Isolation of a Structural Mechanism for Uncoupling T Cell Receptor Signaling from Peptide-MHC Binding.

TCR-signaling strength generally correlates with peptide-MHC binding affinity; however, exceptions exist. We find high-affinity, yet non-stimulatory, interactions occur with high frequency in the human T cell repertoire. Here, we studied human TCRs that are refractory to activation by pMHC ligands despite robust binding. Analysis of 3D affinity, 2D dwell time, and crystal structures of stimulatory versus non-stimulatory TCR-pMHC interactions failed to account for their different signaling outcomes. Using yeast pMHC display, we identified peptide agonists of a formerly non-responsive TCR. Single-molecule force measurements demonstrated the emergence of catch bonds in the activating TCR-pMHC interactions, correlating with exclusion of CD45 from the TCR-APC contact site. Molecular dynamics simulations of TCR-pMHC disengagement distinguished agonist from non-agonist ligands based on the acquisition of catch bonds within the TCR-pMHC interface. The isolation of catch bonds as a parameter mediating the coupling of TCR binding and signaling has important implications for TCR and antigen engineering for immunotherapy.

Antigen Identification for Orphan T Cell Receptors Expressed on Tumor-Infiltrating Lymphocytes.

The immune system can mount T cell responses against tumors; however, the antigen specificities of tumor-infiltrating lymphocytes (TILs) are not well understood. We used yeast-display libraries of peptide-human leukocyte antigen (pHLA) to screen for antigens of "orphan" T cell receptors (TCRs) expressed on TILs from human colorectal adenocarcinoma. Four TIL-derived TCRs exhibited strong selection for peptides presented in a highly diverse pHLA-A∗02:01 library. Three of the TIL TCRs were specific for non-mutated self-antigens, two of which were present in separate patient tumors, and shared specificity for a non-mutated self-antigen derived from U2AF2. These results show that the exposed recognition surface of MHC-bound peptides accessible to the TCR contains sufficient structural information to enable the reconstruction of sequences of peptide targets for pathogenic TCRs of unknown specificity. This finding underscores the surprising specificity of TCRs for their cognate antigens and enables the facile indentification of tumor antigens through unbiased screening.

Vaccination reshapes the virus-specific T cell repertoire in unexposed adults.

We examined how baseline CD4+ T cell repertoire and precursor states impact responses to pathogen infection in humans using primary immunization with yellow fever virus (YFV) vaccine. YFV-specific T cells in unexposed individuals were identified by peptide-MHC tetramer staining and tracked pre- and post-vaccination by tetramers and TCR sequencing. A substantial number of YFV-reactive T cells expressed memory phenotype markers and contained expanded clones in the absence of exposure to YFV. After vaccination, pre-existing YFV-specific T cell populations with low clonal diversity underwent limited expansion, but rare populations with a reservoir of unexpanded TCRs generated robust responses. These altered dynamics reorganized the immunodominance hierarchy and resulted in an overall increase in higher avidity T cells. Thus, instead of further increasing the representation of dominant clones, YFV vaccination recruits rare and more responsive T cells. Our findings illustrate the impact of vaccines in prioritizing T cell responses and reveal repertoire reorganization as a key component of effective vaccination.

Control of Synaptic Connectivity by a Network of Drosophila IgSF Cell Surface Proteins.

We have defined a network of interacting Drosophila cell surface proteins in which a 21-member IgSF subfamily, the Dprs, binds to a nine-member subfamily, the DIPs. The structural basis of the Dpr-DIP interaction code appears to be dictated by shape complementarity within the Dpr-DIP binding interface. Each of the six dpr and DIP genes examined here is expressed by a unique subset of larval and pupal neurons. In the neuromuscular system, interactions between Dpr11 and DIP-γ affect presynaptic terminal development, trophic factor responses, and neurotransmission. In the visual system, dpr11 is selectively expressed by R7 photoreceptors that use Rh4 opsin (yR7s). Their primary synaptic targets, Dm8 amacrine neurons, express DIP-γ. In dpr11 or DIP-γ mutants, yR7 terminals extend beyond their normal termination zones in layer M6 of the medulla. DIP-γ is also required for Dm8 survival or differentiation. Our findings suggest that Dpr-DIP interactions are important determinants of synaptic connectivity.

Deconstructing the peptide-MHC specificity of T cell recognition.

