Human olfactory receptor responses to odorants

Mainland, Joel D.; Li, Yun R.; Zhou, Ting; Liu, Wen Ling L; Matsunami, Hiroaki

doi:10.1038/sdata.2015.2

Cited by 120 publications

(153 citation statements)

References 41 publications

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“…These experiments revealed that MS4A responses occur seconds after odor presentation, with similar or slightly faster response dynamics to those observed with MOR9-1 (Figures S4D and S4E, see Experimental Procedures). Dose-response curves revealed low micromolar EC50s for three specific MS4A/odor pairs, similar to the EC50 observed for MOR9-1/vanillin (Figure 3D), and well within the range of EC50s typically observed for conventional odorant receptor/ligand pairs in vitro (Saito et al, 2009; Mainland et al, 2015). Depleting extracellular calcium abolished MS4A ligand-dependent calcium transients (Figure S4F).…”

Section: Resultssupporting

confidence: 76%

A Family of non-GPCR Chemosensors Defines an Alternative Logic for Mammalian Olfaction

Greer

Bear

Lassance

et al. 2016

Cell

127

134

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Summary Odor perception in mammals is mediated by parallel sensory pathways that convey distinct information about the olfactory world. Multiple olfactory subsystems express characteristic seven-transmembrane G-protein coupled receptors (GPCRs) in a one-receptor-per-neuron pattern that facilitates odor discrimination. Sensory neurons of the “necklace” subsystem are nestled within the recesses of the olfactory epithelium and detect diverse odorants; however, they do not express known GPCR odor receptors. Here we report that members of the four-pass transmembrane MS4A protein family are chemosensors expressed within necklace sensory neurons. These receptors localize to sensory endings and confer responses to ethologically-relevant ligands including pheromones and fatty acids in vitro and in vivo. Individual necklace neurons co-express many MS4A proteins and are activated by multiple MS4A ligands; this pooling of information suggests that the necklace is organized more like subsystems for taste than for smell. The MS4As therefore define a distinct mechanism and functional logic for mammalian olfaction.

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Section: Resultssupporting

confidence: 76%

A Family of non-GPCR Chemosensors Defines an Alternative Logic for Mammalian Olfaction

Greer

Bear

Lassance

et al. 2016

Cell

127

134

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“…The successful cloning and expression of the human olfactory receptors [32] for the development of the bioelectronic nose and the development of nano-biotechnology have improved the performance of the bioelectronic nose. The bioelectronic nose is constructed with biological materials that have been integrated with nanomaterials such as carbon nanotube, conducting polymer, and graphene [21, 27, 42, 67].…”

Section: Introductionmentioning

confidence: 99%

Bioelectronic nose and its application to smell visualization

Ko¹,

Park

2016

J Biol Eng

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There have been many trials to visualize smell using various techniques in order to objectively express the smell because information obtained from the sense of smell in human is very subjective. So far, well-trained experts such as a perfumer, complex and large-scale equipment such as GC-MS, and an electronic nose have played major roles in objectively detecting and recognizing odors. Recently, an optoelectronic nose was developed to achieve this purpose, but some limitations regarding the sensitivity and the number of smells that can be visualized still persist. Since the elucidation of the olfactory mechanism, numerous researches have been accomplished for the development of a sensing device by mimicking human olfactory system. Engineered olfactory cells were constructed to mimic the human olfactory system, and the use of engineered olfactory cells for smell visualization has been attempted with the use of various methods such as calcium imaging, CRE reporter assay, BRET, and membrane potential assay; however, it is not easy to consistently control the condition of cells and it is impossible to detect low odorant concentration. Recently, the bioelectronic nose was developed, and much improved along with the improvement of nano-biotechnology. The bioelectronic nose consists of the following two parts: primary transducer and secondary transducer. Biological materials as a primary transducer improved the selectivity of the sensor, and nanomaterials as a secondary transducer increased the sensitivity. Especially, the bioelectronic noses using various nanomaterials combined with human olfactory receptors or nanovesicles derived from engineered olfactory cells have a potential which can detect almost all of the smells recognized by human because an engineered olfactory cell might be able to express any human olfactory receptor as well as can mimic human olfactory system. Therefore, bioelectronic nose will be a potent tool for smell visualization, but only if two technologies are completed. First, a multi-channel array-sensing system has to be applied for the integration of all of the olfactory receptors into a single chip for mimicking the performance of human nose. Second, the processing technique of the multi-channel system signals should be simultaneously established with the conversion of the signals to visual images. With the use of this latest sensing technology, the realization of a proper smell-visualization technology is expected in the near future.

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“…6. Sensitivities of olfactory receptors appear to be lognormally distributed for (A) flies (33) and (B) humans (34). The histograms of the logarithms of n entries of the sensitivity matrix (orange) are compared with a normal distribution (blue) with the same mean and SD λ exp .…”

Section: Discussionmentioning

confidence: 99%

“…The response of receptors to individual ligands has been measured experimentally for flies (33) and humans (34). We use these published data to estimate the statistics of realistic sensitivity matrices as described in Supporting Information.…”

Section: Optimal Receptormentioning

confidence: 99%

Receptor arrays optimized for natural odor statistics

Zwicker

Murugan

Brenner

2016

Proc. Natl. Acad. Sci. U.S.A.

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Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.iscrimination of olfactory signals occurs in a high-dimensional space of odor stimuli in which a large number of distinct molecules and their mixtures can be distinguished by a much smaller number of receptors (1-3). For example, humans have about 300 distinct olfactory receptors (4), which can sense at least 2,100 odorant molecules (5), and the real number might be much larger (1). Moreover, humans can differentiate between mixtures of up to 30 odorants (6). Such remarkable molecular discrimination is thought to use a combinatorial code (7,8), where typical odorant molecules bind to receptors of multiple types (1, 3). Each receptor type is expressed in many cells (9), and the information from all receptors of the same type is accumulated in corresponding glomeruli in the olfactory bulb (10, 11) (see Fig. 1A). The activity of a single glomerulus is thus the total signal of the associated receptor type, so the information about the odor is encoded in the activity pattern of the glomeruli (11,12). This activity pattern is interpreted by the brain to learn about the composition and the concentration of the inhaled odor. We here study how receptor arrays can maximize the transmitted information.It is known (13, 14) that the input−output characteristics of sensory apparatuses of many organisms are tailored to the statistics of the organism's natural environment to maximize information transmission. For example, in the visual circuit of the fly, the input−output relationship of neurons is matched to the cumulative distribution of the input distribution (13). Similar observations have since been made in many sensory systems (14, 15) and even in transcriptional regulation (16). In all these cases, the distinguishable outputs of the sensory system must be dedicated to equal parts of the input distribution, which is known as Laughlin's principle (13) or histogram equalization (17). Intuitively, more of the response range is dedicated to common stimuli, at the expense of less frequent stimuli (13).Similarly, t...

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Human olfactory receptor responses to odorants

Cited by 120 publications

References 41 publications

A Family of non-GPCR Chemosensors Defines an Alternative Logic for Mammalian Olfaction

A Family of non-GPCR Chemosensors Defines an Alternative Logic for Mammalian Olfaction

Bioelectronic nose and its application to smell visualization

Receptor arrays optimized for natural odor statistics

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