By implementing an external feedback loop one can tightly control the expression of a gene over many cell generations with quantitative accuracy. Controlling precisely the level of a protein of interest will be useful to probe quantitatively the dynamical properties of cellular processes and to drive complex, synthetically-engineered networks. In this chapter we describe a platform for real-time closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells environment, and original software for automated imaging, quantification, and model predictive control. By using an endogenous osmo-stress responsive promoter and playing with the osmolarity of the cells environment, we demonstrate that long-term control can indeed be achieved for both time-constant and time-varying target profiles, at the population level, and even at the single-cell level.
Model predictive control Gene expression High-osmolarity glycerol (HOG) pathway Computational biology Quantitative systems and synthetic biology
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We acknowledge the support of the Agence Nationale de la Recherche (under the references DiSiP-ANR-07-JCJC-0001 and ICEBERG-ANR-10-BINF-06-01), of the Région Ile de France (C’Nano-ModEnv), of the Action d’Envergure ColAge from INRIA/INSERM (Institut Nationale de la Santé et de la Recherche Médicale), of the MechanoBiology Institute, and of the Laboratoire International Associé CAFS (Cell Adhesion France-Singapour).
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