T-Scan: A Genome-wide Method for the Systematic Discovery of T Cell Epitopes.

T cell recognition of specific antigens mediates protection from pathogens and controls neoplasias, but can also cause autoimmunity. Our knowledge of T cell antigens and their implications for human health is limited by the technical limitations of T cell profiling technologies. Here, we present T-Scan, a high-throughput platform for identification of antigens productively recognized by T cells. T-Scan uses lentiviral delivery of antigen libraries into cells for endogenous processing and presentation on major histocompatibility complex (MHC) molecules. Target cells functionally recognized by T cells are isolated using a reporter for granzyme B activity, and the antigens mediating recognition are identified by next-generation sequencing. We show T-Scan correctly identifies cognate antigens of T cell receptors (TCRs) from viral and human genome-wide libraries. We apply T-Scan to discover new viral antigens, perform high-resolution mapping of TCR specificity, and characterize the reactivity of a tumor-derived TCR. T-Scan is a powerful approach for studying T cell responses.

Spheromers reveal robust T cell responses to the Pfizer/BioNTech vaccine and attenuated peripheral CD8+ T cell responses post SARS-CoV-2 infection.

T cells are a critical component of the response to SARS-CoV-2, but their kinetics after infection and vaccination are insufficiently understood. Using "spheromer" peptide-MHC multimer reagents, we analyzed healthy subjects receiving two doses of the Pfizer/BioNTech BNT162b2 vaccine. Vaccination resulted in robust spike-specific T cell responses for the dominant CD4+ (HLA-DRB1∗15:01/S191) and CD8+ (HLA-A∗02/S691) T cell epitopes. Antigen-specific CD4+ and CD8+ T cell responses were asynchronous, with the peak CD4+ T cell responses occurring 1 week post the second vaccination (boost), whereas CD8+ T cells peaked 2 weeks later. These peripheral T cell responses were elevated compared with COVID-19 patients. We also found that previous SARS-CoV-2 infection resulted in decreased CD8+ T cell activation and expansion, suggesting that previous infection can influence the T cell response to vaccination.

ConvNeXt-MHC: improving MHC-peptide affinity prediction by structure-derived degenerate coding and the ConvNeXt model.

Peptide binding to major histocompatibility complex (MHC) proteins plays a critical role in T-cell recognition and the specificity of the immune response. Experimental validation such peptides is extremely resource-intensive. As a result, accurate computational prediction of binding peptides is highly important, particularly in the context of cancer immunotherapy applications, such as the identification of neoantigens. In recent years, there is a significant need to continually improve the existing prediction methods to meet the demands of this field. We developed ConvNeXt-MHC, a method for predicting MHC-I-peptide binding affinity. It introduces a degenerate encoding approach to enhance well-established panspecific methods and integrates transfer learning and semi-supervised learning methods into the cutting-edge deep learning framework ConvNeXt. Comprehensive benchmark results demonstrate that ConvNeXt-MHC outperforms state-of-the-art methods in terms of accuracy. We expect that ConvNeXt-MHC will help us foster new discoveries in the field of immunoinformatics in the distant future. We constructed a user-friendly website at http://www.combio-lezhang.online/predict/, where users can access our data and application.

Peptide-binding specificity prediction using fine-tuned protein structure prediction networks.

Peptide-binding proteins play key roles in biology, and predicting their binding specificity is a long-standing challenge. While considerable protein structural information is available, the most successful current methods use sequence information alone, in part because it has been a challenge to model the subtle structural changes accompanying sequence substitutions. Protein structure prediction networks such as AlphaFold model sequence-structure relationships very accurately, and we reasoned that if it were possible to specifically train such networks on binding data, more generalizable models could be created. We show that placing a classifier on top of the AlphaFold network and fine-tuning the combined network parameters for both classification and structure prediction accuracy leads to a model with strong generalizable performance on a wide range of Class I and Class II peptide-MHC interactions that approaches the overall performance of the state-of-the-art NetMHCpan sequence-based method. The peptide-MHC optimized model shows excellent performance in distinguishing binding and non-binding peptides to SH3 and PDZ domains. This ability to generalize well beyond the training set far exceeds that of sequence-only models and should be particularly powerful for systems where less experimental data are available.

