An olfactory receptor pseudogene whose function emerged in humans: a case study in the evolution of structure-function in GPCRs

DNA damage drives antigen diversification through mosaic Variant Surface Glycoprotein (VSG) formation in Trypanosoma brucei

Antigenic variation, using large genomic repertoires of antigen-encoding genes, allows pathogens to evade host antibody. Many pathogens, including the African trypanosome Trypanosoma brucei, extend their antigenic repertoire through genomic diversification. While evidence suggests that T. brucei depends on the generation of new variant surface glycoprotein (VSG) genes to maintain a chronic infection, a lack of experimentally tractable tools for studying this process has obscured its underlying mechanisms. Here, we present a highly sensitive targeted sequencing approach for measuring VSG diversification. Using this method, we demonstrate that a Cas9-induced DNA double-strand break within the VSG coding sequence can induce VSG recombination with patterns identical to those observed during infection. These newly generated VSGs are antigenically distinct from parental clones and thus capable of facilitating immune evasion. Together, these results provide insight into the mechanisms of VSG diversification and an experimental framework for studying the evolution of antigen repertoires in pathogenic microbes.

Comparative Analysis of Olfactory Receptor Repertoires Sheds Light on the Diet Adaptation of the Bamboo-Eating Giant Panda Based on the Chromosome-Level Genome

The giant panda (Ailuropoda melanoleuca) is the epitome of a flagship species for wildlife conservation and also an ideal model of adaptive evolution. As an obligate bamboo feeder, the giant panda relies on the olfaction for food recognition. The number of olfactory receptor (OR) genes and the rate of pseudogenes are the main factors affecting the olfactory ability of animals. In this study, we used the chromosome-level genome of the giant panda to identify OR genes and compared the genome sequences of OR genes with five other Ursidae species (spectacled bear (Tremarctos ornatus), American black bear (Ursus americanus), brown bear (Ursus arctos), polar bear (Ursus maritimus) and Asian black bear (Ursus thibetanus)). The giant panda had 639 OR genes, including 408 functional genes, 94 partial OR genes and 137 pseudogenes. Among them, 222 OR genes were detected and distributed on 18 chromosomes, and chromosome 8 had the most OR genes. A total of 448, 617, 582, 521 and 792 OR genes were identified in the spectacled bear, American black bear, brown bear, polar bear and Asian black bear, respectively. Clustering analysis based on the OR protein sequences of the six species showed that the OR genes distributed in 69 families and 438 subfamilies based on sequence similarity, and the six mammals shared 72 OR gene subfamilies, while the giant panda had 31 unique OR gene subfamilies (containing 35 genes). Among the 35 genes, there are 10 genes clustered into 8 clusters with 10 known human OR genes (OR8J3, OR51I1, OR10AC1, OR1S2, OR1S1, OR51S1, OR4M1, OR4M2, OR51T1 and OR5W2). However, the kind of odor molecules can be recognized by the 10 known human OR genes separately, which needs further research. The phylogenetic tree showed that 345 (about 84.56%) functional OR genes were clustered as Class-II, while only 63 (about 15.44%) functional OR genes were clustered as Class-I, which required further and more in-depth research. The potential odor specificity of some giant panda OR genes was identified through the similarity to human protein sequences. Sequences similar to OR2B1, OR10G3, OR11H6 and OR11H7P were giant panda-specific lacking, which may be related to the transformation and specialization from carnivore to herbivore of the giant panda. Since our reference to flavoring agents comes from human research, the possible flavoring agents from giant panda-specific OR genes need further investigation. Moreover, the conserved motifs of OR genes were highly conserved in Ursidae species. This systematic study of OR genes in the giant panda will provide a solid foundation for further research on the olfactory function and variation of the giant panda.

Deep sequencing of the murine olfactory receptor neuron transcriptome

The ability of animals to sense and differentiate among thousands of odorants relies on a large set of olfactory receptors (OR) and a multitude of accessory proteins within the olfactory epithelium (OE). ORs and related signaling mechanisms have been the subject of intensive studies over the past years, but our knowledge regarding olfactory processing remains limited. The recent development of next generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice. The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome. In OE samples, nearly all OR and trace amine-associated receptor (TAAR) genes involved in the perception of volatile amines were detectably expressed. Other genes known to participate in olfactory signaling pathways were among the 200 genes with the highest expression levels in the OE. To identify OE-specific genes, we compared olfactory neuron expression profiles with RNA-Seq transcriptome data from different murine tissues. By analyzing different transcript classes, we detected the expression of non-olfactory GPCRs in ORNs and established an expression ranking for GPCRs detected in the OE. We also identified other previously undescribed membrane proteins as potential new players in olfaction. The quantitative and comprehensive transcriptome data provide a virtually complete catalogue of genes expressed in the OE and present a useful tool to uncover candidate genes involved in, for example, olfactory signaling, OR trafficking and recycling, and proliferation.

