Gap junctions are essential to the function of multicellular animals, which require a high degree of coordination between cells. In vertebrates, gap junctions comprise connexins and currently 21 connexins are known in humans. The functions of gap junctions are highly diverse and include exchange of metabolites and electrical signals between cells, as well as functions, which are apparently unrelated to intercellular communication. Given the diversity of gap junction physiology, regulation of gap junction activity is complex. The structure of the various connexins is known to some extent; and structural rearrangements and intramolecular interactions are important for regulation of channel function. Intercellular coupling is further regulated by the number and activity of channels present in gap junctional plaques. The number of connexins in cell-cell channels is regulated by controlling transcription, translation, trafficking, and degradation; and all of these processes are under strict control. Once in the membrane, channel activity is determined by the conductive properties of the connexin involved, which can be regulated by voltage and chemical gating, as well as a large number of posttranslational modifications. The aim of the present article is to review our current knowledge on the structure, regulation, function, and pharmacology of gap junctions. This will be supported by examples of how different connexins and their regulation act in concert to achieve appropriate physiological control, and how disturbances of connexin function can lead to disease. © 2012 American Physiological Society. Compr Physiol 2:1981-2035, 2012.
Gap junctions are comprised of connexins that form cell-to-cell channels which couple neighboring cells to accommodate the exchange of information. The need for communication does, however, change over time and therefore must be tightly controlled. Although the regulation of connexin protein expression by transcription and translation is of great importance, the trafficking, channel activity and degradation are also under tight control. The function of connexins can be regulated by several post translational modifications, which affect numerous parameters; including number of channels, open probability, single channel conductance or selectivity. The most extensively investigated post translational modifications are phosphorylations, which have been documented in all mammalian connexins. Besides phosphorylations, some connexins are known to be ubiquitinated, SUMOylated, nitrosylated, hydroxylated, acetylated, methylated, and γ-carboxyglutamated. The aim of the present review is to summarize our current knowledge of post translational regulation of the connexin family of proteins.
connexin; post translational modification; phosphorylation; sumoylation; nitrosylation; methylation; acetylation; ubiquitination
Secondary metabolites are known to serve a wide range of specialized functions including communication, developmental control and defense. Genome sequencing of several fungal model species revealed that the majority of predicted secondary metabolite related genes are silent in laboratory strains, indicating that fungal secondary metabolites remain an underexplored resource of bioactive molecules. In this study, we combine heterologous expression of regulatory proteins in Aspergillus nidulans with systematic variation of growth conditions and observe induced synthesis of insect juvenile hormone-III and methyl farnesoate. Both compounds are sesquiterpenes belonging to the juvenile hormone class. Juvenile hormones regulate developmental and metabolic processes in insects and crustaceans, but have not previously been reported as fungal metabolites. We found that feeding by Drosophila melanogaster larvae induced synthesis of juvenile hormone in A. nidulans indicating a possible role of juvenile hormone biosynthesis in affecting fungal-insect antagonisms.
Fungal natural products are a rich resource for bioactive molecules. To fully exploit this potential it is necessary to link genes to metabolites. Genetic information for numerous putative biosynthetic pathways has become available in recent years through genome sequencing. However, the lack of solid methodology for genetic manipulation of most species severely hampers pathway characterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to transformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC) encodes a polyketide synthase, ATEG_08453 (gedR) encodes a transcription factor responsible for activation of the geodin gene cluster and ATEG_08460 (gedL) encodes a halogenase that catalyzes conversion of sulochrin to dihydrogeodin. We expect that our approach for transferring intact biosynthetic pathways to a fungus with a well developed genetic toolbox will be instrumental in characterizing the many exciting pathways for secondary metabolite production that are currently being uncovered by the fungal genome sequencing projects.
