A peptide filtering relation quantifies MHC class I peptide optimization

Evidence of focusing the MHC class I immunopeptidome by tapasin

Major Histocompatibility Complex class I (MHC-I) molecules bind and present peptides to cytotoxic T cells, protecting against pathogens and cancer. MHC-I is highly polymorphic and each allotype is promiscuous, and capable of binding a unique and diverse repertoire of peptide ligands. The peptide editing chaperone tapasin optimizes this allotype specific repertoire of peptides, resulting in the selection of high affinity peptides. MHC-I allotypes differ in the extent they engage tapasin. This suggests that tapasin-dependent MHC-I allotypes should present a less diverse repertoire that is enriched in higher-affinity peptides, and which are present in higher abundance, than tapasin independent MHC-I allotypes, which should present a broader repertoire containing peptides with a lower average affinity. Experimental verification of this hypothesis has been confounded by the different peptide binding specificities of MHC-I allotypes. Here, we independently investigated the peptide focusing function of tapasin by introducing a point mutation into a tapasin independent MHC-I allotype that dramatically increased its tapasin dependence without substantially altering its peptide binding specificity. This allowed us to demonstrate ligand focusing by tapasin at both the repertoire level in cellulo, and by using an in vitro system in which tapasin was artificially tethered to MHC-I, at the individual peptide level. We found that tapasin had a greater influence on tapasin dependent MHC-I molecules, and that tapasin modulated peptide selection according to peptide-MHC-I complex stability, disfavoring short-lived peptide-MHC-I complexes. Thus, tapasin dependent MHC-I molecules experience greater tapasin filtering, resulting in less diverse MHC-I immunopeptidomes that are enriched in high affinity peptide-MHC-I complexes.

Endoplasmic Reticulum-Targeted Phototherapy Remodels the Tumor Immunopeptidome to Enhance Immunogenic Cell Death and Adaptive Anti-Tumor Immunity

Background: Endoplasmic reticulum (ER)-targeted phototherapy has emerged as a promising approach to amplify ER stress, induce immunogenic cell death (ICD), and enhance anti-tumor immunity. However, its impact on the antigenicity of dying tumor cells remains poorly understood. Methods: Laser activation of the ER-targeted photosensitizer ER-Cy-poNO2 was performed to investigate its effects on tumor cell antigenicity. Transcriptomic analysis was carried out to assess gene expression changes. Immunopeptidomics profiling was used to identify high-affinity major histocompatibility complex class I (MHC-I) ligands. In vitro functional studies were conducted to evaluate dendritic cell maturation and T lymphocyte activation, while in vivo experiments were performed by combining the identified peptide with poly IC to evaluate anti-tumor immunity. Results: Laser activation of ER-Cy-poNO2 significantly remodeled the antigenic landscape of 4T-1 tumor cells, enhancing their immunogenicity. Transcriptomic analysis revealed upregulation of antigen processing and presentation pathways. Immunopeptidomics profiling identified multiple high-affinity MHC-I ligands, with IF4G3986-994 (QGPKTIEQI) showing exceptional immunogenicity. In vitro, IF4G3986-994 promoted dendritic cell maturation and enhanced T lymphocytes activation. In vivo, the combination of IF4G3986-994 with poly IC elicited robust anti-tumor immunity, characterized by increased CD8+ T lymphocytes infiltration, reduced regulatory T cells (Tregs) in the tumor microenvironment, elevated systemic Interferon-gamma (IFN-γ) levels, and significant tumor growth inhibition without systemic toxicity. Conclusions: These findings establish a mechanistic link between ER stress-driven ICD, immunopeptidome remodeling, and adaptive immune activation, highlighting the potential of ER-targeted phototherapy as a platform for identifying immunogenic peptides and advancing peptide-based cancer vaccines.

