Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures

The primacy model and the structure of olfactory space

Understanding sensory processing relies on the establishment of a consistent relationship between the stimulus space, its neural representation, and perceptual quality. In olfaction, the difficulty in establishing these links lies partly in the complexity of the underlying odor input space and perceptual responses. Based on the recently proposed primacy model for concentration invariant odor identity representation and a few assumptions, we have developed a theoretical framework for mapping the odor input space to the response properties of olfactory receptors. We analyze a geometrical structure containing odor representations in a multidimensional space of receptor affinities and describe its low-dimensional implementation, the primacy hull. We propose the implications of the primacy hull for the structure of feedforward connectivity in early olfactory networks. We test the predictions of our theory by comparing the existing receptor-ligand affinity and connectivity data obtained in the fruit fly olfactory system. We find that the Kenyon cells of the insect mushroom body integrate inputs from the high-affinity (primacy) sets of olfactory receptors in agreement with the primacy theory.

Object-oriented olfaction: challenges for chemosensation and for chemosensory research

Many animal species use olfaction to extract information about objects in their environment. Yet, the specific molecular signature that any given object emits varies due to various factors. Here, we detail why such variability makes chemosensory-mediated object recognition such a hard problem, and we propose that a major function of the elaborate chemosensory network is to overcome it. We describe previous work addressing different elements of the problem and outline future research directions that we consider essential for a full understanding of object-oriented olfaction. In particular, we call for extensive representation of olfactory object variability in chemical, behavioral, and electrophysiological analyses. While written with an emphasis on macrosmatic mammalian species, our arguments apply to all organisms that employ chemosensation to navigate complex environments.

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

Preliminary Investigation of Fruit Mash Inoculation with Pure Yeast Cultures: A Case of Volatile Profile of Industrial-Scale Plum Distillates

This study investigates the effect of pure yeast culture fermentation versus spontaneous fermentation on the volatile compound profile of industrially produced plum brandy. Using traditional distillation methods, the evolution of key volatile compounds is monitored at seven different moments during the distillation process. By integrating advanced analytical techniques such as GC-MS and sensory evaluation, significant differences in the composition of the distillates are highlighted, particularly in terms of ethyl esters and higher alcohols which are key to the sensory properties of the final product. Distillates produced with the addition of pure cultures gave higher concentrations of esters than those obtained by wild fermentation. The results of our industrial research show that the most critical step is to limit the storage of the input raw material, thereby reducing the subsequent risk of producing higher concentrations of 1-propanol. Furthermore, our results indicate that the heart of the distillate can only be removed up to an ethanol content of approximately 450 g/L and that the removal of additional ethanol results in only a 10% increase in the total volume of the distillate, which in turn results in an increase in boiler heating costs of approximately 30%.

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.

Human Olfactory Receptor Sensor for Odor Reconstitution

Among the five human senses, light, sound, and force perceived by the eye, ear, and skin, respectively are physical phenomena, and therefore can be easily measured and expressed as objective, univocal, and simple digital data with physical quantity. However, as taste and odor molecules perceived by the tongue and nose are chemical phenomena, it has been difficult to express them as objective and univocal digital data, since no reference chemicals can be defined. Therefore, while the recording, saving, transmitting to remote locations, and replaying of human visual, auditory, and tactile information as digital data in digital devices have been realized (this series of data flow is defined as DX (digital transformation) in this review), the DX of human taste and odor information is not yet in the realization stage. Particularly, since there are at least 400,000 types of odor molecules and an infinite number of complex odors that are mixtures of these molecules, it has been considered extremely difficult to realize "human olfactory DX" by converting all odors perceived by human olfaction into digital data. In this review, we discuss the current status and future prospects of the development of "human olfactory DX", which we believe can be realized by utilizing odor sensors that employ the olfactory receptors (ORs) that support human olfaction as sensing molecules (i.e., human OR sensor).

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.

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.

Recent trends in aroma release and perception during food oral processing: A review

The dynamic and complex peculiarities of the oral environment present several challenges for controlling the aroma release during food consumption. They also pose higher requirements for designing food with better sensory quality. This requires a comprehensive understanding of the basic rules of aroma transmission and aroma perception during food oral processing and its behind mechanism. This review summarized the latest developments in aroma release from food to retronasal cavity, aroma release and delivery influencing factors, aroma perception mechanisms. The individual variance is the most important factor affecting aroma release and perception. Therefore, the intelligent chewing simulator is the key to establish a standard analytical method. The key odorants perceived from the retronasal cavity should be given more attention during food oral processing. Identification of the olfactory receptor activated by specific odorants and its binding mechanisms are still the bottleneck. Electrophysiology and image technology are the new noninvasive technologies in elucidating the brain signals among multisensory, which can fill the gap between aroma perception and other senses. Moreover, it is necessary to develop a new approach to integrate the relationship among aroma binding parameters, aroma concentration, aroma attributes and cross-modal reactions to make the aroma prediction model more accurate.

