English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A directed protein interaction network for investigating intracellular signal transduction

Vinayagam, A., Stelzl, U., Foulle, R., Plassmann, S., Zenkner, M., Timm, J., et al. (2011). A directed protein interaction network for investigating intracellular signal transduction. Sci Signal, 4(189), rs8. Retrieved from http://stke.sciencemag.org/cgi/reprint/sigtrans;4/189/rs8.pdf.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7854-3 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7855-1
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Vinayagam, A., Author
Stelzl, U.1, Author              
Foulle, R., Author
Plassmann, S., Author
Zenkner, M., Author
Timm, J., Author
Assmus, H. E., Author
Andrade-Navarro, M. A., Author
Wanker, E. E., Author
Affiliations:
1Molecular Interaction Networks (Ulrich Stelzl), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479660              

Content

show
hide
Free keywords: Bayes Theorem; Cell Communication/ physiology; Computational Biology/ methods; Epidermal Growth Factor/metabolism; Extracellular Signal-Regulated MAP Kinases/metabolism; Protein Interaction Maps/ genetics; Signal Transduction/genetics/ physiology; Transcription Factors/metabolism; Two-Hybrid System Techniques
 Abstract: Cellular signal transduction is a complex process involving protein-protein interactions (PPIs) that transmit information. For example, signals from the plasma membrane may be transduced to transcription factors to regulate gene expression. To obtain a global view of cellular signaling and to predict potential signal modulators, we searched for protein interaction partners of more than 450 signaling-related proteins by means of automated yeast two-hybrid interaction mating. The resulting PPI network connected 1126 proteins through 2626 PPIs. After expansion of this interaction map with publicly available PPI data, we generated a directed network resembling the signal transduction flow between proteins with a naive Bayesian classifier. We exploited information on the shortest PPI paths from membrane receptors to transcription factors to predict input and output relationships between interacting proteins. Integration of directed PPI with time-resolved protein phosphorylation data revealed network structures that dynamically conveyed information from the activated epidermal growth factor and extracellular signal-regulated kinase (EGF/ERK) signaling cascade to directly associated proteins and more distant proteins in the network. From the model network, we predicted 18 previously unknown modulators of EGF/ERK signaling, which we validated in mammalian cell-based assays. This generic experimental and computational approach provides a framework for elucidating causal connections between signaling proteins and facilitates the identification of proteins that modulate the flow of information in signaling networks.

Details

show
hide
Language(s):
 Dates: 2011
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Sci Signal
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 4 (189) Sequence Number: - Start / End Page: rs8 Identifier: ISSN: 1937-9145 (Electronic)