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Ternette, N.

Publications and source records attributed to Ternette, N..

15 recordsLinked to original sources

Simplifying principles that underlie the highly complex peptide motif of the promiscuous chicken class I molecule, BF2*21:01

In chickens and humans, classical class I molecules of the major histocompatibility complex (MHC) have a spectrum of correlated properties, including cell surface expression and peptide repertoire. Understanding the impact of these promiscuous generalists and fastidious specialists is of considerable interest. The promiscuous BF2 molecule from the chicken B21 haplotype, BF2*21:01, binds a wide range of peptides by remodelling the peptide-binding site, allowing co-variation of the anchor residues at peptide positions P2 and Pc-2, and binding of an anchor residue at Pc. Using in vitro refolding assays with peptides and peptide libraries, determining thermostability and crystal structures, and analysing a chicken B21 cell line by immunopeptidomics, we found that BF2*21:01 will accommodate many possible combinations at P2 and Pc-2, as well as several hydrophobic amino acids at Pc. However, marked preferences for particular peptide lengths, particular amino acids at the three anchor residues, and particular combinations of amino acids at P2 and Pc-2 as well as at P3 and Pc-3 together lead to high frequencies of major peptides while still allowing the possibility of presenting a wide peptide repertoire. These simplifying principles may eventually allow predictions of pathogen peptides with stable binding for this iconic promiscuous class I molecule, as well as providing the data for more sophisticated peptide prediction methods.

immunology↗

Coxsackievirus B Escapes Antiviral CD8⁺ T Cells but Triggers Robust CD4⁺ Memory Responses

Coxsackieviruses B (CVBs) are plausible triggers of the pancreatic islet autoimmunity leading to type 1 diabetes. Islet autoantibody seroconversion correlates with persistent CVB infections in the gut and pancreas, suggesting defective antiviral control and the need to define immune mechanisms at the intestinal entry site. We investigated how CVB3 modulates antigen presentation, the viral immunopeptidome of enterocytes and antigen-presenting cells, and downstream T-cell immunity. CVB3-infected enterocytes escaped immune recognition by downregulating HLA Class I and viral peptide presentation, impairing CD8+ T-cell responses in vitro. In CVB-seropositive individuals, circulating CVB-reactive CD8+ T cells were stalled in naive-like and exhausted effector/memory states. In contrast, CVB3 induced HLA class II upregulation, promoting robust CD4 T-cell activation. Circulating CVB3-reactive CD4 T cells fully differentiated into polyfunctional T helper memory. These findings indicate that CVB3 antiviral control is predominantly CD4 T-cell-mediated and provide a rationale for mucosal vaccination strategies and immune monitoring tools to follow infection or vaccination. TeaserCoxsackievirus evades CD8+ T-cell immunity in the gut, leaving CD4+ T cells as the main line of antiviral defense.

immunology↗

NetMHCIIphosPan: a machine learning tool for predictingHLA class II antigen presentation of phosphorylated peptides.

Phosphorylated peptides presented by human leukocyte antigen (HLA) class II molecules play pivotal roles in immune regulation, yet their characterization and prediction remain challenging due to data noise and limited HLA coverage. Here, we introduce NetMHCIIphosPan, a prediction method for HLA-II antigen presentation of phosphorylated peptides, developed using mass spectrometry (MS)-based immunopeptidomics datasets. Employing a refined peptide identification workflow, we reanalyzed earlier HLA-II phospholigand datasets and trained predictive models, achieving superior performance compared to models trained on original data. Binding motif analysis revealed that HLA-specific preferences for phospholigands closely aligned with those of unmodified ligands. Incorporating unmodified ligands into training further enhanced predictive accuracy, particularly for HLA-DP and HLA-DQ molecules. NetMHCIIphosPan outperformed existing tools, such as NetMHCIIpan-4.3 and MixMHC2pred-1.3, for prediction of HLA antigen presentation of phosphorylated peptides demonstrating robustness and utility. This work establishes NetMHCIIphosPan as a state-of-the-art tool for understanding the HLA-II phospholigandome, with potential applications in immunotherapy and vaccine design.

