A novel computational approach for simultaneous tracking and feature extraction of C. elegans populations in fluid environments
A novel computational approach for simultaneous tracking and feature extraction of C. elegans populations in fluid environments
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DOI：
10.1109/tbme.2008.918582
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发表时间：
2008-05-01
影响因子：
4.6
通讯作者：
Driscoll, Monica
中科院分区：
文献类型：
--
作者：
Tsechpenakis, Gabriel;Bianchi, Laura;Driscoll, Monica
秀丽隐杆线虫（C. elegans）是广泛用于剖析发育和神经系统功能的保守的基本生物学机制的遗传模型。C.线虫的运动受到复杂的神经元调节，并受到遗传和环境因素的影响;因此，它的分析有望揭示遗传、环境和病理生理过程如何控制行为。迄今为止，基于计算机的方法已被用于分析C。elegans运动;然而，这些都不是高分辨率和高通量的。我们使用计算机视觉方法开发了一种新的自动化方法来分析C。elegans运动我们的方法提供了运动过程中的位置、轨迹和体型信息，旨在有效地跟踪多个动物（C。elegans）在杂乱的图像和光照变化下。我们用这种方法详细描述了C. elegans在液体中的运动，并分析了六个unc-8，一个mec-4和一个odr-1突变体。我们报告的功能，线虫游泳以前没有注意到，并表明我们的方法检测的差异，乍一看相似的突变体的游泳配置文件。
The nematode Caenorhabditis elegans (C. elegans) is a genetic model widely used to dissect conserved basic biological mechanisms of development and nervous system function. C. elegans locomotion is under complex neuronal regulation and is impacted by genetic and environmental factors; thus, its analysis is expected to shed light on how genetic, environmental, and pathophysiological processes control behavior. To date, computer-based approaches have been used for analysis of C. elegans locomotion; however, none of these is both high resolution and high throughput. We used computer vision methods to develop a novel automated approach for analyzing the C. elegans locomotion. Our method provides information on the position, trajectory, and body shape during locomotion and is designed to efficiently track multiple animals (C. elegans) in cluttered images and under lighting variations. We used this method to describe in detail C. elegans movement in liquid for the first time and to analyze six unc-8, one mec-4, and one odr-1 mutants. We report features of nematode swimming not previously noted and show that our method detects differences in the swimming profile of mutants that appear at first glance similar.