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

合作研究：SHF Medium：使用时间代码进行分子通信的语言

• 批准号: 2107246
• 负责人: Rebecca Schulman
• 金额: $ 60万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2107246&HistoricalAwards=false
• 关键词: Collaborative; Research; SHF; Medium; language

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.

分子编程是通过分子相互作用对信息进行编码和处理的学科。在DNA和RNA合成的进步的推动下，这一领域导致了利用生物分子存储信息的变革性方法的发展，无需显微镜进行诊断和“成像”的方法，利用合理设计的分子识别和治疗复杂诊断状态的方法，以及协调潜在材料、设备或药物的大型资料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海量信息存储和处理，加快治疗或疫苗开发，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在分子系统中传输信息的新方法来推动分子计算，该方法基于特定生物分子浓度的时间变化。时间程序将使用体外人工基因网络来制作和解码，在体外人工基因网络中，单个RNA分子将有能力携带在其浓度波动中编码的多个信息。由此产生的时间代码将允许生物分子组件相互通信，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植入式医疗设备之间的通信。这项研究将为生物工程和数据科学带来本科生和研究生教材的创新，并将通过为不同的本科生和K-12学生社区创造暑期研究机会，扩大对计算机科学研究的参与。该项目试图系统地了解如何通过采用控制论和计算机科学中现有的基本工程概念来设计能够识别化学输入信号的不同时间模式的生化电路。它将构建能够产生和识别日益复杂的时间输入模式的体外遗传电路，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。这些电路可以用来增加细胞或光敏材料中可以触发的反应范围，并开发生化工具，使研究活细胞如何产生和解释随时间变化的生化信号变得更容易。研究人员将在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的基础上建立能够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的生化电路的开发以及将它们与光和生物化学输入一起使用的工具的开发将对工程学、材料科学、生物学、生物化学、合成生物学和工程教育产生影响。 这一奖项反映了国家科学基金会的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。