bioinformatics↗

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

molecular biology↗

Interferon-α promotes neo-antigen formation andpreferential HLA-B-restricted antigen presentation in pancreatic β-cells

Interferon (IFN)- is the earliest cytokine signature observed in individuals at risk for type 1 diabetes (T1D), but its effect on the repertoire of HLA Class I (HLA-I)-bound peptides presented by pancreatic {beta}-cells is unknown. Using immunopeptidomics, we characterized the peptide/HLA-I presentation in in-vitro resting and IFN--exposed {beta}-cells. IFN- increased HLA-I expression and peptide presentation, including neo-sequences derived from alternative mRNA splicing, post-translational modifications - notably glutathionylation - and protein cis-splicing. This antigenic landscape relied on processing by both the constitutive and immune proteasome. The resting {beta}-cell immunopeptidome was dominated by HLA-A-restricted ligands. However, IFN- only marginally upregulated HLA-A and largely favored HLA-B, translating into a major increase in HLA-B-restricted peptides and into an increased activation of HLA-B-restricted vs. HLA-A-restricted CD8+ T-cells. A preferential HLA-B hyper-expression was also observed in the islets of T1D vs. non-diabetic donors, and we identified islet-infiltrating CD8+ T-cells from T1D donors reactive to HLA-B-restricted granule peptides. Thus, the inflammatory milieu of insulitis may skew the autoimmune response toward epitopes presented by HLA-B, hence recruiting a distinct T-cell repertoire that may be relevant to T1D pathogenesis.

immunology↗

Identification of neoantigens in esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) has a relatively poor long-term survival and limited treatment options. Promising targets for immunotherapy are short peptide neoantigens containing tumor mutations, presented to cytotoxic T-cells by human leukocyte antigen molecules (HLA). Despite an association between putative neoantigen abundance and therapeutic response across cancers, immunogenic neoantigens are challenging to identify. Here we characterized the mutational and immunopeptidomic landscapes of tumors from a cohort of seven patients with EAC. We directly identified one HLA-I presented neoantigen from one patient, and report functional T-cell responses from a predicted HLA-II neoantigen in a second patient. The predicted class II neoantigen contains both HLA I and II binding motifs. Our exploratory observations are consistent with previous neoantigen studies in finding that neoantigens are rarely directly observed, and an identification success rate following prediction in the order of 10%. However, our identified putative neoantigen is capable of eliciting strong T-cell responses, emphasizing the need for improved strategies for neoantigen identification.

cancer biology↗

Minor differences in peptide presentation between chicken MHC class I molecules can explain differences in disease susceptibility

The highly polymorphic classical major histocompatibility complexes (MHCs) can confer resistance or susceptibility to diseases. The chicken MHC is known to confer decisive resistance or susceptibility to various economically-important pathogens, including the iconic oncogenic herpesvirus that causes Mareks disease (MD). Only one classical class I gene, BF2, is expressed at a high level in chickens, so it was relatively easy to discern a hierarchy from well-expressed thermostable fastidious specialist alleles to promiscuous generalist alleles that are less stable and expressed less on the cell surface. The BF2*1901 is more highly expressed and more thermostable than the closely-related BF2*1501, but the data for peptide repertoire available did not obviously correlate as expected. Here, we confirm for newly-developed chicken lines that the chicken haplotype B15 confers resistance to MD compared to B19. Using gas phase sequencing of peptide pools, and using immunopeptidomics involving mass spectroscopy, we find that the BF2*1901 binds a greater variety of amino acids in some anchor positions than BF2*1501. However, by X-ray crystallography, we find that the peptide-binding groove of BF2*1901 is narrower and shallower. Though the self-peptides bound to BF2*1901 may appear more various than those of BF2*1501, the structures show that the wider and deeper peptide-binding groove of BF2*1501 allows it to tightly accept many more peptides overall, correlating with the expected hierarchies for expression level, thermostability and MD resistance. Moreover, the 2 helix of BF2*1901 is higher than BF2*1501, potentially reducing the number of T cell clones that can recognize this fastidious class I molecule. IMPORTANCEDisease susceptibility mechanism is complicated, but chicken infection of Mareks disease (MD) is one of ideal models, considering the only one highly expressed classical MHC class I, BF2. The different susceptibility of the two close alleles BF2*1901 and BF2*1501 with minor difference of expression and thermostability is still unfathomed. Here, we confirm B15 chicken confers resistance to MD compared to B19. But the BF2*1901 binds a broader variety of anchoring peptides than BF2*1501. This mystery was solved by the structural determination of the two molecules with one similar peptide. The wider and deeper peptide-binding groove of BF2*1501 allows it to tightly accept many more peptides overall, which is concordant to the expected hierarchies for expression level, thermostability and MD resistance.

