Literature DB >> 20967382

A mathematical analysis of nuclear intensity dynamics for Mig1-GFP under consideration of bleaching effects and background noise in Saccharomyces cerevisiae.

Simone Frey1, Kristin Sott, Maria Smedh, Thomas Millat, Peter Dahl, Olaf Wolkenhauer, Mattias Goksör.   

Abstract

Fluorescence microscopy is an imaging technique that provides insights into signal transduction pathways through the generation of quantitative data, such as the spatiotemporal distribution of GFP-tagged proteins in signaling pathways. The data acquired are, however, usually a composition of both the GFP-tagged proteins of interest and of an autofluorescent background, which both undergo photobleaching during imaging. We here present a mathematical model based on ordinary differential equations that successfully describes the shuttling of intracellular Mig1-GFP under changing environmental conditions regarding glucose concentration. Our analysis separates the different bleaching rates of Mig1-GFP and background, and the background-to-Mig1-GFP ratio. By applying our model to experimental data, we can thus extract the Mig1-GFP signal from the overall acquired signal and investigate the influence of kinase and phosphatase on Mig1. We found a stronger regulation of Mig1 through its kinase than through its phosphatase when controlled by the glucose concentration, with a constant (de)phosphorylation rate independent of the glucose concentration. By replacing the term for decreasing excited Mig1-GFP concentration with a constant, we were able to reconstruct the dynamics of Mig1-GFP, as it would occur without bleaching and background noise. Our model effectively demonstrates how data, acquired with an optical microscope, can be processed and used for a systems biology analysis of signal transduction pathways.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20967382     DOI: 10.1039/c005305h

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  6 in total

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

Authors:  Loubna Bendrioua; Maria Smedh; Joachim Almquist; Marija Cvijovic; Mats Jirstrand; Mattias Goksör; Caroline B Adiels; Stefan Hohmann
Journal:  J Biol Chem       Date:  2014-03-13       Impact factor: 5.157

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

Authors:  Joachim Almquist; Loubna Bendrioua; Caroline Beck Adiels; Mattias Goksör; Stefan Hohmann; Mats Jirstrand
Journal:  PLoS One       Date:  2015-04-20       Impact factor: 3.240

3.  The yeast osmostress response is carbon source dependent.

Authors:  Roja Babazadeh; Petri-Jaan Lahtvee; Caroline B Adiels; Mattias Goksör; Jens B Nielsen; Stefan Hohmann
Journal:  Sci Rep       Date:  2017-04-20       Impact factor: 4.379

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

Authors:  Roja Babazadeh; Caroline Beck Adiels; Maria Smedh; Elzbieta Petelenz-Kurdziel; Mattias Goksör; Stefan Hohmann
Journal:  PLoS One       Date:  2013-11-20       Impact factor: 3.240

5.  Rewiring yeast osmostress signalling through the MAPK network reveals essential and non-essential roles of Hog1 in osmoadaptation.

Authors:  Roja Babazadeh; Takako Furukawa; Stefan Hohmann; Kentaro Furukawa
Journal:  Sci Rep       Date:  2014-04-15       Impact factor: 4.379

6.  Systems Level Analysis of the Yeast Osmo-Stat.

Authors:  Soheil Rastgou Talemi; Carl-Fredrik Tiger; Mikael Andersson; Roja Babazadeh; Niek Welkenhuysen; Edda Klipp; Stefan Hohmann; Jörg Schaber
Journal:  Sci Rep       Date:  2016-08-12       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.