Transcription factor clusters regulate genes in eukaryotic cells

Transcription is regulated through binding factors to gene promoters to activate or repress expression, however, the mechanisms by which factors find targets remain unclear. Using single-molecule fluorescence microscopy, we determined in vivo stoichiometry and spatiotemporal dynamics of a GFP tagged repressor, Mig1, from a paradigm signaling pathway of Saccharomyces cerevisiae. We find the repressor operates in clusters, which upon extracellular signal detection, translocate from the cytoplasm, bind to nuclear targets and turnover. Simulations of Mig1 configuration within a 3D yeast genome model combined with a promoter-specific, fluorescent translation reporter confirmed clusters are the functional unit of gene regulation. In vitro and structural analysis on reconstituted Mig1 suggests that clusters are stabilized by depletion forces between intrinsically disordered sequences. We observed similar clusters of a co-regulatory activator from a different pathway, supporting a generalized cluster model for transcription factors that reduces promoter search times through intersegment transfer while stabilizing gene expression

The yeast Mig1 transcriptional repressor is dephosphorylated by glucosedependent and independent mechanisms

A yeast Saccharomyces cerevisiae Snf1 kinase, an analog of mammalian AMPK, regulates glucose derepression of genes required for utilization of alternative carbon sources through the transcriptional repressor Mig1. It has been suggested that the Glc7-Reg1 phosphatase dephosphorylates Mig1. Here we report that Mig1 is dephosphorylated by Glc7-Reg1 in an apparently glucose-dependent mechanism but also by a mechanism independent of glucose and Glc7-Reg1. In addition to serine/threonine phosphatases another process including tyrosine phosphorylation seems crucial for Mig1 regulation. Taken together, Mig1 dephosphorylation appears to be controlled in a complex manner, in line with the importance for rapid and sensitive regulation upon altered glucose concentrations in the growth medium

On Spatial Data in Measuring Urban Livability, An analytical review

Spatial data enables researchers to assess various factors of urban livability. Regarding the development of remote sensing technics and advances in Geographical Information Systems (GIS), large collections of valuable spatial datasets become available for livability researchers. This paper aims to identify relevant spatial data sources in use in livability studies by means of an analytical review on spatial data in livability empirical studies. The paper identified four main categories of spatial data sources including earth observation images collections, mapping services, national geospatial datasets, and private companies’ datasets. The study demarcates that mixed types of raster and vector images sources are more used in livability studies than other single type sources. Also, the paper highlights the fact that spatial data sources cover mainly indicators of urban planning, land use, land cover and natural environment factors. The study concludes that spatial data sources represent a valuable source of data for livability studies, especially aggregated spatial data sources that provide more ready to use data

A Yield Spread Analysis of the Green Bond Premium and Liquidity in the Swedish Green Bond Market

This study investigates green bond premium and liquidity in the Swedish SEK green bond market. Through a matching pair’s methodology with 101 green Swedish SEK Green bonds and conventional counterparts, the yield spread is analyzed through a liquidity risk and a green bond premium perspective. The results of the Swedish SEK green bond sample suggest that green bonds compensate for liquidity and that corporate green bonds seem to be more liquid than their conventional counterparts. The results did not show enough significance on the green bond premium. Hence, no answer on whether green bonds have a higher or lower return solely because of the fact that they are green can be given. The regression results of the green bond premium, however, suggest that the predominant determinants of the size of the green bond premium seem to be whether the bond is a corporate or municipal bond and what type of sector the bond is associated with.MSc in Financ

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

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

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 alpha 1-subunit was glucose-regulated, albeit not by the G1c7-Reg1/2 phosphatase, which performs this function on yeast AMPK/SNFl. 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 alpha 1-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. (C) 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved

Parameter estimates.

<p>Parameter estimates.</p

Illustration of the mathematical model.

<p>Extracellular glucose is controlling the rate of production of nuclear Mig1 and a hypothetical component X. The level of X in turn modulates the degradation of nuclear Mig1.</p

The distribution of maximum a posteriori <i>η</i>.

<p>For experiments 1 to 4 (A to D), the EBEs of <i>η</i>₂ and <i>η</i>₃ are shown as red points. The regions of one and two standard deviations of a normal distribution fitted to the EBEs, and the NLME population estimate of the distribution of <i>η</i>₂ and <i>η</i>₃, are shown as black and filled gray ellipses, respectively.</p