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.

MHC class II binding prediction:a little help from a friend

Vaccines are the greatest single instrument of prophylaxis against infectious diseases, with immeasurable benefits to human wellbeing. The accurate and reliable prediction of peptide-MHC binding is fundamental to the robust identification of T-cell epitopes and thus the successful design of peptide- and protein-based vaccines. The prediction of MHC class II peptide binding has hitherto proved recalcitrant and refractory. Here we illustrate the utility of existing computational tools for in silico prediction of peptides binding to class II MHCs. Most of the methods, tested in the present study, detect more than the half of the true binders in the top 5% of all possible nonamers generated from one protein. This number increases in the top 10% and 15% and then does not change significantly. For the top 15% the identified binders approach 86%. In terms of lab work this means 85% less expenditure on materials, labour and time. We show that while existing caveats are well founded, nonetheless use of computational models of class II binding can still offer viable help to the work of the immunologist and vaccinologist.

Peptide binding prediction for the human class II MHC allele HLA-DP2:a molecular docking approach

MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR a-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides).

The effect of haem limitation and iron restriction on outer membrane proteins and on respiratory systems of non typable Haemophilus influenzae

The effects of haem limitation and iron restriction on cells of non typable Haemophilus influenzae were investigated. Haem limitation was achieved by adding concentrations of haem to growth media which resulted in substantial decreases in final cell yields. Iron restriction was achieved by substituting protoporphyrin IX (PPIX) for haem in the growth medium and adding an iron chelator to the system. The effect of these nutrient limitations on a) outer membrane composition, and b) respiratory systems of non typable H.influenzae was investigated. Several of the strains examined produced new PPIX-specific outer membrane proteins when cultured utilising PPIX as a porphyrin source. The immune response of patients with bronchiectasis to outer membrane antigens of H.influenzae cultured under iron-restricted conditions was analysed by ELISA and immunoblotting techniques. ELISA analysis revealed that individuals with severe bronchiectasis had high titres of antibodies directed against H.influenzae OMs in both serum and sputum. Immunoblotting with homologous serum showed that where PPIX-specific OMPs were produced they were antigenic and were recognised by patients' serum. This suggested that these H.influenzae OMPs may be expressed in vivo. Additionally, the development of the immune responses to non typable H.influenzae outer membrane antigens was investigated using a rat lung model. Bacteria encased in agar beads were inoculated intratracheally into rat lungs, infection was established, and the immune response monitored for 6 weeks. The animals developed antibodies to PPIX-specific OMPs during the course of infection, providing further evidence that H.influenzae express these novel OMP antigens when growing in vivo. Studies in vitro on respiratory systems of phenotypically altered H.influenzae showed that bacteria grown utilising PPIX as a porphyrin source, or under conditions of iron-restriction produced ten fold fewer cytochromes than cells grown in nutrient excess, while haem limited H.influenzae produced no detectable cytochromes. Respiration of various substrates was depressed in haem limited and in PPIX-grown cultures as compared with cells grown in nutrient excess.

Peptide length significantly influences in vitro affinity for MHC class II molecules

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Static energy analysis of MHC class I and class II peptide-binding affinity

Antigenic peptide is presented to a T-cell receptor (TCR) through the formation of a stable complex with a major histocompatibility complex (MHC) molecule. Various predictive algorithms have been developed to estimate a peptide's capacity to form a stable complex with a given MHC class II allele, a technique integral to the strategy of vaccine design. These have previously incorporated such computational techniques as quantitative matrices and neural networks. A novel predictive technique is described, which uses molecular modeling of predetermined crystal structures to estimate the stability of an MHC class II-peptide complex. The structures are remodeled, energy minimized, and annealed before the energetic interaction is calculated.

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.

Toward the atomistic simulation of T cell epitopes automated construction of MHC:peptide structures for free energy calculations

Epitopes mediated by T cells lie at the heart of the adaptive immune response and form the essential nucleus of anti-tumour peptide or epitope-based vaccines. Antigenic T cell epitopes are mediated by major histocompatibility complex (MHC) molecules, which present them to T cell receptors. Calculating the affinity between a given MHC molecule and an antigenic peptide using experimental approaches is both difficult and time consuming, thus various computational methods have been developed for this purpose. A server has been developed to allow a structural approach to the problem by generating specific MHC:peptide complex structures and providing configuration files to run molecular modelling simulations upon them. A system has been produced which allows the automated construction of MHC:peptide structure files and the corresponding configuration files required to execute a molecular dynamics simulation using NAMD. The system has been made available through a web-based front end and stand-alone scripts. Previous attempts at structural prediction of MHC:peptide affinity have been limited due to the paucity of structures and the computational expense in running large scale molecular dynamics simulations. The MHCsim server (http://igrid-ext.cryst.bbk.ac.uk/MHCsim) allows the user to rapidly generate any desired MHC:peptide complex and will facilitate molecular modelling simulation of MHC complexes on an unprecedented scale.

