Odorant Receptor Inhibition Is Fundamental to Odor Encoding

Molecular determinants of olfactory receptor activation: Comparative analysis of Olfr205 and Olfr740 family member responses to indole

Indole is widely present in nature and contributes significantly to the smell of flowers and animal excretion. However, the odor perception mechanism for indole is unclear, despite previous reports suggesting that it activates the Olfr740 family of receptors. In this study, we successfully identified another receptor, Olfr205, that is responsive to indole. Molecular model construction and binding pocket analysis predicted that the A202 residue in transmembrane helix 5 of Olfr205 forms a crucial hydrogen bond with indole, facilitating receptor activation. Additionally, G112 in transmembrane helix 3 of the Olfr740 family is involved in indole activation of receptors. Finally, our mutant function assay showed that substitution of A202 in Olfr205 and G112 in Olfr740 with other amino acids significantly decreased the receptor response to indole, which provides robust evidence to confirm the docking results. In summary, our study is the first to reveal that Olfr205 is an olfactory receptor distinct from those in the Olfr740 family that is activated by indole. Moreover, these receptors display different indole-binding mechanisms. This study sheds light on molecular binding mechanisms and contributes to a deeper understanding of indole perception.

Signal integration and adaptive sensory diversity tuning in Escherichia coli chemotaxis

In uncertain environments, phenotypic diversity can be advantageous for survival. However, as the environmental uncertainty decreases, the relative advantage of having diverse phenotypes decreases. Here, we show how populations of E. coli integrate multiple chemical signals to adjust sensory diversity in response to changes in the prevalence of each ligand in the environment. Measuring kinase activity in single cells, we quantified the sensitivity distribution to various chemoattractants in different mixtures of background stimuli. We found that when ligands bind uncompetitively, the population tunes sensory diversity to each signal independently, decreasing diversity when the signal's ambient concentration increases. However, among competitive ligands, the population can only decrease sensory diversity one ligand at a time. Mathematical modeling suggests that sensory diversity tuning benefits E. coli populations by modulating how many cells are committed to tracking each signal proportionally as their prevalence changes.

Enhancement of transcription efficiency by TAR-Tat system increases the functional expression of human olfactory receptors

Humans have approximately 400 different olfactory receptors (hORs) and recognize odorants through the repertoire of hOR responses. Although the cell surface expression of hORs is critical to evaluate their response, hORs are poorly expressed on the surface of heterologous cells. To address this problem, previous studies have focused on hOR transportation to the membrane. Nevertheless, the response pattern of hORs to odorants has yet to be successfully linked, and the response sensitivity still remains to be improved. In this study, we demonstrate that increasing the transcriptional level can result in a significant increase in cell surface and functional expression of hORs. We used the TAR-Tat system, which increases the transcription efficiency through positive feedback, and found that OR1A1, OR6N2, and OR51M1 exhibited robust expression. Moreover, this system induces enhanced hOR responses to odorants, thus defining four hORs as novel n-hexanal receptors and n-hexanal is an inverse agonist to one of them. Our results suggested that using the TAR-Tat system and increasing the transcriptional level of hORs can help understanding the relationship between hORs and odorants that were previously undetectable. This finding could facilitate the understanding of the sense of smell by decoding the repertoire of hOR responses.

Signal Integration and Adaptive Sensory Diversity Tuning in Escherichia coli Chemotaxis

In uncertain environments, phenotypic diversity can be advantageous for survival. However, as the environmental uncertainty decreases, the relative advantage of having diverse phenotypes decreases. Here, we show how populations of E. coli integrate multiple chemical signals to adjust sensory diversity in response to changes in the prevalence of each ligand in the environment. Measuring kinase activity in single cells, we quantified the sensitivity distribution to various chemoattractants in different mixtures of background stimuli. We found that when ligands bind uncompetitively, the population tunes sensory diversity to each signal independently, decreasing diversity when the signal ambient concentration increases. However, amongst competitive ligands the population can only decrease sensory diversity one ligand at a time. Mathematical modeling suggests that sensory diversity tuning benefits E. coli populations by modulating how many cells are committed to tracking each signal proportionally as their prevalence changes.

A conserved odorant receptor underpins borneol-mediated repellency in culicine mosquitoes

The use of essential oils derived from the camphor tree to repel mosquitoes is an ancient practice that originated in Southeast Asia and gradually spread to China and across Europe via the Maritime Silk Road. The olfactory mechanisms by which these oils elicit avoidance behavior are unclear. Here we show that plant bicyclic monoterpenoids and borneol specifically activate a neural pathway that originates in the orphan olfactory receptor neuron of the capitate peg sensillum in the maxillary palp, and projects to the mediodorsal glomerulus 3 in the antennal lobe. This neuron co-locates with two olfactory receptor neurons tuned to carbon dioxide and octenol that mediate human-host detection. We also confirm that borneol elicits repellency against human-seeking female mosquitoes. Understanding the functional role of the mosquito maxillary palp is essential to investigating olfactory signal integration and host-selection behavior.

