By Albert Lin

Chemosensation—the detection of chemical compounds in the environment—is one of the most important types of sensation across the animal kingdom. Odorant molecules permeate the environment, and effective detection and discriminations of these cues is critical to animals large and small, allowing them to perform behaviors such as finding food or evading threats.

However, identifying and discriminating between odors are complex computational problems for animals due to the diversity of chemical compounds found in nature. Olfactory systems are able, in principle, to detect and discriminate diverse odorants using combinatorial coding strategies. We set out to uncover how odorants are encoded in the nematode C. elegans, a small worm with a compact nervous system—just 302 neurons, of which 11 pairs are chemosensory. Given the small size of this olfactory system, the extent to which C. elegans was capable of discriminating between odorants was unknown.

Using the extensive genetic toolkit available in the worm, we built a transgenic animal in which we could label all 11 chemosensory neuron pairs with the fluorescent calcium sensor GCaMP. To deliver chemosensory stimuli to these animals, we employed a custom microfluidics setup in which a worm could be immobilized and presented with odorant solutions with high temporal precision. We then recorded the neuronal activity of the animal as it experienced these conditions.

Left: We employed a microfluidics device to immobilize C. elegans and present them with odorant solutions in a controlled manner. During stimulus presentations, the animals were imaged with a spinning disk confocal microscope. Right: A dual-color maximum projection image shows the head of the worm. Animals expressed nuclear-localized GCaMP6s (green) in all 11 chemosensory neuron pairs. A sparse wCherry (red) landmark allowed us to uniquely identify each of the neurons.

We studied a broad panel of 23 odors and 5 nematode pheromones and found that responses to these odorants were widespread, with most of these odorants reliably activate a unique combination of chemosensory neurons. From these data, we uncovered diverse tuning properties and dose-response curves across chemosensory neurons and across odorants. We built a multi-class classifier to determine in silico whether the single-trial responses of the neurons contained sufficient information to discriminate odorants, and found that this was indeed the case. From this analysis, we were also able to describe the unique contribution of each of the 11 sensory neuron types to an ensemble-level code for odorants. The results together demonstrate that despite its compact size, the integrated activity of the chemosensory neuron ensemble in the worm contains sufficient information to robustly encode the intensity and identity of diverse chemical stimuli.

Albert Lin was a graduate student in the lab of Aravinthan Samuel (Harvard) and is currently a postdoctoral fellow in the lab of Mala Murthy (Princeton).

Learn more in the original research article:
Lin A, Qin S, Casademunt H, Wu M, Hung W, Cain G, Tan NZ, Valenzuela R, Lesanpezeshki L, Venkatachalam V, Pehlevan C, Zhen M, Samuel ADT. Functional imaging and quantification of multineuronal olfactory responses in C. elegans. Sci Adv. 2023 Mar;9(9):eade1249.