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Automated design of gene circuits with optimal mushroom-bifurcation behaviour

View ORCID ProfileIrene Otero-Muras, View ORCID ProfileRuben Perez-Carrasco, View ORCID ProfileJulio R. Banga, View ORCID ProfileChris P. Barnes
doi: https://doi.org/10.1101/2022.05.09.490426
Irene Otero-Muras
1Computational Synthetic Biology Group. Institute for Integrative Systems Biology (UV, CSIC), Spanish National Research Council, 46980 Valencia, Spain
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  • For correspondence: r.perez-carrasco@imperial.ac.uk
Ruben Perez-Carrasco
2Department of Life Sciences. Imperial College London. London, UK
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Julio R. Banga
3Computational Biology Lab, MBG-CSIC, Spanish National Research Council, 36143 Pontevedra, Spain
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Chris P. Barnes
4Department of Cell and Developmental Biology, University College London, London, UK
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Abstract

Recent advances in synthetic biology are enabling exciting technologies, including the next generation of biosensors, the rational design of cell memory, modulated synthetic cell differentiation and generic multi-functional bio-circuits. These novel applications require the design of gene circuits leading to sophisticated behaviours and functionalities. At the same time, designs need to be kept minimal to avoid compromising cell viability. Bifurcation theory of dynamical systems provides powerful tools to address complex nonlinear dynamics and multifunctionality, linking model topology and kinetic parameters with circuit behaviour. However, the challenge of incorporating bifurcation analysis to automated design has not been accomplished so far. In this work we present an optimisation-based method for the automated forward design of synthetic gene circuits with specified bifurcation diagrams, allowing us to find minimal topologies optimizing the required functionalities and taking into account additional requirements and/or context specifications. We apply the method to design of gene circuits exhibiting the so called mushroom bifurcation, a relatively unexplored multi-functional behaviour of particular relevance for developmental biology. Using the results of the optimisation analysis we explore the capabilities of the resulting circuits for possible applications in advanced biosensors, memory devices, and synthetic cell differentiation.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • * irene.otero.muras{at}csic.es

  • ↵† r.perez-carrasco{at}imperial.ac.uk

  • ↵‡ j.r.banga{at}csic.es

  • ↵§ christopher.barnes{at}ucl.ac.uk

  • https://zenodo.org/record/6024249

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted May 10, 2022.
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Automated design of gene circuits with optimal mushroom-bifurcation behaviour
Irene Otero-Muras, Ruben Perez-Carrasco, Julio R. Banga, Chris P. Barnes
bioRxiv 2022.05.09.490426; doi: https://doi.org/10.1101/2022.05.09.490426
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Automated design of gene circuits with optimal mushroom-bifurcation behaviour
Irene Otero-Muras, Ruben Perez-Carrasco, Julio R. Banga, Chris P. Barnes
bioRxiv 2022.05.09.490426; doi: https://doi.org/10.1101/2022.05.09.490426

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