Apoptosis induction in gastric mucous cells in vitro:lesser potency of Helicobacter pylori than Escherichia coli lipopolysaccharide, but positive interaction with ibuprofen

Non-steroidal anti-inflammatory drugs (NSAIDs) cause peptic ulcer disease, but whether they interact with Helicobacter pylori to promote damage is controversial. Moreover, the reported induction of apoptosis in gastric cells by H. pylori lipopolysaccharide (LPS) (10-9 g /ml) contrasts with studies showing low immunological potency of this LPS. Therefore, the effects of LPS from H. pylori NCTC 11637 and Escherichia coli 0111:B4 on apoptosis in a primary culture of guinea-pig gastric mucous cells were investigated in the presence and absence of the NSAID, ibuprofen. Cell loss was estimated by a crystal violet assay, and apoptosis determined from caspase activity and from condensation and fragmentation of nuclei. Exposure to E. coli LPS for 24 h caused cell loss and enhanced apoptotic activity at concentrations ≥ 10-9 g/ml, but similar effects were only obtained with H. pylori LPS at concentrations ≥10-6 g/ml. Although ibuprofen (250 μM) caused cell loss and apoptosis, addition of either E. coli or H. pylori LPSs further enhanced these effects. In conclusion, LPS and ibuprofen interact to enhance gastric cell loss and apoptosis. In such interactions, E. coli LPS is more potent than that of H. pylori. The low potency of H. pylori LPS may contribute to a chronic low-grade gastritis that can be enhanced by the use of NSAIDs. © W. S. Maney & Son Ltd.

Drug delivery strategies for the treatment of Helicobacter pylori infections

Helicobacter pylori is one of the most common pathogenic bacterial infections, colonising an estimated half of all humans. It is associated with the development of serious gastroduodenal disease - including peptic ulcers, gastric lymphoma and acute chronic gastritis. Current recommended regimes are not wholly effective and patient compliance, side-effects and bacterial resistance can be problematic. Drug delivery to the site of residence in the gastric mucosa may improve efficacy of the current and emerging treatments. Gastric retentive delivery systems potentially allow increased penetration of the mucus layer and therefore increased drug concentration at the site of action. Proposed gastric retentive systems for the enhancement of local drug delivery include floating systems, expandable or swellable systems and bioadhesive systems. Generally, problems with these formulations are lack of specificity, limited to mucus turnover or failure to persist in the stomach. Gastric mucoadhesive systems are hailed as a promising technology to address this issue, penetrating the mucus layer and prolonging activity at the mucus-epithelial interface. This review appraises gastroretentive delivery strategies specifically with regard to their application as a delivery system to target Helicobacter. As drug-resistant strains emerge, the development of a vaccine to eradicate and prevent reinfection is an attractive proposition. Proposed prophylactic and therapeutic vaccines have been delivered using a number of mucosal routes using viral and non-viral vectors. The delivery form, inclusion of adjuvants, and delivery regime will influence the immune response generated. © 2005 Bentham Science Publishers Ltd.

Active membrane transport and receptor proteins from bacteria

A general strategy for the expression of bacterial membrane transport and receptor genes in Escherichia coli is described. Expression is amplified so that the encoded proteins comprise 5-35% of E. coli inner membrane protein. Depending upon their topology, proteins are produced with RGSH6 or a Strep tag at the C-terminus. These enable purification in mg quantities for crystallization and NMR studies. Examples of one nutrient uptake and one multidrug extrusion protein from Helicobacter pylori are described. This strategy is successful for membrane proteins from H. pylori, E. coli, Enterococcus faecalis, Bacillus subtilis, Staphylococcus aureus, Microbacterium liquefaciens, Brucella abortus, Brucella melitensis, Campylobacter jejuni, Neisseria meningitides, Streptomyces coelicolor and Rhodobacter sphaeroides. ©2005 Biochemical Society.

Paracellular permeability is increased by basal lipopolysaccharide in a primary culture of colonic epithelial cells; an effect prevented by an activator of Toll-like receptor-2

Lipopolysaccharide (LPS), which generally activates Toll-like receptor 4 (TLR4), is expressed on commensal colonic bacteria. In a number of tissues, LPS can act directly on epithelial cells to increase paracellular permeability. Such an effect in the colon would have an important impact on the understanding of normal homeostasis and of pathology. Our aim was to use a novel primary culture of colonic epithelial cells grown on Transwells to investigate whether LPS, or Pam(3)CSK( 4), an activator of TLR2, affected paracellular permeability. Consequently, [(14)C]-mannitol transfer and transepithelial electrical resistance (TEER) were measured. The preparation consisted primarily of cytokeratin-18 positive epithelial cells that produced superoxide, stained for mucus with periodic acid-Schiff reagent, exhibited alkaline phosphatase activity and expressed TLR2 and TLR4. Tight junctions and desmosomes were visible by transmission electron microscopy. Basally, but not apically, applied LPS from Escherichia coli increased the permeability to mannitol and to a 10-kDa dextran, and reduced TEER. The LPS from Helicobacter pylori increased paracellular permeability of gastric cells when applied either apically or basally, in contrast to colon cells, where this LPS was active only from the basal aspect. A pan-caspase inhibitor prevented the increase in caspase activity caused by basal E. coli LPS, and reduced the effects of LPS on paracellular permeability. Synthetic Pam(3)CSK(4) in the basal compartment prevented all effects of basal E. coli LPS. In conclusion, LPS applied to the base of the colonic epithelial cells increased paracellular permeability by a mechanism involving caspase activation, suggesting a process by which perturbation of the gut barrier could be exacerbated. Moreover, activation of TLR2 ameliorated such effects.

