Introduction of synthetic circuits into microbes creates competition between circuit and host genes for shared cellular resources, such as ribosomes. This can lead to the emergence of unwanted coupling between the expression of different circuit genes, complicating the design process and potentially leading to circuit failure. By expressing a synthetic 16S rRNA with altered specificity, we can partition the ribosome pool into host-specific and circuit-specific activities. We show mathematically and experimentally that the effects of resource competition can be alleviated by targeting genes to different ribosomal pools. This division of labour can be used to increase flux through a metabolic pathway. We develop a model of cell physiology which is able to capture these observations and use it to design a dynamic resource allocation controller. When implemented, this controller acts to decouple genes by increasing orthogonal ribosome production as the demand for translational resources by a synthetic circuit increases.

Introduction of synthetic circuits into microbes creates competition between circuit and host genes for shared cellular resources, such as ribosomes. This can lead to the emergence of unwanted coupling between the expression of different circuit genes, complicating the design process and potentially leading to circuit failure. By expressing a synthetic 16S rRNA with altered specificity, we can partition the ribosome pool into host-specific and circuit-specific activities. We show mathematically and experimentally that the effects of resource competition can be alleviated by targeting genes to different ribosomal pools. This division of labour can be used to increase flux through a metabolic pathway. We develop a model of cell physiology which is able to capture these observations and use it to design a dynamic resource allocation controller. When implemented, this controller acts to decouple genes by increasing orthogonal ribosome production as the demand for translational resources by a synthetic circuit increases.

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The use of orthogonal ribosomes in combination with dynamic resource allocation controllers is a promising approach for relieving the negative effects of cellular resource limitations on the modularity of synthetic gene circuits. Here, we develop a detailed mechanistic model of gene expression and resource allocation, which when simplified to a tractable level of complexity, allows the rational design of translational resource allocation controllers. Analysis of this model reveals a fundamental design trade-off; that reducing coupling acts to decrease gene expression. Through a sensitivity analysis of the experimentally tuneable controller parameters, we identify how each controller design parameter affects the overall closed-loop behaviour of the system, leading to a detailed set of design guidelines for optimally managing this trade-off. Based on our designs, we evaluated a number of alternative potential experimental implementations of the proposed system using commonly available biological components. Finally, we show that the controller is capable of dynamically allocating ribosomes as needed to restore modularity in a number of more complex synthetic circuits, such as the repressilator, and activation cascades composed of multiple interacting modules.

Recent research in Synthetic Biology has highlighted the potential of translational resource allocation controllers to improve circuit modularity by dynamically allocating finite cellular resources in response to fluctuating circuit demands. The design of such controllers is complicated by the significant levels of parametric uncertainty that arise in their biological implementations. Tools from robust control, such as µ-analysis, can be used to determine the robustness of controller designs to parametric uncertainty, but require further development to allow their application to biomolecular control systems, which are typically highly non-linear, and contain multiple uncertainties that cannot be represented using the standard linear fractional transformation formalism. Here, we show how an LFT (Linear Fractional Transformation)-free formulation of the µ-analysis problem can be used to analyse and compare the robustness of alternative potential implementations of a translational resource allocation controller that utilises orthogonal 'circuit-specific' ribosomes to translate circuit genes. Our results provide useful guidelines for the construction of robust resource allocation circuitry for multiple future biotechnological applications.

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No abstract

The use of orthogonal ribosomes in combination with dynamic resource allocation controllers is a promising approach for relieving the negative effects of cellular resource limitations on the modularity of synthetic gene circuits. Here, we develop a detailed mechanistic model of gene expression and resource allocation, which when simplified to a tractable level of complexity, allows the rational design of translational resource allocation controllers. Analysis of this model reveals a fundamental design trade-off; that reducing coupling acts to decrease gene expression. Through a sensitivity analysis of the experimentally tuneable controller parameters, we identify how each controller design parameter affects the overall closed-loop behaviour of the system, leading to a detailed set of design guidelines for optimally managing this trade-off. Based on our 1 designs, we evaluated a number of alternative potential experimental implementations of the proposed system using commonly available biological components. Finally, we show that the controller is capable of dynamically allocating ribosomes as needed to restore modularity in a number of more complex synthetic circuits, such as the repressilator, and activation cascades composed of multiple interacting modules.