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It has been widely appreciated that numerous bacterial species express chitinases for the purpose of degrading environmental chitin. However, chitinases and chitin-binding proteins are also expressed by pathogenic bacterial species during infection even though mammals do not produce chitin.

MHC restriction, which describes the binding of TCRs from CD4+T cells to class II MHC proteins and TCRs from CD8+T cells to class I MHC proteins, is a hallmark of immunology. Seemingly rare TCRs that break this paradigm exist, but mechanistic insight into their behavior is lacking. TIL1383I is a prototypical class-mismatched TCR, cloned from a CD4+T cell but recognizing the tyrosinase tumor antigen presented by the class I MHC HLA-A2 in a fully functional manner. Here we find that TIL1383I binds this class I target with a highly atypical geometry. Despite unorthodox binding, TCR signaling, antigen specificity, and the ability to use CD8 are maintained. Structurally, a key feature of TIL1383I is an exceptionally long CDR3β loop that mediates functions that are traditionally performed separately by hypervariable and germline loops in canonical TCR structures. Our findings thus expand the range of known TCR binding geometries compatible with normal function and specificity, provide insight into the determinants of MHC restriction, and may help guide TCR selection and engineering for immunotherapy.

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.

The term “microbiota” invokes images of mucosal surfaces densely populated with bacteria. These surfaces and the luminal compartments they form indeed predominantly harbor bacteria., The term “microbiota” invokes images of mucosal surfaces densely populated with bacteria. These surfaces and the luminal compartments they form indeed predominantly harbor bacteria. However, research from this past decade has started to complete the picture by focusing on important but largely neglected constituents of the microbiota: fungi, viruses, and archaea. The community of commensal fungi, also called the mycobiota, interacts with commensal bacteria and the host. It is thus not surprising that changes in the mycobiota have significant impact on host health and are associated with pathological conditions such as inflammatory bowel disease (IBD). In this review we will give an overview of why the mycobiota is an important research area and different mycobiota research tools. We will specifically focus on distinguishing transient and actively colonizing fungi of the oral and gut mycobiota and their roles in health and disease. In addition to correlative and observational studies, we will discuss mechanistic studies on specific cross-kingdom interactions of fungi, bacteria, and the host.

Potassium ion homeostasis is essential for bacterial survival, playing roles in osmoregulation, pH homeostasis, regulation of protein synthesis, enzyme activation, membrane potential adjustment and electrical signaling. To accomplish such diverse physiological tasks, it is not surprising that a single bacterium typically encodes several potassium uptake and release systems. To understand the role each individual protein fulfills and how these proteins work in concert, it is important to identify the molecular details of their function. One needs to understand whether the systems transport ions actively or passively, and what mechanisms or ligands lead to the activation or inactivation of individual systems. Combining mechanistic information with knowledge about the physiology under different stress situations, such as osmostress, pH stress or nutrient limitation, one can identify the task of each system and deduce how they are coordinated with each other. By reviewing the general principles of bacterial membrane physiology and describing the molecular architecture and function of several bacterial K(+)-transporting systems, we aim to provide a framework for microbiologists studying bacterial potassium homeostasis and the many K(+)-translocating systems that are still poorly understood.

T cell receptors (TCRs) have emerged as a new class of immunological therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biology, the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.

Summary CD8+ T cell recognition of peptide epitopes plays a central role in immune responses against pathogens and tumors. However, the rules that govern which peptides are truly recognized by existing T cell receptors (TCRs) remain poorly understood, precluding accurate predictions of neo-epitopes for cancer immunotherapy. Here, we capitalize on recent (neo-)epitope data to train a predictor of immunogenic epitopes (PRIME), which captures molecular properties of both antigen presentation and TCR recognition. PRIME not only improves prioritization of neo-epitopes but also correlates with T cell potency and unravels biophysical determinants of TCR recognition that we experimentally validate. Analysis of cancer genomics data reveals that recurrent mutations tend to be less frequent in patients where they are predicted to be immunogenic, providing further evidence for immunoediting in human cancer. PRIME will facilitate identification of pathogen epitopes in infectious diseases and neo-epitopes in cancer immunotherapy., Graphical Abstract, Highlights Development of a predictor of immunogenic CD8 T-cell epitopes (PRIME) PRIME shows improved prediction accuracy on neo-epitopes PRIME reveals molecular determinants of TCR recognition PRIME supports immunoediting of recurrent cancer mutations, Schmidt et al. develop a predictor of immunogenicity (PRIME) for CD8 T cell epitopes that captures antigen presentation on HLA molecules and TCR recognition. Their results reveal molecular determinants of TCR recognition and support immunoediting acting on recurrent cancer mutations.

