Novel Features of Drosophila Sweet Taste System

Loading...
Thumbnail Image

Date

2019

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

165
views
42
downloads

Abstract

The sense of taste enables animal survival and reproduction by allowing them to detect and discriminate different chemosensory stimuli so as to select for food options that are suitable for ingestion for both themselves and their progeny. A dominant model in the eld suggests that animals' taste coding generally follows a relatively simple and clean scheme - the "labeled-line" model - such that individual taste neurons are predetermined to detect one specific category of tastants (e.g., sweetness) and drive predetermined category-specific behaviors (e.g., acceptance). However, results from several recent studies started to challenge this model, and thus the question of how taste information is processed to drive behaviors remains unsolved. Here, I used the Drosophila melanogaster sweet taste system as a model to address this question. By utilizing multiple approaches of genetic manipulation and neural activity recording, I discovered three unexpected features of the taste system at the molecular, cellular, and circuit levels. First, sweet neurons can sense two categories of taste - sweetness and sourness. Second, the sensitivity of sweet neurons is actively dampened by specific molecules. Third, sweet neurons are composed of at least two functionally distinct subgroups that allow for behavioral responses to sweet taste to be adjusted according to context. Together, this study identifies previously unknown mechanisms by which the Drosophila taste system decodes the identities and the intensities of stimuli and promotes proper behaviors towards them.

Department

Description

Provenance

Citation

Citation

Chen, Hsueh-Ling (2019). Novel Features of Drosophila Sweet Taste System. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/20149.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.