Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli

Abstract

Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.

DOI: http://dx.doi.org/10.7554/eLife.27670.001

eLife digest

Insects follow odor trails carried by the wind to find mates and sources of food. The turbulent motion of the air means that these odors tend to arrive in whiffs with varying intensities and durations, which makes it difficult to distinguish them. Insects use sensory cells called olfactory receptor neurons on their antenna to process odors. Specialized receptor proteins on the surface of these olfactory receptor neurons detect odor molecules and set off a cascade of events in these cells that ends with a signal being sent to the brain.

Much is known about how insects detect and process different kinds of smells, but it remains less clear how their olfactory neurons process the timing and intensity of odor whiffs. Now, Gorur-Shandilya et al. report what happens in the olfactory receptor neurons of fruit flies when they have to compensate for variations in the duration and intensity of odor whiffs.

In the experiments, fruit flies were exposed to two sweet-smelling odors. To do so, Gorur-Shandilya et al. built an apparatus that enabled them to control the airflow with enough precision that they could simulate the variability in the timing and intensity of natural odors in the air. The response of the flies’ olfactory receptor neurons to these smells was recorded. The experiments showed that the neurons could adapt to both the average intensity and the variance in intensity of odor signals.

The ability of these neurons to adapt to the average intensity of the odors followed a specific pattern, which is also seen in sensory cells responsible for vision and touch. Adapting to the average strength of an odor slows down the first of two steps in its processing. However, the second step has a complementary mechanism to speed up signals to the brain, so the timing of an odor whiff is accurately captured regardless of how strong it is. Based on these results, Gorur-Shandilya et al. created a biophysical model that could reproduce the experimental data, including the slowdown in the first step.

The experiments and the model may now help other scientists to investigate how different animals detect and process smells. For example, some insects are pests of agricultural crops, while other insects, such as mosquitos, spread diseases between people. A better understanding of how insects detect odors may help scientists to find ways to interfere with these processes to protect food crops and reduce the spread of tropical diseases.

DOI: http://dx.doi.org/10.7554/eLife.27670.002