OBJECTIVES/GOALS: Our goal is to employ a structure-guided design approach to engineering a safer and more effective variant of the TIL1383I T cell receptor (TCR) currently under study in clinical trials for malignant melanoma METHODS/STUDY POPULATION: Using our unpublished structure of TIL1383I we are in process of designing a panel of TCR variants with the goal of identifying candidates that improve “focus” towards the tyrosinase antigen presented on the MHC class I molecule HLA-A2. RESULTS/ANTICIPATED RESULTS: Structural analysis of TIL1383I revealed key residues, particularly beta-chain residues E97, G101, L102, responsible for engaging the tyrosinase peptide bound to HLA-A2. The crystal structure of TIL1383I in complex with tyrosinase-HLA-A2 also highlighted its uncharacteristic binding geometry and we therefore hypothesize that this binding orientation is associated with the observed CD8 co-receptor independence of TIL1383I. Indeed, functional analysis with TIL1383I-transduced CD8-positive and CD8-negative T cells, transduced T cells expressing a truncated CD8 lacking the intracellular LCK signaling domain, and tyrosinase peptide variants presented by HLA-A2 mutants outline this co-receptor independence. Combined with our interrogation of tyrosinase peptide cross-reactivity via a peptide positional scanning library approach, structure-guided design resulted in the identification of TIL1383I variants with improved binding affinities to the tyrosinase peptide as well as an understanding of structural characteristics that may contribute to TIL1383I’s co-receptor independence.

The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8+ T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

Using a variety of activating and inhibitory receptors, natural killer (NK) cells protect against disease by eliminating cells that have downregulated class I major histocompatibility complex (MHC) proteins, such as in response to cell transformation or viral infection. The inhibitory murine NK receptor Ly49C specifically recognizes the class I MHC protein H-2Kb. Unusual among NK receptors, Ly49C exhibits a peptide-dependent sensitivity to H-2Kb recognition, which has not been explained despite detailed structural studies. To gain further insight into Ly49C peptide sensitivity, we examined Ly49C recognition biochemically and through the lens of dynamic allostery. We found that the peptide sensitivity of Ly49C arises through small differences in H-2Kb-binding affinity. Although molecular dynamics simulations supported a role for peptide-dependent protein dynamics in producing these differences in binding affinity, calorimetric measurements indicated an enthalpically as opposed to entropically driven process. A quantitative linkage analysis showed that this emerges from peptide-dependent dynamic tuning of electrostatic interactions across the Ly49C–H-2Kb interface. We propose a model whereby different peptides alter the flexibility of H-2Kb, which in turn changes the strength of electrostatic interactions across the protein–protein interface. Our results provide a quantitative assessment of how peptides alter Ly49C-binding affinity, suggest the underlying mechanism, and demonstrate peptide-driven allostery at work in class I MHC proteins. Lastly, our model provides a solution for how dynamic allostery could impact binding of some, but not all, class I MHC partners depending on the structural and chemical composition of the interfaces.