In order to survey a universe of major histocompatibility complex (MHC)-presented peptide antigens whose numbers greatly exceed the diversity of the T cell repertoire, T cell receptors (TCRs) are thought to be cross-reactive. However, the nature and extent of TCR cross-reactivity has not been conclusively measured experimentally. We developed a system to identify MHC-presented peptide ligands by combining TCR selection of highly diverse yeast-displayed peptide-MHC libraries with deep sequencing. Although we identified hundreds of peptides reactive with each of five different mouse and human TCRs, the selected peptides possessed TCR recognition motifs that bore a close resemblance to their known antigens. This structural conservation of the TCR interaction surface allowed us to exploit deep-sequencing information to computationally identify activating microbial and self-ligands for human autoimmune TCRs. The mechanistic basis of TCR cross-reactivity described here enables effective surveillance of diverse self and foreign antigens without necessitating degenerate recognition of nonhomologous peptides.

Structural interplay between germline interactions and adaptive recognition determines the bandwidth of TCR-peptide-MHC cross-reactivity.

The T cell antigen receptor (TCR)-peptide-major histocompatibility complex (MHC) interface is composed of conserved and diverse regions, yet the relative contribution of each in shaping recognition by T cells remains unclear. Here we isolated cross-reactive peptides with limited homology, which allowed us to compare the structural properties of nine peptides for a single TCR-MHC pair. The TCR's cross-reactivity was rooted in highly similar recognition of an apical 'hot-spot' position in the peptide with tolerance of sequence variation at ancillary positions. Furthermore, we found a striking structural convergence onto a germline-mediated interaction between the TCR CDR1α region and the MHC α2 helix in twelve TCR-peptide-MHC complexes. Our studies suggest that TCR-MHC germline-mediated constraints, together with a focus on a small peptide hot spot, might place limits on peptide antigen cross-reactivity.

Antigen identification and high-throughput interaction mapping by reprogramming viral entry.

Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immunoreceptor repertoires and the landscape of potential antigens. To address this, we present receptor-antigen pairing by targeted retroviruses, which combines viral pseudotyping and molecular engineering approaches to enable one-pot library-on-library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cell lines expressing human T or B cell receptors allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable and compatible with any cell type. These techniques provide a suite of tools for targeted viral entry, molecular engineering and interaction screens with broad potential applications.

Yeast display platform with expression of linear peptide epitopes for high-throughput assessment of peptide-MHC-II binding.

Yeast display can serve as a powerful tool to assess the binding of peptides to the major histocompatibility complex (pMHC) and pMHC-T-cell receptor binding. However, this approach is often limited by the need to optimize MHC proteins for yeast surface expression, which can be laborious and may not yield productive results. Here we present a second-generation yeast display platform for class II MHC molecules (MHC-II), which decouples MHC-II expression from yeast-expressed peptides, referred to as "peptide display." Peptide display obviates the need for yeast-specific MHC optimizations and increases the scale of MHC-II alleles available for use in yeast display screens. Because MHC identity is separated from the peptide library, a further benefit of this platform is the ability to assess a single library of peptides against any MHC-II. We demonstrate the utility of the peptide display platform across MHC-II proteins, screening HLA-DR, HLA-DP, and HLA-DQ alleles. We further explore parameters of selections, including reagent dependencies, MHC avidity, and use of competitor peptides. In summary, this approach presents an advance in the throughput and accessibility of screening peptide-MHC-II binding.

Separation of Activated T Cells Using Multidimensional Double Spiral (MDDS) Inertial Microfluidics for High-Efficiency CAR T Cell Manufacturing.

This study introduces a T cell enrichment process, capitalizing on the size differences between activated and unactivated T cells to facilitate the isolation of activated, transducible T cells. By employing multidimensional double spiral (MDDS) inertial sorting, our approach aims to remove unactivated or not fully activated T cells post-activation, consequently enhancing the efficiency of chimeric antigen receptor (CAR) T cell manufacturing. Our findings reveal that incorporating a simple, label-free, and continuous MDDS sorting step yields a purer T cell population, exhibiting significantly enhanced viability and CAR-transducibility (with up to 85% removal of unactivated T cells and approximately 80% recovery of activated T cells); we found approximately 2-fold increase in CAR transduction efficiency for a specific sample, escalating from ∼10% to ∼20%, but this efficiency highly depends on the original T cell sample as MDDS sorting would be more effective for samples possessing a higher proportion of unactivated T cells. This new cell separation process could augment the efficiency, yield, and cost-effectiveness of CAR T cell manufacturing, potentially broadening the accessibility of this transformative therapy and contributing to improved patient outcomes.

Self-determination in the T cell repertoire.

The number of T cells specific for various antigens can vary dramatically. In this issue of Immunity, Nelson et al. (2015) report that these differences might be, at least in part, set by the number of cross-reactive self peptides encountered by T cells during development.

Clonal Deletion Prunes but Does Not Eliminate Self-Specific αß CD8(+) T Lymphocytes.

