Odor Space Research Articles

A deep position-encoding model for predicting olfactory perception from molecular structures and electrostatics

Predicting olfactory perceptions from odorant molecules is challenging due to the complex and potentially discontinuous nature of the perceptual space for smells. In this study, we introduce a deep learning model, Mol-PECO (Molecular Representation by Positional Encoding of Coulomb Matrix), designed to predict olfactory perceptions based on molecular structures and electrostatics. Mol-PECO learns the efficient embedding of molecules by utilizing the Coulomb matrix, which encodes atomic coordinates and charges, as an alternative of the adjacency matrix and its Laplacian eigenfunctions as positional encoding of atoms. With a comprehensive dataset of odor molecules and descriptors, Mol-PECO outperforms traditional machine learning methods using molecular fingerprints and graph neural networks based on adjacency matrices. The learned embeddings by Mol-PECO effectively capture the odor space, enabling global clustering of descriptors and local retrieval of similar odorants. This work contributes to a deeper understanding of the olfactory sense and its mechanisms.

Unveiling the odor representation in the inner brain of Drosophila through compressed sensing

The olfaction begins when odorant molecules stimulate a finite number of receptor types in the olfactory neurons. According to the recent connectomics data of the olfactory system, the olfactory neural circuit is multilayered and there is an overall dimensionality reduction from the input to output layer. Compressed sensing (CS) is an algorithm that enables the recovery of high-dimensional signals from the data compressed in a lower dimension when the representation of such signals is sufficiently sparse. By analyzing the recent connectomics data, we find that the organization of the olfactory system effectively satisfies the necessary conditions for CS to work. The neural activity profile of projection neurons (PNs) can be faithfully recovered from a low-dimensional response profile of mushroom body output neurons (MBONs), which can be reconstructed using the electrophysiological recordings of a wide range of odorants. By leveraging the residuals calculated between the measured and the predicted MBON responses, we visualize the perceptual odor space using the residual spectrum and discuss the differentiability of an odor from others. Our study highlights the sparse coding of odor to the receptor space as an essential component for odor identifiability, clarifying the principles underlying the concentration-dependent odor percept. Further, simultaneous exposure of the olfactory system to many different odorants saturates the neural activity profile of PNs, significantly degrading the capacity of signal recovery and resulting in a perceptual state analogous to “olfactory white.” Our study applying CS to the real connectomics data encompassing the neural circuitry from PNs to MBONs via Kenyon cells provides quantitative insights into the neural signal processing and odor representation in the inner brain of . Published by the American Physical Society 2024

Regression Study of Odorant Chemical Space, Molecular Structural Diversity, and Natural Language Description.

Odor is analyzed on the human olfactometry systems in various steps. The mapping from chemical structures to olfactory perceptions of smell is an extremely challenging task. Scientists have been unable to find a measure to distinguish the perceptual similarity between odorants. In this study, we report regression analysis and visualization based on the odorant chemical space. We discuss the relation between the odor descriptors and their structural diversity for odorants groups associated with each odor descriptor. We studied the influence of structural diversity on the odor descriptor predictability. The results suggest that the diversity of molecular structures, which is associated with the same odor descriptor, is related to the resolutional confusion with the odor descriptor.

Calcium imaging of adult olfactory epithelium reveals amines as important odor class in fish.

The odor space of aquatic organisms is by necessity quite different from that of air-breathing animals. The recognized odor classes in teleost fish include amino acids, bile acids, reproductive hormones, nucleotides, and a limited number of polyamines. Conversely, a significant portion of the fish olfactory receptor repertoire is composed of trace amine-associated receptors, generally assumed to be responsible for detecting amines. Zebrafish possess over one hundred of these receptors, but the responses of olfactory sensory neurons to amines have not been known so far. Here we examined odor responses of zebrafish olfactory epithelial explants at the cellular level, employing calcium imaging. We report that amines elicit strong responses in olfactory sensory neurons, with a time course characteristically different from that of ATP-responsive (basal) cells. A quantitative analysis of the laminar height distribution shows amine-responsive cells undistinguishable from ciliated neurons positive for olfactory marker protein. This distribution is significantly different from those measured for microvillous neurons positive for transient receptor potential channel 2 and basal cells positive for proliferating cell nuclear antigen. Our results suggest amines as an important odor class for teleost fish.

Odor Reproduction Technology Using a Small Set of Odor Components

Replicating specific scents by mixing ‘base odors’ is the main idea behind the concept of odor reproduction. Just as primary colors can be combined to generate a wide range of colors in visual perception, the hope is to find a similar principle in olfaction. However, defining such ‘primary odors’ is difficult due to the complexity of our sense of smell, which is much different from vision. In spite of these challenges, numerous scientists have endeavored to identify a combination of basic smell components that can mimic various scents. Currently, the suggested combinations of smell components are typically only successful at recreating specific, intended scents. The range of reproducible scents differs based on the selection of base odors, yet these studies have provided valuable knowledge about the nature of these primary odors. This review paper will focus on the latest studies related to odor reproduction. Understanding odor space, odor reproduction, and the challenges encountered when expanding the range of odors will be explained. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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.

