Synthetic toolkit for precision gene expression control and signal processing in mammalian cells

项目总结/摘要 细胞激活精确的基因表达程序，以响应多因素的化学和生物刺激。 有目的地操纵这一过程是合成生物学的主要目标， 人类细胞可能会导致我们对人类生物学的理解和发展的突破， 下一代的诊断和治疗方法，以复杂的方式应对疾病。不幸的是， 人工控制哺乳动物细胞中基因表达的工具有很大的局限性，限制了我们的研究。 研究基本生物过程和设计更有效的细胞疗法的能力。最 广泛使用的工具是源自细菌转录系统的老一代技术。这些是 在数量上非常有限，这限制了可以同时控制的基因产物的数量。 此外，重要的是，他们使用“简单的”一对一的监管互动， 对设计系统的监管灵活性和复杂性的限制。因此，研究人员 无法创造出复杂的基因表达控制器， 生物化学信号（例如配体、化学诱导物、疾病线索），并调整或重塑相应的基因 激活配置文件。在许多生物医学应用中， 哺乳动物细胞中的基因表达控制器是基于细胞的癌症治疗方法的发展， 免疫和再生医学，这可能会受到与过度激活和组织相关的问题的困扰。 的特异性我们建议通过开发一种新的基因表达合成工具包来克服这些障碍 控制哺乳动物细胞。受后生动物转录系统自然设计的启发，我们的框架 是基于合成转录因子（synTF），可以编程组装合作， 多价络合物。我们以前的工作表明，合作synTF使基因的构建 表达控制电路在酵母中具有极大扩展的信号处理行为。在这里，我们将开发和 表征哺乳动物自组装synTF，其具有用于安装到人细胞中的上级性质 相对于现有的工具。我们将使用这些工具开发三类基因表达控制器， 我们将在人类免疫细胞中展示，选择它们是因为它们在人类生理学中的重要作用， 细胞治疗的潜力：（1）由正交的FDA批准的药物调节的诱导控制器。(2)细胞- 自主控制器，其感测和处理生物刺激，包括合成的配体识别， Notch受体和微环境线索。(3)能够感知和整合的信号整合控制器 多种生物信号来激活转录程序。我们预计，这一工具包将广泛 研究人员使用它来实现跨哺乳动物系统的精确基因表达控制， 合成生物学、细胞重编程和基于细胞的治疗的生物医学应用。的中国梦作出 我们的工具和设计框架免费提供给学术科学界。

PROJECT SUMMARY/ABSTRACT Cells activate precise gene expression programs in response to multifactorial chemical and biological stimuli. The purposeful manipulation of this process is a principal goal of synthetic biology, and its application to human cells could lead to breakthroughs in our understanding of human biology and in the development of next-generation diagnostics and therapeutics that respond in sophisticated ways to disease. Unfortunately, tools to artificially control gene expression in mammalian cells have significant limitations, constraining our ability to study fundamental biological processes and design more effective cell-based therapies. The most widely-used tools are older generation technology, derived from bacterial transcriptional systems. These are greatly limited in number, which restricts the number of gene products that can be simultaneously controlled. Additionally and importantly, they use “simple” one-to-one regulatory interactions, imposing fundamental restrictions on the regulatory flexibility and sophistication of designer systems. As a consequence, researchers are unable to create sophisticated gene expression controllers that can flexibly sense and integrate biochemical signals (e.g. ligands, chemical inducers, disease cues), and tune or reshape corresponding gene activation profiles. Among the many biomedical applications that would be transformed by these precision gene expression controllers in mammalian cells is the development of cell-based therapeutics for cancer, auto- immunity, and regenerative medicine, which can suffer from issues related to over-activation and tissue specificity. We propose to overcome these barriers by developing a novel synthetic toolkit for gene expression control in mammalian cells. Inspired by the natural design of metazoan transcriptional systems, our framework is based on synthetic transcription factors (synTFs) that can be programmed to assemble cooperatively in multivalent complexes. Our previous work showed that cooperative synTFs enable construction of gene expression control circuits with greatly expanded signal processing behavior in yeast. Here we will develop and characterize mammalian self-assembling synTFs that have superior properties for installation into human cells relative to existing tools. We will use these tools to develop three classes of gene expression controllers, which we will demonstrate in human immune cells, chosen for their important role in human physiology and their potential for cellular therapy: (1) Inducible controllers regulated by orthogonal, FDA-approved drugs. (2) Cell- autonomous controllers that sense and process biological stimuli, including ligand recognition by synthetic Notch receptors and microenvironmental cues. (3) Signal integration controllers that can perceive and integrate multiple biological signals to activate transcriptional programs. We anticipate that this toolkit will be broadly used by researchers to enable precision gene expression control across mammalian systems, including in biomedical applications of synthetic biology, cell reprogramming, and cell-based therapeutics. We will make our tools and design framework freely available to the academic scientific community.