N-glycoproteomic analyses of human intestinal enteroids, varying in histo-blood group geno- and phenotypes, reveal a wide repertoire of fucosylated glycoproteins.

Human noroviruses, globally the main cause of viral gastroenteritis, show strain specific affinity for histo-blood group antigens (HBGA) and can successfully be propagated ex vivo in human intestinal enteroids (HIEs). HIEs established from jejunal stem cells of individuals with different ABO, Lewis and secretor geno- and phenotypes, show varying susceptibility to such infections. Using bottom-up glycoproteomic approaches we have defined and compared the N-linked glycans of glycoproteins of seven jejunal HIEs. Membrane proteins were extracted, trypsin digested, and glycopeptides enriched by hydrophilic interaction liquid chromatography and analyzed by nanoLC-MS/MS. The Byonic software was used for glycopeptide identification followed by hands-on verifications and interpretations. Glycan structures and attachment sites were identified from MS2 spectra obtained by higher-energy collision dissociation through analysis of diagnostic saccharide oxonium ions (B-ions), stepwise glycosidic fragmentation of the glycans (Y-ions), and peptide sequence ions (b- and y-ions). Altogether 694 unique glycopeptides from 93 glycoproteins were identified. The N-glycans encompassed pauci- and oligomannose, hybrid- and complex-type structures. Notably, polyfucosylated HBGA-containing glycopeptides of the four glycoproteins tetraspanin-8, carcinoembryonic antigen-related cell adhesion molecule 5, sucrose-isomaltase and aminopeptidase N were especially prominent and were characterized in detail and related to donor ABO, Lewis and secretor types of each HIE. Virtually no sialylated N-glycans were identified for these glycoproteins suggesting that terminal sialylation was infrequent compared to fucosylation and HBGA biosynthesis. This approach gives unique site-specific information on the structural complexity of N-linked glycans of glycoproteins of human HIEs and provides a platform for future studies on the role of host glycoproteins in gastrointestinal infectious diseases.

Defining T cell receptor repertoires using nanovial-based binding and functional screening.

The ability to selectively bind to antigenic peptides and secrete effector molecules can define rare and low-affinity populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs inducing the secretion of effector molecules including IFN-γ and granzyme B that are accumulated on nanovials, allowing sorting based on both binding and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αß-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes and secretions with oligo-barcoded detection antibodies, we could accurately link TCR sequences to specific targets and rank each TCR based on the corresponding cell's secretion level. Using the technique, we identified an expanded repertoire of functional TCRs targeting viral antigens with high specificity and found rare TCRs with activity against cancer-specific splicing-enhanced epitopes.

Prediction of Peptide and TCR CDR3 Loops in Formation of Class I MHC-Peptide-TCR Complexes Using Molecular Models with Solvation.

Formation of major histocompatibility (MHC)-peptide-T cell receptor (TCR) complexes is central to initiation of an adaptive immune response. These complexes form through initial stabilization of the MHC fold via binding of a short peptide, and subsequent interaction of the TCR to form a ternary complex, with contacts made predominantly through the complementarity-determining region (CDR) loops of the TCR. Stimulation of an immune response is central to cancer immunotherapy. This approach depends on identification of the appropriate combinations of MHC molecules, peptides, and TCRs to elicit an antitumor immune response. This prediction is a current challenge in computational biochemistry. In this chapter, we introduce a predictive method that involves generation of multiple peptides and TCR CDR 3 loop conformations, solvation of these conformers in the context of the MHC-peptide-TCR ternary complex, extraction of parameters from the generated complexes, and use of an AI model to evaluate the potential for the assembled ternary complex to support an immune response.

NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions.