Structural spine plasticity: Learning and forgetting of odor-specific subnetworks in the olfactory bulb

Learning to discriminate between different sensory stimuli is essential for survival. In rodents, the olfactory bulb, which contributes to odor discrimination via pattern separation, exhibits extensive structural synaptic plasticity involving the formation and removal of synaptic spines, even in adult animals. The network connectivity resulting from this plasticity is still poorly understood. To gain insight into this connectivity we present here a computational model for the structural plasticity of the reciprocal synapses between the dominant population of excitatory principal neurons and inhibitory interneurons. It incorporates the observed modulation of spine stability by odor exposure. The model captures the striking experimental observation that the exposure to odors does not always enhance their discriminability: while training with similar odors enhanced their discriminability, training with dissimilar odors actually reduced the discriminability of the training stimuli. Strikingly, this differential learning does not require the activity-dependence of the spine stability and occurs also in a model with purely random spine dynamics in which the spine density is changed homogeneously, e.g., due to a global signal. However, the experimentally observed odor-specific reduction in the response of principal cells as a result of extended odor exposure and the concurrent disinhibition of a subset of principal cells arise only in the activity-dependent model. Moreover, this model predicts the experimentally testable recovery of odor response through weak but not through strong odor re-exposure and the forgetting of odors via exposure to interfering odors. Combined with the experimental observations, the computational model provides strong support for the prediction that odor exposure leads to the formation of odor-specific subnetworks in the olfactory bulb.

A key feature of the brain is its ability to learn through the plasticity of its network. The olfactory bulb in the olfactory system is a remarkable brain area whose anatomical structure evolves substantially still in adult animals by establishing new synaptic connections and removing existing ones. We present a computational model for this process and employ it to interpret recent experimental results. By comparing the results of our model with those of a random control model we identify various experimental observations that lend strong support to the notion that the network of the olfactory bulb comprises learned, odor-specific subnetworks. Moreover, our model explains the recent observation that the learning of odors does not always improve their discriminability and provides testable predictions for the recovery of odor response after repeated odor exposure and for when the learning of new odors interferes with retaining the memory of familiar odors.

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.

Disorder and the Neural Representation of Complex Odors

Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circuits leverages disorder, diffuse sensing and redundancy in representation to meet these immense complementary challenges. First, the diffuse and disordered binding of receptors to many molecules compresses a vast but sparsely-structured odor space into a small receptor space, yielding an odor code that preserves similarity in a precise sense. Introducing any order/structure in the sensing degrades similarity preservation. Next, lateral interactions further reduce the correlation present in the low-dimensional receptor code. Finally, expansive disordered projections from the periphery to the central brain reconfigure the densely packed information into a high-dimensional representation, which contains multiple redundant subsets from which downstream neurons can learn flexible associations and valences. Moreover, introducing any order in the expansive projections degrades the ability to recall the learned associations in the presence of noise. We test our theory empirically using data from Drosophila. Our theory suggests that the neural processing of sparse but high-dimensional olfactory information differs from the other senses in its fundamental use of disorder.

Hyperbolic odorant mixtures as a basis for more efficient signaling between flowering plants and bees

Animals use odors in many natural contexts, for example, for finding mates or food, or signaling danger. Most analyses of natural odors search for either the most meaningful components of a natural odor mixture, or they use linear metrics to analyze the mixture compositions. However, we have recently shown that the physical space for complex mixtures is ‘hyperbolic’, meaning that there are certain combinations of variables that have a disproportionately large impact on perception and that these variables have specific interpretations in terms of metabolic processes taking place inside the flower and fruit that produce the odors. Here we show that the statistics of odorants and odorant mixtures produced by inflorescences (Brassica rapa) are also better described with a hyperbolic rather than a linear metric, and that combinations of odorants in the hyperbolic space are better predictors of the nectar and pollen resources sought by bee pollinators than the standard Euclidian combinations. We also show that honey bee and bumble bee antennae can detect most components of the B. rapa odor space that we tested, and the strength of responses correlates with positions of odorants in the hyperbolic space. In sum, a hyperbolic representation can be used to guide investigation of how information is represented at different levels of processing in the CNS.

