Format

Send to

Choose Destination
Cell. 2015 Oct 22;163(3):712-23. doi: 10.1016/j.cell.2015.09.053. Epub 2015 Oct 22.

A human interactome in three quantitative dimensions organized by stoichiometries and abundances.

Author information

1
Max Planck Institute of Biochemistry, 82152 Martinsried, Germany.
2
Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
3
Cell Cycle, Biotechnology Center, TU Dresden, 01307 Dresden, Germany.
4
Medical Systems Biology, UCC, Medical Faculty Carl Gustav Carus, TU Dresden, 01307 Dresden, Germany; Eupheria Biotech GmbH, 01307 Dresden, Germany.
5
Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany; Medical Systems Biology, UCC, Medical Faculty Carl Gustav Carus, TU Dresden, 01307 Dresden, Germany.
6
Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany. Electronic address: hyman@mpi-cbg.de.
7
Max Planck Institute of Biochemistry, 82152 Martinsried, Germany. Electronic address: mmann@biochem.mpg.de.

Abstract

The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.

Comment in

PMID:
26496610
DOI:
10.1016/j.cell.2015.09.053
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center