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The iFly tracking system for an automated locomotor and behavioural analysis of Drosophila melanogaster.

Authors :
Kohlhoff KJ
Jahn TR
Lomas DA
Dobson CM
Crowther DC
Vendruscolo M
Source :
Integrative biology : quantitative biosciences from nano to macro [Integr Biol (Camb)] 2011 Jul; Vol. 3 (7), pp. 755-60. Date of Electronic Publication: 2011 Jun 23.
Publication Year :
2011

Abstract

The use of animal models in medical research provides insights into molecular and cellular mechanisms of human disease, and helps identify and test novel therapeutic strategies. Drosophila melanogaster--the common fruit fly--is one of the most well-established model organisms, as its study can be performed more readily and with far less expense than for other model animal systems, such as mice, fish, or primates. In the case of fruit flies, standard assays are based on the analysis of longevity and basic locomotor functions. Here we present the iFly tracking system, which enables to increase the amount of quantitative information that can be extracted from these studies, and to reduce significantly the duration and costs associated with them. The iFly system uses a single camera to simultaneously track the trajectories of up to 20 individual flies with about 100 μm spatial and 33 ms temporal resolution. The statistical analysis of fly movements recorded with such accuracy makes it possible to perform a rapid and fully automated quantitative analysis of locomotor changes in response to a range of different stimuli. We anticipate that the iFly method will reduce very considerably the costs and the duration of the testing of genetic and pharmacological interventions in Drosophila models, including an earlier detection of behavioural changes and a large increase in throughput compared to current longevity and locomotor assays.<br /> (This journal is © The Royal Society of Chemistry 2011)

Details

Language :
English
ISSN :
1757-9708
Volume :
3
Issue :
7
Database :
MEDLINE
Journal :
Integrative biology : quantitative biosciences from nano to macro
Publication Type :
Academic Journal
Accession number :
21698336
Full Text :
https://doi.org/10.1039/c0ib00149j