Local Cellular and Cytokine Cues in the Spleen Regulate In Situ T Cell Receptor Affinity, Function, and Fate of CD8+ T Cells.

T cells rapidly undergo contraction upon viral clearance, but how T cell function and fate are determined during this phase is unclear. During the contraction phase of an acute infection with lymphocytic choriomeningitis virus, we found that virus-specific CD8+ T cells within the splenic red pulp (RP) had higher two-dimensional (2D) effective affinity than those within the white pulp (WP). This increased antigen recognition of RP-derived CD8+ T cells correlated with more efficient target cell killing and improved control of viremia. FoxP3+ regulatory T cells and cytokine TGF-ß limited the 2D-affinity in the WP during the contraction phase. Anatomical location drove gene expression patterns in CD8+ T cells that led to preferential differentiation of memory precursor WP T cells into long-term memory cells. These results highlight that intricate regulation of T cell function and fate is determined by anatomic compartmentalization during the early immune contraction phase.

V-CARMA: A tool for the detection and modification of antigen-specific T cells.

T cells promote our body's ability to battle cancers and infectious diseases but can act pathologically in autoimmunity. The recognition of peptides presented by major histocompatibility complex (pMHC) molecules by T cell receptors (TCRs) enables T cell-mediated responses. To modify disease-relevant T cells, new tools to genetically modify T cells and decode their antigen recognition are needed. Here, we present an approach using viruses pseudotyped with peptides loaded on MHC called V-CARMA (Viral ChimAeric Receptor MHC-Antigen) to specifically target T cells expressing cognate TCRs for antigen discovery and T cell engineering. We show that lentiviruses displaying antigens on human leukocyte antigen (HLA) class I and class II molecules can robustly infect CD8+ and CD4+ T cells expressing cognate TCRs, respectively. The infection rates of the pseudotyped lentiviruses (PLVs) are correlated with the binding affinity of the TCR to its cognate antigen. Furthermore, peptide-HLA pseudotyped lentivirus V-CARMA constructs can identify target cells from a mixed T cell population, suppress PD-1 expression on CD8+ T cells via PDCD1 shRNA delivery, and induce apoptosis in autoreactive CD4+ T cells. Thus, V-CARMA is a versatile tool for TCR ligand identification and selective T cell manipulation.

Activation and differentiation of cognate T cells by a dextran-based antigen-presenting system for cancer immunotherapy.

Immunotherapeutic modulation of antigen-specific T-cell responses instead of the whole repertoire helps avoid immune-related adverse events. We have developed an artificial antigen-presenting system (aAPS) where multiple copies of a multimeric peptide-MHC class I complex presenting a murine class I MHC restricted ovalbumin-derived peptide (signal 1), along with a costimulatory ligand (signal 2) are chemically conjugated to a dextran backbone. Cognate naive CD8+ T cells, when treated with this aAPS underwent significant expansion and showed an activated phenotype. Furthermore, elevated expression of effector cytokines led to the differentiation of these cells to cytotoxic T lymphocytes which resulted in target cell lysis, indicative of the functional efficacy of the aAPS. CD8+ T cells with decreased proliferative potential due to repeated antigenic stimulation could also be re-expanded by the developed aAPS. Thus, the developed aAPS warrants further engineering for future application as a rapidly customizable personalized immunotherapeutic agent, incorporating patient-specific MHC-restricted tumor antigens and different costimulatory signals to modulate both naive and antigen-experienced but exhausted tumor-specific T cells in cancer.

Peptide mimotopes alter T cell function in cancer and autoimmunity.

T cells recognize and respond to self antigens in both cancer and autoimmunity. One strategy to influence this response is to incorporate amino acid substitutions into these T cell-specific epitopes. This strategy is being reconsidered now with the goal of increasing time to regression with checkpoint blockade therapies in cancer and antigen-specific immunotherapies in autoimmunity. We discuss how these amino acid substitutions change the interactions with the MHC class I or II molecule and the responding T cell repertoire. Amino acid substitutions in epitopes that are the most effective in therapies bind more strongly to T cell receptor and/or MHC molecules and cross-react with the same repertoire of T cells as the natural antigen.

Structures suggest an approach for converting weak self-peptide tumor antigens into superagonists for CD8 T cells in cancer.

