High-throughput discovery of MHC class I- and II-restricted T cell epitopes using synthetic cellular circuits.

Antigen discovery technologies have largely focused on major histocompatibility complex (MHC) class I-restricted human T cell receptors (TCRs), leaving methods for MHC class II-restricted and mouse TCR reactivities relatively undeveloped. Here we present TCR mapping of antigenic peptides (TCR-MAP), an antigen discovery method that uses a synthetic TCR-stimulated circuit in immortalized T cells to activate sortase-mediated tagging of engineered antigen-presenting cells (APCs) expressing processed peptides on MHCs. Live, tagged APCs can be directly purified for deconvolution by sequencing, enabling TCRs with unknown specificity to be queried against barcoded peptide libraries in a pooled screening context. TCR-MAP accurately captures self-reactivities or viral reactivities with high throughput and sensitivity for both MHC class I-restricted and class II-restricted TCRs. We elucidate problematic cross-reactivities of clinical TCRs targeting the cancer/testis melanoma-associated antigen A3 and discover targets of myocarditis-inciting autoreactive T cells in mice. TCR-MAP has the potential to accelerate T cell antigen discovery efforts in the context of cancer, infectious disease and autoimmunity.

TGM4: an immunogenic prostate-restricted antigen.

BACKGROUND: Prostate cancer is the second leading cause of cancer-related death in men in the USA; death occurs when patients progress to metastatic castration-resistant prostate cancer (CRPC). Although immunotherapy with the Food and Drug Administration-approved vaccine sipuleucel-T, which targets prostatic acid phosphatase (PAP), extends survival for 2-4 months, the identification of new immunogenic tumor-associated antigens (TAAs) continues to be an unmet need. METHODS: We evaluated the differential expression profile of castration-resistant prostate epithelial cells that give rise to CRPC from mice following an androgen deprivation/repletion cycle. The expression levels of a set of androgen-responsive genes were further evaluated in prostate, brain, colon, liver, lung, skin, kidney, and salivary gland from murine and human databases. The expression of a novel prostate-restricted TAA was then validated by immunostaining of mouse tissues and analyzed in primary tumors across all human cancer types in The Cancer Genome Atlas. Finally, the immunogenicity of this TAA was evaluated in vitro and in vivo using autologous coculture assays with cells from healthy donors as well as by measuring antigen-specific antibodies in sera from patients with prostate cancer (PCa) from a neoadjuvant clinical trial. RESULTS: We identified a set of androgen-responsive genes that could serve as potential TAAs for PCa. In particular, we found transglutaminase 4 (Tgm4) to be highly expressed in prostate tumors that originate from luminal epithelial cells and only expressed at low levels in most extraprostatic tissues evaluated. Furthermore, elevated levels of TGM4 expression in primary PCa tumors correlated with unfavorable prognosis in patients. In vitro and in vivo assays confirmed the immunogenicity of TGM4. We found that activated proinflammatory effector memory CD8 and CD4 T cells were expanded by monocyte-derived dendritic cell (moDCs) pulsed with TGM4 to a greater extent than moDCs pulsed with either PAP or prostate-specific antigen (PSA), and T cells primed with TGM4-pulsed moDCs produce functional cytokines following a prime/boost regiment or in vitro stimulation. An IgG antibody response to TGM4 was detected in 30% of vaccinated patients, while fewer than 8% of vaccinated patients developed antibody responses to PSA or prostate-specific membrane antigen (PSMA). CONCLUSIONS: These results suggest that TGM4 is an immunogenic, prostate-restricted antigen with the potential for further development as an immunotherapy target.

Epitope profiling reveals binding signatures of SARS-CoV-2 immune response in natural infection and cross-reactivity with endemic human CoVs.

A major goal of current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine efforts is to elicit antibody responses that confer protection. Mapping the epitope targets of the SARS-CoV-2 antibody response is critical for vaccine design, diagnostics, and development of therapeutics. Here, we develop a pan-coronavirus phage display library to map antibody binding sites at high resolution within the complete viral proteomes of all known human-infecting coronaviruses in patients with mild or moderate/severe coronavirus disease 2019 (COVID-19). We find that the majority of immune responses to SARS-CoV-2 are targeted to the spike protein, nucleocapsid, and ORF1ab and include sites of mutation in current variants of concern. Some epitopes are identified in the majority of samples, while others are rare, and we find variation in the number of epitopes targeted between individuals. We find low levels of SARS-CoV-2 cross-reactivity in individuals with no exposure to the virus and significant cross-reactivity with endemic human coronaviruses (CoVs) in convalescent sera from patients with COVID-19.

