The variability of the lifespan phenotype in C.elegans

线虫寿命表型的变异性

• 批准号: 8605143
• 负责人: WALTER FONTANA
• 金额: $ 32.69万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8605143
• 关键词: Affect; Age; Aging; Aging-Related Process; Alzheimer' s Disease; Animals; Attention; Biological Assay; Caenorhabditis elegans; Categories; Cessation of life; Code; Collection; Communities; Computer software; Cues; Data; Data Analyses; Demographer; Demographic Aging; Descriptor; Development; Dimensions; Disease; Electronics; Environment; Future; Gene Family; Gene Mutation; Genes; Genetic; Genome; Genotype; Human; Image; Image Analysis; Imagery; Individual; Insulin Receptor; Knowledge; Laboratory culture; Link; Longevity; Manuals; Maps; Measures; Methods; Modeling; Molecular; Movement; Mutation; Nature; Nematoda; Organism; Parental Ages; Parkinson Disease; Pathway interactions; Pattern; Phenotype; Population; Population Characteristics; Procedures; Process; Protein Kinase; Protocols documentation; Reporting; Research; Resolution; Resources; Risk; Running; Sampling; Schedule; Series; Shapes; Side; Structure; Surveys; Technology; Temperature; Testing; Time; Variant; Work; age effect; age related; base; cancer type; data acquisition; dosage; gene function; gene therapy; genetic variant; hazard; insight; mortality; mutant; public health relevance; reproductive; transcription factor

DESCRIPTION (provided by applicant): Aging is a process shaped by genetics, environment, and chance, all of which conspire to determine an individuals' time of death. A survival curve constitutes the demographic signature of aging at the level of the population. Understanding the survival curve's responsiveness to genetic interventions is a critical step in guiding the development of more structured models of aging. Such models may give insight into the processes that determine the patterns of initiation and progression of age-related diseases, such Alzheimer's and Parkinson's disease and many types of cancer. Large amounts of demographic information are required to support such modeling efforts, and data-acquisition remains a limiting step in contemporary research. We have recently developed a method that greatly accelerates the collection of demographic aging data in C. elegans nematodes, via the automated acquisition of survival curves at high statistical and temporal resolution. This method utilizes modified consumer-electronics flatbed scanners to image worms cultured under standard conditions. Accompanying software automatically processes the resultant time-lapse videos into survival curves. We will use this technology to link genetic and environmental perturbations to a high-precision demographic aging signature at an unprecedented scale. We will acquire and analyze high-resolution lifespan distributions for roughly 2000 mutants representing all classic genes known to affect lifespan in this organism as well as a variety of targeted gene families. We will determine whether survival curves deviate from predictions made by classic aging models and apply functional data analysis to gain insight into the number and nature of dimensions along which the demographic aging signature is most variable. We will group genes into categories in terms of their impact on survival curve shape features, in order to place known gene functions in relation to the demographic aging signature and help illuminate unknown gene functions. This information will be important for future mechanistic studies, and will offer perspective for existing molecular knowledge. We will make our collection of survival curves widely available, thus providing a valuable resource to both the C. elegans research community and demographers.

描述（由申请人提供）：衰老是一个由遗传、环境和机会塑造的过程，所有这些因素共同决定一个人的死亡时间。生存曲线构成人口一级老龄化的人口特征。了解生存曲线对遗传干预的反应是指导开发更结构化的衰老模型的关键一步。这些模型可以让我们深入了解与年龄有关的疾病（如阿尔茨海默氏病和帕金森氏病以及许多类型的癌症）的发生和发展模式。需要大量的人口统计信息来支持这种建模工作，数据采集仍然是当代研究的一个限制性步骤。我们最近开发了一种方法，大大加快了C中人口老龄化数据的收集。线虫，通过高统计和时间分辨率的生存曲线的自动采集。这种方法利用改进的消费电子平板扫描仪在标准条件下培养蠕虫的图像。附带的软件会自动将生成的延时视频处理成生存曲线。我们将利用这项技术，以前所未有的规模将遗传和环境扰动与高精度的人口老龄化特征联系起来。我们将获得和分析大约2000个突变体的高分辨率寿命分布，这些突变体代表已知影响这种生物体寿命的所有经典基因以及各种靶向基因家族。我们将确定生存曲线是否偏离经典老化模型的预测，并应用函数数据分析来深入了解人口老化特征最易变的沿着维度的数量和性质。我们将根据基因对生存曲线形状特征的影响将其分类，以便将已知的基因功能与人口老龄化特征联系起来，并帮助阐明未知的基因功能。这一信息将是重要的未来机制的研究，并将提供现有的分子知识的前景。我们将使我们收集的生存曲线广泛使用，从而为C。elegans研究社区和人口学家。

项目成果

Rules for modeling signal-transduction systems.

• DOI: 10.1126/stke.3442006re6
• 发表时间: 2006-07-18
• 期刊: Science's STKE : signal transduction knowledge environment
• 作者: Hlavacek, William S;Faeder, James R;Fontana, Walter
• 通讯作者: Fontana, Walter

Regulated spatial organization and sensitivity of cytosolic protein oxidation in Caenorhabditis elegans.

• DOI: 10.1038/ncomms6020
• 发表时间: 2014-09-29
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Romero-Aristizabal, Catalina;Marks, Debora S.;Fontana, Walter;Apfeld, Javier
• 通讯作者: Apfeld, Javier

The temporal scaling of Caenorhabditis elegans ageing.

• DOI: 10.1038/nature16550
• 发表时间: 2016-02-04
• 期刊: Nature
• 影响因子: 64.8
• 作者: Stroustrup N;Anthony WE;Nash ZM;Gowda V;Gomez A;López-Moyado IF;Apfeld J;Fontana W
• 通讯作者: Fontana W

Age-Dependence and Aging-Dependence: Neuronal Loss and Lifespan in a C. elegans Model of Parkinson's Disease.

• DOI: 10.3390/biology7010001
• 发表时间: 2017-12-23
• 期刊: Biology
• 影响因子: 4.2
• 作者: Apfeld J;Fontana W
• 通讯作者: Fontana W

Lifespan-on-a-chip: microfluidic chambers for performing lifelong observation of C. elegans.

• DOI: 10.1039/b919265d
• 发表时间: 2010-03-07
• 期刊: Lab on a chip
• 影响因子: 6.1
• 作者: Hulme SE;Shevkoplyas SS;McGuigan AP;Apfeld J;Fontana W;Whitesides GM
• 通讯作者: Whitesides GM