T cell receptors (TCR) define the specificity of T cells and are responsible for their interaction with peptide antigen targets presented in complex with major histocompatibility complex (MHC) molecules. Understanding the rules underlying this interaction hence forms the foundation for our understanding of basic adaptive immunology. Over the last decade, efforts have been dedicated to developing assays for high throughput identification of peptide-specific TCRs. Based on such data, several computational methods have been proposed for predicting the TCR-pMHC interaction. The general conclusion from these studies is that the prediction of TCR interactions with MHC-peptide complexes remains highly challenging. Several reasons form the basis for this including scarcity and quality of data, and ill-defined modeling objectives imposed by the high redundancy of the available data. In this work, we propose a framework for dealing with this redundancy, allowing us to address essential questions related to the modeling of TCR specificity including the use of peptide- versus pan-specific models, how to best define negative data, and the performance impact of integrating of CDR1 and 2 loops. Further, we illustrate how and why it is strongly recommended to include simple similarity-based modeling approaches when validating an improved predictive power of machine learning models, and that such validation should include a performance evaluation as a function of "distance" to the training data, to quantify the potential for generalization of the proposed model. The conclusion of the work is that, given current data, TCR specificity is best modeled using peptide-specific approaches, integrating information from all 6 CDR loops, and with negative data constructed from a combination of true and mislabeled negatives. Comparing such machine learning models to similarity-based approaches demonstrated an increased performance gain of the former as the "distance" to the training data was increased; thus demonstrating an improved generalization ability of the machine learning-based approaches. We believe these results demonstrate that the outlined modeling framework and proposed evaluation strategy form a solid basis for investigating the modeling of TCR specificities and that adhering to such a framework will allow for faster progress within the field. The final devolved model, NetTCR-2.1, is available at https://services.healthtech.dtu.dk/service.php?NetTCR-2.1.

PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes.

Deeper understanding of T-cell-mediated adaptive immune responses is important for the design of cancer immunotherapies and antiviral vaccines against pandemic outbreaks. T-cells are activated when they recognize foreign peptides that are presented on the cell surface by Major Histocompatibility Complexes (MHC), forming peptide:MHC (pMHC) complexes. 3D structures of pMHC complexes provide fundamental insight into T-cell recognition mechanism and aids immunotherapy design. High MHC and peptide diversities necessitate efficient computational modelling to enable whole proteome structural analysis. We developed PANDORA, a generic modelling pipeline for pMHC class I and II (pMHC-I and pMHC-II), and present its performance on pMHC-I here. Given a query, PANDORA searches for structural templates in its extensive database and then applies anchor restraints to the modelling process. This restrained energy minimization ensures one of the fastest pMHC modelling pipelines so far. On a set of 835 pMHC-I complexes over 78 MHC types, PANDORA generated models with a median RMSD of 0.70 Å and achieved a 93% success rate in top 10 models. PANDORA performs competitively with three pMHC-I modelling state-of-the-art approaches and outperforms AlphaFold2 in terms of accuracy while being superior to it in speed. PANDORA is a modularized and user-configurable python package with easy installation. We envision PANDORA to fuel deep learning algorithms with large-scale high-quality 3D models to tackle long-standing immunology challenges.

Information-Driven Docking for TCR-pMHC Complex Prediction.

T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.

Temporal analysis of T-cell receptor-imposed forces via quantitative single molecule FRET measurements.

Mechanical forces acting on ligand-engaged T-cell receptors (TCRs) have previously been implicated in T-cell antigen recognition, yet their magnitude, spread, and temporal behavior are still poorly defined. We here report a FRET-based sensor equipped either with a TCR-reactive single chain antibody fragment or peptide-loaded MHC, the physiological TCR-ligand. The sensor was tethered to planar glass-supported lipid bilayers (SLBs) and informed most directly on the magnitude and kinetics of TCR-imposed forces at the single molecule level. When confronting T-cells with gel-phase SLBs we observed both prior and upon T-cell activation a single, well-resolvable force-peak of approximately 5 pN and force loading rates on the TCR of 1.5 pN per second. When facing fluid-phase SLBs instead, T-cells still exerted tensile forces yet of threefold reduced magnitude and only prior to but not upon activation.

Factors that influence the thymic selection of CD8αα intraepithelial lymphocytes.

Thymocytes bearing αß T cell receptors (TCRαß) with high affinity for self-peptide-MHC complexes undergo negative selection or are diverted to alternate T cell lineages, a process termed agonist selection. Among thymocytes bearing TCRs restricted to MHC class I, agonist selection can lead to the development of precursors that can home to the gut and give rise to CD8αα-expressing intraepithelial lymphocytes (CD8αα IELs). The factors that influence the choice between negative selection versus CD8αα IEL development remain largely unknown. Using a synchronized thymic tissue slice model that supports both negative selection and CD8αα IEL development, we show that the affinity threshold for CD8αα IEL development is higher than for negative selection. We also investigate the impact of peptide presenting cells and cytokines, and the migration patterns associated with these alternative cell fates. Our data highlight the roles of TCR affinity and the thymic microenvironments on T cell fate.

Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.

Porcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the available vaccines. Continuous outbreaks have occurred in Mexico since the early 1980s, which have caused serious economic losses to pig producers. Vaccination can be used to control this disease. Searching for effective antigen candidates against PRV, we first sequenced the PAC1 F protein, then we used various immunoinformatics tools to predict antigenic determinants of B-cells and T-cells against the two glycoproteins of the virus (HN and F proteins). Finally, we used AutoDock Vina to determine the binding energies. We obtained the F gene sequence of a PRV strain collected in the early 1990s in Mexico and compared its amino acid profile with previous and more recent strains, obtaining an identity similarity of 97.78 to 99.26%. For the F proteins, seven linear B-cell epitopes, six conformational B-cell epitopes and twenty-nine T-cell MHC class I epitopes were predicted. For the HN proteins, sixteen linear B-cell epitopes, seven conformational B-cell epitopes and thirty-four T-cell MHC class I epitopes were predicted. The ATRSETDYY and AAYTTTTCF epitopes of the HN protein might be important for neutralizing the viral infection. We determined the in silico binding energy between the predicted epitopes on the F and HN proteins and swine MHC-I molecules. The binding energy of these epitopes ranged from -5.8 to -7.8 kcal/mol. The present study aimed to assess the use of HN and F proteins as antigens, either as recombinant proteins or as a series of peptides that could activate different responses of the immune system. This may help identify relevant immunogens, saving time and costs in the development of new vaccines or diagnostic tools.

Nanodiamond-Mediated Delivery of a G9a Inhibitor for Hepatocellular Carcinoma Therapy.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with high mortality but limited therapeutic options. Epigenetic regulations including DNA methylation and histone modification control gene expressions and play a crucial role during tumorigenesis. G9a, also known as EHMT2 (euchromatic histone-lysine N-methyltransferase 2), is a histone methyltransferase predominantly responsible for dimethylation of histone H3 lysine 9 (H3K9). G9a has been shown to play a key role in promoting tumor progression. Recent studies have identified that G9a is a critical mediator of HCC pathogenesis. UNC0646 is a G9a inhibitor that has shown potent in vitro efficacy. However, due to its water insolubility, the in vivo efficacy of UNC0646 is not satisfactory. In this study, nanodiamonds (NDs) were utilized as a drug delivery platform to improve in vivo delivery of this small-molecule inhibitor. Our results showed that ND-UNC0646 complexes could be rapidly synthesized by physical adsorption, meanwhile possessing favorable drug delivery properties and was able to improve the dispersibility of UNC0646 in water, therefore making it amenable for intravenous administration. The release profile of UNC0646 from ND-UNC0646 was demonstrated to be pH-responsive. Moreover, ND-UNC0646 maintained the biological functionality of UNC0646, with higher efficacy in reducing H3K9 methylation as well as enhanced invasion suppressive effects. Most importantly, increased in vivo efficacy was demonstrated using an orthotopic HCC mouse model, which paves the way of translating this small-molecule inhibitor toward HCC treatment. Our work demonstrates the potential of NDs in the clinical application for HCC treatment.

CD8 Binding of MHC-Peptide Complexes in cis or trans Regulates CD8+ T-cell Responses.

The coreceptor CD8αß can greatly promote activation of T cells by strengthening T-cell receptor (TCR) binding to cognate peptide-MHC complexes (pMHC) on antigen presenting cells and by bringing p56Lck to TCR/CD3. Here, we demonstrate that CD8 can also bind to pMHC on the T cell (in cis) and that this inhibits their activation. Using molecular modeling, fluorescence resonance energy transfer experiments on living cells, biochemical and mutational analysis, we show that CD8 binding to pMHC in cis involves a different docking mode and is regulated by posttranslational modifications including a membrane-distal interchain disulfide bond and negatively charged O-linked glycans near positively charged sequences on the CD8ß stalk. These modifications distort the stalk, thus favoring CD8 binding to pMHC in cis. Differential binding of CD8 to pMHC in cis or trans is a means to regulate CD8+ T-cell responses and provides new translational opportunities.

