SHF:Medium:Collaborative Research:Scaling Up Programmable and Algorithmic DNA Self-Assembly

SHF：中：合作研究：扩大可编程和算法 DNA 自组装

• 批准号: 1162459
• 负责人: Peng Yin
• 金额: $ 20万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1162459&HistoricalAwards=false
• 关键词: SHF; Medium; Collaborative; Research; Scaling

The dominant manufacturing paradigm for human technology has been ?top-down? construction of objects, in the sense that a large entity manipulates smaller entities to put them together into a functional device. For example, in an automotive factory, parts such as doors, windshields, wheels, seats, engines are separately manufactured and then brought together and assembled into a car by either humans or robots that know where each part should go and how it should be attached. In contrast, for billions of years biological organisms have constructed objects using a ?bottom-up? technology, in the sense that the pieces self-assemble or grow without outside assistance. For example, to make a complex molecular machine, enzymes within the cell might synthesize a number of proteins that then diffuse randomly until they bump into each other and click into place; while on a larger scale, a single cell might grow into an elephant. The bottom-up manufacturing paradigm has advantages that top-down methods are unlikely ever to achieve, such as the ability to create meter-scale objects from components with atomic-scale (nanometer) resolution and chemical functionality ? but it requires a level of exquisite control over molecular structure and function that human science and technology has not yet attained. We believe that the primary missing ingredient is information science and technology: information must be encoded within synthetic molecules to control their behavior and to create programmable molecular systems. In this research, the aim is to push the frontiers of information-based molecular self-assembly using DNA nanotechnology. The past fifteen years have seen the development of an abstract theory of algorithmic self-assembly (initiated by Winfree) that merges the mathematical theory of geometrical tiling, the statistical mechanical and kinetic theories of crystal growth, and the algorithmic theory of Turing machine computation. This theory shows how, in principle, synthetic DNA molecules called ?tiles? can be designed to carry information that directs their assembly into complex and sophisticated shapes and patterns. Just as a small program can produce a large and intricate output, a small tile set can result in the self-assembly of a large and intricate object ? the tile set is a ?program? for controlling the molecular self-assembly process. Laboratory experiments in the past fifteen years have demonstrated the foundations of this theory using DNA tile sets on the order of two dozen tile types, i.e. very small molecular programs.In the past year, a new molecular motif for DNA tiles (developed by Yin) has been used to self-assemble molecular structures using up to 1000 distinct tile types that each has a unique target position within the structure, like a self-assembled molecular-scale jigsaw puzzle. This is the simplest type of molecular program. A major goal of the proposed work is demonstrating that the new ?single strand tile? motif can be used to create significantly more complicated self-assembly programs than have been seen to date by reusing distinct tile types in many locations and in an algorithmic fashion, much like living systems that reuse the same molecules in many different ways. Sophisticated algorithmic tile reuse of two dozen to perhaps 1000 or more distinct components vastly expands the capabilities of self-assembly programs. To achieve this, proposed work will (a) improve techniques for an important ?subroutine? for controlling molecular growth, a binary counting process that terminates after growing a pre-specified distance; (b) develop methods and molecular structures for nucleating the growth of single-strand tiles with pre-specified information that serves as ?input? to the molecular program; (c) demonstrate algorithmic growth of single-strand tiles that perform Turing machine and/or cellular automaton computations; (d) investigate proofreading techniques for reducing the rate of errors during self-assembly; and (e) create software tools that facilitate the design and analysis of these complex molecular systems.

人类技术的主导制造范式一直是？自上而下？对象的构造，从这个意义上说，一个大的实体操纵小的实体，将它们放在一起，成为一个功能设备。例如，在一家汽车工厂，门、挡风玻璃、车轮、座椅、发动机等部件被单独制造，然后由人类或机器人组装成一辆汽车，这些人或机器人知道每个部件应该放在哪里，以及应该如何连接。相比之下，数十亿年来，生物有机体一直使用自下而上的方式构建物体。技术，从这个意义上说，这些部件在没有外部帮助的情况下自组装或生长。例如，为了制造一个复杂的分子机器，细胞内的酶可能会合成一些蛋白质，然后随机扩散，直到它们相互碰撞并就位；而在更大的范围内，单个细胞可能会成长为大象。自下而上的制造模式具有自上而下方法不太可能实现的优势，例如能够从具有原子级(纳米)分辨率和化学功能的组件创建米级对象？但它需要对分子结构和功能进行精细控制，这是人类科学和技术尚未达到的。我们认为，缺少的主要因素是信息科学和技术：信息必须在合成分子中编码，以控制它们的行为，并创建可编程的分子系统。在这项研究中，目的是利用DNA纳米技术推动基于信息的分子自组装的前沿。在过去的15年里，算法自组装的抽象理论(由Winfree发起)得到了发展，它融合了几何平铺的数学理论、晶体生长的统计力学和动力学理论以及图灵机计算的算法理论。这一理论表明，在原则上，合成的DNA分子是如何被称为瓷砖的？可以设计成携带信息，将它们组装成复杂和复杂的形状和图案。就像一个小程序可以产生大而复杂的输出一样，一个小的瓷砖集可以导致一个大而复杂的对象的自组装？这套瓷砖是一个程序？用于控制分子自组装过程。过去15年的实验室实验已经证明了这一理论的基础，使用了20多种瓦片类型的DNA瓦片集，即非常小的分子程序。在过去的一年里，一种新的DNA瓦片分子基序(由Yen开发)被用来自组装分子结构，使用多达1000种不同的瓦片类型，每种类型在结构中都有一个唯一的目标位置，就像一个自组装的分子尺度拼图。这是最简单的分子程序。拟议工作的一个主要目标是证明新的单股瓷砖？Motif可以用来创建比迄今看到的要复杂得多的自组装程序，方法是在许多位置以算法方式重复使用不同的瓷砖类型，就像生命系统以许多不同的方式重复使用相同的分子一样。复杂的算法瓦片重用24个到1000个或更多不同的组件，极大地扩展了自组装程序的能力。为了实现这一点，拟议的工作将(A)改进一个重要的子程序的技术？为了控制分子生长，一种在生长到预定距离后终止的二元计数过程；(B)开发方法和分子结构，以预先指定的信息作为输入？来成核单链瓷砖的生长。(C)展示执行图灵机和/或细胞自动机计算的单链瓷砖的算法增长；(D)研究减少自组装过程中错误率的校对技术；以及(E)创建有助于设计和分析这些复杂分子系统的软件工具。