immunology↗

The viral vectored vaccine targeting Thymosin β10 controls tumour growth in a murine model of prostate cancer

Direct analysis of MHC-presented antigens by mass spectrometry has been successfully applied for the evaluation of the antigenic landscape of different human tissues and malignancies in the past. In the current study, for the first time this approach has been applied to investigate a murine prostate cancer peptidome for the development of next generation prostate cancer vaccines using the TRansgenic Adenocarcinoma of Mouse Prostate, TRAMP, model. We have performed immunopeptidomic analysis of the normal mouse prostate and mouse prostate adenocarcinoma samples and identified a number of peptides overexpressed on tumour tissue compared to the normal prostate. We selected two of these proteins previously reported to play a role in carcinogenesis, thymosin beta 4 (Thy{beta}4) and thymosin beta 10 (Thy{beta}10), expressed them in the chimpanzee adenovirus (ChAdOx1) and Modified Vaccinia Ankara (MVA) recombinant viral vectors and evaluated these constructs as a candidate prostate cancer vaccine in a murine prostate cancer model. We have found that the vaccine encoding the Thy{beta}10 polypeptide tethered to the MHC class II associated invariant chain, CD74, significantly delayed outgrowth of established tumours in an ectopic TRAMP-C1 mouse model of prostate cancer. The observed tumour-protective efficacy was not associated with Thy{beta}10-specific cellular or antibody responses, suggesting an existence of other mechanisms underlying anti-tumour effect in this model that are yet to be elucidated.

immunology↗

HLA binding of self-peptides is biased towards proteins with specific molecular functions

Human leukocyte antigen (HLA) is highly polymorphic and plays a key role in guiding adaptive immune responses by presenting foreign and self peptides to T cells. Each HLA variant selects a minor fraction of peptides that match a certain motif required for optimal interaction with the peptide-binding groove. These restriction rules define the landscape of peptides presented to T cells. Given these limitations, one might suggest that the choice of peptides presented by HLA is non-random and there is preferential presentation of an array of peptides that is optimal for distinguishing self and foreign proteins. In this study we explore these preferences with a comparative analysis of self peptides enriched and depleted in HLA ligands. We show that HLAs exhibit preferences towards presenting peptides from certain proteins while disfavoring others with specific functions, and highlight differences between various HLA genes and alleles in those preferences. We link those differences to HLA anchor residue propensities and amino acid composition of preferentially presented proteins. The set of proteins that peptides presented by a given HLA are most likely to be derived from can be used to distinguish between class I and class II HLAs and HLA alleles. Our observations can be extrapolated to explain the protective effect of certain HLA alleles in infectious diseases, and we hypothesize that they can also explain susceptibility to certain autoimmune diseases and cancers. We demonstrate that these differences lead to differential presentation of HIV, influenza virus, SARS-CoV-1 and SARS-CoV-2 proteins by various HLA alleles. Finally, we show that the reported self peptidome preferences of distinct HLA variants can be compensated by combinations of HLA-A/HLA-B and HLA-A/HLA-C alleles in frequent haplotypes.