Apolipoprotein (APO) E is the major risk factor for sporadic Alzheimer disease. Among other functions, APOE is proposed to sequester neurotoxic amyloid-β peptides (Aβ) in the brain, delivering them to cellular catabolism via neuronal APOE receptors. Still, the receptors involved in this process remain controversial. Here, we identified the pro-neurotrophin receptor sortilin as major endocytic pathway for clearance of APOE/Aβ complexes in neurons. Sortilin binds APOE with high affinity. Lack of receptor expression in mice results in accumulation of APOE and of Aβ in the brain, and in aggravated plaque burden. Also, primary neurons lacking sortilin exhibit significantly impaired uptake of APOE/Aβ complexes despite proper expression of other APOE receptors. In spite of higher than normal brain APOE levels, sortilin-deficient animals display anomalies in brain lipid metabolism (e.g., accumulation of sulfatides) seen in APOE-deficient mice, indicating functional deficiency in cellular APOE uptake pathways. Taken together, our findings identified sortilin as an essential neuronal pathway for APOE-containing lipoproteins in vivo and suggest an intriguing link between Aβ catabolism and pro-neurotrophin signaling converging on this receptor.
Pregnancy malaria is caused by Plasmodium falciparum-infected erythrocytes that adhere to the placental receptor chondroitin sulfate A (CSA) and sequester in the placenta; women become resistant to pregnancy malaria as they acquire antiadhesion antibodies that target surface proteins of placental parasites. VAR2CSA, a member of the P. falciparum EMP1 variant surface antigen family, is the leading candidate for a pregnancy malaria vaccine. Because VAR2CSA is a high-molecular-weight protein, a vaccine based on the full-length protein may not be feasible. An alternative approach has been to develop a vaccine targeting individual Duffy binding-like (DBL) domains. In this study, a consortium of laboratories under the Pregnancy Malaria Initiative compared the functional activity of antiadhesion antibodies elicited by different VAR2CSA domains and variants produced in prokaryotic and eukaryotic expression systems. Antisera were initially tested against laboratory lines of maternal parasites, and the most promising reagents were evaluated in the field against fresh placental parasite samples. Recombinant proteins expressed in Escherichia coli elicited antibody levels similar to those expressed in eukaryotic systems, as did the two allelic forms of the DBL4 and DBL5 domains. The procedures developed for this head-to-head comparison will be useful for future evaluation and down-selection of malaria vaccine immunogens.
Changes in the lipid composition of cardiac myocytes have been reported during cardiac hypertrophy, cardiomyopathy, and infarction. Because a recent study indicates a relation between low phosphatidylinositol-bisphosphate (PIP2) levels and reduced intercellular coupling, we tested the hypothesis that agonist-induced changes in PIP2 can result in a reduction of the functional coupling of cardiomyocytes and, consequently, in changes in conduction velocity. Intercellular coupling was measured by Lucifer Yellow dye transfer in cultured neonatal rat cardiomyocytes. Conduction velocity was measured in cardiomyocytes grown on microelectrode arrays. Intercellular coupling was reduced by angiotensin II (43.7±9.3%, N=11) and noradrenaline (58.0±10.7%, N=11). To test if reduced intercellular coupling after agonist stimulation was caused by PIP2-depletion, myocytes were stimulated by angiotensin II (57.3±5.7%, N=14) and then allowed to recover in medium with or without wortmannin (an inhibitor of PIP2 synthesis). Intercellular coupling fully recovered in control medium (102.1±8.9%, N=10), whereas no recovery occurred in the presence of wortmannin (69.3±7.8%, N=12). Inhibition of PKC, calmodulin, or arachidonic acid production did not affect the response to either angiotensin II or noradrenaline. Furthermore, decreasing or increasing PIP2 also decreased and increased intercellular coupling, respectively. This supports the role of PIP2 in the regulation of intercellular coupling. In beating myocytes, conduction velocity was reduced by angiotensin II stimulation, and recovery after wash out was prevented by inhibition of PIP2 production. Reductions in PIP2 inhibit intercellular coupling in cardiomyocytes, and stimulation by physiologically relevant agonists reduces intercellular coupling by this mechanism. The reduction in intercellular coupling lowered conduction velocity.
