Cooperativity to increase Turing pattern space for synthetic biology
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- dc.contributor.author Diambra, Luisca
- dc.contributor.author Senthivel, Vivek Raj, 1983-ca
- dc.contributor.author Bárcena Menéndez, Diego, 1984-ca
- dc.contributor.author Isalan, Markca
- dc.date.accessioned 2015-11-11T13:15:18Z
- dc.date.available 2015-11-11T13:15:18Z
- dc.date.issued 2015
- dc.description.abstract It is hard to bridge the gap between mathematical formulations and biological implementations of Turing patterns, yet this is necessary for both understanding and engineering these networks with synthetic biology approaches. Here, we model a reaction-diffusion system with two morphogens in a monostable regime, inspired by components that we recently described in a synthetic biology study in mammalian cells.1 The model employs a single promoter to express both the activator and inhibitor genes and produces Turing patterns over large regions of parameter space, using biologically interpretable Hill function reactions. We applied a stability analysis and identified rules for choosing biologically tunable parameter relationships to increase the likelihood of successful patterning. We show how to control Turing pattern sizes and time evolution by manipulating the values for production and degradation relationships. More importantly, our analysis predicts that steep dose-response functions arising from cooperativity are mandatory for Turing patterns. Greater steepness increases parameter space and even reduces the requirement for differential diffusion between activator and inhibitor. These results demonstrate some of the limitations of linear scenarios for reaction-diffusion systems and will help to guide projects to engineer synthetic Turing patterns.en
- dc.description.sponsorship M.I. is funded by FP7 ERC 201249 ZINC-HUBS and Wellcome Trust NIA 102944/Z/13/Z.en
- dc.format.mimetype application/pdfca
- dc.identifier.citation Diambra L, Senthivel VR, Menendez DB, Isalan M. Cooperativity to increase Turing pattern space for synthetic biology. ACS synthetic biology. 2015; 4(2): 177-186. DOI 10.1021/sb500233uca
- dc.identifier.doi http://dx.doi.org/10.1021/sb500233u
- dc.identifier.issn 2161-5063
- dc.identifier.uri http://hdl.handle.net/10230/25053
- dc.language.iso engca
- dc.publisher American Chemical Society (ACS)ca
- dc.relation.ispartof ACS synthetic biology. 2015; 4(2): 177-186
- dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/201249
- dc.rights © 2014 American Chemical Society. This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.en
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.subject.keyword Turing patternsen
- dc.subject.keyword Cooperativityen
- dc.subject.keyword Parameter spaceen
- dc.subject.keyword Synthetic biologyen
- dc.subject.other Biologia sintèticaca
- dc.subject.other Bioenginyeriaca
- dc.title Cooperativity to increase Turing pattern space for synthetic biologyen
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca