Towards in silico prediction of immunogenic epitopes

As torrents of new data now emerge from microbial genomics, bioinformatic prediction of immunogenic epitopes remains challenging but vital. In silico methods often produce paradoxically inconsistent results: good prediction rates on certain test sets but not others. The inherent complexity of immune presentation and recognition processes complicates epitope prediction. Two encouraging developments – data driven artificial intelligence sequence-based methods for epitope prediction and molecular modeling methods based on three-dimensional protein structures – offer hope for the future.

Selection of conserved epitopes from hepatitis C virus for pan-populational stimulation of T-cell responses

The hepatitis C virus (HCV) is able to persist as a chronic infection, which can lead to cirrhosis and liver cancer. There is evidence that clearance of HCV is linked to strong responses by CD8 cytotoxic T lymphocytes (CTLs), suggesting that eliciting CTL responses against HCV through an epitope-based vaccine could prove an effective means of immunization. However, HCV genomic plasticity as well as the polymorphisms of HLA I molecules restricting CD8 T-cell responses challenges the selection of epitopes for a widely protective vaccine. Here, we devised an approach to overcome these limitations. From available databases, we first collected a set of 245 HCV-specific CD8 T-cell epitopes, all known to be targeted in the course of a natural infection in humans. After a sequence variability analysis, we next identified 17 highly invariant epitopes. Subsequently, we predicted the epitope HLA I binding profiles that determine their potential presentation and recognition. Finally, using the relevant HLA I-genetic frequencies, we identified various epitope subsets encompassing 6 conserved HCV-specific CTL epitopes each predicted to elicit an effective T-cell response in any individual regardless of their HLA I background. We implemented this epitope selection approach for free public use at the EPISOPT web server. © 2013 Magdalena Molero-Abraham et al.

Macrophages and lymphocyte responiveness to mitogen

Purified B-cells fail to proliferate in response to the strong thymus-independent (TI) antigen Lipopolysaccharide (LPS) in the absence of macrophages (Corbel and Melchers, 1983). The fact that macrophages, or factors derived from them are required is supported by the inability of marginal zone B-cells in infants to respond to highly virulent strains of bacteria such as Neisseria meningitidis and Streptococcus pneumoniae (Timens, 1989). This may be due to the lack of CD21 expression on B-cells in infants which could associate with its co-receptor (C3d) on adjacent macrophages. It is not clear whether cell surface contacts and/or soluble products are involved in lymphocyte-macrophage interactions in response to certain antigens. This thesis describes the importance of the macrophage in lymphocyte responses to T-dependent (TD) and TI antigens. The major findings of this thesis were as follows: (1). Macrophages were essential for a full proliferative response to a range of T - and B-cell mitogens and TI-1 and TI-2 antigens, including Concanavalin A, LPS, Pokeweed mitogen (PWM), Dextran sulphate, Phytohaemagglutinin-P (PHA-P) and Poly[I][C]. (2). A ratio of 1 macrophage to 1000 lymphocytes was sufficient for the mitogens to exert their effects. (3). The optimal conditions were established for the activation of an oxidative burst in cells of the monocyte/macrophage lineage as measured by luminometry. The order of ability was OpZ >PMA/lonomycin >f-MLP >Con A >DS >PHA >Poly[I][C] >LPS >PWM. Responses were only substantial and protracted with OpZ and PMA. Peritoneal macrophages were the most responsive cells, whereas splenic and alveolar macrophages were significantly less active and no response could be elicited with Kupffer cells, thus demonstrating heterogeneity between macrophages. (4). Activated macrophages that were then fixed with paraformaldehyde were unable to restore mitogenic responsiveness, even with a ratio of 1 macrophage to 5 lymphocytes. (5). Although highly purified T- and B-cells could respond to mitogen provided live macrophages were present, maximum activation was only observed when all 3 cell types were present. (6). Supernatants from purified macrophage cultures treated with a range of activators were able to partially restore lymphocyte responses to mitogen in macrophage-depleted splenocyte cultures, and purified T - and B-cell cultures. In fact supernatants from macrophages treated with LPS for only 30 minutes could restore responsiveness. Supernatants from OpZ treated macrophages were without effect. (7). Macrophage supernatants could not induce proliferation in the absence of mitogen. They therefore provide a co-mitogenic signal required by lymphocytes in order to respond to mitogen. (8). Macrophage product profiles revealed that LPS and Con A-treated macrophage supernatants showed elevated levels of IL-1β, TNF -α L TB4 and TXB2. These products were therefore good candidates as the co-mitogenic factor. The possible inhibitory factors secreted by OpZ-treated macrophages were PGE2, IL-10 and NO. (9). The removal of cytokines, eicosanoids and TNF-α from LPS-treated macrophage supernatants using Cycloheximide, Dexamethasone and an MMPI respectively, resulted in the inability of these supernatants to restore macrophage-depleted lymphocyte responses to mitogen. (10). rIL-1β and rTNF-α are co-mitogenic factors, as macrophage-depleted lymphocytes incubated with rIL-1β and rTNF-α can respond to mitogen.

