Automated Behavioral Analysis of Large <em>C. elegans</em> Populations Using a Wide Field-of-view Tracking Platform
Author(s) -
Michele Perni,
Sam Casford,
Francesco A. Aprile,
Ellen A. A. Nollen,
Tuomas P. J. Knowles,
Michele Vendruscolo,
Christopher M. Dobson
Publication year - 2018
Publication title -
journal of visualized experiments
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.596
H-Index - 91
ISSN - 1940-087X
DOI - 10.3791/58643
Subject(s) - caenorhabditis elegans , statistical power , parametric statistics , computational biology , computer science , biology , genomics , phenotype , limit (mathematics) , artificial intelligence , genetics , genome , statistics , gene , mathematics , mathematical analysis
Caenorhabditis elegans is a well-established animal model in biomedical research, widely employed in functional genomics and ageing studies. To assess the health and fitness of the animals under study, one typically relies on motility readouts, such as the measurement of the number of body bends or the speed of movement. These measurements usually involve manual counting, making it challenging to obtain good statistical significance, as time and labor constraints often limit the number of animals in each experiment to 25 or less. Since high statistical power is necessary to obtain reproducible results and limit false positive and negative results when weak phenotypic effects are investigated, efforts have recently been made to develop automated protocols focused on increasing the sensitivity of motility detection and multi-parametric behavioral profiling. In order to extend the limit of detection to the level needed to capture the small phenotypic changes that are often crucial in genetic studies and drug discovery, we describe here a technological development that enables the study of up to 5,000 individual animals simultaneously, increasing the statistical power of the measurements by about 1,000-fold compared to manual assays and about 100-fold compared to other available automated methods.
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