Odorant responses of olfactory sensory neurons expressing the odorant receptor MOR23: A patch clamp analysis in gene-targeted mice

Grosmaître, Xavier; Vassalli, Anne; Mombaerts, Peter; Shepherd, Gordon M.; Ma, Minghong

doi:10.1073/pnas.0508491103

Cited by 147 publications

(143 citation statements)

References 49 publications

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“…This has been documented in recent studies of ORNs in the mouse (Grosmaitre et al, 2006) and directly implies that ORN recruitment is a function of odor concentration.…”

Section: Canonical Energy Calculationssupporting

confidence: 54%

“…The sigmoid concentration-response curve describes the overall transduction mechanism, including ligand binding to olfactory receptors and second messenger cascade. Because firing thresholds and excitability are varying between individual receptors (Grosmaitre et al, 2006), the mean firing rate is not sufficient to describe the range of responses. We have used a Poisson distribution of response frequencies (van Drongelen et al, 1978) such that higher odor concentrations correspond to both higher mean firing frequencies and a greater proportion of responding receptor cells.…”

Section: Canonical Energy Calculationsmentioning

confidence: 99%

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An Energy Budget for the Olfactory Glomerulus

Nawroth

Greer²,

Chen³

et al. 2007

J. Neurosci.

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“…This has been documented in recent studies of ORNs in the mouse (Grosmaitre et al, 2006) and directly implies that ORN recruitment is a function of odor concentration.…”

Section: Canonical Energy Calculationssupporting

confidence: 54%

Section: Canonical Energy Calculationsmentioning

confidence: 99%

An Energy Budget for the Olfactory Glomerulus

Nawroth

Greer²,

Chen³

et al. 2007

J. Neurosci.

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“…The intact olfactory epithelia were prepared following published procedures (42,43). Mice were deeply anesthetized by i.p.…”

Section: Methodsmentioning

confidence: 99%

G protein-coupled odorant receptors underlie mechanosensitivity in mammalian olfactory sensory neurons

Connelly

Grosmaître

et al. 2014

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

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Mechanosensitive cells are essential for organisms to sense the external and internal environments, and a variety of molecules have been implicated as mechanical sensors. Here we report that odorant receptors (ORs), a large family of G protein-coupled receptors, underlie the responses to both chemical and mechanical stimuli in mouse olfactory sensory neurons (OSNs). Genetic ablation of key signaling proteins in odor transduction or disruption of OR-G protein coupling eliminates mechanical responses. Curiously, OSNs expressing different OR types display significantly different responses to mechanical stimuli. Genetic swap of putatively mechanosensitive ORs abolishes or reduces mechanical responses of OSNs. Furthermore, ectopic expression of an OR restores mechanosensitivity in loss-of-function OSNs. Lastly, heterologous expression of an OR confers mechanosensitivity to its host cells. These results indicate that certain ORs are both necessary and sufficient to cause mechanical responses, revealing a previously unidentified mechanism for mechanotransduction. , but our understanding of the mechanical sensors is still limited. We previously discovered that some OSNs in the mammalian nose responded to mechanical stimulation (4), a feature that may allow the nose to carry an afferent signal of breathing to the brain and facilitate binding of orofacial sensation (5). In the current study, we aim to identify the mechanical sensor(s) and mechanotransduction pathway in OSNs.In mammals, smell perception depends on a large family of ORs expressed in OSNs. Out of a repertoire of >1,000 ORs (6, 7), each OSN expresses a single type, which determines its response profile and central target in the brain. Binding of odorant molecules with specific ORs activates the olfactory G protein G olf , which in turn activates type III adenylyl cyclase (ACIII). ACIII activation causes increased production of cAMP, which opens a cyclic nucleotide-gated cation (CNG) channel. The inward current via the CNG channel is further amplified by Cl − outflow through a calcium-activated Cl − channel. This transduction cascade leads to depolarization of OSNs, which fire action potentials carrying the odor information to the brain (8). OSNs expressing the same OR are scattered in one of the few broadly defined zones in the olfactory epithelium, but their axons typically converge onto a pair of glomeruli in the olfactory bulb (9).Here we report that disruption of the olfactory signal transduction cascade completely eliminates mechanical responses in OSNs. OSNs expressing different receptor types display differential responses to mechanical stimuli. For instance, I7, M71, and SR1 neurons have much stronger mechanical responses than MOR23 and mOR-EG neurons. Loss-of-function mutation of the I7 receptor, genetic switch of the M71 receptor, or ablation of the SR1 receptor, abolishes or dramatically reduces mechanical responses in the host OSNs. Furthermore, ectopic expression of the I7 receptor restores mechanosensitivity in loss-of-function mutant I7 cells. ...

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“…This consistency indicates that the available biophysical models are detailed enough to relate the low-level neuron (and sensillum) characteristics to their high-level (spike train) properties. This opens the way to an interpretation of the observed response variability of ORNs expressing the same olfactory receptor (Grosmaître et al, 2006;Jarriault et al, 2010) or different olfactory receptors (Rospars et al, 2003; that is essential for a proper understanding of cerebral olfactory processes.…”

Section: Perspectivesmentioning

confidence: 99%

“…There are two challenges to modelling this input: First, it has to be reconstructed from ORN recordings in many individuals because no electrophysiological technique permits its direct observation in a single animal. Second, any model has to take into account the heterogeneity of ORN responses, even for ORNs expressing the same receptor, as shown in vertebrates (Grosmaître et al, 2006) and in insects (Jarriault et al, 2010). It follows that the cellular level of single neurons must be linked to the population level and stochastic aspects must be taken into account.…”

Section: Introductionmentioning

confidence: 99%

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

Grémiaux¹,

Nowotny²,

Martinez³

et al. 2012

Brain Research

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(2012) Modelling the signal delivered by a population of first-order neurons in a moth olfactory system. Brain Research, 1434. pp. 123-135. ISSN 0006-8993 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/38437/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Grémiaux et al. Highlights > Odour intensity coding in a whole population of moth receptor neurons was modelled. > Frequency (spikes per second) and latency of the first spike were analyzed > The model accounts for the statistical distributions of frequencies and latencies. > The same dose-frequency relation applies at the single cell and population levels. > Predictions based on a biophysical model of frog olfactory neurons are confirmed. Abstract.A statistical model of the population of first-order olfactory receptor neurons (ORNs) is proposed and analysed. It describes the relationship between stimulus intensity (odour concentration) and coding variables such as rate and latency of the population of several thousand sex-pheromone sensitive ORNs in male moths. Although these neurons likely express the same olfactory receptor, they exhibit, at any concentration, a relatively large heterogeneity of responses in both peak firing frequency and latency of the first action potential fired after stimulus onset. The stochastic model is defined by a multivariate distribution of six model parameters that describe the dependence of the peak firing rate and the latency on the stimulus dose. These six parameters and their mutual linear correlations were estimated from experiments in single ORNs and included in the multidimensional model distribution. The model is utilized to reconstruct the peak firing rate and latency of the message sent to the brain by the whole ORN population at different stimulus intensities and to establish their main qualitative and quantitative properties. Finally, these properties are shown to be in agreement with those found previously in a vertebrate ORN population.

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Odorant responses of olfactory sensory neurons expressing the odorant receptor MOR23: A patch clamp analysis in gene-targeted mice

Cited by 147 publications

References 49 publications

An Energy Budget for the Olfactory Glomerulus

An Energy Budget for the Olfactory Glomerulus

G protein-coupled odorant receptors underlie mechanosensitivity in mammalian olfactory sensory neurons

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

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