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.

Olfactory Perception in Relation to the Physicochemical Odor Space.

A growing body of research aims at solving what is often referred to as the stimulus-percept problem in olfactory perception. Although computational efforts have made it possible to predict perceptual impressions from the physicochemical space of odors, studies with large psychophysical datasets from non-experts remain scarce. Following previous approaches, we developed a physicochemical odor space using 4094 molecular descriptors of 1389 odor molecules. For 20 of these odors, we examined associations with perceived pleasantness, intensity, odor quality and detection threshold, obtained from a dataset of 2000 naïve participants. Our results show significant differences in perceptual ratings, and we were able to replicate previous findings on the association between perceptual ratings and the first dimensions of the physicochemical odor space. However, the present analyses also revealed striking interindividual variations in perceived pleasantness and intensity. Additionally, interactions between pleasantness, intensity, and olfactory and trigeminal qualitative dimensions were found. To conclude, our results support previous findings on the relation between structure and perception on the group level in our sample of non-expert raters. In the challenging task to relate olfactory stimulus and percept, the physicochemical odor space can serve as a reliable and helpful tool to structure the high-dimensional space of olfactory stimuli. Nevertheless, human olfactory perception in the individual is not an analytic process of molecule detection alone, but is part of a holistic integration of multisensory inputs, context and experience.

Categorizing Smells: A Localist Approach.

Humans are poorer at identifying smells and communicating about them, compared to other sensory domains. They also cannot easily organize odor sensations in a general conceptual space, where geometric distance could represent how similar or different all odors are. These two generalities are more or less accepted by psychologists, and they are often seen as connected: If there is no conceptual space for odors, then olfactory identification should indeed be poor. We propose here an important revision to this conclusion: We believe that the claim that there is no odor space is true only if by odor space, one means a conceptual space representing all possible odor sensations, in the paradigmatic sense used for instance for color. However, in a less paradigmatic sense, local conceptual spaces representing a given subset of odors do exist. Thus the absence of a global odor space does not warrant the conclusion that there is no olfactory conceptual map at all. Here we show how a localist account provides a new interpretation of experts and cross-cultural categorization studies: Rather than being exceptions to the poor olfactory identification and communication usually seen elsewhere, experts and cross-cultural categorization are here taken to corroborate the existence of local conceptual spaces.

Structure and flexibility in cortical representations of odour space.

The cortex organizes sensory information to enable discrimination and generalization1–4. Systematic representations of chemical odor space have not been described in olfactory cortex, and so it remains unclear how odor relationships are encoded to place chemically distinct but similar odors, like lemon and orange, into perceptual categories, like citrus5–7. Here we demonstrate that both the piriform cortex (PCx) and its sensory inputs from the olfactory bulb represent chemical odor relationships through correlated patterns of activity. However, cortical odor codes differ from those in the bulb: cortex more strongly clusters together representations for related odors, selectively rewrites pairwise odor relationships, and better matches odor perception. The bulb-to-cortex transformation depends upon the associative network originating within PCx, and can be reshaped by passive odor experience. Thus, cortex actively builds a structured representation of chemical odor space that highlights odor relationships; this representation is similar across individuals but remains plastic, suggesting a means through which the olfactory system can assign related odor cues to common and yet personalized percepts.

Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor

Odorant receptors expressed at the peripheral olfactory organs are key proteins for animal volatile sensing. Although they determine the odor space of a given species, their functional characterization is a long process and remains limited. To date, machine learning virtual screening has been used to predict new ligands for such receptors in both mammals and insects, using chemical features of known ligands. In insects, such approach is yet limited to Diptera, whereas insect odorant receptors are known to be highly divergent between orders. Here, we extend this strategy to a Lepidoptera receptor, SlitOR25, involved in the recognition of attractive odorants in the crop pest Spodoptera littoralis larvae. Virtual screening of 3 million molecules predicted 32 purchasable ones whose function has been systematically tested on SlitOR25, revealing 11 novel agonists with a success rate of 28%. Our results show that Support Vector Machine optimizes the discovery of novel agonists and expands the chemical space of a Lepidoptera OR. More, it opens up structure-function relationship analyses through a comparison of the agonist chemical structures. This proof-of-concept in a crop pest could ultimately enable the identification of OR agonists or antagonists, capable of modifying olfactory behaviors in a context of biocontrol.

Odor Stimuli: Not Just Chemical Identity.

