocyte antigen C (HLA-C)-restricted CD8⁺ T cells in HIV-1 control, but these responses are relatively poorly investigated. The number of HLA-C-restricted HIV-1 epitopes identified is much smaller than those of HLA-A-restricted or HLA-B-restricted ones. Here, we utilized a mass spectrometry-based approach to identify HIV-1 peptides presented by HLA-C*14:03 protective and HLA-C*14:02 nonprotective alleles. We identified 25 8- to 11-mer HLA-I-bound HIV-1 peptides from HIV-1-infected HLA-C*14:02⁺/14:03⁺ cells. Analysis of T cell responses to these peptides identified novel 6 T cell epitopes targeted in HIV-1-infected HLA-C*14:02⁺/14:03⁺ subjects. Analyses using HLA stabilization assays demonstrated that all 6 epitope peptides exhibited higher binding to and greater cell surface stabilization of HLA-C*14:02 than HLA-C*14:03. T cell response magnitudes were typically higher in HLA-C*14:02⁺ than HLA-C*14:03⁺ individuals, with responses to the Pol KM9 and Nef epitopes being significantly higher. The results show that HLA-C*14:02 can elicit stronger T cell responses to HIV-1 than HLA-C*14:03 and suggest that the single amino acid difference between these HLA-C14 subtypes at position 21, outside the peptide-binding groove, indirectly influences the stability of peptide-HLA-C*14 complexes and induction/expansion of HIV-specific T cells. Taken together with a previous finding that KIR2DL2⁺ NK cells recognized HLA-C*14:03⁺ HIV-1-infected cells more than HLA-C*14:02⁺ ones, the present study indicates that these HLA-C*14 subtypes differentially impact HIV-1 control by T cells and NK cells.

IMPORTANCE Some human leukocyte antigen (HLA) class I alleles are associated with good clinical outcomes in HIV-1 infection and are called protective HLA alleles. Identification of T cell epitopes restricted by protective HLA alleles can give important insight into virus-immune system interactions and inform design of immune-based prophylactic/therapeutic strategies. Although epitopes restricted by many protective HLA-A/B alleles have been identified, protective HLA-C alleles are relatively understudied. Here, we identified 6 novel T cell epitopes presented by both HLA-C*14:02 (no association with protection) and HLA-C*14:03 (protective) using a mass spectrometry-based immunopeptidome profiling approach. We found that these peptides bound to and stabilized HLA-C*14:02 better than HLA-C*14:03 and observed differences in induction/expansion of epitope-specific T cell responses in HIV-infected HLA-C*14:02⁺ versus HLA-C*14:03⁺ individuals. These results enhance understanding of how the microstructural difference at position 21 between these HLA-C*14 subtypes may influence cellular immune responses involved in viral control in HIV-1 infection.

Unsupervised Mining of HLA-I Peptidomes Reveals New Binding Motifs and Potential False Positives in the Community Database

Modern vaccine designs and studies of human leukocyte antigen (HLA)-mediated immune responses rely heavily on the knowledge of HLA allele-specific binding motifs and computational prediction of HLA-peptide binding affinity. Breakthroughs in HLA peptidomics have considerably expanded the databases of natural HLA ligands and enabled detailed characterizations of HLA-peptide binding specificity. However, cautions must be made when analyzing HLA peptidomics data because identified peptides may be contaminants in mass spectrometry or may weakly bind to the HLA molecules. Here, a hybrid de novo peptide sequencing approach was applied to large-scale mono-allelic HLA peptidomics datasets to uncover new ligands and refine current knowledge of HLA binding motifs. Up to 12-40% of the peptidomics data were low-binding affinity peptides with an arginine or a lysine at the C-terminus and likely to be tryptic peptide contaminants. Thousands of these peptides have been reported in a community database as legitimate ligands and might be erroneously used for training prediction models. Furthermore, unsupervised clustering of identified ligands revealed additional binding motifs for several HLA class I alleles and effectively isolated outliers that were experimentally confirmed to be false positives. Overall, our findings expanded the knowledge of HLA binding specificity and advocated for more rigorous interpretation of HLA peptidomics data that will ensure the high validity of community HLA ligandome databases.