The molecular basis of sugar detection by an insect taste receptor

Animals crave sugars because of their energy potential and the pleasurable sensation of tasting sweetness. Yet all sugars are not metabolically equivalent, requiring mechanisms to detect and differentiate between chemically similar sweet substances. Insects use a family of ionotropic gustatory receptors to discriminate sugars1, each of which is selectively activated by specific sweet molecules2-6. Here, to gain insight into the molecular basis of sugar selectivity, we determined structures of Gr9, a gustatory receptor from the silkworm Bombyx mori (BmGr9), in the absence and presence of its sole activating ligand, D-fructose. These structures, along with structure-guided mutagenesis and functional assays, illustrate how D-fructose is enveloped by a ligand-binding pocket that precisely matches the overall shape and pattern of chemical groups in D-fructose. However, our computational docking and experimental binding assays revealed that other sugars also bind BmGr9, yet they are unable to activate the receptor. We determined the structure of BmGr9 in complex with one such non-activating sugar, L-sorbose. Although both sugars bind a similar position, only D-fructose is capable of engaging a bridge of two conserved aromatic residues that connects the pocket to the pore helix, inducing a conformational change that allows the ion-conducting pore to open. Thus, chemical specificity does not depend solely on the selectivity of the ligand-binding pocket, but it is an emergent property arising from a combination of receptor-ligand interactions and allosteric coupling. Our results support a model whereby coarse receptor tuning is derived from the size and chemical characteristics of the pocket, whereas fine-tuning of receptor activation is achieved through the selective engagement of an allosteric pathway that regulates ion conduction.

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Here, we show that odorant mixtures of increasing complexity evoke progressively denser OSN activity, yet cortical feedback activity is of similar sparsity for all stimuli. Also, representations of complex mixtures are similar in OSNs but are decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibit a sigmoidal relationship, cortical axonal responses are complex and nonmonotonic, which can be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

Predicting and improving complex beer flavor through machine learning

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

General Chemical Reaction Network Theory for Olfactory Sensing Based on G-Protein-Coupled Receptors: Elucidation of Odorant Mixture Effects and Agonist-Synergist Threshold

This work presents a general chemical reaction network theory for olfactory sensing processes that employ G-protein-coupled receptors as olfactory receptors (ORs). The theory can be applied to general mixtures of odorants and an arbitrary number of ORs. Reactions of ORs with G-proteins, in both the presence and absence of odorants, are explicitly considered. A unique feature of the theory is the definition of an odor activity vector consisting of strengths of odorant-induced signals from ORs relative to those due to background G-protein activity in the absence of odorants. It is demonstrated that each component of the odor activity defined this way reduces to a Michaelis-Menten form capable of accounting for cooperation or competition effects between different odorants. The main features of the theory are illustrated for a two-odorant mixture. Known and potential mixture effects, such as suppression, shadowing, inhibition, and synergy, are quantitatively described. Effects of relative values of rate constants, basal activity, and G-protein concentration are also demonstrated.

Signal processing in the vagus nerve: Hypotheses based on new genetic and anatomical evidence

Each organism must regulate its internal state in a metabolically efficient way as it interacts in space and time with an ever-changing and only partly predictable world. Success in this endeavor is largely determined by the ongoing communication between brain and body, and the vagus nerve is a crucial structure in that dialogue. In this review, we introduce the novel hypothesis that the afferent vagus nerve is engaged in signal processing rather than just signal relay. New genetic and structural evidence of vagal afferent fiber anatomy motivates two hypotheses: (1) that sensory signals informing on the physiological state of the body compute both spatial and temporal viscerosensory features as they ascend the vagus nerve, following patterns found in other sensory architectures, such as the visual and olfactory systems; and (2) that ascending and descending signals modulate one another, calling into question the strict segregation of sensory and motor signals, respectively. Finally, we discuss several implications of our two hypotheses for understanding the role of viscerosensory signal processing in predictive energy regulation (i.e., allostasis) as well as the role of metabolic signals in memory and in disorders of prediction (e.g., mood disorders).

A subclass of evening cells promotes the switch from arousal to sleep at dusk

Animals exhibit rhythmic patterns of behavior that are shaped by an internal circadian clock and the external environment. While light intensity varies across the day, there are particularly robust differences at twilight (dawn/dusk). These periods are also associated with major changes in behavioral states, such as the transition from arousal to sleep. However, the neural mechanisms by which time and environmental conditions promote these behavioral transitions are poorly defined. Here, we show that the E1 subclass of Drosophila evening clock neurons promotes the transition from arousal to sleep at dusk. We first demonstrate that the cell-autonomous clocks of E2 neurons alone are required to drive and adjust the phase of evening anticipation, the canonical behavior associated with "evening" clock neurons. We next show that conditionally silencing E1 neurons causes a significant delay in sleep onset after dusk. However, rather than simply promoting sleep, activating E1 neurons produces time- and light- dependent effects on behavior. Activation of E1 neurons has no effect early in the day, but then triggers arousal before dusk and induces sleep after dusk. Strikingly, these phenotypes critically depend on the presence of light during the day. Despite their influence on behavior around dusk, in vivo voltage imaging of E1 neurons reveals that their spiking rate does not vary between dawn and dusk. Moreover, E1-specific clock ablation has no effect on arousal or sleep. Thus, we suggest that, rather than specifying "evening" time, E1 neurons act, in concert with other rhythmic neurons, to promote behavioral transitions at dusk.