Tumors frequently express unmutated self-tumor-associated antigens (self-TAAs). However, trial results using self-TAAs as vaccine targets against cancer are mixed, often attributed to deletion of T cells with high-affinity receptors (TCRs) for self-TAAs during T cell development. Mutating these weak self-TAAs to produce higher affinity, effective vaccines is challenging, since the mutations may not benefit all members of the broad self-TAA-specific T cell repertoire. We previously identified a common weak murine self-TAA that we converted to a highly effective antitumor vaccine by a single amino acid substitution. In this case the modified and natural self-TAAs still raised very similar sets of CD8 T cells. Our structural studies herein show that the modification of the self-TAA resulted in a subtle change in the major histocompatibility complex I-TAA structure. This amino acid substitution allowed a dramatic conformational change in the peptide during subsequent TCR engagement, creating a large increase in TCR affinity and accounting for the efficacy of the modified self-TAA as a vaccine. These results show that carefully selected, well-characterized modifications to a poorly immunogenic self-TAA can rescue the immune response of the large repertoire of weakly responding natural self-TAA-specific CD8 T cells, driving them to proliferate and differentiate into functional effectors. Subsequently, the unmodified self-TAA on the tumor cells, while unable to drive this response, is nevertheless a sufficient target for the CD8 cytotoxic effectors. Our results suggest a pathway for more efficiently identifying variants of common self-TAAs, which could be useful in vaccine development, complementing other current nonantigen-specific immunotherapies.

MHCBI: a pipeline for calculating peptide-MHC binding energy using semi-empirical quantum mechanical methods with explicit/implicit solvent models.

Experimentally estimating peptide-major histocompatibility complex (pMHC) binding affinity has been quite challenging due to the many receptors and the many potential ligands implicated in it. We have thus proposed a straightforward computational methodology considering the different mechanisms involved in pMHC binding to facilitate studying such receptor-ligand interactions. We have developed a pipeline using semi-empirical quantum mechanical methods for calculating pMHC class I and II molecules' binding energy (BE). This pipeline can systematize the methodology for calculating pMHC system BE, enabling the rational design of T-cell epitopes to be used as pharmaceuticals and vaccines.

Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes.

Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide-MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide-MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide-MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.

Antibody-mediated delivery of a viral MHC-I epitope into the cytosol of target tumor cells repurposes virus-specific CD8+ T cells for cancer immunotherapy.

BACKGROUND: Redirecting pre-existing virus-specific cytotoxic CD8+ T lymphocytes (CTLs) to tumors by simulating a viral infection of the tumor cells has great potential for cancer immunotherapy. However, this strategy is limited by lack of amenable method for viral antigen delivery into the cytosol of target tumors. Here, we addressed the limit by developing a CD8+ T cell epitope-delivering antibody, termed a TEDbody, which was engineered to deliver a viral MHC-I epitope peptide into the cytosol of target tumor cells by fusion with a tumor-specific cytosol-penetrating antibody. METHODS: To direct human cytomegalovirus (CMV)-specific CTLs against tumors, we designed a series of TEDbodies carrying various CMV pp65 antigen-derived peptides. CMV-specific CTLs from blood of CMV-seropositive healthy donors were expanded for use in in vitro and in vivo experiments. Comprehensive cellular assays were performed to determine the presentation mechanism of TEDbody-mediated CMV peptide-MHC-I complex (CMV-pMHCI) on the surface of target tumor cells and the recognition and lysis by CMV-specific CTLs. In vivo CMV-pMHCI presentation and antitumor efficacy of TEDbody were evaluated in immunodeficient mice bearing human tumors. RESULTS: TEDbody delivered the fused epitope peptides into target tumor cells to be intracellularly processed and surface displayed in the form of CMV-pMHCI, leading to disguise target tumor cells as virally infected cells for recognition and lysis by CMV-specific CTLs. When systemically injected into tumor-bearing immunodeficient mice, TEDbody efficiently marked tumor cells with CMV-pMHCI to augment the proliferation and cytotoxic property of tumor-infiltrated CMV-specific CTLs, resulting in significant inhibition of the in vivo tumor growth by redirecting adoptively transferred CMV-specific CTLs. Further, combination of TEDbody with anti-OX40 agonistic antibody substantially enhanced the in vivo antitumor activity. CONCLUSION: Our study offers an effective technology for MHC-I antigen cytosolic delivery. TEDbody may thus have utility as a therapeutic cancer vaccine to redirect pre-existing anti-viral CTLs arising from previously exposed viral infections to attack tumors.

