MHC class I bound to an immunodominant Theileria parva epitope demonstrates unconventional presentation to T cell receptors

T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1(214-224) epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design.

Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates:E coli 536

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 <50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

T-cell epitope prediction and immune complex simulation using molecular dynamics:state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

Proteins accessible to immune surveillance show significant T-cell epitope depletion:implications for vaccine design

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

Class I T-cell epitope prediction:improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding

Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.

EpiJen:a server for multistep T cell epitope prediction

Background - The main processing pathway for MHC class I ligands involves degradation of proteins by the proteasome, followed by transport of products by the transporter associated with antigen processing (TAP) to the endoplasmic reticulum (ER), where peptides are bound by MHC class I molecules, and then presented on the cell surface by MHCs. The whole process is modeled here using an integrated approach, which we call EpiJen. EpiJen is based on quantitative matrices, derived by the additive method, and applied successively to select epitopes. EpiJen is available free online. Results - To identify epitopes, a source protein is passed through four steps: proteasome cleavage, TAP transport, MHC binding and epitope selection. At each stage, different proportions of non-epitopes are eliminated. The final set of peptides represents no more than 5% of the whole protein sequence and will contain 85% of the true epitopes, as indicated by external validation. Compared to other integrated methods (NetCTL, WAPP and SMM), EpiJen performs best, predicting 61 of the 99 HIV epitopes used in this study. Conclusion - EpiJen is a reliable multi-step algorithm for T cell epitope prediction, which belongs to the next generation of in silico T cell epitope identification methods. These methods aim to reduce subsequent experimental work by improving the success rate of epitope prediction.

Towards the knowledge-based design of universal influenza epitope ensemble vaccines

Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly-conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly-conserved and experimentally-verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96% and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97% and 88% coverage of observed subtypes.

Is the generation of neo-antigenic determinants by free radicals central to the development of autoimmune rheumatoid disease?

Biomolecules are susceptible to many different post-translational modifications that have important effects on their function and stability, including glycosylation, glycation, phosphorylation and oxidation chemistries. Specific conversion of aspartic acid to its isoaspartyl derivative or arginine to citrulline leads to autoantibody production in models of rheumatoid disease, and ensuing autoantibodies cross-react with native antigens. Autoimmune conditions associate with increased activation of immune effector cells and production of free radical species via NADPH oxidases and nitric oxide synthases. Generation of neo-antigenic determinants by reactive oxygen and nitrogen species ROS and RNS) may contribute to epitope spreading in autoimmunity. The oxidation of amino acids by peroxynitrite, hypochlorous acid and other reactive oxygen species (ROS) increases the antigenicity of DNA, LDL and IgG, generating ligands for which autoantibodies show higher avidity. This review focuses on the evidence for ROS and RNS in promoting the autoimmune responses observed in diseases rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). It considers the evidence for ROS/RNS-induced antigenicity arising as a consequence of failure to remove or repair ROS/RNS damaged biomolecules and suggests that an associated defect, probably in T cell signal processing or/or antigen presentation, is required for the development of disease.

Immunochemical detection of sequence-specific modifications to DNA induced by UV light

Sequence specificity of antibodies to UV-damaged DNA has not been described previously. The antisera investigated here were specific for UV-modified DNA and were absolutely dependent upon the presence of thymine residues. Using a series of oligonucleotides in competition ELISA, increased inhibition was observed with increasing chain length of UV-polythymidylate. A minimum of three adjacent thymines was required for effective inhibition; alone, dimers of thymine were poor antigens. Although UV-irradiated poly(dC) was not antigenic, cytosines could partially replace thymines within the smallest effective epitope (T-T-T) with a high degree of sequence specificity, not previously described. The main epitope induced by UV was formed from adjacent thymines and either a 3' or a 5' pyrimidine.

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

Mutations of beta-arrestin 2 that limit self-association also interfere with interactions with the beta2-adrenoceptor and the ERK1/2 MAPKs:implications for beta2-adrenoceptor signalling via the ERK1/2 MAPKs

FRET (fluorescence resonance energy transfer) and co-immunoprecipitation studies confirmed the capacity of beta-arrestin 2 to self-associate. Amino acids potentially involved in direct protein-protein interaction were identified via combinations of spot-immobilized peptide arrays and mapping of surface exposure. Among potential key amino acids, Lys(285), Arg(286) and Lys(295) are part of a continuous surface epitope located in the polar core between the N- and C-terminal domains. Introduction of K285A/R286A mutations into beta-arrestin 2-eCFP (where eCFP is enhanced cyan fluorescent protein) and beta-arrestin 2-eYFP (where eYFP is enhanced yellow fluorescent protein) constructs substantially reduced FRET, whereas introduction of a K295A mutation had a more limited effect. Neither of these mutants was able to promote beta2-adrenoceptor-mediated phosphorylation of the ERK1/2 (extracellular-signal-regulated kinase 1/2) MAPKs (mitogen-activated protein kinases). Both beta-arrestin 2 mutants displayed limited capacity to co-immunoprecipitate ERK1/2 and further spot-immobilized peptide arrays indicated each of Lys(285), Arg(286) and particularly Lys(295) to be important for this interaction. Direct interactions between beta-arrestin 2 and the beta2-adrenoceptor were also compromised by both K285A/R286A and K295A mutations of beta-arrestin 2. These were not non-specific effects linked to improper folding of beta-arrestin 2 as limited proteolysis was unable to distinguish the K285A/R286A or K295A mutants from wild-type beta-arrestin 2, and the interaction of beta-arrestin 2 with JNK3 (c-Jun N-terminal kinase 3) was unaffected by the K285A/R286A or L295A mutations. These results suggest that amino acids important for self-association of beta-arrestin 2 also play an important role in the interaction with both the beta2-adrenoceptor and the ERK1/2 MAPKs. Regulation of beta-arrestin 2 self-association may therefore control beta-arrestin 2-mediated beta2-adrenoceptor-ERK1/2 MAPK signalling.