Antigen presentation by MHC-II is shaped by competitive and cooperative allosteric mechanisms of peptide exchange

Major histocompatibility complex class II (MHC-II) presents antigens to T helper cells. The spectrum of presented peptides is regulated by the exchange catalyst human leukocyte antigen DM (HLA-DM), which dissociates peptide-MHC-II complexes in the endosome. How susceptible a peptide is to HLA-DM is mechanistically not understood. Here, we present a data-driven mathematical model for the conformational landscape of MHC-II that explains the wide range of measured HLA-DM susceptibilities and predicts why some peptides are largely HLA-DM-resistant. We find that the conformational plasticity of MHC-II mediates both allosteric competition and cooperation between peptide and HLA-DM. Competition causes HLA-DM susceptibility to be proportional to the intrinsic peptide off-rate. Remarkably, diverse MHC-II allotypes with conserved HLA-DM interactions show a universal linear susceptibility function. However, HLA-DM-resistant peptides deviate from this susceptibility function; we predict resistance to be caused by fast peptide association with MHC-II. Thus, our study provides quantitative insight into peptide and MHC-II allotype parameters that shape class-II antigen presentation.

Tapasin assembly surveillance by the RNF185/Membralin ubiquitin ligase complex regulates MHC-I surface expression

Immune surveillance by cytotoxic T cells eliminates tumor cells and cells infected by intracellular pathogens. This process relies on the presentation of antigenic peptides by Major Histocompatibility Complex class I (MHC-I) at the cell surface. The loading of these peptides onto MHC-I depends on the peptide loading complex (PLC) at the endoplasmic reticulum (ER). Here, we uncovered that MHC-I antigen presentation is regulated by ER-associated degradation (ERAD), a protein quality control process essential to clear misfolded and unassembled proteins. An unbiased proteomics screen identified the PLC component Tapasin, essential for peptide loading onto MHC-I, as a substrate of the RNF185/Membralin ERAD complex. Loss of RNF185/Membralin resulted in elevated Tapasin steady state levels and increased MHC-I at the surface of professional antigen presenting cells. We further show that RNF185/Membralin ERAD complex recognizes unassembled Tapasin and limits its incorporation into PLC. These findings establish a novel mechanism controlling antigen presentation and suggest RNF185/Membralin as a potential therapeutic target to modulate immune surveillance.

Advancing our knowledge of antigen processing with computational modelling, structural biology, and immunology

Antigen processing is an immunological mechanism by which intracellular peptides are transported to the cell surface while bound to Major Histocompatibility Complex molecules, where they can be surveyed by circulating CD8+ or CD4+ T-cells, potentially triggering an immunological response. The antigen processing pathway is a complex multistage filter that refines a huge pool of potential peptide ligands derived from protein degradation into a smaller ensemble for surface presentation. Each stage presents unique challenges due to the number of ligands, the polymorphic nature of MHC and other protein constituents of the pathway and the nature of the interactions between them. Predicting the ensemble of displayed peptide antigens, as well as their immunogenicity, is critical for improving T cell vaccines against pathogens and cancer. Our predictive abilities have always been hindered by an incomplete empirical understanding of the antigen processing pathway. In this review, we highlight the role of computational and structural approaches in improving our understanding of antigen processing, including structural biology, computer simulation, and machine learning techniques, with a particular focus on the MHC-I pathway.

Tapasin-mediated editing of the MHC I immunopeptidome is epitope specific and dependent on peptide off-rate, abundance, and level of tapasin expression

Tapasin, a component of the major histocompatibility complex (MHC) I peptide loading complex, edits the repertoire of peptides that is presented at the cell surface by MHC I and thereby plays a key role in shaping the hierarchy of CD8+ T-cell responses to tumors and pathogens. We have developed a system that allows us to tune the level of tapasin expression and independently regulate the expression of competing peptides of different off-rates. By quantifying the relative surface expression of peptides presented by MHC I molecules, we show that peptide editing by tapasin can be measured in terms of “tapasin bonus,” which is dependent on both peptide kinetic stability (off-rate) and peptide abundance (peptide supply). Each peptide has therefore an individual tapasin bonus fingerprint. We also show that there is an optimal level of tapasin expression for each peptide in the immunopeptidome, dependent on its off-rate and abundance. This is important, as the level of tapasin expression can vary widely during different stages of the immune response against pathogens or cancer and is often the target for immune escape.

