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Complex cellular logic computation using ribocomputing devices

Author(s)
Green, Alexander A.; Kim, Jongmin; Ma, Duo; Silver, Pamela A.; Yin, Peng; Collins, James J.; ... Show more Show less
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Abstract
Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our ‘ribocomputing’ systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.
Date issued
2017-07
URI
http://hdl.handle.net/1721.1/119230
Department
Institute for Medical Engineering and Science; Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Synthetic Biology Center
Journal
Nature
Publisher
Nature Publishing Group
Citation
Green, Alexander A. et al. “Complex Cellular Logic Computation Using Ribocomputing Devices.” Nature 548, 7665 (July 2017): 117–121 © 2017 Nature Publishing Group
Version: Author's final manuscript
ISSN
0028-0836
1476-4687

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