Automated real-time quantification of group locomotor activity in Drosophila melanogaster.

Autor: Scaplen KM; Department of Neuroscience, Brown University Providence, Providence, USA., Mei NJ; Department of Neuroscience, Brown University Providence, Providence, USA., Bounds HA; Department of Neuroscience, Brown University Providence, Providence, USA., Song SL; Department of Neuroscience, Brown University Providence, Providence, USA., Azanchi R; Department of Neuroscience, Brown University Providence, Providence, USA., Kaun KR; Department of Neuroscience, Brown University Providence, Providence, USA. Karla_Kaun@brown.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2019 Mar 14; Vol. 9 (1), pp. 4427. Date of Electronic Publication: 2019 Mar 14.
DOI: 10.1038/s41598-019-40952-5
Abstrakt: Recent advances in neurogenetics have highlighted Drosophila melanogaster as an exciting model to study neural circuit dynamics and complex behavior. Automated tracking methods have facilitated the study of complex behaviors via high throughput behavioral screening. Here we describe a newly developed low-cost assay capable of real-time monitoring and quantifying Drosophila group activity. This platform offers reliable real-time quantification with open source software and a user-friendly interface for data acquisition and analysis. We demonstrate the utility of this platform by characterizing ethanol-induced locomotor activity in a dose-dependent manner as well as the effects of thermo and optogenetic manipulation of ellipsoid body neurons important for ethanol-induced locomotor activity. As expected, low doses of ethanol induced an initial startle and slow ramping of group activity, whereas high doses of ethanol induced sustained group activity followed by sedation. Advanced offline processing revealed discrete behavioral features characteristic of intoxication. Thermogenetic inactivation of ellipsoid body ring neurons reduced group activity whereas optogenetic activation increased activity. Together, these data establish the fly Group Activity Monitor (flyGrAM) platform as a robust means of obtaining an online read out of group activity in response to manipulations to the environment or neural activity, with an opportunity for more advanced post-processing offline.
Databáze: MEDLINE
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