The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome

INTRODUCTION

The comprehensive collection of peptides presented by Major Histocompatibility Complex (MHC) molecules on the cell surface is collectively known as the immunopeptidome. The analysis and interpretation of such data sets holds great promise for furthering our understanding of basic immunology and adaptive immune activation and regulation, and for direct rational discovery of T cell antigens and the design of T-cell based therapeutics and vaccines. These applications are however challenged by the complex nature of immunopeptidome data.

AREAS COVERED

Here, we describe the benefits and shortcomings of applying liquid chromatography-tandem mass spectrometry (MS) to obtain large scale immunopeptidome data sets and illustrate how the accurate analysis and optimal interpretation of such data is reliant on the availability of refined and highly optimized machine learning approaches.

EXPERT OPINION

Further we demonstrate how the accuracy of immunoinformatics prediction methods within the field of MHC antigen presentation has benefited greatly from the availability of MS-immunopeptidomics data, and exemplify how optimal antigen discovery is best performed in a synergistic combination of MS experiments and such in silico models trained on large scale immunopeptidomics data.

Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome

Mass spectrometry (MS) based immunopeptidomics is used in several biomedical applications including neo-epitope discovery in oncology, next-generation vaccine development and protein-drug immunogenicity assessment. Immunopeptidome data are highly complex given the expression of multiple HLA alleles on the cell membrane and presence of co-immunoprecipitated contaminants. The absence of tools that deal with these challenges effectively and guide the analysis and interpretation of this complex type of data is currently a major bottleneck for the large-scale application of this technique. To resolve this, we here present the MHCMotifDecon that benefits from state-of-the-art HLA class-I and class-II predictions to accurately deconvolute immunopeptidome datasets and assign individual ligands to the most likely HLA molecule, allowing to identify and characterize HLA binding motifs while discarding co-purified contaminants. We have benchmarked the tool against other state-of-the-art methods and illustrated its application on experimental datasets for HLA-DR demonstrating a previously underappreciated role for HLA-DRB3/4/5 molecules in defining HLA class II immune repertoires. With its ease of use, MHCMotifDecon can efficiently guide interpretation of immunopeptidome datasets, serving the discovery of novel T cell targets. MHCMotifDecon is available at https://services.healthtech.dtu.dk/service.php?MHCMotifDecon-1.0.

Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome

Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopeptidome) following affinity purification of solubilized HLA-peptide complexes. However, in recent years, there has been a growing awareness of the "dark side" of the immunopeptidome: unconventional peptide epitopes, including neoepitopes, which elude detection by conventional search methods because their sequences are not present in reference protein databases (DBs). Here, we establish a bioinformatics workflow to aid identification of peptides generated by noncanonical translation of mRNA or by genome variants. The workflow incorporates both standard transcriptomics software and novel computer programs to produce cell line-specific protein DBs based on three-frame translation of the transcriptome. The final protein DB also includes sequences resulting from variants determined by variant calling on the same RNA-Seq data. We then searched our experimental data against both transcriptome-based and standard DBs using PEAKS Studio (Bioinformatics Solutions, Inc). Finally, further novel software helps to compare the various result sets arising for each sample, pinpoint putative genomic origins for unconventional sequences, and highlight potential neoepitopes. We applied the workflow to study the immunopeptidome of the acute myeloid leukemia cell line THP-1, using RNA-Seq and immunopeptidome data. We confidently identified over 14,000 peptides from three replicates of purified HLA peptides derived from THP-1 cells using the conventional UniProt human proteome. Using the transcriptome-based DB generated using our workflow, we recapitulated >85% of these and also identified 1029 unconventional peptides not explained by UniProt, including 16 sequences caused by nonsynonymous variants. Our workflow, which we term "immunopeptidogenomics," can provide DBs, which include pertinent unconventional sequences and allow neoepitope discovery, without becoming too large to search. Immunopeptidogenomics is a step toward unbiased search approaches that are needed to illuminate the dark side of the immunopeptidome.

