Theoretical studies of gene expression kinetics

在一个典型的基因表达周期中，分子信号进入细胞核，它们与转录因子和DNA相互作用，一个或多个基因被转录成RNA，转录物被编辑，然后被输出到细胞质，在那里被翻译成蛋白质。由于扩散搜索和反应事件的内在随机性，每个步骤所需的时间是一个随机变量。我的研究项目旨在从机制上理解这些随机事件，以及它们对细胞功能和生物工程的影响。用非常粗略的术语来说，我们试图将这些复杂的随机（随机）过程简化为它们的组成部分，理解这些部分，然后将它们重新整合，以便对整个事件链的统计数据有所了解。我建议研究与信使RNA的合成和输出有关的几个相关问题：我的学生和我将详细阐述在我的实验室开发的真核生物（高等生物）转录的数学模型。在这个模型上，我们将增加一个剪接模型（编辑以剪切非编码的中间序列，内含子）。同时，我们将发展一些理论来处理高度拥挤的介质中的扩散和动力学，真核生物核中的普遍条件，以及一些相互作用分子机器的统计理论，这些理论需要处理剪接体和RNA聚合酶之间的相互作用。这些项目合在一起将使我们能够详细地模拟发生在细胞核中的基因表达过程。与此同时，我们正在开发一些理论工具来理解基因表达的控制。这些工具将为分析实验和建模数据以及理解细胞如何控制噪声（随机波动）提供一个框架。考虑到细胞功能在时间和细胞间不可避免的波动的基因表达控制理论也将是生物工程师设计必须对噪声具有鲁棒性的有价值的工具。

In a typical gene expression cycle, molecular signals enter the nucleus, they interact with the transcription factors and with the DNA, one or more genes are transcribed to RNA, the transcript is edited, and then it is exported to the cytoplasm where it is translated to protein. The time required for each of these steps is a random variable due to the intrinsic randomness of diffusive search and of reactive events. My research program seeks to understand these random events mechanistically, as well as their consequences for cellular function and for bioengineering. In very rough terms, we seek to reduce these complex stochastic (random) processes to their constituent parts, to understand the parts, and then to reintegrate them in order to say something about the statistics of the whole chain of events.I propose to work on several related problems relating to the synthesis and export of messenger RNA: My students and I will elaborate a mathematical model of eukaryotic (higher-organism) transcription developed in my laboratory. To this model, we will add a model of splicing (editing to cut out non-coding intervening sequences, introns). In the meantime, we will develop some theory to treat diffusion and kinetics in highly crowded media, the prevailing conditions in the eukaryotic nucleus, as well as some statistical theory of interacting molecular machines, which is required to treat, among other things, the interaction between the spliceosome and RNA polymerase. These projects taken together will allow us to simulate in detail the gene expression processes occurring in the nucleus.In parallel, we are developing some theoretical tools for understanding the control of gene expression. These tools will provide a framework for analyzing both experimental and modeling data, and for understanding how cells control noise (random fluctuations). A control theory of gene expression which takes into account the unavoidable fluctuations in cellular function in time and across cells will also be a valuable tool for bioengineers whose designs must be robust to noise.