Force tuning explains changes in phasic dopamine signaling during stimulus-reward learning

According to a popular hypothesis, phasic dopamine (DA) activity encodes a reward prediction error (RPE) necessary for reinforcement learning. However, recent work showed that DA neurons are necessary for performance rather than learning. One limitation of previous work on phasic DA signaling and RPE is the limited behavioral measures. Here, we measured subtle force exertion while recording and manipulating DA activity in the ventral tegmental area (VTA) during stimulus-reward learning. We found two major populations of DA neurons that increased firing before forward and backward force exertion. Force tuning is the same regardless of learning, reward predictability, or outcome valence. Changes in the pattern of force exertion can explain results traditionally used to support the RPE hypothesis, such as modulation by reward magnitude, probability, and unpredicted reward delivery or omission. Thus VTA DA neurons are not used to signal RPE but to regulate force exertion during motivated behavior.

Antagonistic interactions between odorants alter human odor perception

The olfactory system uses hundreds of odorant receptors (ORs), the largest group of the G-protein-coupled receptor (GPCR) superfamily, to detect a vast array of odorants. Each OR is activated by specific odorous ligands, and like other GPCRs, antagonism can block activation of ORs. Recent studies suggest that odorant antagonisms in mixtures influence olfactory neuron activities, but it is unclear how this affects perception of odor mixtures. In this study, we identified a set of human ORs activated by methanethiol and hydrogen sulfide, two potent volatile sulfur malodors, through large-scale heterologous expression. Screening odorants that block OR activation in heterologous cells identified a set of antagonists, including β-ionone. Sensory evaluation in humans revealed that β-ionone reduced the odor intensity and unpleasantness of methanethiol. Additionally, suppression was not observed when methanethiol and β-ionone were introduced simultaneously to different nostrils. Our study supports the hypothesis that odor sensation is altered through antagonistic interactions at the OR level.

Olfaction: Allosteric modulation

New research indicates that the odor-evoked responses of human olfactory receptors can be enhanced via the non-competitive binding of an allosteric modulator. This modulatory mechanism adds an additional layer of complexity to the peripheral encoding of odors.

Allosteric modulation of a human odorant receptor

Odor perception is first determined by how the myriad of environmental volatiles are detected at the periphery of the olfactory system. The combinatorial activation of dedicated odorant receptors generates enough encoding power for the discrimination of tens of thousands of odorants. Recent studies have revealed that odorant receptors undergo widespread inhibitory modulation of their activity when presented with mixtures of odorants, a property likely required to maintain discrimination and ensure sparsity of the code for complex mixtures. Here, we establish the role of human OR5AN1 in the detection of musks and identify distinct odorants capable of enhancing its activity in binary mixtures. Chemical and pharmacological characterization indicate that specific α-β unsaturated aliphatic aldehydes act as positive allosteric modulators. Sensory experiments show decreased odor detection threshold in humans, suggesting that allosteric modulation of odorant receptors is perceptually relevant and likely adds another layer of complexity to how odors are encoded in the peripheral olfactory system.

A spatial map of antennal-expressed ionotropic receptors in the malaria mosquito

The mosquito's antenna represents its main olfactory appendage for detecting volatile chemical cues from the environment. Whole-mount fluorescence in situ hybridization of ionotropic receptors (IRs) expressed in the antennae reveals that the antenna might be divisible into proximal and distal functional domains. The number of IR-positive cells appear stereotyped within each antennal segment (flagellomere). Highly expressed odor-tuning IRs exhibit distinct co-localization patterns with the IR coreceptors Ir8a, Ir25a, and Ir76b that might predict their functional properties. Genetic knockin and in vivo functional imaging of IR41c-expressing neurons indicate both odor-induced activation and inhibition in response to select amine compounds. Targeted mutagenesis of IR41c does not abolish behavioral responses to the amine compounds. Our study provides a comprehensive map of IR-expressing neurons in the main olfactory appendage of mosquitoes. These findings show organizing principles of Anopheles IR-expressing neurons, which might underlie their functional contribution to the detection of behaviorally relevant odors.

Odor mixtures: A chord with silent notes

The olfactory world is one of complex mixtures and blends containing up to hundreds of molecules. Many of those molecules can act as agonists, antagonists or enhancers at different receptors. This complicates the mechanism by which higher centers construct perceptions of complex mixtures. We propose that along with structural chemistry, psychophysics, the techniques of medicinal chemistry and machine learning can begin to shed light on this difficult neural problem.