Structure Based Prediction of Neoantigen Immunogenicity.

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.

Insights for the design of protein lysine methyltransferase G9a inhibitors.

The epigenetic control of gene expression could be affected by addition and/or removal of post-translational modifications such as phosphorylation, acetylation and methylation of histone proteins, as well as methylation of DNA (5-methylation on cytosines). Misregulation of these modifications is associated with altered gene expression, resulting in various disease conditions. G9a belongs to the protein lysine methyltransferases that specifically methylates the K9 residue of histone H3, leading to suppression of several tumor suppressor genes. In this review, G9a functions, role in various diseases, structural biology aspects for inhibitor design, structure-activity relationship among the reported inhibitors are discussed which could aid in the design and development of potent G9a inhibitors for cancer treatment in the future.

SUMOylation of G9a regulates its function as an activator of myoblast proliferation.

The lysine methyltransferase G9a plays a role in many cellular processes. It is a potent repressor of gene expression, a function attributed to its ability to methylate histone and non-histone proteins. Paradoxically, in some instances, G9a can activate gene expression. However, regulators of G9a expression and activity are poorly understood. In this study, we report that endogenous G9a is SUMOylated in proliferating skeletal myoblasts. There are four potential SUMOylation consensus motifs in G9a. Mutation of all four acceptor lysine residues [K79, K152, K256, and K799] inhibits SUMOylation. Interestingly, SUMOylation does not impact G9a-mediated repression of MyoD transcriptional activity or myogenic differentiation. In contrast, SUMO-defective G9a is unable to enhance proliferation of myoblasts. Using complementation experiments, we show that the proliferation defect of primary myoblasts from conditional G9a-deficient mice is rescued by re-expression of wild-type, but not SUMOylation-defective, G9a. Mechanistically, SUMOylation acts as signal for PCAF (P300/CBP-associated factor) recruitment at E2F1-target genes. This results in increased histone H3 lysine 9 acetylation marks at E2F1-target gene promoters that are required for S-phase progression. Our studies provide evidence by which SUMO modification of G9a influences the chromatin environment to impact cell cycle progression.

How peptide/MHC presence affects the dynamics of the LC13 T-cell receptor.

The interaction between T-cell receptors (TCRs) of T-cells and potentially immunogenic peptides presented by MHCs of antigen presenting cells is one of the most important mechanisms of the adaptive human immune system. A large number of structural simulations of the TCR/peptide/MHC system have been carried out. However, to date no study has investigated the differences of the dynamics between free TCRs and pMHC bound TCRs on a large scale. Here we present a study totalling 37 100 ns investigating the LC13 TCR in its free form as well as in complex with HLA-B*08:01 and different peptides. Our results show that the dynamics of the bound and unbound LC13 TCR differ significantly. This is reflected in (a) expected results such as an increased flexibility and increased solvent accessible surface of the CDRs of unbound TCR simulations but also in (b) less expected results such as lower CDR distances and compactness as well as alteration in the hydrogen bond network around CDR3α of unbound TCR simulations. Our study further emphasises the structural flexibility of TCRs and confirms the importance of the CDR3 loops for the adoption to MHC.

A sarcoidosis clinician's perspective of MHC functional elements outside the antigen binding site.

Sarcoidosis is a multisystem granulomatous disease of unknown cause. Evidence supports an integral role for interactions at the MHC binding site in the development of sarcoidosis. However, despite this evidence, there are clinical data that suggest that additional mechanisms are involved in the immunopathogenesis of this disease. This manuscript provides a brief clinical description of sarcoidosis, and a clinician's perspective of the immunopathogenesis of sarcoidosis in terms of the MHC binding site, MHC functional elements beyond the binding site, and other possible alternative mechanisms. Input from clinicians will be essential in establishing the immunologic cause of sarcoidosis as a detailed phenotypic characterization of disease will be required.

A window of opportunity for cooperativity in the T Cell Receptor.

