A subset of HLA-I peptides are not genomically templated: Evidence for cis- and trans-spliced peptide ligands

Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid De Novo Peptide Sequencing Framework

Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpected processing of RNAs and proteins. De novo peptide sequencing approaches address this limitation but often suffer from low accuracy and require extensive validation by experts. Here, we develop SMSNet, a deep learning-based de novo peptide sequencing framework that achieves >95% amino acid accuracy while retaining good identification coverage. Applications of SMSNet on landmark proteomics and peptidomics studies reveal over 10,000 previously uncharacterized HLA antigens and phosphopeptides, and in conjunction with database-search methods, expand the coverage of peptide identification by almost 30%. The power to accurately identify new peptides of SMSNet would make it an invaluable tool for any future proteomics and peptidomics studies, including tumor neoantigen discovery, antibody sequencing, and proteome characterization of non-model organisms.

An in silico-in vitro Pipeline Identifying an HLA-A*02:01+ KRAS G12V+ Spliced Epitope Candidate for a Broad Tumor-Immune Response in Cancer Patients

Targeting CD8⁺ T cells to recurrent tumor-specific mutations can profoundly contribute to cancer treatment. Some of these mutations are potential tumor antigens although they can be displayed by non-spliced epitopes only in a few patients, because of the low affinity of the mutated non-spliced peptides for the predominant HLA class I alleles. Here, we describe a pipeline that uses the large sequence variety of proteasome-generated spliced peptides and identifies spliced epitope candidates, which carry the mutations and bind the predominant HLA-I alleles with high affinity. They could be used in adoptive T cell therapy and other anti-cancer immunotherapies for large cohorts of cancer patients. As a proof of principle, the application of this pipeline led to the identification of a KRAS G12V mutation-carrying spliced epitope candidate, which is produced by proteasomes, transported by TAPs and efficiently presented by the most prevalent HLA class I molecules, HLA-A^*02:01 complexes.

Combination of Proteogenomics with Peptide De Novo Sequencing Identifies New Genes and Hidden Posttranscriptional Modifications

Next-generation sequencing techniques have considerably increased the number of completely sequenced eukaryotic genomes. These genomes are mostly automatically annotated, and ab initio gene prediction is commonly combined with homology-based search approaches and often supported by transcriptomic data. The latter in particular improve the prediction of intron splice sites and untranslated regions. However, correct prediction of translation initiation sites (TIS), alternative splice junctions, and protein-coding potential remains challenging. Here, we present an advanced proteogenomics approach, namely, the combination of proteogenomics and de novo peptide sequencing analysis, in conjunction with Blast2GO and phylostratigraphy. Using the model fungus Sordaria macrospora as an example, we provide a comprehensive view of the proteome that not only increases the functional understanding of this multicellular organism at different developmental stages but also immensely enhances the genome annotation quality.

Proteogenomics combines proteomics, genomics, and transcriptomics and has considerably improved genome annotation in poorly investigated phylogenetic groups for which homology information is lacking. Furthermore, it can be advantageous when reinvestigating well-annotated genomes. Here, we applied an advanced proteogenomics approach, combining standard proteogenomics with peptide de novo sequencing, to refine annotation of the well-studied model fungus Sordaria macrospora. We investigated samples from different developmental and physiological conditions, resulting in the detection of 104 so-far hidden proteins and annotation changes in 575 genes, including 389 splice site refinements. Significantly, our approach provides peptide-level evidence for 113 single-amino-acid variations and 15 C-terminal protein elongations originating from A-to-I RNA editing, a phenomenon recently detected in fungi. Coexpression and phylostratigraphic analysis of the refined proteome suggest that new functions in evolutionarily young genes correlate with distinct developmental stages. In conclusion, our advanced proteogenomics approach supports and promotes functional studies of fungal model systems.

The future of vaccine development

Vaccines are one of the most successful public health interventions in our history resulting in eradication of small pox, near eradication of polio and major reductions in case number and global morbidity and mortality for numerous diseases (Centers for Disease C, 1999) [1]. However, vaccine development has been less successful against complex infectious diseases, where pathogen variability and/or immune evasion mechanisms have combined to pose major obstacles, and have been unsuccessful against non-communicable diseases, including cancer, autoimmunity, allergy, neurodegenerative and metabolic diseases (Koff et al., 2013) [2]. In addition, the current state of vaccine development is an expensive, slow and laborious process, costing billions of dollars, taking decades, with less than a 10% rate of success (Pronker et al., 2013) [3]. While some vaccines, such as the smallpox vaccine approach the gold standard of life-long protection in everyone following a single immunization, other vaccines are less effective, often requiring multiple immunizations, being less effective to populations most susceptible to disease such as infants, the elderly, and those living in the developing world. There is clearly an urgent need to determine ways to improve not just the effectiveness of the vaccines themselves but also the very processes by which they are developed.