AntigenDB:an immunoinformatics database of pathogen antigens

The continuing threat of infectious disease and future pandemics, coupled to the continuous increase of drug-resistant pathogens, makes the discovery of new and better vaccines imperative. For effective vaccine development, antigen discovery and validation is a prerequisite. The compilation of information concerning pathogens, virulence factors and antigenic epitopes has resulted in many useful databases. However, most such immunological databases focus almost exclusively on antigens where epitopes are known and ignore those for which epitope information was unavailable. We have compiled more than 500 antigens into the AntigenDB database, making use of the literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases. We shall update AntigenDB on a rolling basis, regularly adding antigens from other organisms and extra data analysis tools. AntigenDB is available freely at http://www.imtech.res.in/raghava/antigendb and its mirror site http://www.bic.uams.edu/raghava/antigendb.

Polarised secretion of leukaemia inhibitory factor

Leukaemia inhibitory factor (LIF) is a cytokine that is active on a wide variety of cells. Multiple LIF transcripts have been described. The transcripts LIF-D and LIF-M encode different signal peptides, which in mouse have been associated with differential localisation of the mature protein. LIF-D is associated with a freely diffusible protein, whereas the LIF-M is associated with the extracellular matrix. The polarity of LIF secretion has yet to be described and could illuminate the mechanisms of LIF localisation. Here the polarised endogenous secretion of human LIF and IL-6 in Caco-2 cells was characterised under normal culture conditions and following induction with IL-1b. Whether the apical or basolateral membrane was stimulated influenced the pattern of secretion (LIF: Unstimulated, 59% basolateral. Dual stimulation, 68% basolateral. Basolateral stimulation, 79% basolateral. Apical stimulation, 53% basolateral). IL-6 displayed a similar dependence on the site of stimulation but was predominantly secreted at the membrane that was stimulated. To determine the effect of the alternate signal peptides on the polarity of LIF secretion, LIF was epitope tagged with FLAG. Epitope-tagging with FLAG was used to separate endogenous from exogenous protein expression. However, despite the normal biological activity of LIF-FLAG and detection of the FLAG in a western blot, detection of the LIF-FLAG under non-reducing conditions was not observed, and therefore it was unsuitable for secretion studies. Untagged LIF was expressed exogenously in Madin-Darby canine kidney (MDCK) cells under the control of a tetracycline response promoter that allowed a variety of LIF expression levels to be tested. Exogenous murine LIF was secreted predominantly from the apical (60%) membrane of MDCK cells irrespective of the signal peptide expressed.

The heteromeric 5-HT3A/B receptor:the effect of 5-HT3B subunits on receptor structure and ligand recognition

The 5-HT3 receptors are members of the cys-loop family of ligand-gated ion channels. Two functional subtypes are known, the homomeric 5HT3A and the heteromeric 5HT3A/B receptors, which exhibit distinct biophysical characteristics but are difficult to differentiate pharmacologically. Atomic force microscopy has been used to determine the stoichiometry and architecture of the heteromeric 5HT3A/B receptor. Each subunit was engineered to express a unique C-terminal epitope tag, together with six sequential histidine residues to facilitate nickel affinity purification. The 5-HT3 receptors, ectopically expressed in HEK293 cells, were solubilised, purified and decorated with antibodies to the subunit specific epitope tags. Imaging of individual receptors by atomic force microscopy revealed a pentameric arrangement of subunits in the order BBABA, reading anti-clockwise when viewed from the extracellular face. Homology models for the heteromeric receptor were then constructed using both the electron microscopic structure of the nicotinic acetylcholine receptor, from Torpedo marmorata, and the X-ray crystallographic structure of the soluble acetylcholine binding protein, from Lymnaea stagnalis, as templates. These homology models were used, together with equivalent models constructed for the homomeric receptor, to interpret mutagenesis experiments designed to explore the minimal recognition differences of both the natural agonist, 5-HT, and the competitive antagonist, granisetron, for the two human receptor subtypes. The results of this work revealed that the 5-HT3B subunit residues within the ligand binding site, for both the agonist and antagonist, are accommodating to conservative mutations. They are consistent with the view that the 5-HT3A subunit provides the principal and the 5-HT38 subunit the complementary recognition interactions at the binding interface.

EpiTOP—a proteochemometric tool for MHC class II binding prediction

Motivation: T-cell epitope identification is a critical immunoinformatic problem within vaccine design. To be an epitope, a peptide must bind an MHC protein. Results: Here, we present EpiTOP, the first server predicting MHC class II binding based on proteochemometrics, a QSAR approach for ligands binding to several related proteins. EpiTOP uses a quantitative matrix to predict binding to 12 HLA-DRB1 alleles. It identifies 89% of known epitopes within the top 20% of predicted binders, reducing laboratory labour, materials and time by 80%. EpiTOP is easy to use, gives comprehensive quantitative predictions and will be expanded and updated with new quantitative matrices over time.