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

Defining the T cell transcriptional landscape in pediatric liver transplant rejection at single cell resolution

Acute cellular rejection (ACR) affects >80% of pediatric liver transplant recipients within 5 years, and late ACR is associated with graft failure. Traditional anti-rejection therapy for late ACR is ineffective and has remained unchanged for six decades. Although CD8+ T cells promote late ACR, little has been done to define their specificity and gene expression. Here, we used single-cell sequencing and immune repertoire profiling (10X Genomics) on 30 cryopreserved 16G liver biopsies from 14 patients (5 pre-transplant or with no ACR, 9 with ACR). We identified expanded intragraft CD8+ T cell clonotypes (CD8EXP) and their gene expression profiles in response to anti-rejection treatment. Notably, we found that expanded CD8+ clonotypes (CD8EXP) bore markers of effector and CD56hiCD161- 'NK-like' T cells, retaining their clonotype identity and phenotype in subsequent biopsies from the same patients despite histologic ACR resolution. CD8EXP clonotypes localized to portal infiltrates during active ACR, and persisted in the lobule after histologic ACR resolution. CellPhoneDB analysis revealed differential crosstalk between KC and CD8EXP during late ACR, with activation of the LTB-LTBR pathway and downregulation of TGFß signaling. Therefore, persistently-detected intragraft CD8EXP clones remain active despite ACR treatment and may contribute to long-term allograft fibrosis and failure of operational tolerance.

Prior viral infection primes cross-reactive CD8+ T cells that respond to mouse heart allografts

Introduction

Significant evidence suggests a connection between transplant rejection and the presence of high levels of pre-existing memory T cells. Viral infection can elicit viral-specific memory T cells that cross-react with allo-MHC capable of driving allograft rejection in mice. Despite these advances, and despite their critical role in transplant rejection, a systematic study of allo-reactive memory T cells, their specificities, and the role of cross-reactivity with viral antigens has not been performed.

Methods

Here, we established a model to identify, isolate, and characterize cross-reactive T cells using Nur77 reporter mice (C57BL/6 background), which transiently express GFP exclusively upon TCR engagement. We infected Nur77 mice with lymphocytic choriomeningitis virus (LCMV-Armstrong) to generate a robust memory compartment, where quiescent LCMV-specific memory CD8+ T cells could be readily tracked with MHC tetramer staining. Then, we transplanted LCMV immune mice with allogeneic hearts and monitored expression of GFP within MHC-tetramer defined viral-specific T cells as an indicator of their ability to cross-react with alloantigens.

Results

Strikingly, prior LCMV infection significantly increased the kinetics and magnitude of rejection as well as CD8+ T cell recruitment into allogeneic, but not syngeneic, transplanted hearts, relative to non-infected controls. Interestingly, as early as day 1 after allogeneic heart transplant an average of ~8% of MHC-tetramer+ CD8+ T cells expressed GFP, in contrast to syngeneic heart transplants, where the frequency of viral-specific CD8+ T cells that were GFP+ was <1%. These data show that a significant percentage of viral-specific memory CD8+ T cells expressed T cell receptors that also recognized alloantigens in vivo. Notably, the frequency of cross-reactive CD8+ T cells differed depending upon the viral epitope. Further, TCR sequences derived from cross-reactive T cells harbored distinctive motifs that may provide insight into cross-reactivity and allo-specificity.

Discussion

In sum, we have established a mouse model to track viral-specific, allo-specific, and cross-reactive T cells; revealing that prior infection elicits substantial numbers of viral-specific T cells that cross-react to alloantigen, respond very early after transplant, and may promote rapid rejection.

An integrated approach to the characterization of immune repertoires using AIMS: An Automated Immune Molecule Separator

The adaptive immune system employs an array of receptors designed to respond with high specificity to pathogens or molecular aberrations faced by the host organism. Binding of these receptors to molecular fragments-collectively referred to as antigens-initiates immune responses. These antigenic targets are recognized in their native state on the surfaces of pathogens by antibodies, whereas T cell receptors (TCR) recognize processed antigens as short peptides, presented on major histocompatibility complex (MHC) molecules. Recent research has led to a wealth of immune repertoire data that are key to interrogating the nature of these molecular interactions. However, existing tools for the analysis of these large datasets typically focus on molecular sets of a single type, forcing researchers to separately analyze strongly coupled sequences of interacting molecules. Here, we introduce a software package for the integrated analysis of immune repertoire data, capable of identifying distinct biophysical differences in isolated TCR, MHC, peptide, antibody, and antigen sequence data. This integrated analytical approach allows for direct comparisons across immune repertoire subsets and provides a starting point for the identification of key interaction hotspots in complementary receptor-antigen pairs. The software (AIMS-Automated Immune Molecule Separator) is freely available as an open access package in GUI or command-line form.

Post-translational modifications reshape the antigenic landscape of the MHC I immunopeptidome in tumors

Post-translational modification (PTM) of antigens provides an additional source of specificities targeted by immune responses to tumors or pathogens, but identifying antigen PTMs and assessing their role in shaping the immunopeptidome is challenging. Here we describe the Protein Modification Integrated Search Engine (PROMISE), an antigen discovery pipeline that enables the analysis of 29 different PTM combinations from multiple clinical cohorts and cell lines. We expanded the antigen landscape, uncovering human leukocyte antigen class I binding motifs defined by specific PTMs with haplotype-specific binding preferences and revealing disease-specific modified targets, including thousands of new cancer-specific antigens that can be shared between patients and across cancer types. Furthermore, we uncovered a subset of modified peptides that are specific to cancer tissue and driven by post-translational changes that occurred in the tumor proteome. Our findings highlight principles of PTM-driven antigenicity, which may have broad implications for T cell-mediated therapies in cancer and beyond.

