Dataset Information

Farnesol-detecting olfactory neurons in Drosophila.

ABSTRACT: We set out to deorphanize a subset of putative Drosophila odorant receptors expressed in trichoid sensilla using a transgenic in vivo misexpression approach. We identified farnesol as a potent and specific activator for the orphan odorant receptor Or83c. Farnesol is an intermediate in juvenile hormone biosynthesis, but is also produced by ripe citrus fruit peels. Here, we show that farnesol stimulates robust activation of Or83c-expressing olfactory neurons, even at high dilutions. The CD36 homolog Snmp1 is required for normal farnesol response kinetics. The neurons expressing Or83c are found in a subset of poorly characterized intermediate sensilla. We show that these neurons mediate attraction behavior to low concentrations of farnesol and that Or83c receptor mutants are defective for this behavior. Or83c neurons innervate the DC3 glomerulus in the antennal lobe and projection neurons relaying information from this glomerulus to higher brain centers target a region of the lateral horn previously implicated in pheromone perception. Our findings identify a sensitive, narrowly tuned receptor that mediates attraction behavior to farnesol and demonstrates an effective approach to deorphanizing odorant receptors expressed in neurons located in intermediate and trichoid sensilla that may not function in the classical "empty basiconic neuron" system.

SUBMITTER: Ronderos DS

PROVIDER: S-EPMC3951695 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Farnesol-detecting olfactory neurons in Drosophila.

Ronderos David S DS Lin Chun-Chieh CC Potter Christopher J CJ Smith Dean P DP

The Journal of neuroscience : the official journal of the Society for Neuroscience 20140301 11

We set out to deorphanize a subset of putative Drosophila odorant receptors expressed in trichoid sensilla using a transgenic in vivo misexpression approach. We identified farnesol as a potent and specific activator for the orphan odorant receptor Or83c. Farnesol is an intermediate in juvenile hormone biosynthesis, but is also produced by ripe citrus fruit peels. Here, we show that farnesol stimulates robust activation of Or83c-expressing olfactory neurons, even at high dilutions. The CD36 homol ...[more]

PMID: 24623773

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Project description:The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be, for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

Dataset Information

Farnesol-detecting olfactory neurons in Drosophila.

Publications

Farnesol-detecting olfactory neurons in Drosophila.

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