DNA Computation in Cells
DNA Computation in Cells
批准号:
1617041
负责人:
Alexander Deiters
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-06-01 至 2021-05-31
关键词:
中文摘要
DNA逻辑门是强大的计算设备,因为输出在化学上等同于输入,并且一个门的输出可以作为后续门的输入-类似于电子门。这使得门的串行连接成为可能,产生信号级联,这些信号级联可以组装成基于核酸杂交的复杂分子电路,其中编码程序和运行程序的机器都由DNA组成。使用合成DNA作为人类细胞中生物计算的材料有几个优点:DNA电路依赖于完全可编程的沃森-克里克碱基配对相互作用,因此可以在分子水平上进行合理设计,提供高度的控制。新的组件,如门,放大器和子网络可以很容易地编码在DNA序列中,这提供了模块性和适应性。 研究目标的完成将导致广泛适用的方法,可编程的生物计算设备,在人类细胞中发挥作用。开发的方法将是感兴趣的科学家谁是开发或应用DNA可编程算法或组件的生物系统;此外,他们将促进与microRNA生物学领域的相互作用。DNA计算过程的输出可以很容易地与细胞和生物系统接口,从而将这种方法的影响扩展到更广泛的应用中。此外,与用于分析microRNA模式的传统技术相比,所提出的生物计算电路制造成本低廉且易于组装。由于其多学科性质,该项目将培养下一代学生在寡核苷酸,寡核苷酸化学和细胞生物学编程。为了激发儿童(及其父母)对STEM的兴趣,特别是在计算机科学、生物学和化学的交叉领域,将在博物馆和学校开展基于专业知识的推广活动。本研究将测试细胞microRNA模式检测、分析和设备响应功能是否可以结合到基于DNA的计算电路中。这将代表直接在活细胞内分析microRNA模式的创新方法。基于DNA的电路的输出信号不限于电或光输出(如在传统检测和分析方法的情况下),而是可以被设计为寡核苷酸、荧光团、染料和其他分子。一个创新的基于DNA模拟的生物计算系统将被开发,以保护编码的寡核苷酸程序免受生物环境的影响,高度特异性的自组装能力将为生命系统中的下一代分子计算设备提供灵活的设计。将追求以下研究目标:(1)展示活细胞中日益复杂的DNA计算,(2)将细胞DNA计算与信号放大相结合,(3)设计细胞DNA计算以提供分子输出,以及(4)使用新材料编码寡核苷酸程序以保护DNA设备免受细胞环境的影响。
英文摘要
DNA logic gates are powerful computation devices because the outputs are chemically equivalent to the inputs, and the output of one gate can act as the input for a subsequent gate - similar to electronic gates. This enables serial connections of gates, generating signaling cascades that can be assembled into complex molecular circuits based on nucleic acid hybridization where both the encoded program and the machinery that runs the program are composed of DNA. The use of synthetic DNA as a material for biocomputing in human cells has several advantages: DNA circuits rely on fully programmable Watson-Crick base-pairing interactions and thus can be rationally designed at the molecular level, delivering a high degree of control. New components, such as gates, amplifiers, and sub-networks can be readily encoded in DNA sequences, which provides modularity and adaptability. The completion of the research objectives will lead to broadly applicable approaches to programmable biological computation devices that are functional in human cells. The developed methodologies will be of interest to scientists who are developing or applying DNA-programmable algorithms or assemblies to biological systems; furthermore, they will facilitate interactions with the field of microRNA biology. The outputs of the DNA computation process can be readily interfaced with cellular and organismal systems, thus extending the impact of this methodology into broader applications. In addition, the proposed biocomputing circuitry is inexpensive to manufacture and easy to assemble - in contrast to traditional techniques for the analysis of microRNA patterns. Due to its multidisciplinary nature, this project will train the next generation of students in the programming in oligonucleotides, oligonucleotide chemistry, and cell biology. Based on developed expertise, outreach activities with museums and schools will be conducted in order to excite children at a young age (and their parents) about STEM, specifically at the interface of computer science, biology, and chemistry.This research will test if cellular microRNA pattern detection, analysis, and response functions of devices can be combined in DNA-based computation circuitry. This will represent an innovative approach to the analysis of microRNA patterns directly inside of live cells. Output signals of DNA-based circuits are not restricted to electrical or optical outputs (as in case of traditional detection and analysis methods), but can be designed as oligonucleotides, fluorophores, dyes, and other molecules. An innovative DNA-analog based biocomputing system will be developed in order to protect the encoded oligonucleotide programs from biological environments and highly specific self-assembly capabilities will provide flexible designs for next-generation molecular computation devices in living systems. The following research objectives will be pursued: (1) demonstrate DNA computing of increasing complexity in live cells, (2) interface cellular DNA computing with signal amplification, (3) engineer cellular DNA computing to provide molecular outputs, and (4) use new materials to encode oligonucleotide programs in order to protect the DNA devices from cellular environments.
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会议论文
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