MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, and the TCR repertoire is distinct within individuals, indicating that the MAIT cell repertoire is shaped by prior microbial exposure.
Mucosal-associated invariant T (MAIT) cells express a semi-invariant T cell receptor (TCR) that detects microbial metabolites presented by the nonpolymorphic major histocompatibility complex (MHC)–like molecule MR1. The highly conserved nature of MR1 in conjunction with biased MAIT TCRα chain usage is widely thought to indicate limited ligand presentation and discrimination within a pattern-like recognition system. Here, we evaluated the TCR repertoire of MAIT cells responsive to three classes of microbes. Substantial diversity and heterogeneity were apparent across the functional MAIT cell repertoire as a whole, especially for TCRβ chain sequences. Moreover, different pathogen-specific responses were characterized by distinct TCR usage, both between and within individuals, suggesting that MAIT cell adaptation was a direct consequence of exposure to various exogenous MR1-restricted epitopes. In line with this interpretation, MAIT cell clones with distinct TCRs responded differentially to a riboflavin metabolite. These results suggest that MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, providing a basis for adaptive memory via recruitment of specific repertoires shaped by microbial exposure.
Celiac disease is caused by intolerance to cereal gluten proteins, and HLA-DQ molecules are involved in the disease pathogenesis by presentation of gluten peptides to CD4+ T cells. The α- or β-chain sharing HLA molecules DQ2.5, DQ2.2, and DQ7.5 display different risks for the disease. It was recently demonstrated that T cells of DQ2.5 and DQ2.2 patients recognize distinct sets of gluten epitopes, suggesting that these two DQ2 variants select different peptides for display. To explore whether this is the case, we performed a comprehensive comparison of the endogenous self-peptides bound to HLA-DQ molecules of B-lymphoblastoid cell lines. Peptides were eluted from affinity-purified HLA molecules of nine cell lines and subjected to quadrupole orbitrap mass spectrometry and MaxQuant software analysis. Altogether, 12,712 endogenous peptides were identified at very different relative abundances. Hierarchical clustering of normalized quantitative data demonstrated significant differences in repertoires of peptides between the three DQ variant molecules. The neural network-based method, NNAlign, was used to identify peptide-binding motifs. The binding motifs of DQ2.5 and DQ7.5 concurred with previously established binding motifs. The binding motif of DQ2.2 was strikingly different from that of DQ2.5 with position P3 being a major anchor having a preference for threonine and serine. This is notable as three recently identified epitopes of gluten recognized by T cells of DQ2.2 celiac patients harbor serine at position P3. This study demonstrates that relative quantitative comparison of endogenous peptides sampled from our protein metabolism by HLA molecules provides clues to understand HLA association with disease.
Electronic supplementary material
The online version of this article (doi:10.1007/s00251-014-0819-9) contains supplementary material, which is available to authorized users.
Antigen presentation/processing; Binding motif; Celiac disease; Mass spectrometry; MHC
MHC class I molecules (HLA-I in humans) present peptides derived from endogenous proteins to CTLs. Whereas the peptide-binding specificities of HLA-A and -B molecules have been studied extensively, little is known about HLA-C specificities. Combining a positional scanning combinatorial peptide library approach with a peptide–HLA-I dissociation assay, in this study we present a general strategy to determine the peptide-binding specificity of any MHC class I molecule. We applied this novel strategy to 17 of the most common HLA-C molecules, and for 16 of these we successfully generated matrices representing their peptide-binding motifs. The motifs prominently shared a conserved C-terminal primary anchor with hydrophobic amino acid residues, as well as one or more diverse primary and auxiliary anchors at P1, P2, P3, and/or P7. Matrices were used to generate a large panel of HLA-C–specific peptide-binding data and update our pan-specific NetMHCpan predictor, whose predictive performance was considerably improved with respect to peptide binding to HLA-C. The updated predictor was used to assess the specificities of HLA-C molecules, which were found to cover a more limited sequence space than HLA-A and -B molecules. Assessing the functional significance of these new tools, HLA-C*07:01 transgenic mice were immunized with stable HLA-C*07:01 binders; six of six tested stable peptide binders were immunogenic. Finally, we generated HLA-C tetramers and labeled human CD8+ T cells and NK cells. These new resources should support future research on the biology of HLA-C molecules. The data are deposited at the Immune Epitope Database, and the updated NetMHCpan predictor is available at the Center for Biological Sequence Analysis and the Immune Epitope Database.
Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide–MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0.
MHC class II; Tcell epitope; MHC binding specificity; Peptide–MHC binding; Human leukocyte antigens; Artificial neural networks
The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.
MHC; HLA; Binding motif; Functional clustering; MHC specificity; Supertypes
It is important to accurately determine the performance of peptide:MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last benchmark dataset from 2009 with prediction performances generated on data subsequently added to the Immune Epitope Database (IEDB) which served as a blind set.