Leveraging Immunopeptidomics To Study and Combat Infectious Disease

T cells must recognize pathogen-derived peptides bound to major histocompatibility complexes (MHCs) in order to initiate a cell-mediated immune response against an infection, or to support the development of high-affinity antibody responses. Identifying antigens presented on MHCs by infected cells and professional antigen-presenting cells (APCs) during infection may therefore provide a route toward developing new vaccines. Peptides bound to MHCs can be identified at whole-proteome scale using mass spectrometry-a technique referred to as "immunopeptidomics." This technique has emerged as a powerful tool for identifying potential vaccine targets in the context of many infectious diseases. In this review, we discuss the contributions immunopeptidomic studies have made to understanding antigen presentation and T cell priming in the context of infection and the potential for immunopeptidomics to inform the development of vaccines to address pressing global health problems in infectious disease.

Cloud Computing Based Immunopeptidomics Utilizing Community Curated Variant Libraries Simplifies and Improves Neo-Antigen Discovery in Metastatic Melanoma

Unique peptide neo-antigens presented on the cell surface are attractive targets for researchers in nearly all areas of personalized medicine. Cells presenting peptides with mutated or other non-canonical sequences can be utilized for both targeted therapies and diagnostics. Today's state-of-the-art pipelines utilize complementary proteogenomic approaches where RNA or ribosomal sequencing data helps to create libraries from which tandem mass spectrometry data can be compared. In this study, we present an alternative approach whereby cloud computing is utilized to power neo-antigen searches against community curated databases containing more than 7 million human sequence variants. Using these expansive databases of high-quality sequences as a reference, we reanalyze the original data from two previously reported studies to identify neo-antigen targets in metastatic melanoma. Using our approach, we identify 79 percent of the non-canonical peptides reported by previous genomic analyses of these files. Furthermore, we report 18-fold more non-canonical peptides than previously reported. The novel neo-antigens we report herein can be corroborated by secondary analyses such as high predicted binding affinity, when analyzed by well-established tools such as NetMHC. Finally, we report 738 non-canonical peptides shared by at least five patient samples, and 3258 shared across the two studies. This illustrates the depth of data that is present, but typically missed by lower statistical power proteogenomic approaches. This large list of shared peptides across the two studies, their annotation, non-canonical origin, as well as MS/MS spectra from the two studies are made available on a web portal for community analysis.

Direct identification of HLA-presented CD8 T cell epitopes from transmitted founder HIV-1 variants

Cytotoxic T lymphocytes (CTLs) are a critical arm of the immune response to viral infections. The activation and expansion of antigen specific CTL requires recognition of peptide antigens presented on class I major histocompatibility complex molecules (MHC-1) of infected cells. Methods to identify presented peptide antigens that do not rely on the pre-existence of antigen specific CTL are critical to the development of new vaccines. We infected activated CD4+ T cells with two HIV-1 transmitted founder (TF) isolates and used high-resolution mass spectrometry (MS) to identify HIV peptides bound on MHC-1. Using this approach, we identified 14 MHC-1 bound peptides from across the two TF isolates. Assessment of predicted binding thresholds revealed good association of the identified peptides to the shared HLA alleles between the HIV+ donors and the naïve PBMC sample with three peptides identified through peptide sequencing inducing a CD8 T-cell response (p < 0.05). Direct infection of naïve CD4 cells by HIV TF isolates and sequencing of MHC-I presented peptides by HPLC-MS/MS enables identification of novel peptides that may be missed by alternative epitope mapping strategies and can provide valuable insight in to the first peptides presented by an HIV-infected CD4 cell in the first few days post infection.