A Comprehensive Phenotypic and Functional Immune Analysis Unravels Circulating Anti-Phospholipase A2 Receptor Antibody Secreting Cells in Membranous Nephropathy Patients.

INTRODUCTION: Primary membranous nephropathy (MN) is characterized by the presence of antipodocyte antibodies, but studies describing phenotypic and functional abnormalities in circulating lymphocytes are limited. METHODS: We analyzed 68 different B- and T-cell subsets using flow cytometry in 30 MN patients (before initiating immunosuppression) compared with 31 patients with non-immune-mediated chronic kidney disease (CKD) and 12 healthy individuals. We also measured 19 serum cytokines in MN patients and in healthy controls. Lastly, we quantified the ex vivo production of phospholipase A2 receptor (PLA2R)-specific IgG by plasmablasts (measuring antibodies in culture supernatants and by the newly developed FluoroSpot assay [AutoImmun Diagnostika, Strasberg, Germany]) and assessed the circulating antibody repertoire by phage immunoprecipitation sequencing (PhIP-Seq). RESULTS: After adjusting for multiple testing, plasma cells and regulatory B cells (BREG) were significantly higher (P < 0.05) in MN patients compared with both control groups. The percentages of circulating plasma cells correlated with serum anti-PLA2R antibody levels (P = 0.042) and were associated with disease activity. Ex vivo-expanded PLA2R-specific IgG-producing plasmablasts generated from circulating PLA2R-specific memory B cells (mBCs) correlated with serum anti-PLA2R IgG antibodies (P < 0.001) in MN patients. Tumor necrosis factor-α (TNF-α) was the only significantly increased cytokine in MN patients (P < 0.05), whereas there was no significant difference across study groups in the autoantibody and antiviral antibody repertoire. CONCLUSION: This extensive phenotypic and functional immune characterization shows that autoreactive plasma cells are present in the circulation of MN patients, providing a new therapeutic target and a candidate biomarker of disease activity.

MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing.

Computational prediction of the peptides presented on major histocompatibility complex (MHC) class I proteins is an important tool for studying T cell immunity. The data available to develop such predictors have expanded with the use of mass spectrometry to identify naturally presented MHC ligands. In addition to elucidating binding motifs, the identified ligands also reflect the antigen processing steps that occur prior to MHC binding. Here, we developed an integrated predictor of MHC class I presentation that combines new models for MHC class I binding and antigen processing. Considering only peptides first predicted by the binding model to bind strongly to MHC, the antigen processing model is trained to discriminate published mass spectrometry-identified MHC class I ligands from unobserved peptides. The integrated model outperformed the two individual components as well as NetMHCpan 4.0 and MixMHCpred 2.0.2 on held-out mass spectrometry experiments. Our predictors are implemented in the open source MHCflurry package, version 2.0 (github.com/openvax/mhcflurry).

PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes.

The binding specificities of an individual's antibody repertoire contain a wealth of biological information. They harbor evidence of environmental exposures, allergies, ongoing or emerging autoimmune disease processes, and responses to immunomodulatory therapies, for example. Highly multiplexed methods to comprehensively interrogate antibody-binding specificities have therefore emerged in recent years as important molecular tools. Here, we provide a detailed protocol for performing 'phage immunoprecipitation sequencing' (PhIP-Seq), which is a powerful method for analyzing antibody-repertoire binding specificities with high throughput and at low cost. The methodology uses oligonucleotide library synthesis (OLS) to encode proteomic-scale peptide libraries for display on bacteriophage. These libraries are then immunoprecipitated, using an individual's antibodies, for subsequent analysis by high-throughput DNA sequencing. We have used PhIP-Seq to identify novel self-antigens associated with autoimmune disease, to characterize the self-reactivity of broadly neutralizing HIV antibodies, and in a large international cross-sectional study of exposure to hundreds of human viruses. Compared with alternative array-based techniques, PhIP-Seq is far more scalable in terms of sample throughput and cost per analysis. Cloning and expression of recombinant proteins are not required (versus protein microarrays), and peptide lengths are limited only by DNA synthesis chemistry (up to 90-aa (amino acid) peptides versus the typical 8- to 12-aa length limit of synthetic peptide arrays). Compared with protein microarrays, however, PhIP-Seq libraries lack discontinuous epitopes and post-translational modifications. To increase the accessibility of PhIP-Seq, we provide detailed instructions for the design of phage-displayed peptidome libraries, their immunoprecipitation using serum antibodies, deep sequencing-based measurement of peptide abundances, and statistical determination of peptide enrichments that reflect antibody-peptide interactions. Once a library has been constructed, PhIP-Seq data can be obtained for analysis within a week.

MHCflurry: Open-Source Class I MHC Binding Affinity Prediction.

Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry's prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices.

Two classes of broadly neutralizing antibodies within a single lineage directed to the high-mannose patch of HIV envelope.

UNLABELLED: The high-mannose patch of human immunodeficiency virus (HIV) envelope (Env) elicits broadly neutralizing antibodies (bnAbs) during natural infection relatively frequently, and consequently, this region has become a major target of vaccine design. However, it has also become clear that antibody recognition of the region is complex due, at least in part, to variability in neighboring loops and glycans critical to the epitopes. bnAbs against this region have some shared features and some distinguishing features that are crucial to understand in order to design optimal immunogens that can induce different classes of bnAbs against this region. Here, we compare two branches of a single antibody lineage, in which all members recognize the high-mannose patch. One branch (prototype bnAb PGT128) has a 6-amino-acid insertion in CDRH2 that is crucial for broad neutralization. Antibodies in this branch appear to favor a glycan site at N332 on gp120, and somatic hypermutation is required to accommodate the neighboring V1 loop glycans and glycan heterogeneity. The other branch (prototype bnAb PGT130) lacks the CDRH2 insertion. Antibodies in this branch are noticeably effective at neutralizing viruses with an alternate N334 glycan site but are less able to accommodate glycan heterogeneity. We identify a new somatic variant within this branch that is predominantly dependent on N334. The crystal structure of PGT130 offers insight into differences from PGT128. We conclude that different immunogens may be required to elicit bnAbs that have the optimal characteristics of the two branches of the lineage described. IMPORTANCE: Development of an HIV vaccine is of vital importance for prevention of new infections, and it is thought that elicitation of HIV bnAbs will be an important component of an effective vaccine. Increasingly, bnAbs that bind to the cluster of high-mannose glycans on the HIV envelope glycoprotein, gp120, are being highlighted as important templates for vaccine design. In particular, bnAbs from IAVI donor 36 (PGT125 to PGT131) have been shown to be extremely broad and potent. Combination of these bnAbs enhanced neutralization breadth considerably, suggesting that an optimal immunogen should elicit several antibodies from this family. Here we study the evolution of this antibody family to inform immunogen design. We identify two classes of bnAbs that differ in their recognition of the high-mannose patch and show that different immunogens may be required to elicit these different classes.

Models of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput immunoglobulin sequencing data.

Analyses of somatic hypermutation (SHM) patterns in B cell immunoglobulin (Ig) sequences contribute to our basic understanding of adaptive immunity, and have broad applications not only for understanding the immune response to pathogens, but also to determining the role of SHM in autoimmunity and B cell cancers. Although stochastic, SHM displays intrinsic biases that can confound statistical analysis, especially when combined with the particular codon usage and base composition in Ig sequences. Analysis of B cell clonal expansion, diversification, and selection processes thus critically depends on an accurate background model for SHM micro-sequence targeting (i.e., hot/cold-spots) and nucleotide substitution. Existing models are based on small numbers of sequences/mutations, in part because they depend on data from non-coding regions or non-functional sequences to remove the confounding influences of selection. Here, we combine high-throughput Ig sequencing with new computational analysis methods to produce improved models of SHM targeting and substitution that are based only on synonymous mutations, and are thus independent of selection. The resulting "S5F" models are based on 806,860 Synonymous mutations in 5-mer motifs from 1,145,182 Functional sequences and account for dependencies on the adjacent four nucleotides (two bases upstream and downstream of the mutation). The estimated profiles can explain almost half of the variance in observed mutation patterns, and clearly show that both mutation targeting and substitution are significantly influenced by neighboring bases. While mutability and substitution profiles were highly conserved across individuals, the variability across motifs was found to be much larger than previously estimated. The model and method source code are made available at http://clip.med.yale.edu/SHM.

Autoantigen discovery with a synthetic human peptidome.

Immune responses targeting self-proteins (autoantigens) can lead to a variety of autoimmune diseases. Identification of these antigens is important for both diagnostic and therapeutic reasons. However, current approaches to characterize autoantigens have, in most cases, met only with limited success. Here we present a synthetic representation of the complete human proteome, the T7 peptidome phage display library (T7-Pep), and demonstrate its application to autoantigen discovery. T7-Pep is composed of >413,000 36-residue, overlapping peptides that cover all open reading frames in the human genome, and can be analyzed using high-throughput DNA sequencing. We developed a phage immunoprecipitation sequencing (PhIP-Seq) methodology to identify known and previously unreported autoantibodies contained in the spinal fluid of three individuals with paraneoplastic neurological syndromes. We also show how T7-Pep can be used more generally to identify peptide-protein interactions, suggesting the broader utility of our approach for proteomic research.