bioinformatics↗

Integral use of immunopeptidomics and immunoinformatics for the characterization of antigen presentation and rational identification of BoLA-DR-presented peptides and epitopes

Major histocompatibility complex (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 antigens to elicit functional T cell responses. Liquid chromatography-mass spectrometry (LC-MS) analysis of MHC eluted ligands (EL data) has proven to be a powerful technique for identifying such peptidomes, and methods integrating such data for prediction of antigen presentation have reached a high level of accuracy for both MHC class I and class II. Here, we demonstrate how these techniques and prediction methods can be readily extended to the bovine leukocyte antigen class II DR locus (BoLA-DR). BoLA-DR binding motifs were characterized by EL data derived from 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 MS peptidomics with immunoinformatics for characterization of the BoLA-DR antigen presentation system and provide a novel tool that can be utilised to assist in rational evaluation and selection of bovine CD4 T cell epitopes.

bioinformatics↗

Mapping the SARS-CoV-2 spike glycoprotein-derived peptidome presented by HLA class II on dendritic cells

Understanding and eliciting protective immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an urgent priority. To facilitate these objectives, we have profiled the repertoire of human leukocyte antigen class II (HLA-II)-bound peptides presented by HLA-DR diverse monocyte-derived dendritic cells pulsed with SARS-CoV-2 spike (S) protein. We identify 209 unique HLA-II-bound peptide sequences, many forming nested sets, which map to sites throughout S including glycosylated regions. Comparison of the glycosylation profile of the S protein to that of the HLA-II-bound S peptides revealed substantial trimming of glycan residues on the latter, likely introduced during antigen processing. Our data also highlight the receptor-binding motif in S1 as a HLA-DR-binding peptide-rich region. Results from this study have application in vaccine design, and will aid analysis of CD4+ T cell responses in infected individuals and vaccine recipients.

immunology↗

Elucidating the signatures of proteasome-catalysed peptide splicing

Proteasomes catalyse the degradation of endogenous proteins into oligopeptides, but can concurrently create spliced oligopeptides through ligation of previously non-contiguous peptide fragments. Recent studies have uncovered a formerly unappreciated role for proteasome-catalysed peptide splicing (PCPS) in the generation of non-genomically templated human leukocyte antigen class I (HLA-I)-bound cis-spliced peptides that can be targeted by CD8+ T cells in cancer and infection. However, the mechanisms defining PCPS reactions are poorly understood. Here, we experimentally define the biochemical constraints of proteasome-catalysed cis-splicing reactions by examination of in vitro proteasomal digests of a panel of viral- and self-derived polypeptide substrates using a tailored mass-spectrometry-based de novo sequencing workflow. We show that forward and reverse PCPS reactions display unique splicing signatures, defined by preferential fusion of distinct amino acid residues with stringent peptide length distributions, suggesting sequence- and size-dependent accessibility of splice reactants for proteasomal substrate binding pockets. Our data provide the basis for a more informed mechanistic understanding of PCPS that will facilitate future prediction of spliced peptides from protein sequences.

immunology↗

NOD2 and TLR2 Signal via TBK1 and PI31 to Direct Cross-presentation and CD8 T Cell Responses

NOD2 and TLR2 recognize components of bacterial cell wall peptidoglycan and direct defense against enteric pathogens. CD8+ T cells are important for immunity to such pathogens but how NOD2 and TLR2 induce antigen specific CD8+ T cell responses is unknown. Here, we define how these pattern recognition receptors (PRRs) signal in primary dendritic cells (DCs) to influence MHC class I antigen presentation. We show NOD2 and TLR2 phosphorylate PI31 via TBK1 following activation in DCs. PI31 interacts with TBK1 and Sec16A at endoplasmic reticulum exit sites (ERES), which positively regulates MHC class I peptide loading and immunoproteasome stability. Following NOD2 and TLR2 stimulation, depletion of PI31 or inhibition of TBK1 activity in vivo impairs DC cross-presentation and CD8+ T cell activation. DCs from Crohns patients expressing NOD2 polymorphisms show dysregulated cross-presentation and CD8+ T cell responses. Our findings reveal unidentified mechanisms that underlie CD8+ T cell responses to bacteria in health and in Crohns.