We found that cross-validated performances systematically overestimated performance on the blind set. This was found not to be due to the presence of similar peptides in the cross-validation dataset. Rather, we found that small size and low sequence/affinity diversity of either training or blind datasets were associated with large differences in cross-validated vs. blind prediction performances. We use these findings to derive quantitative rules of how large and diverse datasets need to be to provide generalizable performance estimates.
It has long been known that cross-validated prediction performance estimates often overestimate performance on independently generated blind set data. We here identify and quantify the specific factors contributing to this effect for MHC-I binding predictions. An increasing number of peptides for which MHC binding affinities are measured experimentally have been selected based on binding predictions and thus are less diverse than historic datasets sampling the entire sequence and affinity space, making them more difficult benchmark data sets. This has to be taken into account when comparing performance metrics between different benchmarks, and when deriving error estimates for predictions based on benchmark performance.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-241) contains supplementary material, which is available to authorized users.
Benchmarking of MHC class I predictors; Epitope prediction; Sequence similarity; Cross-validation
Human cytomegalovirus (HCMV) is an important human pathogen. It is a leading cause of congenital infection and a leading infectious threat to recipients of solid organ transplants as well as of allogeneic hematopoietic cell transplants. Moreover, it has recently been suggested that HCMV may promote tumor development. Both CD4+ and CD8+ T cell responses are important for long-term control of the virus, and adoptive transfer of HCMV-specific T cells has led to protection from reactivation and HCMV disease. Identification of HCMV-specific T cell epitopes has primarily focused on CD8+ T cell responses against the pp65 phosphoprotein. In this study, we have focused on CD4+ and CD8+ T cell responses against the immediate early 1 and 2 proteins (IE1 and IE2). Using overlapping peptides spanning the entire IE1 and IE2 sequences, peripheral blood mononuclear cells from 16 healthy, HLA-typed, donors were screened by ex vivo IFN-γ ELISpot and in vitro intracellular cytokine secretion assays. The specificities of CD4+ and CD8+ T cell responses were identified and validated by HLA class II and I tetramers, respectively. Eighty-one CD4+ and 44 CD8+ T cell responses were identified representing at least seven different CD4 epitopes and 14 CD8 epitopes restricted by seven and 11 different HLA class II and I molecules, respectively, in total covering 91 and 98% of the Caucasian population, respectively. Presented in the context of several different HLA class II molecules, two epitope areas in IE1 and IE2 were recognized in about half of the analyzed donors. These data may be used to design a versatile anti-HCMV vaccine and/or immunotherapy strategy.
Background and aim
Previous studies on circulating microparticles (MPs) indicate that the majority of MPs are of a size below the detection limit of most standard flow cytometers. The objective of the present study was to establish a method to analyze MP subpopulations above the threshold of detection of a new generation BD FACSAria™ III digital flow cytometer.
We analyzed MP subpopulations in plasma from 24 healthy individuals (9 males and 15 females). MPs were identified according to their size (<1.0-µm), by Lactadherin-FITC labelling, and by exposure of cell-specific markers. The sensitivity of the flow cytometer was tested against that of a previous-generation instrument FC500. Reproducibility of the FACSAria and our set-up was investigated, and the percentage of phosphatidylserine (PS) exposing MPs binding Lactadherin was determined.
By using a flow cytometric approach we identified and quantitated MPs derived from platelets, monocytes, erythrocytes and endothelial cells. In addition, levels of tissue factor-positive MPs were determined. The FACSAria demonstrated improved sensitivity and increased MP detection range compared to the FC500 instrument. The reproducibility of PS+PMP and PS+MP measurements was 11.7 and 23.2%, respectively. When expressed as a percentage of total MPs, the PS-positive MP population represented 15.1±5.5%, and PS-positive MPs were significantly increased in men.
We have established a method to measure MPs above the detection limit of a new generation flow cytometer and derived from a number of cell-types in a healthy population of men and women.
extracellular vesicles; flow cytometry; coincidence occurrence; platelet-derived; monocyte-derived; endothelial cell-derived; erythrocyte-derived; tissue-factor; lactadherin
Placental malaria is a major health problem for both pregnant women and their fetuses in malaria endemic regions. It is triggered by the accumulation of Plasmodium falciparum-infected erythrocytes (IE) in the intervillous spaces of the placenta and is associated with foetal growth restriction and maternal anemia. IE accumulation is supported by the binding of the parasite-expressed protein VAR2CSA to placental chondroitin sulfate A (CSA). Defining specific CSA-binding epitopes of VAR2CSA, against which to target the immune response, is essential for the development of a vaccine aimed at blocking IE adhesion. However, the development of a VAR2CSA adhesion-blocking vaccine remains challenging due to (i) the large size of VAR2CSA and (ii) the extensive immune selection for polymorphisms and thereby non-neutralizing B-cell epitopes. Camelid heavy-chain-only antibodies (HcAbs) are known to target epitopes that are less immunogenic to classical IgG and, due to their small size and protruding antigen-binding loop, able to reach and recognize cryptic, conformational epitopes which are inaccessible to conventional antibodies. The variable heavy chain (VHH) domain is the antigen-binding site of camelid HcAbs, the so called Nanobody, which represents the smallest known (15 kDa) intact, native antigen-binding fragment. In this study, we have used the Nanobody technology, an approach new to malaria research, to generate small and functional antibody fragments recognizing unique epitopes broadly distributed on VAR2CSA.