Interactions among key residues regulate mammalian odorant receptor trafficking

Odorant receptors (ORs) expressed in mammalian olfactory sensory neurons are essential for the sense of smell. However, structure-function studies of many ORs are hampered by unsuccessful heterologous expression. To understand and eventually overcome this bottleneck, we performed heterologous expression and functional assays of over 80 OR variants and chimeras. Combined with literature data and machine learning, we found that the transmembrane domain 4 (TM4) and its interactions with neighbor residues are important for OR functional expression. The data highlight critical roles of T^4.62 therein. ORs that fail to reach the cell membrane can be rescued by modifications in TM4. Consequently, such modifications in MOR256-3 (Olfr124) also alter OR responses to odorants. T161^4.62 P causes the retention of MOR256-3 in the endoplasmic reticulum (ER), while T161^4.62 P/T148^4.49 A reverses the retention and makes receptor trafficking to cell membrane. This study offers new clues toward wide-range functional studies of mammalian ORs.

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.

State-dependent representations of mixtures by the olfactory bulb

Sensory systems are often tasked to analyse complex signals from the environment, separating relevant from irrelevant parts. This process of decomposing signals is challenging when a mixture of signals does not equal the sum of its parts, leading to an unpredictable corruption of signal patterns. In olfaction, nonlinear summation is prevalent at various stages of sensory processing. Here, we investigate how the olfactory system deals with binary mixtures of odours under different brain states by two-photon imaging of olfactory bulb (OB) output neurons. Unlike previous studies using anaesthetised animals, we found that mixture summation is more linear in the early phase of evoked responses in awake, head-fixed mice performing an odour detection task, due to dampened responses. Despite smaller and more variable responses, decoding analyses indicated that the data from behaving mice was well discriminable. Curiously, the time course of decoding accuracy did not correlate strictly with the linearity of summation. Further, a comparison with naïve mice indicated that learning to accurately perform the mixture detection task is not accompanied by more linear mixture summation. Finally, using a simulation, we demonstrate that, while saturating sublinearity tends to degrade the discriminability, the extent of the impairment may depend on other factors, including pattern decorrelation. Altogether, our results demonstrate that the mixture representation in the primary olfactory area is state-dependent, but the analytical perception may not strictly correlate with linearity in summation.

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.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic ("ephaptic") interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. The best performance is achieved when both mechanisms work in synergy. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Cortical feedback and gating in odor discrimination and generalization

A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.

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.

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.

Widespread Inhibition, Antagonism, and Synergy in Mouse Olfactory Sensory Neurons In Vivo

Sensory information is selectively or non-selectively enhanced and inhibited in the brain, but it remains unclear whether and how this occurs at the most peripheral level. Using in vivo calcium imaging of mouse olfactory bulb and olfactory epithelium in wild-type and mutant animals, we show that odors produce not only excitatory but also inhibitory responses in olfactory sensory neurons (OSNs). Heterologous assays indicate that odorants can act as agonists to some but inverse agonists to other odorant receptors. We also demonstrate that responses to odor mixtures are extensively suppressed or enhanced in OSNs. When high concentrations of odors are mixed, widespread antagonism suppresses the overall response amplitudes and density. In contrast, a mixture of low concentrations of odors often produces synergistic effects and boosts the faint odor inputs. Thus, odor responses are extensively tuned by inhibition, antagonism, and synergy at the most peripheral level, contributing to robust sensory representations.

Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models

There are key unanswered questions when it comes to multicomponent odor discrimination. This study was designed to assess discrimination of odorant mixtures that elicit a singular percept. We collected data to address the following two questions: (1) What odor features do humans notice when attempting to discriminate between subtly different odor mixtures? (2) Are odor mixtures easier to discriminate when an odorant is added, compared with when a component is removed? Using modern aroma chemistry techniques, an odor mixture resembling a generic white wine was constructed. This wine odor mixture was modified using a series of three esters which are commonly found in white wines that vary in chain length and branching. Participants performed a sequence of discrimination tasks for the addition/subtraction of modifiers to the base wine at different concentrations. Only one of the esters (ethyl propanoate) led to a discriminable odor mixture. As concentration of the modifying odorant was increased, discrimination of odor mixtures was first reported because of changes in odor mixture familiarity and then intensity. We found similar sensitivity to changes in odor mixtures regardless whether the modifying compound was added or subtracted, suggesting that perceptual stability of odor mixtures is equally dependent on both imputing missing information (pattern completion) and disregarding extraneous information.

