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Identification and functional analysis of olfactory receptor family reveal unusual characteristics of the olfactory system in the migratory locust.

ABSTRACT: Locusts represent the excellent model of insect olfaction because the animals are equipped with an unusual olfactory system and display remarkable density-dependent olfactory plasticity. However, information regarding receptor molecules involved in the olfactory perception of locusts is very limited. On the basis of genome sequence and antennal transcriptome of the migratory locust, we conduct the identification and functional analysis of two olfactory receptor families: odorant receptors (ORs) and ionotropic receptors (IRs). In the migratory locust, there is an expansion of OR family (142 ORs) while distinctly lower number of IR genes (32 IRs) compared to the repertoires of other insects. The number of the locust OR genes is much less than that of glomeruli in antennal lobe, challenging the general principle of the "one glomerulus-one receptor" observed in other insects. Most OR genes are found in tandem arrays, forming two large lineage-specific subfamilies in the phylogenetic tree. The "divergent IR" subfamily displays a significant contraction, and most of the IRs belong to the "antennal IR" subfamily in the locust. Most ORs/IRs have olfactory-specific expression while some broadly- or internal-expressed members are also found. Differing from holometabolous insects, the migratory locust contains very similar expression profiles of ORs/IRs between nymph and adult stages. RNA interference and behavioral assays indicate that an OR-based signaling pathway, not IR-based, mediates the attraction of locusts to aggregation pheromones. These discoveries provide insights into the unusual olfactory system of locusts and enhance our understanding of the evolution of insect olfaction.

SUBMITTER: Wang Z

PROVIDER: S-EPMC4611004 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Identification and functional analysis of olfactory receptor family reveal unusual characteristics of the olfactory system in the migratory locust.

Wang Zhifeng Z Yang Pengcheng P Chen Dafeng D Jiang Feng F Li Yan Y Wang Xianhui X Kang Le L

Cellular and molecular life sciences : CMLS 20150812 22

Locusts represent the excellent model of insect olfaction because the animals are equipped with an unusual olfactory system and display remarkable density-dependent olfactory plasticity. However, information regarding receptor molecules involved in the olfactory perception of locusts is very limited. On the basis of genome sequence and antennal transcriptome of the migratory locust, we conduct the identification and functional analysis of two olfactory receptor families: odorant receptors (ORs) ...[more]

PMID: 26265180

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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

Identification and functional analysis of olfactory receptor family reveal unusual characteristics of the olfactory system in the migratory locust.

Publications

Identification and functional analysis of olfactory receptor family reveal unusual characteristics of the olfactory system in the migratory locust.

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