Deciphering Human Leukocyte Antigen Susceptibility Maps From Immunopeptidomics Characterization in Oncology and Infections

Genetic variability across the three major histocompatibility complex (MHC) class I genes (human leukocyte antigen [HLA] A, B, and C) may affect susceptibility to many diseases such as cancer, auto-immune or infectious diseases. Individual genetic variation may help to explain different immune responses to microorganisms across a population. HLA typing can be fast and inexpensive; however, deciphering peptides loaded on MHC-I and II which are presented to T cells, require the design and development of high-sensitivity methodological approaches and subsequently databases. Hence, these novel strategies and databases could help in the generation of vaccines using these potential immunogenic peptides and in identifying high-risk HLA types to be prioritized for vaccination programs. Herein, the recent developments and approaches, in this field, focusing on the identification of immunogenic peptides have been reviewed and the next steps to promote their translation into biomedical and clinical practice are discussed.

Incoming HIV virion-derived Gag Spacer Peptide 2 (p1) is a target of effective CD8+ T cell antiviral responses

Persistence of HIV through integration into host DNA in CD4+ T cells presents a major barrier to virus eradication. Viral integration may be curtailed when CD8+ T cells are triggered to kill infected CD4+ T cells through recognition of histocompatibility leukocyte antigen (HLA) class I-bound peptides derived from incoming virions. However, this has been reported only in individuals with "beneficial" HLA alleles that are associated with superior HIV control. Through interrogation of the pre-integration immunopeptidome, we obtain proof of early presentation of a virion-derived HLA-A∗02:01-restricted epitope, FLGKIWPSH (FH9), located in Gag Spacer Peptide 2 (SP2). FH9-specific CD8+ T cell responses are detectable in individuals with primary HIV infection and eliminate HIV-infected CD4+ T cells prior to virus production in vitro. Our data show that non-beneficial HLA class I alleles can elicit an effective antiviral response through early presentation of HIV virion-derived epitopes and also demonstrate the importance of SP2 as an immune target.

Integral Use of Immunopeptidomics and Immunoinformatics for the Characterization of Antigen Presentation and Rational Identification of BoLA-DR-Presented Peptides and Epitopes

MHC peptide binding and presentation is the most selective event defining the landscape of T cell epitopes. Consequently, understanding the diversity of MHC alleles in a given population and the parameters that define the set of ligands that can be bound and presented by each of these alleles (the immunopeptidome) has an enormous impact on our capacity to predict and manipulate the potential of protein Ags to elicit functional T cell responses. Liquid chromatography-mass spectrometry analysis of MHC-eluted ligand data has proven to be a powerful technique for identifying such peptidomes, and methods integrating such data for prediction of Ag presentation have reached a high level of accuracy for both MHC class I and class II. In this study, we demonstrate how these techniques and prediction methods can be readily extended to the bovine leukocyte Ag class II DR locus (BoLA-DR). BoLA-DR binding motifs were characterized by eluted ligand data derived from bovine cell lines expressing a range of DRB3 alleles prevalent in Holstein-Friesian populations. The model generated (NetBoLAIIpan, available as a Web server at www.cbs.dtu.dk/services/NetBoLAIIpan) was shown to have unprecedented predictive power to identify known BoLA-DR-restricted CD4 epitopes. In summary, the results demonstrate the power of an integrated approach combining advanced mass spectrometry peptidomics with immunoinformatics for characterization of the BoLA-DR Ag presentation system and provide a prediction tool that can be used to assist in rational evaluation and selection of bovine CD4 T cell epitopes.

HLA-E-restricted, Gag-specific CD8+ T cells can suppress HIV-1 infection, offering vaccine opportunities

Human leukocyte antigen-E (HLA-E) normally presents an HLA class Ia signal peptide to the NKG2A/C-CD94 regulatory receptors on natural killer (NK) cells and T cell subsets. Rhesus macaques immunized with a cytomegalovirus-vectored simian immunodeficiency virus (SIV) vaccine generated Mamu-E (HLA-E homolog)-restricted T cell responses that mediated post-challenge SIV replication arrest in >50% of animals. However, HIV-1-specific, HLA-E-restricted T cells have not been observed in HIV-1-infected individuals. Here, HLA-E-restricted, HIV-1-specific CD8 + T cells were primed in vitro. These T cell clones and allogeneic CD8 + T cells transduced with their T cell receptors suppressed HIV-1 replication in CD4 + T cells in vitro. Vaccine induction of efficacious HLA-E-restricted HIV-1-specific T cells should therefore be possible.