In most sensory modalities the underlying physical phenomena are well understood, and stimulus properties can be precisely controlled. In olfaction, the situation is different. The presence of specific chemical compounds in the air (or water) is the root cause for perceived odors, but it remains unknown what organizing principles, equivalent to wavelength for light, determine the dimensions of odor space. Equally important, but less in the spotlight, odor stimuli are also complex with respect to their physical properties, including concentration and time-varying spatio-temporal distribution. We still lack a complete understanding or control over these properties, in either experiments or theory. In this review, we will concentrate on two important aspects of the physical properties of odor stimuli beyond the chemical identity of the odorants: (1) The amplitude of odor stimuli and their temporal dynamics. (2) The spatio-temporal structure of odor plumes in a natural environment. Concerning these issues, we ask the following questions: (1) Given any particular experimental protocol for odor stimulation, do we have a realistic estimate of the odorant concentration in the air, and at the olfactory receptor neurons? Can we control, or at least know, the dynamics of odorant concentration at olfactory receptor neurons? (2) What do we know of the spatio-temporal structure of odor stimuli in a natural environment both from a theoretical and experimental perspective? And how does this change if we consider mixtures of odorants? For both topics, we will briefly summarize the underlying principles of physics and review the experimental and theoretical Neuroscience literature, focusing on the aspects that are relevant to animals’ physiology and behavior. We hope that by bringing the physical principles behind odor plume landscapes to the fore we can contribute to promoting a new generation of experiments and models.

Copper-mediated thiol potentiation and mutagenesis-guided modeling suggest a highly conserved copper-binding motif in human OR2M3

Sulfur-containing compounds within a physiological relevant, natural odor space, such as the key food odorants, typically constitute the group of volatiles with the lowest odor thresholds. The observation that certain metals, such as copper, potentiate the smell of sulfur-containing, metal-coordinating odorants led to the hypothesis that their cognate receptors are metalloproteins. However, experimental evidence is sparse—so far, only one human odorant receptor, OR2T11, and a few mouse receptors, have been reported to be activated by sulfur-containing odorants in a copper-dependent way, while the activation of other receptors by sulfur-containing odorants did not depend on the presence of metals. Here we identified an evolutionary conserved putative copper interaction motif CC/CSSH, comprising two copper-binding sites in TMH5 and TMH6, together with the binding pocket for 3-mercapto-2-methylpentan-1-ol in the narrowly tuned human receptor OR2M3. To characterize the copper-binding motif, we combined homology modeling, docking studies, site-directed mutagenesis, and functional expression of recombinant ORs in a cell-based, real-time luminescence assay. Ligand activation of OR2M3 was potentiated in the presence of copper. This effect of copper was mimicked by ionic and colloidal silver. In two broadly tuned receptors, OR1A1 and OR2W1, which did not reveal a putative copper interaction motif, activation by their most potent, sulfur-containing key food odorants did not depend on the presence of copper. Our results suggest a highly conserved putative copper-binding motif to be necessary for a copper-modulated and thiol-specific function of members from three subfamilies of family 2 ORs.

Mosaic representations of odors in the input and output layers of the mouse olfactory bulb.

The elementary stimulus features encoded by the olfactory system remain poorly understood. We examined the relationship between 1,666 physical-chemical descriptors of odors and the activity of olfactory bulb inputs and outputs in awake mice. Glomerular and mitral and tufted cell responses were sparse and locally heterogeneous, with only a weak dependence of their positions on physical-chemical properties. Odor features represented by ensembles of mitral and tufted cells were overlapping but distinct from those represented in glomeruli, which is consistent with an extensive interplay between feedforward and feedback inputs to the bulb. This reformatting was well described as a rotation in odor space. The physical-chemical descriptors accounted for a small fraction in response variance, and the similarity of odors in the physical-chemical space was a poor predictor of similarity in neuronal representations. Our results suggest that commonly used physical-chemical properties are not systematically represented in bulbar activity and encourage further searches for better descriptors of odor space.

Grid-like Neural Representations Support Olfactory Navigation of a Two-Dimensional Odor Space

Searching for food, friends, and mates often begins with an airborne scent. Importantly, odor concentration rises with physical proximity to an odorous source, suggesting a framework for orienting within olfactory landscapes to optimize behavior. Here, we created a two-dimensional odor space composed purely of odor stimuli to model how a navigator encounters smells in a natural environment. We show that human subjects can learn to navigate in olfactory space and form predictions of to-be-encountered smells. During navigation, fMRI responses in entorhinal cortex and ventromedial prefrontal cortex take the form of grid-like representations with hexagonal periodicity and entorhinal grid strength scaled with behavioral performance across subjects. The identification of olfactory grid-like codes with 6-fold symmetry highlights a unique neural mechanism by which odor information can be assembled into spatially navigable cognitive maps, optimizing orientation, and path finding toward an odor source.

Numerical Models and In Vitro Assays to Study Odorant Receptors.