Opposing peripheral fates of tissue-restricted self antigen-specific conventional and regulatory CD4+ T cells.

The development of self antigen-specific T cells is influenced by how the self antigen is expressed. Here, we created a mouse in which a model self antigen is conditionally expressed in different tissue environments. Using peptide:MHCII tetramer-based cell enrichment methods, we examined the development of corresponding endogenous self antigen-specific CD4+ T cell populations. While ubiquitous self antigen expression resulted in efficient deletion of self antigen-specific T cells in the thymus, some tissue-restricted expression patterns resulted in partial deletion of the population in peripheral lymphoid organs. Deletion specifically affected Foxp3- conventional T cells (Tconv) with a bias towards high avidity TCR expressing cells in the case of thymic, but not peripheral deletion. In contrast, Foxp3+ Treg exhibited elevated frequencies with increased TCR avidity. T cells surviving deletion were functionally impaired, with Tconv cells exhibiting more impairment than Tregs. Collectively, our results illustrate how postthymic recognition of tissue-restricted self antigens results in opposing developmental fates for Tconv and Treg cell subsets.

Possible role of HLA class-I genotype in SARS-CoV-2 infection and progression: A pilot study in a cohort of Covid-19 Spanish patients.

Human Leukocyte Antigen (HLA) includes a large set of genes with important actions in immune response against viral infection. Numerous studies have revealed the existence of significant associations between certain HLA alleles and the susceptibility and prognosis of different infectious diseases. In this pilot study we analyse the binding affinity between 66 class I HLA alleles and SARS-CoV-2 viral peptides, and its association with the severity of the disease. A total of 45 Spanish patients with mild, moderate and severe SARS-CoV-2 infection were typed for HLA class I; after that, we analysed if an in silico model of HLA I-viral peptide binding affinity and classical HLA supertypes could be correlated to the severity of the disease. Our results suggest that patients with mild disease present Class I HLA molecules with a higher theoretical capacity for binding SARS-Cov-2 peptides and showed greater heterozygosity when comparing them with moderate and severe groups. In this regard, identifying HLA-SARS-CoV-2 peptides binding differences between individuals would help to clarify the heterogeneity of clinical responses to the disease and will also be useful to guide a personalized treatment according to its particular risk.

IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen-specific T cell receptors (TCRs). However, current wet-lab assays for identifying peptide MHC binding are too expensive and time-consuming to meet the clinical needs. In this study, we developed an in silico method with a deep convolutional neural network (CNN) model, iConMHC, to predict peptide MHC binding affinity. Unlike other in silico methods that only learn from properties of amino acid in neoantigen peptides alone and/or MHCs alone, iConMHC learns from physical and chemical interaction properties between pairwise amino acids from the two molecules. These properties, such as contact potentials and distances in folded proteins, directly affect neoantigen-MHC binding affinity. In addition, IConMHC is a pan-allele model that is capable of making predictions for all the MHC alleles. Even for those rare MHC alleles without training data, iConMHC can make predictions with reasonable accuracy. We benchmarked iConMHC with other commonly used MHC-I binding predictors and found our model performs better than most of the pan-allele models.

How an alloreactive T-cell receptor achieves peptide and MHC specificity.

T-cell receptor (TCR) allorecognition is often presumed to be relatively nonspecific, attributable to either a TCR focus on exposed major histocompatibility complex (MHC) polymorphisms or the degenerate recognition of allopeptides. However, paradoxically, alloreactivity can proceed with high peptide and MHC specificity. Although the underlying mechanisms remain unclear, the existence of highly specific alloreactive TCRs has led to their use as immunotherapeutics that can circumvent central tolerance and limit graft-versus-host disease. Here, we show how an alloreactive TCR achieves peptide and MHC specificity. The HCV1406 TCR was cloned from T cells that expanded when a hepatitis C virus (HCV)-infected HLA-A2- individual received an HLA-A2+ liver allograft. HCV1406 was subsequently shown to recognize the HCV nonstructural protein 3 (NS3):1406-1415 epitope with high specificity when presented by HLA-A2. We show that NS3/HLA-A2 recognition by the HCV1406 TCR is critically dependent on features unique to both the allo-MHC and the NS3 epitope. We also find cooperativity between structural mimicry and a crucial peptide "hot spot" and demonstrate its role, along with the MHC, in directing the specificity of allorecognition. Our results help explain the paradox of specificity in alloreactive TCRs and have implications for their use in immunotherapy and related efforts to manipulate TCR recognition, as well as alloreactivity in general.