Critical Review of Existing MHC I Immunopeptidome Isolation Methods

Major histocompatibility complex class I (MHC I) plays a crucial role in the development of adaptive immune response in vertebrates. MHC molecules are cell surface protein complexes loaded with short peptides and recognized by the T-cell receptors (TCR). Peptides associated with MHC are named immunopeptidome. The MHC I immunopeptidome is produced by the proteasome degradation of intracellular proteins. The knowledge of the immunopeptidome repertoire facilitates the creation of personalized antitumor or antiviral vaccines. A huge number of publications on the immunopeptidome diversity of different human and mouse biological samples-plasma, peripheral blood mononuclear cells (PBMCs), and solid tissues, including tumors-appeared in the scientific journals in the last decade. Significant immunopeptidome identification efficiency was achieved by advances in technology: the immunoprecipitation of MHC and mass spectrometry-based approaches. Researchers optimized common strategies to isolate MHC-associated peptides for individual tasks. They published many protocols with differences in the amount and type of biological sample, amount of antibodies, type and amount of insoluble support, methods of post-fractionation and purification, and approaches to LC-MS/MS identification of immunopeptidome. These parameters have a large impact on the final repertoire of isolated immunopeptidome. In this review, we summarize and compare immunopeptidome isolation techniques with an emphasis on the results obtained.

HLA tapasin independence: broader peptide repertoire and HIV control

Human leukocyte antigen (HLA) class I allotypes vary in their ability to present peptides in the absence of tapasin, an essential component of the peptide loading complex. We quantified tapasin dependence of all allotypes that are common in European and African Americans (n = 97), which revealed a broad continuum of values. Ex vivo examination of cytotoxic T cell responses to the entire HIV-1 proteome from infected subjects indicates that tapasin-dependent allotypes present a more limited set of distinct peptides than do tapasin-independent allotypes, data supported by computational predictions. This suggests that variation in tapasin dependence may impact the strength of the immune responses by altering peptide repertoire size. In support of this model, we observed that individuals carrying HLA class I genotypes characterized by greater tapasin independence progress more slowly to AIDS and maintain lower viral loads, presumably due to increased breadth of peptide presentation. Thus, tapasin dependence level, like HLA zygosity, may serve as a means to restrict or expand breadth of the HLA-I peptide repertoire across humans, ultimately influencing immune responses to pathogens and vaccines.

Variations in MHC class I antigen presentation and immunopeptidome selection pathways

Major histocompatibility class I (MHC-I) proteins mediate immunosurveillance against pathogens and cancers by presenting antigenic or mutated peptides to antigen receptors of CD8+ T cells and by engaging receptors of natural killer (NK) cells. In humans, MHC-I molecules are highly polymorphic. MHC-I variations permit the display of thousands of distinct peptides at the cell surface. Recent mass spectrometric studies have revealed unique and shared characteristics of the peptidomes of individual MHC-I variants. The cell surface expression of MHC-I–peptide complexes requires the functions of many intracellular assembly factors, including the transporter associated with antigen presentation (TAP), tapasin, calreticulin, ERp57, TAP-binding protein related (TAPBPR), endoplasmic reticulum aminopeptidases (ERAPs), and the proteasomes. Recent studies provide important insights into the structural features of these factors that govern MHC-I assembly as well as the mechanisms underlying peptide exchange. Conformational sensing of MHC-I molecules mediates the quality control of intracellular MHC-I assembly and contributes to immune recognition by CD8 at the cell surface. Recent studies also show that several MHC-I variants can follow unconventional assembly routes to the cell surface, conferring selective immune advantages that can be exploited for immunotherapy.