Odor encoding by signals in the olfactory bulb

To understand the operation of the olfactory system, it is essential to know how information is encoded in the olfactory bulb. We applied Shannon information theoretic methods to address this, with signals from up to 57 glomeruli simultaneously optically imaged from presynaptic inputs in glomeruli in the mouse dorsal (dOB) and lateral (lOB) olfactory bulb, in response to six exemplar pure chemical odors. We discovered that, first, the tuning of these signals from glomeruli to a set of odors is remarkably broad, with a mean sparseness of 0.83 and a mean signal correlation of 0.64. Second, both of these factors contribute to the low information that is available from the responses of even populations of many tens of glomeruli, which was only 1.35 bits across 33 glomeruli on average, compared with the 2.58 bits required to perfectly encode these six odors. Third, although there is considerable interest in the possibility of temporal encoding of stimulus including odor identity, the amount of information in the temporal aspects of the presynaptic glomerular responses was low (mean 0.11 bits) and, importantly, was redundant with respect to the information available from the rates. Fourth, the information from simultaneously recorded glomeruli asymptotes very gradually and nonlinearly, showing that glomeruli do not have independent responses. Fifth, the information from a population became available quite rapidly, within 100 ms of sniff onset, and the peak of the glomerular response was at 200 ms. Sixth, the information from the lOB was not additive with that of the dOB.NEW & NOTEWORTHY We report broad tuning and low odor information available across the lateral and dorsal bulb populations of glomeruli. Even though response latencies can be significantly predictive of stimulus identity, such contained very little information and none that was not redundant with information based on rate coding alone. Last, in line with the emerging notion of the important role of earliest stages of responses ("primacy"), we report a very rapid rise in information after each inhalation.

Olfactory coding

Modern humans live in real and digital environments dominated by sight and sound, but the vast majority of organisms on the planet rely on information received through air- or water-borne molecules to find food, avoid danger, and reproduce. Olfaction is at once both the primitive sensory modality and one of the hardest to understand, in large part due to the complexity of olfactory stimulus space. Whereas light and sound are easily ordered along natural physical axes that are reflected in their respective sensory codes, the organizational axes of odor space are not obvious. The search for systematic relationships between physicochemical characteristics of monomolecular odorants (carbon chain length, bond numbers, functional groups, etc.) and human perception of odorants suggests that olfactory perceptual space is a relatively low-dimensional structure. Odor descriptors provided by human observers are often significantly correlated. For instance, odors perceived as 'woody' are also likely to be described as 'warm', and many studies converge on hedonic valence or 'pleasantness' as being one of the most important dimensions of how people perceive odors. The identification of additional perceptual 'primaries' around which olfaction is organized is an active area of investigation, and a useful account of olfactory coding must explain this transformation of odor stimuli from the high dimensional chemical space to a lower dimensional perceptual space.

Effects of 3-octen-2-one on human olfactory receptor responses to vanilla flavor

Most of the odors that humans perceive daily are complex odors. It is believed that the modulation, enhancement, and suppression of overall complex odors are caused by interactions between odor molecules. In this study, to understand the interaction between odor molecules at the level of human olfactory receptor responses, the effects of 3-octen-2-one, which has been shown to modulate vanilla flavors, were analyzed using a human olfactory receptor sensor that uses all human olfactory receptors (388 types) as sensing molecules. As a result, the response intensity of 1 common receptor (OR1D2) was synergistically enhanced in vanilla flavor with 3-octen-2-one compared with vanilla flavor, and the response of 1 receptor (OR5K1) to vanilla flavor was completely suppressed. These results strongly suggested that the response of human olfactory receptors to complex odors is enhanced or suppressed by relatively few other odor molecules.

More than meets the AI: The possibilities and limits of machine learning in olfaction

Can machine learning crack the code in the nose? Over the past decade, studies tried to solve the relation between chemical structure and sensory quality with Big Data. These studies advanced computational models of the olfactory stimulus, utilizing artificial intelligence to mine for clear correlations between chemistry and psychophysics. Computational perspectives promised to solve the mystery of olfaction with more data and better data processing tools. None of them succeeded, however, and it matters as to why this is the case. This article argues that we should be deeply skeptical about the trend to black-box the sensory system's biology in our theories of perception. Instead, we need to ground both stimulus models and psychophysical data on real causal-mechanistic explanations of the olfactory system. The central question is: Would knowledge of biology lead to a better understanding of the stimulus in odor coding than the one utilized in current machine learning models? That is indeed the case. Recent studies about receptor behavior have revealed that the olfactory system operates by principles not captured in current stimulus-response models. This may require a fundamental revision of computational approaches to olfaction, including its psychological effects. To analyze the different research programs in olfaction, we draw on Lloyd's "Logic of Research Questions," a philosophical framework which assists scientists in explicating the reasoning, conceptual commitments, and problems of a modeling approach in question.

Context-dependent reversal of odorant preference is driven by inversion of the response in a single sensory neuron type

The valence and salience of individual odorants are modulated by an animal’s innate preferences, learned associations, and internal state, as well as by the context of odorant presentation. The mechanisms underlying context-dependent flexibility in odor valence are not fully understood. Here, we show that the behavioral response of Caenorhabditis elegans to bacterially produced medium-chain alcohols switches from attraction to avoidance when presented in the background of a subset of additional attractive chemicals. This context-dependent reversal of odorant preference is driven by cell-autonomous inversion of the response to these alcohols in the single AWC olfactory neuron pair. We find that while medium-chain alcohols inhibit the AWC olfactory neurons to drive attraction, these alcohols instead activate AWC to promote avoidance when presented in the background of a second AWC-sensed odorant. We show that these opposing responses are driven via engagement of distinct odorant-directed signal transduction pathways within AWC. Our results indicate that context-dependent recruitment of alternative intracellular signaling pathways within a single sensory neuron type conveys opposite hedonic valences, thereby providing a robust mechanism for odorant encoding and discrimination at the periphery.