Rapid identification of CMV-specific TCRs via reverse TCR cloning system based on bulk TCR repertoire data

Advances in next-generation sequencing (NGS) have improved the resolution of T-cell receptor (TCR) repertoire analysis, and recent single-cell sequencing has made it possible to obtain information about TCR pairs. In our previous study, cytomegalovirus (CMV) pp65-specific T-cell response restricted by a single human leukocyte antigen (HLA) class I allotype was observed in an individual. Therefore, to effectively clone an antigen-specific TCR from these T cells, we developed a TCR cloning system that does not require a single cell level. First, we established the improved Jurkat reporter cell line, which was TCRαβ double knock-out and expressed CD8αβ molecules. Furthermore, functional TCRs were directly obtained by reverse TCR cloning using unique CDR3-specific PCR primers after bulk TCR sequencing of activation marker-positive CD8 T cells by NGS. A total of 15 TCRα and 14 TCRβ strands were successfully amplified by PCR from cDNA of 4-1BB-positive CD8 T cells restricted by HLA-A*02:01, HLA-A*02:06, HLA-B*07:02, and HLA-B*40:06. The panels with combinations of TCRα and TCRβ genes were investigated using Jurkat reporter cell line and artificial antigen-presenting cells (APCs). In two TCR pairs restricted by HLA-A*02:01, one TCR pair by HLA-A*02:06, four TCR pairs by HLA-B*07:02, and one TCR pair by HLA-B*40:06, their specificity and affinity were confirmed. The TCR pair of A*02:01/1-1 showed alloreactivity to HLA-A*02:06. The one TCR pair showed a higher response to the naturally processed antigen than that of the peptide pool. This reverse TCR cloning system will not only provide functional information to TCR repertoire analysis by NGS but also help in the development of TCR-T therapy.

The important role of non-covalent drug-protein interactions in drug hypersensitivity reactions

Drug hypersensitivity reactions (DHR) are heterogeneous and unusual immune reactions with rather unique clinical presentations. Accumulating evidence indicates that certain non‐covalent drug‐protein interactions are able to elicit exclusively effector functions of antibody reactions or complete T‐cell reactions which contribute substantially to DHR. Here, we discuss three key interactions; (a) mimicry: whereby soluble, non‐covalent drug‐protein complexes (“fake antigens”) mimic covalent drug‐protein adducts; (b) increased antibody affinity: for example, in quinine‐type immune thrombocytopenia where the drug gets trapped between antibody and membrane‐bound glycoprotein; and (c) p‐i‐stimulation: where naïve and memory T cells are activated by direct binding of drugs to the human leukocyte antigen and/or T‐cell receptors. This transient drug‐immune receptor interaction initiates a polyclonal T‐cell response with mild‐to‐severe DHR symptoms. Notable complications arising from p‐i DHR can include viral reactivations, autoimmunity, and multiple drug hypersensitivity. In conclusion, DHR is characterized by abnormal immune stimulation driven by non‐covalent drug‐protein interactions. This contrasts DHR from “normal” immunity, which relies on antigen‐formation by covalent hapten‐protein adducts and predominantly results in asymptomatic immunity.

Analysis of T-Cell Receptor Repertoire in Transplantation: Fingerprint of T Cell-mediated Alloresponse

T cells play a key role in determining allograft function by mediating allogeneic immune responses to cause rejection, and recent work pointed their role in mediating tolerance in transplantation. The unique T-cell receptor (TCR) expressed on the surface of each T cell determines the antigen specificity of the cell and can be the specific fingerprint for identifying and monitoring. Next-generation sequencing (NGS) techniques provide powerful tools for deep and high-throughput TCR profiling, and facilitate to depict the entire T cell repertoire profile and trace antigen-specific T cells in circulation and local tissues. Tailing T cell transcriptomes and TCR sequences at the single cell level provides a full landscape of alloreactive T-cell clones development and biofunction in alloresponse. Here, we review the recent advances in TCR sequencing techniques and computational tools, as well as the recent discovery in overall TCR profile and antigen-specific T cells tracking in transplantation. We further discuss the challenges and potential of using TCR sequencing-based assays to profile alloreactive TCR repertoire as the fingerprint for immune monitoring and prediction of rejection and tolerance.

T cells targeted to TdT kill leukemic lymphoblasts while sparing normal lymphocytes

Unlike chimeric antigen receptors, T-cell receptors (TCRs) can recognize intracellular targets presented on human leukocyte antigen (HLA) molecules. Here we demonstrate that T cells expressing TCRs specific for peptides from the intracellular lymphoid-specific enzyme terminal deoxynucleotidyl transferase (TdT), presented in the context of HLA-A*02:01, specifically eliminate primary acute lymphoblastic leukemia (ALL) cells of T- and B-cell origin in vitro and in three mouse models of disseminated B-ALL. By contrast, the treatment spares normal peripheral T- and B-cell repertoires and normal myeloid cells in vitro, and in vivo in humanized mice. TdT is an attractive cancer target as it is highly and homogeneously expressed in 80-94% of B- and T-ALLs, but only transiently expressed during normal lymphoid differentiation, limiting on-target toxicity of TdT-specific T cells. TCR-modified T cells targeting TdT may be a promising immunotherapy for B-ALL and T-ALL that preserves normal lymphocytes.