Chimeric antigen receptor (CAR) T cells targeting a pathogenic MHC class II:peptide complex modulate the progression of autoimmune diabetes.

A primary initiating epitope in the NOD mouse model of Type 1 Diabetes (T1D) lies between residues 9 and 23 of the insulin B chain. The B:9-23 peptide can bind to the NOD MHC class II molecule (I-Ag7) in multiple registers, but only one, (register 3, R3), creates complexes able to stimulate the majority of pathogenic B:9-23-specific CD4+ T cells. Previously we generated a monoclonal antibody (mAb287) that targets this critical I-Ag7-B:9-23(R3) complex. When given weekly to pre-diabetic mice at either early or late stages of disease, mAb287 was able to delay or prevent T1D in the treated animals. Although the precise mechanism of action of mAb287 remains unclear, we hypothesized that it may involve deletion of antigen presenting cells (APCs) bearing the pathogenic IAg7-B:9-23(R3) complexes, and that this process might be rendered more efficient by re-directing cytotoxic T cells using a mAb287 chimeric antigen receptor (287-CAR). As anticipated, 287-CAR T cells secreted IFN-γ in response to stimulation by I-Ag7-B:9-23(R3) complexes expressed on artificial APCs, but not I-Ag7 loaded with other peptides, and killed the presenting cells in vitro. A single infusion of 287-CAR CD8+ T cells to young (5 week old) NOD mice significantly delayed the onset of overt hyperglycemia compared to untreated animals (p = 0.022). None of the 287-CAR CD8+ T cell treated mice developed diabetes before 18 weeks of age, while 29% of control-CAR T cell treated mice (p = 0.044) and 52% of the un-treated mice (p = 0.0001) had developed T1D by this time. However, the protection provided by 287-CAR CD8+ T cells declined with time, and no significant difference in overall incidence by 30 weeks between the 3 groups was observed. Mechanistic studies indicated that the adoptively transferred 287-CAR T cells selectively homed to pancreatic lymph nodes, and in some animals could persist for at least 1-2 weeks post-transfer, but were essentially undetectable 10-15 weeks later. Our study demonstrates that CAR T cells specific for a pathogenic MHC class II:peptide complex can be effective in vivo, but that a single infusion of the current iteration can only delay, but not prevent, the development of T1D. Future studies should therefore be directed towards optimizing strategies designed to improve the longevity of the transferred cells.

How structural adaptability exists alongside HLA-A2 bias in the human αß TCR repertoire.

How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining αß TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged "hot-spot" region that is almost exclusive to the α1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Vα and Vß genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs.

Detection, phenotyping, and quantification of antigen-specific T cells using a peptide-MHC dodecamer.

Here we report a peptide-MHC (pMHC) dodecamer as a "next generation" technology that is a significantly more sensitive and versatile alternative to pMHC tetramers for the detection, isolation, and phenotypic analysis of antigen-specific T cells. In particular, dodecamers are able to detect two- to fivefold more antigen-specific T cells in both human and murine CD4(+)and CD8(+)αß T-cell compartments compared with the equivalent tetramers. The low-affinity, tetramer-negative, dodecamer-positive T cells showed comparable effector cytokine responses as those of high-affinity, tetramer-positive T cells. Dodecamers are able to detect early stage CD4(+)CD8(+)double-positive thymocytes on which T-cell receptors are 10- to 30-fold less dense than mature T cells. Dodecamers also show utility in the analysis of γδ T cells and in cytometry by time-of-flight applications. This construct has a simple structure with a central scaffold protein linked to four streptavidin molecules, each having three pMHC ligands or other molecules. The dodecamer is straightforward and inexpensive to produce and is compatible with current tetramer technology and commercially available streptavidin conjugates.

Improved methods for predicting peptide binding affinity to MHC class II molecules.

Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2.