RNA circuits for cell state determination in mammalian cells in vitro and in vivo

 描述：生物学使用复杂的调节网络来感知和调节细胞状态。可以类似地控制基因表达的时间和位置的合成分子电路将在靶向疾病治疗、细胞重新编程等方面有重要的应用。然而，一种可靠的、可扩展的、通用的可编程基因表达的分子技术尚未被证明。在这里，我们提出了一种范式转换的方法来应对这一挑战：我们将开发基于RNA链置换的细胞生物计算机。到目前为止，链置换主要是在无细胞环境下用DNA寡核苷酸证明的。链置换已被有效地应用于无细胞DNA纳米技术，以构建复杂的多输入逻辑电路、可编程纳米结构和分子马达。由数百个DNA寡核苷酸组成的逻辑电路构成了迄今为止建造的最大的人造分子电路。事实上，目前还没有其他工程技术支持类似复杂、可扩展和模块化的分子电路的从头设计，这使得这种方法成为在细胞中进行生物计算的有趣候选方法。在这里，我们计划通过使用RNA而不是DNA来将链置换电路引入细胞环境，包括内源RNA和基于RNA的基因调节的传感器。通过利用上述转录因子和启动子的正向调控，我们可以快速构建更复杂的电路，细胞过程，从而可以更容易地传递。我们估计，链置换电路的编码可以比使用转录调控的等效电路的遗传编码紧凑10倍。DNA是信息存储媒介，而转录的RNA是信息处理媒介。我们的RNA部件经过精心设计，可通过专门的传感和驱动组件与细胞环境互动。我们将证明，原则上，任何内源细胞mRNA或miRNA都可以是输入，输出基因的表达可以通过RNA-RNA相互作用来调节。我们将构建多输入感官电路，提供关于细胞状态的高内容信息，并将其应用于了解体外和体内4T1小鼠乳腺癌模型的生物标记物水平和相关性。重要的是，我们能够以更小的DNA足迹编码高度复杂的遗传程序，这将使我们能够克服目前复杂电路在体内传递的限制。我们最初专注于将乳腺癌作为一个模型系统，但我们的技术可以很容易地适应其他生物标志物、癌症类型和疾病模型。事实上，我们认为这种基于合理设计方法的适应性是拟议技术的关键优势。我们预计，我们的技术将适用于许多其他需要检测、分析和控制细胞状态的应用，包括诊断和成像应用、对疾病模型的理解或多阶段分化的程序化控制。

 DESCRIPTION: Biology uses complex regulatory networks to sense and regulate cell state. Synthetic molecular circuits that can similarly control the timing and location of gene expression will have important applications in targeted disease therapy, cellular reprogramming, and beyond. However, a reliable, scalable, and general molecular technology for programmable gene expression has not yet been demonstrated. Here, we propose a paradigm shifting approach to this challenge: we will develop RNA strand displacement-based cellular bio computers. To date, strand displacement has primarily been demonstrated with DNA oligonucleotides in cell free settings. Strand displacement has been used effectively in cell-free DNA nanotechnology to build complex multi-input logic circuits, programmable nanostructures and molecular motors. Logic circuits made from hundreds of DNA oligonucleotides constitute the largest man-made molecular circuits built so far. In fact, there is currently no other engineering technology that supports de novo design of similarly complex, scalable and modular molecular circuitry, making this approach an intriguing candidate for performing biological computation in cells. Here we plan to bring strand displacement circuits to the cellular environment through the use of RNA instead of DNA, including sensors for endogenous RNA and RNA-based gene regulation. By foregoing the use of transcription factors and promoter regulation orthogonal with we can rapidly build more sophisticated circuits, cellular processes , which can be delivered more easily. We estimate that encoding of strand displacement circuits can be up to 10-fold more compact than genetic encoding of an equivalent circuit using transcriptional regulation. DNA serves as the information-storage medium, while transcribed RNA acts as the information- processing medium. Our RNA parts are engineered to interact with the cell milieu through specialized sensing and actuation components. We will demonstrate that, in principle, any endogenous cellular mRNA or miRNA can be an input, and that output gene expression can be regulated through RNA-RNA interactions. We will construct multi-input sensory circuits that provide high content information about cell state, and apply this for understanding biomarker levels and correlations for an in vitro and an in vivo 4T1 mouse breast cancer model. Importantly, our ability to encode highly sophisticated genetic programs with a much smaller DNA footprint will allow us to overcome current in vivo delivery limitations of complex circuitry. We initially focus on breast cancer as a model system but our technology can readily be adapted to other biomarkers, cancer types, and disease models. In fact, we believe that this adaptability, grounded in a rational design approach, is the key strength of the proposed technology. We expect that our technology will become relevant for many other applications that require sensing, analysis and control of cell state, including diagnostics and imaging applications, understanding of disease models, or programmed control of multi-stage differentiation.