Single-cell analysis and synthetic control of mammalian chromatin dynamics and gene regulation

项目总结： 可预测的哺乳动物细胞工程对于发展数量生物学和 实现精准医疗的承诺。为了开发细胞工程的预测框架，我们 需要了解基因调控如何在动态染色质环境中发挥作用。 尽管过去几年见证了基因和表观遗传编辑工具的蓬勃发展，但仍有 测量和预测染色质对基因表达的影响面临的主要挑战。首先，染色质- 介导性调控导致细胞间基因表达的异质性，因此许多问题很难解决 用跨单元格平均的方法来回答。其次，在大多数实验设计中，染色质状态和 同时，DNA的组成各不相同，因此很难单独区分染色质的作用。第三, 染色质调节跨越多个分子机制和长度尺度，使得整合变得困难 将这些数据输入到一个连贯的预测模型中。 为了应对这些挑战，我们将开发和结合合成生物学的新工具， 单细胞技术和数学建模。我们将通过直接操控染色质状态 在一个确定的位置重新招募和释放染色质调节剂，然后在单个 使用时间推移显微镜、流式细胞仪和下一代测序技术对细胞进行分析。最后，我们会 建立一个数学模型，将特定位点的分子细节与整个染色质状态相结合 在相同的牢房里。 我们将使用这些工具来回答有关染色质动力学对基因的作用的基本问题。 调控：(1)为什么不同类型的细胞有不同的沉默动力学和表观遗传记忆？(2)如何 染色质修饰的速度和影响的传播范围有多大？(3)转录因子如何在 启动子和增强子与染色质调节因子相互作用决定基因表达？ 总而言之，这些基本问题的答案和新测量技术的发展， 控制和模拟基因表达将促进哺乳动物合成生物学和基础 染色质和基因调控的生物学领域。

Project Summary: Predictable mammalian cell engineering is essential both for advancing quantitative biology and realizing the promise of precision medicine. In order to develop a predictive framework for cell engineering, we need to understand how gene regulation functions in the context of a dynamic chromatin environment. While the last few years have witnessed a boom in genetic and epigenetic editing tools, there are still major challenges for measuring and predicting the effect of chromatin on gene expression. First, chromatin- mediated control results in cell-to-cell heterogeneity of gene expression, so many questions are difficult to answer with methods that average across cells. Second, in most experimental designs the chromatin state and DNA composition vary at the same time, making it difficult to disentangle the role of chromatin alone. Third, chromatin regulation spans multiple molecular mechanisms and length-scales, making it difficult to integrate these data into a coherent predictive model. In order to address these challenges, we will develop and combine new tools in synthetic biology, single-cell techniques, and mathematical modelling. We will directly manipulate the chromatin state via recruitment and release of chromatin regulators at a defined locus, and then measure the outcome in single cells over time using time-lapse microscopy, flow cytometry and next generation sequencing. Finally, we will build a mathematical model that integrates molecular details at a specific locus with the overall chromatin state in the same cells. We will use these tools to answer essential questions about the role of chromatin dynamics on gene regulation: (1) Why do different cell types have different silencing dynamics and epigenetic memory? (2) How fast and how far do chromatin modifications and their effects spread? (3) How do transcription factors at promoters and enhancers interact with chromatin regulators to determine gene expression? Together, the answer to these basic questions and the development of new techniques for measuring, controlling, and modeling gene expression will advance both mammalian synthetic biology and the basic biology fields of chromatin and gene regulation.