Mixture and Concentration Effects on Odorant Receptor Response Patterns In Vivo

Natural odors are mixtures of volatile chemicals (odorants). Odors are encoded as responses of distinct subsets of the hundreds of odorant receptors and trace amine-associated receptors expressed monogenically by olfactory sensory neurons. This is an elegantly simple mechanism for differentially encoding odors but it is susceptible to complex dose–response relationships and interactions between odorants at receptors, which may help explain olfactory phenomena, such as mixture suppression, synthetic versus elemental odor processing, and poorly predictable perceptual outcomes of new odor mixtures. In this study, in vivo tests in freely behaving mice confirm evidence of a characteristic receptor response pattern consisting of a few receptors with strong responses and a greater number of weakly responding receptors. Odorant receptors responsive to an odor are often unrelated and widely divergent in sequence, even when the odor consists of a single species of odorant. Odorant receptor response patterns to a citrus odor broaden with concentration. Some highly sensitive receptors respond only to a low concentration but others respond in proportion to concentration, a feature that may be critical for concentration-invariant perception. Other tests find evidence of interactions between odorants in vivo. All of the odorant receptor responses to a moderate concentration of the fecal malodor indole are suppressed by a high concentration of the floral odorant, α-ionone. Such suppressive effects are consistent with prior evidence that odorant interactions at individual odorant receptors are common.

Modulation of the combinatorial code of odorant receptor response patterns in odorant mixtures

The perception of odors relies on combinatorial codes consisting of odorant receptor (OR) response patterns to encode odor identity. The modulation of these patterns by odorant interactions at ORs potentially explains several olfactory phenomena: mixture suppression, unpredictable sensory outcomes, and the perception of odorant mixtures as unique objects. We determined OR response patterns to 4 odorants and 3 binary mixtures in vivo in mice, identifying 30 responsive ORs. These patterns typically had a few strongly responsive ORs and a greater number of weakly responsive ORs. The ORs responsive to an odorant were often unrelated sequences distributed across several OR subfamilies. Mixture responses predicted pharmacological interactions between odorants, which were tested in vitro by heterologous expression of ORs in cultured cells. These tests provided independent evidence confirming odorant agonists for 13 ORs and identified both suppressive and additive effects of mixing odorants. This included 11 instances of antagonism of ORs by an odorant, 1 instance of additive responses to a binary mixture, 1 instance of suppression of a strong agonist by a weak agonist, and the discovery of an inverse agonist for an OR. These findings demonstrate that interactions between odorants at ORs are common.

Stochastic and Temporal Models of Olfactory Perception

Olfactory systems typically process signals produced by mixtures composed of very many natural odors, some that can be elicited by single compounds. The several hundred different olfactory receptors aided by several dozen different taste receptors are sufficient to define our complex chemosensory world. However, sensory processing by selective adaptation and mixture suppression leaves only a few perceptual components recognized at any time. Thresholds determined by stochastic processes are described by functions relating stimulus detection to concentration. Relative saliences of mixture components are established by relating component recognition to concentration in the presence of background components. Mathematically distinct stochastic models of perceptual component dominance in binary mixtures were developed that accommodate prediction of an appropriate range of probabilities from 0 to 1, and include errors in identifications. Prior short-term selective adaptation to some components allows temporally emergent recognition of non-adapted mixture-suppressed components. Thus, broadly tuned receptors are neutralized or suppressed by activation of other more efficacious receptors. This ‘combinatorial’ coding is more a process of subtraction than addition, with the more intense components dominating the perception. It is in this way that complex chemosensory mixtures are reduced to manageable numbers of odor notes and taste qualities.

