Publication: High-throughput automated phenotyping of two genetic mouse models of huntington's disease
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Program
KU-Authors
KU Authors
Co-Authors
Oakeshott, Stephen
Shamy, Jul Lea T
El-Khodor, Bassem Fouad
Filippov, Igor V.
Mushlin, Richard A.
Port, Russell G.
Connor, David
Paintdakhi, Ahmad
Menalled, Liliana B.
Ramboz, Sylvie
Advisor
Publication Date
2013
Language
English
Type
Journal Article
Journal Title
Journal ISSN
Volume Title
Abstract
Phenotyping with traditional behavioral assays constitutes a major bottleneck in the primary screening, characterization, and validation of genetic mouse modelsof disease, leading to downstream delays in drug discovery efforts. We present a novel and comprehensive one-stop approach to phenotyping, the PhenoCube™. This system simultaneously captures the cognitive performance, motor activity, and circadian patterns of group-housed mice by use of home-cage operant conditioning modules (IntelliCage) and custom-built computer vision software. We evaluated two different mouse models of Huntington's Disease (HD), the R6/2 and the BACHD in the PhenoCube™ system. Our results demonstrated that this system can efficiently capture and track alterations in both cognitive performance and locomotor activity patterns associated with these disease models. This work extends our prior demonstration that PhenoCube™ can characterize circadian dysfunction in BACHD mice and shows that this system, with the experimental protocols used, is a sensitive and efficient tool for a first pass high-throughput screening of mouse disease models in general and mouse models of neurodegeneration in particular
Description
Source:
PLOS Currents
Publisher:
Public Library of Science
Keywords:
Subject
Medicine, Circadian rhythm, Cognition