OBJECTIVES/GOALS: Neoantigen vaccine immunotherapies have shown promise in clinical trials, but identifying which peptides to include in a vaccine remains a challenge. We aim to establish that molecular structural features can help predict which neoantigens to target to achieve tumor regression. METHODS/STUDY POPULATION: Proteins were prepared by recombinant expression in E. coli followed by in vitro refolding. Correctly folded proteins were purified by chromatography. Affinities of protein-protein interactions were measured by surface plasmon resonance (SPR) and thermal stabilities of proteins were determined by differential scanning fluorimetry. All experiments were performed at least in triplicate. Protein crystals were obtained by hanging drop vapor diffusion. The protein crystal structures were solved by molecular replacement and underwent several rounds of automated refinement. Molecular dynamics simulations were performed using the AMBER molecular dynamics package. RESULTS/ANTICIPATED RESULTS: A T cell receptor (TCR) expressed by tumor-infiltrating T cells exhibited a 20-fold stronger binding affinity to the neoantigen peptide compared to the self-peptide. X-ray crystal structures of the peptides with the major histocompatibility complex (MHC) protein demonstrated that a non-mutated residue in the peptide samples different positions with the mutation. The difference in conformations of the non-mutated residue was supported by molecular dynamics simulations. Crystal structures of the TCR engaging both peptide/MHCs suggested that the conformation favored by the mutant peptide was crucial for TCR binding. The TCR bound the neoantigen/MHC with faster binding kinetics. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results suggest that the mutation impacts the conformation of another residue in the peptide, and this alteration allows for more favorable T cell receptor binding to the neoantigen. This highlights the potential of non-mutated residues in contributing to neoantigen recognition.

OBJECTIVES/SPECIFIC AIMS: We are exploring the structure of the interaction between an immunogenic neoantigen and a T cell receptor (TCR) that recognizes the neoantigen while tolerating the counterpart self antigen. No structural example exists to date of how a TCR can discriminate between a neoantigen and the self antigen. We aim to determine the structural and biophysical features that underlie the immunogenicity for this neoantigen, and the features we determine are likely to be present in other immunogenic neoantigens. Algorithms to predict the immunogenicity of neoantigens are available, but do not incorporate structural or biophysical factors. We aim to improve these methods for immunogenic neoantigen prediction by determining structural and biophysical factors that result in recognition by the immune system. METHODS/STUDY POPULATION: Recombinant protein expression, production, and purification. Protein x-ray crystallography. Biophysical protein-protein binding experiments RESULTS/ANTICIPATED RESULTS: The T cell receptor (TCR) bound to the neoantigen with an affinity 15-fold higher than the self antigen. The leucine to phenylalanine mutation occurs at position 8 of a 9-amino acid long peptide antigen. This position is typically in the interface bound by the T cell receptor. The structures of the unbound neoantigen and self antigen showed that the mutated residue was in the TCR interface. Additionally we noted a change in the side chain position of a proximal tryptophan, potentially due to clashes with the larger phenylalanine residue. The structure of the TCR bound to the neoantigen showed that the TCR interacted with the tryptophan in the mutation-induced conformation and with the phenylalanine residue. Thus the mutation may be altering TCR binding affinity by interactions of the residue itself with the TCR, and by locking the proximal tryptophan residue in an optimal position to interact with the TCR. We are testing the contributions of each of these factors to the overall affinity change. Hydrophobicity has been linked to immunogenicity, so mutations that increase hydrophobicity compared to the self antigen are likely to be immunogenic. However, leucine and phenylalanine are similar on hydrophobicity scales. On the other hand, a side chain rotation is unlikely to represent a large energy barrier. Therefore, we hypothesize that another property of the phenylalanine, such as size or aromaticity, is driving the affinity difference. DISCUSSION/SIGNIFICANCE OF IMPACT: Traditional forms of cancer therapy do not specifically target cancer cells, and their toxicity to healthy cells limits their effectiveness. Immunotherapy, which involves orchestrating a specific anti-cancer immune response, is now an established cancer therapy. Several forms of immunotherapy target “neoantigens,” which are derived from mutated proteins in cancer, and are therefore are cancer-specific. Neoantigens represent a foothold that can allow the immune system to distinguish between cancer cells and healthy cells, and thus specifically target cancer cells for destruction while imparting no activity toward healthy cells that lack the neoantigen. Most cancer mutations that result in neoantigens arise from random passenger mutations in cancer and will be different among patients. Neoantigen-based cancer therapies are thus a precision medicine technique. The quality of neoantigens to induce an immune response (immunogenicity), which relates to how likely they are to be presented to the immune system and recognized as foreign, has been shown to be a critical factor in predicting the outcome of immunotherapy treatment. We are investigating, on a structural and biophysical level, features that may increase the likelihood of a neoantigen being recognized as foreign by the immune system. The structural insight we gain can be incorporated into algorithms that predict neoantigens from cancer exome sequencing for patient-specific identification of immunogenic neoantigens for immunotherapeutic intervention.