A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology.

Max Carbonell-Ballestero, Salva Duran-Nebreda, Raúl Montañez, Ricard Solé, Javier Macía, Carlos Rodríguez-Caso

Index: Nucleic Acids Res. 42(22) , 14060-9, (2014)

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Abstract

Within the field of synthetic biology, a rational design of genetic parts should include a causal understanding of their input-output responses-the so-called transfer function-and how to tune them. However, a commonly adopted strategy is to fit data to Hill-shaped curves without considering the underlying molecular mechanisms. Here we provide a novel mathematical formalization that allows prediction of the global behavior of a synthetic device by considering the actual information from the involved biological parts. This is achieved by adopting an enzymology-like framework, where transfer functions are described in terms of their input affinity constant and maximal response. As a proof of concept, we characterize a set of Lux homoserine-lactone-inducible genetic devices with different levels of Lux receptor and signal molecule. Our model fits the experimental results and predicts the impact of the receptor's ribosome-binding site strength, as a tunable parameter that affects gene expression. The evolutionary implications are outlined. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.