It has long been thought that clonal deletion efficiently removes almost all self-specific T cells from the peripheral repertoire. We found that self-peptide MHC-specific CD8(+) T cells in the blood of healthy humans were present in frequencies similar to those specific for non-self antigens. For the Y chromosome-encoded SMCY antigen, self-specific T cells exhibited only a 3-fold lower average frequency in males versus females and were anergic with respect to peptide activation, although this inhibition could be overcome by a stronger stimulus. We conclude that clonal deletion prunes but does not eliminate self-specific T cells and suggest that to do so would create holes in the repertoire that pathogens could readily exploit. In support of this hypothesis, we detected T cells specific for all 20 amino acid variants at the p5 position of a hepatitis C virus epitope in a random group of blood donors.

Machine learning optimization of peptides for presentation by class II MHCs.

SUMMARY: T cells play a critical role in cellular immune responses to pathogens and cancer and can be activated and expanded by Major Histocompatibility Complex (MHC)-presented antigens contained in peptide vaccines. We present a machine learning method to optimize the presentation of peptides by class II MHCs by modifying their anchor residues. Our method first learns a model of peptide affinity for a class II MHC using an ensemble of deep residual networks, and then uses the model to propose anchor residue changes to improve peptide affinity. We use a high throughput yeast display assay to show that anchor residue optimization improves peptide binding. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Antibody complementarity determining region design using high-capacity machine learning.

MOTIVATION: The precise targeting of antibodies and other protein therapeutics is required for their proper function and the elimination of deleterious off-target effects. Often the molecular structure of a therapeutic target is unknown and randomized methods are used to design antibodies without a model that relates antibody sequence to desired properties. RESULTS: Here, we present Ens-Grad, a machine learning method that can design complementarity determining regions of human Immunoglobulin G antibodies with target affinities that are superior to candidates derived from phage display panning experiments. We also demonstrate that machine learning can improve target specificity by the modular composition of models from different experimental campaigns, enabling a new integrative approach to improving target specificity. Our results suggest a new path for the discovery of therapeutic molecules by demonstrating that predictive and differentiable models of antibody binding can be learned from high-throughput experimental data without the need for target structural data. AVAILABILITY AND IMPLEMENTATION: Sequencing data of the phage panning experiment are deposited at NIH's Sequence Read Archive (SRA) under the accession number SRP158510. We make our code available at https://github.com/gifford-lab/antibody-2019. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Casting a wider net: Immunosurveillance by nonclassical MHC molecules.

Most studies of T lymphocytes focus on recognition of classical major histocompatibility complex (MHC) class I or II molecules presenting oligopeptides, yet there are numerous variations and exceptions of biological significance based on recognition of a wide variety of nonclassical MHC molecules. These include αß and γδ T cells that recognize different class Ib molecules (CD1, MR-1, HLA-E, G, F, et al.) that are nearly monomorphic within a given species. Collectively, these T cells can be considered "unconventional," in part because they recognize lipids, metabolites, and modified peptides. Unlike classical MHC-specific cells, unconventional T cells generally exhibit limited T-cell antigen receptor (TCR) repertoires and often produce innate immune cell-like rapid effector responses. Exploiting this system in new generation vaccines for human immunodeficiency virus (HIV), tuberculosis (TB), other infectious agents, and cancer was the focus of a recent workshop, "Immune Surveillance by Non-classical MHC Molecules: Improving Diversity for Antigens," sponsored by the National Institute of Allergy and Infectious Diseases. Here, we summarize salient points presented regarding the basic immunobiology of unconventional T cells, recent advances in methodologies to measure unconventional T-cell activity in diseases, and approaches to harness their considerable clinical potential.

Stress-testing the relationship between T cell receptor/peptide-MHC affinity and cross-reactivity using peptide velcro.

T cell receptors (TCRs) bind to peptide-major histocompatibility complex (pMHC) with low affinity (Kd ∼ µM), which is generally assumed to facilitate cross-reactive TCR "scanning" of ligands. To understand the relationship between TCR/pMHC affinity and cross-reactivity, we sought to engineer an additional weak interaction, termed "velcro," between the TCR and pMHC to probe the specificities of TCRs at relatively low and high affinities. This additional interaction was generated through an eight-amino acid peptide library covalently linked to the N terminus of the MHC-bound peptide. Velcro was selected through an affinity-based isolation and was subsequently shown to enhance the cognate TCR/pMHC affinity in a peptide-dependent manner by ∼10-fold. This was sufficient to convert a nonstimulatory ultra-low-affinity ligand into a stimulatory ligand. An X-ray crystallographic structure revealed how velcro interacts with the TCR. To probe TCR cross-reactivity, we screened TCRs against yeast-displayed pMHC libraries with and without velcro, and found that the peptide cross-reactivity profiles of low-affinity (Kd > 100 µM) and high-affinity (Kd ∼ µM) TCR/pMHC interactions are remarkably similar. The conservation of recognition of the TCR for pMHC across affinities reveals the nature of low-affinity ligands for which there are important biological functions and has implications for understanding the specificities of affinity-matured TCRs.