Identification of volatile compounds correlated with consumer acceptability of strawberry preserves: Untargeted GC-MS analysis

Volatile compounds that impact the acceptability of strawberry preserves were investigated by untargeted GC-MS flavoromics analysis. Chemical profiles for fifteen strawberry preserves were modeled against consumer liking scores by orthogonal partial least squares (OPLS) with good fit (R²Y = 0.998) and predictive ability (Q² = 0.853). Ten highly predictive compounds were selected, nine of which were identified, and eight of which were quantified using tandem mass spectrometry. Sensory recombination difference testing revealed that the addition of predictive compounds to an average-liked preserve at levels found in the most-liked preserve induced a perceptible difference to frequent consumers of strawberry jams. One of the highly predictive compounds was identified (MS and synthesis) as a novel linalool oxide product 2-methyl-2-vinyl-tetrahydrofuran with a fruity, herbal-minty, piney aroma and a low odor threshold value.

An In Vitro HL-1 Cardiomyocyte-Based Olfactory Biosensor for Olfr558-Inhibited Efficiency Detection

Some short-chain fatty acids with a pungent or unpleasant odor are important components of human body odor. These malodors severely threaten human health. The antagonists of malodors would help to improve odor perception by affecting the interaction between odors and their receptors. However, the traditional odor detection and analysis methods, such as MOS, electrochemical, conductive polymer gas sensors, or chromatography-mass spectrometry are not suitable for screening the antagonists since they are unable to detect the ligand efficacy after odor-receptor binding. In this study, RT-PCR results showed that HL-1 cardiomyocytes endogenously express the olfactory receptor 558 (Olfr558) which can be activated by several malodorous short-chain fatty acids. Therefore, an in vitro HL-1 cardiomyocyte-based olfactory biosensor (HCBO-biosensor) was developed by combining cardiomyocytes and microelectrode array (MEA) chips for screening the potential antagonists of the Olfr558. Firstly, it showed that the biosensor specifically responded to ligands of Olfr558 through odor stimulation experiments. Then, an odor response model of HL-1 cardiomyocytes was constructed by a ligand of Olfr558 (isovaleric acid). The response feature of the in vitro HCBO-biosensor to individual odors and mixtures with a potential antagonist (citral or β-damascenone) were extracted and compared. Finally, the Olfr558-inhibited efficiency was indirectly detected by comparing the half-maximal inhibitory concentration of isovaleric acid. The results showed that β-damascenone greatly inhibited Olfr558 while citral showed no significant inhibitory effect. In conclusion, we built a novel screening method for the antagonists of Olfr558 based on HL-1 cardiomyocytes and the MEA chip which will assist odor-related companies to develop novel antagonists of Olfr558.

Functional analysis of human olfactory receptors with a high basal activity using LNCaP cell line

Humans use a family of more than 400 olfactory receptors (ORs) to detect odorants. However, deorphanization of ORs is a critical issue because the functional properties of more than 80% of ORs remain unknown, thus, hampering our understanding of the relationship between receptor function and perception. HEK293 cells are the most commonly used heterologous expression system to determine the function of a given OR; however, they cannot functionally express a majority of ORs probably due to a lack of factor(s) required in cells in which ORs function endogenously. Interestingly, ORs have been known to be expressed in a variety of cells outside the nose and play critical physiological roles. These findings prompted us to test the capacity of cells to functionally express a specific repertoire of ORs. In this study, we selected three cell lines that endogenously express functional ORs. We demonstrated that human prostate carcinoma (LNCaP) cell lines successfully identified novel ligands for ORs that were not recognized when expressed in HEK293 cells. Further experiments suggested that the LNCaP cell line was effective for functional expression of ORs, especially with a high basal activity, which impeded the sensitive detection of ligand-mediated activity of ORs. This report provides an efficient functional assay system for a specific repertoire of ORs that cannot be characterized in current cell systems.

A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell

The sense of smell helps us navigate the environment, but its molecular architecture and underlying logic remain understudied. The spatial location of odorant receptor genes (Olfrs) in the nose is thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we create a genome-wide 3D atlas of the mouse olfactory mucosa (OM). Topographic maps of genes differentially expressed in space reveal that both Olfrs and non-Olfrs are distributed in a continuous and overlapping fashion over at least five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize, providing direct evidence for the chromatographic theory of olfaction. This resource resolves the molecular architecture of the mouse OM and will inform future studies on mechanisms underlying Olfr gene choice, axonal pathfinding, patterning of the nervous system, and basic logic for the peripheral representation of smell.

