Document Detail

Fluctuation analysis of activity biosensor images for the study of information flow in signaling pathways.
MedLine Citation:
PMID:  23280114     Owner:  NLM     Status:  MEDLINE    
Comprehensive understanding of cellular signal transduction requires accurate measurement of the information flow in molecular pathways. In the past, information flow has been inferred primarily from genetic or protein-protein interactions. Although useful for overall signaling, these approaches are limited in that they typically average over populations of cells. Single-cell data of signaling states are emerging, but these data are usually snapshots of a particular time point or limited to averaging over a whole cell. However, many signaling pathways are activated only transiently in specific subcellular regions. Protein activity biosensors allow measurement of the spatiotemporal activation of signaling molecules in living cells. These data contain highly complex, dynamic information that can be parsed out in time and space and compared with other signaling events as well as changes in cell structure and morphology. We describe in this chapter the use of computational tools to correct, extract, and process information from time-lapse images of biosensors. These computational tools allow one to explore the biosensor signals in a multiplexed approach in order to reconstruct the sequence of signaling events and consequently the topology of the underlying pathway. The extraction of this information, dynamics and topology, provides insight into how the inputs of a signaling network are translated into its biochemical or mechanical outputs.
Marco Vilela; Nadia Halidi; Sebastien Besson; Hunter Elliott; Klaus Hahn; Jessica Tytell; Gaudenz Danuser
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Methods in enzymology     Volume:  519     ISSN:  1557-7988     ISO Abbreviation:  Meth. Enzymol.     Publication Date:  2013  
Date Detail:
Created Date:  2013-01-02     Completed Date:  2013-06-05     Revised Date:  2014-10-02    
Medline Journal Info:
Nlm Unique ID:  0212271     Medline TA:  Methods Enzymol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  253-76     Citation Subset:  IM    
Copyright Information:
Copyright © 2013 Elsevier Inc. All rights reserved.
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MeSH Terms
Affinity Labels
Biosensing Techniques*
Cell Shape
Signal Transduction*
Grant Support
Reg. No./Substance:
0/Affinity Labels

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