The role of insulin and the insulin-like growth factors in the proliferation of the rat thymic lymphocyte

Concanavalin A, provoked a 35-fold increase in the rate of proliferation of rat thymocytes. Insulin (10-6M), and insulin-like growth factor I (10-10M) approximately doubled the rate of DNA synthesis. Both of these structurally related molecules acted through the type I insulin-like growth factor receptor. The sequential addition of Concanavalin A and insulin, promoted a much greater proliferative response than to either of the two agonists alone. Insulin also increased the uptake of glucose and amino acids by the cells. Glucose uptake was enhanced at insulin concentrations of 10-6M and 10-10M. Amino acid uptake was more strongly affected at the higher concentration. Insulin-like growth factor I (10-11M) also enhanced amino acid uptake. The effects of insulin on metabolism were mediated by both insulin and type I insulin-like growth factor receptors. These effects were greatly enhanced after a pre-treatment with Concanavalin A. Concanavalin A provided a primary mitogenic signal to the cells. Amongst the responses was an increased expression of insulin and/or type I insulin-like growth factor receptors. The consequent enhanced cellular sensitivity to these agonists, enabled them to facilitate the passage of the cells through the cell cycle by: i) providing a secondary mitogenic signal, and ii) promoting the uptake of raw materials and energy substrates. The initiation of DNA synthesis and passage through the cell cycle was thus punctuated by the sequential expression of various cell surface receptors. This regulated cellular sensitivity, enabling them to react in a precisely orchestrated fashion to hormones and other molecules in their environment. The intracellular mechanism of insulin action remains an enigma. Although the presence of extracellular calcium was essential for insulin stimulation of amino acid uptake and DNA synthesis, the cation did not subserve a direct mediator function. Insulin promoted an increase in intracellular pH, which was mediated by the Na+/H+ antiport. Other mechanisms were probably also involved in mediating the full cellular response to insulin.

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102:a bioinformatic approach to the prediction of new epitopes

Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

Toward an atomistic understanding of the immune synapse:large-scale molecular dynamics simulation of a membrane-embedded TCR-pMHC-CD4 complex

T-cell activation requires interaction of T-cell receptors (TCR) with peptide epitopes bound by major histocompatibility complex (MHC) proteins. This interaction occurs at a special cell-cell junction known as the immune or immunological synapse. Fluorescence microscopy has shown that the interplay among one agonist peptide-MHC (pMHC), one TCR and one CD4 provides the minimum complexity needed to trigger transient calcium signalling. We describe a computational approach to the study of the immune synapse. Using molecular dynamics simulation, we report here on a study of the smallest viable model, a TCR-pMHC-CD4 complex in a membrane environment. The computed structural and thermodynamic properties are in fair agreement with experiment. A number of biomolecules participate in the formation of the immunological synapse. Multi-scale molecular dynamics simulations may be the best opportunity we have to reach a full understanding of this remarkable supra-macromolecular event at a cell-cell junction.

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.

Significant alterations in peripheral blood lymphocyte subsets in patients with somatoform disorder