Peptide Presentation to T Cells: Solving the Immunogenic Puzzle: Systems Immunology Profiling of Antigen Presentation for Prediction of CD8+ T Cell Immunogenicity

The vertebrate immune system uses an impressive arsenal of mechanisms to combat harmful cellular states such as infection. One way is via cells delivering real-time snapshots of their protein content to the cell surface in the form of short peptides. Specialized immune cells (T cells) sample these peptides and assess whether they are foreign, warranting an action such as destruction of the infected cell. The delivery of peptides to the cell surface is termed antigen processing and presentation, and decades of research have provided unprecedented understanding of this process. However, predicting the capacity for a given peptide to be immunogenic-to elicit a T cell response-has remained both enigmatic and a long sought-after goal. In the era of big data, a point is being approached where the steps of antigen processing and presentation can be quantified and assessed against peptide immunogenicity in order to build predictive models. This review presents new findings in this area and contemplates challenges ahead.

A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules

Major histocompatibility complex-I (MHC-I) molecules play a central role in the immune response to viruses and cancers. They present peptides on the surface of affected cells, for recognition by cytotoxic T cells. Determining which peptides are presented, and in what proportion, has profound implications for developing effective, medical treatments. However, our ability to predict peptide presentation levels is currently limited. Existing prediction algorithms focus primarily on the binding affinity of peptides to MHC-I, and do not predict the relative abundance of individual peptides on the surface of antigen-presenting cells in situ which is a critical parameter for determining the strength and specificity of the ensuing immune response. Here, we develop and experimentally verify a mechanistic model for predicting cell-surface presentation of competing peptides. Our approach explicitly models key steps in the processing of intracellular peptides, incorporating both peptide binding affinity and intracellular peptide abundance. We use the resulting model to predict how the peptide repertoire is modified by interferon-γ, an immune modulator well known to enhance expression of antigen processing and presentation proteins.

Direct evidence for conformational dynamics in major histocompatibility complex class I molecules

Major histocompatibility complex class I molecules (MHC I) help protect jawed vertebrates by binding and presenting immunogenic peptides to cytotoxic T lymphocytes. Peptides are selected from a large diversity present in the endoplasmic reticulum. However, only a limited number of peptides complement the polymorphic MHC specificity determining pockets in a way that leads to high-affinity peptide binding and efficient antigen presentation. MHC I molecules possess an intrinsic ability to discriminate between peptides, which varies in efficiency between allotypes, but the mechanism of selection is unknown. Elucidation of the selection mechanism is likely to benefit future immune-modulatory therapies. Evidence suggests peptide selection involves transient adoption of alternative, presumably higher energy conformations than native peptide-MHC complexes. However, the instability of peptide-receptive MHC molecules has hindered characterization of such conformational plasticity. To investigate the dynamic nature of MHC, we refolded MHC proteins with peptides that can be hydrolyzed by UV light and thus released. We compared the resultant peptide-receptive MHC molecules with non-hydrolyzed peptide-loaded MHC complexes by monitoring the exchange of hydrogen for deuterium in solution. We found differences in hydrogen-deuterium exchange between peptide-loaded and peptide-receptive molecules that were negated by the addition of peptide to peptide-receptive MHC molecules. Peptide hydrolysis caused significant increases in hydrogen-deuterium exchange in sub-regions of the peptide-binding domain and smaller increases elsewhere, including in the α3 domain and the non-covalently associated β2-microglobulin molecule, demonstrating long-range dynamic communication. Comparing two MHC allotypes revealed allotype-specific differences in hydrogen-deuterium exchange, consistent with the notion that MHC I plasticity underpins peptide selection.

Tailored Approaches in Drug Development and Diagnostics: From Molecular Design to Biological Model Systems

Approaches to increase the efficiency in developing drugs and diagnostics tools, including new drug delivery and diagnostic technologies, are needed for improved diagnosis and treatment of major diseases and health problems such as cancer, inflammatory diseases, chronic wounds, and antibiotic resistance. Development within several areas of research ranging from computational sciences, material sciences, bioengineering to biomedical sciences and bioimaging is needed to realize innovative drug development and diagnostic (DDD) approaches. Here, an overview of recent progresses within key areas that can provide customizable solutions to improve processes and the approaches taken within DDD is provided. Due to the broadness of the area, unfortunately all relevant aspects such as pharmacokinetics of bioactive molecules and delivery systems cannot be covered. Tailored approaches within (i) bioinformatics and computer-aided drug design, (ii) nanotechnology, (iii) novel materials and technologies for drug delivery and diagnostic systems, and (iv) disease models to predict safety and efficacy of medicines under development are focused on. Current developments and challenges ahead are discussed. The broad scope reflects the multidisciplinary nature of the field of DDD and aims to highlight the convergence of biological, pharmaceutical, and medical disciplines needed to meet the societal challenges of the 21st century.