Biological constraints on configural odour mixture perception

Animals, including humans, detect odours and use this information to behave efficiently in the environment. Frequently, odours consist of complex mixtures of odorants rather than single odorants, and mixtures are often perceived as configural wholes, i.e. as odour objects (e.g. food, partners). The biological rules governing this 'configural perception' (as opposed to the elemental perception of mixtures through their components) remain weakly understood. Here, we first review examples of configural mixture processing in diverse species involving species-specific biological signals. Then, we present the original hypothesis that at least certain mixtures can be processed configurally across species. Indeed, experiments conducted in human adults, newborn rabbits and, more recently, in rodents and honeybees show that these species process some mixtures in a remarkably similar fashion. Strikingly, a mixture AB (A, ethyl isobutyrate; B, ethyl maltol) induces configural processing in humans, who perceive a mixture odour quality (pineapple) distinct from the component qualities (A, strawberry; B, caramel). The same mixture is weakly configurally processed in rabbit neonates, which perceive a particular odour for the mixture in addition to the component odours. Mice and honeybees also perceive the AB mixture configurally, as they respond differently to the mixture compared with its components. Based on these results and others, including neurophysiological approaches, we propose that certain mixtures are convergently perceived across various species of vertebrates/invertebrates, possibly as a result of a similar anatomical organization of their olfactory systems and the common necessity to simplify the environment's chemical complexity in order to display adaptive behaviours.

Evolution of brain-expressed biogenic amine receptors into olfactory trace amine-associated receptors

The family of trace amine-associated receptors (TAARs) is distantly related to G protein-coupled biogenic aminergic receptors. TAARs are found in the brain as well as in the olfactory epithelium where they detect biogenic amines. However, the functional relationship of receptors from distinct TAAR subfamilies and in different species is still uncertain. Here, we perform a thorough phylogenetic analysis of 702 TAAR-like (TARL) and TAAR sequences from 48 species. We show that a clade of Tarl genes has greatly expanded in lampreys, whereas the other Tarl clade consists of only one or two orthologs in jawed vertebrates and is lost in amniotes. We also identify two small clades of Taar genes in sharks related to the remaining Taar genes in bony vertebrates, which are divided into four major clades. We further identify ligands for 61 orphan TARLs and TAARs from sea lamprey, shark, ray-finned fishes, and mammals, as well as novel ligands for two 5-hydroxytryptamine receptor 4 orthologs, a serotonin receptor subtype closely related to TAARs. Our results reveal a pattern of functional convergence and segregation: TARLs from sea lamprey and bony vertebrate olfactory TAARs underwent independent expansions to function as chemosensory receptors, whereas TARLs from jawed vertebrates retain ancestral response profiles and may have similar functions to TAAR1 in the brain. Overall, our data provide a comprehensive understanding of the evolution and ligand recognition profiles of TAARs and TARLs.

Understanding responses to chemical mixtures: looking forward from the past

Our goal in this article is to provide a perspective on how to understand the nature of responses to chemical mixtures. In studying responses to mixtures, researchers often identify "mixture interactions"-responses to mixtures that are not accurately predicted from the responses to the mixture's individual components. Critical in these studies is how to predict responses to mixtures and thus to identify a mixture interaction. We explore this issue with a focus on olfaction and on the first level of neural processing-olfactory sensory neurons-although we use examples from taste systems as well and we consider responses beyond sensory neurons, including behavior and psychophysics. We provide a broadly comparative perspective that includes examples from vertebrates and invertebrates, from genetic and nongenetic animal models, and from literature old and new. In the end, we attempt to recommend how to approach these problems, including possible future research directions.

Paradoxical relationship between speed and accuracy in olfactory figure-background segregation

In natural settings, many stimuli impinge on our sensory organs simultaneously. Parsing these sensory stimuli into perceptual objects is a fundamental task faced by all sensory systems. Similar to other sensory modalities, increased odor backgrounds decrease the detectability of target odors by the olfactory system. The mechanisms by which background odors interfere with the detection and identification of target odors are unknown. Here we utilized the framework of the Drift Diffusion Model (DDM) to consider possible interference mechanisms in an odor detection task. We first considered pure effects of background odors on either signal or noise in the decision-making dynamics and showed that these produce different predictions about decision accuracy and speed. To test these predictions, we trained mice to detect target odors that are embedded in random background mixtures in a two-alternative choice task. In this task, the inter-trial interval was independent of behavioral reaction times to avoid motivating rapid responses. We found that increased backgrounds reduce mouse performance but paradoxically also decrease reaction times, suggesting that noise in the decision making process is increased by backgrounds. We further assessed the contributions of background effects on both noise and signal by fitting the DDM to the behavioral data. The models showed that background odors affect both the signal and the noise, but that the paradoxical relationship between trial difficulty and reaction time is caused by the added noise.

Sensory systems are constantly stimulated by signals from many objects in the environment. Segmentation of important signals from the cluttered background is therefore a task that is faced by all sensory systems. For many mammalians, the sense of smell is the primary sense that guides many daily behaviors. As such, the olfactory system must be able to detect and identify odors of interest against varying and dynamic backgrounds. Here we studied how background odors interfere with the detection of target odors. We trained mice on a task in which they are presented with odor mixtures and are required to report whether they include either of two target odors. We analyze the behavioral data using a common model of sensory-guided decision-making—the drift-diffusion-model. In this model, decisions are influenced by two elements: a drift which is the signal produced by the stimulus, and noise. We show that the addition of background odors has a dual effect—a reduction in the drift, as well as an increase in the noise. The increased noise also causes more rapid decisions, thereby producing a paradoxical relationship between trial difficulty and decision speed; mice make faster decisions on more difficult trials.