Identification of Tumor Antigens in the HLA Peptidome of Patient-derived Xenograft Tumors in Mouse

Personalized cancer immunotherapy targeting patient-specific cancer/testis antigens (CTA) and neoantigens may benefit from large-scale tumor human leukocyte antigen (HLA) peptidome (immunopeptidome) analysis, which aims to accurately identify antigens presented by tumor cells. Although significant efforts have been invested in analyzing the HLA peptidomes of fresh tumors, it is often impossible to obtain sufficient volumes of tumor tissues for comprehensive HLA peptidome characterization. This work attempted to overcome some of these obstacles by using patient-derived xenograft tumors (PDX) in mice as the tissue sources for HLA peptidome analysis. PDX tumors provide a proxy for the expansion of the patient tumor by re-grafting them through several passages to immune-compromised mice. The HLA peptidomes of human biopsies were compared with those derived from PDX tumors. Larger HLA peptidomes were obtained from the significantly larger PDX tumors as compared with the patient biopsies. The HLA peptidomes of different PDX tumors derived from the same source tumor biopsy were very reproducible, even following subsequent passages to new naïve mice. Many CTA-derived HLA peptides were discovered, as well as several potential neoantigens/variant sequences. Taken together, the use of PDX tumors for HLA peptidome analysis serves as a highly expandable and stable source of reproducible and authentic peptidomes, opening up new opportunities for defining large HLA peptidomes when only small tumor biopsies are available. This approach provides a large source for tumor antigens identification, potentially useful for personalized immunotherapy.

Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST

Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants' times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST.IMPORTANCE The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.

Identification of antigens presented by MHC for vaccines against tuberculosis

Mycobacterium tuberculosis (M.tb) is responsible for more deaths globally than any other pathogen. The only available vaccine, bacillus Calmette-Guérin (BCG), has variable efficacy throughout the world. A more effective vaccine is urgently needed. The immune response against tuberculosis relies, at least in part, on CD4⁺ T cells. Protective vaccines require the induction of antigen-specific CD4⁺ T cells via mycobacterial peptides presented by MHC class-II in infected macrophages. In order to identify mycobacterial antigens bound to MHC, we have immunoprecipitated MHC class-I and class-II complexes from THP-1 macrophages infected with BCG, purified MHC class-I and MHC class-II peptides and analysed them by liquid chromatography tandem mass spectrometry. We have successfully identified 94 mycobacterial peptides presented by MHC-II and 43 presented by MHC-I, from 76 and 41 antigens, respectively. These antigens were found to be highly expressed in infected macrophages. Gene ontology analysis suggests most of these antigens are associated with membranes and involved in lipid biosynthesis and transport. The sequences of selected peptides were confirmed by spectral match validation and immunogenicity evaluated by IFN-gamma ELISpot against peripheral blood mononuclear cell from volunteers vaccinated with BCG, M.tb latently infected subjects or patients with tuberculosis disease. Three antigens were expressed in viral vectors, and evaluated as vaccine candidates alone or in combination in a murine aerosol M.tb challenge model. When delivered in combination, the three candidate vaccines conferred significant protection in the lungs and spleen compared with BCG alone, demonstrating proof-of-concept for this unbiased approach to identifying new candidate antigens.

Protective vaccines against Mycobacterium tuberculosis (M.tb), such as bacillus Calmette-Guérin (BCG), trigger strong CD4 T-cell responses specific to mycobacterium peptides, but their efficacy is variable. Paulo Bettencourt and colleagues now identify a set of mycobacterium peptides presented by BCG-infected macrophages via major compatibility complexes (MHC), and show that three of these antigens can be combined to formulate a vaccine that confers improved protection to Mtb infection in mice. After identifying 94 MHC-II-associated and 43 MHC-I-associated mycobacterium peptides, the researchers performed immunogenicity assays with peripheral blood mononuclear cells from BCG-vaccinated donors, latent Mtb-infected patients and patients with tuberculosis, and show that a set of these peptides was recognised by the immune cells, validating their potential as possible components for new Mtb vaccine formulations. These findings further support the value of immunopeptidomics for the identification of new antigens for effective vaccine alternatives.

