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Ir76b is a Co-receptor for Amine Responses in Drosophila Olfactory Neurons.

ABSTRACT: Two large families of olfactory receptors, the Odorant Receptors (ORs) and Ionotropic Receptors (IRs), mediate responses to most odors in the insect olfactory system. Individual odorant binding "tuning" OrX receptors are expressed by olfactory neurons in basiconic and trichoid sensilla and require the co-receptor Orco. The situation for IRs is more complex. Different tuning IrX receptors are expressed by olfactory neurons in coeloconic sensilla and rely on either the Ir25a or Ir8a co-receptors; some evidence suggests that Ir76b may also act as a co-receptor, but its function has not been systematically examined. Surprisingly, recent data indicate that nearly all coeloconic olfactory neurons co-express Ir25a, Ir8a, and Ir76b. Here, we demonstrate that Ir76b and Ir25a function together in all amine-sensing olfactory receptor neurons. In most neurons, loss of either co-receptor abolishes amine responses. In contrast, amine responses persist in the absence of Ir76b or Ir25a in ac1 sensilla but are lost in a double mutant. We show that responses mediated by acid-sensing neurons do not require Ir76b, despite their expression of this co-receptor. Our study also demonstrates that one population of coeloconic olfactory neurons exhibits Ir76b/Ir25a-dependent and Orco-dependent responses to distinct odorants. Together, our data establish the role of Ir76b as a bona fide co-receptor, which acts in partnership with Ir25a. Given that these co-receptors are among the most highly conserved olfactory receptors and are often co-expressed in chemosensory neurons, our data suggest Ir76b and Ir25a also work in tandem in other insects.

SUBMITTER: Vulpe A

PROVIDER: S-EPMC8635857 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundIn vertebrates and invertebrates, sensory neurons adapt to variable ambient conditions, such as the duration or repetition of a stimulus, a physiological mechanism considered as a simple form of non-associative learning and neuronal plasticity. Although various signaling pathways, as cAMP, cGMP, and the inositol 1,4,5-triphosphate receptor (InsP3R) play a role in adaptation, their precise mechanisms of action at the cellular level remain incompletely understood. Recently, in Drosophila, we reported that odor-induced Ca2+-response in axon terminals of olfactory receptor neurons (ORNs) is related to odor duration. In particular, a relatively long odor stimulus (such as 5 s) triggers the induction of a second component involving intracellular Ca2+-stores.ResultsWe used a recently developed in-vivo bioluminescence imaging approach to quantify the odor-induced Ca2+-activity in the axon terminals of ORNs. Using either a genetic approach to target specific RNAs, or a pharmacological approach, we show that the second component, relying on the intracellular Ca2+-stores, is responsible for the adaptation to repetitive stimuli. In the antennal lobes (a region analogous to the vertebrate olfactory bulb) ORNs make synaptic contacts with second-order neurons, the projection neurons (PNs). These synapses are modulated by GABA, through either GABAergic local interneurons (LNs) and/or some GABAergic PNs. Application of GABAergic receptor antagonists, both GABAA or GABAB, abolishes the adaptation, while RNAi targeting the GABABR (a metabotropic receptor) within the ORNs, blocks the Ca2+-store dependent component, and consequently disrupts the adaptation. These results indicate that GABA exerts a feedback control. Finally, at the behavioral level, using an olfactory test, genetically impairing the GABABR or its signaling pathway specifically in the ORNs disrupts olfactory adapted behavior.ConclusionTaken together, our results indicate that a relatively long lasting form of adaptation occurs within the axon terminals of the ORNs in the antennal lobes, which depends on intracellular Ca2+-stores, attributable to a positive feedback through the GABAergic synapses.

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.

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Ir76b is a Co-receptor for Amine Responses in Drosophila Olfactory Neurons.

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