Studies of DNA replication and single-molecule dynamics

在这个应用程序中，我提出了三个相互关联的生物物理学和统计物理学的项目。 主要重点是与DNA复制相关的问题，包括建模和实验方面。 建模方面利用了实验技术的最新进展，这些技术提供了关于“复制状态”的大量数据集（描述了在给定的基因组区域，哪些部分在给定的时间内复制，哪些部分没有复制）。 有了大型数据集和我们以前开发的了解复制的工具，我们的团队处于独特的地位，可以回答许多关于复制如何进行的问题，无论是在正常还是异常条件下。 特别是，我们将开始比较不同生物体的复制“程序”，观察复制在发育过程中是如何变化的，以及观察突变体和癌细胞中复制是如何改变的。 我们还扩展了我们的建模形式，以便能够分析复制过程中出现的不同类型的问题（例如DNA链中的切口或双链断裂）。 与生物学家合作者一起，我们也将开始开发研究单细胞水平复制的仪器，与迄今为止所做的群体研究形成对比。 拥有单细胞数据首先解决了解释来自细胞周期不同步的细胞的数据的技术问题。 更重要的是，它将使我们能够评估在名义上相同的细胞中看到的基因转录的变异性是否也存在于复制中。 最后，我们正在建立并将使用“反馈陷阱”来研究纳米粒子和分子相互作用。 这样的陷阱将有助于更好地理解统计力学中的基本问题，如“麦克斯韦的恶魔”，以及在更“自然”的条件下DNA-蛋白质相互作用的问题。

In this application, I propose three interrelated projects in biophysics and statistical physics. The primary focus is on issues related to DNA replication, with both modeling and experimental aspects. The modeling aspects exploit the recent advances in experimental techniques that are giving large sets of data about the "replication state" (depicting, at a given region of the genome, which parts have and which have not been replicated at a given time). With large datasets and with the tools we have previously developed to understand replication, our group is uniquely positioned to answer many questions about how replication proceeds, under both normal and abnormal conditions. In particular, we shall begin to compare the replication "programs" of different organisms, to look at how replication changes during development, and to look at how replication is altered in mutants and in cancer cells. We are also extending our modeling formalism to be able to analyze different kinds of problems that arise during replication (such as nicks in a strand of DNA or double-strand breaks). In conjunction with biologist collaborators, we will also begin development of apparatus to study replication at the single-cell level, in contrast to the population studies done to date. Having single-cell data solves, first of all, the technical problem of interpreting data from cells whose cell cycles are not well-synchronized. Even more important, it will allow us to assess whether the kinds of variability seen in nominally identical cells for gene transcription is also present for replication. Finally, we are building and shall use a "feedback trap" to study nanoparticles and molecular interactions. Such a trap will contribute to a better understanding of such fundamental questions in statistical mechanics as "Maxwell's demon" as well as questions for DNA-protein interactions under more "natural" conditions.