Bio-computational Image Analysis to Define Indicators of C. elegans Healthspan

描述（由申请人提供）：现代老龄化研究的一个中心目标是寻求创新的方法来确定分子策略，以最大限度地延长人类健康寿命。虽然模型系统如C.虽然已经利用秀丽线虫来确定影响寿命的数百个基因，但是还没有对延长健康寿命的突变进行特异性和定向的遗传筛选。在释放强大的基因方法来解决这个极其重要的问题方面遇到障碍的一个主要原因是，没有快速评分的健康寿命指标可以广泛用于基因筛查。在这里，我们提出了一个合作项目，其中我们联合收割机的专业知识在C。elegans老化生物学与复杂的，国家的最先进的图像处理能力。我们的目标是开发运动分析程序，测量和报告与年龄相关的运动衰退的多个方面，建立一个容易得分和广泛有用的健康跨度量表。我们的具体目标是：目标一。开发图像分析方案，以快速可靠地测量C. elegans运动in liquid液体. Aim II.使用自动化分析对野生型和示例性健康跨度突变体中年龄相关的游泳下降进行评分。Aim III.调整和优化游泳成像方案，用于健康寿命的高通量分析。通过仔细控制和训练集来执行我们的合作项目，我们将揭示大量与年龄相关的运动能力下降的生物学。我们将描述多个定量参数，这些参数表明种群和个体动物中的减速是如何发生的;我们可能会定义年龄差的动物与年龄好的动物的具体标准;我们将详细描述胰岛素信号如何促进运动健康寿命;我们将调查影响多个过程的长寿基因的代表性群体，以确定那些也赋予健康寿命效应的基因。从长远来看（超出本申请的范围），我们将使用开发的健康寿命评分能力来确定延长健康寿命的遗传和药理学方法。我们计划将这个评分系统提供给C。elegans研究社区用于老化研究和其他应用。

DESCRIPTION (provided by applicant): A central goal of modern aging research is to seek innovative ways to identify molecular strategies to maximize human healthspan. Although model systems such as C. elegans have been exploited to define hundreds of genes affecting longevity, specific and directed genetic screens for mutations that extend healthspan have not yet been pursued. A major reason for the roadblock in unleashing powerful genetic approaches to this profoundly important problem is that there are no rapidly scored indicators of healthspan that can be used broadly in genetic screens. Here we propose a collaborative project in which we combine expertise in C. elegans aging biology with sophisticated, state-of-the-art image processing capability. Our goal is to develop motion analysis programs that measure and report multiple aspects of age-related locomotion decline, establishing an easily scored and broadly useful healthspan scale. Our specific aims are: Aim I. To develop image analysis protocols to rapidly and reliably measure multiple parameters/indicators of C. elegans locomotion in liquid. Aim II. To use automated analysis to score age-related swimming decline in wild type and exemplary healthspan mutants. Aim III. To adapt and optimize swimming imaging protocols for high throughput analysis of healthspan. By executing our collaborative project with careful controls and training sets, we will reveal a considerable amount about the biology of age-related locomotory decline. We will describe multiple quantitative parameters that indicate how slow-down transpires both in populations and in individual animals; we may define specific criteria for animals that age poorly vs. those that age well; we will describe in detail how insulin signaling boosts locomotory healthspan; we will survey representative groups of longevity genes that affect multiple processes to determine those that also confer healthspan effects. Over the long term (beyond the scope of this application), we will use the developed healthspan scoring capacity to identify genetic and pharmacological approaches toward extending healthspan. We plan to make this scoring system available to the C. elegans research community for use in aging studies and additional applications.