A biohybrid nose for evaluation of odor masking in the peripheral olfactory system

Olfaction is a synthetic sense in which odor mixtures elicit emergent perceptions at the expense of perceiving the individual components. The most common result of mixing two odors is masking one component by another. However, there is lack of analytical techniques for measuring the sense of smell, which is mediated by cross-odorant interactions. Here, we propose a biohybrid nose for objective and quantitative evaluation of malodor masking efficiency of perfumed products. This biohybrid nose is constructed by integrating mammalian olfactory epithelium with microelectrode array chip to read out the olfactory information as electrical signal from multiple tissue sites. The intrinsic odor response of olfactory epithelium is found to be represented by widespread spatiotemporal oscillatory activity. The masking efficiency of fragrance is quantified by calculating the relative difference between the malodor and the binary mixture (malodor + fragrance) response patterns. Results indicate that masking efficiency of fragrance is concentration-dependent, whereas completely masking may occurs when fragrance is employed at a concentration 2-3 orders of magnitude higher than malodor. This study demonstrates for the first time that capitalizing on the biological sense of smell to create biohybrid system provides an effective technique to resolve more complex biosensing-related issues such as odor interactions in mixtures.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.. [DOI: 10.1101/2020.07.23.217216]

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla.

We found that NSIs improve mixture ratio detection and plume structure sensing and they do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Author summary

Myelin is important to isolate neurons and avoid disruptive electrical interference between them; it can be found in almost any neural assembly. However, there are a few exceptions to this rule and it remains unclear why. One particularly interesting case is the electrical interaction between olfactory sensory neurons co-housed in the sensilla of insects. Here, we created a computational model of the early stages of the Drosophila olfactory system and observed that the electrical interference between olfactory receptor neurons can be a useful trait that can help flies, and other insects, to navigate the complex plumes of odorants in their natural environment.

With the model we were able to shed new light on the trade-off of adopting this mechanism: We found that the non-synaptic interactions (NSIs) improve both the identification of the concentration ratio in mixtures of odorants and the discrimination of odorant mixtures emanating from a single source from odorants emitted from separate sources – both highly advantageous. However, they also decrease the dynamic range of the olfactory sensory neurons – a clear disadvantage.

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.

Odorant Receptor Inhibition Is Fundamental to Odor Encoding

Most natural odors are complex mixtures of volatile components, competing to bind odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) of the nose. To date, surprisingly little is known about how OR antagonism shapes neuronal representations in the detection layer of the olfactory system. Here, we investigated its prevalence, the degree to which it disrupts OR ensemble activity, and its conservation across phylogenetically related ORs. Calcium imaging microscopy of dissociated OSNs revealed significant inhibition, often complete attenuation, of responses to indole-a commonly occurring volatile associated with both floral and fecal odors-by a set of 36 tested odorants. To confirm an OR mechanism for the observed inhibition, we performed single-cell transcriptomics on OSNs exhibiting specific response profiles to a diagnostic panel of odorants and identified three paralogous receptors-Olfr740, Olfr741, and Olfr743-which, when tested in vitro, recapitulated OSN responses. We screened ten ORs from the Olfr740 gene family with ∼800 perfumery-related odorants spanning a range of chemical scaffolds and functional groups. Over half of these compounds (430) antagonized at least one of the ten ORs. OR activity fitted a mathematical model of competitive receptor binding and suggests normalization of OSN ensemble responses to odorant mixtures is the rule rather than the exception. In summary, we observed OR antagonism occurred frequently and in a combinatorial manner. Thus, extensive receptor-mediated computation of mixture information appears to occur in the olfactory epithelium prior to transmission of odor information to the olfactory bulb.

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.

Habituation as a neural algorithm for online odor discrimination

Habituation is a form of simple memory that suppresses neural activity in response to repeated, neutral stimuli. This process is critical in helping organisms guide attention toward the most salient and novel features in the environment. Here, we follow known circuit mechanisms in the fruit fly olfactory system to derive a simple algorithm for habituation. We show, both empirically and analytically, that this algorithm is able to filter out redundant information, enhance discrimination between odors that share a similar background, and improve detection of novel components in odor mixtures. Overall, we propose an algorithmic perspective on the biological mechanism of habituation and use this perspective to understand how sensory physiology can affect odor perception. Our framework may also help toward understanding the effects of habituation in other more sophisticated neural systems.

Widespread receptor-driven modulation in peripheral olfactory coding

Olfactory responses to single odors have been well characterized but in reality we are continually presented with complex mixtures of odors. We performed high-throughput analysis of single-cell responses to odor blends using Swept Confocally Aligned Planar Excitation (SCAPE) microscopy of intact mouse olfactory epithelium, imaging ~10,000 olfactory sensory neurons in parallel. In large numbers of responding cells, mixtures of odors did not elicit a simple sum of the responses to individual components of the blend. Instead, many neurons exhibited either antagonism or enhancement of their response in the presence of another odor. All eight odors tested acted as both agonists and antagonists at different receptors. We propose that this peripheral modulation of responses increases the capacity of the olfactory system to distinguish complex odor mixtures.

