AF: SHF: Small: Adaptive molecular computation using buffered strand displacement networks

AF：SHF：小：使用缓冲链位移网络的自适应分子计算

基本信息

批准号：
1525553
负责人：
Matthew Lakin
金额：
$ 45万
依托单位：
University of New Mexico
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1525553&HistoricalAwards=false
关键词：
AF SHF Small Adaptive molecular

项目摘要

Learning and adaptation are fundamental processes in living systems. Human beings are clearly capable of learning complex concepts, but even unicellular organisms such as bacteria are capable of adaptive response to external stimuli. This suggests that synthetic systems of biomolecules could, in principle, be developed to enable sustained operation and exhibit similar adaptive behaviors. Thanks to advances in the tools developed in the fields of biotechnology and nanotechnology, it is now becoming possible to engineer such systems in the laboratory. This project will study the design and experimental implementation of synthetic DNA-based information processing systems that exhibit adaptive behaviors such as learning. Successful completion of this research will enable future development of synthetic biochemical systems capable of sustained operation, which could have practical applications such as long-term health monitoring, as well as providing insights into the biochemical basis of learning in biological systems. The project will support training and education of undergraduate and graduate students.This project will study learning and adaptation in synthetic biochemical systems implemented using DNA strand displacement reactions. In DNA strand displacement reaction networks, multi-strand DNA "gate" structures are used to process information that is encoded using single strands of DNA, by binding to freely-diffusing single strands and releasing other single strands into solution in response. In this project, a particular class of DNA strand displacement gates known as "buffered gates" will be developed. A buffered gate is one where a large quantity of gates start in an inactive state and a subset are activated to carry out their computational task: once each gate is consumed, in addition to its usual outputs the gate also releases a strand to activate a new gate from the buffer, so the population of active gates remains roughly constant. In this project, buffered gate systems will be studied in simulation and in the laboratory. Crucially, buffered gate systems in which one gate controls the availability of activating strands for another buffered gate will be studied. This will enable information to be stored and updated with the molecular system, thereby enabling adaptive behavior. This concept will be used as the fundamental design building block to implement molecular computing systems capable of adaptive behavior in response to externally-provided input signals. The goal of this project will be to design, simulate and implement molecular logic systems that demonstrate adaptive behavior, for example, implementing supervised learning algorithms.

学习和适应是生命系统的基本过程。人类显然有能力学习复杂的概念，但即使是细菌等单细胞生物也能够对外部刺激做出适应性反应。这表明原则上可以开发生物分子的合成系统以实现持续运行并表现出类似的适应性行为。由于生物技术和纳米技术领域开发的工具的进步，现在在实验室中设计此类系统已成为可能。该项目将研究基于合成 DNA 的信息处理系统的设计和实验实施，该系统表现出学习等适应性行为。这项研究的成功完成将使未来能够开发出能够持续运行的合成生化系统，该系统可以具有长期健康监测等实际应用，并为生物系统学习的生化基础提供见解。该项目将支持本科生和研究生的培训和教育。该项目将研究使用 DNA 链置换反应实现的合成生化系统的学习和适应。在 DNA 链置换反应网络中，多链 DNA“门”结构用于处理使用单链 DNA 编码的信息，通过与自由扩散的单链结合并将其他单链释放到溶液中作为响应。在这个项目中，将开发一类特殊的 DNA 链置换门，称为“缓冲门”。缓冲门是指大量门以非活动状态启动并激活一个子集来执行其计算任务的门：一旦每个门被消耗，除了其通常的输出之外，门还会释放一条链来激活新的链。门来自缓冲区，因此活动门的数量大致保持不变。在这个项目中，缓冲门系统将在模拟和实验室中进行研究。至关重要的是，我们将研究缓冲门系统，其中一个门控制另一个缓冲门激活链的可用性。这将使信息能够通过分子系统进行存储和更新，从而实现适应性行为。这一概念将用作基本设计构建模块，以实现能够响应外部提供的输入信号而做出自适应行为的分子计算系统。该项目的目标是设计、模拟和实现展示自适应行为的分子逻辑系统，例如实现监督学习算法。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Robust Heterochiral Strand Displacement Using Leakless Translators

使用无泄漏翻译器实现稳健的异手性链置换

DOI：
10.1021/acssynbio.0c00131
发表时间：
2020-07
期刊：
ACS Synthetic Biology
影响因子：
4.7
作者：
Mallette, Tracy L.;Stojanovic, Milan N.;Stefanovic, Darko;Lakin, Matthew R.
通讯作者：
Lakin, Matthew R.

Domain-Specific Programming Languages for Computational Nucleic Acid Systems

计算核酸系统的特定领域编程语言

DOI：
10.1021/acssynbio.0c00050
发表时间：
2020-07
期刊：
ACS Synthetic Biology
影响因子：
4.7
作者：
Lakin, Matthew R.;Phillips, Andrew
通讯作者：
Phillips, Andrew

Microcompartments for Protection and Isolation of Nanoscale DNA Computing Elements

用于保护和隔离纳米级 DNA 计算元件的微室

DOI：
10.1021/acsami.9b03143
发表时间：
2019-03
期刊：
ACS Applied Materials & Interfaces
影响因子：
9.5
作者：
Fabry;Fetrow, Madalyn Elise;Oloyede, Ayomide;Yang, Kyung;Stojanovic, Milan N.;Stefanovic, Darko;Graves, Steven W.;Carroll, Nick J.;Lakin, Matthew R.
通讯作者：
Lakin, Matthew R.

Sequential super-resolution imaging using DNA strand displacement

使用 DNA 链位移的连续超分辨率成像

DOI：
10.1371/journal.pone.0203291
发表时间：
2018-08
期刊：
PLOS ONE
影响因子：
3.7
作者：
Pallikkuth, Sandeep;Martin, Cheyenne;Farzam, Farzin;Edwards, Jeremy S.;Lakin, Matthew R.;Lidke, Diane S.;Lidke, Keith A.;Abraham, Thomas
通讯作者：
Abraham, Thomas

A Logic Programming Language for Computational Nucleic Acid Devices

计算核酸器件的逻辑编程语言