Connexin; Gap junctions; PIP2; Cardiomyocytes
We have recently developed a high-density photolithographic, peptide array technology with a theoretical upper limit of 2 million different peptides per array of 2 cm2. Here, we have used this to perform complete and exhaustive analyses of linear B cell epitopes of a medium sized protein target using human serum albumin (HSA) as an example. All possible overlapping 15-mers from HSA were synthesized and probed with a commercially available polyclonal rabbit anti-HSA antibody preparation. To allow for identification of even the weakest epitopes and at the same time perform a detailed characterization of key residues involved in antibody binding, the array also included complete single substitution scans (i.e. including each of the 20 common amino acids) at each position of each 15-mer peptide. As specificity controls, all possible 15-mer peptides from bovine serum albumin (BSA) and from rabbit serum albumin (RSA) were included as well. The resulting layout contained more than 200.000 peptide fields and could be synthesized in a single array on a microscope slide. More than 20 linear epitope candidates were identified and characterized at high resolution i.e. identifying which amino acids in which positions were needed, or not needed, for antibody interaction. As expected, moderate cross-reaction with some peptides in BSA was identified whereas no cross-reaction was observed with peptides from RSA. We conclude that high-density peptide microarrays are a very powerful methodology to identify and characterize linear antibody epitopes, and should advance detailed description of individual specificities at the single antibody level as well as serologic analysis at the proteome-wide level.
Brugada syndrome (BrS) is a clinical entity first described in 1992. BrS is characterized by ST-segment elevations in the right precordial leads and susceptibility to ventricular arrhythmias and sudden cardiac death. It affects young subjects, predominantly males, with structurally normal hearts. The prevalence varies with ethnicity ranging from 1:2,000 to 1:100,000 in different parts of the world. Today, hundreds of variants in 17 genes have been associated with BrS of which mutations in SCN5A, coding for the cardiac voltage-gated sodium channel, accounts for the vast majority. Despite this, approximately 70% of BrS cases cannot be explained genetically with the current knowledge. Moreover, the monogenic role of some of the variants previously described as being associated with BrS has been questioned by their occurrence in about 4% (1:23) of the general population as found in NHLBI GO Exome Sequencing Project (ESP) currently including approximately 6500 individuals. If we add the variants described in the five newest identified genes associated with BrS, they appear at an even higher prevalence in the ESP (1:21). The current standard treatment of BrS is an implantable cardioverter-defibrillator (ICD). The risk stratification and indications for ICD treatment are based on the ECG and on the clinical and family history. In this review we discuss the genetic basis of BrS.
Brugada syndrome; genetics; Exome Sequencing Project; mutation; treatment
Members of the Plasmodium falciparum Erythrocyte Membrane protein 1 (PfEMP1) family expressed on the surface of malaria-infected erythrocytes mediate binding of the parasite to different receptors on the vascular lining. This process drives pathologies, and severe childhood malaria has been associated with the expression of particular subsets of PfEMP1 molecules. PfEMP1 are grouped into subtypes based on upstream sequences and the presence of semi-conserved PfEMP1 domain compositions named domain cassettes (DCs). Earlier studies have indicated that DC5-containing PfEMP1 (DC5-PfEMP1) are more likely to be expressed in children with severe malaria disease than in children with uncomplicated malaria, but these PfEMP1 subtypes only dominate in a relatively small proportion of the children with severe disease. In this study, we have characterised the genomic sequence characteristic for DC5, and show that two genetically different parasite lines expressing DC5-PfEMP1 bind PECAM1, and that anti-DC5-specific antibodies inhibit binding of DC5-PfEMP1-expressing parasites to transformed human bone marrow endothelial cells (TrHBMEC). We also show that antibodies against each of the four domains characteristic for DC5 react with native PfEMP1 expressed on the surface of infected erythrocytes, and that some of these antibodies are cross-reactive between the two DC5-containing PfEMP1 molecules tested. Finally, we confirm that anti-DC5 antibodies are acquired early in life by individuals living in malaria endemic areas, that individuals having high levels of these antibodies are less likely to develop febrile malaria episodes and that the antibody levels correlate positively with hemoglobin levels.
Identifying which mutation(s) within a given genotype is responsible for an observable phenotype is important in many aspects of molecular biology. Here, we present SigniSite, an online application for subgroup-free residue-level genotype–phenotype correlation. In contrast to similar methods, SigniSite does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set phenotype. As output, SigniSite displays a sequence logo, depicting the strength of the phenotype association of each residue and a heat-map identifying ‘hot’ or ‘cold’ regions. SigniSite was benchmarked against SPEER, a state-of-the-art method for the prediction of specificity determining positions (SDP) using a set of human immunodeficiency virus protease-inhibitor genotype–phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found to outperform SPEER. SigniSite is available at: http://www.cbs.dtu.dk/services/SigniSite/.
