Direct tests of the role of stem cells in minimizing mutation accumulation

描述（由申请人提供）：DNA序列中的突变可导致癌症和衰老。关于自然发生的突变的原因，特别是关于DNA复制错误的重要性，仍然存在很大的不确定性。此外，人们对多细胞生物用来最大限度地减少突变积累的策略知之甚少。我们将集中讨论一个已经得到广泛认可但几乎没有正式测试的特定假设。由John凯恩斯提出的这一假说认为，慢循环干细胞通过周期性地用经历较少循环的祖细胞更新快循环细胞库，使分化细胞经历的平均分裂次数最小化（该次数是“谱系深度”）。通过这一机制，干细胞可以最大限度地减少复制依赖性突变的积累.为了测量DNA复制在突变累积中的重要性，并测试谱系深度的最小化是否自然地用于最小化突变累积，我们将利用一个定义明确且高度易处理的干细胞模型系统：C.线虫生殖系我们将采取两种相辅相成的办法。在第一种方法中，我们将开发简单的复制依赖性突变累积的计算模拟，并询问干细胞及其后代之间的细胞周期长度分布是什么样的，通过模拟预测，以最大限度地减少突变累积。我们将逐步扩展这些模型，特别是通过允许不依赖复制的突变来源。我们将确定最能解释我们的实验细胞周期数据和第二种方法中获得的突变累积数据的模型。这将使我们能够推断DNA复制在突变积累中的作用，以及细胞周期长度控制在限制这种积累中的作用。在第二种方法中，我们将询问生殖细胞周期特性的任意变化是否会改变突变积累的动态并使这种积累次优。我们将首先描述关键生殖细胞调控网络突变体中细胞周期长度的分布。然后，我们将开发一种关键的实验工具来测量突变在老化生殖系中积累的速率。在自然条件下测量突变的挑战在于它们发生的频率极低。因此，我们将建立一个突变报告的高灵敏度和非常低的背景。我们将在野生型和突变体中使用该报告基因。这将扩大我们的理论模型的定量基础，并提供了一个直接的测试的假设，细胞周期长度控制是用来最大限度地减少突变积累。总的来说，这项工作将为理解多细胞生物体使用的策略提供坚实的基础，以最大限度地减少随着年龄的突变积累。

DESCRIPTION (provided by applicant): Mutations in DNA sequences can cause cancer and aging. Large uncertainties remain about causes of naturally-occurring mutations, and in particular about the importance of DNA replication errors. Furthermore, little is known about strategies used by multicellular organisms to minimize the accumulation of mutations. We will focus on a particular hypothesis that has received widespread recognition but little formal testing. This hypothesis, proposed by John Cairns, postulates that slow- cycling stem cells minimize the average number of divisions that differentiated cells have gone through (that number is a "pedigree depth") by periodically refreshing a pool of faster-cycling cells with progenitors that have undergone fewer cycles. By this mechanism, stem cells would minimize replication- dependent mutation accumulation. To measure the importance of DNA replication in mutation accumulation, and to test whether minimization of pedigree depth is naturally used to minimize mutation accumulation, we will leverage a well-defined and highly-tractable stem cell model system: the C. elegans germ line. We will follow two complementary approaches. In a first approach we will develop simple computational simulations of replication-dependent mutation accumulation, and ask what distribution of cell cycle lengths between stem cells and their descendants are predicted by simulations to minimize mutation accumulation. We will progressively expand these models, notably by allowing for a replication-independent source of mutations. We will identify the models that best account for our experimental cell cycle data, and for mutation accumulation data acquired in the second approach. This will allow us to infer the role of DNA replication in mutation accumulation, and the role of cell cycle length control in limiting that accumulation. In a second approach, we will ask if arbitrary changes in germ cell cycle properties alter the dynamics of mutation accumulation and render that accumulation suboptimal. We will first characterize the distribution of cell cycle lengths in key germline regulatory network mutants. We will then develop a critical experimental tool to measure the rate at which mutations accumulate in aging germ lines. The challenge in measuring mutations under natural conditions is that they occur at extremely low frequency. We will thus build a mutation reporter of high sensitivity and extraordinarily-low background. We will use this reporter in wild type and in mutants. This will expand the quantitative basis for our theoretical models, and provide a direct test of the hypothesis that cell cycle length control is used to minimize mutation accumulation. Overall, this work will provide a solid foundation to understand strategies used by multicellular organisms to minimize mutation accumulation with age.