A multitude of cell screening assays for diagnostic and research applications rely on quantitative measurements of a sample in the presence of different reagent concentrations. Standard methods rely on microtiter plates of varying well density, which provide simple and standardized sample addressability. However, testing hundreds of chemical dilutions requires complex automation, and typical well volumes of microtiter plates are incompatible with the analysis of a small number of cells. Here, we present a microfluidic device for creating a high-resolution chemical gradient spanning 200 nanoliter wells. Using air-based shearing, we show that the individual wells can be compartmentalized without altering the concentration gradient, resulting in a large set of isolated nanoliter cell culture wells. We provide an analytical and numerical model for predicting the concentration within each culture chamber and validate it against experimental results. We apply our system for the investigation of yeast cell metabolic gene regulation in the presence of different ratios of galactose/glucose concentrations and successfully resolve the nutrient threshold at which the cells activate the galactose pathway.
Cellular protein homeostasis requires continuous monitoring of stress in the endoplasmic reticulum (ER). Stress-detection networks control protein homeostasis by mitigating the deleterious effects of protein accumulation, such as aggregation and misfolding, with precise modulation of chaperone production. Here, we develop a coarse model of the unfolded protein response in yeast and use multi-objective optimization to determine which sensing and activation strategies optimally balance the trade-off between unfolded protein accumulation and chaperone production. By comparing a stress-sensing mechanism that responds directly to the level of unfolded protein in the ER to a mechanism that is negatively regulated by unbound chaperones, we show that chaperone-mediated sensors are more efficient than sensors that detect unfolded proteins directly. This results from the chaperone-mediated sensor having separate thresholds for activation and deactivation. Finally, we demonstrate that a sensor responsive to both unfolded protein and unbound chaperone does not further optimize homeostatic control. Our results suggest a strategy for designing stress sensors and may explain why BiP-mitigated ER stress-sensing networks have evolved.
Cellular protein homeostasis requires continuous monitoring of stress in the endoplasmic reticulum (ER). Stress detection networks control protein homeostasis by mitigating the deleterious effects of protein accumulation, such as aggregation and misfolding, with precise modulation of chaperone production. Here, we develop a coarse model of the unfolded protein response in yeast, and use multi-objective optimization to determine which sensing and activation strategies optimally balance the trade-off between unfolded protein accumulation and chaperone production. By comparing a stress-sensing mechanism that responds directly to the level of unfolded protein in the ER to a mechanism that is negatively regulated by unbound chaperones, we show that chaperone-mediated sensors are more efficient than sensors that detect unfolded proteins directly. This results from the chaperone-mediated sensor having separate thresholds for activation and deactivation. Lastly, we demonstrate that a sensor responsive to both unfolded protein and unbound chaperone does not further optimize homeostatic control. Our results suggest a strategy for designing stress sensors and may explain why BiP-mitigated ER stress sensing networks have evolved.keywords: unfolded protein response; endoplasmic reticulum stress; feedback; pareto optimization; biological sensor . CC-BY 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
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