Host genotype and time dependent antigen presentation of viral peptides: predictions from theory

The rate of progression of HIV infected individuals to AIDS is known to vary with the genotype of the host, and is linked to their allele of human leukocyte antigen (HLA) proteins, which present protein degradation products at the cell surface to circulating T-cells. HLA alleles are associated with Gag-specific T-cell responses that are protective against progression of the disease. While Pol is the most conserved HIV sequence, its association with immune control is not as strong. To gain a more thorough quantitative understanding of the factors that contribute to immunodominance, we have constructed a model of the recognition of HIV infection by the MHC class I pathway. Our model predicts surface presentation of HIV peptides over time, demonstrates the importance of viral protein kinetics, and provides evidence of the importance of Gag peptides in the long-term control of HIV infection. Furthermore, short-term dynamics are also predicted, with simulation of virion-derived peptides suggesting that efficient processing of Gag can lead to a 50% probability of presentation within 3 hours post-infection, as observed experimentally. In conjunction with epitope prediction algorithms, this modelling approach could be used to refine experimental targets for potential T-cell vaccines, both for HIV and other viruses.

Parameter estimation for gene regulatory networks: a two-stage MCMC Bayesian approach

Genetic regulatory networks have emerged as a useful way to elucidate the biochemical pathways for biological functions. Yet, determination of the exact parametric forms for these models remain a major challenge. In this paper, we present a novel computational approach implemented in C++ to solve this inverse problem. This takes the form of an optimization stage first after which Bayesian filtering takes place. The key advantage of such a flexible, general and robust approach is that it provides us with a joint probability distribution of the model parameters instead of single estimates, which we can propagate to final predictions. We apply these ideas to time series data from gene circuit models using state space representation. We show that unsound terms from a more generalized model can be efficiently pruned by our approach. We believe our work offers a new insight towards understanding the behaviour, mechanisms and thermodynamics of system biology.

The Role of Multiscale Protein Dynamics in Antigen Presentation and T Lymphocyte Recognition

T lymphocytes are stimulated when they recognize short peptides bound to class I proteins of the major histocompatibility complex (MHC) protein, as peptide-MHC complexes. Due to the diversity in T-cell receptor (TCR) molecules together with both the peptides and MHC proteins they bind to, it has been difficult to design vaccines and treatments based on these interactions. Machine learning has made some progress in trying to predict the immunogenicity of peptide sequences in the context of specific MHC class I alleles but, as such approaches cannot integrate temporal information and lack explanatory power, their scope will always be limited. Here, we advocate a mechanistic description of antigen presentation and TCR activation which is explanatory, predictive, and quantitative, drawing on modeling approaches that collectively span several length and time scales, being capable of furnishing reliable biological descriptions that are difficult for experimentalists to provide. It is a form of multiscale systems biology. We propose the use of chemical rate equations to describe the time evolution of the foreign and host proteins to explain how the original proteins end up being presented on the cell surface as peptide fragments, while we invoke molecular dynamics to describe the key binding processes on the molecular level, including those of peptide-MHC complexes with TCRs which lie at the heart of the immune response. On each level, complementary methods based on machine learning are available, and we discuss the relationship between these divergent approaches. The pursuit of predictive mechanistic modeling approaches requires experimentalists to adapt their work so as to acquire, store, and expose data that can be used to verify and validate such models.

Partial Dissociation of Truncated Peptides Influences the Structural Dynamics of the MHCI Binding Groove

