Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Kanagawa 226-8503, Japan.
Acc Chem Res. 2011 Dec 20;44(12):1369-79. doi: 10.1021/ar200128b. Epub 2011 Oct 19.
Creating artificial biological systems is an important research endeavor. Each success contributes to synthetic biology and adds to our understanding of the functioning of the biomachinery of life. In the construction of large, complex systems, a modular approach simplifies the design process: a multilayered system can be prepared by integrating simple modules. With the concept of modularity, a variety of synthetic biological systems have been constructed, both in vivo and in vitro. But to properly develop systems with desired functions that integrate multiple modules, researchers need accurate mathematical models. In this Account, we review the development of a modularized artificial biological system known as RTRACS (reverse transcription and transcription-based autonomous computing system). In addition to modularity, model-guided predictability is an important feature of RTRACS. RTRACS has been developed as an in vitro artificial biological system through the assembly of RNA, DNA, and enzymes. A fundamental module of RTRACS receives an input RNA with a specific sequence and returns an output RNA with another specific sequence programmed in the main body, which is composed of DNA and enzymes. The conversion of the input RNA to the output RNA is achieved through a series of programmed reactions performed by the components assembled in the module. Through the substitution of a subset of components, a module that performs the AND operation was constructed. Other logical operations could be constructed with RTRACS modules. An integration of RTRACS modules has allowed the theoretical design of more complex functions, such as oscillation. The operations of these RTRACS modules were readily predicted with a numerical simulation based on a mathematical model using realistic parameters. RTRACS has the potential to model highly complex systems that function like a living cell. RTRACS was designed to be integrated with other molecules or molecular devices, for example, aptazymes, cell-free expression systems, and liposomes. For the integration of these new modules, the quantitative controls of each module based on the numerical simulation will be instructive. The capabilities of RTRACS promise to provide models of complex biomolecular systems that are able to detect the environment, assess the situation, and react to overcome the situation. Such a smart biomolecular system could be useful in many applications, such as drug delivery systems.
构建人工生物系统是一项重要的研究工作。每一次成功都为合成生物学做出了贡献，并增进了我们对生命生物机械功能的理解。在构建大型复杂系统时，模块化方法简化了设计过程：可以通过整合简单的模块来制备多层系统。通过模块化的概念，已经构建了各种体内和体外的合成生物学系统。但是，为了正确开发具有所需功能的集成多个模块的系统，研究人员需要准确的数学模型。在本报告中，我们回顾了模块化人工生物系统 RTRACS（逆转录和基于转录的自主计算系统）的发展。除了模块化，模型引导的可预测性是 RTRACS 的一个重要特征。RTRACS 是通过组装 RNA、DNA 和酶作为体外人工生物系统开发的。RTRACS 的一个基本模块接收具有特定序列的输入 RNA，并返回主体中编程的另一个具有特定序列的输出 RNA，该主体由 DNA 和酶组成。通过在模块中组装的组件执行的一系列编程反应，将输入 RNA 转换为输出 RNA。通过替换组件的子集，构建了执行 AND 操作的模块。可以使用 RTRACS 模块构建其他逻辑操作。RTRACS 模块的集成允许对更复杂的功能（例如振荡）进行理论设计。使用基于使用实际参数的数学模型的数值模拟可以轻松预测这些 RTRACS 模块的操作。RTRACS 具有模拟功能类似于活细胞的高度复杂系统的潜力。RTRACS 的设计目的是与其他分子或分子设备集成，例如适体酶、无细胞表达系统和脂质体。为了集成这些新模块，基于数值模拟的每个模块的定量控制将具有指导意义。RTRACS 的功能有望提供能够检测环境、评估情况并做出反应以克服情况的复杂生物分子系统模型。这样的智能生物分子系统在许多应用中可能很有用，例如药物输送系统。
