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

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.Fundacion Botín, Banco de Santander through its Santander Universities Global Division [BES-2010-038940 to/nR.M., C.R.C.]; ERC SYNCOM [291294 to M.C.B.]; FPI MINECO fellowship [to S.D.N.]. Funding for open access charge: ERC SYNCOM [291294]