Mycobacterium tuberculosis peptides presented by HLA-E molecules are targets for human CD8 T-cells with cytotoxic as well as regulatory activity

Tuberculosis (TB) is an escalating global health problem and improved vaccines against TB are urgently needed. HLA-E restricted responses may be of interest for vaccine development since HLA-E displays very limited polymorphism (only 2 coding variants exist), and is not down-regulated by HIV-infection. The peptides from Mycobacterium tuberculosis (Mtb) potentially presented by HLA-E molecules, however, are unknown. Here we describe human T-cell responses to Mtb-derived peptides containing predicted HLA-E binding motifs and binding-affinity for HLA-E. We observed CD8(+) T-cell proliferation to the majority of the 69 peptides tested in Mtb responsive adults as well as in BCG-vaccinated infants. CD8(+) T-cells were cytotoxic against target-cells transfected with HLA-E only in the presence of specific peptide. These T cells were also able to lyse M. bovis BCG infected, but not control monocytes, suggesting recognition of antigens during mycobacterial infection. In addition, peptide induced CD8(+) T-cells also displayed regulatory activity, since they inhibited T-cell proliferation. This regulatory activity was cell contact-dependent, and at least partly dependent on membrane-bound TGF-beta. Our results significantly increase our understanding of the human immune response to Mtb by identification of CD8(+) T-cell responses to novel HLA-E binding peptides of Mtb, which have cytotoxic as well as immunoregulatory activity.

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

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).

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.

Identification of the HLA-DM/HLA-DR interface

Human leukocyte antigen (HLA)-DM is a critical participant in antigen presentation that catalyzes the dissociation of the Class II-associated Invariant chain-derived Peptide (CLIP) from the major histocompatibility complex (MHC) Class II molecules. There is competition amongst peptides for access to an MHC Class II groove and it has been hypothesised that DM functions as a 'peptide editor' that catalyzes the replacement of one peptide for another within the groove. It is established that the DM catalyst interacts directly with the MHC Class II but the precise location of the interface is unknown. Here, we combine previously described mutational data with molecular docking and energy minimisation simulations to identify a putative interaction site of >4000A2 which agrees with known point mutational data for both the DR and DM molecule. The docked structure is validated by comparison with experimental data and previously determined properties of protein-protein interfaces. A possible dissociation mechanism is suggested by the presence of an acidic cluster near the N terminus of the bound peptide.

The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used clustering techniques are introduced in the following section: principal component analysis (PCA) and hierarchical clustering. PCA calculates the variance between variables and groups them into a few uncorrelated groups or principal components (PCs) that are orthogonal to each other. Hierarchical clustering is carried out by separating data into many clusters and merging similar clusters together. Here, we use an example of human leukocyte antigen (HLA) supertype classification to demonstrate the usage of the two methods. Two programs, Generating Optimal Linear Partial Least Square Estimations (GOLPE) and Sybyl, are used for PCA and hierarchical clustering, respectively. However, the reader should bear in mind that the methods have been incorporated into other software as well, such as SIMCA, statistiXL, and R.

Peptide binding to the HLA-DRB1 supertype:a proteochemometrics analysis

A proteochemometrics approach was applied to a set of 2666 peptides binding to 12 HLA-DRB1 proteins. Sequences of both peptide and protein were described using three z-descriptors. Cross terms accounting for adjacent positions and for every second position in the peptides were included in the models, as well as cross terms for peptide/protein interactions. Models were derived based on combinations of different blocks of variables. These models had moderate goodness of fit, as expressed by r2, which ranged from 0.685 to 0.732; and good cross-validated predictive ability, as expressed by q2, which varied from 0.678 to 0.719. The external predictive ability was tested using a set of 356 HLA-DRB1 binders, which showed an r2(pred) in the range 0.364-0.530. Peptide and protein positions involved in the interactions were analyzed in terms of hydrophobicity, steric bulk and polarity.

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide:can the α3 and β2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004

A comparative molecular similarity indices (CoMSIA) study of peptide binding to the HLA-A3 superfamily

Epitope identification is the basis of modern vaccine design. The present paper studied the supermotif of the HLA-A3 superfamily, using comparative molecular similarity indices analysis (CoMSIA). Four alleles with high phenotype frequencies were used: A*1101, A*0301, A*3101 and A*6801. Five physicochemical properties—steric bulk, electrostatic potential, local hydro-phobicity, hydrogen-bond donor and acceptor abilities—were considered and ‘all fields’ models were produced for each of the alleles. The models have a moderate level of predictivity and there is a good correlation between the data. A revised HLA-A3 supermotif was defined based on the comparison of favoured and disfavoured properties for each position of the MHC bound peptide. The present study demonstrated that CoMSIA is an effective tool for studying peptide–MHC interactions.

The HLA-A2-supermotif:a QSAR definition

Identification of epitopes capable of binding multiple HLA types will significantly rationalise the development of epitope-based vaccines. A quantitative method assessing the contribution of each amino acid at each position was applied to over 500 nonamer peptides binding to 5 MHC alleles — A*0201, A*0202, A*0203, A*0206 and A*6802 — which together define the HLA-A2-like supertype. FXIGXI (L)IFV was identified as a supermotif for the A2-supertype based on the contributions of the common preferred amino acids at each of the nine positions. The results indicate that HLA-A*6802 is an intermediate allele standing between A2 and A3 supertypes: at anchor position 2 it is closer to A3 and at anchor position 9 it is nearer to A2. Models are available free on-line at http://www.jenner.ac.uk/MHCPred and can be used for binding affinity prediction.

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0:a quantitative molecular docking study

Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.