MISTIC (mutual information server to infer coevolution) is a web server for graphical representation of the information contained within a MSA (multiple sequence alignment) and a complete analysis tool for Mutual Information networks in protein families. The server outputs a graphical visualization of several information-related quantities using a circos representation. This provides an integrated view of the MSA in terms of (i) the mutual information (MI) between residue pairs, (ii) sequence conservation and (iii) the residue cumulative and proximity MI scores. Further, an interactive interface to explore and characterize the MI network is provided. Several tools are offered for selecting subsets of nodes from the network for visualization. Node coloring can be set to match different attributes, such as conservation, cumulative MI, proximity MI and secondary structure. Finally, a zip file containing all results can be downloaded. The server is available at http://mistic.leloir.org.ar. In summary, MISTIC allows for a comprehensive, compact, visually rich view of the information contained within an MSA in a manner unique to any other publicly available web server. In particular, the use of circos representation of MI networks and the visualization of the cumulative MI and proximity MI concepts is novel.
Several studies have associated mutations in genes encoding potassium channels and accessory subunits involved in cardiac repolarization with increased susceptibility of atrial fibrillation (AF). Recently, the Krüppel-like factor 15 (Klf15) was found to transcriptionally control rhythmic expression of KChIP2, a critical subunit required for generating the transient outward potassium current (Ito), and that deficiency or excess of Klf15 increased the susceptibility of arrhythmias. On this basis we hypothesized that mutations in Klf15 could be associated with AF. A total of 209 unrelated Caucasian lone AF patients were screened for mutations in Klf15 by direct sequencing. No mutations in the lone AF cohort were found. In one patient we found a synonymous variant (c.36C > T). In NHLBI GO Exome Sequencing Project (ESP) the variant was present in 31 of 4269 Caucasian individuals and in 3 of 2200 African Americans. In our cohort Klf15 was not associated with lone AF.
lone AF; Klf15; ESP; genetics; mutation
The development of neutralizing anti-drug-antibodies to the Factor VIII protein-therapeutic is currently the most significant impediment to the effective management of hemophilia A. Common non-synonymous single nucleotide polymorphisms (ns-SNPs) in the F8 gene occur as six haplotypes in the human population (denoted H1 to H6) of which H3 and H4 have been associated with an increased risk of developing anti-drug antibodies. There is evidence that CD4+ T-cell response is essential for the development of anti-drug antibodies and such a response requires the presentation of the peptides by the MHC-class-II (MHC-II) molecules of the patient. We measured the binding and half-life of peptide-MHC-II complexes using synthetic peptides from regions of the Factor VIII protein where ns-SNPs occur and showed that these wild type peptides form stable complexes with six common MHC-II alleles, representing 46.5% of the North American population. Next, we compared the affinities computed by NetMHCIIpan, a neural network-based algorithm for MHC-II peptide binding prediction, to the experimentally measured values and concluded that these are in good agreement (area under the ROC-curve of 0.778 to 0.972 for the six MHC-II variants). Using a computational binding predictor, we were able to expand our analysis to (a) include all wild type peptides spanning each polymorphic position; and (b) consider more MHC-II variants, thus allowing for a better estimation of the risk for clinical manifestation of anti-drug antibodies in the entire population (or a specific sub-population). Analysis of these computational data confirmed that peptides which have the wild type sequence at positions where the polymorphisms associated with haplotypes H3, H4 and H5 occur bind MHC-II proteins significantly more than a negative control. Taken together, the experimental and computational results suggest that wild type peptides from polymorphic regions of FVIII constitute potential T-cell epitopes and thus could explain the increased incidence of anti-drug antibodies in hemophilia A patients with haplotypes H3 and H4.