Proteogenomic discovery of cancer antigens: Neoantigens and beyond

Host T cells infiltrate the cancer lesion and contribute to patient survival. T cells recognize antigen peptides displayed by the cancer cell human leukocyte antigen (HLA) system. Cancer antigens constitute an essential element of T-cell discrimination and play an indispensable role in anti-cancer responses. HLA ligandome analysis directly and comprehensively detects the peptides that are naturally presented by HLA of given cells, leading to discovery of cancer antigens. A proteogenomic approach, which combines conventional proteomics with genomic information, has further deciphered the landscape of the cancer HLA ligandome. Neoantigens that arise from somatic mutations are arguably the major type of peptides patient T cells recognize. Moreover, cancer cells present peptides derived from alleged noncoding regions, which also elicit T-cell responses thereby serving as cancer antigens. The diversity of newly discovered antigen sources implies that T cells are capable of sensing a variety of genomic aberrations in cancer.

Proteogenomics: advances in cancer antigen research

T cells recognize antigen peptides displayed by HLA molecules and specifically eliminate their target cells. Identification of responsible antigens as well as understanding the mechanism by which antigens are produced inside cells are equally crucial for cancer immunology. In this review, we introduce proteogenomics and its applications in cancer antigen research, which leverages mass spectrometry and next-generation sequencing. The approach comprehensively captures immunopeptidome displayed by HLA, revealing new classes of antigens, such as mutation-derived neoantigens, spliced peptides, and non-coding region derived peptides. These antigens may serve as therapeutic targets or biomarkers. Thus, proteogenomics is a promising approach for cancer antigen research and contributes to immunotherapy development.

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

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

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

HIPs and HIP-reactive T cells

Mounting evidence implicates hybrid insulin peptides (HIPs) as important autoantigens in the development of type 1 diabetes (T1D). These fusion peptides formed between insulin and other pancreatic beta cell-derived peptides contain non-genomically encoded amino acid sequences, making them plausible targets for autoreactive T cells in T1D. HIPs are detectable by mass spectrometry in human and murine islets and are targeted by diabetes-inducing T cells in non-obese diabetic mice as well as by T cells isolated from the residual pancreatic islets of human organ donors with T1D. The discovery of HIPs comes with numerous new challenges, as well as opportunities to study the pathogenesis of T1D. Here we review the original discovery of HIPs and describe recent studies investigating the role of HIP-reactive T cells in the development of diabetes. We also discuss potential mechanisms that may be responsible for the generation of HIPs in beta cells and describe challenges that need to be addressed in the field of mass spectrometry to enable the discovery of new HIPs. The identification of these potentially disease-driving antigens in T1D is of key interest to the field as it may provide new tools to predict, prevent and potentially reverse the disease.

The Evolving Landscape of Autoantigen Discovery and Characterization in Type 1 Diabetes

Type 1 diabetes (T1D) is an autoimmune disease that is caused, in part, by T cell-mediated destruction of insulin-producing β-cells. High risk for disease, in those with genetic susceptibility, is predicted by the presence of two or more autoantibodies against insulin, the 65-kDa form of glutamic acid decarboxylase (GAD65), insulinoma-associated protein 2 (IA-2), and zinc transporter 8 (ZnT8). Despite this knowledge, we still do not know what leads to the breakdown of tolerance to these autoantigens, and we have an incomplete understanding of T1D etiology and pathophysiology. Several new autoantibodies have recently been discovered using innovative technologies, but neither their potential utility in monitoring disease development and treatment nor their role in the pathophysiology and etiology of T1D has been explored. Moreover, neoantigen generation (through posttranslational modification, the formation of hybrid peptides containing two distinct regions of an antigen or antigens, alternative open reading frame usage, and translation of RNA splicing variants) has been reported, and autoreactive T cells that target these neoantigens have been identified. Collectively, these new studies provide a conceptual framework to understand the breakdown of self-tolerance, if such modifications occur in a tissue- or disease-specific context. A recent workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases brought together investigators who are using new methods and technologies to identify autoantigens and characterize immune responses toward these proteins. Researchers with diverse expertise shared ideas and identified resources to accelerate antigen discovery and the detection of autoimmune responses in T1D. The application of this knowledge will direct strategies for the identification of improved biomarkers for disease progression and treatment response monitoring and, ultimately, will form the foundation for novel antigen-specific therapeutics. This Perspective highlights the key issues that were addressed at the workshop and identifies areas for future investigation.

How C-terminal additions to insulin B-chain fragments create superagonists for T cells in mouse and human type 1 diabetes

In type 1 diabetes (T1D), proinsulin is a major autoantigen and the insulin B:9-23 peptide contains epitopes for CD4+ T cells in both mice and humans. This peptide requires carboxyl-terminal mutations for uniform binding in the proper position within the mouse IAg7 or human DQ8 major histocompatibility complex (MHC) class II (MHCII) peptide grooves and for strong CD4+ T cell stimulation. Here, we present crystal structures showing how these mutations control CD4+ T cell receptor (TCR) binding to these MHCII-peptide complexes. Our data reveal stricking similarities between mouse and human CD4+ TCRs in their interactions with these ligands. We also show how fusions between fragments of B:9-23 and of proinsulin C-peptide create chimeric peptides with activities as strong or stronger than the mutated insulin peptides. We propose transpeptidation in the lysosome as a mechanism that could accomplish these fusions in vivo, similar to the creation of fused peptide epitopes for MHCI presentation shown to occur by transpeptidation in the proteasome. Were this mechanism limited to the pancreas and absent in the thymus, it could provide an explanation for how diabetogenic T cells escape negative selection during development but find their modified target antigens in the pancreas to cause T1D.

