Molecular programming : engineering chemical computing systems with DNA

Date

2020-10-09

Authors

Wang, Boya

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Abstract

After billions of years of evolution, nature gifts us versatile biological machines with complicated and robust behaviors. Can we understand and recapitulate the complexity of biology by de novo engineering biological systems? Can we integrate man-made knowledge or principles with the biology systems we try to build to achieve or go beyond the complexity of nature? The development of DNA nanotechnology has uncovered the uniqueness and the programmability of DNA molecules as a candidate for engineering complex molecular systems. The advances in the the field of DNA nanotechnology, such as building DNA computers, DNA therapeutic sensors, DNA amplifiers, DNA robots or DNA data storage are promising, yet the application is still in its infancy. This dissertation explores three topics. First of all, we engineer robust molecular information processing systems. We experimentally demonstrate a de novo engineered DNA cascade that is robust to errors. We theoretically analyze the taxonomy of low-error molecular cascades and the trade-offs between error and signal attenuation. We experimentally characterize different types of molecular interactions that lead to signal attenuation. Secondly, we develop in-memory and parallel computation with information stored in DNA. We theoretically design computation programs for binary counting and cellular automaton Rule 110, the latter of which is Turing universal. We experimentally establish the implementation of binary counting programs. Lastly, we experimentally program molecular computation at thermodynamic equilibrium. It is promising that the topics of the thesis will contribute to the further development of DNA nanotechnology.

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