Contribution of proteasome-catalyzed peptide cis-splicing to viral targeting by CD8+ T cells in HIV-1 infection

Peptides generated by proteasome-catalyzed splicing of noncontiguous amino acid sequences have been shown to constitute a source of nontemplated human leukocyte antigen class I (HLA-I) epitopes, but their role in pathogen-specific immunity remains unknown. CD8+ T cells are key mediators of HIV type 1 (HIV-1) control, and identification of novel epitopes to enhance targeting of infected cells is a priority for prophylactic and therapeutic strategies. To explore the contribution of proteasome-catalyzed peptide splicing (PCPS) to HIV-1 epitope generation, we developed a broadly applicable mass spectrometry-based discovery workflow that we employed to identify spliced HLA-I-bound peptides on HIV-infected cells. We demonstrate that HIV-1-derived spliced peptides comprise a relatively minor component of the HLA-I-bound viral immunopeptidome. Although spliced HIV-1 peptides may elicit CD8+ T cell responses relatively infrequently during infection, CD8+ T cells primed by partially overlapping contiguous epitopes in HIV-infected individuals were able to cross-recognize spliced viral peptides, suggesting a potential role for PCPS in restricting HIV-1 escape pathways. Vaccine-mediated priming of responses to spliced HIV-1 epitopes could thus provide a novel means of exploiting epitope targets typically underutilized during natural infection.

Identification of Immunodominant HIV-1 Epitopes Presented by HLA-C*12:02, a Protective Allele, Using an Immunopeptidomics Approach

Despite the fact that the cell surface expression level of HLA-C on both uninfected and HIV-infected cells is lower than those of HLA-A and -B, increasing evidence suggests an important role for HLA-C and HLA-C-restricted CD8⁺ T cell responses in determining the efficiency of viral control in HIV-1-infected individuals. Nonetheless, HLA-C-restricted T cell responses are much less well studied than HLA-A/B-restricted ones, and relatively few optimal HIV-1 CD8⁺ T cell epitopes restricted by HLA-C alleles have been defined. Recent improvements in the sensitivity of mass spectrometry (MS)-based approaches for profiling the immunopeptidome present an opportunity for epitope discovery on a large scale. Here, we employed an MS-based immunopeptidomic strategy to characterize HIV-1 peptides presented by a protective allele, HLA-C*12:02. We identified a total of 10,799 unique 8- to 12-mer peptides, including 15 HIV-1 peptides. The latter included 2 previously reported immunodominant HIV-1 epitopes, and analysis of T cell responses to the other HIV-1 peptides detected revealed an additional immunodominant epitope. These findings illustrate the utility of MS-based approaches for epitope definition and emphasize the capacity of HLA-C to present immunodominant T cell epitopes in HIV-infected individuals, indicating the importance of further evaluation of HLA-C-restricted responses to identify novel targets for HIV-1 prophylactic and therapeutic strategies.IMPORTANCE Mass spectrometry (MS)-based approaches are increasingly being employed for large-scale identification of HLA-bound peptides derived from pathogens, but only very limited profiling of the HIV-1 immunopeptidome has been conducted to date. Notably, a growing body of evidence has recently begun to indicate a protective role for HLA-C in HIV-1 infection, which may suggest that despite the fact that levels of HLA-C expression on both uninfected and HIV-1-infected cells are lower than those of HLA-A/B, HLA-C still presents epitopes to CD8⁺ T cells effectively. To explore this, we analyzed HLA-C*12:02-restricted HIV-1 peptides presented on HIV-1-infected cells expressing only HLA-C*12:02 (a protective allele) using liquid chromatography-tandem MS (LC-MS/MS). We identified a number of novel HLA-C*12:02-bound HIV-1 peptides and showed that although the majority of them did not elicit T cell responses during natural infection in a Japanese cohort, they included three immunodominant epitopes, emphasizing the contribution of HLA-C to epitope presentation on HIV-infected cells.