Objective: Previous studies have suggested that somatoform disorders (SFD) might be associated with changes in the function of the central and autonomic nervous systems. The aim of this study was to examine the possible immunological differences between SFD and healthy controls. Methods: Twenty-four patients with SFD and 13 healthy individuals completed the psychological questionnaires to assess symptom reporting [Symptom Checklist-90 Revised (SCL-90-R)] and to diagnose for SFD [Screening for Somatoform Symptoms scale (SOMS-scale)]. Participants also provided a blood sample taken in the morning, which was analysed with an automated cell counter to determine the number of leucocytes per μl and with flow cytometry to determine lymphocyte subsets. Results: With the exception of a higher T4/T8 ratio in the patient group, which was mainly because of lower CD8 counts, there were no significant differences in the absolute number of lymphocytes (subsets) between patients with SFD and healthy subjects. A positive correlation between B-lymphocyte subsets (CD19+CD22+, CD19+CD5+, CD19+CD3-) to all scales of the SCL-90-R, except somatisation, were found in SFD. Additionally, a positive correlation was found in SFD between CD14+CD16+ monocytes and somatisation (0.573) on the SCL-90-R scale. Conclusion: These data indicate that patients with SFD have an enhanced humoral immunity as shown by increased B-cell numbers and furthermore an elevated T4/T8 ratio because of lower CD8 suppressor cells. Further studies will be required to determine whether these alterations in lymphocyte subsets are directly involved in the pathophysiology of SFD. © 2007 Blackwell Munksgaard.

Ultra-endurance exercise:unanswered questions in redox biology and immunology

Ultra-endurance races are extreme exercise events that can take place over large parts of a day, several consecutive days or over weeks and months interspersed by periods of rest and recovery. Since the first ultraendurance races in the late 1970s, around 1000 races are now held worldwide each year, and more than 100000 people take part. Although these athletes appear to be fit and healthy, there have been occasional reports of severe complications following ultra-endurance exercise. Thus there is concern that repeated extreme exercise events could have deleterious effects on health, which might be brought about by the high levels of ROS (reactive oxygen species) produced during exercise. Studies that have examined biomarkers of oxidative damage following ultra-endurance exercise have found measurements to be elevated for several days, which has usually been interpreted to reflect increased ROS production. Levels of the antioxidant molecule GSH (reduced glutathione) are depleted for 1 month or longer following ultra-endurance exercise, suggesting an impaired capacity to copewith ROS. The present paper summarizes studies that have examined the oxidative footprint of ultra-endurance exercise in light of current thinking in redox biology and the possible health implications of such extreme exercise. © The Authors Journal compilation © 2014 Biochemical Society.

Determinants of human immunodeficiency virus type 1 escape from the primary CD8+ cytotoxic T lymphocyte response

CD8+ cytotoxic T lymphocytes (CTLs) play an important role in containment of virus replication in primary human immunodeficiency virus (HIV) infection. HIV's ability to mutate to escape from CTL pressure is increasingly recognized; but comprehensive studies of escape from the CD8 T cell response in primary HIV infection are currently lacking. Here, we have fully characterized the primary CTL response to autologous virus Env, Gag, and Tat proteins in three patients, and investigated the extent, kinetics, and mechanisms of viral escape from epitope-specific components of the response. In all three individuals, we observed variation beginning within weeks of infection at epitope-containing sites in the viral quasispecies, which conferred escape by mechanisms including altered peptide presentation/recognition and altered antigen processing. The number of epitope-containing regions exhibiting evidence of early CTL escape ranged from 1 out of 21 in a subject who controlled viral replication effectively to 5 out of 7 in a subject who did not. Evaluation of the extent and kinetics of HIV-1 escape from >40 different epitope-specific CD8 T cell responses enabled analysis of factors determining escape and suggested that escape is restricted by costs to intrinsic viral fitness and by broad, codominant distribution of CTL-mediated pressure on viral replication.

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.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Transporter associated with antigen processing preselection of peptides binding to the MHC:a bioinformatic evaluation

TAP is responsible for the transit of peptides from the cytosol to the lumen of the endoplasmic reticulum. In an immunological context, this event is followed by the binding of peptides to MHC molecules before export to the cell surface and recognition by T cells. Because TAP transport precedes MHC binding, TAP preferences may make a significant contribution to epitope selection. To assess the impact of this preselection, we have developed a scoring function for TAP affinity prediction using the additive method, have used it to analyze and extend the TAP binding motif, and have evaluated how well this model acts as a preselection step in predicting MHC binding peptides. To distinguish between MHC alleles that are exclusively dependent on TAP and those exhibiting only a partial dependence on TAP, two sets of MHC binding peptides were examined: HLA-A*0201 was selected as a representative of partially TAP-dependent HLA alleles, and HLA-A*0301 represented fully TAP-dependent HLA alleles. TAP preselection has a greater impact on TAP-dependent alleles than on TAP-independent alleles. The reduction in the number of nonbinders varied from 10% (TAP-independent) to 33% (TAP-dependent), suggesting that TAP preselection is an important component in the successful in silico prediction of T cell epitopes.