A computational microscope focused on the sense of smell

In this article, we review studies of the protagonists of the perception of smell focusing on Odorant-Binding Proteins and Olfactory Receptors. We notably put forward studies performed by means of molecular modeling, generally combined with experimental data. Those works clearly emphasize that computational approaches are now a force to reckon with. In the future, they will certainly be more and more used, notably in the framework of a computational microscope meant to observe how the laws of physics govern the biomolecular systems originating our sense of smell.

DOR - a Database of Olfactory Receptors - Integrated Repository for Sequence and Secondary Structural Information of Olfactory Receptors in Selected Eukaryotic Genomes

Olfaction is the response to odors and is mediated by a class of membrane-bound proteins called olfactory receptors (ORs). An understanding of these receptors serves as a good model for basic signal transduction mechanisms and also provides important clues for the strategies adopted by organisms for their ultimate survival using chemosensory perception in search of food or defense against predators. Prior research on cross-genome phylogenetic analyses from our group motivated the addressal of conserved evolutionary trends, clustering, and ortholog prediction of ORs. The database of olfactory receptors (DOR) is a repository that provides sequence and structural information on ORs of selected organisms (such as Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Homo sapiens). Users can download OR sequences, study predicted membrane topology, and obtain cross-genome sequence alignments and phylogeny, including three-dimensional (3D) structural models of 100 selected ORs and their predicted dimer interfaces. The database can be accessed from http://caps.ncbs.res.in/DOR. Such a database should be helpful in designing experiments on point mutations to probe into the possible dimerization modes of ORs and to even understand the evolutionary changes between different receptors.

The state of the art of odorant receptor deorphanization: a report from the orphanage

The odorant receptors (ORs) provide our main gateway to sensing the world of volatile chemicals. This involves a complex encoding process in which multiple ORs, each of which detects its own set of odorants, work as an ensemble to produce a distributed activation code that is presumably unique to each odorant. One marked challenge to decoding the olfactory code is OR deorphanization, the identification of a set of activating odorants for a particular receptor. Here, we survey various methods used to try to express defined ORs of interest. We also suggest strategies for selecting odorants for test panels to evaluate the functional expression of an OR. Integrating these tools, while retaining awareness of their idiosyncratic limitations, can provide a multi-tiered approach to OR deorphanization, spanning the initial discovery of a ligand to vetting that ligand in a physiologically relevant setting.

Databases in SenseLab for the genomics, proteomics, and function of olfactory receptors

We present here, the salient aspects of three databases: Olfactory Receptor Database (ORDB) is a repository of genomics and proteomics information of ORs; OdorDB stores information related to odorous compounds, specifically identifying those that have been shown to interact with olfactory rectors; and OdorModelDB disseminates information related to computational models of olfactory receptors (ORs). The data stored among these databases is integrated. Presented in this chapter are descriptions of these resources, which are part of the SenseLab suite of databases, a discussion of the computational infrastructure that enhances the efficacy of information storage, retrieval, dissemination, and automated data population from external sources.

Knowledge-Driven, Data-Assisted Integrative Pathway Analytics

Target and biomarker selection in drug discovery relies extensively on the use of various genomics platforms. These technologies generate large amounts of data that can be used to gain novel insights in biology. There is a strong need to mine these information-rich datasets in an effective and efficient manner. Pathway and network based approaches have become an increasingly important methodology to mine bioinformatics datasets derived from ‘omics’ technologies. These approaches also find use in exploring the unknown biology of a disease or functional process. This chapter provides an overview of pathway databases and network tools, network architecture, text mining and existing methods used in knowledge-driven data analysis. It shows examples of how these databases and tools can be used integratively to apply existing knowledge and network-based approach in data analytics.

Hydrophobicity profiles in G protein-coupled receptor transmembrane helical domains

The lack of a crystallographically derived structure for all but three G (TP [guanosine triphosphate]-binding) protein-coupled receptor (GPCRs) proteins necessitates the use of computationally derived methods to determine their structures. Computational methodologies allow a mechanistic glimpse into GPCR-ligand interactions at a molecular level to better understand the initial steps leading to a protein's biologic functions, ie, protecting the ligands that activate, deactivate, or inhibit the protein, stabilizing protein structure in the membrane's lipid bilayer, and ensuring that the hydrophilic environment within the GPCR-binding pocket is maintained. Described here is a formalism that quantifies the amphiphilic nature of a helix, by determining the effective hydrophobicity (or hydrophilicity) at specific positions around it. This formalism will enable computational protein modelers to position helices so that the functional aspects of GPCRs are adequately represented in the model. Hydro-Eff®, an online tool, allows users to calculate effective helical hydrophobicities.