A Bayesian framework for high-throughput T cell receptor pairing.

MOTIVATION: The study of T cell receptor (TCR) repertoires has generated new insights into immune system recognition. However, the ability to robustly characterize these populations has been limited by technical barriers and an inability to reliably infer heterodimeric chain pairings for TCRs. RESULTS: Here, we describe a novel analytical approach to an emerging immune repertoire sequencing method, improving the resolving power of this low-cost technology. This method relies upon the distribution of a T cell population across a 96-well plate, followed by barcoding and sequencing of the relevant transcripts from each T cell. Multicell Analytical Deconvolution for High Yield Paired-chain Evaluation (MAD-HYPE) uses Bayesian inference to more accurately extract TCR information, improving our ability to study and characterize T cell populations for immunology and immunotherapy applications. AVAILABILITY AND IMPLEMENTATION: The MAD-HYPE algorithm is released as an open-source project under the Apache License and is available from https://github.com/birnbaumlab/MAD-HYPE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

T cell receptor signaling is limited by docking geometry to peptide-major histocompatibility complex.

T cell receptor (TCR) engagement of peptide-major histocompatibility complex (pMHC) is essential to adaptive immunity, but it is unknown whether TCR signaling responses are influenced by the binding topology of the TCR-peptide-MHC complex. We developed yeast-displayed pMHC libraries that enabled us to identify new peptide sequences reactive with a single TCR. Structural analysis showed that four peptides bound to the TCR with distinct 3D and 2D affinities using entirely different binding chemistries. Three of the peptides that shared a common docking mode, where key TCR-MHC germline interactions are preserved, induced TCR signaling. The fourth peptide failed to induce signaling and was recognized in a substantially different TCR-MHC binding mode that apparently exceeded geometric tolerances compatible with signaling. We suggest that the stereotypical TCR-MHC docking paradigm evolved from productive signaling geometries and that TCR signaling can be modulated by peptides that are recognized in alternative TCR-pMHC binding orientations.

Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in highly public receptors.

BACKGROUND: The adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cell's specificity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire of millions of unique receptors in each individual. Although many studies have examined how TCR repertoires change in response to disease or drugs, few have explored the temporal dynamics of the TCR repertoire in healthy individuals. RESULTS: Here we report immunosequencing of TCR ß chains (TCRß) from the blood of three healthy individuals at eight time points over one year. TCRß repertoires of all peripheral-blood T cells and sorted memory T cells clustered clearly by individual, systematically demonstrating that TCRß repertoires are specific to individuals across time. This individuality was absent from TCRßs from naive T cells, suggesting that the differences resulted from an individual's antigen exposure history, not genetic background. Many characteristics of the TCRß repertoire (e.g., diversity, clonality) were stable across time, although we found evidence of T cell expansion dynamics even within healthy individuals. We further identified a subset of "persistent" TCRßs present across all time points. These receptors were rich in clonal and highly public receptors and may play a key role in immune system maintenance. CONCLUSIONS: Our results highlight the importance of longitudinal sampling of the immune system, providing a much-needed baseline for TCRß dynamics in healthy individuals. Such a baseline will improve interpretation of changes in the TCRß repertoire during disease or treatment.

Molecular architecture of the αß T cell receptor-CD3 complex.

αß T-cell receptor (TCR) activation plays a crucial role for T-cell function. However, the TCR itself does not possess signaling domains. Instead, the TCR is noncovalently coupled to a conserved multisubunit signaling apparatus, the CD3 complex, that comprises the CD3εγ, CD3εδ, and CD3ζζ dimers. How antigen ligation by the TCR triggers CD3 activation and what structural role the CD3 extracellular domains (ECDs) play in the assembled TCR-CD3 complex remain unclear. Here, we use two complementary structural approaches to gain insight into the overall organization of the TCR-CD3 complex. Small-angle X-ray scattering of the soluble TCR-CD3εδ complex reveals the CD3εδ ECDs to sit underneath the TCR α-chain. The observed arrangement is consistent with EM images of the entire TCR-CD3 integral membrane complex, in which the CD3εδ and CD3εγ subunits were situated underneath the TCR α-chain and TCR ß-chain, respectively. Interestingly, the TCR-CD3 transmembrane complex bound to peptide-MHC is a dimer in which two TCRs project outward from a central core composed of the CD3 ECDs and the TCR and CD3 transmembrane domains. This arrangement suggests a potential ligand-dependent dimerization mechanism for TCR signaling. Collectively, our data advance our understanding of the molecular organization of the TCR-CD3 complex, and provides a conceptual framework for the TCR activation mechanism.