EMT/BSSE Synthetic Biological Integrated Circuits for Computing

EMT/BSSE 计算用合成生物集成电路

• 批准号: 1129098
• 负责人: Gregory Timp
• 金额: $ 19.91万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1129098&HistoricalAwards=false
• 关键词: EMT; BSSE; Synthetic; Biological; Integrated

EMT/BSSE: Synthetic Biological Integrated Circuits for ComputingAbstractSynthetic biology promises a new paradigm for information processing. By rewiring gene networks, the molecular biology of the cell can be co-opted to produce all the modules used for computation. Moreover, these modules can be produced in very large numbers inexpensively from a single bacterium literally overnight by designing circuits with built-in antibiotic resistance. But the promise of synthetic biology for information processing won?t be realized until engineered gene networks operating in different cells can be assembled into integrated circuits to reliably express a computing function. The prospects for a biological integrated circuit hinge on solutions to three problems: control over the microenvironment of the cell, which affects signal transmission and timing; the difficulty of cascading elements due to the long response time evident in the synthesized gene circuits; and the stochastic noise that develops from biochemical reactions involving a small number of molecules. In this research, the investigators synthesize gene circuits designed for high sensitivity and high signal-to-noise protein production, transform bacteria with them, and then assemble the different bacteria with submicron precision into large arrays using molecular signals to wire them together to express a complex computing function. The researchers sort through a succession of gene circuits using directed evolution in pursuit of sensitivity and stability with respect to noise. To efficiently produce proteins with high signal-to-noise ratio without excessive energy, they leverage a protocol that uses MazF, an mRNA interferase, to produce only the proteins of interest in living E. coli and otherwise arrest cell growth. Once the gene networks are designed and tested, the different bacteria are assembled on a hydrogel scaffold with submicron precision into 3D circuits using optical tweezers.

摘要合成生物学为信息处理提供了一种新的范式。通过重新连接基因网络，细胞的分子生物学可以协同产生用于计算的所有模块。此外，通过设计内置抗生素抗性的电路，这些模块可以在一夜之间从单个细菌中大量廉价地生产出来。但是合成生物学在信息处理方面的承诺赢了吗？直到在不同细胞中运行的工程基因网络可以组装成集成电路来可靠地表达计算功能，才能实现。生物集成电路的前景取决于三个问题的解决方案：对细胞微环境的控制，它会影响信号的传输和定时；在合成的基因电路中，级联元件由于响应时间长而存在困难；随机噪声是由涉及少量分子的生化反应产生的。在这项研究中，研究人员合成了为高灵敏度和高信噪比蛋白质生产而设计的基因电路，用它们转化细菌，然后用分子信号将不同的细菌以亚微米精度组装成大型阵列，将它们连接在一起，以表达复杂的计算功能。研究人员利用定向进化对一系列基因回路进行排序，以追求对噪音的敏感性和稳定性。为了在不消耗过多能量的情况下有效地产生高信噪比的蛋白质，他们利用了一种使用MazF（一种mRNA干扰酶）的方案，只在活的大肠杆菌中产生感兴趣的蛋白质，否则就会阻止细胞生长。一旦基因网络被设计和测试，不同的细菌被组装在一个亚微米精度的水凝胶支架上，使用光学镊子形成3D电路。