In-silico design of peptides for inhibition of HLA-A*03-KLIETYFSK complex as a new drug design for treatment of multiples sclerosis disease

Multiple sclerosis is recognized as a chronic inflammatory disease. Human leukocyte antigen (HLA) plays an important role in initiating adaptive immune responses. HLA class I is present in almost all nucleated cells and presents the cleaved endogenous peptide antigens to cytotoxic T cells. HLA-A*03 is one of the HLA class I alleles, which is reported as substantially related HLA to MS disease. In 2011, the structure of the HLA-A*03 in complex was identified with an immunodominant proteolipid protein (PLP) epitope (KLIETYFSK). This complex has been reported as an important autoantigen-presenting complex in MS pathogenesis. In this study, new peptides were designed to bind to this complex that may prevent specific pathogenic cytotoxic T cell binding to this autoantigen-presenting complex and CNS demyelination. Herein, 14 new helical peptides containing 19 amino acids were designed and their structures were predicted using the PEP-FOLD server. The binding of each designed peptide to the mentioned complex was then performed. A mutation approach was used by the BeAtMuSiC server to improve the binding affinity of the designed peptide. In each position, amino acid substitutions leading to an increase in the binding affinity of the peptide to the mentioned complex were determined. Finally, the resulting complexes were simulated for 40 ns using AMBER18 software. The results revealed that out of 14 designed peptides, "WRYWWKDWAKQFRQFYRWF" peptide exhibited the highest affinity for binding to the mentioned complex. This peptide can be considered as a potential drug to control multiple sclerosis disease in patients carrying the HLA-A*03 allele.

High Throughput Human T Cell Receptor Sequencing: A New Window Into Repertoire Establishment and Alloreactivity

Recent advances in high throughput sequencing (HTS) of T cell receptors (TCRs) and in transcriptomic analysis, particularly at the single cell level, have opened the door to a new level of understanding of human immunology and immune-related diseases. In this article, we discuss the use of HTS of TCRs to discern the factors controlling human T cell repertoire development and how this approach can be used in combination with human immune system (HIS) mouse models to understand human repertoire selection in an unprecedented manner. An exceptionally high proportion of human T cells has alloreactive potential, which can best be understood as a consequence of the processes governing thymic selection. High throughput TCR sequencing has allowed assessment of the development, magnitude and nature of the human alloresponse at a new level and has provided a tool for tracking the fate of pre-transplant-defined donor- and host-reactive TCRs following transplantation. New insights into human allograft rejection and tolerance obtained with this method in combination with single cell transcriptional analyses are reviewed here.

Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.

Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes

The physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets.

Blockade of HVEM for Prostate Cancer Immunotherapy in Humanized Mice

Simple Summary

Current immune checkpoint inhibitors have shown limitations for immunotherapy of prostate cancer. Thus, it is crucial to investigate other immune checkpoints to prevent disease progression in patients with prostate cancer. Here, we first show that the HVEM/BTLA immune checkpoint is associated with disease progression in patients. We then show that immunotherapy aimed at targeting HVEM reduced tumor growth twofold in vivo in a humanized mouse model of the pathology. The mode of action of the therapy was dependent on CD8⁺ T cells and is associated with improved T cell activation and reduced exhaustion. Finally, we demonstrated that HVEM expressed by the tumor negatively regulated the anti-tumor immune response. Our results indicate that targeting HVEM might be an attractive option for patients with prostate cancer.

Abstract

The herpes virus entry mediator (HVEM) delivers a negative signal to T cells mainly through the B and T lymphocyte attenuator (BTLA) molecule. Thus, HVEM/BTLA may represent a novel immune checkpoint during an anti-tumor immune response. However, a formal demonstration that HVEM can represent a target for cancer immunotherapy is still lacking. Here, we first showed that HVEM and BTLA mRNA expression levels were associated with a worse progression-free interval in patients with prostate adenocarcinomas, indicating a detrimental role for the HVEM/BTLA immune checkpoint during prostate cancer progression. We then showed that administration of a monoclonal antibody to human HVEM resulted in a twofold reduction in the growth of a prostate cancer cell line in NOD.SCID.gc-null mice reconstituted with human T cells. Using CRISPR/Cas9, we showed that the therapeutic effect of the mAb depended on HVEM expression by the tumor, with no effect on graft vs. host disease or activation of human T cells in the spleen. In contrast, the proliferation and number of tumor-infiltrating leukocytes increased following treatment, and depletion of CD8⁺ T cells partly alleviated treatment’s efficacy. The expression of genes belonging to various T cell activation pathways was enriched in tumor-infiltrating leukocytes, whereas genes associated with immuno-suppressive pathways were decreased, possibly resulting in modifications of leukocyte adhesion and motility. Finally, we developed a simple in vivo assay in humanized mice to directly demonstrate that HVEM expressed by the tumor is an immune checkpoint for T cell-mediated tumor control. Our results show that targeting HVEM is a promising strategy for prostate cancer immunotherapy.

