Record Details

Programming complex behavior in dNA-based molecular circuits and robots [electronic resource] / Anupama Thubagere Jagadeesh ; Lulu Qian, advisor ; Richard M. Murray, co-advisor.
Pasadena, California : California Institute of Technology, 2017.
1 online resource (ix, 128 leaves) : digital (17 Mb), illustrations (some color).
CIT theses ; 2017
Integrated electronic circuits, like those found in cellphones and computers, are ubiquitous in our information-driven society. The success of electronics has, in part, been due its modular architecture that enables individual components to be independently improved while the overall device functionality remains unchanged. Over the last two decades the emerging field of dynamic DNA nanotechnology has been trying to apply the underlying philosophy of electronics to biochemical circuits. DNA nanotechnology employs rationally designed DNA molecules as building blocks of biochemical circuits that can, in principle, enable powerful applications like diagnostics and therapeutics. Researchers in the field of DNA nanotechnology have developed simple elements to construct biomolecular systems with desired functions. They have also developed molecular compilers for defining design principles. The cost of DNA synthesis has decreased by over three orders of magnitude in the past decade. This has lead to a non-trivial number of small scale circuits, like DNA-based logic gates and chemical oscillators, being implemented. However, the scalability of this approach has yet to be clearly demonstrated. n this thesis, we will discuss our main contributions to facilitating the advancement of DNA nanotechnology by developing systematic approaches for constructing modular DNA building blocks. These modules can be used to construct biochemical circuits and molecular robotic systems. The performance of the modules can be individually tuned and integrated into large-scale systems. Using automated circuit-design software and cheap unpurified DNA, we demonstrated the design and construction of a complex synthetic biochemical circuit consisting of 78 distinct DNA species. The circuit is capable of computing the transition rules of a cell updating its state based on its neighboring cells, defined in a classic computational model called cellular automata. Using a bottom-up approach, we first characterized the component necessary for basic Boolean logic computation. We then systematically integrated more circuit elements and eventually constructed the full circuit. By developing a systematic procedure for building DNA-based circuits using unpurified components, we significantly simplified the experimental procedure. By using unpurified DNA components, we reduced the cost and technical barrier for circuit construction, thus making the design and synthesis of complex DNA circuits accessible to even novice researchers. Next we demonstrated a cargo sorting DNA nano-robot, using a simple algorithm and modular building blocks. The DNA robot has a leg and two foot domains for exploring a two-dimensional DNA origami surface, and an arm and hand domain for picking up randomly located cargos and dropping them off at their designated locations. It is completely autonomous and is programmed to perform a random walk without requiring an external energy source. Further, we demonstrated sorting multiple copies of two distinct cargo species on the same origami. Additionally, by compartmentalizing each sorting task on a single origami, we showed that two distinct sorting tasks can be implemented on different origami simultaneously in the same test tube. The recognition of a cargo is embedded in its destination, therefore it is possible to scale up the system simply by having multiple types of cargos. The same robot design can be used for performing multiple instances of distinct tasks in parallel. The different modules can be integrated to perform diverse functions, including applications in time-release targeted therapeutics.
Advisor and committee chair names found in the thesis' metadata record in the digital repository.
Dissertation note:
Thesis (Ph. D.) -- California Institute of Technology, 2017.
Bibliography, etc. note:
Includes bibliographical references.
Linked resources:
Caltech Connect
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 Record created 2017-11-08, last modified 2018-09-17

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