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Published December 26, 2018 | Supplemental Material + Published
Journal Article Open

Effective design principles for leakless strand displacement systems

Abstract

Artificially designed molecular systems with programmable behaviors have become a valuable tool in chemistry, biology, material science, and medicine. Although information processing in biological regulatory pathways is remarkably robust to error, it remains a challenge to design molecular systems that are similarly robust. With functionality determined entirely by secondary structure of DNA, strand displacement has emerged as a uniquely versatile building block for cell-free biochemical networks. Here, we experimentally investigate a design principle to reduce undesired triggering in the absence of input (leak), a side reaction that critically reduces sensitivity and disrupts the behavior of strand displacement cascades. Inspired by error correction methods exploiting redundancy in electrical engineering, we ensure a higher-energy penalty to leak via logical redundancy. Our design strategy is, in principle, capable of reducing leak to arbitrarily low levels, and we experimentally test two levels of leak reduction for a core "translator" component that converts a signal of one sequence into that of another. We show that the leak was not measurable in the high-redundancy scheme, even for concentrations that are up to 100 times larger than typical. Beyond a single translator, we constructed a fast and low-leak translator cascade of nine strand displacement steps and a logic OR gate circuit consisting of 10 translators, showing that our design principle can be used to effectively reduce leak in more complex chemical systems.

Additional Information

© 2018 National Academy of Sciences. Published under the PNAS license. Edited by Ronald R. Breaker, Yale University, New Haven, CT, and approved November 9, 2018 (received for review April 20, 2018). PNAS published ahead of print December 13, 2018. B.W. and D.S. were supported by NSF Grants CCF-1618895 and CCF-1652824. C.T. and E.W. acknowledge support from NSF Grants CCF/HCC-1213127, CCF-1317694, and CCF/SHF-1718938 and the Gordon and Betty Moore Foundation's Programmable Molecular Technology Initiative. C.T. also thanks the Natural Sciences and Engineering Research Council of Canada for a Banting Fellowship. A.D.E. was supported by NSF Grant DBI-0939454, International Funding Agency Grant ERASynBio 1541244, and Welch Foundation Grant F-1654. Author contributions: B.W., C.T., E.W., and D.S. designed research; B.W. performed research; B.W., C.T., A.D.E., E.W., and D.S. analyzed data; and B.W., C.T., E.W., and D.S. wrote the paper. The authors declare no conflict of interests. This article is a PNAS Direct Submission. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1806859115/-/DCSupplemental.

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Published - E12182.full.pdf

Supplemental Material - pnas.1806859115.sapp.pdf

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