Genomic and functional characterization of G protein-coupled receptors in the human pathogen Schistosoma mansoni and the model planarian Schmidtea mediterranea

G protein-coupled receptors (GPCRs) constitute the largest known superfamily of integral membrane proteins, and represent a particularly lucrative set of chemotherapeutic targets. These seven transmembrane receptors play a central role in eukaryotic signal transduction and physiology, mediating cellular responses to a diverse range of extracellular stimuli. The phylum Platyhelminthes is of considerable medical and biological importance, housing prominent human pathogens as well as established model organisms in the realm of developmental and stem cell biology. There exists ample motivation to elucidate the structural and functional properties of GPCRs in this phylum. The availability of whole genome sequence data for the human blood fluke Schistosoma mansoni and the model planarian Schmidtea mediterranea paves the way for the first genome-wide analyses of platyhelminth GPCRs. Extensive efforts were made to delineate the receptor complements of these organisms. Further work primarily focuses on validation of a novel method for elucidating receptor function in the native cell membrane environment. Together, these genomic and functional data improve our understanding of basic platyhelminth receptor biology and shed light on a promising set of anthelmintic drug targets. Application of a transmembrane-focused it in silico protocol led to the discovery of 116 S. mansoni and 333 S. mediterranea GPCRs, followed by extensive curation of underlying gene models. Phylogenetic analysis of the resulting dataset confirmed the presence of the primary metazoan GRAFS families and revealed novel lineage-specific receptor groupings, including a large platyhelminth-specific Rhodopsin-like subfamily (PROF1) and a planarian-specific Adhesion-like family (PARF1). Support vector machines (SVMs) were trained and used for ligand-based classification of full-length Rhodopsin GPCRs, complementing phylogenetic and homology-based classification. PROF1 receptors were further revealed as neuronally-expressed endoGPCRs via whole mount in situ hybridization. In light of the unreliable nature of heterologous approaches to GPCR deorphanization, a novel loss-of-function assay was developed for ascertaining the ligand and G protein coupling properties of GPCRs in their native cell membrane environment. RNA interference (RNAi) was used in conjunction with a cAMP radioimmunoassay (RIA) to monitor second messenger modulation in response to the translational suppression of individual receptors. This strategy was applied to the deorphanization of both neuropeptide and aminergic GPCRs, allowing for the determination of Gαs and Gαi/o-mediated signaling. Loss-of-function phenotypic assays were performed in parallel. While these results establish the potential of this approach, future work can lead to further optimizations and the eventual adaptation of this protocol to higher-throughput platforms

Predicting Ion Channels Genes and Their Types With Machine Learning Techniques

Motivation: The number of ion channels is increasing rapidly. As many of them are associated with diseases, they are the targets of more than 700 drugs. The discovery of new ion channels is facilitated by computational methods that predict ion channels and their types from protein sequences.Methods: We used the SVMProt and the k-skip-n-gram methods to extract the feature vectors of ion channels, and obtained 188- and 400-dimensional features, respectively. The 188- and 400-dimensional features were combined to obtain 588-dimensional features. We then employed the maximum-relevance-maximum-distance method to reduce the dimensions of the 588-dimensional features. Finally, the support vector machine and random forest methods were used to build the prediction models to evaluate the classification effect.Results: Different methods were employed to extract various feature vectors, and after effective dimensionality reduction, different classifiers were used to classify the ion channels. We extracted the ion channel data from the Universal Protein Resource (UniProt, http://www.uniprot.org/) and Ligand-Gated Ion Channel databases (http://www.ebi.ac.uk/compneur-srv/LGICdb/LGICdb.php), and then verified the performance of the classifiers after screening. The findings of this study could inform the research and development of drugs

The molecular underpinnings of neuronal cell identity in the stomatogastric ganglion of cancer borealis

Throughout the life of an organism, the nervous system must be able to balance changing in response to environmental stimuli with the need to produce reliable, repeatable activity patterns to create stereotyped behaviors. Understanding the mechanisms responsible for this regulation requires a wealth of knowledge about the neural system, ranging from network connectivity and cell type identification to intrinsic neuronal excitability and transcriptomic expression. To make strides in this area, we have employed the well-described stomatogastric nervous system of the Jonah crab Cancer borealis to examine the molecular underpinnings and regulation of neuron cell identity. Several crustacean circuits, including the stomatogastric nervous system and the cardiac ganglion, continue to provide important new insights into circuit dynamics and modulation (Diehl, White, Stein, & Nusbaum, 2013; Marder, 2012; Marder & Bucher, 2007; Williams et al., 2013), but this work has been partially hampered by the lack of extensive molecular sequence knowledge in crustaceans. Here we generated de novo transcriptome assembly from central nervous system tissue for C. borealis producing 42,766 contigs, focusing on an initial identification, curation, and comparison of genes that will have the most profound impact on our understanding of circuit function in these species. This included genes for 34 distinct ion channel types, 17 biogenic amine and 5 GABA receptors, 28 major transmitter receptor subtypes including glutamate and acetylcholine receptors, and 6 gap junction proteins -- the Innexins. ... With this reference transcriptome and annotated sequences in hand, we sought to determine the strengths and limitations of using the neuronal molecular profile to classify them into cell types. ... Since the resulting activity of a neuron is the product of the expression of ion channel genes, we sought to further probe the expression profile of neurons across a range of cell types to understand how these patterns of mRNA abundance relate to the properties of individual cell types. ... Finally, we sought to better understand the molecular underpinnings of how these correlated patterns of mRNA expression are generated and maintained.Includes bibliographical reference

Profiling patterns of interhelical associations in membrane proteins.