Antigen processing on MHCI involves the exchange of low-affinity peptides by high-affinity, immunodominant ones. This peptide editing process is mediated by tapasin and ERAAP at the peptide C- and N-terminus, respectively. Since tapasin does not contact the peptide directly, a sensing mechanism involving conformational changes likely allows tapasin to distinguish antigen-loaded MHCI molecules from those occupied by weakly bound, non-specific peptides. To understand this mechanism at the atomic level, we performed molecular dynamics simulations of MHCI allele B*44:02 loaded with peptides truncated or modified at the C- or N-terminus. We show that the deletion of peptide anchor residues leads to reversible, partial dissociation of the peptide from MHCI on the microsecond timescale. Fluctuations in the MHCI α2-1 helix segment, bordering the binding groove and cradled by tapasin in the PLC, are influenced by the peptide C-terminus occupying the nearby F-pocket. Simulations of tapasin complexed with MHCI bound to a low-affinity peptide show that tapasin widens the MHCI binding groove near the peptide C-terminus and weakens the attractive forces between MHCI and the peptide. Our simulations thus provide a detailed, spatially resolved picture of MHCI plasticity, revealing how peptide loading status can affect key structural regions contacting tapasin.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell's own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors-tapasin for class I and HLA-DM for class II-contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell’s own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors—tapasin for class I and HLA-DM for class II—contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Recent advances in Major Histocompatibility Complex (MHC) class I antigen presentation: Plastic MHC molecules and TAPBPR-mediated quality control

We have known since the late 1980s that the function of classical major histocompatibility complex (MHC) class I molecules is to bind peptides and display them at the cell surface to cytotoxic T cells. Recognition by these sentinels of the immune system can lead to the destruction of the presenting cell, thus protecting the host from pathogens and cancer. Classical MHC class I molecules (MHC I hereafter) are co-dominantly expressed, polygenic, and exceptionally polymorphic and have significant sequence diversity. Thus, in most species, there are many different MHC I allotypes expressed, each with different peptide-binding specificity, which can have a dramatic effect on disease outcome. Although MHC allotypes vary in their primary sequence, they share common tertiary and quaternary structures. Here, we review the evidence that, despite this commonality, polymorphic amino acid differences between allotypes alter the ability of MHC I molecules to change shape (that is, their conformational plasticity). We discuss how the peptide loading co-factor tapasin might modify this plasticity to augment peptide loading. Lastly, we consider recent findings concerning the functions of the non-classical MHC I molecule HLA-E as well as the tapasin-related protein TAPBPR (transporter associated with antigen presentation binding protein-related), which has been shown to act as a second quality-control stage in MHC I antigen presentation.

Expressing Redundancy among Linear-Epitope Sequence Data Based on Residue-Level Physicochemical Similarity in the Context of Antigenic Cross-Reaction

Epitope-based design of vaccines, immunotherapeutics, and immunodiagnostics is complicated by structural changes that radically alter immunological outcomes. This is obscured by expressing redundancy among linear-epitope data as fractional sequence-alignment identity, which fails to account for potentially drastic loss of binding affinity due to single-residue substitutions even where these might be considered conservative in the context of classical sequence analysis. From the perspective of immune function based on molecular recognition of epitopes, functional redundancy of epitope data (FRED) thus may be defined in a biologically more meaningful way based on residue-level physicochemical similarity in the context of antigenic cross-reaction, with functional similarity between epitopes expressed as the Shannon information entropy for differential epitope binding. Such similarity may be estimated in terms of structural differences between an immunogen epitope and an antigen epitope with reference to an idealized binding site of high complementarity to the immunogen epitope, by analogy between protein folding and ligand-receptor binding; but this underestimates potential for cross-reactivity, suggesting that epitope-binding site complementarity is typically suboptimal as regards immunologic specificity. The apparently suboptimal complementarity may reflect a tradeoff to attain optimal immune function that favors generation of immune-system components each having potential for cross-reactivity with a variety of epitopes.

Molecular mechanism of peptide editing in the tapasin-MHC I complex

Immune recognition of infected or malignantly transformed cells relies on antigenic peptides exposed at the cell surface by major histocompatibility complex class I (MHC I) molecules. Selection and loading of peptides onto MHC I is orchestrated by the peptide-loading complex (PLC), a multiprotein assembly whose structure has not yet been resolved. Tapasin, a central component of the PLC, stabilises MHC I and catalyses the exchange of low-affinity against high-affinity, immunodominant peptides. Up to now, the molecular basis of this peptide editing mechanism remained elusive. Here, using all-atom molecular dynamics (MD) simulations, we unravel the atomic details of how tapasin and antigen peptides act on the MHC I binding groove. Force distribution analysis reveals an intriguing molecular tug-of-war mechanism: only high-affinity peptides can exert sufficiently large forces to close the binding groove, thus overcoming the opposite forces exerted by tapasin to open it. Tapasin therefore accelerates the release of low-affinity peptides until a high-affinity antigen binds, promoting subsequent PLC break-down. Fluctuation and entropy analyses show how tapasin chaperones MHC I by stabilising it in a peptide-receptive conformation. Our results explain previous experiments and mark a key step towards a better understanding of adaptive immunity.