SVRMHC prediction server for MHC-binding peptides

The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. Recently, we demonstrated the appealing performance of SVRMHC, an SVR-based quantitative modeling method for peptide-MHC interactions, when applied to three mouse class I MHC molecules. Subsequently, we have greatly extended the construction of SVRMHC models and have established such models for more than 40 class I and class II MHC molecules. Here we present the SVRMHC web server for predicting peptide-MHC binding affinities using these models. Benchmarked percentile scores are provided for all predictions. The larger number of SVRMHC models available allowed for an updated evaluation of the performance of the SVRMHC method compared to other well- known linear modeling methods. SVRMHC is an accurate and easy-to-use prediction server for epitope-MHC binding with significant coverage of MHC molecules. We believe it will prove to be a valuable resource for T cell epitope researchers.

Effect of maternal protein restriction during pregnancy and postweaning high-fat feeding on diet-induced thermogenesis in adult mouse offspring

Purpose: Prenatal undernutrition followed by postweaning feeding of a high-fat diet results in obesity in the adult offspring. In this study, we investigated whether diet-induced thermogenesis is altered as a result of such nutritional mismatch. Methods: Female MF-1 mice were fed a normal protein (NP, 18 % casein) or a protein-restricted (PR, 9 % casein) diet throughout pregnancy and lactation. After weaning, male offspring of both groups were fed either a high-fat diet (HF; 45 % kcal fat) or standard chow (C, 7 % kcal fat) to generate the NP/C, NP/HF, PR/C and PR/HF adult offspring groups (n = 7-11 per group). Results: PR/C and NP/C offspring have similar body weights at 30 weeks of age. Postweaning HF feeding resulted in significantly heavier NP/HF offspring (P <0.01), but not in PR/HF offspring, compared with their chow-fed counterparts. However, the PR/HF offspring exhibited greater adiposity (P <0.01) v the NP/HF group. The NP/HF offspring had increased energy expenditure and increased mRNA expression of uncoupling protein-1 and β-3 adrenergic receptor in the interscapular brown adipose tissue (iBAT) compared with the NP/C mice (both at P <0.01). No such differences in energy expenditure and iBAT gene expression were observed between the PR/HF and PR/C offspring. Conclusions: These data suggest that a mismatch between maternal diet during pregnancy and lactation, and the postweaning diet of the offspring, can attenuate diet-induced thermogenesis in the iBAT, resulting in the development of obesity in adulthood. © 2014 Springer-Verlag Berlin Heidelberg.

In silico prediction of peptide-MHC binding affinity using SVRMHC

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.

Predicting class II MHC-Peptide binding:a kernel based approach using similarity scores

Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

Fetal growth restriction results in remodeled and less efficient hearts in children

Background— Fetal growth restriction (FGR) affects 5% to 10% of newborns and is associated with increased cardiovascular mortality in adulthood. The most commonly accepted hypothesis is that fetal metabolic programming leads secondarily to diseases associated with cardiovascular disease, such as obesity, diabetes mellitus, and hypertension. Our main objective was to evaluate the alternative hypothesis that FGR induces primary cardiac changes that persist into childhood. Methods and Results— Within a cohort of fetuses with growth restriction identified in fetal life and followed up into childhood, we randomly selected 80 subjects with FGR and compared them with 120 normally grown fetuses, matched for gender, birth date, and gestational age at birth. Cardiovascular assessment was performed in childhood (mean age of 5 years). Compared with control subjects, children with FGR had a different cardiac shape, with increased transversal diameters and more globular cardiac ventricles. Although left ejection fraction was similar among the study groups, stroke volume was reduced significantly, which was compensated for by an increased heart rate to maintain output in severe FGR. This was associated with subclinical longitudinal systolic dysfunction (decreased myocardial peak velocities) and diastolic changes (increased E/E' ratio and E deceleration time). Children with FGR also had higher blood pressure and increased intima-media thickness. For all parameters evaluated, there was a linear increase with the severity of growth restriction. Conclusions— These findings suggest that FGR induces primary cardiac and vascular changes that could explain the increased predisposition to cardiovascular disease in adult life. If these results are confirmed, the impact of strategies with beneficial effects on cardiac remodeling should be explored in children with FGR.

Statistical deconvolution of enthalpic energetic contributions to MHC-peptide binding affinity

Background - MHC Class I molecules present antigenic peptides to cytotoxic T cells, which forms an integral part of the adaptive immune response. Peptides are bound within a groove formed by the MHC heavy chain. Previous approaches to MHC Class I-peptide binding prediction have largely concentrated on the peptide anchor residues located at the P2 and C-terminus positions. Results - A large dataset comprising MHC-peptide structural complexes was created by re-modelling pre-determined x-ray crystallographic structures. Static energetic analysis, following energy minimisation, was performed on the dataset in order to characterise interactions between bound peptides and the MHC Class I molecule, partitioning the interactions within the groove into van der Waals, electrostatic and total non-bonded energy contributions. Conclusion - The QSAR techniques of Genetic Function Approximation (GFA) and Genetic Partial Least Squares (G/PLS) algorithms were used to identify key interactions between the two molecules by comparing the calculated energy values with experimentally-determined BL50 data. Although the peptide termini binding interactions help ensure the stability of the MHC Class I-peptide complex, the central region of the peptide is also important in defining the specificity of the interaction. As thermodynamic studies indicate that peptide association and dissociation may be driven entropically, it may be necessary to incorporate entropic contributions into future calculations.