The mutational landscape of human olfactory G protein-coupled receptors

Abstract

Background Olfactory receptors (ORs) constitute a large family of sensory proteins that enable us to recognize a wide range of chemical volatiles in the environment. By contrast to the extensive information about human olfactory thresholds for thousands of odorants, studies of the genetic influence on olfaction are limited to a few examples. To annotate on a broad scale the impact of mutations at the structural level, here we analyzed a compendium of 119,069 natural variants in human ORs collected from the public domain. Results OR mutations were categorized depending on their genomic and protein contexts, as well as their frequency of occurrence in several human populations. Functional interpretation of the natural changes was estimated from the increasing knowledge of the structure and function of the G protein-coupled receptor (GPCR) family, to which ORs belong. Our analysis reveals an extraordinary diversity of natural variations in the olfactory gene repertoire between individuals and populations, with a significant number of changes occurring at the structurally conserved regions. A particular attention is paid to mutations in positions linked to the conserved GPCR activation mechanism that could imply phenotypic variation in the olfactory perception. An interactive web application (hORMdb, Human Olfactory Receptor Mutation Database) was developed for the management and visualization of this mutational dataset. Conclusion We performed topological annotations and population analysis of natural variants of human olfactory receptors and provide an interactive application to explore human OR mutation data. We envisage that the utility of this information will increase as the amount of available pharmacological data for these receptors grow. This effort, together with ongoing research in the study of genetic changes in other sensory receptors could shape an emerging sensegenomics field of knowledge, which should be considered by food and cosmetic consumer product manufacturers for the benefit of the general population.

The Role of Knockout Olfactory Receptor Genes in Odor Discrimination

“…The identified variants’ complete characteristics were detailed in Table 1 and Supplementary Tables S1–S3 . By comparison with the hORMdb database [ 36 ], we found information on 39 variants belonging to genes comprising 13 out of 18 OR families. All but one (14_20666175_C_CA/rs55781225) were annotated as affecting all gnomAD populations.…”

“…We defined “burden of OR-KO genes” as the total number of OR genes KO per individual and compared alternative allele (ALT) frequencies of HKO variants with data from 1000 Genomes Project phase 3 [ 34 ] and gnomAD v.2.1.1 [ 35 ] using the R implementation of the Chi-squared test. We extracted information about topological annotations from the Human Olfactory Receptor Mutation Database (hORMdb) [ 36 ].…”

Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose

“…In addition, computational molecular modeling has been useful to understand the effect of genetic variants of TASR2s and ORs on ligand sensitivity (Biarnés et al 2010 ; Marchiori et al 2013 ; Geithe et al 2017 ; March et al, 2015 ; Cierco-Jiménez et al 2021 ). In the aforementioned case of TAS2R38, an ensemble of receptor homology models was generated, followed by molecular docking of PTC and further refinement with multiscale MD simulations (Biarnés et al 2010 ; Marchiori et al 2013 ).…”

“…For instance, ORDB (Crastro et al 2002 ), OlfactionDB (Modena et al 2011 ), OdorDB (Marenco et al 2013 ) and the Leibniz-LSB@TUM Odorant Database (Dunkel et al 2014 ; Kreissl et al 2019 ) contain information about odorant molecules and/or their cognate olfactory receptors. Complementarily, HORDE (Olender et al 2013 ) is dedicated to olfactory receptor SNPs and haplotypes and their frequency in the population, whereas hORMdb (Cierco-Jiménez et al 2021 ) additionally maps the sequence variants onto known topological positions of class A GPCRs to predict the functional impact of such mutations. As in the case of bitter tastants, machine learning approaches have also been developed for odorants (Lötsch et al 2019 ).…”

Vocal Creativity in Elephant Sound Production

“…This requires control over different vocal systems, e.g., of the larynx and supra-laryngeal nasal and oral vocal tract structures in the low-frequency rumbles [ 10 , 13 , 16 ]. In trumpets, the mode of production remains speculative, although, theoretically, trumpets are incongruently high in frequency for laryngeal sound production [ 10 , 12 , 17 ]. Asian elephants have been shown to produce species-specific high-pitched squeaks, reaching a mean fundamental frequency of up to 2 kHz, by forcing air through the tensed lips, inducing self-sustained lip vibration (lip buzzing; see [ 17 ]).…”