Single-cell study links metabolism with nutrient signaling and reveals sources of variability.

BACKGROUND: The yeast AMPK/SNF1 pathway is best known for its role in glucose de/repression. When glucose becomes limited, the Snf1 kinase is activated and phosphorylates the transcriptional repressor Mig1, which is then exported from the nucleus. The exact mechanism how the Snf1-Mig1 pathway is regulated is not entirely elucidated. RESULTS: Glucose uptake through the low affinity transporter Hxt1 results in nuclear accumulation of Mig1 in response to all glucose concentrations upshift, however with increasing glucose concentration the nuclear localization of Mig1 is more intense. Strains expressing Hxt7 display a constant response to all glucose concentration upshifts. We show that differences in amount of hexose transporter molecules in the cell could cause cell-to-cell variability in the Mig1-Snf1 system. We further apply mathematical modelling to our data, both general deterministic and a nonlinear mixed effect model. Our model suggests a presently unrecognized regulatory step of the Snf1-Mig1 pathway at the level of Mig1 dephosphorylation. Model predictions point to parameters involved in the transport of Mig1 in and out of the nucleus as a majorsource of cell to cell variability. CONCLUSIONS: With this modelling approach we have been able to suggest steps that contribute to the cell-to-cell variability. Our data indicate a close link between the glucose uptake rate, which determines the glycolytic rate, and the activity of the Snf1/Mig1 system. This study hence establishes a close relation between metabolism and signalling.

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.

Network reconstruction and validation of the Snf1/AMPK pathway in baker's yeast based on a comprehensive literature review.

BACKGROUND/OBJECTIVES: The SNF1/AMPK protein kinase has a central role in energy homeostasis in eukaryotic cells. It is activated by energy depletion and stimulates processes leading to the production of ATP while it downregulates ATP-consuming processes. The yeast SNF1 complex is best known for its role in glucose derepression. METHODS: We performed a network reconstruction of the Snf1 pathway based on a comprehensive literature review. The network was formalised in the rxncon language, and we used the rxncon toolbox for model validation and gap filling. RESULTS: We present a machine-readable network definition that summarises the mechanistic knowledge of the Snf1 pathway. Furthermore, we used the known input/output relationships in the network to identify and fill gaps in the information transfer through the pathway, to produce a functional network model. Finally, we convert the functional network model into a rule-based model as a proof-of-principle. CONCLUSIONS: The workflow presented here enables large scale reconstruction, validation and gap filling of signal transduction networks. It is analogous to but distinct from that established for metabolic networks. We demonstrate the workflow capabilities, and the direct link between the reconstruction and dynamic modelling, with the Snf1 network. This network is a distillation of the knowledge from all previous publications on the Snf1/AMPK pathway. The network is a knowledge resource for modellers and experimentalists alike, and a template for similar efforts in higher eukaryotes. Finally, we envisage the workflow as an instrumental tool for reconstruction of large signalling networks across Eukaryota.

The mammalian AMP-activated protein kinase complex mediates glucose regulation of gene expression in the yeast Saccharomyces cerevisiae.

The AMP-activated protein kinase (AMPK) controls energy homeostasis in eukaryotic cells. Here we expressed hetero-trimeric mammalian AMPK complexes in a Saccharomyces cerevisiae mutant lacking all five genes encoding yeast AMPK/SNF1 components. Certain mammalian complexes complemented the growth defect of the yeast mutant on non-fermentable carbon sources. Phosphorylation of the AMPK α1-subunit was glucose-regulated, albeit not by the Glc7-Reg1/2 phosphatase, which performs this function on yeast AMPK/SNF1. AMPK could take over SNF1 function in glucose derepression. While indirectly acting anti-diabetic drugs had no effect on AMPK in yeast, compound 991 stimulated α1-subunit phosphorylation. Our results demonstrate a remarkable functional conservation of AMPK and that glucose regulation of AMPK may not be mediated by regulatory features of a specific phosphatase.

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

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.

Potent anti-respiratory syncytial virus activity of a cholestanol-sulfated tetrasaccharide conjugate.

A number of different viruses including respiratory syncytial virus (RSV) initiate infection of cells by binding to cell surface glycosaminoglycans and sulfated oligo- and polysaccharide mimetics of these receptors exhibit potent antiviral activity in cultured cells. We investigated whether the introduction of different lipophilic groups to the reducing end of sulfated oligosaccharides would modulate their anti-RSV activity. Our results demonstrate that the cholestanol-conjugated tetrasaccharide (PG545) exhibited ∼5- to 16-fold enhanced anti-RSV activity in cultured cells compared with unmodified sulfated oligosaccharides. Furthermore, PG545 displayed virus-inactivating (virucidal) activity, a feature absent in sulfated oligosaccharides. To inhibit RSV infectivity PG545 had to be present during the initial steps of viral infection of cells. The anti-RSV activity of PG545 was due to both partial inhibition of the virus attachment to cells and a more profound interference with some post-attachment steps as PG545 efficiently neutralized infectivity of the cell-adsorbed virus. The anti-RSV activity of PG545 was reduced when tested in the presence of human nasal secretions. Serial passages of RSV in the presence of increasing concentrations of PG545 selected for weakly resistant viral variants that comprised the F168S and the P180S amino acid substitutions in the viral G protein. Altogether we identified a novel and potent inhibitor of RSV, which unlike sulfated oligo- and polysaccharide compounds, could irreversibly inactivate RSV infectivity.

Two novel fusion inhibitors of human respiratory syncytial virus.

To search for novel drugs against human respiratory syncytial virus (RSV), we have screened a diversity collection of 16,671 compounds for anti-RSV activity in cultures of HEp-2 cells. Two of the hit compounds, i.e., the N-(2-hydroxyethyl)-4-methoxy-N-methyl-3-(6-methyl[1,2,4]triazolo[3,4-a]phthalazin-3-yl)benzenesulfonamide (designated as P13) and the 1,4-bis(3-methyl-4-pyridinyl)-1,4-diazepane (designated as C15), reduced the virus infectivity with IC50 values of 0.11 and 0.13µM respectively. The concentration of P13 and C15 that reduced the viability of HEp-2 cells by 50% was 310 and 75µM respectively. Both P13 and C15 exhibited no direct virucidal activity or inhibitory effects on the virus attachment to cells. However, to inhibit formation of RSV-induced syncytial plaques P13 and C15 had to be present during the virus entry into the cells and the cell-to-cell transmission of the virus. The RSV multiplication in HEp-2 cells in the presence of P13 or C15 resulted in rapid selection of viral variants that were ∼1000 times less sensitive to these drugs than original virus. Sequencing of resistant viruses revealed presence of amino acid substitutions in the F protein of RSV, i.e., the D489G for C15-selected, and the T400I and N197T (some clones) for the P13-selected virus variants. In conclusion, we have identified two novel fusion inhibitors of RSV, and the detailed understanding of their mode of antiviral activity including selection for the drug resistant viral variants may help to develop selective and efficient anti-RSV drugs.