Combined with interventional therapy, immunotherapy can create a new outlook for tumor treatment

Recent progress in immunotherapy provides hope of a complete cure to cancer patients. However, recent studies have reported that only a limited number of cancer patients with a specific immune status, known as "cold tumor", can benefit from a single immune agent. Although the combination of immune agents with different mechanisms can partially increase the low response rate and improve efficacy, it can also result in more side effects. Therefore, discovering therapies that can improve tumors' response rate to immunotherapy without increasing toxicity for patients is urgently needed. Tumor interventional therapy is promising. It mainly includes transcatheter arterial chemoembolization, ablation, radioactive particle internal irradiation, and photodynamic interventional therapy based on a luminal stent. Interventional therapy can directly kill tumor cells by targeted drug delivery in situ, thus reducing drug dosage and systemic toxicity like cytokine release syndrome. More importantly, interventional therapy can regulate the immune system through numerous mechanisms, making it a suitable choice for immunotherapy to combine with. In this review, we provide a brief description of immunotherapies (and their side effects) on tumors of different immune types and preliminarily elaborate on interventional therapy mechanisms to improve immune efficacy. We also discuss the progress and challenges of the combination of interventional therapy and immunotherapy.

DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning

MOTIVATION

The mutations of cancers can encode the seeds of their own destruction, in the form of T-cell recognizable immunogenic peptides, also known as neoantigens. It is computationally challenging, however, to accurately prioritize the potential neoantigen candidates according to their ability of activating the T-cell immunoresponse, especially when the somatic mutations are abundant. Although a few neoantigen prioritization methods have been proposed to address this issue, advanced machine learning model that is specifically designed to tackle this problem is still lacking. Moreover, none of the existing methods considers the original DNA loci of the neoantigens in the perspective of 3D genome which may provide key information for inferring neoantigens' immunogenicity.

RESULTS

In this study, we discovered that DNA loci of the immunopositive and immunonegative MHC-I neoantigens have distinct spatial distribution patterns across the genome. We therefore used the 3D genome information along with an ensemble pMHC-I coding strategy, and developed a group feature selection-based deep sparse neural network model (DNN-GFS) that is optimized for neoantigen prioritization. DNN-GFS demonstrated increased neoantigen prioritization power comparing to existing sequence-based approaches. We also developed a webserver named deepAntigen (http://yishi.sjtu.edu.cn/deepAntigen) that implements the DNN-GFS as well as other machine learning methods. We believe that this work provides a new perspective toward more accurate neoantigen prediction which eventually contribute to personalized cancer immunotherapy.

AVAILABILITY AND IMPLEMENTATION

Data and implementation are available on webserver: http://yishi.sjtu.edu.cn/deepAntigen.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of amino acid residues of T-cell receptors interacting with HLA-A*02-restricted antigen peptides

Background

The present study aimed to explore residues’ properties interacting with HLA-A*02-restricted peptides on T-cell receptors (TCRs) and their effects on bond types of interaction and binding free energy.

Methods

We searched the crystal structures of HLA-A*02-restricted peptide-TCR complexes from the Protein Data Bank (PDB) database and subsequently collected relevant parameters. We then employed Schrodinger to analyze the bond types of interaction and Gromacs 2019 to evaluate the TCR-antigen peptide complex’s molecular dynamics simulation. Finally, we compared the changes of bond types of interaction and binding free energy before and after residue substitution to ensure consistency of the conditions before and after residue substitution.

Results

The main sites on the antigen peptides that formed the intermolecular interaction [hydrogen bond (HB) and pi stack] with TCRs were P4, P8, P2, and P6. The hydrophobicity of the amino acids inside or outside the disulfide bond of TCRs may be related to the intermolecular interaction and binding free energy between TCRs and peptides. Residues located outside the disulfide bond of TCR α or β chains and forming pi stack force played favorable roles in the complex intermolecular interaction and binding free energy. The residues of the TCR α or β chains that interacted with peptides were replaced by alanine (Ala) or glycine (Gly), and their intermolecular binding free energy of the complex had been improved. However, it had nothing to do with the formation of HB.

Conclusions

The findings of this study suggest that the hydrophobic nature of the amino acids inside or outside the disulfide bonds on the TCR may be associated with the intermolecular interaction and binding between the TCR and polypeptide. The residues located outside the TCR α or β single-chain disulfide bond and forming the pi-stack force showed a beneficial effect on the intermolecular interaction and binding of the complex. In addition, the part of the residues on the TCR α or β single chain that produced bond types of interaction with the polypeptide after being replaced by Ala or Gly, the intermolecular binding free energy of the complex was increased, regardless of whether HB was formed.