Casting the Net-Connecting Auxin Signaling to the Plant Genome

Auxin represents one of the most potent and most versatile hormonal signals in the plant kingdom. Built on a simple core of only a few dedicated components, the auxin signaling system plays important roles for diverse aspects of plant development, physiology, and defense. Key to the diversity of context-dependent functional outputs generated by cells in response to this small molecule are gene duplication events and sub-functionalization of signaling components on the one hand, and a deep embedding of the auxin signaling system into complex regulatory networks on the other hand. Together, these evolutionary innovations provide the mechanisms to allow each cell to display a highly specific auxin response that suits its individual requirements. In this review, we discuss the regulatory networks connecting auxin with a large number of diverse pathways at all relevant levels of the signaling system ranging from biosynthesis to transcriptional response.

Prolactin-sensitive olfactory sensory neurons regulate male preference in female mice by modulating responses to chemosensory cues

Chemosensory cues detected in the nose need to be integrated with the hormonal status to trigger appropriate behaviors, but the neural circuits linking the olfactory and the endocrine system are insufficiently understood. Here, we characterize olfactory sensory neurons in the murine nose that respond to the pituitary hormone prolactin. Deletion of prolactin receptor in these cells results in impaired detection of social odors and blunts male preference in females. The prolactin-responsive olfactory sensory neurons exhibit a distinctive projection pattern to the brain that is similar across different individuals and express a limited subset of chemosensory receptors. Prolactin modulates the responses within these neurons to discrete chemosensory cues contained in male urine, providing a mechanism by which the hormonal status can be directly linked with distinct olfactory cues to generate appropriate behavioral responses.

OdoriFy: A conglomerate of artificial intelligence-driven prediction engines for olfactory decoding

The molecular mechanisms of olfaction, or the sense of smell, are relatively underexplored compared with other sensory systems, primarily because of its underlying molecular complexity and the limited availability of dedicated predictive computational tools. Odorant receptors (ORs) allow the detection and discrimination of a myriad of odorant molecules and therefore mediate the first step of the olfactory signaling cascade. To date, odorant (or agonist) information for the majority of these receptors is still unknown, limiting our understanding of their functional relevance in odor-induced behavioral responses. In this study, we introduce OdoriFy, a Web server featuring powerful deep neural network-based prediction engines. OdoriFy enables (1) identification of odorant molecules for wildtype or mutant human ORs (Odor Finder); (2) classification of user-provided chemicals as odorants/nonodorants (Odorant Predictor); (3) identification of responsive ORs for a query odorant (OR Finder); and (4) interaction validation using Odorant-OR Pair Analysis. In addition, OdoriFy provides the rationale behind every prediction it makes by leveraging explainable artificial intelligence. This module highlights the basis of the prediction of odorants/nonodorants at atomic resolution and for the ORs at amino acid levels. A key distinguishing feature of OdoriFy is that it is built on a comprehensive repertoire of manually curated information of human ORs with their known agonists and nonagonists, making it a highly interactive and resource-enriched Web server. Moreover, comparative analysis of OdoriFy predictions with an alternative structure-based ligand interaction method revealed comparable results. OdoriFy is available freely as a web service at https://odorify.ahujalab.iiitd.edu.in/olfy/.

What the odor is not: Estimation by elimination

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

A physicochemical model of odor sampling

We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system's discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.

Position Review: Functional Selectivity in Mammalian Olfactory Receptors

There is increasing appreciation that G-protein-coupled receptors (GPCRs) can initiate diverse cellular responses by activating multiple G proteins, arrestins, and other biochemical effectors. Structurally different ligands targeting the same receptor are thought to stabilize the receptor in multiple distinct active conformations such that specific subsets of signaling effectors are engaged at the exclusion of others, creating a bias toward a particular outcome, which has been referred to as ligand-induced selective signaling, biased agonism, ligand-directed signaling, and functional selectivity, among others. The potential involvement of functional selectivity in mammalian olfactory signal transduction has received little attention, notwithstanding the fact that mammalian olfactory receptors comprise the largest family of mammalian GPCRs. This position review considers the possibility that, although such complexity in G-protein function may have been lost in the specialization of olfactory receptors to serve as sensory receptors, the ability of olfactory receptor neurons (ORNs) to function as signal integrators and growing appreciation that this functionality is widespread in the receptor population suggest otherwise. We pose that functional selectivity driving 2 opponent inputs have the potential to generate an output that reflects the balance of ligand-dependent signaling, the direction of which could be either suppressive or synergistic and, as such, needs to be considered as a mechanistic basis for signal integration in mammalian ORNs.

Encoding innately recognized odors via a generalized population code

Odors carrying intrinsic values often trigger instinctive aversive or attractive responses. It is not known how innate valence is encoded. An intuitive model suggests that the information is conveyed through specific channels in hardwired circuits along the olfactory pathway, insulated from influences of other odors, to trigger innate responses. Here, we show that in mice, mixing innately aversive or attractive odors with a neutral odor and, surprisingly, mixing two odors with the same valence, abolish the innate behavioral responses. Recordings from the olfactory bulb indicate that odors are not masked at the level of peripheral activation and glomeruli independently encode components in the mixture. In contrast, crosstalk among the mitral and tufted (M/T) cells changes their patterns of activity such that those elicited by the mixtures can no longer be linearly decoded as separate components. The changes in behavioral and M/T cell responses are associated with reduced activation of brain areas linked to odor preferences. Thus, crosstalk among odor channels at the earliest processing stage in the olfactory pathway leads to re-coding of odor identity to abolish valence associated with the odors. These results are inconsistent with insulated labeled lines and support a model of a common mechanism of odor recognition for both innate and learned valence associations.