Proteolytic dynamics of human 20S thymoproteasome

An efficient immunosurveillance of CD8⁺ T cells in the periphery depends on positive/negative selection of thymocytes and thus on the dynamics of antigen degradation and epitope production by thymoproteasome and immunoproteasome in the thymus. Although studies in mouse systems have shown how thymoproteasome activity differs from that of immunoproteasome and strongly impacts the T cell repertoire, the proteolytic dynamics and the regulation of human thymoproteasome are unknown. By combining biochemical and computational modeling approaches, we show here that human 20S thymoproteasome and immunoproteasome differ not only in the proteolytic activity of the catalytic sites but also in the peptide transport. These differences impinge upon the quantity of peptide products rather than where the substrates are cleaved. The comparison of the two human 20S proteasome isoforms depicts different processing of antigens that are associated to tumors and autoimmune diseases.

Most viral peptides displayed by class I MHC on infected cells are immunogenic

CD8+ T cells are essential effectors in antiviral immunity, recognizing short virus-derived peptides presented by MHC class I (pMHCI) on the surface of infected cells. However, the fraction of viral pMHCI on infected cells that are immunogenic has not been shown for any virus. To approach this fundamental question, we used peptide sequencing by high-resolution mass spectrometry to identify more than 170 vaccinia virus pMHCI presented on infected mouse cells. Next, we screened each peptide for immunogenicity in multiple virus-infected mice, revealing a wide range of immunogenicities. A surprisingly high fraction (>80%) of pMHCI were immunogenic in at least one infected mouse, and nearly 40% were immunogenic across more than half of the mice screened. The high number of peptides found to be immunogenic and the distribution of responses across mice give us insight into the specificity of antiviral CD8+ T cell responses.

Identification of Hybrid Insulin Peptides (HIPs) in Mouse and Human Islets by Mass Spectrometry

We recently discovered hybrid insulin peptides (HIPs) as a novel class of post-translationally modified peptides in murine-derived beta cell tumors, and we demonstrated that these molecules are autoantigens in type 1 diabetes (T1D). A HIP consists of an insulin fragment linked to another secretory granule peptide via a peptide bond. We verified that autoreactive CD4 T cells in both mouse and human autoimmune diabetes recognize these modified peptides. Here, we use mass spectrometric analyses to confirm the presence of HIPs in both mouse and human pancreatic islets. We also present criteria for the confident identification of these peptides. This work supports the hypothesis that HIPs are autoantigens in human T1D and provides a foundation for future efforts to interrogate this previously unknown component of the beta cell proteome.

Mapping the MHC Class I-Spliced Immunopeptidome of Cancer Cells

Anticancer immunotherapies demand optimal epitope targets, which could include proteasome-generated spliced peptides if tumor cells were to present them. Here, we show that spliced peptides are widely presented by MHC class I molecules of colon and breast carcinoma cell lines. The peptides derive from hot spots within antigens and enlarge the antigen coverage. Spliced peptides also represent a large number of antigens that would otherwise be neglected by patrolling T cells. These antigens tend to be long, hydrophobic, and basic. Thus, spliced peptides can be a key to identifying targets in an enlarged pool of antigens associated with cancer.

A Review on T Cell Epitopes Identified Using Prediction and Cell-Mediated Immune Models for Mycobacterium tuberculosis and Bordetella pertussis

In the present review, we summarize work from our as well as other groups related to the characterization of bacterial T cell epitopes, with a specific focus on two important pathogens, namely, Mycobacterium tuberculosis (Mtb), the bacterium that causes tuberculosis (TB), and Bordetella pertussis (BP), the bacterium that causes whooping cough. Both bacteria and their associated diseases are of large societal significance. Although vaccines exist for both pathogens, their efficacy is incomplete. It is widely thought that defects and/or alteration in T cell compartments are associated with limited vaccine effectiveness. As discussed below, a full genome-wide map was performed in the case of Mtb. For BP, our focus has thus far been on the antigens contained in the acellular vaccine; a full genome-wide screen is in the planning stage. Nevertheless, the sum-total of the results in the two different bacterial systems allows us to exemplify approaches and techniques that we believe are generally applicable to the mapping and characterization of human immune responses to bacterial pathogens. Finally, we add, as a disclaimer, that this review by design is focused on the work produced by our laboratory as an illustration of approaches to the study of T cell responses to Mtb and BP, and is not meant to be comprehensive, nor to detract from the excellent work performed by many other groups.