A unified design space of synthetic stripe-forming networks

Synthetic biology is a promising tool to study the function and properties of gene regulatory networks. Gene circuits with predefined behaviours have been successfully built and modelled, but largely on a case-by-case basis. Here we go beyond individual networks and explore both computationally and...

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Bibliographic Details
Published in:Nature communications 2014-09, Vol.5 (1), p.4905-4905, Article 4905
Main Authors: Schaerli, Yolanda, Munteanu, Andreea, Gili, Magüi, Cotterell, James, Sharpe, James, Isalan, Mark
Format: Article
Language:English
Subjects:
38/35
631/553/2691
631/553/338/552
Base Sequence
Cloning, Molecular
Escherichia coli
Fluorescence
Gene Regulatory Networks - genetics
Genetic Engineering - methods
Humanities and Social Sciences
Models, Genetic
Molecular Sequence Data
multidisciplinary
Plasmids - genetics
Reverse Transcriptase Polymerase Chain Reaction
Science
Science (multidisciplinary)
Sequence Analysis, DNA
Synthetic Biology - methods
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Summary:Synthetic biology is a promising tool to study the function and properties of gene regulatory networks. Gene circuits with predefined behaviours have been successfully built and modelled, but largely on a case-by-case basis. Here we go beyond individual networks and explore both computationally and synthetically the design space of possible dynamical mechanisms for 3-node stripe-forming networks. First, we computationally test every possible 3-node network for stripe formation in a morphogen gradient. We discover four different dynamical mechanisms to form a stripe and identify the minimal network of each group. Next, with the help of newly established engineering criteria we build these four networks synthetically and show that they indeed operate with four fundamentally distinct mechanisms. Finally, this close match between theory and experiment allows us to infer and subsequently build a 2-node network that represents the archetype of the explored design space. Constructing gene circuits with predefined behaviours is typically done on a case-by-case basis. Schaerli et al. instead computationally explore the design space for 3-node networks that generate a stripe in response to a morphogen gradient, and build networks based on their simplest possible forms.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms5905