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

Artikel i vetenskaplig tidskrift
Författare S Frey
Kristin Sott
Maria Smedh
T Millat
Peter Dahl
O Wolkenhauer
Mattias Goksör
Publicerad i MOLECULAR BIOSYSTEMS
Volym 7
Nummer/häfte 1
Sidor 215-223
ISSN 1742-206X
Publiceringsår 2011
Publicerad vid Institutionen för cell- och molekylärbiologi
Institutionen för fysik (GU)
Sidor 215-223
Språk en
Länkar dx.doi.org/10.1039/c005305h
Ämneskategorier Medicinska grundvetenskaper, Fysik

Sammanfattning

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.

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