Pseudogene: lessons from PCR bias, identification and resurrection

Pseudogenes are fragments of non-functional genomic DNA with high sequences similarity to normal functional genes. They are a kind of non-coding DNA produced by gene duplications or retrotranspositions. Pseudogenes exist in human genome at a large quantity which is nearly as much as that of normal functional genes. They could cause PCR bias in molecular biology experiments and confuse related analysis. On the other hand, pesudogenes are important elements in genomics study for getting an integral picture of genome annotation. They give diverse information of evolutionary history and are regarded as genome fossils. Worldwide research project "encyclopedia of DNA elements"(ENCODE) founded in recent years have enhanced our understanding of pseudogenes. Approaches established to identify pseudogenes include PseudoPipe, HAVANA method, PseudoFinder, RetroFinder, GIS-PET method and consensus method. This paper discuss pseudogenes with respect to the formation mechanisms, distribution, and problems for PCR, importance and identification of pseudogenes. Furthermore, potential resurrection of pseudogenes and their potential function are discussed.

Odor detection by humans of lineal aliphatic aldehydes and helional as gauged by dose-response functions

We have measured concentration detection (i.e., psychometric) functions to determine the odor detectability of homologous aliphatic aldehydes (propanal, butanal, hexanal, octanal, and nonanal) and helional. Subjects (16 < or = n < or = 18) used a 3-alternative forced-choice procedure against carbon-filtered air (blanks), under an ascending concentration approach. Generation, delivery, and control of each vapor were achieved via an 8-station vapor delivery device. Gas chromatography served to quantify the concentrations presented. Group and individual functions were modeled by a sigmoid (logistic) equation. Odor detection thresholds (ODTs) were defined as the concentration producing a detectability (P) halfway (P = 0.5) between chance (P = 0.0) and perfect detection (P = 1.0). ODTs decreased with carbon chain length: 2.0, 0.46, 0.33, and 0.17 ppb, respectively, from propanal to octanal, but the threshold increased for nonanal (0.53 ppb), revealing maximum sensitivity for the 8-carbon member. The strong olfactory receptor (OR) ligands octanal and helional (0.14 ppb) showed the lowest thresholds. ODTs fell at the lower end of previously reported values. Interindividual variability (ODT ratios) amounted to a factor ranging from 10 to 50, lower than typically reported, and was highest for octanal and hexanal. The behavioral dose-response functions emerge at concentrations 2-5 orders of magnitude lower than those required for functions tracing the activation of specific human ORs by the same aldehydes in cell/molecular studies, after all functions were expressed as vapor concentrations.

Olfactory psychometric functions for homologous 2-ketones

We measured concentration-detection (i.e., psychometric) odor functions for the homologous ketones propanone (acetone), 2-pentanone, 2-heptanone, and 2-nonanone. Under a forced-choice procedure, stimuli were presented via an 8-channel air-dilution olfactometer that allowed natural sampling of the odorant and whose output was quantified by gas chromatography. Subjects (17-22 per compound) comprised young adults from both genders, all normosmics and nonsmokers. A sigmoid (logistic) equation tightly fitted group and individual functions. The odor detection threshold (ODT) was the concentration detectable at halfway (P=0.5) between chance (P=0.0) and perfect (P=1.0) detection. Odor sensitivity increased (i.e., thresholds decreased) from acetone to heptanone, remaining constant for nonanone. This relative trend was also observed in previous work and in odor thresholds compilations, but the absolute ODTs obtained here were consistently at the lower end of those reported before. Interindividual variability of ODTs was about 1 order of magnitude. These odor functions measured behaviorally in humans were obtained at vapor concentrations 1000 times lower than functions measured via activation, with similar 2-ketones, of receptor neurons converging into individual olfactory glomeruli of mice, visualized with calcium sensitive dyes. Odorant concentrations presented as vapors (as in behavioral studies) and those presented as liquids (as in cellular/tissue studies) can be rendered equivalent via liquid-vapor partition coefficients and, then, compared in relative olfactory potency. These comparisons can reveal how sensitivity is progressively shaped across levels of the neural pathway.

Computational Biology of Olfactory Receptors

Olfactory receptors, in addition to being involved in first step of the physiological processes that leads to olfaction, occupy an important place in mammalian genomes. ORs constitute super families in these genomes. Elucidating ol-factory receptor function at a molecular level can be aided by a computationally derived structure and an understanding of its interactions with odor molecules. Experimental functional analyses of olfactory receptors in conjunction with computational studies serve to validate findings and generate hypotheses. We present here a review of the research efforts in: creating computational models of olfactory receptors, identifying binding strategies for these receptors with odorant molecules, performing medium to long range simulation studies of odor ligands in the receptor binding region, and identifying amino acid positions within the receptor that are responsible for ligand-binding and olfactory receptor activation. Written as a primer and a teaching tool, this review will help researchers extend the methodologies described herein to other GPCRs.