Caroline B. Adiels

Sustained glycolytic oscillations in individual isolated yeast cells

Yeast glycolytic oscillations have been studied since the 1950s in cell‐free extracts and intact cells. For intact cells, sustained oscillations have so far only been observed at the population level, i.e. for synchronized cultures at high biomass concentrations. Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. This is the first time that sustained limit‐cycle oscillations have been demonstrated in isolated yeast cells.

Osmostress-induced cell volume loss delays yeast Hog1 signaling by limiting diffusion processes and by Hog1-specific effects.

Signal transmission progresses via a series of transient protein-protein interactions and protein movements, which require diffusion within a cell packed with different molecules. Yeast Hog1, the effector protein kinase of the High Osmolarity Glycerol pathway, translocates transiently from the cytosol to the nucleus during adaptation to high external osmolarity. We followed the dynamics of osmostress-induced cell volume loss and Hog1 nuclear accumulation upon exposure of cells to different NaCl concentrations. While Hog1 nuclear accumulation peaked within five minutes following mild osmotic shock it was delayed up to six-fold under severe stress. The timing of Hog1 nuclear accumulation correlated with the degree of cell volume loss and the cells capacity to recover. Also the nuclear translocation of Msn2, the transcription factor of the general stress response pathway, is delayed upon severe osmotic stress suggesting a general phenomenon. We show by direct measurements that the general diffusion rate of Hog1 in the cytoplasm as well as its rate of nuclear transport are dramatically reduced following severe volume reduction. However, neither Hog1 phosphorylation nor Msn2 nuclear translocation were as much delayed as Hog1 nuclear translocation. Our data provide direct evidence that signaling slows down during cell volume compression, probably as a consequence of molecular crowding. Hence one purpose of osmotic adaptation is to restore optimal diffusion rates for biochemical and cell biological processes. In addition, there may be mechanisms slowing down especially Hog1 nuclear translocation under severe stress in order to prioritize Hog1 cytosolic targets.

Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels

Background: Little is known about the signaling dynamics of AMP-activated protein kinase. Results: We define the dynamics of yeast AMPK signaling under different glucose concentrations. Conclusion: The Snf1-Mig1 signaling system monitors glucose concentration changes and absolute glucose levels to adjust the metabolism to a wide range of conditions. Significance: This description of AMPK signaling dynamics will stimulate studies defining the integration of signaling and metabolism. Analysis of the time-dependent behavior of a signaling system can provide insight into its dynamic properties. We employed the nucleocytoplasmic shuttling of the transcriptional repressor Mig1 as readout to characterize Snf1-Mig1 dynamics in single yeast cells. Mig1 binds to promoters of target genes and mediates glucose repression. Mig1 is predominantly located in the nucleus when glucose is abundant. Upon glucose depletion, Mig1 is phosphorylated by the yeast AMP-activated kinase Snf1 and exported into the cytoplasm. We used a three-channel microfluidic device to establish a high degree of control over the glucose concentration exposed to cells. Following regimes of glucose up- and downshifts, we observed a very rapid response reaching a new steady state within less than 1 min, different glucose threshold concentrations depending on glucose up- or downshifts, a graded profile with increased cell-to-cell variation at threshold glucose concentrations, and biphasic behavior with a transient translocation of Mig1 upon the shift from high to intermediate glucose concentrations. Fluorescence loss in photobleaching and fluorescence recovery after photobleaching data demonstrate that Mig1 shuttles constantly between the nucleus and cytoplasm, although with different rates, depending on the presence of glucose. Taken together, our data suggest that the Snf1-Mig1 system has the ability to monitor glucose concentration changes as well as absolute glucose levels. The sensitivity over a wide range of glucose levels and different glucose concentration-dependent response profiles are likely determined by the close integration of signaling with the metabolism and may provide for a highly flexible and fast adaptation to an altered nutritional status.

Allosteric regulation of phosphofructokinase controls the emergence of glycolytic oscillations in isolated yeast cells

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three‐dimensional state‐space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP.

Hydrodynamic Cell Trapping for High Throughput Single-Cell Applications

The possibility to conduct complete cell assays under a precisely controlled environment while consuming minor amounts of chemicals and precious drugs have made microfluidics an interesting candidate for quantitative single-cell studies. Here, we present an application-specific microfluidic device, cellcomb, capable of conducting high-throughput single-cell experiments. The system employs pure hydrodynamic forces for easy cell trapping and is readily fabricated in polydimethylsiloxane (PDMS) using soft lithography techniques. The cell-trapping array consists of V-shaped pockets designed to accommodate up to six Saccharomyces cerevisiae (yeast cells) with the average diameter of 4 μm. We used this platform to monitor the impact of flow rate modulation on the arsenite (As(III)) uptake in yeast. Redistribution of a green fluorescent protein (GFP)-tagged version of the heat shock protein Hsp104 was followed over time as read out. Results showed a clear reverse correlation between the arsenite uptake and three different adjusted low = 25 nL min−1, moderate = 50 nL min−1, and high = 100 nL min−1 flow rates. We consider the presented device as the first building block of a future integrated application-specific cell-trapping array that can be used to conduct complete single cell experiments on different cell types.

