Gene expression plays a central role in the orchestration of cellular processes. The use of inducible promoters to change the expression level of a gene from its physiological level has significantly contributed to the understanding of the functioning of regulatory networks. However, from a quantitative point of view, their use is limited to short-term, population-scale studies to average out cell-to-cell variability and gene expression noise and limit the nonpredictable effects of internal feedback loops that may antagonize the inducer action. Here, we show that, by implementing an external feedback loop, one can tightly control the expression of a gene over many cell generations with quantitative accuracy. To reach this goal, we developed 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 osmostress responsive promoter and playing with the osmolarity of the cells environment, we show that long-term control can, indeed, be achieved for both time-constant and time-varying target profiles at the population and even the single-cell levels. Importantly, we provide evidence that real-time control can dynamically limit the effects of gene expression stochasticity. We anticipate that our method will be useful to quantitatively probe the dynamic properties of cellular processes and drive complex, synthetically engineered networks.model based control | computational biology | high osmolarity glycerol pathway | quantitative systems biology U nderstanding the information processing abilities of biological systems is a central problem for systems and synthetic biology (1-6). The properties of a living system are often inferred from the observation of its response to static perturbations. Timevarying perturbations have the potential to be much more informative regarding the dynamics of cellular functions (7-12). Currently, it is not possible to precisely perturb protein levels in an analogous manner, even though this perturbation would be instrumental in our understanding of gene regulatory networks. Indeed, despite the development of novel regulatory systems, including various RNA-based solutions (13), transcriptional control by means of inducible promoters is still the preferred method for manipulating protein levels (14, 15). Unfortunately, inducible promoters have several generic limitations. First, there is a significant delay between gene expression activation and effective protein synthesis. Second, many cellular processes can interfere with gene expression through internal feedback loops whose effects are hard to predict. Third, the process of gene expression shows significant levels of noise (16)(17)(18). Given these limitations, novel experimental strategies are required to gain quantitative, real-time control of gene expression in vivo.Here, we see the...

Regulation of the cellular volume is fundamental for cell survival and function. Deviations from equilibrium trigger dedicated signaling and transcriptional responses that mediate water homeostasis and volume recovery. Cells are densely packed with proteins, and molecular crowding may play an important role in cellular processes. Indeed, increasing molecular crowding has been shown to modify the kinetics of biochemical reactions in vitro; however, the effects of molecular crowding in living cells are mostly unexplored. Here, we report that, in yeast, a sudden reduction in cellular volume, induced by severe osmotic stress, slows down the dynamics of several signaling cascades, including the stress-response pathways required for osmotic adaptation. We show that increasing osmotic compression decreases protein mobility and can eventually lead to a dramatic stalling of several unrelated signaling and cellular processes. The rate of these cellular processes decreased exponentially with protein density when approaching stalling osmotic compression. This suggests that, under compression, the cytoplasm behaves as a soft colloid undergoing a glass transition. Our results shed light on the physical mechanisms that force cells to cope with volume fluctuations to maintain an optimal protein density compatible with cellular functions.