Massive Expansion of Bitter Taste Receptors in Blind Cavefish, Astyanax mexicanus.

A sensory deficit both at the individual and at the species level can be compensated by increased acuity in other senses. The loss of vision in blind cavefish, Astyanax mexicanus, appears to be partially counterbalanced by enhanced chemosensory perception. Whether such improvement also involves adaptive changes in chemosensory receptor repertoires was unknown. The typical bitter taste receptor repertoire of teleost fish is reported as 3-5 genes, much smaller than that of many terrestrial species. Interestingly, several fish species, for example, mudskipper, have evolved a terrestrial lifestyle, but again it was unknown, whether this change in habitat is reflected in the size of gustatory receptor repertoires. We have searched the genomes of 15 fish species and performed a thorough phylogenetic analysis to delineate their bitter taste receptor repertoires. We report no adaptation for 4 mudskipper species, which exhibit 3-4 bitter taste receptor genes, and thus a typical teleost repertoire, shaped by few gene losses and minor gene duplications from an ancestral repertoire of 4 genes. However, and in sharp contrast to all other teleost fish species analyzed, blind cavefish possess more than 20 intact bitter taste receptors and several pseudogenes, rivaling the complexity of the human bitter taste receptor repertoire. The gene duplications giving rise to the current cavefish bitter taste receptor repertoire appear to have occurred well before the loss of vision, consistent with this increase in repertoire size constituting a preadaptive trait that conceivably could compensate to some extent for the lack of visual cues.

Representation Learning for Class C G Protein-Coupled Receptors Classification.

G protein-coupled receptors (GPCRs) are integral cell membrane proteins of relevance for pharmacology. The complete tertiary structure including both extracellular and transmembrane domains has not been determined for any member of class C GPCRs. An alternative way to work on GPCR structural models is the investigation of their functionality through the analysis of their primary structure. For this, sequence representation is a key factor for the GPCRs' classification context, where usually, feature engineering is carried out. In this paper, we propose the use of representation learning to acquire the features that best represent the class C GPCR sequences and at the same time to obtain a model for classification automatically. Deep learning methods in conjunction with amino acid physicochemical property indices are then used for this purpose. Experimental results assessed by the classification accuracy, Matthews' correlation coefficient and the balanced error rate show that using a hydrophobicity index and a restricted Boltzmann machine (RBM) can achieve performance results (accuracy of 92.9%) similar to those reported in the literature. As a second proposal, we combine two or more physicochemical property indices instead of only one as the input for a deep architecture in order to add information from the sequences. Experimental results show that using three hydrophobicity-related index combinations helps to improve the classification performance (accuracy of 94.1%) of an RBM better than those reported in the literature for class C GPCRs without using feature selection methods.

Family A G-Protein coupled receptors: an overview of structure-function relationships

Family A G-protein coupled receptors (AGPCRs) form the largest group of correlate receptors whose structure, a bundle of seven-trans-membrane (7 TM) helices, may be activated thus becoming able to transduce a signal from the extracellular medium to the cytosol. This activation may be constitutional, for instance due to permanent structural modifications, or be physiologically triggered by agonist binding at an external and accessible specific site. Based on thestructures of agonists, AGPCRs may be divided according to pharmacological assays into many classes of receptors, each one comprising many types or sub-types of proteins, as differentiated by specific binding of inhibitors, all of them performing a multitude of functions. It is noteworthy that AGPCRs have been more recently cloned and their sequences of amino acids determined in a large scale, a condition that has allowed these receptors to be sorted by a new criterium. Sequence analyses have consistently matched functional assays for classification of AGPCRs except for a certain number of functionally unknown receptors which have been cataloged as orphan receptors. A colossal number of AGPCRs, more than 10,000 sequences belonging to more than 1,000 different types of receptors, may nowadays be multiply-aligned what has been enabling the determination of parameters of residue conservation and characterization of special motifs along the structure of these proteins. There are at the present time, high-resolution 3D structures for the following AGPCRs: inactive rhodopsin, retinal-free opsin, Beta adrenoceptor and adenosine receptors. Among them, hodopsin structures are reliable enough to be used as prototypes for analyses of residue conservation and mechanisms of activation of receptors, specially at the level of the more conserved structure in the cytosolic half of their 7TM bundle.