Layered analysis and control of biochemical

reaction networks

Thomas P. Prescott? and Antonis Papachristodoulou Department of Engineering Science, University of Oxford, United Kingdom E-mail: thomas.prescott@dtc.ox.ac.uk

Abstract

The conceptual hierarchy of biological parts and modules 1 is an important design principle for engineering synthetic biological systems, or enhancing existing systems to have additional functional sophistication. Many researchers have suggested that the modular design princi- ple is mirrored in evolved biological systems, and a large amount of research has uncovered modular structures in large-scale biological systems. 2â??5 By decomposing such a system, its analysis and redesign can be decomposed into that of its subsystems and their interconnec- tion. Modules are a specific type of subsystem made up of groups of biochemical species which together perform a specific function. However, the mechanisms by which modules in- teract often result in retroactivity, 6 where the behaviour of isolated modules changes in the context of the overall system. This impedance effect can cause synthetic modules to behave differently to expectations. We propose an alternative approach to the characterisation of network structure, termed layering. 7,8 Subsystems (called layers) are defined as groups of reactions, where any number of layers can contribute to the evolution of each species. In existing networks, strategies for choosing the reaction partition include taking separation in

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timescale or spatial scale into account. An important consequence of the layering framework for Synthetic Biology is that it distinguishes retroactivity, which arises from overlaying mul- tiple layersâ?? contributions to the same species, from inter-layer dependencies. By making this distinction, the context of each synthetic layer is treated as an input, and its inputâ??output behaviour therefore remains the same in any context. Thus layering presents a flexible new design principle for engineering synthetic biological systems.

Keywords Biochemical reaction networks; Structure; Modularity; Retroactivity; Layers

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