Neural dynamics in response to binary taste mixtures

Taste stimuli encountered in the natural environment are usually combinations of multiple tastants. Although a great deal is known about how neurons in the taste system respond to single taste stimuli in isolation, less is known about how the brain deals with such mixture stimuli. Here, we probe the responses of single neurons in primary gustatory cortex (GC) of awake rats to an array of taste stimuli including 100% citric acid (100 mM), 100% sodium chloride (100 mM), 100% sucrose (100 mM), and a range of binary mixtures (90/10, 70/30, 50/50, 30/70, and 10/90%). We tested for the presence of three different hypothetical response patterns: 1) responses varying monotonically as a function of concentration of sucrose (or acid) in the mixture (the “monotonic” pattern); 2) responses increasing or decreasing as a function of degree of mixture of the stimulus (the “mixture” pattern); and 3) responses that change abruptly from being similar to one pure taste to being similar the other (the “categorical” pattern). Our results demonstrate the presence of both monotonic and mixture patterns within responses of GC neurons. Specifically, further analysis (that included the presentation of 50 mM sucrose and citric acid) made it clear that mixture suppression reliably precedes a palatability-related pattern. The temporal dynamics of the emergence of the palatability-related pattern parallel the temporal dynamics of the emergence of preference behavior for the same mixtures as measured by a brief access test. We saw no evidence of categorical coding.

Inhibitory Odorant Signaling in Mammalian Olfactory Receptor Neurons

Odorants inhibit as well as excite olfactory receptor neurons (ORNs) in many species of animals. Cyclic nucleotide-dependent activation of canonical mammalian ORNs is well established but it is still unclear how odorants inhibit these cells. Here we further implicate phosphoinositide-3-kinase (PI3K), an indispensable element of PI signaling in many cellular processes, in olfactory transduction in rodent ORNs. We show that odorants rapidly and transiently activate PI3K in the olfactory cilia and in the olfactory epithelium in vitro. We implicate known G-protein–coupled isoforms of PI3K and show that they modulate not only the magnitude but also the onset kinetics of the electrophysiological response of ORNs to complex odorants. Finally, we show that the ability of a single odorant to inhibit another can be PI3K dependent. Our collective results provide compelling support for the idea that PI3K-dependent signaling mediates inhibitory odorant input to mammalian ORNs and at least in part contributes to the mixture suppression typically seen in the response of ORNs to complex natural odorants.

Gustatory neural coding in the monkey cortex: mixtures

1. Psychophysicists have shown that the intensity and quality of a taste stimulus, as perceived by humans, is modified by including that stimulus in a mixture. Gustatory neurons in the primary taste cortex (anterior insula and frontal operculum) of the cynomolgus macaque are involved with the coding of stimulus intensity and quality, and so should reflect the impact of these stimulus interactions. 2. We recorded the activity of 48 neurons in primary taste cortex in response to the oral application of each of the four basic stimuli, their six possible dyads, the four triads, and the tetrad of all four. Stimuli were maintained at a constant intensity in all mixtures by increasing their concentrations as the number of components rose. 3. Glucose was the most effective basic stimulus, followed by quinine HCl, NaCl, and HCl. The mean response to dyads was suppressed by 50% from the sum of responses to the two unmixed components. The response to triads was 62% lower than the sum of responses to their three components, and activity evoked by the tetrad was suppressed by 74% from the sum of all four individual responses. Therefore there was nearly total suppression in the sense that the responses to the mixtures were approximately 1/2, 1/3, and 1/4 the sums of responses to two, three, and four components, respectively. 4. Neurons could be divided into four subtypes: those that responded best to each of the basic stimuli. All subtypes except HCl cells were about equally suppressed when their preferred stimulus was included in a mixture. HCl was a particularly ineffective stimulus, such that this subtype responded poorly and so was less susceptible to mixture suppression. 5. Taste quality, as indexed by correlation coefficients among profiles of activity, was quite predictable for dyads. If the mixture included HCl, the profile it generated correlated poorly (about +0.20) with that of HCl and rather well (about +0.60) with that of the other component. If HCl was not included, the mixture's profile correlated about +0.40 with that of each component. 6. The profile generated by the mixture of three stimuli was predictable only if one of the components was HCl. In that case, the triad elicited a profile midway between those of the other two components, i.e., the contribution of HCl was largely ignored. When HCl was not involved, or when all four basic stimuli were combined, the resulting profiles were poorly correlated with those of all basic stimuli. 7. The contribution made by each basic taste to human perception and to the macaque's neurophysiological response was compared for all mixtures. The contribution was often quite similar for human and macaque, but when differences occurred, they were typically due to lower activity from HCl cells in the macaque, a loss that was replaced mainly by larger responses from glucose neurons. 8. The magnitude of responses to mixtures in the macaque taste cortex matches well with expectations from human psychophysical studies. The presumed quality of the response to mixtures is also similar, except that HCl is less effective in monkeys and sugars more so.