title: Iterative experiment design guides the characterization of a light-inducible gene expression circuit.
abstract: Systems biology rests on the idea that biological complexity can be better unraveled through the interplay of modeling and experimentation. However, the success of this approach depends critically on the informativeness of the chosen experiments, which is usually unknown a priori. Here, we propose a systematic scheme based on iterations of optimal experiment design, flow cytometry experiments, and Bayesian parameter inference to guide the discovery process in the case of stochastic biochemical reaction networks. To illustrate the benefit of our methodology, we apply it to the characterization of an engineered light-inducible gene expression circuit in yeast and compare the performance of the resulting model with models identified from nonoptimal experiments. In particular, we compare the parameter posterior distributions and the precision to which the outcome of future experiments can be predicted. Moreover, we illustrate how the identified stochastic model can be used to determine light induction patterns that make either the average amount of protein or the variability in a population of cells follow a desired profile. Our results show that optimal experiment design allows one to derive models that are accurate enough to precisely predict and regulate the protein expression in heterogeneous cell populations over extended periods of time.
authors.affiliation: Automatic Control Laboratory, ETH Zurich, CH-8092 Zurich, Switzerland;
authors.forename: Jakob
authors.initials: J
authors.lastname: Ruess
authors.affiliation: Automatic Control Laboratory, ETH Zurich, CH-8092 Zurich, Switzerland;
authors.forename: Francesca
authors.initials: F
authors.lastname: Parise
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Milias-Argeitis
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland.
authors.forename: Mustafa
authors.initials: M
authors.lastname: Khammash
authors.affiliation: Automatic Control Laboratory, ETH Zurich, CH-8092 Zurich, Switzerland; lygeros@control.ee.ethz.ch.
authors.forename: John
authors.initials: J
authors.lastname: Lygeros
mesh_terms: D005786:Gene Expression Regulation; D008027:Light; D013269:Stochastic Processes; D049490:Systems Biology
keywords: in vivo control; light-induced gene expression; optimal experiment design; parameter inference; stochastic kinetic models