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。合成的分子电路可以类似地控制基因表达的时间和位置，这将在靶向疾病治疗、细胞重编程等方面具有重要的应用。然而，用于可编程基因表达的可靠的、可扩展的和通用的分子技术尚未得到证实。在这里，我们提出了一个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中用DNA寡核苷酸证明的。链置换已被有效地用于无细胞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从头设计类似的复杂，可扩展和模块化的分子电路，使这种方法成为在细胞中进行生物计算的有趣候选者。在这里，我们计划通过使用RNA而不是DNA，将链置换电路引入细胞环境，包括内源性RNA和基于RNA的基因调控的传感器。通过前述使用转录因子和启动子调控正交与我们可以快速建立更复杂的电路，细胞过程，可以更容易地交付。我们估计，编码的链置换电路可以高达10倍更紧凑的遗传编码的等效电路，使用转录调控。DNA作为信息存储介质，而转录的RNA作为信息处理介质。我们的RNA部分被设计成通过专门的传感和驱动组件与细胞环境相互作用。我们将证明，原则上，任何内源性细胞mRNA或miRNA都可以是输入，并且输出基因表达可以通过RNA-RNA相互作用进行调节。我们将构建多输入感觉电路，提供有关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志物水平和相关性。重要的是，我们用更小的DNA足迹编码高度复杂的遗传程序的能力将使我们能够克服复杂电路的体内传递限制。我们最初专注于乳腺癌作为模型系统，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，我们相信这种基于合理设计方法的适应性是所提出的技术的关键优势。我们希望我们的技术将与许多其他需要传感，分析和控制细胞状态的应用相关，包括诊断和成像应用，疾病模型的理解或多阶段分化的程序控制。

 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.