Genetic Bias, Diversity Indices, Physiochemical Properties and CDR3 Motifs Divide Auto-Reactive from Allo-Reactive T-Cell Repertoires

The distinct properties of allo-reactive T-cell repertoires are not well understood. To investigate whether auto-reactive and allo-reactive T-cell repertoires encoded distinct properties, we used dextramer enumeration, enrichment, single-cell T-cell receptor (TCR) sequencing and multiparameter analysis. We found auto-reactive and allo-reactive T-cells differed in mean ex vivo frequency which was antigen dependent. Allo-reactive T-cells showed clear differences in TCR architecture, with enriched usage of specific T-cell receptor variable (TRBJ) genes and broader use of T-cell receptor variable joining (TRBJ) genes. Auto-reactive T-cell repertoires exhibited complementary determining regions three (CDR3) lengths using a Gaussian distribution whereas allo-reactive T-cell repertoires exhibited distorted patterns in CDR3 length. CDR3 loops from allo-reactive T-cells showed distinct physical-chemical properties, tending to encode loops that were more acidic in charge. Allo-reactive T-cell repertoires differed in diversity metrics, tending to show increased overall diversity and increased homogeneity between repertoires. Motif analysis of CDR3 loops showed allo-reactive T-cell repertoires differed in motif preference which included broader motif use. Collectively, these data conclude that allo-reactive T-cell repertoires are indeed different to auto-reactive repertoires and provide tangible metrics for further investigations and validation. Given that the antigens studied here are overexpressed on multiple cancers and that allo-reactive TCRs often show increased ligand affinity, this new TCR bank also has translational potential for adoptive cell therapy, soluble TCR-based therapy and rational TCR design.

CRISPR/Cas9 Ribonucleoprotein Complex-Mediated Efficient B2M Knockout in Human Induced Pluripotent Stem Cells (iPSCs)

Advances in induced pluripotent stem cell (iPSC) technology provide a renewable source of cells for tissue regeneration and therefore hold great promise for cell replacement therapy. However, immune rejection of allograft due to human leukocyte antigen (HLA) mismatching remains a major challenge. Considerable efforts have been devoted to overcoming the immunogenicity of allograft transplantation. One of the approaches is an elimination of HLA molecules on the surface of allogeneic cells using genome editing technology to generate universal stem cells. Here, we present a simple and effective genome editing approach to knockout the β-2-immunoglobulin (B2M) gene, which encodes B2M protein that forms a heterodimer with HLA class I proteins, in induced pluripotent stem cells (iPSCs) leading to HLA class I (HLA-I) depletion. We also describe detailed procedures for validation of the B2M-knockout iPSCs using flow cytometry, and genotypic analysis for potential off-target regions. Our protocol is also applicable for knocking out other genes in iPSCs and other cell types.

TCR Recognition of Peptide-MHC-I: Rule Makers and Breakers

T cells are a critical part of the adaptive immune system that are able to distinguish between healthy and unhealthy cells. Upon recognition of protein fragments (peptides), activated T cells will contribute to the immune response and help clear infection. The major histocompatibility complex (MHC) molecules, or human leukocyte antigens (HLA) in humans, bind these peptides to present them to T cells that recognise them with their surface T cell receptors (TCR). This recognition event is the first step that leads to T cell activation, and in turn can dictate disease outcomes. The visualisation of TCR interaction with pMHC using structural biology has been crucial in understanding this key event, unravelling the parameters that drive this interaction and their impact on the immune response. The last five years has been the most productive within the field, wherein half of current unique TCR-pMHC-I structures to date were determined within this time. Here, we review the new insights learned from these recent TCR-pMHC-I structures and their impact on T cell activation.

ZIAQ: a quantile regression method for differential expression analysis of single-cell RNA-seq data

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) has enabled the simultaneous transcriptomic profiling of individual cells under different biological conditions. scRNA-seq data have two unique challenges that can affect the sensitivity and specificity of single-cell differential expression analysis: a large proportion of expressed genes with zero or low read counts ('dropout' events) and multimodal data distributions.

RESULTS

We have developed a zero-inflation-adjusted quantile (ZIAQ) algorithm, which is the first method to account for both dropout rates and complex scRNA-seq data distributions in the same model. ZIAQ demonstrates superior performance over several existing methods on simulated scRNA-seq datasets by finding more differentially expressed genes. When ZIAQ was applied to the comparison of neoplastic and non-neoplastic cells from a human glioblastoma dataset, the ranking of biologically relevant genes and pathways showed clear improvement over existing methods.

AVAILABILITY AND IMPLEMENTATION

ZIAQ is implemented in the R language and available at https://github.com/gefeizhang/ZIAQ.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

How to Make an Immune System and a Foreign Host Quickly Cohabit in Peace? The Challenge of Acute Graft-Versus-Host Disease Prevention After Allogeneic Hematopoietic Cell Transplantation

Allogeneic hematopoietic cell transplantation (alloHCT) has been used as cellular immunotherapy against hematological cancers for more than six decades. Its therapeutic efficacy relies on the cytoreductive effects of the conditioning regimen but also on potent graft-versus-tumor (GVT) reactions mediated by donor-derived immune cells. However, beneficial GVT effects may be counterbalanced by acute GVHD (aGVHD), a systemic syndrome in which donor immune cells attack healthy tissues of the recipient, resulting in severe inflammatory lesions mainly of the skin, gut, and liver. Despite standard prophylaxis regimens, aGVHD still occurs in approximately 20–50% of alloHCT recipients and remains a leading cause of transplant-related mortality. Over the past two decades, advances in the understanding its pathophysiology have helped to redefine aGVHD reactions and clinical presentations as well as developing novel strategies to optimize its prevention. In this review, we provide a brief overview of current knowledge on aGVHD immunopathology and discuss current approaches and novel strategies being developed and evaluated in clinical trials for aGVHD prevention. Optimal prophylaxis of aGVHD would prevent the development of clinically significant aGVHD, while preserving sufficient immune responsiveness to maintain beneficial GVT effects and immune defenses against pathogens.

