Probing the characteristics of genetic circuits integrated in mammalian cells and

描述（由申请人提供）：细胞中分子信号的复杂组合是多基因疾病（包括癌症和遗传性疾病）的极好指标。能够检测这些病症的系统可以用作在单细胞水平上以实现最佳和高度特异性的健康护理的方式进行诊断、预防、治疗和监测的高度选择性工具。朝着这个方向，科学家们已经开发出第一代遗传电路，作为信息处理系统。然而，这些原型的实用性和可扩展性受到单个电池中电路的不同组件之间的化学计量波动的阻碍。因此，构建复杂的表达单位是至关重要的，其基因产物将仅微弱地依赖于细胞中的单位拷贝数和整体转录效率。 这些独立的单位然后可以合并成网络，预计在面对巨大的内部波动时可以可靠地运作。我们认为，特定的网络架构（或拓扑结构）可能会提供实现这一目标的解决方案。对于一组给定的路径元素，可能的拓扑结构的数量很大，并且随着元素的数量呈指数级增长，使得它们的详尽调查变得无形。幸运的是，最近的研究发现，某些拓扑比其他拓扑出现得更频繁。这些拓扑结构被称为“网络基序”，由相对较少的元素组成，并作为“模块”或“节点”嵌入较大的网络和路径中。 基于初步的实验，我们形成了这样的假设，即生物网络基序的特定家族可以用于减少细胞内活性的噪声和波动，最重要的是，减少拷贝数的变异性。进一步研究这些结果与拟议的实验可以从根本上改变该领域，并导致几个健康相关的诊断和治疗应用。更一般地说，由于许多人类疾病本质上是网络层面的现象，解开生物基序的特性是理解人类生物学的核心。 我们的长期目标是构建功能性和可扩展的合成基因电路，能够在面对大的内部波动时执行预定的功能。拟议的目标将使我们更接近这一目标。更具体地说，我们的目标是在哺乳动物细胞中构建和整合一系列反馈和前馈基序电路，利用构建模块库并使用病毒递送和重组酶系统。为了验证我们的假设，我们将使用显微镜和流式细胞术测量来表征遗传电路的噪声和拷贝数依赖性。最后，我们建议实现第一代基因电路，用于检测和监测内源性miRNA信号。我们的目的是表明，在电路中使用上述拓扑结构使它们适合于高通量监测，并提高了miRNA传感的准确性。 公共卫生相关性：我们提出了一个全面的表征特定的电路架构及其实施在第一代传感器的内源性信号检测和监测。这些结果将引发与公共卫生相关的广泛应用，特别是以可靠的方式监测和处理细胞内信号。

DESCRIPTION (provided by applicant): Complex combinations of molecular signals in cells are an excellent indicator of multi-gene disorders, including cancers and hereditary diseases. A system capable to detect these conditions may be used as a highly selective tool for diagnosis, prevention, treatment, and monitoring at a single-cell level in ways that achieve optimal and highly specific health-care. Towards this direction, scientists have developed first generation genetic circuits that operate as information-processing systems. However, the utility and scalability of these prototypes is hampered by fluctuations in stoichiometry between different components of the circuit in individual cells. Therefore, it is critical to construct sophisticated expression units whose gene product will depend only weakly on the number of unit copies in a cell and on the global transcription efficiency. Such stand-alone units could then be combined into networks that could be expected to function reliably in the face of large internal fluctuations. We argue that particular network architectures (or topologies) may provide the solution towards this goal. The number of possible topologies for a given set of pathway elements is large and it grows exponentially with the number of elements, making their exhaustive investigation intangible. Fortunately, recent research has uncovered that certain topologies appear more frequently than others. Those topologies, named "network motifs", are composed of relatively few elements and are embedded as "modules" or "nodes" in larger networks and pathways. Based on preliminary experiments, we form the hypothesis that specific families of biological network motifs can be used to reduce noise and fluctuations in intracellular activity and most importantly, the copy number variability. Further investigation of these results with the proposed experiments can radically change the field and lead to several health-related diagnostic and therapeutic applications. More generally, as many human diseases are essentially network-level phenomena, unraveling properties of biological motifs is central to understanding human biology. Our long-term objective is to construct functional and scalable synthetic gene circuits able to perform predetermined functions in the face of large internal fluctuations. The proposed aims will bring us considerably closer to this objective. More specifically, we aim to construct and integrate in mammalian cells a range of feedback and feedforward motif circuits, utilizing a library of building blocks and using both viral delivery and recombinase systems. In order to test our hypothesis, we will characterize the noise and copy number dependence of the genetic circuits using microscopy and flow cytometry measurements. Finally, we propose to implement a first generation of genetic circuits for detection and monitoring of endogenous miRNA signals. We aim to show that the use of the aforementioned topologies in the circuits renders them suitable for high- throughput monitoring and yields increased accuracy in the miRNA sensing. PUBLIC HEALTH RELEVANCE: We propose a comprehensive characterization of specific circuit architectures and their implementation in first generation sensors for endogenous signal detection and monitoring. The results will spark a wide range of applications relevant to public health and specific to monitoring and processing intracellular signals in a reliable manner.