The development of anti-drug antibodies to therapeutic proteins is a significant impediment to development and licensure of therapeutic proteins and limits their clinical utility. The development of such antibodies requires CD4+ T-cell activation, which is mediated by the recognition of epitopes presented by MHC class-II (MHC-II) molecules. Here, we use experimental measurements and computational predictions of peptide-MHC-II affinities to study the clinical observation that African-American hemophilia A patients have a higher incidence of anti-drug antibodies to Factor VIII than Caucasian patients. Specifically, we used the experimental data to select and validate a computational prediction method which, in turn, allowed us to expand our analysis to a larger repertoire of peptide-MHC-II complexes. We showed that wild type peptides spanning haplotype polymorphisms common in the African American population bind MHC-II proteins significantly more than a negative control, thus providing a mechanistic explanation of the phenomenon in this population.
Over the last 60 years, the resources and the research in the Danish Twin Registry (DTR) have periodically been summarized. Here, we give a short overview of the DTR and a more comprehensive description of new developments in the twenty-first century. First, we outline our experience over the last decade of combining questionnaire and survey data with national demographic, social, and health registers in Statistics Denmark. Second, we describe our most recent data collection effort, which was conducted during the period 2008–2011 and included both in-person assessments of 14,000+ twins born 1931–1969 and sampling of biological material, hereby expanding and consolidating the DTR biobank. Third, two examples of intensively studied twin cohorts are given. The new developments in the DTR in the last decade have facilitated the ongoing research and laid the groundwork for new research directions.
twin register; biobank; register-based research; metabolic syndrome; birth weight discordance; Denmark
Diabetes increases the risk of cardiovascular complications including arrhythmias, but the underlying mechanisms remain to be established. Decreased conduction velocity (CV), which is an independent risk factor for re-entry arrhythmias, is present in models with streptozotocin (STZ) induced type 1 diabetes. Whether CV is also disturbed in models of type 2 diabetes is currently unknown.
We used Zucker Diabetic Fatty (ZDF) rats, as a model of type 2 diabetes, and their lean controls Zucker Diabetic Lean (ZDL) rats to investigate CV and its response to the anti-arrhythmic peptide analogue AAP10. Gap junction remodeling was examined by immunofluorescence and western blotting. Cardiac histomorphometry was examined by Masson`s Trichrome staining and intracellular lipid accumulation was analyzed by Bodipy staining.
CV was significantly slower in ZDF rats (56±1.9 cm/s) compared to non-diabetic controls (ZDL, 66±1.6 cm/s), but AAP10 did not affect CV in either group. The total amount of Connexin43 (C×43) was identical between ZDF and ZDL rats, but the amount of lateralized C×43 was significantly increased in ZDF rats (42±12 %) compared to ZDL rats (30±8%), p<0.04. Judged by electrophoretic mobility, C×43 phosphorylation was unchanged between ZDF and ZDL rats. Also, no differences in cardiomyocyte size or histomorphometry including fibrosis were observed between groups, but the volume of intracellular lipid droplets was 4.2 times higher in ZDF compared to ZDL rats (p<0.01).
CV is reduced in type 2 diabetic ZDF rats. The CV disturbance may be partly explained by increased lateralization of C×43, but other factors are likely also involved. Our data indicates that lipotoxicity potentially may play a role in development of conduction disturbances and arrhythmias in type 2 diabetes.
Diabetic cardiomyopathy; Arrhythmia; Lipotoxicity; Conduction velocity; Gap junctions; Type 2 diabetes; Zucker Diabetic Fatty (ZDF) rats
Mycophenolic acid (MPA) is a fungal secondary metabolite and the active component in several immunosuppressive pharmaceuticals. The gene cluster coding for the MPA biosynthetic pathway has recently been discovered in Penicillium brevicompactum, demonstrating that the first step is catalyzed by MpaC, a polyketide synthase producing 5-methylorsellinic acid (5-MOA). However, the biochemical role of the enzymes encoded by the remaining genes in the MPA gene cluster is still unknown. Based on bioinformatic analysis of the MPA gene cluster, we hypothesized that the step following 5-MOA production in the pathway is carried out by a natural fusion enzyme MpaDE, consisting of a cytochrome P450 (MpaD) in the N-terminal region and a hydrolase (MpaE) in the C-terminal region. We verified that the fusion gene is indeed expressed in P. brevicompactum by obtaining full-length sequence of the mpaDE cDNA prepared from the extracted RNA. Heterologous coexpression of mpaC and the fusion gene mpaDE in the MPA-nonproducer Aspergillus nidulans resulted in the production of 5,7-dihydroxy-4-methylphthalide (DHMP), the second intermediate in MPA biosynthesis. Analysis of the strain coexpressing mpaC and the mpaD part of mpaDE shows that the P450 catalyzes hydroxylation of 5-MOA to 4,6-dihydroxy-2-(hydroxymethyl)-3-methylbenzoic acid (DHMB). DHMB is then converted to DHMP, and our results suggest that the hydrolase domain aids this second step by acting as a lactone synthase that catalyzes the ring closure. Overall, the chimeric enzyme MpaDE provides insight into the genetic organization of the MPA biosynthesis pathway.
