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

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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.