Computational Modeling, Formal Analysis, and Tools for Systems Biology

As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

TAPBPR: a new player in the MHC class I presentation pathway

In order to provide specificity for T cell responses against pathogens and tumours, major histocompatibility complex (MHC) class I molecules present high-affinity peptides at the cell surface to T cells. A key player for peptide loading is the MHC class I-dedicated chaperone tapasin. Recently we discovered a second MHC class I-dedicated chaperone, the tapasin-related protein TAPBPR. Here, we review the major steps in the MHC class I pathway and the TAPBPR data. We discuss the potential function of TAPBPR in the MHC class I pathway and the involvement of this previously uncharacterised protein in human health and disease.

Selector function of MHC I molecules is determined by protein plasticity

The selection of peptides for presentation at the surface of most nucleated cells by major histocompatibility complex class I molecules (MHC I) is crucial to the immune response in vertebrates. However, the mechanisms of the rapid selection of high affinity peptides by MHC I from amongst thousands of mostly low affinity peptides are not well understood. We developed computational systems models encoding distinct mechanistic hypotheses for two molecules, HLA-B*44:02 (B*4402) and HLA-B*44:05 (B*4405), which differ by a single residue yet lie at opposite ends of the spectrum in their intrinsic ability to select high affinity peptides. We used in vivo biochemical data to infer that a conformational intermediate of MHC I is significant for peptide selection. We used molecular dynamics simulations to show that peptide selector function correlates with protein plasticity, and confirmed this experimentally by altering the plasticity of MHC I with a single point mutation, which altered in vivo selector function in a predictable way. Finally, we investigated the mechanisms by which the co-factor tapasin influences MHC I plasticity. We propose that tapasin modulates MHC I plasticity by dynamically coupling the peptide binding region and α3 domain of MHC I allosterically, resulting in enhanced peptide selector function.

Transport and quality control of MHC class I molecules in the early secretory pathway

Folding and peptide binding of major histocompatibility complex (MHC) class I molecules have been thoroughly researched, but the mechanistic connection between these biochemical events and the progress of class I through the early secretory pathway is much less well understood. This review focuses on the question how the partially assembled forms of class I (which lack high-affinity peptide and/or the light chain beta-2 microglobulin) are retained inside the cell. Such investigations offer researchers exciting chances to understand the connections between class I structure, conformational dynamics, peptide binding kinetics and thermodynamics, intracellular transport, and antigen presentation.

Saposins modulate human invariant Natural Killer T cells self-reactivity and facilitate lipid exchange with CD1d molecules during antigen presentation

Lipid transfer proteins, such as molecules of the saposin family, facilitate extraction of lipids from biological membranes for their loading onto CD1d molecules. Although it has been shown that prosaposin-deficient mice fail to positively select invariant natural killer T (iNKT) cells, it remains unclear whether saposins can facilitate loading of endogenous iNKT cell agonists in the periphery during inflammatory responses. In addition, it is unclear whether saposins, in addition to loading, also promote dissociation of lipids bound to CD1d molecules. To address these questions, we used a combination of cellular assays and demonstrated that saposins influence CD1d-restricted presentation to human iNKT cells not only of exogenous lipids but also of endogenous ligands, such as the self-glycosphingolipid β-glucopyranosylceramide, up-regulated by antigen-presenting cells following bacterial infection. Furthermore, we demonstrated that in human myeloid cells CD1d-loading of endogenous lipids after bacterial infection, but not at steady state, requires trafficking of CD1d molecules through an endo-lysosomal compartment. Finally, using BIAcore assays we demonstrated that lipid-loaded saposin B increases the off-rate of lipids bound to CD1d molecules, providing important insights into the mechanisms by which it acts as a "lipid editor," capable of fine-tuning loading and unloading of CD1d molecules. These results have important implications in understanding how to optimize lipid-loading onto antigen-presenting cells, to better harness iNKT cells central role at the interface between innate and adaptive immunity.

