Computational design of digital and memory biological devices.
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Summary.We show how to use an automated procedure to design logic and sequential transcription circuits.This methodology will allow advancing the rational design of biological devices to more complex systems, and we propose the first design of a biological JK-latch memory device.
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PubMed Central - PubMed
Affiliation: Instituto de Biologia Molecular y Celular de Plantas, CSIC-Universidad Politecnica de Valencia, Valencia, Spain.
ABSTRACT
The use of combinatorial optimization techniques with computational design allows the development of automated methods to design biological systems. Automatic design integrates design principles in an unsupervised algorithm to sample a larger region of the biological network space, at the topology and parameter levels. The design of novel synthetic transcriptional networks with targeted behaviors will be key to understand the design principles underlying biological networks. In this work, we evolve transcriptional networks towards a targeted dynamics, by using a library of promoters and coding sequences, to design a complex biological memory device. The designed sequential transcription network implements a JK-Latch, which is fully predictable and richer than other memory devices. Furthermore, we present designs of transcriptional devices behaving as logic gates, and we show how to create digital behavior from analog promoters. Our procedure allows us to propose a scenario for the evolution of multi-functional genetic networks. In addition, we discuss the decomposability of regulatory networks in terms of genetic modules to develop a given cellular function. Summary. We show how to use an automated procedure to design logic and sequential transcription circuits. This methodology will allow advancing the rational design of biological devices to more complex systems, and we propose the first design of a biological JK-latch memory device. No MeSH data available. |
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Mentions: Multiple approaches are available to describe biological networks, particularly transcriptional circuits. We consider for this work a deterministic and continuous model to describe the regulatory interactions between genes. Further works will take into account stochastic effects on the system. A whole description of these networks considers all the species involved in the processes of transcription, translation, and regulation, such as DNA, mRNA and proteins (see Fig. 1). In general, a regulation between a transcription factor (repressor or activator) and a gene can be modeled according the following differential equations1\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$ \frac{\hbox{d}}{\hbox{d}t}[V] = \rho [U]^n - \sigma [V], $$\end{document}2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$ \frac{\hbox{d}}{\hbox{d}t}[D] = \mu [V:D] - \theta [V][D], $$\end{document}3\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$ \frac{\hbox{d}}{\hbox{d}t}[R] = \varphi [D] + \psi [V:D] - \lambda [R] - \delta [R], $$\end{document}4\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$ \frac{\hbox{d}}{\hbox{d}t}[Y] = \lambda [R] - \beta [Y], $$\end{document}where U is the non-active form of the regulator and V its active form (i.e., transcription factor). ρ and σ are the kinetic coefficients for n-merization. If a regulator does not n-merize, this description is also valid with U = V, n = 1, ρ = σ. D is the DNA, R the mRNA, and Y the folded protein from that regulated gene. θ and μ are the kinetic coefficients for binding and unbinding between the transcription factor and the promoter, respectively. φ and ψ are the transcriptional kinetics from free and occupied DNA, respectively. We assume that DNA is not degraded, mRNA does it with kinetics δ, and protein with β. λ is the translational kinetics. We have considered that the cellular resources, such as RNA-Polymerases, Ribosomes, nucleotides and amino-acids, are sufficient to sustain a synthetic system and could be assumed constant. Thus, the transcription and translation rates only depend on the amounts of DNA and mRNA, respectively. We add an additional mass balance equation,5\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$ [D_t]=[D]+[V:D], $$\end{document}as the amount of DNA within the cell is conserved. Those equations can be rewritten for more than one transcription factor.Fig. 1 |
View Article: PubMed Central - PubMed
Affiliation: Instituto de Biologia Molecular y Celular de Plantas, CSIC-Universidad Politecnica de Valencia, Valencia, Spain.
No MeSH data available.