Collaborative Research: SHF Medium: A language for molecular communication using temporal codes

分子编程是通过分子相互作用编码和处理信息的学科。通过DNA和RNA合成的进步，这一领域已经导致了使用生物分子存储信息的变革性方法的发展，在没有显微镜的情况下进行诊断和“成像”的方法，用合理设计的分子识别和处理复杂诊断状态的方法，以及协调潜在材料，设备或药物的大型库的合成和评估的方法。进一步扩大分子程序的能力有望实现大规模信息存储和处理，加速治疗或疫苗开发，并完全自动化化学和材料合成和处理。该项目将通过开发一种基于特定生物分子浓度随时间变化的分子系统中传输信息的新方法来推进分子计算。时间程序将使用体外人工基因网络产生和解码，其中单个RNA分子将有能力携带在其浓度波动中编码的多种信息。由此产生的时间代码将允许生物分子组件彼此通信以协调它们的努力，从而允许开发集成分子设备。这些方法可以用于生物工程的其他领域，例如用于生物分子过程和可植入医疗设备之间的通信。 由此产生的研究将为生物工程和数据科学带来本科和研究生教育材料的创新，并将扩大参与计算机科学研究，创造夏季研究机会，以多样化的社区本科生和K-12名学生。本项目旨在系统地了解如何设计生化电路，通过采用现有的基本原理，控制理论和计算机科学的工程概念。它将构建体外遗传电路，可以生成和识别越来越复杂的时间输入模式，以验证和优化我们的方法。然后将采用电路来检测光和不同生物分子信号的时间变化。这些电路可用于增加细胞或光敏材料中可触发的反应范围，并开发生物化学工具，使研究活细胞如何产生和解释随时间变化的生物化学信号变得更容易。研究人员将利用他们在1）计算机科学和集成生化系统设计以及2）信号处理和反馈控制方面的合作经验和互补专业知识，构建可以解释离散和连续域信号及其组合的电路。能够识别特定时间输入的新生化电路的开发以及将其与光和生化输入一起使用的工具的开发将影响工程，材料科学，生物学，生物化学，合成生物学和工程教育。  该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。

Molecular programming is the discipline of encoding and processing information through molecular interactions. Enabled by advances in DNA and RNA synthesis, this field has led to the development of transformative methods to store information using biomolecules, methods to perform diagnostics and “imaging” without a microscope, methods to recognize and treat complex diagnostic states with rationally designed molecules, as well as methods to orchestrate the synthesis and assessment of large libraries of potential materials, devices or drugs. Further scaling up the capabilities of molecular programs promises to enable massive information storage and processing, to accelerate therapeutic or vaccine development, and to fully automate chemical and materials synthesis and processing. This project will advance molecular computing by developing a new approach to transmitting information in molecular systems that is based on temporal changes in the concentrations of specific biomolecules. Temporal programs will be produced and decoded using in-vitro artificial gene networks, where individual RNA molecules will have the capacity to carry multiple messages encoded in the fluctuations of their concentration. The resulting temporal codes will allow biomolecular components to communicate with one another to coordinate their efforts, allowing the development of integrated molecular devices. These methods could be used in other areas of bioengineering, such as for communication between biomolecular processes and implantable medical devices. The resulting research will bring innovation in undergraduate and graduate educational material for bioengineering and data science, and will broaden participation in computer science research by creating summer research opportunities to a diverse community of undergraduates and K-12 students.This project seeks to systematically understand how to design biochemical circuits that can recognize different temporal patterns of chemical input signals by adopting existing fundamental engineering concepts from control theory and computer science. It will construct in-vitro genetic circuits that can generate and recognize temporal input patterns of increasing complexity to validate and optimize our approach. Circuits will then be adopted for the detection of temporal variations in light and different biomolecular signals. These circuits could be used to increase the range of responses that can be triggered in cells or in light-sensitive materials, and to develop biochemical tools to make it easier to study how living cells produce and interpret time-varying biochemical signals. The investigators will build on their collaborative experience and complementary expertise in 1) computer science and integrated biochemical systems design and 2) signal processing and feedback control to build circuits that can interpret both discrete and continuous domain signals as well as their combinations. The development of new biochemical circuits capable of recognizing specific temporal inputs and the development of tools to use them with light and biochemical inputs will impact engineering, materials science, biology, biochemistry, synthetic biology and engineering education.  This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.