Synergism of tapasin and human leukocyte antigens in resolving hepatitis C virus infection

CD8+ T-cell responses to hepatitis C virus (HCV) are important in generating a successful immune response and spontaneously clearing infection. Human leukocyte antigen (HLA) class I presents viral peptides to CD8+ T cells to permit detection of infected cells, and tapasin is an important component of the peptide loading complex for HLA class I. We sought to determine if tapasin polymorphisms affected the outcome of HCV infection. Patients with resolved or chronic HCV infection were genotyped for the known G/C coding polymorphism in exon 4 of the tapasin gene. In a European, but not a US, Caucasian population, the tapasin G allele was significantly associated with the outcome of HCV infection, being found in 82.5% of resolvers versus 71.3% of persistently infected individuals (P = 0.02, odds ratio [OR] = 1.90 95% confidence interval [CI] = 1.11-3.23). This was more marked at the HLA-B locus at which heterozygosity of both tapasin and HLA-B was protective (P < 0.03). Individuals with an HLA-B allele with an aspartate at residue 114 and the tapasin G allele were more likely to spontaneously resolve HCV infection (P < 0.00003, OR = 3.2 95% CI = 1.6-6.6). Additionally, individuals with chronic HCV and the combination of an HLA-B allele with an aspartate at residue 114 and the tapasin G allele also had stronger CD8+ T-cell responses (P = 0.02, OR = 2.58, 95% CI-1.05-6.5).

CONCLUSION

Tapasin alleles contribute to the outcome of HCV infection by synergizing with polymorphisms at HLA-B in a population-specific manner. This polymorphism may be relevant for peptide vaccination strategies against HCV infection.

Algorithmic modeling quantifies the complementary contribution of metabolic inhibitions to gemcitabine efficacy

Gemcitabine (2,2-difluorodeoxycytidine, dFdC) is a prodrug widely used for treating various carcinomas. Gemcitabine exerts its clinical effect by depleting the deoxyribonucleotide pools, and incorporating its triphosphate metabolite (dFdC-TP) into DNA, thereby inhibiting DNA synthesis. This process blocks the cell cycle in the early S phase, eventually resulting in apoptosis. The incorporation of gemcitabine into DNA takes place in competition with the natural nucleoside dCTP. The mechanisms of indirect competition between these cascades for common resources are given with the race for DNA incorporation; in clinical studies dedicated to singling out mechanisms of resistance, ribonucleotide reductase (RR) and deoxycytidine kinase (dCK) and human equilibrative nucleoside transporter1 (hENT1) have been associated to efficacy of gemcitabine with respect to their roles in the synthesis cascades of dFdC-TP and dCTP. However, the direct competition, which manifests itself in terms of inhibitions between these cascades, remains to be quantified. We propose an algorithmic model of gemcitabine mechanism of action, verified with respect to independent experimental data. We performed in silico experiments in different virtual conditions, otherwise difficult in vivo, to evaluate the contribution of the inhibitory mechanisms to gemcitabine efficacy. In agreement with the experimental data, our model indicates that the inhibitions due to the association of dCTP with dCK and the association of gemcitabine diphosphate metabolite (dFdC-DP) with RR play a key role in adjusting the efficacy. While the former tunes the catalysis of the rate-limiting first phosphorylation of dFdC, the latter is responsible for depletion of dCTP pools, thereby contributing to gemcitabine efficacy with a dependency on nucleoside transport efficiency. Our simulations predict the existence of a continuum of non-efficacy to high-efficacy regimes, where the levels of dFdC-TP and dCTP are coupled in a complementary manner, which can explain the resistance to this drug in some patients.

Immunodominance: a pivotal principle in host response to viral infections

We encounter pathogens on a daily basis and our immune system has evolved to mount an immune response following an infection. An interesting phenomenon that has evolved in response to clearing bacterial and viral infections is called immunodominance. Immunodominance refers to the phenomenon that, despite co-expression of multiple major histocompatibility complex class I alleles by host cells and the potential generation of hundreds of distinct antigenic peptides for recognition following an infection, a large portion of the anti-viral cytotoxic T lymphocyte population targets only some peptide/MHC class I complexes. Here we review the main factors contributing to immunodominance in relation to influenza A and HIV infection. Of special interest are the factors contributing to immunodominance in humans and rodents following influenza A infection. By critically reviewing these findings, we hope to improve understanding of the challenges facing the discovery of new factors enabling better anti-viral vaccine strategies in the future.