Aging of S. cerevisiae in a Dynamically Changing Environment

描述（由申请人提供）：衰老是一个复杂的过程，受遗传和环境因素的影响，“变老”的负面影响可以采取多种形式。单个细胞的寿命，如神经元和干细胞，影响多细胞生物衰老的速度和优雅。营养胁迫和遗传不稳定性已被确定为真核生物寿命的关键决定因素。然而，虽然已经确定了许多与衰老有关的重要途径，但限制寿命的基本机制仍然不确定。这项研究的一个障碍是难以跟踪长期行为，不仅是在人类和其他长寿哺乳动物中，而且在更简单的模式生物中也是如此。而单细胞S.尽管酿酒酵母是最不复杂的衰老模型，并且最适合于遗传和分子操作，但是用于监测衰老的现有方法，即使在这种快速生长的生物体中，仍然是有限的。 我们建议使用微流控技术作为一个实验平台的研究老化的S。啤酒。由于生长环境对真核生物的寿命有很大的影响，我们将开发一种高度平行的微流体装置，该装置能够将单独的细胞群体置于动态环境中。我们将联合收割机与新的图像处理技术相结合，从而能够观察在静态和动态环境中生长的单细胞的老化动态。该平台的优势是，可以生成个体生物从出生到衰老的终生统计数据。我们将展示这个平台的潜力，通过专注于衰老的关键决定因素，热量摄入，为长期动态提供新的见解。我们将首先使用微流体梯度平台将大量细胞置于一系列静态葡萄糖浓度下，来表征静态热量限制（CR）对寿命的影响。因为CR可能不需要恒定以延长寿命，我们接下来将研究动态CR对寿命的影响，以深入了解生物体对低营养水平的反应机制。 遗传因素对衰老也有很大的影响。在人的一生中，基因突变的积累会导致与衰老有关的疾病，如癌症的发生。酵母是这种现象的一个令人惊讶的有用模型，因为当母细胞达到细胞分裂的临界数量时，它们被观察到切换到基因组不稳定的状态。这种转换导致杂合性丢失（洛）事件的频繁发生。我们将开发一种方法，采用双色荧光显微镜跟踪洛事件，我们将使用我们的微流控平台来观察响应CR的洛频率的变化。最后，酵母中的代谢循环，表现为氧化还原状态的振荡，已被证明是由参与寿命延长的途径调节。我们将使用一种修饰的荧光蛋白，它沿着我们的动态微流体平台来检测氧化状态，以确定寿命与酵母代谢振荡周期的关系。 公共卫生相关性：衰老过程受环境和遗传因素的影响。提供次优营养水平的环境已被证明可以大大延长许多模式生物的寿命，从酵母到哺乳动物。我们将开发一个高度并行的微流控平台，以观察和表征影响真核衰老重要方面的环境和遗传因素之间的相互作用。

DESCRIPTION (provided by applicant): Aging is a complex process governed by both genetic and environmental factors, and the negative effects of "growing old" can take on many forms. The life spans of individual cells, such as neurons and stem cells, influence the rate and grace with which multi-cellular organisms age. Nutritional stress and genetic instability have been identified as key determinants of life span in eukaryotes. However, while many important pathways involved in aging have been identified, the fundamental mechanisms that limit life span remain undefined. One hindrance to this research is the difficulty in tracking long-term behaviors, not just in humans and other long-lived mammals, but in simpler model organisms as well. While the single-celled S. cerevisiae is the least complicated model for aging and the most amenable to genetic and molecular manipulations, the existing methods for monitoring aging, even in this rapidly growing organism, remain limited. We propose to use microfluidic technology as an experimental platform for the study of aging in S. cerevisiae. As the growth environment has a large impact on the life span of eukaryotes, we will develop a highly parallel microfluidic device with the ability to subject separate populations of cells to a dynamic environment. We will combine this with new image processing techniques, enabling the observation of aging dynamics in single cells growing in both static and dynamic environments. This platform will have the advantage of generating life-long statistics for individual organisms as they progress from birth to old age. We will demonstrate the potential of this platform to provide new insight into long-term dynamics by focusing on a key determinant of aging, caloric intake. We will first characterize the effect of static Calorie Restriction (CR) on life span usinga microfluidic gradient platform to subject large populations of cells to a range of static glucose concentrations. Because CR may not need to be constant in order to extend life span, we will next investigate the effect of dynamic CR on longevity, in order to gain insight into the mechanisms by which an organism responds to low nutrient levels. Genetic factors also have a strong influence on aging. The accumulation of genetic mutations over the course of a lifetime leads to the onset of aging-related diseases, such as cancer. Yeast is a surprisingly useful model for this phenomenon, as mother cells are observed to switch to a state of genomic instability when they reach a critical number of cell divisions. This switch leads to the frequent occurrence of loss-of-heterozygosity (LOH) events. We will develop a method for employing two-color fluorescence microscopy to track LOH events, and we will use our microfluidic platform to observe changes in LOH frequency in response to CR. Finally, a metabolic cycle in yeast, manifested by oscillations in redox state, has been shown to be regulated by pathways involved in life span extension. We will use a modified fluorescent protein that senses oxidative state along with our dynamic microfluidic platform to determine how life span is related to the period of metabolic oscillations in yeast. PUBLIC HEALTH RELEVANCE: The aging process is governed by both the environment and genetics. Environments that provide sub-optimal levels of nutrients have been shown to greatly increase life span in numerous model organisms, from yeasts to mammals. We will develop a highly parallel microfluidic platform to observe and characterize the interplay between environmental and genetic factors that affect important aspects of eukaryotic aging.