Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen ...presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.
Display omitted
•24,000 HLA class I peptides were identified through a scalable MS-based pipeline.•Mono-allelic data revealed binding motifs that were validated biochemically.•Comprehensive analyses provide an updated portrait of antigen processing rules.•Neural networks were trained for 16 alleles and outperform standard by 2-fold.
HLA class I binding prediction has traditionally been based on biochemical binding experiments. Abelin and colleagues present an LC-MS/MS-based workflow and analytical framework that greatly accelerates gains in prediction performance. Key advances include the discovery of sequence motifs and improved quantification of the roles of gene expression and proteasomal processing.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically ...measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.
Identifying immunodominant T cell epitopes remains a significant challenge in the context of infectious disease, autoimmunity, and immuno-oncology. To address the challenge of antigen discovery, we ...developed a quantitative proteomic approach that enabled unbiased identification of major histocompatibility complex class II (MHCII)-associated peptide epitopes and biochemical features of antigenicity. On the basis of these data, we trained a deep neural network model for genome-scale predictions of immunodominant MHCII-restricted epitopes. We named this model bacteria originated T cell antigen (BOTA) predictor. In validation studies, BOTA accurately predicted novel CD4 T cell epitopes derived from the model pathogen Listeria monocytogenes and the commensal microorganism Muribaculum intestinale. To conclusively define immunodominant T cell epitopes predicted by BOTA, we developed a high-throughput approach to screen DNA-encoded peptide-MHCII libraries for functional recognition by T cell receptors identified from single-cell RNA sequencing. Collectively, these studies provide a framework for defining the immunodominance landscape across a broad range of immune pathologies.
Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human ...leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.
Display omitted
•Affinity-tagging protocol enables proteomic profiling of individual HLA-II alleles•Even in “hot” tumors, professional APCs—not cancer cells—drive HLA-II expression•Cellular localization influences which phagocytosed cancer proteins get presented•Machine-learning models for binding and processing improve HLA-II prediction
Despite their role in directing T cell responses, HLA-II epitopes remain difficult to predict, hindering their therapeutic potential. Abelin et al. develop proteomic strategies that resolve diverse HLA-II motifs and pinpoint tumor epitopes that are presented by professional APCs. These data enable improved HLA-II epitope prediction and therapeutic targeting.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Deregulation of signaling pathways is a hallmark of malignant transformation. Signaling-associated phosphoproteins can be degraded to generate cancer-specific phosphopeptides that are presented by ...major histocompatibility complex (MHC) class I and II molecules and recognized by T cells; however, the contribution of these phosphoprotein-specific T cells to immune surveillance is unclear. We identified 95 phosphopeptides presented on the surface of primary hematological tumors and normal tissues, including 61 that were tumor-specific. Phosphopeptides were more prevalent on more aggressive and malignant samples. CD8(+) T cell lines specific for these phosphopeptides recognized and killed both leukemia cell lines and human leukocyte antigen-matched primary leukemia cells ex vivo. Notably, healthy individuals showed robust CD8(+) T cell responses against many of these phosphopeptides within the circulating memory compartment. This immunity was significantly reduced or absent in some leukemia patients. This reduction correlated with clinical outcome; however, immunity was restored after allogeneic stem cell transplantation. These results suggest that phosphopeptides may be targets of cancer immune surveillance in humans, and point to their importance for development of vaccine-based and T cell adoptive transfer immunotherapies.
A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer‐specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human ...leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA‐peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA‐ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA‐binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA‐ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes ...in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.
To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.
The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease ...pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each 'ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors.
Targeted synthetic vaccines have the potential to transform our response to viral outbreaks, yet the design of these vaccines requires a comprehensive knowledge of viral immunogens. Here, we report ...severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) peptides that are naturally processed and loaded onto human leukocyte antigen-II (HLA-II) complexes in infected cells. We identify over 500 unique viral peptides from canonical proteins as well as from overlapping internal open reading frames. Most HLA-II peptides colocalize with known CD4+ T cell epitopes in coronavirus disease 2019 patients, including 2 reported immunodominant regions in the SARS-CoV-2 membrane protein. Overall, our analyses show that HLA-I and HLA-II pathways target distinct viral proteins, with the structural proteins accounting for most of the HLA-II peptidome and nonstructural and noncanonical proteins accounting for the majority of the HLA-I peptidome. These findings highlight the need for a vaccine design that incorporates multiple viral elements harboring CD4+ and CD8+ T cell epitopes to maximize vaccine effectiveness.
Display omitted
•Immunopeptidome analysis of SARS-CoV-2 peptides naturally presented on HLA class II•Some HLA-II peptides originate from noncanonical SARS-CoV-2 proteins ORF9b and ORF3c•Class I and class II HLA complexes present different subsets of viral proteins
Weingarten-Gabbay et al. map the repertoire of SARS-CoV-2 peptides naturally presented on HLA-II. The authors uncover HLA-II peptides originating from noncanonical ORFs and highlight striking differences between viral proteins that are presented on class I and class II HLAs, resulting in distinct targets for killer and helper T cells.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the ...currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be “protein coding.”
Display omitted
•Ribo-seq paired with proteomics-based methods optimally detects noncanonical ORFs.•Data quality and analytical pipelines impact the output of a Ribo-seq experiment.•Noncanonical ORF catalogs variably report both high- and low-stringency nominations.•A framework for standardized noncanonical ORF evidence will advance the field.
The human genome encodes thousands of noncanonical ORFs along with protein-coding genes. As a nascent field, many questions about them remain: How many exist? Do they encode proteins? What evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-Seq) to discern genome-wide ribosome occupancy and immunopeptidomics to detect peptides presented by major histocompatibility complex molecules. This article synthesizes the current state of noncanonical ORF research and proposes standards for their future investigation and reporting.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PDF