Cortical processing of configurally perceived odor mixtures

Most odors are not composed of a single volatile chemical species, but rather are mixtures of many different volatile molecules, the perception of which is dependent on the identity and relative concentrations of the components. Changing either the identity or ratio of components can lead to shifts between configural and elemental perception of the mixture. For example, a 30/70 ratio of ethyl isobutyrate (odorant A, a strawberry scent) and ethyl maltol (odorant B, a caramel scent) is perceived as pineapple by humans - a configural percept distinct from the components. In contrast, a 68/32 ratio of the same odorants is perceived elementally, and is identified as the component odors. Here, we examined single-unit responses in the anterior and posterior piriform cortex (aPCX and pPCX) of mice to these A and B mixtures. We first demonstrate that mouse behavior is consistent with a configural/elemental perceptual shift as concentration ratio varies. We then compared responses to the configural mixture to those evoked by the elemental mixture, as well as to the individual components. Hierarchical cluster analyses suggest that in the mouse aPCX, the configural mixture was coded as distinct from both components, while the elemental mixture was coded as similar to the components. In contrast, mixture perception did not predict pPCX ensemble coding. Similar electrophysiological results were also observed in rats. The results suggest similar perceptual characteristics of the AB mixture across species, and a division in the roles of aPCX and pPCX in the coding of configural and elemental odor mixtures.

Computational prediction methods to simulate structure and binding sites of coumarin with olfactory receptor 5P3

Olfactory receptor 5P3 is coded by OR5P3 gene in human OR5P3 and recognized as the receptor for coumarin present in 30% of fragrances and might adversely affect human health. OR5P3 are also associated with coumarin-related breast cancer development and acquired tamoxifen resistance in breast cancer cells. Previously various investigators noted that coumarin acts as a ligand for OR5P3 and binding of this molecule to OR5P3 leads to downstream changes in the olfactory bulb and central nervous system. However, the interaction between OR5P3 and its ligands at molecular level is not well understood. The aim of this study was to develop a computerized approach to simulate the binding process of coumarin to OR5P3 and determine the binding sites at a molecular level. It is conceivable that understanding this binding mechanism to a specific OR may aid in identification of receptors responsible olfaction and non-olfaction disorders such as breast cancer. The approach employed in this study may thus be utilized in future studies to simulate bind of specific chemicals to ORs and potentially have therapeutic applications.

Semiochemical and Communication Ecology of the Emerald Ash Borer, Agrilus planipennis (Coleoptera: Buprestidae)

Knowledge of buprestid chemical ecology is sparse but the appearance of the invasive pest Agrilus planipennis Fairmaire in North America has provided the impetus to study in detail the semiochemistry and ecology of this important buprestid. The macrocyclic lactone (3Z)-12-dodecenolide [(3Z)-lactone] is identified as a key antennally-active compound that is produced by females and attracts males. Though a weak trap attractant alone, when combined with the host kairomone (3Z)-hexenol and the important visual cue of a green canopy trap, significant increases in male trap capture occur, thus defining (3Z)-lactone as both a sex pheromone of A. planipennis as well as the first and only known buprestid pheromone. The non-natural stereoisomer (3E)-12-dodecenolide and the saturated analog, 12-dodecanolide also exhibit mimetic activities towards male A. planipennis, suggesting a notable plasticity in this pheromonal structural motif. Efficient synthetic routes to these compounds have been developed. A series of fluoro-12-dodecanolides has also been synthesized containing CF2 groups as a strategy to bias the conformational space accessed by these macrolides and to assess if the analogs may act as mimetics for 12-dodecanolide pheromones associated in A. planipennis. These compounds also afford a unique opportunity to study the binding affinities of lactone surrogates with A. planipennis chemosensory proteins and olfactory receptors. Some progress has also been made in identifying the genes involved in the reception, processing and degradation of volatiles in this invasive insect. It is now evident that the behavior and ecology of A. planipennis involves a complex pattern of sensory modalities, including visual, tactile, olfactory and potentially acoustic components. Earlier reviews focused on studies of attractive host volatiles in development of a trapping system for early detection and visual and contact phenomena in A. planipennis mate finding. This review will update the semiochemistry and chemical ecology of A. planipennis and discuss studies on chemistry and behavior that have identified female-produced pheromone components and host kairomones.

Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): Only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to 12 monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.