Amorphous computation with transcription logic gates

使用转录逻辑门进行非晶计算

• 批准号: 8128479
• 负责人: Andrew D Ellington
• 金额: $ 30.05万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8128479
• 关键词: Address; Algorithms; Analog Computers; Base Sequence; Behavior; Binding; Biological; Biological Process; Biology; Blood Platelets; Cells; Coin; Complex; Computer Systems; Computer software; Computers; DNA; DNA Structure; Detection; Development; Devices; Diagnostic; Diffuse; Diffusion; Disease; Drosophila genus; Eating; Elements; Embryonic Development; Engineering; Feedback; Future; Generations; Genetic; Genetic Transcription; Hormones; Hydrolysis; Individual; Insulin; Kinetics; Knowledge; Lead; Learning; Logic; Memory; Modeling; Molecular; Molecular Computations; Molecular Computers; Molecular Conformation; Morphogenesis; Nanotechnology; Nucleic Acids; Nucleic acid sequencing; Organism; Output; Pattern; Pattern Formation; Platelet-Derived Growth Factor; Positioning Attribute; Process; Proteins; RNA; Reaction; Research; Research Personnel; Running; Signal Transduction; Structure; Surface; System; Testing; Time; Work; base; commercial application; cytokine; nanoscale; operation; programs; promoter; public health relevance; research study; response; self assembly; sensor; software development; sugar; two-dimensional; Address; Algorithms; Analog Computers; Base Sequence; Behavior; Binding; Biological; Biological Process; Biology; Blood Platelets; Cells; Coin; Complex; Computer Systems; Computer software; Computers; DNA; DNA Structure; Detection; Development; Devices; Diagnostic; Diffuse; Diffusion; Disease; Drosophila genus; Eating; Elements; Embryonic Development; Engineering; Feedback; Future; Generations; Genetic; Genetic Transcription; Hormones; Hydrolysis; Individual; Insulin; Kinetics; Knowledge; Lead; Learning; Logic; Memory; Modeling; Molecular; Molecular Computations; Molecular Computers; Molecular Conformation; Morphogenesis; Nanotechnology; Nucleic Acids; Nucleic acid sequencing; Organism; Output; Pattern; Pattern Formation; Platelet-Derived Growth Factor; Positioning Attribute; Process; Proteins; RNA; Reaction; Research; Research Personnel; Running; Signal Transduction; Structure; Surface; System; Testing; Time; Work; base; commercial application; cytokine; nanoscale; operation; programs; promoter; public health relevance; research study; response; self assembly; sensor; software development; sugar; two-dimensional

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.

要研究的基本概念是如何适应生物学，以合理地编程，以便更容易地为各种研究和商业应用设计分子和最终的生物。广泛的遗传可编程性将需要一种新型的生物计算机。麻省理工学院研究人员创造了“无定形计算机”一词，以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，有限的记忆力，本地通信，没有对位置的先验知识，并且没有同步时钟。描述为“无定形”是APROPOS-从无形的，看似无组织的质量中出现在此类计算机上执行的算法的结果。为了实施实用的无定形计算，我们已经建模并开始构建转录逻辑门的二维阵列。实际上，从一个启动子扩散转录的RNA分子与另一个启动子结合，并激活它或灭活。这种转录逻辑门的优点是地址空间本质上与核酸序列空间（缩放到4N）一样大。将建立在广义平台的无定形计算平台上的里程碑包括：1。开发可再现的测试台以在表面上进行编程。 2。从固定的“切换”开关中生成图案。 3。产生编程行为：体育场波。 4。信号扩增和传感器功能。通过开发依赖于扩散的算法，信息丰富的分子来启动栅极结构，我们开始构建运行模块化遗传软件的生物计算机。我们在开发该软件时获得的原则将产生远远超出任何单个算法或实例化的影响。二维阵列和随附的分子计算将成为建模和试验复杂信息系统中的反应扩散动力学的测试床。除了能够从分子传感器的信号放大（里程碑4）之外，这些实验还解决了纳米技术的关键问题之一：如何对复杂设备的自组装进行编程。 公共卫生相关性：我们建议开发一种新型的分子计算机，一台无定形计算机。这台计算机将像生物一样操作：单个处理器（如细胞）将被编程以根据可扩散信号（例如激素，胰岛素）进行有限的操作（例如吃糖）。但是，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分子在处理器的状态和功能之间移动。我们建议一种构造新型计算机的分级方法，从标准化的测试构建，通过静态演示模式形成到模式形成的动态演示，以作为血液，血小板衍生的生长因子中重要蛋白质的传感器作为传感器。我们开发的新遗传计算机将是模块化的，可扩展，并将创建一个新的范式，从而可以合理地开发生物软件。这些询问的结果应有助于了解发展，包括在疾病形成期间有时发育有时会出现问题，并可能有助于建造纳米级设备进行治疗和诊断。