A novel neoantigen discovery approach based on chromatin high order conformation

Background

High-throughput sequencing technology has yielded reliable and ultra-fast sequencing for DNA and RNA. For tumor cells of cancer patients, when combining the results of DNA and RNA sequencing, one can identify potential neoantigens that stimulate the immune response of the T cell. However, when the somatic mutations are abundant, it is computationally challenging to efficiently prioritize the identified neoantigen candidates according to their ability of activating the T cell immuno-response.

Methods

Numerous prioritization or prediction approaches have been proposed to address this issue but none of them considers the original DNA loci of the neoantigens from the perspective of 3D genome. Based on our previous discoveries, we propose to investigate the distribution of neoantigens with different immunogenicity abilities in 3D genome and propose to adopt this important information into neoantigen prediction.

Results

We retrospect the DNA origins of the immuno-positive and immuno-negative neoantigens in the context of 3D genome and discovered that DNA loci of the immuno-positive neoantigens and immuno-negative neoantigens have very different distribution pattern. Specifically, comparing to the background 3D genome, DNA loci of the immuno-positive neoantigens tend to locate at specific regions in the 3D genome. We thus used this information into neoantigen prediction and demonstrated the effectiveness of this approach.

Conclusion

We believe that the 3D genome information will help to increase the precision of neoantigen prioritization and discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.

Structural dissimilarity from self drives neoepitope escape from immune tolerance

T-cell recognition of peptides incorporating nonsynonymous mutations, or neoepitopes, is a cornerstone of tumor immunity and forms the basis of new immunotherapy approaches including personalized cancer vaccines. Yet as they are derived from self-peptides, the means through which immunogenic neoepitopes overcome immune self-tolerance are often unclear. Here we show that a point mutation in a non-major histocompatibility complex anchor position induces structural and dynamic changes in an immunologically active ovarian cancer neoepitope. The changes pre-organize the peptide into a conformation optimal for recognition by a neoepitope-specific T-cell receptor, allowing the receptor to bind the neoepitope with high affinity and deliver potent T-cell signals. Our results emphasize the importance of structural and physical changes relative to self in neoepitope immunogenicity. Considered broadly, these findings can help explain some of the difficulties in identifying immunogenic neoepitopes from sequence alone and provide guidance for developing novel, neoepitope-based personalized therapies.

Understanding TCR affinity, antigen specificity, and cross-reactivity to improve TCR gene-modified T cells for cancer immunotherapy

Adoptive cell transfer (ACT) using T cell receptor (TCR) gene-modified T cells is an exciting and rapidly evolving field. Numerous preclinical and clinical studies have demonstrated various levels of feasibility, safety, and efficacy using TCR-engineered T cells to treat cancer and viral infections. Although evidence suggests their use can be effective, to what extent and how to improve these therapeutics are still matters of investigation. As TCR affinity has been generally accepted as the central role in defining T cell specificity and sensitivity, selection for and generation of high affinity TCRs has remained a fundamental approach to design more potent T cells. However, traditional methods for affinity-enhancement by random mutagenesis can induce undesirable cross-reactivity causing on- and off-target adverse events, generate exhausted effectors by overstimulation, and ignore other kinetic and cellular parameters that have been shown to impact antigen specificity. In this Focussed Research Review, we comment on the preclinical and clinical potential of TCR gene-modified T cells, summarize our contributions challenging the role TCR affinity plays in antigen recognition, and explore how structure-guided design can be used to manipulate antigen specificity and TCR cross-reactivity to improve the safety and efficacy of TCR gene-modified T cells used in ACT.

Specific Donor HLA-DR Types Correlate With Altered Susceptibility to Development of Chronic Lung Allograft Dysfunction

BACKGROUND

The greatest challenge to long-term graft survival is the development of chronic lung allograft dysfunction. Th17 responses to collagen type V (colV) predispose lung transplant patients to the severe obstructive form of chronic lung allograft dysfunction, known as bronchiolitis obliterans syndrome (BOS). In a previous study cohort (n = 54), pretransplant colV responses were increased in recipients expressing HLA-DR15, consistent with the high binding avidity of colV (α1) peptides for HLA-DR15, whereas BOS incidence, which was known to be strongly associated with posttransplant autoimmunity to colV, was higher in patients who themselves lacked HLA-DR15, but whose lung donor expressed it.

METHODS

To determine if this DR-restricted effect on BOS incidence could be validated in a larger cohort, we performed a retrospective analysis of outcomes for 351 lung transplant recipients transplanted between 1988 and 2008 at the University of Wisconsin. All subjects were followed until graft loss, death, loss to follow-up, or through 2014, with an average follow-up of 7 years. Comparisons were made between recipients who did or did not develop BOS. Grading of BOS followed the recommendations of the international society for heart and lung transplantation.

RESULTS

Donor HLA-DR15 was indeed associated with increased susceptibility to severe BOS in this population. We also discovered that HLA-DR7 expression by the donor or HLA-DR17 expression by the recipient decreased susceptibility.

CONCLUSIONS

We show in this retrospective study that specific donor HLA class II types are important in lung transplantation, because they are associated with either protection from or susceptibility to development of severe BOS.