A System-Wide Understanding of the Human Olfactory Percept Chemical Space

The fundamental units of olfactory perception are discrete 3D structures of volatile chemicals that each interact with specific subsets of a very large family of hundreds of odorant receptor proteins, in turn activating complex neural circuitry and posing a challenge to understand. We have applied computational approaches to analyze olfactory perceptual space from the perspective of odorant chemical features. We identify physicochemical features associated with ~150 different perceptual descriptors and develop machine-learning models. Validation of predictions shows a high success rate for test set chemicals within a study, as well as across studies more than 30 years apart in time. Due to the high success rates, we are able to map ~150 percepts onto a chemical space of nearly 0.5 million compounds, predicting numerous percept-structure combinations. The chemical structure-to-percept prediction provides a system-level view of human olfaction and opens the door for comprehensive computational discovery of fragrances and flavors.

Imaging the living brain: An argument for ruthless reductionism from olfactory neurobiology

Should theories of "higher-level" cognitive effects originate in "lower-level" molecular mechanisms? This paper supports reductionist explanations of sensory perception via molecular mechanisms in neurobiology. It shows that molecular and cellular mechanisms must constitute the material foundation to derive better theories and models for neuroscience. In support of "bottom-up theorizing", I explore the recent application of a new real-time molecular imaging technique (SCAPE microscopy) to mixture coding in olfaction. Seemingly emergent "higher-level" psychological effects in odor perception, irreducible to the physical stimulus, are linked back to underlying molecular mechanisms at the receptor level. The SCAPE study has notable theoretical impact. It provides a possible answer to the neurocomputational challenge in olfaction from combinatorial coding at the periphery: how does the brain discriminate different complex mixtures from widespread and overlapping receptor activation? The failure of previous reductionist structure-odor explanations is shown to reside in misconceptualizations of the critical causal elements involved. Causally fundamental features are not of parts independently of a mechanism. Components and their relevant features are units via their causal role within a mechanism. Here, new technologies allow revisiting our understanding of the ontology and levels of organization of a system.

Odor coding in the mammalian olfactory epithelium

Noses are extremely sophisticated chemical detectors allowing animals to use scents to interpret and navigate their environments. Odor detection starts with the activation of odorant receptors (ORs), expressed in mature olfactory sensory neurons (OSNs) populating the olfactory mucosa. Different odorants, or different concentrations of the same odorant, activate unique ensembles of ORs. This mechanism of combinatorial receptor coding provided a possible explanation as to why different odorants are perceived as having distinct odors. Aided by new technologies, several recent studies have found that antagonist interactions also play an important role in the formation of the combinatorial receptor code. These findings mark the start of a new era in the study of odorant-receptor interactions and add a new level of complexity to odor coding in mammals.

Olfaction: Receptor Antagonistes

Odor receptors of the mammalian olfactory system have long been known to be activated in combinatorial fashion by odorants. A large-scale study now reveals that inhibition of receptors by odorants is comparably prevalent and combinatorial.

Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice

Odor landscapes contain complex blends of molecules that each activate unique, overlapping populations of olfactory sensory neurons (OSNs). Despite the presence of hundreds of OSN subtypes in many animals, the overlapping nature of odor inputs may lead to saturation of neural responses at the early stages of stimulus encoding. Information loss due to saturation could be mitigated by normalizing mechanisms such as antagonism at the level of receptor-ligand interactions, whose existence and prevalence remains uncertain. By imaging OSN axon terminals in olfactory bulb glomeruli as well as OSN cell bodies within the olfactory epithelium in freely breathing mice, we find widespread antagonistic interactions in binary odor mixtures. In complex mixtures of up to 12 odorants, antagonistic interactions are stronger and more prevalent with increasing mixture complexity. Therefore, antagonism is a common feature of odor mixture encoding in OSNs and helps in normalizing activity to reduce saturation and increase information transfer.

Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants

The perception of aroma mixtures is based on interactions beginning at the peripheral olfactory system, but the process remains poorly understood. The perception of a mixture of ethyl isobutyrate (Et-iB, strawberry-like odor) and ethyl maltol (Et-M, caramel-like odor) was investigated previously in both human and animal studies. In those studies, the binary mixture of Et-iB and Et-M was found to be configurally processed. In humans, the mixture was judged as more typical of a pineapple odor, similar to allyl hexanoate (Al-H, pineapple-like odor), than the odors of the individual components. To explore the key features of this aroma blend, we developed an in silico approach based on molecules having at least one of the odors—strawberry, caramel or pineapple. A dataset of 293 molecules and their related odors was built. We applied the notion of a “social network” to describe the network of the odors. Additionally, we explored the structural properties of the molecules in this dataset. The network of the odors revealed peculiar links between odors, while the structural study emphasized key characteristics of the molecules. The association between “strawberry” and “caramel” notes, as well as the structural diversity of the “strawberry” molecules, were notable. Such elements would be key to identifying potential odors/odorants to form aroma blends.