A single pair of pharyngeal neurons functions as a commander to reject high salt in Drosophila melanogaster
Sang, J.; Dhakal, S.; Shrestha, B.; Nath, D. K.; Kim, Y.; Ganguly, A.; Montell, C.; Lee, Y.
Show abstract
Salt is an essential nutrient for survival, while excessive NaCl can be detrimental. In the fruit fly, Drosophila melanogaster, internal taste organs in the pharynx are critical gatekeepers impacting the decision to accept or reject a food. Currently, our understanding of the mechanism through which pharyngeal gustatory receptor neurons (GRNs) sense high salt are rudimentary. Here, we found that a member of the ionotropic receptor family, Ir60b, is expressed exclusively in a pair of GRNs activated by high salt. Using a two-way choice assay (DrosoX) to measure ingestion volume, we demonstrate that IR60b and two coreceptors IR25a and IR76b, are required to prevent high salt consumption. Mutants lacking external taste organs but retaining the internal taste organs in the pharynx exhibit much higher salt avoidance than flies with all taste organs but missing the three IRs. Our findings highlight the vital role for IRs in a pharyngeal GRN to control ingestion of high salt.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Optogenetic induction of appetitive and aversive taste memories in Drosophila 97%
- Molecular characterization of gustatory second-order neurons reveals integrative mechanisms of gustatory and metabolic information 97%
- Chloride-dependent mechanisms of multimodal sensory discrimination and neuropathic sensitization in Drosophila 96%
Similar papers in this journal
- Neuromedin U signaling regulates memory retrieval of learned salt avoidance in a C. elegans gustatory circuit 96%
- Innate behavior sequence progression by peptide-mediated interorgan crosstalk 96%
- CMTr cap-adjacent 2`-O-ribose mRNA methyltransferases are required for reward learning and mRNA localization to synapses 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.