Entrainment of heterogeneous glycolytic oscillations in single cells

Cell signaling, gene expression, and metabolism are affected by cell-cell heterogeneity and random changes in the environment. The effects of such fluctuations on cell signaling and gene expression have recently been studied intensively using single-cell experiments. In metabolism heterogeneity may be particularly important because it may affect synchronisation of metabolic oscillations, an important example of cell-cell communication. This synchronisation is notoriously difficult to describe theoretically as the example of glycolytic oscillations shows: neither is the mechanism of glycolytic synchronisation understood nor the role of cell-cell heterogeneity. To pin down the mechanism and to assess its robustness and universality we have experimentally investigated the entrainment of glycolytic oscillations in individual yeast cells by periodic external perturbations. We find that oscillatory cells synchronise through phase shifts and that the mechanism is insensitive to cell heterogeneity (robustness) and similar for different types of external perturbations (universality).

Heterogeneity of glycolytic oscillatory behaviour in individual yeast cells.

There are many examples of oscillations in biological systems and one of the most investigated is glycolytic oscillations in yeast. These oscillations have been studied since the 1950s in dense, synchronized populations and in cell‐free extracts, but it has for long been unknown whether a high cell density is a requirement for oscillations to be induced, or if individual cells can oscillate also in isolation without synchronization. Here we present an experimental method and a detailed kinetic model for studying glycolytic oscillations in individual, isolated yeast cells and compare them to previously reported studies of single‐cell oscillations. The importance of single‐cell studies of this phenomenon and relevant future research questions are also discussed.

Design and fabrication of a scalable liver-lobule-on-a-chip microphysiological platform

The design and fabrication of a very large-scale liver-lobule (VLSLL)-on-a-chip device, providing a microphysiological niche for hepatocytes, is described. The device consists of an integrated network of liver-lobule-like hexagonal tissue-culture chambers constructed in a hybrid layout with a separate seed-feed network. As a key feature, each chamber contains a central outlet mimicking the central vein of a liver lobule. Separating chamber walls located between the culture area and feed network protects cells from the shear force of the convective flow. Arrays of designated passages convey nutrients to the cells by diffusion-dominated mass transport. We simulated the flow velocity, shear stress and diffusion of glucose molecules inside and outside the culture chambers under a continuous flow rate of 1 μl min-1. As proof of concept, human hepatocellular carcinoma cells (HepG2) were cultured for periods of 5 and 14 days and human-induced pluripotent stem cell (hiPSC)-derived hepatocytes for 21 days. Stabilized albumin secretion and urea synthesis were observed in the microfluidic devices and cells maintained morphology and functionality during the culture period. Furthermore, we observed 3D tissue-like structure and bile-canaliculi network formation in the chips. Future applications of the described platform include drug development and toxicity studies, as well as the modeling of patient-specific liver diseases, and integration in multi-organ human-on-a-chip systems.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability.

Induction of sustained glycolytic oscillations in single yeast cells using microfluidics and optical tweezers

Yeast glycolytic oscillations have been studied since the 1950s in cell free extracts and in intact cells. Until recently, sustained oscillations have only been observed in intact cells at the population level. The aim of this study was to investigate sustained glycolytic oscillations in single cells. Optical tweezers were used to position yeast cells in arrays with variable cell density in the junction of a microfluidic flow chamber. The microfluidic flow chambers were fabricated using soft lithography and the flow rates in the different inlet channels were individually controlled by syringe pumps. Due to the low Reynolds number, the solutions mixed by diffusion only. The environment in the junction of the chamber could thus be controlled by changing the flow rates in the inlet channels, with a complete change of environment within 2 s. The optimum position of the cell array was determined by simulations, to ensure complete coverage of the intended solution without any concentration gradients over the cell array. Using a DAPI filter set, the NADH auto fluorescence could be monitored in up to 100 cells simultaneously. Sustained oscillations were successfully induced in individual, isolated cells within specific flow rates and concentrations of glucose and cyanide. By changing the flow rates without changing the surrounding solution, it was found that the cell behavior was dependent on the concentration of chemicals in the medium rather than the flow rates in the range tested. Furthermore, by packing cells tightly, cell-to-cell interaction and synchronization could be studied.