The T-cell antigen receptor (TCR) is pre-organised in oligomers, known as nanoclusters. Nanoclusters could provide a framework for inter-TCR cooperativity upon peptide antigen-major histocompatibility complex (pMHC) binding. Here we have used soluble pMHC oligomers in search for cooperativity effects along the plasma membrane plane. We find that initial binding events favour subsequent pMHC binding to additional TCRs, during a narrow temporal window. This behaviour can be explained by a 3-state model of TCR transition from Resting to Active, to a final Inhibited state. By disrupting nanoclusters and hampering the Active conformation, we show that TCR cooperativity is consistent with TCR nanoclusters adopting the Active state in a coordinated manner. Preferential binding of pMHC to the Active TCR at the immunological synapse suggests that there is a transient time frame for signal amplification in the TCR, allowing the T cells to keep track of antigen quantity and binding time.

Discovery of Reversible DNA Methyltransferase and Lysine Methyltransferase G9a Inhibitors with Antitumoral in Vivo Efficacy.

Using knowledge- and structure-based approaches, we designed and synthesized reversible chemical probes that simultaneously inhibit the activity of two epigenetic targets, histone 3 lysine 9 methyltransferase (G9a) and DNA methyltransferases (DNMT), at nanomolar ranges. Enzymatic competition assays confirmed our design strategy: substrate competitive inhibitors. Next, an initial exploration around our hit 11 was pursued to identify an adequate tool compound for in vivo testing. In vitro treatment of different hematological neoplasia cell lines led to the identification of molecules with clear antiproliferative efficacies (GI50 values in the nanomolar range). On the basis of epigenetic functional cellular responses (levels of lysine 9 methylation and 5-methylcytosine), an acceptable therapeutic window (around 1 log unit) and a suitable pharmacokinetic profile, 12 was selected for in vivo proof-of-concept ( Nat. Commun. 2017 , 8 , 15424 ). Herein, 12 achieved a significant in vivo efficacy: 70% overall tumor growth inhibition of a human acute myeloid leukemia (AML) xenograft in a mouse model.

Detailed Exploration around 4-Aminoquinolines Chemical Space to Navigate the Lysine Methyltransferase G9a and DNA Methyltransferase Biological Spaces.

Epigenetic regulators that exhibit aberrant enzymatic activities or expression profiles are potential therapeutic targets for cancers. Specifically, enzymes responsible for methylation at histone-3 lysine-9 (like G9a) and aberrant DNA hypermethylation (DNMTs) have been implicated in a number of cancers. Recently, molecules bearing a 4-aminoquinoline scaffold were reported as dual inhibitors of these targets and showed a significant in vivo efficacy in animal models of hematological malignancies. Here, we report a detailed exploration around three growing vectors born by this chemotype. Exploring this chemical space led to the identification of features to navigate G9a and DNMT1 biological spaces: not only their corresponding exclusive areas, selective compounds, but also common spaces. Thus, we identified from selective G9a and first-in-class DNMT1 inhibitors, >1 log unit between their IC50 values, with IC50 < 25 nM (e.g., 43 and 26, respectively) to equipotent inhibitors with IC50 < 50 nM for both targets (e.g., 13). Their ADME/Tox profiling and antiproliferative efficacies, versus some cancer cell lines, are also reported.

Treatment of T1D via optimized expansion of antigen-specific Tregs induced by IL-2/anti-IL-2 monoclonal antibody complexes and peptide/MHC tetramers.

Type 1 diabetes can be overcome by regulatory T cells (Treg) in NOD mice yet an efficient method to generate and maintain antigen-specific Treg is difficult to come by. Here, we devised a combination therapy of peptide/MHC tetramers and IL-2/anti-IL-2 monoclonal antibody complexes to generate antigen-specific Treg and maintain them over extended time periods. We first optimized treatment protocols conceived to obtain an improved islet-specific Treg/effector T cell ratio that led to the in vivo expansion and activation of these Treg as well as to an improved suppressor function. Optimized protocols were applied to treatment for testing diabetes prevention in NOD mice as well as in an accelerated T cell transfer model of T1D. The combined treatment led to robust protection against diabetes, and in the NOD model, to a close to complete prevention of insulitis. Treatment was accompanied with increased secretion of IL-10, detectable in total splenocytes and in Foxp3- CD4 T cells. Our data suggest that a dual protection mechanism takes place by the collaboration of Foxp3+ and Foxp3- regulatory cells. We conclude that antigen-specific Treg are an important target to improve current clinical interventions against this disease.