System for comprehensive tracking and analysis of C. elegans behaviors

描述(申请人提供)：土壤线虫，秀丽线虫(C.elegans)，是一种很有前途的模式生物，用于评估潜在的发育和神经毒物对多细胞生物的影响。然而，为了确定将线虫作为毒理学研究中实用和有效的模型的可能性，必须创建中等吞吐量技术来监测包括生长、大小、繁殖、取食和运动在内的表型特征。目前实践中的方法不利于中等吞吐量的研究，因为它们往往是手工的，执行起来很费力。值得注意的是，缺乏在不同实验条件下表现良好的计算机化自动定量线虫分析工具。我们建议开发一种商业产品，该产品将由一个计算机显微镜系统组成，该系统允许研究人员对自由移动的线虫的运动和其他复杂行为进行先进的自动化、定量分析。我们相信，引入强大的商业软件解决方案将大大有助于通过使用线虫的替代体内毒理学测试来进一步取代和减少传统的毒理学测试。与公共卫生的相关性：拟议的项目将允许自动完成目前人工执行的复杂和繁重的任务，从而使使用模式生物--秀丽线虫(C.elegans)的研究能够以比目前可行的更快的速度进行。这将使研究人员能够增加涉及定量行为分析的研究的吞吐量。该项目的总体效果将显著提高毒理学、环境监测、生态学和神经科学研究等多个领域的研究生产率和有效性。

DESCRIPTION (provided by applicant): The soil nematode, Caenorhabditis elegans (C. elegans), is a promising model organism to assess the effects of potential developmental and neurological toxicants on multi-cellular organisms. However, to determine the possibility of using C. elegans as a practical and efficient model in toxicology studies, medium throughput technologies must be created to monitor phenotypic characteristics including growth, size, reproduction, feeding, and movement. Methods in current practice are not conducive to medium-throughput studies because they are often manual and laborious to perform. There is a noticeable lack of computerized automated quantitative C. elegans analysis tools that perform well in the presence of differing experimental conditions. We propose to develop a commercial product that will be composed of a computerized microscope system that allows investigators to perform advanced automated, quantitative analyses of the locomotion and other complex behaviors of freely moving C. elegans nematodes. We believe that introduction of a robust commercial software solution will significantly contribute to further replacement and reduction of conventional toxicology tests by alternative in vivo toxicology assays using C. elegans. Public Health Relevance: The proposed project will enable research using the model organism, Caenorhabditis elegans (C. elegans), to occur at a faster pace than is currently feasible by allowing complex and laborious tasks currently performed manually to be done automatically. This will allow researchers to increase the throughput of studies involving quantitative behavioral analysis. The overall effect of this project will significantly improve the productivity and effectiveness of research in such diverse fields as toxicology, environmental monitoring, ecology and neuroscience research.