Amorphous computation with transcription logic gates

要研究的基本概念是如何使生物学适应合理的可编程性，以便分子和最终的生物体可以更容易地被设计用于各种研究和商业应用。广泛的遗传可编程性将需要一种新型的生物计算机。术语“无定形计算机”是由麻省理工学院的研究人员创造的，用来描述由大量相同的计算机组成的计算系统，每个计算机都具有有限的处理能力，有限的内存，本地通信，没有位置的先验知识，也没有同步时钟。“无定形”的描述是恰当的-在这样的计算机上执行的算法的结果从一个无形的，看似无组织的质量中出现。为了实现实际的，无定形的计算，我们已经建模，并开始建立二维阵列的转录逻辑门。在实践中，从一个启动子转录的RNA分子扩散，结合到另一个启动子上，并激活它或使其无效。这种转录逻辑门的优点是地址空间基本上与核酸序列空间一样大（缩放到4 n）。将建立一个通用平台的无定形计算的里程碑包括：1。开发一个可重复的测试平台，用于在表面上编程。2.从固定的“拨动”开关生成模式。3.产生一个程序化的行为：体育场波。4.信号放大和传感器功能。通过开发依赖于可扩散的、信息丰富的分子来驱动门结构的算法，我们开始建造运行模块化遗传软件的生物计算机。我们在开发这个软件时获得的原则将产生远远超出任何单个算法或实例的影响。二维阵列和伴随的分子计算将成为复杂信息系统中反应扩散动力学建模和实验的试验平台。除了能够放大来自分子传感器的信号（里程碑4），这些实验还解决了纳米技术中的一个关键问题：如何编程复杂设备的自组装。 公共卫生相关性：我们建议开发一种新型的分子计算机，一种无定形计算机。这台计算机将像生物体一样运行：单个处理器（如细胞）将被编程，根据可扩散的信号（如激素、胰岛素）执行有限的一组操作（如吃糖）。然而，我们将使用DNA元素作为处理器，而不是细胞。DNA元件将使可扩散的RNA分子在处理器之间移动，并改变处理器的状态和功能。我们提出了一个分级的方法来构建我们的新型计算机，从一个标准化的测试平台，通过静态演示模式形成的动态演示模式形成的应用程序作为传感器的一个重要的蛋白质在血液中，血小板衍生生长因子。我们开发的新的基因计算机将是模块化和可扩展的，并将创造一个新的范式，允许生物软件的合理开发。这些调查的结果应该有助于了解发展，包括在疾病形成过程中发展有时是如何出错的，并可能有助于构建用于治疗和诊断的纳米级设备。

The basic concept to be investigated is how to adapt biology to being rationally programmable, so that molecules and eventually organisms can be more readily engineered for a variety of research and commercial applications. Extensive genetic programmability will require a new type of biological computer. The term "amorphous computer" was coined by MIT researchers to describe computing systems comprised of very large numbers of identical computers each of which possessed limited processing power, limited memory, local communcation, no a priori knowledge of position, and no synchronizing clock. The description as "amorphous" is apropos - the results of algorithms executing on such computers emerge from a shapeless, seemingly unorganized, mass. In order to implement practical, amorphous computations, we have modeled and are beginning to build two-dimensional arrays of transcriptional logic gates. In practice, RNA molecules transcribed from one promoter diffuse, bind to another promoter, and either activate it or inactivate it. The advantages of such transcriptional logic gates is that the address space is essentially as large as nucleic acid sequence space (scaling to 4n). Milestones that will build towards a generalized platform for amorphous computation include: 1. Developing a reproducible testbed for programming on surfaces. 2. Pattern generation from immobilized 'toggle' switches. 3. Generating a programmed behavior: the stadium wave. 4. Signal amplification and sensor function. By developing algorithms that rely upon diffusible, information rich molecules to actuate gate structures we are beginning to build biological computers that run modular genetic software. The principles that we acquire in developing this software will have an impact well beyond any individual algorithms or instantiations. The 2-D arrays and accompanying molecular computations will become a testbed for both modeling and experimenting with reaction-diffusion kinetics in complex informational systems. Beyond enabling amplification of signals from molecular sensors (Milestone 4), these experiments also address one of the key problems in nanotechnology: how to program the self-assembly of complex devices. PUBLIC HEALTH RELEVANCE: We propose to develop a new type of molecular computer, an amorphous computer. This computer will operate much like organisms do: individual processors (like cells) will be programmed to carry out a limited set of operations (like eating sugar) based on diffusible signals (like the hormone, insulin). However, instead of cells we will use DNA elements as the processors. The DNA elements will make diffusible RNA molecules that will move between, and alter the state and function of, the processors. We suggest a graded approach to the construction of our new type of computer, building from a standardized testbed through a static demonstration of pattern formation to a dynamic demonstration of pattern formation to the application as a sensor for an important protein in the blood, platelet-derived growth factor. The new genetic computer that we develop will be modular and expandable, and will create a new paradigm that allows for the rational development of biological software. The results of these inquiries should help understand development, including how development sometimes goes awry during disease formation, and may assist with building nanoscale devices for therapy and diagnostics.