The interaction between antibodies and antigens is one of the most important immune system mechanisms for clearing infectious organisms from the host. Antibodies bind to antigens at sites referred to as B-cell epitopes. Identification of the exact location of B-cell epitopes is essential in several biomedical applications such as; rational vaccine design, development of disease diagnostics and immunotherapeutics. However, experimental mapping of epitopes is resource intensive making in silico methods an appealing complementary approach. To date, the reported performance of methods for in silico mapping of B-cell epitopes has been moderate. Several issues regarding the evaluation data sets may however have led to the performance values being underestimated: Rarely, all potential epitopes have been mapped on an antigen, and antibodies are generally raised against the antigen in a given biological context not against the antigen monomer. Improper dealing with these aspects leads to many artificial false positive predictions and hence to incorrect low performance values. To demonstrate the impact of proper benchmark definitions, we here present an updated version of the DiscoTope method incorporating a novel spatial neighborhood definition and half-sphere exposure as surface measure. Compared to other state-of-the-art prediction methods, Discotope-2.0 displayed improved performance both in cross-validation and in independent evaluations. Using DiscoTope-2.0, we assessed the impact on performance when using proper benchmark definitions. For 13 proteins in the training data set where sufficient biological information was available to make a proper benchmark redefinition, the average AUC performance was improved from 0.791 to 0.824. Similarly, the average AUC performance on an independent evaluation data set improved from 0.712 to 0.727. Our results thus demonstrate that given proper benchmark definitions, B-cell epitope prediction methods achieve highly significant predictive performances suggesting these tools to be a powerful asset in rational epitope discovery. The updated version of DiscoTope is available at www.cbs.dtu.dk/services/DiscoTope-2.0.
The human immune system has an incredible ability to fight pathogens (bacterial, fungal and viral infections). One of the most important immune system events involved in clearing infectious organisms is the interaction between the antibodies and antigens (molecules such as proteins from the pathogenic organism). Antibodies bind to antigens at sites known as B-cell epitopes. Hence, identification of areas on the surface antigens capable of binding to antibodies (also known as B-cell epitopes) may aid the development of various immune related applications (e.g. vaccines and immunotherapeutic). However, experimental identification of B-cell epitopes is a resource intensive task, thereby making computer-aided methods an appealing complementary approach. Previously reported performances of methods for B cell epitope predictive have been moderate. Here, we present an updated version of the B-cell epitope prediction method; DiscoTope, that on the basis of a protein structure and epitope propensity scores predicts residues likely to be involved in B-cell epitopes. We demonstrate that the low performances to some extent can be explained by poorly defined benchmarks, and that inclusion of additional biological information greatly enhances the predictive performance. This suggests that, given proper benchmark definitions, state-of-the-art B cell epitope prediction methods perform significantly better than generally assumed.
