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Abstract No.: TuP-011
Session: Biomolecular Assemblies
Presentation date: Tue, Aug 29, 2006
Presentation time: 09:50 – 11:20

Topology and Dynamics of a Protein-interaction Network involved in Cell-growth Control

Oliver Rinner1, Timo Glatter1, Samuel Bader1, Katja Koehler2, Irena Jevtov2, Erich Brunner2, Hugo Stocker2, Ernst Hafen2, Ruedi Aebersold1, Matthias Gstaiger1

1 Institute for Molecular Systems Biology, ETH, Zurich, Switzerland
2 Institute of Zoology, University of Zurich, Zurich, Switzerland

Correspondence address: Oliver Rinner, Institute for Molecular Systems Biology, ETH Honggerberg, HPT E 76, Zurich, 8093 Switzerland.

Keywords: Complex; Mass Spectrometry; Network; Quantitative Analysis.

Novel aspect: Quantitative mass spectrometry, combination of genetics and proteomics, protein-complex dynamics.

 

The control of cellular growth under changing environmental conditions (e.g. oxygen saturation state, presence and concentration of growth hormones and nutrients) is an essential physiological process with important clinical implications. It is a truly complex process that involves the coordination of numerous cellular events including transcription, translation, cytoskeletal re-organization, energy metabolism and more.

We developed and applied an integrated strategy for the systematic analysis of the regulatory networks involved in cellular growth control. Building on the results of a genetic screen in Drosophila melanogaster that identified numerous genes affecting cellular growth, approximately 50 genes were selected for transgenic expression in Drosophila cell lines. This set of genes contains known components from the Insulin and Tor signaling pathways, as well as genes where a link to growth regulation has not been established yet.

By applying advanced quantitative proteomic techniques we started to identify dynamic protein interaction networks that control cellular growth. The pull-downs are done under growth promoting and growth inhibiting conditions, revealing changes in complex composition as consequence of changes in cellular signaling.

The first results confirm previously described interaction partners and reveal new high confidence interactors of growth related proteins. Furthermore we identify overlapping components of protein complexes such as 14-3-3 proteins that are differentially enriched under growth promoting versus growth inhibiting conditions.

We expect that this study by combining the power of hypothesis-driven and systematic, large scale analyses will significantly enhance our systems level understanding of cellular signaling in general and provide an integrative view on the molecular architecture and dynamics of molecular networks that have important clinical implications for diseases linked to altered growth control such as cancer or the metabolic syndrome.