Automated Acquisition of C. elegans Survival Curves with a Flatbed Scanner

摘要：在个体层面上，衰老是一个由多种随机、遗传和环境因素塑造的过程，所有这些因素共同设定了一系列可能的死亡时间。在人口的层面上，老龄化过程的终点——死亡——成为人们关注的焦点。大量的个体对死亡时间的概率分布进行抽样，得出了构成老龄化人口特征的生存曲线。生存曲线是对研究人员有用的统计数据的中心部分，无论他们在多大的粒度水平上研究衰老的哪个方面。通过扩大其统计和时间分辨率，可以大大提高全生存曲线作为线虫衰老研究中的一种测定方法的意义，超越手工协议设定的实际限制。为此，我们开发了一种自动获取秀丽隐杆线虫种群存活曲线的方法，该方法采用平板扫描仪对含有蠕虫的培养皿进行成像，并自动将所得图像时间序列转换为存活曲线。根据对曲线形状的细微影响，高分辨率生存曲线将是对基因进行分类的理想方法。此外，自动化方法固有的标准化使得在相同的遗传（或环境）扰动下获得的生存数据在实验室中累积起来。最后，自动获取的曲线可以跨实验室进行比较，也可以与以前通过相同方法获得的所有其他曲线进行比较，从而产生数据“网络效应”。预计外界对我们的程序感兴趣，我们的提案旨在调整我们的技术，以便成功转移到其他实验室。

DESCRIPTION (provided by applicant): Notice number: NOT-OD-09-058 Notice Title: NIH Announces the Availability of Recovery Act funds for Competitive Revision Application ABSTRACT At the level of an individual, aging is a process shaped by multiple stochastic, genetic, and environmental factors, all of which conspire to set a range of possible death times. At the level of a population, it is the endpoint of the aging process-death-that comes into focus. A large number of individuals sample the probability distribution of death times, giving rise to a survival curve that constitutes the demographic signature of aging. The survival curve is a central piece of statistical data useful to researchers regardless of which aspects of aging they study at what level of granularity. The significance of the full survival curve as an assay in C. elegans aging research can be greatly enhanced by expanding its statistical and temporal resolution beyond the practical limitations set by manual protocols. For this purpose we have developed an automated method for acquiring survival curves in C. elegans populations by adapting flatbed scanners for imaging Petri plates containing worms and automatically converting the resultant time series of images into a survival curve. High-resolution survival curves would be an ideal way to classify genes in terms of subtle impacts on curve shape. Moreover, the standardization inherent in an automated method makes survival data acquired for the same genetic (or environmental) perturbation cumulative across laboratories. Finally, automatically acquired curves can be compared across laboratories as well as against all other curves previously acquired by the same method, creating a data "network effect". Anticipating outside interest in our procedure, our proposal aims to adapt our technology for successful transfer to other laboratories. PUBLIC HEALTH RELEVANCE: The survival curve of genetically identical individuals is a powerful tool in the study of aging. A robust technology for the automated and inexpensive generation of high-resolution survival curves of large worm (C. elegans) populations will have broad impact on the study of aging. We have developed a prototype of such a technology and will adapt it for successful transfer to other laboratories.