The binding of antigens to antibodies is one of the key events in an immune response against foreign molecules and is a critical element of several biomedical applications including vaccines and immunotherapeutics. For development of such applications, the identification of antibody binding sites (B-cell epitopes) is essential. However experimental epitope mapping is highly cost-intensive and computer-aided methods do in general have moderate performance. One major reason for this moderate performance is an incomplete understanding of what characterizes an epitope. To fill this gap, we here developed a novel framework for comparing and superimposing B-cell epitopes and applied it on a dataset of 107 non-similar antigen:antibody structures extracted from the PDB database. With the presented framework, we were able to describe the general B-cell epitope as a flat, oblong, oval shaped volume consisting of predominantly hydrophobic amino acids in the center flanked by charged residues. The average epitope was found to be made up of ~15 residues with one linear stretch of 5 or more residues constituting more than half of the epitope size. Furthermore, the epitope area is predominantly constrained to a plane above the antibody tip, in which the epitope is orientated in a −30 to 60 degree angle relative to the light to heavy chain antibody direction. Contrary to previously findings, we did not find a significant deviation between the amino acid composition in epitopes and the composition of equally exposed parts of the antigen surface. Our results, in combination with previously findings, give a detailed picture of the B-cell epitope that may be used in development of improved B-cell prediction methods.
Antibody; Antigen; Epitope; Structure; Amino acid distribution
Peptide-major histocompatibility complex (p-MHC) class I tetramer complexes have facilitated the early detection and functional characterisation of epitope specific CD8+ cytotoxic T lymphocytes (CTL). Here, we report on the generation of seven recombinant bovine leukocyte antigens (BoLA) and recombinant bovine β2-microglobulin from which p-MHC class I tetramers can be derived in ~48 h. We validated a set of p-MHC class I tetramers against a panel of CTL lines specific to seven epitopes on five different antigens of Theileria parva, a protozoan pathogen causing the lethal bovine disease East Coast fever. One of the p-MHC class I tetramers was tested in ex vivo assays and we detected T. parva specific CTL in peripheral blood of cattle at day 15-17 post-immunization with a live parasite vaccine. The algorithm NetMHCpan predicted alternative epitope sequences for some of the T. parva CTL epitopes. Using an ELISA assay to measure peptide-BoLA monomer formation and p-MHC class I tetramers of new specificity, we demonstrate that a predicted alternative epitope Tp229-37 rather than the previously reported Tp227-37 epitope is the correct Tp2 epitope presented by BoLA-6*04101. We also verified the prediction by NetMHCpan that the Tp587-95 epitope reported as BoLA-T5 restricted can also be presented by BoLA-1*02301, a molecule similar in sequence to BoLA-T5. In addition, Tp587-95 specific bovine CTL were simultaneously stained by Tp5-BoLA-1*02301 and Tp5-BoLA-T5 tetramers suggesting that one T cell receptor can bind to two different BoLA MHC class I molecules presenting the Tp587-95 epitope and that these BoLA molecules fall into a single functional supertype.
Sequestration of Plasmodium falciparum-infected erythrocytes in host blood vessels is a key triggering event in the pathogenesis of severe childhood malaria, which is responsible for about one million deaths every year1. Sequestration is mediated by specific interactions between members of the P. falciparum erythrocyte membrane protein 1 (PfEMP1) family and receptors on the endothelial lining2. Severe malaria is associated with expression of specific PfEMP1 subtypes containing domain cassettes (DC) 8 and 133, but the endothelial receptor for parasites expressing these proteins was unknown4,5. Here, we identify endothelial protein C receptor (EPCR), which mediates cytoprotective effects of activated protein C6, as the endothelial receptor for DC8 and DC13 PfEMP1. We show that EPCR binding is mediated through the N-terminal cysteine-rich interdomain region (CIDRα1) of DC8 and group A PfEMP1 subfamilies and that CIDRα1 interferes with protein C binding to EPCR. This PfEMP1 adhesive property links P. falciparum cytoadhesion to a host receptor involved in anticoagulation and endothelial cytoprotective pathways and has implications for understanding malaria pathology and the development of new malaria interventions.
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
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/.