Interventional therapy combined with immune checkpoint inhibitors: Emerging opportunities for cancer treatment in the era of immunotherapy

Immune checkpoint inhibitors-based immunotherapy offers a new effective modality in the treatment of advanced malignancies. Considering the remarkable efficacy of immune checkpoint inhibitors in clinical trials, the FDA has approved a variety of immune checkpoint inhibitors for the treatment of advanced tumors. However, only limited patients with certain cancers can benefit from monotherapy of immune checkpoint inhibitors. Interventional therapy for cancer can not only destroy the primary tumors, but also regulate the immune system through different mechanisms, which provides a potential possibility for the combination of immune checkpoint inhibitors and interventional modalities in cancer treatment. This article reviews the possible synergistic mechanisms of interventional therapy combined with immune checkpoint inhibitors and summarizes the research progress of the combined therapy in cancer treatment.

Computational Modeling of Hepatitis C Virus Envelope Glycoprotein Structure and Recognition

Hepatitis C virus (HCV) is a major global health concern, and though therapeutic options have improved, no vaccine is available despite decades of research. As HCV can rapidly mutate to evade the immune response, an effective HCV vaccine must rely on identification and characterization of sites critical for broad immune protection and viral neutralization. This knowledge depends on structural and mechanistic insights of the E1 and E2 envelope glycoproteins, which assemble as a heterodimer on the surface of the virion, engage coreceptors during host cell entry, and are the primary targets of antibodies. Due to the challenges in determining experimental structures, structural information on E1 and E2 and their interaction is relatively limited, providing opportunities to model the structures, interactions, and dynamics of these proteins. This review highlights efforts to model the E2 glycoprotein structure, the assembly of the functional E1E2 heterodimer, the structure and binding of human coreceptors, and recognition by key neutralizing antibodies. We also discuss a comparison of recently described models of full E1E2 heterodimer structures, a simulation of the dynamics of key epitope sites, and modeling glycosylation. These modeling efforts provide useful mechanistic hypotheses for further experimental studies of HCV envelope assembly, recognition, and viral fitness, and underscore the benefit of combining experimental and computational modeling approaches to reveal new insights. Additionally, computational design approaches have produced promising candidates for epitope-based vaccine immunogens that specifically target key epitopes, providing a possible avenue to optimize HCV vaccines versus using native glycoproteins. Advancing knowledge of HCV envelope structure and immune recognition is highly applicable toward the development of an effective vaccine for HCV and can provide lessons and insights relevant to modeling and characterizing other viruses.

Alloreactive T Cell Receptor Diversity against Structurally Similar or Dissimilar HLA-DP Antigens Assessed by Deep Sequencing

T cell alloreactivity is mediated by a self-human leukocyte antigen (HLA)-restricted T cell receptor (TCR) repertoire able to recognize both structurally similar and dissimilar allogeneic HLA molecules (i.e., differing by a single or several amino acids in their peptide-binding groove). We hypothesized that thymic selection on self-HLA molecules could have an indirect impact on the size and diversity of the alloreactive response. To test this possibility, we used TCR Vβ immunophenotyping and immunosequencing technology in a model of alloreactivity between self-HLA selected T cells and allogeneic HLA-DPB1 (DPB1) differing from self-DPB1*04:02 by a single (DPB1*02:01) or several (DPB1*09:01) amino acids in the peptide-binding groove. CD4+ T cells from three different self-DPB1*04:01,*04:02 individuals were stimulated with HeLa cells stably transduced with the relevant peptide processing machinery, co-stimulatory molecules, and HLA-DP. Flow cytometric quantification of the DPB1-specific T cell response measured as upregulation of the activation marker CD137 revealed significantly lower levels of alloreactivity against DPB1*02:01 compared with DPB1*09:01 (mean CD4+CD137+ frequency 35.2 ± 9.9 vs. 61.5 ± 7.7%, respectively, p < 0.0001). These quantitative differences were, however, not reflected by differences in the breadth of the alloreactive response at the Vβ level, with both alloantigens eliciting specific responses from all TCR-Vβ specificities tested by flow cytometry, albeit with higher levels of reactivity from most Vβ specificities against DPB1*09:01. In line with these observations, TCRB-CDR3 immunosequencing showed no significant differences in mean clonality of sorted CD137+CD4+ cells alloreactive against DPB1*02:01 or DPB1*09:01 [0.39 (0.36–0.45) and 0.39 (0.30–0.46), respectively], or in the cumulative frequencies of the 10 most frequent responding clones (55–67 and 58–62%, respectively). Most of the clones alloreactive against DPB1*02:01 (68.3%) or DPB1*09:01 (75.3%) were characterized by low-abundance (i.e., they were not appreciable among the pre-culture T cells). Interestingly, however, their cumulative frequency was lower against DPB1*02:01 compared with DPB1*09:01 (mean cumulative frequency 35.3 vs. 50.6%, respectively). Our data show that, despite lower levels of alloreactivity, a similar clonal diversity can be elicited by structurally similar compared with structurally dissimilar HLA-DPB1 alloantigens and demonstrate the power of TCRB immunosequencing in unraveling subtle qualitative changes not appreciable by conventional methods.

