Multiscale tools and approaches for understanding and engineering cell-fate transitions

项目摘要 合成生物学的目标是利用生物系统的力量来动态地获取信息， 细胞，使合成生物医学任务，如肿瘤监测，病原体识别，或细胞命运， 重新编程细胞工程中的这些任务依赖于强大的机制来调节转基因， 酶的递送、遗传校正和细胞疗法。为了充分发挥其潜力，哺乳动物 合成生物学需要用于在原代细胞中实施基因表达的可靠控制的基础工具。 例如，转基因沉默（例如表达丧失）仍然是有效地抑制转基因表达的常见挑战。 工程原代细胞跨越一系列长度和时间尺度的监管层协调事件， 与细胞信号传导的分子结合调节基因表达，从而调节细胞命运。多尺度方法是 需要整合控制细胞命运转变的不同过程。细胞命运的转变代表了 需要协调从表观遗传和细胞骨架重塑到增殖的多个过程的事件 和转录。了解这些转变可能会阐明癌基因如何利用这些过程来驱动 细胞转化在这里，我们提出了一个多尺度的方法来理解和工程细胞的命运， 转换（例如重编程、分化）。 从我们以前的工作，以确定原则的细胞命运的转变，我们确定了系统水平 限制了重新编程的限制，并开发了一种鸡尾酒，使小鼠的重新编程增加了100倍 细胞比较人类和小鼠对重编程的反应，我们发现了物种特异性差异。 在增殖，信号传导和先天免疫反应过程中的重编程，可能有助于降低 人类细胞的重编程率。我们建议检查这些分子相关性，以确定每个 影响重新编程过程和结果。我们将利用这些见解来设计遗传控制器， 引导细胞重新编程我们已经确定了一种优化重编程的策略， 瞬时“擦除”阶段之后是“写入”阶段以建立新的单元命运。我们建议发展 控制器能够自主地引导单元通过这些竞争目标以提高效率 重新编程。遗传控制器是由合成基因电路连接到天然基因组成的 监管网络。虽然已经在增强的合成的逻辑设计上投入了大量的努力， 电路（例如，用于同步的群体感应、边缘检测的电路），关于如何实现 细胞硬件和遗传元素的涌现的三维结构影响电路。这里我们 建议提高我们对转录如何重塑DNA以及它如何影响DNA性能的理解。 基因回路确定染色质结构在细胞特性中的作用将指导分子工程的努力 to build建立genetic基因controllers控制器capable能够to regulate调节behavior行为.我们预计，我们开发的原则和工具 将广泛适用于细胞工程应用以及研究细胞命运转变。

Project summary Synthetic biology aims to harness the power of biological systems to dynamically access information in the cell, enabling synthetic biomedical tasks such as tumor surveillance, pathogen identification, or cell-fate reprogramming. Such tasks in cellular engineering rely on robust mechanisms to regulate transgenes for the delivery of enzymes, genetic corrections, and cellular therapies. To unleash its full potential, mammalian synthetic biology requires foundational tools for implementing reliable control of gene expression in primary cells. For example, transgene silencing (e.g. loss of expression) remains a common challenge to effectively engineering primary cells. Layers of regulation across a range of length- and time-scales coordinate events from molecular binding to cell signaling regulate gene expression and thus cell fate. Multiscale approaches are needed to integrate the diverse processes that control cell-fate transitions. Cell-fate transitions represent pivotal events requiring coordination of multiple processes from epigenetic and cytoskeletal remodeling to proliferation and transcription. Understanding these transitions may illuminate how oncogenes coopt these processes to drive cellular transformation. Here, we propose a multiscale approach for understanding and engineering cell-fate transitions (e.g. reprogramming, differentiation). From our previous work to identify principles of cell-fate transitions, we identified systems-level constraints that limited reprogramming and developed a cocktail that increased reprograming 100-fold in mouse cells. Comparing the human and mouse response to reprogramming, we identified species-specific differences in proliferation, signaling, and the innate immune response during reprogramming that may contribute to lower reprogramming rates for human cells. We propose to examine these molecular correlates to determine how each impacts the reprogramming process and outcomes. We will use these insights to design genetic controllers to guide cells through reprogramming. Already we have identified a strategy to optimize reprogramming by inducing a transient “erase” phase followed by a “write” phase to establish the new cell fate. We propose to develop controllers capable of autonomously guiding cells through these competing objectives to enhance the efficiency of reprogramming. Genetic controllers are composed from synthetic gene circuits connected to native gene regulatory networks. While significant efforts have been devoted to the logical design of enhanced synthetic circuitry (e.g. circuits for synchronized quorum sensing, edge-detection), less is understood regarding how cellular hardware and the emergent three-dimensional structure of genetic elements affect circuits. Here, we propose to improve our understanding how transcription reshapes DNA and how it impacts the performance of gene circuits. Defining the role of chromatin structure in cellular identity will guide molecular engineering efforts to build genetic controllers capable of regulating behavior. We anticipate that the principles and tools we develop will be broadly applicable across cellular engineering applications as well as for investigating cell-fate transitions.