A novel set of methods has been developed to characterize polytopic membrane proteins at the topological, organellar and functional level, in order to reduce the existing functional gap in the membrane proteome. Firstly, a novel clustering tool was implemented, named PROCLASS, to facilitate the manual curation of large sets of proteins, in readiness for feature extraction. TMLOOP and TMLOOP writer were implemented to refine current topological models by predicting membrane dipping loops. TMLOOP applies weighted predictive rules in a collective motif method, to overcome the inherent limitations of single motif methods. The approach achieved 92.4% accuracy in sensitivity and 100% reliability in specificity and 1,392 topological models described in the Swiss-Prot database were refined. The subcellular location (TMLOCATE) and molecular function (TMFUN) prediction methods rely on the TMDEPTH feature extraction method along data mining techniques. TMDEPTH uses refined topological models and amino acid sequences to calculate pairs of residues located at a similar depth in the membrane. Evaluation of TMLOCATE showed a normalized accuracy of 75% in discriminating between proteins belonging to the main organelles. At a sequence similarity threshold of 40%, TMFLTN predicted main functional classes with a sensitivity of 64.1-71.4%) and 70% of the olfactory GPCRs were correctly predicted. At a sequence similarity threshold of 90%, main functional classes were predicted with a sensitivity of 75.6-92.8%) and class A GPCRs were sub-classified with a sensitivity of 84.5%>-92.9%. These results reflect a direct association between the spatial arrangement of residues in the transmembrane regions and the capacity for polytopic membrane proteins to carry out their functions. The developed methods have for the first time categorically shown that the transmembrane regions hold essential information associated with a wide range of functional properties such as filtering and gating processes, subcellular location and molecular function

Prediction of DNase I Hypersensitive Sites by Using Pseudo Nucleotide Compositions

DNase I hypersensitive sites (DHS) associated with a wide variety of regulatory DNA elements. Knowledge about the locations of DHS is helpful for deciphering the function of noncoding genomic regions. With the acceleration of genome sequences in the postgenomic age, it is highly desired to develop cost-effective computational methods to identify DHS. In the present work, a support vector machine based model was proposed to identify DHS by using the pseudo dinucleotide composition. In the jackknife test, the proposed model obtained an accuracy of 83%, which is competitive with that of the existing method. This result suggests that the proposed model may become a useful tool for DHS identifications

Functional prediction of bioactive toxins in scorpion venom through bioinformatics

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Pharmacological and functional regulation of two-pore domain potassium channels

Two pore domain potassium (K2P) channels underlie the background potassium leak currents of excitable cells. In this study, the whole cell patch clamp technique was used with transiently transfected human embryonic kidney cells, and cerebellar granule neurones (CGNs) in primary culture, to compare the pharmacological properties of acid sensitive K2P channels. Zn2+, La3+, Cu2+, ruthenium red and Ru-360 blocked TASK-1 and TASK-3 channel currents. Substitution of external sodium ions with N-methyl-D-glucamine and choline also caused a significant reduction in TASK-1 and TASK-3 currents, demonstrating that maximal conductance through these potassium channels requires the presence of external sodium ions. Whilst Cu2+ blocked TASK-1 and TASK-3 channel currents, TASK-2 currents were not affected by the ion. Mannitol, a scavenger of hydroxyl radicals, did not alter Cu2+ block of TASK-3 currents showing hydroxyl radical production was not the underlying mechanism. Application of thiol oxidant, DTNB (5’,5’-dithio-bis(2 nitrobenzoic acid)), showed a potent block, mimicking that of Cu2+ in size and reversibility. DTNB and Cu2+ block were reversed by disulphide-reducing DTT (dithiothreitol), suggesting thiol rich cysteine residues played a fundamental role in <y, TASK-3 current block by Cu . The standing-outward, voltage-insensitive potassium current in CGNs also showed DTNB and copper sensitivity. Substitutions of TASK-3 cysteine residues to alanine and serine retained copper sensitivity while whole cell current amplitude diminished and a sensitivity to alkaline pH (8.4) was introduced to TASK-3. Point mutation of cysteine 110 was found to be key in facilitating the pH 8.4 potentiation of current. Cu2+ and DTNB were applied to a TASK-2/TASK-3 chimera channel where a robust, albeit reduced, block was observed. The central role of the TASK channels in neuronal excitability is demonstrated by their extensive physiological and cross-species distribution and varied mechanisms of regulation. In this study, the interaction of essential trace element Cu2+ was shown to be a significant mechanism of TASK regulation.Open acces