In all vertebrate animals, CD8+ cytotoxic T lymphocytes (CTLs) are controlled by major histocompatibility complex class I (MHC-I) molecules. These are highly polymorphic peptide receptors selecting and presenting endogenously derived epitopes to circulating CTLs. The polymorphism of the MHC effectively individualizes the immune response of each member of the species. We have recently developed efficient methods to generate recombinant human MHC-I (also known as human leukocyte antigen class I, HLA-I) molecules, accompanying peptide-binding assays and predictors, and HLA tetramers for specific CTL staining and manipulation. This has enabled a complete mapping of all HLA-I specificities (“the Human MHC Project”). Here, we demonstrate that these approaches can be applied to other species. We systematically transferred domains of the frequently expressed swine MHC-I molecule, SLA-1*0401, onto a HLA-I molecule (HLA-A*11:01), thereby generating recombinant human/swine chimeric MHC-I molecules as well as the intact SLA-1*0401 molecule. Biochemical peptide-binding assays and positional scanning combinatorial peptide libraries were used to analyze the peptide-binding motifs of these molecules. A pan-specific predictor of peptide–MHC-I binding, NetMHCpan, which was originally developed to cover the binding specificities of all known HLA-I molecules, was successfully used to predict the specificities of the SLA-1*0401 molecule as well as the porcine/human chimeric MHC-I molecules. These data indicate that it is possible to extend the biochemical and bioinformatics tools of the Human MHC Project to other vertebrate species.
Recombinant MHC; Peptide specificity; Binding predictions
In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We we have updated the prediction servers servers, NetMHC-3.2, NetMHCpan-2.2, and a new consensus method, NetMHCcons, which, in their previous versions, have been evaluated to be among the very best performing MHC:peptide binding predictors available. Here we describe the background for these methods, and the rationale behind the different optimisation steps implemented in the methods. We go through the practical use of the methods, which are publicly available in the form of relatively fast and simple web interfaces. Furthermore, we will review results optained in actual epitope discovery projects where previous implementations of the described methods have been used in the initial selection of potential epitopes. Selected potential epitopes were all evaluated experimentally using ex vivo assays.
The prediction of the network of protein-protein interactions (PPI) of an organism is crucial for the understanding of biological processes and for the development of new drugs. Machine learning methods have been successfully applied to the prediction of PPI in yeast by the integration of multiple direct and indirect biological data sources. However, experimental data are not available for most organisms. We propose here an ensemble machine learning approach for the prediction of PPI that depends solely on features independent from experimental data. We developed new estimators of the coevolution between proteins and combined them in an ensemble learning procedure.
We applied this method to a dataset of known co-complexed proteins in Escherichia coli and compared it to previously published methods. We show that our method allows prediction of PPI with an unprecedented precision of 95.5% for the first 200 sorted pairs of proteins compared to 28.5% on the same dataset with the previous best method.
A close inspection of the best predicted pairs allowed us to detect new or recently discovered interactions between chemotactic components, the flagellar apparatus and RNA polymerase complexes in E. coli.
Prediction methods as well as experimental methods for T-cell epitope discovery have developed significantly in recent years. High-throughput experimental methods have made it possible to perform full-length protein scans for epitopes restricted to a limited number of MHC alleles. The high costs and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest. MHC binding prediction methods are today of a very high quality and can predict MHC binding peptides with high accuracy. This is possible for a large range of MHC alleles and relevant length of binding peptides. The predictions can easily be performed for complete proteomes of any size. Prediction methods are still, however, dependent on good experimental methods for validation, and should merely be used as a guide for rational epitope discovery. We expect prediction methods as well as experimental validation methods to continue to develop and that we will soon see clinical trials of products whose development has been guided by prediction methods.
CTL; epitope; HLA; MHC; prediction; T cell; vaccine
Several studies have shown that cancers actively regulate alternative splicing. Altered splicing mechanisms in cancer lead to cancer-specific transcripts different from the pool of transcripts occurring only in healthy tissue. At the same time, altered presentation of HLA class I epitopes is frequently observed in various types of cancer. Down-regulation of genes related to HLA class I antigen processing has been observed in several cancer types, leading to fewer HLA class I antigens on the cell surface. Here, we use a peptidome wide analysis of predicted alternative splice forms, based on a publicly available database, to show that peptides over-represented in cancer splice variants comprise significantly fewer predicted HLA class I epitopes compared to peptides from normal transcripts. Peptides over-represented in cancer transcripts are in the case of the three most common HLA class I supertype representatives consistently found to contain fewer predicted epitopes compared to normal tissue. We observed a significant difference in amino acid composition between protein sequences associated with normal versus cancer tissue, as transcripts found in cancer are enriched with hydrophilic amino acids. This variation contributes to the observed significant lower likelihood of cancer-specific peptides to be predicted epitopes compared to peptides found in normal tissue.