Unraveling the sense of smell relies on understanding how odorant receptors recognize odorant molecules. Given the vastness of the odorant chemical space and the complexity of the odorant receptor space, computational methods are in line to propose rules connecting them. We hereby propose an in silico and an in vitro approach, which, when combined are extremely useful for assessing chemogenomic links. In this chapter we mostly focus on the mining of already existing data through machine learning methods. This approach allows establishing predictions that map the chemical space and the receptor space. Then, we describe the method for assessing the activation of odorant receptors and their mutants through luciferase reporter gene functional assays.

Mammalian odorant receptor tuning breadth persists across distinct odorant panels.

The molecular receptive range (MRR) of a mammalian odorant receptor (OR) is the set of odorant structures that activate the OR, while the distribution of these odorant structures across odor space is the tuning breadth of the OR. Variation in tuning breadth is thought to be an important property of ORs, with the MRRs of these receptors varying from narrowly to broadly tuned. However, defining the tuning breadth of an OR is a technical challenge. For practical reasons, a screening panel that broadly covers odor space must be limited to sparse coverage of the many potential structures in that space. When screened with such a panel, ORs with different odorant specificities, but equal tuning breadths, might appear to have different tuning breadths due to chance. We hypothesized that ORs would maintain their tuning breadths across distinct odorant panels. We constructed a new screening panel that was broadly distributed across an estimated odor space and contained compounds distinct from previous panels. We used this new screening panel to test several murine ORs that were previously characterized as having different tuning breadths. ORs were expressed in Xenopus laevis oocytes and assayed by two-electrode voltage clamp electrophysiology. MOR256-17, an OR previously characterized as broadly tuned, responded to nine novel compounds from our new screening panel that were structurally diverse and broadly dispersed across an estimated odor space. MOR256-22, an OR previously characterized as narrowly tuned, responded to a single novel compound that was structurally similar to a previously known ligand for this receptor. MOR174-9, a well-characterized receptor with a narrowly tuned MRR, did not respond to any novel compounds in our new panel. These results support the idea that variation in tuning breadth among these three ORs is not an artifact of the screening protocol, but is an intrinsic property of the receptors.

Functional characterization of odorant receptors in the ponerine ant, Harpegnathos saltator

Animals use a variety of sensory modalities-including visual, acoustic, and chemical-to sense their environment and interact with both conspecifics and other species. Such communication is especially critical in eusocial insects such as honey bees and ants, where cooperation is critical for survival and reproductive success. Various classes of chemoreceptors have been hypothesized to play essential roles in the origin and evolution of eusociality in ants, through their functional roles in pheromone detection that characterizes reproductive status and colony membership. To better understand the molecular mechanisms by which chemoreceptors regulate social behaviors, we investigated the roles of a critical class of chemoreceptors, the odorant receptors (ORs), from the ponerine ant Harpegnathos saltator in detecting cuticular hydrocarbon pheromones. In light of the massive OR expansion in ants (∼400 genes per species), a representative survey based on phylogenetic and transcriptomic criteria was carried out across discrete odorant receptor subfamilies. Responses to several classes of semiochemicals are described, including cuticular hydrocarbons and mandibular gland components that act as H. saltator pheromones, and a range of more traditional general odorants. When viewed through the prism of caste-specific OR enrichment and distinctive OR subfamily odorant response profiles, our findings suggest that whereas individual HsOrs appear to be narrowly tuned, there is no apparent segregation of tuning responses within any discrete HsOr subfamily. Instead, the HsOR gene family as a whole responds to a broad array of compounds, including both cuticular hydrocarbons and general odorants that are likely to mediate distinct behaviors.

Molecular Basis of Olfactory Chemoreception in the Common Bed Bug, Cimex lectularius

As one of the most notorious ectoparasites, bed bugs rely heavily on human or animal blood sources for survival, mating and reproduction. Chemoreception, mediated by the odorant receptors on the membrane of olfactory sensory neurons, plays a vital role in their host seeking and risk aversion processes. We investigated the responses of odorant receptors to a large spectrum of semiochemicals, including human odorants and plant-released volatiles and found that strong responses were sparse; aldehydes/ketones were the most efficient stimuli, while carboxylic acids and aliphatics/aromatics were comparatively less effective in eliciting responses from bed bug odorant receptors. In bed bugs, both the odorant identity and concentrations play important roles in determining the strength of these responses. The odor space constructed based on the responses from all the odorant receptors tested revealed that odorants within the same chemical group are widely dispersed while odorants from different groups are intermingled, suggesting the complexity of odorant encoding in the bed bug odorant receptors. This study provides a comprehensive picture of the olfactory coding mechanisms of bed bugs that will ultimately contribute to the design and development of novel olfactory-based strategies to reduce both the biting nuisance and disease transmission from bed bugs.