Calmodulin regulates the olfactory performance in Drosophila melanogaster

Insect odorant receptors (ORs) detect volatile chemical cues with high sensitivity. These ORs operate as ligand-gated ion channels and are formed by heptahelical OrX and Orco (co-receptor) proteins. A highly conserved calmodulin (CaM) binding site (CBS) 336SAIKYWVER344 within the second intracellular loop of Drosophila melanogaster Orco constitutes a target for regulating OR performance. Here we asked how a point mutation K339N in this CBS affects the olfactory performance of Drosophila melanogaster. We first asked how this mutation would affect the odor responses of olfactory sensory neurons (OSNs). Using Ca2+ imaging in an ex-vivo antenna preparation, we activated all OR (OrX/Orco) expressing neurons using the synthetic agonist VUAA1. In a next attempt, we restricted the OR spectrum to Or22a expressing neurons (Or22a/Orco) and stimulated these OSNs with the ligand ethyl hexanoate. In both approaches, we found that flies carrying the K339N point mutation in Orco display a reduced olfactory response. We also found that the mutation abolishes the capability of OSNs to sensitize by repeated weak odor stimuli. Next, we asked whether OrcoK339N might affect the odor localization performance. Using a wind tunnel bioassay, we found that odor localization in flies carrying the OrcoK339N mutation was severely diminished.

Using a Mobile Robot with Interpolation and Extrapolation Method for Chemical Source Localization in Dynamic Advection-diffusion Environment

<span lang="EN-US">this paper address the problem of mapping likely particle path derived from a chemical source using interpolation and extrapolation method. Order localization is the problem of finding the source of an odor or other volatile chemical. Most localization method require the robot to follow the odor plume along its entire length, which is time consuming and may be especially difficult in a cluttered environment. In this paper, a map of sensors’ environment was used, together with the path line of airflow, to predict the pattern of air movement. The robot then used the airflow pattern to reason about the probable location of the odor source. This demonstrates that interpolation and extrapolation method can be used to assist odor localization search and indicates that similar techniques have great operating in an unstructured environment to reason about its surroundings. This paper present details of getting the model of particle path using interpolation and extrapolation method, model of particle path surrounding the obstacles and openings, result of practical odor source location simulation.</span>