Mass spectrometry-based identification of MHC-bound peptides for immunopeptidomics

Peptide antigens bound to molecules encoded by the major histocompatibility complex (MHC) and presented on the cell surface form the targets of T lymphocytes. This critical arm of the adaptive immune system facilitates the eradication of pathogen-infected and cancerous cells, as well as the production of antibodies. Methods to identify these peptide antigens are critical to the development of new vaccines, for which the goal is the generation of effective adaptive immune responses and long-lasting immune memory. Here, we describe a robust protocol for the identification of MHC-bound peptides from cell lines and tissues, using nano-ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (nUPLC-MS/MS) and recent improvements in methods for isolation and characterization of these peptides. The protocol starts with the immunoaffinity capture of naturally processed MHC-peptide complexes. The peptides dissociate from the class I human leukocyte antigens (HLAs) upon acid denaturation. This peptide cargo is then extracted and separated into fractions by HPLC, and the peptides in these fractions are identified using nUPLC-MS/MS. With this protocol, several thousand peptides can be identified from a wide variety of cell types, including cancerous and infected cells and those from tissues, with a turnaround time of 2-3 d.

Identification of novel HIV-1-derived HLA-E-binding peptides

Non-classical class Ib MHC-E molecule is becoming an increasingly interesting component of the immune response. It is involved in both the adaptive and innate immune responses to several chronic infections including HIV-1 and, under very specific circumstances, likely mediated a unique vaccine protection of rhesus macaques against pathogenic SIV challenge. Despite being recently in the spotlight for HIV-1 vaccine development, to date there is only one reported human leukocyte antigen (HLA)-E-binding peptide derived from HIV-1. In an effort to help start understanding the possible functions of HLA-E in HIV-1 infection, we determined novel HLA-E binding peptides derived from HIV-1 Gag, Pol and Vif proteins. These peptides were identified in three independent assays, all quantifying cell-surface stabilization of HLA-E*01:01 or HLA-E*01:03 molecules upon peptide binding, which was detected by HLA-E-specific monoclonal antibody and flow cytometry. Thus, following initial screen of over 400 HIV-1-derived 15-mer peptides, 4 novel 9-mer peptides PM9, RL9, RV9 and TP9 derived from 15-mer binders specifically stabilized surface expression of HLA-E*01:03 on the cell surface in two separate assays and 5 other binding candidates EI9, MD9, NR9, QF9 and YG9 gave a binding signal in only one of the two assays, but not both. Overall, we have expanded the current knowledge of HIV-1-derived target peptides stabilizing HLA-E cell-surface expression from 1 to 5, thus broadening inroads for future studies. This is a small, but significant contribution towards studying the fine mechanisms behind HLA-E actions and their possible use in development of a new kind of vaccines.

Immunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens

The recent development in immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cells in the treatment of cancer has not only demonstrated the potency of utilizing T-cell reactivity for cancer therapy, but has also highlighted the need for developing new approaches to discover targets suitable for such novel therapeutics. Here we analyzed the immunopeptidomes of six HLA-A2-positive triple negative breast cancer (TNBC) samples by nano-ultra performance liquid chromatography tandem mass spectrometry (nUPLC-MS2 ). Immunopeptidomic profiling identified a total of 19 675 peptides from tumor and adjacent normal tissue and 130 of the peptides were found to have higher abundance in tumor than in normal tissues. To determine potential therapeutic target proteins, we calculated the average tumor-associated cohort coverage (aTaCC) that represents the percentage coverage of each protein in this cohort by peptides that had higher tumoral abundance. Cofilin-1 (CFL-1), interleukin-32 (IL-32), proliferating cell nuclear antigen (PCNA), syntenin-1 (SDCBP), and ribophorin-2 (RPN-2) were found to have the highest aTaCC scores. We propose that these antigens could be evaluated further for their potential as targets in breast cancer immunotherapy and the small cohort immunopeptidomics analysis technique could be used in a wide spectrum of target discovery. Data are available via ProteomeXchange with identifier PXD009738.