Probing the characteristics of genetic circuits integrated in mammalian cells and

描述(申请人提供)：细胞中分子信号的复杂组合是包括癌症和遗传性疾病在内的多基因疾病的极好指标。能够检测这些情况的系统可以用作高度选择性的工具，用于以实现最佳和高度特定的保健的方式在单细胞水平上进行诊断、预防、治疗和监测。朝着这个方向，科学家们已经开发出了作为信息处理系统运行的第一代遗传电路。然而，这些原型的实用性和可扩展性受到单个细胞中不同电路组件之间化学计量比波动的阻碍。因此，构建复杂的表达单位是至关重要的，其基因产物将仅弱地依赖于细胞中的单位拷贝数和全局转录效率。然后，这些独立的单位可以合并成网络，预计在面对巨大的内部波动时能够可靠地发挥作用。我们认为，特定的网络体系结构(或拓扑)可以提供实现这一目标的解决方案。给定的一组通路元素的可能拓扑的数量很大，并且随着元素的数量呈指数增长，使得它们的详尽调查是不可见的。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。这些拓扑被称为“网络基元”，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。在初步实验的基础上，我们形成了这样的假设，即特定的生物网络基序家族可以用来减少噪音和细胞内活动的波动，最重要的是，减少拷贝数的可变性。通过拟议的实验进一步研究这些结果可以从根本上改变这一领域，并导致几种与健康相关的诊断和治疗应用。更广泛地说，由于许多人类疾病本质上是网络级现象，解开生物主题的属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性的合成基因电路，能够在面对巨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，我们的目标是利用构建块库和使用病毒递送和重组酶系统，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。为了验证我们的假设，我们将使用显微镜和流式细胞仪测量来表征遗传电路的噪声和拷贝数依赖关系。最后，我们建议实现第一代遗传电路，用于检测和监测内源性miRNA信号。我们的目标是表明，在电路中使用上述拓扑结构使其适合高通量监测，并提高了miRNA传感的准确性。 与公共健康相关：我们提出了特定电路体系结构的全面特征及其在第一代传感器中的实现，用于内源性信号检测和监测。这一结果将引发与公共健康相关的广泛应用，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.