Characteristics of inflammatory reactions during development of liver abscess in hamsters inoculated with Entamoeba nuttalli

Background

Entamoeba nuttalli is an intestinal protozoan with pathogenic potential that can cause amebic liver abscess. It is highly prevalent in wild and captive macaques. Recently, cysts were detected in a caretaker of nonhuman primates in a zoo, indicating that E. nuttalli may be a zoonotic pathogen. Therefore, it is important to evaluate the pathogenicity of E. nuttalli in detail and in comparison with that of E. histolytica.

Methodology/Principal findings

Trophozoites of E. nuttalli GY4 and E. histolytica SAW755 strains were inoculated into liver of hamsters. Expression levels of proinflammatory factors of hamsters and virulence factors from E. histolytica and E. nuttalli were compared between the two parasites. Inoculations with trophozoites of E. nuttalli resulted in an average necrotic area of 24% in liver tissue in 7 days, whereas this area produced by E. histolytica was nearly 50%. Along with the mild liver tissue damage induced by E. nuttalli, expression levels of proinflammatory factors (TNF-α, IL-6 and IL-1β) and amebic virulence protein genes (lectins, cysteine proteases and amoeba pores) in local tissues were lower with E. nuttalli in comparison with E. histolytica. In addition, M2 type macrophages were increased in E. nuttalli-induced amebic liver abscesses in the late stage of disease progression and lysate of E. nuttalli trophozoites induced higher arginase expression than E. histolytica in vitro.

Conclusions/Significance

The results show that differential secretion of amebic virulence proteins during E. nuttalli infection triggered lower levels of secretion of various cytokines and had an impact on polarization of macrophages towards a M1/M2 balance. However, regardless of the degree of macrophage polarization, there is unambiguous evidence of an intense acute inflammatory reaction in liver of hamsters after infection by both Entamoeba species.

Entamoeba nuttalli is the phylogenetically closest protozoan to Entamoeba histolytica and is highly prevalent in macaques. Previous studies have indicated that E. nuttalli is virulent in a hamster model. In this study, we compared the immunopathological basis of formation of liver abscess in hamsters between E. nuttalli and E. histolytica. Mild liver tissue damage developed after intrahepatic injection of trophozoites of E. nuttalli, and lower expression levels of genes for host proinflammatory factors and amebic virulence proteins were detected at the edges of liver abscesses induced by E. nuttalli. In addition, alternatively activated macrophages were increased in E. nuttalli-induced liver abscesses in the late stage of disease progression. The lysate of E. nuttalli trophozoites also induced higher arginase expression than E. histolytica in vitro. Polarization of macrophages is likely to affect the degree of acute inflammatory reactions in liver in an animal model during E. nuttalli infection. Our data reveal new characteristics of abscess formation by E. nuttalli.

Altered Peptide Ligands Impact the Diversity of Polyfunctional Phenotypes in T Cell Receptor Gene-Modified T Cells

The use of T cell receptor (TCR) gene-modified T cells in adoptive cell transfer has had promising clinical success, but often, simple preclinical evaluation does not necessarily accurately predict treatment efficacy or safety. Preclinical studies generally evaluate one or a limited number of type 1 cytokines to assess antigen recognition. However, recent studies have implicated other "typed" T cells in effective anti-tumor/viral immunity, and limited functional evaluations may underestimate cross-reactivity. In this study, we use an altered peptide ligand (APL) model and multi-dimensional flow cytometry to evaluate polyfunctionality of TCR gene-modified T cells. Evaluating six cytokines and the lytic marker CD107a on a per cell basis revealed remarkably diverse polyfunctional phenotypes within a single T cell culture and among peripheral blood lymphocyte (PBL) donors. This polyfunctional assessment identified unexpected phenotypes, including cells producing both type 1 and type 2 cytokines, and highlighted interferon γ^neg (IFNγ^neg) antigen-reactive populations overlooked in our previous studies. Additionally, APLs skewed functional phenotypes to be less polyfunctional, which was not necessarily related to changes in TCR-peptide-major histocompatibility complex (pMHC) affinity. A better understanding of gene-modified T cell functional diversity may help identify optimal therapeutic phenotypes, predict clinical responses, anticipate off-target recognition, and improve the design and delivery of TCR gene-modified T cells.

Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes

T cell specificity emerges from a myriad of processes, ranging from the biological pathways that control T cell signaling to the structural and physical mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and physical studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophysical principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunology.

Peptide and Peptide-Dependent Motions in MHC Proteins: Immunological Implications and Biophysical Underpinnings

Structural biology of peptides presented by class I and class II MHC proteins has transformed immunology, impacting our understanding of fundamental immune mechanisms and allowing researchers to rationalize immunogenicity and design novel vaccines. However, proteins are not static structures as often inferred from crystallographic structures. Their components move and breathe individually and collectively over a range of timescales. Peptides bound within MHC peptide-binding grooves are no exception and their motions have been shown to impact recognition by T cell and other receptors in ways that influence function. Furthermore, peptides tune the motions of MHC proteins themselves, which impacts recognition of peptide/MHC complexes by other proteins. Here, we review the motional properties of peptides in MHC binding grooves and discuss how peptide properties can influence MHC motions. We briefly review theoretical concepts about protein motion and highlight key data that illustrate immunological consequences. We focus primarily on class I systems due to greater availability of data, but segue into class II systems as the concepts and consequences overlap. We suggest that characterization of the dynamic “energy landscapes” of peptide/MHC complexes and the resulting functional consequences is one of the next frontiers in structural immunology.