immunology↗

NNAlign_MA; semi-supervised MHC peptidome deconvolution for accurate characterization of MHC binding motifs and improved T cell epitope prediction

Antigen presentation by Major Histocompatibility Complex (MHC) is a cornerstone of the cellular immune system, and characterization of the rules defining which peptides are suitable for MHC presentation is of key interest for understanding T cell immunogenicity and the development of T cell driven therapeutics. The collective set of peptides presented on a cell surface by MHC molecules is known as the immunopeptidome. Due to the vast MHC polymorphism, this peptidome is unique between individuals. Current state-of-the-art liquid chromatography mass spectrometry (LC-MS) technologies allow the identification of large peptidomes specific for a given host or cell line, and numerous studies have proven this data to be a rich source of information for learning the rules of MHC-mediated antigen presentation. The data obtained with MS techniques is usually poly-specific - i.e. it contains multiple sequence motifs matching the different MHC molecules expressed in the system under investigation. Deconvolution of this poly-specificity has proven a challenge, and imposes a substantial limitation for learning MHC specific rules for antigen presentation from immunopeptidome data. This since each ligand first must be unambiguously associated to its presenting MHC molecule(s) within the haplotype of the cell line. Here, we describe NNAlign_MA, a method that is able to address this challenge. NNAlign_MA is capable of taking a mixed training set composed of single-allele (SA) data (peptides assigned to single MHCs) and multi-allele (MA) data (peptides with multiple options for MHCs assignments) as input, and in a fully automated manner deconvolute the individual MHC restriction of all MA sequences while learning the binding specificities of all the MHCs present in the training set. The NNAlign_MA method was benchmarked on a large and diverse dataset, covering human MHC class I and class II, and bovine class I (BoLA) data. For all cases, the method was demonstrated to have unprecedented performance compared to state-of-the-art methods, achieving a complete deconvolution of binding motifs contained within poly-specificity MS eluted ligand data and an improved predictive performance for identification of both eluted ligands and T cell epitopes. Given its very high flexibility and ease of use, we expect NNAlign_MA to serve as an effective tool to increase our understanding of the rules for MHC antigen presentation and guide the development of novel T cell-based therapeutics.

bioinformatics↗

Improved prediction of Bovine Leucocyte Antigens (BoLA) presented ligands by use of MS eluted ligands and in-vitro binding data; impact for the identification T cell epitopes

Peptide binding to MHC class I molecules is the single most selective step in antigen presentation and the strongest single correlate to peptide cellular immunogenicity. The cost of experimentally characterizing the rules of peptide presentation for a given MHC-I molecule is extensive, and predictors of peptide-MHC interactions constitute an attractive alternative.\n\nRecently, an increasing amount of MHC presented peptides identified by mass spectrometry (MS ligands) has been published. Handling and interpretation of MS ligand data is in general challenging due to the poly-specificity nature of the data. We here outline a general pipeline for dealing with this challenge, and accurately annotate ligands to the relevant MHC-I molecule they were eluted from by use of GibbsClustering and binding motif information inferred from in-silico models. We illustrate the approach here in the context of MHCI molecules (BoLA) of cattle. Next, we demonstrate how such annotated BoLA MS ligand data can readily be integrated with in-vitro binding affinity data in a prediction model with very high and unprecedented performance for identification of BoLA-I restricted T cell epitopes.\n\nThe approach has here been applied to the BoLA-I system, but the pipeline is readily applicable to MHC systems in other species.

immunology↗