Literature DB >> 24495737

Dynamic DNA-toolbox reaction circuits: a walkthrough.

Alexandre Baccouche1, Kevin Montagne2, Adrien Padirac3, Teruo Fujii3, Yannick Rondelez4.   

Abstract

In living organisms, the integration of signals from the environment and the molecular computing leading to a cellular response are orchestrated by Gene Regulatory Networks (GRN). However, the molecular complexity of in vivo genetic regulation makes it next to impossible to describe in a quantitative manner. Reproducing, in vitro, reaction networks that could mimic the architecture and behavior of in vivo networks, yet lend themselves to mathematical modeling, represents a useful strategy to understand, and even predict, the function of GRN. In this paper, we define a set of in vitro, DNA-based molecular transformations that can be linked to each other in such a way that the product of one transformation can activate or inhibit the production of one or several other DNA compounds. Therefore, these reactions can be wired in arbitrary networks. This approach provides an experimental way to reproduce the dynamic features of genetic regulation in a test tube. We introduce the rules to design the necessary DNA species, a guide to implement the chemical reactions and ways to optimize the experimental conditions. We finally show how this framework, or "DNA toolbox", can be used to generate an inversion module, though many other behaviors, including oscillators and bistable switches, can be implemented.
Copyright © 2014 Elsevier Inc. All rights reserved.

Keywords:  Chemical oscillators; DNA toolbox; Enzymatic circuit; Molecular programming; Reaction networks

Mesh:

Substances:

Year:  2014        PMID: 24495737     DOI: 10.1016/j.ymeth.2014.01.015

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  20 in total

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9.  Fuel-Driven Transient DNA Strand Displacement Circuitry with Self-Resetting Function.

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10.  A small-molecule chemical interface for molecular programs.

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Journal:  Nucleic Acids Res       Date:  2021-07-21       Impact factor: 16.971

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